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Sample records for residential electrical demand

  1. Residential electricity demand in Singapore

    International Nuclear Information System (INIS)

    Ang, B.W.; Goh, T.N.; Liu, X.Q.

    1992-01-01

    Residential electricity consumption in Singapore increased at a rate of 8.8% per year between 1972 and 1990. Estimates of the long-run income and price elasticities are 1.0 and -0.35, respectively. The energy-conservation campaigns that have been launched are found to have marginal effects on consumption. A statistical analysis shows that the consumption is sensitive to small changes in climatic variables, particularly the temperature, which is closely linked to the growing diffusion of electric appliances for environmental controls. There has been a temporal increase in the ownership levels of appliances associated with increasing household incomes. However, other factors were involved since the ownership levels would also increase over time after the elimination of the income effect. A large part of the future growth in electricity demand will arise from the growing need for air-conditioning, which will lead to increasingly large seasonal variations in electricity use. (author)

  2. 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.

  3. 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.

  4. 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.

  5. Electricity demand for South Korean residential sector

    Energy Technology Data Exchange (ETDEWEB)

    Sa' ad, Suleiman [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

    2009-12-15

    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. (author)

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. Meeting residential space heating demand with wind-generated electricity

    International Nuclear Information System (INIS)

    Hughes, Larry

    2010-01-01

    Worldwide, many electricity suppliers are faced with the challenge of trying to integrate intermittent renewables, notably wind, into their energy mix to meet the needs of those services that require a continuous supply of electricity. Solutions to intermittency include the use of rapid-response backup generation and chemical or mechanical storage of electricity. Meanwhile, in many jurisdictions with lengthy heating seasons, finding secure and preferably environmentally benign supplies of energy for space heating is also becoming a significant challenge because of volatile energy markets. Most, if not all, electricity suppliers treat these twin challenges as separate issues: supply (integrating intermittent renewables) and demand (electric space heating). However, if space heating demand can be met from an intermittent supply of electricity, then both of these issues can be addressed simultaneously. One such approach is to use off-the-shelf electric thermal storage systems. This paper examines the potential of this approach by applying the output from a 5.15 MW wind farm to the residential heating demands of detached households in the Canadian province of Prince Edward Island. The paper shows that for the heating season considered, up to 500 households could have over 95 percent of their space heating demand met from the wind farm in question. The benefits as well as the limitations of the approach are discussed in detail. (author)

  11. Market-based Demand Response via Residential Plug-in Electric Vehicles in Smart Grids

    OpenAIRE

    Rassaei, Farshad; Soh, Wee-Seng; Chua, Kee-Chaing

    2015-01-01

    Flexibility in power demand, diverse usage patterns and storage capability of plug-in electric vehicles (PEVs) grow the elasticity of residential electricity demand remarkably. This elasticity can be utilized to form the daily aggregated demand profile and/or alter instantaneous demand of a system wherein a large number of residential PEVs share one electricity retailer or an aggregator. In this paper, we propose a demand response (DR) technique to manage vehicle-to-grid (V2G) enabled PEVs' e...

  12. 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

  13. Residential demand response reduces air pollutant emissions on peak electricity demand days in New York City

    International Nuclear Information System (INIS)

    Gilbraith, Nathaniel; Powers, Susan E.

    2013-01-01

    Many urban areas in the United States have experienced difficulty meeting the National Ambient Air Quality Standards (NAAQS), partially due to pollution from electricity generating units. We evaluated the potential for residential demand response to reduce pollutant emissions on days with above average pollutant emissions and a high potential for poor air quality. The study focused on New York City (NYC) due to non-attainment with NAAQS standards, large exposed populations, and the existing goal of reducing pollutant emissions. The baseline demand response scenario simulated a 1.8% average reduction in NYC peak demand on 49 days throughout the summer. Nitrogen oxide and particulate matter less than 2.5 μm in diameter emission reductions were predicted to occur (−70, −1.1 metric tons (MT) annually), although, these were not likely to be sufficient for NYC to meet the NAAQS. Air pollution mediated damages were predicted to decrease by $100,000–$300,000 annually. A sensitivity analysis predicted that substantially larger pollutant emission reductions would occur if electricity demand was shifted from daytime hours to nighttime hours, or the total consumption decreased. Policies which incentivize shifting electricity consumption away from periods of high human and environmental impacts should be implemented, including policies directed toward residential consumers. - Highlights: • The impact of residential demand response on air emissions was modeled. • Residential demand response will decrease pollutant emissions in NYC. • Emissions reductions occur during periods with high potential for poor air quality. • Shifting demand to nighttime hours was more beneficial than to off-peak daytime hours

  14. Quantifying the Flexibility of Residential Electricity Demand in 2050: a Bottom-Up Approach

    OpenAIRE

    van Stiphout, Arne; Engels, Jonas; Guldentops, Dries; Deconinck, Geert

    2015-01-01

    This work presents a new method to quantify the flexibility of automatic demand response applied to residential electricity demand using price elasticities. A stochastic bottom-up model of flexible electricity demand in 2050 is presented. Three types of flexible devices are implemented: electrical heating, electric vehicles and wet appliances. Each house schedules its flexible demand w.r.t. a varying price signal, in order to minimize electricity cost. Own- and cross-price elasticities are ob...

  15. Smart electric storage heating and potential for residential demand response

    OpenAIRE

    Darby, S

    2017-01-01

    Low-carbon transition plans for temperate and sub-polar regions typically involve some electrification of space heating. This poses challenges to electricity system operation and market design, as it increases overall demand and alters the temporal patterns of that demand. One response to the challenge is to ‘smarten’ electrical heating, enabling it to respond to network conditions by storing energy at times of plentiful supply, releasing it in response to customer demands and offering rapid-...

  16. 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. (author)

  17. 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.

  18. 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.

  19. 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.

  20. 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.

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

    Science.gov (United States)

    Muratori, Matteo

    2018-03-01

    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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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)

  7. Introducing a demand-based electricity distribution tariff in the residential sector: Demand response and customer perception

    International Nuclear Information System (INIS)

    Bartusch, Cajsa; Wallin, Fredrik; Odlare, Monica; Vassileva, Iana; Wester, Lars

    2011-01-01

    Increased demand response is essential to fully exploit the Swedish power system, which in turn is an absolute prerequisite for meeting political goals related to energy efficiency and climate change. Demand response programs are, nonetheless, still exceptional in the residential sector of the Swedish electricity market, one contributory factor being lack of knowledge about the extent of the potential gains. In light of these circumstances, this empirical study set out with the intention of estimating the scope of households' response to, and assessing customers' perception of, a demand-based time-of-use electricity distribution tariff. The results show that households as a whole have a fairly high opinion of the demand-based tariff and act on its intrinsic price signals by decreasing peak demand in peak periods and shifting electricity use from peak to off-peak periods. - Highlights: → Households are sympathetic to demand-based tariffs, seeing as they relate to environmental issues. → Households adjust their electricity use to the price signals of demand-based tariffs. → Demand-based tariffs lead to a shift in electricity use from peak to off-peak hours. → Demand-based tariffs lead to a decrease in maximum demand in peak periods. → Magnitude of these effects increases over time.

  8. 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)

  9. 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

  10. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Alberini, Anna [Department of Agricultural Economics, University of Maryland (United States); Centre for Energy Policy and Economics (CEPE), ETH Zurich (Switzerland); Gibson Institute and Institute for a Sustainable World, School of Biological Sciences, Queen' s University Belfast, Northern Ireland (United Kingdom); Filippini, Massimo, E-mail: mfilippini@ethz.ch [Centre for Energy Policy and Economics (CEPE), ETH Zurich (Switzerland); Department of Economics, University of Lugano (Switzerland)

    2011-09-15

    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.

  12. 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)

  13. 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)

  14. 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.

  15. An analysis of a demand charge electricity grid tariff in the residential sector

    International Nuclear Information System (INIS)

    Stokke, A. V.; Doorman, G.L.; Ericson, T.

    2010-01-01

    This paper analyzes the demand response from residential electricity consumers to a demand charge grid tariff. The tariff charges the maximum hourly peak consumption in each of the winter months Dec, Jan, and Feb, thus giving incentives to reduce peak consumption. We use hourly electricity consumption data from 443 households, as well as data on their grid and power prices, the local temperature, wind speed, and hours of daylight. The panel data set is analyzed with a fixed effects regression model. The estimates indicate average demand reductions up to 0.37 kWh/h per household in response to the tariff. This is on average a 5% reduction, with a maximum reduction of 12% in hour 8 in Dec. The consumers did not receive any information on their continuous consumption or any reminders when the tariff was in effect. It is likely that the consumption reductions would have been even higher with more information to the consumers.

  16. 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

  17. 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

  18. 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.

  19. 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

  20. Impact Analysis of Customized Feedback Interventions on Residential Electricity Load Consumption Behavior for Demand Response

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2018-03-01

    Full Text Available Considering the limitations of traditional energy-saving policies, a kind of energy conservation method called the Information Feedback to Residential Electricity Load Customers, which could impact the demand response capacity, has increasingly received more attention. However, most of the current feedback programs provide the same feedback information to all customers regardless of their diverse characteristics, which may reduce the energy-saving effects or even backfire. This paper attempts to investigate how different types of customers may change their behaviors under a set of customized feedback. We conducted a field survey study in Qinhuangdao (QHD, China. First, we conducted semi-structured interviews to classify four groups of customers of different energy-saving awareness, energy-saving potential, and behavioral variability. Then, 156 QHD households were surveyed using scenarios to collect feedback of different scenarios. Social science theories were used to guide the discussion on the behavior changes as a result of different feedback strategies and reveal the reasons for customers’ behaviors. Using the Chi-Square test of independence, the variables that have strong correlations with the categories of residents are extracted to provide references for residents’ classification. Finally, the practical implications and needs for future research are discussed.

  1. 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

  2. Residential energy demand in Brazil

    International Nuclear Information System (INIS)

    Arouca, M.; Gomes, F.M.; Rosa, L.P.

    1981-01-01

    The energy demand in Brazilian residential sector is studied, discussing the methodology for analyzing this demand from some ideas suggested, for developing an adequate method to brazilian characteristics. The residential energy consumption of several fuels in Brazil is also presented, including a comparative evaluation with the United States and France. (author)

  3. 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

  4. 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.

  5. Responsiveness of residential electricity demand to dynamic tariffs : experiences from a large field test in the Netherlands

    NARCIS (Netherlands)

    Klaassen, E.A.M.; Kobus, C.B.A.; Frunt, J.; Slootweg, J.G.

    2016-01-01

    To efficiently facilitate the energy transition it is essential to evaluate the potential of demand response in practice. Based on the results of a Dutch smart grid pilot, this paper assesses the potential of both manual and semi-automated demand response in residential areas. To stimulate demand

  6. Responsiveness of residential electricity demand to dynamic tariffs : Experiences from a large field test in the Netherlands

    NARCIS (Netherlands)

    Klaassen, EAM; Kobus, C.B.A.; Frunt, J; Slootweg, JG

    2016-01-01

    To efficiently facilitate the energy transition it is essential to evaluate the potential of demand response in practice. Based on the results of a Dutch smart grid pilot, this paper assesses the potential of both manual and semi-automated demand response in residential areas. To stimulate demand

  7. 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

  8. Responsiveness of residential electricity demand to dynamic tariffs: Experiences from a large field test in the Netherlands

    OpenAIRE

    Klaassen, EAM; Kobus, C.B.A.; Frunt, J; Slootweg, JG

    2016-01-01

    To efficiently facilitate the energy transition it is essential to evaluate the potential of demand response in practice. Based on the results of a Dutch smart grid pilot, this paper assesses the potential of both manual and semi-automated demand response in residential areas. To stimulate demand response, a dynamic tariff and smart appliances were used. The participating households were informed about the tariff day-ahead through a home energy management system, connected to a display instal...

  9. 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

  10. Demand for electrical energy

    International Nuclear Information System (INIS)

    Bergougnoux, J.; Fouquet, D.

    1983-01-01

    The different utilizations of electric energy are reviewed in the residential and tertiary sectors, in the industry. The competitive position of electricity in regard to other fuels has been strengthned by the sudden rise in the price of oil in 1973-1974 and 1979-1980. The evolution of electricity prices depended on the steps taken to adjust the electricity generation system. The substitution of electricity applications for hydro-carbons is an essential point of energy policy. The adjustment at all times, at least cost and most reliability, of the supply of electricity to the demand for it is a major problem in the design and operation of electric systems. National demand for power at a given moment is extremely diversified. Electricity consumption presents daily and seasonal variations, and variations according to the different sectors. Forecasting power requirements is for any decision on operation or investment relating to an electrical system. Load management is desirable (prices according to the customers, optional tariffs for ''peak-day withdrawal''). To conclude, prospects for increased electricity consumption are discussed [fr

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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

    Energy Technology Data Exchange (ETDEWEB)

    Nakajima, Tadahiro [The Kansai Electric Power Company, Incorporated, 6-16, Nakanoshima 3-chome, Kita-Ku, Osaka 530-8270 (Japan); Hamori, Shigeyuki [Faculty of Economics, Kobe University 2-1, Rokkodai, Nada-Ku, Kobe 657-8501 (Japan)

    2010-05-15

    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. (author)

  17. 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

  18. 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

  19. Pay for load demand - electricity pricing with load demand component

    International Nuclear Information System (INIS)

    Pyrko, Jurek; Sernhed, Kerstin; Abaravicius, Juozas

    2003-01-01

    This publication is part of a project called Direct and Indirect Load Control in Buildings. Peak load problems have attracted considerable attention in Sweden during last three winters, caused by a significant decrease in available reserve power, which is a consequence of political decisions and liberalisation of the electricity market. A possible way to lower peak loads, avoiding electricity shortages and reducing electricity costs both for users and utilities, is to make customers experience the price difference during peak load periods and, in this way, become more aware of their energy consumption pattern and load demand. As of January 1st 2001, one of the Swedish energy utilities - Sollentuna Energi - operating in the Stockholm area, introduced a new electricity tariff with differentiated grid fees based on a mean value of the peak load every month. This tariff was introduced for all residential customers in the service area. The objective of this study is to investigate the extent to which a Load Demand Component, included in electricity pricing, can influence energy use and load demand in residential buildings. What are the benefits and disadvantages for customers and utilities? This paper investigates the impact of the new tariff on the utility and different types of typical residential customers, making comparisons with previous tariff. Keywords Load demand, electricity pricing, tariff, residential customers, energy behaviour

  20. Electricity demand in Tunisia

    International Nuclear Information System (INIS)

    Gam, Imen; Ben Rejeb, Jaleleddine

    2012-01-01

    This paper examines the global electricity demand in Tunisia as a function of gross domestic product in constant price, the degree of urbanization, the average annual temperature, and the real electricity price per Kwh. This demand will be examined employing annual data over a period spanning almost thirty one years from 1976 to 2006. A long run relationship between the variables under consideration is determined using the Vector Autoregressive Regression. The empirical results suggest that the electricity demand in Tunisia is sensitive to its past value, any changes in gross domestic product and electricity price. The electricity price effects have a negative impact on long-run electricity consumption. However, the gross domestic product and the past value of electricity consumption have a positive effect. Moreover, the causality test reveals a unidirectional relationship between price and electricity consumption. Our empirical findings are effective to policy makers to maintain the electricity consumption in Tunisia by using the appropriate strategy. - Highlights: ► This paper examined the electricity demand in Tunisia in the long-run. ► The empirical analysis revealed that in the long-run the electricity demand is affected by changes in its past value, GDP in constant price and real electricity price. ► There is a unidirectional relationship between price and electricity consumption, that is to say, that the electricity price causes the consumption. ► Those results suggest that a pricing policy can be an effective instrument to rationalize the electricity consumption in Tunisia in the long-run.

  1. 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)

  2. 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)

  3. 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.

  4. 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, .......g. building energy simulations. •The demand level of houses with different number of occupants is well captured....

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

    OpenAIRE

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

    2017-01-01

    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 less grid capacity may be needed. However, the introduction of residential demand response programmes to support the development of smart grids that includes renewable generation is hampered by a ...

  6. 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.

  7. 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

  8. Analysis of a Residential Building Energy Consumption Demand Model

    Directory of Open Access Journals (Sweden)

    Meng Liu

    2011-03-01

    Full Text Available In order to estimate the energy consumption demand of residential buildings, this paper first discusses the status and shortcomings of current domestic energy consumption models. Then it proposes and develops a residential building energy consumption demand model based on a back propagation (BP neural network model. After that, taking residential buildings in Chongqing (P.R. China as an example, 16 energy consumption indicators are introduced as characteristics of the residential buildings in Chongqing. The index system of the BP neutral network prediction model is established and the multi-factorial BP neural network prediction model of Chongqing residential building energy consumption is developed using the Cshap language, based on the SQL server 2005 platform. The results obtained by applying the model in Chongqing are in good agreement with actual ones. In addition, the model provides corresponding approximate data by taking into account the potential energy structure adjustments and relevant energy policy regulations.

  9. 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

  10. 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)

  11. Demand flexibility from residential heat pump

    DEFF Research Database (Denmark)

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

    2014-01-01

    Demand response (DR) is considered as a potentially effective tool to compensate generation intermittency imposed by renewable sources. Further, DR can instigate to offer optimum asset utilization and to avoid or delay the need for new infrastructure investment. Being a sizable load together...... 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...

  12. Estimating the Determinants of Residential Water Demand in Italy

    OpenAIRE

    Giulia Romano; Nicola Salvati; Andrea Guerrini

    2014-01-01

    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 cli...

  13. 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...

  14. 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.

  15. Energy efficiency to reduce residential electricity and natural gas use under climate change.

    Science.gov (United States)

    Reyna, Janet L; Chester, Mikhail V

    2017-05-15

    Climate change could significantly affect consumer demand for energy in buildings, as changing temperatures may alter heating and cooling loads. Warming climates could also lead to the increased adoption and use of cooling technologies in buildings. We assess residential electricity and natural gas demand in Los Angeles, California under multiple climate change projections and investigate the potential for energy efficiency to offset increased demand. We calibrate residential energy use against metered data, accounting for differences in building materials and appliances. Under temperature increases, we find that without policy intervention, residential electricity demand could increase by as much as 41-87% between 2020 and 2060. However, aggressive policies aimed at upgrading heating/cooling systems and appliances could result in electricity use increases as low as 28%, potentially avoiding the installation of new generation capacity. We therefore recommend aggressive energy efficiency, in combination with low-carbon generation sources, to offset projected increases in residential energy demand.

  16. Cut Electric Bills by Controlling Demand

    Science.gov (United States)

    Grumman, David L.

    1974-01-01

    Electric bills can be reduced by lowering electric consumption and by controlling demand -- the amount of electricity used at a certain point in time. Gives tips to help reduce electric demand at peak power periods. (Author/DN)

  17. 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...

  18. 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

  19. 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)

  20. 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.

  1. 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...

  2. 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

  3. The aging US population and residential energy demand

    International Nuclear Information System (INIS)

    Tonn, Bruce; Eisenberg, Joel

    2007-01-01

    This piece explores the relationships between a rapidly aging U.S. population and the demand for residential energy. Data indicate that elderly persons use more residential energy than younger persons. In this time of steeply rising energy costs, energy is an especially important financial issue for the elderly with low and/or fixed incomes. As the absolute number of elderly as well as their proportion of the total US population both continue to increase, energy and the elderly population looms as another energy policy challenge

  4. 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.

  5. Neural network controller for Active Demand-Side Management with PV energy in the residential sector

    International Nuclear Information System (INIS)

    Matallanas, E.; Castillo-Cagigal, M.; Gutiérrez, A.; Monasterio-Huelin, F.; Caamaño-Martín, E.; Masa, D.; Jiménez-Leube, J.

    2012-01-01

    Highlights: ► We have developed a neural controller for Active Demand-Side Management. ► The controller consists of Multilayer Perceptrons evolved with a genetic algorithm. ► The architecture of the controller is distributed and modular. ► The simulations show that the electrical local behavior improves. ► Active Demand-Side Management helps users to control his energy behaviour. -- Abstract: In this paper, we describe the development of a control system for Demand-Side Management in the residential sector with Distributed Generation. The electrical system under study incorporates local PV energy generation, an electricity storage system, connection to the grid and a home automation system. The distributed control system is composed of two modules: a scheduler and a coordinator, both implemented with neural networks. The control system enhances the local energy performance, scheduling the tasks demanded by the user and maximizing the use of local generation.

