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.
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)
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.
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
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
Monthly Electrical Energy Overview January 2017
International Nuclear Information System (INIS)
2017-02-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for January 2017. The cold spell of January 2017 caused a strong increase in gross electricity demand (+14.3%) compared to January 2016. The French exchange balance was in favour of imports for the second consecutive month. Demand recorded a peak on 20/01/2017 at 94.2 GW. It is the highest peak since February 2012. Corrected electricity demand trend stabilised in January 2017. Fossil fuel thermal generation was 8.3 TWh up by 71% compared to January 2016. Solar production grew significantly compared to last year with a 37.7% increase. The balance of exchanges was in favour of imports for the second consecutive month with a total of 0.95 TWh of electricity imported. 4 new installations went into service in January 2017
The analysis of Taiwan's residential electricity demand under the electricity tariff policy
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.
Monthly Electrical Energy Overview August 2016
International Nuclear Information System (INIS)
2016-09-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for July and August 2016. Demand increased by +1.8% compared to August 2015 due in particular to the heat wave that occurred at the end of the month. Corrected for weather effects, total demand increased, led by the demand from households, professionals and small businesses. To respond to the increased demand resulting from the heat wave, thermal generation using fossil fuel was used (up 145% compared to August 2015). For the first time, solar production broke the 1 TWh threshold in July and August. During the week of the start of the academic year, on Monday, 29 August, the balance of French electricity exchanges was in favour of imports for over 8 hrs. The July/August period was used to put 33 new installations into service
Monthly Electrical Energy Overview October 2016
International Nuclear Information System (INIS)
2016-11-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for October 2016. French gross electricity demand fell by 1.9%. The monthly balance of cross-border exchanges remain in favour of exports but dropped to its historically lowest point since February 2012. Corrected for climate factors, overall demand remained stable compared with October 2015. The fall in nuclear and hydraulic generation was offset by thermal fossil fuel generation that reached, with 5 TWh, its highest level since February 2015. Renewable generation excluding hydraulic increased in October, after the sharp fall of the previous month. Over the whole of the month, French exchanges remained in favour of exports although they fell by 89% compared to October 2015. 20 new installations went into service in October
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
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
Monthly Electrical Energy Overview September 2017
International Nuclear Information System (INIS)
2017-10-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for September 2017. Gross domestic demand increased slightly compared to September 2016, despite a monthly average temperature of less than 3.4 deg. C. The monthly balance of trade was positive (i.e. France was a net exporter) and increased by 73% compared to September 2016. Total demand corrected for climate contingencies remained stable. Demand by large industry continued its upward trend. Nuclear generation was up 11% compared to September 2016 and reached 29.3 TWh. Wind power production increased 66% compared to September 2016. The Greoux-les-Bains photovoltaic plant was connected to the public electricity transmission network. The plant has a generating power of 70 MW. The Grand-Est and Hauts-de-France regions really benefited from the strong winds observed across France. They thus contributed the most to the record levels of solar and wind generation recorded in September. Market prices were up in most European countries despite a notable decline in week 37. The monthly balance of trade remained exporter. 15 new installations went into service in September
Monthly Electrical Energy Overview November 2016
International Nuclear Information System (INIS)
2016-12-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for November 2016. The cool weather in November caused an increase in demand (+8% compared with November 2015). The monthly French exports balance dropped to its historically lowest point since February 2012. The trend in adjusted electricity demand was slightly down. The nuclear generation deficit was offset by the rise in thermal fossil fuel generation that, at 6.7 TWh, reached its highest level since February 2012. The average wind load factor reached almost 30%, the highest level since March 2016. Over the whole of the month, French exchanges remained slightly in favour of exports as they fell by 92% compared to November 2015. 33 new installations went into service in November 2016
Directory of Open Access Journals (Sweden)
Jeng-Fung Chen
2018-02-01
Full Text Available Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate planning and prediction of electricity load are therefore vital. In this study, a novel approach for forecasting monthly electricity demands by wavelet transform and a neuro-fuzzy system is proposed. Firstly, the most appropriate inputs are selected and a dataset is constructed. Then, Haar wavelet transform is utilized to decompose the load data and eliminate noise. In the model, a hierarchical adaptive neuro-fuzzy inference system (HANFIS is suggested to solve the curse-of-dimensionality problem. Several heuristic algorithms including Gravitational Search Algorithm (GSA, Cuckoo Optimization Algorithm (COA, and Cuckoo Search (CS are utilized to optimize the clustering parameters which help form the rule base, and adaptive neuro-fuzzy inference system (ANFIS optimize the parameters in the antecedent and consequent parts of each sub-model. The proposed approach was applied to forecast the electricity load of Hanoi, Vietnam. The constructed models have shown high forecasting performances based on the performance indices calculated. The results demonstrate the validity of the approach. The obtained results were also compared with those of several other well-known methods including autoregressive integrated moving average (ARIMA and multiple linear regression (MLR. In our study, the wavelet CS-HANFIS model outperformed the others and provided more accurate forecasting.
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
Monthly Electrical Energy Overview December 2016
International Nuclear Information System (INIS)
2017-01-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for December 2016. Demand in December 2016 was higher by more than 13% compared to December 2015, due to the significantly lower temperatures. The balance of exchanges was in favour of imports for the first time since February 2012. The December overview is published in the same time as the 2016 annual electricity report (http://bilan-electrique-2016.rte-france.com/). You will find there the analysis of the whole year. Adjusted electricity demand remained unchanged. Fossil fuel thermal generation reached 7.4 TWh, its highest level since February 2012. Wind power production was low, with an average wind load factor of around 17%. The monthly balance of French exchanges was in favour of imports, which had not happened since February 2012. 25 new installations went into service in December 2016
Monthly Electrical Energy Overview October 2017
International Nuclear Information System (INIS)
2017-11-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for Monthly gross domestic demand fell by 5.2% compared to October 2016, due to above-normal temperatures. The monthly trade balance was in favour of exports. Total demand corrected for climate contingencies remained stable. Demand by heavy industry continued its upward trend. Monthly nuclear generation fell by 3.3% compared to October 2016. The rainfall deficit resulted in a reduction of almost 11% in hydropower production compared to October 2016. Wind power production rose 46.7% compared to October 2016. Photovoltaic production fell by 2.2% compared to October 2016. The solar load factor fell in almost all French regions compared to October 2016. Market prices continued to increase, in particular in Belgium and in France where nuclear availability was strongly reduced. The monthly balance of trade for France was once again positive in October 2017. 15 new installations went into service in October
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.
Monthly Electrical Energy Overview Mars 2017
International Nuclear Information System (INIS)
2017-04-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for March 2017. With 2 deg. C over the normal average temperature, March 2017 was the hottest March recorded over the period 1900-2017. Therefore, gross French power demand fell by 9.4% compared to March 2016. A new record instantaneous balance in favour of exports was reached at over 17 GW. Gross demand was down compared to March 2016, due to milder temperatures. RE generation excluding hydraulic rose after 4 months of falls, driven by favourable weather conditions. The maximum coverage rate of demand by wind power generation reached a new record (18.2%) benefiting from the presence of windy conditions over the country in March. The monthly regional coverage rate of demand by generation of renewable origin exceeded 23% in the Occitanie, Auvergne-Rhone-Alpes, Grand-Est, Provence-Alpes-Cote d'Azur and Nouvelle-Aquitaine regions. The fall in prices continued throughout Europe. On 30 March at 19.30 a new record instantaneous balance in favour of exports was recorded at over 17 GW. 1 new installation went into service in March 2017
Monthly Electrical Energy Overview June 2017
International Nuclear Information System (INIS)
2017-07-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for June 2017. Average temperatures in June increased by +2.7 deg. compared to June 2016. Demand in June increased by +1.76% compared to June 2016. Demand in June increased by 1.76% compared to June 2016, due in particular to the heat wave that occurred between 19 and 22. Hydraulic generation was again penalized by the lack of rainfall with a fall of 28.6% compared to June 2016. Solar generation was up by 26.7%, driven by the high amount of sunlight in the month. The heat wave had a strong impact on demand in the regions most affected by the high temperatures: Champagne-Ardenne, Pays de la Loire, Midi-Pyrenees. Market prices increased in the south of Europe. France imported more than it exported via Switzerland. Overall, French exchanges remained in favour of exports in the month. 14 new installations went into service in June
Predicting summer residential electricity demand across the U.S.A using climate information
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.
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
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
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.
Monthly Electrical Energy Overview May 2017
International Nuclear Information System (INIS)
2017-06-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for May 2017. Demand increased slightly versus May 2016 with higher average temperatures (+1.6 deg.) over this period. Demand rose by 0.9% compared with May 2016. Hydraulic generation was again impacted by the lack of rain with a fall of 12,6% compared with May 2016. Solar generation increased by 20%, driven by the growth of the park and the high amounts of sunshine observed over the month. It is in Auvergne-Rhone-Alpes, Grand-Est, Hauts-de-France, Ile-de-France and Provence-Alpes-Cote d'Azur (PACA) that annual final demand from heavy industry was at its highest for 2016. In these regions, except for Ile-de-France, the chemicals, para-chemicals, metallurgy and steel sectors consumed the most energy. Market prices were relatively stable in most European countries. France had an export balance with all countries outside its borders. With 1.85 TWh, the export balance for monthly trades with Spain reached a new record. 7 new installations went into service in May
Monthly Electrical Energy Overview April 2017
International Nuclear Information System (INIS)
2017-05-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for April 2017. Despite lower than normal temperatures (-0.8 deg. C), April remained milder than that of the previous year, resulting in a slight fall in demand. For the third month in a row, demand fell compared to the same month in the previous year (-6.2%). Hydraulic generation suffered from the dry weather in April with a fall of 35% compared to April 2016. The good amount of sunlight this month as well as the increase in the installed photovoltaic base allowed solar generation to jump by more than 36%. The rainfall deficit over the country affected hydraulic generation with falls of as much as -80% in the Centre-Val de Loire region. Variations in market prices were mixed depending on the countries. The balance of exports was in France's favour on all its borders, with a national export balance greater than 5 TWh. 9 new installations went into service in April
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)
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.
Cut Electric Bills by Controlling Demand
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)
Electricity demand and storage dispatch modeling for buildings and implications for the smartgrid
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.
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
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)
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
Energy Technology Data Exchange (ETDEWEB)
Smith, Sandra R.; Johnson, Melvin; McClevey, Kenneth; Calopedis, Stephen; Bolden, Deborah
1992-05-01
The Electric Power Monthly is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fuel are also displayed for the North American Electric Reliability Council (NERC) regions. Additionally, statistics by company and plant are published in the EPM on capability of new plants, new generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel.
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
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.
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-08-01
The Energy Information Administration (EIA) prepares the Electric Power Monthly (EPM) for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source, consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead.
Monthly Electrical Energy Overview February 2017
International Nuclear Information System (INIS)
2017-03-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for February 2017. The monthly balance of French exchanges once again passed back in favour of exports in February 2017, despite a fall in nuclear and hydraulic generation. Gross demand was down compared to February 2016, due to milder temperatures. Fossil fuel thermal generation totalled 6.1 TWh, up by 65% compared to February 2016. Due to fluctuating winds, February 2017 recorded both an instantaneous generation peak for the wind and solar sectors (11.3 GW), and a fall in monthly wind generation compared to February 2016. The fall in wind power generation was not uniform over the country: the Southwest experienced stormy episodes boosting generation whereas that in the North-East fell sharply. Market prices were sharply lower Europe-wide. The balance in favour of exports totalled 3.4 TWh in February 2017. 11 installations went into service in this month
Electricity Demand Forecasting Using a Functional State Space Model
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...
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)
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)
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
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.
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)
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
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.
Simulation of demand side participation in Spanish short term electricity markets
International Nuclear Information System (INIS)
Valencia-Salazar, I.; Alvarez, C.; Escriva-Escriva, G.; Alcazar-Ortega, M.
2011-01-01
Highlights: → Benefits from customer active participation can be obtained with a proper generation of bids and offers. → Simulation of Spanish customers' participation is shown in daily, intra-daily and balancing markets. → Market efficiency and economics profits arise in balancing markets by using customer load reductions. → Real market prices and real customers' consumptions profiles are used in the simulations. -- Abstract: Demand response resources management is one of the most investigated solutions oriented to improve the efficiency in electricity markets. In this paper, the capability of customers to participate in short term markets is analyzed. An available methodology to analyze the daily and monthly energy consumptions of large customers is used to create energy offers and bids. This allows customers to participate in energy markets in order to buy, as first step, the usual electricity consumption and, additionally, to offer demand reductions in the short term electricity markets. Additionally, this paper shows the customer potential to participate in the Spanish electricity markets.
Electric power monthly, August 1993
Energy Technology Data Exchange (ETDEWEB)
1993-08-13
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EPM is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.
Electric power monthly, September 1993
Energy Technology Data Exchange (ETDEWEB)
1993-09-17
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EPM is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.
Electric power monthly, May 1994
Energy Technology Data Exchange (ETDEWEB)
1994-05-01
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Statistics by company and plant are published on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels.
Electric power monthly, April 1994
Energy Technology Data Exchange (ETDEWEB)
1994-04-01
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the U.S., Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. This April 1994 issue contains 1993 year-end data and data through January 1994.
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.
Electric Power Monthly, July 1990
Energy Technology Data Exchange (ETDEWEB)
1990-10-12
The Electric Power Monthly (EPM) is prepared by the Electric Power Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, and average revenue per kilowatthour of electricity sold. Data on net generation are also displayed at the North American Electric Reliability Council (NERC) region level. Additionally, company and plant level information are published in the EPM on capability of new plants, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost in fuel. Quantity, quality, and cost of fuel data lag the net generation, fuel consumption, fuel stocks, electricity sales, and average revenue per kilowatthour data by 1 month. This difference in reporting appears in the national, Census division, and State level tables. However, at the plant level, all statistics presented are for the earlier month for the purpose of comparison. 12 refs., 4 figs., 48 tabs.
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)
A Panel Data Analysis of Electricity Demand in Pakistan
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...
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.
Australia's long-term electricity demand forecasting using deep neural networks
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...
Electric power monthly, April 1993
Energy Technology Data Exchange (ETDEWEB)
1993-05-07
The Electric Power Monthly is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.
Electric power monthly, May 1993
Energy Technology Data Exchange (ETDEWEB)
1993-05-25
The Electric Power Monthly (EPM) is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.
Electric power monthly, July 1994
Energy Technology Data Exchange (ETDEWEB)
1994-07-01
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. The EPM is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. Statistics by company and plant are published in the EPM on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels. Data on quantity, quality, and cost of fossil fuels lag data on net generation, fuel consumption, fuel stocks, electricity sales, and average revenue per kilowatthour by 1 month. This difference in reporting appears in the US, Census division, and State level tables. However, for purposes of comparison, plant-level data are presented for the earlier month.
An electricity system : 18-month outlook from Oct 2004 to March 2006
International Nuclear Information System (INIS)
2004-01-01
This report presents a resource assessment by the Independent Electricity Market Operator (IMO) for the 18-month period from October 2004 to March 2006. It is based on the IMO's forecast of electricity demand. The information was provided by power generators in Ontario. The outlook for the electricity system has improved due to new resource additions in 2004 which have improved the general supply situation. The Brighton Beach (580 MW) and Kirkland Lake (32 MW) facilities have completed commissioning since the last quarterly outlook. Plans have also been announced to return the nuclear Pickering Unit 1 to service for a projected capacity increase of 515 MW by the fall of 2005. The impending shutdown of 1150 MW of coal-fired generation at Lakeview Thermal Generating Station in Mississauga in April 2005 emphasizes the importance of improving transmission and generation capacity in the Toronto area. Requests for Proposals for 300 MW of renewable energy supply have been issued by the Ontario government along with requests for 2,500 MW of new clean generation and demand-side projects. This report also includes updated values for existing resource scenarios and planned resource scenarios. The reliability of Ontario's transmission system was also assessed along with the adequacy of the existing resource to meet the forecast demand. The existing installed generation resources include 5 nuclear stations generating 10,850 MW of electricity, 5 coal stations generating 7,564 MW of electricity, 23 oil and gas fired stations generating 4,976 MW of electricity, 61 hydroelectric stations generating 7,676 MW of electricity, and 2 other stations generating 66 MW of electricity. Although the existing resource scenario is better than in previous reports, imports will be required under extreme weather conditions to help meet electricity demand in Ontario during peak periods. 19 tabs., 10 figs
Electric Power Monthly, June 1990
Energy Technology Data Exchange (ETDEWEB)
1990-09-13
The EPM is prepared by the Electric Power Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, electricity sales, and average revenue per kilowatthour of electricity sold. Data on net generation are also displayed at the North American Electric Reliability Council (NERC) region level. Additionally, company and plant level information are published in the EPM on capability of new plants, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel. Quantity, quality, and cost of fuel data lag the net generation, fuel consumption, fuel stocks, electricity sales, and average revenue per kilowatthour data by 1 month. This difference in reporting appears in the national, Census division, and State level tables. However, at the plant level, all statistics presented are for the earlier month for the purpose of comparison. 40 tabs.
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
International Nuclear Information System (INIS)
2001-01-01
The Independent Electricity Market Operator (IMO) has monitored the state of electricity demand and available supply in Ontario and has reported its findings to the Minister of Energy, Science and Technology and to the Ontario Energy Board. This report presents the IMO's assessment of the adequacy of resources and transmission for the Ontario electricity system for the 18-month period from January 2002 to June 2003. The assessment was based on current information on forecasts of electricity demand and available supply. The existing installed generation within Ontario was summarized. Existing power facilities include nuclear, coal, oil, gas, hydroelectric, wind-powered, wood and waste-fuelled generation. The installations range from less than 1 MW in size to 881 MW net electrical output. The total generating capacity in Ontario is 29,523 MW, excluding embedded generators that are not managed by the Ontario Electricity Financial Corporation or generation not connected to the IMO-controlled grid. In addition, the Bruce Nuclear Unit was not included because it is currently in laid-up state. This report discussed changes from the previous 18-month outlook in terms of power demand. It also presented outlooks of the transmission outage plan, system voltage, thermal concerns and forced outages. The general conclusion reached in this report is that there will be sufficient resources and transmission available to Ontario to supply Ontario demands and to meet the Northeast Power Coordinating Council (NPCC) resource criteria for the next 18 months. tabs., figs
Estimating elasticity for residential electricity demand in China.
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.
Electric power monthly, June 1994
Energy Technology Data Exchange (ETDEWEB)
1994-06-01
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.
Electric power monthly, August 1994
Energy Technology Data Exchange (ETDEWEB)
1994-08-24
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.
Electric power monthly, July 1993
Energy Technology Data Exchange (ETDEWEB)
1993-07-29
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.
Electric power monthly, November 1994
International Nuclear Information System (INIS)
1994-11-01
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended
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.
Connecting plug-in vehicles with green electricity through consumer demand
Axsen, Jonn; Kurani, Kenneth S.
2013-03-01
The environmental benefits of plug-in electric vehicles (PEVs) increase if the vehicles are powered by electricity from ‘green’ sources such as solar, wind or small-scale hydroelectricity. Here, we explore the potential to build a market that pairs consumer purchases of PEVs with purchases of green electricity. We implement a web-based survey with three US samples defined by vehicle purchases: conventional new vehicle buyers (n = 1064), hybrid vehicle buyers (n = 364) and PEV buyers (n = 74). Respondents state their interest in a PEV as their next vehicle, in purchasing green electricity in one of three ways, i.e., monthly subscription, two-year lease or solar panel purchase, and in combining the two products. Although we find that a link between PEVs and green electricity is not presently strong in the consciousness of most consumers, the combination is attractive to some consumers when presented. Across all three respondent segments, pairing a PEV with a green electricity program increased interest in PEVs—with a 23% demand increase among buyers of conventional vehicles. Overall, about one-third of respondents presently value the combination of a PEV with green electricity; the proportion is much higher among previous HEV and PEV buyers. Respondents’ reported motives for interest in both products and their combination include financial savings (particularly among conventional buyers), concerns about air pollution and the environment, and interest in new technology (particularly among PEV buyers). The results provide guidance regarding policy and marketing strategies to advance PEVs and green electricity demand.
