WorldWideScience

Sample records for residential electrical demand

  1. Forecasting residential electricity demand in provincial China.

    Science.gov (United States)

    Liao, Hua; Liu, Yanan; Gao, Yixuan; Hao, Yu; Ma, Xiao-Wei; Wang, Kan

    2017-03-01

    In China, more than 80% electricity comes from coal which dominates the CO2 emissions. Residential electricity demand forecasting plays a significant role in electricity infrastructure planning and energy policy designing, but it is challenging to make an accurate forecast for developing countries. This paper forecasts the provincial residential electricity consumption of China in the 13th Five-Year-Plan (2016-2020) period using panel data. To overcome the limitations of widely used predication models with unreliably prior knowledge on function forms, a robust piecewise linear model in reduced form is utilized to capture the non-deterministic relationship between income and residential electricity consumption. The forecast results suggest that the growth rates of developed provinces will slow down, while the less developed will be still in fast growing. The national residential electricity demand will increase at 6.6% annually during 2016-2020, and populous provinces such as Guangdong will be the main contributors to the increments.

  2. Modelling and forecasting Turkish residential electricity demand

    International Nuclear Information System (INIS)

    Dilaver, Zafer; Hunt, Lester C

    2011-01-01

    This research investigates the relationship between Turkish residential electricity consumption, household total final consumption expenditure and residential electricity prices by applying the structural time series model to annual data over the period from 1960 to 2008. Household total final consumption expenditure, real energy prices and an underlying energy demand trend are found to be important drivers of Turkish residential electricity demand with the estimated short run and the long run total final consumption expenditure elasticities being 0.38 and 1.57, respectively, and the estimated short run and long run price elasticities being -0.09 and -0.38, respectively. Moreover, the estimated underlying energy demand trend, (which, as far as is known, has not been investigated before for the Turkish residential sector) should be of some benefit to Turkish decision makers in terms of energy planning. It provides information about the impact of past policies, the influence of technical progress, the impacts of changes in consumer behaviour and the effects of changes in economic structure. Furthermore, based on the estimated equation, and different forecast assumptions, it is predicted that Turkish residential electricity demand will be somewhere between 48 and 80 TWh by 2020 compared to 40 TWh in 2008. - Research highlights: → Estimated short run and long run expenditure elasticities of 0.38 and 1.57, respectively. → Estimated short run and long run price elasticities of -0.09 and -0.38, respectively. → Estimated UEDT has increasing (i.e. energy using) and decreasing (i.e. energy saving) periods. → Predicted Turkish residential electricity demand between 48 and 80 TWh in 2020.

  3. Electricity demand for South Korean residential sector

    International Nuclear Information System (INIS)

    Sa'ad, Suleiman

    2009-01-01

    This study estimates the electricity demand function for the residential sector of South Korea with the aim of examining the effects of improved energy efficiency, structural factors and household lifestyles on electricity consumption. In the study, time series data for the period from 1973 to 2007 is used in a structural time series model to estimate the long-term price and income elasticities and annual growth of underlying energy demand trend (UEDT) at the end of the estimation period. The result shows a long-term income elasticity of 1.33 and a long-term price elasticity of -0.27% with -0.93% as the percentage growth of UEDT at the end of the estimation period. This result suggests that, in order to encourage energy efficiency in the residential sector, the government should complement the market based pricing policies with non-market policies such as minimum energy efficiency standards and public enlightenment.

  4. Quebec residential electricity demand: a microeconometric approach

    International Nuclear Information System (INIS)

    Bernard, J.T.; Bolduc, D.; Belanger, D.

    1996-01-01

    An economic analysis of Quebec residential electricity demand was studied by micro-simulation models. These structural models describe all components which lead to decisions upon durable holdings and electric appliance usage. The demand for space and water heating systems was evaluated. Recent price change in favour of energy sources other than electricity were taken into account. Price and income elasticity ratios were found to be low, as expected when estimating short term use. The role played by socio-economic variables on the choice of space-water heating systems and electricity use was also examined. Recent conversions have indicated a trend toward preference by households in favour of natural gas or oil over electricity. 18 refs., 5 tabs., 1 fig

  5. The Sensitivity of Residential Electricity Demand in Indonesia

    Directory of Open Access Journals (Sweden)

    Stranti Nastiti Kusumaningrum

    2018-03-01

    Full Text Available Since 2013, the residential electricity price for High VA (Volt-Ampere households has changed due to changes in pricing policies. This paper analyzes the responsiveness of residential electricity demand to the change in electricity prices and income among two different household groups (Low VA and High VA in 2011 and 2014. Using an electricity consumption model and the Quantile Regression method, the results show that residential electricity demand is price and income inelastic. Income elasticity is lower than price elasticity. Furthermore, the effects on price elasticity also found in the Low VA group, whose rate remained stable. At the same time, evidence proves the impact of the change in pricing policy on income elasticity remains unclear. This result implies that the government has to be more careful in regulating electricity prices for the low VA group, while maintaining economic stability.DOI: 10.15408/sjie.v7i2.6048

  6. Estimating elasticity for residential electricity demand in China.

    Science.gov (United States)

    Shi, G; Zheng, X; Song, F

    2012-01-01

    Residential demand for electricity is estimated for China using a unique household level dataset. Household electricity demand is specified as a function of local electricity price, household income, and a number of social-economic variables at household level. We find that the residential demand for electricity responds rather sensitively to its own price in China, which implies that there is significant potential to use the price instrument to conserve electricity consumption. Electricity elasticities across different heterogeneous household groups (e.g., rich versus poor and rural versus urban) are also estimated. The results show that the high income group is more price elastic than the low income group, while rural families are more price elastic than urban families. These results have important policy implications for designing an increasing block tariff.

  7. Modelling residential electricity demand in the GCC countries

    International Nuclear Information System (INIS)

    Atalla, Tarek N.; Hunt, Lester C.

    2016-01-01

    This paper aims at understanding the drivers of residential electricity demand in the Gulf Cooperation Council countries by applying the structural time series model. In addition to the economic variables of GDP and real electricity prices, the model accounts for population, weather, and a stochastic underlying energy demand trend as a proxy for efficiency and human behaviour. The resulting income and price elasticities are informative for policy makers given the paucity of previous estimates for a region with particular political structures and economies subject to large shocks. In particular, the estimates allow for a sound assessment of the impact of energy-related policies suggesting that if policy makers in the region wish to curtail future residential electricity consumption they would need to improve the efficiency of appliances and increase energy using awareness of consumers, possibly by education and marketing campaigns. Moreover, even if prices were raised the impact on curbing residential electricity growth in the region is likely to be very small given the low estimated price elasticities—unless, that is, prices were raised so high that expenditure on electricity becomes such a large proportion of income that the price elasticities increase (in absolute terms). - Highlights: • Residential electricity demand for Bahrain, Kuwait, Oman, and Saudi Arabia • Estimated residential electricity demand relationships using STSM/UEDT approach • LR income and price elasticities from 0.43 to 0.71 and − 0.16 to zero respectively • Impact CDD elasticities from 0.2 to 0.7 • Estimated UEDTs suggest exogenous electricity using behaviour.

  8. Accelerating residential PV expansion: demand analysis for competitive electricity markets

    International Nuclear Information System (INIS)

    Duke, Richard; Williams, Robert; Payne, Adam

    2005-01-01

    This article quantifies the potential market for grid-connected, residential photovoltaic (PV) electricity integrated into new homes built in the US. It complements an earlier supply-side analysis by the authors that demonstrates the potential to reduce PV module prices below $1.5/W p by scaling up existing thin-film technology in 100 MW p /yr manufacturing facilities. The present article demonstrates that, at that price, PV modules may be cost effective in 125,000 new home installations per year (0.5 GW p /yr). While this market is large enough to support multiple scaled up thin-film PV factories, inefficient energy pricing and demand-side market failures will inhibit prospective PV consumers without strong public policy support. Net metering rules, already implemented in many states to encourage PV market launch, represent a crude but reasonable surrogate for efficient electricity pricing mechanisms that may ultimately emerge to internalize the externality benefits of PV. These public benefits include reduced air pollution damages (estimated costs of damage to human health from fossil fuel power plants are presented in Appendix A), deferral of transmission and distribution capital expenditures, reduced exposure to fossil fuel price risks, and increased electricity system reliability for end users. Thus, net metering for PV ought to be implemented as broadly as possible and sustained until efficient pricing is in place. Complementary PV 'buydowns' (e.g., a renewable portfolio standard with a specific PV requirement) are needed to jumpstart regional PV markets

  9. Managing Residential Electricity Demand Through Provision of Better Feedback

    Science.gov (United States)

    Collins, Myles

    New and affordable technology for providing detailed feedback on household electricity usage presents a host of opportunities for utilities and policy-makers to manage demand. This dissertation examines ways to use these devices to reduce - and shift the timing of - energy use in the residential sector by influencing consumers' behavior. The first portion of the study analyzes the impact of programmable thermostats (PTs) on energy use, focusing on residents' knowledge of climate control settings in the dwelling. I found that of households with natural gas heating systems, young households with PTs used 17 percent less heating energy on average. In addition, residents who did not know their thermostat settings tended to use 10 percent more energy for heating. The main portion of the dissertation focuses specifically on the potential for better feedback on electricity usage to reduce household energy consumption. The existing literature suggests that feedback can reduce electricity consumption in homes by 5 to 20 percent, but that significant uncertainties remain in our knowledge of the effectiveness of feedback. These uncertainties include the variation in feedback effectiveness between demographic groups and consumers in different climate regions. This analysis uses these uncertainties to perform an exploratory analysis to determine the conditions under which the benefits of feedback outweigh the costs and to compare the cost-effectiveness of providing feedback against that of other DSM programs. I found that benefits would likely outweigh costs for enhanced monthly billing and real-time feedback and that cost-effectiveness was superior to that of other DSM programs for these types of feedback. For feedback that is disaggregated by appliance type, cost effectiveness was competitive with other DSM programs under a limited set of cases. This study also examines how energy consumption devices should display feedback on GHG emissions from electricity use under a real

  10. Electricity consumption in G7 countries: A panel cointegration analysis of residential demand elasticities

    International Nuclear Information System (INIS)

    Narayan, Paresh Kumar; Smyth, Russell; Prasad, Arti

    2007-01-01

    This article applies recently developed panel unit root and panel cointegration techniques to estimate the long-run and short-run income and price elasticities for residential demand for electricity in G7 countries. The panel results indicate that in the long-run residential demand for electricity is price elastic and income inelastic. The study concludes that from an environmental perspective there is potential to use pricing policies in the G7 countries to curtail residential electricity demand, and thus curb carbon emissions, in the long run

  11. The analysis of Taiwan's residential electricity demand under the electricity tariff policy

    Science.gov (United States)

    Chen, Po-Jui

    In October 2013, the Taiwan Power Company (Taipower), the monopolized state utility service in Taiwan, implemented an electricity tariff adjustment policy to reduce residential electricity demand. Using bi-monthly billing data from 6,932 electricity consumers, this study examine how consumers respond to an increase in electricity prices. This study employs an empirical approach that takes advantage of quasi-random variation over a period of time when household bills were affected by a change in electricity price. The study found that this price increase caused a 1.78% decline in residential electricity consumption, implying a price elasticity of -0.19 for summer-season months and -0.15 for non-summer-season months. The demand for electricity is therefore relatively inelastic, likely because it is hard for people to change their electricity consumption behavior in the short-term. The results of this study highlight that demand-side management cannot be the only lever used to address Taiwan's forecasted decrease in electricity supply.

  12. Estimation of Iranian price elasticities of residential electricity demand

    Directory of Open Access Journals (Sweden)

    Yeganeh Mousavi Jahromi

    2014-06-01

    Full Text Available This paper presents a study to determine demand for electricity in city of Yazd, Iran over the period of 1998-2008. Using vector error correction model (VECM based on seasonal information, the study determines that electricity has no elasticity in short term in household expenditure. Therefore, government policy on increasing price of electricity will not influence demand. However, electricity maintains elasticity over the long-term period and an increase on price of electricity could motivate consumers to reduce their consumption by purchasing energy efficient facilities. Therefore, any governmental strategy to increase price may have positive impact on economy. The study also detects a positive and meaningful relationship between temperature and electricity consumption.

  13. Price freezes, durables and residential electricity demand - Evidence from the Greater Buenos Aires

    Energy Technology Data Exchange (ETDEWEB)

    Casarin, Ariel; Delfino, Maria Eugenia

    2010-09-15

    This paper examines the determinants of residential electricity demand in the Greater Buenos Aires between 1997 and 2006. During the second half of this period, residential tariffs remained nominally fixed, while an income boom boosted up the sales of durables. This study differs from previous works in that it explicitly considers the impact of the stock of air-conditioners on residential demand. The paper reports short- and long-run elasticities and examines the contribution of prices and durables to recent demand growth. Simulations illustrate the impact of prices and durables on future demand.

  14. Impact of Uncoordinated Plug-in Electric Vehicle Charging on Residential Power Demand

    Energy Technology Data Exchange (ETDEWEB)

    Muratori, Matteo [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-01-22

    Electrification of transport offers opportunities to increase energy security, reduce carbon emissions, and improve local air quality. Plug-in electric vehicles (PEVs) are creating new connections between the transportation and electric sectors, and PEV charging will create opportunities and challenges in a system of growing complexity. Here, I use highly resolved models of residential power demand and PEV use to assess the impact of uncoordinated in-home PEV charging on residential power demand. While the increase in aggregate demand might be minimal even for high levels of PEV adoption, uncoordinated PEV charging could significantly change the shape of the aggregate residential demand, with impacts for electricity infrastructure, even at low adoption levels. Clustering effects in vehicle adoption at the local level might lead to high PEV concentrations even if overall adoption remains low, significantly increasing peak demand and requiring upgrades to the electricity distribution infrastructure. This effect is exacerbated when adopting higher in-home power charging.

  15. Impact of uncoordinated plug-in electric vehicle charging on residential power demand

    Science.gov (United States)

    Muratori, Matteo

    2018-01-01

    Electrification of transport offers opportunities to increase energy security, reduce carbon emissions, and improve local air quality. Plug-in electric vehicles (PEVs) are creating new connections between the transportation and electric sectors, and PEV charging will create opportunities and challenges in a system of growing complexity. Here, I use highly resolved models of residential power demand and PEV use to assess the impact of uncoordinated in-home PEV charging on residential power demand. While the increase in aggregate demand might be minimal even for high levels of PEV adoption, uncoordinated PEV charging could significantly change the shape of the aggregate residential demand, with impacts for electricity infrastructure, even at low adoption levels. Clustering effects in vehicle adoption at the local level might lead to high PEV concentrations even if overall adoption remains low, significantly increasing peak demand and requiring upgrades to the electricity distribution infrastructure. This effect is exacerbated when adopting higher in-home power charging.

  16. Short- and long-run time-of-use price elasticities in Swiss residential electricity demand

    International Nuclear Information System (INIS)

    Filippini, Massimo

    2011-01-01

    This paper presents an empirical analysis on the residential demand for electricity by time-of-day. This analysis has been performed using aggregate data at the city level for 22 Swiss cities for the period 2000-2006. For this purpose, we estimated two log-log demand equations for peak and off-peak electricity consumption using static and dynamic partial adjustment approaches. These demand functions were estimated using several econometric approaches for panel data, for example LSDV and RE for static models, and LSDV and corrected LSDV estimators for dynamic models. The attempt of this empirical analysis has been to highlight some of the characteristics of the Swiss residential electricity demand. The estimated short-run own price elasticities are lower than 1, whereas in the long-run these values are higher than 1. The estimated short-run and long-run cross-price elasticities are positive. This result shows that peak and off-peak electricity are substitutes. In this context, time differentiated prices should provide an economic incentive to customers so that they can modify consumption patterns by reducing peak demand and shifting electricity consumption from peak to off-peak periods. - Highlights: → Empirical analysis on the residential demand for electricity by time-of-day. → Estimators for dynamic panel data. → Peak and off-peak residential electricity are substitutes.

  17. Estimation of urban residential electricity demand in China using household survey data

    International Nuclear Information System (INIS)

    Zhou, Shaojie; Teng, Fei

    2013-01-01

    This paper uses annual urban household survey data of Sichuan Province from 2007 to 2009 to estimate the income and price elasticities of residential electricity demand, along with the effects of lifestyle-related variables. The empirical results show that in the urban area of Sichuan province, the residential electricity demand is price- and income-inelastic, with price and income elasticities ranging from −0.35 to −0.50 and from 0.14 to 0.33, respectively. Such lifestyle-related variables as demographic variables, dwelling size and holdings of home appliances, are also important determinants of residential electricity demand, especially the latter. These results are robust to a variety of sensitivity tests. The research findings imply that urban residential electricity demand continues to increase with the growth of income. The empirical results have important policy implications for the Multistep Electricity Price, which been adopted in some cities and is expected to be promoted nationwide through the installation of energy-efficient home appliances. - Highlights: • We estimate price and income elasticities in China using household survey data. • The current study is the first such study in China at this level. • Both price and income are inelastic. • Behavior factors have important impact on electricity consumption

  18. Modeling future demand for energy resources: A study of residential electricity usage in Thailand

    Science.gov (United States)

    Nilagupta, Prapassara

    1999-12-01

    Thailand has a critical need for effective long-term energy planning because of the country's rapidly increasing energy consumption. In this study, the demand for electricity by the residential sector is modeled using a framework that provides detailed estimates of the timing and spatial distribution of changes in energy demand. A population model was developed based on the Cohort-Component method to provide estimates of population by age, sex and urban/non-urban residency in each province. A residential electricity end user model was developed to estimate future electricity usage in urban and non-urban households of the seventy-six provinces in Thailand during the period 1999--2019. Key variables in this model include population, the number of households, family household size, and characteristics of eleven types of electric household appliance such as usage intensity, input power, and saturation rate. The methodology employed in this study is a trending method which utilizes expert opinion to estimate future variables based on a percentage change from the most current value. This study shows that from 1994 to 2019 Thailand will experience an increase in population from 55.4 to 83.6 million. Large percentage population increases will take place in Bangkok, Nonthaburi, Samut Prakarn, Nakhon Pathom and Chonburi. At a national level, the residential electricity consumption will increase from approximately 19,000 to 8 1,000 GWh annually. Consumption in non-urban households will be larger than in urban households, with respective annual increases of 8.0% and 6.2% in 2019. The percent increase of the average annual electricity consumption will be four times the average annual percent population increase. Increased electricity demand is largely a function of increased population and increased demand for high-energy appliances such as air conditioners. In 1994, air conditioning was responsible for xx% of total residential electricity demand. This study estimates that in

  19. Predicting summer residential electricity demand across the U.S.A using climate information

    Science.gov (United States)

    Sun, X.; Wang, S.; Lall, U.

    2017-12-01

    We developed a Bayesian Hierarchical model to predict monthly residential per capita electricity consumption at the state level across the USA using climate information. The summer period was selected since cooling requirements may be directly associated with electricity use, while for winter a mix of energy sources may be used to meet heating needs. Historical monthly electricity consumption data from 1990 to 2013 were used to build a predictive model with a set of corresponding climate and non-climate covariates. A clustering analysis was performed first to identify groups of states that had similar temporal patterns for the cooling degree days of each state. Then, a partial pooling model was applied to each cluster to assess the sensitivity of monthly per capita residential electricity demand to each predictor (including cooling-degree-days, gross domestic product (GDP) per capita, per capita electricity demand of previous month and previous year, and the residential electricity price). The sensitivity of residential electricity to cooling-degree-days has an identifiable geographic distribution with higher values in northeastern United States.

  20. Evolution of residential electricity demand by end-use in Quebec 1979-1989: A conditional demand analysis

    International Nuclear Information System (INIS)

    Lafrance, G.; Perron, D.

    1994-01-01

    Some of the main conclusions are presented from a temporal analysis of three large-scale electricity demand surveys (1979, 1984, and 1989) for the Quebec residential sector. A regression method called conditional demand analysis was used. The study allows a number of conclusions about certain electricity consumption trends by end-uses from 1979 to 1989 by household type and by vintage category. For example, the results indicate that decreasing electricity consumption between 1979 and 1984 for a typical dwelling equipped with electric space heating was mainly related to a large decline in net heating consumption. Overall, the results suggest that some permanent energy savings have been realized by a typical household equipped with an electric heating system due to improvements in standards and changes in customer behavior. These energy savings were partly offset by increased electricity consumption from the purchase of new appliances and an increase in the demand for hot water. 7 refs., 1 fig., 8 tabs

  1. Norwegian residential electricity demand - a microeconomic assessment of the growth from 1976 to 1993

    International Nuclear Information System (INIS)

    Halvorsen, B.; Larsen, B.M.

    2001-01-01

    The Norwegian residential electricity consumption increased by an average of 3% annually during the period 1976-1993. Political signals indicate that the growth in Norwegian residential energy consumption should be reduced, and that it may be necessary to increase energy taxes. Based on data for the sample of households from the annual consumer expenditure survey, we study factors that are of importance explaining the growth in Norwegian residential electricity demand during this period. Nearly half of the growth is due to an increase in the number of households, while the rest reflects an increase in average consumption per household. The increase in average consumption per household is due to an increasing number of households possessing electric household appliances such as dryers and dishwashers, an increase in real disposable household income and in the floor space of dwellings. (author)

  2. The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration

    International Nuclear Information System (INIS)

    Narayan, P.K.; Smyth, R.

    2005-01-01

    This paper reports estimates of the long- and short-run elasticities of residential demand for electricity in Australia using the bounds testing procedure to cointegration, within an autoregressive distributive lag framework. In the long run, we find that income and own price are the most important determinants of residential electricity demand, while temperature is significant some of the time and gas prices are insignificant. Our estimates of long-run income elasticity and price elasticity of demand are consistent with previous studies, although they are towards the lower end of existing estimates. As expected, the short-run elasticities are much smaller than the long-run elasticities, and the coefficients on the error-correction coefficients are small consistent with the fact that in the short-run energy appliances are fixed. (author)

  3. Mining residential water and electricity demand data in Southern California to inform demand management strategies

    Science.gov (United States)

    Cominola, A.; Spang, E. S.; Giuliani, M.; Castelletti, A.; Loge, F. J.; Lund, J. R.

    2016-12-01

    Demand side management strategies are key to meet future water and energy demands in urban contexts, promote water and energy efficiency in the residential sector, provide customized services and communications to consumers, and reduce utilities' costs. Smart metering technologies allow gathering high temporal and spatial resolution water and energy consumption data and support the development of data-driven models of consumers' behavior. Modelling and predicting resource consumption behavior is essential to inform demand management. Yet, analyzing big, smart metered, databases requires proper data mining and modelling techniques, in order to extract useful information supporting decision makers to spot end uses towards which water and energy efficiency or conservation efforts should be prioritized. In this study, we consider the following research questions: (i) how is it possible to extract representative consumers' personalities out of big smart metered water and energy data? (ii) are residential water and energy consumption profiles interconnected? (iii) Can we design customized water and energy demand management strategies based on the knowledge of water- energy demand profiles and other user-specific psychographic information? To address the above research questions, we contribute a data-driven approach to identify and model routines in water and energy consumers' behavior. We propose a novel customer segmentation procedure based on data-mining techniques. Our procedure consists of three steps: (i) extraction of typical water-energy consumption profiles for each household, (ii) profiles clustering based on their similarity, and (iii) evaluation of the influence of candidate explanatory variables on the identified clusters. The approach is tested onto a dataset of smart metered water and energy consumption data from over 1000 households in South California. Our methodology allows identifying heterogeneous groups of consumers from the studied sample, as well as

  4. Response of residential electricity demand to price: The effect of measurement error

    International Nuclear Information System (INIS)

    Alberini, Anna; Filippini, Massimo

    2011-01-01

    In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured. To address these issues, we estimate a dynamic partial adjustment model using the Kiviet corrected Least Square Dummy Variables (LSDV) (1995) and the Blundell-Bond (1998) estimators. We find that the long-term elasticities produced by the Blundell-Bond system GMM methods are largest, and that from the bias-corrected LSDV are greater than that from the conventional LSDV. From an energy policy point of view, the results obtained using the Blundell-Bond estimator where we instrument for price imply that a carbon tax or other price-based policy may be effective in discouraging residential electricity consumption and hence curbing greenhouse gas emissions in an electricity system mainly based on coal and gas power plants. - Research Highlights: → Updated information on price elasticities for the US energy policy. → Taking into account measurement error in the price variable increase price elasticity. → Room for discouraging residential electricity consumption using price increases.

  5. Estimating short and long-term residential demand for electricity. New evidence from Sri Lanka

    Energy Technology Data Exchange (ETDEWEB)

    Athukorala, P.P.A Wasantha; Wilson, Clevo [School of Economics and Finance, Queensland University of Technology, Brisbane (Australia)

    2010-09-15

    This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand - per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas - using annual data for Sri Lanka for the period, 1960-2007. The study uses unit root, cointegration and error-correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, - 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 0.32, - 0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity of 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity and (4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages in the country. (author)

  6. Estimating short and long-term residential demand for electricity. New evidence from Sri Lanka

    International Nuclear Information System (INIS)

    Athukorala, P.P.A Wasantha; Wilson, Clevo

    2010-01-01

    This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand - per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas - using annual data for Sri Lanka for the period, 1960-2007. The study uses unit root, cointegration and error-correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, - 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 0.32, - 0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity of 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity and (4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages in the country. (author)

  7. The Risk of Residential Peak Electricity Demand: A Comparison of Five European Countries

    Directory of Open Access Journals (Sweden)

    Jacopo Torriti

    2017-03-01

    Full Text Available The creation of a Europe-wide electricity market combined with the increased intermittency of supply from renewable sources calls for an investigation into the risk of aggregate peak demand. This paper makes use of a risk model to assess differences in time-use data from residential end-users in five different European electricity markets. Drawing on the Multinational Time-Use Survey database, it assesses risk in relation to the probability of electrical appliance use within households for five European countries. Findings highlight in which countries and for which activities the risk of aggregate peak demand is higher and link smart home solutions (automated load control, dynamic pricing and smart appliances to different levels of peak demand risk.

  8. Reducing Gridlock on the Grid: Utility Trends in Managing Peak Electric Load through Residential Demand Response

    Science.gov (United States)

    McDonald, Betsy

    Utilities across the United States are piloting residential demand response programs to help manage peak electric demand. Using publicly available program evaluations, this thesis analyzes nine such programs to uncover and synthesize the range of program offerings, goals, enrollment strategies, and customer experiences. This review reveals that program participation, components, and results differ based on a variety of factors, including geographic characteristics, program goals, and implementation strategies. The diversity of program designs and evaluation findings suggests an underlying tension between the need to generate cost-effective program impacts and the desire to increase accessibility so that program benefits are not exclusive to certain segments of the population. For more significant and impactful engagement, program goals may need to shift. State level policy support could help shift program goals toward increasing program accessibility. Future research should explore creative strategies that target existing barriers and allow for more inclusive deployment.

  9. The long-run price sensitivity dynamics of industrial and residential electricity demand: The impact of deregulating electricity prices

    International Nuclear Information System (INIS)

    Adom, Philip Kofi

    2017-01-01

    This study examines the demand-side of Ghana's electricity sector. We test two important related hypotheses: (1) deregulation of electricity price does not promote energy conservation, and (2) demand-price relationship is not an inverted U-shaped. The Stock and Watson dynamic OLS is used to address the so-called second-order bias. The result showed that, deregulation of electricity price in Ghana has induced behaviours that are more consistent with energy conservation improvements. The demand-price relationship is an inverted U, which suggests that there is a price range that end-users can tolerate further price rise and still increase their consumption of electricity. However, the degree of price tolerability is higher for residential consumers than industrial consumers. The simulation results showed that, further economic growth is likely to compromise energy conservation but more in the industrial sector than the residential sector. On the other hand, future crude oil price is likely to deteriorate energy conservation in the initial years after 2016, but this trend is likely to reverse after the year 2020. Pricing mechanisms are potent to induce energy conservation but inadequate. The results suggest that they should be complemented with other stringent policies such as a mandatory energy reduction policy, investment in renewables, and personalization of energy efficiency programs. - Highlights: • Studies the demand-side of the electricity sector • Deregulating electricity price promotes energy conservation • Demand-price relationship is an inverted U-shaped • Pricing policies should be combined with other energy mandatory reduction policies

  10. Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand

    Science.gov (United States)

    Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

    2015-01-01

    Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the

  11. Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand.

    Science.gov (United States)

    Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

    2015-01-01

    Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers' peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers' location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual 'map' of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations

  12. Massive coordination of residential embedded electricity generation and demand response using the PowerMatcher approach

    International Nuclear Information System (INIS)

    Kamphuis, I.G.; Hommelberg, M.P.F.; Warmer, C.J.; Kok, J.K.

    2007-01-01

    Different driving forces push the electricity production towards decentralization. The projected increase of distributed power generation on the residential level with an increasing proportion of intermittent renewable energy resources poses problems for continuously matching the energy balance when coordination takes place centrally. On the other hand, new opportunities arise by intelligent clustering of generators and demand in so-called Virtual Power Plants. Part of the responsibility for new coordination mechanisms, then, has to be laid locally. To achieve this, the current electricity infrastructure is expected to evolve into a network of networks (including ICT (Information and Communication Technology)-networks), in which all system parts communicate with one another, are aware of each other's context and may influence each other. In this paper, a multi-agent systems approach, using price signal-vectors from an electronic market is presented as an appropriate technology needed for massive control and coordination tasks in these future electricity networks. The PowerMatcher, a market-based control concept for supply and demand matching (SDM) in electricity networks, is discussed. The results within a simulation study show the ability to raise the simultaneousness of electricity production and consumption within (local) control clusters with cogeneration and heat-pumps by exchanging price signals and coordinated allocation using market algorithms. The control concept, however, can also be applied in other business cases like reduction of imbalance cost in commercial portfolios or virtual power plant operators, utilizing distributed generators. Furthermore, a PowerMatcher-based field test configuration with 15 Stirling-engine powered micro-CHP's is described, which is currently in operation within a field test in the Netherlands

  13. Industrial and residential electricity demand dynamics in Japan: How did price and income elasticities evolve from 1989 to 2014?

    International Nuclear Information System (INIS)

    Wang, Nan; Mogi, Gento

    2017-01-01

    This study estimates the price and income elasticities of industrial and residential electricity demand in Japan with the annual data from 1989 to 2014. A time varying parameter (TVP) model with the Kalman filter is applied to monitor the evolution of consumer behaviors in the “post-bubble” period given the exogenous shock (financial crisis in 2008) and the structural breaks (electricity deregulation and Fukushima Daiichi crisis). The TVP model can provide a robust estimation of elasticities and can detect the outliers and the structural breaks. The results suggest that both industrial and residential consumers become less sensitive to price after the electricity deregulation and the financial crisis, and more sensitive to price after the Fukushima Daiichi crisis. Especially the industrial sector is less sensitive to price after the retail deregulation. By contrast, the income elasticities of industrial and residential sector consumers are stable during the examined period. Results also indicate that a negative relationship exists between the price elasticity of electricity demand and the price level of electricity after the electric sector deregulation. Some insights on the further electric sector reform and the environmental taxation in Japan are also provided. - Highlights: • A time varying parameter model is calculated with the Kalman filter. • Income elasticities are stable while price elasticities are time-varying. • Industrial sector is less sensitive to price change than residential sector. • Negative relationship between price elasticity and price level is found.

  14. Impact of roof integrated PV orientation on the residential electricity peak demand

    International Nuclear Information System (INIS)

    Sadineni, Suresh B.; Atallah, Fady; Boehm, Robert F.

    2012-01-01

    Highlights: ► A study to demonstrate peak load reductions at the substation. ► A new residential energy efficient community named Villa Trieste is being developed. ► The peak demand from the homes has decreased by 38% through energy efficiency. ► Orientation of roof integrated PV has less influence on the summer peak demand. ► Increasing thermostat temperature during peak by 1 °C can significantly reduce peaks. -- Abstract: Peak electricity demand has been an issue in the Desert Southwest region of the US, due to extreme summer temperatures. To address this issue, a consortium was formed between the University of Nevada, Las Vegas, Pulte Homes, and NV Energy. An energy efficient residential community was developed by the team in Las Vegas with approximately 200 homes to study substation-level peak reduction strategies. A summer peak reduction of more than 65%, between 1:00 PM and 7:00 PM, compared to code standard housing developments is the targeted goal of the project. Approximately 50 homes are already built and some are occupied. The energy performances of the homes have been monitored and are presented in this paper. Several peak electric load reduction strategies such as energy efficiency in buildings, roof integrated photovoltaics (PV) and direct load control have been applied. Though all the homes in the developed community are installed with 1.8 kW p PV systems, the orientation of the PV system depends on the building orientation. Focus of this paper is to find the impact of PV orientation on the peak load from a building. In addition, different time-of-use (TOU) energy pricing options are offered by the local electrical utility company. Hence it is important to find an optimal pricing option for each building. A computer model has been developed for one of the homes in the new development using building energy simulation code, ENERGY-10. Calculations on the PV orientations have shown that a south and 220° (i.e. 40° west of due south

  15. Electricity demand in Kazakhstan

    International Nuclear Information System (INIS)

    Atakhanova, Zauresh; Howie, Peter

    2007-01-01

    Properties of electricity demand in transition economies have not been sufficiently well researched mostly due to data limitations. However, information on the properties of electricity demand is necessary for policy makers to evaluate effects of price changes on different consumers and obtain demand forecasts for capacity planning. This study estimates Kazakhstan's aggregate demand for electricity as well as electricity demand in the industrial, service, and residential sectors using regional data. Firstly, our results show that price elasticity of demand in all sectors is low. This fact suggests that there is considerable room for price increases necessary to finance generation and distribution system upgrading. Secondly, we find that income elasticity of demand in the aggregate and all sectoral models is less than unity. Of the three sectors, electricity demand in the residential sector has the lowest income elasticity. This result indicates that policy initiatives to secure affordability of electricity consumption to lower income residential consumers may be required. Finally, our forecast shows that electricity demand may grow at either 3% or 5% per year depending on rates of economic growth and government policy regarding price increases and promotion of efficiency. We find that planned supply increases would be sufficient to cover growing demand only if real electricity prices start to increase toward long-run cost-recovery levels and policy measures are implemented to maintain the current high growth of electricity efficiency

  16. Progress towards Managing Residential Electricity Demand: Impacts of Standards and Labeling for Refrigerators and Air Conditioners in India

    Energy Technology Data Exchange (ETDEWEB)

    McNeil, Michael A.; Iyer, Maithili

    2009-05-30

    The development of Energy Efficiency Standards and Labeling (EES&L) began in earnest in India in 2001 with the Energy Conservation Act and the establishment of the Indian Bureau of Energy Efficiency (BEE). The first main residential appliance to be targeted was refrigerators, soon to be followed by room air conditioners. Both of these appliances are of critical importance to India's residential electricity demand. About 15percent of Indian households own a refrigerator, and sales total about 4 million per year, but are growing. At the same time, the Indian refrigerator market has seen a strong trend towards larger and more consumptive frost-free units. Room air conditioners in India have traditionally been sold to commercial sector customers, but an increasing number are going to the residential sector. Room air conditioner sales growth in India peaked in the last few years at 20percent per year. In this paper, we perform an engineering-based analysis using data specific to Indian appliances. We evaluate costs and benefits to residential and commercial sector consumers from increased equipment costs and utility bill savings. The analysis finds that, while the BEE scheme presents net benefits to consumers, there remain opportunities for efficiency improvement that would optimize consumer benefits, according to Life Cycle Cost analysis. Due to the large and growing market for refrigerators and air conditioners in India, we forecast large impacts from the standards and labeling program as scheduled. By 2030, this program, if fully implemented would reduce Indian residential electricity consumption by 55 TWh. Overall savings through 2030 totals 385 TWh. Finally, while efficiency levels have been set for several years for refrigerators, labels and MEPS for these products remain voluntary. We therefore consider the negative impact of this delay of implementation to energy and financial savings achievable by 2030.

  17. The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency

    Energy Technology Data Exchange (ETDEWEB)

    Letschert, Virginie; McNeil, Michael A.

    2008-05-13

    With the emergence of China as the world's largest energy consumer, the awareness of developing country energy consumption has risen. According to common economic scenarios, the rest of the developing world will probably see an economic expansion as well. With this growth will surely come continued rapid growth in energy demand. This paper explores the dynamics of that demand growth for electricity in the residential sector and the realistic potential for coping with it through efficiency. In 2000, only 66% of developing world households had access to electricity. Appliance ownership rates remain low, but with better access to electricity and a higher income one can expect that households will see their electricity consumption rise significantly. This paper forecasts developing country appliance growth using econometric modeling. Products considered explicitly - refrigerators, air conditioners, lighting, washing machines, fans, televisions, stand-by power, water heating and space heating - represent the bulk of household electricity consumption in developing countries. The resulting diffusion model determines the trend and dynamics of demand growth at a level of detail not accessible by models of a more aggregate nature. In addition, the paper presents scenarios for reducing residential consumption through cost-effective and/or best practice efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, which allows for a realistic assessment of efficiency opportunities at the national or regional level. The past decades have seen some of the developing world moving towards a standard of living previously reserved for industrialized countries. Rapid economic development, combined with large populations has led to first China and now India to emerging as &apos

  18. Analysis of PG&E`s residential end-use metered data to improve electricity demand forecasts -- final report

    Energy Technology Data Exchange (ETDEWEB)

    Eto, J.H.; Moezzi, M.M.

    1993-12-01

    This report summarizes findings from a unique project to improve the end-use electricity load shape and peak demand forecasts made by the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). First, the direct incorporation of end-use metered data into electricity demand forecasting models is a new approach that has only been made possible by recent end-use metering projects. Second, and perhaps more importantly, the joint-sponsorship of this analysis has led to the development of consistent sets of forecasting model inputs. That is, the ability to use a common data base and similar data treatment conventions for some of the forecasting inputs frees forecasters to concentrate on those differences (between their competing forecasts) that stem from real differences of opinion, rather than differences that can be readily resolved with better data. The focus of the analysis is residential space cooling, which represents a large and growing demand in the PG&E service territory. Using five years of end-use metered, central air conditioner data collected by PG&E from over 300 residences, we developed consistent sets of new inputs for both PG&E`s and CEC`s end-use load shape forecasting models. We compared the performance of the new inputs both to the inputs previously used by PG&E and CEC, and to a second set of new inputs developed to take advantage of a recently added modeling option to the forecasting model. The testing criteria included ability to forecast total daily energy use, daily peak demand, and demand at 4 P.M. (the most frequent hour of PG&E`s system peak demand). We also tested the new inputs with the weather data used by PG&E and CEC in preparing their forecasts.

  19. Controlling the demand for electricity: strategies and challenges in the residential sector of the OECD countries

    International Nuclear Information System (INIS)

    Lebot, B.

    2003-01-01

    By reinforcing policies to improve the energy efficiency of household appliances (particularly by rating the efficiency of each appliance as a minimum of its overall cost from 2005 onwards), the member countries of the IEA are in a position to reduce their annual CO 2 emissions by approximately 322 million tonnes (Mt) by 2010, compared to what they would have obtained using current policies. In 2030, this same policy will make it possible to achieve an annual saving of 1 110 TWh in the consumption of electricity, (572 Mt of CO 2 each year). This measure alone will meet 30% of the objectives of the member countries of the IEA under the Kyoto agreements concerning climatic change. These reductions can be obtained at a negative cost for society as the additional cost generated by improvements in energy efficiency is offset by savings made in operating costs during the life of the appliance. Thus, in the United States, each tonne of CO 2 saved in this way in 2020 will generate $65 for society. In Europe, every tonne of CO 2 saved will generate a gain of euros 169 (the difference being accounted for by the higher cost of electricity and by lower energy efficiency standards currently existing in Europe). It is possible to make major savings in all regions of the OECD, despite the vast diversity of the various situations of the countries. In the member countries of the IEA, the policies in place have already demonstrated their economic effectiveness in reducing demand for energy and greenhouse gas emissions. Up to 2000, they made it possible to reduce greenhouse gas emissions by approximately 46 Mt of CO 2 each year. These policies will contribute to reducing emissions by 126 Mt of CO 2 each year up to 2010. International co-operation offers real advantages in the deployment of policies for controlling the demand for energy by households. Manufacturers, consumers and governments all benefit from greater transparency in the marketplace, improved comparisons of test methods

  20. The role of energy and investment literacy for residential electricity demand and end-use efficiency

    NARCIS (Netherlands)

    Blasch, J.E.; Boogen, Nina; Filippini, Massimo; Kumar, Nilkanth

    2017-01-01

    This paper estimates the level of transient and persistent efficiency in the use of electricity in Swiss households using the newly developed generalized true random effects model (GTREM). An unbalanced panel dataset of 1, 994 Swiss households from 2010 to 2014 collected via a household survey is

  1. Residential Electricity Consumption in Poland

    Directory of Open Access Journals (Sweden)

    Edyta Ropuszyńska-Surma

    2016-01-01

    Full Text Available Key factors influencing electricity consumption in the residential sector in Poland have been identified. A fixed-effects model was used, which includes time effects, and a set of covariates, based on the model developed by Houthakker et al. This model estimates electricity demand by using lagged values of the dependent variable along with current and lagged values of electricity prices, and other variables that affect electricity demand such as: population, economic growth, income per capita, price of related goods, etc. The model has been identified according to the research results of the authors and those obtained by Bentzen and Engsted. The set of covariates was extended to the lagged electricity price given by a tariff (taken from two years previous to the time of interest and heating degree days index, a very important factor in European Union countries, where the climate is temperate. The authors propose four models of residential electricity demand, for which a confidence interval of 95% has been assumed. Estimation was based on Polish quarterly data for the years 2003-2013. (original abstract

  2. Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response

    International Nuclear Information System (INIS)

    Zheng, Menglian; Meinrenken, Christoph J.; Lackner, Klaus S.

    2014-01-01

    Highlights: • Storage-based demand response (loadshifting) is underutilized in residential sector. • Economics (arbitrage savings versus equipment cost) are not well understood. • Stochastic demand models and real-life tariffs can illuminate economic viability. • A range of available storage options provide economically viable DR. • Daily/seasonal stochastic demand variations crucial to understanding optimum capacity. - Abstract: Demand response (DR) is one of many approaches to address temporal mismatches in demand and supply of grid electricity. More common in the commercial sector, DR usually refers to reducing consumption at certain hours or seasons, thus reducing peak demand from the grid. In the residential sector, where sophisticated appliance-level controls such as automatic dimming of lights or on-demand lowering of air conditioning are less common, building-based electricity storage to shift grid consumption from peak to off-peak times could provide DR without requiring consumers to operate their appliances on shifted or reduced schedules: Storage would be dispatched to appliances as needed while still shaving peaks on the grid. Technologically, storage and two-way-inverters are readily available to enable such residential DR. Economically, however, the situation is less clear. Specifically, are time-varying electricity tariffs available such that electricity cost reduction via arbitrage could offset manufacturing, financing, and installation costs of the required storage? To address this question we (i) devise an agent-based appliance-level stochastic model to simulate the electricity demand of an average U.S. household; (ii) loadshift the demand via simple dispatch strategies; and (iii) determine potential profits to the building owner, i.e. reduced electricity cost of the modified demand with realistic tariffs (Con Edison, NY) minus storage cost. We determine the economic viability for a range of traditional and advanced storage technologies

  3. A High-Resolution Spatially Explicit Monte-Carlo Simulation Approach to Commercial and Residential Electricity and Water Demand Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Morton, April M [ORNL; McManamay, Ryan A [ORNL; Nagle, Nicholas N [ORNL; Piburn, Jesse O [ORNL; Stewart, Robert N [ORNL; Surendran Nair, Sujithkumar [ORNL

    2016-01-01

    Abstract As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for high resolution spatially explicit estimates for energy and water demand has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy and water consumption, many are provided at a course spatial resolution or rely on techniques which depend on detailed region-specific data sources that are not publicly available for many parts of the U.S. Furthermore, many existing methods do not account for errors in input data sources and may therefore not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more flexible Monte-Carlo simulation approach to high-resolution residential and commercial electricity and water consumption modeling that relies primarily on publicly available data sources. The method s flexible data requirement and statistical framework ensure that the model is both applicable to a wide range of regions and reflective of uncertainties in model results. Key words: Energy Modeling, Water Modeling, Monte-Carlo Simulation, Uncertainty Quantification Acknowledgment This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

  4. ELECTRICITY DEMAND AND ELECTRICITY VALUE

    OpenAIRE

    Henry Lim; Glenn Jenkins

    2000-01-01

    The estimation of the demand for electricity is important in the appraisal of power projects because it often affects the benefits of the projects. For projects that involve a decision about the timing of investment- when to install new capacity to meet the demand- the precision of the electricity demand forecast can be critical. For others, when electric tariff policy is involved, it is essential to relate the demand for electricity with tariffs through the use of an electricity demand model...

  5. Influence of India’s transformation on residential energy demand

    International Nuclear Information System (INIS)

    Bhattacharyya, Subhes C.

    2015-01-01

    Highlights: • The middle income group emerges as the dominant segment by 2030. • Commercial residential energy demand increases 3–4 folds compared to 2010. • Electricity and LPG demand grows above 6% per year in the reference scenario. • India faces the potential of displacing the domination of biomass by 2030. - Abstract: India’s recent macro-economic and structural changes are transforming the economy and bringing significant changes to energy demand behaviour. Life-style and consumption behaviour are evolving rapidly due to accelerated economic growth in recent times. The population structure is changing, thereby offering the country with the potential to reap the population dividend. The country is also urbanising rapidly, and the fast-growing middle class segment of the population is fuelling consumerism by mimicking international life-styles. These changes are likely to have significant implications for energy demand in the future, particularly in the residential sector. Using the end-use approach of demand analysis, this paper analyses how residential energy demand is likely to evolve as a consequence of India’s transformation and finds that by 2030, India’s commercial energy demand in the residential sector can quadruple in the high scenario compared to the demand in 2010. Demand for modern fuels like electricity and liquefied petroleum gas is likely to grow at a faster rate. However, there is a window of opportunity to better manage the evolution of residential demand in India through energy efficiency improvement

  6. Change in consumer sensitivity to electricity prices in response to retail deregulation: A panel empirical analysis of the residential demand for electricity in the United States

    International Nuclear Information System (INIS)

    Nakajima, Tadahiro; Hamori, Shigeyuki

    2010-01-01

    About ten years have passed since the deregulation of the U.S. retail electricity market, and it is now generally accepted that the available data is adequate to quantitatively assess and compare conditions before and after deregulation. This study, therefore, estimates the changes in price elasticity in the residential electricity market to examine the changes, if any, in household sensitivity (as a result of retail electricity market deregulation policies) to residential electricity rates. Specifically, six types of panel data are prepared, based on three cross-sections-all states (except for Alaska and Hawaii) and the District of Columbia, deregulated states, and non-deregulated states-and two time series-the period before deregulation and the period after deregulation. The panel empirical analysis techniques are used to determine whether or not the variables are stationary, and to estimate price elasticity. We find that there is no substantial difference in the price elasticity between deregulated and non-deregulated states for both periods-before deregulation and after deregulation. Thus, it can be said that the deregulation of the retail electricity market has not made consumers more sensitive to electricity rates and that retail deregulation policies are not the cause of price elasticity differences between deregulated and non-deregulated states.

  7. Electrical network capacity support from demand side response: Techno-economic assessment of potential business cases for small commercial and residential end-users

    International Nuclear Information System (INIS)

    Martínez Ceseña, Eduardo A.; Good, Nicholas; Mancarella, Pierluigi

    2015-01-01

    Demand Side Response (DSR) is recognised for its potential to bring economic benefits to various electricity sector actors, such as energy retailers, Transmission System Operators (TSOs) and Distribution Network Operators (DNOs). However, most DSR is provided by large industrial and commercial consumers, and little research has been directed to the quantification of the value that small (below 100 kW) commercial and residential end-users could accrue by providing DSR services. In particular, suitable models and studies are needed to quantify potential business cases for DSR from small commercial and residential end-users. Such models and studies should consider the technical and physical characteristics of the power system and demand resources, together with the economic conditions of the power market. In addition, the majority of research focuses on provision of energy arbitrage or ancillary services, with very little attention to DSR services for network capacity support. Accordingly, this paper presents comprehensive techno-economic methodologies for the quantification of three capacity-based business cases for DSR from small commercial and residential end-users. Case study results applied to a UK context indicate that, if the appropriate regulatory framework is put in place, services for capacity support to both DNOs and TSOs can result into potentially attractive business cases for DSR from small end-users with minimum impact on their comfort level. -- Highlights: •We present three business cases for DSR from domestic and commercial end-users. •A comprehensive techno-economic methodology is proposed for the quantification of each DSR business cases. •The regulatory implications associated with each business case are discussed

  8. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  9. Comprehensive areal model of residential heating demands

    Energy Technology Data Exchange (ETDEWEB)

    Tessmer, R.G. Jr.

    1978-01-01

    Data sources and methodology for modeling annual residential heating demands are described. A small areal basis is chosen, census tract or minor civil division, to permit estimation of demand densities and economic evaluation of community district heating systems. The demand model is specified for the entire nation in order to provide general applicability and to permit validation with other published fuel consumption estimates for 1970.

  10. A hybrid society model for simulating residential electricity consumption

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Minjie [School of Electrical Engineering, Beijing Jiaotong University, Beijing (China); State Power Economic Research Institute, Beijing (China); Hu, Zhaoguang [State Power Economic Research Institute, Beijing (China); Wu, Junyong; Zhou, Yuhui [School of Electrical Engineering, Beijing Jiaotong University, Beijing (China)

    2008-12-15

    In this paper, a hybrid social model of econometric model and social influence model is proposed for evaluating the influence of pricing policy and public education policy on residential habit of electricity using in power resources management. And, a hybrid society simulation platform based on the proposed model, called residential electricity consumption multi-agent systems (RECMAS), is designed for simulating residential electricity consumption by multi-agent system. RECMAS is composed of consumer agent, power supplier agent, and policy maker agent. It provides the policy makers with a useful tool to evaluate power price policies and public education campaigns in different scenarios. According to an influenced diffusion mechanism, RECMAS can simulate the residential electricity demand-supply chain and analyze impacts of the factors on residential electricity consumption. Finally, the proposed method is used to simulate urban residential electricity consumption in China. (author)

  11. A hybrid society model for simulating residential electricity consumption

    International Nuclear Information System (INIS)

    Xu, Minjie; Hu, Zhaoguang; Wu, Junyong; Zhou, Yuhui

    2008-01-01

    In this paper, a hybrid social model of econometric model and social influence model is proposed for evaluating the influence of pricing policy and public education policy on residential habit of electricity using in power resources management. And, a hybrid society simulation platform based on the proposed model, called residential electricity consumption multi-agent systems (RECMAS), is designed for simulating residential electricity consumption by multi-agent system. RECMAS is composed of consumer agent, power supplier agent, and policy maker agent. It provides the policy makers with a useful tool to evaluate power price policies and public education campaigns in different scenarios. According to an influenced diffusion mechanism, RECMAS can simulate the residential electricity demand-supply chain and analyze impacts of the factors on residential electricity consumption. Finally, the proposed method is used to simulate urban residential electricity consumption in China. (author)

  12. Detailed residential electric determination

    Energy Technology Data Exchange (ETDEWEB)

    1984-06-01

    Data on residential loads has been collected from four residences in real time. The data, measured at 5-second intervals for 53 days of continuous operation, were statistically characterized. An algorithm was developed and incorporated into the modeling code SOLCEL. Performance simulations with SOLCEL using these data as well as previous data collected over longer time intervals indicate that no significant errors in system value are introduced through the use of long-term average data.

  13. Social implications of residential demand response in cool temperate climates

    International Nuclear Information System (INIS)

    Darby, Sarah J.; McKenna, Eoghan

    2012-01-01

    Residential electrical demand response (DR) offers the prospect of reducing the environmental impact of electricity use, and also the supply costs. However, the relatively small loads and numerous actors imply a large effort: response ratio. Residential DR may be an essential part of future smart grids, but how viable is it in the short to medium term? This paper reviews some DR concepts, then evaluates the propositions that households in cool temperate climates will be in a position to contribute to grid flexibility within the next decade, and that that they will allow some automated load control. Examples of demand response from around the world are discussed in order to assess the main considerations for cool climates. Different tariff types and forms of control are assessed in terms of what is being asked of electricity users, with a focus on real-time pricing and direct load control in energy systems with increasingly distributed resources. The literature points to the significance of thermal loads, supply mix, demand-side infrastructure, market regulation, and the framing of risks and opportunities associated with DR. In concentrating on social aspects of residential demand response, the paper complements the body of work on technical and economic potential. - Highlights: ► Demand response implies major change in governance of electricity systems. ► Households in cool temperate climates can be flexible, mainly with thermal loads. ► DR requires simple tariffs, appropriate enabling technology, education, and feedback. ► Need to test consumer acceptance of DR in specific conditions. ► Introduce tariffs with technologies e.g., TOU tariff plus DLC with electric vehicles.

  14. Probabilistic Quantification of Potentially Flexible Residential Demand

    DEFF Research Database (Denmark)

    Kouzelis, Konstantinos; Mendaza, Iker Diaz de Cerio; Bak-Jensen, Birgitte

    2014-01-01

    The balancing of power systems with high penetration of renewable energy is a serious challenge to be faced in the near future. One of the possible solutions, recently capturing a lot of attention, is demand response. Demand response can only be achieved by power consumers holding loads which allow...... them to modify their normal power consumption pattern, namely flexible consumers. However flexibility, despite being constantly mentioned, is usually not properly defined and even rarer quantified. This manuscript introduces a methodology to identify and quantify potentially flexible demand...... of residential consumers. The procedure is based on non-flexible consumer clustering and subsequent statistical analysis. Consequently, the power consumption pattern of a flexible consumer is compared to a 3D probability distribution created by the previously referred methodology. The results show a strong...

  15. Autonomous Hybrid Priority Queueing for Scheduling Residential Energy Demands

    Science.gov (United States)

    Kalimullah, I. Q.; Shamroukh, M.; Sahar, N.; Shetty, S.

    2017-05-01

    The advent of smart grid technologies has opened up opportunities to manage the energy consumption of the users within a residential smart grid system. Demand response management is particularly being employed to reduce the overall load on an electricity network which could in turn reduce outages and electricity costs. The objective of this paper is to develop an intelligible scheduler to optimize the energy available to a micro grid through hybrid queueing algorithm centered around the consumers’ energy demands. This is achieved by shifting certain schedulable load appliances to light load hours. Various factors such as the type of demand, grid load, consumers’ energy usage patterns and preferences are considered while formulating the logical constraints required for the algorithm. The algorithm thus obtained is then implemented in MATLAB workspace to simulate its execution by an Energy Consumption Scheduler (ECS) found within smart meters, which automatically finds the optimal energy consumption schedule tailor made to fit each consumer within the micro grid network.

  16. Demand Side Management in non-residential buildings; Demand Side Management in Nichtwohngebaeuden

    Energy Technology Data Exchange (ETDEWEB)

    Jungwirth, Johannes [Technische Univ. Muenchen (DE). Lehrstuhl fuer Energiewirtschaft und Anwendungstechnik (IfE)

    2011-07-01

    Due to the fluctuating supply characteristics and a paradigm shift, the strong expansion of renewable energy generators expect the structure of the concept of energy supply. An integration of renewables into the electricity grid requires new ways to compensate the discrepancy between production and consumption. The implementation of a demand-side management requires an electrical load and the possibility to control consumers in response to an external signal. From this perspective, the author of the contribution under consideration reports on innovative systems for the realization of a demand-side management in non-residential buildings.

  17. Estimating Response to Price Signals in Residential Electricity Consumption

    OpenAIRE

    Huang, Yizhang

    2013-01-01

    Based on a previous empirical study of the effect of a residential demand response program in Sala, Sweden, this project  investigated the economic consequences of consumer behaviour change after a demand-based time of use distribution tariff was employed. The economic consequences of consumers were proven to be disadvantageous in terms of unit electricity price. Consumers could achieve more electricity bill saving through stabilising their electricity consumption during peak hours, and this ...

  18. Price and income elasticities of residential energy demand in Germany

    International Nuclear Information System (INIS)

    Schulte, Isabella; Heindl, Peter

    2017-01-01

    We apply a quadratic expenditure system to estimate price and expenditure elasticities of residential energy demand (electricity and heating) in Germany. Using official expenditure data from 1993 to 2008, we estimate an expenditure elasticity for electricity of 0.3988 and of 0.4055 for space heating. The own price elasticity for electricity is −0.4310 and −0.5008 in the case of space heating. Disaggregation of households by expenditure and socio-economic composition reveals that the behavioural response to energy price changes is weaker (stronger) for low-income (top-income) households. There are considerable economies of scale in residential energy use but scale effects are not well approximated by the new OECD equivalence scale. Real increases in energy prices show a regressive pattern of incidence, implying that the welfare consequences of direct energy taxation are larger for low income households. The application of zero-elasticities in assessments of welfare consequences of energy taxation strongly underestimates potential welfare effects. The increase in inequality is 22% smaller when compared to the application of disaggregated price and income elasticities as estimated in this paper. - Highlights: • We estimate price, income, and expenditure elasticities for residential energy demand in Germany. • We differentiate elasticities by income groups and household type. • Electricity and space heating are necessary goods since the expenditure elasticities are smaller than unity. • Low-income households show a weaker reaction to changing prices when compared to high-income households. • Direct energy taxation has regressive effects, meaning that larger burdens fall upon low-income households.

