Television peaks in electricity demand

This paper discusses the effect that breaks in television programmes have upon the demand for electricity. The results of a study which correlates the pattern of household electricity consumption with the timings of commercial and end-of-programme breaks are summarized. A theory of audience release is developed and various policy implications are explored.     

Electricity consumption forecasting in Italy using linear regression models

The influence of economic and demographic variables on the annual electricity consumption in Italy has been investigated with the intention to develop a long-term consumption forecasting model.The time period considered for the historical data is from 1970 to 2007. Different regression models were developed, using historical electricity consumption, gross domestic product (GDP), gross domestic product per capita (GDP per capita) and population.A first part of the paper considers the estimation of GDP, price and GDP per capita elasticities of domestic and non-domestic electricity consumption. The domestic and non-domestic short run price elasticities are found to be both approximately equal to −0.06, while long run elasticities are equal to −0.24 and −0.09, respectively. On the contrary, the elasticities of GDP and GDP per capita present higher values.In the second part of the paper, different regression models, based on co-integrated or stationary data, are presented. Different statistical tests are employed to check the validity of the proposed models.A comparison with national forecasts, based on complex econometric models, such as Markal-Time, was performed, showing that the developed regressions are congruent with the official projections, with deviations of ±1% for the best case and ±11% for the worst. These deviations are to be considered acceptable in relation to the time span taken into account.     

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

This study assesses the electricity demand pattern in the relatively temperate climate of the Netherlands (latitude 52°30′N). Daily electricity demand and average temperature during the period from 1970 until 2007 are investigated for possible trends in the temperature dependence of electricity demand. We hypothesize that the increased use of cooling applications has shifted the temperature dependence of electricity demand upwards in summer months. Our results show significant increases in temperature dependence of electricity demand in May, June, September, October and during the summer holidays. During the period studied, temperature dependence in these months has shifted from negative to positive, meaning that a higher temperature now leads to an increased electricity demand in these months, rather than a decreased demand as observed historically. Although electricity demand in countries with moderate summer temperatures such as the Netherlands generally peaks in winter months and shows a minimum in summer months, this trend may signal the development of an additional peak in summer, especially given the expected climatic change. As power generating capacity may be negatively influenced by higher temperatures due to decreasing process cooling possibilities, an increasing electricity demand at higher temperatures may have important consequences for power generation capacity planning and maintenance scheduling.     

Input-output table of electricity demand and its application

It is very important for electric utility to determine dominant sectors which have more impacts on electricity consumption in national economy system. In this paper, an input-output perspective and methodology is proposed to handle this issue. The input-output table of electricity demand (IOTED) is put forward based on the input-output table of national economy (IOTNE). The relevancy of electricity demand in various sectors is revealed by means of electricity consumption chains (ECCs), which are key components in the IOTED. Besides, a new concept, electricity demand multiplier (EDM), is presented to identify dominant sectors imposing great impacts on electricity demand quantitatively. In order to testify the effectiveness of the proposed methodology, a case based on provincial economy system in China is studied. Dominant sectors are identified and discussed.     

Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models

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.     

Natural gas demand in Turkey

On average, energy demand of Turkey is mounting by 8% annually, one of the highest rates in the world. Among primary energy sources, natural gas is the fastest growing one in Turkey. Gas consumption started at 0.5 bcm (billion cubic meters) in 1987 and reached approximately 35 bcm in 2007. Turkish natural gas usage is projected to further increase remarkably in coming years. The present paper focuses the characteristics of this demand and estimates short and long-run price and income elasticities of sectoral natural gas demand in Turkey. The future growth in this demand is also forecasted using an ARIMA modelling and the results are compared with official projections. The paper reveals that natural gas demand elasticities are quite low, meaning that consumers do not respond possible abusive price increases by decreasing their demand or substituting natural gas with other energy sources. Since consumers are prone to monopoly abuse by incumbent, there is a need for market regulation in Turkish natural gas market. Based on forecasts obtained, it is clear that the current official projections do not over/under-estimate natural gas demand although past official projections highly overestimated it.     

A seasonal hybrid procedure for electricity demand forecasting in China

Electricity is a special energy which is hard to store, so the electricity demand forecasting in China remains an important problem. This paper aims at developing an improved hybrid model for electricity demand in China, which takes the advantages of moving average procedure, combined method, hybrid model and adaptive particle swarm optimization algorithm, known as MA-C-WH. It is designed for making trend and seasonal adjustments which simultaneously presents the electricity demand forecasts. Four actual electricity demand time series in China power grids are selected to illustrate the proposed MA-C-WH model, and one existing seasonal autoregressive integrated moving average model (SARIMA) is selected to compare with the proposed model using the same data series. The results of popular forecasting precision indexes show that our proposed model is an effective forecasting technique for seasonal time series with nonlinear trend.     