Connecting plug-in vehicles with green electricity through consumer demand
International Nuclear Information System (INIS)
Axsen, Jonn; Kurani, Kenneth S
2013-01-01
The environmental benefits of plug-in electric vehicles (PEVs) increase if the vehicles are powered by electricity from ‘green’ sources such as solar, wind or small-scale hydroelectricity. Here, we explore the potential to build a market that pairs consumer purchases of PEVs with purchases of green electricity. We implement a web-based survey with three US samples defined by vehicle purchases: conventional new vehicle buyers (n = 1064), hybrid vehicle buyers (n = 364) and PEV buyers (n = 74). Respondents state their interest in a PEV as their next vehicle, in purchasing green electricity in one of three ways, i.e., monthly subscription, two-year lease or solar panel purchase, and in combining the two products. Although we find that a link between PEVs and green electricity is not presently strong in the consciousness of most consumers, the combination is attractive to some consumers when presented. Across all three respondent segments, pairing a PEV with a green electricity program increased interest in PEVs—with a 23% demand increase among buyers of conventional vehicles. Overall, about one-third of respondents presently value the combination of a PEV with green electricity; the proportion is much higher among previous HEV and PEV buyers. Respondents’ reported motives for interest in both products and their combination include financial savings (particularly among conventional buyers), concerns about air pollution and the environment, and interest in new technology (particularly among PEV buyers). The results provide guidance regarding policy and marketing strategies to advance PEVs and green electricity demand. (letter)
Indonesia’s Electricity Demand Dynamic Modelling
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.
Electric power monthly, February 1994
Energy Technology Data Exchange (ETDEWEB)
1994-02-16
The Electric Power Monthly (EMP) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. Statistics by company and plant are published in the EPM on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels.
Electric power monthly, January 1994
International Nuclear Information System (INIS)
1994-01-01
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. This publication provides monthly statistics at the US Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. Statistics by company and plant are published in the EPM on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels
Electric power monthly, January 1994
Energy Technology Data Exchange (ETDEWEB)
1994-01-26
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. This publication provides monthly statistics at the US Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. Statistics by company and plant are published in the EPM on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels.
Electric power monthly, October 1993
Energy Technology Data Exchange (ETDEWEB)
1993-10-20
The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. Statistics by company and plant are published in the EPM on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels.
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
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.
Electric Power Monthly, March 1991
International Nuclear Information System (INIS)
1991-01-01
The Electric Power Monthly (EPM) presents monthly summaries of electric utility statistics at the national, Census division, and state level. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data are presented on generation, fuel consumption, stockpiles, costs, sales, and unusual occurrences. Fuels considered are: coal, petroleum, natural gas, nuclear power, and hydroelectric power. 4 figs., 48 tabs
Demand forecasting of electricity in Indonesia with limited historical data
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).
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
Electric power monthly, April 1991
International Nuclear Information System (INIS)
1991-01-01
The Electric Power Monthly (EPM) presents monthly summaries of electric utility statistics at the national Census division, and State level. The purpose of this publication is to provide energy decision makers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data are given for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatt hour of electricity sold. Data on net generation are also displayed at the North American Electric Reliability Council (NERC) region level. Additionally, statistics at the company and plant level are published in the EPM on capability of new plants, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel. 6 figs., 57 tabs
Subramani, Gopinath; Ramachandaramurthy, Vigna K.; Padmanaban, Sanjeevikumar; Mihet-Popa, Lucian; Blaabjerg, Frede; Guerrero, Josep M.
2017-01-01
Under the current energy sector framework of electricity tariff in Malaysia, commercial and industrial customers are required to pay the maximum demand (MD) charge apart from the net consumption charges every month. The maximum demand charge will contribute up to 20% of the electricity bill, and will hence result in commercial and industrial customers focussing on alternative energy supply to minimize the billing cost. This paper aims to review the technical assessment methods of a grid-conne...
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)
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.
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.
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).
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.
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
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)
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)
Monthly Electrical Energy Overview July and August 2017
International Nuclear Information System (INIS)
2017-09-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for July and August 2017. Demand was stable compared to July and August 2016. The average temperatures were close to those of 2016: +0.3 deg. C in July and -0.6 deg. C in August. Demand remained stable with a slight increase (+0.5%) in July and a slight decrease (0.3%) in August. Hydraulic generation was impacted by the lack of rain with a fall of 26.5% in July compared with 2016. Wind power generation was up by 67.6% and reached 1,699 TWh in July compared to 2016 buoyed by good wind conditions. Generation of electricity from wind now exceeds the total energy produced over the same period in 2016. The Grand-Est, Hauts-de-France, Occitanie and Centre- Val de Loire regions contribute 70% of the increase in wind power generation in July. The French price decreased in August. Overall, French exchanges remained in favour of exports in July and August 22 new installations went into service in July and August
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.
Visualising electricity demand: use and users of a 3D chart from the 1950s
Directory of Open Access Journals (Sweden)
Alice Cliff
2018-05-01
Full Text Available Showing electricity demand by the hour, day, month and year, this 3D chart offers a rich visualisation of energy data in the UK from the years 1951–54. Acquired by the Museum of Science & Industry, Manchester, the object is significant as a tangible record of past practice, both of the electricity supply industry and its consumers. In this paper, we offer a close inspection of the object, and following its clues, we generate ideas about the chart’s use and users. In addition to commenting on the rhythmic patterning of daily and seasonal loads, we reflect on the role of the object at the time of its construction, in terms of forecasting, price-setting and load-shifting, and lobbying and demonstration. The object literally materialises electricity demand, providing a distinctive 3D representation, and in so doing prompting questions about how demand changes over time, and in time, and how our practices of everyday life constitute this demand. We conclude by offering a new interpretation of the object as a tool, as well as historical data.
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/
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 ...
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)
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)
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
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
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.
Forecasting residential electricity demand in provincial China.
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.
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.
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.
Prediction on the charging demand for electric vehicles in Chengdu
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.
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.
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
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.)
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.)
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
Directory of Open Access Journals (Sweden)
Pełka Paweł
2017-01-01
Full Text Available Electricity demand forecasting is of important role in power system planning and operation. In this work, fuzzy nearest neighbour regression has been utilised to estimate monthly electricity demands. The forecasting model was based on the pre-processed energy consumption time series, where input and output variables were defined as patterns representing unified fragments of the time series. Relationships between inputs and outputs, which were simplified due to patterns, were modelled using nonparametric regression with weighting function defined as a fuzzy membership of learning points to the neighbourhood of a query point. In an experimental part of the work the model was evaluated using real-world data. The results are encouraging and show high performances of the model and its competitiveness compared to other forecasting models.
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.
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.
Short-term electric power demand forecasting based on economic-electricity transmission model
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.
Electric Power Monthly, June 1988
International Nuclear Information System (INIS)
1988-06-01
The data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The Energy Information Administration (EIA) collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. The Electric Power Monthly contains information from three data sources: the Form EIA-759, 'Monthly Power Plant Report'; the Federal Energy Regulatory Commission (FERC) Form 423, 'Monthly Report of Cost and Quality of Fuels for Electric Plants ; and the Form EIA-826, M onthly Electric Sales and Revenue Report with State Distributions'. The Form EIA-759 collects data from all operators of electric utility generating plants (except those having plants solely on standby), approximately 800 of the more than 3,200 electric utilities in the United States. To reduce the reporting burden for utilities, the FERC Form 423 and Form EIA-826 data are based on samples, which cover less than 100 percent of all central station generating utilities. The FERC Form 423 collects data from steam-electric power generating plants with a combined installed nameplate capacity of 50 megawatts or larger (approximately 230 electric utilities). The 50-megawatt threshold was established by FERC. The Form EIA-826 collects sales and revenue data in the residential, commercial, industrial, and other sectors of the economy. Other sales data collected include public street and highway lighting, other sales to public authorities, sales to railroads and railways, and interdepartmental sales. Respondents to the Form EIA-826 were statistically chosen and include approximately 225 privately and publicly owned electric utilities from a universe of more than 3,200 utilities. The sample selection for the Form EIA-826 is evaluated annually. Currently, the Form EIA-826 data account for approximately 83 percent
Electric power monthly, March 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-03-20
This report for March 1995, presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead.
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
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.
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
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
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)
Electric energy demand and supply prospects for California
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.
Medium-term electric power demand forecasting based on economic-electricity transmission model
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.
Directory of Open Access Journals (Sweden)
Zhanglin Peng
2015-04-01
Full Text Available Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the development of EVs industrialization in the developing countries. This paper seeks to research the industrialization path & prospect of American EVs by forecasting electric vehicles demand and its proportion to the whole car sales based on the historical 37 EVs monthly sales and Cars monthly sales spanning from Dec. 2010 to Dec. 2013, and find out the key measurements to help Chinese government and automobile enterprises to promote Chinese EVs industrialization. Design/methodology: Compared with Single Exponential Smoothing method and Double Exponential Smoothing method, Triple exponential smoothing method is improved and applied in this study. Findings: The research results show that: American EVs industry will keep a sustained growth in the next 3 months. Price of the EVs, price of fossil oil, number of charging station, EVs technology and the government market & taxation polices have a different influence to EVs sales. So EVs manufacturers and policy-makers can adjust or reformulate some technology tactics and market measurements according to the forecast results. China can learn from American EVs polices and measurements to develop Chinese EVs industry. Originality/value: The main contribution of this paper is to use the triple exponential smoothing method to forecast the electric vehicles demand and its proportion to the whole automobile sales, and analyze the industrial development of Chinese electric vehicles by American EVs industry.
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....
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.
International Nuclear Information System (INIS)
2001-01-01
One of the responsibilities of Ontario's Independent Electricity Market Operator (IMO) is to make sure that existing and proposed generation and transmission facilities can meet the province's energy needs. This report presents an assessment of the adequacy of resources and transmission for Ontario's electricity system for the 18 month period from October 2001 to March 2003. It is also meant to advise the Ontario Energy Board of any adverse conditions that might be avoided through adjustment or coordination of maintenance plans for generation and transmission equipment. The assessment is based on forecasts of electricity demand, available supply and capability of the existing transmission system. Outage plans of generators and transmitters were based on information as of August 3, 2001. An 18 month forecast of electricity demand for Ontario was presented along with the resources and transmission systems that are expected to be available during the study period. The overall assessment is that there will be sufficient resources and transmission available in Ontario to supply the predicted energy demand and to meet the specified reserve margins under the forecasted conditions. The report included graphs which depicted how the weekly peak Ontario demand plus a weekly reserve requirement can be met for each week of the Outlook timeframe. The resource adequacy assessment takes into account all types of weather conditions on a probabilistic basis. 16 tabs., 8 figs
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.
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
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.
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.
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
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
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.
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.
Hourly price elasticity pattern of electricity demand in the German day-ahead market
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...
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%
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.
Electric Power Monthly, August 1990. [Glossary included
Energy Technology Data Exchange (ETDEWEB)
1990-11-29
The Electric Power Monthly (EPM) presents monthly summaries of electric utility statistics at the national, Census division, and State level. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data includes generation by energy source (coal, oil, gas, hydroelectric, and nuclear); generation by region; consumption of fossil fuels for power generation; sales of electric power, cost data; and unusual occurrences. A glossary is included.
Quantifying the Flexibility of Residential Electricity Demand in 2050: a Bottom-Up Approach
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...
Electric power monthly, May 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-05-01
This publication presents monthly electricity statistics for a wide audience including Congress, Federal and Stage agencies, the electric utility industry, and the general public. Purpose is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. EIA collected the information to fulfill its data collection and dissemination responsibilities in Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.
International Nuclear Information System (INIS)
Shao, Zhen; Yang, Shan-Lin; Gao, Fei
2014-01-01
Highlights: • A new stationary time series smoothing-based semiparametric model is established. • A novel semiparametric additive model based on piecewise smooth is proposed. • We model the uncertainty of data distribution for mid-term electricity forecasting. • We provide efficient long horizon simulation and extraction for external variables. • We provide stable and accurate density predictions for mid-term electricity demand. - Abstract: Accurate mid-term electricity demand forecasting is critical for efficient electric planning, budgeting and operating decisions. Mid-term electricity demand forecasting is notoriously complicated, since the demand is subject to a range of external drivers, such as climate change, economic development, which will exhibit monthly, seasonal, and annual complex variations. Conventional models are based on the assumption that original data is stable and normally distributed, which is generally insignificant in explaining actual demand pattern. This paper proposes a new semiparametric additive model that, in addition to considering the uncertainty of the data distribution, includes practical discussions covering the applications of the external variables. To effectively detach the multi-dimensional volatility of mid-term demand, a novel piecewise smooth method which allows reduction of the data dimensionality is developed. Besides, a semi-parametric procedure that makes use of bootstrap algorithm for density forecast and model estimation is presented. Two typical cases in China are presented to verify the effectiveness of the proposed methodology. The results suggest that both meteorological and economic variables play a critical role in mid-term electricity consumption prediction in China, while the extracted economic factor is adequate to reveal the potentially complex relationship between electricity consumption and economic fluctuation. Overall, the proposed model can be easily applied to mid-term demand forecasting, and
Long-term water demand for electricity, industry and households
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,
International Nuclear Information System (INIS)
Robinson, A.P.; Blythe, P.T.; Bell, M.C.; Hübner, Y.; Hill, G.A.
2013-01-01
This paper quantifies the recharging behaviour of a sample of electric vehicle (EV) drivers and evaluates the impact of current policy in the north east of England on EV driver recharging demand profiles. An analysis of 31,765 EV trips and 7704 EV recharging events, constituting 23,805 h of recharging, were recorded from in-vehicle loggers as part of the Switch EV trials is presented. Altogether 12 private users, 21 organisation individuals and 32 organisation pool vehicles were tracked over two successive six month trial periods. It was found that recharging profiles varied between the different user types and locations. Private users peak demand was in the evening at home recharging points. Organisation individual vehicles were recharged primarily upon arrival at work. Organisation pool users recharged at work and public recharging points throughout the working day. It is recommended that pay-as-you-go recharging be implemented at all public recharging locations, and smart meters be used to delay recharging at home and work locations until after 23:00 h to reduce peak demand on local power grids and reduce carbon emissions associated with EV recharging. - Highlights: • Study of EV driver recharging habits in the north east of England. • 7704 electric vehicle recharging events, comprising 23,805 h were collected. • There was minimal recharging during off- peak hours. • Free parking and electricity at point of use encouraged daytime recharging. • Need for financial incentives and smart solutions to better manage recharging demand peaks
Bayesian Analysis of Demand Elasticity in the Italian Electricity Market
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...
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....
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)
Impact of peak electricity demand in distribution grids: a stress test
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.
Electric power demand forecasting using interval time series. A comparison between VAR and iMLP
International Nuclear Information System (INIS)
Garcia-Ascanio, Carolina; Mate, Carlos
2010-01-01
Electric power demand forecasts play an essential role in the electric industry, as they provide the basis for making decisions in power system planning and operation. A great variety of mathematical methods have been used for demand forecasting. The development and improvement of appropriate mathematical tools will lead to more accurate demand forecasting techniques. In order to forecast the monthly electric power demand per hour in Spain for 2 years, this paper presents a comparison between a new forecasting approach considering vector autoregressive (VAR) forecasting models applied to interval time series (ITS) and the iMLP, the multi-layer perceptron model adapted to interval data. In the proposed comparison, for the VAR approach two models are fitted per every hour, one composed of the centre (mid-point) and radius (half-range), and another one of the lower and upper bounds according to the interval representation assumed by the ITS in the learning set. In the case of the iMLP, only the model composed of the centre and radius is fitted. The other interval representation composed of the lower and upper bounds is obtained from the linear combination of the two. This novel approach, obtaining two bivariate models each hour, makes possible to establish, for different periods in the day, which interval representation is more accurate. Furthermore, the comparison between two different techniques adapted to interval time series allows us to determine the efficiency of these models in forecasting electric power demand. It is important to note that the iMLP technique has been selected for the comparison, as it has shown its accuracy in forecasting daily electricity price intervals. This work shows the ITS forecasting methods as a potential tool that will lead to a reduction in risk when making power system planning and operational decisions. (author)
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.
Research on electricity market operation mechanism and its benefit of demand side participation
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.
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
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.
Electric Power monthly, November 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-11-01
This publication presents monthly electricity statistics for a wide audience including Congress, Federal and state agencies, the electric utility industry, and the general public. Purpose is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.
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
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
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
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
Which electricity market design to encourage the development of demand response?
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,...
Which electricity market design to encourage the development of demand response?
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-...
Smart electric storage heating and potential for residential demand response
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-...
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...
International Nuclear Information System (INIS)
2004-01-01
This report presents a resource assessment by the Independent Electricity Market Operator (IMO) for the 18-month period from April 2004 to September 2005. It is based on the IMO's forecast of electricity demand. The information was provided by power generators in Ontario. The outlook for the electricity system has improved due to the return to service of 3 nuclear units and the addition of more than 700 MW of generation. The return to service of the nuclear units has decreased Ontario's reliance on imports to help meet energy demand in the province. The shutdown of 1150 MW of coal-fired generation at Lakeview Thermal Generating Station in Mississauga emphasizes the importance of improving transmission and generation capacity in the Toronto area. This report also includes updated values for existing resource scenarios and planned resource scenarios. The reliability of Ontario's transmission system was also assessed along with the adequacy of the existing resource to meet the forecast demand. The existing installed generation resources include 5 nuclear stations generating 10,831 MW of electricity, 5 coal stations generating 7,564 MW of electricity, 22 oil and gas fired stations generating 4,364 MW of electricity, 61 hydroelectric stations generating 7,676 MW of electricity, and 2 other stations generating 66 MW of electricity. Although the existing resource scenario is better than in previous reports, imports will be required under extreme weather conditions to help meet electricity demand in Ontario during peak periods. 21 tabs., 10 figs
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...
Demand Response Within Current Electricity Wholesale Market Design
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...
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)
Market-based Demand Response via Residential Plug-in Electric Vehicles in Smart Grids
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...
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.
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
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
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)
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
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)
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)
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....
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.
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.
A Review of Demand Forecast for Charging Facilities of Electric Vehicles
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.
Electric power monthly with data for November 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-02-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.
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
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.
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...
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.
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
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
Price-elastic demand in deregulated electricity markets
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...
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.
Impact of uncoordinated plug-in electric vehicle charging on residential power demand
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.
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.
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
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.
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
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...
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)
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.
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
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.
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
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.
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.
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)
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)
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
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
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
Electric power monthly, July 1997 with data for April 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-07-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. 57 tabs.
Electric power monthly, June 1997 with data for March 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-06-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. 63 tabs.
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
Electric Power Monthly, September 1995: With data for June 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-09-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.
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
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.
Electric power monthly, August 1998, with data for May 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-08-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. 9 refs., 57 tabs.
Electric power monthly, March 1999 with data for December 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-03-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be sued in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. 63 tabs.
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)
Modeling of demand response in electricity markets : effects of price elasticity
International Nuclear Information System (INIS)
Banda, E.C.; Tuan, L.A.
2007-01-01
A design mechanism for the optimal participation of customer load in electricity markets was presented. In particular, this paper presented a modified market model for the optimal procurement of interruptible loads participating in day-ahead electricity markets. The proposed model considers the effect of price elasticity and demand-response functions. The objective was to determine the role that price elasticity plays in electricity markets. The simulation model can help the Independent System Operator (ISO) identify customers offering the lowest price of interruptible loads and load flow patterns that avoid problems associated with transmission congestion and transmission losses. Various issues associated with procurement of demand-response offerings such as advance notification, locational aspect of load, and power factor of the loads, were considered. It was shown that demand response can mitigate price volatility by allowing the ISO to maintain operating reserves during peak load periods. It was noted that the potential benefits of the demand response program would be reduced when price elasticity of demand is taken into account. This would most likely occur in actual developed open electricity markets, such as Nordpool. This study was based on the CIGRE 32-bus system, which represents the Swedish high voltage power system. It was modified for this study to include a broad range of customer characteristics. 18 refs., 2 tabs., 14 figs
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.
Electric power monthly January 1997 with data for October 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-01-01
This publication presents monthly electricity statistical data. Information is included on U.S. electric utility net generation, consumption of fossil fuels, and fossil-fuel stocks; U.S. electric utility sales; receipts and cost of fossil fuels at utilities; and monthly plant aggregates. A glossary is included.
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)
Electric power monthly: April 1996, with data for January 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-04-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decision makers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatt hour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. 64 tabs.
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
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
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.
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)
The design of optimal electric power demand management contracts
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
International Nuclear Information System (INIS)
Mirasgedis, S.; Sarafidis, Y.; Georgopoulou, E.; Kotroni, V.; Lagouvardos, K.; Lalas, D.P.