  19. Demand of elderly people for residential care: an exploratory study

    NARCIS (Netherlands)

    van Bilsen, P.; Hamers, J.; Groot, W.; Spreeuwenberg, C.

    2006-01-01

    Background: Because of the rapid aging population, the demand for residential care exceeds availability. This paper presents the results of a study that focuses on the demand of elderly people for residential care and determinants (elderly people's personal characteristics, needs and resources) that

  20. Household electricity demand profiles

    DEFF Research Database (Denmark)

    Marszal, Anna Joanna; Heiselberg, Per Kvols; Larsen, Olena Kalyanova

    2016-01-01

    Highlights •A 1-min resolution household electricity load model is presented. •Model adapts a bottom-up approach with single appliance as the main building block. •Load profiles are used to analyse the flexibility potential of household appliances. •Load profiles can be applied in other domains, e...

  1. Modeling and analysis of long term energy demands in residential sector of pakistan

    International Nuclear Information System (INIS)

    Rashid, T.; Sahir, M.H.

    2015-01-01

    Residential sector is the core among the energy demand sectors in Pakistan. Currently, various techniques are being used worldwide to assess future energy demands including integrated system modeling (ISM). Therefore, the current study is focused on implementation of ISM approach for future energy demand analysis of Pakistan's residential sector in terms of increase in population, rapid urbanization, household size and type, and increase/decrease in GDP. A detailed business-as-usual (BAU) model is formulated in TIMES energy modeling framework using different factors like growth in future energy services, end-use technology characterization, and restricted fuel supplies. Additionally, the developed model is capable to compare the projected energy demand under different scenarios e.g. strong economy, weak economy and energy efficiency. The implementation of ISM proved a viable approach to predict the future energy demands of Pakistan's residential sector. Furthermore, the analysis shows that the energy consumption in the residential sector would be 46.5 Mtoe (Million Ton of Oil Equivalent) in 2040 compared to 23 Mtoe of the base year (2007) along with 600% increase in electricity demands. The study further maps the potential residential energy policies to congregate the future demands. (author)

  2. The structure of residential energy demand in Greece

    International Nuclear Information System (INIS)

    Rapanos, Vassilis T.; Polemis, Michael L.

    2006-01-01

    This paper attempts to shed light on the determinants of residential energy demand in Greece, and to compare it with some other OECD countries. From the estimates of the short-run and long-run elasticities of energy demand for the period 1965-1999, we find that residential energy demand appears to be price inelastic. Also, we do not find evidence of a structural change probably because of the low efficiency of the energy sector. We find, however, that the magnitude of the income elasticity varies substantially between Greece and other OECD countries

  3. Demand flexibility from residential heat pump

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2014-01-01

    with high thermal time constant, heat pumps (HP) can offer a great deal of flexibility in the future intelligent grids especially to compensate fluctuating generation. However, the HP flexibility is highly dependent on thermal demand profile, namely hot water and space heating demand. This paper proposes...... price based scheduling followed by a demand dispatch based central control and a local voltage based adaptive control, to realize HP demand flexibility. Two-step control architecture, namely local primary control encompassed by the central coordinative control, is proposed to implement...... the aforementioned control techniques. Results show that HP flexibility can contribute significantly to both the local network and system level balancing....

  4. Projecting Electricity Demand in 2050

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, Donna J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Belzer, David B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Markel, Tony [National Renewable Energy Lab. (NREL), Golden, CO (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kintner-Meyer, Michael C. W. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-07-01

    This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% - 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly data for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.

  5. Simulating Residential Water Demand and Water Pricing Issues

    OpenAIRE

    Phoebe Koundouri; Mavra Stithou; Philippos Melissourgos

    2013-01-01

    This chapter aims to simulate residential water demand in order to explore the importance of water for residential use. In addition, data on the water cost of supplying water in the residents of Asopos area from local distributors were collected. In order to capture the importance of water use specific parameters are examined and are used as indexes of water use. Some of these indexes are the population of the catchment, the number of households connected to the public water distribution syst...

  6. Pilot Evaluation of Energy Savings from Residential Energy Demand Feedback Devices

    Energy Technology Data Exchange (ETDEWEB)

    Parker, Danny S. [Florida Solar Energy Center, Cocoa, FL (United States); Hoak, David [Florida Solar Energy Center, Cocoa, FL (United States); Cummings, Jamie [Florida Solar Energy Center, Cocoa, FL (United States)

    2008-01-01

    This report discusses instantaneous feedback on household electrical demand has shown promise to reduce energy consumption. This report reviews past research and describes a two year pilot evaluation of a low cost residential energy feedback system installed in twenty case study homes in FL.

  7. Optimized Energy Management of a Single-House Residential Micro-Grid With Automated Demand Response

    DEFF Research Database (Denmark)

    Anvari-Moghaddam, Amjad; Monsef, Hassan; Rahimi-Kian, Ashkan

    2015-01-01

    In this paper, an intelligent multi-objective energy management system (MOEMS) is proposed for applications in residential LVAC micro-grids where households are equipped with smart appliances, such as washing machine, dishwasher, tumble dryer and electric heating and they have the capability to t...... to reduce residential energy use and improve the user’s satisfaction degree by optimal management of demand/generation sides.......In this paper, an intelligent multi-objective energy management system (MOEMS) is proposed for applications in residential LVAC micro-grids where households are equipped with smart appliances, such as washing machine, dishwasher, tumble dryer and electric heating and they have the capability...... to take part in demand response (DR) programs. The superior performance and efficiency of the proposed system is studied through several scenarios and case studies and validated in comparison with the conventional models. The simulation results demonstrate that the proposed MOEMS has the capability...

  8. Second life battery energy storage system for residential demand response service

    DEFF Research Database (Denmark)

    Saez-de-Ibarra, Andoni; Martinez-Laserna, Egoitz; Koch-Ciobotaru, Cosmin

    2015-01-01

    The integration of renewable energies and the usage of battery energy storage systems (BESS) into the residential buildings opens the possibility for minimizing the electricity bill for the end-user. This paper proposes the use of batteries that have already been aged while powering electric...... vehicles, during their main first life application, for providing residential demand response service. The paper considers the decayed characteristics of these batteries and optimizes the rating of such a second life battery energy storage system (SLBESS) for maximizing the economic benefits of the user...

  9. The impact of residential demand response on the costs of a fossil-free system reserve

    DEFF Research Database (Denmark)

    Katz, Jonas; Balyk, Olexandr; Hevia Koch, Pablo Alejandro

    2016-01-01

    In order to achieve a better understanding of the system value of residential demand response, we study the potential impact of flexible demand on the costs of system reserves in a fossil-free electricity supply. Comparing these costs with traditional means of regulation our analysis aims...... to contribute to determining the least-cost options for regulation in a fossil-free power system. We extend an existing energy system model with demand response and reserve modelling and analyse the impact for the case of Denmark in 2035 to reflect a system based on renewable resources for electricity...

  10. Load curve modelling of the residential segment electric power consumption applying a demand side energy management program; Modelagem da curva de carga das faixas de consumo de energia eletrica residencial a partir da aplicacao de um programa de gerenciamento de energia pelo lado da demanda

    Energy Technology Data Exchange (ETDEWEB)

    Rahde, Sergio Barbosa [Pontificia Univ. Catolica do Rio Grande do Sul, Porto Alegre (Brazil). Dept. de Engenharia Mecanica e Mecatronica]. E-mail: sergio@em.pucrs.br; Kaehler, Jose Wagner [Pontificia Univ. Catolica do Rio Grande do Sul, Porto Alegre (Brazil). Faculdade de Engenharia]. E-mail: kaehlerjw@pucrs.br

    2000-07-01

    The dissertation aims to offer a current vision on the use of electrical energy inside CEEE's newly defined area of operation. It also intends to propose different alternatives to set up a Demand Side Management (DSM) project to be carried out on the same market segment, through a Residential Load Management program. Starting from studies developed by DNAEE (the Brazilian federal government's agency for electrical energy), to establish the load curve characteristics, as well as from a research on electrical equipment ownership and electricity consumption habits, along with the contribution supplied by other utilities, especially in the US, an evaluation is offered, concerning several approaches to residential energy management, setting up conditions that simulate the residential segment's scenarios and their influence on the general system's load. (author)

  11. Reforming residential electricity tariff in China: Block tariffs pricing approach

    International Nuclear Information System (INIS)

    Sun, Chuanwang; Lin, Boqiang

    2013-01-01

    The Chinese households that make up approximately a quarter of world households are facing a residential power tariff reform in which a rising block tariff structure will be implemented, and this tariff mechanism is widely used around the world. The basic principle of the structure is to assign a higher price for higher income consumers with low price elasticity of power demand. To capture the non-linear effects of price and income on elasticities, we set up a translog demand model. The empirical findings indicate that the higher income consumers are less sensitive than those with lower income to price changes. We further put forward three proposals of Chinese residential electricity tariffs. Compared to a flat tariff, the reasonable block tariff structure generates more efficient allocation of cross-subsidies, better incentives for raising the efficiency of electricity usage and reducing emissions from power generation, which also supports the living standards of low income households. - Highlights: • We design a rising block tariff structure of residential electricity in China. • We set up a translog demand model to find the non-linear effects on elasticities. • The higher income groups are less sensitive to price changes. • Block tariff structure generates more efficient allocation of cross-subsidies. • Block tariff structure supports the living standards of low income households

  12. Impact of Rate Design Alternatives on Residential Solar Customer Bills. Increased Fixed Charges, Minimum Bills and Demand-based Rates

    Energy Technology Data Exchange (ETDEWEB)

    Bird, Lori [National Renewable Energy Lab. (NREL), Golden, CO (United States); Davidson, Carolyn [National Renewable Energy Lab. (NREL), Golden, CO (United States); McLaren, Joyce [National Renewable Energy Lab. (NREL), Golden, CO (United States); Miller, John [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2015-09-01

    With rapid growth in energy efficiency and distributed generation, electric utilities are anticipating stagnant or decreasing electricity sales, particularly in the residential sector. Utilities are increasingly considering alternative rates structures that are designed to recover fixed costs from residential solar photovoltaic (PV) customers with low net electricity consumption. Proposed structures have included fixed charge increases, minimum bills, and increasingly, demand rates - for net metered customers and all customers. This study examines the electricity bill implications of various residential rate alternatives for multiple locations within the United States. For the locations analyzed, the results suggest that residential PV customers offset, on average, between 60% and 99% of their annual load. However, roughly 65% of a typical customer's electricity demand is non-coincidental with PV generation, so the typical PV customer is generally highly reliant on the grid for pooling services.

  13. Residential water demand with endogenous pricing: The Canadian Case

    Science.gov (United States)

    Reynaud, Arnaud; Renzetti, Steven; Villeneuve, Michel

    2005-11-01

    In this paper, we show that the rate structure endogeneity may result in a misspecification of the residential water demand function. We propose to solve this endogeneity problem by estimating a probabilistic model describing how water rates are chosen by local communities. This model is estimated on a sample of Canadian local communities. We first show that the pricing structure choice reflects efficiency considerations, equity concerns, and, in some cases, a strategy of price discrimination across consumers by Canadian communities. Hence estimating the residential water demand without taking into account the pricing structures' endogeneity leads to a biased estimation of price and income elasticities. We also demonstrate that the pricing structure per se plays a significant role in influencing price responsiveness of Canadian residential consumers.

  14. Modeling Residential Electricity Consumption Function in Malaysia: Time Series Approach

    OpenAIRE

    L. L. Ivy-Yap; H. A. Bekhet

    2014-01-01

    As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 period. Unlike previous studies on Malaysia, the current study focuses on the residential secto...

  15. A Framework for Understanding and Generating Integrated Solutions for Residential Peak Energy Demand

    Science.gov (United States)

    Buys, Laurie; Vine, Desley; Ledwich, Gerard; Bell, John; Mengersen, Kerrie; Morris, Peter; Lewis, Jim

    2015-01-01

    Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times. PMID:25807384

  16. Public goods and private interests: Understanding non-residential demand for green power

    Energy Technology Data Exchange (ETDEWEB)

    Wiser, Ryan H.; Fowlie, Meredith; Holt, Edward A.

    2001-01-01

    This article presents the results of the first large-scale mail survey of non-residential green power customers in the United States. The survey explored the motivations, attitudes, and experiences of 464 business, non-profit, and public-sector customers that have voluntarily opted to purchase - and frequently pay a premium for - renewable electricity. Results of this study should be of value to marketers interested in targeting these customer segments, to policy makers interested in fostering and understanding non-residential demand for green power, and to academics pondering the motivations for firms to engage in such voluntary environmental initiatives.

  17. US residential energy demand and energy efficiency: A stochastic demand frontier approach

    International Nuclear Information System (INIS)

    Filippini, Massimo; Hunt, Lester C.

    2012-01-01

    This paper estimates a US frontier residential aggregate energy demand function using panel data for 48 ‘states’ over the period 1995 to 2007 using stochastic frontier analysis (SFA). Utilizing an econometric energy demand model, the (in)efficiency of each state is modeled and it is argued that this represents a measure of the inefficient use of residential energy in each state (i.e. ‘waste energy’). This underlying efficiency for the US is therefore observed for each state as well as the relative efficiency across the states. Moreover, the analysis suggests that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controlling for a range of economic and other factors, the measure of energy efficiency obtained via this approach is. This is a novel approach to model residential energy demand and efficiency and it is arguably particularly relevant given current US energy policy discussions related to energy efficiency.

  18. Moving from Outsider to Insider: Peer Status and Partnerships between Electricity Utilities and Residential Consumers

    Science.gov (United States)

    Morris, Peter; Buys, Laurie; Vine, Desley

    2014-01-01

    An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008. By 2011, both the peak demand and grid supplied electricity consumption had decreased to below pre-intervention levels. This case study research explored the relationship developed between the utility, community and individual consumer from the residential customer perspective through qualitative research of 22 residential households. It is proposed that an energy utility can be highly successful at peak demand reduction by becoming a community member and a peer to residential consumers and developing the necessary trust, access, influence and partnership required to create the responsive environment to change. A peer-community approach could provide policymakers with a pathway for implementing pro-environmental behaviour for low carbon communities, as well as peak demand reduction, thereby addressing government emission targets while limiting the cost of living increases from infrastructure expenditure. PMID:24979234

  19. Moving from outsider to insider: peer status and partnerships between electricity utilities and residential consumers.

    Science.gov (United States)

    Morris, Peter; Buys, Laurie; Vine, Desley

    2014-01-01

    An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008. By 2011, both the peak demand and grid supplied electricity consumption had decreased to below pre-intervention levels. This case study research explored the relationship developed between the utility, community and individual consumer from the residential customer perspective through qualitative research of 22 residential households. It is proposed that an energy utility can be highly successful at peak demand reduction by becoming a community member and a peer to residential consumers and developing the necessary trust, access, influence and partnership required to create the responsive environment to change. A peer-community approach could provide policymakers with a pathway for implementing pro-environmental behaviour for low carbon communities, as well as peak demand reduction, thereby addressing government emission targets while limiting the cost of living increases from infrastructure expenditure.

  20. Optimization Models and Methods for Demand-Side Management of Residential Users: A Survey

    Directory of Open Access Journals (Sweden)

    Antimo Barbato

    2014-09-01

    Full Text Available The residential sector is currently one of the major contributors to the global energy balance. However, the energy demand of residential users has been so far largely uncontrollable and inelastic with respect to the power grid conditions. With the massive introduction of renewable energy sources and the large variations in energy flows, also the residential sector is required to provide some flexibility in energy use so as to contribute to the stability and efficiency of the electric system. To address this issue, demand management mechanisms can be used to optimally manage the energy resources of customers and their energy demand profiles. A very promising technique is represented by demand-side management (DSM, which consists in a proactive method aimed at making users energy-efficient in the long term. In this paper, we survey the most relevant studies on optimization methods for DSM of residential consumers. Specifically, we review the related literature according to three axes defining contrasting characteristics of the schemes proposed: DSM for individual users versus DSM for cooperative consumers, deterministic DSM versus stochastic DSM and day-ahead DSM versus real-time DSM. Based on this classification, we provide a big picture of the key features of different approaches and techniques and discuss future research directions.

  1. P. Electricity demand, substitution and resources

    International Nuclear Information System (INIS)

    1976-01-01

    This report discusses the demand for electricity in New Zealand, the accuracy of demand predictions, and whether some other form of energy could be substituted for electricity. It then discusses past and possible future electricity generation in New Zealand by geothermal steam and hydro power and the resources of gas and coal that could be made available for electricity generation

  2. Households' hourly electricity consumption and peak demand in Denmark

    DEFF Research Database (Denmark)

    Møller Andersen, Frits; Baldini, Mattia; Hansen, Lars Gårn

    2017-01-01

    The electrification of residential energy demand for heating and transportation is expected to increase peak load and require additional generation and transmission capacities. Electrification also provides an opportunity to increase demand response. With a focus on household electricity......, for an individual household, the consumption of each of these technologies roughly doubles the household's consumption and considerably increases their potential for flexibility. Thus, in order to introduce incentives for demand flexibility, while considering reducing peak consumption, policy makers should...... consumption, we analyse the contribution of appliances and new services, such as individual heat pumps and electric vehicles, to peak consumption and the need for demand response incentives to reduce the peak.Initially, the paper presents a new model that represents the hourly electricity consumption profile...

  3. Estimating the Determinants of Residential Water Demand in Italy

    Directory of Open Access Journals (Sweden)

    Giulia Romano

    2014-09-01

    Full Text Available The aim of this study was to estimate the determinants of residential water demand for chief towns of every Italian province, in the period 2007–2009, using the linear mixed-effects model estimated with the restricted-maximum-likelihood method. Results confirmed that the applied tariff had a negative effect on residential water consumption and that it was a relevant driver of domestic water consumption. Moreover, income per capita had a positive effect on water consumption. Among measured climatic and geographical features, precipitation and altitude exerted a strongly significant negative effect on water consumption, while temperature did not influence water demand. Further, data show that small towns in terms of population served were characterized by lower levels of consumption. Water utilities ownership itself did not have a significant effect on water consumption but tariffs were significantly lower and residential water consumption was higher in towns where the water service was managed by publicly owned water utilities. However, further research is needed to gain a better understanding of the connection between ownership of water utilities and water prices and water consumption.

  4. Elasticities of electricity demand in urban Indian households

    International Nuclear Information System (INIS)

    Filippini, Massimo; Pachauri, Shonali

    2004-01-01

    In the past, several electricity demand studies have been published for India based on aggregate macro data at the country or sub-national/state level. Since the underlying theory of consumer demand is based on the behaviour of individual agents, the use of micro data, which reflects individual and household behaviour, more closely, can shed greater light on the nature of consumer responses. In this paper, seasonal price and income elasticities of electricity demand in the residential sector of all urban areas of India are estimated for the first time using disaggregate level survey data for about 30,000 households. Three electricity demand functions have been econometrically estimated using monthly data for the winter, monsoon and summer season in order to understand the extent to which factors like income, prices, household size and other household specific characteristics, influence variations observed in individual households' electricity demand. The results show electricity demand is income and price inelastic in all three seasons, and that household, demographic and geographical variables are significant in determining electricity demand

  5. Residential green power demand in the United States

    Energy Technology Data Exchange (ETDEWEB)

    Dagher, Leila; Bird, Lori; Heeter, Jenny

    2017-12-01

    This paper investigates the demand determinants of green power in the U.S. residential sector. The data employed were collected by the National Renewable Energy Laboratory and consist of a cross-section of seven utilities observed over 13 years. A series of tests are performed that resulted in estimating a demand equation using the one-way cross-section random effects model. As expected, we find that demand is highly price inelastic. More interestingly though, is that elasticity with respect to number of customers is 0.52 leading to the conclusion that new subscribers tend to purchase less green power on average than the existing customers. Another compelling finding is that obtaining accreditation will have a 28.5% positive impact on consumption. Knowing that gaining green accreditation is important to the success of programs, utilities may want to seek certification and highlight it in their advertising campaigns.

  6. Price, environment and security: Exploring multi-modal motivation in voluntary residential peak demand response

    International Nuclear Information System (INIS)

    Gyamfi, Samuel; Krumdieck, Susan

    2011-01-01

    Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response projects aim to manage peak demand by applying price signals and automated load shedding technologies. This research investigates voluntary load shedding in response to information about the security of supply, the emission profile and the cost of meeting critical peak demand in the customers' network. Customer willingness to change behaviour in response to this information was explored through mail-back survey. The diversified demand modelling method was used along with energy audit data to estimate the potential peak load reduction resulting from the voluntary demand response. A case study was conducted in a suburb of Christchurch, New Zealand, where electricity is the main source for water and space heating. On this network, all water heating cylinders have ripple-control technology and about 50% of the households subscribe to differential day/night pricing plan. The survey results show that the sensitivity to supply security is on par with price, with the emission sensitivity being slightly weaker. The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. - Highlights: → Multiple-factor behaviour intervention is necessarily for effective residential demand response. → Security signals can achieve result comparable to price. → The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. → New Zealand's energy policy should include innovation and development of VDR programmes and technologies.

  7. Accelerating residential PV expansion: supply analysis for competitive electricity markets

    International Nuclear Information System (INIS)

    Payne, Adam; Williams, Robert H.; Duke, Richard

    2001-01-01

    Photovoltaic (PV) technology is now sufficiently advanced that market support mechanisms such as net metering plus a renewable portfolio standard (RPS) could induce rapid PV market growth in grid-connected applications. With such support mechanisms, markets would be sufficiently large that manufacturers could profitably build and operate 100 MW p /yr PV module factories, and electricity costs for residential rooftop PV systems would compare favorably with residential electricity prices in certain areas (e.g., California and the greater New York region in the US). This prospect is illustrated by economic and market analyses for one promising technology (amorphous silicon thin-film PV) from the perspectives of both module manufacturers and buyers of new homes with rooftop PV systems. With public policies that reflect the distributed and environmental benefits offered by PV-and that can sustain domestic PV market demand growth at three times the historical growth rate for a period of the order of two decades - PV could provide 3% of total US electricity supply by 2025. (Author)

  8. Distributed demand-side management optimisation for multi-residential users with energy production and storage strategies

    Directory of Open Access Journals (Sweden)

    Emmanuel Chifuel Manasseh

    2014-12-01

    Full Text Available This study considers load control in a multi-residential setup where energy scheduler (ES devices installed in smart meters are employed for demand-side management (DSM. Several residential end-users share the same energy source and each residential user has non-adjustable loads and adjustable loads. In addition, residential users may have storage devices and renewable energy sources such as wind turbines or solar as well as dispatchable generators. The ES devices exchange information automatically by executing an iterative distributed algorithm to locate the optimal energy schedule for each end-user. This will reduce the total energy cost and the peak-to-average ratio (PAR in energy demand in the electric power distribution. Users possessing storage devices and dispatchable generators strategically utilise their resources to minimise the total energy cost together with the PAR. Simulation results are provided to evaluate the performance of the proposed game theoretic-based distributed DSM technique.

  9. Optimum residential load management strategy for real time pricing (RTP) demand response programs

    International Nuclear Information System (INIS)

    Lujano-Rojas, Juan M.; Monteiro, Cláudio; Dufo-López, Rodolfo; Bernal-Agustín, José L.

    2012-01-01

    This paper presents an optimal load management strategy for residential consumers that utilizes the communication infrastructure of the future smart grid. The strategy considers predictions of electricity prices, energy demand, renewable power production, and power-purchase of energy of the consumer in determining the optimal relationship between hourly electricity prices and the use of different household appliances and electric vehicles in a typical smart house. The proposed strategy is illustrated using two study cases corresponding to a house located in Zaragoza (Spain) for a typical day in summer. Results show that the proposed model allows users to control their diary energy consumption and adapt their electricity bills to their actual economical situation. - Highlights: ► This work shows an optimal load management strategy for residential consumers. ► It has been considered the communication infrastructure of the future smart grid. ► A study case shows the optimal utilization of some appliances and electric vehicles. ► Results showed that the proposed model allows users to reduce their electricity bill.

  10. Challenge: Getting Residential Users to Shift Their Electricity Usage Patterns

    DEFF Research Database (Denmark)

    Brewer, Robert S.; Verdezoto, Nervo; Rasmussen, Mia Kruse

    2015-01-01

    Increased renewable electricity production, coupled with emerging sectors of electricity consumption such as electric vehicles, has led to the desire to shift the times of the day electricity is consumed to better match generation. Different methods have been proposed to shift residential electri...

  11. Evaluation of automated residential demand response with flat and dynamic pricing

    International Nuclear Information System (INIS)

    Swisher, Joel; Wang, Kitty; Stewart, Stewart

    2005-01-01

    This paper reviews the performance of two recent automated load management programs for residential customers of electric utilities in two American states. Both pilot programs have been run with about 200 participant houses each, and both programs have control populations of similar customers without the technology or program treatment. In both cases, the technology used in the pilot is GoodWatts, an advanced, two-way, real-time, comprehensive home energy management system. The purpose of each pilot is to determine the household kW reduction in coincident peak electric load from the energy management technology. Nevada Power has conducted a pilot program for Air-Conditioning Load Management (ACLM), in which customers are sent an electronic curtailment signal for three-hour intervals during times of maximum peak demand. The participating customers receive an annual incentive payment, but otherwise they are on a conventional utility tariff. In California, three major utilities are jointly conducting a pilot demonstration of an Automated Demand Response System (ADRS). Customers are on a time-of-use (ToU) tariff, which includes a critical peak pricing (CPP) element. During times of maximum peak demand, customers are sent an electronic price signal that is three times higher than the normal on-peak price. Houses with the automated GoodWatts technology reduced their demand in both the ACLM and the ADRS programs by about 50% consistently across the summer curtailment or super peak events, relative to homes without the technology or any load management program or tariff in place. The absolute savings were greater in the ACLM program, due to the higher baseline air conditioning loads in the hotter Las Vegas climate. The results suggest that either automated technology or dynamic pricing can deliver significant demand response in low-consumption houses. However, for high-consumption houses, automated technology can reduce load by a greater absolute kWh difference. Targeting

  12. The performance of residential micro-cogeneration coupled with thermal and electrical storage

    Science.gov (United States)

    Kopf, John

    Over 80% of residential secondary energy consumption in Canada and Ontario is used for space and water heating. The peak electricity demands resulting from residential energy consumption increase the reliance on fossil-fuel generation stations. Distributed energy resources can help to decrease the reliance on central generation stations. Presently, distributed energy resources such as solar photovoltaic, wind and bio-mass generation are subsidized in Ontario. Micro-cogeneration is an emerging technology that can be implemented as a distributed energy resource within residential or commercial buildings. Micro-cogeneration has the potential to reduce a building's energy consumption by simultaneously generating thermal and electrical power on-site. The coupling of a micro-cogeneration device with electrical storage can improve the system's ability to reduce peak electricity demands. The performance potential of micro-cogeneration devices has yet to be fully realized. This research addresses the performance of a residential micro-cogeneration device and it's ability to meet peak occupant electrical loads when coupled with electrical storage. An integrated building energy model was developed of a residential micro-cogeneration system: the house, the micro-cogeneration device, all balance of plant and space heating components, a thermal storage device, an electrical storage device, as well as the occupant electrical and hot water demands. This model simulated the performance of a micro-cogeneration device coupled to an electrical storage system within a Canadian household. A customized controller was created in ESP-r to examine the impact of various system control strategies. The economic performance of the system was assessed from the perspective of a local energy distribution company and an end-user under hypothetical electricity export purchase price scenarios. It was found that with certain control strategies the micro-cogeneration system was able to improve the

  13. Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system

    International Nuclear Information System (INIS)

    Jiang, Yibo; Xu, Jian; Sun, Yuanzhang; Wei, Congying; Wang, Jing; Ke, Deping; Li, Xiong; Yang, Jun; Peng, Xiaotao; Tang, Bowen

    2017-01-01

    Highlights: • Improving the utilization of wind power by the demand response of residential hybrid energy system. • An optimal scheduling of home energy management system integrating micro-CHP. • The scattered response capability of consumers is aggregated by demand bidding curve. • A stochastic day-ahead economic dispatch model considering demand response and wind power. - Abstract: As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.

  14. Option value of electricity demand response

    Energy Technology Data Exchange (ETDEWEB)

    Sezgen, Osman; Goldman, C.A. [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley CA 94720 (United States); Krishnarao, P. [Citigroup Energy Inc., 1301 Fannin St, Houston, TX 77002 (United States)

    2007-02-15

    As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand-response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand-response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution-specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets. (author)

  15. Option value of electricity demand response

    International Nuclear Information System (INIS)

    Sezgen, Osman; Goldman, C.A.; Krishnarao, P.

    2007-01-01

    As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand-response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand-response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution-specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets. (author)

  16. Hawaiian Electric Company Demand Response Roadmap Project

    Energy Technology Data Exchange (ETDEWEB)

    Levy, Roger [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-01-12

    The objective of this project was to develop a “roadmap” to guide the Hawaiian Electric Company (HECO) demand response (DR) planning and implementation in support of the Hawaii Clean Energy Initiative (HCEI) 70% clean energy goal by 2030.

  17. Intelligent demand side management of residential building energy systems

    Science.gov (United States)

    Sinha, Maruti N.

    Advent of modern sensing technologies, data processing capabilities and rising cost of energy are driving the implementation of intelligent systems in buildings and houses which constitute 41% of total energy consumption. The primary motivation has been to provide a framework for demand-side management and to improve overall reliability. The entire formulation is to be implemented on NILM (Non-Intrusive Load Monitoring System), a smart meter. This is going to play a vital role in the future of demand side management. Utilities have started deploying smart meters throughout the world which will essentially help to establish communication between utility and consumers. This research is focused on investigation of a suitable thermal model of residential house, building up control system and developing diagnostic and energy usage forecast tool. The present work has considered measurement based approach to pursue. Identification of building thermal parameters is the very first step towards developing performance measurement and controls. The proposed identification technique is PEM (Prediction Error Method) based, discrete state-space model. The two different models have been devised. First model is focused toward energy usage forecast and diagnostics. Here one of the novel idea has been investigated which takes integral of thermal capacity to identify thermal model of house. The purpose of second identification is to build up a model for control strategy. The controller should be able to take into account the weather forecast information, deal with the operating point constraints and at the same time minimize the energy consumption. To design an optimal controller, MPC (Model Predictive Control) scheme has been implemented instead of present thermostatic/hysteretic control. This is a receding horizon approach. Capability of the proposed schemes has also been investigated.

  18. FORECASTING RESIDENTIAL ELECTRICITY CONSUMPTION IN BRAZIL: APPLICATION OF THE ARX MODEL

    Directory of Open Access Journals (Sweden)

    Joao Bosco de Castro

    2010-11-01

    Full Text Available This work aims to propose the application of the ARX model to forecast residential electricity consumption in Brazil. Such estimates are critical for decision making in the energy sector,  from a technical, economic and environmentally sustainable standpoint. The demand for electricity follows a multiplicative model based on economic theory and involves four explanatory variables: the cost of residential electricity, the actual average income, the inflation of domestic utilities and the electricity consumption. The coefficients of the electricity consumption equation  were determined using the ARX model, which considers the influence of exogenous variables to estimate the dependent variable and employs an autoregression process for residual modeling to improve the explanatory power. The resulting model has a determination coefficient of 95.4 percent and all estimated coefficients were significant at the 0.10 descriptive level. Residential electricity consumption estimates were also determined for January and February 2010 within the 95 percent confidence interval, which included the actual consumption figures observed. The proposed model has been shown to be useful for estimating residential electricity consumption  in Brazil. Key-words: Time series. Electricity consumption. ARX modeling. 

  19. Electricity demand savings from distributed solar photovoltaics

    International Nuclear Information System (INIS)

    Glassmire, John; Komor, Paul; Lilienthal, Peter

    2012-01-01

    Due largely to recent dramatic cost reductions, photovoltaics (PVs) are poised to make a significant contribution to electricity supply. In particular, distributed applications of PV on rooftops, brownfields, and other similar applications – hold great technical potential. In order for this potential to be realized, however, PV must be “cost-effective”—that is, it must be sufficiently financially appealing to attract large amounts of investment capital. Electricity costs for most commercial and industrial end-users come in two forms: consumption (kWh) and demand (kW). Although rates vary, for a typical larger commercial or industrial user, demand charges account for about ∼40% of total electricity costs. This paper uses a case study of PV on a large university campus to reveal that even very large PV installations will often provide very small demand reductions. As a result, it will be very difficult for PV to demonstrate cost-effectiveness for large commercial customers, even if PV costs continue to drop. If policymakers would like PV to play a significant role in electricity generation – for economic development, carbon reduction, or other reasons – then rate structures will need significant adjustment, or improved distributed storage technologies will be needed. - Highlights: ► Demand charges typically account for ∼40% of total electricity costs for larger electricity users. ► Distributed photovoltaic (PV) systems provide minimal demand charge reductions. ► As a result, PVs are not a financially viable alternative to centralized electricity. ► Electricity rate structures will need changes for PV to be a major electricity source.

  20. Residential electricity consumption in Portugal: Findings from top-down and bottom-up models

    International Nuclear Information System (INIS)

    Wiesmann, Daniel; Lima Azevedo, Ines; Ferrao, Paulo; Fernandez, John E.

    2011-01-01

    An econometric study of the Portuguese residential electricity consumption is presented, with a focus on the influence of dwelling characteristics on consumption. The relationship between the dwelling and household characteristics on per capita residential electricity consumption is estimated at two different scales, involving two distinct databases: the first includes data at the municipality level for 2001, the second is the most recent Portuguese consumer expenditure survey that was collected in 2005 and 2006. The results of the analysis at both scales are consistent and indicate that household and dwelling characteristics have a significant influence on residential electricity consumption. Our results show that in Portugal the direct effect of income on electricity consumption is low and becomes smaller when more relevant control variables are included in the analysis. Future demand of electricity in Portugal will be significantly influenced by trends in socioeconomic factors as well as changes in the building stock. These trends should be taken in consideration in the formulation of policy measures to reduce electricity consumption. - Research highlights: → Econometric study of per capita residential electricity consumption in Portugal. → Comparing models at two levels of aggregation: by municipality and by household. → Using proxies for the dwelling characteristics on the municipality level. → Results from both scales are consistent. → Income elasticity is low and the influence of dwelling characteristics is significant.

  1. Residential Demand Response Scheduling with Consideration of Consumer Preferences

    Directory of Open Access Journals (Sweden)

    Raka Jovanovic

    2016-01-01

    Full Text Available This paper proposes a new demand response scheduling framework for an array of households, which are grouped into different categories based on socio-economic factors, such as the number of occupants, family decomposition and employment status. Each of the households is equipped with a variety of appliances. The model takes the preferences of participating households into account and aims to minimize the overall production cost and, in parallel, to lower the individual electricity bills. In the existing literature, customers submit binary values for each time period to indicate their operational preferences. However, turning the appliances “on” or “off” does not capture the associated discomfort levels, as each appliance provides a different service and leads to a different level of satisfaction. The proposed model employs integer values to indicate household preferences and models the scheduling problem as a multi-objective mixed integer programming. The main thrust of the framework is that the multi-level preference modeling of appliances increases their “flexibility”; hence, the job scheduling can be done at a lower cost. The model is evaluated by using the real data provided by the Department of Energy & Climate Change, UK. In the computational experiments, we examine the relation between the satisfaction of consumers based on the appliance usage preferences and the electricity costs by exploring the Pareto front of the related objective functions. The results show that the proposed model leads to significant savings in electricity cost, while maintaining a good level of customer satisfaction.

  2. Electricity demand and supply to 2020

    International Nuclear Information System (INIS)

    Bertel, E.

    1991-01-01

    This paper will attempt to make projections of energy and electricity demand, and the possible share of nuclear generation in global supply, up to 2020. This horizon has been chosen because the long lead times prevailing in the energy sector imply long-term planning, even though the degree of uncertainty is quite large when looking several decades ahead. Electricity demand, as well as primary energy consumption, depends on many technical and economic factors, obviously including demography. Using statistical data for past decades, it is possible to quantify by econometric methods and the links between energy and electricity consumption and economic parameters. The models defined may then be used to make projections of future electricity consumption. The share of nuclear electricity in primary energy supply can be estimated by taking into account the various constraints and lead times limiting the deployment of nuclear generating capacity, and the shares of other energy sources in electricity generation in each country or region. It should be emphasized that the scenarios presented below are illustrative, and are not forecasts of future energy and electricity demand. Because of the method adopted and the assumptions made, the scenarios reflect a 'conventional wisdom'. However, they do incorporate concerns for environmental protection and improvements regarding energy efficiency. (author)

  3. Analysis and modeling of active occupancy of the residential sector in Spain: An indicator of residential electricity consumption

    International Nuclear Information System (INIS)

    López-Rodríguez, M.A.; Santiago, I.; Trillo-Montero, D.; Torriti, J.; Moreno-Munoz, A.

    2013-01-01

    The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy. -- Highlights: •Active occupancy profiles of Spanish dwellings has been obtained and modeled from Time Use Survey data. •Occupancy profiles resulting from the model can be used to model domestic energy consumption. •The presence of three peaks of active occupation was verified, which coincide with morning, noon and evening. •Manual and incentive-based DSM programmes are considered the most suitable for Spanish dwellings. •TV electricity consumption becomes important at aggregate level

  4. Indications for a changing electricity demand pattern : The temperature dependence of electricity demand in the Netherlands

    NARCIS (Netherlands)

    Hekkenberg, M.; Benders, R. M. J.; Moll, H. C.; Uiterkamp, A. J. M. Schoot

    This study assesses the electricity demand pattern in the relatively temperate climate of the Netherlands (latitude 52 degrees 30'N). Daily electricity demand and average temperature during the period from 1970 until 2007 are investigated for possible trends in the temperature dependence of

  5. Assessing Impact of Large-Scale Distributed Residential HVAC Control Optimization on Electricity Grid Operation and Renewable Energy Integration

    Science.gov (United States)

    Corbin, Charles D.

    Demand management is an important component of the emerging Smart Grid, and a potential solution to the supply-demand imbalance occurring increasingly as intermittent renewable electricity is added to the generation mix. Model predictive control (MPC) has shown great promise for controlling HVAC demand in commercial buildings, making it an ideal solution to this problem. MPC is believed to hold similar promise for residential applications, yet very few examples exist in the literature despite a growing interest in residential demand management. This work explores the potential for residential buildings to shape electric demand at the distribution feeder level in order to reduce peak demand, reduce system ramping, and increase load factor using detailed sub-hourly simulations of thousands of buildings coupled to distribution power flow software. More generally, this work develops a methodology for the directed optimization of residential HVAC operation using a distributed but directed MPC scheme that can be applied to today's programmable thermostat technologies to address the increasing variability in electric supply and demand. Case studies incorporating varying levels of renewable energy generation demonstrate the approach and highlight important considerations for large-scale residential model predictive control.

  6. The demand for electricity in Israel

    International Nuclear Information System (INIS)

    Beenstock, M.; Goldin, E.; Nabot, D.

    1999-01-01

    Quarterly data for Israel are used to compare and contrast three dynamic econometric methodologies for estimating the demand for electricity by households and industrial companies. These are the Dynamic Regression Model and two approaches to cointegration (OLS and Maximum Likelihood). Since we find evidence of seasonal unit roots in the data we also test for seasonal cointegration. We find that the scale elasticities are similar in all three approaches but the OLS price elasticities are considerably lower. Moreover, OLS suggests non-cointegration. The paper concludes by stochastically simulating the DRMs to calculate upside-risk in electricity demand. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

  7. Exploring utility organization electricity generation, residential electricity consumption, and energy efficiency: A climatic approach

    International Nuclear Information System (INIS)

    Craig, Christopher A.; Feng, Song

    2017-01-01

    Highlights: • Study examined impact of electricity fuel sources and consumption on emissions. • 97.2% of variability in emissions explained by coal and residential electricity use. • Increasing cooling degree days significantly related to increased electricity use. • Effectiveness of state-level energy efficiency programs showed mixed results. - Abstract: This study examined the impact of electricity generation by fuel source type and electricity consumption on carbon emissions to assess the role of climatic variability and energy efficiency (EE) in the United States. Despite high levels of greenhouse gas emissions, residential electricity consumption continues to increase in the United States and fossil fuels are the primary fuel source of electricity generation. 97.2% of the variability in carbon emissions in the electricity industry was explained by electricity generation from coal and residential electricity consumption. The relationships between residential electricity consumption, short-term climatic variability, long-term climatic trends, short-term reduction in electricity from EE programs, and long-term trends in EE programs was examined. This is the first study of its nature to examine these relationships across the 48 contiguous United States. Inter-year and long-term trends in cooling degree days, or days above a baseline temperature, were the primary climatic drivers of residential electricity consumption. Cooling degree days increased across the majority of the United States during the study period, and shared a positive relationship with residential electricity consumption when findings were significant. The majority of electricity reduction from EE programs was negatively related to residential electricity consumption where findings were significant. However, the trend across the majority of states was a decrease in electricity reduction from EE while residential electricity consumption increased. States that successfully reduced consumption

  8. Indonesia’s Electricity Demand Dynamic Modelling

    Science.gov (United States)

    Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

    2017-06-01

    Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

  9. Restructuring Electricity Markets when Demand is Uncertain

    DEFF Research Database (Denmark)

    Boom, Anette; Buehler, Stefan

    2006-01-01

    We examine the effects of reorganizing electricity markets on capacity investments, retail prices and welfare when demand is uncertain. We study the following market configurations: (i) integrated monopoly, (ii) integrated duopoly with wholesale trade, and (iii) separated duopoly with wholesale...... are such that the separated (integrated) duopoly with wholesale trade performs best (worst) in terms of welfare.Keywords: Electricity, Investments, Generating Capacities, Vertical Integration, Monopoly and Competition.JEL-Classification: D42, D43, D44, L11, L12, L13...

  10. Electricity: Residential Wiring. Secondary Schools. Curriculum Guide.

    Science.gov (United States)

    Trust Territory of the Pacific Islands Dept. of Education, Saipan.

    This curriculum guide on residential wiring for secondary students is one of six developed for inservice teachers at Marianas High School in Saipan. The guide provides the rationale, description, goals, and objectives of the program; the program of studies and performance objectives by levels; samples of lesson plans for effective delivery of…

  11. How might residential PV change the energy demand curve in Poland

    Directory of Open Access Journals (Sweden)

    Jurasz Jakub

    2016-01-01

    Full Text Available Photovoltaics (PV in terms of installed capacity play a minor role in the portfolio of renewable energy sources (RES in Poland. However current market tendencies indicate that residential PV installations are gaining on popularity and may in future significantly contribute to covering national energy demand. This study investigates the potential impact of numerous residential PV installations on the shape and statistical properties of the polish energy demand curve. Analysis employed statistical data on mean household energy consumption in different districts, typical energy demand patterns and hourly values of irradiation for the year 2012. Obtained results indicate that there is a possibility to integrate in total as much as 300 000 residential PV installations (0.9 GW from which generated energy will be utilized by households within given district. Further analysis has shown that to some extent increasing number of residential PV decreases the value of energy demand coefficient of variation.

  12. Electricity Demand Forecasting Using a Functional State Space Model

    OpenAIRE

    Nagbe , Komi; Cugliari , Jairo; Jacques , Julien

    2018-01-01

    In the last past years the liberalization of the electricity supply, the increase variability of electric appliances and their use, and the need to respond to the electricity demand in the real time had made electricity demand forecasting a challenge. To this challenge, many solutions are being proposed. The electricity demand involves many sources such as economic activities, household need and weather sources. All this sources make hard electricity demand forecasting. To forecast the electr...

  13. Policy analysis of electricity demand flexibility

    DEFF Research Database (Denmark)

    Katz, Jonas

    The large-scale development of variable renewable energy sources, like wind and solar power, increases the demand for flexibility in power systems. At the same time, their electricity production replaces that of conventional power plants – the traditional suppliers of flexibility, and consequently...... include a clear commitment to develop an "intelligent" energy system that utilises the flexibility potential of the demand side, a coherent policy strategy covering all aspects of the flexibility challenge has not yet been defined. By use of economic models and concepts of policy analysis, this thesis...... flexibility on the demand side. Its potential could be substantial and technical solutions are available. Still, demand flexibility is largely unutilised and establishing an enabling policy and regulatory framework has been identified as one of the major challenges. While the latest Danish energy policies...

  14. Optimal behavior of responsive residential demand considering hybrid phase change materials

    International Nuclear Information System (INIS)

    Shafie-khah, M.; Kheradmand, M.; Javadi, S.; Azenha, M.; Aguiar, J.L.B. de; Castro-Gomes, J.; Siano, P.; Catalão, J.P.S.

    2016-01-01

    Highlights: • An operational model of HEM system incorporating with a hybrid PCM is proposed in this paper. • Incorporation of hybrid PCM mortar had a complementary effect on the proposed HEM system. • The proposed model ensures the technical and economic limits of batteries and electrical appliances. • The customer’s electricity cost can be reduced up to 48% by utilizing the proposed model. - Abstract: Due to communication and technology developments, residential consumers are enabled to participate in Demand Response Programs (DRPs), control their consumption and decrease their cost by using Household Energy Management (HEM) systems. On the other hand, capability of energy storage systems to improve the energy efficiency causes that employing Phase Change Materials (PCM) as thermal storage systems to be widely addressed in the building applications. In this paper, an operational model of HEM system considering the incorporation of more than one type of PCM in plastering mortars (hybrid PCM) is proposed not only to minimize the customer’s cost in different DRPs but also to guaranty the habitants’ satisfaction. Moreover, the proposed model ensures the technical and economic limits of batteries and electrical appliances. Different case studies indicate that implementation of hybrid PCM in the buildings can meaningfully affect the operational pattern of HEM systems in different DRPs. The results reveal that the customer’s electricity cost can be reduced up to 48% by utilizing the proposed model.

  15. Economic Rebalancing and Electricity Demand in China

    Energy Technology Data Exchange (ETDEWEB)

    He, Gang [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Advanced Light Source (ALS); Stony Brook Univ., NY (United States); Lin, Jiang [Energy Foundation, Beijing (China); Yuan, Alexandria [Energy Foundation, Beijing (China)

    2015-11-01

    Understanding the relationship between economic growth and electricity use is essential for power systems planning. This need is particularly acute now in China, as the Chinese economy is going through a transition to a more consumption and service oriented economy. This study uses 20 years of provincial data on gross domestic product (GDP) and electricity consumption to examine the relationship between these two factors. We observe a plateauing effect of electricity consumption in the richest provinces, as the electricity demand saturates and the economy develops and moves to a more service-based economy. There is a wide range of forecasts for electricity use in 2030, ranging from 5,308 to 8,292 kWh per capita, using different estimating functions, as well as in existing studies. It is therefore critical to examine more carefully the relationship between electricity use and economic development, as China transitions to a new growth phase that is likely to be less energy and resource intensive. The results of this study suggest that policymakers and power system planners in China should seriously re-evaluate power demand projections and the need for new generation capacity to avoid over-investment that could lead to stranded generation assets.

  16. Demand response in Indian electricity market

    International Nuclear Information System (INIS)

    Siddiqui, Md Zakaria; Maere d'Aertrycke, Gauthier de; Smeers, Yves

    2012-01-01

    This paper outlines a methodology for implementing cost of service regulation in retail market for electricity in India when wholesale market is liberalised and operates through an hourly spot market. As in a developing country context political considerations make tariff levels more important than supply security, satisfying the earmarked level of demand takes a back seat. Retail market regulators are often forced by politicians to keep the retail tariff at suboptimal level. This imposes budget constraint on distribution companies to procure electricity that it requires to meet the earmarked level of demand. This is the way demand response is introduced in the system and has its impact on spot market prices. We model such a situation of not being able to serve the earmarked demand as disutility to the regulator which has to be minimised and we compute associated equilibrium. This results in systematic mechanism for cutting loads. We find that even a small cut in ability of the distribution companies to procure electricity from the spot market has profound impact on the prices in the spot market. - Highlights: ► Modelling the impact of retail tariff in different states on spot prices of electricity in India. ► Retail tariffs are usually fixed below appropriate levels by states due to political reasons. ► Due to revenue constraint distribution utility withdraws demand from spot market in peak hours. ► This adversely affects the scarcity rent of generators and subsequently future investment. ► We show possibility of strategic behaviour among state level regulators in setting retail tariff.

  17. Utility Sector Impacts of Reduced Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Coughlin, Katie

    2014-12-01

    This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

  18. Forecasted electric power demands for the Baltimore Gas and Electric Company. Volume 1 and Volume 2. Documentation manual

    International Nuclear Information System (INIS)

    Estomin, S.L.; Beach, J.E.; Goldsmith, J.V.

    1991-05-01

    The two-volume report presents the results of an econometric forecast of peak load and electric power demand for the Baltimore Gas and Electric Company (BG ampersand E) through the year 2009. Separate energy sales models were estimated for residential sales in Baltimore City, residential sales in the BG ampersand E service area excluding Baltimore City, commercial sales, industrial sales, streetlighting sales, and Company use plus losses. Econometric equations were also estimated for electric space heating and air conditioning saturation in Baltimore City and in the remainder of the BG ampersand E service territory. In addition to the energy sales models and the electric space conditioning saturation models, econometric models of summer and winter peak demand on the BG ampersand E system were estimated

  19. Price impact on urban residential water demand: A dynamic panel data approach

    Science.gov (United States)

    ArbuéS, Fernando; BarberáN, Ramón; Villanúa, Inmaculada

    2004-11-01

    In this paper, we formulate and estimate a model of residential water demand with the aim of evaluating the potential of pricing policies as a mechanism for managing residential water. The proposed econometric model offers a new perspective on urban water demand analysis by combining microlevel data with a dynamic panel data estimation procedure. The empirical application suggests that residential users are more responsive to a lagged average price specification. Another result of the estimated model is that price is a moderately effective tool in reducing residential water demand within the present range of prices, with the estimated values for income elasticity and "elasticity of consumption with respect to family size" reinforcing this conclusion.

  20. Development and Demonstration of the Open Automated Demand Response Standard for the Residential Sector

    Energy Technology Data Exchange (ETDEWEB)

    Herter, Karen; Rasin, Josh; Perry, Tim

    2009-11-30

    The goal of this study was to demonstrate a demand response system that can signal nearly every customer in all sectors through the integration of two widely available and non- proprietary communications technologies--Open Automated Demand Response (OpenADR) over lnternet protocol and Utility Messaging Channel (UMC) over FM radio. The outcomes of this project were as follows: (1) a software bridge to allow translation of pricing signals from OpenADR to UMC; and (2) a portable demonstration unit with an lnternet-connected notebook computer, a portfolio of DR-enabling technologies, and a model home. The demonstration unit provides visitors the opportunity to send electricity-pricing information over the lnternet (through OpenADR and UMC) and then watch as the model appliances and lighting respond to the signals. The integration of OpenADR and UMC completed and demonstrated in this study enables utilities to send hourly or sub-hourly electricity pricing information simultaneously to the residential, commercial and industrial sectors.

  1. Assessing Impact of Large-Scale Distributed Residential HVAC Control Optimization on Electricity Grid Operation and Renewable Energy Integration

    OpenAIRE

    Corbin, Charles

    2014-01-01

    Demand management is an important component of the emerging Smart Grid, and a potential solution to the supply-demand imbalance occurring increasingly as intermittent renewable electricity is added to the generation mix. Model predictive control (MPC) has shown great promise for controlling HVAC demand in commercial buildings, making it an ideal solution to this problem. MPC is believed to hold similar promise for residential applications, yet very few examples exist in the literature despite...

  2. Electric demand and the antinuclear movement

    International Nuclear Information System (INIS)

    Studness, C.M.

    1984-01-01

    The author feels that, with electric demand growth of 4.5 to 5% per year expected, it will be only a matter of time before stepping-up the stream of utility capacity additions becomes an important issue. If demand grows 4.5% per year instead of 2.8% as projected by NERC, demand will be 10% higher and peak reserve margins about 12 percentage points lower than envisioned by the NERC projections after five years. By 1988 or 1989, little or no excess capacity will remain, and the utilities will be faced with adding twice as much capacity annually as now planned to avoid service deterioration. As questions about the adequacy of current utility capacity plans and concerns about service quality move toward center stage, the antinuclear movement should find it increasingly difficult to garner the broad support it now enjoys. Capacity represented by any uncompleted nuclear plants will appear increasingly beneficial, and those who do not have strong antinuclear sentiments should become increasingly hesitant about lending support to the movement. Accordingly, electric demand growth in due course can be expected to drain marginal supporters from the antinuclear movement and thereby erode the movement's vitality

  3. Assessing the potential of residential HVAC systems for demand-side management

    NARCIS (Netherlands)

    van der Klauw, Thijs; Hoogsteen, Gerwin; Gerards, Marco Egbertus Theodorus; Hurink, Johann L.; Feng, Xianyong; Hebner, Robert E.

    This paper investigates the potential of residential heating, ventilation and air conditioning systems to contribute to dynamic demand-side management. Thermal models for seven houses in Austin, Texas are developed with the goal of using them in a planning based demand-side management methodology.

  4. determinants of residential per capita water demand of makurdi

    African Journals Online (AJOL)

    user

    the demand. Rapid development has also brought about increase in the uses of water as houses are now with gardens, increased number of cars and water using home appliances. This rapid growth in water demand has to be accompanied by regular review and adjustment in planning, designing and management of.

  5. Future demand for electricity in Nigeria

    International Nuclear Information System (INIS)

    Ibitoye, F.I.; Adenikinju, A.

    2007-01-01

    Availability and reliability of electricity supplies have always been vexed issue in Nigeria. With an estimated population of 130 million people in AD 2005, Nigeria is the most populous country in Africa and belongs to the group of countries with the lowest electricity consumption per capita in the continent. Nigeria is also ranked among the poorest countries in the world. This paper examines the likely trend in the demand for electricity over the next 25 years under the assumptions that (i) there is a rapid economic development such that Nigeria transforms from low- to middle-income economy during this period, (ii) Nigeria meets the millennium development goals (MDG) in AD 2015, and (iii) the country achieves the status of an industrializing nation. For these to happen, this paper projects that electric-power generation will have to rise from the current capacity of 6500 MW to over 160 GW in AD 2030. This level of supply will be significant enough to increase the per capita electricity consumption to about 5000 kWh per capita by the year 2030. Even then, this just compares with the AD 2003 per capital consumption of some industrializing countries. Analysis of the level of investment required to meet the projected power demand indicates that annual investment cost will rise from US3.8 billion in AD 2006 to a peak of US21 billion in AD 2028. The total investment stream over the 25 year period comes to US262 billion or roughly US10 billion per annum. (author)

  6. Game-Theoretic Energy Management for Residential Users with Dischargeable Plug-in Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Bingtuan Gao

    2014-11-01

    Full Text Available The plug-in electric vehicle (PEV has attracted more and more attention because of the energy crisis and environmental pollution, which is also the main shiftable load of the residential users’ demand side management (DSM system in the future smart grid (SG. In this paper, we employ game theory to provide an autonomous energy management system among residential users considering selling energy back to the utility company by discharging the PEV’s battery. By assuming all users are equipped with smart meters to execute automatic energy consumption scheduling (ECS and the energy company can adopt adequate pricing tariffs relating to time and level of energy usage, we formulate an energy management game, where the players are the residential users and the strategies are their daily schedules of household appliance use. We will show that the Nash equilibrium of the formulated energy management game can guarantee the global optimization in terms of minimizing the energy costs, where the depreciation cost of PEV’s battery because of discharging and selling energy back is also considered. Simulation results verify that the proposed game-theoretic approach can reduce the total energy cost and individual daily electricity payment. Moreover, since plug-in electric bicycles (PEBs are currently widely used in China, simulation results of residential users owing household appliances and bidirectional energy trading of PEBs are also provided and discussed.

  7. Model documentation report: Residential sector demand module of the national energy modeling system

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

  8. Review of barriers to the introduction of residential demand response : A case study in the Netherlands

    NARCIS (Netherlands)

    Weck, M. H J; van Hooff, J.; van Sark, W. G J H M

    Demand response, defined as the shifting of electricity demand, is generally believed to have value both for the grid and for the market: by matching demand more closely to supply, consumers could profit from lower prices, while in a smart grid environment, more renewable electricity can be used and

  9. Balancing islanded residential microgrids using demand side management

    NARCIS (Netherlands)

    Hoogsteen, Gerwin; van der Klauw, Thijs; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria; Feng, Xianyong; Hebner, Robert E.

