Determining the responsibility of manufacturing sectors regarding electricity consumption. The Spanish case

The aim of this paper is to develop a methodology based on the input-output approach which allows us to identify the structural and technological responsibility of manufacturing sectors in electricity consumption. Sectors with a high structural responsibility are those whose products are strongly demanded by other sectors and this leads to a high electricity consumption/production. Sectors with a high technological responsibility are those whose technologies use inputs which directly or indirectly require much electricity independently of the composition of final demand in the economy. This methodology is applied to the manufacturing sectors in Spain. It is found out that the chemical sector and industries manufacturing metal products have a large structural responsibility, but their technological responsibility is low. In contrast, the mineral (non-metallic) sectors form a cluster of industries with a high technological responsibility.     

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.     

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.     

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.     

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.     

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.     

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.     

Reductions in electricity consumption and power demand in case of the mass use of compact fluorescent lamps

The paper presents a general methodology for the evaluation of the reduction in electricity consumption and its market value, as well as the reduction of the peak power demand in case of the mass use of compact fluorescent lamps (CFLs), illustrated on the Serbian power system. The evaluation was based on the assumption that the two most used incandescent lamps in each of 25–50% of the total number of dwellings in Serbia will be replaced with adequate CFLs, and that the same total number of lamps will be replaced in residential and non-residential sectors. The daily diagrams of the total electrical power demand in Serbia for days with the maximum and minimum yearly peak loads are presented and compared with the corresponding daily diagrams which took into account the planned lamp replacement and the coincidence factors (CFs) for the observed lamps, which in case of the residential sector are obtained by on-site monitoring of 344 dwellings. It was shown that, in order to precisely calculate the cost-effectiveness of the planned action, decrease of electricity consumption has to be calculated for each hour, because the electricity cost rate (ECR) usually changes on an hourly basis.     

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.     

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.     

江西省电力需求预算与邻省的比较研究

本文通过对江西省周边发达省份过去和现在的国民经济发展和能源消费情况的研究,利用横向比较法来校核江西省电量预测的结果和数学模型。     

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.     

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.     

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

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.     

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

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.     

Assessing the influence of manufacturing sectors on electricity demand. A cross-country input-output approach

The production and consumption of electricity is a major source of CO₂ 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.     

Plug-in hybrid electric vehicle impacts on hourly electricity demand in the United States

In this study we explore the effects of different charging behaviors of PHEVs in the United States on electricity demand profiles and energy use, in terms of time of day and location (at home, the workplace, or public areas). Based on driving behavior statistics on vehicle distance traveled and daily trips (US DOT, 2003) in the US, we develop a simulation algorithm to estimate the PHEV charging profiles of electricity demand with plausible plug-in times and depth of discharge of the PHEVs.     

The effects of electricity pricing on PHEV competitiveness

Plug-in hybrid electric vehicles (PHEVs) will soon start to be introduced into the transportation sector, thereby raising a host of issues related to their use, adoption and effects on the electricity sector. Their introduction has the potential to significantly reduce carbon emissions from the transportation sector, which has led to government policies aimed at easing their introduction. If their widespread adoption is set as a target it is imperative to consider the effects of existing policies that may increase or decrease their adoption rate. In this study, we present a micro level electricity demand model that can gauge the effects of PHEVs on household electricity consumption and the subsequent economic attractiveness of the vehicles. We show that the electricity pricing policy available to the consumer is a very significant factor in the economic competitiveness of PHEVs. Further analysis shows that the increasing tier electricity pricing system used in California will substantially blunt adoption of PHEVs in the state; and time of use electricity pricing will render PHEVs more economically attractive in any state.     

How do energy & environmental policy goals and instruments affect electricity demand? A framework for the analysis

Several measures in the environment and energy realms are currently being implemented in the EU and its Member States. Three of these instruments, with an impact on the electricity market, are demand side management activities, promotion of electricity from renewable energy sources and measures aimed at the mitigation of Greenhouse Gas (GHG) emissions. The objective of this paper is to analyse the impact of these energy efficiency and environmental goals and instruments on electricity demand and costs to electricity consumers when electricity markets are either national or international and when those policies are implemented by a national or an international institution. The paper shows that the effectiveness and impact of those measures largely depends on the demand response in the electricity market. An additional conclusion is that, when either the electricity markets or the support policies are national, distortions may occur, i.e. the reductions in electricity demand in one country may be subsidised by consumers or taxpayers in another country.     

The theory of maximum kW demand charges for electricity

The kilowatt (kW) demand charge characterizes most electricity price schedules for industrial customers, yet it has not been analysed thoroughly (compared with time-of-use rates). This article shows how such charges complicate interpretations of past estimates of the industrial demand for electricity. Using a utility maximization (cost minimization) model, we derive consistent demand curves, which are shown potentially to be subject to discontinuities.