2007-01-01
This paper focuses on the potential upcoming impacts of climate change in the 21st century on electricity demand at regional/national levels for regions where topography and location result in large differences in local climate. To address this issue, a regional climate model, PRECIS, has been used to predict future climatic conditions under different emissions scenarios (namely A2 and B2 of the IPCC special report on emissions scenarios (SRES)) as an input to a multiple regression model of the sensitivity of electricity demand in the Greek interconnected power system to climate and socio-economic factors. The economic development input to the multiple regression model follows the same storylines of the SRES scenarios upto 2100 and includes sub-scenarios to cover larger and smaller economic development rates. The results of the analysis indicate an increase of the annual electricity demand attributable solely to climate change of 3.6-5.5% under all scenarios examined, most of which results from increased annual variability with substantial increases during the summer period that outweighs moderate declines estimated for the winter period. This becomes more pronounced if inter-annual variability, especially of summer months, is taken into consideration. It was also found that in the long run, economic development will have a strong effect on future electricity demand, thus increasing substantially the total amount of energy consumed for cooling and heating purposes. This substantial increase in energy demand with strong annual variability will lead to the need for inordinate increases of installed capacity, a large percentage of which will be under utilized. Thus, appropriate adaptation strategies (e.g. new investments, interconnections with other power systems, energy saving programmes, etc.) need to be developed at the state level in order to ensure the security of energy supply. (author)
A perspective on electric vehicles: cost-benefit analysis and potential demand
International Nuclear Information System (INIS)
2011-01-01
This report proposes some quantitative elements to assess the large scale diffusion of electric vehicles and analyse the potential demand for such vehicles. The first part proposes a cost-benefit analysis of the development of electric vehicles based on estimated costs and expected benefits by 2020. It addresses the following issues: framework and hypothesis, total cost of ownership, costs related to the deployment of a network of recharging infrastructures, assessment of external costs, and comparative cost-benefit analysis of electric vehicles. In the second part, the authors aim at identifying a potential demand for electric vehicles from the 2008 French national transport displacement survey (ENTD 2008) which provides recent data on the mobility of the French population
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.)
Electric power monthly, February 1999 with data for November 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-02-01
The Electric Power Monthly presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decision makers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Statistics are provided for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatt-hour of electricity sold.
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.
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 ...
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.
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
18-month outlook : an assessment of the reliability of the Ontario Electricity System
International Nuclear Information System (INIS)
2005-01-01
This paper provides an 18 month forecast of the Ontario electricity system, as well as an outline of activities and recent developments relating to the issue of reliability. An additional aim of the paper was to identify potentially adverse conditions that may require adjustment or coordination of maintenance plans for generation and transmission equipment. Requests for proposals (RFPs) for renewable generation within the specified time-frame were also discussed, as well as the return to service of Ontario Power Generation's Pickering Unit 1. Reduced reserve levels for the summer of 2005 were anticipated, and details of forecasted peak demand, generator maintenance, new generation and price-responsive demand adjustments and forced outage rates were presented. It was suggested that adequate market mechanisms were in place to manage reserve levels. Developments concerning the new Parkway Transformer station were reviewed. A resource outlook was provided. Available resources were expected to exceed planning requirements with the exception of 6 weeks in the summer of 2005. A projected capacity increase was also anticipated, due to the return of Pickering 1 and an additional 515 MW in the fall of 2005. Price-responsive demands were forecasted to exceed 650 MW due to increases in dispatchable load. It was suggested that in order to ensure power demand during peak periods, imports may be required under extreme weather conditions, combined with the possible deferral or cancellation of generation maintenance. Transmission impacts due to shutdowns were discussed. Voltage system requirements were reviewed, along with details of the installation of additional shunt capacitors and transformer controls. The electricity market was reviewed in the context of current overall economic conditions. Data forecasting normal peak demand was presented for the entire outlook period. 19 tabs., 10 figs
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.
Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach
Directory of Open Access Journals (Sweden)
Karin Kandananond
2011-08-01
Full Text Available Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA, artificial neural network (ANN and multiple linear regression (MLR—were utilized to formulate prediction models of the electricity demand in Thailand. The objective was to compare the performance of these three approaches and the empirical data used in this study was the historical data regarding the electricity demand (population, gross domestic product: GDP, stock index, revenue from exporting industrial products and electricity consumption in Thailand from 1986 to 2010. The results showed that the ANN model reduced the mean absolute percentage error (MAPE to 0.996%, while those of ARIMA and MLR were 2.80981 and 3.2604527%, respectively. Based on these error measures, the results indicated that the ANN approach outperformed the ARIMA and MLR methods in this scenario. However, the paired test indicated that there was no significant difference among these methods at α = 0.05. According to the principle of parsimony, the ARIMA and MLR models might be preferable to the ANN one because of their simple structure and competitive performance
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.)
Electric Power Monthly with data for July 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-10-01
This publication provides monthly statistics at the state, census division, and U.S. levels for net generation; fossil fuel consumption and stocks, quantity, and quality of fossil fuels; cost of fossil fuels; electricity retail sales; associated revenue; and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council regions. Statistics on net generation are published by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. The monthly update is summarized, and industry developments are briefly described. 57 tabs.
Electric power monthly, September 1998, with data for June 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-09-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The Electric Power Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
Electric power monthly, April 1999 with data for January 1999
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-04-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The Electric Power Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
Electric power monthly: October 1995, with data for July 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-10-19
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
Demand Response Application forReliability Enhancement in Electricity Market
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...
Electric power monthly, December 1998 with data for September 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-12-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities. 57 tabs.
Electric power monthly, December 1997 with data for September 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-12-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 63 tabs.
Electric power monthly, May 1999, with data for February 1999
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-05-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decision makers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatt hour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 64 tabs.
Electric power monthly: October 1996, with data for July 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-10-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. This report contains approximately 60 tables.
Electric power monthly, May 1998, with data for February 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-05-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974. The EPM provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. 30 refs., 58 tabs.
Electric power monthly, May 1995 with data for February 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-05-24
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisiommakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuel, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
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.
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...
Electric power monthly, March 1998 with data for December 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-03-01
The Electric Power Monthly (EPM) provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. 63 tabs.
Electric power monthly with data for October 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-01-01
This publication provides monthly statistics at the State, Census division, and U.S. levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council regions. Statistics are published on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. A monthly utility update and summary of industry developments are also included. 63 tabs., 1 fig.
Electric power monthly with data for August 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-11-01
This publication provides monthly statistics at the state, census division, and U.S. levels for net generation; fossil fuel consumption and stocks, quantity, and quality of fossil fuels; cost of fossil fuels; electricity retail sales; associated revenue; and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council regions. Statistics on net generation are published by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. The monthly update is summarized, and industry developments are briefly described. 1 fig., 63 tabs.
Electric power monthly, November 1998, with data for August 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-11-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The Electric Power Division; Office of Coal, Nuclear, Electric and Alternate fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 57 tabs.
Electric power monthly, October 1998, with data for July 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-10-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The Electric Power Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 57 tabs.
Electric power monthly, June 1999, with data for March 1999
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-06-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The Electric Power Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 57 tabs.
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)
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)
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.
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)
Examining demand response, renewable energy and efficiencies to meet growing electricity needs
International Nuclear Information System (INIS)
Elliot, N.; Eldridge, M.; Shipley, A.M.; Laitner, J.S.; Nadel, S.; Silverstein, A.; Hedman, B.; Sloan, M.
2007-01-01
While Texas has already taken steps to improve its renewable energy portfolio (RPS), and its energy efficiency improvement program (EEIP), the level of savings that utilities can achieve through the EEIP can be greatly increased. This report estimated the size of energy efficiency and renewable energy resources in Texas, and suggested a range of policy options that might be adopted to further extend EEIP. Current forecasts suggest that peak demand in Texas will increase by 2.3 per cent annually from 2007-2012, a level of growth which is threatening the state's ability to maintain grid reliability at reasonable cost. Almost 70 per cent of installed generating capacity is fuelled by natural gas in Texas. Recent polling has suggested that over 70 per cent of Texans are willing support increased spending on energy efficiency. Demand response measures that may be implemented in the state include incentive-based programs that pay users to reduce their electricity consumption during specific times and pricing programs, where customers are given a price signal and are expected to moderate their electricity usage. By 2023, the widespread availability of time-varying retail electric rates and complementary communications and control methods will permanently change the nature of electricity demand in the state. At present, the integrated utilities in Texas offer a variety of direct load control and time-of-use, curtailable, and interruptible rates. However, with the advent of retail competition now available as a result of the structural unbundling of investor-owned utilities, there is less demand response available in Texas. It was concluded that energy efficiency, demand response, and renewable energy resources can meet the increasing demand for electricity in Texas over the next 15 years. 4 figs
Monthly Electrical Energy Overview November 2013
International Nuclear Information System (INIS)
2013-11-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for November 2013
Monthly Electrical Energy Overview November 2015
International Nuclear Information System (INIS)
2015-11-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for November 2015
Monthly Electrical Energy Overview November 2014
International Nuclear Information System (INIS)
2014-11-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for November 2014
Monthly Electrical Energy Overview December 2012
International Nuclear Information System (INIS)
2012-12-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for December 2012
Monthly Electrical Energy Overview May 2013
International Nuclear Information System (INIS)
2013-05-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for May 2013
Monthly Electrical Energy Overview April 2015
International Nuclear Information System (INIS)
2015-04-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for April 2015
Monthly Electrical Energy Overview December 2013
International Nuclear Information System (INIS)
2013-12-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for December 2013
Monthly Electrical Energy Overview April 2013
International Nuclear Information System (INIS)
2013-04-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for April 2013
Monthly Electrical Energy Overview October 2013
International Nuclear Information System (INIS)
2013-10-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for October 2013
Monthly Electrical Energy Overview May 2015
International Nuclear Information System (INIS)
2015-05-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for May 2015
Monthly Electrical Energy Overview March 2013
International Nuclear Information System (INIS)
2013-03-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for March 2013
Monthly Electrical Energy Overview September 2012
International Nuclear Information System (INIS)
2012-09-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for September 2012
Monthly Electrical Energy Overview June 2013
International Nuclear Information System (INIS)
2013-06-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for June 2013
Monthly Electrical Energy Overview June 2016
International Nuclear Information System (INIS)
2016-06-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for June 2016
Monthly Electrical Energy Overview November 2012
International Nuclear Information System (INIS)
2012-11-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for November 2012
Monthly Electrical Energy Overview February 2013
International Nuclear Information System (INIS)
2013-02-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for February 2013
Monthly Electrical Energy Overview January 2013
International Nuclear Information System (INIS)
2013-01-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for January 2013
Monthly Electrical Energy Overview October 2014
International Nuclear Information System (INIS)
2014-10-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for October 2014
Monthly Electrical Energy Overview December 2014
International Nuclear Information System (INIS)
2014-12-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for December 2014
Monthly Electrical Energy Overview December 2015
International Nuclear Information System (INIS)
2015-12-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for December 2015
Monthly Electrical Energy Overview June 2015
International Nuclear Information System (INIS)
2015-06-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for June 2015
Monthly Electrical Energy Overview May 2014
International Nuclear Information System (INIS)
2014-05-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for May 2014
Monthly Electrical Energy Overview April 2014
International Nuclear Information System (INIS)
2014-04-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for April 2014
Monthly Electrical Energy Overview April 2016
International Nuclear Information System (INIS)
2016-04-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for April 2016
Monthly Electrical Energy Overview February 2016
International Nuclear Information System (INIS)
2016-02-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for February 2016
Monthly Electrical Energy Overview October 2015
International Nuclear Information System (INIS)
2015-10-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for October 2015
Monthly Electrical Energy Overview September 2015
International Nuclear Information System (INIS)
2015-09-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for September 2015
Monthly Electrical Energy Overview May 2016
International Nuclear Information System (INIS)
2016-05-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for May 2016
Monthly Electrical Energy Overview March 2015
International Nuclear Information System (INIS)
2015-03-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for March 2015
Monthly Electrical Energy Overview March 2016
International Nuclear Information System (INIS)
2016-03-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for March 2016
Monthly Electrical Energy Overview March 2014
International Nuclear Information System (INIS)
2014-03-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for March 2014
Monthly Electrical Energy Overview February 2015
International Nuclear Information System (INIS)
2015-02-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for February 2015
Monthly Electrical Energy Overview February 2014
International Nuclear Information System (INIS)
2014-02-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for February 2014
Monthly Electrical Energy Overview January 2014
International Nuclear Information System (INIS)
2014-01-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for January 2014
Monthly Electrical Energy Overview January 2016
International Nuclear Information System (INIS)
2016-01-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for January 2016
Monthly Electrical Energy Overview June 2014
International Nuclear Information System (INIS)
2014-06-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for June 2014
Monthly Electrical Energy Overview August 2014
International Nuclear Information System (INIS)
2014-08-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for July-August 2014
Monthly Electrical Energy Overview September 2013
International Nuclear Information System (INIS)
2013-09-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for September 2013
Monthly Electrical Energy Overview September 2014
International Nuclear Information System (INIS)
2014-09-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for September 2014
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
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
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...
The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers
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.
Electric power monthly: February 1995, with data for November 1994
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-02-22
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. 64 tabs.
Electric power monthly, May 1997 with data for February 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-05-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. 63 tabs.
Electric power monthly, April 1998, with data for January 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-04-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. 63 tabs.
Electric power monthly: March 1996, with data for December 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-03-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decision makers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. 69 tabs.
Electric power monthly, January 1999 with data for October 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-01-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. 1 fig., 63 tabs.
Electric power monthly, July 1998 with data for April 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-07-01
The Electric Power Monthly (EPM) presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.
Electric power monthly, January 1991. [Contains glossary
Energy Technology Data Exchange (ETDEWEB)
1991-01-17
This publication provides monthly statistics at the national, Census division, and state levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, and average revenue per kilowatthour of electricity sold. Data on net generation are also displayed at the North American Electric Reliability Council (NERC) region level. Additionally, company and plant level information are published in the EPM on capability of new plants, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel. 4 figs., 48 tabs.
Spatial–Temporal Analysis of the Heat and Electricity Demand of the Swiss Building Stock
Directory of Open Access Journals (Sweden)
Stefan Schneider
2017-08-01
Full Text Available In 2015, space heating and domestic hot water production accounted for around 40% of the Swiss final energy consumption. Reaching the goals of the 2050 energy strategy will require significantly reducing this share despite the growing building stock. Renewables are numerous but subject to spatial–temporal constraints. Territorial planning of energy distribution systems enabling the integration of renewables requires having a spatial–temporal characterization of the energy demand. This paper presents two bottom-up statistical extrapolation models for the estimation of the geo-dependent heat and electricity demand of the Swiss building stock. The heat demand is estimated by means of a statistical bottom-up model applied at the building level. At the municipality level, the electricity load curve is estimated by combining socio-economic indicators with average consumption per activity and/or electric device. This approach also allows to break down the estimated electricity demand according to activity type (e.g., households, various industry, and service activities and appliance type (e.g., lighting, motor force, fridges. The total estimated aggregated demand is 94 TWh for heat and 58 TWh for electricity, which represent a deviation of 2.9 and 0.5%, respectively compared to the national energy consumption statistics. In addition, comparisons between estimated and measured electric load curves are done to validate the proposed approach. Finally, these models are used to build a geo-referred database of heat and electricity demand for the entire Swiss territory. As an application of the heat demand model, a realistic saving potential is estimated for the existing building stock; this potential could be achieved through by a deep retrofit program. One advantage of the statistical bottom-up model approach is that it allows to simulate a building stock that replicates the diversity of building demand. This point is important in order to
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)
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.
International Nuclear Information System (INIS)
Yu, L.; Li, Y.P.; Huang, G.H.
2016-01-01
In this study, a FSSOM (fuzzy-stochastic simulation-optimization model) is developed for planning EPS (electric power systems) with considering peak demand under uncertainty. FSSOM integrates techniques of SVR (support vector regression), Monte Carlo simulation, and FICMP (fractile interval chance-constrained mixed-integer programming). In FSSOM, uncertainties expressed as fuzzy boundary intervals and random variables can be effectively tackled. In addition, SVR coupled Monte Carlo technique is used for predicting the peak-electricity demand. The FSSOM is applied to planning EPS for the City of Qingdao, China. Solutions of electricity generation pattern to satisfy the city's peak demand under different probability levels and p-necessity levels have been generated. Results reveal that the city's electricity supply from renewable energies would be low (only occupying 8.3% of the total electricity generation). Compared with the energy model without considering peak demand, the FSSOM can better guarantee the city's power supply and thus reduce the system failure risk. The findings can help decision makers not only adjust the existing electricity generation/supply pattern but also coordinate the conflict interaction among system cost, energy supply security, pollutant mitigation, as well as constraint-violation risk. - Highlights: • FSSOM (Fuzzy-stochastic simulation-optimization model) is developed for planning EPS. • It can address uncertainties as fuzzy-boundary intervals and random variables. • FSSOM can satisfy peak-electricity demand and optimize power allocation. • Solutions under different probability levels and p-necessity levels are analyzed. • Results create tradeoff among system cost and peak-electricity demand violation risk.
Demand side management program evaluation based on industrial and commercial field data
International Nuclear Information System (INIS)
Eissa, M.M.
2011-01-01
Demand Response is increasingly viewed as an important tool for use by the electric utility industry in meeting the growing demand for electricity. There are two basic categories of demand response options: time varying retail tariffs and incentive Demand Response Programs. is applying the time varying retail tariffs program, which is not suitable according to the studied load curves captured from the industrial and commercial sectors. Different statistical studies on daily load curves for consumers connected to 22 kV lines are classified. The load curve criteria used for classification is based on peak ratio and night ratio. The data considered here is a set of 120 annual load curves corresponding to the electric power consumption (the western area in the King Saudi Arabia (KSA)) of many clients in winter and some months in the summer (peak period). The study is based on real data from several Saudi customer sectors in many geographical areas with larger commercial and industrial customers. The study proved that the suitable Demand Response for the ESC is the incentive program. - Highlights: → Study helps in selecting the proper demand side program. → A credit will be given for the customers during summer months. → Reduction in the electric bill. → Monthly bill credit is decreased based on customers' peak load reduction. → Guide for applying the proper demand side program suitable for the utility and customers.
Determinants of electricity demand for newly electrified low-income African households
International Nuclear Information System (INIS)
Louw, Kate; Conradie, Beatrice; Howells, Mark; Dekenah, Marcus
2008-01-01
Access to clean, affordable and appropriate energy is an important enabler of development. Energy allows households to meet their most basic subsistence needs; it is a central feature of all the millennium development goals (MDGs) and, while a lack of access to energy may not be a cause of poverty, addressing the energy needs of the impoverished lets them access services which in turn address the causes of poverty. While much is known about the factors affecting the decisions made when choosing between fuel types within a household, few quantitative studies have been carried out in South Africa to determine the extent to which these factors affect energy choice decisions. It is assumed that the factors traditionally included in economic demand such as price and income of the household affect choice; tastes and preferences as well as external factors such as distance to fuel suppliers are expected to influence preferences. This study follows two typical low-income rural sites in South Africa, Antioch and Garagapola, where the Electricity Basic Services Support Tariff (EBSST) was piloted in 2002. The EBSST is set at 50 kWh/month per household for low domestic consumers; this is worth approximately R20 (±US$3). This subsidy is a lifeline tariff, where households receive the set amount of units per month, free of charge irrespective of whether more units are purchased. These data (collected in 2001 and 2002), recently collated with detailed electricity consumption data, allow us to determine the drivers of electricity consumption within these households. The sample analysed is taken from the initial phase of the study, when no FBE had been introduced to the households. This enabled the study presented here to make use of the well-populated datasets to assess what affects the electricity use decision in these households. This paper attempts to assess which factors affected the decision-making process for electricity consumption within these households. A brief history
International Nuclear Information System (INIS)
Azadeh, A.; Saberi, M.; Ghaderi, S.F.; Gitiforouz, A.; Ebrahimipour, V.
2008-01-01
This study presents an integrated fuzzy system, data mining and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy system or time series and the integrated algorithm could be an ideal substitute for such cases. To construct fuzzy systems, a rule base is needed. Because a rule base is not available, for the case of demand function, look up table which is one of the extracting rule methods is used to extract the rule base. This system is defined as FLT. Also, decision tree method which is a data mining approach is similarly utilized to extract the rule base. This system is defined as FDM. Preferred time series model is selected from linear (ARMA) and nonlinear model. For this, after selecting preferred ARMA model, McLeod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, preferred nonlinear model is selected and compare with preferred ARMA model and finally one of this is selected as time series model. At last, ANOVA is used for selecting preferred model from fuzzy models and time series model. Also, the impact of data preprocessing and postprocessing on the fuzzy system performance is considered by the algorithm. In addition, another unique feature of the proposed algorithm is utilization of autocorrelation function (ACF) to define input variables, whereas conventional methods which use trial and error method. Monthly electricity consumption of Iran from 1995 to 2005 is considered as the case of this study. The MAPE estimation of genetic algorithm (GA), artificial neural network (ANN) versus the proposed algorithm shows the appropriateness of the proposed algorithm
Directory of Open Access Journals (Sweden)
Cristhian Moreno-Chaparro
2011-12-01
Full Text Available This paper proposes a monthly electricity forecast method for the National Interconnected System (SIN of Colombia. The method preprocesses the time series using a Multiresolution Analysis (MRA with Discrete Wavelet Transform (DWT; a study for the selection of the mother wavelet and her order, as well as the level decomposition was carried out. Given that original series follows a non-linear behaviour, a neural nonlinear autoregressive (NAR model was used. The prediction was obtained by adding the forecast trend with the estimated obtained by the residual series combined with further components extracted from preprocessing. A bibliographic review of studies conducted internationally and in Colombia is included, in addition to references to investigations made with wavelet transform applied to electric energy prediction and studies reporting the use of NAR in prediction.