  6. 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.

  7. 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

  8. 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.

  9. 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

    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......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......'s energy consumption during a period of one year. Furthermore, simulations were performed considering real data of PV generation, consumption, prices taken from the Spanish market and costs of battery and photovoltaic systems....

  10. 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.

  11. 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.

  12. 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

  13. Estimation of the demand for electricity

    NARCIS (Netherlands)

    van Helden, GJ; Leeflang, PSH; Sterken, E

    The residential consumer of electricity is often faced with a price schedule, where the price per kWh differs according to the amountof electricity consumed. 1 1In this study, the relations between the price per kWh are not considered as a function of the time-of-use(TOU). The determination of TOU

  14. 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.

  15. 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

  16. Retailing residential electricity : A concept that makes sense?

    International Nuclear Information System (INIS)

    MacDonald, C.

    2003-07-01

    A heated debate centres around the deregulation of the electricity industry and the retailing of residential electricity. An assessment of the current situation in the industry was provided in this paper to provide a basis for discussion. The experience gained both in Alberta and Texas in residential retail was examined. The main issue of concern is whether residential customers will benefit from deregulation of the electricity sector. The Retail Energy Deregulation (RED) Index provides a benchmark for those jurisdictions considering the residential options. Deregulation has not led to significant benefits to residential customers in most jurisdictions. The electricity industry will always require a central dispatch/market process that will have to designed, governed, regulated, modified regularly. The benefits to residential consumers are not expected for a very long time. Standard market design is an issue that will require attention. refs., 7 figs

  17. Predicting residential energy and water demand using publicly available data

    International Nuclear Information System (INIS)

    Hoşgör, Enes; Fischbeck, Paul S.

    2015-01-01

    Highlights: • We built regression models using publicly available data as independent variables. • These models were used to predict monthly utility usage. • Such models can empower demand-side management program design, implementation and evaluation. • As well as planning for changes in energy and water demand. - Abstract: The overarching objective behind this work is to merge publicly available data with utility consumption histories and extract statistically significant insight on utility usage for a group of houses (n = 7022) in Gainesville, USA. This study investigates the statistical descriptive power of publicly available information for modeling utility usage. We first examine the deviations that arise from monthly utility usage reading dates as reading dates tend to shift and reading periods tend to vary across different months. Then we run regression models for individual months which in turn we compare to a yearly regression model which accounts for months as a dummy variable to understand whether a monthly model or a yearly model has a larger statistical power. It is shown that publicly available data can be used to model residential utility usage in the absence of highly private utility data. The obtained results are helpful for utilities for two reasons: (1) using the models to predict the monthly changes in demand; and (2) predicting utility usage can be translated into energy-use intensity as a first-cut metric for energy efficiency targeting in their service territory to meet their state demand reduction targets

  18. 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)

  19. 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.

  20. Analysis of Cool Roof Coatings for Residential Demand Side Management in Tropical Australia

    Directory of Open Access Journals (Sweden)

    Wendy Miller

    2015-06-01

    Full Text Available Cool roof coatings have a beneficial impact on reducing the heat load of a range of building types, resulting in reduced cooling energy loads. This study seeks to understand the extent to which cool roof coatings could be used as a residential demand side management (DSM strategy for retrofitting existing housing in a constrained network area in tropical Australia where peak electrical demand is heavily influenced by residential cooling loads. In particular this study seeks to determine whether simulation software used for building regulation purposes can provide networks with the ‘impact certainty’ required by their DSM principles. The building simulation method is supported by a field experiment. Both numerical and experimental data confirm reductions in total consumption (kWh and energy demand (kW. The nature of the regulated simulation software, combined with the diverse nature of residential buildings and their patterns of occupancy, however, mean that simulated results cannot be extrapolated to quantify benefits to a broader distribution network. The study suggests that building data gained from regulatory simulations could be a useful guide for potential impacts of widespread application of cool roof coatings in this region. The practical realization of these positive impacts, however, would require changes to the current business model for the evaluation of DSM strategies. The study provides seven key recommendations that encourage distribution networks to think beyond their infrastructure boundaries, recognising that the broader energy system also includes buildings, appliances and people.

  1. 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.

  2. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

    Science.gov (United States)

    Honjo, Keita; Shiraki, Hiroto; Ashina, Shuichi

    2018-01-01

    After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the earthquake.

  3. 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

  4. 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

  5. Perspective on electricity demand beyond 2010

    International Nuclear Information System (INIS)

    Appert, O.

    2000-01-01

    Electricity demand has been the fastest growing form of energy use in the OECD for several decades. Historically there have been strong links between national income (gross domestic product), prices and electricity use. If the trends of the past continue, the annual growth rate of electricity demand to 2020 could reach 2% in the OECD and over 4% in developing countries. Although electricity demand is expected to continue the trend of strong growth in the OECD and also in other regions of the world over the coming decades, there is some question in developed countries of the extent to which electricity demand will be moderated by '' saturation ''. That is, will demand growth level off as electricity completes its penetration into most potential applications and equipment becomes more energy efficient? Will commitments to reduce emissions of conventional airborne pollutants and carbon dioxide increase the cost of electricity generation and slow electricity's demand growth? Or, working in the opposite direction, will new end-uses continue to drive electricity's increasing share of final energy consumption? Will lower prices due to electricity market reform have an impact? This paper explores these issues and provides insights in the likely trends in these areas. (author)

  6. 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.

  7. California DREAMing: The design of residential demand responsive technology with people in mind

    Science.gov (United States)

    Peffer, Therese Evelyn

    Electrical utilities worldwide are exploring "demand response" programs to reduce electricity consumption during peak periods. Californian electrical utilities would like to pass the higher cost of peak demand to customers to offset costs, increase reliability, and reduce peak consumption. Variable pricing strategies require technology to communicate a dynamic price to customers and respond to that price. However, evidence from thermostat and energy display studies as well as research regarding energy-saving behaviors suggests that devices cannot effect residential demand response without the sanction and participation of people. This study developed several technologies to promote or enable residential demand response. First, along with a team of students and professors, I designed and tested the Demand Response Electrical Appliance Manager (DREAM). This wireless network of sensors, actuators, and controller with a user interface provides information to intelligently control a residential heating and cooling system and to inform people of their energy usage. We tested the system with computer simulation and in the laboratory and field. Secondly, as part of my contribution to the team, I evaluated machine-learning to predict a person's seasonal temperature preferences by analyzing existing data from office workers. The third part of the research involved developing an algorithm that generated temperature setpoints based on outdoor temperature. My study compared the simulated energy use using these setpoints to that using the setpoints of a programmable thermostat. Finally, I developed and tested a user interface for a thermostat and in-home energy display. This research tested the effects of both energy versus price information and the context of sponsorship on the behavior of subjects. I also surveyed subjects on the usefulness of various displays. The wireless network succeeded in providing detailed data to enable an intelligent controller and provide feedback to

  8. Power plant site evaluation, electric energy demand forecasts - Douglas Point Site. Volume 3. Final report

    International Nuclear Information System (INIS)

    Wilson, J.W.

    1975-07-01

    This is part of a series of reports containing an evaluation of the proposed Douglas Point nuclear generating station site located on the Potomac River in Maryland 30 miles south of Washington, D.C. This report contains chapters on the Potomac Electric Power Company's market, forecasting future demand, modelling, a residential demand model, a nonresidential demand model, the Southern Maryland Electric Cooperative Model, short term predictive accuracy, and total system requirements

  9. Electric utilities and the demand for natural gas

    Energy Technology Data Exchange (ETDEWEB)

    Uri, N D; Atkinson, S

    1976-03-01

    The scarcity of natural gas has given rise to a series of priorities of deliveries based on end use and drafted by the Federal Power Commission. The U.S. Supreme Court, on June 7, 1972, held that the Commission has jurisdiction over curtailments in the service of gas in interstate commerce to both resale and direct industrial customers. This decision reversed a Fifth Circuit Court ruling that protected direct industrial customers from curtailments. The FPC priority curtailments are classed from 1 to 9, for which electric utilities are concentrated in classes 4 to 9. As weather conditions become more severe, not only do the residential and commercial consumers demand more electrical energy, they also demand more natural gas. The result is that there is less natural gas available for electric utilities to use for generation so they change to an alternative fuel. A demand model for the short term for natural gas for electric utilities is given; primary factors involve the price of natural gas, the prices of substitute fuels, and the demand for electrical energy by the various consumer classes. (MCW)

  10. 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.

  11. Have Chinese water pricing reforms reduced urban residential water demand?

    Science.gov (United States)

    Zhang, B.; Fang, K. H.; Baerenklau, K. A.

    2017-06-01

    China continues to deal with severe levels of water scarcity and water pollution. To help address this situation, the Chinese central government initiated urban water pricing reforms in 2002 that emphasized the adoption of increasing block rate (IBR) price structures in place of existing uniform rate structures. By combining urban water use records with microlevel data from the Chinese Urban Household Survey, this research investigates the effectiveness of this national policy reform. Specifically, we compare household water consumption in 28 cities that adopted IBR pricing structures during 2002-2009, with that of 110 cities that had not yet done so. Based on difference-in-differences models, our results show that the policy reform reduced annual residential water demand by 3-4% in the short run and 5% in the longer run. These relatively modest reductions are consistent with the generous nature of the IBR pricing structures that Chinese cities have typically chosen to implement. Our results imply that more efforts are needed to address China's persistent urban water scarcity challenges.

  12. Energy demand of electricity generation

    International Nuclear Information System (INIS)

    Drahny, M.

    1992-01-01

    The complex energy balance method was applied to selected electricity generation subsystems. The hydroelectric, brown coal based, and nuclear based subsystems are defined. The complex energy balance basically consists in identifying the mainstream and side-stream energy inputs and outputs for both the individual components and the entire electricity generation subsystem considered. Relationships for the complete energy balance calculation for the i-th component of the subsystem are given, and its side-stream energy inputs and outputs are defined. (J.B.). 4 figs., 4 refs

  13. Photovoltaic electricity generation: Value for residential and commercial sectors

    Science.gov (United States)

    Bhattacharjee, Ujjwal

    The photovoltaic (PV) industry in the US has seen an upsurge in recent years, and PV holds great promise as a renewable technology with no greenhouse gas emissions with its use. We aim to assess the value of PV based electricity for users in the residential and commercial sectors focusing on the financial impacts it has, which may not be greatly recognized. Specifically, we pursue two goals. First, the emerging 'renewable portfolio standard (RPS)' adopted in several states in the country has been a driving force for large scale PV deployment, but financial incentives offered to PV in different RPS states differ considerably. We use life cycle cost model to estimate the cost of PV based electricity for thirty-two RPS states in the country. Results indicate that the levelized cost of PV electricity is high (40 to 60 Cents/kWh). When the contribution of the financial incentives (along with the cost of energy saved) is taken into account, the cost of PV based electricity is negative in some RPS states such as California, New Jersey, New York, while for most of the RPS states the cost of PV electricity continues to remain high. In addition, the states with negative or low cost of PV electricity have been driving the PV diffusion in the residential sector. Therefore, a need to adjust the financial incentive structure in different RPS states is recommended for homogenous development of the residential PV market in the country. Second, we assess the value of the PV in reducing the highest peak load demand in commercial buildings and hence the high value demand charge. The Time-of-Use (TOU) based electricity tariff is widely used by electric utilities in the commercial sector. Energy and peak load are two important facets of the TOU tariff regime. Tools are well established to estimate the energy contribution from a PV system (installed in a commercial building), but not power output on a short time interval. A joint conditional probability model has been developed that

  14. A multi-scale adaptive model of residential energy demand

    International Nuclear Information System (INIS)

    Farzan, Farbod; Jafari, Mohsen A.; Gong, Jie; Farzan, Farnaz; Stryker, Andrew

    2015-01-01

    Highlights: • We extend an energy demand model to investigate changes in behavioral and usage patterns. • The model is capable of analyzing why demand behaves the way it does. • The model empowers decision makers to investigate DSM strategies and effectiveness. • The model provides means to measure the effect of energy prices on daily profile. • The model considers the coupling effects of adopting multiple new technologies. - Abstract: In this paper, we extend a previously developed bottom-up energy demand model such that the model can be used to determine changes in behavioral and energy usage patterns of a community when: (i) new load patterns from Plug-in Electrical Vehicles (PEV) or other devices are introduced; (ii) new technologies and smart devices are used within premises; and (iii) new Demand Side Management (DSM) strategies, such as price responsive demand are implemented. Unlike time series forecasting methods that solely rely on historical data, the model only uses a minimal amount of data at the atomic level for its basic constructs. These basic constructs can be integrated into a household unit or a community model using rules and connectors that are, in principle, flexible and can be altered according to the type of questions that need to be answered. Furthermore, the embedded dynamics of the model works on the basis of: (i) Markovian stochastic model for simulating human activities, (ii) Bayesian and logistic technology adoption models, and (iii) optimization, and rule-based models to respond to price signals without compromising users’ comfort. The proposed model is not intended to replace traditional forecasting models. Instead it provides an analytical framework that can be used at the design stage of new products and communities to evaluate design alternatives. The framework can also be used to answer questions such as why demand behaves the way it does by examining demands at different scales and by playing What-If games. These

  15. 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)

  16. 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)

  17. 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.

  18. Assessing the benefits of residential demand response in a real time distribution energy market

    International Nuclear Information System (INIS)

    Siano, Pierluigi; Sarno, Debora

    2016-01-01

    Highlights: • A new probabilistic methodology, integrating DR in a distribution energy market is proposed. • The method can alleviate distribution network congestions. • This method based on D-LMPs allows cost savings for end-user customers. • Innovative thermal and shiftable loads Real Time control algorithms are also presented. - Abstract: In the field of electricity distribution networks and with the advent of smart grids and microgrids, the use of Distribution Locational Marginal Price (D-LMPs) in a Real Time (RT) distribution market managed by a Distribution System Operator (DSO) is discussed in presence of empowered residential end-users that are able to bid for energy by a demand aggregator while following Demand Response (DR) initiatives. Each customer is provided by a transactive controller, which reads the locational market signals and answers with a bid taking into account the user preferences about some appliances involved in DR activities and controlled by smart plugs-in. In particular, Heating Ventilation and Air Conditioning (HVAC) appliances and shiftable loads are controlled so that their consumption profile can be modified according to the price of energy. In order to assess the effectiveness of the proposed method in terms of energy and cost saving, an innovative probabilistic methodology for evaluating the impact of residential DR choices considering uncertainties related to load demand, user preferences, environmental conditions, house thermal behavior and wholesale market trends has been proposed. The uncertainties related to the stochastic variations of the variables involved are modeled by using the Monte Carlo Simulation (MCS) method. The combination of MCS and RT distribution market simulation based on D-LMPs are used to assess the operation and impact of the DR method over one month. Simulations results on an 84-buses distribution network confirmed that the proposed method allows saving costs for residential end-users and making

  19. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Wiesmann, Daniel, E-mail: daniel.wiesmann@ist.utl.p [Instituto Superior Tecnico, Technical University of Lisbon, Avenida Rovisco Pais 1, 1049-001 Lisbon (Portugal); Lima Azevedo, Ines [Department of Engineering and Public Policy, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States); Ferrao, Paulo [Instituto Superior Tecnico, Technical University of Lisbon, Avenida Rovisco Pais 1, 1049-001 Lisbon (Portugal); Fernandez, John E. [Department of Architecture, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States)

    2011-05-15

    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: {yields} Econometric study of per capita residential electricity consumption in Portugal. {yields} Comparing models at two levels of aggregation: by municipality and by household. {yields} Using proxies for the dwelling characteristics on the municipality level. {yields} Results from both scales are consistent. {yields} Income elasticity is low and the influence of dwelling characteristics is significant.

  1. The flexibility of household electricity demand over time

    International Nuclear Information System (INIS)

    Halvorsen, B.; Larsen, B.M.

    2001-01-01

    Empirical estimates of long run effects on residential electricity demand from changes in the electricity price are usually estimated by cross-sectional variation in the current stock of electric household appliances across households at a certain point in time. Here, we use a discrete-continuous approach modeling the long run effects by investments in new appliances. We apply the annual Norwegian Survey of Consumer Expenditure for the period 1975 to 1994 to estimate the short and long run own price elasticities in the two approaches. We find the estimated long run elasticity only slightly more price elastic than the short run. We also find that the long run elasticity does not differ significantly between the two approaches. The reason for both results is that, since there is no alternative source of energy for these appliances, there are no substitution effects

  2. 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

  3. Forecast electricity demand in Quebec: Development plan 1993

    International Nuclear Information System (INIS)

    1992-01-01

    Demographic, economic, and energy prospects are the determining factors in estimating demand for electricity in Quebec. In average scenarios developed for 1992-2010, the Quebec population will grow 0.5%/y and the gross domestic product will increase 2.6%/y. Firm electricity sales by Hydro-Quebec will grow to 197.9 TWh by 2010, or 2.2%/y. Sales in the residential and farm sectors should grow 1.3%/y and sales in the general and institutional sectors should rise by 2.2%/y. Electricity demand in the industrial sector, rising at an estimated 2.9%/y in 1992-2010, is chiefly responsible for the anticipated growth in Hydro-Quebec's overall sales. The nonferrous smelting, refining, chemicals, and paper industries will account for ca 60% of this growth. In the municipal services and public transportation sectors, demand should grow 3.3%/y, and over half the growth forecast in this sector can be attributed to the impact that new uses of electricity are expected to have after 2005. High- and low-growth scenarios offer alternative visions of demand growth based on different but equally valid assumptions about demographic and economic growth. In terms of firm electricity sales, the high- and low-growth scenarios differ by 50 TWh in 2010. Hydro-Quebec has retained two strategic orientations that will influence growth in electricity sales: the development of industrial markets and extension of the energy-savings objective of 9.3 TWh forecast to the year 2000. Taking these two orientations into account, the growth rate for electricity sales in the average scenario would be 1.8%/y rather than 2.2%/y. 25 figs., 81 tabs

  4. 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.

  5. 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

  6. Human behaviour and energy demand : How behavioural science can be used to reduceenergy demand in the residential sector

    OpenAIRE

    Kaczmarek, Haiko

    2015-01-01

    The threat of human induced climate change is imminent. The reason is an everyincreasing demand for energy and products, producing more and more greenhousegas emissions. Everybody needs to take responsibility now. The estimations are thatwith 2% annual energy savings from residential households 12TWh and 3.3 billionmetric tonnes of CO2 can be saved per year. Greenely, a startup from KIC InnoEnergy,wants to engage residential households to change their energy behaviour athome. They combine a s...

  7. 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.

  8. 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)

  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...... trade. Assuming that wholesale prices can react to changes in retail prices (but not vice versa), we find that generators install sufficient capacity to serve retail demand in each market configuration, thus avoiding blackouts. Furthermore, aggregate capacity levels and retail prices...

  10. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

    Directory of Open Access Journals (Sweden)

    Keita Honjo

    Full Text Available After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE. However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price. Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case. The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the

  11. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect

    Science.gov (United States)

    Shiraki, Hiroto; Ashina, Shuichi

    2018-01-01

    After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan’s NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers’ electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%–6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2–2.26 MtCO2 (−4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan’s electricity demand and CO2 emissions after the

  12. The demand for electricity in Israel

    Energy Technology Data Exchange (ETDEWEB)

    Beenstock, M. [Department of Economics, Hebrew University of Jerusalem, Mount Scopus, 91905 Jerusalem (Israel); Goldin, E.; Nabot, D. [EG Consulting, Hameasef 11, Jerusalem (Israel)

    1999-04-01

    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.)

  13. 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.)

  14. 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.

  15. 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.

  16. Meeting/Managing the demand for electricity

    International Nuclear Information System (INIS)

    Draper, E.L.

    1994-01-01

    In the United States, the demand for electricity is increasing, so several energy sources have to be considered. Fuel and gas are taken into account for new generating capacity. But there are still environmental concerns and costs associated with coal. It is also predicted that orders will be set for new nuclear units for the middle of the decade. (TEC). 3 figs

  17. 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.

  18. Residential-energy-demand modeling and the NIECS data base: an evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Cowing, T.G.; Dubin, J.A.; McFadden, D.