    2016-01-01

    Now that the internet of things is emerging, control of domestic assets within the smart micro grids is also gaining interest. Furthermore, these micro grids may operate in islanded mode for short periods. Various demand side management approaches are presented in literature to control these assets.

  10. Empirical Investigations of the Opportunity Limits of Automatic Residential Electric Load Shaping: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Cruickshank, Robert F.; Henze, Gregor P.; Balaji, Rajagopalan; Hodge, Bri-Mathias S.; Florita, Anthony R.

    2017-04-01

    Residential electric load shaping is often modeled as infrequent, utility-initiated, short-duration deferral of peak demand through direct load control. In contrast, modeled herein is the potential for frequent, transactive, intraday, consumer-configurable load shaping for storage-capable thermostatically controlled electric loads (TCLs), including refrigerators, freezers, and hot water heaters. Unique to this study are 28 months of 15-minute-interval observations of usage in 101 homes in the Pacific Northwest United States that specify exact start, duration, and usage patterns of approximately 25 submetered loads per home. The magnitudes of the load shift from voluntarily-participating TCL appliances are aggregated to form hourly upper and lower load-shaping limits for the coordination of electrical generation, transmission, distribution, storage, and demand. Empirical data are statistically analyzed to define metrics that help quantify load-shaping opportunities.

  11. Effect of demand management on regulated and deregulated electricity sectors

    International Nuclear Information System (INIS)

    Fahrioglu, Murat

    2016-01-01

    Our society derives a quantifiable benefit from electric power. In particular, forced outages or blackouts have enormous consequences on society, one of which is loss of economic surplus. The society relies on having a continuous supply of electrical energy. Some customers may willingly risk this continuous supply and participate in demand management programs for electrical power. If the power system grid is in trouble, electric utilities need to have demand relief. Customers willing to reduce their demand to help the system can receive an incentive fee for helping the utilities. Demand relief can be system wide or location specific. Sometimes it can be more effective to fix the electrical demand vs. supply imbalance from the demand side. The value of demand management contracts is greatly affected by customer location. Inclusion of locational attributes into the contract design procedure increases the effectiveness of the contracts by helping a utility get more value from its demand management programs. Independent System Operators and regulators, among others, can also benefit from effective demand management. This paper will investigate how this type of demand management contracts can help the electricity sector both in regulated and deregulated environments. - Highlights: • Demand management can help prevent forced electricity outages. • Both electric utilities and ISOs can use demand management. • Regulated and deregulated electricity sectors can benefit from demand management. • Demand management contracts can be effectively used in power system grids.

  12. Charging Schedule for Electric Vehicles in Danish Residential Distribution Grids

    DEFF Research Database (Denmark)

    Pillai, Jayakrishnan Radhakrishna; Huang, Shaojun; Bak-Jensen, Birgitte

    2015-01-01

    , the vehicle owner, vehicle fleet operator and other parties involved in the process could economically benefit from the process. This paper investigates an optimal EV charging plan in Danish residential distribution grids in view of supporting high volumes of wind power in electricity grids. The results...... energy sources like wind in power systems. The EV batteries could be used to charge during periods of excess electricity production from wind power and reduce the charging rate or discharge on deficit of power in the grid, supporting system stability and reliability. By providing such grid services......The prospects of Electric Vehicles (EVs) in providing clean transportation and supporting renewable electricity is widely discussed in sustainable energy forums worldwide. The battery storage of EVs could be used to address the variability and unpredictability of electricity produced from renewable...

  13. Feasibility and potential of thermal demand side management in residential buildings considering different developments in the German energy market

    International Nuclear Information System (INIS)

    Wolisz, Henryk; Punkenburg, Carl; Streblow, Rita; Müller, Dirk

    2016-01-01

    Highlights: • A scenario analysis for the German energy market in the year 2030 is performed. • Growing demand for flexible electric capacities is identified in all scenarios. • Significant potential for domestic demand side management is identified. • A distinct potential for dynamic operation of domestic supply systems is found. • The necessity for a quick introduction of smart metering and control is found. - Abstract: A transition in the electricity market is required to manage the volatility of increasing renewable energy generation. These fluctuations can be faced with flexible consumption through Demand Side Management (DSM), establishment of further centralized storage capacities and provisioning of dynamic back up generation capacities. At least the latter two options can impose large establishment and operation costs upon the electricity market. Therefore, the feasibility and the resulting potential of coupling the electricity grid with the thermal supply of residential buildings is analysed in this paper. Thereby, inexpensive and widespread thermal storage capacities could be used to improve the integration of dynamic renewable electricity generation. In this paper the technical and economical key impact factors for such thermal DSM approach are elaborated. Based on a literature review, the identified key factors are aggregated to form consistent scenarios of the German “Energiewende” (turnaround in energy policy). The practicability and possible magnitude of the intended DSM is then analysed based on the identified scenarios. All resulting scenarios highlight the growing demand for a flexible electricity market. Especially in scenarios with strong growth of renewable electricity generation, up to 45 GW of flexible electric capacities would be required in Germany by the year 2030. Furthermore, the analysis demonstrates that independently of the energy market development, it is very likely that electricity coupled supply systems will

  14. Price and expenditure elasticities of residential energy demand during urbanization: An empirical analysis based on the household-level survey data in China

    International Nuclear Information System (INIS)

    Sun, Chuanwang; Ouyang, Xiaoling

    2016-01-01

    Urbanization, one of the most obvious characteristics of economic growth in China, has an apparent “lock-in effect” on residential energy consumption pattern. It is expected that residential sector would become a major force that drives China's energy consumption after urbanization process. We estimate price and expenditure elasticities of residential energy demand using data from China's Residential Energy Consumption Survey (CRECS) that covers households at different income levels and from different regional and social groups. Empirical results from the Almost Ideal Demand System model are in accordance with the basic expectations: the demands for electricity, natural gas and transport fuels are inelastic in the residential sector due to the unreasonable pricing mechanism. We further investigate the sensitivities of different income groups to prices of the three types of energy. Policy simulations indicate that rationalizing energy pricing mechanism is an important guarantee for energy sustainable development during urbanization. Finally, we put forward suggestions on energy pricing reform in the residential sector based on characteristics of China's undergoing urbanization process and the current energy consumption situations.

  15. Income and price elasticities of electricity demand: Aggregate and sector-wise analyses

    International Nuclear Information System (INIS)

    Jamil, Faisal; Ahmad, Eatzaz

    2011-01-01

    Cointegration and vector error correction modeling approaches are widely used in electricity demand analysis. The study rigorously examines the determinants of electricity demand at aggregate and sectoral levels in Pakistan. In the backdrop of severe electricity shortages, our empirical findings give support to the existence of a stable long-run relationship among the variables and indicate that electricity demand is elastic in the long run to both income and price at aggregate level. At sectoral level, long-run income and price elasticity estimates follow this pattern except in agricultural sector, where electricity demand is found elastic to output but inelastic to electricity price. On the contrary, the coefficients for income and price are rather small and mostly insignificant in the short run. We employed temperature index, price of diesel oil and capital stock at aggregate and sectoral levels as exogenous variables. These variables account for most of the variations in electricity demand in the short run. It shows that mechanization of the economy significantly affect the electricity demand at macro level. Moreover, elastic electricity demand with respect to electricity price in most of the sectors implies that electricity price as a policy tool can be used for efficient use and conservation. - Highlights: → The study conducts analysis for aggregate and four sectors. → Sectoral analyses are for residential, commercial, manufacturing and agricultural sectors. → We obtained higher positive income and negative price elasticity in the long run. → The higher price elasticity implies that price can be used as a policy tool. → Capital stock and temperature variables explain most of the short-run demand fluctuations.

  16. Evaluating the effect of conservation motivations on residential water demand.

    Science.gov (United States)

    Maas, Alexander; Goemans, Christopher; Manning, Dale; Kroll, Stephan; Arabi, Mazdak; Rodriguez-McGoffin, Mariana

    2017-07-01

    Utilities and water suppliers in the southwestern United States have used education and conservation programs over the past two decades in an attempt to ameliorate the pressures of increasing water scarcity. This paper builds on a long history of water demand and environmental psychology literature and attempts to answer a simple question: do households primarily motivated by environmental and social (E&S) considerations consume water differently than households motivated primarily by cost and convenience (C&C)? We find that E&S consumers use less water than C&C consumers on average. We also find that there is no statistical difference between E&S and C&C consumers in their consumption responses to changing prices, temperature, and precipitation. This implies that targeting future conservation efforts to self-reported consumer groups may not improve policy effectiveness. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Automatic demand response referred to electricity spot price. Demo description

    International Nuclear Information System (INIS)

    Grande, Ove S.; Livik, Klaus; Hals, Arne

    2006-05-01

    This report presents background, technical solution and results from a test project (Demo I) developed in the DRR Norway) project. Software and technology from two different vendors, APAS and Powel ASA, are used to demonstrate a scheme for Automatic Demand Response (ADR) referred to spot price level and a system for documentation of demand response and cost savings. Periods with shortage of energy supply and hardly any investments in new production capacity have turned focus towards the need for increased price elasticity on the demand side in the Nordic power market. The new technology for Automatic Meter Reading (AMR) and Remote Load Control (RLC) provides an opportunity to improve the direct market participation from the demand side by introducing automatic schemes that reduce the need for customer attention to hourly market prices. The low prioritized appliances, and not the total load, are in this report defined as the Demand Response Objects, based on the assumption that there is a limit for what the customers are willing to pay for different uses of electricity. Only disconnection of residential water heaters is included in the demo, due to practical limitations. The test was performed for a group of single family houses over a period of 2 months. All the houses were equipped with a radio controlled 'Ebox' unit attached to the water heater socket. The settlement and invoicing were based on hourly metered values (kWh/h), which means that the customer benefit is equivalent to the accumulated changes in the electricity cost per hour. The actual load reduction is documented by comparison between the real meter values for the period and a reference curve. The curves show significant response to the activated control in the morning hours. In the afternoon it is more difficult to register the response, probably due to 'disturbing' activities like cooking etc. Demo I shows that load reduction referred to spot price level can be done in a smooth way. The experiences

  18. Economic demand response model in liberalised electricity markets with respect to flexibility of consumers

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2017-01-01

    . The most important solution can be demand response (DR) programs. This paper proposes an economic DR model for residential consumers in liberalized electricity markets to change their consumption pattern from times of high energy prices to other times to maximize their utility functions. This economic...... electricity at flat rates while paying no attention to the problems of this industry. This attitude was the source of many problems, sometimes leading to collapse of power systems and widespread blackouts. Restructuring of the electricity industry however provided a multitude of solutions to these problems...

  19. R and D options for demand side management in Japanese electric utilities

    International Nuclear Information System (INIS)

    Yamamoto, Takahiko

    1996-01-01

    Japanese electric demand has been steadily increasing in accordance with the economic growth. However, Japanese electric utilities are facing several problems; increasing construction cost of power facilities, siting constraints and the environmental issue of greenhouse gas emissions. To overcome these problems, electric utilities have been promoting demand-side-management (DSM) activities as well as supplier-side measures, with some presently being carried out through promoting energy conservation technologies and introducing electric tariff options of specific contracts for residential/commercial and industrial consumers. Japanese electric utilities have been carrying out R and D for the future, in particular, energy storage and heat storage which contribute to the improvement of load factor. In this paper, I would like to outline the R and D options for DSM in Japan. (author)

  20. Econometric Modeling: An Application to the Demand for Electricity ...

    African Journals Online (AJOL)

    The empirical results show an inverse relationship between real appliance purchase price, the real per capita income and the demand for electricity. Also the rate of population growth rate as a proxy for electricity consumers appears to be insignificant. This reveals the clear fact that the demand for electricity is greater than ...

  1. Smart Electric Vehicle Charging System : Controlling Multiple Electrical Vehicle Chargers using OCPP to Limit Electricity Demand

    OpenAIRE

    Ness, Gaute

    2017-01-01

    Master's thesis Renewable Energy ENE500 - University of Agder 2017 Peak demand is a problem when Electrical Vehicle charging is introduced in the electricity grid. Local limitations like fuses and transformer capacity can rapidly be overloaded if multiple Electrical Vehicles are charging at the same time. This can be solved by shifting these loads in time. This master’s Thesis presents a solution by using the communication protocol OCPP to restrict one or more chargers below a set demand l...

  2. Time-of-use based electricity demand response for sustainable manufacturing systems

    International Nuclear Information System (INIS)

    Wang, Yong; Li, Lin

    2013-01-01

    As required by the Energy Policy Act of 2005, utility companies across the U.S. are offering TOU (time-of-use) based electricity demand response programs. The TOU rate gives consumers opportunities to manage their electricity bill by shifting use from on-peak periods to mid-peak and off-peak periods. Reducing the amount of electricity needed during the peak load times makes it possible for the power grid to meet consumers' needs without building more costly backup infrastructures and help reduce GHG (greenhouse gas) emissions. Previous research on the applications of TOU and other electricity demand response programs has been mainly focused on residential and commercial buildings while largely neglected industrial manufacturing systems. This paper proposes a systems approach for TOU based electricity demand response for sustainable manufacturing systems under the production target constraint. Key features of this approach include: (i) the electricity related costs including both consumption and demand are integrated into production system modeling; (ii) energy-efficient and demand-responsive production scheduling problems are formulated and the solution technique is provided; and (iii) the effects of various factors on the near-optimal scheduling solutions are examined. The research outcome is expected to enhance the energy efficiency, electricity demand responsiveness, and cost effectiveness of modern manufacturing systems. - Highlights: • We propose a TOU based demand response approach for manufacturing systems. • Both electricity consumption and demand are integrated into the system modeling. • Energy-efficient and demand-responsive production scheduling problems are formulated. • The meta-heuristic solution technique is provided. • The effects of various factors on the scheduling solutions are examined

  3. Long-term water demand for electricity, industry and households

    NARCIS (Netherlands)

    Bijl, David L.; Bogaart, Patrick W.; Kram, Tom; de Vries, Bert J M; van Vuuren, Detlef P.

    2016-01-01

    Better water demand projections are needed in order to better assess water scarcity. The focus in this paper is on non-agricultural water demand, as this is the fastest-growing and least well-modelled demand component. We describe an end use-oriented model for future water demand in the electricity,

  4. Control strategies and cycling demands for Li-ion storage batteries in residential micro-cogeneration systems

    International Nuclear Information System (INIS)

    Darcovich, K.; Kenney, B.; MacNeil, D.D.; Armstrong, M.M.

    2015-01-01

    Highlights: • Canadian home energy system modeled with PV, ICE CHP, battery and power grid. • Battery function is modeled on fundamental electrochemical principles. • Techno-economics of control strategies assessed. • Impact of control strategies battery cycles is developed for wear analysis. • Non-monotonic nature of battery cycles with transient renewables is discussed. - Abstract: Energy storage units have become important components in residential micro-cogeneration (MCG) systems. As MCG systems are often connected to single residences or buildings in a wide variety of settings, they are frequently unique and highly customized. Lithium-ion batteries have recently gained some profile as energy storage units of choice, because of their good capacity, high efficiency, robustness and ability to meet the demands of typical residential electrical loads. In the present work, modeled scenarios are explored which examine the performance of a MCG system with an internal combustion engine, photovoltaic input and a Li-ion storage battery. An electricity demand profile from new data collected in Ottawa, Canada is used to provide a full year energy use context for the analyses. The demands placed on the battery are examined to assess the suitability of the battery size and performance, as well as control related functionalities which reveal significantly varying battery use, and led to a quantitative expression for equivalent cycles. The energy use simulations are derived from electrochemical fundamentals adapted for a larger battery pack. Simulation output provides the basis for techno-economic commentary on how to assess large-scale Li-ion batteries for effective electrical storage purposes in MCG systems, and the impact of the nature of the control strategy on the battery service life

  5. Integration of Solar Photovoltaics and Electric Vehicles in Residential Grids

    DEFF Research Database (Denmark)

    Pillai, Jayakrishnan Radhakrishna; Huang, Shaojun; Bak-Jensen, Birgitte

    2013-01-01

    In the last few years, there is an increased penetration of solar photovoltaic (SPV) units in low voltage (LV) distribution grids. Also electric vehicles (EVs) are introduced to these LV networks. This has caused the distribution networks to be more active and complex as these local generation...... and load units are characterised by unpredictable and diverse operating characteristics. This paper analyses the combined effect of SPVs and EVs in LV Danish residential grids. The EVs charging needs based on typical driving patterns of passenger cars and SPV power profiles during winter/summer days...

  6. Residential implementation of critical-peak pricing of electricity

    International Nuclear Information System (INIS)

    Herter, Karen

    2007-01-01

    This paper investigates how critical-peak pricing (CPP) affects households with different usage and income levels, with the goal of informing policy makers who are considering the implementation of CPP tariffs in the residential sector. Using a subset of data from the California Statewide Pricing Pilot of 2003-04, average load change during summer events, annual percent bill change, and post-experiment satisfaction ratings are calculated across six customer segments, categorized by historical usage and income levels. Findings show that high-use customers respond significantly more in kW reduction than do low-use customers, while low-use customers save significantly more in percentage reduction of annual electricity bills than do high-use customers-results that challenge the strategy of targeting only high-use customers for CPP tariffs. Across income levels, average load and bill changes were statistically indistinguishable, as were satisfaction rates-results that are compatible with a strategy of full-scale implementation of CPP rates in the residential sector. Finally, the high-use customers earning less than $50,000 annually were the most likely of the groups to see bill increases-about 5% saw bill increases of 10% or more-suggesting that any residential CPP implementation might consider targeting this customer group for increased energy efficiency efforts

  7. A Comparison of Optimal Operation of a Residential Fuel Cell Co-Generation System Using Clustered Demand Patterns Based on Kullback-Leibler Divergence

    Directory of Open Access Journals (Sweden)

    Takumi Hasizume

    2013-01-01

    Full Text Available When evaluating residential energy systems like co-generation systems, hot water and electricity demand profiles are critical. In this paper, the authors aim to extract basic time-series demand patterns from two kinds of measured demand (electricity and domestic hot water, and also aim to reveal effective demand patterns for primary energy saving. Time-series demand data are categorized with a hierarchical clustering method using a statistical pseudo-distance, which is represented by the generalized Kullback-Leibler divergence of two Gaussian mixture distributions. The classified demand patterns are built using hierarchical clustering and then a comparison is made between the optimal operation of a polymer electrolyte membrane fuel cell co-generation system and the operation of a reference system (a conventional combination of a condensing gas boiler and electricity purchased from the grid using the appropriately built demand profiles. Our results show that basic demand patterns are extracted by the proposed method, and the heat-to-power ratio of demand, the amount of daily demand, and demand patterns affect the primary energy saving of the co-generation system.

  8. Electricity demand forecasting using regression, scenarios and pattern analysis

    CSIR Research Space (South Africa)

    Khuluse, S

    2009-02-01

    Full Text Available The objective of the study is to forecast national electricity demand patterns for a period of twenty years: total annual consumption and understanding seasonal effects. No constraint on the supply of electricity was assumed...

  9. Price elasticity estimation of electricity demand in France

    International Nuclear Information System (INIS)

    Bourbonnais, Regis; Keppler, Jan Horst

    2013-10-01

    On request of the French Union of Electricity (UFE), the authors have carried out a series of econometric statistical tests in order to determine the price elasticity of electricity demand in France. The results obtained are all solid and realistic

  10. Demand side management of electric car charging

    DEFF Research Database (Denmark)

    Finn, P.; Fitzpatrick, C.; Connolly, David

    2012-01-01

    in terms of distributed energy storage and flexible load. This paper examines how optimising the charging cycles of an electriccar using DSM (DemandSideManagement) based on a number of criteria could be used to achieve financial savings, increased demand on renewable energy, reduce demand on thermal...... generation plant, and reduce peak load demand. The results demonstrate that significant gains can be achieved using currently available market data which highlights the point that DSM can be implemented without any further technological advents....

  11. Impact of Scheduling Flexibility on Demand Profile Flatness and User Inconvenience in Residential Smart Grid System

    Directory of Open Access Journals (Sweden)

    Naveed Ul Hassan

    2013-12-01

    Full Text Available The objective of this paper is to study the impact of scheduling flexibility on both demand profile flatness and user inconvenience in residential smart grid systems. Temporal variations in energy consumption by end users result in peaks and troughs in the aggregated demand profile. In a residential smart grid, some of these peaks and troughs can be eliminated through appropriate load balancing algorithms. However, load balancing requires user participation by allowing the grid to re-schedule some of their loads. In general, more scheduling flexibility can result in more demand profile flatness, however the resulting inconvenience to users would also increase. In this paper, our objective is to help the grid determine an appropriate amount of scheduling flexibility that it should demand from users, based on which, proper incentives can be designed. We consider three different types of scheduling flexibility (delay, advance scheduling and flexible re-scheduling in flexible loads and develop both optimal and sub-optimal scheduling algorithms. We discuss their implementation in centralized and distributed manners. We also identify the existence of a saturation point. Beyond this saturation point, any increase in scheduling flexibility does not significantly affect the flatness of the demand profile while user inconvenience continues to increase. Moreover, full participation of all the households is not required since increasing user participation only marginally increases demand profile flatness.

  12. Industrial electricity demand for Turkey: A structural time series analysis

    International Nuclear Information System (INIS)

    Dilaver, Zafer; Hunt, Lester C.

    2011-01-01

    This research investigates the relationship between Turkish industrial electricity consumption, industrial value added and electricity prices in order to forecast future Turkish industrial electricity demand. To achieve this, an industrial electricity demand function for Turkey is estimated by applying the structural time series technique to annual data over the period 1960 to 2008. In addition to identifying the size and significance of the price and industrial value added (output) elasticities, this technique also uncovers the electricity Underlying Energy Demand Trend (UEDT) for the Turkish industrial sector and is, as far as is known, the first attempt to do this. The results suggest that output and real electricity prices and a UEDT all have an important role to play in driving Turkish industrial electricity demand. Consequently, they should all be incorporated when modelling Turkish industrial electricity demand and the estimated UEDT should arguably be considered in future energy policy decisions concerning the Turkish electricity industry. The output and price elasticities are estimated to be 0.15 and - 0.16 respectively, with an increasing (but at a decreasing rate) UEDT and based on the estimated equation, and different forecast assumptions, it is predicted that Turkish industrial electricity demand will be somewhere between 97 and 148 TWh by 2020. -- Research Highlights: → Estimated output and price elasticities of 0.15 and -0.16 respectively. → Estimated upward sloping UEDT (i.e. energy using) but at a decreasing rate. → Predicted Turkish industrial electricity demand between 97 and 148 TWh in 2020.

  13. Modeling of Residential Water Demand Using Random Effect Model,Case Study: Arak City

    Directory of Open Access Journals (Sweden)

    Seyed Hossein Sajadifar

    2011-10-01

    Full Text Available The present study tries to apply the “Partial Adjustment Model” and “Random Effect Model” techniques to the Stone-Greay’s linear expenditure system, in order to estimate the "Residential Seasonal Demand" for water in Arak city. Per capita water consumption of family residences is regressed on marginal price, per capita income, price of other goods, average temperature and average rainfall. Panel data approaches based on a sample of 152 observations from Arak city referred to 1993-2003. From the estimation of the Elasticity-price of the residential water demand, we want to know how a policy of responsive pricing can lead to more efficient household water consumption inArakcity. Results also indicated that summer price elasticity was twice the winter and price and income elasticity was less than 1 in all cases.

  14. Assessing incentive contracts for reducing residential electricity consumption: new experimental methods for new results

    International Nuclear Information System (INIS)

    Frachet, Laure

    2013-01-01

    Facing economic, political and environmental stakes, electricity providers are nowadays developing incentive tools, in order to reduce consumer's demand, particularly during peak demand periods. For residential customers, these tools can be tariffs (dynamic pricing of time-of-use tariffs), or informative devices or services (feedbacks on historical or real-time consumption, given on various media). They might go along with automation systems that can help cutting of some electric devices when needed. In order to evaluate the capacity of these settings among their customers, electricity utilities are developing quite a few studies, which are mainly field experiment often called pilots. During these pilots, demand response tools are implemented on a population sample. These long and expensive studies lid to quantitative and qualitative analysis. We have compiled about 40 of them and extract from this survey some generalizable teachings. We have shown what these results were and highlighted pilot programs' methodological limits. In order to propose a substitute to these heavy experimentations, we assessed the capacity or experimental economics. This relatively new discipline's objective is to evaluation the efficiency of institutions, like markets, but also to study what animate economic agents' behaviour, e.g. preferences, beliefs, cognitive biases, willingness to pay... We were also able to elaborate an experimental protocol dedicated to the evaluation of some demand response contracts' acceptability. The results collected during 14 experimental sessions gave us some innovative clues and insight on these contracts acceptability. But, beyond these results, we have demonstrated that even if experimental economics can't obviously be a substitute for field experiments, it can represent an interesting exploratory methodology. To sum up the experimental economics can take part of residential customers' behaviour understanding, performing

  15. Electric energy demand and supply prospects for California

    Science.gov (United States)

    Jones, H. G. M.

    1978-01-01

    A recent history of electricity forecasting in California is given. Dealing with forecasts and regulatory uncertainty is discussed. Graphs are presented for: (1) Los Angeles Department of Water and Power and Pacific Gas and Electric present and projected reserve margins; (2) California electricity peak demand forecast; and (3) California electricity production.

  16. Study on reduction of consumption and peak demand of electric power used in residential houses with solar heating and PV systems; Solar house no fuka heijunka to energy sakugen koka ni kansuru kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    Udagawa, M.; Endo, T. [Kogakuin University, Tokyo (Japan)

    1994-12-08

    A model house was simulated to reduce the consumption and peak demand for the photovoltaic power generation system, and solar heat air heating and hot water supply system in the solar house. As a type of construction, both wooden construction and reinforced concrete (RC) construction were selected with a total floor area of 125m{sup 2}. All the rooms were equipped with an air conditioner by heat pump from the air thermal source. A solar heat floor heater was simultaneously installed on the first floor. The hot water supply load was 4.8MWh per year. A commercial grid-connected on-site system was applied to the photovoltaic power generation with a 20m{sup 2} wide monocrystalline Si solar cell panel. As for the fluctuation in power load, the peak at the time of rising is more reduced in the RC house than in the wooden house, because the former is smaller in temperature fluctuation than the latter during the intermittence of air conditioning (as per the specified operational schedule). Therefore, the power is more leveled off in the former than in the latter. Between both, difference was hardly made in energy consumption per year. The ratio of dependency was 47% upon the photovoltaic power generation system, while it was 50% and 77%, under the air heating power load and hot water supply power load, respectively, upon the solar heat air heating and hot water supply system, so that both systems were considerably effective in saving the energy. 5 refs., 7 figs., 1 tab.

  17. Impact of residential PV adoption on Retail Electricity Rates

    International Nuclear Information System (INIS)

    Cai, Desmond W.H.; Adlakha, Sachin; Low, Steven H.; De Martini, Paul; Mani Chandy, K.

    2013-01-01

    The price of electricity supplied from home rooftop photo voltaic (PV) solar cells has fallen below the retail price of grid electricity in some areas. A number of residential households have an economic incentive to install rooftop PV systems and reduce their purchases of electricity from the grid. A significant portion of the costs incurred by utility companies are fixed costs which must be recovered even as consumption falls. Electricity rates must increase in order for utility companies to recover fixed costs from shrinking sales bases. Increasing rates will, in turn, result in even more economic incentives for customers to adopt rooftop PV. In this paper, we model this feedback between PV adoption and electricity rates and study its impact on future PV penetration and net-metering costs. We find that the most important parameter that determines whether this feedback has an effect is the fraction of customers who adopt PV in any year based solely on the money saved by doing so in that year, independent of the uncertainties of future years. These uncertainties include possible changes in rate structures such as the introduction of connection charges, the possibility of PV prices dropping significantly in the future, possible changes in tax incentives, and confidence in the reliability and maintainability of PV. -- Highlights: •Households who install PV reduce their electricity consumption from the grid. •Electricity rates must increase for utility companies to recover its fixed costs. •However, higher electricity rates give households more incentives to adopt PV. •We find that this feedback has significant impact on PV uptake only in later years. •Utility companies could lose a significant fraction of high consumption customers

  18. Estimating the residential demand function for natural gas in Seoul with correction for sample selection bias

    International Nuclear Information System (INIS)

    Yoo, Seung-Hoon; Lim, Hea-Jin; Kwak, Seung-Jun

    2009-01-01

    Over the last twenty years, the consumption of natural gas in Korea has increased dramatically. This increase has mainly resulted from the rise of consumption in the residential sector. The main objective of the study is to estimate households' demand function for natural gas by applying a sample selection model using data from a survey of households in Seoul. The results show that there exists a selection bias in the sample and that failure to correct for sample selection bias distorts the mean estimate, of the demand for natural gas, downward by 48.1%. In addition, according to the estimation results, the size of the house, the dummy variable for dwelling in an apartment, the dummy variable for having a bed in an inner room, and the household's income all have positive relationships with the demand for natural gas. On the other hand, the size of the family and the price of gas negatively contribute to the demand for natural gas. (author)

  19. Determining the Effects on Residential Electricity Prices and Carbon Emissions of Electricity Market Restructuring in Alberta

    Science.gov (United States)

    Jahangir, Junaid Bin

    When electricity restructuring initiatives were introduced in Alberta, and finalized with the institution of retail electricity market competition in 2001, it was argued that the changes would deliver lower electricity prices to residential consumers. However, residential electricity prices in Alberta increased dramatically in 2001, and have never returned to their pre-restructuring levels. Proponents of restructuring argue that electricity prices would have been even higher under continued regulation, citing the effect of considerably higher natural gas prices and the roles of other variables. However, many Alberta residential electricity consumers tend to attribute their higher electricity prices to factors such as market power and manipulation associated with restructuring. Since the effects of restructuring on electricity prices cannot be evaluated by simply comparing prices before and after it occurred, the main objective of this thesis is to determine what electricity prices would have been under continued regulation, and to compare them with what was actually observed. To determine these counterfactual electricity prices, a structural model of the determinants of Alberta residential electricity prices is developed, estimated for the prerestructuring period, and used to forecast (counterfactual) prices in the postrestructuring period. However, in forming these forecasts it is necessary to separately account for changes in explanatory variables that could be viewed as occurring due to the restructuring (endogenous) from those changes that would Since the effects of restructuring on electricity prices cannot be evaluated by simply comparing prices before and after it occurred, the main objective of this thesis is to determine what electricity prices would have been under continued regulation, and to compare them with what was actually observed. To determine these counterfactual electricity prices, a structural model of the determinants of Alberta residential

  20. An electricity generation planning model incorporating demand response

    International Nuclear Information System (INIS)

    Choi, Dong Gu; Thomas, Valerie M.

    2012-01-01

    Energy policies that aim to reduce carbon emissions and change the mix of electricity generation sources, such as carbon cap-and-trade systems and renewable electricity standards, can affect not only the source of electricity generation, but also the price of electricity and, consequently, demand. We develop an optimization model to determine the lowest cost investment and operation plan for the generating capacity of an electric power system. The model incorporates demand response to price change. In a case study for a U.S. state, we show the price, demand, and generation mix implications of a renewable electricity standard, and of a carbon cap-and-trade policy with and without initial free allocation of carbon allowances. This study shows that both the demand moderating effects and the generation mix changing effects of the policies can be the sources of carbon emissions reductions, and also shows that the share of the sources could differ with different policy designs. The case study provides different results when demand elasticity is excluded, underscoring the importance of incorporating demand response in the evaluation of electricity generation policies. - Highlights: ► We develop an electric power system optimization model including demand elasticity. ► Both renewable electricity and carbon cap-and-trade policies can moderate demand. ► Both policies affect the generation mix, price, and demand for electricity. ► Moderated demand can be a significant source of carbon emission reduction. ► For cap-and-trade policies, initial free allowances change outcomes significantly.

  1. A Cost-Effective Electric Vehicle Charging Method Designed For Residential Homes with Renewable Energy

    Science.gov (United States)

    Lie, T. T.; Liang, Xiuli; Haque, M. H.

    2015-03-01

    Most of the electrical infrastructure in use around the world today is decades old, and may be illsuited to widespread proliferation of personal Electric Vehicles (EVs) whose charging requirements will place increasing strain on grid demand. In order to reduce the pressure on the grid and taking benefits of off peak charging, this paper presents a smart and cost effective EV charging methodology for residential homes equipped with renewable energy resources such as Photovoltaic (PV) panels and battery. The proposed method ensures slower battery degradation and prevents overcharging. The performance of the proposed algorithm is verified by conducting simulation studies utilizing running data of Nissan Altra. From the simulation study results, the algorithm is shown to be effective and feasible which minimizes not only the charging cost but also can shift the charging time from peak value to off-peak time.

  2. [Demography perspectives and forecasts of the demand for electricity].

    Science.gov (United States)

    Roy, L; Guimond, E

    1995-01-01

    "Demographic perspectives form an integral part in the development of electric load forecasts. These forecasts in turn are used to justify the addition and repair of generating facilities that will supply power in the coming decades. The goal of this article is to present how demographic perspectives are incorporated into the electric load forecasting in Quebec. The first part presents the methods, hypotheses and results of population and household projections used by Hydro-Quebec in updating its latest development plan. The second section demonstrates applications of such demographic projections for forecasting the electric load, with a focus on the residential sector." (SUMMARY IN ENG AND SPA) excerpt

  3. U.S. electric utility demand-side management 1995

    International Nuclear Information System (INIS)

    1997-01-01

    The US Electric Utility Demand-Side Management report is prepared by the Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternative Fuels; Energy Information Administration (EIA); US Department of Energy. The report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ''Profile: US Electric Utility Demand-Side Management'', presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs

  4. U.S. electric utility demand-side management 1995

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-01-01

    The US Electric Utility Demand-Side Management report is prepared by the Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternative Fuels; Energy Information Administration (EIA); US Department of Energy. The report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ``Profile: US Electric Utility Demand-Side Management``, presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

  5. Industrial companies' demand for electricity. Evidence from a micropanel

    International Nuclear Information System (INIS)

    Bjoerner, T.B.; Togeby, M.; Jensen, H.H.

    2001-01-01

    The paper presents a micro-econometric analysis of industrial companies' demand for electricity. Previous studies on electricity consumption in the industrial sector have relied on aggregate data or cross-section observations. Here we present an econometric study on electricity demand based on a panel of 2949 Danish companies followed from 1983 to 1996. It is found that estimators of electricity demand that take account of the panel structure (fixed effect models) yield considerably lower price and production elasticities compared to estimators that do not (like cross-section models). It is also investigated how various company characteristics like size, type of industrial sub-sector and electricity intensity in production influence price and production elasticities. It appears that companies with a high electricity intensity also have a high own-price elasticity

  6. Use of demand response in electricity markets

    DEFF Research Database (Denmark)

    Singh, Sri Niwas; Østergaard, Jacob

    2010-01-01

    Demand response (DR) can provide sufficient measure, if implemented successfully, to provide economic, secure and stable supply to the customers even under the variability of the generated output from renewable energy source such as wind and solar. However, there are several issues to be analyzed...

  7. An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand

    International Nuclear Information System (INIS)

    Ji, L.; Niu, D.X.; Huang, G.H.

    2014-01-01

    In this paper a stochastic robust optimization problem of residential micro-grid energy management is presented. Combined cooling, heating and electricity technology (CCHP) is introduced to satisfy various energy demands. Two-stage programming is utilized to find the optimal installed capacity investment and operation control of CCHP (combined cooling heating and power). Moreover, interval programming and robust stochastic optimization methods are exploited to gain interval robust solutions under different robustness levels which are feasible for uncertain data. The obtained results can help micro-grid managers minimizing the investment and operation cost with lower system failure risk when facing fluctuant energy market and uncertain technology parameters. The different robustness levels reflect the risk preference of micro-grid manager. The proposed approach is applied to residential area energy management in North China. Detailed computational results under different robustness level are presented and analyzed for providing investment decision and operation strategies. - Highlights: • An inexact two-stage stochastic robust programming model for CCHP management. • The energy market and technical parameters uncertainties were considered. • Investment decision, operation cost, and system safety were analyzed. • Uncertainties expressed as discrete intervals and probability distributions

  8. The demand function for residential heat through district heating system and its consumption benefits in Korea

    International Nuclear Information System (INIS)

    Lim, Seul-Ye; Kim, Hyo-Jin; Yoo, Seung-Hoon

    2016-01-01

    The demand for residential heat (RH) through a district heating system (DHS) has been and will be expanded in Korea due to its better performance in energy efficiency and the abatement of greenhouse gas emissions than decentralized boilers. The purposes of this paper are two-fold. The first is to obtain the demand function for DHS-based RH in Korea and investigate the price and income elasticities of the demand employing the quarterly data covering the period 1988–2013. The short-run price and income elasticities are estimated as −0.700 and 0.918, respectively. Moreover, the long-run elasticities are −1.253 and 1.642, respectively. The second purpose is to measure the consumption benefits of DHS-based-RH employing the economic theory that they are the sum of the actual payment and consumer surplus for the consumption. Considering that the average price and estimated consumer surplus of the DHS-based RH use in 2013 are computed to be KRW 87,870 (USD 84.1) and KRW 62,764 (USD 60.1) per Gcal, the consumption benefits of the DHS-based RH are calculated to be KRW 150,634 (USD 144.2) per Gcal. This information can be beneficially utilized to conduct an economic feasibility study for a new DHS project related to RH supply. - Highlights: • Demand for residential heat (RH) from district heating system (DHS) is expanding. • We estimate the demand function for and consumption benefits of DHS-based RH. • Short-run price and income elasticities are −0.700 and 0.918, respectively. • Long-run price and income elasticities are −1.253 and 1.642, respectively. • Consumption benefits of DHS-based RH are KRW 150,634 (USD 144.2) per Gcal.

  9. Forecasts of demand for electricity: 1980 - 2000

    International Nuclear Information System (INIS)

    1981-01-01

    Forecasts of the growth rate of electrical energy consumption in Canada over the period 1980 to 2000 are presented and then translated into requirements for generating capacity beyond existing and currently committed facilities. Two sets of forecasts are presented: one based on statistical modelling techniques of the Dept. of Energy, Mines and Resources, and a second which represents the views of each provincial electrical utility. It is possible to foresee the need for from two to seven more power reactors beyond Darlington in Ontario, and there is a potential role for nuclear generation in Quebec beyond the mid-1990s. The Atlantic region could accommodate a second reactor in the 1990s

  10. Why Electricity Demand Is Highly Income-Elastic in Spain: A Cross-Country Comparison Based on an Index-Decomposition Analysis

    Directory of Open Access Journals (Sweden)

    Julián Pérez-García

    2017-03-01

    Full Text Available Since 1990, Spain has had one of the highest elasticities of electricity demand in the European Union. We provide an in-depth analysis into the causes of this high elasticity, and we examine how these same causes influence electricity demand in other European countries. To this end, we present an index-decomposition analysis of growth in electricity demand which allows us to identify three key factors in the relationship between gross domestic product (GDP and electricity demand: (i structural change; (ii GDP growth; and (iii intensity of electricity use. Our findings show that the main differences in electricity demand elasticities across countries and time are accounted for by the fast convergence in residential per capita electricity consumption. This convergence has almost concluded, and we expect the Spanish energy demand elasticity to converge to European standards in the near future.

  11. U.S. electric utility demand-side management 1993

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-07-01

    This report presents comprehensive information on electric power industry demand-side management activities in the United States at the national, regional, and utility levels. Data is included for energy savings, peakload reductions, and costs.

  12. Meteorology and electric power demand; Variabili meteorologici e fabbisogno elettrico

    Energy Technology Data Exchange (ETDEWEB)

    Bonelli, P. [CESI Rubattino, Milan (Italy); Starita, S. [Associazione Ingegneri per l' Ambiente e il Territorio, Partecipazione a iniziative di terzi, Milan (Italy)

    2001-06-01

    A predictable correlation between electric power demand and meteorology variation is analyzed. [Italian] Esiste una correlazione prevedibile tra l'anadamento del fabbisogno elettrico e le variabili meteorologiche.

  13. Estimation of electricity demand of Iran using two heuristic algorithms

    International Nuclear Information System (INIS)

    Amjadi, M.H.; Nezamabadi-pour, H.; Farsangi, M.M.

    2010-01-01

    This paper deals with estimation of electricity demand of Iran based on economic indicators using Particle Swarm Optimization (PSO) Algorithm. The estimation is based on Gross Domestic Product (GDP), population, number of customers and average price electricity by developing two different estimation models: a linear model and a non-linear model. The proposed models are obtained based upon available actual data of 21 years; since 1980-2000. Then the models obtained are used to estimate the electricity demand of the target years; for a period of time e.g. 2001-2006 and the results obtained are compared with the actual demand during this period. Furthermore, to validate the results obtained by PSO, genetic algorithm (GA) is applied to solve the problem. The results show that the PSO is a useful optimization tool for solving the problem using two developed models and can be used as an alternative solution to estimate the future electricity demand.

  14. Dynamics of Electricity Demand in Lesotho: A Kalman Filter Approach

    Directory of Open Access Journals (Sweden)

    Thamae Retselisitsoe Isaiah

    2015-04-01

    Full Text Available This study provides an empirical analysis of the time-varying price and income elasticities of electricity demand in Lesotho for the period 1995-2012 using the Kalman filter approach. The results reveal that economic growth has been one of the main drivers of electricity consumption in Lesotho while electricity prices are found to play a less significant role since they are monopoly-driven and relatively low when compared to international standards. These findings imply that increases in electricity prices in Lesotho might not have a significant impact on consumption in the short-run. However, if the real electricity prices become too high over time, consumers might change their behavior and sensitivity to price and hence, energy policymakers will need to reconsider their impact in the long-run. Furthermore, several exogenous shocks seem to have affected the sensitivity of electricity demand during the period prior to regulation, which made individuals, businesses and agencies to be more sensitive to electricity costs. On the other hand, the period after regulation has been characterized by more stable and declining sensitivity of electricity demand. Therefore, factors such as regulation and changes in the country’s economic activities appear to have affected both price and income elasticities of electricity demand in Lesotho.

  15. Economic Microgrid Planning Algorithm with Electric Vehicle Charging Demands

    Directory of Open Access Journals (Sweden)

    Sung-Guk Yoon

    2017-09-01

    Full Text Available Two of the most important technologies for future power systems to reduce greenhouse gas are electric vehicles (EVs and renewable generation. When EVs become more common, the overall demand of electricity will significantly increase because EVs consume a large amount of electricity. Also, a daily load curve with EVs heavily depends on how much electricity EVs consume and when electricity is consumed. The microgrid is an important technology to promote renewable generation, and the increased demand and changed load curve should be considered in the microgrid planning stage to install robust and economical microgrids. In this paper, we propose an algorithm for microgrid planning with EV charging demand to find the most economical configuration through which to maximally utilize renewable generation. The algorithm uses a renewable generation-following EV charging scheme and HOMER. Through simulations, it is shown that the microgrid constructed by the proposed algorithm reduces the investment cost and CO2 emission.

  16. Residential Demand Response Behaviour Modeling applied to Cyber-physical Intrusion Detection

    DEFF Research Database (Denmark)

    Heussen, Kai; Tyge, Emil; Kosek, Anna Magdalena

    2017-01-01

    A real-time demand response system can be viewed as a cyber-physical system, with physical systems dependent on cyber infrastructure for coordination and control, which may be vulnerable to cyber-attacks. The time domain dynamic behaviour of individual residential demand responses is governed...... by a mix of physical system parameters, exogenous influences, user behaviour and preferences, which can be characterized by unstructured models such as a time-varying finite impulse response. In this study, which is based on field data, it is shown how this characteristic response behaviours can...... be identified and how the characterization can be updated continuously. Finally, we propose an approach to apply this behaviour characterization to the identification of anomalous and potentially malicious behaviour modifications as part of a cyber-physical intrusion detection mechanism....

  17. Coordinated Demand Response and Distributed Generation Management in Residential Smart Microgrids

    DEFF Research Database (Denmark)

    Anvari-Moghaddam, Amjad; Mokhtari, Ghassem; Guerrero, Josep M.

    2016-01-01

    potentials to increase the functionality of a typical demand-side management (DSM) strategy, and typical implementation of building-level DERs by integrating them into a cohesive, networked package that fully utilizes smart energy-efficient end-use devices, advanced building control/automation systems....... Finally, the effectiveness and applicability of the proposed model is tested and validated in different operating modes compared to the existing models. The findings of this chapter show that by the use of an expert EMS that coordinates supply and demand sides simultaneously, it is very possible not only......Nowadays with the emerging of small-scale integrated energy systems (IESs) in form of residential smart microgrids (SMGs), a large portion of energy can be saved through coordinated scheduling of smart household devices and management of distributed energy resources (DERs). There are significant...

  18. Functional forms and price elasticities in a discrete continuous choice model of the residential water demand

    Science.gov (United States)

    Vásquez Lavín, F. A.; Hernandez, J. I.; Ponce, R. D.; Orrego, S. A.

    2017-07-01

    During recent decades, water demand estimation has gained considerable attention from scholars. From an econometric perspective, the most used functional forms include log-log and linear specifications. Despite the advances in this field and the relevance for policymaking, little attention has been paid to the functional forms used in these estimations, and most authors have not provided justifications for their selection of functional forms. A discrete continuous choice model of the residential water demand is estimated using six functional forms (log-log, full-log, log-quadratic, semilog, linear, and Stone-Geary), and the expected consumption and price elasticity are evaluated. From a policy perspective, our results highlight the relevance of functional form selection for both the expected consumption and price elasticity.

  19. Turkey opens electricity markets as demand grows

    Energy Technology Data Exchange (ETDEWEB)

    McKeigue, J.; Da Cunha, A.; Severino, D. [Global Business Reports (United States)

    2009-06-15

    Turkey's growing power market has attracted investors and project developers for over a decade, yet their plans have been dashed by unexpected political or financial crises or, worse, obstructed by a lengthy bureaucratic approval process. Now, with a more transparent retail electricity market, government regulators and investors are bullish on Turkey. Is Turkey ready to turn the power on? This report closely examine Turkey's plans to create a power infrastructure capable of providing the reliable electricity supplies necessary for sustained economic growth. It was compiled with on-the-ground research and extensive interview with key industrial and political figures. Today, hard coal and lignite account for 21% of Turkey's electricity generation and gas-fired plants account for 50%. The Alfin Elbistan-B lignite-fired plant has attracted criticism for its lack of desulfurization units and ash dam facilities that have tarnished the industry's image. A 1,100 MW hard-coal fired plant using supercritical technology is under construction. 9 figs., 1 tab.

  20. Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices

    Science.gov (United States)

    Chassin, David P.; Donnelly, Matthew K.; Dagle, Jeffery E.

    2006-12-12

    Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices are described. In one aspect, an electrical power distribution control method includes providing electrical energy from an electrical power distribution system, applying the electrical energy to a load, providing a plurality of different values for a threshold at a plurality of moments in time and corresponding to an electrical characteristic of the electrical energy, and adjusting an amount of the electrical energy applied to the load responsive to an electrical characteristic of the electrical energy triggering one of the values of the threshold at the respective moment in time.

  1. Consumer behavior in renewable electricity: Can branding in accordance with identity signaling increase demand for renewable electricity and strengthen supplier brands?

    International Nuclear Information System (INIS)

    Hanimann, Raphael; Vinterbäck, Johan; Mark-Herbert, Cecilia

    2015-01-01

    A higher percentage of energy from renewable resources is an important goal on many environmental policy agendas. Yet, the demand for renewable electricity in liberalized markets has developed much more slowly than the demand for other green products. To date, research has mainly examined the willingness to pay for renewable electricity, but limited research has been conducted on the motivations behind it. The concept of identity signaling has proven to play a significant role in consumer behavior for green products. However, (renewable) electricity in the Swedish residential market typically lacks two important drivers for identity signaling: visibility and product involvement. A consumer choice simulation among 434 Swedish households compared consumer choices for renewable electricity contracts. The results show a positive effect of identity signaling on the demand for renewable electricity and yield suggestions for increasing the share of renewable electricity without market distorting measures. This leads to implications for policymakers, electricity suppliers and researchers. - Highlights: • Low demand for renewable electricity contracts falls short of high market potential. • For this study a consumer choice simulation for electricity contracts was processed. • Higher visibility and involvement increases demand for green electricity contracts. • Branding that enables identity signaling contributes to green energy policy goals

  2. Potential Effect and Analysis of High Residential Solar Photovoltaic (PV Systems Penetration to an Electric Distribution Utility (DU

    Directory of Open Access Journals (Sweden)

    Jeffrey Tamba Dellosa

    2016-11-01

    Full Text Available The Renewable Energy Act of 2008 in the Philippines provided an impetus for residential owners to explore solar PV installations at their own rooftops through the Net-Metering policy. The Net-Metering implementation through the law however presented some concerns with inexperienced electric DU on the potential effect of high residential solar PV system installations. It was not known how a high degree of solar integration to the grid can possibly affect the operations of the electric DU in terms of energy load management. The primary objective of this study was to help the local electric DU in the analysis of the potential effect of high residential solar PV system penetration to the supply and demand load profile in an electric distribution utility (DU grid in the province of Agusan del Norte, Philippines. The energy consumption profiles in the year 2015 were obtained from the electric DU operating in the area. An average daily energy demand load profile was obtained from 0-hr to the 24th hour of the day based from the figures provided by the electric DU. The assessment part of the potential effect of high solar PV system integration assumed four potential total capacities from 10 Mega Watts (MW to 40 MW generated by all subscribers in the area under study at a 10 MW interval. The effect of these capacities were measured and analyzed with respect to the average daily load profile of the DU. Results of this study showed that a combined installations beyond 20 MWp coming from all subscribers is not viable for the local electric DU based on their current energy demand or load profile. Based from the results obtained, the electric DU can make better decisions in the management of high capacity penetration of solar PV systems in the future, including investment in storage systems when extra capacities are generated. Article History: Received July 15th 2016; Received in revised form Sept 23rd 2016; Accepted Oct 1st 2016; Available online How to Cite

  3. Reducing Electricity Demand Peaks by Scheduling Home Appliances Usage

    DEFF Research Database (Denmark)

    Rossello Busquet, Ana; Kardaras, Georgios; Iversen, Villy Bæk

    2011-01-01

    . On the contrary, the low priority devices have to pause their operation, when the algorithm dictates it, and resume it in the future. This can become beneficial for both energy companies and users. The electricity suppliers companies will be capable of regulating power generation during demand peaks periods....... Moreover, users can be granted lower electricity bill rates for accepting delaying the operation of some of their appliances. In order to analyze this scenario, teletraffic engineering theory, which is used in evaluating the performance of telecommunication networks, is used. A reversible fair scheduling......Nowadays there is a tendency to consume electricity during the same period of the day leading to demand peaks. Regular energy consumption habits lead to demand peaks at specific temporal intervals, because users consume power at the same time. In order to avoid demand peaks, users’ appliances...

  4. Simulation of annual electric lighting demand using various occupancy profiles

    DEFF Research Database (Denmark)

    Iversen, Anne; Andersen, Philip Hvidthøft Delff; Svendsen, Svend

    2013-01-01

    This paper describes an investigation of the effect on electric lighting demand of applying occupancy models of various resolution to climate-based daylight modelling. The lighting demand was evaluated for a building zone with the occupant always present, with occupancy corresponding to absence...... factors, based on an estimated annual mean occupancy, based on estimated 1-hour mean occupancy, and based on 2-min occupancy intervals. The results showed little difference in the annual electric lighting demand when the same occupancy profile was used every day, as opposed to when profiles were used...... where occupancy varied every day. Furthermore, the results showed that annual electric lighting demand was evaluated slightly conservatively when a mean absence factor was applied as opposed to using dynamic occupancy profiles....

  5. An Empirical Analysis of Electricity Demand in Pakistan

    Directory of Open Access Journals (Sweden)

    Noel Alter

    2011-01-01

    Full Text Available Study utilizes cointegration and vector error correction analysis to determination the long and short run dynamics between electricity demand and its determinants. Study uses time series data for Pakistan from 1970 to 2010. Johansen cointegration test indicate that variables integrate in the long run. Error correction term reflects the convergence of variables towards equilibrium. Electricity acts as a necessity in short run and luxury in long run. Study concludes that effective price and income policies, group pricing policy and peak-load pricing policy should be exercised for electricity demand management.

  6. US electric utility demand-side management, 1994

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-26

    The report presents comprehensive information on electric power industry demand-side management (DSM) activities in US at the national, regional, and utility levels. Objective is provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ``Profile: US Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions, and costs attributable to DSM.

  7. Price-elastic demand in deregulated electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Siddiqui, Afzal S.

    2003-05-01

    The degree to which any deregulated market functions efficiently often depends on the ability of market agents to respond quickly to fluctuating conditions. Many restructured electricity markets, however, experience high prices caused by supply shortages and little demand-side response. We examine the implications for market operations when a risk-averse retailer's end-use consumers are allowed to perceive real-time variations in the electricity spot price. Using a market-equilibrium model, we find that price elasticity both increases the retailers revenue risk exposure and decreases the spot price. Since the latter induces the retailer to reduce forward electricity purchases, while the former has the opposite effect, the overall impact of price responsive demand on the relative magnitudes of its risk exposure and end-user price elasticity. Nevertheless, price elasticity decreases cumulative electricity consumption. By extending the analysis to allow for early settlement of demand, we find that forward stage end-user price responsiveness decreases the electricity forward price relative to the case with price-elastic demand only in real time. Moreover, we find that only if forward stage end-user demand is price elastic will the equilibrium electricity forward price be reduced.

  8. Accelerated electricity conservation in Juneau, Alaska: A study of household activities that reduced demand 25%

    International Nuclear Information System (INIS)

    Leighty, Wayne; Meier, Alan

    2011-01-01

    An avalanche destroyed the main hydroelectric transmission line to Juneau, Alaska in April, 2008. Diesel-generated electricity was substituted, causing electricity prices to increase 500% for 45 days. Electricity demand fell by 25% during the supply disruption. Most of the reduction occurred before the higher rates were implemented. Some conservation - about 8% of historic consumption - persisted after the transmission line was repaired and prices returned to normal. Consumers reduced energy use through a combination of new habits and technical improvements. A survey of residential consumers indicated that the average household undertook 10 conservation actions, with major changes in lighting, space heating, fuel switching, and water and appliance use. We propose a method for prioritizing conservation actions for promotion according to their impact in electricity savings (as a function of popularity, effectiveness, and persistence) and a dynamic framework for electricity use before, during, and after a supply disruption (i.e., both the magnitude and rates of change in electricity conservation). - Research highlights: → An electricity supply disruption caused prices to increase 500% for 45 days. → Electricity conservation of 25% occurred in a matter of days. → Electricity conservation of 8% persisted after the supply disruption was repaired. → Conservation occurred through behavior change and technology adoption. → The disruption induced consumers to try new behaviors that became new habits.

  9. U.S. electric utility demand-side management 1996

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-01

    The US Electric Utility Demand-Side Management report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it related to the US electric power industry. The first chapter, ``Profile: U.S. Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

  10. Modeling and Forecasting Electricity Demand in Azerbaijan Using Cointegration Techniques

    Directory of Open Access Journals (Sweden)

    Fakhri J. Hasanov

    2016-12-01

    Full Text Available Policymakers in developing and transitional economies require sound models to: (i understand the drivers of rapidly growing energy consumption and (ii produce forecasts of future energy demand. This paper attempts to model electricity demand in Azerbaijan and provide future forecast scenarios—as far as we are aware this is the first such attempt for Azerbaijan using a comprehensive modelling framework. Electricity consumption increased and decreased considerably in Azerbaijan from 1995 to 2013 (the period used for the empirical analysis—it increased on average by about 4% per annum from 1995 to 2006 but decreased by about 4½% per annum from 2006 to 2010 and increased thereafter. It is therefore vital that Azerbaijani planners and policymakers understand what drives electricity demand and be able to forecast how it will grow in order to plan for future power production. However, modeling electricity demand for such a country has many challenges. Azerbaijan is rich in energy resources, consequently GDP is heavily influenced by oil prices; hence, real non-oil GDP is employed as the activity driver in this research (unlike almost all previous aggregate energy demand studies. Moreover, electricity prices are administered rather than market driven. Therefore, different cointegration and error correction techniques are employed to estimate a number of per capita electricity demand models for Azerbaijan, which are used to produce forecast scenarios for up to 2025. The resulting estimated models (in terms of coefficients, etc. and forecasts of electricity demand for Azerbaijan in 2025 prove to be very similar; with the Business as Usual forecast ranging from about of 19½ to 21 TWh.