Structural and behavioural foundations of competitive electricity prices
International Nuclear Information System (INIS)
Bunn, D.W.
2004-01-01
This chapter presents a basic introduction to price formation in the new electricity markets and examines power system economics and electricity market liberalisation. Topics discussed include wholesale electricity prices, the case of gas, the effect of the instantaneous nature of the electricity product, spot markets for electricity, and the ability of industrial companies to influence prices. Market fundamentals are reviewed, and institutional reform and strategic evolution are explored. British daily average power and gas prices, monthly forward prices on the British power and gas markets, seasonal demand profile, electricity demand UK 98/00, annual cost of each plant, price formation in 1997, and monthly demand and wholesale prices in England and Wales 1990-1998 are among the graphs provided
International Nuclear Information System (INIS)
Tarancon, Miguel Angel; Callejas Albinana, Fernando; Del Rio, Pablo
2010-01-01
The production and consumption of electricity is a major source of CO 2 emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input-output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price. (author)
Energy Technology Data Exchange (ETDEWEB)
Tarancon, Miguel Angel; Callejas Albinana, Fernando [Faculty of Law and Social Sciences, Universidad de Castilla - La Mancha, Ronda de Toledo s/n, 13071 Ciudad Real (Spain); Del Rio, Pablo [Institute for Public Policies and Goods (IPP), Centro de Ciencias Humanas y Sociales, CSIC, C/Albasanz 26-28, 28037 Madrid (Spain)
2010-04-15
The production and consumption of electricity is a major source of CO{sub 2} emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input-output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price. (author)
Electric power monthly. June 1966 with data for March 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-06-01
This publication presents monthly electricity statistics for a wide audience including Congress, Federal and state agencies, the electric utility industry, and the general public, with the purpose of providing energy decisionmakers with accurate, timely information that may be used in forming various perspectives on electric issues that lie ahead. EIA collected the information in this report to fulfill its data collection and dissemination responsibilities (Public Law 93-275). A section on upgrading transmission capacity for wholesale electric power trade is included. The tables include US electric power at a glance, utility net generation, utility consumption of fossil fuels, fossil-fuel stocks/receipts/cost at utilities, utility sales/revenue/revenue per kWh, and monthly plant aggregates.
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
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....
Electric power monthly, October 1991. [CONTAINS GLOSSARY
Energy Technology Data Exchange (ETDEWEB)
1991-10-11
This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fuel are also displayed at the North American Electric Reliability Council (NERC) region level. Additionally, statistics at the company and plant level are published in the EPM on capability of new plants, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel. 4 figs., 63 tabs.
Electric Power Monthly, September 1991. [CONTAINS GLOSSARY
Energy Technology Data Exchange (ETDEWEB)
1991-09-12
This publication provides monthly statistics at the national, Census division, and state levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fuel are also displayed at the North American Electric Reliability Council (NERC) region level. Additionally, statistics at the company and plant level are published in the EPM on capability of new plants, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel. 4 figs., 63 tabs.
Modeling sustainable long-term electricity supply-demand in Africa
International Nuclear Information System (INIS)
Ouedraogo, Nadia S.
2017-01-01
Highlights: • This study is one of the first detailed and complete representation of the African power system. • It models, within LEAP, possible future paths for the regional power systems. • All the end-users and supply side activities and actors are considered. • Three scenarios are examined: the baseline, the renewable energy, and the energy efficiency. • The energy efficiency scenario has allowed to draw a sustainable pathway for electrification. - Abstract: This paper develops a scenario-based model to identify and provide an array of electricity demand in Africa, and to derive them from the African power system of development. A system-based approach is performed by applying the scenario methodology developed by Schwartz in the context of the energy-economic modeling platform ‘Long-range Energy Alternative Planning’. Four scenarios are investigated. The Business as Usual scenario (BAU) replicates the regional and national Master Plans. The renewable-promotion scenario increases the share of renewable energy in the electricity mix. The demand and supply side efficiency scenarios investigate the impact of energy efficiency measures on the power system. The results show an increase in electricity demand by 4% by 2040, supply shortages and high emissions of Greenhouse Gases. Contrary to expectations, the renewable energy scenario did not emerge as the best solution to a sustainable electrification of the region. The energy efficiency scenarios have allowed us to draw a sustainable pathway for electrification.
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
Electric power monthly, July 1999, with data for April 1999
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-07-01
The Electric Power Division, Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the Electric Power Monthly (EPM). This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatt hour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 1 fig., 64 tabs.
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.
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...
A demand/supply and price outlook for electricity in Ontario
International Nuclear Information System (INIS)
Dalton, J.
2004-01-01
This paper examined electricity pricing issues for both the immediate future as well as over the long term. The near term outlook resources for the summer of 2004 were reviewed. Intermediate critical supply and demand issues were projected with consideration given to the return of the Pickering A plant and coal phase out. In the long term, it was considered that pricing and demand would reflect conservation issues and demand side response, as well as the timing of Requests For Proposals (RFPs) and the phase out of coal-fired capacity. The impact of the coal phase-out in Ontario was examined, with particular reference to timing and market structure implications. Potential conservation impacts were presented and projected Ontario supply/demand balances were evaluated. The challenges facing the new market structure include pricing dynamics and a reliance on RFPs. The significance of specifying diversity objectives was also discussed. It was concluded that the Ontario Ministry of Energy should play a role in establishing targets for conservation, renewable energy and the overall supply of electricity. Rigorous analysis is necessary before specifying targets in terms of hydroelectric and nuclear generation as opposed to non-fossil generation. tabs., figs
Electricity demand load forecasting of the Hellenic power system using an ARMA model
Energy Technology Data Exchange (ETDEWEB)
Pappas, S.Sp. [ASPETE - School of Pedagogical and Technological Education Department of Electrical Engineering Educators N. Heraklion, 141 21 Athens (Greece); Ekonomou, L.; Chatzarakis, G.E.; Skafidas, P.D. [ASPETE-School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece); Karampelas, P. [Hellenic American University, IT Department, 12 Kaplanon Str., 106 80 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24 100 Kalamata (Greece); Katsikas, S.K. [University of Piraeus, Department of Technology Education and Digital Systems, 150 Androutsou St., 18 532 Piraeus (Greece)
2010-03-15
Effective modeling and forecasting requires the efficient use of the information contained in the available data so that essential data properties can be extracted and projected into the future. As far as electricity demand load forecasting is concerned time series analysis has the advantage of being statistically adaptive to data characteristics compared to econometric methods which quite often are subject to errors and uncertainties in model specification and knowledge of causal variables. This paper presents a new method for electricity demand load forecasting using the multi-model partitioning theory and compares its performance with three other well established time series analysis techniques namely Corrected Akaike Information Criterion (AICC), Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The suitability of the proposed method is illustrated through an application to actual electricity demand load of the Hellenic power system, proving the reliability and the effectiveness of the method and making clear its usefulness in the studies that concern electricity consumption and electricity prices forecasts. (author)
International Nuclear Information System (INIS)
Toksari, M. Duran
2009-01-01
This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear A COEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic A COEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios. (author)
Monthly bulletin of electric power market - November 1988
International Nuclear Information System (INIS)
1988-01-01
This bulletin deals with the brazilian electric power consumption in November 1988, containing data about the total consumption, the growth rates, the special tariffs and monthly evolution in each brazilian region. The economic indexes of industrial production, the market and the prices of electric power and petroleum products are also presented. (C.G.C.)
Monthly bulletin of electric power market - July 1988
International Nuclear Information System (INIS)
1988-01-01
This bulletin deals with the brazilian electric power consumption in July 1988, containing data about the total consumption, the growth rates, the special tariffs and monthly evolution in each brazilian region. The economic indexes of industrial production, the market and the prices of electric power and petroleum products are also presented. (C.G.C.)
Monthly bulletin of electric power market - September 1988
International Nuclear Information System (INIS)
1988-01-01
This bulletin deals with the brazilian electric power consumption in September 1988, containing data about the total consumption, the growth rates, the special tariffs and monthly evolution in each brazilian region. The economic indexes of industrial production, the market and the prices of electric power and petroleum products are also presented. (C.G.C.)
Electric power monthly, February 1998 with data for November 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-02-01
The Electric Power Monthly (EPM) provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 63 tabs.
An assessment of the influence of demand response on demand elasticity in electricity retail market
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
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...
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
Impacts of demand response and renewable generation in electricity power market
Zhao, Zhechong
This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating
Energy management for vehicle power net with flexible electric load demand
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
The value of online information for demand response in Walrasian electricity markets
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
International Nuclear Information System (INIS)
Al-Mulla, A.; Maheshwari, G.P.; Al-Nakib, D.; ElSherbini, A.; Alghimlas, F.; Al-Taqi, H.; Al-Hadban, Y.
2013-01-01
Highlights: • Enhanced building operations were applied for eight large government buildings in Kuwait. • The enhanced building operations led to demand savings of 8.90 MW during the national peak hour. • Nationwide guidelines were developed for implementing the enhanced operations in similar government buildings in Kuwait. • The peak electrical demand reduction is likely to be 488 MW by the year 2030. - Abstract: An approach for managing electrical demand through enhanced building operations in hot climates is evaluated and demonstrated in this paper. The approach focuses on implementing enhanced operations in government buildings, since they are easier to implement and administer. These enhanced operations included early reduction of cooling supply before the end of the occupancy period, improved time-of-day control after occupancy period and reduced lighting. A total of eight government buildings with different construction and system characteristics were selected for implementing these enhanced operations. These buildings have a total air-conditioning area of 4.39 × 10 5 m 2 and a combined peak electrical demand of 29.3 MW. The enhanced operations resulted in demand savings of 8.90 MW during the national peak hour. Temperatures build up inside the buildings were monitored and found to be within acceptable ranges. Guidelines for nationwide implementation in similar buildings were developed based on the results of this work. Implementation is estimated to reduce demand by 488 MW by the year 2030, which amounts to capital savings of $585 million. These projected values would be important to adopt energy efficient policies for the country. Additional reductions in energy and fuel consumption are added benefits, which would result in large financial and environmental savings to the country. Moreover, the enhanced building operations would be an important tool to avoid any blackouts by properly reducing the peak electrical demand as well as operating the
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.
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.
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.
International Nuclear Information System (INIS)
Wang Yuanyuan; Wang Jianzhou; Zhao Ge; Dong Yao
2012-01-01
Electricity demand forecasting could prove to be a useful policy tool for decision-makers; thus, accurate forecasting of electricity demand is valuable in allowing both power generators and consumers to make their plans. Although a seasonal ARIMA model is widely used in electricity demand analysis and is a high-precision approach for seasonal data forecasting, errors are unavoidable in the forecasting process. Consequently, a significant research goal is to further improve forecasting precision. To help people in the electricity sectors make more sensible decisions, this study proposes residual modification models to improve the precision of seasonal ARIMA for electricity demand forecasting. In this study, PSO optimal Fourier method, seasonal ARIMA model and combined models of PSO optimal Fourier method with seasonal ARIMA are applied in the Northwest electricity grid of China to correct the forecasting results of seasonal ARIMA. The modification models forecasting of the electricity demand appears to be more workable than that of the single seasonal ARIMA. The results indicate that the prediction accuracy of the three residual modification models is higher than the single seasonal ARIMA model and that the combined model is the most satisfactory of the three models. - Highlights: ► Three residual modification models are proposed to improve the precision of seasonal ARIMA. ► Accurate electricity demand forecast is helpful for a power production sector to come to a correct and reasonable decision. ► The results conclude that the residual modification approaches could enhance the prediction accuracy of seasonal ARIMA. ► The modification models could be applied to forecast electricity demand.
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.
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.
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.
Energy systems scenario modelling and long term forecasting of hourly electricity demand
Directory of Open Access Journals (Sweden)
Poul Alberg Østergaard
2015-06-01
Full Text Available The Danish energy system is undergoing a transition from a system based on storable fossil fuels to a system based on fluctuating renewable energy sources. At the same time, more of and more of the energy system is becoming electrified; transportation, heating and fuel usage in industry and elsewhere. This article investigates the development of the Danish energy system in a medium year 2030 situation as well as in a long-term year 2050 situation. The analyses are based on scenario development by the Danish Climate Commission. In the short term, it is investigated what the effects will be of having flexible or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model. The results show that even with a limited short-term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrated wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long-term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps and electric vehicles in the long-term future overshadows any effects of changes in hourly demand curve profiles.
Medium- and long-term electric power demand forecasting based on the big data of smart city
Wei, Zhanmeng; Li, Xiyuan; Li, Xizhong; Hu, Qinghe; Zhang, Haiyang; Cui, Pengjie
2017-08-01
Based on the smart city, this paper proposed a new electric power demand forecasting model, which integrates external data such as meteorological information, geographic information, population information, enterprise information and economic information into the big database, and uses an improved algorithm to analyse the electric power demand and provide decision support for decision makers. The data mining technology is used to synthesize kinds of information, and the information of electric power customers is analysed optimally. The scientific forecasting is made based on the trend of electricity demand, and a smart city in north-eastern China is taken as a sample.
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
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
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
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.
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
Monthly Electrical Energy Overview July August 2015
International Nuclear Information System (INIS)
2015-08-01
This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for July-August 2015
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)
Electric power monthly, December 1996 with data for September 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-12-01
The report presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatt hour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 57 tabs.
Electric power monthly with data for October 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-01-01
The Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and U.S. levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
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
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
International Nuclear Information System (INIS)
Thatcher, Marcus J.
2007-01-01
In this paper, we describe a method for constructing regional electricity demand data sets at 30 min intervals, which are consistent with climate change scenarios. Specifically, we modify a commonly used linear regression model between regional electricity demand and climate to also describe intraday variability in demand so that regional load duration curves (LDCs) can be predicted. The model is evaluated for four different Australian states that are participants in the Australian National Electricity Market (NEM) and the resultant data sets are found to reproduce each state's LDCs with reasonable accuracy. We also apply the demand model to CSIRO's Mk 3 global climate model data sets that have been downscaled to 60 km resolution using CSIRO's conformal-cubic atmospheric model to estimate how LDCs change as a consequence of a 1 C increase in the average temperature of Australian state capital cities. These regional electricity demand data sets are then useful for economic modelling of electricity markets such as the NEM. (author)
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
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.
Generation Adequacy Report on the electricity supply-demand balance in France - 2007 Edition
International Nuclear Information System (INIS)
2008-01-01
Under the terms of the Law of 10 February 2000, at least every two years, RTE (Reseau de Transport d'Electricite), working under the aegis of the Government, establishes a multi-annual Generation Adequacy Report on the electricity supply-demand balance in France. A new regulatory framework specifies the methods to be used by RTE for drawing up this independent technical expert report. The Generation Adequacy Report is one of the elements used by the Minister for Energy and the Government in general, to determine the Multi-annual Investment Programme (referred to by the French acronym PPI) for investing in energy generation facilities, introduced by the above-mentioned law. RTE publishes the report, which also appears on-line on the operator's web site www.rtefrance.com. This principle of transparency means that the information can be circulated to all the players involved in the power system and helps drive the energy debate. RTE published a previous report in 2005, which was partially updated in 2006. The Generation Adequacy Report is part of measures aimed at ensuring the security of the French electricity supply. It is intended to identify the risks of imbalances between electricity demand and the generation supply available to satisfy it over a period of around fifteen years. Consequently, it identifies the generation capacity required to meet peak demand. The choice of generation technologies to be developed, which is dictated by environmental and economic concerns, is not covered by the Generation Adequacy Report, but is a matter for the other players involved in the French electric system, and more generally, the orientations determined by the PPI. In order to carry out the analysis of the overall supply- demand balance in mainland France, RTE establishes domestic electricity demand forecasts, which it then compares with expected developments in the generating fleet
Optimal wind-hydro solution for the Marmara region of Turkey to meet electricity demand
International Nuclear Information System (INIS)
Dursun, Bahtiyar; Alboyaci, Bora; Gokcol, Cihan
2011-01-01
Wind power technology is now a reliable electricity production system. It presents an economically attractive solution for the continuously increasing energy demand of the Marmara region located in Turkey. However, the stochastic behavior of wind speed in the Marmara region can lead to significant disharmony between wind energy production and electricity demand. Therefore, to overcome wind's variable nature, a more reliable solution would be to integrate hydropower with wind energy. In this study, a methodology to estimate an optimal wind-hydro solution is developed and it is subsequently applied to six typical different site cases in the Marmara region in order to define the most beneficial configuration of the wind-hydro system. All numerical calculations are based on the long-term wind speed measurements, electrical load demand and operational characteristics of the system components. -- Research highlights: → This study is the first application of a wind-hydro pumped storage system in Turkey. → The methodology developed in this study is applied to the six sites in the Marmara region of Turkey. A wind - hydro pumped storage system is proposed to meet the electric energy demand of the Marmara region.
Directory of Open Access Journals (Sweden)
Qunli Wu
2017-01-01
Full Text Available Path-coefficient analysis is utilized to investigate the direct and indirect effects of economic growth, population growth, urbanization rate, industrialization level, and carbon intensity on electricity demand of China. To improve the projection accuracy of electricity demand, this study proposes a hybrid bat algorithm, Gaussian perturbations, and simulated annealing (BAG-SA optimization method. The proposed BAG-SA algorithm not only inherits the simplicity and efficiency of the standard BA with a capability of searching for global optimality but also enhances local search ability and speeds up the global convergence rate. The BAG-SA algorithm is employed to optimize the coefficients of the multiple linear and quadratic forms of electricity demand estimation model. Results indicate that the proposed algorithm has higher precision and reliability than the coefficients optimized by other single-optimization methods, such as genetic algorithm, particle swarm optimization algorithm, or bat algorithm. And the quadratic form of BAG-SA electricity demand estimation model has better fitting ability compared with the multiple linear form of the model. Therefore, the quadratic form of the model is applied to estimate electricity demand of China from 2016 to 2030. The findings of this study demonstrate that China’s electricity demand will reach 14925200 million KWh in 2030.
Modeling and Analysis of Commercial Building Electrical Loads for Demand Side Management
Berardino, Jonathan
In recent years there has been a push in the electric power industry for more customer involvement in the electricity markets. Traditionally the end user has played a passive role in the planning and operation of the power grid. However, many energy markets have begun opening up opportunities to consumers who wish to commit a certain amount of their electrical load under various demand side management programs. The potential benefits of more demand participation include reduced operating costs and new revenue opportunities for the consumer, as well as more reliable and secure operations for the utilities. The management of these load resources creates challenges and opportunities to the end user that were not present in previous market structures. This work examines the behavior of commercial-type building electrical loads and their capacity for supporting demand side management actions. This work is motivated by the need for accurate and dynamic tools to aid in the advancement of demand side operations. A dynamic load model is proposed for capturing the response of controllable building loads. Building-specific load forecasting techniques are developed, with particular focus paid to the integration of building management system (BMS) information. These approaches are tested using Drexel University building data. The application of building-specific load forecasts and dynamic load modeling to the optimal scheduling of multi-building systems in the energy market is proposed. Sources of potential load uncertainty are introduced in the proposed energy management problem formulation in order to investigate the impact on the resulting load schedule.
Electric power monthly with data for December 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-03-01
The Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and U.S. levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
Electric power monthly with data for January 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-04-01
The Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and U.S. levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
Dynamic Modeling of Kosovo's Electricity Supply-Demand, Gaseous Emissions and Air Pollution
Directory of Open Access Journals (Sweden)
Sadik Bekteshi
2015-09-01
Full Text Available In this paper is described the developing of an integrated electricity supply–demand, gaseous emission and air pollution model for study of possible baseline electricity developments and available options to mitigate emissions. This model is constructed in STELLA software, which makes use of Systems Dynamics Modeling as the methodology. Several baseline scenarios have been developed from this model and a set of options of possible developments of Kosovo's Electricity Supply–Demand and Gaseous Emissions are investigated. The analysis of various scenarios results in medium growth scenarios (MGS that imply building of generation capacities and increase in participation of the electricity generation from renewable sources. MGS would be 10% of the total electricity generation and ensure sustainable development of the electricity sector. At the same time, by implementation of new technologies, this would be accompanied by reduced GHG (CO2 and NOx emissions by 60% and significant reduction for air pollutants (dust and SO2 by 40% compared to the business-as-usual (BAU case. Conclusively, obtained results show that building of new generation capacities by introducing new technologies and orientation on environmentally friendly energy sources can ensure sustainable development of the electricity sector in Kosovo.