    1982-01-01

    The purpose of this report is to evaluate the 1978-1979 National Interim Energy Consumption Survey (NIECS) data base in terms of its usefulness for estimating residential energy demand models based on household appliance choice and utilization decisions. The NIECS contains detailed energy usage information at the household level for 4081 households during the April 1978 to March 1979 period. Among the data included are information on the structural and thermal characteristics of the housing unit, demographic characteristics of the household, fuel usage, appliance characteristics, and actual energy consumption. The survey covers the four primary residential fuels-electricity, natural gas, fuel oil, and liquefied petroleum gas - and includes detailed information on recent household conservation and retrofit activities. Section II contains brief descriptions of the major components of the NIECS data set. Discussions are included on the sample frame and the imputation procedures used in NIECS. There are also two extensive tables, giving detailed statistical and other information on most of the non-vehicle NIECS variables. Section III contains an assessment of the NIECS data, focusing on four areas: measurement error, sample design, imputation problems, and additional data needed to estimate appliance choice/use models. Section IV summarizes and concludes the report.

  19. 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...

  20. 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.

  1. 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

    electricity use from the less desirable times to more desirable times, including: feedback technology, pricing incentives, smart appliances, and energy storage. Based on our experience in this area, we present three challenges for residential shifting: getting users to understand the concept of shifting...

  2. 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.

  3. Estimating U.S. residential demand for fuelwood in the presence of selectivity

    Science.gov (United States)

    Daly, Ryan Michael

    Residential energy consumers have options for home heating. With many applications, appliances, and fuel types, fuelwood used for heating faces stiff competition in modern society from other fuels. This study estimates demand for domestic fuelwood. It also examines whether evidence of bias exists from residential homes choosing to use fuelwood. The use of OLS as an estimator will yield biased results if such selectivity exists. Selectivity is addressed with a Heckman (1979) two-step procedure; bias in fuelwood demand estimation using OLS is reduced. Non-wood energy prices and income are major determinants of fuelwood demand. Geographical regions and urbanization confirm results from prior studies.

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. Demand-controlling marketing of electric utilities

    Energy Technology Data Exchange (ETDEWEB)

    Raffee, H; Fritz, W

    1980-01-01

    In situations like the shortage of energy resources the particular autonomy of the users concerning energy demand raises more and more aggravating problems for the electric utilities (EU) and, last not least, for society (i.e. the peak-load problem, threatening bottlenecks in the supply situation). Thus the requirement for a demand-controlling marketing strategy of the EU with the help of which the individual demand should be influenced in the following manner is legitimate. The article discusses the targets, strategies, and instruments of marketing performed by the EU under the aspect of their efficiency concerning demand control. The discussion leads to e.g. the following results: that a marketing strategy for the sensible, responsible, and efficent use of energy, in the long-term, serves both the interests of the users and the interests of the EU; that such a marketing programme can have the required controlling effects especially with the help of strategies like market segmentation and cooperation. The discussion makes also clear that a demand-controlling marketing strategy of the EU can hardly be realized without a considerable change within the organization of the EU on one hand and, on the other, without expanding the marketing programme toward a marketing strategy of balance.

  10. Lifestyle factors in U.S. residential electricity consumption

    International Nuclear Information System (INIS)

    Sanquist, Thomas F.; Orr, Heather; Shui Bin; Bittner, Alvah C.

    2012-01-01

    A multivariate statistical approach to lifestyle analysis of residential electricity consumption is described and illustrated. Factor analysis of selected variables from the 2005 U.S. Residential Energy Consumption Survey (RECS) identified five lifestyle factors reflecting social and behavioral patterns associated with air conditioning, laundry usage, personal computer usage, climate zone of residence, and TV use. These factors were also estimated for 2001 RECS data. Multiple regression analysis using the lifestyle factors yields solutions accounting for approximately 40% of the variance in electricity consumption for both years. By adding the household and market characteristics of income, local electricity price and access to natural gas, variance accounted for is increased to approximately 54%. Income contributed ∼1% unique variance to the models, indicating that lifestyle factors reflecting social and behavioral patterns better account for consumption differences than income. Geographic segmentation of factor scores shows distinct clusters of consumption and lifestyle factors, particularly in suburban locations. The implications for tailored policy and planning interventions are discussed in relation to lifestyle issues. - Highlights: ► Illustrates lifestyle analysis of residential electricity consumption. ► Lifestyle factors based on social and behavioral decisions and equipment use. ► Regression models using lifestyle factors account for 40% of consumption variance. ► Lifestyle factors are stable over time when applied to other data sets. ► Energy reduction opportunities are identified by segmentation analysis.

  11. 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)

  12. 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.

  13. 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

  14. Assessing Residential Customer Satisfaction for Large Electric Utilities

    OpenAIRE

    Lea Kosnik; L. Douglas Smith; Satish Nayak; Maureen Karig; Mark Konya; Kristy Lovett; Zhennan Liu; Harrison Luvai

    2015-01-01

    Electric utilities, like other service organizations, rely on customer surveys to assess the quality of their services and customer relations. With responses to an in-depth survey of 2,216 residential customers, complementary data from geo-coded public sources, aggregate assessments of performance by J.D. Power & Associates from their independent surveys, historical records of individual customer usage and bill payments, streams of published media content and records of actual service deliver...

  15. 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.

  16. Electric heat-pumps in residential buildings

    Energy Technology Data Exchange (ETDEWEB)

    1983-03-01

    Since the end of 1979 every other day an electrically operated heat-pump has started operation in Berlin (West). Pros and cons of heat-pumps are a much discussed subject. But what is the opinion of the user. As it is not known the BEWAG carried out a written customer inquiry in the summer 1982. The aim of the inquiry was to improve the advisory service by means of the answers obtained, to obtain information about the reliability or liability to defects of the heat pump, the mechanism they operate on and to know how big the oil substitution potential is. Customer satisfaction with the heat pumps was a further point of interest.

  17. 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

    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......, 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...

  18. 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...... before DR implementation. This paper critically examines the present practices of the DR in the various electricity markets existing in the world including Europe. The prospect of DR in various market levels such as day-ahead (spot) market, hour-ahead market, real time/regulating market and ancillary...... market is analyzed. This paper also addresses the key issues and challenges in the implementation of DR in the electricity markets....

  19. Micro-generation dispatch in a smart residential multi-carrier energy system considering demand forecast error

    International Nuclear Information System (INIS)

    Sanjari, M.J.; Karami, H.; Gooi, H.B.

    2016-01-01

    Highlights: • Combination of day-ahead and hour-ahead optimizations to design online controller. • Investigating the effect of load forecast error on the system operating cost. • Proposing effective method for hour-ahead resource re-dispatch. • Using the HSS algorithm as a powerful and effective optimization method. • Combining long-term and short-term strategies for optimal dispatch of resources. - Abstract: This paper deals with a residential hybrid thermal/electrical grid-connected home energy system incorporating real data for the load demand. A day-ahead scheduling (DAS) algorithm for dispatching different resources has been developed in previous studies to determine the optimal operation scheduling for the distributed energy resources at each time interval so that the operational cost of a smart house is minimized. However, demand of houses may be changed in each hour and cannot be exactly predicted one day ahead. System complexity caused by nonlinear dynamics of the fuel cell, as a combined heat and power device, and battery charging and discharging time make it difficult to find the optimal operating point of the system by using the optimization algorithms quickly in online applications. In this paper, the demand forecast error is studied and a near-optimal dispatch strategy by using artificial neural network (ANN) is proposed for the residential energy system when the demand changes are known one hour ahead with respect to the predicted day-ahead values. The day-ahead and hour-ahead optimizations are combined and ANN training inputs are adjusted according to the problem such that the economic dispatch of different energy resources can be achieved by the proposed method compared with previous studies. Using the model of the fuel cell extracted from experimental measurement and real data for the load demand makes the results more applicable in real residential energy systems.

  20. The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers

    Science.gov (United States)

    Ivanin, O. A.; Direktor, L. B.

    2018-05-01

    The problem of short-term forecasting of electric power demand of stand-alone consumers (small inhabited localities) situated outside centralized power supply areas is considered. The basic approaches to modeling the electric power demand depending on the forecasting time frame and the problems set, as well as the specific features of such modeling, are described. The advantages and disadvantages of the methods used for the short-term forecast of the electric demand are indicated, and difficulties involved in the solution of the problem are outlined. The basic principles of arranging artificial neural networks are set forth; it is also shown that the proposed method is preferable when the input information necessary for prediction is lacking or incomplete. The selection of the parameters that should be included into the list of the input data for modeling the electric power demand of residential areas using artificial neural networks is validated. The structure of a neural network is proposed for solving the problem of modeling the electric power demand of residential areas. The specific features of generation of the training dataset are outlined. The results of test modeling of daily electric demand curves for some settlements of Kamchatka and Yakutia based on known actual electric demand curves are provided. The reliability of the test modeling has been validated. A high value of the deviation of the modeled curve from the reference curve obtained in one of the four reference calculations is explained. The input data and the predicted power demand curves for the rural settlement of Kuokuiskii Nasleg are provided. The power demand curves were modeled for four characteristic days of the year, and they can be used in the future for designing a power supply system for the settlement. To enhance the accuracy of the method, a series of measures based on specific features of a neural network's functioning are proposed.

  1. Electricity contract choices of Finnish residential customers. A choice based conjoint analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rouvinen, S.; Matero, J. (Univ. of Eastern Finland, Joensuu (Finland), School of Forest Sciences), e-mail: seppo.rouvinen@uef.fi, e-mail: jukka.matero@uef.fi

    2010-07-01

    Our aim is to examine how different environmental attributes of electricity contracts affect the residential customer choices when heterogeneity in customer preferences and motivations is taken into account. The data was acquired by a mail questionnaire to random sample of Finnish people in October-November 2009 with a response rate of 38 %. In addition to conventional questions, like questions on socio-demographic and agreements of energy related statements, the discrete choice experiment (DCE) of electricity contracts was included. The choice sets in the DCE had three electricity contract alternatives with varying levels of predetermined attributes (including unit price, supplier type, frequency of power outages, energy source and CO{sub 2} emissions). In this paper, we present the findings of our DCE design. Modeling respondent choices resulted in implicit prices for various electricity contract attributes that provide guidance for green marketing strategies of electricity suppliers and energy related informational activities of public institutions. We conclude that currently the potential for increasing demand-based environmental competitiveness from the wood electricity differentiation remains limited as we did not find any significant market segment of residential customers with strong preferences for wood over other sources of electricity (including 'mixture'). (orig.)

  2. 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

  3. 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.

  4. Residential response to voluntary time-of-use electricity rates

    Energy Technology Data Exchange (ETDEWEB)

    Mostafa Baladi, S. [Laurits R. Christensen Associates, Inc. Ames, IA 50011-1070 (United States); Herriges, Joseph A. [Iowa State University, 280D Heady Hall, Department of Economics, Iowa State University, Ames, IA 50011-1070 (United States); Sweeney, Thomas J. [MidAmerican Energy, Des Moines, Iowa (United States)

    1998-09-01

    The response of residential households to voluntary Time-of-Use (TOU) electricity rates is estimated using data from a recent experiment at Midwest Power Systems of Iowa. The study`s design allows us to examine both the participation decision and the customer`s load pattern changes once the TOU rate structure was in effect. Substitution elasticities between on-peak and off-peak electricity usage are estimated and compared to those obtained in earlier mandatory programs, indicating whether program volunteers are more responsive to TOU pricing than the typical household. Attitudinal questionnaires allow us to examine the role of usage perceptions in program participation

  5. 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.

  6. Norwegian Residential Energy Demand: Coordinated use of a System Engineering and a Macroeconomic Model

    Directory of Open Access Journals (Sweden)

    Tor A Johnsen

    1996-07-01

    Full Text Available In Norway, the system engineering model MARKAL and the macroeconomic model MSG-EE are both used in studies of national CO2 controlling strategies. MARKAL is a linear programming model that calculates a composite set of technologies necessary to meet demand and environmental constraints at minimised total energy expenditure. MSG-EE is an applied general equilibrium model including the link between economic activity, energy demand and emissions to air. MSG-EE has a theory consistent description of the link between income, prices and energy demand, but the representation of technological improvements is simple. MARKAL has a sophisticated description of future energy technology options, but includes no feedback to the general economy. A project for studying the potential for a coordinated use of these two models was initiated and funded by the Norwegian Research Council (NFR. This paper gives a brief presentation of the two models. Results from independent model calculations show that MARKAL gives a signficant lower residential energy demand than MSG-EE does. This is explained by major differences in modelling approach. A first attempt of coordinating the residential energy demand in the models is reported. This attempt shows that implementing results from MARKAL, in MSG-EE for the residential sector alone gives little impact on the general economy. A further development of an iteration procedure between the models should include all energy using sectors.

  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...

  8. Prediction on the charging demand for electric vehicles in Chengdu

    Science.gov (United States)

    yun, Cai; wanquan, Zhang; wei, You; pan, Mao

    2018-03-01

    The development of the electric vehicle charging station facilities speed directly affect the development of electric vehicle speed. And the charging demand of electric vehicles is one of the main factors influencing the electric vehicle charging facilities. The paper collected and collated car ownership in recent years, the use of elastic coefficient to predict Chengdu electric vehicle ownership, further modeling to give electric vehicle charging demand.

  9. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Jamil, Faisal, E-mail: fsljml@hotmail.com [School of Economics, Quaid-e-Azam University, Islamabad (Pakistan); Ahmad, Eatzaz, E-mail: eatzaz@qau.edu.pk [School of Economics, Quaid-e-Azam University, Islamabad (Pakistan)

    2011-09-15

    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.

  11. 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

  12. 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

  13. 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...

  14. 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

  15. A Panel Data Analysis of Electricity Demand in Pakistan

    OpenAIRE

    Azam Chaudhry

    2010-01-01

    This paper looks at the economy-wide demand and the firm level demand for electricity in Pakistan. The economy wide estimation of electricity demand uses panel data from 63 countries from 1998-2008, and finds that the elasticity of demand for electricity with respect to per capita income is approximately 0.69, which implies that a 1% increase in per capita income will lead to a 0.69% increase in the demand for electricity. The firm level analysis uses firm level data from the World Bank’s Ent...

  16. 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)

  17. Demand forecasting of electricity in Indonesia with limited historical data

    Science.gov (United States)

    Dwi Kartikasari, Mujiati; Rohmad Prayogi, Arif

    2018-03-01

    Demand forecasting of electricity is an important activity for electrical agents to know the description of electricity demand in future. Prediction of demand electricity can be done using time series models. In this paper, double moving average model, Holt’s exponential smoothing model, and grey model GM(1,1) are used to predict electricity demand in Indonesia under the condition of limited historical data. The result shows that grey model GM(1,1) has the smallest value of MAE (mean absolute error), MSE (mean squared error), and MAPE (mean absolute percentage error).

  18. 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.

  19. 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.

  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. Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method

    Directory of Open Access Journals (Sweden)

    Jun Dong

    2018-04-01

    Full Text Available For better utilizing renewable energy resources and improving the sustainability of power systems, demand response is widely applied in China, especially in recent decades. Considering the massive potential flexible resources in the residential sector, demand response programs are able to achieve significant benefits. This paper proposes an effective performance evaluation framework for such programs aimed at residential customers. In general, the evaluation process will face multiple criteria and some uncertain factors. Therefore, we combine the multi-criteria decision making concept and fuzzy set theory to accomplish the model establishment. By introducing trapezoidal fuzzy numbers into the Vlsekriterijumska Optimizacijia I Kompromisno Resenje (VIKOR method, the evaluation model can effectively deal with the subjection and fuzziness of experts’ opinions. Furthermore, we ameliorate the criteria weight determination procedure of traditional models via combining the fuzzy Analytic Hierarchy Process and Shannon entropy method, which can incorporate objective information and subjective judgments. Finally, the proposed evaluation framework is verified by the empirical analysis of five demand response projects in Chinese residential areas. The results give a valid performance ranking of the five alternatives and indicate that more attention should be paid to the criteria affiliated with technology level and economy benefits. In addition, a series of sensitivity analyses are conducted to examine the validity and effectiveness of the established evaluation framework and results. The study improves traditional multi-criteria decision making method VIKOR by introducing trapezoidal fuzzy numbers and combination weighing technique, which can provide an effective mean for performance evaluation of residential demand response programs in a fuzzy environment.

  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. 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

  4. 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,

  5. 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.

  6. 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

  7. Economic analysis of second use electric vehicle batteries for residential energy storage and load-levelling

    International Nuclear Information System (INIS)

    Heymans, Catherine; Walker, Sean B.; Young, Steven B.; Fowler, Michael

    2014-01-01

    The reuse of Li-ion EV batteries for energy storage systems (ESS) in stationary settings is a promising technology to support improved management of demand and supply of electricity. In this paper, MatLAB simulation of a residential energy profile and regulated cost structure is used to analyze the feasibility of and cost savings from repurposing an EV battery unit for peak-shifting. in situ residential energy storage can contribute to the implementation of a smart grid by supporting the reduction of demand during typical peak use periods. Use of an ESS increases household energy use but potentially improves economic effectiveness and reduces greenhouse gas emissions. The research supports the use of financial incentives for Li-ion battery reuse in ESS, including lower energy rates and reduced auxiliary fees. - Highlights: • EV Li-ion batteries can be reused in stationary energy storage systems (ESS). • A single ESS can shift 2 to 3 h of electricity used in a house. • While energy use increases, potential economic and environmental effectiveness improve. • ESS supports smart grid objectives. • Incentives like reduced fees are needed to encourage implementation of Li-ion battery ESS

  8. 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)

  9. Brazilian residential sector demand administration programs: opportunities, costs and barriers; Programas de administracao da demanda para o setor residencial brasileiro: oportunidades, custos e barreiras

    Energy Technology Data Exchange (ETDEWEB)

    Jannuzzi, Gilberto de Martino [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica; Santos, Vanice Ferreira dos; Ugaya, Cassia Maria Lie; Madureira, Ronaldo Goncalves; Salcedo, Marco Vinicio Yanez [Universidade Estadual de Campinas, SP (Brazil)

    1995-12-31

    This work aims to present some results and discussions concerning the implementation of demand side management projects for the Brazilian residential sector. The economic advantages of these programs for the electric power utilities is presented as well as the barriers and problems. The opportunities for the application of such programs in a national level are presented and the expected difficulties discussed. A case study is presented 3 tabs., 3 refs.

  10. 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...

  11. 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

  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. 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.

  14. ELECTRICITY DEMAND IN A NORTHERN MEXICO METROPOLITAN ECONOMY

    Directory of Open Access Journals (Sweden)

    Thomas M. Fullerton

    2014-10-01

    Full Text Available Using an error correction framework, this study analyzes the long- and short-run dynamics of electricity demand in Ciudad Juarez, a large metropolitan economy on Mexico’s northern border. Demand is decomposed into the total number of electricity accounts and electricity usage per customer, each of which is modeled separately. A two-stage least squares approach is used to estimate the per customer electricity demand equations due to the endogeneity of the average price variable. The results indicate sustained growth in population, employment, and income can be expected to exert substantial upward pressure on regional electric power demand. Furthermore, demand is found to be price-inelastic in this metropolitan area, suggesting that rate increases can help raise the revenues necessary to fund expansion of the electrical grid.

  15. Modelling weather effects for impact analysis of residential time-of-use electricity pricing

    International Nuclear Information System (INIS)

    Miller, Reid; Golab, Lukasz; Rosenberg, Catherine

    2017-01-01

    Analyzing the impact of pricing policies such as time-of-use (TOU) is challenging in the presence of confounding factors such as weather. Motivated by a lack of consensus and model selection details in prior work, we present a methodology for modelling the effect of weather on residential electricity demand. The best model is selected according to explanatory power, out-of-sample prediction accuracy, goodness of fit and interpretability. We then evaluate the effect of mandatory TOU pricing in a local distribution company in southwestern Ontario, Canada. We use a smart meter dataset of over 20,000 households which is particularly suited to our analysis: it contains data from the summer before and after the implementation of TOU pricing in November 2011, and all customers transitioned from tiered rates to TOU rates at the same time. We find that during the summer rate season, TOU pricing results in electricity conservation across all price periods. The average demand change during on-peak and mid-peak periods is −2.6% and −2.4% respectively. Changes during off-peak periods are not statistically significant. These TOU pricing effects are less pronounced compared to previous studies, underscoring the need for clear, reproducible impact analyses which include full details about the model selection process. - Highlights: • We study models for the effect of weather on residential electricity demand. • We evaluate the effect of mandatory TOU pricing in a local distribution company in Ontario, Canada. • We find the effect of TOU pricing to be less pronounced compared to previous studies.

