Residential implementation of critical-peak pricing of electricity

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

Household consumption of electricity in Brazil between 1985 and 2013

This article describes the electricity consumption in Brazilian residences between 1985 and 2013 through linear regressions. The explanatory variables considered were the number of households, effective consumption of families as a proxy for family income, and electricity tariff for households. To deal with the power generation crisis of 2001 we have introduced a dummy variable in the form of a step function. With such explanatory variables, we were able to account for the reduction of household electricity consumption caused by the policies conducted in 2001 and their permanent consequences. The regression presented coefficient of determination of 0.9892, and the several statistic tests conducted assured the existence of long-term relation between the electricity consumption in residences and the explanatory variables. The obtained elasticities for the household consumption of electricity with respect to number of residences, family income and residential tariff of electricity were 1.534±0.095, 0.189±0.049, and −0.230±0.060, respectively. These results allowed understanding the evolution over time of the household consumption of electricity in Brazil. They suggest that the electric sector in Brazil should pursue an active policy to manage demand of residential electricity using tariffs as a means to control it.     

Residential response to critical-peak pricing of electricity: California evidence

This paper analyzes data from 483 households that took part in a critical-peak pricing (CPP) experiment between July and September 2004. Using a regression-based approach to quantify hourly baseline electric loads that would have occurred absent CPP events, we show a statistically significant average participant response in each hour. Average peak response estimates are provided for each of twelve experimental strata, by climate zone and building type. Results show that larger users respond more in both absolute and percentage terms, and customers in the coolest climate zone respond most as a percentage of their baseline load. Finally, an analysis involving the two different levels of critical-peak prices – $0.50/kWh and $0.68/kWh – indicates that households did not respond more to the higher CPP rate.     

Changes in industrial electricity consumption in china from 1998 to 2007

Electricity consumption in the industrial sector experienced a dramatic increase between 1998 and 2007, accounting for approximately 75% of China’s total electricity consumption. This study analyzes the potential factors influencing the growth of electricity consumption in China’s industrial sector over the past decade using a logarithmic mean Divisia index I decomposition method. Results show that activity effect and shift effect (caused by the change in the electricity’s share of industrial energy use) are the major factors responsible for the rise in electricity consumption between 1998 and 2007. It is found that structural change also contributed to the increase in electricity consumption, it had only a small effect. In contrast, the technological effect is responsible for a decrease in electricity consumption during this period. The influences of technological effects and shift effects followed approximately an inverse-U-shaped and U-shaped curve, respectively. Furthermore, the results show that the main contributors to incremental electricity consumption among industrial subsectors were manufacturing of raw chemical material and products, manufacturing of non-metal mineral products, smelting and pressing of ferrous and non-ferrous metals, and production and supply of electric power and heat power. These sectors should take priority for industrial restructuring in order to implement policies for energy and electricity savings.     

Effects of demand side management on Chinese household electricity consumption: Empirical findings from Chinese household survey

China’s residential electricity demand has grown rapidly over the last three decades and given the expected continued growth, demand side management (DSM) can play an important role in reducing electricity demand. By using micro-level data collected from 1450 households in 27 provinces in the first-ever China Residential Energy Consumption Survey in 2012, this study estimates the effects of three DSM measures empirically: tiered household electricity pricing, China Energy Label program, and information feedback mechanisms. We find these measures have contributed to moderating residential electricity demand growth but additional policy reform and tools are needed to increase their effectiveness and impact. Residential electricity demand is found to be price- and income- inelastic and tiered pricing alone may not be as effective in electricity conservation. The statistically significant relationship between China Energy Label efficient refrigerators - but not televisions - and lowered residential electricity consumption reflect mixed program effectiveness. Lastly, of the information feedback currently available through electricity bills, payment frequency and meters, only meter reader is estimated to be statistically significant. Important policy implications and recommendations for improving each of these three DSM measures to expand their impact on reducing residential electricity consumption are identified.     

Decomposition analysis of the variations in residential electricity consumption in Brazil for the 1980–2007 period: Measuring the activity,intensity and structure effects

Introduced at the end of the 1970s to study the impacts of structural changes on electricity consumption by industry, index decomposition analysis techniques have been extended to various other areas to help in the formulation of energy policies, notably in developed countries. However, few authors have applied these techniques to study the evolution of energy consumption in developing countries. In Brazil, the few available studies have focused only on the industrial sector. In this article, we apply the decomposition technique called the logarithmic mean Divisia index (LMDI) to electricity consumption of the Brazilian residential sector, to explain its evolution in terms of the activity, structure and intensity affects, over the period from 1980 to 2007. The technique is sufficiently robust and flexible to perform this analysis, by disaggregating residential consumers by consumption classes and regions of the country. Among the main results is measurement of the impact of government programs for income transfer and universal service on variations in residential consumption, typical of developing countries.     