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....
Efficient Use of Behavioral Tools to Reduce Electricity Demand of Domestic Consumers
Directory of Open Access Journals (Sweden)
Elbaz Shimon
2016-12-01
Full Text Available Purpose: The present study investigated the main literature on the subject of methods and policies for reducing the electricity demand of domestic consumers, in order to identify the place of behavioral tools. Methodology: We used secondary sources, performing a literature review, together with analysis and synthesis. Findings: Policy makers prefer to use tools offered by neoclassical economics, such as various forms of taxation, fines and financial incentives in order to make domestic electricity consumers save electricity, on the assumption that consumers will make rational decisions while maximizing their personal benefit. However, studies conducted in recent years in the field of behavioral economics, which are based on the assumption that consumers’ decisions are not rational and are affected by cognitive biases, showed that the use of behavioral tools, such as detailed online information (feedback,social comparison information, information on varying rates (dynamic pricing and general information (advertising campaign, are tools that are not less appropriate than the ones the neoclassical economics offers, mainly because electricity is an invisible product and consumers are unable to assess it by normal cognitive measures. Using an interdisciplinary combination of behavioral tools that come from a variety of approaches taken from a wide variety of different academic fields, it is possible to receive efficient results in the endeavor of reducing electricity demand. Implications: Although the neoclassical economics still remains the fundamental theory used by policymakers, it is recommended to consider behavioral economics as a complementary approach to the neoclassical economics, and combine behavioral tools in the policymakers’ toolbox, especially when those tools do not require a significant financial investment, thus efficiently maximizing the reduction of electricity demand among domestic consumers. These theoretical results will be
This paper compares the climate change impacts on U.S. electricity demand and supply from three models: the Integrated Planning Model (IPM), the Regional Energy Deployment System (ReEDS) model, and GCAM. Rising temperatures cause an appreciable net increase in electricity demand....
International Nuclear Information System (INIS)
Åberg, M.; Widén, J.; Henning, D.
2012-01-01
In the future, district heating companies in Sweden must adapt to energy efficiency measures in buildings and variable fuel and electricity prices. Swedish district heating demands are expected to decrease by 1–2% per year and electricity price variations seem to be more unpredictable in the future. A cost-optimisation model of a Swedish local district heating system is constructed using the optimisation modelling tool MODEST. A scenario for heat demand changes due to increased energy efficiency in buildings, combined with the addition of new buildings, is studied along with a sensitivity analysis for electricity price variations. Despite fears that heat demand reductions will decrease co-generation of clean electricity and cause increased global emissions, the results show that anticipated heat demand changes do not increase the studied system's primary energy use or global CO 2 emissions. The results further indicate that the heat production plants and the fuels used within the system have crucial importance for the environmental impact of district heat use. Results also show that low seasonal variations in electricity price levels with relatively low winter prices promote the use of electric heat pumps. High winter prices on the other hand promote co-generation of heat and electricity in CHP plants. -- Highlights: ► A MODEST optimisation model of the Uppsala district heating system is built. ► The impact of heat demand change on heat and electricity production is examined. ► An electricity price level sensitivity analysis for district heating is performed. ► Heat demand changes do not increase the primary energy use or global CO 2 emissions. ► Low winter prices promote use of electric heat pumps for district heating production.
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.
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.
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.
Directory of Open Access Journals (Sweden)
S. Saravanan
2012-07-01
Full Text Available Power System planning starts with Electric load (demand forecasting. Accurate electricity load forecasting is one of the most important challenges in managing supply and demand of the electricity, since the electricity demand is volatile in nature; it cannot be stored and has to be consumed instantly. The aim of this study deals with electricity consumption in India, to forecast future projection of demand for a period of 19 years from 2012 to 2030. The eleven input variables used are Amount of CO2 emission, Population, Per capita GDP, Per capita gross national income, Gross Domestic savings, Industry, Consumer price index, Wholesale price index, Imports, Exports and Per capita power consumption. A new methodology based on Artificial Neural Networks (ANNs using principal components is also used. Data of 29 years used for training and data of 10 years used for testing the ANNs. Comparison made with multiple linear regression (based on original data and the principal components and ANNs with original data as input variables. The results show that the use of ANNs with principal components (PC is more effective.
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
Dealing with Demand in Electric Grids with an Adaptive Consumption Management Platform
Directory of Open Access Journals (Sweden)
Diego M. Jiménez-Bravo
2018-01-01
Full Text Available The control of consumption in homes and workplaces is an increasingly important aspect if we consider the growing popularity of smart cities, the increasing use of renewable energies, and the policies of the European Union on using energy in an efficient and clean way. These factors make it necessary to have a system that is capable of predicting what devices are connected to an electrical network. For demand management, the system must also be able to control the power supply to these devices. To this end, we propose the use of a multiagent system that includes agents with advanced reasoning and learning capacities. More specifically, the agents incorporate a case-based reasoning system and machine learning techniques. Besides, the multiagent system includes agents that are specialized in the management of the data acquired and the electrical devices. The aim is to adjust the consumption of electricity in networks to the electrical demand, and this will be done by acting automatically on the detected devices. The proposed system provides promising results; it is capable of predicting what devices are connected to the power grid at a high success rate. The accuracy of the system makes it possible to act according to the device preferences established in the system. This allows for adjusting the consumption to the current demand situation, without the risk of important home appliances being switched off.
Reducing Energy Demand Using Wheel-Individual Electric Drives to Substitute EPS-Systems
Directory of Open Access Journals (Sweden)
Jürgen Römer
2018-01-01
Full Text Available The energy demand of vehicles is influenced, not only by the drive systems, but also by a number of add-on systems. Electric vehicles must satisfy this energy demand completely from the battery. Hence, the use of power steering systems directly result in a range reduction. The “e2-Lenk” joint project funded by the German Federal Ministry of Education and Research (BMBF involves a novel steering concept for electric vehicles to integrate the function of steering assistance into the drive-train. Specific distribution of driving torque at the steered axle allows the steering wheel torque to be influenced to support the steering force. This provides a potential for complete substitution of conventional power steering systems and reduces the vehicle’s energy demand. This paper shows the potential of wheel-individual drives influencing the driver’s steering torque using a control technique based on classical EPS control plans. Compared to conventional power-assisted steering systems, a reduced energy demand becomes evident over a wide range of operating conditions.
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
Electric power monthly with data for June 1997
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-09-01
This publication provides monthly statistics at the state, census division, and U.S. levels for net generation; fossil fuel consumption and stocks, quantity, and quality of fossil fuels; cost of fossil fuels; electricity retail sales; associated revenue; and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity, and cost of fossil fuels are also displayed for the North American Electric Reliability Council regions. Statistics on net generation by energy source and capability of new generating units by company and plant are also included. A section is included in the report which summarizes major industry developments. 1 fig., 64 tabs.
International Nuclear Information System (INIS)
Wood, Michael; Alsayegh, Osamah A.
2014-01-01
This paper describes the influences of oil revenue and government's policies toward economic developments and energy efficiency on the electricity and water demands. A Kuwait-specific electricity and water demand model was developed based on historic data of oil income, gross domestic product (GDP), population and electric load and water demand over the past twelve years (1998–2010). Moreover, the model took into account the future mega projects, annual new connected loads and expected application of energy conservation programs. It was run under six circumstances representing the combinations of three oil income scenarios and two government action policies toward economic diversification and energy conservation. The first government policy is the status quo with respect to economic diversification and applying energy conservation programs. The second policy scenario is the proactive strategy of raising the production of the non-oil sector revenue and enforcing legislations toward energy demand side management and conservation. In the upcoming 20 years, the average rates of change of the electric load and water demand increase are 0.13 GW and 3.0 MIGD, respectively, per US dollar oil price increase. Moreover, through proactive policy, the rates of average load and water demand decrease are 0.13 GW and 2.9 MIGD per year, respectively. - Highlights: • Kuwait-specific electricity and water demand model is presented. • Strong association between oil income and electricity and water demands. • Rate of change of electric load per US dollar oil price change is 0.13 GW. • Rate of change of water demand per US dollar oil price change is 3.0 MIGD. • By 2030, efficiency lowers electric load and water demand by 10 and 6%, respectively
Electrical demand forecast in two different scenarios of socio-economic development
International Nuclear Information System (INIS)
Goni, M.R.
1996-01-01
A projection of electrical demand for two different scenarios is presented in the study. The study period is 1993-2010 and 1993 has been taken as base year. In this planning study MAED program was used as well as all available information from INDEC (National Statistical Body), CAMMESA (Electrical Market Company) and Ministery of Economy. The results in the base year achieved an accuracy higher than 98%. The scenarios described two different rates of growth and electrical penetration in energy uses. (author). 3 refs., 9 figs., 2 tabs
Secular trends in monthly heating and cooling demands in Croatia
Cvitan, Lidija; Sokol Jurković, Renata
2016-08-01
This paper analyzes long-term heating and cooling trends for five locations in Croatia from 1901 to 2008 to assist in the revision of Croatia's heating and cooling energy policy. Trends in monthly heating degree-days (HDD) and cooling degree-days (CDD) were determined for three related temperature threshold values each and analyzed to provide insight into the influence of desired thermal comfort on the extent of changes in energy consumption. Monthly trends in the corresponding number of heating days (HD) and cooling days (CD) were also analyzed. A basic investigation of HDD, HD, CDD, and CD trends proved to be essential to the development of a complete description of important climate-related conditions that impact energy demands associated with heating and cooling. In a few cases, the dependence of the trends on the implemented temperature thresholds was rather pronounced and was reflected in great spatial and temporal variations in monthly trends. The statistical significance of the detected monthly trends illustrated a diverse range of possible impacts of climate changes on heating and cooling energy consumption both across and within three main climate regions in Croatia (continental, mountainous, and maritime). It is confirmed that the applied monthly scale for analyses is suitable for assessing heating and cooling practices.
Directory of Open Access Journals (Sweden)
Gang Du
2015-06-01
Full Text Available Electricity intensity is an important indicator for measuring production efficiency. A comparative study could offer a new perspective on investigating determinants of electricity demand. The Japanese non-metallic mineral products industry is chosen as the object for comparison considering its representative position in production efficiency. By adopting the cointegration model, this paper examines influencing factors of electricity demand in Japanese and Chinese non-metallic mineral products industries under the same framework. Results indicate that although economic growth and industrial development stages are different between the two countries, major factors that affect the sectoral energy consumption are the same. Specifically, economic growth and industrial activity contribute to the growth of sectoral electricity consumption, while R&D intensity, per capita productivity and electricity price are contributors to the decline of sectoral electricity consumption. Finally, in order to further investigate the development trend of sectoral electricity demand, future electricity consumption and conservation potential are predicted under different scenarios. Electricity demand of the Chinese non-metallic mineral products industry is predicted to be 680.53 TWh (terawatt-hours in 2020 and the sectoral electricity conservation potentials are estimated to be 118.26 TWh and 216.25 TWh under the moderate and advanced electricity-saving scenarios, respectively.
Directory of Open Access Journals (Sweden)
O. V. Russkov
2015-01-01
Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost
Assessing long-term effects of demand response policies in wholesale electricity markets
International Nuclear Information System (INIS)
Cepeda, Mauricio; Saguan, Marcelo
2014-05-01
This paper deals with the practical problems related to long-term issues in electricity markets in the presence of demand response development. Different policies have been implemented around the world aiming to develop demand response potential. Externalities, in particular the CO_2 externality, have been one of the key elements in the debate on the effectiveness of different policies regarding demand response development. Policy makers have several options to deal with this externality. The most direct one is to correct the externality by setting a CO_2 price at a level that corresponds to the cost to society of the corresponding CO_2 emissions. One alternative solution could be to subsidize carbon-free technologies as demand response. In this paper we examine potential long-term impacts of these two policies. We rely on a long-term market simulation model that characterizes expansion decisions in a competitive regime. We test for each policy two different scenarios regarding the possibility of internalization of the CO_2 externality. The results show that differences in development policies affect both investments and social costs in the wholesale electricity market and confirm previous findings that a market-driven development of demand response with the internalization of the CO_2 externality is the most efficient approach. (authors)
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
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
Generation adequacy report 2009 on the electricity supply - demand balance in France
International Nuclear Information System (INIS)
2009-01-01
Under the terms of the Law of February 10, 2000, RTE (Reseau de Transport d'Electricite), working under the aegis of the Public Authorities, periodically establishes a multi-annual forecast report on the balance of electricity supply and demand in France. The Generation Adequacy Report is one basis for the Minister for Energy, and the Public Authorities in general, to build the Multi-annual Investment Plan (referred to in this document by its French acronym PPI for Programmation Pluri-annuelle des Investissements) for electricity generation facilities, introduced by the above-mentioned law. The Generation Adequacy Report deals with the security of the French electricity supply. It intends to identify over a period of about fifteen years the risks of imbalances in continental France between the electricity demand and the generation capacity available to supply it. It enables the identification of the generation capacity required to meet the peaks of demand. The choice of generation technologies to be developed, which is dictated by environmental and economic concerns, is not covered by the Generation Adequacy Report, but is a matter for the other stakeholders in the French electric system, under the guidelines determined by the PPI. The Generation Adequacy Report is published by RTE on its web site and thus accessible to all to serve transparency and contribute to the French energy debate. This document is the fourth edition of the Generation Adequacy Report published by RTE, following its 2003, 2005 and 2007 editions. RTE publishes partial updates in-between to reflect developments in generation capacity. The last update was published in 2008. The time horizon of the 2009 edition of the Generation Adequacy Report is 2025. (author)
Future Electricity Demand of the Emerging European Countries and the CIS Countries
Directory of Open Access Journals (Sweden)
Mehmet Fatih Bayramoglu
2016-10-01
Full Text Available Nowadays, one of the leading factors used in the evaluation of a country’s economic development is energy consumption. Because of economic growth, demand for energy is also increasing. In this study, the emerging European countries’ (the Czech Republic, Poland, Romania, Turkey and the CIS countries’ (Kazakhstan, Russia, Ukraine, Uzbekistan electricity consumption has been forecasted for five years period (2015-2019. In the study, GM(1,1 Rolling Model, which is developed in the framework of Grey System Theory is used as a mathematical model for real-time forecasting. The results of the study show that there will not be a significant change in electricity demand in this two area during the 2015-2109 period.
A long- and short-run analysis of electricity demand in Ciudad Juarez
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.
Energy Technology Data Exchange (ETDEWEB)
Solinski, J.
2004-07-01
The paper presents a preliminary forecast of Poland's future coal demand until 2030, particularly the demand for electric power. Two scenarios are examined - one of average GDP growth rate of 3.5% and a second of 4.5%. Implementation of the first scenario would enable Poland to achieve in 2030 today's levels of per capita electricity consumption in main EU countries, with a forecast consumption level of 280 TWh. By 2030, coal's share in electricity production would fall to about 7%, the remainder being from gas, nuclear and renewable sources. 11 refs., 5 tabs.
Optimal Electricity Charge Strategy Based on Price Elasticity of Demand for Users
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.
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.
Estimating the price elasticity for demand for electricity by sector in South Africa
Directory of Open Access Journals (Sweden)
Roula Inglesi-Lotz
2011-12-01
Full Text Available This paper analyses electricity consumption patterns in South Africa in an attempt to understand and identify the roots of the current electricity crisis. This is done by investigating various economic sectors’ responses to price changes using panel data for the period 1993–2004. Positive and statistically significant price elasticities over this period were found for the transport (rail and commercial sectors while there are positive, but small and statistically insignificant responses to price changes in the agriculture and mining sectors. Only the industrial sector responded to changes in electricity prices according to theory, namely illustrating negative demand elasticities. This sector, however, dominates electricity consumption resulting in aggregate demand elasticities that are negative. These results explain, in part, the current electricity crisis. Given the historic low level of electricity prices in conjunction with, on the whole, a real price decline, i.e. price increases lower than the inflation rate; there was no major incentive to reduce electricity consumption and/or to be efficient. This result supports the notion that prices do have an important signalling effect in the economy. Hence, the electricity prices should be considered not only from an economic growth or social vantage point, but also from a supply and technocratic perspective, which includes environmental factors such as CO2-emissions. Prices should not be determined without considering the system-wide implications thereof.
Energy Technology Data Exchange (ETDEWEB)
Acket, C
2009-02-15
Meeting about the CO{sub 2} emissions from electric heating showed that the leak of adaptation from nuclear reactors led the use of thermal power plants (coal, petroleum, gas) to control the demand variations. This argument is analyzed in the document: is it possible to replace those thermal power plants by nuclear reactors? In this framework the author analyzes the network needs, the electricity sources and the demand answer and the specificities of the nuclear. (A.L.B.)
International Nuclear Information System (INIS)
Gibbons, J.
2006-01-01
This paper proposed an alternative to importing coal-fired electricity from the Ohio Valley on smog alert days in Ontario. It was suggested that the Ontario Power Authority (OPA) should pay large electricity consumers to shift some of their consumption from peak to off-peak hours. It was observed that demand response programs which pay consumers to shift demands to off-peak hours can provide multiple benefits to Ontario, including reduced air pollution on smog-alert days, a reduction in the spot price of electricity and reduced price volatility. In addition, demand response programs reduce the risk of blackouts and brownouts, as well as the need for new electricity generation and transmission infrastructure. It was noted that the Independent Electricity System Operator (IESO) and the OPA are planning to introduce demand response programs for the summer of 2006. However, the IESO's emergency load reduction program will be operated only during emergency situations to avoid the need for voltage reductions, while the OPA proposes to introduce a non-emergency demand response program which will be activated during most smog-alert days. Various amendments to the proposed program were suggested in this paper, including the establishment of price parity with coal-fired electricity imports; the provision of notification by 3 PM of the need for demand reductions the following day; no capping on the quantity of demand reductions that the OPA will purchase at a lower cost than electricity imports; and that the OPA's proposed Capacity Building Demand Response Program should proceed as quickly as possible without a pre-determined MW cap. 4 refs., 6 figs
Electric Power monthly, November 1995 with data for August 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-11-15
This report presents monthly electricity statistics, with the purpose of providing energy decisionmakers with accurate, timely information that may be used in forming various perspectives on electric issues that lie ahead. EIA collected the information in this report to fulfill its data collection and dissemination responsibilities; the information are from six data sources: forms EIA-759, FERC Form 423, EIA-826, EIA-861, EIA-860, and Form OE-417R. An article on reclicensing and environmental issues affecting hydropower is included. Then the statistics are presented in: US electric power at a glance, utility net generation, utility consumption of fossil fuels, fossil-fuel stocks at utilities, fossil fuel receipts and costs, utility sales/revenue/average revenue per kWh, and monthly plant aggregates. Finally, nonutility power producer statistics, bibliography, technical notes, and a glossary are presented.
Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System
Directory of Open Access Journals (Sweden)
Bo Lin
2017-10-01
Full Text Available This paper investigates how to develop a learning-based demand response approach for electric water heater in a smart home that can minimize the energy cost of the water heater while meeting the comfort requirements of energy consumers. First, a learning-based, data-driven model of an electric water heater is developed by using a nonlinear autoregressive network with external input (NARX using neural network. The model is updated daily so that it can more accurately capture the actual thermal dynamic characteristics of the water heater especially in real-life conditions. Then, an optimization problem, based on the NARX water heater model, is formulated to optimize energy management of the water heater in a day-ahead, dynamic electricity price framework. A genetic algorithm is proposed in order to solve the optimization problem more efficiently. MATLAB (R2016a is used to evaluate the proposed learning-based demand response approach through a computational experiment strategy. The proposed approach is compared with conventional method for operation of an electric water heater. Cost saving and benefits of the proposed water heater energy management strategy are explored.
International Nuclear Information System (INIS)
Perwez, Usama; Sohail, Ahmed; Hassan, Syed Fahad; Zia, Usman
2015-01-01
The long-term forecasting of electricity demand and supply has assumed significant importance in fundamental research to provide sustainable solutions to the electricity issues. In this article, we provide an overview of structure of electric power sector of Pakistan and a summary of historical electricity demand & supply data, current status of divergent set of energy policies as a framework for development and application of a LEAP (Long-range Energy Alternate Planning) model of Pakistan's electric power sector. Pakistan's LEAP model is used to analyze the supply policy selections and demand assumptions for future power generation system on the basis of economics, technicality and implicit environmental implications. Three scenarios are enacted over the study period (2011–2030) which include BAU (Business-As-Usual), NC (New Coal) & GF (Green Future). The results of these scenarios are compared in terms of projected electricity demand & supply, net present cost analysis (discount rate at 4%, 7% and 10%) and GHG (greenhouse gas) emission reductions, along with sensitivity analysis to study the effect of varying parameters on total cost. A concluding section illustrates the policy implications of model for futuristic power generation and environmental policies in Pakistan. - Highlights: • Pakistan-specific electricity demand model is presented. • None of the scenarios exceeded the price of 12 US Cents/kWh. • By 2030, fuel cost is the most dominant factor to influence electricity per unit cost. • By 2030, CO_2 emissions per unit electricity will increase significantly in coal scenario relative to others. • By 2030, the penetration of renewable energy and conservation policies can save 70.6 tWh electricity.