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

    International Nuclear Information System (INIS)

    Yamamoto, T.

    1995-01-01

    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 tariff options for residential/commercial and industrial consumers. R and D works have been carried out on various fields such as energy storage and heat storage which contribute to the improvement of the load factor. 5 figs., 2 tabs

  17. 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.

  18. 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......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......, and an integrated communications architecture to efficiently manage energy and comfort at the end-use location. By the aid of such technologies, residential consumers have also the capability to mitigate their energy costs and satisfy their own requirements paying less attention to the configuration of the energy...

  19. Decomposition of electricity demand in China's industrial sector

    International Nuclear Information System (INIS)

    Steenhof, Paul A.

    2006-01-01

    In the past five years, China's demand for electricity has accelerated far beyond what central planners had forecasted, leading to supply constraints and costly brownouts throughout the country. This paper presents analysis of the effect of changes in the industrial sector on electricity demand, an important economic sector contributing to these above patterns as it consumes nearly 70% of the electricity generated in China. Using decomposition analysis, it is found that both increased industrial activity and fuel shifts helped increase industrial sector electricity demand between 1998 and 2002, the period of focus in this study, but significant increases in energy efficiency countered this

  20. A summary of demand response in electricity markets

    International Nuclear Information System (INIS)

    Albadi, M.H.; El-Saadany, E.F.

    2008-01-01

    This paper presents a summary of demand response (DR) in deregulated electricity markets. The definition and the classification of DR as well as potential benefits and associated cost components are presented. In addition, the most common indices used for DR measurement and evaluation are highlighted, and some utilities' experiences with different demand response programs are discussed. Finally, the effect of demand response in electricity prices is highlighted using a simulated case study. (author)

  1. 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

    Before restructuring in the electricity industry, the primary decision-makers of the electricity market were deemed to be power generation and transmission companies, market regulation boards, and power industry regulators. In this traditional structure, consumers were interested in receiving...... 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....... 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...

  2. 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.

  3. [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

  4. 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.

  5. 77 FR 2743 - Recovery Directorate Fact Sheet 9580.213, Residential Electrical Meter Repair-“Power Up”

    Science.gov (United States)

    2012-01-19

    ...] Recovery Directorate Fact Sheet 9580.213, Residential Electrical Meter Repair--``Power Up'' AGENCY: Federal..., Residential Electrical Meter Repair--``Power Up.'' DATES: Comments must be received by February 21, 2012... authority, FEMA may fund the repair of residential electrical meters damaged in a major disaster or...

  6. Energy demand of the German and Dutch residential building stock under climate change

    Science.gov (United States)

    Olonscheck, Mady; Holsten, Anne; Walther, Carsten; Kropp, Jürgen P.

    2014-05-01

    In order to mitigate climate change, extraordinary measures are necessary in the future. The building sector, in particular, offers considerable potential for transformation to lower energy demand. On a national level, however, successful and far-reaching measures will likely be taken only if reliable estimates regarding future energy demand from different scenarios are available. The energy demand for space heating and cooling is determined by a combination of behavioral, climatic, constructional, and demographic factors. For two countries, namely Germany and the Netherlands, we analyze the combined effect of future climate and building stock changes as well as renovation measures on the future energy demand for room conditioning of residential buildings until 2060. We show how much the heating energy demand will decrease in the future and answer the question of whether the energy decrease will be exceeded by an increase in cooling energy demand. Based on a sensitivity analysis, we determine those influencing factors with the largest impact on the future energy demand from the building stock. Both countries have national targets regarding the reduction of the energy demand for the future. We provide relevant information concerning the annual renovation rates that are necessary to reach these targets. Retrofitting buildings is a win-win option as it not only helps to mitigate climate change and to lower the dependency on fossil fuels but also transforms the buildings stock into one that is better equipped for extreme temperatures that may occur more frequently with climate change. For the Netherlands, the study concentrates not only on the national, but also the provincial level, which should facilitate directed policy measures. Moreover, the analysis is done on a monthly basis in order to ascertain a deeper understanding of the future seasonal energy demand changes. Our approach constitutes an important first step towards deeper insights into the internal dynamics

  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. 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.

  9. The Assessment of Climatological Impacts on Agricultural Production and Residential Energy Demand

    Science.gov (United States)

    Cooter, Ellen Jean

    The assessment of climatological impacts on selected economic activities is presented as a multi-step, inter -disciplinary problem. The assessment process which is addressed explicitly in this report focuses on (1) user identification, (2) direct impact model selection, (3) methodological development, (4) product development and (5) product communication. Two user groups of major economic importance were selected for study; agriculture and gas utilities. The broad agricultural sector is further defined as U.S.A. corn production. The general category of utilities is narrowed to Oklahoma residential gas heating demand. The CERES physiological growth model was selected as the process model for corn production. The statistical analysis for corn production suggests that (1) although this is a statistically complex model, it can yield useful impact information, (2) as a result of output distributional biases, traditional statistical techniques are not adequate analytical tools, (3) the model yield distribution as a whole is probably non-Gausian, particularly in the tails and (4) there appears to be identifiable weekly patterns of forecasted yields throughout the growing season. Agricultural quantities developed include point yield impact estimates and distributional characteristics, geographic corn weather distributions, return period estimates, decision making criteria (confidence limits) and time series of indices. These products were communicated in economic terms through the use of a Bayesian decision example and an econometric model. The NBSLD energy load model was selected to represent residential gas heating consumption. A cursory statistical analysis suggests relationships among weather variables across the Oklahoma study sites. No linear trend in "technology -free" modeled energy demand or input weather variables which would correspond to that contained in observed state -level residential energy use was detected. It is suggested that this trend is largely the

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

    OpenAIRE

    D'Errico, Maria; Bollino, Carlo

    2015-01-01

    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 h...

  11. The Relationship between Residential Electricity Consumption and Income: A Piecewise Linear Model with Panel Data

    Directory of Open Access Journals (Sweden)

    Yanan Liu

    2016-10-01

    Full Text Available There are many uncertainties and risks in residential electricity consumption associated with economic development. Knowledge of the relationship between residential electricity consumption and its key determinant—income—is important to the sustainable development of the electric power industry. Using panel data from 30 provinces for the 1995–2012 period, this study investigates how residential electricity consumption changes as incomes increase in China. Previous studies typically used linear or quadratic double-logarithmic models imposing ex ante restrictions on the indistinct relationship between residential electricity consumption and income. Contrary to those models, we employed a reduced piecewise linear model that is self-adaptive and highly flexible and circumvents the problem of “prior restrictions”. Robust tests of different segment specifications and regression methods are performed to ensure the validity of the research. The results provide strong evidence that the income elasticity was approximately one, and it remained stable throughout the estimation period. The income threshold at which residential electricity consumption automatically remains stable or slows has not been reached. To ensure the sustainable development of the electric power industry, introducing higher energy efficiency standards for electrical appliances and improving income levels are vital. Government should also emphasize electricity conservation in the industrial sector rather than in residential sector.

  12. 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

  13. 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

  14. Demand Response Within Current Electricity Wholesale Market Design

    OpenAIRE

    Ramos Gutierrez, Ariana Isabel; De Jonghe, Cedric; Six, Daan; Belmans, Ronnie

    2013-01-01

    The introduction of intermittent energy resources calls for the ability to modulate consumption patterns according to electricity availability. This paper provides a brief overview of the main electricity market design characteristics and places demand response within the framework of the existing timeline of market operation. The main differences between electricity markets lie in the price formation mechanisms where some markets pay-as- cleared and some pay- as- bid for the electricity tran...

  15. Simulating Residential Demand in Singapore through Five Decades of Demographic Change

    Science.gov (United States)

    Davis, N. R.; Fernández, J.

    2011-12-01

    Singapore's rapid and well-documented development over the last half-century provides an ideal case for studying urban metabolism. Extensive data [1, 2] facilitate the modeling of historical dynamics of population and resource consumption. This paper presents an agent-based population model that simulates key demographic factors - number, size, and relative income of households - through fifty years of development in Singapore. This is the first step in a broader study linking demographic factors to residential demand for urban land, materials, water, and energy. Previous studies of the resource demands of housing stock have accounted for demographics by modifying the important population driver with a single, aggregated "lifestyle" term [3, 4]. However, demographic changes that result from development can influence the nature of the residential sector, and warrant a closer look. Increasing levels of education and affluence coupled with decreasing birth rates have yielded an aging population and changing family structures in Singapore [5]. These factors all contribute to an increasingly resource-intense residential sector. Singaporeans' elevated per capita income and life expectancy have created demand for larger household area, which means a growing percentage of available land must be dedicated to residential use [6]. While the majority of Singapore's housing is public - a strategy designed to maximize land use efficiency - residents are increasingly seeking private alternatives [7]. In the private sector, lower density housing puts even greater pressure on the finite supply of undeveloped land. Agent-based modeling is used to study the selected aspects of demography. The population is disaggregated into historical time-series distributions of age, family size, education, and income. We propose a simplified methodology correlating average education level with birth rate, and income to categorize households and establish housing unit demand. Aggregated lifestyle

  16. 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.

  17. Demand side management of electric car charging

    DEFF Research Database (Denmark)

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

    2012-01-01

    the purchase of alternative energy vehicles in an effort to achieve 10% EV (electric vehicle) penetration in the country's road fleet by 2020. The replacement of ICE (internal combustion engine) vehicles with EV equivalents poses challenges for grid operators while simultaneously offering opportunities...

  18. 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.

  19. Electrical Assessment, Capacity, and Demand Study for Fort Wainwright, Alaska

    National Research Council Canada - National Science Library

    Vavrin, John L; Brown, III, William T; Kemme, Michael R; Allen, Marcus A; Percle, Wayne J; Loran, Robert T; Stauffer, David B; Hudson, Kenneth

    2007-01-01

    .... Of particular importance was that FWA management projected that the installation might experience electrical power shortages during the impending winter of 2006/2007 due to increases in energy demand...

  20. 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

  1. Using Hydrated Salt Phase Change Materials for Residential Air Conditioning Peak Demand Reduction and Energy Conservation in Coastal and Transitional Climates in the State of California

    Science.gov (United States)

    Lee, Kyoung Ok

    The recent rapid economic and population growth in the State of California have led to a significant increase in air conditioning use, especially in areas of the State with coastal and transitional climates. This fact makes that the electric peak demand be dominated by air conditioning use of residential buildings in the summer time. This extra peak demand caused by the use of air conditioning equipment lasts only a few days out of the year. As a result, unavoidable power outages have occurred when electric supply could not keep up with such electric demand. This thesis proposed a possible solution to this problem by using building thermal mass via phase change materials to reduce peak air conditioning demand loads. This proposed solution was tested via a new wall called Phase Change Frame Wall (PCFW). The PCFW is a typical residential frame wall in which Phase Change Materials (PCMs) were integrated to add thermal mass. The thermal performance of the PCFWs was first evaluated, experimentally, in two test houses, built for this purpose, located in Lawrence, KS and then via computer simulations of residential buildings located in coastal and transitional climates in California. In this thesis, a hydrated salt PCM was used, which was added in concentrations of 10% and 20% by weight of the interior sheathing of the walls. Based on the experimental results, under Lawrence, KS weather, the PCFWs at 10% and 20% of PCM concentrations reduced the peak heat transfer rates by 27.0% and 27.3%, on average, of all four walls, respectively. Simulated results using California climate data indicated that PCFWs would reduce peak heat transfer rates by 8% and 19% at 10% PCM concentration and 12.2% and 27% at 20% PCM concentration for the coastal and transitional climates, respectively. Furthermore, the PCFWs, at 10% PCM concentration, would reduce the space cooling load and the annual energy consumption by 10.4% and 7.2%, on average in both climates, respectively.

  2. 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.

  3. 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

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

    Science.gov (United States)

    Chassin, David P [Pasco, WA; Donnelly, Matthew K [Kennewick, WA; Dagle, Jeffery E [Richland, WA

    2011-12-06

    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.

  5. 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

  6. An exploratory analysis of California residential customer response to critical peak pricing of electricity

    International Nuclear Information System (INIS)

    Herter, Karen; McAuliffe, Patrick; Rosenfeld, Arthur

    2007-01-01

    This paper summarizes the results from an exploratory analysis of residential customer response to a critical peak pricing (CPP) experiment in California, in which 15 times per year participating customers received high price signals dispatched by a local electricity distribution company. The high prices were about three times the on-peak price for the otherwise applicable time-of-use rate. Using hourly load data collected during the 15-month experiment, we find statistically significant load reduction for participants both with and without automated end-use control technologies. During 5-h critical peak periods, participants without control technology used up to 13% less energy than they did during normal peak periods. Participants equipped with programmable communicating thermostats used 25% and 41% less for 5 and 2h critical events, respectively. Thus, this paper offers convincing evidence that the residential sector can provide substantial contributions to retail demand response, which is considered a potential tool for mitigating market power, stabilizing wholesale market prices, managing system reliability, and maintaining system resource adequacy. (author)

  7. 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....

  8. Demand Response Application forReliability Enhancement in Electricity Market

    OpenAIRE

    Romera Pérez, Javier

    2015-01-01

    The term reliability is related with the adequacy and security during operation of theelectric power system, supplying the electricity demand over time and saving thepossible contingencies because every inhabitant needs to be supplied with electricity intheir day to day. Operating the system in this way entails spending money. The first partof the project is going to be an analysis of the reliability and the economic impact of it.During the last decade, electric utilities and companies had be...

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. Measuring the financial impact of demand response for electricity retailers

    International Nuclear Information System (INIS)

    Feuerriegel, Stefan; Neumann, Dirk

    2014-01-01

    Due to the integration of intermittent resources of power generation such as wind and solar, the amount of supplied electricity will exhibit unprecedented fluctuations. Electricity retailers can partially meet the challenge of matching demand and volatile supply by shifting power demand according to the fluctuating supply side. The necessary technology infrastructure such as Advanced Metering Infrastructures for this so-called Demand Response (DR) has advanced. However, little is known about the economic dimension and further effort is strongly needed to realistically quantify the financial impact. To succeed in this goal, we derive an optimization problem that minimizes procurement costs of an electricity retailer in order to control Demand Response usage. The evaluation with historic data shows that cost volatility can be reduced by 7.74%; peak costs drop by 14.35%; and expenditures of retailers can be significantly decreased by 3.52%. - Highlights: • Ex post simulation to quantify financial impacts of demand response. • Effects of Demand Response are simulated based on real-world data. • Procurement costs of an average electricity retailer decrease by 3.4%. • Retailers can cut hourly peak expenditures by 12.1%. • Cost volatility is reduced by 12.2%

  14. Reevaluation of Turkey's hydropower potential and electric energy demand

    International Nuclear Information System (INIS)

    Yueksek, Omer

    2008-01-01

    This paper deals with Turkey's hydropower potential and its long-term electric energy demand predictions. In the paper, at first, Turkey's energy sources are briefly reviewed. Then, hydropower potential is analyzed and it has been concluded that Turkey's annual economically feasible hydropower potential is about 188 TWh, nearly 47% greater than the previous estimation figures of 128 TWh. A review on previous prediction models for Turkey's long-term electric energy demand is presented. In order to predict the future demand, new increment ratio scenarios, which depend on both observed data and future predictions of population, energy consumption per capita and total energy consumption, are developed. The results of 11 prediction models are compared and analyzed. It is concluded that Turkey's annual electric energy demand predictions in 2010, 2015 and 2020 vary between 222 and 242 (average 233) TWh; 302 and 356 (average 334) TWh; and 440 and 514 (average 476) TWh, respectively. A discussion on the role of hydropower in meeting long-term demand is also included in the paper and it has been predicted that hydropower can meet 25-35% of Turkey's electric energy demand in 2020

  15. 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.

  16. 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.

  17. Climate change and electricity demand in Brazil: A stochastic approach

    International Nuclear Information System (INIS)

    Trotter, Ian M.; Bolkesjø, Torjus Folsland; Féres, José Gustavo; Hollanda, Lavinia

    2016-01-01

    We present a framework for incorporating weather uncertainty into electricity demand forecasting when weather patterns cannot be assumed to be stable, such as in climate change scenarios. This is done by first calibrating an econometric model for electricity demand on historical data, and subsequently applying the model to a large number of simulated weather paths, together with projections for the remaining determinants. Simulated weather paths are generated based on output from a global circulation model, using a method that preserves the trend and annual seasonality of the first and second moments, as well as the spatial and serial correlations. The application of the framework is demonstrated by creating long-term, probabilistic electricity demand forecasts for Brazil for the period 2016–2100 that incorporates weather uncertainty for three climate change scenarios. All three scenarios indicate steady growth in annual average electricity demand until reaching a peak of approximately 1071–1200 TWh in 2060, then subsequently a decline, largely reflecting the trajectory of the population projections. The weather uncertainty in all scenarios is significant, with up to 400 TWh separating the 10th and the 90th percentiles, or approximately ±17% relative to the mean. - Highlights: • Large number of realistic weather paths generated based on output from a single GCM. • Simulated weather paths used to include weather uncertainty in demand forecasting. • We present a probabilistic electricity demand forecast for Brazil 2016–2100. • Annual Brazilian electricity demand will peak around 2060 at about 1071–1200 TWh. • Significant weather uncertainty, ∼400 TWh separating the 10th and 90th percentiles.

  18. 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)

    1994-12-31

    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.

  19. 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.

  20. Modeling climate feedbacks to electricity demand: The case of China

    International Nuclear Information System (INIS)

    Asadoorian, Malcolm O.; Eckaus, Richard S.; Schlosser, C. Adam

    2008-01-01

    This paper is an empirical investigation of the effects of climate on the use of electricity by consumers and producers in urban and rural areas within China. It takes advantage of an unusual combination of temporal and regional data sets in order to estimate temperature, as well as price and income elasticities of electricity demand. The estimated positive temperature/electric power feedback implies a continually increasing use of energy to produce electric power which, in China, is primarily based on coal. In the absence of countervailing measures, this will contribute to increased emissions, increased atmospheric concentrations of greenhouse gases, and increases in greenhouse warming

  1. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Sa' ad, Suleiman [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

    2011-01-15

    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)

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

    Energy Technology Data Exchange (ETDEWEB)

    Sa' ad, Suleiman, E-mail: suleimansaad@gmail.co [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

    2011-01-15

    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.

  4. 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)

  5. Reducing Electricity Demand Peaks by Scheduling Home Appliances Usage

    DEFF Research Database (Denmark)

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

    2011-01-01

    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...... should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power...... consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions...

  6. Exploring variance in residential electricity consumption: Household features and building properties

    International Nuclear Information System (INIS)

    Bartusch, Cajsa; Odlare, Monica; Wallin, Fredrik; Wester, Lars

    2012-01-01

    Highlights: ► Statistical analysis of variance are of considerable value in identifying key indicators for policy update. ► Variance in residential electricity use is partly explained by household features. ► Variance in residential electricity use is partly explained by building properties. ► Household behavior has a profound impact on individual electricity use. -- Abstract: Improved means of controlling electricity consumption plays an important part in boosting energy efficiency in the Swedish power market. Developing policy instruments to that end requires more in-depth statistics on electricity use in the residential sector, among other things. The aim of the study has accordingly been to assess the extent of variance in annual electricity consumption in single-family homes as well as to estimate the impact of household features and building properties in this respect using independent samples t-tests and one-way as well as univariate independent samples analyses of variance. Statistically significant variances associated with geographic area, heating system, number of family members, family composition, year of construction, electric water heater and electric underfloor heating have been established. The overall result of the analyses is nevertheless that variance in residential electricity consumption cannot be fully explained by independent variables related to household and building characteristics alone. As for the methodological approach, the results further suggest that methods for statistical analysis of variance are of considerable value in indentifying key indicators for policy update and development.