  11. Data-driven behavioural modelling of residential water consumption to inform water demand management strategies

    Science.gov (United States)

    Giuliani, Matteo; Cominola, Andrea; Alshaf, Ahmad; Castelletti, Andrea; Anda, Martin

    2016-04-01

    The continuous expansion of urban areas worldwide is expected to highly increase residential water demand over the next few years, ultimately challenging the distribution and supply of drinking water. Several studies have recently demonstrated that actions focused only on the water supply side of the problem (e.g., augmenting existing water supply infrastructure) will likely fail to meet future demands, thus calling for the concurrent deployment of effective water demand management strategies (WDMS) to pursue water savings and conservation. However, to be effective WDMS do require a substantial understanding of water consumers' behaviors and consumption patterns at different spatial and temporal resolutions. Retrieving information on users' behaviors, as well as their explanatory and/or causal factors, is key to spot potential areas for targeting water saving efforts and to design user-tailored WDMS, such as education campaigns and personalized recommendations. In this work, we contribute a data-driven approach to identify household water users' consumption behavioural profiles and model their water use habits. State-of-the-art clustering methods are coupled with big data machine learning techniques with the aim of extracting dominant behaviors from a set of water consumption data collected at the household scale. This allows identifying heterogeneous groups of consumers from the studied sample and characterizing them with respect to several consumption features. Our approach is validated onto a real-world household water consumption dataset associated with a variety of demographic and psychographic user data and household attributes, collected in nine towns of the Pilbara and Kimberley Regions of Western Australia. Results show the effectiveness of the proposed method in capturing the influence of candidate determinants on residential water consumption profiles and in attaining sufficiently accurate predictions of users' consumption behaviors, ultimately providing

  12. Flexibility dynamics in clusters of residential demand response and distributed generation

    NARCIS (Netherlands)

    MacDougall, P.A.; Kok, J.K.; Warmer, C.; Roossien, B.

    2013-01-01

    Supply and demand response is a untapped resource in the current electrical system. However little work has been done to investigate the dynamics of utilizing such flexibility as well as the potential effects it could have on the infrastructure. This paper provides a starting point to seeing the

  13. Demand response in experimental electricity markets

    Directory of Open Access Journals (Sweden)

    Barreda-Tarrazona, Iván

    2012-03-01

    Full Text Available We study consumers’ behavior in an experimental electricity market. Subjects make decisions concerning the quantity of electric energy they want to consume in three different pricing environments. In the baseline framework, they decide under a system of fixed prices, invariant to consumption schedule as well as to network restrictions. The other two environments correspond to dynamic pricing systems combined with incentives that aim at cutting energy consumption in a number of selected situations characterized by high network congestion. In such situations, in the first environment subjects get a bonus if they reduce their peak consumption below a certain level, while in the second one, consumers are sanctioned for consuming in peak times. From a social welfare perspective, our experimental data confirm that a dynamic system for prices is more efficient than a fixed one. Moreover, a dynamic scheme with sanctions, although less preferred by consumers, is more effective than the one with bonuses in order to reduce peak consumption. Dynamic pricing with bonuses reaches a good balance between efficiency and consumer acceptance.

    Estudiamos el comportamiento de los consumidores en un mercado de electricidad diseñado en el laboratorio. Los sujetos experimentales toman decisiones sobre la cantidad de electricidad que desean consumir en tres contextos diferentes. En el tratamiento base, los consumidores deciden bajo un sistema de precios fijos, en el que el precio es invariable tanto a la franja horaria de consumo como a las restricciones de la red. Los otros dos contextos corresponden a sistemas dinámicos de precios combinados con incentivos cuyo objetivo es la reducción del consumo en algunas situaciones seleccionadas caracterizadas por una alta congestión de la red. En estas situaciones, en el primer contexto, se bonifica la reducción del consumo en la hora punta por debajo de cierto nivel, mientras que en el segundo, los consumidores

  14. One rate does not fit all: An empirical analysis of electricity tariffs for residential microgrids

    NARCIS (Netherlands)

    G. Fridgen (Gilbert); M.T. Kahlen (Micha); W. Ketter (Wolfgang); Rieger, A. (Alexander); Thimmel, M. (Markus)

    2017-01-01

    textabstractIncreasingly, residential customers are deploying PV units to lower electricity bills and contribute to a more sustainable use of resources. This selective decentralization of power generation, however, creates significant challenges, because current transmission and distribution grids

  15. The price elasticity of electricity demand in South Australia

    International Nuclear Information System (INIS)

    Fan Shu; Hyndman, Rob J.

    2011-01-01

    In this paper, the price elasticity of electricity demand, representing the sensitivity of customer demand to the price of electricity, has been estimated for South Australia. We first undertake a review of the scholarly literature regarding electricity price elasticity for different regions and systems. Then we perform an empirical evaluation of the historic South Australian price elasticity, focussing on the relationship between price and demand quantiles at each half-hour of the day. This work attempts to determine whether there is any variation in price sensitivity with the time of day or quantile, and to estimate the form of any relationships that might exist in South Australia. - Highlights: → We review the scholarly literature on electricity own-price elasticity for different regions and systems. → We use annual log-linear econometric models of the electricity demand to estimate the historic South Australian price elasticity. → We focus on the relationship between price and demand quantiles at each half-hour of the day. → The overall price elasticity in South Australia ranges from -0.363 to -0.428.

  16. The effects of critical peak pricing for electricity demand management on home-based trip generation

    Directory of Open Access Journals (Sweden)

    Masanobu Kii

    2014-03-01

    Full Text Available This paper examines electricity critical peak pricing (CPP as a measure for controlling electricity demand at critical peak times. This pricing scheme is designed to facilitate energy conservation not only inside but also outside the home. For this study, we surveyed consumer propensity to leave the home under CPP schemes and analyzed the impact of CPP on consumer cost. The results indicated that higher prices induce a higher rate of going out, while residential conditions such as population density and access to public transportation have a relatively small impact on leaving the home and average energy conservation. However, this is not always the case for aged households with limited mobility; residential conditions have a substantial effect on this segment of the population. Combined with a reduced ability to go out, electricity pricing has a greater negative impact on aged people. These results imply that improving accessibility through transportation development and urban compaction is an effective means of saving electricity alleviating the negative impact of CPP on the aged society of the future.

  17. Risk management and participation planning of electric vehicles in smart grids for demand response

    International Nuclear Information System (INIS)

    Nezamoddini, Nasim; Wang, Yong

    2016-01-01

    Demand response (DR) can serve as an effective tool to better balance the electricity demand and supply in the smart grid. It is defined as 'the changes in electricity usage by end-use customers from their normal consumption patterns' in response to pricing and incentive payments. This paper focuses on new opportunities for DR with electric vehicles (EVs). EVs are potential distributed energy resources that support both the grid-to-vehicle and vehicle-to-grid modes. Their participation in the time-based (e.g., time-of-use) and incentive-based (e.g., regulation services) DR programs helps improve the stability and reduce the potential risks to the grid. Smart scheduling of EV charging and discharging activities also supports high penetration of renewables with volatile energy generation. This paper proposes a novel stochastic model from the Independent System Operator's perspective for risk management and participation planning of EVs in the smart grid for DR. The risk factors considered in this paper involve those caused by uncertainties in renewables (wind and solar), load patterns, parking patterns, and transmission lines' reliability. The effectiveness of the model in response to various settings such as the area type (residential, commercial, and industrial), the EV penetration level, and the risk level has been investigated. - Highlights: • We identify new opportunities for demand response (DR) using electric vehicles (EVs). • We integrate EVs in both grid-to-vehicle and vehicle-to-grid modes in smart grids. • EV participation for both time- and incentive-based DR programs are modelled. • We consider uncertainties in renewables, load, parking, and transmission lines. • Model case studies are demonstrated in residential, commercial, and industrial areas.

  18. Electricity demand and basic needs: Empirical evidence from China's households

    International Nuclear Information System (INIS)

    He, Xiaoping; Reiner, David

    2016-01-01

    An increasing block tariff (IBT) has been implemented nationwide in the residential sector in China since 2012. However, knowledge about IBT design is still limited, particularly how to determine the electricity volume for the first block of an IBT scheme. Assuming the first block should be set based on some measure of electricity poverty; we attempt to model household electricity demand such that the range of basic needs can be established. We show that in Chinese households there exists a threshold for electricity consumption with respect to income, which could be considered a measure of electricity poverty, and the threshold differs between rural and urban areas. For rural (urban) families, electricity consumption at the level of 7th (5th) income decile households can be considered the threshold for basic needs or a measure of electricity poverty since household electricity demand in rural (urban) areas does not respond to income changes until after 7th (5th) income decile. Accordingly, the first IBT block for some provinces (e.g., Beijing) appears to have been set at a level that is too high. Over time however, given continued rapid growth, the IBT will begin to better reflect actual basic needs. - Highlights: • Basic electricity needs of a household are investigated with survey data. • The Basic electricity needs differ between the rural and urban households. • The first block of the IBTs in China has proven too high and beyond the basic needs. • The initial policy targets of the IBTs in China will be difficult to achieve.

  19. Energy requirements of a multi-sensor based demand control ventilation system in residential buildings

    Energy Technology Data Exchange (ETDEWEB)

    Chul Seong, Nam; Min Hong, Sung; Won Yoon, Dong [Kyoungwon University, Seoul (Korea, Republic of); Jun Moon, Hyeun [Dankook University, Yongin (Korea, Republic of); Augenbroe, Godfried [Georgia Institute of Technology, Atlanta (United States)

    2010-07-01

    Nowadays, people spend most of their time indoors. Therefore indoor air quality is of high importance and the building regulation in Korea was revised to apply 0.7 air change rate in residential apartment housing. However residents do not often operate mechanical ventilation systems mainly due to their utility cost. The aim of this paper is to present a demand control ventilation (DCV) system which implements ventilation strategies to meet the ventilation requirements. An evaluation was conducted on both conventional ventilation and sensor based DCV systems to compare their energy requirements. The study showed that the use of the DCV system results in a better indoor air quality and a lower energy consumption than conventional ventilation. This paper highlighted that the Korean ventilation regulation is not enough to control the CO2 concentration and that the use of the sensor-based DCV would result in a healthier and more comfortable indoor environment.

  20. Technical Resource Potential of Non-disruptive Residential Demand Response in Denmark

    DEFF Research Database (Denmark)

    Mathieu, Johanna; Rasmussen, Theis Bo; Sørensen, Mads

    2014-01-01

    Denmark has one of the most aggressive renewable energy strategies in the world; however, large penetrations of fluctuating renewable energy resources will pose new problems in the Danish power system. Demand response (DR) has the potential to mitigate these problems by providing a new source...... technical resource potentials, and use real data from Denmark. We find that country-wide load flexibility is on the order of GWs and GWhs, and will increase drastically over the next 20 years due to electrification of space heating systems and vehicles. However, we also find that flexibility is time...... of flexibility. This paper estimates the technical resource potential of residential DR in Denmark. We focus on DR that is non-disruptive to the consumer, meaning that DR actions harness inherent load flexibility and are not noticeable by the consumer. We build on existing methodologies for computing DR...

  1. Model documentation report: Residential sector demand module of the National Energy Modeling System

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document that provides a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

  2. The impact of residential, commercial, and transport energy demand uncertainties in Asia on climate change mitigation

    International Nuclear Information System (INIS)

    Koljonen, Tiina; Lehtilä, Antti

    2012-01-01

    Energy consumption in residential, commercial and transport sectors have been growing rapidly in the non-OECD Asian countries over the last decades, and the trend is expected to continue over the coming decades as well. However, the per capita projections for energy demand in these particular sectors often seem to be very low compared to the OECD average until 2050, and it is clear that the scenario assessments of final energy demands in these sectors include large uncertainties. In this paper, a sensitivity analysis have been carried out to study the impact of higher rates of energy demand growths in the non-OECD Asia on global mitigation costs. The long term energy and emission scenarios for China, India and South-East Asia have been contributed as a part of Asian Modeling Exercise (AME). The scenarios presented have been modeled by using a global TIMES-VTT energy system model, which is based on the IEA-ETSAP TIMES energy system modeling framework and the global ETSAP-TIAM model. Our scenario results indicate that the impacts of accelerated energy demand in the non-OECD Asia has a relatively small impact on the global marginal costs of greenhouse gas abatement. However, with the accelerated demand projections, the average per capita greenhouse gas emissions in the OECD were decreased while China, India, and South-East Asia increased their per capita greenhouse gas emissions. This indicates that the costs of the greenhouse gas abatement would especially increase in the OECD region, if developing Asian countries increase their final energy consumption more rapidly than expected. - Highlights: ► Scenarios of final energy demands in developing Asia include large uncertainties. ► Impact of accelerated Asian energy demand on global mitigation costs is quite low. ► Accelerated Asian energy consumption increases GHG abatement costs in the OECD. ► 3.7 W/m 3 target is feasible in costs even with accelerated Asian energy demands. ► 2.6 W/m 2 target is beyond

  3. The power to choose. Demand response in liberalized electricity markets

    International Nuclear Information System (INIS)

    2003-01-01

    Highly volatile electricity prices are becoming a more frequent and unwanted characteristic of modern electricity wholesale markets. But low demand elasticity, mainly the result of a lack of incentives and consumers' inability to control demand, means that consumer behaviour is not reflected in the cost of energy. This study analyses the impact of price-responsive demand and shows how pricing, policy and technology can be used to inform consumer behaviour and choice. Informed choice and market-based valuation of electricity supply will ensure liberalized markets are competitive, efficient, less volatile and able to provide long term security of supply. Significant benefits will occur even if only 5% of customers become responsive to price-incentives and information. And customers will respond to well designed programs, thereby developing a role in ensuring efficient price formulation for electricity. This study analyses the economic, efficiency and security benefits and identifies the changes in electricity tariffs and the network infrastructure needed to achieve greater demand response

  4. Long-term electricity contract optimization with demand uncertainties

    International Nuclear Information System (INIS)

    Chan, Pang; Hui, Chi-Wai; Li, Wenkai; Sakamoto, Haruo; Hirata, Kentaro; Li, Pu

    2006-01-01

    This paper presents a study on selecting electricity contracts for a large-scale chemical production plant, which requires electricity importation, under demand uncertainty. Two common types of electricity contracts are considered, time zone (TZ) contract and loading curve (LC) contract. A multi-period linear probabilistic programming model is adopted for the contract selection and optimization. Hence, by using the probabilistic programming, a solution procedure is proposed that allow users to determine the best electricity contract according to their desired confident level of the uncertainties. In addition, due to the fact that the demand of product is uncertain, if one considers the overage and shortage of the products in the market as well, an interesting result can be obtained. The methodology is explained in the paper. (author)

  5. The dynamics of sectoral electricity demand for a panel of US states: New evidence on the consumption–growth nexus

    International Nuclear Information System (INIS)

    Saunoris, James W.; Sheridan, Brandon J.

    2013-01-01

    In this paper, we use a panel of the 48 contiguous US states over the period 1970–2009 to examine the dynamics of electricity demand in addressing the four hypotheses set forth in the literature: growth, conservation, neutrality, and feedback. In doing so we provide both short-run and long-run elasticity estimates for electricity demand. Recent developments in nonstationary panel estimation techniques allow for heterogeneity in the coefficients while examining the direction of causality among electricity consumption, electricity prices, and income growth. In addition to the full sample, we also disaggregate the sample into three sectors: commercial, industrial, and residential. The short-run results provide evidence in favor of the growth hypothesis for the aggregate sample, as well as for the industrial sector. For the residential and commercial sectors, the conservation hypothesis is supported. Long-run results favor the conservation hypothesis. To ascertain differences in electricity demand relating to electricity intensity we also examine states based on their efficiency in electricity consumption. Overall, the results yield in favor of the growth hypothesis for low intensity states and conservation hypothesis for high intensity states. - Highlights: • We use dynamic panel techniques to model electricity demand by sector for US states. • The conservation hypothesis is supported in the long run; short-run results are mixed. • The conservation hypothesis is supported in the high-electricity-intensity subsample. • The growth hypothesis is supported in the low-electricity-intensity subsample. • Policies aimed at energy conservation should be long-run in nature

  6. Energy saving or privatization? The case of the electric residential sector of Mexico; Ahorro de energia o privatizacion? El caso del sector electrico residencial de Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Friedmann, Rafael [University of California, Berkeley, CA (United States)

    1993-12-31

    The validity of the premise that proposes the privatization of the electric sector as a solution to the problem of obtaining enough investment capital for the continuous expansion of the electric sector is examined. It is shown that the growth of the demand foreseen for the residential sector for year 2000, can be totally reduced by introducing technologies economically feasible to increase the efficiency and end uses of the residential electricity. With the efficient use of the electricity, the economical development is allowed for the residential sector, without large increments of the residential electricity demand. [Espanol] Se examina la validez de la premisa que propone la privatizacion del sector electrico como una solucion al problema de conseguir suficientes capitales de inversion para la continua expansion del sector. Se muestra que se puede reducir casi totalmente el crecimiento en la demanda prevista del sector residencial al ano 2000, introduciendo tecnologias economicamente factibles para aumentar la eficiencia en los usos finales de electricidad residencial. Con el uso eficiente de la electricidad, se permite el desarrollo economico del sector residencial sin grandes incrementos en la demanda residencial de electricidad.

  7. Impacts of Demand-Side Resources on Electric Transmission Planning

    Energy Technology Data Exchange (ETDEWEB)

    Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sanstad, Alan H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-01-01

    Will demand resources such as energy efficiency (EE), demand response (DR), and distributed generation (DG) have an impact on electricity transmission requirements? Five drivers for transmission expansion are discussed: interconnection, reliability, economics, replacement, and policy. With that background, we review the results of a set of transmission studies that were conducted between 2010 and 2013 by electricity regulators, industry representatives, and other stakeholders in the three physical interconnections within the United States. These broad-based studies were funded by the US Department of Energy and included scenarios of reduced load growth due to EE, DR, and DG. While the studies were independent and used different modeling tools and interconnect-specific assumptions, all provided valuable results and insights. However, some caveats exist. Demand resources were evaluated in conjunction with other factors, and limitations on transmission additions between scenarios made understanding the role of demand resources difficult. One study, the western study, included analyses over both 10- and 20-year planning horizons; the 10-year analysis did not show near-term reductions in transmission, but the 20-year indicated fewer transmission additions, yielding a 36percent capital cost reduction. In the eastern study the reductions in demand largely led to reductions in local generation capacity and an increased opportunity for low-cost and renewable generation to export to other regions. The Texas study evaluated generation changes due to demand, and is in the process of examining demand resource impacts on transmission.

  8. Flexible demand in the GB domestic electricity sector in 2030

    International Nuclear Information System (INIS)

    Drysdale, Brian; Wu, Jianzhong; Jenkins, Nick

    2015-01-01

    Highlights: • Annual domestic demand by category and daily flexible load profiles are shown to 2030. • Valuable flexible demand requires loads to be identifiable, accessible, and useful. • The extent of flexible demand varies significantly on a diurnal and seasonal basis. • Barriers to accessing domestic demand include multiple low value loads and apathy. • Existing market structure a barrier to fully rewarding individual load flexibility. - Abstract: In order to meet greenhouse gas emissions targets the Great Britain (GB) future electricity supply will include a higher fraction of non-dispatchable generation, increasing opportunities for demand side management to maintain a supply/demand balance. This paper examines the extent of flexible domestic demand (FDD) in GB, its usefulness in system balancing and appropriate incentives to encourage consumers to participate. FDD, classified as electric space and water heating (ESWH), and cold and wet appliances, amounts to 59 TW h in 2012 (113 TW h total domestic demand) and is calculated to increase to 67 TW h in 2030. Summer and winter daily load profiles for flexible loads show significant seasonal and diurnal variations in the total flexible load and between load categories. Low levels of reflective consumer engagement with electricity consumption and a resistance to automation present barriers to effective access to FDD. A value of £1.97/household/year has been calculated for cold appliance loads used for frequency response in 2030, using 2013 market rates. The introduction of smart meters in GB by 2020 will allow access to FDD for system balancing. The low commercial value of individual domestic loads increases the attractiveness of non-financial incentives to fully exploit FDD. It was shown that appliance loads have different characteristics which can contribute to an efficient power system in different ways

  9. Aggregate electricity demand in South Africa: Conditional forecasts to 2030

    International Nuclear Information System (INIS)

    Inglesi, Roula

    2010-01-01

    In 2008, South Africa experienced a severe electricity crisis. Domestic and industrial electricity users had to suffer from black outs all over the country. It is argued that partially the reason was the lack of research on energy, locally. However, Eskom argues that the lack of capacity can only be solved by building new power plants. The objective of this study is to specify the variables that explain the electricity demand in South Africa and to forecast electricity demand by creating a model using the Engle-Granger methodology for co-integration and Error Correction models. By producing reliable results, this study will make a significant contribution that will improve the status quo of energy research in South Africa. The findings indicate that there is a long run relationship between electricity consumption and price as well as economic growth/income. The last few years in South Africa, price elasticity was rarely taken into account because of the low and decreasing prices in the past. The short-run dynamics of the system are affected by population growth, too After the energy crisis, Eskom, the national electricity supplier, is in search for substantial funding in order to build new power plants that will help with the envisaged lack of capacity that the company experienced. By using two scenarios for the future of growth, this study shows that the electricity demand will drop substantially due to the price policies agreed - until now - by Eskom and the National Energy Regulator South Africa (NERSA) that will affect the demand for some years. (author)

  10. Aggregate electricity demand in South Africa: Conditional forecasts to 2030

    Energy Technology Data Exchange (ETDEWEB)

    Inglesi, Roula [Department of Economics, Faculty of Economic and Management Sciences, University of Pretoria, Main Campus, Pretoria 0002 (South Africa)

    2010-01-15

    In 2008, South Africa experienced a severe electricity crisis. Domestic and industrial electricity users had to suffer from black outs all over the country. It is argued that partially the reason was the lack of research on energy, locally. However, Eskom argues that the lack of capacity can only be solved by building new power plants. The objective of this study is to specify the variables that explain the electricity demand in South Africa and to forecast electricity demand by creating a model using the Engle-Granger methodology for co-integration and Error Correction models. By producing reliable results, this study will make a significant contribution that will improve the status quo of energy research in South Africa. The findings indicate that there is a long run relationship between electricity consumption and price as well as economic growth/income. The last few years in South Africa, price elasticity was rarely taken into account because of the low and decreasing prices in the past. The short-run dynamics of the system are affected by population growth, too After the energy crisis, Eskom, the national electricity supplier, is in search for substantial funding in order to build new power plants that will help with the envisaged lack of capacity that the company experienced. By using two scenarios for the future of growth, this study shows that the electricity demand will drop substantially due to the price policies agreed - until now - by Eskom and the National Energy Regulator South Africa (NERSA) that will affect the demand for some years. (author)

  11. Data-Driven Baseline Estimation of Residential Buildings for Demand Response

    Directory of Open Access Journals (Sweden)

    Saehong Park

    2015-09-01

    Full Text Available The advent of advanced metering infrastructure (AMI generates a large volume of data related with energy service. This paper exploits data mining approach for customer baseline load (CBL estimation in demand response (DR management. CBL plays a significant role in measurement and verification process, which quantifies the amount of demand reduction and authenticates the performance. The proposed data-driven baseline modeling is based on the unsupervised learning technique. Specifically we leverage both the self organizing map (SOM and K-means clustering for accurate estimation. This two-level approach efficiently reduces the large data set into representative weight vectors in SOM, and then these weight vectors are clustered by K-means clustering to find the load pattern that would be similar to the potential load pattern of the DR event day. To verify the proposed method, we conduct nationwide scale experiments where three major cities’ residential consumption is monitored by smart meters. Our evaluation compares the proposed solution with the various types of day matching techniques, showing that our approach outperforms the existing methods by up to a 68.5% lower error rate.

  12. Underlying energy demand trends in South Korean and Indonesian aggregate whole economy and residential sectors

    International Nuclear Information System (INIS)

    Sa'ad, Suleiman

    2011-01-01

    This paper used annual time series data over the period 1973-2008 to estimate energy demand functions for South Korea and Indonesian aggregated whole economy and Residential sectors. Furthermore, the underlying energy demand trend (UEDT), which may be non-linear and reflects not only technical progress, which usually produces greater energy efficiency, but also other factors such as changes in consumer tastes and the economic structure that may be working in the opposite direction, is also examined in the paper. In estimating the price and income elasticities, the study applies Harvey's structural time series approach where a stochastic trend is used as a proxy for UEDT. Empirical evidence from this study reveals that the estimated long-run income and price elasticities range from 0.58 to 1.15 and from -0.09 to -066, respectively. Furthermore the stochastic form for the UEDT is preferred for both countries and sectors, suggesting a wide variation in the exogenous effects of energy saving technical progress in addition to other pertinent exogenous factors such as economic structure, consumer preferences, and socio-economic influences. (author)

  13. Analyses of demand response in Denmark[Electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Moeller Andersen, F.; Grenaa Jensen, S.; Larsen, Helge V.; Meibom, P.; Ravn, H.; Skytte, K.; Togeby, M.

    2006-10-15

    Due to characteristics of the power system, costs of producing electricity vary considerably over short time intervals. Yet, many consumers do not experience corresponding variations in the price they pay for consuming electricity. The topic of this report is: are consumers willing and able to respond to short-term variations in electricity prices, and if so, what is the social benefit of consumers doing so? Taking Denmark and the Nord Pool market as a case, the report focuses on what is known as short-term consumer flexibility or demand response in the electricity market. With focus on market efficiency, efficient allocation of resources and security of supply, the report describes demand response from a micro-economic perspective and provides empirical observations and case studies. The report aims at evaluating benefits from demand response. However, only elements contributing to an overall value are presented. In addition, the analyses are limited to benefits for society, and costs of obtaining demand response are not considered. (au)

  14. Simulation of demand management and grid balancing with electric vehicles

    Science.gov (United States)

    Druitt, James; Früh, Wolf-Gerrit

    2012-10-01

    This study investigates the potential role of electric vehicles in an electricity network with a high contribution from variable generation such as wind power. Electric vehicles are modelled to provide demand management through flexible charging requirements and energy balancing for the network. Balancing applications include both demand balancing and vehicle-to-grid discharging. This study is configured to represent the UK grid with balancing requirements derived from wind generation calculated from weather station wind speeds on the supply side and National Grid data from on the demand side. The simulation models 1000 individual vehicle entities to represent the behaviour of larger numbers of vehicles. A stochastic trip generation profile is used to generate realistic journey characteristics, whilst a market pricing model allows charging and balancing decisions to be based on realistic market price conditions. The simulation has been tested with wind generation capacities representing up to 30% of UK consumption. Results show significant improvements to load following conditions with the introduction of electric vehicles, suggesting that they could substantially facilitate the uptake of intermittent renewable generation. Electric vehicle owners would benefit from flexible charging and selling tariffs, with the majority of revenue derived from vehicle-to-grid participation in balancing markets.

  15. Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

    Directory of Open Access Journals (Sweden)

    Maytham S. Ahmed

    2016-09-01

    Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.

  16. Labor demand effects of rising electricity prices: Evidence for Germany

    International Nuclear Information System (INIS)

    Cox, Michael; Peichl, Andreas; Pestel, Nico; Siegloch, Sebastian

    2014-01-01

    Germany continues to play a pioneering role in replacing conventional power plants with renewable energy sources. While this might be beneficial with respect to environmental quality, it also implies increasing electricity prices. The extent to which this is associated with negative impacts on employment depends on the interrelationship between labor and electricity as input factors in the production process. In this paper, we estimate cross-price elasticities between electricity and heterogeneous labor for the German manufacturing sector. We use administrative linked employer–employee micro-data combined with information on sector-level electricity prices and usage over the period 2003–2007. We find positive, but small conditional cross-price elasticities of labor demand with respect to electricity prices, which means that electricity as an input factor can be replaced by labor to a limited extent when the production level is held constant. In the case of adjustable output, we find negative unconditional cross-price elasticities, implying that higher electricity prices lead to output reductions and to lower labor demand, with low- and high-skilled workers being affected more than medium-skilled. Resulting adverse distributional effects and potential overall job losses may pose challenges for policy-makers in securing public support for the German energy turnaround. - Highlights: • We estimate cross-price elasticities for electricity and labor in manufacturing. • We use linked employer–employee micro-data from Germany for 2003 to 2007. • We find a weak substitutability between electricity and labor for constant output. • We find complementarity between electricity and labor for adjustable output. • Low- and high-skilled workers are more affected than medium-skilled

  17. Testing viability of cross subsidy using time-variant price elasticities of industrial demand for electricity: Indian experience

    International Nuclear Information System (INIS)

    Chattopadhyay, Pradip

    2007-01-01

    Indian electric tariffs are characterized by very high rates for industrial and commercial classes to permit subsidized electric consumption by residential and agricultural customers. We investigate the viability of this policy using monthly data for 1997-2003 on electric consumption by a few large industrial customers under the aegis of a small distribution company in the state of Uttar Pradesh. For a given price/cost ratio, it can be shown that if the cross-subsidizing class' electricity demand is sufficiently elastic, increasing the class' rates fail to recover incremental cross-subsidy necessary to support additional revenues for subsidized classes. This suboptimality is tested by individually estimating time-variant price-elasticities of demand for these industrial customers using Box-Cox and linear regressions. We find that at least for some of these customers, cross-subsidy was suboptimal prior to as late as October 2001, when rates were changed following reforms

  18. Impact of Demand-Side Management on Thermal Comfort and Energy Costs in a Residential nZEB

    Directory of Open Access Journals (Sweden)

    Thibault Q. Péan

    2017-05-01

    Full Text Available In this study, simulation work has been carried out to investigate the impact of a demand-side management control strategy in a residential nZEB. A refurbished apartment within a multi-family dwelling representative of Mediterranean building habits was chosen as a study case and modelled within a simulation framework. A flexibility strategy based on set-point modulation depending on the energy price was applied to the building. The impact of the control strategy on thermal comfort was studied in detail with several methods retrieved from the standards or other literature, differentiating the effects on day and night living zones. It revealed a slight decrease of comfort when implementing flexibility, although this was not prejudicial. In addition, the applied strategy caused a simultaneous increase of the electricity used for heating by up to 7% and a reduction of the corresponding energy costs by up to around 20%. The proposed control thereby constitutes a promising solution for shifting heating loads towards periods of lower prices and is able to provide benefits for both the user and the grid sides. Beyond that, the activation of energy flexibility in buildings (nZEB in the present case will participate in a more successful integration of renewable energy sources (RES in the energy mix.

  19. Deregulation of Electricity Market and Drivers of Demand for Electrical Energy in Industry

    Directory of Open Access Journals (Sweden)

    Bojnec Štefan

    2016-09-01

    Full Text Available This paper investigates deregulation of electricity market focusing on electricity prices and drivers of demand for electrical energy in industry in Slovenia. The patterns in evolution of real electricity price developments and the three main components of the electricity price are calculated: liberalized market share for purchased electricity price, regulated infrastructure share for use of electricity network grids and mandatory state charges in the sale of electricity (duty, excise duty and value-added tax. To calculate the real value of electricity prices, producer price index of industrial commodities for electricity prices in industry is used as deflator and implicit deflator of gross domestic product for the size of the economy. In the empirical econometric part is used regression analysis for the amount electricity consumption in the industry depending on the real gross domestic product, direct and cross-price elasticity for natural gas prices in the industry. The results confirmed volatility in real electricity price developments with their increasing tendency and the increasing share of different taxes and state charges in the electricity prices for industry. Demand for electrical energy in industry is positively associated with gross domestic product and price of natural gas as substitute for electrical energy in industry use, and negatively associated with prices of electrical energy for industry.

  20. Climate, extreme heat, and electricity demand in California

    Energy Technology Data Exchange (ETDEWEB)

    Miller, N.L.; Hayhoe, K.; Jin, J.; Auffhammer, M.

    2008-04-01

    Climate projections from three atmosphere-ocean climate models with a range of low to mid-high temperature sensitivity forced by the Intergovernmental Panel for Climate Change SRES higher, middle, and lower emission scenarios indicate that, over the 21st century, extreme heat events for major cities in heavily air-conditioned California will increase rapidly. These increases in temperature extremes are projected to exceed the rate of increase in mean temperature, along with increased variance. Extreme heat is defined here as the 90 percent exceedance probability (T90) of the local warmest summer days under the current climate. The number of extreme heat days in Los Angeles, where T90 is currently 95 F (32 C), may increase from 12 days to as many as 96 days per year by 2100, implying current-day heat wave conditions may last for the entire summer, with earlier onset. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-2099 tend to be 20-30 percent higher than those projected under the lower B1 emission scenario, ranging from approximately double the historical number of days for inland California cities (e.g. Sacramento and Fresno), up to four times for previously temperate coastal cities (e.g. Los Angeles, San Diego). These findings, combined with observed relationships between high temperature and electricity demand for air-conditioned regions, suggest potential shortfalls in transmission and supply during T90 peak electricity demand periods. When the projected extreme heat and peak demand for electricity are mapped onto current availability, maintaining technology and population constant only for demand side calculations, we find the potential for electricity deficits as high as 17 percent. Similar increases in extreme heat days are suggested for other locations across the U.S. southwest, as well as for developing nations with rapidly increasing electricity demands. Electricity response to recent extreme heat events, such

  1. Energy Savings Potential and Opportunities for High-Efficiency Electric Motors in Residential and Commercial Equipment

    Energy Technology Data Exchange (ETDEWEB)

    Goetzler, William [Navigant Consulting, Inc., Burlington, MA (United States); Sutherland, Timothy [Navigant Consulting, Inc., Burlington, MA (United States); Reis, Callie [Navigant Consulting, Inc., Burlington, MA (United States)

    2013-12-04

    This report describes the current state of motor technology and estimates opportunities for energy savings through application of more advanced technologies in a variety of residential and commercial end uses. The objectives of this report were to characterize the state and type of motor technologies used in residential and commercial appliances and equipment and to identify opportunities to reduce the energy consumption of electric motor-driven systems in the residential and commercial sectors through the use of advanced motor technologies. After analyzing the technical savings potential offered by motor upgrades and variable speed technologies, recommended actions are presented.

  2. Australia's long-term electricity demand forecasting using deep neural networks

    OpenAIRE

    Hamedmoghadam, Homayoun; Joorabloo, Nima; Jalili, Mahdi

    2018-01-01

    Accurate prediction of long-term electricity demand has a significant role in demand side management and electricity network planning and operation. Demand over-estimation results in over-investment in network assets, driving up the electricity prices, while demand under-estimation may lead to under-investment resulting in unreliable and insecure electricity. In this manuscript, we apply deep neural networks to predict Australia's long-term electricity demand. A stacked autoencoder is used in...

  3. Two-Stage Electricity Demand Modeling Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Krzysztof Gajowniczek

    2017-10-01

    Full Text Available Forecasting of electricity demand has become one of the most important areas of research in the electric power industry, as it is a critical component of cost-efficient power system management and planning. In this context, accurate and robust load forecasting is supposed to play a key role in reducing generation costs, and deals with the reliability of the power system. However, due to demand peaks in the power system, forecasts are inaccurate and prone to high numbers of errors. In this paper, our contributions comprise a proposed data-mining scheme for demand modeling through peak detection, as well as the use of this information to feed the forecasting system. For this purpose, we have taken a different approach from that of time series forecasting, representing it as a two-stage pattern recognition problem. We have developed a peak classification model followed by a forecasting model to estimate an aggregated demand volume. We have utilized a set of machine learning algorithms to benefit from both accurate detection of the peaks and precise forecasts, as applied to the Polish power system. The key finding is that the algorithms can detect 96.3% of electricity peaks (load value equal to or above the 99th percentile of the load distribution and deliver accurate forecasts, with mean absolute percentage error (MAPE of 3.10% and resistant mean absolute percentage error (r-MAPE of 2.70% for the 24 h forecasting horizon.

  4. Bayesian Analysis of Demand Elasticity in the Italian Electricity Market

    Directory of Open Access Journals (Sweden)

    Maria Chiara D'Errico

    2015-09-01

    Full Text Available The liberalization of the Italian electricity market is a decade old. Within these last ten years, the supply side has been extensively analyzed, but not the demand side. The aim of this paper is to provide a new method for estimation of the demand elasticity, based on Bayesian methods applied to the Italian electricity market. We used individual demand bids data in the day-ahead market in the Italian Power Exchange (IPEX, for 2011, in order to construct an aggregate demand function at the hourly level. We took into account the existence of both elastic and inelastic bidders on the demand side. The empirical results show that elasticity varies significantly during the day and across periods of the year. In addition, the elasticity hourly distribution is clearly skewed and more so in the daily hours. The Bayesian method is a useful tool for policy-making, insofar as the regulator can start with a priori historical information on market behavior and estimate actual market outcomes in response to new policy actions.

  5. Forecasted electric power demands for the Delmarva Power and Light Company. Volume 1 and Volume 2. Documentation manual

    International Nuclear Information System (INIS)

    Estomin, S.L.; Beach, J.E.

    1990-10-01

    The two-volume report presents the results of an econometric forecast of peak load and electric power demands for the Delmarva Power and Light Company (DP ampersand L) through the year 2008. Separate sets of models were estimated for the three jurisdictions served by DP ampersand L: Delaware, Maryland and Virginia. For both Delaware and Maryland, econometric equations were estimated for residential, commercial, industrial, and streetlighting sales. For Virginia, equations were estimated for residential, commercial plus industrial, and streetlighting sales; separate industrial and commercial equations were not estimated for Virginia due to the relatively small size of DP ampersand L's Virginia Industrial load. Wholesale sales were econometrically estimated for the DP ampersand L system as a whole. In addition to the energy sales models, an econometric model of annual (summer) peak demand was estimated for the Company

  6. Energy and electricity demand forecasting for nuclear power planning in developing countries

    International Nuclear Information System (INIS)

    1988-07-01

    This Guidebook is designed to be a reference document to forecast energy and electricity demand. It presents concepts and methodologies that have been developed to make an analytical approach to energy/electricity demand forecasting as part of the planning process. The Guidebook is divided into 6 main chapters: (Energy demand and development, energy demand analysis, electric load curve analysis, energy and electricity demand forecasting, energy and electricity demand forecasting tools used in various organizations, IAEA methodologies for energy and electricity demand forecasting) and 3 appendices (experience with case studies carried out by the IAEA, reference technical data, reference economic data). A bibliography and a glossary complete the Guidebook. Refs, figs and tabs

  7. Techno-economic feasibility of hybrid diesel/PV/wind/battery electricity generation systems for non-residential large electricity consumers under southern Iran climate conditions

    International Nuclear Information System (INIS)

    Baneshi, Mehdi; Hadianfard, Farhad

    2016-01-01

    Highlights: • A hybrid electricity generation system for a large electricity consumer was studied. • The PV and wind electricity potentials under given climate conditions were evaluated. • Technical, economical, and environmental issues of different systems were discussed. • The optimum configuration of components was obtained. • The impacts of governmental incentives on economic viability of systems were examined. - Abstract: This paper aims to study the techno-economical parameters of a hybrid diesel/PV/wind/battery power generation system for a non-residential large electricity consumer in the south of Iran. As a case study, the feasibility of running a hybrid system to meet a non-residential community’s load demand of 9911 kWh daily average and 725 kW peak load demand was investigated. HOMER Pro software was used to model the operation of the system and to identify the appropriate configuration of it based on comparative technical, economical, and environmental analysis. Both stand alone and grid connected systems were modeled. The impacts of annual load growth and governmental energy policies such as providing low interest loan to renewable energy projects, carbon tax, and modifying the grid electricity price on viability of the system were discussed. Results show that for off-grid systems the cost of electricity (COE) and the renewable fraction of 9.3–12.6 ₵/kWh and 0–43.9%, respectively, are achieved with photovoltaic (PV) panel, wind turbine, and battery sizes of 0–1000 kW, 0–600 kW, and 1300 kWh, respectively. For on grid systems without battery storage the range of COE and renewable fraction are 5.7–8.4 ₵/kWh and 0–53%, respectively, for the same sizes of PV panel and wind turbine.

  8. Electricity demand for Sri Lanka: A time series analysis

    Energy Technology Data Exchange (ETDEWEB)

    Amarawickrama, Himanshu A. [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom); Infrastructure Advisory, Ernst and Young LLP, 1 More London Place, London SE1 2AF (United Kingdom); Hunt, Lester C. [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

    2008-05-15

    This study estimates electricity demand functions for Sri Lanka using six econometric techniques. It shows that the preferred specifications differ somewhat and there is a wide range in the long-run price and income elasticities with the estimated long-run income elasticity ranging from 1.0 to 2.0 and the long-run price elasticity from 0 to -0.06. There is also a wide range of estimates of the speed with which consumers would adjust to any disequilibrium, although the estimated impact income elasticities tended to be more in agreement ranging from 1.8 to 2.0. Furthermore, the estimated effect of the underlying energy demand trend varies between the different techniques; ranging from being positive to zero to predominantly negative. Despite these differences, the forecasts generated from the six models up until 2025 do not differ significantly. It is therefore encouraging that the Sri Lanka electricity authorities can have some faith in econometrically estimated models used for forecasting. Nonetheless, by the end of the forecast period in 2025 there is a variation of around 452 MW in the base forecast peak demand that, in relative terms for a small electricity generation system like Sri Lanka's, represents a considerable difference. (author)

  9. The residential electricity sector in Denmark: A description of current conditions

    DEFF Research Database (Denmark)

    Kitzing, Lena; Katz, Jonas; Schröder, Sascha Thorsten

    We provide an overview of the current conditions and framework for residential electricity consumption in Denmark. This includes a general overview of the sector, the retail market and the regulatory framework. We describe the regulations currently in place and changes which have been decided...... in the area, which are listed in the Glossary towards the end of the report. We also attach a list and description of the major sources of information and data that can be obtained and downloaded for analysis of the Danish residential electricity sector....

  10. Residential water demand and water consumption: an econometric analysis on municipal panel data

    International Nuclear Information System (INIS)

    Musolesi, Antonio; Nosvelli, Mario

    2005-01-01

    This paper focuses on residential water demand estimation, a rather neglected issue in the Italian environmental economics literature as compared to other European countries and the USA. This may depend on the difficulties in gathering proper data and, most of all, panel data. In some cases statistical information are not suitably collected, while in other cases legal privacy ties put some obstacles to data set transfer. Our panel data set refers to 102 municipalities in Lombardy (Italy) for the period 1998-2002. When estimating the effect of water price, we control for other relevant variables such as: income, households demographical variables - (age structure, number of component for each family) number of firms in tertiary sector, water system length. In the considered period, the data show both an increase in population (1,5 %) and in the number of water consumers (7%) associated, on aggregate, with a slight reduction in water consumption (-1,1 %). Water demand models are estimated both in a static and in a dynamic framework. In the former, the emphasis is set on the sources of endogeneity in the average price by estimating a system of simultaneous equations and relevant variables for assessing consumer behaviour - such as socio demographic ones - are incorporated in the model. In the latter, econometric methods especially designed for endogeneity in panel data models (Arellano e Bond, 1991), are employed in order to estimate the long run elasticity of water demand with respect to average price. We find evidence both that consumers significantly respond to average price only in the long run with an elasticity of about - 0,3-0,4 and that income and demographic variables are crucial in explaining consumers' behaviour. Furthermore, water consumption presents a strong auto-regressive component, showing the emergence of inertia and path dependency in consumption habits. Such results suggest important implications for water policy planning. On one side demographic

  11. Environmental determinants of unscheduled residential outages in the electrical power distribution of Phoenix, Arizona

    International Nuclear Information System (INIS)

    Maliszewski, Paul J.; Larson, Elisabeth K.; Perrings, Charles

    2012-01-01

    The sustainability of power infrastructures depends on their reliability. One test of the reliability of an infrastructure is its ability to function reliably in extreme environmental conditions. Effective planning for reliable electrical systems requires knowledge of unscheduled outage sources, including environmental and social factors. Despite many studies on the vulnerability of infrastructure systems, the effect of interacting environmental and infrastructural conditions on the reliability of urban residential power distribution remains an understudied problem. We model electric interruptions using outage data between the years of 2002 and 2005 across Phoenix, Arizona. Consistent with perceptions of increased exposure, overhead power lines positively correlate with unscheduled outages indicating underground cables are more resistant to failure. In the presence of overhead lines, the interaction between birds and vegetation as well as proximity to nearest desert areas and lakes are positive driving factors explaining much of the variation in unscheduled outages. Closeness to the nearest arterial road and the interaction between housing square footage and temperature are also significantly positive. A spatial error model was found to provide the best fit to the data. Resultant findings are useful for understanding and improving electrical infrastructure reliability. - Highlights: ► Unscheduled outages were related to interacting environmental and infrastructural conditions. ► Underground feeders are more resistant to failure. ► In the presence of overhead lines, birds, vegetation, and proximity to desert areas are positive driving factors. ► Proximity to arterial roads and a proxy for energy demand were significantly positive. ► Outages were most spatially dependent up to around 350 m.

  12. Assessment of the impact of energy-efficient household appliances on the electricity consumption in the residential sector of Brazil

    Energy Technology Data Exchange (ETDEWEB)

    Morishita, Claudia; Ghisi, Enedir

    2010-09-15

    In many countries the residential sector accounts for about 20.0% of the electricity consumption, which increases the concern about energy savings. The main objective of this paper is to assess the impact of energy-efficient household appliances on the electricity consumption of the Brazilian residential sector by using electricity end-use data. The consumption of each appliance is obtained based on official data from existing studies, being estimated for a dwelling and for the whole residential sector. Results indicate that the potential for energy savings by replacing existing appliances with energy-efficient household appliances would be 29.5% in the residential sector of Brazil.

  13. Spatial analysis of the electrical energy demand in Greece

    International Nuclear Information System (INIS)

    Tyralis, Hristos; Mamassis, Nikos; Photis, Yorgos N.

    2017-01-01

    The Electrical Energy Demand (EED) of the agricultural, commercial and industrial sector in Greece, as well as its use for domestic activities, public and municipal authorities and street lighting are analysed spatially using Geographical Information System and spatial statistical methods. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the NUTS (Nomenclature of Territorial Units for Statistics) level 3. The aim is to identify spatial patterns of the EED and its transformations such as the ratios of the EED to socioeconomic variables, i.e. the population, the total area, the population density and the Gross Domestic Product (GDP). Based on the analysis, Greece is divided in five regions, each one with a different development model, i.e. Attica and Thessaloniki which are two heavily populated major poles, Thessaly and Central Greece which form a connected geographical region with important agricultural and industrial sector, the islands and some coastal areas which are characterized by an important commercial sector and the rest Greek areas. The spatial patterns can provide additional information for policy decision about the electrical energy management and better representation of the regional socioeconomic conditions. - Highlights: • We visualize spatially the Electrical Energy Demand (EED) in Greece. • We apply spatial analysis methods to the EED data. • Spatial patterns of the EED are identified. • Greece is classified in five distinct groups, based on the analysis. • The results can be used for optimal planning of the electric system.

  14. Integration of plug-in hybrid electric vehicles (PHEV) with grid connected residential photovoltaic energy systems

    Science.gov (United States)

    Nagarajan, Adarsh; Shireen, Wajiha

    2013-06-01

    This paper proposes an approach for integrating Plug-In Hybrid Electric Vehicles (PHEV) to an existing residential photovoltaic system, to control and optimize the power consumption of residential load. Control involves determining the source from which residential load will be catered, where as optimization of power flow reduces the stress on the grid. The system built to achieve the goal is a combination of the existing residential photovoltaic system, PHEV, Power Conditioning Unit (PCU), and a controller. The PCU involves two DC-DC Boost Converters and an inverter. This paper emphasizes on developing the controller logic and its implementation in order to accommodate the flexibility and benefits of the proposed integrated system. The proposed controller logic has been simulated using MATLAB SIMULINK and further implemented using Digital Signal Processor (DSP) microcontroller, TMS320F28035, from Texas Instruments

  15. Aligning PEV Charging Times with Electricity Supply and Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, Cabell [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-06-05

    Plug-in electric vehicles (PEVs) are a growing source of electricity consumption that could either exacerbate supply shortages or smooth electricity demand curves. Extensive research has explored how vehicle-grid integration (VGI) can be optimized by controlling PEV charging timing or providing vehicle-to-grid (V2G) services, such as storing energy in vehicle batteries and returning it to the grid at peak times. While much of this research has modeled charging, implementation in the real world requires a cost-effective solution that accounts for consumer behavior. To function across different contexts, several types of charging administrators and methods of control are necessary to minimize costs in the VGI context.

  16. Hybrid systems to address seasonal mismatches between electricity production and demand in nuclear renewable electrical grids

    International Nuclear Information System (INIS)

    Forsberg, Charles

    2013-01-01

    A strategy to enable zero-carbon variable electricity production with full utilization of renewable and nuclear energy sources has been developed. Wind and solar systems send electricity to the grid. Nuclear plants operate at full capacity with variable steam to turbines to match electricity demand with production (renewables and nuclear). Excess steam at times of low electricity prices and electricity demand go to hybrid fuel production and storage systems. The characteristic of these hybrid technologies is that the economic penalties for variable nuclear steam inputs are small. Three hybrid systems were identified that could be deployed at the required scale. The first option is the gigawatt-year hourly-to-seasonal heat storage system where excess steam from the nuclear plant is used to heat rock a kilometer underground to create an artificial geothermal heat source. The heat source produces electricity on demand using geothermal technology. The second option uses steam from the nuclear plant and electricity from the grid with high-temperature electrolysis (HTR) cells to produce hydrogen and oxygen. Hydrogen is primarily for industrial applications; however, the HTE can be operated in reverse using hydrogen for peak electricity production. The third option uses variable steam and electricity for shale oil production. -- Highlights: •A system is proposed to meet variable hourly to seasonal electricity demand. •Variable solar and wind electricity sent to the grid. •Base-load nuclear plants send variable steam for electricity and hybrid systems. •Hybrid energy systems can economically absorb gigawatts of variable steam. •Hybrid systems include geothermal heat storage, hydrogen, and shale-oil production

  17. VersiCharge-SG - Smart Grid Capable Electric Vehicle Supply Equipment (EVSE) for Residential Applications

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Dong [National Renewable Energy Lab. (NREL), Golden, CO (United States); Haas, Harry [National Renewable Energy Lab. (NREL), Golden, CO (United States); Terricciano, Paul [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2015-09-30

    some real life experimentation and sporadic deployment of these technologies [14]. By many accounts, the second decade of the 21st Century is expected to be the time when mass volume production and popular usage of these AFV technologies, especially EV, will materialize. The current DOE request for proposals recognizes the need for major technological changes to ensure that the above national goal is realizable. Two major challenges have been identified: (1) major reduction in the cost of ownership of EVSEs, and (2) managing additional EV loads in the power grid while maintaining power quality, reliability, and affordability. We note that the two challenges are closely linked – A holistic approach to true lifecycle cost of EVSE ownership will certainly include any taxes and surcharges that can be put in place for major potential investments in the grid, and higher electricity charges in case of more frequent and longer peak periods. From a societal perspective, this cost could also include the lost GDP (computed on a local basis) and revenue for businesses at local and regional levels when the grid is no longer capable of meeting the demand and unexpected outages occur. A typical end-point electrical distribution system delivers power to a residential EVSE from the neighborhood distribution pole, as shown in Fig.1. This pole has a transformer (neighboring step-down transformer) that steps down the utility medium voltage to dual 120VAC single phase (also called 240VAC split phase). This voltage is fed through a meter into the residential load control center. The load control center consists of branch circuit breakers and distributes the power supply within various areas of the residential unit. One of the branch circuits from the load control center feeds EV charging station for the unit. An electric vehicle charger is plugged into the socket of the EV charging station and other end of this charger is connected to the vehicle during charging. Figure 1 illustrates a

  18. Roles of income, price and household size on residential electricity consumption: Comparison of Hawaii with similar climate zone states

    Directory of Open Access Journals (Sweden)

    Melek Yalcintas

    2017-11-01

    Linear regression analysis indicates that household size is an important variable in determining the residential electricity consumption in Oahu, however is not a determining factor in other islands. It was also observed that unlike Oahu, income and price alone are not good indicators of residential electricity consumption for the islands of Hawaii, Maui and Kauai.

  19. Financial incentive approaches for reducing peak electricity demand, experience from pilot trials with a UK energy provider

    International Nuclear Information System (INIS)

    Bradley, Peter; Coke, Alexia; Leach, Matthew

    2016-01-01

    Whilst tariff-based approaches to load-shifting are common in the residential sector, incentive-based approaches are rare. This is so, even though providing customers incentives to shape their power consumption patterns has substantial potential. This paper presents findings from an exploratory UK pilot study that trials financial payments and detailed energy feedback to incentivise load-shifting of residential electricity consumption. An intervention study was implemented measuring actual energy use by individual households as well as conducting surveys and interviews. From the trials it was found that the approaches resulted in reductions in peak time energy use. Evidence from the study found that the incentives-based approaches were able to overcome some of the barriers to response experienced in Time-of-Use studies, though less good on others. Interestingly, the height of the barriers varied by the electricity-using practice and the incentivising approach applied. The height of the barriers also varied by participant. The study concludes by identifying that broad participation in demand response is likely to require a suite of incentivising approaches that appeal to different people, a key policy finding of interest to international agencies, government, public and private sector entities. - Highlights: • Novel study of financial incentive approaches for shifting residential energy. • First academic paper comprehensively identifying barriers to time of use tariffs. • First study reporting barriers to financial incentive approaches for demand response. • Incentive study design can be applied by government and energy companies.

  20. Modeling global residential sector energy demand for heating and air conditioning in the context of climate change

    International Nuclear Information System (INIS)

    Isaac, Morna; Vuuren, Detlef P. van

    2009-01-01

    In this article, we assess the potential development of energy use for future residential heating and air conditioning in the context of climate change. In a reference scenario, global energy demand for heating is projected to increase until 2030 and then stabilize. In contrast, energy demand for air conditioning is projected to increase rapidly over the whole 2000-2100 period, mostly driven by income growth. The associated CO 2 emissions for both heating and cooling increase from 0.8 Gt C in 2000 to 2.2 Gt C in 2100, i.e. about 12% of total CO 2 emissions from energy use (the strongest increase occurs in Asia). The net effect of climate change on global energy use and emissions is relatively small as decreases in heating are compensated for by increases in cooling. However, impacts on heating and cooling individually are considerable in this scenario, with heating energy demand decreased by 34% worldwide by 2100 as a result of climate change, and air-conditioning energy demand increased by 72%. At the regional scale considerable impacts can be seen, particularly in South Asia, where energy demand for residential air conditioning could increase by around 50% due to climate change, compared with the situation without climate change

  1. Demand side management in recycling and electricity retail pricing

    Science.gov (United States)

    Kazan, Osman

    This dissertation addresses several problems from the recycling industry and electricity retail market. The first paper addresses a real-life scheduling problem faced by a national industrial recycling company. Based on their practices, a scheduling problem is defined, modeled, analyzed, and a solution is approximated efficiently. The recommended application is tested on the real-life data and randomly generated data. The scheduling improvements and the financial benefits are presented. The second problem is from electricity retail market. There are well-known patterns in daily usage in hours. These patterns change in shape and magnitude by seasons and days of the week. Generation costs are multiple times higher during the peak hours of the day. Yet most consumers purchase electricity at flat rates. This work explores analytic pricing tools to reduce peak load electricity demand for retailers. For that purpose, a nonlinear model that determines optimal hourly prices is established based on two major components: unit generation costs and consumers' utility. Both are analyzed and estimated empirically in the third paper. A pricing model is introduced to maximize the electric retailer's profit. As a result, a closed-form expression for the optimal price vector is obtained. Possible scenarios are evaluated for consumers' utility distribution. For the general case, we provide a numerical solution methodology to obtain the optimal pricing scheme. The models recommended are tested under various scenarios that consider consumer segmentation and multiple pricing policies. The recommended model reduces the peak load significantly in most cases. Several utility companies offer hourly pricing to their customers. They determine prices using historical data of unit electricity cost over time. In this dissertation we develop a nonlinear model that determines optimal hourly prices with parameter estimation. The last paper includes a regression analysis of the unit generation cost

  2. Electrification Opportunities in the Transportation Sector and Impact of Residential Charging

    Energy Technology Data Exchange (ETDEWEB)

    Muratori, Matteo [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-04-04

    This presentation provides an overview of electrification opportunities in the transportation sector and present results of a study assessing the impact of residential charging on residential power demand and electric power distribution infrastructure.

  3. Electric vehicles in low voltage residential grid: a danish case study

    DEFF Research Database (Denmark)

    Pillai, Jayakrishnan Radhakrishna; Huang, Shaojun; Thøgersen, Paul

    2012-01-01

    Electric Vehicles (EVs) have gained large interest in the energy sector as a carrier to support clean transportation and green electricity. The potential to use battery storages of electric vehicles as a sink for excess electricity that may result from large integration of wind power, especially......, is absolutely essential for the system operators to plan and implement the levels of grid reinforcement and intelligence required. This paper investigates the local grid limitations to accommodate large amount of EVs of sizable power ratings in residential areas. The case study applied in this paper uses...