Directory of Open Access Journals (Sweden)
Sayed Mahdi Mostafavi
2016-07-01
Full Text Available Electrical energy is as one of the important effective factors on economic growth and development. In recent decades, numerous studies in different countries to estimate and forecast electricity demand in different parts of the economy have been made. In this paper, using the method ARDL, estimation and forecasting of electricity demand in the services sector of Iran are determined for the time period from 1983 to 2012. Estimated equations show that the added value of the services sector and a significant positive impact on the demand for electricity in this sector. The price elasticity for services sector is smaller than 1 due to low electricity prices and subsidized electricity. Hence, electricity prices have little impact on the demand for electricity. The results of the estimate represents a long-term relationship between the variables in the services sector. In this paper, based on amendments to the law on subsidies and estimated values, anticipated electricity demand until the end of the fifth development plan was carried out. The results indicate an increase in power consumption in the services sector.
Electric power monthly, December 1995 with data for September 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-12-14
This publication presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. Its purpose is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. EIA collected the information to fulfill its data collection and dissemination responsibilities. (User instructions on EIA`s electronic publishing system are included, as is a glossary.)
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...
Regulating electricity demand peaks for home appliances using reversible fair scheduling
DEFF Research Database (Denmark)
Kardaras, Georgios; Rossello Busquet, Ana; Iversen, Villy Bæk
2010-01-01
This paper describes a novel methodology for regulating electricity demand peaks for home appliances. To achieve this objective, we will make use of the reversible fair scheduling algorithm originally developed for telecommunication networks. The main concept behind this approach is the aggregati...
Predicting the electricity demand of an oil industry region on the basis of a stochastic model
Energy Technology Data Exchange (ETDEWEB)
Ragimova, R A; Khaykin, I Ye
1979-01-01
A justified decision to accept a particular development design may be made only on the basis of a scientific prediction of the basic technical and economic indicators. Used as the basic factor which impacts on the electricity demand is the total oil production and the flow of the total liquid pumped from the bowels of the earth. The initial information is statistical data about the expenditure of electricity, the oil and liquid production for 8-10 years. The existence is accepted of a direct relation between the resultive and the factorial signs. Based on a normal law of distribution of random errors, reliable probabilities are found for determining the electricity demand of an object with an assigned degree of precision. Calculations through the proposed model in the practical work of the energy services make it possible to expose the degree of quantitative influence of the basic parameters of the development of a deposit on the value of the expenditure of electricity and to justifiably predict the electricity demand for oil production.
Demand Response in U.S. Electricity Markets: Empirical Evidence
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 ...
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.
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...
Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D.; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan
2018-04-01
Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2 = 0.91. The electric demand was found to be more sensitive to GDP ( r = 0.96) than population growth ( r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.
Directory of Open Access Journals (Sweden)
Jinchao Li
2018-01-01
Full Text Available Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have positive influences on electric grid investment demand, but the impact of population scale, social electricity consumption, and installed electrical capacity on electric grid investment is not remarkable. We divide different regions in China into the eastern region, central region, and western region to analyze influence factors of electric grid investment, finally obtaining key factors in the eastern, central, and western regions. In the end, according to the analysis of key factors, we make a prediction about China’s electric grid investment for 2020 in different scenarios. The results offer a certain understanding for the development trend of China’s electric grid investment and contribute to the future development of electric grid investment.
International Nuclear Information System (INIS)
Al-Iriani, Mahmoud A.
2005-01-01
The oil crisis of the 1970s has increased the concern about the continuity of oil imports flow to major oil-importing developed countries. Numerous policy measures including electricity demand-side management (DSM) programs have been adopted in such countries. These measures aim at reducing the growing need for electricity power that increases the dependency on imported foreign oil and damages the environment. On the other hand, the perception that energy can be obtained at very low cost in oil-rich countries led to less attention being paid to the potential of DSM policies in these countries. This paper discusses such potential using the case of the United Arab Emirates (UAE). Since air conditioning is a major source of electric energy consumption, the relationship between climate conditions and electric energy consumption is considered. An electricity demand model is constructed using time series techniques. The fitted model seems to represent these relationships rather well. Forecasts for electricity consumption using the estimated model indicate that a small reduction in cooling degrees requirement might induce a significant reduction in electric energy demand. Hence, a DSM program is proposed with policy actions to include, among others, measures to reduce cooling degrees requirement
The effects of demand uncertainty on strategic gaming in the merit-order electricity pool market
Frem, Bassam
In a merit-order electricity pool market, generating companies (Gencos) game with their offered incremental cost to meet the electricity demand and earn bigger market shares and higher profits. However when the demand is treated as a random variable instead of as a known constant, these Genco gaming strategies become more complex. After a brief introduction of electricity markets and gaming, the effects of demand uncertainty on strategic gaming are studied in two parts: (1) Demand modelled as a discrete random variable (2) Demand modelled as a continuous random variable. In the first part, we proposed an algorithm, the discrete stochastic strategy (DSS) algorithm that generates a strategic set of offers from the perspective of the Gencos' profits. The DSS offers were tested and compared to the deterministic Nash equilibrium (NE) offers based on the predicted demand. This comparison, based on the expected Genco profits, showed the DSS to be a better strategy in a probabilistic sense than the deterministic NE. In the second part, we presented three gaming strategies: (1) Deterministic NE (2) No-Risk (3) Risk-Taking. The strategies were then tested and their profit performances were compared using two assessment tools: (a) Expected value and standard deviation (b) Inverse cumulative distribution. We concluded that despite yielding higher profit performance under the right conjectures, Risk-Taking strategies are very sensitive to incorrect conjectures on the competitors' gaming decisions. As such, despite its lower profit performance, the No-Risk strategy was deemed preferable.
Generation Adequacy Report on the electricity supply-demand balance in France. 2009 Edition
International Nuclear Information System (INIS)
2010-01-01
Under the terms of the Law of February 10, 2000, RTE (Reseau de Transport d'Electricite), working under the aegis of the Public Authorities, periodically establishes a multi-annual forecast report on the balance of electricity supply and demand in France. The Generation Adequacy Report is one basis for the Minister for Energy, and the Public Authorities in general, to build the Multi-annual Investment Plan (referred to in this document by its French acronym PPI for Programmation Pluri-annuelle des Investissements) for electricity generation facilities, introduced by the above-mentioned law. The Generation Adequacy Report deals with the security of the French electricity supply. It intends to identify over a period of about fifteen years the risks of imbalances in continental France between the electricity demand and the generation capacity available to supply it. It enables the identification of the generation capacity required to meet the peaks of demand. The choice of generation technologies to be developed, which is dictated by environmental and economic concerns, is not covered by the Generation Adequacy Report, but is a matter for the other stakeholders in the French electric system, under the guidelines determined by the PPI. The Generation Adequacy Report is published by RTE on its web site and thus accessible to all to serve transparency and contribute to the French energy debate. This document is the fourth edition of the Generation Adequacy Report published by RTE, following its 2003, 2005 and 2007 editions. RTE publishes partial updates in-between to reflect developments in generation capacity. The last update was published in 2008. The time horizon of the 2009 edition of the Generation Adequacy Report is 2025
Demand elasticity of oil in Barbados
Energy Technology Data Exchange (ETDEWEB)
Moore, Alvon, E-mail: armoore@centralbank.org.bb [Economist, Central Bank of Barbados, Toms Adams Financial Centre, Bridgetown (Barbados)
2011-06-15
The importation of oil is a significant component of Barbados' imports, rising from 7% of imports in 1998 to over 20% in 2009. This increase has impacted greatly on the level of foreign reserves. As a price-taker, relying entirely on imported oil for our energy needs could prove a continuous drain on the economy. With a view to formulating an appropriate energy policy for Barbados, this paper analyses the demand for oil using monthly data from 1998 to 2009. The paper estimates the elasticities of demand for oil by employing single equation cointegration approach and comparing the results with countries that rely heavily on imported oil and whose policy objective are to alter their energy structure to rely less on imported oil. The results show that the demand for oil imports is price inelastic in the long run. The consumption of oil is responsive to past consumption, prices, income, electricity consumption and the number of appliances imported in the short-run. A policy framework to reduce the use of oil for electricity consumption via alternative energy sources should be considered and the taxation of oil imports given its elasticity is a good source of revenue. - Highlights: > Demand for oil is price inelastic in the long-run (-0.552). > The relationship between oil demand and income is insignificant in the long run. > As electricity consumption increases by 1%, the demand for oil rises by 1.43%. > Need to determine if investments in alternative sources can offset demand for oil. > Investment in alternative resources may be required before gains are realised.
International Nuclear Information System (INIS)
Neves, Diana; Silva, Carlos A.
2015-01-01
The present study uses the DHW (domestic hot water) electric backup from solar thermal systems to optimize the total electricity dispatch of an isolated mini-grid. The proposed approach estimates the hourly DHW load, and proposes and simulates different DR (demand response) strategies, from the supply side, to minimize the dispatch costs of an energy system. The case study consists on optimizing the electricity load, in a representative day with low solar radiation, in Corvo Island, Azores. The DHW backup is induced by three different demand patterns. The study compares different DR strategies: backup at demand (no strategy), pre-scheduled backup using two different imposed schedules, a strategy based on linear programming, and finally two strategies using genetic algorithms, with different formulations for DHW backup – one that assigns number of systems and another that assigns energy demand. It is concluded that pre-determined DR strategies may increase the generation costs, but DR strategies based on optimization algorithms are able to decrease generation costs. In particular, linear programming is the strategy that presents the lowest increase on dispatch costs, but the strategy based on genetic algorithms is the one that best minimizes both daily operation costs and total energy demand, of the system. - Highlights: • Integrated hourly model of DHW electric impact and electricity dispatch of isolated grid. • Proposal and comparison of different DR (demand response) strategies for DHW backup. • LP strategy presents 12% increase on total electric load, plus 5% on dispatch costs. • GA strategy presents 7% increase on total electric load, plus 8% on dispatch costs
Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui
2018-01-01
The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.
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)
Estimating deficit probabilities with price-responsive demand in contract-based electricity markets
International Nuclear Information System (INIS)
Galetovic, Alexander; Munoz, Cristian M.
2009-01-01
Studies that estimate deficit probabilities in hydrothermal systems have generally ignored the response of demand to changing prices, in the belief that such response is largely irrelevant. We show that ignoring the response of demand to prices can lead to substantial over or under estimation of the probability of an energy deficit. To make our point we present an estimation of deficit probabilities in Chile's Central Interconnected System between 2006 and 2010. This period is characterized by tight supply, fast consumption growth and rising electricity prices. When the response of demand to rising prices is acknowledged, forecasted deficit probabilities and marginal costs are shown to be substantially lower
Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan
2018-04-01
Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2 = 0.91. The electric demand was found to be more sensitive to GDP (r = 0.96) than population growth (r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.
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...
International Nuclear Information System (INIS)
Sirin, Selahattin Murat; Gonul, Mustafa Sinan
2016-01-01
Electricity sector has been transformed from state-owned monopolistic utilities to competitive markets with an aim to promote incentives for improving efficiency, reducing costs and increasing service quality to customers. One of the cardinal assumptions of the liberalized and competitive electricity markets is the rational actor, and decision-makers are assumed to make the best decisions that maximize their utility. However, a vast literature on behavioral economics has shown the weakness of economic theory in explaining and predicting individuals’ decision-making behavior. This issue is quite important for competition in electricity markets in which consumers’ preferences have a significant role. Despite its importance, this issue has almost been neglected in Turkey, which has taken major steps in electricity sector restructuring. Therefore, this paper aims to examine switching and demand response behavior in Turkish electricity market by using multiple correspondence and panel data analysis, and findings are discussed in light of the neoclassical and behavioral economics literature. Analyses’ results show that consumers’ switching and demand response behavior is consistent with the neoclassical literature to some extent; however, behavioral factors are also affecting consumers’ decisions. Furthermore, there are systemic problems that hinder effective functioning of the electricity market and restrict competition. - Highlights: • Behavioral economics can provide insights for consumer’ decisions. • Switching and demand response behavior is examined by econometric methods. • Results is consistent with the neoclassical literature to some extent • However, behavioral factors are also affecting consumers’ decisions.
Bulk electric system reliability evaluation incorporating wind power and demand side management
Huang, Dange
correlations and the interactive effects of wind power and load forecast uncertainty on system reliability are examined. The concept of the security cost associated with operating in the marginal state in the well-being framework is incorporated in the economic analyses associated with system expansion planning including wind power and load forecast uncertainty. Overall reliability cost/worth analyses including security cost concepts are applied to select an optimal wind power injection strategy in a bulk electric system. The effects of the various demand side management measures on system reliability are illustrated using the system, load point, and well-being indices, and the reliability index probability distributions. The reliability effects of demand side management procedures in a bulk electric system including wind power and load forecast uncertainty considerations are also investigated. The system reliability effects due to specific demand side management programs are quantified and examined in terms of their reliability benefits.
International Nuclear Information System (INIS)
Kale, Rajesh V.; Pohekar, Sanjay D.
2014-01-01
Forecasting of electricity demand has assumed a lot of importance to provide sustainable solutions to the electricity problems. LEAP has been used to forecast electricity demand for the target year 2030, for the state of Maharashtra (India). Holt’s exponential smoothing method has been used to arrive at suitable growth rates. Probable projections have been generated using uniform gross domestic product (GDP) growth rate and different values of elasticity of demands. Three scenarios have been generated which include Business as Usual (BAU), Energy Conservation (EC) and Renewable Energy (REN). Subsequent analysis on the basis of energy, environmental influence and cost has been done. In the target year 2030, the projected electricity demand for BAU and REN has increased by 107.3 per cent over the base year 2012 and EC electricity demand has grown by 54.3 per cent. The estimated values of green house gas (GHG) for BAU and EC, in the year 2030, are 245.2 per cent and 152.4 per cent more than the base year and for REN it is 46.2 per cent less. Sensitivity analysis has been performed to study the effect on the total cost of scenarios. Policy implications in view of the results obtained are also discussed. - Highlights: • Forecasted electricity scenarios by Long Range Energy Alternatives Planning (LEAP). • Critically analyzed the demand and supply prior to 2012 for a period of six years. • Used Holt’s exponential smoothing method ARIMA (0,1,1) for finding growth rates. • Devised suitable LEAP model for the generated scenarios. • Discussed policy implications for the generated scenarios
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
Generation adequacy report on the electricity supply-demand balance in France - 2012 edition
International Nuclear Information System (INIS)
2012-01-01
After an introduction presenting the objective of this report and the method used for the forecasts, this document proposes, first, an analysis of the medium-term evolution of: 1 - electricity consumption (past trends, medium-term perspectives, medium-term consumption scenarios); 2 - electricity supply (nuclear production, centralised and decentralised production from fossil-fueled power plants, hydro-power, wind-power and photovoltaic production, peak-load management); 3 - supply and demand balance (probabilistic approach, reference scenario, scenario sensitivity with respect to the demand). Then it presents the long-term determining factors (socio-economic context, energy efficiency, energy mix, interconnected grids development) and the long-term prospective scenarios (medium- and strong-consumption, new-mix, low growth). Finally, a summary and a comparison with the 2011 report is made
International Nuclear Information System (INIS)
Shen, Peihong; Zhao, Zhiguo; Zhan, Xiaowen; Li, Jingwei
2017-01-01
In this paper, an energy management strategy based on logic threshold is proposed for a plug-in hybrid electric vehicle. The plug-in hybrid electric vehicle powertrain model is established using MATLAB/Simulink based on experimental tests of the power components, which is validated by the comparison with the verified simulation model which is built in the AVL Cruise. The influence of the driving torque demand decision on the fuel economy of plug-in hybrid electric vehicle is studied using a simulation. The optimization method for the driving torque demand decision, which refers to the relationship between the accelerator pedal opening and driving torque demand, from the perspective of fuel economy is formulated. The dynamically changing inertia weight particle swarm optimization is used to optimize the decision parameters. The simulation results show that the optimized driving torque demand decision can improve the PHEV fuel economy by 15.8% and 14.5% in the fuel economy test driving cycle of new European driving cycle and worldwide harmonized light vehicles test respectively, using the same rule-based energy management strategy. The proposed optimization method provides a theoretical guide for calibrating the parameters of driving torque demand decision to improve the fuel economy of the real plug-in hybrid electric vehicle. - Highlights: • The influence of the driving torque demand decision on the fuel economy is studied. • The optimization method for the driving torque demand decision is formulated. • An improved particle swarm optimization is utilized to optimize the parameters. • Fuel economy is improved by using the optimized driving torque demand decision.
Electric power monthly, June 1995 with data for March 1995
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-06-19
The Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and US levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 68 tabs.
Electric power monthly, September 1996, with data for June 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-09-01
The Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy prepares the EPM. This publication provides monthly statistics at the State, Census division, and U.S. levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatt hour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
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
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
Electric power monthly, August 1996, with data for May 1996
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-08-09
This publication presents monthly electricity statistics for a wide audience including Congress, Federal and state agencies, the electric utility industry, and the general public. Purpose is to provide energy decisionmakers with accurate, timely information that may be used in forming various perspectives on electric issues that lie ahead. EIA collected the information to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974. Statistics are presented in this publication on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant.
Natural graphite demand and supply - Implications for electric vehicle battery requirements
Olson, Donald W.; Virta, Robert L.; Mahdavi, Mahbood; Sangine, Elizabeth S.; Fortier, Steven M.
2016-01-01
Electric vehicles have been promoted to reduce greenhouse gas emissions and lessen U.S. dependence on petroleum for transportation. Growth in U.S. sales of electric vehicles has been hindered by technical difficulties and the high cost of the lithium-ion batteries used to power many electric vehicles (more than 50% of the vehicle cost). Groundbreaking has begun for a lithium-ion battery factory in Nevada that, at capacity, could manufacture enough batteries to power 500,000 electric vehicles of various types and provide economies of scale to reduce the cost of batteries. Currently, primary synthetic graphite derived from petroleum coke is used in the anode of most lithium-ion batteries. An alternate may be the use of natural flake graphite, which would result in estimated graphite cost reductions of more than US$400 per vehicle at 2013 prices. Most natural flake graphite is sourced from China, the world's leading graphite producer. Sourcing natural flake graphite from deposits in North America could reduce raw material transportation costs and, given China's growing internal demand for flake graphite for its industries and ongoing environmental, labor, and mining issues, may ensure a more reliable and environmentally conscious supply of graphite. North America has flake graphite resources, and Canada is currently a producer, but most new mining projects in the United States require more than 10 yr to reach production, and demand could exceed supplies of flake graphite. Natural flake graphite may serve only to supplement synthetic graphite, at least for the short-term outlook.
Demand elasticity of oil in Barbados
International Nuclear Information System (INIS)
Moore, Alvon
2011-01-01
The importation of oil is a significant component of Barbados' imports, rising from 7% of imports in 1998 to over 20% in 2009. This increase has impacted greatly on the level of foreign reserves. As a price-taker, relying entirely on imported oil for our energy needs could prove a continuous drain on the economy. With a view to formulating an appropriate energy policy for Barbados, this paper analyses the demand for oil using monthly data from 1998 to 2009. The paper estimates the elasticities of demand for oil by employing single equation cointegration approach and comparing the results with countries that rely heavily on imported oil and whose policy objective are to alter their energy structure to rely less on imported oil. The results show that the demand for oil imports is price inelastic in the long run. The consumption of oil is responsive to past consumption, prices, income, electricity consumption and the number of appliances imported in the short-run. A policy framework to reduce the use of oil for electricity consumption via alternative energy sources should be considered and the taxation of oil imports given its elasticity is a good source of revenue. - Highlights: → Demand for oil is price inelastic in the long-run (-0.552). → The relationship between oil demand and income is insignificant in the long run. → As electricity consumption increases by 1%, the demand for oil rises by 1.43%. → Need to determine if investments in alternative sources can offset demand for oil. → Investment in alternative resources may be required before gains are realised.
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
Deetman, Sebastiaan; Pauliuk, Stefan; van Vuuren, Detlef P; van der Voet, Ester; Tukker, Arnold
2018-04-17
This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework.