  7. Scenario analysis on future electricity supply and demand in Japan

    International Nuclear Information System (INIS)

    Zhang, Qi; Ishihara, Keiichi N.; Mclellan, Benjamin C.; Tezuka, Tetsuo

    2012-01-01

    Under continuing policies of CO 2 emissions reduction, it is crucial to consider scenarios for Japan to realize a safe and clean future electricity system. The development plans for nuclear power and renewable energy - particularly solar and wind power - are being reconsidered in light of the Fukushima nuclear accident. To contribute to this, in the present study, three electricity supply scenarios for 2030 are proposed according to different future nuclear power development policies, and the maximum penetration of renewable energy generation is pursued. On the other side of the equation, three electricity demand scenarios are also proposed considering potential energy saving measures. The purpose of the study is to demonstrate quantitatively the technological, economic and environmental impacts of different supply policy selections and demand assumptions on future electricity systems. The scenario analysis is conducted using an input–output hour-by-hour simulation model subject to constraints from technological, economic and environmental perspectives. The obtained installed capacity mix, power generation mix, CO 2 emissions, and generation cost of the scenarios were inter-compared and analyzed. The penetration of renewable energy generation in a future electricity system in Japan, as well as its relationship with nuclear power share was uncovered. -- Highlights: ► Scenario analysis is conducted on future electricity systems under different supply policies and demand assumptions. ► Scenario analysis is conducted using a input–output hour-by-hour simulation model for real-time demand-supply balance. ► The technological, economic and environmental impacts of supply policies and demand assumptions on future electricity systems are studied. ► The maximum penetration of renewable energy generation is pursued in the scenario analysis using the hour-by-hour simulation. ► The relationship between the penetration levels of renewable energy and nuclear power

  8. 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.

  9. 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

  10. Modeling and forecasting of electrical power demands for capacity planning

    International Nuclear Information System (INIS)

    Al-Shobaki, S.; Mohsen, M.

    2007-01-01

    Jordan imports oil from neighboring countries for use in power production. As such, the cost of electricity production is high compared to oil producing countries. It is anticipated that Jordan will face major challenges in trying to meet the growing energy and electricity demands while also developing the energy sector in a way that reduces any adverse impacts on the economy, the environment and social life. This paper described the development of forecasting models to predict future generation and sales loads of electrical power in Jordan. Two models that could be used for the prediction of electrical energy demand in Amman, Jordan were developed and validated. An analysis of the data was also presented. The first model was based on the levels of energy generated by the National Electric Power Company (NEPCO) and the other was based on the levels of energy sold by the company in the same area. The models were compared and the percent error was presented. Energy demand was also forecasted across the next 60 months for both models. Results were then compared with the output of the in-house forecast model used by NEPCO to predict the levels of generated energy needed across the 60 months time period. It was concluded that the NEPCO model predicted energy demand higher than the validated generated data model by an average of 5.25 per cent. 8 refs., 5 tabs., 15 figs

  11. Modeling and forecasting of electrical power demands for capacity planning

    Energy Technology Data Exchange (ETDEWEB)

    Al-Shobaki, S. [Hashemite Univ., Zarka (Jordan). Dept. of Industrial Engineering; Mohsen, M. [Hashemite Univ., Zarka (Jordan). Dept. of Mechanical Engineering

    2007-07-01

    Jordan imports oil from neighboring countries for use in power production. As such, the cost of electricity production is high compared to oil producing countries. It is anticipated that Jordan will face major challenges in trying to meet the growing energy and electricity demands while also developing the energy sector in a way that reduces any adverse impacts on the economy, the environment and social life. This paper described the development of forecasting models to predict future generation and sales loads of electrical power in Jordan. Two models that could be used for the prediction of electrical energy demand in Amman, Jordan were developed and validated. An analysis of the data was also presented. The first model was based on the levels of energy generated by the National Electric Power Company (NEPCO) and the other was based on the levels of energy sold by the company in the same area. The models were compared and the percent error was presented. Energy demand was also forecasted across the next 60 months for both models. Results were then compared with the output of the in-house forecast model used by NEPCO to predict the levels of generated energy needed across the 60 months time period. It was concluded that the NEPCO model predicted energy demand higher than the validated generated data model by an average of 5.25 per cent. 8 refs., 5 tabs., 15 figs.

  12. 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

  13. Modulation strategies of integrated HVAC systems used in residential buildings for demand-side management at different scales

    OpenAIRE

    Georges, Emeline

    2017-01-01

    The integration of renewable energy sources in the electricity production mix has an important impact on the management of the electricity grid, due to their intermittency. In particular, to ensure grid balancing, there is a rising need for flexibility, both on the supply and demand sides. A possible solution to help achieve grid balancing is the smart modulation of the electrical load in a "demand following supply" scheme through demand-side management. In this context, the objective of...

  14. Demand for natural gas: residential and commercial markets in Ontario and British Columbia. [Econometric-model analysis

    Energy Technology Data Exchange (ETDEWEB)

    Berndt, E R [Univ. of British Columbia, Vancouver; Watkins, G C

    1977-02-01

    An econometric model is used to project natural gas demand in the residential and commercial market sectors. The model specification is a generalization of one developed by Balestra and Nerlove (Econometrica, 34: 585-612(1966)). Demand that is potentially variable because it is not committed to past investments (flexibe demand) is distinguished from demand that is inflexible because it is tied to existing equipment stocks (captive demand). Attention is focused on the effect of temperature variations on gas demand. The nonlinear equation system is estimated by a maximum-likelihood method, using annual data for British Columbia and Ontario during the period of 1959 to 1974. Results show that only in the long run does price have a significant impact on demand. The model is applicable for medium-term policy simulation, but is limited to natural gas fuel. 15 references.

  15. Price-elastic demand in deregulated electricity markets

    OpenAIRE

    Siddiqui, Afzal S.

    2003-01-01

    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 mo...

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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)

  1. 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)

  2. 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)

  3. An assessment of the influence of demand response on demand elasticity in electricity retail market

    NARCIS (Netherlands)

    Fonteijn, R.; Babar, M.; Kamphuis, I.G.

    2015-01-01

    A transition towards a sustainable society is currently ongoing. In the electrical power system, this is reflected by the increasing share of renewable energy sources (RES). The weather dependence of some RES results in intermittent and volatile behaviour, thus matching supply and demand has become

  4. Impact of energy storage in buildings on electricity demand side management

    International Nuclear Information System (INIS)

    Qureshi, Waqar A.; Nair, Nirmal-Kumar C.; Farid, Mohammad M.

    2011-01-01

    Research highlights: → Phase change material (PCM) application for space heating has been implemented and assessed for built environment. → Real-Time Pricing (RTP) is assessed as tool to implement Demand Side Management programs effectively. → Two buildings, with and without PCM, have been compared for space heating using RTP in functional electricity market. → PCM found to offer peak load shifting, energy conservation, and reduction in price of electricity. -- Abstract: This paper assesses impact of using phase change materials (PCM) in buildings to leverage its thermal energy storage capability. The emphasis is from an electricity demand side perspective with case studies that incorporates wholesale electricity market data of New Zealand. The results presented in this paper show that for space heating application significant advantages could be obtained using PCM built structures. These positive impacts include peak load shifting, energy conservation and reduction in peak demand for network line companies and potential reduction in electricity consumption and savings for residential customers. This paper uses a testing facility that consists of two identically designed and shaped offices built at Tamaki Campus location of the University of Auckland, New Zealand. The walls and ceilings of one office are finished with ordinary gypsum boards while the interior of the other office is finished with PCM impregnated gypsum boards. Controlled heating facility is provided in both the offices for maintaining temperature within the range of human comfort. This facility is equipped with advanced data acquisition equipment for data monitoring and archiving both locally within the offices and also remotely. Through actual observations and analysis this paper demonstrates two major impacts of DSM. First, the application of phase change material (PCM) in building environment enabling efficient thermal storage to achieve some reduction in the overall electrical energy

  5. The role of hydropower in meeting Turkey's electric energy demand

    International Nuclear Information System (INIS)

    Yuksek, Omer; Komurcu, Murat Ihsan; Yuksel, Ibrahim; Kaygusuz, Kamil

    2006-01-01

    The inherent technical, economic and environmental benefits of hydroelectric power, make it an important contributor to the future world energy mix, particularly in the developing countries. These countries, such as Turkey, have a great and ever-intensifying need for power and water supplies and they also have the greatest remaining hydro potential. From the viewpoint of energy sources such as petroleum and natural gas, Turkey is not a rich country; but it has an abundant hydropower potential to be used for generation of electricity and must increase hydropower production in the near future. This paper deals with policies to meet the increasing electricity demand for Turkey. Hydropower and especially small hydropower are emphasized as Turkey's renewable energy sources. The results of two case studies, whose results were not taken into consideration in calculating Turkey's hydro electric potential, are presented. Turkey's small hydro power potential is found to be an important energy source, especially in the Eastern Black Sea Region. The results of a study in which Turkey's long-term demand has been predicted are also presented. According to the results of this paper, Turkey's hydro electric potential can meet 33-46% of its electric energy demand in 2020 and this potential may easily and economically be developed

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

    DEFF Research Database (Denmark)

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

    2017-01-01

    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...... of households in Denmark. The model considers hourly consumption profiles for different household appliances and their contribution to annual household electricity consumption. When applying the model to an official scenario for annual electricity consumption, assuming non-flexible consumption due...... to a considerable introduction of electric vehicles and individual heat pumps, household consumption is expected to increase considerably, especially peak hour consumption is expected to increase.Next the paper presents results from a new experiment where household customers are given economic and/or environmental...

  7. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Chattopadhyay, Pradip [New Hampshire Public Utilities Commission, 21 South Fruit Street, Suite 10, Concord NH 03301 (United States)]. E-mail: pradip.chattopadhyay@puc.nh.gov

    2007-01-15

    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.

  9. 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

  10. The impact of consumer behavior on residential energy demand for space heating

    Energy Technology Data Exchange (ETDEWEB)

    Haas, R.; Auer, H.; Biermayr, P. [Vienna Univ. of Technology (Austria). Inst. of Energy Economics

    1998-04-01

    Besides technical parameters, consumer behavior is the most important issue with respect to energy consumption in households. In this paper, the results of a cross-section analysis of Austrian households are presented. The impact of the following parameters on residential energy demand for space heating have been investigated: (i) thermal quality of buildings; (ii) consumer behavior; (iii) heating degree days; (iv) building type (single- or multi-family dwellings). The result of this investigation provides evidence of a rebound-effect of about 15 to 30% due to building retrofit. This leads to the conclusion that energy savings achieved in practice (and straightforward the reduction in CO{sub 2} emissions) due to energy conservation measures will be lower than those calculated in engineering conservation studies. Straightforward, the most important conclusions for energy policy makers are: (i) Standards, building codes, respectively, are important tools to increase the thermal quality of new buildings; and (ii) Due to prevailing low energy prices, a triggering tool has to be implemented which may be rebates or loans. (orig.)

  11. Demand response offered by households with direct electric heating

    International Nuclear Information System (INIS)

    Kofod, C.; Togeby, M.

    2004-01-01

    The peak power balance in the Nordic power system is gradually turning to be very tight, especially in the electric area of southern Sweden and eastern Denmark. Power stations are closed and hardly any investments in new production are carried out. Demand response is considered essential when the formation of spot prices shall send the signal of needed investments in new capacity. Demand response which are based on individual preferences, and carried out automatically, can be one way to increase the volume of price elastic demand. Demand response need hourly metering for calculation and documentation of the decrease in demand, and controllability in order to meet the timing requirements. Within the EU SAVE project EFFLOCOM (2002 - 2004), a Danish demand response pilot project was established in 2003 including 25 single family homes with direct electrical heating. The system has been tested during the winter 2003/2004. The tested technologies include hourly metering, communication by GRPS as well as the Internet. GPRS is used for daily remote meter reading and automatic control of the electric heating including individual control of up to five zones. The system is designed for automatic activation when the Nord Pool hourly Elspot prices exceed preset levels. The system can also be used as regulating power. The EFFLOCOM Web Bite includes an interactive demonstrator of the system. The developed customer Web Bite is including the services: 1) Access to setting the limits for the maximum duration of interruption for up to five different control zones for two periods of the day and for three price levels. 2) Access to stop an actual interruption. 3) A report on the hourly, daily, weekly and monthly use of electricity and the saved bonus by demand response control. The report is updated daily. The goals of up to 5 kW controlled per house were fulfilled. Besides the demand response bonus the customers have also saved electricity. A customer survey did show that the

  12. 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.

  13. Heating and cooling energy demand and related emissions of the German residential building stock under climate change

    International Nuclear Information System (INIS)

    Olonscheck, Mady; Holsten, Anne; Kropp, Juergen P.

    2011-01-01

    The housing sector is a major consumer of energy. Studies on the future energy demand under climate change which also take into account future changes of the building stock, renovation measures and heating systems are still lacking. We provide the first analysis of the combined effect of these four influencing factors on the future energy demand for room conditioning of residential buildings and resulting greenhouse gas (GHG) emissions in Germany until 2060. We show that the heating energy demand will decrease substantially in the future. This shift will mainly depend on the number of renovated buildings and climate change scenarios and only slightly on demographic changes. The future cooling energy demand will remain low in the future unless the amount of air conditioners strongly increases. As a strong change in the German energy mix is not expected, the future GHG emissions caused by heating will mainly depend on the energy demand for future heating. - Highlights: → The future heating energy demand of German residential buildings strongly decreases. → Extent of these changes mainly depends on the number of renovated buildings. → Demographic changes will only play a minor role. → Cooling energy demand will remain low in future but with large insecurities. → Germany's 2050 emission targets for the building stock are ambitious.

  14. 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.

  15. 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

  16. Warm homes: Drivers of the demand for heating in the residential sector in New Zealand

    International Nuclear Information System (INIS)

    Howden-Chapman, Philippa; Viggers, Helen; Chapman, Ralph; O'Dea, Des; Free, Sarah; O'Sullivan, Kimberley

    2009-01-01

    New Zealand houses are large, often poorly constructed and heated, by OECD standards, and consequently are colder and damper indoors than recommended by the World Health Organisation. This affects both the energy consumption and the health of households. The traditional New Zealand household pattern of only heating one room of the house has been unchanged for decades, although there has been substantial market penetration of unflued gas heaters and more recently heat pumps. This paper describes the residential sector and the results of two community-based trials of housing and heating interventions that have been designed to measure the impact of (1) retrofitting insulation and (2) replacing unflued gas heaters and electric resistance heaters with heat pumps, wood pellet burners and flued gas heaters. The paper describes findings on the rebound effect or 'take-back'-the extent to which households take the gains from insulation and heating improvements as comfort (higher temperatures) rather than energy savings, and compares energy-saving patterns with those suggested by an earlier study. Findings on these aspects of household space heating are discussed in the context of the New Zealand government's policy drive for a more sustainable energy system, and the implications for climate change policy.

  17. 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...

  18. 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.

  19. 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....

  20. 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.

  1. An Analysis on change of household electricity demand pattern

    Energy Technology Data Exchange (ETDEWEB)

    Na, In Gang [Korea Energy Economics Institute, Euiwang (Korea)

    1999-01-01

    The object of this study is to analyze the behavioral pattern change of household electricity demand. Through the cross section analysis using materials from the energy total research report, the change in income elasticity of household electricity demand was studied. In this study, two methodologies were used. Firstly, it was shown that the effect of an income variable was very significant with a positive value in simultaneous equations model using exponential equations of electrical appliances holding. Cross section income effect showed a various distribution according to the season or income level. Overall, it was calculated at 0.111 when the appliances are fixed and 0.432 when even appliances are changed. Secondly, using a choice convenient correction model, it is resulted that lambda, the choice convenient correction factor, has a positive value and is statistically significant. In 1996, income elasticity of electricity demand for households with air-conditioning was 0.305 and for households without air-conditioning was 0.172. Income elasticity of households with air-conditioning is increasing as time goes by while income elasticity of households without air-conditioning is decreasing. (author). 32 refs., 35 tabs.

  2. 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

  3. Demand for electric power in major markets worldwide

    Energy Technology Data Exchange (ETDEWEB)

    Roeder, A [ABB Asea Brown Boveri Ltd., Zurich (Switzerland)

    1990-01-01

    One third of primary energy consumption is today being used to generate electrical power. The author discusses with the aid of statistics and diagrams, the various uses of energy, and the per capita energy consumption throughout the world. He considers that future demand for power depends to a large extent on GNP but also on fuel prices and reserves, energy policies and environmental concerns. On balance, these will lead to the introduction of clean coal technologies and a renaissance of nuclear power stations in the near future but until then gas-fired power plant will continue to play a dominant role in meeting power demands. 9 figs., 8 tabs.

  4. 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

  5. A Study on Grid-Square Statistics Based Estimation of Regional Electricity Demand and Regional Potential Capacity of Distributed Generators

    Science.gov (United States)

    Kato, Takeyoshi; Sugimoto, Hiroyuki; Suzuoki, Yasuo

    We established a procedure for estimating regional electricity demand and regional potential capacity of distributed generators (DGs) by using a grid square statistics data set. A photovoltaic power system (PV system) for residential use and a co-generation system (CGS) for both residential and commercial use were taken into account. As an example, the result regarding Aichi prefecture was presented in this paper. The statistical data of the number of households by family-type and the number of employees by business category for about 4000 grid-square with 1km × 1km area was used to estimate the floor space or the electricity demand distribution. The rooftop area available for installing PV systems was also estimated with the grid-square statistics data set. Considering the relation between a capacity of existing CGS and a scale-index of building where CGS is installed, the potential capacity of CGS was estimated for three business categories, i.e. hotel, hospital, store. In some regions, the potential capacity of PV systems was estimated to be about 10,000kW/km2, which corresponds to the density of the existing area with intensive installation of PV systems. Finally, we discussed the ratio of regional potential capacity of DGs to regional maximum electricity demand for deducing the appropriate capacity of DGs in the model of future electricity distribution system.

  6. 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.

  7. Development of the Optimum Operation Scheduling Model of Domestic Electric Appliances for the Supply-Demand Adjustment in a Power System

    Science.gov (United States)

    Ikegami, Takashi; Iwafune, Yumiko; Ogimoto, Kazuhiko

    The high penetration of variable renewable generation such as Photovoltaic (PV) systems will cause the issue of supply-demand imbalance in a whole power system. The activation of the residential power usage, storage and generation by sophisticated scheduling and control using the Home Energy Management System (HEMS) will be needed to balance power supply and demand in the near future. In order to evaluate the applicability of the HEMS as a distributed controller for local and system-wide supply-demand balances, we developed an optimum operation scheduling model of domestic electric appliances using the mixed integer linear programming. Applying this model to several houses with dynamic electricity prices reflecting the power balance of the total power system, it was found that the adequate changes in electricity prices bring about the shift of residential power usages to control the amount of the reverse power flow due to excess PV generation.

  8. 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

  9. Managing electrical demand through difficult periods: California's experience with demand response

    International Nuclear Information System (INIS)

    Wikler, G.; Ghosh, D.Ph.D.

    2010-01-01

    This paper provides a brief overview of California's electricity situation and the relevance of Demand Response (DR) in addressing some of the challenges faced by the State's electricity system. It then discusses California's experience with DR, market rules that influence what role DR plays and attempts to integrate wholesale-retail level program offerings in the State, and some of the key drivers that are likely to enhance the role of DR. Lastly, the paper identifies some of the key challenges facing implementers of DR programs and discusses how many of those challenges could potentially be overcome. (authors)

  10. 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

  11. Reducing electricity demand peaks by scheduling home appliances usage

    Energy Technology Data Exchange (ETDEWEB)

    Rossello-Busquet, A.; Kardaras, G.; Baek Iversen, V.; Soler, J.; Dittmann, L.

    2011-05-15

    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 should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions. 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 (RFS) algorithm, which was originally developed for telecommunication networks, is applied. The purpose is to analyze how a power consumption limit and priorities for home appliances will affect the demand peak and the users' everyday life. Verification of the effectiveness of the RFS algorithm is done by means of simulation and by using real data for power consumption and operation hours. The defined maximum power limit of 750 and 1000 Watt was not exceeded during

  12. Demand Response in U.S. Electricity Markets: Empirical Evidence

    OpenAIRE

    Cappers, Peter

    2009-01-01

    Empirical evidence concerning demand response (DR) resources is needed in order to establish baseline conditions, develop standardized methods to assess DR availability and performance, and to build confidence among policymakers, utilities, system operators, and stakeholders that DR resources do offer a viable, cost-effective alternative to supply-side investments. This paper summarizes the existing contribution of DR resources in U.S. electric power markets. In 2008, customers enrolled in ...

  13. Production in Italian industry: Electric power demand indicators

    International Nuclear Information System (INIS)

    Ajello, V.