Electricity consumption by battery-powered consumer electronics: A household-level survey

The rapid proliferation of battery-powered consumer electronics and their reliance on inefficient linear transformers has been suggested to be an important part of the rapid growth in “miscellaneous” electricity consumption in recent years, but detailed data are scarce. We conducted a survey of 34 randomly selected households (HHs) in Northern California about the number, type, and usage of consumer electronics. We also measured the energy consumption of 85 typical consumer electronic devices through various parts of the charge cycle. These primary data were supplemented by national sales information for consumer electronics. Results indicate that typical HHs own 8.4 rechargeable devices, which have a total average demand of 12–17 W per HH. Statewide, this amounts to 160–220 MW of demand, with the peak occurring in the late evening, and about 1600 GWh per year. Only about 15% of this energy is used for battery charging, the rest is lost as waste heat during no-load and charge maintenance periods. Technical options to increase the efficiency of these devices, and the research and policy steps needed to realize these savings are discussed.     

The distributed lag between electricity demand and price

This paper investigates the lagged relationship between electricity price changes and consumer response. It finds some evidence that price rises can induce rather long-term effects with detectable influence up to a decade. This tentative conclusion is important because it implies that recent increases may have a greater effect on future demand than is normally supposed.     

Modelling fuel demand for different socio-economic groups

The fuel demand literature provides a range of estimates of the long and short-run price and income elasticities of gasoline demand for different countries and states. These estimates can be very useful in predicting the overall impacts of policy approaches designed to reduce fuel consumption and to address concerns of carbon emissions or energy security. However, analysis of policy options based on elasticities that are homogenous across income groups provides no information about the relative distributional burden that may be faced by different sectors of the population. Different responses to the same change in price or income are likely to occur, dependent on both travel needs and income levels. This paper estimates gasoline demand elasticities for different income quintiles in the United States to test for heterogeneity in demand response. Group wise summary consumer expenditure data for 20 years is used to derive the elasticity estimates. The results show that the elasticities do vary across groups and follow a U-pattern from the lowest to the highest income quintile. The lowest income quintile is found to have the largest price elasticity. The lowest and the highest income quintiles appear to be statistically insensitive to any changes in income. The rebound effect also follows the U-pattern, with the highest rebound observed among the wealthiest households. Rural households appear to have lower price elasticity than households in urban areas.     

Aggregate electricity demand in South Africa: Conditional forecasts to 2030

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, tooAfter 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.     

The price elasticity of electricity demand in South Australia

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.     

Electricity demand price elasticity in China based on computable general equilibrium model analysis

Based on the CGE model, this paper simulates the impact of electricity price adjustment on demand for electricity, and the simulation results show the range of electricity elasticities of different consumers. The elasticities of the high power-consuming sectors are relatively larger. However, the absolute values of the price elasticities are less than one. Furthermore, this paper quantitatively analyses the price elasticity of different categories of users, which are classified according to the objectives of China’s electricity price reform. The elasticity absolute value of Industry & Commerce is around 0.018, that of Residents is around 0.300 and that of Agriculture is around 0.066. Finally, the price elasticities of different consumers in 2005 and 2007 are calculated through the CGE model, and it is discovered that the price elasticity absolute values in 2007 are less than that in 2005. The analytical results of this paper can provide corresponding support for the formulation of electricity pricing mechanisms for the developing countries.     

Estimation of residential electricity demand function in Seoul by correction for sample selection bias

This paper attempts to estimate the residential electricity demand function in Seoul. To this end, we collected the data from a survey of households in Seoul and employed the bivariate model to rectify the undesirable impacts of non-response data. The results show that the size of family, the size of house, dummy for having a plasma display panel television, dummy for having an air conditioner, and the household's income have positive relationships with the residential electricity demand. On the other hand, electricity price contributes negatively to the residential electricity demand. In addition, the price and income elasticities were estimated as −0.2463 and 0.0593, respectively, implying that residential electricity demand in Seoul is price- and income-inelastic. Such useful information is expected to help policy-makers regulate the residential electricity supply and predict the effect of the price on the residential electricity demand in the future.     

Electricity securitization in China

This paper discusses the past and the status quo of electricity securitization in China. First, the stranded cost securitization in American electricity industry and the ongoing securitization progress in emerging market countries are investigated, which enlightens the way of electricity securitization in China. Through analysis of electricity industry in China, the paper proposes constructive policy suggestions for regulators who intend to prompt securitization to develop electricity infrastructure, and detailed recommendations for companies who plan to raise money at reduced cost. It is concluded that even though it is at the very beginning stage in China, securitization not only provides financing for investment projects, but also speeds up the reform by stranded cost securitization, a novel idea for electricity industry in China.     

Electricity demand for South Korean residential sector

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.     

Grey prediction with rolling mechanism for electricity demand forecasting of Turkey

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.     

The demand for gasoline: a comment on the cross-section analysis by Drollas

A recent article [1] used data for 1977 from different countries to estimate the long-run price elasticity of demand for gasoline. Some aspects can be criticized, particularly the interpretation of the results and the model used. An alternative is developed which accepts that the key factor influencing gasoline consumption is the stock of cars. However, energy use per car will vary depending on the size of the country and its average income and price of fuel. This model gives a non-linear equation which is estimated using the same data. All the coefficients are significant with the price elasticity being inelastic.     

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

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.     

Turkey’s short-term gross annual electricity demand forecast by fuzzy logic approach

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.