2018-01-01
This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework. PMID:29533657
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
Modelling electricity demand in Ghana revisited: The role of policy regime changes
International Nuclear Information System (INIS)
Adom, Philip Kofi; Bekoe, William
2013-01-01
As policy regime changes, demand elasticities are unlikely to be constant since individuals change how they form their expectations, and this will change the estimated decision rules. In this paper, the time-varying nature of electricity demand elasticities prior to and post the economic reform period in Ghana is analysed using the FM-OLS. Three different sample periods -pre-reform, post-reform, and full-period- was used in the analysis. The result from the full-sample period revealed that in the long-run electricity demand is significantly affected by industry efficiency, industry value added, and real per capita GDP. Urbanization rate, however, has no significant effect. The pre-reform estimate showed lower income, output, and urbanization elasticities but higher industry energy efficiency elasticity relative to the post-reform period. This suggests that technological change in the pre-reform period has been energy saving whilst technological change in the post reform period has been energy consuming. The result further showed evidence of changing structure of the economy from the more energy intensive sector to the less energy intensive sector after the reform. Government should renew her effort in promoting energy saving technologies in the industrial sector and adjust the industrial structure to encourage the expansion of low energy intensive industries or high technology efficient industries. - Highlights: • The study investigates time-varying nature of demand elasticities prior to 1983 and after 1983. • Result shows differences in demand elasticities prior to and post the reform. • Pre-reform period is characterised with energy saving technology. • Post-reform period is characterised with energy consuming technology. • The post-reform result reveals evidence of gradual structural shift in the economy
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
International Nuclear Information System (INIS)
Strengers, Yolande
2012-01-01
Demand managers currently draw on a limited range of psychology and economic theories in order to shift and shed peak electricity demand. These theories place individual consumers and their attitudes, behaviours and choices at the centre of the problem. This paper reframes the issue of peak electricity demand using theories of social practices, contending that the ‘problem’ is one of transforming, technologically-mediated social practices. It reflects on how this body of theory repositions and refocuses the roles and practices of professions charged with the responsibility and agency for affecting and managing energy demand. The paper identifies three areas where demand managers could refocus their attention: (i) enabling co-management relationships with consumers; (ii) working beyond their siloed roles with a broader range of human and non-human actors; and (iii) promoting new practice ‘needs’ and expectations. It concludes by critically reflecting on the limited agency attributed to ‘change agents’ such as demand managers in dominant understandings of change. Instead, the paper proposes the need to identify and establish a new group of change agents who are actively but often unwittingly involved in reconfiguring the elements of problematic peaky practices. - Highlights: ► I reframe peak electricity demand as a problem of changing social practices. ► Micro-grids, and dynamic pricing reorient household routines and enable co-management. ► Infrastructures inside and outside the home configure peaky practices. ► Demand managers are encouraged to promote and challenge consumer ‘needs’. ► I identify a new group of change agents implicated in peaky practices.
International Nuclear Information System (INIS)
Lechtenböhmer, Stefan; Nilsson, Lars J.; Åhman, Max; Schneider, Clemens
2016-01-01
The need for deep decarbonisation in the energy intensive basic materials industry is increasingly recognised. In light of the vast future potential for renewable electricity the implications of electrifying the production of basic materials in the European Union is explored in a what-if thought-experiment. Production of steel, cement, glass, lime, petrochemicals, chlorine and ammonia required 125 TW-hours of electricity and 851 TW-hours of fossil fuels for energetic purposes and 671 TW-hours of fossil fuels as feedstock in 2010. The resulting carbon dioxide emissions were equivalent to 9% of total greenhouse gas emissions in EU28. A complete shift of the energy demand as well as the resource base of feedstocks to electricity would result in an electricity demand of 1713 TW-hours about 1200 TW-hours of which would be for producing hydrogen and hydrocarbons for feedstock and energy purposes. With increased material efficiency and some share of bio-based materials and biofuels the electricity demand can be much lower. Our analysis suggest that electrification of basic materials production is technically possible but could have major implications on how the industry and the electric systems interact. It also entails substantial changes in relative prices for electricity and hydrocarbon fuels. - Highlights: • Energy intensive basic materials industry has a high share in EU greenhouse gas emissions. • Decarbonising these industries is very important, but still relatively unexplored. • Electrification is possible regarding renewable energy resources and technologies. • Combination with energy and materials efficiency, biofuels and CCS is crucial. • Electrification needs very high amounts of electricity and strong policies.
Grey prediction with rolling mechanism for electricity demand forecasting of Turkey
International Nuclear Information System (INIS)
Akay, Diyar; Atak, Mehmet
2007-01-01
The need for energy supply, especially for electricity, has been increasing in the last two decades in Turkey. In addition, owing to the uncertain economic structure of the country, electricity consumption has a chaotic and nonlinear trend. Hence, electricity configuration planning and estimation has been the most critical issue of active concern for Turkey. The Turkish Ministry of Energy and Natural Resources (MENR) has officially carried out energy planning studies using the Model of Analysis of the Energy Demand (MAED). In this paper, Grey prediction with rolling mechanism (GPRM) approach is proposed to predict the Turkey's total and industrial electricity consumption. GPRM approach is used because of high prediction accuracy, applicability in the case of limited data situations and requirement of little computational effort. Results show that proposed approach estimates more accurate results than the results of MAED, and have explicit advantages over extant studies. Future projections have also been done for total and industrial sector, respectively
International Nuclear Information System (INIS)
Yu, Shiwei; Wang, Ke; Wei, Yi-Ming
2015-01-01
Highlights: • A hybrid self-adaptive PSO–GA-RBF model is proposed for electricity demand prediction. • Each mixed-coding particle is composed by two coding parts of binary and real. • Five independent variables have been selected to predict future electricity consumption in Wuhan. • The proposed model has a simpler structure or higher estimating precision than other ANN models. • No matter what the scenario, the electricity consumption of Wuhan will grow rapidly. - Abstract: The present study proposes a hybrid Particle Swarm Optimization and Genetic Algorithm optimized Radial Basis Function (PSO–GA-RBF) neural network for prediction of annual electricity demand. In the model, each mixed-coding particle (or chromosome) is composed of two coding parts, binary and real, which optimizes the structure of the RBF by GA operation and the parameters of the basis and weights by a PSO–GA implementation. Five independent variables have been selected to predict future electricity consumption in Wuhan by using optimized networks. The results shows that (1) the proposed PSO–GA-RBF model has a simpler network structure (fewer hidden neurons) or higher estimation precision than other selected ANN models; and (2) no matter what the scenario, the electricity consumption of Wuhan will grow rapidly at average annual growth rates of about 9.7–11.5%. By 2020, the electricity demand in the planning scenario, the highest among the scenarios, will be 95.85 billion kW h. The lowest demand is estimated for the business-as-usual scenario, and will be 88.45 billion kW h
The electricity supply-demand balance for the summer of 2016 - June 2016. Synthesis
International Nuclear Information System (INIS)
2016-06-01
Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the summer of 2016
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
Contrasting electricity demand with wind power supply: case study in Hungary
International Nuclear Information System (INIS)
Kiss, P.; Janosi, I. M.; Varga, L.
2009-01-01
We compare the demand of a large electricity consumer with supply given by wind farms installed at two distant geographic locations. Obviously such situation is rather unrealistic, however our main goal is a quantitative characterization of the intermittency of wind electricity. The consumption pattern consists of marked daily and weekly cycles interrupted by periods of holidays. In contrast, wind electricity production has neither short-time nor seasonal periodicities. We show that wind power integration over a restricted area cannot provide a stable base load supply, independently of the excess capacity. Further essential result is that the statistics are almost identical for a weekly periodic pattern of consumption and a constant load of the same average value. The length of both adequate supply and shortfall intervals exhibits a scale-free (power-law) frequency distribution, possible consequences are shortly discussed. (author)
Contrasting Electricity Demand with Wind Power Supply: Case Study in Hungary
Directory of Open Access Journals (Sweden)
Imre M. Jánosi
2009-09-01
Full Text Available We compare the demand of a large electricity consumer with supply given by wind farms installed at two distant geographic locations. Obviously such situation is rather unrealistic, however our main goal is a quantitative characterization of the intermittency of wind electricity. The consumption pattern consists of marked daily and weekly cycles interrupted by periods of holidays. In contrast, wind electricity production has neither short-time nor seasonal periodicities. We show that wind power integration over a restricted area cannot provide a stable baseload supply, independently of the excess capacity. Further essential result is that the statistics are almost identical for a weekly periodic pattern of consumption and a constant load of the same average value. The length of both adequate supply and shortfall intervals exhibits a scale-free (power-law frequency distribution, possible consequences are shortly discussed.
International Nuclear Information System (INIS)
Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio; Morais, Hugo; Vale, Zita
2015-01-01
Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand. - Highlights: • Asset-light electricity retail providers subject to financial risks. • Incentive-based demand response program to manage the financial risks. • Maximizing the payoff of electricity retail providers in day-ahead market. • Mixed integer nonlinear programming to manage the risks
Controlling market power and price spikes in electricity networks: Demand-side bidding.
Rassenti, Stephen J; Smith, Vernon L; Wilson, Bart J
2003-03-04
In this article we report an experiment that examines how demand-side bidding can discipline generators in a market for electric power. First we develop a treatment without demand-side bidding; two large firms are allocated baseload and intermediate cost generators such that either firm might unilaterally withhold the capacity of its intermediate cost generators from the market to benefit from the supracompetitive prices that would result from only selling its baseload units. In a converse treatment, ownership of some of the intermediate cost generators is transferred from each of these firms to two other firms such that no one firm could unilaterally restrict output to spawn supracompetitive prices. Having established a well controlled data set with price spikes paralleling those observed in the naturally occurring economy, we also extend the design to include demand-side bidding. We find that demand-side bidding completely neutralizes the exercise of market power and eliminates price spikes even in the presence of structural market power.
Furusawa, Ken; Sugihara, Hideharu; Tsuji, Kiichiro
Opened wholesale electric power market in April 2005, deregulation of electric power industry in Japan has faced a new competitive environment. In the new environment, Independent Power Producer (: IPP), Power Producer and Supplier (: PPS), Load Service Entity (: LSE) and electric utility can trade electric energy through both bilateral contracts and single-price auction at the electricity market. In general, the market clearing price (: MCP) is largely changed by amount of total load demand in the market. The influence may cause price spike, and consequently the volatility of MCP will make LSEs and their customers to face a risk of revenue and cost. DSM is attracted as a means of load leveling, and has effect on decreasing MCP at peak load period. Introducing Energy Storage systems (: ES) is one of DSM in order to change demand profile at customer-side. In case that customers decrease their own demand at jumped MCP, a bidding strategy of generating companies may be changed their strategy. As a result, MCP is changed through such complex mechanism. In this paper the authors evaluate MCP by multi-agent. It is considered that customer-side ES has an effect on MCP fluctuation. Through numerical examples, this paper evaluates the influence on MCP by controlling customer-side ES corresponding to variation of MCP.
Energy Technology Data Exchange (ETDEWEB)
Johnson Controls [Comision Federal de Electricidad (Mexico)
2005-07-01
Administrative measures allow a reduction in the energy consumption, but not always in the electrical demand. Control measures allow a reduction in the billing of the electrical demand, but not always in the energy consumption. This is why it is explained in this document what management and control of the electrical demand is, as well as its control strategies, the control alternatives, the billing demand and at the same time graphical representations along with three practical cases on the management of demand in air compressors, air conditioning equipment and in corporative buildings are presented. [Spanish] La aplicacion de las medidas administrativas permite reducir el consumo de energia, pero no siempre la demanda electrica. La aplicacion de medidas de control permiten reducir la demanda electrica facturable, pero no siempre el consumo de energia. Es por eso que en este documento se explica que es la administracion y el control de la demanda electrica, sus estrategias de control, las alternativas de control, la demanda facturable, representaciones graficas y tres casos practicos sobre la administracion de demanda en compresores de aire, la administracion de demanda en aire acondicionado y la administracion de demanda en un edificio corporativo.
Electric power monthly, June 1998, with data for March 1998
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-06-01
The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the State, Census division, and Us levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity retail sales, associated revenue, and average revenue per kilowatthour of electricity sold. In addition, data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source; consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. 5 refs., 57 tabs.
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.
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)
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
Kahl, Annelen; Dujardin, Jérôme; Dupuis, Sonia; Lehning, Michael
2017-04-01
One of the major problems with solar PV in the context of a fully renewable electricity production at mid-latitudes is the trend of higher production in summer and lower production in winter. This trend is most often exactly opposite to demand patterns, causing a seasonal mismatch that requires extensive balancing power from other production sources or large storage capacities. Which possibilities do we have to bring PV production into closer correlation with demand? This question motivated our research and in response we investigated the effects of placing PV panels at different tilt angles in regions with extensive snow cover to increase winter production from ground reflected short wave radiation. The aim of this project is therefore to quantify the effect of varying snow cover duration (SCD) and of panel tilt angle on the annual total production and on production during winter months when electricity is most needed. We chose Switzerland as ideal test site, because it has a wide range of snow cover conditions and a high potential for renewable electricity production. But methods can be applied to other regions of comparable conditions for snow cover and irradiance. Our analysis can be separated into two steps: 1. A systematic, GIS and satellite-based analysis for all of Switzerland: We use time series of satellite-derived irradiance, and snow cover characteristics together with land surface cover types and elevation information to quantify the environmental conditions and to estimate potential production and ideal tilt angles. 2. A scenario-based analysis that contrasts the production patterns of different placement scenarios for PV panels in urban, rural and mountainous areas. We invoke a model of a fully renewable electricity system (including Switzerland's large hydropower system) at national level to compute the electricity import and storage capacity that will be required to balance the remaining mismatch between production and demand to further illuminate
A weather regime characterisation of Irish wind generation and electricity demand in winters 2009–11
Cradden, Lucy C.; McDermott, Frank
2018-05-01
Prolonged cold spells were experienced in Ireland in the winters of 2009–10 and 2010–11, and electricity demand was relatively high at these times, whilst wind generation capacity factors were low. Such situations can cause difficulties for an electricity system with a high dependence on wind energy. Studying the atmospheric conditions associated with these two winters offers insights into the large-scale drivers for cold, calm spells, and helps to evaluate if they are rare events over the long-term. The influence of particular atmospheric patterns on coincidental winter wind generation and weather-related electricity demand is investigated here, with a focus on blocking in the North Atlantic/European sector. The occurrences of such patterns in the 2009–10 and 2010–11 winters are examined, and 2010–11 in particular was found to be unusual in a long-term context. The results are discussed in terms of the relevance to long-term planning and investment in the electricity system.
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.
International Nuclear Information System (INIS)
Günay, M. Erdem
2016-01-01
In this work, the annual gross electricity demand of Turkey was modeled by multiple linear regression and artificial neural networks as a function population, gross domestic product per capita, inflation percentage, unemployment percentage, average summer temperature and average winter temperature. Among these, the unemployment percentage and the average winter temperature were found to be insignificant to determine the demand for the years between 1975 and 2013. Next, the future values of the statistically significant variables were predicted by time series ANN models, and these were simulated in a multilayer perceptron ANN model to forecast the future annual electricity demand. The results were validated with a very high accuracy for the years that the electricity demand was known (2007–2013), and they were also superior to the official predictions (done by Ministry of Energy and Natural Resources of Turkey). The model was then used to forecast the annual gross electricity demand for the future years, and it was found that, the demand will be doubled reaching about 460 TW h in the year 2028. Finally, it was concluded that the approach applied in this work can easily be implemented for other countries to make accurate predictions for the future. - Highlights: • Electricity demand of Turkey increased from 15.6 to 246.4 TW h in 1975–2013 period. • Population, GDP per capita, inflation and average summer temperature influence demand. • Future values of descriptor variables can be predicted by time series ANN models. • ANN model simulated by the predicted values of descriptors can forecast the demand. • Demand is forecasted to be doubled reaching about 460 TW h in the year 2028.
Demand side management in recycling and electricity retail pricing
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
International Nuclear Information System (INIS)
Suharta, Herliyani; Hoetman, A. R.; Sayigh, A. m.
2006-01-01
The paper describe the evaluation of conventional energy usage and electricity condition in Indonesia. Also there is discussion on 14 facts that will affect the security in providing the electricity and other house hold energy demand. Those covers a picture of the growth of energy demand, oil subsidy, limited and remaining natural resources, crude petroleum export and import projection, forecast of un-risk natural gas production, gas and coal for electric generation, declining of coal deposit. An effort and considerations to increase the use of renewable energy (RE) are also described. It covers a power plant selection to mach the RE resources to partly fulfill the electricity development planning, its electricity price and also the use of RE resources to fulfill the energy need in household.(Author)
International Nuclear Information System (INIS)
Flues, Florens; Löschel, Andreas; Lutz, Benjamin Johannes; Schenker, Oliver
2014-01-01
The European Union's current climate and energy policy has to operate under an ex ante unforeseen economic crisis. As a consequence prices for carbon emission allowances in the EU Emissions Trading System collapsed. However, this price collapse may be amplified by the interaction of a carbon emission cap with supplementary policy targets such as minimum shares for renewables in the power sector. The static interaction between climate and renewable policies has been discussed extensively. This paper extends this debate by analysing the efficiency and effectiveness of a policy portfolio containing a cap and trade scheme and a target for a minimum renewable share in different states of aggregate electricity demand. Making use of a simple partial equilibrium model of the power sector we identify an asymmetric interaction of emissions trading and renewable quotas with respect to different states of aggregate electricity demand. The results imply that unintended consequences of the policy interaction may be particularly severe and costly when aggregate electricity demand is low and that carbon prices are more sensitive to changes in economic activity if they are applied in combination with renewable energy targets. Our analysis of the policy interaction focuses on the EU, yet the conclusions may also be of relevance for fast growing emerging economies like China. - Highlights: • A minimum renewable quota that is added to an existing emissions trading system causes excess costs. • Excess costs depend on electricity demand and are highest when electricity demand is low. • Excess costs can reach up to 1.2 Billion Euro annually in the European Union in 2030. • CO 2 prices are more sensitive to changes in electricity demand if combined with minimum renewable quota
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.
Tegen, Suzanne Isabel Helmholz
This dissertation introduces new techniques for calculating and comparing statewide economic impacts from new coal, natural gas and wind power plants, as well as from demand-side management programs. The impetus for this work was two-fold. First, reviews of current literature and projects revealed that there was no standard way to estimate statewide economic impacts from new supply- and demand-side electricity options. Second, decision-makers who were interviewed stated that they were overwhelmed with data in general, but also lacked enough specific information about economic development impacts to their states from electricity, to make informed choices. This dissertation includes chapters on electricity decision-making and on economic impacts from supply and demand. The supply chapter compares different electricity options in three states which vary in natural resource content: Arizona, Colorado and Michigan. To account for differing capacity factors, resources are compared on a per-megawatt-hour basis. The calculations of economic impacts from new supply include: materials and labor for construction, operations, maintenance, fuel extraction, fuel transport, as well as property tax, financing and landowner revenues. The demand-side chapter compares residential, commercial and industrial programs in Iowa. Impact calculations include: incremental labor and materials for program planning, installation and operations, as well as sales taxes and electricity saved. Results from supply-side calculations in the three states analyzed indicate that adding new wind power can have a greater impact to a state's economy than adding new gas or coal power due to resource location, taxes and infrastructure. Additionally, demand-side management programs have a higher relative percentage of in-state dollar flow than supply-side solutions, though demand-side programs typically involve fewer MWh and dollars than supply-side generation. Methods for this dissertation include researching
The electricity supply-demand balance for the winter of 2015-2016. Synthesis - November 2015
International Nuclear Information System (INIS)
2015-11-01
Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the winter of 2015-2016
Dynamics of electricity supply and demand in Kerala: a macro econometric analysis
Energy Technology Data Exchange (ETDEWEB)
Pillai, P P
1981-01-01
Kerala has the reputation of being a surplus state in electricity, but per capita consumption (at 76 kWh compared to 130 kWh for Tamil Nadu during the same period) is one of the lowest in India. The state ranks only seventh in terms of installed capacity and is lower than the overall average of 32.12 MW per million of population. Industrial and technological development will mean that supply will be inadequate, and Kerala will have to import electricity unless corrective measures are taken. Abundant hydro-electric sources provide the state with non-polluting and inexpensive power as well as irrigation. This source must be maximized as the state promotes industry and raises its standard of living. This book analyzes Kerala's electricity supply, system efficiency, future demand, rural electrification programs, and economic development, and makes several recommendations for planning and implementing an increase in power production. 13 references, 1 figures, 34 tables.
International Nuclear Information System (INIS)
Andrenacci, N.; Ragona, R.; Valenti, G.