    1993-01-01

    The effects of the recession in Italy were first evidenced during the period spanning 1990-1992 with a sharp drop in the international competitiveness of Italian products. This phase was then followed by a significant drop in internal demand, the devaluation of the Italian Lira and subsequent market uncertainty. This paper presents graphs of national and regional electric power production and consumption figures which reflect the downturn in the viability of the Italian economy, especially in the industrial sector

  14. FACTORS DECREASING HOUSEHOLD ELECTRICITY DEMAND – A QUALITATIVE APPROACH

    Directory of Open Access Journals (Sweden)

    Shimon ELBAZ

    2018-05-01

    Full Text Available Reducing energy consumption through changes in individual consumers’ behaviors is one of the most important challenges of the present society and near future. Our qualitative study, based on semi-structured interviews, deals with the investigation of household consumer behavior, in order to explore ways for reducing the electricity demand, in the particular cultural context of a country with high levels of energy consumption in both summer and winter times – Israel. Various approaches, coming from economics, sociology, psychology or education were tested, for limiting the use of a particular, invisible and intangible merchandise - electricity. The main objective of the present study was to determine consumers’ perceptions about the various approaches that could be used to decrease the domestic demand and consumption of electricity. A secondary objective was to identify, based on consumers’ perceptions, the factors of influence that could be used in future quantitative researches and governance strategies. We found out that investigated families have a high level of education in the field of electricity consumption and marketing campaigns, which would make the classic energy educational approach less efficient. Household electricity consumers in Israel have awareness and willingness not to waste or consume electricity beyond what is necessary, but the necessary level is positioned quite high. The social comparison approach appears to be ineffective, as well, even if it proved its efficiency in other cultures. The psychological and the economic approach could be partially efficient, if certain influence factors are widely used. These factors include mainly the magnitude of the savings, the perceived behavioral control, the personal thermal comfort and the pro-environmental attitude. The most important managerial implication concerns the strategies that could be conceived by electricity companies and national authorities – based on un

  15. Mitigation of the Impact of High Plug-in Electric Vehicle Penetration on Residential Distribution Grid Using Smart Charging Strategies

    Directory of Open Access Journals (Sweden)

    Chong Cao

    2016-12-01

    Full Text Available Vehicle electrification presents a great opportunity to reduce transportation greenhouse gas emissions. The greater use of plug-in electric vehicles (PEVs, however, puts stress on local distribution networks. This paper presents an optimal PEV charging control method integrated with utility demand response (DR signals to mitigate the impact of PEV charging to several aspects of a grid, including load surge, distribution accumulative voltage deviation, and transformer aging. To build a realistic PEV charging load model, the results of National Household Travel Survey (NHTS have been analyzed and a stochastic PEV charging model has been defined based on survey results. The residential distribution grid contains 120 houses and is modeled in GridLAB-D. Co-simulation is performed using Matlab and GridLAB-D to enable the optimal control algorithm in Matlab to control PEV charging loads in the residential grid modeled in GridLAB-D. Simulation results demonstrate the effectiveness of the proposed optimal charging control method in mitigating the negative impacts of PEV charging on the residential grid.

  16. The effect of economic factors and energy efficiency programs on residential electricity consumption

    Science.gov (United States)

    Sakai, Mihoko

    Many countries have implemented policies to correct market and behavioral failures that lead to inefficient energy use. It is important to know what factors and policies can effectively overcome such failures and improve energy efficiency; however, a comprehensive analysis has been difficult because of data limitations. Using state scores compiled by American organizations recently, and adopting fixed-effects regression models, I analyze the joint impacts of relevant factors and policy programs on residential electricity consumption in each U.S. state. The empirical results reveal that increases in electricity price have small and negative effects, and increases in personal income have positive effects on residential electricity sales per capita (a measure of energy efficiency). The results suggest that it may take time for economic factors to affect electricity sales. The effects of personal income suggest the difficulty of controlling residential electricity consumption; however, they also imply that there is some room in households to reduce electricity use. The study also finds that programs and budgets of several policies seem to be associated with electricity sales. The estimates from a model including interaction terms suggest the importance of including multiple policies when analyzing and designing policies to address electricity efficiency. The results also imply the possibility of rebound effects of some policies, whereby improvements in energy efficiency lead to increases in energy consumption due to the associated lower per unit cost. Future studies should analyze both short-term and long-term effects of economic factors and policies, based on improved and accumulated time series and panel data, in order to design more effective policies for improving residential electricity efficiency.

  17. 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

  18. 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.

  19. A critical look at residential electricity conservation campaigns in a developing country environment

    International Nuclear Information System (INIS)

    Martino Jannuzzi, G. de; Ferreira Santos, V. dos

    1993-01-01

    This paper analyse survey results of the effectiveness of information campaigns to promote energy efficiency among residential consumers in Brazil. The survey found that consumers have a relatively good knowledge of conservation measures to improve electricity usage. Nevertheless, other approaches are needed to promote energy conservation in the household sector. (author). 3 refs, 4 figs, 2 tabs

  20. Experimental device for the residential heating with heat pipe and electric heat storage blocks

    Energy Technology Data Exchange (ETDEWEB)

    Vasiliev, L L; Boldak, I M; Domorod, L S; Rabetsky, M I; Schirokov, E I [AN Belorusskoj SSR, Minsk (Belarus). Inst. Teplo- i Massoobmena

    1992-01-01

    Residential heating using electric heat storage blocks nowadays is an actual problem from the point of view of heat recovery and nature protection. In the Luikov Heat and Mass Transfer Institute a new residential electrical heater capable of heating chambers by controlling air temperature and heat output using heat pipes and an electric heat storage block was developed. This heater (BETA) is fed from the source of energy and during 7 h of night time accumulates energy sufficiently to heat 10 m{sup 3} during 24 h. Heating device BETA has a ceramic thermal storage block, electric heaters and a heat pipe with evaporator inside the ceramic block and constant temperature (65{sup o}C) finned condenser outside it. The condenser temperature could be controlled easily. BETA is compact, has high thermal response, accurate air temperature control and safe operation. Such types of residential heaters are necessary for heating residential and office building in the Mogilev and Gomel regions in Byelorussia which suffered after the Chernobyl catastrophe. (Author).

  1. Hourly price elasticity pattern of electricity demand in the German day-ahead market

    OpenAIRE

    Knaut, Andreas; Paulus, Simon

    2016-01-01

    System security in electricity markets relies crucially on the interaction between demand and supply over time. However, research on electricity markets has been mainly focusing on the supply side arguing that demand is rather inelastic. Assuming perfectly inelastic demand might lead to delusive statements regarding the price formation in electricity markets. In this article we quantify the short-run price elasticity of electricity demand in the German day-ahead market and show that demand is...

  2. 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.

  3. Medium-term electric power demand forecasting based on economic-electricity transmission model

    Science.gov (United States)

    Li, Wenfeng; Bao, Fangmin; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Mao, Yubin; Wang, Jiangbo; Liu, Junhui

    2018-06-01

    Electric demand forecasting is a basic work to ensure the safe operation of power system. Based on the theories of experimental economics and econometrics, this paper introduces Prognoz Platform 7.2 intelligent adaptive modeling platform, and constructs the economic electricity transmission model that considers the economic development scenarios and the dynamic adjustment of industrial structure to predict the region's annual electricity demand, and the accurate prediction of the whole society's electricity consumption is realized. Firstly, based on the theories of experimental economics and econometrics, this dissertation attempts to find the economic indicator variables that drive the most economical growth of electricity consumption and availability, and build an annual regional macroeconomic forecast model that takes into account the dynamic adjustment of industrial structure. Secondly, it innovatively put forward the economic electricity directed conduction theory and constructed the economic power transfer function to realize the group forecast of the primary industry + rural residents living electricity consumption, urban residents living electricity, the second industry electricity consumption, the tertiary industry electricity consumption; By comparing with the actual value of economy and electricity in Henan province in 2016, the validity of EETM model is proved, and the electricity consumption of the whole province from 2017 to 2018 is predicted finally.

  4. The design of optimal electric power demand management contracts

    Science.gov (United States)

    Fahrioglu, Murat

    1999-11-01

    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. Electric utilities try to provide reliable supply of electric power to their customers. Maximum customer benefit derives from minimum cost and sufficient supply availability. Customers willing to share in "availability risk" can derive further benefit by participating in controlled outage programs. Specifically, whenever utilities foresee dangerous loading patterns, there is a need for a rapid reduction in demand either system-wide or at specific locations. The utility needs to get relief in order to solve its problems quickly and efficiently. This relief can come from customers who agree to curtail their loads upon request in exchange for an incentive fee. This thesis shows how utilities can get efficient load relief while maximizing their economic benefit. This work also shows how estimated customer cost functions can be calibrated, using existing utility data, to help in designing efficient demand management contracts. In order to design such contracts, optimal mechanism design is adopted from "Game Theory" and applied to the interaction between a utility and its customers. The idea behind mechanism design is to design an incentive structure that encourages customers to sign up for the right contract and reveal their true value of power. If a utility has demand management contracts with customers at critical locations, most operational problems can be solved efficiently. This thesis illustrates how locational attributes of customers incorporated into demand management contract design can have a significant impact in solving system problems. This kind of demand management contracts can also be used by an Independent System Operator (ISO). During times of congestion a loss of economic surplus occurs. When the market is too slow or cannot help relieve congestion, demand management

  5. 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.

  6. 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

  7. Demand response in liberalized electricity markets - the Nordic case

    International Nuclear Information System (INIS)

    Bjoerndal, Mette; Lund, Arne-Christian; Rud, Linda

    2005-01-01

    The liberalization of the Nordic electricity markets started with the deregulation of the Norwegian market, and the later inclusion of Sweden, Denmark and Finland in The Nord Pool area has provided a truly international marketplace, where prices are quoted for all the Nordic countries except Iceland. The structure of the Norwegian supply side was a favorable starting point for the liberalization process with many independent (hydropower) producers and, following the Energy Act of 1991, the vertical separation of competitive production on the one hand and regulated transmission / distribution one the other hand (implemented as a requirement of separation of financial accounts). Moreover, since the mid 1990s (unregulated) retail competition has provided market based price-signals to customers, even to individual households. In this paper we will focus on the potential benefits of demand flexibility in order to enhance the performance of the electricity market in attaining optimal operation and development of the electricity system. These benefits will depend on the price elasticity of the demand. However, whether it is possible to act on price changes also depends on the information provided to and from the customers. Especially for short run flexibility, this may require two way communication devises for larger customer groups, which raises questions like who is to pay for the investments needed, and who will benefit from them. Demand response also depends on the marginal signals resulting from the different contracts offered to the customers. Today this includes ''variable'' price, spot price (based on Nord Pool Elspot) and fixed price contracts. Customer flexibility depends on the possibility of substitution for instance to other fuels / alternative energy provisions. Finally, flexibility will differ between customer classes, for instance households, industry, power intensive industry etc. In this paper we investigate demand response and customer flexibility in

  8. 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.

  9. Modeling of Monthly Residential and Commercial Electricity Consumption Using Nonlinear Seasonal Models—The Case of Hong Kong

    Directory of Open Access Journals (Sweden)

    Wai-Ming To

    2017-06-01

    Full Text Available Accurate modeling and forecasting monthly electricity consumption are the keys to optimizing energy management and planning. This paper examines the seasonal characteristics of electricity consumption in Hong Kong—a subtropical city with 7 million people. Using the data from January 1970 to December 2014, two novel nonlinear seasonal models for electricity consumption in the residential and commercial sectors were obtained. The models show that the city’s monthly residential and commercial electricity consumption patterns have different seasonal variations. Specifically, monthly residential electricity consumption (mainly for appliances and cooling in summer has a quadratic relationship with monthly mean air temperature, while monthly commercial electricity consumption has a linear relationship with monthly mean air temperature. The nonlinear seasonal models were used to predict residential and commercial electricity consumption for the period January 2015–December 2016. The correlations between the predicted and actual values were 0.976 for residential electricity consumption and 0.962 for commercial electricity consumption, respectively. The root mean square percentage errors for the predicted monthly residential and commercial electricity consumption were 7.0% and 6.5%, respectively. The new nonlinear seasonal models can be applied to other subtropical urban areas, and recommendations on the reduction of commercial electricity consumption are given.

  10. Electric Water Heater Modeling and Control Strategies for Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.

    2012-07-22

    Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid

  11. Agent-Based Architectures and Algorithms for Energy Management in Smart Grids. Application to Smart Power Generation and Residential Demand Response

    International Nuclear Information System (INIS)

    Roche, Robin

    2012-01-01

    Due to the convergence of several profound trends in the energy sector, smart grids are emerging as the main paradigm for the modernization of the electric grid. Smart grids hold many promises, including the ability to integrate large shares of distributed and intermittent renewable energy sources, energy storage and electric vehicles, as well as the promise to give consumers more control on their energy consumption. Such goals are expected to be achieved through the use of multiple technologies, and especially of information and communication technologies, supported by intelligent algorithms. These changes are transforming power grids into even more complex systems, that require suitable tools to model, simulate and control their behaviors. In this dissertation, properties of multi-agent systems are used to enable a new systemic approach to energy management, and allow for agent-based architectures and algorithms to be defined. This new approach helps tackle the complexity of a cyber-physical system such as the smart grid by enabling the simultaneous consideration of multiple aspects such as power systems, the communication infrastructure, energy markets, and consumer behaviors. The approach is tested in two applications: a 'smart' energy management system for a gas turbine power plant, and a residential demand response system. An energy management system for gas turbine power plants is designed with the objective to minimize operational costs and emissions, in the smart power generation paradigm. A gas turbine model based on actual data is proposed, and used to run simulations with a simulator specifically developed for this problem. A meta-heuristic achieves dynamic dispatch among gas turbines according to their individual characteristics. Results show that the system is capable of operating the system properly while reducing costs and emissions. The computing and communication requirements of the system, resulting from the selected architecture, are

  12. 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

  13. 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

  14. Simulating residential demand response: Improving socio-technical assumptions in activity-based models of energy demand

    OpenAIRE

    McKenna, E.; Higginson, S.; Grunewald, P.; Darby, S. J.

    2017-01-01

    Demand response is receiving increasing interest as a new form of flexibility within low-carbon power systems. Energy models are an important tool to assess the potential capability of demand side contributions. This paper critically reviews the assumptions in current models and introduces a new conceptual framework to better facilitate such an assessment. We propose three dimensions along which change could occur, namely technology, activities and service expectations. Using this framework, ...

  15. 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

  16. 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.

  17. 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.

  18. Modeling and forecasting of electrical power demands for capacity planning

    International Nuclear Information System (INIS)

    Al-Shobaki, Salman; Mohsen, Mousa

    2008-01-01

    This paper describes the development of forecasting models to predict future generation and electrical power consumption in Jordan. This is critical to production cost since power is generated by burning expensive imported oil. Currently, the National Electric Power Company (NEPCO) is using regression models that only accounts for trend dynamics in their planning of loads and demand levels. The models are simplistic and are based on generated energy historical levels. They produce results on yearly bases and do not account for monthly variability in demand levels. The paper presents two models, one based on the generated energy data and the other is based on the consumed energy data. The models account for trend, monthly seasonality, and cycle dynamics. Both models are compared to NEPCO's model and indicate that NEPCO is producing energy at levels higher than needed (5.25%) thus increasing the loss in generated energy. The developed models also show a 13% difference between the generated energy and the consumed energy that is lost due to transmission line and in-house consumption

  19. Modeling and forecasting of electrical power demands for capacity planning

    Energy Technology Data Exchange (ETDEWEB)

    Al-Shobaki, Salman [Department of Industrial Engineering, Hashemite University, Zarka 13115 (Jordan); Mohsen, Mousa [Department of Mechanical Engineering, Hashemite University, Zarka 13115 (Jordan)

    2008-11-15

    This paper describes the development of forecasting models to predict future generation and electrical power consumption in Jordan. This is critical to production cost since power is generated by burning expensive imported oil. Currently, the National Electric Power Company (NEPCO) is using regression models that only accounts for trend dynamics in their planning of loads and demand levels. The models are simplistic and are based on generated energy historical levels. They produce results on yearly bases and do not account for monthly variability in demand levels. The paper presents two models, one based on the generated energy data and the other is based on the consumed energy data. The models account for trend, monthly seasonality, and cycle dynamics. Both models are compared to NEPCO's model and indicate that NEPCO is producing energy at levels higher than needed (5.25%) thus increasing the loss in generated energy. The developed models also show a 13% difference between the generated energy and the consumed energy that is lost due to transmission line and in-house consumption. (author)

  20. Short-term electric power demand forecasting based on economic-electricity transmission model

    Science.gov (United States)

    Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

    2018-04-01

    Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

  1. 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

  2. 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.)

  3. 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.

  4. 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

  5. Conceptual Framework and Computational Research of Hierarchical Residential Household Water Demand

    Directory of Open Access Journals (Sweden)

    Baodeng Hou

    2018-05-01

    Full Text Available Although the quantity of household water consumption does not account for a huge proportion of the total water consumption amidst socioeconomic development, there has been a steadily increasing trend due to population growth and improved urbanization standards. As such, mastering the mechanisms of household water demand, scientifically predicting trends of household water demand, and implementing reasonable control measures are key focuses of current urban water management. Based on the categorization and characteristic analysis of household water, this paper used Maslow’s Hierarchy of Needs to establish a level and grade theory of household water demand, whereby household water is classified into three levels (rigid water demand, flexible water demand, and luxury water demand and three grades (basic water demand, reasonable water demand, and representational water demand. An in-depth analysis was then carried out on the factors that influence the computation of household water demand, whereby equations for different household water categories were established, and computations for different levels of household water were proposed. Finally, observational experiments on household water consumption were designed, and observation and simulation computations were performed on three typical households in order to verify the scientific outcome and rationality of the computation of household water demand. The research findings contribute to the enhancement and development of prediction theories on water demand, and they are of high theoretical and realistic significance in terms of scientifically predicting future household water demand and fine-tuning the management of urban water resources.

  6. 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).

  7. 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/

  8. 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.

  9. 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

  10. Surging electricity demand growth bolsters outlook for natural gas

    International Nuclear Information System (INIS)

    Koen, A.D.

    1994-01-01

    Economic expansion and regulatory reform are combining to boost global opportunities for burning gas to generate electric power. Companies producing, marketing, or transporting gas are capitalizing on the improved outlook by seizing on synergistic roles in the power generation chain. Much of the improved outlook for gas stems from projected hearty increases in global demand for electricity. Bechtel Power Corp., estimates global power generation capacity during 1994--2003 will increase to as much as 1.2 billion kw, about 25% of which could be added by independent power production (IPPs). Since about 200 bcf of gas reserves producing about 20 MMcfd of gas is needed to fuel of a 100,000 kw electric generating station for 25 years, that adds up to a major growth opportunity for gas producers. The paper discusses the assessment of gas reserves, US power growth, the intent of the Energy Policy Act of 1992 (Epact), effects of Epact, gas industry response, power marketing units, synergistic possibilities, effects on US utilities, international power imperatives, non-US projects, funding good projects, and forecasting future developments

  11. 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.)

  12. C-Vine copula mixture model for clustering of residential electrical load pattern data

    OpenAIRE

    Sun, M; Konstantelos, I; Strbac, G

    2016-01-01

    The ongoing deployment of residential smart meters in numerous jurisdictions has led to an influx of electricity consumption data. This information presents a valuable opportunity to suppliers for better understanding their customer base and designing more effective tariff structures. In the past, various clustering methods have been proposed for meaningful customer partitioning. This paper presents a novel finite mixture modeling framework based on C-vine copulas (CVMM) for carrying out cons...

  13. 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.