  4. Dispatchable Hydrogen Production at the Forecourt for Electricity Demand Shaping

    Directory of Open Access Journals (Sweden)

    Abdulla Rahil

    2017-10-01

    Full Text Available Environmental issues and concerns about depletion of fossil fuels have driven rapid growth in the generation of renewable energy (RE and its use in electricity grids. Similarly, the need for an alternative to hydrocarbon fuels means that the number of fuel cell vehicles is also expected to increase. The ability of electricity networks to balance supply and demand is greatly affected by the variable, intermittent output of RE generators; however, this could be relieved using energy storage and demand-side response (DSR techniques. One option would be production of hydrogen by electrolysis powered from wind and solar sources. The use of tariff structures would provide an incentive to operate electrolysers as dispatchable loads. The aim of this paper is to compare the cost of hydrogen production by electrolysis at garage forecourts in Libya, for both dispatchable and continuous operation, without interruption of fuel supply to vehicles. The coastal city of Derna was chosen as a case study, with the renewable energy being produced via a wind turbine farm. Wind speed was analysed in order to determine a suitable turbine, then the capacity was calculated to estimate how many turbines would be needed to meet demand. Finally, the excess power was calculated, based on the discrepancy between supply and demand. The study looked at a hydrogen refueling station in both dispatchable and continuous operation, using an optimisation algorithm. The following three scenarios were considered to determine whether the cost of electrolytic hydrogen could be reduced by a lower off-peak electricity price. These scenarios are: Standard Continuous, in which the electrolyser operates continuously on a standard tariff of 12 p/kWh; Off-peak Only, in which the electrolyser operates only during off-peak periods at the lower price of 5 p/kWh; and 2-Tier Continuous, in which the electrolyser operates continuously on a low tariff at off-peak times and a high tariff at other

  5. Residential energy usage comparison: Findings

    Energy Technology Data Exchange (ETDEWEB)

    Smith, B.A.; Uhlaner, R.T.; Cason, T.N.; Courteau, S. (Quantum Consulting, Inc., Berkeley, CA (United States))

    1991-08-01

    This report presents the research methods and results from the Residential Energy Usage Comparison (REUC) project, a joint effort by Southern California Edison Company (SCE) and the Electric Power Research Institute (EPRI). The REUC project design activities began in early 1986. The REUC project is an innovative demand-site project designed to measure and compare typical energy consumption patterns of energy efficient residential electric and gas appliances. 95 figs., 33 tabs.

  6. What do customers want from improved residential electricity services? Evidence from a choice experiment

    International Nuclear Information System (INIS)

    Huh, Sung-Yoon; Woo, JongRoul; Lim, Sesil; Lee, Yong-Gil; Kim, Chang Seob

    2015-01-01

    Improvements in customer satisfaction as well as product/service quality represent a common objective of all businesses, and electricity services are no exception. Using choice experiments and a mixed logit model, this study quantitatively analyzes customers' preferences and their marginal willingness to pay for improved residential electricity services. The study provides an ex ante evaluation of customers' acceptance of hypothetical electricity services. According to the results, customers consider the electricity bill and the electricity mix as the two most important attributes when choosing their electricity services. Customers are willing to pay 2.2% more in the average electricity bill (an additional monthly electricity bill of KRW 1,064; USD 0.96) for a significant increase in the share of renewable energy, which is far less than the actual cost of achieving this renewable target. Therefore, it is better to maintain the current electricity mix in principle, and the renewable share should be gradually expanded instead of making a sudden change in the electricity mix. In addition, customers are willing to pay KRW 6,793 (USD 6.15) more to reduce blackouts once in a year and KRW 64/year (USD 0.06/year) to reduce a minute of each blackout. -- Highlights: •Customers' preferences for improved residential electricity services are analyzed. •Empirical setting is a sample of residents in South Korea. •The electricity bills and electricity mix are important to customers. •Increase in electricity bill of different electricity mix is considered

  7. State-level electricity demand forecasting model. [For 1980, 1985, 1990

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, H. D.

    1978-01-01

    This note briefly describes the Oak Ridge National Laboratory (ORNL) state-level electricity demand (SLED) forecasting model developed for the Nuclear Regulatory Commission. Specifically, the note presents (1) the special features of the model, (2) the methodology used to forecast electricity demand, and (3) forecasts of electricity demand and average price by sector for 15 states for 1980, 1985, 1990.

  8. Increasing Block Tariffs in an Arid Developing Country: A Discrete/Continuous Choice Model of Residential Water Demand in Jordan

    Directory of Open Access Journals (Sweden)

    Christian Klassert

    2018-02-01

    Full Text Available Arid developing countries face growing challenges from water scarcity, which are exacerbated by deficient piped water supply infrastructures. Increasing block tariffs (IBTs, charging higher rates with increasing water consumption, can potentially reconcile cost recovery to finance these infrastructures with an equitable and affordable sharing of the cost burden. A firm understanding of the impacts of varying prices and socio-economic conditions on residential water demand is necessary for designing IBTs that promote these objectives. Consistently estimating water demand under an IBT requires a discrete/continuous choice (DCC model. Despite this, few econometric studies of arid developing countries have applied this state-of-the-art approach. This paper applies a DCC model to estimate residential water demand under IBTs in the severely water-stressed country of Jordan, using 15,811 country-wide household-level observations from five years up to 2013. We extend Hewitt and Hanemann’s original DCC formulation in order to accommodate IBTs featuring a linearly progressive tariff block. We then use the resulting demand function to assess Jordan’s 2013 IBTs and alternative IBT designs. Under the estimated price elasticities, very few IBT designs achieve a full recovery of the financial costs of water provision, but we still identify a potential to improve cost recovery and affordability.

  9. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, Donna [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Belzer, David B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Markel, Tony [National Renewable Energy Lab. (NREL), Golden, CO (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kintner-Meyer, Michael [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2012-06-15

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

  10. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    2012-06-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  11. Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Najafi, Hamid Reza; Anvari-Moghaddam, Amjad

    2017-01-01

    In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits in response...... to energy price changes and get incentives in return. In this paper, we study the effect of various time-based rate (TBR) programs on the stochastic day-ahead energy and reserve scheduling in residential islanded microgrids (MGs). An effective approach is presented to schedule both energy and reserve...... in presence of renewable energy resources (RESs) and electric vehicles (EVs). An economic model of responsive load is also proposed on the basis of elasticity factor to model the behavior of customers participating in various DR programs. A two-stage stochastic programming model is developed accordingly...

  12. A demand response modeling for residential consumers in smart grid environment using game theory based energy scheduling algorithm

    Directory of Open Access Journals (Sweden)

    S. Sofana Reka

    2016-06-01

    Full Text Available In this paper, demand response modeling scheme is proposed for residential consumers using game theory algorithm as Generalized Tit for Tat (GTFT Dominant Game based Energy Scheduler. The methodology is established as a work flow domain model between the utility and the user considering the smart grid framework. It exhibits an algorithm which schedules load usage by creating several possible tariffs for consumers such that demand is never raised. This can be done both individually and among multiple users of a community. The uniqueness behind the demand response proposed is that, the tariff is calculated for all hours and the load during the peak hours which can be rescheduled is shifted based on the Peak Average Ratio. To enable the vitality of the work simulation results of a general case of three domestic consumers are modeled extended to a comparative performance and evaluation with other algorithms and inference is analyzed.

  13. MV and LV Residential Grid Impact of Combined Slow and Fast Charging of Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Niels Leemput

    2015-03-01

    Full Text Available This article investigates the combined low voltage (LV and medium voltage (MV residential grid impact for slow and fast electric vehicle (EV charging, for an increasing local penetration rate and for different residential slow charging strategies. A realistic case study for a Flemish urban distribution grid is used, for which three residential slow charging strategies are modeled: uncoordinated charging, residential off-peak charging, and EV-based peak shaving. For each slow charging strategy, the EV hosting capacity is determined, with and without the possibility of fast charging, while keeping the grid within its operating limits. The results show that the distribution grid impact is much less sensitive to the presence of fast charging compared to the slow charging strategy. EV-based peak shaving results in the lowest grid impact, allowing for the highest EV hosting capacity. Residential off-peak charging has the highest grid impact, due the load synchronization effect that occurs, resulting in the lowest EV hosting capacity. Therefore, the EV users should be incentivized to charge their EVs in a more grid-friendly manner when the local EV penetration rate becomes significant, as this increases the EV hosting capacity much more than the presence of fast charging decreases it.

  14. Methodology of demand forecast by market analysis of electric power and load curves

    International Nuclear Information System (INIS)

    Barreiro, C.J.; Atmann, J.L.

    1989-01-01

    A methodology for demand forecast of consumer classes and their aggregation is presented. An analysis of the actual attended market can be done by appropriate measures and load curves studies. The suppositions for the future market behaviour by consumer classes (industrial, residential, commercial, others) are shown, and the actions for optimise this market are foreseen, obtained by load curves modulations. The process of future demand determination is obtained by the appropriate aggregation of this segmented demands. (C.G.C.)

  15. Implementation and Control of a Residential Electrothermal Microgrid Based on Renewable Energies, a Hybrid Storage System and Demand Side Management

    Directory of Open Access Journals (Sweden)

    Julio Pascual

    2014-01-01

    Full Text Available This paper proposes an energy management strategy for a residential electrothermal microgrid, based on renewable energy sources. While grid connected, it makes use of a hybrid electrothermal storage system, formed by a battery and a hot water tank along with an electrical water heater as a controllable load, which make possible the energy management within the microgrid. The microgrid emulates the operation of a single family home with domestic hot water (DHW consumption, a heating, ventilation and air conditioning (HVAC system as well as the typical electric loads. An energy management strategy has been designed which optimizes the power exchanged with the grid profile in terms of peaks and fluctuations, in applications with high penetration levels of renewables. The proposed energy management strategy has been evaluated and validated experimentally in a full scale residential microgrid built in our Renewable Energy Laboratory, by means of continuous operation under real conditions. The results show that the combination of electric and thermal storage systems with controllable loads is a promising technology that could maximize the penetration level of renewable energies in the electric system.

  16. Uncertainty analysis of daily potable water demand on the performance evaluation of rainwater harvesting systems in residential buildings.

    Science.gov (United States)

    Silva, Arthur Santos; Ghisi, Enedir

    2016-09-15

    The objective of this paper is to perform a sensitivity analysis of design variables and an uncertainty analysis of daily potable water demand to evaluate the performance of rainwater harvesting systems in residential buildings. Eight cities in Brazil with different rainfall patterns were analysed. A numeric experiment was performed by means of computer simulation of rainwater harvesting. A sensitivity analysis was performed using variance-based indices for identifying the most important design parameters for rainwater harvesting systems when assessing the potential for potable water savings and underground tank capacity sizing. The uncertainty analysis was performed for different scenarios of potable water demand with stochastic variations in a normal distribution with different coefficients of variation throughout the simulated period. The results have shown that different design variables, such as potable water demand, number of occupants, rainwater demand, and roof area are important for obtaining the ideal underground tank capacity and estimating the potential for potable water savings. The stochastic variations on the potable water demand caused amplitudes of up to 4.8% on the potential for potable water savings and 9.4% on the ideal underground tank capacity. Average amplitudes were quite low for all cities. However, some combinations of parameters resulted in large amplitude of uncertainty and difference from uniform distribution for tank capacities and potential for potable water savings. Stochastic potable water demand generated low uncertainties in the performance evaluation of rainwater harvesting systems; therefore, uniform distribution could be used in computer simulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. The evolution of the energy demand in France in the industrial, residential and transportation sectors

    International Nuclear Information System (INIS)

    2006-01-01

    This document provides information, from 1970 to 2005, on the evolution of the energy intensity (ratio between the primary energy consumption and the gross domestic product in volume) and the actions of energy control for the industrial, residential and transportation sectors. (A.L.B.)

  18. Hierarchical predictive control scheme for distributed energy storage integrated with residential demand and photovoltaic generation

    NARCIS (Netherlands)

    Lampropoulos, I.; Garoufalis, P.; van den Bosch, P.P.J.; Kling, W.L.

    2015-01-01

    A hierarchical control scheme is defined for the energy management of a battery energy storage system which is integrated in a low-voltage distribution grid with residential customers and photovoltaic installations. The scope is the economic optimisation of the integrated system by employing

  19. Integrating a hydrogen fuel cell electric vehicle with vehicle-to-grid technology, photovoltaic power and a residential building

    NARCIS (Netherlands)

    Robledo, C.B.; Oldenbroek, V.D.W.M.; Abbruzzese, F.; van Wijk, A.J.M.

    2018-01-01

    This paper presents the results of a demonstration project, including building-integrated photovoltaic (BIPV) solar panels, a residential building and a hydrogen fuel cell electric vehicle (FCEV) for combined mobility and power generation, aiming to achieve a net zero-energy residential building

  20. Latin American electric power developments and hydrocarbon demands

    International Nuclear Information System (INIS)

    Sierra, G.S.

    1994-01-01

    Energy sectors in Latin American countries are undergoing a series of far-reaching changes in institutional arrangements and roles. These changes will have a decisive influence on energy sector evolution in coming decades. The results of two decades of mismanagement in the region's energy sector are outlined, showing stagnation in the electric power and petroleum industries caused by such factors as bureaucratic management, preferential treatment given to public enterprises, the adoption of objectives other than economic profitability, insufficient self-generation of resources due to tariffs not reflecting economic costs, and heavy debt burdens. If forecasts of future energy demand in Latin America are correct, the region's hydrocarbon sector will have to invest ca US$20 billion/y and the electric power sector nearly the same amount. This is considered beyond the capacity of the region's industries. Private sector participation is expected to raise the efficiency level of the hydrocarbon and power industries through such initiatives as privatization (complete or partial), joint government-private ventures, subcontracting, direct investment, and opening of monopolies such as power distribution to third-party competition. The state role in this process will be to create a suitable environment for private enterprise including clear and stable rules and regulatory frameworks. Financing options are discussed along with ways to reduce investment requirements. It is especially possible to reduce such requirements in the power sector through such means as retrofitting of plants with more modern equipment, reducing power losses, improved metering and billing, energy substitution, demand-side management, and energy conservation programs

  1. Non-residential water demand model validated with extensive measurements and surveys

    NARCIS (Netherlands)

    Pieterse-Quirijns, I.; Blokker, E.J.M.; van der Blom, E.C.; Vreeburg, J.H.G.

    2013-01-01

    Existing Dutch guidelines for the design of the drinking water and hot water system of nonresidential buildings are based on outdated assumptions on peak water demand or on unfounded assumptions on hot water demand. They generally overestimate peak demand values required for the design of an

  2. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Christensen, Dane T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Isley, Steven C. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-21

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

  3. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Isley, Steven C [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Christensen, Dane T [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-07-03

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

  4. Electricity Customer Clustering Following Experts’ Principle for Demand Response Applications

    Directory of Open Access Journals (Sweden)

    Jimyung Kang

    2015-10-01

    Full Text Available The clustering of electricity customers might have an effective meaning if, and only if, it is verified by domain experts. Most of the previous studies on customer clustering, however, do not consider real applications, but only the structure of clusters. Therefore, there is no guarantee that the clustering results are applicable to real domains. In other words, the results might not coincide with those of domain experts. In this paper, we focus on formulating clusters that are applicable to real applications based on domain expert knowledge. More specifically, we try to define a distance between customers that generates clusters that are applicable to demand response applications. First, the k-sliding distance, which is a new distance between two electricity customers, is proposed for customer clustering. The effect of k-sliding distance is verified by expert knowledge. Second, a genetic programming framework is proposed to automatically determine a more improved distance measure. The distance measure generated by our framework can be considered as a reflection of the clustering principles of domain experts. The results of the genetic programming demonstrate the possibility of deriving clustering principles.

  5. Residential consumers in the Cape Peninsula's willingness to pay for premium priced green electricity

    International Nuclear Information System (INIS)

    Oliver, Henry; Volschenk, Jako; Smit, Eon

    2011-01-01

    A number of studies have explored the willingness (i.e. stated willingness as opposed to actual willingness) of consumers to pay a premium for green electricity in developed countries. However, little is known about how this translates into an emerging economy context. This study investigates the level of willingness of residential households in South Africa's Cape Peninsula to pay a premium for electricity from renewable energy. It methodologically drew on recent contributions in the literature on norm-motivated behaviour used to identify testable factors that could influence residential consumers' willingness to pay (WTP). Interestingly, the study found a significant positive link between household income and WTP for green electricity, contrary to the findings of some previous studies. Not only are higher income households more likely to pay a premium, but typically they are also willing to pay a bigger premium. It was also further established that the view that green electricity is reliable, involvement in the recycling of waste and the belief that everyone should contribute to green electricity generation drive the WTP. - Research Highlights: →The study explored the drivers of willingness to pay (WTP) a premium for green electricity. →All the hypothesised drivers of WTP a premium were found to be significant. →Contrary to some former studies, income was found to be a good predictor of WTP and the pledged premium. →The quantum of the premium positively correlates with income levels.

  6. Residential Consumer-Centric Demand-Side Management Based on Energy Disaggregation-Piloting Constrained Swarm Intelligence: Towards Edge Computing.

    Science.gov (United States)

    Lin, Yu-Hsiu; Hu, Yu-Chen

    2018-04-27

    The emergence of smart Internet of Things (IoT) devices has highly favored the realization of smart homes in a down-stream sector of a smart grid. The underlying objective of Demand Response (DR) schemes is to actively engage customers to modify their energy consumption on domestic appliances in response to pricing signals. Domestic appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption intelligently. Besides, to residential customers for DR implementation, maintaining a balance between energy consumption cost and users’ comfort satisfaction is a challenge. Hence, in this paper, a constrained Particle Swarm Optimization (PSO)-based residential consumer-centric load-scheduling method is proposed. The method can be further featured with edge computing. In contrast with cloud computing, edge computing—a method of optimizing cloud computing technologies by driving computing capabilities at the IoT edge of the Internet as one of the emerging trends in engineering technology—addresses bandwidth-intensive contents and latency-sensitive applications required among sensors and central data centers through data analytics at or near the source of data. A non-intrusive load-monitoring technique proposed previously is utilized to automatic determination of physical characteristics of power-intensive home appliances from users’ life patterns. The swarm intelligence, constrained PSO, is used to minimize the energy consumption cost while considering users’ comfort satisfaction for DR implementation. The residential consumer-centric load-scheduling method proposed in this paper is evaluated under real-time pricing with inclining block rates and is demonstrated in a case study. The experimentation reported in this paper shows the proposed residential consumer-centric load-scheduling method can re-shape loads by home appliances in response to DR signals. Moreover, a phenomenal reduction in peak power consumption is achieved

  7. Optimisation of a Swedish district heating system with reduced heat demand due to energy efficiency measures in residential buildings

    International Nuclear Information System (INIS)

    Åberg, M.; Henning, D.

    2011-01-01

    The development towards more energy efficient buildings, as well as the expansion of district heating (DH) networks, is generally considered to reduce environmental impact. But the combined effect of these two progressions is more controversial. A reduced heat demand (HD) due to higher energy efficiency in buildings might hamper co-production of electricity and DH. In Sweden, co-produced electricity is normally considered to displace electricity from less efficient European condensing power plants. In this study, a potential HD reduction due to energy efficiency measures in the existing building stock in the Swedish city Linköping is calculated. The impact of HD reduction on heat and electricity production in the Linköping DH system is investigated by using the energy system optimisation model MODEST. Energy efficiency measures in buildings reduce seasonal HD variations. Model results show that HD reductions primarily decrease heat-only production. The electricity-to-heat output ratio for the system is increased for HD reductions up to 30%. Local and global CO 2 emissions are reduced. If co-produced electricity replaces electricity from coal-fired condensing power plants, a 20% HD reduction is optimal for decreasing global CO 2 emissions in the analysed DH system. - Highlights: ► A MODEST optimisation model of the Linköping district heating system is used. ► The impact of heat demand reduction on heat and electricity production is examined. ► Model results show that heat demand reductions decrease heat-only production. ► Local and global CO 2 emissions are reduced. ► The system electricity-to-heat output increases for reduced heat demand up to 30%.

  8. Application of an almost ideal demand system (AIDS) to Ethiopian rural residential energy use: Panel data evidence

    International Nuclear Information System (INIS)

    Guta, Dawit Diriba

    2012-01-01

    It is well known that poor rural households in low-income economies are reliant on traditional fuels to meet basic domestic energy needs, but little is known about the specific underlying socio-economic drivers of residential fuel choices in Ethiopia. I used the linear approximation almost ideal demand system (LAAIDS) with normalized prices to compute expenditure elasticity and a multinomial logit model (MLM) to examine household fuel use. The LAAIDS model result showed that expenditure was elastic for modern fuels, but inelastic for traditional fuels. Regression results from the MLM indicated that fuel choice behaviour of rural households could be more accurately described as ‘fuel stacking’ behaviour as opposed to the ‘energy ladder’ hypothesis. In rural areas household fuel choice may be constrained by limited access to commercial fuels and efficient cook stoves, supply dependency and affordability, consumer preferences and a web of other intricate factors. Rural households had less incentive for fuel switching due to underlying factors and the availability of fuel wood without direct financial cost. With continued deforestation and receding forests, households are expected to develop inter fuel substitution and switching behaviour conditional on access to modern energy technologies. - Highlights: ► Two step LAAIDS model and MLM were applied to analysis of residential fuel use. ► I examined issues of ‘energy ladder’ versus ‘fuel stacking’ behavior of households. ► Controlling other factors increase in welfare increases demand for modern fuel. ► Traditional fuels are income inelastic but not necessarily cheaper. ► Residential fuel choice is determined by intricate web of socio-economic factors.

  9. Electric power demand in Brazil; Demanda de energia eletrica no Brasil

    Energy Technology Data Exchange (ETDEWEB)

    Mendonca, Mario Jorge Cardoso de [Instituto de Pesquisa Economica Aplicada (IPEA), Brasilia, DF (Brazil); Amaral, Marcelo Rubens do [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1999-07-01

    The article introduces two mathematical models to estimate the electric power demand in Brazil. Both models are tested considering that the electricity demand in Brazil can be explained through the electric power tariff in function of income and price variables. The results are compared and analyzed.

  10. Impact of peak electricity demand in distribution grids: a stress test

    NARCIS (Netherlands)

    Hoogsteen, Gerwin; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria; Schuring, Friso; Kootstra, Ben

    2015-01-01

    The number of (hybrid) electric vehicles is growing, leading to a higher demand for electricity in distribution grids. To investigate the effects of the expected peak demand on distribution grids, a stress test with 15 electric vehicles in a single street is conducted and described in this paper.

  11. Development of a High-Fidelity Model for an Electrically Driven Energy Storage Flywheel Suitable for Small Scale Residential Applications

    Directory of Open Access Journals (Sweden)

    Mustafa E. Amiryar

    2018-03-01

    Full Text Available Energy storage systems (ESS are key elements that can be used to improve electrical system efficiency by contributing to balance of supply and demand. They provide a means for enhancing the power quality and stability of electrical systems. They can enhance electrical system flexibility by mitigating supply intermittency, which has recently become problematic, due to the increased penetration of renewable generation. Flywheel energy storage systems (FESS are a technology in which there is gathering interest due to a number of advantages offered over other storage solutions. These technical qualities attributed to flywheels include high power density, low environmental impact, long operational life, high round-trip efficiency and high cycle life. Furthermore, when configured in banks, they can store MJ levels of energy without any upper limit. Flywheels configured for grid connected operation are systems comprising of a mechanical part, the flywheel rotor, bearings and casings, and the electric drive part, inclusive of motor-generator (MG and power electronics. This contribution focusses on the modelling and simulation of a high inertia FESS for energy storage applications which has the potential for use in the residential sector in more challenging situations, a subject area in which there are few publications. The type of electrical machine employed is a permanent magnet synchronous motor (PMSM and this, along with the power electronics drive, is simulated in the MATLAB/Simulink environment. A brief description of the flywheel structure and applications are given as a means of providing context for the electrical modelling and simulation reported. The simulated results show that the system run-down losses are 5% per hour, with overall roundtrip efficiency of 88%. The flywheel speed and energy storage pattern comply with the torque variations, whilst the DC-bus voltage remains constant and stable within ±3% of the rated voltage, regardless of

  12. Air pollution, nuclear power and electricity demand: an economic perspective

    International Nuclear Information System (INIS)

    Chapman, D.; Mount, T.; Czerwinski, M.; Younger, M.

    1983-09-01

    We have studied the potential for physical or financial disruption of the electric utility system in New York as it may be affected by nuclear power availability, air pollution control policy, inflation, and economic growth. The method of analysis is the EPA-sponsored CCMU model which integrates utility economics, demand forecasting and customer charges, air pollution control, and power plant dispatching. The CCMU model is a partial version of the AUSM; the latter model is being developed to include coal supply and capacity planning. Of all the cases examined, only one type seems to create a severe crisis which leads to possible public reorganization of the industry. These are the cases in which the Shoreham and Nine Mile 2 plants are not operated, and 50% or more of the investment cost is not allowed in the rate base. In these circumstances, the state's utilities would apparently be unable to meet debt obligations and would also need to discontinue dividend payments. The extremity of this situation should be emphasized. These specific cases already assume that liability for debt and dividend payments has been shared equally over all of the state's utilities and customers. It assumes that the state's Power Pool has already implemented a plan by which the principal owners of the two plants are relieved of their principal financial and generating responsibilities. In all other cases studied, the statewide industry appears capable of managing the problems examined

  13. Barriers and Opportunities to Broader Adoption of Integrated Demand Side Management at Electric Utilities: A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Potter, Jennifer [Hawaii Natural Energy Institute, Honolulu, HI (United States); Stuart, Elizabeth [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Div.; Cappers, P [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Div.

    2018-02-13

    Integrated demand-side management (IDSM) is a strategic approach to designing and delivering a portfolio of demand side management (DSM) programs to customers. IDSM typically delivers customer centric strategies with the goal of increasing the amount of DSM in the field, but doing so in a way that integrates various measures and technologies to improve their collective performance and/or penetration. Specifically, IDSM can be defined as the integrated or coordinated delivery of three or more of: (1) energy efficiency (EE), (2) demand response (DR), (3) distributed generation (DG), (4) storage, (5) electric vehicle (EV) technologies, and (6) time-based rate programs to residential and commercial electric utility customers. The electric industry’s limited experience deploying IDSM to date suggests that significant barriers may exist. A Berkeley Lab report “Barriers and Opportunities to Broader Adoption of Integrated Demand Side Management at Electric Utilities: A Scoping Study” explores recent electric utility experience with IDSM to provide an assessment of the barriers and potential benefits perceived or experienced by program administrators in their attempts to implement integrated programs. The research draws on surveys and interviews with eleven staff from a sample of eight DSM program administrators and program implementers who were currently implementing or had previously attempted to implement an IDSM program or initiative. Respondents provided their perspectives on drivers for IDSM and barriers to broader deployment. They also reported on actions they had undertaken to promote expanded delivery of IDSM and provided their assessments of the most important under-tapped opportunities for expanding IDSM efforts, both for program administrator and regulatory organizations.

  14. Aggregate demand for electricity in South Africa: An analysis using the bounds testing approach to cointegration

    Energy Technology Data Exchange (ETDEWEB)

    Amusa, Hammed; Mabugu, Ramos [Financial and Fiscal Commission, Private Bag X69, Halfway Gardens, 1685 Midrand (South Africa); Amusa, Kafayat [Department of Economics, University of South Africa, P.O. Box 392, UNISA 0003 (South Africa)

    2009-10-15

    Electricity demand in South Africa has grown at a very rapid rate over the past decade. As part of reform initiatives to enhance long-term sustainability of the country's electricity industry, South Africa's authorities have in recent years sought to develop an electricity pricing framework that is cost reflective and forms the cornerstone of demand management schemes meant to foster changes in consumption behaviour and enhance efficiency in resource use. The effects of any pricing policy on aggregate electricity consumption will depend on a useful understanding of the factors that influence electricity demand, and the magnitude to which electricity demand responds to changes in such factors. In this context, this paper applies the bounds testing approach to cointegration within an autoregressive distributed lag framework to examine the aggregate demand for electricity in South Africa during the period 1960-2007. The results indicate that in the long run, income is the main determinant of electricity demand. With electricity prices having an insignificant effect on aggregate electricity demand, future pricing policies will need to ensure that electricity prices are cost reflective and enhance efficiency of electricity supply and use. (author)

  15. Module Embedded Micro-inverter Smart Grid Ready Residential Solar Electric System

    Energy Technology Data Exchange (ETDEWEB)

    Agamy, Mohammed [GE Global Research Center, Niskayuna, NY (United States)

    2015-10-27

    The “Module Embedded Micro-inverter Smart Grid Ready Residential Solar Electric System” program is focused on developing innovative concepts for residential photovoltaic (PV) systems with the following objectives: to create an Innovative micro-inverter topology that reduces the cost from the best in class micro-inverter and provides high efficiency (>96% CEC - California Energy Commission), and 25+ year warranty, as well as reactive power support; integrate micro-inverter and PV module to reduce system price by at least $0.25/W through a) accentuating dual use of the module metal frame as a large area heat spreader reducing operating temperature, and b) eliminating redundant wiring and connectors; and create micro-inverter controller handles smart grid and safety functions to simplify implementation and reduce cost.

  16. A Hybrid dasymetric and machine learning approach to high-resolution residential electricity consumption modeling

    Energy Technology Data Exchange (ETDEWEB)

    Morton, April M [ORNL; Nagle, Nicholas N [ORNL; Piburn, Jesse O [ORNL; Stewart, Robert N [ORNL; McManamay, Ryan A [ORNL

    2017-01-01

    As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for detailed information regarding residential energy consumption patterns has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy consumption, the majority of techniques are highly dependent on region-specific data sources and often require building- or dwelling-level details that are not publicly available for many regions in the United States. Furthermore, many existing methods do not account for errors in input data sources and may not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more general hybrid approach to high-resolution residential electricity consumption modeling by merging a dasymetric model with a complementary machine learning algorithm. The method s flexible data requirement and statistical framework ensure that the model both is applicable to a wide range of regions and considers errors in input data sources.

  17. Electricity pricing as a demand-side management strategy: Western lessons for developing countries

    Energy Technology Data Exchange (ETDEWEB)

    Hill, L.J.

    1990-12-01

    Electric utilities in the Western world have increasingly realized that load commitments can be met not only by constructing new generating plants but also by influencing electricity demand. This demand-side management (DSM) process requires that electric utilities promote measures on the customer's side of the meter to directly or indirectly influence electricity consumption to meet desired load objectives. An important demand-side option to achieve these load objectives is innovative electricity pricing, both by itself and as a financial incentive for other demand-site measures. This study explores electricity pricing as a DSM strategy, addressing four questions in the process: What is the Western experience with DSM in general and electricity pricing in particular Do innovative pricing strategies alter the amount and pattern of electricity consumption Do the benefits of these pricing strategies outweigh the costs of implementation What are future directions in electricity pricing Although DSM can be used to promote increases in electricity consumption for electric utilities with excess capacity as well as to slow demand growth for capacity-short utilities, emphasis here is placed on the latter. The discussion should be especially useful for electric utilities in developing countries that are exploring alternatives to capacity expansion to meet current and future electric power demand.

  18. Longrun supply and demand of new residential construction in the United States: 1986 to 2040.

    Science.gov (United States)

    Claire A. Montgomery

    1989-01-01

    A model of U.S. housing demand and supply was developed that projects housing starts for use in long-term forest planning. Housing demand was shown to respond to the current sale price and the user capital cost of housing and to the size and age composition of the population. Current sale price is determined in the new construction market. Supply of new construction...

  19. A scoping study: demand side measures on the UK electrical system

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-07-01

    The study is intended to eventually bring about a number of improvements in the UK electrical system, particularly in regard to Demand Side Management (DSM). Among the benefits envisaged are (a) increased security of supply when the network is under stress; (b) reduction in costs; (c) simpler outage management; (d) carbon saving and (e) increased energy efficiency. So far, these potential benefits have attracted little attention in the residential and small business sectors of the market: suggested reasons for this are listed. Taking into account the experience of other countries, three options are presented for a UK DSM programme: they are (i) customer initiated; (ii) supplier initiated and (iii) distributor initiated. At present, all the suggested options need further study and to aid the development for small customers, five possible initiatives are suggested. This final report (95 pages) includes a detailed description of the research required and a tender process for a customer-initiated programme. The report was prepared by KEMA Limited under contract to the DTI.

  20. A scoping study: demand side measures on the UK electrical system

    International Nuclear Information System (INIS)

    2005-01-01

    The study is intended to eventually bring about a number of improvements in the UK electrical system, particularly in regard to Demand Side Management (DSM). Among the benefits envisaged are (a) increased security of supply when the network is under stress; (b) reduction in costs; (c) simpler outage management; (d) carbon saving and (e) increased energy efficiency. So far, these potential benefits have attracted little attention in the residential and small business sectors of the market: suggested reasons for this are listed. Taking into account the experience of other countries, three options are presented for a UK DSM programme: they are (i) customer initiated; (ii) supplier initiated and (iii) distributor initiated. At present, all the suggested options need further study and to aid the development for small customers, five possible initiatives are suggested. This final report (95 pages) includes a detailed description of the research required and a tender process for a customer-initiated programme. The report was prepared by KEMA Limited under contract to the DTI

  1. The impact of VAT introduction on UK residential energy demand: an investigation using the cointegration approach

    International Nuclear Information System (INIS)

    Fouquet, Roger

    1995-01-01

    Over a two-year period, which started in April 1994, the real price of energy to UK households was expected to rise by 17.5% as a result of value-added tax (VAT) introduction. The regressive nature of the tax forced the government to limit VAT on residential fuel to 8%. Using a cointegration approach, to take account of the non-stationarity fuel consumption time series, this paper estimates real energy and fuel specific price and income elasticities for the period 1974:1-1994:1. They suggest that natural gas has a positive real energy price elasticity indicating that, as real price of energy rises, households scrap inefficient heaters and invest in more efficient ones, principally natural gas. These estimates enable projections to be made of the impact of the introduction of VAT and imply a rise in natural gas consumption as a result of the additional VAT, although at the expense of other less efficient fuels. (author)

  2. Did residential electricity rates fall after retail competition? A dynamic panel analysis

    International Nuclear Information System (INIS)

    Swadley, Adam; Yücel, Mine

    2011-01-01

    A key selling point for the restructuring of electricity markets was the promise of lower prices. There is not much consensus in earlier studies on the effects of electricity deregulation in the U.S., particularly for residential customers. Part of the reason for not finding a consistent link with deregulation and lower prices was that the removal of transitional price caps led to higher prices. In addition, the timing of the removal of price caps coincided with rising fuel prices, which were passed on to consumers in a competitive market. Using a dynamic panel model, we analyze the effect of participation rates, fuel costs, market size, a rate cap and switch to competition for 16 states and the District of Columbia. We find that an increase in participation rates, price controls, a larger market, and high shares of hydro in electricity generation lower retail prices, while increases in natural gas and coal prices increase rates. We also find that retail competition makes the market more efficient by lowering the markup of retail prices over wholesale costs. The effects of a competitive retail electricity market are mixed across states, but generally appear to lower prices in states with high participation rates. - Highlights: ► We analyze the effects of retail competition in electricity markets on residential retail prices. ► Analysis carried out using a dynamic panel model; monthly data for 17 U.S. states. ► More customer participation and larger market lead to lower prices. ► Higher fuel costs increase retail prices, but with a lag. ► Retail competition leads to a more efficient electricity market.

  3. A case study of electric utility demand reduction with commerical solar water heaters

    Energy Technology Data Exchange (ETDEWEB)

    Ewert, M.; Hoffner, J.E.; Panico, D. (City of Austin Electric Utility Dept., Austin, TX (US))

    1991-05-01

    The City of Austin, is studying the impact of solar water heaters on summer peak electric demand. One passive and two active solar water heating systems were installed on city owned commercial buildings which had electric water heaters in 1985 and have been monitored for two years. This paper reports on a method that has been developed to determine the peak demand reduction attributable to the solar systems. Results show that solar water heating systems are capable of large demand reductions as long as there is a large hot water demand to displace. The average noncoincident demand reduction (during the water heater's peak output) ranged from 0.8 to 5.8 kilowatts per system, however, the coincident demand reduction during the utility peak demand period was 0.3 to 0.8 kilowatts per system. Thus, a critical factor when assessing the benefit to the electric utility is the time of hot water demand.

  4. Climate change and peak demand for electricity: Evaluating policies for reducing peak demand under different climate change scenarios

    Science.gov (United States)

    Anthony, Abigail Walker

    This research focuses on the relative advantages and disadvantages of using price-based and quantity-based controls for electricity markets. It also presents a detailed analysis of one specific approach to quantity based controls: the SmartAC program implemented in Stockton, California. Finally, the research forecasts electricity demand under various climate scenarios, and estimates potential cost savings that could result from a direct quantity control program over the next 50 years in each scenario. The traditional approach to dealing with the problem of peak demand for electricity is to invest in a large stock of excess capital that is rarely used, thereby greatly increasing production costs. Because this approach has proved so expensive, there has been a focus on identifying alternative approaches for dealing with peak demand problems. This research focuses on two approaches: price based approaches, such as real time pricing, and quantity based approaches, whereby the utility directly controls at least some elements of electricity used by consumers. This research suggests that well-designed policies for reducing peak demand might include both price and quantity controls. In theory, sufficiently high peak prices occurring during periods of peak demand and/or low supply can cause the quantity of electricity demanded to decline until demand is in balance with system capacity, potentially reducing the total amount of generation capacity needed to meet demand and helping meet electricity demand at the lowest cost. However, consumers need to be well informed about real-time prices for the pricing strategy to work as well as theory suggests. While this might be an appropriate assumption for large industrial and commercial users who have potentially large economic incentives, there is not yet enough research on whether households will fully understand and respond to real-time prices. Thus, while real-time pricing can be an effective tool for addressing the peak load

  5. Identifying Household Residential Electricity Un-subscribers under Two Electricity Subsidy Regimes in Indonesia

    OpenAIRE

    Sulistiyo, Mohammad Herman; Banchongphanith, Latdaphone; Kaneko, Shinji

    2011-01-01

    The use of electricity without a contract with a utility company is a form of electricity theft in Indonesia. The problem of illegal connection to the grid is neither widely acknowledged nor is discussed in detail in the recent literature. To enable deep discussions regarding issues of electricity fraud in Indonesia, this study aims to firstly identify the electricity un-subscribers, and then classify the un-subscribers by different tariff blocks based on the SUSENAS survey data. By comparing...

  6. Benefits and challenges of electrical demand response: A critical review

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Pinson, Pierre; Madsen, Henrik

    2014-01-01

    Advances in IT, control and forecasting capabilities have made demand response a viable, and potentially attractive, option to increase power system flexibility. This paper presents a critical review of the literature in the field of demand response, providing an overview of the benefits...... and challenges of demand response. These benefits include the ability to balance fluctuations in renewable generation and consequently facilitate higher penetrations of renewable resources on the power system, an increase in economic efficiency through the implementation of real-time pricing, and a reduction...... in generation capacity requirements. Nevertheless, demand response is not without its challenges. The key challenges for demand response centre around establishing reliable control strategies and market frameworks so that the demand response resource can be used optimally. One of the greatest challenges...

  7. A novel machine learning approach for estimation of electricity demand: An empirical evidence from Thailand

    International Nuclear Information System (INIS)

    Mostafavi, Elham Sadat; Mostafavi, Seyyed Iman; Jaafari, Arefeh; Hosseinpour, Fariba

    2013-01-01

    Highlights: • A hybrid approach is presented for the estimation of the electricity demand. • The proposed method integrates the capabilities of GP and SA. • The GSA model makes accurate predictions of the electricity demand. - Abstract: This study proposes an innovative hybrid approach for the estimation of the long-term electricity demand. A new prediction equation was developed for the electricity demand using an integrated search method of genetic programming and simulated annealing, called GSA. The annual electricity demand was formulated in terms of population, gross domestic product (GDP), stock index, and total revenue from exporting industrial products of the same year. A comprehensive database containing total electricity demand in Thailand from 1986 to 2009 was used to develop the model. The generalization of the model was verified using a separate testing data. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the electricity demand. The GSA model provides accurate predictions of the electricity demand. Furthermore, the proposed model outperforms a regression and artificial neural network-based models

  8. Measurement, Verification and Additionality of Electricity Demand Reductions : Final report – recast

    NARCIS (Netherlands)

    Lovinfosse, I. de; Janeiro, L.; Blok, K.; Larkin, J.

    2012-01-01

    This project supports the Electricity Demand Reduction (EDR) project in the Department of Energy and Climate Change (DECC). It was commissioned to explore the needs and requirements for a robust approach to measurement, verification and additionality (M&V and additionality) of electricity demand

  9. Modelling aggregate domestic electricity demand in Ghana: An autoregressive distributed lag bounds cointegration approach

    International Nuclear Information System (INIS)

    Adom, Philip Kofi; Bekoe, William; Akoena, Sesi Kutri Komla

    2012-01-01

    In spite of the varying supply boosting efforts made by various governments to deal with the existing demand–supply gap in the electricity sector, the incessant growth in aggregate domestic electricity demand has made these efforts futile. As an objective, this paper attempts to identify the factors responsible for the historical growth trends in aggregate domestic electricity demand quantifying their effects both in the short-run and long-run periods using the ARDL Bounds cointegration approach and the sample period 1975 to 2005. In the long-run, real per capita GDP, industry efficiency, structural changes in the economy, and degree of urbanisation are identified as the main driving force behind the historical growth trend in aggregate domestic electricity demand. However, in the short-run, real per capita GDP, industry efficiency, and degree of urbanisation are the main drivers of aggregate domestic electricity demand. Industry efficiency is the only factor that drives aggregate domestic electricity demand downwards. However, the negative efficiency effect is insufficient to have outweighed the positive income, output, and demographic effects, hence the continual growth in aggregate domestic electricity demand. As a policy option, we recommend that appropriate electricity efficiency standards be implemented at the industry level. - Highlights: ► Real per capita GDP is the primary determinant of electricity demand both in the short and long-run. ► Industrial efficiency, structural changes and urbanisation rate play secondary role. ► The positive income, output, and demographic effects outweigh the negative efficiency effects.

  10. The role of price elastic demand in market power in the Nordic electricity markets

    International Nuclear Information System (INIS)

    Ravn, H.F.

    2004-01-01

    The paper discusses the modelling and analysis of market power and price elastic demand in the Nordic electricity spot market, Nordpool. The modelling of market power in the electricity sector must take into account a number of features that are specific to the electricity sector. First, electricity cannot be stored, but must be produced simultaneously with consumption. This aspect is, however, modified by the possibility of using hydro reservoirs as an indirect electricity storage. Second, the electricity transmission network plays an important role by breaking the market into several geographically separate sub-markets with different prices. Moreover, the specific bottlenecks may differ from hour to hour, according to the balance between supply and demand in each sub-market. Third, the demand side is presently characterised by very limited experience with hour to-hour-changes in electricity prices and very limited experience with short time adjustments of electricity consumption in response to changes in the electricity price. In the present paper three basic models for supply side competition on the Nordpool spot market will be presented, viz., perfect competition, Cournot competition and Supply Function Equilibrium. The models represent price and quantity settlement, including determination of price areas (bottle necks), in accordance with the way the Nordpool market functions. The models will incorporate electricity demand which is responsive to the electricity price. The paper describes the role of demand response for the determination of the electricity prices in each of the three supply side competition models. (au)

  11. Assessment of demand for natural gas from the electricity sector in India

    DEFF Research Database (Denmark)

    Shukla, P.R.; Dhar, Subash; Victor, David G.

    2009-01-01

    competes with coal as a base-load option if price difference is below US $ 4 per MBtu. At higher price difference gas penetrates only the peak power market. Gas demand is lower in the high economic growth scenario, since electricity sector is more flexible in substitution of primary energy. Gas demand......Electricity sector is among the key users of natural gas. The sustained electricity deficit and environment policies have added to an already rising demand for gas. This paper tries to understand gas demand in future from electricity sector. This paper models the future demand for gas in India from...... the electricity sector under alternative scenarios for the period 2005–2025, using bottom-up ANSWER MARKAL model. The scenarios are differentiated by alternate economic growth projections and policies related to coal reforms, infrastructure choices and local environment. The results across scenarios show that gas...

  12. Electricity demand in France: what's at stake for the energy transition?

    International Nuclear Information System (INIS)

    Berghmans, Nicolas

    2017-02-01

    This study identifies five key issues linked to electricity consumption to be taken into consideration in the management of the French power system transition: articulating the building stock renovation strategy and electricity consumption; integrating demand for electricity stemming from the development of electric vehicles; addressing winter 'peak' demand with specific demand-side policies; establishing energy demand management economic models as a flexible solution for the power system; identifying the impact of the emergence of a power system that is decentralised, balanced locally and connected with other energy carriers on the nature of demand for power from the grid. In the context of weak economic and demographic growth, the recent stabilization of electricity demand in France can be attributed to 'structural' factors, i.e. the continued expansion of the tertiary sector in the economy and the acceleration in energy efficiency gains. This evolution was poorly anticipated by stakeholders in the sector, which contributed to an imbalance between electricity demand and supply in Europe. In the absence of a major disruption, planning for transition in the electrical system should be made assuming relatively stable demand. However, major transformations will change the nature of the requirements placed on the electricity system: the times at which energy is consumed, the ability to manage the demand side of the system, and the geographical location of electricity demand within the network. Five key challenges are identified to anticipate the development of electricity consumption patterns: the role of electricity in satisfying building sector heating requirements, the integration of electric vehicle charging, the evolution of the winter demand peak, the development of demand-side management, and the emergence of an electric system based on local-level balancing. Too often considered an exogenous factor, the development in electricity

  13. Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty

    International Nuclear Information System (INIS)

    Huang, Yun-Hsun; Wu, Jung-Hua; Hsu, Yu-Ju

    2016-01-01

    Traditional electricity supply planning models regard the electricity demand as a deterministic parameter and require the total power output to satisfy the aggregate electricity demand. But in today's world, the electric system planners are facing tremendously complex environments full of uncertainties, where electricity demand is a key source of uncertainty. In addition, electricity demand patterns are considerably different for different regions. This paper developed a multi-region optimization model based on two-stage stochastic programming framework to incorporate the demand uncertainty. Furthermore, the decision tree method and Monte Carlo simulation approach are integrated into the model to simplify electricity demands in the form of nodes and determine the values and probabilities. The proposed model was successfully applied to a real case study (i.e. Taiwan's electricity sector) to show its applicability. Detail simulation results were presented and compared with those generated by a deterministic model. Finally, the long-term electricity development roadmap at a regional level could be provided on the basis of our simulation results. - Highlights: • A multi-region, two-stage stochastic programming model has been developed. • The decision tree and Monte Carlo simulation are integrated into the framework. • Taiwan's electricity sector is used to illustrate the applicability of the model. • The results under deterministic and stochastic cases are shown for comparison. • Optimal portfolios of regional generation technologies can be identified.

  14. Short-Term Multiple Forecasting of Electric Energy Loads for Sustainable Demand Planning in Smart Grids for Smart Homes

    Directory of Open Access Journals (Sweden)

    Adeshina Y. Alani

    2017-10-01

    Full Text Available Energy consumption in the form of fuel or electricity is ubiquitous globally. Among energy types, electricity is crucial to human life in terms of cooking, warming and cooling of shelters, powering of electronic devices as well as commercial and industrial operations. Users of electronic devices sometimes consume fluctuating amounts of electricity generated from smart-grid infrastructure owned by the government or private investors. However, frequent imbalance is noticed between the demand and supply of electricity, hence effective planning is required to facilitate its distribution among consumers. Such effective planning is stimulated by the need to predict future consumption within a short period. Although several interesting classical techniques have been used for such predictions, they still require improvement for the purpose of reducing significant predictive errors when used for short-term load forecasting. This research develops a near-zero cooperative probabilistic scenario analysis and decision tree (PSA-DT model to address the lacuna of enormous predictive error faced by the state-of-the-art models. The PSA-DT is based on a probabilistic technique in view of the uncertain nature of electricity consumption, complemented by a DT to reinforce the collaboration of the two techniques. Based on detailed experimental analytics on residential, commercial and industrial data loads, the PSA-DT model outperforms the state-of-the-art models in terms of accuracy to a near-zero error rate. This implies that its deployment for electricity demand planning will be of great benefit to various smart-grid operators and homes.

  15. The management of the household demand for electricity: a review of 30 years of experiments around the world

    International Nuclear Information System (INIS)

    Lesgards, V.; Frachet, L.

    2012-01-01

    Since the end of 1970's, experiments to test the impact of providing information, then of variable pricing, on the demand for electricity by households have developed considerably around the world. Initially undertaken in the USA and in the UK, where they analysed the impact of consumer information on overall demand, after the year 2000 these pilot efforts have been extended to most OECD member countries and aim too to reduce peak demand with appropriate price incentives. In recent years methodological improvements have been made in establishing the cause and effect relationship between these stimuli and the induced modification in consumption (internal validity). On top of methodological gains, the analysis of these experiments reveals some salient characteristics of the residential consumers' behaviour: the absence of any tangible and durable impact of solely using information on demand, the lasting incentive effect of variable pricing on reducing consumption at peak times, often creating a trend, as well as a strong heterogeneity of household reactions to these different stimuli. (authors)

  16. Meeting the Electrical Energy Needs of a Residential Building with a Wind-Photovoltaic Hybrid System

    Directory of Open Access Journals (Sweden)

    Mohammad Hosein Mohammadnezami

    2015-03-01

    Full Text Available A complete hybrid system including a photovoltaic cell, a wind turbine, and battery is modeled to determine the best approach for sizing the system to meet the electrical energy needs of a residential building. In evaluating system performance, the city of Tehran is used as a case study. Matlab software is used for analyzing the data and optimizing the system for the given application. Further, the cost of the system design is investigated, and shows that the electrical cost of the hybrid system in Tehran is 0.62 US$/kWh, which is 78% less expensive than a wind turbine system and 34% less expensive than a photovoltaic system.

  17. A nonlinear approach to modelling the residential electricity consumption in Ethiopia

    International Nuclear Information System (INIS)

    Gabreyohannes, Emmanuel

    2010-01-01

    In this paper an attempt is made to model, analyze and forecast the residential electricity consumption in Ethiopia using the self-exciting threshold autoregressive (SETAR) model and the smooth transition regression (STR) model. For comparison purposes, the application was also extended to standard linear models. During the empirical presentation of both models, significant nonlinear effects were found and linearity was rejected. The SETAR model was found out to be relatively better than the linear autoregressive model in out-of-sample point and interval (density) forecasts. Results from our STR model showed that the residual variance of the fitted STR model was only about 65.7% of that of the linear ARX model. Thus, we can conclude that the inclusion of the nonlinear part, which basically accounts for the arrival of extreme price events, leads to improvements in the explanatory abilities of the model for electricity consumption in Ethiopia. (author)

  18. Forecasting the demand for electric vehicles: accounting for attitudes and perceptions

    OpenAIRE

    Glerum, Aurélie; Stankovikj, Lidija; Thémans, Michaël; Bierlaire, Michel

    2012-01-01

    In the context of the arrival of electric vehicles on the car market, new mathematical models are needed to understand and predict the impact on the market shares. This research provides a comprehensive methodology to forecast the demand of a technology which is not widespread yet, such as electric cars. It aims at providing contributions regarding three issues related to the prediction of the demand for electric vehicles: survey design, model estimation and forecasting. We develop a stated p...

  19. Generation Adequacy Report on the electricity supply-demand balance in France - 2011 Edition

    International Nuclear Information System (INIS)

    2012-01-01

    Working under the aegis of public authorities, RTE periodically prepares and makes public a multi-annual forecast of the electricity supply-demand balance in France, as required by law. The purpose of this report is to evaluate the ability of the French power system, in interaction with neighbouring systems, to properly satisfy demand, based on the likeliest scenarios for trends in demand, demand response and generation

  20. Result checking concerning on-demand ventilation and residential comfort; Erfolgskontrolle Bedarfslueftung und Wohnkomfort - Schlussbericht

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, D.; Amsler, S.

    2000-07-01

    This report takes a look at the results of a study made on end-user behaviour, acceptance and room-air quality in housing fitted with on-demand ventilation. A total of 274 various apartments at five locations in Switzerland were analysed over a period of six years. The varying factors at the different locations are discussed. The results obtained are commented on. Conclusions and recommendations are made for future installations. The methods used for the survey are discussed, as are questioning methods and the questionnaires used. The results include information on household structures and occupation, airing habits, room temperature and quality, humidity, unpleasant odours, noise and traffic noise as well as health and social aspects. Knowledge gained and questions still to be answered are noted.

  1. Formulation of a projection model of electric power demand applied to isolated systems in natural development: the case of the brazilian electric company of Rondonia territory; Formulacao de um modelo de projecao de demanda de energia eletrica aplicado a sistemas isolados em desenvolvimento natural: o caso da CERON - Centrais Eletricas de Rondonia

    Energy Technology Data Exchange (ETDEWEB)

    Dourado, Rosana Aparecida

    2004-07-01

    The Electricity inserts it self more than other services in the economy and in the Brasilian society resulting an increase of market of electrical energy more than that of economy e consequently in the national energy bases. Given the importance of the definition of the demand of electrical energy inside the development process of a region, the objective of this dissertation is to propose a model of forecasting energy demand applied to a small scale utility. With basing on the foundation that the electrical energy demand varies accordingly with the region, social levels and economical conditions and also the activities developed, the method utilized was a definition of a set of representative variables in this context, using the relation between the population an the number of residential consumers; consumption per residential consumer and the consumption structure of the residential segment over the total demand. The results with the application of the model utilizing this philosophy of the technique of modeling scenes, permitted the definition of electrical energy demand for the market of the Brazilian electric company CERON S.A. like a case study. (author)

  2. Modeling hourly consumption of electricity and district heat in non-residential buildings

    International Nuclear Information System (INIS)

    Kipping, A.; Trømborg, E.

    2017-01-01

    Models for hourly consumption of heat and electricity in different consumer groups on a regional level can yield important data for energy system planning and management. In this study hourly meter data, combined with cross-sectional data derived from the Norwegian energy label database, is used to model hourly consumption of both district heat and electrical energy in office buildings and schools which either use direct electric heating (DEH) or non-electric hydronic heating (OHH). The results of the study show that modeled hourly total energy consumption in buildings with DEH and in buildings with OHH (supplied by district heat) exhibits differences, e.g. due to differences in heat distribution and control systems. In a normal year, in office buildings with OHH the main part of total modeled energy consumption is used for electric appliances, while in schools with OHH the main part is used for heating. In buildings with OHH the share of modeled annual heating energy is higher than in buildings with DEH. Although based on small samples our regression results indicate that the presented method can be used for modeling hourly energy consumption in non-residential buildings, but also that larger samples and additional cross-sectional information could yield improved models and more reliable results. - Highlights: • Schools with district heating (DH) tend to use less night-setback. • DH in office buildings tends to start earlier than direct electric heating (DEH). • In schools with DH the main part of annual energy consumption is used for heating. • In office buildings with DH the main part is used for electric appliances. • Buildings with DH use a larger share of energy for heating than buildings with DEH.

  3. Short- and long-run elasticities of electricity demand in the Korean service sector

    International Nuclear Information System (INIS)

    Lim, Kyoung-Min; Lim, Seul-Ye; Yoo, Seung-Hoon

    2014-01-01

    This paper attempts to examine the electricity demand function in the Korean service sector using the annual data covering the period 1970–2011. The short- and long-run elasticities of electricity demand with respect to price and income are empirically estimated using a co-integration and error-correction model. The short- and long-run price elasticities are estimated to be −0.421 and −1.002, respectively. The short- and long-run income elasticities are computed to be 0.855 and 1.090, respectively. Electricity demand in the service sector is inelastic to changes in both price and income in the short-run, but elastic in the long-run. Therefore, it appears that a pricing policy is more effective than the direct regulation of reducing electricity demand in the long-run in order to stabilize the electricity demand in the service sector. Moreover, it is necessary to encourage a more efficient use of electricity to cope with increasing demand for electricity following economic growth because the electricity demand in the service sector is income-elastic in the long-run. - Highlights: • We examine the electricity demand function in the Korean service sector. • We use the annual data covering the period 1970–2011. • The demand function is estimated using a co-integration and error-correction model. • The short- and long-run price elasticities are −0.421 and −1.002, respectively. • The short- and long-run income elasticities are 0.855 and 1.090, respectively

  4. Electricity demand and conservation potential in the Chinese nonmetallic mineral products industry

    International Nuclear Information System (INIS)

    Lin, Boqiang; Ouyang, Xiaoling

    2014-01-01

    As the high energy-consuming manufacturing industry, electricity consumption of nonmetallic mineral products in China accounted for 7.93% of industrial, 5.84% of national and 1.33% of global electricity consumption in 2010. This study attempts to specify the determinants of sectoral electricity demand, forecast future electricity consumption by creating a model using the Johansen cointegration methodology and estimate the sectoral electricity conservation potential. Results indicate that GDP per capita is the leading force explaining the sectoral electricity consumption increase, while value-added per worker, R and D intensity and electricity price are the main factors contributing to the sectoral electricity consumption decrease. Results demonstrate that sectoral electricity consumption in 2020 will be 369.79–464.83 billion kWh under the low-growth scenario and 530.14–666.39 billion kWh under the high-growth scenario. Moreover, under the low-growth scenario, the sectoral electricity conservation potential in 2020 will be 33.72–95.03 billion kWh, accounting for 0.45–1.26% of China's total electricity demand in 2020; under the high-growth scenario, the sectoral electricity conservation potential in 2020 will be 48.34–136.24 billion kWh, accounting for 0.26–0.74% of world's total electricity consumption in 2010 respectively. Finally, we provide some policy recommendations for encouraging energy conservation in China's nonmetallic mineral products industry. - Highlights: • A long-term relationship of electricity demand in nonmetallic minerals industry is established. • Determinants of the sectoral electricity consumption are specified. • The sectoral electricity demand and saving potential are analyzed using scenarios analysis. • Electricity saving potential will be 48.34–136.24 billion kWh under the high-growth scenario

  5. Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

    DEFF Research Database (Denmark)

    Morais, Hugo; Sousa, Tiago; Vale, Zita

    2014-01-01

    be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve...... and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32...