2016-01-01
Highlights: • A demand-side approach to the location of charging infrastructure problem is discussed in the paper. • The analysis is based on a large data-set of private vehicle travels within the urban area of Rome. • Cluster analysis is applied to the data to find the optimal location zones for charging infrastructures. • The daily energy demand and the average number of users per day are calculated for each and every charging infrastructure. - Abstract: Despite all the acknowledged advantages in terms of environmental impact reduction, energy efficiency and noise reduction, the electric mobility market is below expectations. In fact, electric vehicles have limitations that pose several important challenges for achieving a sustainable mobility system: among them, the availability of an adequate charging infrastructure is recognized as a fundamental requirement and appropriate approaches to optimize public and private investments in this field are to be delineated. In this paper we consider actual data on conventional private vehicle usage in the urban area of Rome to carry out a strategy for the optimal allocation of charging infrastructures into portions (subareas) of the urban area, based on an analysis of a driver sample under the assumption of a complete switch to an equivalent fleet of electric vehicles. Moreover, the energy requirement for each one of the subareas is estimated in terms of the electric energy used by the equivalent fleet of electric vehicles to reach their destination. The model can be easily generalized to other problems regarding facility allocation based on user demand.
Province gets serious about demand management
International Nuclear Information System (INIS)
Anon
2003-01-01
Directives from the Minister to the Ontario Energy Board to review options for demand-side management and demand reduction activities, and discussion papers describing the policy framework needed to implement demand management, are indications of renewed interest by the provincial government in demand-side management of Ontario's electric power supply. This renewed interest comes on the hills of a 5.5 per cent increase in electricity use, a 33 per cent increase in imports, and consumption records broken in 10 of the last 12 months. A 117-page study was released in April by Navigant Consulting, entitled 'Demand response blueprint for Ontario' which estimates that if the Ontario market had 250 MW of additional demand response, customers providing the demand response would have saved $20 million by reducing their demand when HOEP was greater than $120/MWh, while other customers would have saved $170 million due to lower HOEP, and would have enjoyed greater reliability as a result of the increase in reserve margins. Other than price signals to induce customers to save, the Navigant report suggest paying customers not to consume during peak periods. The report estimates that such a policy could generate a total demand response of 350 MW and a $235 million reduction in revenue to generators. The Navigan report also includes a large number of detailed analysis and recommendations. One among them is for the extensive use of interval meters for customers with loads over 200 kW. The report tends to be critical of the recent price freeze ordered by the Ontario government, claiming that the freeze could increase consumption, making prices more volatile and increasing the cost to the government even more. Successful demand response programs from California, New York and the New England states are cited as examples for Ontario to emulate
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...
What is the Impact of Utility Demand Charges on a DCFC host
International Nuclear Information System (INIS)
Francfort, James Edward
2015-01-01
The PEV Electric Vehicle Supply Equipment (EVSE) delivered by The EV Project included both AC Level 2 and DCFC units. Over 100 of these dual-port Blink DC fast chargers were deployed by The EV Project. These DCFCs were installed in workplaces and in publicly accessible locations near traffic hubs, retail centers, parking lots, restaurants, and similar locations. The Blink DCFC is capable of charging at power up to 60 kW. Its dual-port design sequences the charge from one port to the other, delivering power to only one of two vehicles connected at a time. The actual power delivered through a port is determined by the PEV's on-board battery management system (BMS). Both the power and the total energy used to recharge a PEV can represent a significant cost for the charging site host. Many electric utilities impose fees for power demand as part of their commercial rate structure. The demand charge incurred by a customer is related to the peak power used during a monthly billing cycle. This is in contrast to the cumulative total energy usage that is the more familiar utility charge seen for most residential services. A demand charge is typically assessed for the highest average power over any 15 minute interval during the monthly billing cycle. One objective of The EV Project was to identify and elucidate the motivations and barriers to potential DCFC site hosts. The application of electric utility demand charges is one such potential barrier. This subject was introduced in the paper: DC Fast Charge - Demand Charge Reduction1. It discussed demand charge impact in general terms in order to focus on potential mitigation actions. This paper identifies specific cases in order to quantify the impact of demand charges on EV Project DCFC hosts.
What is the Impact of Utility Demand Charges on a DCFC host
Energy Technology Data Exchange (ETDEWEB)
Francfort, James Edward [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-06-01
The PEV Electric Vehicle Supply Equipment (EVSE) delivered by The EV Project included both AC Level 2 and DCFC units. Over 100 of these dual-port Blink DC fast chargers were deployed by The EV Project. These DCFCs were installed in workplaces and in publicly accessible locations near traffic hubs, retail centers, parking lots, restaurants, and similar locations. The Blink DCFC is capable of charging at power up to 60 kW. Its dual-port design sequences the charge from one port to the other, delivering power to only one of two vehicles connected at a time. The actual power delivered through a port is determined by the PEV’s on-board battery management system (BMS). Both the power and the total energy used to recharge a PEV can represent a significant cost for the charging site host. Many electric utilities impose fees for power demand as part of their commercial rate structure. The demand charge incurred by a customer is related to the peak power used during a monthly billing cycle. This is in contrast to the cumulative total energy usage that is the more familiar utility charge seen for most residential services. A demand charge is typically assessed for the highest average power over any 15 minute interval during the monthly billing cycle. One objective of The EV Project was to identify and elucidate the motivations and barriers to potential DCFC site hosts. The application of electric utility demand charges is one such potential barrier. This subject was introduced in the paper: DC Fast Charge - Demand Charge Reduction1. It discussed demand charge impact in general terms in order to focus on potential mitigation actions. This paper identifies specific cases in order to quantify the impact of demand charges on EV Project DCFC hosts.
Regional electric power demand elasticities of Japan's industrial and commercial sectors
International Nuclear Information System (INIS)
Hosoe, Nobuhiro; Akiyama, Shu-ichi
2009-01-01
In the assessment and review of regulatory reforms in the electric power market, price elasticity is one of the most important parameters that characterize the market. However, price elasticity has seldom been estimated in Japan; instead, it has been assumed to be as small as 0.1 or 0 without proper examination of the empirical validity of such a priori assumptions. We estimated the regional power demand functions for nine regions, in order to quantify the elasticity, and found the short-run price elasticity to be 0.09-0.30 and the long-run price elasticity to be 0.12-0.56. Inter-regional comparison of our estimation results suggests that price elasticity in rural regions is larger than that in urban regions. Popular assumptions of small elasticity of 0.1, for example, could be suitable for examining Japan's aggregate power demand but not power demand functions that focus on respective regions. Furthermore, assumptions about smaller elasticity values such as 0.01 and 0 could not be supported statistically by this study.
Directory of Open Access Journals (Sweden)
Chi-Chun Lo
2016-02-01
Full Text Available This paper presents an optimal dispatch model of an ice storage air-conditioning system for participants to quickly and accurately perform energy saving and demand response, and to avoid the over contact with electricity price peak. The schedule planning for an ice storage air-conditioning system of demand response is mainly to transfer energy consumption from the peak load to the partial-peak or off-peak load. Least Squares Regression (LSR is used to obtain the polynomial function for the cooling capacity and the cost of power consumption with a real ice storage air-conditioning system. Based on the dynamic electricity pricing, the requirements of cooling loads, and all technical constraints, the dispatch model of the ice-storage air-conditioning system is formulated to minimize the operation cost. The Improved Ripple Bee Swarm Optimization (IRBSO algorithm is proposed to solve the dispatch model of the ice storage air-conditioning system in a daily schedule on summer. Simulation results indicate that reasonable solutions provide a practical and flexible framework allowing the demand response of ice storage air-conditioning systems to demonstrate the optimization of its energy savings and operational efficiency and offering greater energy efficiency.
Forward-looking report of the electricity supply-demand balance in France. 2011
International Nuclear Information System (INIS)
2011-01-01
After an introduction presenting the objective of this report and the method used for its predictions, this document proposes an analysis of energy consumption: past trends, context of predictions, building up of predictions, global predictions, impact of demand control, comparison with a previous forward-looking assessment, comparison with other scenarios and other European countries. It analyses and discusses power consumption predictions (electricity consumption time variations, load curve evolution perspectives, peak power), production supply (current stock, thermal nuclear, thermal fossil, thermal decentralized, hydroelectric, wind energy, and photovoltaic production), the evolution of the supply-demand balance on a medium term for France and for two French regions. It finally proposes a long term prospective vision regarding energy
Pricing of electricity in Indonesia
International Nuclear Information System (INIS)
Amarullah, M.
1983-01-01
The objectives of this study are 1) to establish a sound theoretical basis for the determinants of electricity demand in Indonesia, 2) to measure the welfare losses of existing electricity pricing, and 3) to suggest a method of reducing these welfare losses. An econometric model for electricity demand is estimated using pooled time-series of fifteen regions in Indonesia covering the period 1970-1979. The short run price elasticities for both residential and industrial/business sectors are found to be inelastic, while the long run price elasticities for these sectors are found to be quite elastic with a value of -.61 for the residential sector and of -1.1 for the industrial/business sector. Income elasticity is .8 in the short run and around 1.00 for the long run. The exposure variable that captures the accessibility of electricity, has long run elasticity of 1.00 for the residential sector and less than 1.00 for the industrial/business sector. Due to distributional considerations, the 1980's electricity rate was set below its efficient level, and has created a welfare loss of Rp.8273.23 million per month. This accounts for 36.03% of the monthly electricity revenue. A rebate mechanism is recommended in this study, which provides a way to mitigate conflicting aspects of efficiency and equity
International Nuclear Information System (INIS)
2008-05-01
Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the summer of 2008
Modeling Demand Response in Electricity Retail Markets as a Stackelberg Game
DEFF Research Database (Denmark)
Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre
We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price-sequence, w......We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price...... with Equilibrium Constraints (MPEC) and cast as a Mixed Integer Linear Program (MILP), which can be solved using off-the-shelf optimization software. In an illustrative example, we consider a retailer associated with both flexible demand and wind power production. Such an example shows the efficiency of dynamic...
A high-resolution stochastic model of domestic activity patterns and electricity demand
International Nuclear Information System (INIS)
Widen, Joakim; Waeckelgard, Ewa
2010-01-01
Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings' indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.
International Nuclear Information System (INIS)
Askarzadeh, Alireza
2014-01-01
The importance of energy demand estimation stems from energy planning, formulating strategies and recommending energy policies. Most often, energy demand is mathematically formulated by socio-economic indicators. The challenging problem is to determine the optimal or near optimal weighting factors. Inspired by social behavior of bird flocking or fish schooling, PSO (particle swarm optimization) is a population-based search technique which has attracted significant attention to tackle the complexity of difficult optimization problems. This paper studies the performance of different PSO variants for estimating Iran's electricity demand. Seven PSO variants namely, original PSO, PSO-w (PSO with weighting factor), PSO-cf (PSO with constriction factor), PSO-rf (PSO with repulsion factor), PSO-vc (PSO with velocity control), CLPSO (comprehensive learning PSO) and a MPSO (modified PSO), are used to find the unknown weighting factors based on the data from 1982 to 2003. The validation process is then conducted by testing the optimized models by using the data from 2004 to 2009. It is seen that PSO-vc produces more promising results than the other variants, HS (harmony search) and ABSO (artificial bee swarm optimization) algorithms in terms of MAPE (mean absolute percentage error). This value is obtained 2.47 and 2.50 for the exponential and quadratic models, respectively. - Highlights: • Electricity demand estimation is modelled using socio-economic indicators. • Different PSO variants are investigated in terms of accuracy. • Exponential model can estimate the Iran's electricity demand with high accuracy. • PSO with velocity control produces more accurate result than the others
Nair, Madhavan; Guduru, Rakesh; Liang, Ping; Hong, Jeongmin; Sagar, Vidya; Khizroev, Sakhrat
2013-01-01
Although highly active anti-retroviral therapy has resulted in remarkable decline in the morbidity and mortality in AIDS patients, inadequately low delivery of anti-retroviral drugs across the blood-brain barrier results in virus persistence. The capability of high-efficacy-targeted drug delivery and on-demand release remains a formidable task. Here we report an in vitro study to demonstrate the on-demand release of azidothymidine 5'-triphosphate, an anti-human immunodeficiency virus drug, from 30 nm CoFe2O4@BaTiO3 magneto-electric nanoparticles by applying a low alternating current magnetic field. Magneto-electric nanoparticles as field-controlled drug carriers offer a unique capability of field-triggered release after crossing the blood-brain barrier. Owing to the intrinsic magnetoelectricity, these nanoparticles can couple external magnetic fields with the electric forces in drug-carrier bonds to enable remotely controlled delivery without exploiting heat. Functional and structural integrity of the drug after the release was confirmed in in vitro experiments with human immunodeficiency virus-infected cells and through atomic force microscopy, spectrophotometry, Fourier transform infrared and mass spectrometry studies.
How to Estimate Demand Charge Savings from PV on Commercial Buildings
Energy Technology Data Exchange (ETDEWEB)
Gagnon, Pieter J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bird, Lori A [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-09-28
Rooftop photovoltaic (PV) systems are compensated through retail electricity tariffs - and for commercial and industrial customers, these are typically comprised of three components: a fixed monthly charge, energy charges, and demand charges. Of these, PV's ability to reduce demand charges has traditionally been the most difficult to estimate. In this fact sheet we explain the basics of demand charges, and provide a new method that a potential customer or PV developer can use to estimate a range of potential demand charge savings for a proposed PV system. These savings can then be added to other project cash flows, in assessing the project's financial performance.
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
Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models
Energy Technology Data Exchange (ETDEWEB)
Pappas, S.S. [Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi, 83 200 Samos (Greece); Ekonomou, L.; Chatzarakis, G.E. [Department of Electrical Engineering Educators, ASPETE - School of Pedagogical and Technological Education, N. Heraklion, 141 21 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24100 Kalamata (Greece); Katsikas, S.K. [Department of Technology Education and Digital Systems, University of Piraeus, 150 Androutsou Srt., 18 532 Piraeus (Greece); Liatsis, P. [Division of Electrical Electronic and Information Engineering, School of Engineering and Mathematical Sciences, Information and Biomedical Engineering Centre, City University, Northampton Square, London EC1V 0HB (United Kingdom)
2008-09-15
This study addresses the problem of modeling the electricity demand loads in Greece. The provided actual load data is deseasonilized and an AutoRegressive Moving Average (ARMA) model is fitted on the data off-line, using the Akaike Corrected Information Criterion (AICC). The developed model fits the data in a successful manner. Difficulties occur when the provided data includes noise or errors and also when an on-line/adaptive modeling is required. In both cases and under the assumption that the provided data can be represented by an ARMA model, simultaneous order and parameter estimation of ARMA models under the presence of noise are performed. The produced results indicate that the proposed method, which is based on the multi-model partitioning theory, tackles successfully the studied problem. For validation purposes the produced results are compared with three other established order selection criteria, namely AICC, Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The developed model could be useful in the studies that concern electricity consumption and electricity prices forecasts. (author)
Grid-tied photovoltaic and battery storage systems with Malaysian electricity tariff
DEFF Research Database (Denmark)
Subramani, Gopinath; Ramachandaramurthy, Vigna K.; Padmanaban, Sanjeevikumar
2017-01-01
Under the current energy sector framework of electricity tariff in Malaysia, commercial and industrial customers are required to pay the maximum demand (MD) charge apart from the net consumption charges every month. The maximum demand charge will contribute up to 20% of the electricity bill......, and will hence result in commercial and industrial customers focussing on alternative energy supply to minimize the billing cost. This paper aims to review the technical assessment methods of a grid-connected solar photovoltaic (PV)-battery storage system-with respect to maximum demand shaving. An effective......, technical, and economic aspects of the solar PV-battery system and the Malaysian electricity tariff for commercial and industrial customers....
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.
Energy Technology Data Exchange (ETDEWEB)
Sakamoto, S. [Kansai Electric Power Co. Inc., Osaka (Japan)
1997-10-10
Kansai Electric Power has developed a system which reads the demand data for 30min. stored in the compound demand meter for power supply/demand (CDM), and prints the load curves. It is for customers of high-voltage power of less than 500kW, where load management is less extensive than that in larger users, for initial consulting on improvement of load factor (recommendation of heat storage contracts). It is to be installed on the spot to display the load curves, to allow the expert visiting the site to issue initial proposals immediately. It displays `daily demands by time zone` instead of `monthly power consumption` previously provided, and makes the graph of demands by time zone. It is designed to be compact, light, and easily and safely handled. The field test results indicate that the system can be sufficiently practical with the major performance items. 4 figs., 1 tab.
International Nuclear Information System (INIS)
Battke, Benedikt; Schmidt, Tobias S.
2015-01-01
Highlights: • A definition of multi-purpose technologies (MPTs) is proposed. • Opportunities for a cost-efficient demand-pull policy strategy for MPTs are derived. • The multi-purpose character of stationary electricity storage (SES) is shown. • An exemplary profitability assessment of one SES technology supports the argument. - Abstract: Stationary electricity storage technologies (SES) allow to increase the shares of intermittent renewable energy technologies in electricity networks. As SES currently exhibit high costs, policy makers have started introducing demand-pull policies in order to foster their diffusion and drive these technologies further down the learning curve. However, as observed in the case of renewable energy technologies, demand-pull policies for technologies can come at high costs in cases where the profitability gap that needs to be covered by the policy support is large. Yet, SES can create value in multiple distinct applications in the power system – making it a “multi-purpose technology”. We argue that policy makers can make use of the multi-purpose character of SES to limit costs of demand-pull policies. We propose a policy strategy which grants support based on the profitability gap in the different applications, thereby moving down the learning curve efficiently. To support our argumentation, we firstly conduct a comprehensive literature review of SES applications exemplifying the multi-purpose character of these technologies. Second, we assess the profitability of one SES technology (vanadium redox flow battery) in five SES applications, highlighting a strong variation of the profitability gap across these applications
International Nuclear Information System (INIS)
Morais, H.; Sousa, T.; Soares, J.; Faria, P.; Vale, Z.
2015-01-01
Highlights: • Definition fuel shifting demand response programs applied to the electric vehicles. • Integration of the proposed fuel shifting in energy resource management algorithm. • Analysis of fuel shifting contribution to support the consumption increasing. • Analysis of fuel shifting contribution to support the electric vehicles growing. • Sensitivity analysis considering different electric vehicles penetration levels. - Abstract: In the smart grids context, distributed energy resources management plays an important role in the power systems’ operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important to develop adequate methodologies to schedule the electric vehicles’ charge and discharge processes, avoiding network congestions and providing ancillary services. This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting into the network. These programs are included in an energy resources management algorithm which integrates the management of other resources. The paper presents a case study considering a 37-bus distribution network with 25 distributed generators, 1908 consumers, and 2430 plug-in vehicles. Two scenarios are tested, namely a scenario with high photovoltaic generation, and a scenario without photovoltaic generation. A sensitivity analyses is performed in order to evaluate when each energy resource is required
International Nuclear Information System (INIS)
Lee, Y. E.; Chang, H. S.
2011-01-01
Only 12 of 54 nuclear reactors are in operation as of September 1, 2011 in the wake of the earthquake and tsunami in Japan. The share of nuclear power in the nation's installation capacity fell to about 14% in August from about 30% before March 11, 2011. Government or many of research institutes estimated that the power supply system in Japan would fall to the minus reserve margin, if the nuclear power stations could not be restarted as scheduled. However, the current situation of power supply system in Japan is less severe than expected before, because the power companies and public have engaged in various diligent efforts to boost supply capacity or reduce demand in response to the electric power crisis. This paper aims to analyze the how much Japan electric power supply system depends on the nuclear power, what kinds of countermeasures of electric power supply-demand are taken by electricity companies in summer time to avoid the blackouts and why the saving electricity in Japan could be possible unlike Korea. Insights from this paper would be taken into account in the long term energy planning, even though the further study in depth should be followed
Directory of Open Access Journals (Sweden)
Peng Wang
2018-06-01
Full Text Available Reasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%. Different key performance indicators (KPI differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML produces the optimal power development path, as it provides the lowest discounted cost.
International Nuclear Information System (INIS)
Syed, F.; Fowler, M.; Wan, D.; Maniyali, Y.
2009-01-01
This paper details the development of an energy demand model for a hydrogen-electric vehicle fleet and the modelling of the fleet interactions with a clean energy hub. The approach taken is to model the architecture and daily operation of every individual vehicle in the fleet. A generic architecture was developed based on understanding gained from existing detailed models used in vehicle powertrain design, with daily operation divided into two periods: charging and travelling. During the charging period, the vehicle charges its Electricity Storage System (ESS) and refills its Hydrogen Storage System (HSS), and during the travelling period, the vehicle depletes the ESS and HSS based on distance travelled. Daily travel distance is generated by a stochastic model and is considered an input to the fleet model. The modelling of a clean energy hub is also presented. The clean energy hub functions as an interface between electricity supply and the energy demand (i.e. hydrogen and electricity) of the vehicle fleet. Finally, a sample case is presented to demonstrate the use of the fleet model and its implications on clean energy hub sizing. (author)