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

    Science.gov (United States)

    Hu, Yu-Chen

    2018-01-01

    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

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

    Directory of Open Access Journals (Sweden)

    Yu-Hsiu Lin

    2018-04-01

    Full Text Available 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

  16. 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

  17. Electricity demand of manufacturing sector in Turkey. A translog cost approach

    International Nuclear Information System (INIS)

    Boeluek, Guelden; Koc, A. Ali

    2010-01-01

    This paper models factor demand for manufacturing sector in Turkey. We estimated a translog cost function with four factor consist of capital, labor, intermediate input and electricity over the 1980-2001. Our objective, taking in the consideration electricity as production input, was twofold: on the one hand, to estimate the price elasticity of electricity demand in manufacturing sector, and on the other hand to use cross-price and Morishima Elasticities of Substitution results for structural analysis regarding effects of electricity liberalization which initiated in 2001. Empirical result shows that electricity demand is relatively price sensitive (- 0.85). Our result in terms of electricity price is consistent with the previous studies. While electricity-labor and electricity-capital inputs are complementary, results indicate the existence of substitution possibilities between electricity and intermediate input. This means that changes in electricity prices have impact on labor demand and investment demand. These results have important implications for public policy. (author)

  18. Electricity demand of manufacturing sector in Turkey. A translog cost approach

    Energy Technology Data Exchange (ETDEWEB)

    Boeluek, Guelden; Koc, A. Ali [Akdeniz University, Department of Economics, Antalya, 07058 (Turkey)

    2010-05-15

    This paper models factor demand for manufacturing sector in Turkey. We estimated a translog cost function with four factor consist of capital, labor, intermediate input and electricity over the 1980-2001. Our objective, taking in the consideration electricity as production input, was twofold: on the one hand, to estimate the price elasticity of electricity demand in manufacturing sector, and on the other hand to use cross-price and Morishima Elasticities of Substitution results for structural analysis regarding effects of electricity liberalization which initiated in 2001. Empirical result shows that electricity demand is relatively price sensitive (- 0.85). Our result in terms of electricity price is consistent with the previous studies. While electricity-labor and electricity-capital inputs are complementary, results indicate the existence of substitution possibilities between electricity and intermediate input. This means that changes in electricity prices have impact on labor demand and investment demand. These results have important implications for public policy. (author)

  19. 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.

  20. Electric and gas utility marketing of residential energy conservation case studies

    Energy Technology Data Exchange (ETDEWEB)

    None

    1980-05-01

    The objective of this research was to obtain information about utility conservation marketing techniques from companies actively engaged in performing residential conservation services. Many utilities currently are offering comprehensive services (audits, listing of contractors and lenders, post-installation inspection, advertising, and performing consumer research). Activities are reported for the following utilities: Niagara Mohawk Power Corporation; Tampa Electric Company; Memphis Light, Gas, and Water Division; Northern States Power-Wisconsin; Public Service Company of Colorado; Arizona Public Service Company; Pacific Gas and Electric Company; Sacramento Municipal Utility District; and Pacific Power and Light Company.

  1. 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

  2. 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%.

  3. Demand response in U.S. electricity markets: Empirical evidence

    International Nuclear Information System (INIS)

    Cappers, Peter; Goldman, Charles; Kathan, David

    2010-01-01

    Empirical evidence concerning demand response (DR) resources is needed in order to establish baseline conditions, develop standardized methods to assess DR availability and performance, and to build confidence among policymakers, utilities, system operators, and stakeholders that DR resources do offer a viable, cost-effective alternative to supply-side investments. This paper summarizes the existing contribution of DR resources in U.S. electric power markets. In 2008, customers enrolled in existing wholesale and retail DR programs were capable of providing ∝38,000 MW of potential peak load reductions in the United States. Participants in organized wholesale market DR programs, though, have historically overestimated their likely performance during declared curtailments events, but appear to be getting better as they and their agents gain experience. In places with less developed organized wholesale market DR programs, utilities are learning how to create more flexible DR resources by adapting legacy load management programs to fit into existing wholesale market constructs. Overall, the development of open and organized wholesale markets coupled with direct policy support by the Federal Energy Regulatory Commission has facilitated new entry by curtailment service providers, which has likely expanded the demand response industry and led to product and service innovation. (author)

  4. Energy in the residential building. Electricity, heat, e-mobility. 2. rev. and enl. ed.

    International Nuclear Information System (INIS)

    Schwarzburger, Heiko

    2017-01-01

    Photovoltaics, heat pumps and fuel cells offer enormous potential for sustainable energy supply in residential buildings. Solar thermal energy and wood-fired boilers also play an important role in refurbishment. Due to the wide range of possible combinations, the wishes of building owners and homeowners for an ecologically and economically individually adapted energy concept can be fulfilled accurately. This book provides you with a holistic approach to the residential building and its supply of electricity, heat and water. All processes that play a role in the house's energy consumption are examined in their entirety for their potentials and potential savings. The author analyses and describes in detail the resources of buildings and their surroundings - and how they can be used for a truly independent supply. The focus is on reducing energy consumption and costs, the generation and supply of energy from renewable sources and energy storage - considered in new construction and modernisation. The supply of water is also dealt with if it touches on energy issues. The author draws attention to standards and regulations and gives practical advice for planning and installation. The focus is on the so-called sector coupling: electricity from the sun, wind and hydrogen is used to supply electrical consumers in the home, charging technology for electric vehicles, hot water and heating. The time of the boilers and combustion engines has elapsed. Clean electricity and digital controls - power and intelligence - determine the regenerative building technology. [de

  5. 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...... in countries like Denmark, is widely discussed and promoted. However, the wide-spread adoption of EVs requires the provision of intelligent grid and EV charging infrastructure. To analyse and understand the amount of EVs that could be integrated in the local distribution grids, within its existing capabilities......, 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...

  6. 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

  7. 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.

  8. 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.

  9. Feasibility study on combined use of residential SOFC cogeneration system and plug-in hybrid electric vehicle from energy-saving viewpoint

    International Nuclear Information System (INIS)

    Wakui, Tetsuya; Wada, Naohiro; Yokoyama, Ryohei

    2012-01-01

    Highlights: ► Optimal operational planning for combined use of SOFC-CGS and PHEV is conducted. ► Charging PHEV with SOFC-CGS increases electric capacity factor of SOFC-CGS. ► Energy-saving effect of combined use is higher than that of their separate use. ► Combined use provides energy savings in both residential and transport sectors. - Abstract: The energy-saving effect of a combined use of a residential solid oxide fuel cell cogeneration system (SOFC-CGS) that adopts a continuous operation, and a plug-in hybrid electric vehicle (PHEV) is discussed by optimal operational planning based on mixed-integer linear programming. This combined use aims to increase the electric capacity factor of the SOFC-CGS by charging the PHEV using the SOFC-CGS electric power output late at night, and targets the application in regions where the reverse power flow from residential cogeneration systems to commercial electric power systems is not permitted, like in Japan. The optimal operation patterns of the combined use of 0.7-kWe SOFC-CGS and PHEV for a simulated energy demand with a sampling time of 1 h and various daily running distances of the PHEV show that this combined use increases the electric capacity factor of the SOFC-CGS and saves more energy in comparison with their separate use in which the SOFC-CGS is used but the PHEV is charged only with purchased electric power. Furthermore, it is found that at the PHEV daily running distance of 12 km/d, the reduction rate of the annual primary energy consumption for this combined use increases by up to 3.7 percentage points relative to their separate use. Consequently, this feasibility study reveals that the combined use of the SOFC-CGS and PHEV provides the synergistic effect on energy savings in the residential and transport sectors. For the practical use, simulation scenarios considering the energy demand fluctuations with short periods and real-time pricing of the purchased electric power must be considered as future

  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. 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...

  12. 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)

  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. 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

  15. 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.

  16. Which electricity market design to encourage the development of demand response?

    OpenAIRE

    Vincent Rious, Fabien Roques and Yannick Perez

    2012-01-01

    Demand response is a cornerstone problem in electricity markets under climate change constraint. Most liberalized electricity markets have a poor track record at encouraging the deployment of smart meters and the development of demand response. In Europe, different models are considered for demand response, from a development under a regulated regime to a development under competitive perspectives. In this paper, focusing on demand response and smart metering for mid-size and small consumers,...

  17. Which electricity market design to encourage the development of demand response?

    OpenAIRE

    Rious , Vincent; Perez , Yannick; Roques , Fabien

    2015-01-01

    International audience; Demand response is a cornerstone problem in electricity markets under climate change constraints. Most liberalized electricity markets have a poor track record at encouraging the deployment of smart meters and the development of demand response. In Europe, different models are considered for demand response, from a development under a regulated regime to a development under competitive perspectives. In this paper focusing on demand response and smart metering for mid-­...

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

    International Nuclear Information System (INIS)

    Amusa, Hammed; Amusa, Kafayat; Mabugu, Ramos

    2009-01-01

    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.

  19. 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)

  20. The electric tariff in the residential sector; Tarificacion electrica en el sector residencial

    Energy Technology Data Exchange (ETDEWEB)

    Sheinbaum Pardo, Claudia [Instituto de Ingenieria, Universidad Nacional Autonoma de Mexico (UNAM), Mexico, D. F. (Mexico)

    1997-12-31

    The main objective of this paper is to make an historical revision and analyze the current condition of the electric tariffs in the Mexican residential sector and ask ourselves if the equalization of tariffs generates the possibility that the entire population has access to the electricity service. The document is divided into three parts. The first one presents the history and the tendencies of the tariffs in the domestic sector in Mexico since 1973 until 1996 and the current tariff structure. The second one describes the characteristics of the residential users and mention is made of how the increment of the electric tariffs would affect the various population sectors. The last part of this paper presents some tariff criteria, that take into account energy conservation measures [Espanol] El objetivo principal de este trabajo es hacer una revision historica y analizar la situacion actual de las tarifas electricas en el sector residencial mexicano y preguntarnos si la igualdad de tarifas genera la posibilidad de que toda la poblacion tenga acceso al servicio electrico. El documento se divide en tres partes. La primera presenta la historia y tendencias de las tarifas del sector domestico en Mexico desde 1973 hasta 1996 y la estructura tarifaria actual. La segunda describe las caracteristicas de los usuarios residenciales y se menciona como afectaria el incremento de las tarifas electricas a los distintos sectores de la poblacion. La ultima parte de este trabajo presenta algunos criterios de tarificacion, que toman en cuenta medidas de ahorro de energia

  1. 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.

  2. 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

  3. 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...

  4. Demand Response With Micro-CHP Systems

    NARCIS (Netherlands)

    Houwing, M.; Negenborn, R.R.; De Schutter, B.

    2011-01-01

    With the increasing application of distributed energy resources and novel information technologies in the electricity infrastructure, innovative possibilities to incorporate the demand side more actively in power system operation are enabled. A promising, controllable, residential distributed

  5. Analysis and design of a Taguchi-Grey based electricity demand predictor for energy management systems

    International Nuclear Information System (INIS)

    Yao, Albert W.L.; Chi, S.C.

    2004-01-01

    In order to use electricity efficiently, a demand control management system is one of the effective ways to reduce energy consumption and electric bills. An electricity demand control system is used as a means to monitor and manage the usage of electricity effectively. Moreover, it is a useful tool for avoiding penalties beyond the contracted demand value of electricity with the electric power company. In this project, we developed a Taguchi-Grey based predictor to forecast the demand value of electricity on line. In a Grey prediction, the parameter settings are highly relevant to the accuracy of forecasting. A Taguchi method was employed to optimize the parameter settings for the Grey based electricity demand value predictor. Our experimental results show that the optimal parameter settings of the Grey prediction are α=0.4, five point modeling and three minute sampling time of the data acquisition system. The improved Taguchi-Grey based electricity demand predictor in conjunction with the PC based electricity demand control system is a cost effective and efficient means to manage the usage of electricity

  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

    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...... for demand response is the lack of experience, and the consequent need to employ extensive assumptions when modelling and evaluating this resource. This paper concludes with an examination of these assumptions, which range from assuming a fixed linear price–demand relationship for price responsive demand...

  7. Prospective Life Cycle Assessment of the Increased Electricity Demand Associated with the Penetration of Electric Vehicles in Spain

    OpenAIRE

    Zaira Navas-Anguita; Diego García-Gusano; Diego Iribarren

    2018-01-01

    The penetration of electric vehicles (EV) seems to be a forthcoming reality in the transport sector worldwide, involving significant increases in electricity demand. However, many countries such as Spain have not yet set binding policy targets in this regard. When compared to a business-as-usual situation, this work evaluates the life-cycle consequences of the increased electricity demand of the Spanish road transport technology mix until 2050. This is done by combining Life Cycle Assessment ...

  8. 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 inevitable

  9. 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

  10. 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.

  11. Wright tariffs in the Spanish electricity industry: the case of residential consumption

    International Nuclear Information System (INIS)

    Castro-Rodriguez, F.

    1999-01-01

    In this paper a capacity price model is developed for the Spanish electricity industry which allows the presentation of the Spanish utilization level tariffs as an example of duration tariffs (Wright tariffs) when duration is approximated by the ratio of consumption to power used. Using this model and data on the residential consumption of electricity, several optimal two-part tariffs are computed, considering different hypothesis on the configuration of the generating equipment. It has been found that the optimal tariff maintaining universal service increases welfare if the generating equipment and the output assignment to the different technologies are taken as given. Furthermore, if the regulator is concerned not only with efficiency, but also with distributive issues, then welfare losses associated with the existing regulatory regime are even larger

  12. 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)

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

    Energy Technology Data Exchange (ETDEWEB)

    Gabreyohannes, Emmanuel [Ethiopian Civil Service College, P.O.Box 5648, Addis Ababa (Ethiopia)

    2010-05-15

    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)

  14. Job-Demands, Job Control, Social Support, Self-Efficacy, and Burnout of Staff of Residential Children's Homes

    Science.gov (United States)

    Brouwers, André; Tomic, Welko

    2016-01-01

    The aim of the current study was to examine among educational staff members of residential children's homes to what extent task demands, job control, emotional and social support from colleagues and management as well as self-efficacy beliefs concerning coping with aggressive behaviour in youngsters are associated with emotional exhaustion,…

  15. 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

  16. 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...... there will be high power demand from HPs and the selection of supplemental heating for heat pumps has a big impact on the peak electrical power load of heating. The study in this paper gives an estimate of the scale of the electricity demand with high penetration of heat pumps in the Nordic area....

  17. 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.

  18. 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)

  19. 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

    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...... 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...

  20. A demand/supply and price outlook for electricity in Ontario

    International Nuclear Information System (INIS)

    Dalton, J.

    2004-01-01

    This paper presents the demand/supply and price outlook for electricity in Ontario. The paper examines the near term outlook, critical demand and supply issues, the projected Ontario demand/supply balances and finally concludes by looking at the challenges for Ontario's new market structure

  1. 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 consumption is in fact central

  2. The Private Net Benefits of Residential Solar PV: The Role of Electricity Tariffs, Tax Incentives and Rebates

    OpenAIRE

    Severin Borenstein

    2015-01-01

    With dramatic declines in the cost of solar PV technology over the last 5 years, the electricity industry is in the midst of discussions about whether to use this low-polluting renewable energy source in grid-scale generation or in distributed generation (DG), mostly with rooftop solar PV. California has led the growth in DG solar in the U.S. I use 2007 to early 2014 residential data from Pacific Gas & Electric – the utility with largest number of residential solar customers in the U.S. – to ...

  3. 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)

  4. 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.

  5. 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.

  6. Economic information from Smart Meter: Nexus Between Demand Profile and Electricity Retail Price Between Demand Profile and Electricity Retail Price

    OpenAIRE

    Yu, Yang; Liu, Guangyi; Zhu, Wendong; Wang, Fei; Shu, Bin; Zhang, Kai; Rajagopal, Ram; Astier, Nicolas

    2016-01-01

    In this paper, we demonstrate that a consumer's marginal system impact is only determined by their demand profile rather than their demand level. Demand profile clustering is identical to cluster consumers according to their marginal impacts on system costs. A profile-based uniform-rate price is economically efficient as real-time pricing. We develop a criteria system to evaluate the economic efficiency of an implemented retail price scheme in a distribution system by comparing profile cluste...

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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)

  12. 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...... with closed formulae as a function of charging time. Specific manufacturer model of electric vehicles is used as study case....

  13. 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.

  14. Study of forecasting maximum demand of electric power

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, B.C.; Hwang, Y.J. [Korea Energy Economics Institute, Euiwang (Korea, Republic of)

    1997-08-01

    As far as the past performances of power supply and demand in Korea is concerned, one of the striking phenomena is that there have been repeated periodic surpluses and shortages of power generation facilities. Precise assumption and prediction of power demands is the basic work in establishing a supply plan and carrying out the right policy since facilities investment of the power generation industry requires a tremendous amount of capital and a long construction period. The purpose of this study is to study a model for the inference and prediction of a more precise maximum demand under these backgrounds. The non-parametric model considered in this study, paying attention to meteorological factors such as temperature and humidity, does not have a simple proportionate relationship with the maximum power demand, but affects it through mutual complicated nonlinear interaction. I used the non-parametric inference technique by introducing meteorological effects without importing any literal assumption on the interaction of temperature and humidity preliminarily. According to the analysis result, it is found that the non-parametric model that introduces the number of tropical nights which shows the continuity of the meteorological effect has better prediction power than the linear model. The non- parametric model that considers both the number of tropical nights and the number of cooling days at the same time is a model for predicting maximum demand. 7 refs., 6 figs., 9 tabs.

  15. A MEMS AC current sensor for residential and commercial electricity end-use monitoring

    International Nuclear Information System (INIS)

    Leland, E S; Wright, P K; White, R M

    2009-01-01

    This paper presents a novel prototype MEMS sensor for alternating current designed for monitoring electricity end-use in residential and commercial environments. This new current sensor design is comprised of a piezoelectric MEMS cantilever with a permanent magnet mounted on the cantilever's free end. When placed near a wire carrying AC current, the magnet is driven sinusoidally, producing a voltage in the cantilever proportional to the current being measured. Analytical models were developed to predict the applicable magnetic forces and piezoelectric voltage output in order to guide the design of a sensor prototype. This paper also details the fabrication process for this sensor design. Released piezoelectric MEMS cantilevers have been fabricated using a four-mask process and aluminum nitride as the active piezoelectric material. Dispenser-printed microscale composite permanent magnets have been integrated, resulting in the first MEMS-scale prototypes of this current sensor design

  16. Unleashing Flexibility from Electric Boilers and Heat Pumps in Danish Residential Distribution Network

    DEFF Research Database (Denmark)

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

    2018-01-01

    and thereby improving its techno-economic efficiency. The data used for the evaluation are also from the real household sites in Denmark provided by the district heating utility. Focus is on the low-voltage grid, and that’s very relevant since many doesn’t expect any flexibility from that voltage level. Study...... this model is compared to responses from an average model of the hot water storage tank to evaluate the benefit of the more detailed model. Finally, analysis on consumption patterns of electrical and thermal loads in residential buildings in Northern Jutland, Denmark, are used for analysis of the system...... and use of thermal units as flexible consumer loads in the low voltage (LV) distribution network grid. The models of EB and HP with storage tank are briefly discussed in relation to the actual control and flexibility based on grid condition and status of storage tank temperature or position...

  17. A pseudo-panel data model of household electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Bernard, Jean-Thomas; Bolduc, Denis [GREEN, Department of Economics, Universite Laval, Quebec (Canada); Yameogo, Nadege-Desiree [Analysis Group Inc., 1080 Beaver Hill, Suite 1810, Montreal, Quebec (Canada)

    2011-01-15

    We study the dynamic behaviour of household electricity consumption on the basis of four large independent surveys conducted in the province of Quebec from 1989 to 2002. The latter region displays some rather unique features such as the very extensive use of electricity for space heating in a cold climate and the wide range of energy sources used to meet space heating requirements. We adopt approach to create 25 cohorts of households that form a pseudo-panel. The cohorts have on average 131 households. The model error terms allow for group heteroskedasticity and serial correlation. Short-run and long-run own and cross-price elasticities are statistically significant. Electricity and natural gas are estimated to be substitutes while electricity and fuel oil are complements, as it may occur in the Quebec context. The estimate of the income elasticity is not significant. Comparisons with related studies are provided. (author)

  18. 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

  19. 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

  20. Demand participation in the restructured Electric Reliability Council of Texas market

    International Nuclear Information System (INIS)

    Zarnikau, Jay W.

    2010-01-01

    Does an electricity market which has been restructured to foster competition provide greater opportunities for demand response than a traditional regulated utility industry? The experiences of the restructured Electric Reliability Council of Texas (ERCOT) market over the past eight years provide some hope that it is possible to design a competitive market which will properly value and accommodate demand response. While the overall level of demand response in ERCOT is below the levels enjoyed prior to restructuring, there have nonetheless been some promising advances, including the integration of demand-side resources into competitive markets for ancillary services. ERCOT's experiences demonstrate that the degree of demand participation in a restructured market is highly sensitive to the market design. But even in a market which has been deregulated to a large degree, regulatory intervention and special demand-side programs may be needed in order to bolster demand response. (author)

  1. Latin American electric power developments and hydrocarbon demands

    International Nuclear Information System (INIS)

    Sanchez Sierra, G.