  6. Effects of heat and electricity saving measures in district-heated multistory residential buildings

    International Nuclear Information System (INIS)

    Truong, Nguyen Le; Dodoo, Ambrose; Gustavsson, Leif

    2014-01-01

    Highlights: • We analyzed the potential for energy savings in district heated buildings. • Measures that reduce more peak load production give higher primary energy savings. • Efficient appliances increase heat demand but give net primary energy savings. • Efficient appliances give the largest net primary energy savings. - Abstract: The effects of heat and electricity saving measures in district-heated buildings can be complex because these depend not only on how energy is used on the demand side but also on how energy is provided from the supply side. In this study, we analyze the effects of heat and electricity saving measures in multistory concrete-framed and wood-framed versions of an existing district-heated building and examine the impacts of the reduced energy demand on different district heat (DH) production configurations. The energy saving measures considered are for domestic hot water reduction, building thermal envelope improvement, ventilation heat recovery (VHR), and household electricity savings. Our analysis is based on a measured heat load profile of an existing DH production system in Växjö, Sweden. Based on the measured heat load profile, we model three minimum-cost DH production system using plausible environmental and socio-political scenarios. Then, we investigate the primary energy implications of the energy saving measures applied to the two versions of the existing building, taking into account the changed DH demand, changed cogenerated electricity, and changed electricity use due to heat and electricity saving measures. Our results show that the difference between the final and primary energy savings of the concrete-framed and wood-framed versions of the case-study building is minor. The primary energy efficiency of the energy saving measures depends on the type of measure and on the composition of the DH production system. Of the various energy saving measures explored, electricity savings give the highest primary energy savings

  7. Residential Water Demand in a Mexican Biosphere Reserve: Evidence of the Effects of Perceived Price

    Directory of Open Access Journals (Sweden)

    Marco Antonio Almendarez-Hernández

    2016-09-01

    Full Text Available The purpose of this paper is to provide empirical evidence for policy-makers of water management, evaluate the applicability of economic variables such as price and other factors that affect demand, and determine the impact thereof on decision-making surrounding water management in the El Vizcaino Biosphere Reserve in Mexico. We estimated a dynamic function with an average price specification, as well as price perception specification. Findings demonstrated that consumers tend to react to perceived average price but not to the marginal price. Furthermore, long-term price elasticity was found to be higher than short-term elasticity, and both elasticities were found to be inelastic. Inelastic elasticities, coupled with rising prices, generate substantial revenues with which to improve water planning and supply quality and to expand service coverage. The results suggest that users’ level of knowledge surrounding price is a key factor to take into account when restructuring rates, especially in situations where consumers do not readily possess the necessary information about their rate structure and usage within a given billing period. Furthermore, the results can help water management policy-makers to achieve goals of economic efficiency, social equity, and environmental sustainability.

  8. Electric power supply and demand for the contiguous United States, 1980-1989

    Energy Technology Data Exchange (ETDEWEB)

    None

    1980-06-01

    A limited review is presented of the outlook for the electric power supply and demand during the period 1980 to 1989. Only the adequacy and reliability aspects of bulk electric power supply in the contiguous US are considered. The economic, financial and environmental aspects of electric power system planning and the distribution of electricity (below the transmission level) are topics of prime importance, but they are outside the scope of this report.

  9. Projected Demand and Potential Impacts to the National Airspace System of Autonomous, Electric, On-Demand Small Aircraft

    Science.gov (United States)

    Smith, Jeremy C.; Viken, Jeffrey K.; Guerreiro, Nelson M.; Dollyhigh, Samuel M.; Fenbert, James W.; Hartman, Christopher L.; Kwa, Teck-Seng; Moore, Mark D.

    2012-01-01

    Electric propulsion and autonomy are technology frontiers that offer tremendous potential to achieve low operating costs for small-aircraft. Such technologies enable simple and safe to operate vehicles that could dramatically improve regional transportation accessibility and speed through point-to-point operations. This analysis develops an understanding of the potential traffic volume and National Airspace System (NAS) capacity for small on-demand aircraft operations. Future demand projections use the Transportation Systems Analysis Model (TSAM), a tool suite developed by NASA and the Transportation Laboratory of Virginia Polytechnic Institute. Demand projections from TSAM contain the mode of travel, number of trips and geographic distribution of trips. For this study, the mode of travel can be commercial aircraft, automobile and on-demand aircraft. NASA's Airspace Concept Evaluation System (ACES) is used to assess NAS impact. This simulation takes a schedule that includes all flights: commercial passenger and cargo; conventional General Aviation and on-demand small aircraft, and operates them in the simulated NAS. The results of this analysis projects very large trip numbers for an on-demand air transportation system competitive with automobiles in cost per passenger mile. The significance is this type of air transportation can enhance mobility for communities that currently lack access to commercial air transportation. Another significant finding is that the large numbers of operations can have an impact on the current NAS infrastructure used by commercial airlines and cargo operators, even if on-demand traffic does not use the 28 airports in the Continental U.S. designated as large hubs by the FAA. Some smaller airports will experience greater demand than their current capacity allows and will require upgrading. In addition, in future years as demand grows and vehicle performance improves other non-conventional facilities such as short runways incorporated into

  10. Analysis of the electricity supply-demand balance for the winter period 2009-2010

    International Nuclear Information System (INIS)

    2009-10-01

    Every year, RTE conducts a prospective study of the balance between supply and demand for electricity for the coming winter period, covering the whole of mainland France. This period of the year is looked at closely, primarily due to the high levels of electricity demand seen during cold snaps. The study by RTE is used to identify periods where the supply-demand balance comes under strain; it explores the measures that can be taken by electricity market players and RTE to avoid any interruption in supply during peak demand periods in France. RTE is responsible for managing the balance between supply and demand for electricity in mainland France, in real time. To do this, it anticipates potential risks that may supply may come under strain - well in advance - and informs market players. If periods are identified where the supply-demand balance comes under strain, RTE works with the electricity generators to look at possible ways of altering the schedules for shutting down generating units, and takes account of the possibilities for demand response (load reduction) reported by suppliers. As a last resort, if these preemptive measures prove insufficient and the situation becomes critical, RTE alerts the government of the risk that supply will be interrupted, and takes action in real time to limit the impact on the power system. For temperatures close to seasonal norms, the forecast outlook for the electricity supply-demand balance appears significantly less favourable than last winter until the end of January. Imports could be required between mid-November 2009 and the end of January 2010, to cover electricity demand in France and satisfy the technical security margin stipulated by RTE. To do this, suppliers would have to look to the European markets, in addition to activating demand response (load reduction) possibilities with their customer portfolios. In the event of an intense and sustained spell of cold weather, the technical limit for imports into the French

  11. Research on electricity market operation mechanism and its benefit of demand side participation

    Science.gov (United States)

    Han, Shuai; Yan, Xu; Qin, Li-juan; Lin, Xi-qiao; Zeng, Bo

    2017-08-01

    Demand response plays an important role in maintaining the economic stability of the system, and has the characteristics of high efficiency, low cost, fast response, good environmental benefits and so on. Demand side resource is an important part of electricity market. The research of demand side resources in our country is still in the initial stage, but the opening of the electricity sales side provides a broad prospect for the development of electricity market. This paper summarizes the main types of demand side resources in our country, analyzes the economic principle of demand response from the micro perspective, puts forward some suggestions on the operation mechanism of China’s demand side resources participating in the electricity market under the condition of electricity sales side opening, analyzes the current situation of pricing in the electricity wholesale market and sets up the pricing strategy of the centralized wholesale market with the demand side power supply participating in quotation, which makes the social and economic benefits reach the maximum.

  12. Simulating demand for electric vehicles using revealed preference data

    International Nuclear Information System (INIS)

    Driscoll, Áine; Lyons, Seán; Mariuzzo, Franco; Tol, Richard S.J.

    2013-01-01

    We have modelled the market for new cars in Ireland with the aim of quantifying the values placed on a range of observable car characteristics. Mid-sized petrol cars with a manual transmission sell best. Price and perhaps fuel cost are negatively associated with sales, and acceleration and perhaps range are positively associated. Hybrid cars are popular. The values of car characteristics are then used to simulate the likely market shares of three new electric vehicles. Electric vehicles tend to be more expensive even after tax breaks and subsidies are applied, but we assume their market shares would benefit from an “environmental” premium similar to those of hybrid cars. The “environmental” premium and the level of subsidies would need to be raised to incredible levels to reach the government target of 10% market penetration of all-electric vehicles. -- Highlights: •Market values placed on a range of observable car characteristics are quantified. •We simulate market shares of electrical vehicles from values of car characteristics. •We assume electric vehicles will benefit from an “environmental” premium. •Large premium not enough to reach government targets for market penetration. •Very high subsidies required to reach government targets for market penetration

  13. The Power of Electric Vehicles - Exploring the Value of Flexible Electricity Demand in a Multi-actor Context

    NARCIS (Netherlands)

    Verzijlbergh, R.A.

    2013-01-01

    Electric vehicles (EVs) have the potential to play a crucial role in clean and intelligent power systems. The key to this potential lies in the flexibility that EVs provide by the ability to shift their electricity demand in time. This flexibility can be used to facilitate the integration of

  14. Impacts of +2 °C global warming on electricity demand in Europe

    Directory of Open Access Journals (Sweden)

    Andrea Damm

    2017-08-01

    Full Text Available The electricity sector is not only a substantial source of carbon emissions, but also vulnerable to climate change, both due to the growing share of renewables and due to temperature related changes in seasonal demand patterns. In this study we provide information on the impacts of +2 °C global warming on heating and cooling electricity demand for 26 European countries, based on 11 EURO-CORDEX climate simulations, presenting mean changes but also weather-induced changes in peak demand. Smooth transition regression models are used to estimate the relationship between daily electricity consumption and population weighted temperature. Assuming present demographic and economic structures, global warming by 2 °C reduces electricity consumption in most European countries. The reduced heating electricity demand outweighs the increase in cooling demand. The highest decrease in relative terms is found for Norway (up to −5.2%, followed by Sweden, Estonia, Finland, and France. Italy is the only country for which an overall increase in electricity demand is projected. The decrease of electricity demand in absolute terms is projected to be by far the highest in France (between −10 TW h and −16 TW h p. a.. In most countries peak demand of electricity for cooling and heating increases, whereby climate scenario uncertainties in case of heating are high. Altogether, a cross-country comparison heavily suggests that climate is not the main driver for the amount of electricity used for heating and cooling purposes, but rather energy policy.

  15. Economic data for projections of unconstrained demand for electric energy for manufacturing, 1985. Working paper

    Energy Technology Data Exchange (ETDEWEB)

    Netzer, D.

    1973-08-01

    The possible impact of areawide residential location policy on future residential electricity usage in the Tri-State Metropolitan Region Centering on New York City is investigated. This report outlines procedures for projecting value added by two-digit manufacturing industry and by county, to 1985. Regression equations developed on the basis of historical data (through 1970) are applied to projections of the independent variables to 1985. The principal economic variables are the price of electric power and value added by manufacturing in constant dollars by two-digit industry, for each of the 23 counties in the region. The substantive economic activity projection is that of employment by two-digit industry by county.

  16. Voluntary Management of Residential Water Demand in Low and Middle-Low Income Households: Case Study of Soacha (colombia)

    Science.gov (United States)

    Acosta, R.; Rodriguez, J. P.

    2016-12-01

    Water resources availability is a global concern due to increasing demands, decreasing quality and uncertain spatio-temporal variability (United Nations, 2009). In urban contexts research on efficient water use is a priority to cope with the future vulnerability of water supplies as a result of the impacts of climate change (Bates et al, 2008). Following the proposed methodologies of He and Kua (2013) for implementing programs to promote sustainable energy consumption, we focused on the use of educational strategies to promote a voluntary rationalization of residential water demand. We collaborated with three schools in Soacha (Colombia) where students ranging from 12 to 15 years participated in the project as promoters of educational campaigns inside their families, covering 120 low and middle-low income households. Three intervention or treatment strategies (i.e. e-learning, in-person active learning activities and graphical learning tools) were carried out over a period of 5 months. We analyzed the effects of the treatments strategies in reducing water consumption rates and the dependence of this variable on socio-demographic, economic, environmental, and life quality factors by using personal interviews and self reported water saving technics. The results showed that educational campaigns have a positive effect on reducing consumption in the households. Graphical learning tools accounted for the highest reduction in water consumption. Moreover, the results of the study suggests that socio-economic factors such as type of house, social level, income, and life quality variables significantly affect the variability in water consumption, which is an important fact to consider in similar cases where communities face difficult socio-economic conditions, displacement or high rates of urban growth.

  17. Interim report by a Committee on Demands and Supplies of Electric Enterprise Council

    International Nuclear Information System (INIS)

    1984-01-01

    An interim report by a committee on demands and supplies, Electric Enterprise Council, was given for the period up to the year 2000. The demands of electric power in Japan were set as 658,000 million kWh for 1990 and 768,000 million kWh for 1995. The electric power enterprises appear to be at a major turning point at present, that is, the growth in the demands tended to slow down. The features of the situation are then the stabilized supply, supply cost reduction, reasonable power source constitution, etc. The following things are described. Background and policy; power demand outlook and supply measures; power supply and supply efficiency (the composition of power sources, respective power sources with supply targets and problems, etc.); power demand/supply outlook for 2000. (Mori, K.)

  18. Demand, generation and price in the Norwegian market for electric power

    International Nuclear Information System (INIS)

    Johnsen, T.A.

    2001-01-01

    We analyse the simultaneous determination of supply, demand and price in the competitive Norwegian electricity market. Deregulated in 1991, this market is pretty mature and it offers numerous data required carrying out an interesting study. Stochastic and seasonal water inflow, water storage possibilities and demand variations make this market interesting both from a theoretical and empirical view. We establish a small supply-demand model of the Norwegian electricity market. The model is estimated using weekly data from 1994 to 1995. Data for 1996 are used for post-sample examination of the model. Unexpected inflow, snow and temperature conditions explain a large part of the variation in the electricity generation, demand and price. Within and post-sample simulation of the estimated model reproduce demand and price patterns considerably well

  19. A Review of Demand Forecast for Charging Facilities of Electric Vehicles

    Science.gov (United States)

    Jiming, Han; Lingyu, Kong; Yaqi, Shen; Ying, Li; Wenting, Xiong; Hao, Wang

    2017-05-01

    The demand forecasting of charging facilities is the basis of its planning and locating, which has important role in promoting the development of electric vehicles and alleviating the energy crisis. Firstly, this paper analyzes the influence of the charging mode, the electric vehicle population and the user’s charging habits on the demand of charging facilities; Secondly, considering these factors, the recent analysis on charging and switching equipment demand forecast is divided into two methods—forecast based on electric vehicle population and user traveling behavior. Then, the article analyzes the two methods and puts forward the advantages and disadvantages. Finally, in view of the defects of current research, combined with the current situation of the development of the city and comprehensive consideration of economic, political, environmental and other factors, this paper proposes an improved demand forecasting method which has great practicability and pertinence and lays the foundation for the plan of city electric facilities.

  20. The electric energy demand-side planning: necessity and possibilities of execution

    International Nuclear Information System (INIS)

    Sposito, E.S.

    1991-05-01

    Aiming at reducing the level of investments, is presented a demand-side planning approach, divided into two parts. The first part is an analysis on the actual need of our demand-side approaching. In view of this, is showed a set of data and comments both on economic and technological aspects concerning the electric network and sector, as well as evaluation of the social, ecological and financial aspects which could act against the full expansion of the electric system. In the second part, a demand-side planning methodology is introduced, as well as its main concepts, its variables and its instruments of affecting the demand: energy conservation, replacement of sources, reduction of losses and electric power decentralized generation. Each of them is fully detailed in a set of planning policies and actions. Concluding is presented the basic elements of a National Electric Energy Substitution and Conservation Plan - PLANSCON. (author)

  1. Operational demands as determining factor for electric bus charging infrastructure

    NARCIS (Netherlands)

    Beekman, R.; Van Den Hoed, R.

    2016-01-01

    Many cities in Europe have ambitious goals when it comes to making their public transport buses emission free. This article outlines the reasoning behind the choices made in the city of Amsterdam with regards to charging infrastructure for electric buses. Emphasising the importance of operational

  2. Demand Response in Europe's Electricity Sector: Market barriers and outstanding issues

    International Nuclear Information System (INIS)

    Eid, Cherrelle

    2015-01-01

    In October 2014, Europe's drive for sustainability has been further continued with the set objectives for 2030, aiming for 40% emission reduction compared to 1990 levels and at least a 27% share of renewable energy sources. For the longer term, the European Commission (EC) targets a zero CO 2 emitting electricity sector in 2050. Those objectives for the electricity sector have a large impact on the expected development of electricity generation, but also on the evolution of demand. To meet those objectives, a larger share of electricity supply will come from intermittent sources like wind turbines and solar panels. In an electric system that is largely based on renewable electricity sources, it is desired to have higher electricity consumption in moments when more renewable electricity is being produced, and a lower consumption in times of lower renewable production. Demand response is related to the adaptability of the electricity demand to the availability of supply. The development of demand response is rooted in the need for carbon emission reductions and for efficient use of installed generation capacities with the growth of power consumption. In addition to providing flexibility to the electric system, demand response could be a direct source of revenue to households and businesses. In 2013, in the United States, businesses and homeowners earned over $2.2 billion in revenues from demand response together with other avoided investment in grid infrastructure and power plants. This source of direct revenue could also be made available in Europe and would release financial benefits to local economies (SEDC, 2014). The reliability improvements as well as the economic and sustainability potential coming from a more responsive electricity demand are fully acknowledged. However, demand response is still immaturely developed in Europe. If Europe wants to make a step forward to a more sustainable electricity sector, the development of demand response is an

  3. Energy-environment policy goals and instruments and electricity demand response. A framework for the analysis

    International Nuclear Information System (INIS)

    Rio, Pablo del; Hernandez, F.

    2004-01-01

    The environment and energy realms have traditionally been two major focus of attention of EU and Member State (MS) policy. This attention has intensified in recent years as a response to, both, internal and external events and strategies (i.e., the Kyoto Protocol). In this context, the EU and its MS have set ambitious goals in the environmental and energy contexts and are already implementing packages of policies and measures. Both policies interact. Although there might be conflicts between both, there are also mutually reinforcing effects with significant policy implications. Actually, as stated in the Amsterdam Treaty, environmental protection is one of the major goals of energy policy (together with 'security of supply' and 'competitive energy systems'). On the other hand, the energy sector is instrumental in the success of environmental policy. In this context, a wide array of measures are currently being implemented in the EU and its MS which have a more or less direct impact on the electricity market. Particularly, Demand Side Management (DSM) activities, promotion of electricity from renewable energy sources (RES-E) and measures aimed at the mitigation of Greenhouse Gas (GHG) emissions are arguably three major instruments which have the potential to contribute to energy and environmental goals. The effectiveness and impact of there measures depends to a large extent on the demand response in the electricity market. Some of there measures affect the electricity demand curve, while others do not have a direct impact on the demand curve but affect the quantity of electricity demand by displacing the electricity supply curve. In turn, the effectiveness of energy and environmental policies may be different when electricity demand response varies (i.e., different elasticity demand). This paper entails an initial effort to provide a theoretical framework for the analysis of the interactions between electricity demand response and the above mentioned energy

  4. Hawaii demand-side management resource assessment. Final report, Reference Volume 3 -- Residential and commercial sector DSM analyses: Detailed results from the DBEDT DSM assessment model; Part 1, Technical potential

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-04-01

    The Hawaii Demand-Side Management Resource Assessment was the fourth of seven projects in the Hawaii Energy Strategy (HES) program. HES was designed by the Department of Business, Economic Development, and Tourism (DBEDT) to produce an integrated energy strategy for the State of Hawaii. The purpose of Project 4 was to develop a comprehensive assessment of Hawaii`s demand-side management (DSM) resources. To meet this objective, the project was divided into two phases. The first phase included development of a DSM technology database and the identification of Hawaii commercial building characteristics through on-site audits. These Phase 1 products were then used in Phase 2 to identify expected energy impacts from DSM measures in typical residential and commercial buildings in Hawaii. The building energy simulation model DOE-2.1E was utilized to identify the DSM energy impacts. More detailed information on the typical buildings and the DOE-2.1E modeling effort is available in Reference Volume 1, ``Building Prototype Analysis``. In addition to the DOE-2.1E analysis, estimates of residential and commercial sector gas and electric DSM potential for the four counties of Honolulu, Hawaii, Maui, and Kauai through 2014 were forecasted by the new DBEDT DSM Assessment Model. Results from DBEDTs energy forecasting model, ENERGY 2020, were linked with results from DOE-2.1E building energy simulation runs and estimates of DSM measure impacts, costs, lifetime, and anticipated market penetration rates in the DBEDT DSM Model. Through its algorithms, estimates of DSM potential for each forecast year were developed. Using the load shape information from the DOE-2.1E simulation runs, estimates of electric peak demand impacts were developed. Numerous tables and figures illustrating the technical potential for demand-side management are included.

  5. The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application

    International Nuclear Information System (INIS)

    Inglesi-Lotz, R.

    2011-01-01

    In South Africa, the electricity mismatch of supply and demand has been of major concern. Additional to past problems, the 2008 electricity crisis made the solution crucial after its damaging consequences to the economy. The disagreement on the need and consequences of the continuous electricity price hikes worsens the situation. To contribute to the recent electricity debate, this paper proposes a time-varying price elasticity of demand for electricity; the sensitivity of electricity consumption to price fluctuations changes throughout the years. The main purpose of this study is the estimation of the price elasticity of electricity in South Africa during the period 1980-2005 by employing an advanced econometric technique, the Kalman filter. Apart from the decreasing effect of electricity prices to consumption (-71.8% in the 1990s and -94.5% in the 2000s in average), our results conclude to an important finding: the higher the prices (for example in the 1980s) the higher the sensitivity of consumers to price fluctuations. Thus, further increases of the electricity prices may lead to changes in the behaviour of electricity consumers, focusing their efforts on improving their efficiency levels by introducing demand-side management techniques or even turning to other sources of - cheaper - energy. - Highlights: → The price elasticity of South Africa's electricity demand (1980-2005) is examined. → The Kalman filter methodology is used to show elasticity changes over time. → Decreasing effect of electricity prices to consumption over the years is found. → The higher the prices of electricity were, the higher the sensitivity of consumption. → If electricity prices increase, consumers will choose to consume more efficiently.

  6. The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application

    Energy Technology Data Exchange (ETDEWEB)

    Inglesi-Lotz, R., E-mail: roula.inglesi@up.ac.za [Department of Economics, EMS Building, University of Pretoria, Gauteng 0002 (South Africa)

    2011-06-15

    In South Africa, the electricity mismatch of supply and demand has been of major concern. Additional to past problems, the 2008 electricity crisis made the solution crucial after its damaging consequences to the economy. The disagreement on the need and consequences of the continuous electricity price hikes worsens the situation. To contribute to the recent electricity debate, this paper proposes a time-varying price elasticity of demand for electricity; the sensitivity of electricity consumption to price fluctuations changes throughout the years. The main purpose of this study is the estimation of the price elasticity of electricity in South Africa during the period 1980-2005 by employing an advanced econometric technique, the Kalman filter. Apart from the decreasing effect of electricity prices to consumption (-71.8% in the 1990s and -94.5% in the 2000s in average), our results conclude to an important finding: the higher the prices (for example in the 1980s) the higher the sensitivity of consumers to price fluctuations. Thus, further increases of the electricity prices may lead to changes in the behaviour of electricity consumers, focusing their efforts on improving their efficiency levels by introducing demand-side management techniques or even turning to other sources of - cheaper - energy. - Highlights: > The price elasticity of South Africa's electricity demand (1980-2005) is examined. > The Kalman filter methodology is used to show elasticity changes over time. > Decreasing effect of electricity prices to consumption over the years is found. > The higher the prices of electricity were, the higher the sensitivity of consumption. > If electricity prices increase, consumers will choose to consume more efficiently.

  7. Evaluation of the Demand Response Performance of Electric Water Heaters

    Energy Technology Data Exchange (ETDEWEB)

    Mayhorn, Ebony T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Widder, Sarah H. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Parker, Steven A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pratt, Richard M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chassin, Forrest S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-03-17

    The purpose of this project is to verify or refute many of the concerns raised by utilities regarding the ability of large tank HPWHs to perform DR by measuring the performance of HPWHs compared to ERWHs in providing DR services. perform DR by measuring the performance of HPWHs compared to ERWHs in providing DR services. This project was divided into three phases. Phase 1 consisted of week-long laboratory experiments designed to demonstrate technical feasibility of individual large-tank HPWHs in providing DR services compared to large-tank ERWHs. In Phase 2, the individual behaviors of the water heaters were then extrapolated to a population by first calibrating readily available water heater models developed in GridLAB-D simulation software to experimental results obtained in Phase 1. These models were used to simulate a population of water heaters and generate annual load profiles to assess the impacts on system-level power and residential load curves. Such population modeling allows for the inherent and permanent load reduction accomplished by the more efficient HPWHs to be considered, in addition to the temporal DR services the water heater can provide by switching ON or OFF as needed by utilities. The economic and emissions impacts of using large-tank water heaters in DR programs are then analyzed from the utility and consumer perspective, based on National Impacts Analysis in Phase 3. Phase 1 is discussed in this report. Details on Phases 2 and 3 can be found in the companion report (Cooke et al. 2014).

  8. Electricity supply and demand scenarios for the Southern African power pool

    CSIR Research Space (South Africa)

    Spalding-Fecher, R

    2017-02-01

    Full Text Available The study presents long-term electricity supply and demand scenarios for the twelve countries in the Southern African Power Pool, based on detailed bottom-up demand analysis for all countries and a set of internally consistent development scenarios...

  9. Electricity demand profile with high penetration of heat pumps in Nordic area

    DEFF Research Database (Denmark)

    Liu, Zhaoxi; Wu, Qiuwei; Nielsen, Arne Hejde

    2013-01-01

    This paper presents the heat pump (HP) demand profile with high HP penetration in the Nordic area in order to achieve the carbon neutrality power system. The calculation method in the European Standard EN14825 was used to estimate the HP electricity demand profile. The study results show...

  10. Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

    International Nuclear Information System (INIS)

    Kucukali, Serhat; Baris, Kemal

    2010-01-01

    This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning.

  11. Short-Term Electrical Peak Demand Forecasting in a Large Government Building Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Jason Grant

    2014-03-01

    Full Text Available The power output capacity of a local electrical utility is dictated by its customers’ cumulative peak-demand electrical consumption. Most electrical utilities in the United States maintain peak-power generation capacity by charging for end-use peak electrical demand; thirty to seventy percent of an electric utility’s bill. To reduce peak demand, a real-time energy monitoring system was designed, developed, and implemented for a large government building. Data logging, combined with an application of artificial neural networks (ANNs, provides short-term electrical load forecasting data for controlled peak demand. The ANN model was tested against other forecasting methods including simple moving average (SMA, linear regression, and multivariate adaptive regression splines (MARSplines and was effective at forecasting peak building electrical demand in a large government building sixty minutes into the future. The ANN model presented here outperformed the other forecasting methods tested with a mean absolute percentage error (MAPE of 3.9% as compared to the SMA, linear regression, and MARSplines MAPEs of 7.7%, 17.3%, and 7.0% respectively. Additionally, the ANN model realized an absolute maximum error (AME of 8.2% as compared to the SMA, linear regression, and MARSplines AMEs of 26.2%, 45.1%, and 22.5% respectively.

  12. Demand-side management pricing options in electric utilities

    International Nuclear Information System (INIS)

    Sardana, P.; Herman, P.

    1990-01-01

    In 1989 Ontario Hydro implemented optional time-of-use (TOU) rates at the wholesale level for all municipal utilities in the province. At the same time, mandatory TOU rates were implemented for large users (customers with loads in excess of 5 MW) served by municipal utilities and Ontario Hydro's direct customers. To fully explore the potential of rate structures as demand-side management (DSM) tools, Ontario Hydro retained a consulting firm to carry out a survey of innovative rate structures in other jurisdications. The survey was intended to identify: the status quo of rate structures in other jurisdictions that were designed specifically to encourage DSM; a profile of the cost basis of the rate structures, for example whether traditional embedded cost of service analyses or contentious methods such as marginal cost pricing were used; whether innovative rates have been successful, and customer reactions and attitudes; and how innovative rates fit into the overall strategy of the utilities. It was found that TOU, interruptible and end-use targeted rates are the rate structures of choice for many utilities. Most are concerned with deferring capacity, reducing peak demand, and shifting load out of peak periods. Most utilities report success with their programs and satisfaction with the present form of the programs. 5 tabs

  13. A speculation on the debate about the future electricity demand in Korea

    International Nuclear Information System (INIS)

    Lim, Chae Young; Moon, Kee Hwan

    2005-01-01

    Since 1991, Korean government established the Long term Power Development Plan(LPDP) to secure a stable electricity supply. With the introduction of market mechanism into electricity supply sector, that plan has been changed into the Basic Plan of the Electricity supply and demand(BPE), which plays a role as a nonbinding guideline or a reference rather than the implementation plan. The BPE still has its importance as a tool providing market participants with appropriate information of future electricity market. According to the second BPE, released at the end of 2004, electricity demand is projected to grow at 2.5% per annum and reach 416.5TWh in 2017 from 293.6TWh in 2003. Based on the projected demand, power expansion plan provided by utilities has established. In the process of formulating the BPE, there were hot debates on the excess capacity margins for certain period of planning time. Some people, especially from environmental groups maintained that many Koreans were wasteful with electricity so that stronger policy for curbing the electricity consumption should be introduced rather than commissioning of additional power plants. They referred to relatively high number of the electricity intensity of Korea as the grounds of their argument. However, electricity intensity in a region or a country is influenced by various factors and higher intensity does not necessarily mean more wasteful consumption of electricity. We have compared various aspects of electricity demand in Korea with other countries to speculate the argument that electricity consumption in Korea is too high. We have also discussed electricity projection in the BPE

  14. Assessment of end-use electricity consumption and peak demand by Townsville's housing stock

    International Nuclear Information System (INIS)

    Ren, Zhengen; Paevere, Phillip; Grozev, George; Egan, Stephen; Anticev, Julia

    2013-01-01

    We have developed a comprehensive model to estimate annual end-use electricity consumption and peak demand of housing stock, considering occupants' use of air conditioning systems and major appliances. The model was applied to analyse private dwellings in Townsville, Australia's largest tropical city. For the financial year (FY) 2010–11 the predicted results agreed with the actual electricity consumption with an error less than 10% for cooling thermostat settings at the standard setting temperature of 26.5 °C and at 1.0 °C higher than the standard setting. The greatest difference in monthly electricity consumption in the summer season between the model and the actual data decreased from 21% to 2% when the thermostat setting was changed from 26.5 °C to 27.5 °C. Our findings also showed that installation of solar panels in Townville houses could reduce electricity demand from the grid and would have a minor impact on the yearly peak demand. A key new feature of the model is that it can be used to predict probability distribution of energy demand considering (a) that appliances may be used randomly and (b) the way people use thermostats. The peak demand for the FY estimated from the probability distribution tracked the actual peak demand at 97% confidence level. - Highlights: • We developed a model to estimate housing stock energy consumption and peak demand. • Appliances used randomly and thermostat settings for space cooling were considered. • On-site installation of solar panels was also considered. • Its' results agree well with the actual electricity consumption and peak demand. • It shows the model could provide the probability distribution of electricity demand

  15. Strategic Generation Capacity Choice under Demand Uncertainty : Analysis of Nash Equilibria in Electricity Markets

    NARCIS (Netherlands)

    Gürkan, G.; Ozdemir, O.; Smeers, Y.

    2013-01-01

    Abstract: We analyze a two-stage game of strategic firms facing uncertain demand and exerting market power in decentralized electricity markets. These firms choose their generation capacities at the first stage while anticipating a perfectly competitive future electricity spot market outcome at the

  16. Regulating electricity demand peaks for home appliances using reversible fair scheduling

    DEFF Research Database (Denmark)

    Kardaras, Georgios; Rossello Busquet, Ana; Iversen, Villy Bæk

    2010-01-01

    This paper describes a novel methodology for regulating electricity demand peaks for home appliances. To achieve this objective, we will make use of the reversible fair scheduling algorithm originally developed for telecommunication networks. The main concept behind this approach is the aggregati....... Moreover, users will be granted lower electricity bill rates for accepting prolonging the operation of some of their home appliances....

  17. Optimal Electricity Charge Strategy Based on Price Elasticity of Demand for Users

    Science.gov (United States)

    Li, Xin; Xu, Daidai; Zang, Chuanzhi

    The price elasticity is very important for the prediction of electricity demand. This paper mainly establishes the price elasticity coefficient for electricity in single period and inter-temporal. Then, a charging strategy is established based on these coefficients. To evaluate the strategy proposed, simulations of the two elastic coefficients are carried out based on the history data of a certain region.

  18. Letter to the Editor: Electric Vehicle Demand Model for Load Flow Studies

    DEFF Research Database (Denmark)

    Garcia-Valle, Rodrigo; Vlachogiannis, Ioannis (John)

    2009-01-01

    This paper introduces specific and simple model for electric vehicles suitable for load flow studies. The electric vehicles demand system is modelled as PQ bus with stochastic characteristics based on the concept of queuing theory. All appropriate variables of stochastic PQ buses are given...

  19. Saving, efficiency and management of electric sector demand

    International Nuclear Information System (INIS)

    Sanchez de Tembleque, L. J.

    2007-01-01

    Spanish economic model of development is based on energy consumption, and its main source is imported fossil fuels, which have some environmental and scarcity consequences in the mid term, among others. These problems could be reduced in two ways: economic activity reduction or energy efficiency improvement. In the presence of these possibilities, It may be desirable to bet for saving and energy efficiency, to maintain the economic development. This assignment analyzes the main available regulatory and social mechanisms to promote saving and energy efficiency in the power sector, like systems to internalize social costs in the electricity price, efficiency standards, and encourage the new saving culture. (Author) 15 refs

  20. A long- and short-run analysis of electricity demand in Ciudad Juarez

    Science.gov (United States)

    Mendez-Carrillo, Ericka Cecilia

    Economic growth and appliance saturation are increasing electricity consumption in Mexico. Annual frequency data from 1990 to 2012 are utilized to develop an error correction framework that sheds light on short- and long-run electricity consumption behavior in Ciudad Juarez, a large Mexican metropolitan economy at the border with the United States. The results for this study reveal that electricity is an inelastic normal good in this market. Moreover, natural gas is found to be a weak complement to electricity. With regards to the customer base in this urban economy, population, employment, and income exercise positive and statistically significant impacts on the demand for electricity hook-ups.

  1. The demand for electricity in Australia to 2020

    International Nuclear Information System (INIS)

    Orchison, K.

    2003-01-01

    Pursuing a secure, reliable electricity supply, therefore, is easily explained as a high national priority here as elsewhere and the cost of doing so in the next 12-20 years will be measured in billions of dollars - according to ESAA calculations, some $30 billion by 2012 and probably more than $40 billion by 2020, not including the billions likely to be needed to ensure an adequate supply of natural gas to generators. In any scenario that makes sense to ESAA, natural gas, black coal and brown coal will dominate as fuels for electricity generation. Obviously, renewable energy, driven by government subsidy through a program that mandates retailer purchases, will grow in use, but at 2020 it is not remotely likely that fossil fuels will have less than 80 percent of the generation mix. A brief word here about the prospect for nuclear power use in Australia in this time frame. ESAA simply cannot see a nuclear development being pursued - for political reasons if for no other

  2. Impact of plug-in hybrid electric vehicles charging demand on the optimal energy management of renewable micro-grids

    International Nuclear Information System (INIS)

    Kavousi-Fard, Abdollah; Abunasri, Alireza; Zare, Alireza; Hoseinzadeh, Rasool

    2014-01-01

    This paper suggests a new stochastic expert framework to investigate the charging effect of plug-in hybrid electric vehicles (PHEVs) on the optimal operation and management of micro-grids (MGs). In this way, a useful method based on smart charging approach is proposed to consider the charging demand of PHEVs in both residential location and public charging stations. The analysis is simulated for 24 h considering the uncertainties associated with the forecast error in the charging demand of PHEVs, hourly load consumption, hourly energy price and Renewable Energy Sources (RESs) output power. In order to see the effect of storage devices on the operation of the MG, NiMH-Battery is also incorporated in the MG. According to the high complexity of the problem, a new optimization method called θ-krill herd (θ-KH) algorithm is proposed which uses the phase angle vectors to update the velocity/position of krill animals with faster and more stable convergence. In addition, a new modification method is proposed to improve the search ability of the algorithm, effectively. The suggested problem is examined on an MG including different RESs such as photovoltaic (PV), fuel cells (FCs), wind turbine (WT), micro turbine (MT) and battery as the storage device. - Highlights: • Introducing an expert stochastic framework for optimal operation and management of MGs including PHEVs. • Introducing a new artificial optimization algorithm based on KH evolutionary technique. • Introducing a new version of KH algorithm called θ-KH for the optimization applications. • Modeling the uncertainty of forecast error in Wind turbine, Photovoltaics, market price, load data, PHEVs electric charging demand in an intelligent framework

  3. Hybrid Forecasting Approach Based on GRNN Neural Network and SVR Machine for Electricity Demand Forecasting

    Directory of Open Access Journals (Sweden)

    Weide Li

    2017-01-01

    Full Text Available Accurate electric power demand forecasting plays a key role in electricity markets and power systems. The electric power demand is usually a non-linear problem due to various unknown reasons, which make it difficult to get accurate prediction by traditional methods. The purpose of this paper is to propose a novel hybrid forecasting method for managing and scheduling the electricity power. EEMD-SCGRNN-PSVR, the proposed new method, combines ensemble empirical mode decomposition (EEMD, seasonal adjustment (S, cross validation (C, general regression neural network (GRNN and support vector regression machine optimized by the particle swarm optimization algorithm (PSVR. The main idea of EEMD-SCGRNN-PSVR is respectively to forecast waveform and trend component that hidden in demand series to substitute directly forecasting original electric demand. EEMD-SCGRNN-PSVR is used to predict the one week ahead half-hour’s electricity demand in two data sets (New South Wales (NSW and Victorian State (VIC in Australia. Experimental results show that the new hybrid model outperforms the other three models in terms of forecasting accuracy and model robustness.

  4. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes.

    Science.gov (United States)

    Kelly, Jack; Knottenbelt, William

    2015-01-01

    Many countries are rolling out smart electricity meters. These measure a home's total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the 'ground truth' demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

  5. Evolution of industrial sector electricity demand in Costa Rica

    International Nuclear Information System (INIS)

    Fischer, Steven C.

    2005-01-01

    This note is a preliminary investigation into the relationship between the efficiency of electricity utilization in the Costa Rican industrial sector and the competitive pressures generated by the implementation of economic reforms, in particular, the progressive liberalization of international trade, in the years since the debt and economic crisis of the early 1980s. The steady, year-by-year, reduction in the rate of import tariff protection, with only temporary interruptions and reverses, has been the most consistently implemented component of the macroeconomic, trade, and financial sector reforms upon which this country has embarked over the past two decades. The note sheds some light on the nature of the general policy environment that is conductive to an efficient utilization of energy in the productive sectors and to the success of national energy efficiency promotion programs in this and other parts of the world. (Author)

  6. Impacts of Demand-Side Management on Electrical Power Systems: A Review

    Directory of Open Access Journals (Sweden)

    Hussein Jumma Jabir

    2018-04-01

    Full Text Available Electricity demand has grown over the past few years and will continue to grow in the future. The increase in electricity demand is mainly due to industrialization and the shift from a conventional to a smart-grid paradigm. The number of microgrids, renewable energy sources, plug-in electric vehicles and energy storage systems have also risen in recent years. As a result, future electricity grids have to be revamped and adapt to increasing load levels. Thus, new complications associated with future electrical power systems and technologies must be considered. Demand-side management (DSM programs offer promising solutions to these issues and can considerably improve the reliability and financial performances of electrical power systems. This paper presents a review of various initiatives, techniques, impacts and recent developments of the DSM of electrical power systems. The potential benefits derived by implementing DSM in electrical power networks are presented. An extensive literature survey on the impacts of DSM on the reliability of electrical power systems is also provided for the first time. The research gaps within the broad field of DSM are also identified to provide directions for future work.

  7. Monthly electric energy demand forecasting with neural networks and Fourier series

    International Nuclear Information System (INIS)

    Gonzalez-Romera, E.; Jaramillo-Moran, M.A.; Carmona-Fernandez, D.

    2008-01-01

    Medium-term electric energy demand forecasting is a useful tool for grid maintenance planning and market research of electric energy companies. Several methods, such as ARIMA, regression or artificial intelligence, have been usually used to carry out those predictions. Some approaches include weather or economic variables, which strongly influence electric energy demand. Economic variables usually influence the general series trend, while weather provides a periodic behavior because of its seasonal nature. This work investigates the periodic behavior of the Spanish monthly electric demand series, obtained by rejecting the trend from the consumption series. A novel hybrid approach is proposed: the periodic behavior is forecasted with a Fourier series while the trend is predicted with a neural network. Satisfactory results have been obtained, with a lower than 2% MAPE, which improve those reached when only neural networks or ARIMA were used for the same purpose. (author)

  8. Modelling of Hot Water Storage Tank for Electric Grid Integration and Demand Response Control

    DEFF Research Database (Denmark)

    Sinha, Rakesh; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    , selection of a proper model is equally important. The results obtained from comparison of two models (when input to the model is thermal energy demand) are present with their significance and advantages for grid integration and demand response. Models mathematics are shown in detail with the validation......District heating (DH), based on electric boilers, when integrated into electric network has potential of flexible load with direct/indirect storage to increase the dynamic stability of the grid in terms of power production and consumption with wind and solar. The two different models of electric...... boilers for grid integration are investigated: single mass model (with uniform temperature inside tank) and two mass model (with ideal single stratified layers). In order to investigate the influence of demand response and grid voltage quality with the measurable parameter of electrical boiler in practice...

  9. Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach

    Directory of Open Access Journals (Sweden)

    Jeyhun I. Mikayilov

    2017-11-01

    Full Text Available Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan.

  10. An analysis of the impact of Renewable Portfolio Standards on residential electricity prices

    Science.gov (United States)

    Larson, Andrew James

    A Renewable Portfolio Standard (RPS) has become a popular policy for states seeking to increase the amount of renewable energy generated for consumers of electricity. The success of these state programs has prompted debate about the viability of a national RPS. The impact that these state level policies have had on the price consumers pay for electricity is the subject of some debate. Several federal organizations have conducted studies of the impact that a national RPS would have on electricity prices paid by consumers. NREL and US EIA utilize models that analyze the inputs in electricity generation to examine the future price impact of changes to electricity generation and show marginal increases in prices paid by end users. Other empirical research has produced similar results, showing that the existence of an RPS increases the price of electricity. These studies miss important aspects of RPS policies that may change how we view these price increases from RPS policies. By examining the previous empirical research on RPS policies, this study seeks to identify the controls necessary to build an effective model. These controls are utilized in a fixed effects model that seeks to show how the controls and variables of interest impact electricity prices paid by residential consumers of electricity. This study utilizes a panel data set from 1990 to 2014 to analyze the impact of these policies controlling for generating capacity, the regulatory status of utilities in each state, demographic characteristics of the states, and fuel prices. The results of the regressions indicate that prices are likely to be higher in states that have an RPS compared to states that do not have such a policy. Several of the characteristics mentioned above have price impacts, and so discussing RPS policies in the context of other factors that contribute to electricity prices is essential. In particular, the regulatory status of utilities in each state is an important determinate of price as

  11. Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

    OpenAIRE

    Jinchao Li; Lin Chen; Yuwei Xiang; Jinying Li; Dong Peng

    2018-01-01

    Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have pos...

  12. Electricity deregulation, spot price patterns and demand-side management

    International Nuclear Information System (INIS)

    Li, Y.; Flynn, P.C.

    2006-01-01

    This paper examines extensive hourly or half-hourly power price data from 14 deregulated power markets. It analyzes average diurnal patterns, relationship to system load, volatility, and consistency over time. Diurnal patterns indicate the average price spread between off-peak and on-peak and weekend vs. weekday power consumption. Volatility is measured by price velocity: the average normalized hourly change in power price, calculated daily. The calculated price velocity is broken down into an expected component that arises from the diurnal pattern and an unexpected component that arises from unknown factors. The analysis reveals significant differences among markets, suggesting that demand-side management (DSM) of power consumption is far more difficult in some markets than in others. At one extreme, Spain, Britain and Scandinavia show consistent diurnal price patterns, a stable relationship between price and system load, and a low unexplained component of price volatility. A power consumer in these markets could form a reasonable expectation of a reward for DSM of elective power consumption. At the other extreme, two markets in Australia show erratic diurnal price patterns from year to year, low correlation between price and system load, and a high amount of unexpected price velocity. A power consumer in these markets would have far greater difficulty in realizing a benefit from DSM. Markets that experienced one period of very high prices without a clear external cause, such as California and Alberta, appear to have a significant longer-term erosion of public support for deregulation. (author)

  13. An Assessment of Global Electric-Sector Water Demands to 2100 under the Latest Scenarios

    Science.gov (United States)

    Ando, N.; Yoshikawa, S.; Kanae, S.

    2016-12-01

    Electricity demands are likely to continue growing in the coming decades, due to population and economy growth. The electric growth could lead water demands to increase because some kinds of power generation methods such as thermal power generation require large amount of water. Many countries still rely on thermal power generation. Thus, we are concerned that electricity generation could be a big factor to accelerate water scarcity. In this study, to assess the electric-sector impacts on water demands, we estimated future electric-sector water withdrawal and consumption in 17 regions from 2010 to 2100. The water withdrawal and consumption are calculated by using electricity generation and water demand intensities. The data set of future electricity generation is derived by the Asia-Pacific Integrated Model. This model applied the latest scenarios for global climate change studies, the socio-economic scenario (SSPs) and the radiative forcing scenario (RCPs). We used the water demands intensity data set of Macknick et al. (2012). Water demand intensities for power plants considerably varies by power plant cooling systems. Therefore, we constructed cooling system share scenarios. Our results indicated that by 2100, the water withdrawal and consumption in current developing countries increased and caught up with that in current developed countries. We found that socio-economic scenarios (SSPs) has large impacts on the water withdrawal and consumption. Sustainable society (SSP1) and conventional development society (SSP5) have higher economic growth than fragmentation society (SSP3). The sustainable society needs smaller amount of the water withdrawal and consumption compared with fragmentation society. In contrast, the conventional development society needs larger amount of the water withdrawal and consumption compared with fragmentation society. Therefore, higher economic growth did not always lead less electric-sector water withdrawal and consumption. A shift of

  14. Extreme daily increases in peak electricity demand: Tail-quantile estimation

    International Nuclear Information System (INIS)

    Sigauke, Caston; Verster, Andréhette; Chikobvu, Delson

    2013-01-01

    A Generalized Pareto Distribution (GPD) is used to model extreme daily increases in peak electricity demand. The model is fitted to years 2000–2011 recorded data for South Africa to make a comparative analysis with the Generalized Pareto-type (GP-type) distribution. Peak electricity demand is influenced by the tails of probability distributions as well as by means or averages. At times there is a need to depart from the average thinking and exploit information provided by the extremes (tails). Empirical results show that both the GP-type and the GPD are a good fit to the data. One of the main advantages of the GP-type is the estimation of only one parameter. Modelling of extreme daily increases in peak electricity demand helps in quantifying the amount of electricity which can be shifted from the grid to off peak periods. One of the policy implications derived from this study is the need for day-time use of electricity billing system similar to the one used in the cellular telephone/and fixed line-billing technology. This will result in the shifting of electricity demand on the grid to off peak time slots as users try to avoid high peak hour charges. - Highlights: ► Policy makers should design demand response strategies to save electricity. ► Peak electricity demand is influenced by tails of probability distributions. ► Both the GSP and the GPD are a good fit to the data. ► Accurate assessment of level and frequency of extreme load forecasts is important.

  15. Preliminary guidelines for electricity distributor conservation and demand management activities : a guide for conservation and demand management investment

    International Nuclear Information System (INIS)

    2004-01-01

    In May 2004, electricity distributors in Ontario were asked to submit deferral accounts to the Ontario Energy Board to track expenditures on conservation and demand management initiatives. The deferral accounts must be established before the distributor could recover the costs through the next installment of the allowable return on equity in March 2004. The Board will determine the appropriateness of the actual expenditures. These guidelines offer short-term assistance to distributors in establishing conservation and demand management plans and initiatives. The following specific measures may be supported by the Board: energy efficiency; operational changes to smart control systems; load management measures which facilitate interruptible and dispatchable loads, dual fuel applications, thermal storage and demand response; fuel switching measures; programs targeted to low income and hard to reach consumers; and, distributed energy options such as tri-generation, cogeneration, ground source heat pumps, wind and biomass systems. These guidelines described the regulatory treatment of conservation and demand management investments along with cost effectiveness, allocation of costs, monitoring, evaluation, and implementation. 1 appendix

  16. Demand curves of electric energy in domestic sector in two regions of Mexico; Curvas de demanda de energia electrica en sector domestico de dos regiones de Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Maqueda Zamora, Martin Roberto; Sanchez Viveros, Luis Agustin [Instituto de Investigaciones Electricas, Cuernavaca, Morelos (Mexico)

    2011-07-01

    In this work, is presented the analysis of residential consumption, regarding the temperature of two areas and types of electrical appliances. A shape characteristic of the load of the electrical energy is obtained for two geographical areas in Mexico. The consumption information was obtained from measurements in residential consumers and from the Mexican Utility. It is also shown the demand profile of the main residential appliances, obtained from smart metering equipment to separate the residential users' load profiles. It is shown the effect of the different variables analyzed on the electrical power consumption, mainly the type of equipment, the geographical localization, the weather (temperature, humidity and vegetation type). With the results attained, the definition of effective energy-saving programs and its effectiveness can be obtained. [Spanish] En este trabajo se presenta el analisis del consumo residencial considerando la temperatura de las dos areas y tipos de aparatos electricos. Se obtiene una forma caracteristica de la carga de energia electrica de dos areas geograficas de Mexico. La informacion sobre el consumo se obtuvo de mediciones en consumidores residenciales y de una empresa electrica mexicana. Tambien se muestra el perfil de demanda de los principales aparatos residenciales, derivado de equipos de medicion inteligentes para separar los perfiles de carga de usuarios residenciales. Se muestra el efecto de diferentes variables analizadas en el consumo de energia electrica, principalmente el tipo de equipo, la localizacion geografica, el clima (temperatura, humedad y tipo de vegetacion). Con los resultados alcanzados pueden definirse programas de ahorro de energia efectivos y lograr implantarlos.

  17. Future demand in electrical power and meeting this demand, in particular with the aid of nuclear energy

    International Nuclear Information System (INIS)

    1976-07-01

    As a part of the research program in question, the study deals with meeting the electrical power demand in the FRG until the year 2000 in the best possible way with regard to costs, and evaluating the long-term technical, ecological, and economical effects resulting thereof. With the aid of a model, the construction of additional plants and the use of the FRG's power plant network, always applying economical criteria, are investigated while allowing for adequate assurance of supply. It becomes obvious that the power plants and fuels available influence a 25-year planning period. In the year 2000, nuclear energy will play a dominating role in meeting the demand, the conventional thermal power plants will be used more for coping with the above-average medium laods, while peak loads will be met, above all, by pump storage stations. (UA) [de

  18. Electricity supply and demand analysis in electric system of Uruguay 2000-2007 period

    International Nuclear Information System (INIS)

    2008-01-01

    This article is about the following topics: energy analysis, production and use, supply and demand, energy consumption evolution, energy sources, energy demand by economic sector between years 2000-2007, energy range, energy growing rate, demanding maximum power, growing maximum rate, exported and imported energy.

  19. The potential demand for bioenergy in residential heating applications (bio-heat) in the UK based on a market segment analysis

    International Nuclear Information System (INIS)

    Jablonski, S.; Pantaleo, A.; Bauen, A.; Pearson, P.; Panoutsou, C.; Slade, R.

    2008-01-01

    How large is the potential demand for bio-heat in the UK? Whilst most research has focused on the supply of biomass for energy production, an understanding of the potential demand is crucial to the uptake of heat from bioenergy. We have designed a systematic framework utilising market segmentation techniques to assess the potential demand for biomass heat in the UK. First, the heat market is divided into relevant segments, characterised in terms of their final energy consumption, technological and fuel supply options. Second, the key technical, economic and organisational factors that affect the uptake of bioenergy in each heat segment are identified, classified and then analysed to reveal which could be strong barriers, which could be surmounted easily, and for which bioenergy heat represents an improvement compared to alternatives. The defined framework is applied to the UK residential sector. We identify provisionally the most promising market segments for bioenergy heat, and their current levels of energy demand. We find that, depending on the assumptions, the present potential demand for bio-heat in the UK residential sector ranges between 3% (conservative estimate) and 31% (optimistic estimate) of the total energy consumed in the heat market. (author)

  20. Electric Boiler and Heat Pump Thermo-Electrical Models for Demand Side Management Analysis in Low Voltage Grids

    DEFF Research Database (Denmark)

    Diaz de Cerio Mendaza, Iker; Bak-Jensen, Birgitte; Chen, Zhe

    2013-01-01

    on the power system control and operation, created by this unstable way of generation, Demand Side Management turns to be a promising solution. The storage capacity from thermo-electric units, like electric boilers and heat pumps, allows operating them with certain freedom. Hence they can be employed under...... certain coordination, to actively respond to the power system fluctuations. The following paper presents two simple thermo-electrical models of an electrical boiler and an air-source CO2 heat pump system. The purpose is using them in low voltage grids analysis to assess their capacity and flexibility...... as active loads. The models were simulated under different Danish daily domestic hot water and space heating profiles. Results showed that under high heating demand conditions the flexibility of this kind of units may be drastically restricted due to their continuous operation....

  1. Electric Boiler and Heat Pump Thermo-Electrical Models for Demand Side Management Analysis in Low Voltage Grids

    DEFF Research Database (Denmark)

    Diaz de Cerio Mendaza, Iker; Bak-Jensen, Birgitte; Chen, Zhe

    2013-01-01

    The last fifteen years many European countries have integrated large percentage of renewable energy on their electricity generation mix. In Denmark the 21.3% of the electricity consumed nowadays is produced by the wind, and it has planned to be the 50% by 2025. In order to front future challenges...... on the power system control and operation, created by this unstable way of generation, Demand Side Management turns to be a promising solution. The storage capacity from thermo-electric units, like electric boilers and heat pumps, allows operating them with certain freedom. Hence they can be employed under...... certain coordination, to actively respond to the power system fluctuations. The following paper presents two simple thermo-electrical models of an electrical boiler and an air-source CO2 heat pump system. The purpose is using them in low voltage grids analysis to assess their capacity and flexibility...

  2. Forecasting Water Demand in Residential, Commercial, and Industrial Zones in Bogotá, Colombia, Using Least-Squares Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Carlos Peña-Guzmán

    2016-01-01

    Full Text Available The Colombian capital, Bogotá, has undergone massive growth in a short period of time. Naturally, this growth has increased the city’s water demand. The prediction of this demand will help understand and analyze consumption behavior, thereby allowing for effective management of the urban water cycle. This paper uses the Least-Squares Support Vector Machines (LS-SVM model for forecasting residential, industrial, and commercial water demand in the city of Bogotá. The parameters involved in this study include the following: monthly water demand, number of users, and total water consumption bills (price for the three studied uses. Results provide evidence of the model’s accuracy, producing R2 between 0.8 and 0.98, with an error percentage under 12%.

  3. Electricity demand by the commercial sector in Kuwait: an econometric analysis

    International Nuclear Information System (INIS)

    Eltony, M.N.; Hajeeh, M.