Relationship between electricity consumption and economic growth of Guangdong Province in China

Guangdong is a province with the most electricity consumption (EC) and the fastest economic growth in China. However, there has long been a contradiction between electricity supply and demand in Guangdong and this trend may exist for a long time in the foreseeable future. Therefore, the research on the relationship between EC and economic growth of Guangdong is of very important practical significance to the formulation of relevant policy. In this paper, the econometrics method of granger causality test and co-integration test is used to analyze the relationship between EC and economic growth of Guangdong from 1978 to 2010. The results indicate that there is unidirectional causality between the economic growth and the EC, and the growth of gross domestic product (GDP) and gross industrial output value (GIOV) is the impetus to promote the growth of installedβcapacity (ICAP) and the EC. Therefore, the appropriate restraint of excessive growth of power industry will not necessarily slow down economic growth. There has been a long-term stable equilibrium relationship between the EC and the economic growth. When the GDP and GIOV grows 1 unit respectively, the EC of Guangdong province will increase 0.97 and 0.64 unit respectively. The long-term marginal utility of the EC is more than 1.     

The demand for residential electricity in South Africa

This paper examines the residential demand for electricity in South Africa as a function of real gross domestic product per capita, and the price of electricity during the period 1978–2005. We make use of the bounds testing approach to cointegration within an autoregressive distributed framework, suggested by Pesaran et al. [2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16(3) 289–326]. Following the literature, we use a linear double-logarithmic form using income and price as independent variables in the empirical analysis. In the long run, we find that income is the main determinant of electricity demand, while electricity price is insignificant.     

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

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

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

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

Short-term prediction of household electricity consumption: Assessing weather sensitivity in a Mediterranean area

Urban microclimatic variations, along with a rapid reduction of unit cost of air-conditioning (AC) equipments, can be addressed as some of the main causes of the raising residential energy demand in the more developed countries. This paper presents a forecasting model based on an Elman artificial neural network (ANN) for the short-time prediction of the household electricity consumption related to a suburban area. Due to the lack of information about the real penetration of electric appliances in the investigated area and their utilization profiles it was not possible to implement a statistical model to define the weather and climate sensitivities of appliance energy consumption. For this reason an ANN model was used to predict the household electric energy demand of the investigated area and to evaluate the influence of the AC equipments on the overall consumption.The data used to train the network were recorded in Palermo (Italy) and include electric current intensity and weather variables as temperature, relative humidity, global solar radiation, atmospheric pressure and wind speed values between June 1, 2002 and September 10, 2003.The work pointed out the importance of a thermal discomfort index, the Humidex index, for a simple but effective evaluation of the conditions affecting the occupant behaviour and thus influencing the household electricity consumption related to the use of heating, ventilation and air conditioning (HVAC) appliances. The prediction performances of the model are satisfying and bear out the ability of ANNs to manage incomplete and noisy data, solve nonlinear problems and learn complex underlying relationships between input and output patterns.     

Forecasting of Turkey's net electricity energy consumption on sectoral bases

In this study forecast of Turkey's net electricity energy consumption on sectoral basis until 2020 is explored. Artificial neural networks (ANN) is preferred as forecasting tool. The reasons behind choosing ANN are the ability of ANN to forecast future values of more than one variable at the same time and to model the nonlinear relation in the data structure. Founded forecast results by ANN are compared with official forecasts.     

Short and long-run elasticities in US residential electricity demand: a co-integration approach

Co-integration techniques show promise in the analysis of short- and long-run effects of economic variables on energy use. We use these techniques to develop an error correction model of annual US residential electricity demand. We construct equipment stock indices and estimate the model for 1949–1993. Our analysis suggests a structural shift in consumption during the 1960s. We discuss reasons for this shift, report the short- and long-run elasticities, provide forecasts for 1994–1995, and compare the model's forecasts with other published forecasts.     

Non-linear dynamics of electric power losses,electricity consumption,and GDP in Jamaica

We examine the relationship between electric power losses, electric power consumption, and GDP in Jamaica for the period 1971 to 2014 accounting for the non-linear growth in GDP. There are two key findings. First, there are cointegrating relationships between the energy variables and GDP. In the long run, a positive shock to electric power losses has a negative impact on GDP, but one to electric power consumption has a positive impact that peters out over time. Second, in the short run, the growth in the energy variables Granger cause GDP growth. We discuss the implications of these findings.     