    1995-01-01

    Latin American countries must address issues such as financing, management (business, technical, environmental) and low-income sectors to promote the structural changes required in energy supply and demand to optimise efficient use. Private sector participation is not only a matter of ownership but raising the level of efficiency. The state's role will be to ensure stability, confidence and environmental safeguards. (author)

  2. 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.

  3. 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

  4. The effects of electric vehicles on residential households in the city of Indianapolis

    International Nuclear Information System (INIS)

    Huang Shisheng; Safiullah, Hameed; Xiao Jingjie; Hodge, Bri-Mathias S.; Hoffman, Ray; Soller, Joan; Jones, Doug; Dininger, Dennis; Tyner, Wallace E.; Liu, Andrew; Pekny, Joseph F.

    2012-01-01

    There is an increasing impetus to transform the U.S transportation sector and transition away from the uncertainties of oil supply. One of the most viable current solutions is the adoption of electric vehicles (EVs). These vehicles allow for a transportation system that would be flexible in its fuel demands. However, utilities may need to address questions such as distribution constraints, electricity tariffs and incentives and public charging locations before large scale electric vehicle adoption can be realized. In this study, the effect of electric vehicles on households in Indianapolis is examined. A four-step traffic flow model is used to characterize the usage characteristics of vehicles in the Indianapolis metropolitan area. This data is then used to simulate EV usage patterns which can be used to determine household electricity usage characteristics. These results are differentiated by the zones with which the households are associated. Economic costs are then calculated for the individual households. Finally, possible public charging locations are examined. - Highlights: ► Traffic flow modeling is used to accurately characterize EV usage in Indianapolis. ► EV usage patterns are simulated to determine household electricity usage patterns. ► Economic costs are calculated for the households for electric vehicles. ► Possible public charging locations are examined.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. Demand for power in Calcutta Electricity Supply Corporation area

    Energy Technology Data Exchange (ETDEWEB)

    Banerjee, N

    1980-07-01

    Since the early 1970's there has been a continuous crisis of power supply to the Calcutta industrial region. Historical records show that only the peak demand has grown and has a potential for growth, which, with an unchanging base demand, results in a low load factor and consequently inefficient power system operation. Attempts to shift industrial loads by operating industrial plants during non-peak hours are described. Adverse economic conditions eliminated the need for extra working shifts. It is concluded that the power system supplying the Calcutta region has an insufficient peak load generating capacity and an uneconomic load curve and that stricter hourly schedules for power use by industries should be adhered to in order to minimize these problems. (LCL)

  11. 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

  12. 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.)

  13. 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)

  14. 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.

  15. Prospective Life Cycle Assessment of the Increased Electricity Demand Associated with the Penetration of Electric Vehicles in Spain

    Directory of Open Access Journals (Sweden)

    Zaira Navas-Anguita

    2018-05-01

    Full Text Available The penetration of electric vehicles (EV seems to be a forthcoming reality in the transport sector worldwide, involving significant increases in electricity demand. However, many countries such as Spain have not yet set binding policy targets in this regard. When compared to a business-as-usual situation, this work evaluates the life-cycle consequences of the increased electricity demand of the Spanish road transport technology mix until 2050. This is done by combining Life Cycle Assessment and Energy Systems Modelling under three alternative scenarios based on the low, medium, or high penetration rate of EV. In all cases, EV deployment is found to involve a relatively small percentage (<4% of the final electricity demand. Wind power and waste-to-energy plants arise as the main technologies responsible for meeting the increased electricity demand associated with EV penetration. When considering a high market penetration (20 million EV by 2050, the highest annual impacts potentially caused by the additional electricity demand are 0.93 Mt CO2 eq, 0.25 kDALY, and 30.34 PJ in terms of climate change, human health, and resources, respectively. Overall, EV penetration is concluded to slightly affect the national power generation sector, whereas it could dramatically reduce the life-cycle impacts associated with conventional transport.

  16. 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).

  17. 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

  18. Electric shovels meet the demands for mining operations

    Energy Technology Data Exchange (ETDEWEB)

    Fiscor, S.

    2008-03-15

    Rugged, intelligent shovels offer better productivity and help mine operators avoid costly downtime in a very tight market. In 2007 P & H Mining Equipment began to produce a new breed of electric mining shovels designed to help reduce operating cost in coal and other mining operations. These were designated the P & H C-Series. All have an advanced communication, command and control system called the Centurion system. Coal mining applications for this series include 4100XPCs in Australia, China and Wyoming, USA. The Centurion system provides information on shovel performance and systems health which is communicated via graphic user interface terminals to the operators cab. Bucyrus International is developing a hydraulic crowd mechanism for its electric shovels and is now field testing one for its 495 series shovel. The company has also added greater capability in the primary software in the drive system for troubleshooting and fault identification to quickly diagnose problems onboard or remotely. 4 photos.

  19. 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.

  20. 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.

  1. The value of online information for demand response in Walrasian electricity markets

    NARCIS (Netherlands)

    F.N. Claessen (Felix); B.J. Liefers (Bart); M. Kaisers (Michael); J.A. La Poutré (Han)

    2015-01-01

    textabstractSmart energy systems integrate renewables and demand response. Most European electricity markets coordinate the resulting time-varying flexibility in demand and supply by organising day-ahead trade with Walrasian mechanisms, using simultaneous call auctions and sealed bids. These

  2. 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...

  3. 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

  4. 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

  5. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Kucukali, Serhat [Civil Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey); Baris, Kemal [Mining Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey)

    2010-05-15

    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. (author)

  7. 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)

  8. 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

  9. 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

  10. 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

  11. Study of some aspects of the long-run domestic demand for electricity in New Zealand

    Energy Technology Data Exchange (ETDEWEB)

    Stent, A F

    1982-01-01

    This study investigates the long-run domestic demand for electricity in New Zealand over the period 1945 to 1972. The first part analyzes the ownership of electrical appliances using data from the five yearly censuses of population and dwellings. A dynamic appliance ownership model is developed for the analysis. This model explains the proportion of households, in small regional districts, with ownership status of a particular appliance type when observed at census time. It measures the effects of prices, income, and household taste characteristics on ownership. The main results include estimates of long-run electricity price effects. The second part of the thesis estimates dynamic demand equations for electricity. A flow-adjustment model is fitted to moving cross sections of data for individual Electrical Supply Authority districts in the North and South Islands separately. The final part of the thesis undertakes a synthesis of electricity price effects on appliance ownership (from the first part) and electricity demand (from the second part). This indicates substantial consistency in the estimates obtained. The main conclusions for electricity price are that this variable has been a significant factor in explaining the variation in domestic electricity consumption over the period; that the relationship has been inelastic in the later part, in both short and long-runs; and that long-run effects are mainly via the use of the electrical services.

  12. Energy management for vehicle power net with flexible electric load demand

    NARCIS (Netherlands)

    Kessels, J.T.B.A.; Bosch, van den P.P.J.; Koot, M.W.T.; Jager, de A.G.

    2005-01-01

    The electric power demand in road vehicles increases rapidly and to supply all electric loads efficiently, energy management (EM) turns out to be a necessity. In general, EM exploits the storage capacity of a buffer connected to the vehicle's power net, such that energy is stored or retrieved at

  13. 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.

  14. 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

  15. 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

  16. Learning from the implementation of residential optional time of use pricing in the United States electricity industry

    Science.gov (United States)

    Li, Xibao

    Residential time-of-use (TOU) rates have been in practice in the U.S. since the 1970s. However, for institutional, political, and regulatory reasons, only a very small proportion of residential customers are actually on these schedules. In this thesis, I explore why this is the case by empirically investigating two groups of questions: (1) On the "supply" side: Do utilities choose to offer TOU rates in residential sectors on their own initiative if state commissions do not order them to do so? Since utilities have other options, what is the relationship between the TOU rate and other alternatives? To answer these questions, I survey residential tariffs offered by more than 100 major investor-owned utilities, study the impact of various factors on utilities' rate-making behavior, and examine utility revealed preferences among four rate options: seasonal rates, inverted block rates, demand charges, and TOU rates. Estimated results suggest that the scale of residential sectors and the revenue contribution from residential sectors are the only two significant factors that influence utility decisions on offering TOU rates. Technical and economic considerations are not significant statistically. This implies that the little acceptance of TOU rates is partly attributed to utilities' inadequate attention to TOU rate design. (2) On the "demand" side: For utilities offering TOU tariffs, why do only a very small proportion of residential customers choose these tariffs? What factors influence customer choices? Unlike previous studies that used individual-level experimental data, this research employs actual aggregated information from 29 utilities offering optional TOU rates. By incorporating neo-classical demand analysis into an aggregated random coefficient logit model, I investigate the impact of both price and non-price tariff characteristics and non-tariff factors on customer choice behavior. The analysis indicates that customer pure tariff preference (which captures the

  17. 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.

  18. 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...... 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...... 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...

  19. 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

    2015-03-01

    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.

  20. 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.

  1. 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.

  2. The application of seasonal latent variable in forecasting electricity demand as an alternative method

    International Nuclear Information System (INIS)

    Sumer, Kutluk Kagan; Goktas, Ozlem; Hepsag, Aycan

    2009-01-01

    In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with seasonal latent variable in forecasting electricity demand by using data that belongs to 'Kayseri and Vicinity Electricity Joint-Stock Company' over the 1997:1-2005:12 periods. This study tries to examine the advantages of forecasting with ARIMA, SARIMA methods and with the model has seasonal latent variable to each other. The results support that ARIMA and SARIMA models are unsuccessful in forecasting electricity demand. The regression model with seasonal latent variable used in this study gives more successful results than ARIMA and SARIMA models because also this model can consider seasonal fluctuations and structural breaks

  3. 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)

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. What is demand response? Contributing to secure security-of-supply at the electricity markets

    International Nuclear Information System (INIS)

    Grenaa Jensen, Stine; Skytte, Klaus; Togeby, Mikael

    2004-01-01

    There is a common understanding that demand response can reduce the total costs of electricity reliability. There has especially been a growing interest in the electricity market where high spot prices in peak periods and blackouts have recently been seen. It is not easy from the existing literature to find a common definition of demands response. Often the term demand response is used broadly without looking at the time dimension. However, it does not make sense to talk about demand response without talking about when, for how long the energy is used or saved, and at which costs. This paper surveys these subjects and set up a systematic grouping of the different characteristics of demand response. It especially looks at the time dimension. (au)

  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. 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)

  11. 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)

  12. 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.

  13. The impact of demand side management strategies in the penetration of renewable electricity

    International Nuclear Information System (INIS)

    Pina, André; Silva, Carlos; Ferrão, Paulo

    2012-01-01

    High fuel costs, increasing energy security and concerns with reducing emissions have pushed governments to invest in the use of renewable energies for electricity generation. However, the intermittence of most renewable resources when renewable energy provides a significant share of the energy mix can create problems to electricity grids, which can be minimized by energy storage systems that are usually not available or expensive. An alternative solution consists on the use of demand side management strategies, which can have the double effect of reducing electricity consumption and allowing greater efficiency and flexibility in the grid management, namely by enabling a better match between supply and demand. This work analyzes the impact of demand side management strategies in the evolution of the electricity mix of Flores Island in the Azores archipelago which is characterized by high shares of renewable energy and therefore the introduction of more renewable energy sources makes it an interesting case study for testing innovative solutions. The electricity generation system is modeled in TIMES, a software which optimizes the investment and operation of wind and hydro plants until 2020 based on scenarios for demand growth, deployment of demand response technologies in the domestic sector and promotion of behavioral changes to eliminate standby power. The results show that demand side management strategies can lead to a significant delay in the investment on new generation capacity from renewable resources and improve the operation of the existing installed capacity. -- Highlights: ► Energy efficiency can help reduce the need for investment in more renewable energy. ► Dynamic demand helps increase the use of renewable energy in low demand periods. ► Around 40% of total consumption by domestic appliances is used as dynamic demand. ► The load of domestic appliances is mainly shifted to the 5:00 to 9:00 period.

  14. Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey

    International Nuclear Information System (INIS)

    Erdogdu, Erkan

    2007-01-01

    In the early 2000s, the Republic of Turkey has initiated an ambitious reform program in her electricity market, which requires privatization, liberalization as well as a radical restructuring. The most controversial reason behind, or justification for, recent reforms has been the rapid electricity demand growth; that is to say, the whole reform process has been a part of the endeavors to avoid the so-called 'energy crisis'. Using cointegration analysis and autoregressive integrated moving average (ARIMA) modelling, the present article focuses on this issue by both providing an electricity demand estimation and forecast, and comparing the results with official projections. The study concludes, first, that consumers' respond to price and income changes is quite limited and therefore there is a need for economic regulation in Turkish electricity market; and second, that the current official electricity demand projections highly overestimate the electricity demand, which may endanger the development of both a coherent energy policy in general and a healthy electricity market in particular

  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. 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.

  17. 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.

  18. 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

  19. 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...

  20. 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.

  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. 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

  3. Integration scenarios of Demand Response into electricity markets: Load shifting, financial savings and policy implications

    International Nuclear Information System (INIS)

    Feuerriegel, Stefan; Neumann, Dirk

    2016-01-01

    Demand Response allows for the management of demand side resources in real-time; i.e. shifting electricity demand according to fluctuating supply. When integrated into electricity markets, Demand Response can be used for load shifting and as a replacement for both control reserve and balancing energy. These three usage scenarios are compared based on historic German data from 2011 to determine that load shifting provides the highest benefit: its annual financial savings accumulate to €3.110 M for both households and the service sector. This equals to relative savings of 2.83% compared to a scenario without load shifting. To improve Demand Response integration, the proposed model suggests policy implications: reducing bid sizes, delivery periods and the time-lag between market transactions and delivery dates in electricity markets. - Highlights: •Comparison of 3 scenarios to integrate Demand Response into electricity markets. •These are: optimize procurement, offer as control reserve, avoid balancing energy. •Ex post simulation to quantify financial impact and policy implications. •Highest savings from load shifting with a cost reduction of 3%. •Model suggests reducing bid sizes, delivery periods and time lags as policy issues.

  4. 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.

  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. 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.

  7. 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.

  8. Developing a Mixed Neural Network Approach to Forecast the Residential Electricity Consumption Based on Sensor Recorded Data.

    Science.gov (United States)

    Oprea, Simona-Vasilica; Pîrjan, Alexandru; Căruțașu, George; Petroșanu, Dana-Mihaela; Bâra, Adela; Stănică, Justina-Lavinia; Coculescu, Cristina

    2018-05-05

    In this paper, we report a study having as a main goal the obtaining of a method that can provide an accurate forecast of the residential electricity consumption, refining it up to the appliance level, using sensor recorded data, for residential smart homes complexes that use renewable energy sources as a part of their consumed electricity, overcoming the limitations of not having available historical meteorological data and the unwillingness of the contractor to acquire such data periodically in the future accurate short-term forecasts from a specialized institute due to the implied costs. In this purpose, we have developed a mixed artificial neural network (ANN) approach using both non-linear autoregressive with exogenous input (NARX) ANNs and function fitting neural networks (FITNETs). We have used a large dataset containing detailed electricity consumption data recorded by sensors, monitoring a series of individual appliances, while in the NARX case we have also used timestamps datasets as exogenous variables. After having developed and validated the forecasting method, we have compiled it in view of incorporating it into a cloud solution, being delivered to the contractor that can provide it as a service for a monthly fee to both the operators and residential consumers.

  9. Electricity demand and storage dispatch modeling for buildings and implications for the smartgrid

    Science.gov (United States)

    Zheng, Menglian; Meinrenken, Christoph

    2013-04-01

    As an enabler for demand response (DR), electricity storage in buildings has the potential to lower costs and carbon footprint of grid electricity while simultaneously mitigating grid strain and increasing its flexibility to integrate renewables (central or distributed). We present a stochastic model to simulate minute-by-minute electricity demand of buildings and analyze the resulting electricity costs under actual, currently available DR-enabling tariffs in New York State, namely a peak/offpeak tariff charging by consumed energy (monthly total kWh) and a time of use tariff charging by power demand (monthly peak kW). We then introduce a variety of electrical storage options (from flow batteries to flywheels) and determine how DR via temporary storage may increase the overall net present value (NPV) for consumers (comparing the reduced cost of electricity to capital and maintenance costs of the storage). We find that, under the total-energy tariff, only medium-term storage options such as batteries offer positive NPV, and only at the low end of storage costs (optimistic scenario). Under the peak-demand tariff, however, even short-term storage such as flywheels and superconducting magnetic energy offer positive NPV. Therefore, these offer significant economic incentive to enable DR without affecting the consumption habits of buildings' residents. We discuss implications for smartgrid communication and our future work on real-time price tariffs.

  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. 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...... 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...

  12. Generation of synthetic sequences of electricity demand: Application in South Australia

    International Nuclear Information System (INIS)

    Magnano, L.; Boland, J.W.

    2007-01-01

    We have developed a model to generate synthetic sequences of half-hourly electricity demand. The generated sequences represent possible realisations of electricity load that could have occurred. Each of the components included in the model has a physical interpretation. These components are yearly and daily seasonality which were modelled using Fourier series, weekly seasonality modelled with dummy variables, and the relationship with current temperature described by polynomial functions of temperature. Finally the stochastic component was modelled with autoregressive moving average (ARMA) processes. These synthetic sequences were developed for two purposes. The first one is to use them as input data in market simulation software. The second one is to build probability distributions of the outputs to calculate probabilistic forecasts. As an application several summers of half-hourly electricity demand were generated and from them the value of demand that is not expected to be exceeded more than once in 10 years was calculated

  13. 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.)

  14. 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.

  15. Considering supply and demand of electric energy in life cycle assessments - a review of current methodologies

    International Nuclear Information System (INIS)

    Rehberger, M.; Hiete, M.

    2015-01-01

    A stable power grid requires a balance between electricity supply and demand. To compensate for changes in the demand the network operator puts on or takes off power plants from the net. Peak load plants operate only at times of high electricity demand. As levels for air pollutants emissions are typically lower for peak load plants for reasons of cost-effectiveness, one could argue that a unit of electric energy consumed during peak load has always been associated with a higher environmental impact than at other times. Furthermore, renewable energy technologies, smart approaches for improving the matching between electricity consumption and supply and new products such as electric vehicles or net zero emission buildings gain in importance. In life cycle assessment (LCA) environmental impacts associated with the production and possibly transmission of electricity are most often assessed based on temporally averaged national electricity mixes as electricity flows cannot be traced back to their origin. Neither fluctuations in the supply structure nor the composition of energy supply at a certain moment or regional differences are accounted for. A literature review of approaches for handling electricity in LCA is carried out to compare strengths and weaknesses of the approaches. A better understanding and knowledge about the source of electricity at a given time and place might be valuable information for further reducing environmental impacts, e.g. by shifting electricity consumption to times with ample supply of renewables. Integrating such information into LCA will allow a fairer assessment of a variety of new products which accept a lower energy efficiency to achieve a better integration of renewables into the grid. (authors)

  16. A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand

    International Nuclear Information System (INIS)

    Orea, Luis; Llorca, Manuel; Filippini, Massimo

    2015-01-01

    This paper brings attention to the fact that the energy demand frontier model introduced by Filippini and Hunt (2011, 2012) is closely connected to the measurement of the so-called rebound effect associated with improvements in energy efficiency. In particular, we show that their model implicitly imposes a zero rebound effect, which contradicts most of the available empirical evidence on this issue. We relax this restrictive assumption through the modelling of a rebound-effect function that mitigates or intensifies the effect of an efficiency improvement on energy consumption. We illustrate our model with an empirical application that aims to estimate a US frontier residential aggregate energy demand function using panel data for 48 states over the period 1995 to 2011. Average values of the rebound effect in the range of 56–80% are found. Therefore, policymakers should be aware that most of the expected energy reduction from efficiency improvements may not be achieved. - Highlights: • A new approach to measuring rebound effects in energy consumption is presented. • We illustrate our proposal with an application to US residential energy demand. • Relatively large rebound effects in the range of 56–80% are found. • Energy-inefficient states tend to exhibit low rebound effects. • We identify states where energy-saving policies should be more effective

  17. Advancing aging society and its effect on the re