    1999-01-01

    This paper models and estimates electricity demand by the Kuwaiti commercial sector, using an error correction model. It also simulates the estimated model under three scenarios and presents an analysis of the results. The empirical results indicate that short- and long-run electricity consumption and the level of economic activity are interrelated. The forecasts show that electricity consumption varies directly with economic growth. They also suggest that an increase of 100 per cent in nominal electricity prices will lead to a reduction in commercial sector electricity demand of 45 per cent by the year 2010. The simulation of the model under the different scenarios demonstrates that the potential for energy conservation exists in the commercial sector

  4. Analysis of residential, industrial and commercial sector responses to potential electricity supply constraints in the 1990s

    Energy Technology Data Exchange (ETDEWEB)

    Fisher, Z.J.; Fang, J.M.; Lyke, A.J.; Krudener, J.R.

    1986-09-01

    There is considerable debate over the ability of electric generation capacity to meet the growing needs of the US economy in the 1990s. This study provides new perspective on that debate and examines the possibility of power outages resulting from electricity supply constraints. Previous studies have focused on electricity supply growth, demand growth, and on the linkages between electricity and economic growth. This study assumes the occurrence of electricity supply shortfalls in the 1990s and examines the steps that homeowners, businesses, manufacturers, and other electricity users might take in response to electricity outages.

  5. Impacts of the 2011 Tohoku earthquake on electricity demand in Japan. State space approach

    International Nuclear Information System (INIS)

    Honjo, Keita; Ashina, Shuichi

    2017-01-01

    Some papers report that consumers' electricity saving behavior (Setsuden) after the 2011 Tohoku Earthquake resulted in the reduction of the domestic electricity demand. However, time variation of the electricity saving effect (ESE) has not yet been sufficiently investigated. In this study, we develop a state space model of monthly electricity demand using long-term data, and estimate time variation of the ESE. We also estimate time variation of CO 2 emissions caused by Setsuden. Our result clearly indicates that Setsuden after the earthquake was not temporary but became established as a habit. Between March 2011 and October 2015, the ESE on power demand ranged from 2.9% to 6.9%, and the ESE on light demand ranged from 2.6% to 9.0%. The ESE on the total electricity demand was 3.2%-7.5%. Setsuden also contributed to the reduction of CO 2 emissions, but it could not offset the emissions increase caused by the shutdown of nuclear power plants. (author)

  6. Forecasting monthly peak demand of electricity in India—A critique

    International Nuclear Information System (INIS)

    Rallapalli, Srinivasa Rao; Ghosh, Sajal

    2012-01-01

    The nature of electricity differs from that of other commodities since electricity is a non-storable good and there have been significant seasonal and diurnal variations of demand. Under such condition, precise forecasting of demand for electricity should be an integral part of the planning process as this enables the policy makers to provide directions on cost-effective investment and on scheduling the operation of the existing and new power plants so that the supply of electricity can be made adequate enough to meet the future demand and its variations. Official load forecasting in India done by Central Electricity Authority (CEA) is often criticized for being overestimated due to inferior techniques used for forecasting. This paper tries to evaluate monthly peak demand forecasting performance predicted by CEA using trend method and compare it with those predicted by Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) model. It has been found that MSARIMA model outperforms CEA forecasts both in-sample static and out-of-sample dynamic forecast horizons in all five regional grids in India. For better load management and grid discipline, this study suggests employing sophisticated techniques like MSARIMA for peak load forecasting in India. - Highlights: ► This paper evaluates monthly peak demand forecasting performance by CEA. ► Compares CEA forecasts it with those predicted by MSARIMA model. ► MSARIMA model outperforms CEA forecasts in all five regional grids in India. ► Opportunity exists to improve the performance of CEA forecasts.

  7. The Effect of Temperature on the Electricity Demand: An Empirical Investigation

    Science.gov (United States)

    Kim, H.; Kim, I. G.; Park, K. J.; Yoo, S. H.

    2015-12-01

    This paper attempts to estimate the electricity demand function in Korea with quarterly data of average temperature, GDP and electricity price over the period 2005-2013. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the electricity demand function. The results show that short-run price and income elasticities of the electricity demand are estimated to be -0.569 and 0.631 respectively. They are statistically significant at the 1% level. Moreover, long-run income and price elasticities are estimated to be 1.589 and -1.433 respectively. Both of results reveal that the demand for electricity demand is about 15.2℃. It is shown that power of explanation and goodness-of-fit statistics are improved in the use of the lagged dependent variable model rather than conventional model. Acknowledgements: This research was carried out as a part of "Development and application of technology for weather forecast" supported by the 2015 National Institute of Meteorological Research (NIMR) in the Korea Meteorological Administration.

  8. High-resolution stochastic integrated thermal–electrical domestic demand model

    International Nuclear Information System (INIS)

    McKenna, Eoghan; Thomson, Murray

    2016-01-01

    Highlights: • A major new version of CREST’s demand model is presented. • Simulates electrical and thermal domestic demands at high-resolution. • Integrated structure captures appropriate time-coincidence of variables. • Suitable for low-voltage network and urban energy analyses. • Open-source development in Excel VBA freely available for download. - Abstract: This paper describes the extension of CREST’s existing electrical domestic demand model into an integrated thermal–electrical demand model. The principle novelty of the model is its integrated structure such that the timing of thermal and electrical output variables are appropriately correlated. The model has been developed primarily for low-voltage network analysis and the model’s ability to account for demand diversity is of critical importance for this application. The model, however, can also serve as a basis for modelling domestic energy demands within the broader field of urban energy systems analysis. The new model includes the previously published components associated with electrical demand and generation (appliances, lighting, and photovoltaics) and integrates these with an updated occupancy model, a solar thermal collector model, and new thermal models including a low-order building thermal model, domestic hot water consumption, thermostat and timer controls and gas boilers. The paper reviews the state-of-the-art in high-resolution domestic demand modelling, describes the model, and compares its output with three independent validation datasets. The integrated model remains an open-source development in Excel VBA and is freely available to download for users to configure and extend, or to incorporate into other models.

  9. Modeling electric load and water consumption impacts from an integrated thermal energy and rainwater storage system for residential buildings in Texas

    International Nuclear Information System (INIS)

    Upshaw, Charles R.; Rhodes, Joshua D.; Webber, Michael E.

    2017-01-01

    Highlights: • Hydronic integrated rainwater thermal storage (ITHERST) system concept presented. • ITHERST system modeled to assess peak electric load shifting and water savings. • Case study shows 75% peak load reduction and 9% increase in energy consumption. • Potable rainwater collection could provide ∼50–90% of water used for case study. - Abstract: The United States’ built environment is a significant direct and indirect consumer of energy and water. In Texas, and other parts of the Southern and Western US, air conditioning loads, particularly from residential buildings, contribute significantly to the peak electricity load on the grid, straining transmission. In parallel, water resources in these regions are strained by growing populations and shrinking supplies. One potential method to address both of these issues is to develop integrated thermal energy and auxiliary water (e.g. rainwater, greywater, etc.) storage and management systems that reduce peak load and freshwater consumption. This analysis focuses on a proposed integrated thermal energy and rainwater storage (ITHERST) system that is incorporated into a residential air-source chiller/heat pump with hydronic distribution. This paper describes a step-wise hourly thermodynamic model of the thermal storage system to assess on-peak performance, and a daily volume-balance model of auxiliary water collection and consumption to assess water savings potential. While the model is generalized, this analysis uses a case study of a single family home in Austin, Texas to illustrate its capabilities. The results indicate this ITHERST system could reduce on-peak air conditioning electric power demand by over 75%, with increased overall electric energy consumption of approximately 7–9%, when optimally sized. Additionally, the modeled rainwater collection reduced municipal water consumption by approximately 53–89%, depending on the system size.

  10. ON THE DEMAND DYNAMICS OF ELECTRICITY IN GHANA: DO EXOGENOUS NON-ECONOMIC VARIABLES COUNT?

    Directory of Open Access Journals (Sweden)

    Ishmael Ackah

    2014-04-01

    Full Text Available The purpose of this study is to identify and quantify the effect of endogenous and exogenous economic factors on electricity demand in Ghana. The Structural Time Series Model is employed due to its ability to capture exogenous non-economic variables. The findings reveal that education has significant effect on electricity consumption in both the short and the long run. Education has inverse relationship with electricity consumption implying that the more consumers are educated, the less electricity they consume. The study also reveals that price changes have less impact on electricity consumption in the short run and that efficiency in electricity consumption has improved since 1971 and will continue for the next twenty years. The study recommends that more public education should be carried out to enhance energy conservation and also, realistic prices should be charge for electricity consumption to allow private investment into the sector.

  11. Residential Mechanical Precooling

    Energy Technology Data Exchange (ETDEWEB)

    German, Alea [Davis Energy Group, Davis, CA (United States). Alliance for Residential Building Innovation (ARBI); Hoeschele, Marc [Davis Energy Group, Davis, CA (United States). Alliance for Residential Building Innovation (ARBI)

    2014-12-01

    Residential air conditioning (AC) represents a challenging load for many electric utilities with poor load factors. Mechanical precooling improves the load factor by shifting cooling operation from on-peak to off-peak hours. This provides benefits to utilities and the electricity grid, as well as to occupants who can take advantage of time-of-use (TOU) electricity rates. Performance benefits stem from reduced compressor cycling, and shifting condensing unit operation to earlier periods of the day when outdoor temperatures are more favorable to operational efficiency. Finding solutions that save energy and reduce demand on the electricity grid is an important national objective and supports key Building America goals. The Alliance for Residential Building Innovation team evaluated mechanical AC precooling strategies in homes throughout the United States. EnergyPlus modeling was used to evaluate two homes with different performance characteristics in seven climates. Results are applicable to new construction homes and most existing homes built in the last 10 years, as well as fairly efficient retrofitted homes. A successful off-peak AC strategy offers the potential for increased efficiency and improved occupant comfort, and promotes a more reliable and robust electricity grid. Demand response capabilities and further integration with photovoltaic TOU generation patterns provide additional opportunities to flatten loads and optimize grid impacts.

  12. Interim report of the supply/demand committee in Electric Enterprises Council

    International Nuclear Information System (INIS)

    1982-01-01

    Following a similar report made two odd years ago, an interim report was presented concerning the outlook of electric power demand and the development target for fiscal 1990, and also the electric power demand in the year 2000 to indicate the future direction. During the past two years, the energy situation both domestic and abroad has largely changed, including energy saving practice, petroleum substitute development, etc. The aggregate demand of electric power in fiscal 1990 was estimated at 795,000 million kwh, up about 4.3 % yearly from that in fiscal 1980. The target for nuclear power generation in fiscal 1990 was put at 46 million kw (22.0 % of the total power capacity). Then in the year 2000, the nuclear power generation in terms of capacity will be about 30 % of the aggregate total. (Mori, K.)

  13. Preliminary Examination of the Supply and Demand Balance for Renewable Electricity

    Energy Technology Data Exchange (ETDEWEB)

    Swezey, B.; Aabakken, J.; Bird, L.

    2007-10-01

    In recent years, the demand for renewable electricity has accelerated as a consequence of state and federal policies and the growth of voluntary green power purchase markets, along with the generally improving economics of renewable energy development. This paper reports on a preliminary examination of the supply and demand balance for renewable electricity in the United States, with a focus on renewable energy projects that meet the generally accepted definition of "new" for voluntary market purposes, i.e., projects installed on or after January 1, 1997. After estimating current supply and demand, this paper presents projections of the supply and demand balance out to 2010 and describe a number of key market uncertainties.

  14. Development of an Energy-Savings Calculation Methodology for Residential Miscellaneous Electric Loads: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Hendron, R.; Eastment, M.

    2006-08-01

    In order to meet whole-house energy savings targets beyond 50% in residential buildings, it will be essential that new technologies and systems approaches be developed to address miscellaneous electric loads (MELs). These MELs are comprised of the small and diverse collection of energy-consuming devices found in homes, including what are commonly known as plug loads (televisions, stereos, microwaves), along with all hard-wired loads that do not fit into other major end-use categories (doorbells, security systems, garage door openers). MELs present special challenges because their purchase and operation are largely under the control of the occupants. If no steps are taken to address MELs, they can constitute 40-50% of the remaining source energy use in homes that achieve 60-70% whole-house energy savings, and this percentage is likely to increase in the future as home electronics become even more sophisticated and their use becomes more widespread. Building America (BA), a U.S. Department of Energy research program that targets 50% energy savings by 2015 and 90% savings by 2025, has begun to identify and develop advanced solutions that can reduce MELs.

  15. Estimation of Turkey Electric Energy Demand until Year 2035 Using TLBO Algorithm

    OpenAIRE

    TEFEK, Mehmet Fatih; UGUZ, Harun

    2016-01-01

    In this study, the estimation of Turkey primary electric energy demanduntil 2035 is tried to estimate by using Teaching-Learning Based Optimization(TLBO) Algorithm. Two models are proposed which are based on economicindicators TLBO algorithm linear energy demand (TLBOEDL) and TLBO algorithmquadratic energy demand (TLBOEDQ). In both of these two models the indicatorsused are Gross Domestic Product (GDP), population, importation and exportation.After a comparison of these two models with real v...

  16. Modeling of demand response in electricity markets : effects of price elasticity

    International Nuclear Information System (INIS)

    Banda, E.C.; Tuan, L.A.

    2007-01-01

    A design mechanism for the optimal participation of customer load in electricity markets was presented. In particular, this paper presented a modified market model for the optimal procurement of interruptible loads participating in day-ahead electricity markets. The proposed model considers the effect of price elasticity and demand-response functions. The objective was to determine the role that price elasticity plays in electricity markets. The simulation model can help the Independent System Operator (ISO) identify customers offering the lowest price of interruptible loads and load flow patterns that avoid problems associated with transmission congestion and transmission losses. Various issues associated with procurement of demand-response offerings such as advance notification, locational aspect of load, and power factor of the loads, were considered. It was shown that demand response can mitigate price volatility by allowing the ISO to maintain operating reserves during peak load periods. It was noted that the potential benefits of the demand response program would be reduced when price elasticity of demand is taken into account. This would most likely occur in actual developed open electricity markets, such as Nordpool. This study was based on the CIGRE 32-bus system, which represents the Swedish high voltage power system. It was modified for this study to include a broad range of customer characteristics. 18 refs., 2 tabs., 14 figs

  17. Forecasting electricity demand in South Africa: A critique of Eskom’s projections

    Directory of Open Access Journals (Sweden)

    Anastassios Pouris

    2010-03-01

    Full Text Available Within a short period, Eskom has applied to the National Energy Regulator of South Africa (NERSA for the third time since the 2008 electricity crisis, proposing a multiyear price determination for the periods 2010−2011 and 2012−2013. The new application, submitted at the end of September 2009, motivated for the debate of strategies with which the consequences of the proposed price hikes could be predicted, measured and controlled. In his presentation to Parliament in February 2009, Eskom’s then CEO, Mr Jacob Maroga presented the current energy situation in the country, the reasons for the crisis in 2007−2008, as well as the challenges of the future. The purpose of this paper is to contribute some new ideas and perspectives to Eskom’s existing arguments regarding the demand for electricity. The most important issue is the fact that Eskom does not sufficiently take into account the impact of the electricity prices in their electricity demand forecast. This study proposed that prices have a high impact on the demand for electricity (price elasticity of -0.5. Employing similar assumptions for the country’s economic growth as Eskom, the results of the forecasting exercise indicated a substantial decrease in demand (scenario 1: -31% in 2025 and scenario 2:-18% in 2025. This study’s findings contrasted significantly with Eskom’s projection, which has extensive implications as far as policy is concerned.

  18. The demand for electric energy in Saudi Arabia: an empirical investigation

    International Nuclear Information System (INIS)

    Diabi, A.

    1998-01-01

    The demand for electricity in Saudi Arabia has grown rapidly, and a number of factors account for this growth. The aim of this paper is to estimate the level of this demand and test for its main determinants. Cross-sectional data (i.e. regional) spanning the period 1980-92 and several estimators are used to achieve reliable estimates of the short-run and long-run own-price and income elasticities. The findings seem to be quite reasonable. First, the fixed effects method seems to fit the data better. Secondly, both the sign and the size of virtually all the elasticity estimates lie within the plausible range and most of them are statistically significant at ten per cent. Overall, the empirical evidence suggests that the demand for electricity in Saudi Arabia is both price- and income-inelastic. However, the influence of urbanisation on electricity consumption is clearly larger than that of real income. Thirdly, the estimated speed of adjustment implies very short adjustment lags in the demand for electricity in Saudi Arabia. And finally, among the policy issues that are of relevance is the current pricing policy, which has been making the whole electricity sector suffer a loss

  19. A perspective on electric vehicles: cost-benefit analysis and potential demand

    International Nuclear Information System (INIS)

    2011-01-01

    This report proposes some quantitative elements to assess the large scale diffusion of electric vehicles and analyse the potential demand for such vehicles. The first part proposes a cost-benefit analysis of the development of electric vehicles based on estimated costs and expected benefits by 2020. It addresses the following issues: framework and hypothesis, total cost of ownership, costs related to the deployment of a network of recharging infrastructures, assessment of external costs, and comparative cost-benefit analysis of electric vehicles. In the second part, the authors aim at identifying a potential demand for electric vehicles from the 2008 French national transport displacement survey (ENTD 2008) which provides recent data on the mobility of the French population

  20. Integrated Management of Residential Energy Resources

    Directory of Open Access Journals (Sweden)

    Antunes C. H.

    2012-10-01

    Full Text Available The increasing deployment of distributed generation systems based on renewables in the residential sector, the development of information and communication technologies and the expected evolution of traditional power systems towards smart grids are inducing changes in the passive role of end-users, namely with stimuli to change residential demand patterns. The residential user should be able to make decisions and efficiently manage his energy resources by taking advantages from his flexibility in load usage with the aim to minimize the electricity bill without depreciating the quality of energy services provided. The aim of this paper is characterizing electricity consumption in the residential sector and categorizing the different loads according to their typical usage, working cycles, technical constraints and possible degree of control. This categorization of end-use loads contributes to ascertain the availability of controllable loads to be managed as well as the different direct management actions that can be implemented. The ability to implement different management actions over diverse end-use load will increase the responsiveness of demand and potentially raises the willingness of end-users to accept such activities. The impacts on the aggregated national demand of large-scale dissemination of management systems that would help the end-user to make decisions regarding electricity consumption are predicted using a simulator that generates the aggregated residential sector electricity consumption under variable prices.

  1. The electricity supply-demand balance for the summer of 2016 - June 2016. Synthesis

    International Nuclear Information System (INIS)

    2016-06-01

    Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the summer of 2016

  2. Estimating deficit probabilities with price-responsive demand in contract-based electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Galetovic, Alexander [Facultad de Ciencias Economicas y Empresariales, Universidad de los Andes, Santiago (Chile); Munoz, Cristian M. [Departamento de Ingenieria Electrica, Universidad de Chile, Mariano Sanchez Fontecilla 310, piso 3 Las Condes, Santiago (Chile)

    2009-02-15

    Studies that estimate deficit probabilities in hydrothermal systems have generally ignored the response of demand to changing prices, in the belief that such response is largely irrelevant. We show that ignoring the response of demand to prices can lead to substantial over or under estimation of the probability of an energy deficit. To make our point we present an estimation of deficit probabilities in Chile's Central Interconnected System between 2006 and 2010. This period is characterized by tight supply, fast consumption growth and rising electricity prices. When the response of demand to rising prices is acknowledged, forecasted deficit probabilities and marginal costs are shown to be substantially lower. (author)

  3. Estimating deficit probabilities with price-responsive demand in contract-based electricity markets

    International Nuclear Information System (INIS)

    Galetovic, Alexander; Munoz, Cristian M.

    2009-01-01

    Studies that estimate deficit probabilities in hydrothermal systems have generally ignored the response of demand to changing prices, in the belief that such response is largely irrelevant. We show that ignoring the response of demand to prices can lead to substantial over or under estimation of the probability of an energy deficit. To make our point we present an estimation of deficit probabilities in Chile's Central Interconnected System between 2006 and 2010. This period is characterized by tight supply, fast consumption growth and rising electricity prices. When the response of demand to rising prices is acknowledged, forecasted deficit probabilities and marginal costs are shown to be substantially lower. (author)

  4. Estimating the price elasticity for demand for electricity by sector in South Africa

    Directory of Open Access Journals (Sweden)

    Roula Inglesi-Lotz

    2011-12-01

    Full Text Available This paper analyses electricity consumption patterns in South Africa in an attempt to understand and identify the roots of the current electricity crisis. This is done by investigating various economic sectors’ responses to price changes using panel data for the period 1993–2004. Positive and statistically significant price elasticities over this period were found for the transport (rail and commercial sectors while there are positive, but small and statistically insignificant responses to price changes in the agriculture and mining sectors. Only the industrial sector responded to changes in electricity prices according to theory, namely illustrating negative demand elasticities. This sector, however, dominates electricity consumption resulting in aggregate demand elasticities that are negative. These results explain, in part, the current electricity crisis. Given the historic low level of electricity prices in conjunction with, on the whole, a real price decline, i.e. price increases lower than the inflation rate; there was no major incentive to reduce electricity consumption and/or to be efficient. This result supports the notion that prices do have an important signalling effect in the economy. Hence, the electricity prices should be considered not only from an economic growth or social vantage point, but also from a supply and technocratic perspective, which includes environmental factors such as CO2-emissions. Prices should not be determined without considering the system-wide implications thereof.

  5. Behavioral aspects of regulation: A discussion on switching and demand response in Turkish electricity market

    International Nuclear Information System (INIS)

    Sirin, Selahattin Murat; Gonul, Mustafa Sinan

    2016-01-01

    Electricity sector has been transformed from state-owned monopolistic utilities to competitive markets with an aim to promote incentives for improving efficiency, reducing costs and increasing service quality to customers. One of the cardinal assumptions of the liberalized and competitive electricity markets is the rational actor, and decision-makers are assumed to make the best decisions that maximize their utility. However, a vast literature on behavioral economics has shown the weakness of economic theory in explaining and predicting individuals’ decision-making behavior. This issue is quite important for competition in electricity markets in which consumers’ preferences have a significant role. Despite its importance, this issue has almost been neglected in Turkey, which has taken major steps in electricity sector restructuring. Therefore, this paper aims to examine switching and demand response behavior in Turkish electricity market by using multiple correspondence and panel data analysis, and findings are discussed in light of the neoclassical and behavioral economics literature. Analyses’ results show that consumers’ switching and demand response behavior is consistent with the neoclassical literature to some extent; however, behavioral factors are also affecting consumers’ decisions. Furthermore, there are systemic problems that hinder effective functioning of the electricity market and restrict competition. - Highlights: • Behavioral economics can provide insights for consumer’ decisions. • Switching and demand response behavior is examined by econometric methods. • Results is consistent with the neoclassical literature to some extent • However, behavioral factors are also affecting consumers’ decisions.

  6. Automated Demand Response: The Missing Link in the Electricity Value Chain

    Energy Technology Data Exchange (ETDEWEB)

    McKane, Aimee; Rhyne, Ivin; Lekov, Alex; Thompson, Lisa; Piette, MaryAnn

    2009-08-01

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This ?electricity value chain? defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to"demo" potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives.1 In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies

  7. Automated Demand Response: The Missing Link in the Electricity Value Chain

    Energy Technology Data Exchange (ETDEWEB)

    McKane, Aimee; Rhyne, Ivin; Piette, Mary Ann; Thompson, Lisa; Lekov, Alex

    2008-08-01

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This 'electricity value chain' defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to 'demo' potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives. In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to Open

  8. Spatial–Temporal Analysis of the Heat and Electricity Demand of the Swiss Building Stock

    Directory of Open Access Journals (Sweden)

    Stefan Schneider

    2017-08-01

    Full Text Available In 2015, space heating and domestic hot water production accounted for around 40% of the Swiss final energy consumption. Reaching the goals of the 2050 energy strategy will require significantly reducing this share despite the growing building stock. Renewables are numerous but subject to spatial–temporal constraints. Territorial planning of energy distribution systems enabling the integration of renewables requires having a spatial–temporal characterization of the energy demand. This paper presents two bottom-up statistical extrapolation models for the estimation of the geo-dependent heat and electricity demand of the Swiss building stock. The heat demand is estimated by means of a statistical bottom-up model applied at the building level. At the municipality level, the electricity load curve is estimated by combining socio-economic indicators with average consumption per activity and/or electric device. This approach also allows to break down the estimated electricity demand according to activity type (e.g., households, various industry, and service activities and appliance type (e.g., lighting, motor force, fridges. The total estimated aggregated demand is 94 TWh for heat and 58 TWh for electricity, which represent a deviation of 2.9 and 0.5%, respectively compared to the national energy consumption statistics. In addition, comparisons between estimated and measured electric load curves are done to validate the proposed approach. Finally, these models are used to build a geo-referred database of heat and electricity demand for the entire Swiss territory. As an application of the heat demand model, a realistic saving potential is estimated for the existing building stock; this potential could be achieved through by a deep retrofit program. One advantage of the statistical bottom-up model approach is that it allows to simulate a building stock that replicates the diversity of building demand. This point is important in order to

  9. Examining demand response, renewable energy and efficiencies to meet growing electricity needs

    International Nuclear Information System (INIS)

    Elliot, N.; Eldridge, M.; Shipley, A.M.; Laitner, J.S.; Nadel, S.; Silverstein, A.; Hedman, B.; Sloan, M.

    2007-01-01

    While Texas has already taken steps to improve its renewable energy portfolio (RPS), and its energy efficiency improvement program (EEIP), the level of savings that utilities can achieve through the EEIP can be greatly increased. This report estimated the size of energy efficiency and renewable energy resources in Texas, and suggested a range of policy options that might be adopted to further extend EEIP. Current forecasts suggest that peak demand in Texas will increase by 2.3 per cent annually from 2007-2012, a level of growth which is threatening the state's ability to maintain grid reliability at reasonable cost. Almost 70 per cent of installed generating capacity is fuelled by natural gas in Texas. Recent polling has suggested that over 70 per cent of Texans are willing support increased spending on energy efficiency. Demand response measures that may be implemented in the state include incentive-based programs that pay users to reduce their electricity consumption during specific times and pricing programs, where customers are given a price signal and are expected to moderate their electricity usage. By 2023, the widespread availability of time-varying retail electric rates and complementary communications and control methods will permanently change the nature of electricity demand in the state. At present, the integrated utilities in Texas offer a variety of direct load control and time-of-use, curtailable, and interruptible rates. However, with the advent of retail competition now available as a result of the structural unbundling of investor-owned utilities, there is less demand response available in Texas. It was concluded that energy efficiency, demand response, and renewable energy resources can meet the increasing demand for electricity in Texas over the next 15 years. 4 figs

  10. Electrical demand forecast in two different scenarios of socio-economic development

    International Nuclear Information System (INIS)

    Goni, M.R.

    1996-01-01

    A projection of electrical demand for two different scenarios is presented in the study. The study period is 1993-2010 and 1993 has been taken as base year. In this planning study MAED program was used as well as all available information from INDEC (National Statistical Body), CAMMESA (Electrical Market Company) and Ministery of Economy. The results in the base year achieved an accuracy higher than 98%. The scenarios described two different rates of growth and electrical penetration in energy uses. (author). 3 refs., 9 figs., 2 tabs

  11. Modeling and Analysis of Commercial Building Electrical Loads for Demand Side Management

    Science.gov (United States)

    Berardino, Jonathan

    In recent years there has been a push in the electric power industry for more customer involvement in the electricity markets. Traditionally the end user has played a passive role in the planning and operation of the power grid. However, many energy markets have begun opening up opportunities to consumers who wish to commit a certain amount of their electrical load under various demand side management programs. The potential benefits of more demand participation include reduced operating costs and new revenue opportunities for the consumer, as well as more reliable and secure operations for the utilities. The management of these load resources creates challenges and opportunities to the end user that were not present in previous market structures. This work examines the behavior of commercial-type building electrical loads and their capacity for supporting demand side management actions. This work is motivated by the need for accurate and dynamic tools to aid in the advancement of demand side operations. A dynamic load model is proposed for capturing the response of controllable building loads. Building-specific load forecasting techniques are developed, with particular focus paid to the integration of building management system (BMS) information. These approaches are tested using Drexel University building data. The application of building-specific load forecasts and dynamic load modeling to the optimal scheduling of multi-building systems in the energy market is proposed. Sources of potential load uncertainty are introduced in the proposed energy management problem formulation in order to investigate the impact on the resulting load schedule.

  12. Towards a demand-side smart domestic electrical energy management system

    CSIR Research Space (South Africa)

    Dlodlo, N

    2013-01-01

    Full Text Available Energy conservation concerns call for end-users to regulate their electrical consumption and help achieve a balance between the available energy supply and demand. Therefore there is a need for rigorous research into smart home energy management...

  13. Power System Transient Stability Improvement Using Demand Side Management in Competitive Electricity Markets

    DEFF Research Database (Denmark)

    Hu, Weihao; Wang, Chunqi; Chen, Zhe

    2012-01-01

    for demand side management generates different load profiles and may provide an opportunity to improve the transient stability of power systems with high wind power penetrations. In this paper, the idea of the power system transient stability improvement by using optimal load response to the electricity...

  14. Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Karin Kandananond

    2011-08-01

    Full Text Available Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA, artificial neural network (ANN and multiple linear regression (MLR—were utilized to formulate prediction models of the electricity demand in Thailand. The objective was to compare the performance of these three approaches and the empirical data used in this study was the historical data regarding the electricity demand (population, gross domestic product: GDP, stock index, revenue from exporting industrial products and electricity consumption in Thailand from 1986 to 2010. The results showed that the ANN model reduced the mean absolute percentage error (MAPE to 0.996%, while those of ARIMA and MLR were 2.80981 and 3.2604527%, respectively. Based on these error measures, the results indicated that the ANN approach outperformed the ARIMA and MLR methods in this scenario. However, the paired test indicated that there was no significant difference among these methods at α = 0.05. According to the principle of parsimony, the ARIMA and MLR models might be preferable to the ANN one because of their simple structure and competitive performance

  15. Smart grids, demand-side management and decentralised electricity production: Mounting a national R and D programme

    International Nuclear Information System (INIS)

    2010-01-01

    of investment RTE, ERDF and EDF-R and D dispose of teams that can identify future R and D needs, pilot and conduct research, and integrate the results, often obtained in collaboration with other parties, in innovative demonstration projects set up by operators. This is no longer the case for many of their European counterparts where research teams have shrunk to a minimum, following cost-cutting decisions and 'rationalisation' of grid activities (decisions made on the basis of short-term business policies, often encouraged by regulators 3). These encouraging observations notwithstanding, transmission and distribution grid operators in France consider that they must acquire further knowledge pertaining to the sizing and operation of electricity networks. Five policy options underlie this vision extending to 2020, a vision aimed at validating new directions for the evolution of these networks: 1 - Strengthen the capacity of the transmission grid to integrate an energy bouquet that complies with European commitments for de-carbonising electricity generation, via the development of renewable energy, 2 - Make the distribution grid flexible and reliable enough to meet the consumer demand and the requirements of energy service vendors, 3 - Coordinate interaction between transmission operators and distributors so as to reinforce the reliability of the grid in France, optimise its energy performance and contribute to building the single electricity market in Europe, 4 - Encourage electricity demand management as an additional source of supply and economic competitiveness, 5 - Expand decentralised generation, particularly to help further reduce energy demand in commercial and residential buildings

  16. Adaptation possibilities of the nuclear electricity production to the demand; Possibilites d'adaptation de la production d'electricite nucleaires a la demande

    Energy Technology Data Exchange (ETDEWEB)

    Acket, C

    2009-02-15

    Meeting about the CO{sub 2} emissions from electric heating showed that the leak of adaptation from nuclear reactors led the use of thermal power plants (coal, petroleum, gas) to control the demand variations. This argument is analyzed in the document: is it possible to replace those thermal power plants by nuclear reactors? In this framework the author analyzes the network needs, the electricity sources and the demand answer and the specificities of the nuclear. (A.L.B.)

  17. Comparisons of recent growth in actual demand, planned demand, and planned generating capacity at U. S. electric utilities

    Energy Technology Data Exchange (ETDEWEB)

    Bopp, A.E. (James Madison Univ., Harrisonburg, VA (United States))

    1994-12-01

    During the winter of 1993, a number of U.S. electric utilities and some regional power pools discovered that current load exceeded generating capacity. Load restrictions followed, as entire regions-not just isolated utilities or even states-cut back. Was 1993 a typical, or simply a preview of the future If a preview, how did this shortage occur For a number of years, utilities, regulatory agencies, and power pools have been planning to add capacity at a much lower rate than the rate at which load has been growing. The National Electricity Reliability Council (NERC) has projected that eight of it's nine regions will have demand growth exceed capacity growth. The only region where capacity is growing faster is in the Texas Region. There are four reasons behind this shortage: excess capacity in the 1980's, disbelief in current forecasts, passage of the Clean Air act bringing stricter regulation on power plants, and the herd mentality where utilities have all delayed new plant construction.

  18. Setting up charging electric stations within residential communities in current China: Gaming of government agencies and property management companies

    International Nuclear Information System (INIS)

    Wu, Tian; Ma, Lin; Mao, Zhonggen; Ou, Xunmin

    2015-01-01

    The difficulty of charging electric vehicles (EVs) is now hindering their further development. Governments generally choose to build stations for home charging (including piles) within residential communities. Given the conflict of interest between various government agencies and property management companies, constructing a charging station within residential communities would result in welfare loss for the property management companies and therefore lead to the principal–agent problem. This paper constructs a two-period imperfect information game theory model to study the moral hazard involved in this issue and government agencies' optimal choice. In the analytic solution of the model, we find that the optimal choice for a farsighted government agency is to constantly improve the incentive mechanism and introduce charging stations only when the conflict of interest is eliminated. Any benefits derived from government regulations by force would prove short-lived. The government should focus on long-term returns in the development of EVs, and its optimal mechanism should be designed to mitigate the principal–agent problem of property management companies, thereby accelerate the progress of EV charging infrastructure and improve overall social welfare. - Highlights: • The charging of electric vehicles (EVs) is hindering their use. • A game theory model is used for analysis of EV charging station construction. • Charging stations are in residential communities in China. • Government agencies are constantly improving incentive mechanisms

  19. Electric Industry Restructuring in Ohio: Residential and Low Income Customer Impacts; TOPICAL

    International Nuclear Information System (INIS)

    Eisenberg, J

    2001-01-01

    This report analyzes the electric utilities in Ohio in order to determine how they are situated for the coming of competition. It begins with the status of the utilities as of 1995, the last year for which detailed data were available, and determines the detailed underlying cost structure behind the rates charged to customers. The study then develops a number of restructuring scenarios to be analyzed. These scenarios cover different approaches to dividing stranded asset costs between customers and stockholders, and between different groups of customers. They also cover wholesale versus retail competition, different regulatory structures for those services still under regulation, and new approaches to stranded asset costs such as securitization--the use of special bonds to reduce costs. Throughout the report the special emphasis is on the impact of restructuring on low-income residential customers. Low-income customers are the most vulnerable to changes in the regulatory structure with the fewest alternative options. The report finds that there are a great deal of above-market cost, potentially stranded assets in Ohio--approximately$8.75 billion in 1995. The annual above-market costs total over$3 billion, of which about 2/3 is recovery of capital related costs and 1/3 is recovery of energy related costs. The distribution of stranded assets in Ohio is very uneven. Some utilities such as Cleveland Electric and Ohio Edison have very high levels of above-market costs. In contrast, Ohio Power has, under some estimates, costs which are actually below market costs. The study looks separately at the near-term or transition period (approximately the next seven to ten years) and the longer term competitive market period. During the transition period the costs of stranded assets are being collected from customers while competitive markets are being developed. In the longer term market period it is assumed that all of the stranded asset costs have been collected and that the

  20. Estimating the net electricity energy generation and demand using the ant colony optimization approach. Case of Turkey

    International Nuclear Information System (INIS)

    Toksari, M. Duran

    2009-01-01

    This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear A COEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic A COEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios. (author)

  1. Efficient Use of Behavioral Tools to Reduce Electricity Demand of Domestic Consumers

    Directory of Open Access Journals (Sweden)

    Elbaz Shimon

    2016-12-01

    Full Text Available Purpose: The present study investigated the main literature on the subject of methods and policies for reducing the electricity demand of domestic consumers, in order to identify the place of behavioral tools. Methodology: We used secondary sources, performing a literature review, together with analysis and synthesis. Findings: Policy makers prefer to use tools offered by neoclassical economics, such as various forms of taxation, fines and financial incentives in order to make domestic electricity consumers save electricity, on the assumption that consumers will make rational decisions while maximizing their personal benefit. However, studies conducted in recent years in the field of behavioral economics, which are based on the assumption that consumers’ decisions are not rational and are affected by cognitive biases, showed that the use of behavioral tools, such as detailed online information (feedback,social comparison information, information on varying rates (dynamic pricing and general information (advertising campaign, are tools that are not less appropriate than the ones the neoclassical economics offers, mainly because electricity is an invisible product and consumers are unable to assess it by normal cognitive measures. Using an interdisciplinary combination of behavioral tools that come from a variety of approaches taken from a wide variety of different academic fields, it is possible to receive efficient results in the endeavor of reducing electricity demand. Implications: Although the neoclassical economics still remains the fundamental theory used by policymakers, it is recommended to consider behavioral economics as a complementary approach to the neoclassical economics, and combine behavioral tools in the policymakers’ toolbox, especially when those tools do not require a significant financial investment, thus efficiently maximizing the reduction of electricity demand among domestic consumers. These theoretical results will be

  2. The Effect of Electric Load Profiles on the Performance of Off-Grid Residential Hybrid Renewable Energy Systems

    Directory of Open Access Journals (Sweden)

    Stephen Treado

    2015-10-01

    Full Text Available This paper investigates the energy performance of off-grid residential hybrid renewable electric power systems, particularly the effect of electric load profiles on the ability to harvest available solar energy and avoid the consumption of auxiliary energy in the form of propane. The concepts are illustrated by an analysis of the energy performance of electric and propane-fired refrigerators. Off-grid electric power systems frequently incorporate a renewable source, such as wind or solar photovoltaic (PV, with a back-up power provided by a propane fueled motor/generator. Among other design decisions, residential consumers face the choice of employing an electric refrigerator with a conventional vapor compression refrigeration system, or a fuel-fired refrigerator operating as an absorption refrigeration system. One interesting question is whether it is more advantageous from an energy perspective to use electricity to run the refrigerator, which might be provided by some combination of the PV and propane motor/generator, thereby taking advantage of the relatively higher electric refrigerator Coefficient of Performance (COP and free solar energy but having to accept a low electrical conversion efficiency of the motor/generator, or use thermal energy from the combustion of propane to produce the refrigeration effect via an absorption system, albeit with a much lower COP. The analysis is complicated by the fact that most off-grid renewable electrical power systems utilize a battery bank to provide electrical power when it is not available from the wind turbine or PV system, so the state of charge of the battery bank will have a noticeable impact on what energy source is available at any moment in time. Daily electric load profiles combined with variable solar energy input determine the state of charge of the battery bank, with the degree of synchronization between the two being a critical factor in determining performance. The annual energy usage

  3. Energy systems scenario modelling and long term forecasting of hourly electricity demand

    Directory of Open Access Journals (Sweden)

    Poul Alberg Østergaard

    2015-06-01

    Full Text Available The Danish energy system is undergoing a transition from a system based on storable fossil fuels to a system based on fluctuating renewable energy sources. At the same time, more of and more of the energy system is becoming electrified; transportation, heating and fuel usage in industry and elsewhere. This article investigates the development of the Danish energy system in a medium year 2030 situation as well as in a long-term year 2050 situation. The analyses are based on scenario development by the Danish Climate Commission. In the short term, it is investigated what the effects will be of having flexible or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model. The results show that even with a limited short-term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrated wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long-term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps and electric vehicles in the long-term future overshadows any effects of changes in hourly demand curve profiles.

  4. Dealing with Demand in Electric Grids with an Adaptive Consumption Management Platform

    Directory of Open Access Journals (Sweden)

    Diego M. Jiménez-Bravo

    2018-01-01

    Full Text Available The control of consumption in homes and workplaces is an increasingly important aspect if we consider the growing popularity of smart cities, the increasing use of renewable energies, and the policies of the European Union on using energy in an efficient and clean way. These factors make it necessary to have a system that is capable of predicting what devices are connected to an electrical network. For demand management, the system must also be able to control the power supply to these devices. To this end, we propose the use of a multiagent system that includes agents with advanced reasoning and learning capacities. More specifically, the agents incorporate a case-based reasoning system and machine learning techniques. Besides, the multiagent system includes agents that are specialized in the management of the data acquired and the electrical devices. The aim is to adjust the consumption of electricity in networks to the electrical demand, and this will be done by acting automatically on the detected devices. The proposed system provides promising results; it is capable of predicting what devices are connected to the power grid at a high success rate. The accuracy of the system makes it possible to act according to the device preferences established in the system. This allows for adjusting the consumption to the current demand situation, without the risk of important home appliances being switched off.

  5. Assessing long-term effects of demand response policies in wholesale electricity markets

    International Nuclear Information System (INIS)

    Cepeda, Mauricio; Saguan, Marcelo

    2014-05-01

    This paper deals with the practical problems related to long-term issues in electricity markets in the presence of demand response development. Different policies have been implemented around the world aiming to develop demand response potential. Externalities, in particular the CO 2 externality, have been one of the key elements in the debate on the effectiveness of different policies regarding demand response development. Policy makers have several options to deal with this externality. The most direct one is to correct the externality by setting a CO 2 price at a level that corresponds to the cost to society of the corresponding CO 2 emissions. One alternative solution could be to subsidize carbon-free technologies as demand response. In this paper we examine potential long-term impacts of these two policies. We rely on a long-term market simulation model that characterizes expansion decisions in a competitive regime. We test for each policy two different scenarios regarding the possibility of internalization of the CO 2 externality. The results show that differences in development policies affect both investments and social costs in the wholesale electricity market and confirm previous findings that a market-driven development of demand response with the internalization of the CO 2 externality is the most efficient approach. (authors)

  6. Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances.

    Science.gov (United States)

    Deetman, Sebastiaan; Pauliuk, Stefan; van Vuuren, Detlef P; van der Voet, Ester; Tukker, Arnold

    2018-04-17

    This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework.

  7. Grey prediction with rolling mechanism for electricity demand forecasting of Turkey

    International Nuclear Information System (INIS)

    Akay, Diyar; Atak, Mehmet

    2007-01-01

    The need for energy supply, especially for electricity, has been increasing in the last two decades in Turkey. In addition, owing to the uncertain economic structure of the country, electricity consumption has a chaotic and nonlinear trend. Hence, electricity configuration planning and estimation has been the most critical issue of active concern for Turkey. The Turkish Ministry of Energy and Natural Resources (MENR) has officially carried out energy planning studies using the Model of Analysis of the Energy Demand (MAED). In this paper, Grey prediction with rolling mechanism (GPRM) approach is proposed to predict the Turkey's total and industrial electricity consumption. GPRM approach is used because of high prediction accuracy, applicability in the case of limited data situations and requirement of little computational effort. Results show that proposed approach estimates more accurate results than the results of MAED, and have explicit advantages over extant studies. Future projections have also been done for total and industrial sector, respectively

  8. Electricity decision-making: New techniques for calculating statewide economic impacts from new power supply and demand-side management programs

    Science.gov (United States)

    Tegen, Suzanne Isabel Helmholz

    This dissertation introduces new techniques for calculating and comparing statewide economic impacts from new coal, natural gas and wind power plants, as well as from demand-side management programs. The impetus for this work was two-fold. First, reviews of current literature and projects revealed that there was no standard way to estimate statewide economic impacts from new supply- and demand-side electricity options. Second, decision-makers who were interviewed stated that they were overwhelmed with data in general, but also lacked enough specific information about economic development impacts to their states from electricity, to make informed choices. This dissertation includes chapters on electricity decision-making and on economic impacts from supply and demand. The supply chapter compares different electricity options in three states which vary in natural resource content: Arizona, Colorado and Michigan. To account for differing capacity factors, resources are compared on a per-megawatt-hour basis. The calculations of economic impacts from new supply include: materials and labor for construction, operations, maintenance, fuel extraction, fuel transport, as well as property tax, financing and landowner revenues. The demand-side chapter compares residential, commercial and industrial programs in Iowa. Impact calculations include: incremental labor and materials for program planning, installation and operations, as well as sales taxes and electricity saved. Results from supply-side calculations in the three states analyzed indicate that adding new wind power can have a greater impact to a state's economy than adding new gas or coal power due to resource location, taxes and infrastructure. Additionally, demand-side management programs have a higher relative percentage of in-state dollar flow than supply-side solutions, though demand-side programs typically involve fewer MWh and dollars than supply-side generation. Methods for this dissertation include researching

  9. Connecting plug-in vehicles with green electricity through consumer demand

    International Nuclear Information System (INIS)

    Axsen, Jonn; Kurani, Kenneth S

    2013-01-01

    The environmental benefits of plug-in electric vehicles (PEVs) increase if the vehicles are powered by electricity from ‘green’ sources such as solar, wind or small-scale hydroelectricity. Here, we explore the potential to build a market that pairs consumer purchases of PEVs with purchases of green electricity. We implement a web-based survey with three US samples defined by vehicle purchases: conventional new vehicle buyers (n = 1064), hybrid vehicle buyers (n = 364) and PEV buyers (n = 74). Respondents state their interest in a PEV as their next vehicle, in purchasing green electricity in one of three ways, i.e., monthly subscription, two-year lease or solar panel purchase, and in combining the two products. Although we find that a link between PEVs and green electricity is not presently strong in the consciousness of most consumers, the combination is attractive to some consumers when presented. Across all three respondent segments, pairing a PEV with a green electricity program increased interest in PEVs—with a 23% demand increase among buyers of conventional vehicles. Overall, about one-third of respondents presently value the combination of a PEV with green electricity; the proportion is much higher among previous HEV and PEV buyers. Respondents’ reported motives for interest in both products and their combination include financial savings (particularly among conventional buyers), concerns about air pollution and the environment, and interest in new technology (particularly among PEV buyers). The results provide guidance regarding policy and marketing strategies to advance PEVs and green electricity demand. (letter)

  10. Connecting plug-in vehicles with green electricity through consumer demand

    Science.gov (United States)

    Axsen, Jonn; Kurani, Kenneth S.

    2013-03-01

    The environmental benefits of plug-in electric vehicles (PEVs) increase if the vehicles are powered by electricity from ‘green’ sources such as solar, wind or small-scale hydroelectricity. Here, we explore the potential to build a market that pairs consumer purchases of PEVs with purchases of green electricity. We implement a web-based survey with three US samples defined by vehicle purchases: conventional new vehicle buyers (n = 1064), hybrid vehicle buyers (n = 364) and PEV buyers (n = 74). Respondents state their interest in a PEV as their next vehicle, in purchasing green electricity in one of three ways, i.e., monthly subscription, two-year lease or solar panel purchase, and in combining the two products. Although we find that a link between PEVs and green electricity is not presently strong in the consciousness of most consumers, the combination is attractive to some consumers when presented. Across all three respondent segments, pairing a PEV with a green electricity program increased interest in PEVs—with a 23% demand increase among buyers of conventional vehicles. Overall, about one-third of respondents presently value the combination of a PEV with green electricity; the proportion is much higher among previous HEV and PEV buyers. Respondents’ reported motives for interest in both products and their combination include financial savings (particularly among conventional buyers), concerns about air pollution and the environment, and interest in new technology (particularly among PEV buyers). The results provide guidance regarding policy and marketing strategies to advance PEVs and green electricity demand.

  11. Climate Change Impacts on Electricity Demand and Supply in the United States: A Multi-Model Comparison

    Science.gov (United States)

    This paper compares the climate change impacts on U.S. electricity demand and supply from three models: the Integrated Planning Model (IPM), the Regional Energy Deployment System (ReEDS) model, and GCAM. Rising temperatures cause an appreciable net increase in electricity demand....

  12. Analysis and Estimation of Electric Power Demand in Russian Far East

    Science.gov (United States)

    Oleinik, E. B.; Sidorova, N. G.

    2017-10-01

    This article reviews the current situation in the fuel and energy complex (FEC) of the Russian Far East, distinguishes its specific features, estimates the volume of investments required for further development of FEC in the Russian Far East. The use of econometric models makes it possible to get a forecast of electric power production, which serves as a basis of evaluation of the region’s electric power demand. It is noted that the main problem of the region development is surplus of energy production and a continuous population decline. The authors offer major strategic directions of development and mechanisms of energy policy implementation.

  13. Analysing socioeconomic diversity and scaling effects on residential electricity load profiles in the context of low carbon technology uptake

    International Nuclear Information System (INIS)

    McKenna, R.; Hofmann, L.; Merkel, E.; Fichtner, W.; Strachan, N.

    2016-01-01

    Adequately accounting for interactions between Low Carbon Technologies (LCTs) at the building level and the overarching energy system means capturing the granularity associated with decentralised heat and power supply in residential buildings. The approach presented here adds novelty in terms of a realistic socioeconomic differentiation by employing dwelling/household archetypes (DHAs) and neighbourhood clusters at the Output Area (OA) level. These archetypes are combined with a mixed integer linear program (MILP) to generate optimum (minimum cost) technology configurations and operation schedules. Even in the baseline case, without any LCT penetration, a substantial deviation from the standard load profile (SLP) is encountered, suggesting that for some neighbourhoods this profile is not appropriate. With the application of LCTs, including heat pumps, micro-CHP and photovoltaic (PV), this effect is much stronger, including more negative residual load, more variability, and higher ramps with increased LCT penetration, and crucially different between neighbourhood clusters. The main policy implication of the study is the importance of understanding electrical load profiles at the neighbourhood level, because of the consequences they have for investment in the overarching energy system, including transmission and distribution infrastructure, and centralised generation plant. Further work should focus on attaining a superior socioeconomic differentiation between households. - Highlights: • Low carbon technologies (LCTs) for heat/electricity in residential buildings. • Socioeconomic effects and interactions with overarching energy system. • Building thermal/electrical model combined with optimisation. • Significant differences between neighbourhood load profiles. • Policy implications: support for LCTs and investment in infrastructure.

  14. Medium- and long-term electric power demand forecasting based on the big data of smart city

    Science.gov (United States)

    Wei, Zhanmeng; Li, Xiyuan; Li, Xizhong; Hu, Qinghe; Zhang, Haiyang; Cui, Pengjie

    2017-08-01

    Based on the smart city, this paper proposed a new electric power demand forecasting model, which integrates external data such as meteorological information, geographic information, population information, enterprise information and economic information into the big database, and uses an improved algorithm to analyse the electric power demand and provide decision support for decision makers. The data mining technology is used to synthesize kinds of information, and the information of electric power customers is analysed optimally. The scientific forecasting is made based on the trend of electricity demand, and a smart city in north-eastern China is taken as a sample.

  15. Future Electricity Demand of the Emerging European Countries and the CIS Countries

    Directory of Open Access Journals (Sweden)

    Mehmet Fatih Bayramoglu

    2016-10-01

    Full Text Available Nowadays, one of the leading factors used in the evaluation of a country’s economic development is energy consumption. Because of economic growth, demand for energy is also increasing. In this study, the emerging European countries’ (the Czech Republic, Poland, Romania, Turkey and the CIS countries’ (Kazakhstan, Russia, Ukraine, Uzbekistan  electricity consumption has been forecasted for five years period (2015-2019. In the study, GM(1,1 Rolling Model, which is developed in the framework of Grey System Theory is used as a mathematical model for real-time forecasting. The results of the study show that there will not be a significant change in electricity demand in this two area during the 2015-2109 period.

  16. Energy Systems Scenario Modelling and Long Term Forecasting of Hourly Electricity Demand

    DEFF Research Database (Denmark)

    Alberg Østergaard, Poul; Møller Andersen, Frits; Kwon, Pil Seok

    2015-01-01

    . The results show that even with a limited short term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrate wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant...... effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps....... This article investigates the development of the Danish energy system in a medium year 2030 situation as well as in a long-term year 2050 situation. The analyses are based on scenario development by the Danish Climate Commission. In the short term, it is investigated what the effects will be of having flexible...

  17. Generation adequacy report on the electricity supply-demand balance in France - 2012 edition

    International Nuclear Information System (INIS)

    2012-01-01

    After an introduction presenting the objective of this report and the method used for the forecasts, this document proposes, first, an analysis of the medium-term evolution of: 1 - electricity consumption (past trends, medium-term perspectives, medium-term consumption scenarios); 2 - electricity supply (nuclear production, centralised and decentralised production from fossil-fueled power plants, hydro-power, wind-power and photovoltaic production, peak-load management); 3 - supply and demand balance (probabilistic approach, reference scenario, scenario sensitivity with respect to the demand). Then it presents the long-term determining factors (socio-economic context, energy efficiency, energy mix, interconnected grids development) and the long-term prospective scenarios (medium- and strong-consumption, new-mix, low growth). Finally, a summary and a comparison with the 2011 report is made

  18. Cost-competitiveness of organic photovoltaics for electricity self-consumption at residential buildings: A comparative study of Denmark and Greece under real market conditions

    DEFF Research Database (Denmark)

    Chatzisideris, Marios Dimos; Laurent, Alexis; Christoforidis, Georgios C.

    2017-01-01

    To address sustainability challenges, photovoltaics (PV) are regarded as a promising renewable energy technology. Decreasing PV module costs and increasing residential electricity prices have made self-consumption of PV-generated electricity financially more attractive than exporting to the grid...... has not been evaluated under real market conditions, especially under PV self-consumption schemes. In this study, we investigate the self-consumption of electricity generation from conventional and organic PV systems installed at residential houses in two different countries, Denmark and Greece, under...... applying to all PV technologies show that PV systems installed at residential houses in Greece perform economically better than those in Denmark do in terms of self-sufficiency and gross electricity bill savings (i.e. excluding PV costs). Using the two country cases, which present very different settings...

  19. Estimating Demand Response Load Impacts: Evaluation of BaselineLoad Models for Non-Residential Buildings in California

    Energy Technology Data Exchange (ETDEWEB)

    Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote,Sila

    2008-01-01

    Both Federal and California state policymakers areincreasingly interested in developing more standardized and consistentapproaches to estimate and verify the load impacts of demand responseprograms and dynamic pricing tariffs. This study describes a statisticalanalysis of the performance of different models used to calculate thebaseline electric load for commercial buildings participating in ademand-response (DR) program, with emphasis onthe importance of weathereffects. During a DR event, a variety of adjustments may be made tobuilding operation, with the goal of reducing the building peak electricload. In order to determine the actual peak load reduction, an estimateof what the load would have been on the day of the event without any DRactions is needed. This baseline load profile (BLP) is key to accuratelyassessing the load impacts from event-based DR programs and may alsoimpact payment settlements for certain types of DR programs. We testedseven baseline models on a sample of 33 buildings located in California.These models can be loosely categorized into two groups: (1) averagingmethods, which use some linear combination of hourly load values fromprevious days to predict the load on the event, and (2) explicit weathermodels, which use a formula based on local hourly temperature to predictthe load. The models were tested both with and without morningadjustments, which use data from the day of the event to adjust theestimated BLP up or down.Key findings from this study are: - The accuracyof the BLP model currently used by California utilities to estimate loadreductions in several DR programs (i.e., hourly usage in highest 3 out of10 previous days) could be improved substantially if a morning adjustmentfactor were applied for weather-sensitive commercial and institutionalbuildings. - Applying a morning adjustment factor significantly reducesthe bias and improves the accuracy of all BLP models examined in oursample of buildings. - For buildings with low load

  20. ENCOURAGING ELECTRICITY SAVINGS IN A UNIVERSITY RESIDENTIAL HALL THROUGH A COMBINATION OF FEEDBACK, VISUAL PROMPTS, AND INCENTIVES

    Science.gov (United States)

    Bekker, Marthinus J; Cumming, Tania D; Osborne, Nikola K.P; Bruining, Angela M; McClean, Julia I; Leland, Louis S

    2010-01-01

    This experiment investigated the combined use of visual prompts, daily feedback, and rewards to reduce electricity consumption in a university residential hall. After a 17-day baseline period, the experimental intervention was introduced in the intervention hall, and no change was made in the control hall. Energy usage decreased in the intervention hall, but energy usage did not change appreciably in the control hall. In the intervention hall, mean daytime and nighttime savings were 16.2% and 10.7%, respectively, compared to savings of 3.8% (day) and 6.5% (night) in the control hall. PMID:21119909

  1. Performance Analysis of Short-Term Electricity Demand with Atmospheric Variables

    Directory of Open Access Journals (Sweden)

    Kamal Chapagain

    2018-04-01

    Full Text Available The quality of short-term electricity demand forecasting is essential for the energy market players for operation and trading activities. Electricity demand is significantly affected by non-linear factors, such as climatic conditions, calendar components and seasonal behavior, which have been widely reported in the literature. This paper considers parsimonious forecasting models to explain the importance of atmospheric variables for hourly electricity demand forecasting. Many researchers include temperature as a major weather component. If temperature is included in a model, other weather components, such as relative humidity and wind speed, are considered as less effective. However, several papers mention that there is a significant impact of atmospheric variables on electricity demand. Therefore, the main purpose of this study is to investigate the impact of the following atmospheric variables: rainfall, relative humidity, wind speed, solar radiation, and cloud cover to improve the forecasting accuracy. We construct three different multiple linear models (Model A, Model B, and Model C including the auto-regressive moving average with exogenous variables (ARMAX with the mentioned exogenous weather variables to compare the performances for Hokkaido Prefecture, Japan. The Bayesian approach is applied to estimate the weight of each variable with Gibbs sampling to approximate the estimation of the coefficients. The overall mean absolute percentage error (MAPE performances of Model A, Model B, and Model C are estimated as 2.43%, 1.98% and 1.72%, respectively. This means that the accuracy is improved by 13.4% by including rainfall, snowfall, solar radiation, wind speed, relative humidity, and cloud cover data. The results of the statistical test indicate that these atmospheric variables and the improvement in accuracy are statistically significant in most of the hours. More specifically, they are significant during highly fluctuating and peak hours.