Compact fluorescent lighting and residential natural gas consumption: Testing for interactive effects

Replacing incandescent light bulbs with compact fluorescents (CFLs) has traditionally been seen as a cost effective means of promoting energy conservation. Recently, however, the magnitude of energy savings associated with CFLs has been called into question. Specifically, recent findings suggest an “interactive effect” associated with the replacement of incandescent light bulbs with CFLs in the residential sector. In this scenario, the reduced wattage of CFLs, relative to incandescent bulbs, generates less heat, which in turn, requires additional natural gas usage during the heating season. Engineering studies suggest the magnitude of the effect is significant in energy terms, which implies that the energy savings associated with CFLs may be significantly overstated. In this paper, we use billing analysis to test for the presence of interactive effects. Our analysis is based on a comprehensive dataset that includes monthly household electricity and natural gas usage, the number of CFL bulbs installed, the installation date, and a set of household characteristics. Our results suggest that CFLs do indeed save electricity. However, we do not find any support for the hypothesis that CFLs cause increased usage of natural gas.     

Residential electricity consumption in industrialized countries: Changes since 1973

We consider the evolution of residential electricity use since the early 1970s in 11 OECD countries. Average growth in demand has been higher in Europe and Japan than in the U.S. This result is mainly attributable to the difference in saturation of appliances and electricity heating, which was higher in the U.S. than elsewhere at the beginning of the period. Growth in appliance ownership was responsible for high growth rates from 1960 through around 1973, when electric heating began to become popular in many countries. By the early 1980s, more efficient appliances and tighter new homes dampened growth in demand in most countries. Average growth in electricity demand per household between 1978 and 1983 was generally less than 2% per yr, and was negative in some countries.     

Characteristics of residential energy consumption in China: Findings from a household survey

A comprehensive survey of 1450 households in 26 Chinese provinces was undertaken in 2012 to identify the characteristics and potential driving forces of residential energy consumption in China. The survey covers six areas: household characteristics, dwelling characteristics, kitchen and home appliances, space heating and cooling, residential transportation, and electricity billing, metering, and pricing options. The results show that a typical Chinese household in 2012 consumed 1426 kilograms standard coal equivalent, which is approximately 44 percent of the 2009 level in the United States and 38 percent of the 2008 level in the EU-27. District heating, natural gas, and electricity are three major residential energy sources, while space heating, cooking, and water heating are three major end-use activities. Moreover, the results suggest a large urban–rural gap in terms of energy sources and purpose of usage. Commercial energy is used mainly for space heating in urban areas, while biomass dominates mainly for cooking purpose in rural areas. The survey results can help decision makers and scholars identify energy conservation opportunities, and evaluate the effectiveness of energy policies.     

Forecasting weekly electricity consumption : A case study

This paper describes the application of time-series modelling techniques to electricity consumption data for a particular power board. Modelling is performed on total consumption, the data being available on a weekly basis with exact measurements for approximately the past 11 years. Both unforced and forced models are considered. An initial data analysis is performed to ascertain the influence of temperature and rainfall inputs on the model, and later on, a spectral analysis is used to investigate the frequency components present in the time-series data. A significant component of the determination of time-series models is the selection of an appropriate model order. Both low and high order models are evaluated, and their properties compared. For the unforced case, both AR (autoregressive) and ARMA (autoregressive moving average) models are considered. For the forced case, these model structures are extended to include ARX and ARMAX models which have one or more exogenous inputs. Such models are further extended by considering the possibility of predicting the inputs to the models, when a forecasting approach is required. Simulation results are provided for all cases together with a measure of the prediction accuracy. Comparisons are made for the various model structures, as well as models based on short and long data records and models which are driven with an external noise sequence or merely released from appropriate initial conditions.     

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

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.     

Seasonal variations in residential and commercial sector electricity consumption in Hong Kong

We present the energy use situation in Hong Kong from 1979 to 2006. The primary energy requirement (PER) nearly tripled during the 28-year period, rising from 195,405 to 566,685 TJ, about two-third of which was used for electricity generation. The residential and commercial sectors are the two largest electricity end-users with an average annual growth rate of 5.9% and 7.4%, respectively. The monthly consumption in these two sectors shows distinct seasonal variations mainly due to changes in the air-conditioning requirements, which are affected by the prevailing weather conditions. Principal component analysis of five major climatic variables—dry-bulb temperature, wet-bulb temperature, global solar radiation, clearness index and wind speed—was conducted. Measured sector-wide electricity consumption was correlated with the corresponding two principal components determined using multiple regression technique. The regression models could give a very good indication of the annual electricity use (largely within a few percents), but individual monthly estimation could differ by up to 24%. It was also found that the climatic indicators determined appeared to show a slight increasing trend during the 28-year period indicating a subtle, but gradual change of climatic conditions that might affect future air-conditioning requirements.