  2. Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies (City Energy: From Data to Decisions)

    Energy Technology Data Exchange (ETDEWEB)

    Office of Strategic Programs, Strategic Priorities and Impact Analysis Team

    2017-09-29

    This fact sheet "Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies" explains how the City of Asheville used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

  3. Dynamic management of integrated residential energy systems

    Science.gov (United States)

    Muratori, Matteo

    This study combines principles of energy systems engineering and statistics to develop integrated models of residential energy use in the United States, to include residential recharging of electric vehicles. These models can be used by government, policymakers, and the utility industry to provide answers and guidance regarding the future of the U.S. energy system. Currently, electric power generation must match the total demand at each instant, following seasonal patterns and instantaneous fluctuations. Thus, one of the biggest drivers of costs and capacity requirement is the electricity demand that occurs during peak periods. These peak periods require utility companies to maintain operational capacity that often is underutilized, outdated, expensive, and inefficient. In light of this, flattening the demand curve has long been recognized as an effective way of cutting the cost of producing electricity and increasing overall efficiency. The problem is exacerbated by expected widespread adoption of non-dispatchable renewable power generation. The intermittent nature of renewable resources and their non-dispatchability substantially limit the ability of electric power generation of adapting to the fluctuating demand. Smart grid technologies and demand response programs are proposed as a technical solution to make the electric power demand more flexible and able to adapt to power generation. Residential demand response programs offer different incentives and benefits to consumers in response to their flexibility in the timing of their electricity consumption. Understanding interactions between new and existing energy technologies, and policy impacts therein, is key to driving sustainable energy use and economic growth. Comprehensive and accurate models of the next-generation power system allow for understanding the effects of new energy technologies on the power system infrastructure, and can be used to guide policy, technology, and economic decisions. This

  4. Impacts of Various Characteristics of Electricity and Heat Demand on the Optimal Configuration of a Microgrid

    Science.gov (United States)

    Bando, Shigeru; Watanabe, Hiroki; Asano, Hiroshi; Tsujita, Shinsuke

    A methodology was developed to design the number and capacity for each piece of equipment (e.g. gas engines, batteries, thermal storage tanks) in microgrids with combined heat and power systems. We analyzed three types of microgrids; the first one consists of an office building and an apartment, the second one consists of a hospital and an apartment, the third one consists of a hotel, office and retails. In the methodology, annual cost is minimized by considering the partial load efficiency of a gas engine and its scale economy, and the optimal number and capacity of each piece of equipment and the annual operational schedule are determined by using the optimal planning method. Based on calculations using this design methodology, it is found that the optimal number of gas engines is determined by the ratio of bottom to peak of the electricity demand and the ratio of heat to electricity demand. The optimal capacity of a battery required to supply electricity for a limited time during a peak demand period is auxiliary. The thermal storage tank for space cooling and space heating is selected to minimize the use of auxiliary equipment such as a gas absorption chiller.

  5. Reducing Energy Demand Using Wheel-Individual Electric Drives to Substitute EPS-Systems

    Directory of Open Access Journals (Sweden)

    Jürgen Römer

    2018-01-01

    Full Text Available The energy demand of vehicles is influenced, not only by the drive systems, but also by a number of add-on systems. Electric vehicles must satisfy this energy demand completely from the battery. Hence, the use of power steering systems directly result in a range reduction. The “e2-Lenk” joint project funded by the German Federal Ministry of Education and Research (BMBF involves a novel steering concept for electric vehicles to integrate the function of steering assistance into the drive-train. Specific distribution of driving torque at the steered axle allows the steering wheel torque to be influenced to support the steering force. This provides a potential for complete substitution of conventional power steering systems and reduces the vehicle’s energy demand. This paper shows the potential of wheel-individual drives influencing the driver’s steering torque using a control technique based on classical EPS control plans. Compared to conventional power-assisted steering systems, a reduced energy demand becomes evident over a wide range of operating conditions.

  6. A demand/supply and price outlook for electricity in Ontario

    International Nuclear Information System (INIS)

    Dalton, J.

    2004-01-01

    This paper examined electricity pricing issues for both the immediate future as well as over the long term. The near term outlook resources for the summer of 2004 were reviewed. Intermediate critical supply and demand issues were projected with consideration given to the return of the Pickering A plant and coal phase out. In the long term, it was considered that pricing and demand would reflect conservation issues and demand side response, as well as the timing of Requests For Proposals (RFPs) and the phase out of coal-fired capacity. The impact of the coal phase-out in Ontario was examined, with particular reference to timing and market structure implications. Potential conservation impacts were presented and projected Ontario supply/demand balances were evaluated. The challenges facing the new market structure include pricing dynamics and a reliance on RFPs. The significance of specifying diversity objectives was also discussed. It was concluded that the Ontario Ministry of Energy should play a role in establishing targets for conservation, renewable energy and the overall supply of electricity. Rigorous analysis is necessary before specifying targets in terms of hydroelectric and nuclear generation as opposed to non-fossil generation. tabs., figs

  7. Impacts of demand response and renewable generation in electricity power market

    Science.gov (United States)

    Zhao, Zhechong

    This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating

  8. Generation adequacy report 2009 on the electricity supply - demand balance in France

    International Nuclear Information System (INIS)

    2009-01-01

    Under the terms of the Law of February 10, 2000, RTE (Reseau de Transport d'Electricite), working under the aegis of the Public Authorities, periodically establishes a multi-annual forecast report on the balance of electricity supply and demand in France. The Generation Adequacy Report is one basis for the Minister for Energy, and the Public Authorities in general, to build the Multi-annual Investment Plan (referred to in this document by its French acronym PPI for Programmation Pluri-annuelle des Investissements) for electricity generation facilities, introduced by the above-mentioned law. The Generation Adequacy Report deals with the security of the French electricity supply. It intends to identify over a period of about fifteen years the risks of imbalances in continental France between the electricity demand and the generation capacity available to supply it. It enables the identification of the generation capacity required to meet the peaks of demand. The choice of generation technologies to be developed, which is dictated by environmental and economic concerns, is not covered by the Generation Adequacy Report, but is a matter for the other stakeholders in the French electric system, under the guidelines determined by the PPI. The Generation Adequacy Report is published by RTE on its web site and thus accessible to all to serve transparency and contribute to the French energy debate. This document is the fourth edition of the Generation Adequacy Report published by RTE, following its 2003, 2005 and 2007 editions. RTE publishes partial updates in-between to reflect developments in generation capacity. The last update was published in 2008. The time horizon of the 2009 edition of the Generation Adequacy Report is 2025. (author)

  9. Control Method Based on Demand Response Needs of Isolated Bus Regulation with Series-Resonant Converters for Residential Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Shu-Huai Zhang

    2017-05-01

    Full Text Available Considering the effects of isolation and high efficiency, a series-resonant DC-DC converter (L-L-C type, with two inductors and a capacitor has been introduced into a residential photovoltaic (PV generation and storage system in this work, and a voltage gain curve upwarp drifting problem was found. In this paper, the reason of upwarp drifting in the voltage gain curve is given, and a new changing topological control method to solve the voltage regulation problem under light load conditions is proposed. Firstly, the ideal and actual first harmonic approximation (FHA models are given, and this drifting problem is ascribed to the multiple peaks of higher-order resonance between resonant tank and parasitic capacitors. Then the paper presents the pulse-frequency-modulation (PFM driver signals control method to translate the full-bridge LLC into a half-bridge LLC converter, and with this method the voltage gain could easily be reduced by half. Based on this method, the whole voltage and resonant current sharing control methods in on-line and off-line mode are proposed. The parameters design and optimization methods are also discussed in detail. Finally, a residential PV system platform based on the proposed parallel 7-kW full-bridge LLC converter is built to verify the proposed control method and theoretical analysis.

  10. Simulation of demand side participation in Spanish short term electricity markets

    International Nuclear Information System (INIS)

    Valencia-Salazar, I.; Alvarez, C.; Escriva-Escriva, G.; Alcazar-Ortega, M.

    2011-01-01

    Highlights: → Benefits from customer active participation can be obtained with a proper generation of bids and offers. → Simulation of Spanish customers' participation is shown in daily, intra-daily and balancing markets. → Market efficiency and economics profits arise in balancing markets by using customer load reductions. → Real market prices and real customers' consumptions profiles are used in the simulations. -- Abstract: Demand response resources management is one of the most investigated solutions oriented to improve the efficiency in electricity markets. In this paper, the capability of customers to participate in short term markets is analyzed. An available methodology to analyze the daily and monthly energy consumptions of large customers is used to create energy offers and bids. This allows customers to participate in energy markets in order to buy, as first step, the usual electricity consumption and, additionally, to offer demand reductions in the short term electricity markets. Additionally, this paper shows the customer potential to participate in the Spanish electricity markets.

  11. Clean coal technology choices relating to the future supply and demand of electricity in Southern Africa

    International Nuclear Information System (INIS)

    Lennon, S.J.

    1997-01-01

    The finalization of the United Nations Framework Convention on Climate Change (UNFCCC) has catalysed a high degree of debate and interest in the future of coal-fired power generation. Fossil fuel combustion is responsible for a significant percentage of pollutants emitted globally, and coal will continue to play a major role in the energy portfolios of many countries. This is particularly true for developing countries. This fact has resulted in a major focus on technologies which improve the efficiency of coal combustion and conversion to electrical energy, as well as technologies which directly of indirectly reduce overall emissions. The issues around clean coal technologies (CCT) and their evolution, development and uptake in both developed and developing countries are complex. This paper addresses these issues in a Southern African context, viewed from the policy perspective of developing countries and presented in a framework of electricity supply and demand considerations in the region. The principal climate change policy elements proposed for South Africa are presented in the context of the current electricity supply and demand situation in the region. These are presented in the context of Eskom's Integrated Electricity Planning (IEP) process including the environmental considerations inherent in decision-making processes. The potential future of the CCT, barriers to their introduction and potential measures to facilitate their accelerated adoption are discussed. (author). 4 refs., 5 tabs., 2 figs

  12. Contrasting electricity demand with wind power supply: case study in Hungary

    International Nuclear Information System (INIS)

    Kiss, P.; Janosi, I. M.; Varga, L.

    2009-01-01

    We compare the demand of a large electricity consumer with supply given by wind farms installed at two distant geographic locations. Obviously such situation is rather unrealistic, however our main goal is a quantitative characterization of the intermittency of wind electricity. The consumption pattern consists of marked daily and weekly cycles interrupted by periods of holidays. In contrast, wind electricity production has neither short-time nor seasonal periodicities. We show that wind power integration over a restricted area cannot provide a stable base load supply, independently of the excess capacity. Further essential result is that the statistics are almost identical for a weekly periodic pattern of consumption and a constant load of the same average value. The length of both adequate supply and shortfall intervals exhibits a scale-free (power-law) frequency distribution, possible consequences are shortly discussed. (author)

  13. Contrasting Electricity Demand with Wind Power Supply: Case Study in Hungary

    Directory of Open Access Journals (Sweden)

    Imre M. Jánosi

    2009-09-01

    Full Text Available We compare the demand of a large electricity consumer with supply given by wind farms installed at two distant geographic locations. Obviously such situation is rather unrealistic, however our main goal is a quantitative characterization of the intermittency of wind electricity. The consumption pattern consists of marked daily and weekly cycles interrupted by periods of holidays. In contrast, wind electricity production has neither short-time nor seasonal periodicities. We show that wind power integration over a restricted area cannot provide a stable baseload supply, independently of the excess capacity. Further essential result is that the statistics are almost identical for a weekly periodic pattern of consumption and a constant load of the same average value. The length of both adequate supply and shortfall intervals exhibits a scale-free (power-law frequency distribution, possible consequences are shortly discussed.

  14. Cost-saving potentials using demand side management in households and electric mobility

    Energy Technology Data Exchange (ETDEWEB)

    Schinz, S.; Najib, H.; Steiner, L. [Darmstadt Univ. of Technology (Germany). Inst. for Renewable Energies

    2010-07-01

    The increasing share of renewable energies in the electricity production has an influence on the grid and on the electricity markets, where higher price fluctuations are expected. One way of integrating renewable energies is using demand side management (DSM). In this case online energy markets enable private households to participate with their loads in these markets. Especially their household appliances participate on the basis of hourly electricity prices. Thus these markets can provide DSM-services for the grid by means of aggregating household loads. To estimate the cost-savings of DSM for the purpose of reducing electricity costs in private households different gadget-models are developed and minimal costs are calculated by formulating linear optimization models. In private households especially refrigerators, freezers, washing machines, tumble- dryers and dishwashers can be considered as shiftable loads for DSM purposes. This application of DSM is examined in this paper precisely. Future developments regarding DSM are analyzed with scenarios for 2010 and 2030. The gadget-models have average specifications of gadgets in Europe and Germany. Their operation is optimized for minimal electricity cost over one year on the basis of electricity prices from the European Energy Exchange EEX in Leipzig, Germany. Finally DSM in Micro Grids is analyzed and different control options are considered to solve the voltage stability problem. (orig.)

  15. Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

    Directory of Open Access Journals (Sweden)

    Jinchao Li

    2018-01-01

    Full Text Available Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have positive influences on electric grid investment demand, but the impact of population scale, social electricity consumption, and installed electrical capacity on electric grid investment is not remarkable. We divide different regions in China into the eastern region, central region, and western region to analyze influence factors of electric grid investment, finally obtaining key factors in the eastern, central, and western regions. In the end, according to the analysis of key factors, we make a prediction about China’s electric grid investment for 2020 in different scenarios. The results offer a certain understanding for the development trend of China’s electric grid investment and contribute to the future development of electric grid investment.

  16. Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

    International Nuclear Information System (INIS)

    Morais, Hugo; Sousa, Tiago; Vale, Zita; Faria, Pedro

    2014-01-01

    Highlights: • Multi-objective optimization of operation costs and load factor. • Contribution of electric vehicles to load diagram leveling. • Use of epigraph variables to transform non-convex functions in convex ones. • Evaluation of the obtained results considering different EVs penetration. - Abstract: Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management

  17. Impact of oil prices, economic diversification policies and energy conservation programs on the electricity and water demands in Kuwait

    International Nuclear Information System (INIS)

    Wood, Michael; Alsayegh, Osamah A.

    2014-01-01

    This paper describes the influences of oil revenue and government's policies toward economic developments and energy efficiency on the electricity and water demands. A Kuwait-specific electricity and water demand model was developed based on historic data of oil income, gross domestic product (GDP), population and electric load and water demand over the past twelve years (1998–2010). Moreover, the model took into account the future mega projects, annual new connected loads and expected application of energy conservation programs. It was run under six circumstances representing the combinations of three oil income scenarios and two government action policies toward economic diversification and energy conservation. The first government policy is the status quo with respect to economic diversification and applying energy conservation programs. The second policy scenario is the proactive strategy of raising the production of the non-oil sector revenue and enforcing legislations toward energy demand side management and conservation. In the upcoming 20 years, the average rates of change of the electric load and water demand increase are 0.13 GW and 3.0 MIGD, respectively, per US dollar oil price increase. Moreover, through proactive policy, the rates of average load and water demand decrease are 0.13 GW and 2.9 MIGD per year, respectively. - Highlights: • Kuwait-specific electricity and water demand model is presented. • Strong association between oil income and electricity and water demands. • Rate of change of electric load per US dollar oil price change is 0.13 GW. • Rate of change of water demand per US dollar oil price change is 3.0 MIGD. • By 2030, efficiency lowers electric load and water demand by 10 and 6%, respectively

  18. Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

    Directory of Open Access Journals (Sweden)

    Gang Du

    2015-06-01

    Full Text Available Electricity intensity is an important indicator for measuring production efficiency. A comparative study could offer a new perspective on investigating determinants of electricity demand. The Japanese non-metallic mineral products industry is chosen as the object for comparison considering its representative position in production efficiency. By adopting the cointegration model, this paper examines influencing factors of electricity demand in Japanese and Chinese non-metallic mineral products industries under the same framework. Results indicate that although economic growth and industrial development stages are different between the two countries, major factors that affect the sectoral energy consumption are the same. Specifically, economic growth and industrial activity contribute to the growth of sectoral electricity consumption, while R&D intensity, per capita productivity and electricity price are contributors to the decline of sectoral electricity consumption. Finally, in order to further investigate the development trend of sectoral electricity demand, future electricity consumption and conservation potential are predicted under different scenarios. Electricity demand of the Chinese non-metallic mineral products industry is predicted to be 680.53 TWh (terawatt-hours in 2020 and the sectoral electricity conservation potentials are estimated to be 118.26 TWh and 216.25 TWh under the moderate and advanced electricity-saving scenarios, respectively.

  19. The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use. A review

    International Nuclear Information System (INIS)

    Newsham, Guy R.; Bowker, Brent G.

    2010-01-01

    Peak demand for electricity in North America is expected to grow, challenging electrical utilities to supply this demand in a cost-effective, reliable manner. Therefore, there is growing interest in strategies to reduce peak demand by eliminating electricity use, or shifting it to non-peak times. This strategy is commonly called 'demand response'. In households, common strategies are time-varying pricing, which charge more for energy use on peak, or direct load control, which allows utilities to curtail certain loads during high demand periods. We reviewed recent North American studies of these strategies. The data suggest that the most effective strategy is a critical peak price (CPP) program with enabling technology to automatically curtail loads on event days. There is little evidence that this causes substantial hardship for occupants, particularly if they have input into which loads are controlled and how, and have an override option. In such cases, a peak load reduction of at least 30% is a reasonable expectation. It might be possible to attain such load reductions without enabling technology by focusing on household types more likely to respond, and providing them with excellent support. A simple time-of-use (TOU) program can only expect to realise on-peak reductions of 5%. (author)

  20. Estimation of European Union residential sector space cooling potential

    International Nuclear Information System (INIS)

    Jakubcionis, Mindaugas; Carlsson, Johan

    2017-01-01

    Data on European residential space cooling demands are scarce and often of poor quality. This can be concluded from a review of the Comprehensive Assessments on the energy efficiency potential in the heating and cooling sector performed by European Union Member States under Art. 14 of the Energy Efficiency Directive. This article estimates the potential space cooling demands in the residential sector of the EU and the resulting impact on electricity generation and supply systems using the United States as a proxy. A georeferenced approach was used to establish the potential residential space cooling demand in NUTS-3 regions of EU. The total potential space cooling demand of the EU was estimated to be 292 TW h for the residential sector in an average year. The additional electrical capacity needed was estimated to 79 GW. With proper energy system development strategies, e.g. matching capacity of solar PV with cooling demand, or introduction of district cooling, the stresses on electricity system from increasing cooling demand can be mitigated. The estimated potential of space cooling demand, identified in this paper for all EU Members States, could be used while preparing the next iteration of EU MS Comprehensive Assessments or other energy related studies. - Highlights: • An estimation of EU space cooling demand potential in residential sector is presented. • An estimate of space cooling demand potential is based on using USA data as a proxy. • Significant cooling demand increase can be expected. • Cooling demand increase would lead to increased stress in energy supply systems. • Proper policies and strategies might measurably decrease the impact on energy systems.

  1. A perspective on electric vehicles: cost-benefit analysis and potential demand; Les vehicules electriques en perspective. Analyse couts-avantages et demande potentielle

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-07-01

    This report proposes some quantitative elements to assess the large scale diffusion of electric vehicles and analyse the potential demand for such vehicles. The first part proposes a cost-benefit analysis of the development of electric vehicles based on estimated costs and expected benefits by 2020. It addresses the following issues: framework and hypothesis, total cost of ownership, costs related to the deployment of a network of recharging infrastructures, assessment of external costs, and comparative cost-benefit analysis of electric vehicles. In the second part, the authors aim at identifying a potential demand for electric vehicles from the 2008 French national transport displacement survey (ENTD 2008) which provides recent data on the mobility of the French population

  2. Driving Demand for Home Energy Improvements: Motivating residential customers to invest in comprehensive upgrades that eliminate energy waste, avoid high utility bills, and spur the economy

    Energy Technology Data Exchange (ETDEWEB)

    Fuller, Merrian C.

    2010-09-20

    Policy makers and program designers in the U.S. and abroad are deeply concerned with the question of how to scale up energy efficiency to a level that is commensurate both to the scale of the energy and climate challenges we face, and to the potential for energy savings that has been touted for decades. When policy makers ask what energy efficiency can do, the answers usually revolve around the technical and economic potential of energy efficiency - they rarely hone in on the element of energy demand that matters most for changing energy usage in existing homes: the consumer. A growing literature is concerned with the behavioral underpinnings of energy consumption. We examine a narrower, related subject: How can millions of Americans be persuaded to divert valued time and resources into upgrading their homes to eliminate energy waste, avoid high utility bills, and spur the economy? With hundreds of millions of public dollars flowing into incentives, workforce training, and other initiatives to support comprehensive home energy improvements, it makes sense to review the history of these programs and begin gleaning best practices for encouraging comprehensive home energy improvements. Looking across 30 years of energy efficiency programs that targeted the residential market, many of the same issues that confronted past program administrators are relevant today: How do we cost-effectively motivate customers to take action? Who can we partner with to increase program participation? How do we get residential efficiency programs to scale? While there is no proven formula - and only limited success to date with reliably motivating large numbers of Americans to invest in comprehensive home energy improvements, especially if they are being asked to pay for a majority of the improvement costs - there is a rich and varied history of experiences that new programs can draw upon. Our primary audiences are policy makers and program designers - especially those that are relatively

  3. Generation adequacy report on the electricity supply-demand balance in France. 2016 edition + executive summary

    International Nuclear Information System (INIS)

    2016-01-01

    After a presentation of the elaboration framework of this generation adequacy report, and of the objectives of the risk analysis, this report proposes a detailed analysis of electricity consumption in France. It describes the main determining factors of electric power consumption: energy efficiency, economic growth, demography, and transfers and new uses of electricity. It proposes a sector-based analysis of energy demand (housing sector, office building sector, industrial sector, transport, energy and agriculture sectors), and an assessment of perspectives for power consumption. It also proposes a power-based analysis of electricity consumption: influence of temperature on electricity consumption, analysis of the load curve, perspectives for electricity consumption peak. The next part addresses the evolution of electricity supply in France. It presents the existing production fleet, proposes an overview of renewable energies (ground-based wind energy, offshore wind energy and marine energies, solar photovoltaic energy, bio-energies, hydraulic energy), presents some characteristics of the French nuclear fleet (installed capacity, availability), analyses the flame-based thermal fleet (oil-based, coal-based, gas-based combined, combustion turbine, and decentralised thermal installations). It also discusses the issue of load management, and proposes a synthetic overview of the electricity production fleet (supply evolutions on the medium term, evolutions with respect to the 2015 provisional assessment). The next chapter reports a risk analysis on the medium term by presenting indicators of supply safety, by proposing a failure risk analysis (diagnosis on the medium term, comparison with the previous provisional assessment, sensitivity to extreme events), by presenting energy assessments, by reporting sensitivity analysis (to consumption hypotheses, to hypotheses related to the development of renewable energies, to hypotheses related to the nuclear fleet), by reporting

  4. Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

    Directory of Open Access Journals (Sweden)

    O. V. Russkov

    2015-01-01

    Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost

  5. A high-resolution stochastic model of domestic activity patterns and electricity demand

    International Nuclear Information System (INIS)

    Widen, Joakim; Waeckelgard, Ewa

    2010-01-01

    Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings' indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.

  6. Machine Learning for Identifying Demand Patterns of Home Energy Management Systems with Dynamic Electricity Pricing

    Directory of Open Access Journals (Sweden)

    Derck Koolen

    2017-11-01

    Full Text Available Energy management plays a crucial role in providing necessary system flexibility to deal with the ongoing integration of volatile and intermittent energy sources. Demand Response (DR programs enhance demand flexibility by communicating energy market price volatility to the end-consumer. In such environments, home energy management systems assist the use of flexible end-appliances, based upon the individual consumer’s personal preferences and beliefs. However, with the latter heterogeneously distributed, not all dynamic pricing schemes are equally adequate for the individual needs of households. We conduct one of the first large scale natural experiments, with multiple dynamic pricing schemes for end consumers, allowing us to analyze different demand behavior in relation with household attributes. We apply a spectral relaxation clustering approach to show distinct groups of households within the two most used dynamic pricing schemes: Time-Of-Use and Real-Time Pricing. The results indicate that a more effective design of smart home energy management systems can lead to a better fit between customer and electricity tariff in order to reduce costs, enhance predictability and stability of load and allow for more optimal use of demand flexibility by such systems.

  7. Controlling market power and price spikes in electricity networks: Demand-side bidding.

    Science.gov (United States)

    Rassenti, Stephen J; Smith, Vernon L; Wilson, Bart J

    2003-03-04

    In this article we report an experiment that examines how demand-side bidding can discipline generators in a market for electric power. First we develop a treatment without demand-side bidding; two large firms are allocated baseload and intermediate cost generators such that either firm might unilaterally withhold the capacity of its intermediate cost generators from the market to benefit from the supracompetitive prices that would result from only selling its baseload units. In a converse treatment, ownership of some of the intermediate cost generators is transferred from each of these firms to two other firms such that no one firm could unilaterally restrict output to spawn supracompetitive prices. Having established a well controlled data set with price spikes paralleling those observed in the naturally occurring economy, we also extend the design to include demand-side bidding. We find that demand-side bidding completely neutralizes the exercise of market power and eliminates price spikes even in the presence of structural market power.

  8. Generation adequacy report on the electricity supply-demand balance in France. 2015 edition + executive summary

    International Nuclear Information System (INIS)

    2016-01-01

    France's new energy transition law for green growth takes effect in 2015, and it will support RTE in its task of assessing and analysing security of electricity supply. Indeed, RTE is required by law to periodically publish Generation Adequacy Reports on the balance between electricity supply and demand. This year's report will be used in security of supply analyses conducted as part of the planning of the next multi-annual energy program. Another highlight of 2015 is the operational implementation of the capacity mechanism. Electricity suppliers now have to contribute to security of supply in proportion to their customers' consumption via a new obligation-based system. The 2015 Generation Adequacy Report was prepared within this context. The supply-demand balance outlook is considerably better over the entire medium-term horizon than in the 2014 Generation Adequacy Report. This is a result of generators' recent decisions to keep oil-fired and combined-cycle gas plants in the market. Included in the possible courses of action RTE identified in its previous Generation Adequacy Report, these decisions were taken just as the capacity mechanism was being implemented operationally. A downward revision of demand assumptions has also improved the security of supply outlook. The 2015 Generation Adequacy Report paints a much more favourable picture of the supply-demand balance over the next five years than the previous edition. Significant margins are foreseen during the next two winters. This year's Generation Adequacy Report also includes detailed assumptions about the evolution of the European mix, which will play an increasingly important role in guaranteeing security of supply in France. Indeed, interconnections will help reduce the shortfall risk by 8 to 10 GW over the next five winters. Lastly, a new chapter about flexibility requirements and the variability of residual demand associated with the growing share of renewable generation in the

  9. Survey of electric utility demand for coal. [1972-1992; by utility and state

    Energy Technology Data Exchange (ETDEWEB)

    Asbury, J.G.; Caruso, J.V.; Kouvalis, A.; Maslowski, C.S.

    1979-08-01

    This report presents the results of a survey of electric utility demand for coal in the United States. The sources of survey information are: (1) Federal Energy Regulatory Commission Form 423 data on utility coal purchases during the period July 1972 through December 1978 and (2) direct telephone survey data on utility coal-purchase intentions for power plants to be constructed by 1992. Price and quantity data for coal used in existing plants are presented to illustrate price and market-share trends in individual coal-consuming states during recent years. Coal source, quality, quantity, and transportation data are reported for existing and planned generating plants.

  10. Modeling Demand Response in Electricity Retail Markets as a Stackelberg Game

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre

    We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price-sequence, w......We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price...... with Equilibrium Constraints (MPEC) and cast as a Mixed Integer Linear Program (MILP), which can be solved using off-the-shelf optimization software. In an illustrative example, we consider a retailer associated with both flexible demand and wind power production. Such an example shows the efficiency of dynamic...

  11. Customer-economics of residential photovoltaic systems (Part 1): The impact of high renewable energy penetrations on electricity bill savings with net metering

    International Nuclear Information System (INIS)

    Darghouth, Naïm R.; Barbose, Galen; Wiser, Ryan H.

    2014-01-01

    Residential photovoltaic (PV) systems in the US are often compensated at the customer's underlying retail electricity rate through net metering. Given the uncertainty in future retail rates and the inherent links between rates and the customer–economics of behind-the-meter PV, there is growing interest in understanding how potential changes in rates may impact the value of bill savings from PV. In this article, we first use a production cost and capacity expansion model to project California hourly wholesale electricity market prices under two potential electricity market scenarios, including a reference and a 33% renewables scenario. Second, based on the wholesale electricity market prices generated by the model, we develop retail rates (i.e., flat, time-of-use, and real-time pricing) for each future scenario based on standard retail rate design principles. Finally, based on these retail rates, the bill savings from PV is estimated for 226 California residential customers under two types of net metering, for each scenario. We find that high renewable penetrations can drive substantial changes in residential retail rates and that these changes, together with variations in retail rate structures and PV compensation mechanisms, interact to place substantial uncertainty on the future value of bill savings from residential PV. - Highlights: • We investigate the impact of high renewables on customer economics of solar. • We model three types of residential retail electricity rates. • Based on the rates, we calculate the bill savings from photovoltaic (PV) generation. • High renewables penetration can lead to lower bill savings with time-varying rates. • There is substantial uncertainty in the future bill savings from residential PV

  12. Natural graphite demand and supply - Implications for electric vehicle battery requirements

    Science.gov (United States)

    Olson, Donald W.; Virta, Robert L.; Mahdavi, Mahbood; Sangine, Elizabeth S.; Fortier, Steven M.

    2016-01-01

    Electric vehicles have been promoted to reduce greenhouse gas emissions and lessen U.S. dependence on petroleum for transportation. Growth in U.S. sales of electric vehicles has been hindered by technical difficulties and the high cost of the lithium-ion batteries used to power many electric vehicles (more than 50% of the vehicle cost). Groundbreaking has begun for a lithium-ion battery factory in Nevada that, at capacity, could manufacture enough batteries to power 500,000 electric vehicles of various types and provide economies of scale to reduce the cost of batteries. Currently, primary synthetic graphite derived from petroleum coke is used in the anode of most lithium-ion batteries. An alternate may be the use of natural flake graphite, which would result in estimated graphite cost reductions of more than US$400 per vehicle at 2013 prices. Most natural flake graphite is sourced from China, the world's leading graphite producer. Sourcing natural flake graphite from deposits in North America could reduce raw material transportation costs and, given China's growing internal demand for flake graphite for its industries and ongoing environmental, labor, and mining issues, may ensure a more reliable and environmentally conscious supply of graphite. North America has flake graphite resources, and Canada is currently a producer, but most new mining projects in the United States require more than 10 yr to reach production, and demand could exceed supplies of flake graphite. Natural flake graphite may serve only to supplement synthetic graphite, at least for the short-term outlook.

  13. Research on industrialization of electric vehicles with its demand forecast using exponential smoothing method

    Directory of Open Access Journals (Sweden)

    Zhanglin Peng

    2015-04-01

    Full Text Available Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the development of EVs industrialization in the developing countries. This paper seeks to research the industrialization path & prospect of American EVs by forecasting electric vehicles demand and its proportion to the whole car sales based on the historical 37 EVs monthly sales and Cars monthly sales spanning from Dec. 2010 to Dec. 2013, and find out the key measurements to help Chinese government and automobile enterprises to promote Chinese EVs industrialization. Design/methodology: Compared with Single Exponential Smoothing method and Double Exponential Smoothing method, Triple exponential smoothing method is improved and applied in this study. Findings: The research results show that:  American EVs industry will keep a sustained growth in the next 3 months.  Price of the EVs, price of fossil oil, number of charging station, EVs technology and the government market & taxation polices have a different influence to EVs sales. So EVs manufacturers and policy-makers can adjust or reformulate some technology tactics and market measurements according to the forecast results. China can learn from American EVs polices and measurements to develop Chinese EVs industry. Originality/value: The main contribution of this paper is to use the triple exponential smoothing method to forecast the electric vehicles demand and its proportion to the whole automobile sales, and analyze the industrial development of Chinese electric vehicles by American EVs industry.

  14. Forecasting Monthly Electricity Demands by Wavelet Neuro-Fuzzy System Optimized by Heuristic Algorithms

    Directory of Open Access Journals (Sweden)

    Jeng-Fung Chen

    2018-02-01

    Full Text Available Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate planning and prediction of electricity load are therefore vital. In this study, a novel approach for forecasting monthly electricity demands by wavelet transform and a neuro-fuzzy system is proposed. Firstly, the most appropriate inputs are selected and a dataset is constructed. Then, Haar wavelet transform is utilized to decompose the load data and eliminate noise. In the model, a hierarchical adaptive neuro-fuzzy inference system (HANFIS is suggested to solve the curse-of-dimensionality problem. Several heuristic algorithms including Gravitational Search Algorithm (GSA, Cuckoo Optimization Algorithm (COA, and Cuckoo Search (CS are utilized to optimize the clustering parameters which help form the rule base, and adaptive neuro-fuzzy inference system (ANFIS optimize the parameters in the antecedent and consequent parts of each sub-model. The proposed approach was applied to forecast the electricity load of Hanoi, Vietnam. The constructed models have shown high forecasting performances based on the performance indices calculated. The results demonstrate the validity of the approach. The obtained results were also compared with those of several other well-known methods including autoregressive integrated moving average (ARIMA and multiple linear regression (MLR. In our study, the wavelet CS-HANFIS model outperformed the others and provided more accurate forecasting.

  15. Grid-tied photovoltaic and battery storage systems with Malaysian electricity tariff:A review on maximum demand shaving

    OpenAIRE

    Subramani, Gopinath; Ramachandaramurthy, Vigna K.; Padmanaban, Sanjeevikumar; Mihet-Popa, Lucian; Blaabjerg, Frede; Guerrero, Josep M.

    2017-01-01

    Under the current energy sector framework of electricity tariff in Malaysia, commercial and industrial customers are required to pay the maximum demand (MD) charge apart from the net consumption charges every month. The maximum demand charge will contribute up to 20% of the electricity bill, and will hence result in commercial and industrial customers focussing on alternative energy supply to minimize the billing cost. This paper aims to review the technical assessment methods of a grid-conne...

  16. Mitigating the Impacts of Uncontrolled Air Flow on Indoor Environmental Quality and Energy Demand in Non-Residential Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Hugh I. Henderson; Jensen Zhang; James B. Cummings; Terry Brennan

    2006-07-31

    This multi-faceted study evaluated several aspects of uncontrolled air flows in commercial buildings in both Northern and Southern climates. Field data were collected from 25 small commercial buildings in New York State to understand baseline conditions for Northern buildings. Laboratory wall assembly testing was completed at Syracuse University to understand the impact of typical air leakage pathways on heat and moisture transport within wall assemblies for both Northern and Southern building applications. The experimental data from the laboratory tests were used to verify detailed heat and moisture (HAM) simulation models that could be used to evaluate a wider array of building applications and situations. Whole building testing at FSEC's Building Science Laboratory (BSL) systematically evaluated the energy and IAQ impacts of duct leakage with various attic and ceiling configurations. This systematic test carefully controlled all aspects of building performance to quantify the impact of duct leakage and unbalanced flow. The newest features of the EnergyPlus building simulation tool were used to model the combined impacts of duct leakage, ceiling leakage, unbalanced flows, and air conditioner performance. The experimental data provided the basis to validate the simulation model so it could be used to study the impact of duct leakage over a wide range of climates and applications. The overall objective of this project was to transfer work and knowledge that has been done on uncontrolled air flow in non-residential buildings in Florida to a national basis. This objective was implemented by means of four tasks: (1) Field testing and monitoring of uncontrolled air flow in a sample of New York buildings; (2) Detailed wall assembly laboratory measurements and modeling; (3) Whole building experiments and simulation of uncontrolled air flows; and (4) Develop and implement training on uncontrolled air flows for Practitioners in New York State.

  17. Electricity Demand Projection Using a Path-Coefficient Analysis and BAG-SA Approach: A Case Study of China

    Directory of Open Access Journals (Sweden)

    Qunli Wu

    2017-01-01

    Full Text Available Path-coefficient analysis is utilized to investigate the direct and indirect effects of economic growth, population growth, urbanization rate, industrialization level, and carbon intensity on electricity demand of China. To improve the projection accuracy of electricity demand, this study proposes a hybrid bat algorithm, Gaussian perturbations, and simulated annealing (BAG-SA optimization method. The proposed BAG-SA algorithm not only inherits the simplicity and efficiency of the standard BA with a capability of searching for global optimality but also enhances local search ability and speeds up the global convergence rate. The BAG-SA algorithm is employed to optimize the coefficients of the multiple linear and quadratic forms of electricity demand estimation model. Results indicate that the proposed algorithm has higher precision and reliability than the coefficients optimized by other single-optimization methods, such as genetic algorithm, particle swarm optimization algorithm, or bat algorithm. And the quadratic form of BAG-SA electricity demand estimation model has better fitting ability compared with the multiple linear form of the model. Therefore, the quadratic form of the model is applied to estimate electricity demand of China from 2016 to 2030. The findings of this study demonstrate that China’s electricity demand will reach 14925200 million KWh in 2030.

  18. Determining optimal interconnection capacity on the basis of hourly demand and supply functions of electricity

    International Nuclear Information System (INIS)

    Keppler, Jan Horst; Meunier, William; Coquentin, Alexandre

    2017-01-01

    Interconnections for cross-border electricity flows are at the heart of the project to create a common European electricity market. At the time, increase in production from variable renewables clustered during a limited numbers of hours reduces the availability of existing transport infrastructures. This calls for higher levels of optimal interconnection capacity than in the past. In complement to existing scenario-building exercises such as the TYNDP that respond to the challenge of determining optimal levels of infrastructure provision, the present paper proposes a new empirically-based methodology to perform Cost-Benefit analysis for the determination of optimal interconnection capacity, using as an example the French-German cross-border trade. Using a very fine dataset of hourly supply and demand curves (aggregated auction curves) for the year 2014 from the EPEX Spot market, it constructs linearized net export (NEC) and net import demand curves (NIDC) for both countries. This allows assessing hour by hour the welfare impacts for incremental increases in interconnection capacity. Summing these welfare increases over the 8 760 hours of the year, this provides the annual total for each step increase of interconnection capacity. Confronting welfare benefits with the annual cost of augmenting interconnection capacity indicated the socially optimal increase in interconnection capacity between France and Germany on the basis of empirical market micro-data. (authors)

  19. Modeling the Capacity and Emissions Impacts of Reduced Electricity Demand. Part 1. Methodology and Preliminary Results

    Energy Technology Data Exchange (ETDEWEB)

    Coughlin, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Shen, Hongxia [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Chan, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; McDevitt, Brian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Sturges, Andrew [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division

    2013-02-07

    Policies aimed at energy conservation and efficiency have broad environmental and economic impacts. Even if these impacts are relatively small, they may be significant compared to the cost of implementing the policy. Methodologies that quantify the marginal impacts of reduced demand for energy have an important role to play in developing accurate measures of both the benefits and costs of a given policy choice. This report presents a methodology for estimating the impacts of reduced demand for electricity on the electric power sector as a whole. The approach uses the National Energy Modeling System (NEMS), a mid-range energy forecast model developed and maintained by the U.S. Department of Energy, Energy Information Administration (EIA)(DOE EIA 2013). The report is organized as follows: In the rest of this section the traditional NEMS-BT approach is reviewed and an outline of the new reduced form NEMS methodology is presented. Section 2 provides an overview of how the NEMS model works, and describes the set of NEMS-BT runs that are used as input to the reduced form approach. Section 3 presents our NEMS-BT simulation results and post-processing methods. In Section 4 we show how the NEMS-BT output can be generalized to apply to a broader set of end-uses. In Section 5 we disuss the application of this approach to policy analysis, and summarize some of the issues that will be further investigated in Part 2 of this study.

  20. Integrating Demand-Side Resources into the Electric Grid: Economic and Environmental Considerations

    Science.gov (United States)

    Fisher, Michael J.

    Demand-side resources are taking an increasingly prominent role in providing essential grid services once provided by thermal power plants. This thesis considers the economic feasibility and environmental effects of integrating demand-side resources into the electric grid with consideration given to the diversity of market and environmental conditions that can affect their behavior. Chapter 2 explores the private economics and system-level carbon dioxide reduction when using demand response for spinning reserve. Steady end uses like lighting are more than twice as profitable as seasonal end uses because spinning reserve is needed year-round. Avoided carbon emission damages from using demand response instead of fossil fuel generation for spinning reserve are sufficient to justify incentives for demand response resources. Chapter 3 quantifies the system-level net emissions rate and private economics of behind-the-meter energy storage. Net emission rates are lower than marginal emission rates for power plants and in-line with estimates of net emission rates from grid-level storage. The economics are favorable for many buildings in regions with high demand charges like California and New York, even without subsidies. Future penetration into regions with average charges like Pennsylvania will depend greatly on installation cost reductions and wholesale prices for ancillary services. Chapter 4 outlines a novel econometric model to quantify potential revenues from energy storage that reduces demand charges. The model is based on a novel predictive metric that is derived from the building's load profile. Normalized revenue estimates are independent of the power capacity of the battery holding other performance characteristics equal, which can be used to calculate the profit-maximizing storage size. Chapter 5 analyzes the economic feasibility of flow batteries in the commercial and industrial market. Flow batteries at a 4-hour duration must be less expensive on a dollar per

  1. An analysis of the factors influencing demand-side management activity in the electric utility industry

    Science.gov (United States)

    Bock, Mark Joseph

    Demand-side management (DSM), defined as the "planning, implementation, and monitoring of utility activities designed to encourage consumers to modify their pattern of electricity usage, including the timing and level of electricity demand," is a relatively new concept in the U.S. electric power industry. Nevertheless, in twenty years since it was first introduced, utility expenditures on DSM programs, as well as the number of such programs, have grown rapidly. At first glance, it may seem peculiar that a firm would actively attempt to reduce demand for its primary product. There are two primary explanations as to why a utility might pursue DSM: regulatory mandate, and self-interest. The purpose of this dissertation is to determine the impact these influences have on the amount of DSM undertaken by utilities. This research is important for two reasons. First, it provides insight into whether DSM will continue to exist as competition becomes more prevalent in the industry. Secondly, it is important because no one has taken a comprehensive look at firm-level DSM activity on an industry-wide basis. The primary data set used in this dissertation is the U.S. Department of Energy's Annual Electric Utility Report, Form EIA-861, which represents the most comprehensive data set available for analyzing DSM activity in the U.S. There are four measures of DSM activity in this data set: (1) utility expenditures on DSM programs; (2) energy savings by DSM program participants; and (3) the actual and (4) the potential reductions in peak load resulting from utility DSM measures. Each is used as the dependent variable in an econometric analysis where independent variables include various utility characteristics, regulatory characteristics, and service territory and customer characteristics. In general, the results from the econometric analysis suggest that in 1993, DSM activity was primarily the result of regulatory pressure. All of the evidence suggests that if DSM continues to

  2. Regional electric power demand elasticities of Japan's industrial and commercial sectors

    International Nuclear Information System (INIS)

    Hosoe, Nobuhiro; Akiyama, Shu-ichi

    2009-01-01

    In the assessment and review of regulatory reforms in the electric power market, price elasticity is one of the most important parameters that characterize the market. However, price elasticity has seldom been estimated in Japan; instead, it has been assumed to be as small as 0.1 or 0 without proper examination of the empirical validity of such a priori assumptions. We estimated the regional power demand functions for nine regions, in order to quantify the elasticity, and found the short-run price elasticity to be 0.09-0.30 and the long-run price elasticity to be 0.12-0.56. Inter-regional comparison of our estimation results suggests that price elasticity in rural regions is larger than that in urban regions. Popular assumptions of small elasticity of 0.1, for example, could be suitable for examining Japan's aggregate power demand but not power demand functions that focus on respective regions. Furthermore, assumptions about smaller elasticity values such as 0.01 and 0 could not be supported statistically by this study.

  3. Electric power of residential photovoltaic power system; Jutakuyo taiyoko hatsuden system no hatsudenryo

    Energy Technology Data Exchange (ETDEWEB)

    Asano, K.; Kawamura, H.; Yamanaka, S.; Kawamura, H.; Ono, H.; Hayashi, K.; Naganawa, H. [Meijo University, Nagoya (Japan); Asai, H.

    1996-10-27

    Measurement was done on the annual power generation of a residential photovoltaic power system that was most suitable for the present situation in utilizing solar energy; and an examination was made on the basis of the data of a module in which an optimal operation load control was separately installed in order to operate the system more effectively. As a result, it was found that the introduction of a 3kW class system was currently most desirable as a residential photovoltaic power system, and that the problem of the optimal operation load control was crucial for the more efficient power generation. The resistance value of the optimal operation load was stable between 6 and 8 ohm in the daytime in fine weather. However, it was observed that, where no sufficient insolation was expected, the optimal operation load was ten times as much as in fine weather, being easily influenced by the environmental elements. In addition, it was revealed that, if the operation load was fixed at a specific value (6 ohm) in a clear day, the power generation was only about 85% compared with the case of controlling the optimal operation load. This figure was obtained under comparatively favorable conditions, however. 8 refs., 7 figs.

  4. Stopping coal-fired electricity imports on smog days : a review of the OPA's proposed 250 MW demand response program

    International Nuclear Information System (INIS)

    Gibbons, J.

    2006-01-01

    This paper proposed an alternative to importing coal-fired electricity from the Ohio Valley on smog alert days in Ontario. It was suggested that the Ontario Power Authority (OPA) should pay large electricity consumers to shift some of their consumption from peak to off-peak hours. It was observed that demand response programs which pay consumers to shift demands to off-peak hours can provide multiple benefits to Ontario, including reduced air pollution on smog-alert days, a reduction in the spot price of electricity and reduced price volatility. In addition, demand response programs reduce the risk of blackouts and brownouts, as well as the need for new electricity generation and transmission infrastructure. It was noted that the Independent Electricity System Operator (IESO) and the OPA are planning to introduce demand response programs for the summer of 2006. However, the IESO's emergency load reduction program will be operated only during emergency situations to avoid the need for voltage reductions, while the OPA proposes to introduce a non-emergency demand response program which will be activated during most smog-alert days. Various amendments to the proposed program were suggested in this paper, including the establishment of price parity with coal-fired electricity imports; the provision of notification by 3 PM of the need for demand reductions the following day; no capping on the quantity of demand reductions that the OPA will purchase at a lower cost than electricity imports; and that the OPA's proposed Capacity Building Demand Response Program should proceed as quickly as possible without a pre-determined MW cap. 4 refs., 6 figs

  5. Paying the full cost of power : an indicative comparative analysis of residential electricity rates across Canadian provinces

    International Nuclear Information System (INIS)

    Goulding, A.J.; Sabatier, G.

    2005-01-01

    This study was commissioned to review electricity rates charged to residential consumers across Canada and to determine how the basics of ratemaking change from province to province. Rates in each province vary significantly due to differences in the industry structure and their resource base. It was noted that direct comparisons are difficult because some rates reflect the financing, fuel and opportunity costs of power. For that reason, a simple adjustment factor was developed for fair comparison between jurisdictions. This assessment compared the all-in cost to final consumers which includes power generation, transmission, distribution and all other charges, as calculated by Statistics Canada. It was revealed that Alberta is Canada's only province where prices to final consumers reflect the market value of the underlying commodity. Ratepayers have the advantage of not being responsible for bad investment choices in the power sector and there are no hidden subsidies due to provincial ownership of power resources. Another consumer advantage is that they receive appropriate price signals in terms of energy consumption and conservation. This report suggests that low electricity rates in other provinces can be expected to rise much more rapidly than those in Alberta in the coming decade as consumers may be charged the full value of the electricity they use. 18 refs., 9 figs

  6. Learning Residential Electrical Wiring through Computer Simulation: The Impact of Computer-Based Learning Environments on Student Achievement and Cognitive Load

    Science.gov (United States)

    Liu, Han-Chin; Su, I-Hsien

    2011-01-01

    Multimedia learning environments such as computer simulations are widely accepted as tools for supporting science learning. Although the design of multimedia learning environments can be domain specific, few studies have focused on the use of computer simulations for learning residential electrical wiring. This study aimed to determine whether…

  7. Improved estimation of electricity demand function by integration of fuzzy system and data mining approach

    International Nuclear Information System (INIS)

    Azadeh, A.; Saberi, M.; Ghaderi, S.F.; Gitiforouz, A.; Ebrahimipour, V.

    2008-01-01

    This study presents an integrated fuzzy system, data mining and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy system or time series and the integrated algorithm could be an ideal substitute for such cases. To construct fuzzy systems, a rule base is needed. Because a rule base is not available, for the case of demand function, look up table which is one of the extracting rule methods is used to extract the rule base. This system is defined as FLT. Also, decision tree method which is a data mining approach is similarly utilized to extract the rule base. This system is defined as FDM. Preferred time series model is selected from linear (ARMA) and nonlinear model. For this, after selecting preferred ARMA model, McLeod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, preferred nonlinear model is selected and compare with preferred ARMA model and finally one of this is selected as time series model. At last, ANOVA is used for selecting preferred model from fuzzy models and time series model. Also, the impact of data preprocessing and postprocessing on the fuzzy system performance is considered by the algorithm. In addition, another unique feature of the proposed algorithm is utilization of autocorrelation function (ACF) to define input variables, whereas conventional methods which use trial and error method. Monthly electricity consumption of Iran from 1995 to 2005 is considered as the case of this study. The MAPE estimation of genetic algorithm (GA), artificial neural network (ANN) versus the proposed algorithm shows the appropriateness of the proposed algorithm

  8. Comparison of a Constant Air Volume (CAV) and a Demand Controlled Ventilation (DCV) System in a Residential Building

    DEFF Research Database (Denmark)

    Mortensen, Dorthe Kragsig; Nielsen, Toke Rammer; Topp, Claus

    2008-01-01

    The aim of this paper was to compare the indoor climate and the energy performance of a Constant Air Volume (CAV) system of 0.5h-1 with a Demand Controlled Ventilation (DCV) system controlled by occupancy and relative humidity for a studio apartment. Furthermore the impact of building materials...... it was found that the energy consumption for heating and operating the ventilation system could be reduced by respectively 8.0% and 10.6 % in the case of DCV without negative impact on the indoor climate. Including the hygroscopic properties of the materials resulted in a reduction of the energy consumption...... for heating and operating the ventilation system by respectively 9.5% and 17.1 % in favour of the DCV system....

  9. A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility.

    Science.gov (United States)

    Mureddu, Mario; Facchini, Angelo; Scala, Antonio; Caldarelli, Guido; Damiano, Alfonso

    2018-01-10

    We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas.

  10. Determinants of electricity demand for newly electrified low-income African households

    International Nuclear Information System (INIS)

    Louw, Kate; Conradie, Beatrice; Howells, Mark; Dekenah, Marcus

    2008-01-01

    Access to clean, affordable and appropriate energy is an important enabler of development. Energy allows households to meet their most basic subsistence needs; it is a central feature of all the millennium development goals (MDGs) and, while a lack of access to energy may not be a cause of poverty, addressing the energy needs of the impoverished lets them access services which in turn address the causes of poverty. While much is known about the factors affecting the decisions made when choosing between fuel types within a household, few quantitative studies have been carried out in South Africa to determine the extent to which these factors affect energy choice decisions. It is assumed that the factors traditionally included in economic demand such as price and income of the household affect choice; tastes and preferences as well as external factors such as distance to fuel suppliers are expected to influence preferences. This study follows two typical low-income rural sites in South Africa, Antioch and Garagapola, where the Electricity Basic Services Support Tariff (EBSST) was piloted in 2002. The EBSST is set at 50 kWh/month per household for low domestic consumers; this is worth approximately R20 (±US$3). This subsidy is a lifeline tariff, where households receive the set amount of units per month, free of charge irrespective of whether more units are purchased. These data (collected in 2001 and 2002), recently collated with detailed electricity consumption data, allow us to determine the drivers of electricity consumption within these households. The sample analysed is taken from the initial phase of the study, when no FBE had been introduced to the households. This enabled the study presented here to make use of the well-populated datasets to assess what affects the electricity use decision in these households. This paper attempts to assess which factors affected the decision-making process for electricity consumption within these households. A brief history

  11. The opening of electricity and gas markets to residential customers. Annual barometer - First wave. December 2007

    International Nuclear Information System (INIS)

    2007-01-01

    Since July 1, 2007, French residential customers can freely chose their energy supplier. A quantitative inquiry has been carried out by LH2 on behalf of the French Energy Regulatory Commission (CRE) on a sample of 1501 households representative of the overall French households. The aim of this barometer is to answer the following questions: what is the level of knowledge and information of individuals about the opening of energy markets and the new regulation in force? How do they perceive this opening? What is their behaviour in front of the opening of markets to competition? Four years after the full opening of energy markets, this first inquiry has permitted to draw up a first status of the knowledge, behaviour and opinion of individuals with respect to the opening of these markets. (J.S.)

  12. Residential heat pumps in the future Danish energy system

    DEFF Research Database (Denmark)

    Petrovic, Stefan; Karlsson, Kenneth Bernard

    2016-01-01

    Denmark is striving towards 100% renewable energy system in 2050. Residential heat pumps are expected to be a part of that system.We propose two novel approaches to improve the representation of residential heat pumps: Coefficients of performance (COPs) are modelled as dependent on air and ground...... temperature while installation of ground-source heat pumps is constrained by available ground area. In this study, TIMES-DK model is utilised to test the effects of improved modelling of residential heat pumps on the Danish energy system until 2050.The analysis of the Danish energy system was done...... for politically agreed targets which include: at least 50% of electricity consumption from wind power starting from 2020, fossil fuel free heat and power sector from 2035 and 100% renewable energy system starting from 2050. Residential heat pumps supply around 25% of total residential heating demand after 2035...

  13. Assessing the influence of manufacturing sectors on electricity demand. A cross-country input-output approach

    Energy Technology Data Exchange (ETDEWEB)

    Tarancon, Miguel Angel; Callejas Albinana, Fernando [Faculty of Law and Social Sciences, Universidad de Castilla - La Mancha, Ronda de Toledo s/n, 13071 Ciudad Real (Spain); Del Rio, Pablo [Institute for Public Policies and Goods (IPP), Centro de Ciencias Humanas y Sociales, CSIC, C/Albasanz 26-28, 28037 Madrid (Spain)

    2010-04-15

    The production and consumption of electricity is a major source of CO{sub 2} emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input-output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price. (author)

  14. Density prediction and dimensionality reduction of mid-term electricity demand in China: A new semiparametric-based additive model

    International Nuclear Information System (INIS)

    Shao, Zhen; Yang, Shan-Lin; Gao, Fei

    2014-01-01

    Highlights: • A new stationary time series smoothing-based semiparametric model is established. • A novel semiparametric additive model based on piecewise smooth is proposed. • We model the uncertainty of data distribution for mid-term electricity forecasting. • We provide efficient long horizon simulation and extraction for external variables. • We provide stable and accurate density predictions for mid-term electricity demand. - Abstract: Accurate mid-term electricity demand forecasting is critical for efficient electric planning, budgeting and operating decisions. Mid-term electricity demand forecasting is notoriously complicated, since the demand is subject to a range of external drivers, such as climate change, economic development, which will exhibit monthly, seasonal, and annual complex variations. Conventional models are based on the assumption that original data is stable and normally distributed, which is generally insignificant in explaining actual demand pattern. This paper proposes a new semiparametric additive model that, in addition to considering the uncertainty of the data distribution, includes practical discussions covering the applications of the external variables. To effectively detach the multi-dimensional volatility of mid-term demand, a novel piecewise smooth method which allows reduction of the data dimensionality is developed. Besides, a semi-parametric procedure that makes use of bootstrap algorithm for density forecast and model estimation is presented. Two typical cases in China are presented to verify the effectiveness of the proposed methodology. The results suggest that both meteorological and economic variables play a critical role in mid-term electricity consumption prediction in China, while the extracted economic factor is adequate to reveal the potentially complex relationship between electricity consumption and economic fluctuation. Overall, the proposed model can be easily applied to mid-term demand forecasting, and