Price Elasticity Of Electricity Demand Research Articles

Ultra-short-term Load Forecasting Based on Real-Time Response of Classified Flexible Loads

Ultra-short-term load forecasting is an important basis for optimization and adjustment of power generation plans and dispatch plans. Based on the radial basis function neural network, the inert load is predicted, and the flexible load is predicted based on the price elasticity of electricity demand. Then, combined with the range of the flexible load, an ultra-short-term forecast interval for the total load is constructed. This paper studies the total load after considering the flexible load for demand response, and verifies the feasibility of the proposed method with an example.

Research on Defensive Strategy of Real-Time Price Attack Based on Multiperson Zero-Determinant

The smart grid solves the growing load demand of electrical customers through two-way real-time communication of electricity supply and demand sides and home energy management system (HEMS). However, these technical features also bring network security risks to the real-time price signal of the smart grid. The real-time price attack (RTPA) can maliciously raise the real-time price in smart meter, resulting in an increase in electrical customers load demand, causing the extensive damage to the power transmission lines due to overload. In this paper, we based on the behavioral relationship between load demand of electrical customers and real-time price of electricity suppliers (ES), defined the game relationship between RTPA, ES, and electrical customers, established a price elasticity of electricity demand (PEED) model, and proposed a defensive strategy of real-time price attack based on multiperson zero-determinant strategy (MPZDS). The experimental results show that the combination of MPZDS to some extent cut the expected load demand of electrical customers and protect the safety of power transmission lines.

One price doesn't fit all: An examination of heterogeneity in price elasticity of residential electricity in India

Although well-designed consumer electricity pricing can improve access, contribute to higher metering, increase penetration of energy efficient technologies, limit extent of the rebound effect, and influence viability of electricity distribution utilities in India, there has been no comprehensive, policy-relevant assessment of price elasticities of electricity demand in the country. The objective of this study is to estimate price elasticity of residential electricity consumption and disaggregate it by state, rural and urban residence, and income categories to provide evidence for electricity tariff setting in India. We combine survey data from five rounds of nationally-representative household consumption expenditure surveys covering the period 2005–2012 with administrative data on electricity deficit and improve on methods applied in previous studies by estimating price elasticities using a quadratic form to account for constraints in electricity supply. We find that while the average price elasticity at the national level is −0.39 (95% confidence interval: −0.46, −0.31), it varies significantly by state, rural and urban residence, and income categories. Our results indicate that a “one ‘price’ fits all” policy may not be an effective approach to electricity tariff setting in India and a data-driven understanding of heterogeneities in price elasticities can better inform residential electricity tariff design in the country.

Income and price elasticities of electricity demand in Australia: Evidence of state‐specific heterogeneity

This paper estimates country‐wide and state‐level income and price elasticities of electricity demand in Australia for the period 1999Q1–2013Q2 using the National Electricity Market data and the autoregressive‐distributed lag model. The results suggest that the long‐run income and price elasticities are inelastic and are statistically significant with theoretically consistent signs. The country‐wide income and price elasticities are estimated to be 0.41 and −0.38, respectively. It is also found that there exists state‐specific heterogeneity in both speed and magnitude of the electricity consumption adjustment in response to changes in income and electricity price. These results have important policy implications, including the need to use state‐specific elasticities in the scenario analysis of the energy pricing policy.

Response to extreme energy price changes: evidence from Ukraine

Large but temporary price increases are sometimes deployed on days when the demand for electricity is extremely high due to exceptionally warm or cold weather. But what happens when the extreme price changes are permanent? Between January 2013 and April 2016, natural gas and electricity prices in Ukraine increased dramatically (up to 300% of the initial rates). We exploit variation in tariffs over time and across customers to estimate the price elasticity of electricity demand using a panel dataset with monthly meter readings from households in the city of Uzhhorod in Ukraine. We ask three research questions. First, what is the price elasticity of consumption implicit in the response (if any) to these large electricity price changes? Second, is there evidence of heterogeneity in the price elasticity of electricity demand driven by dwelling or household characteristics, or by consumer understanding of block pricing and/or own consumption levels? Third, how quickly do household adjust their consumption after a price change? Histograms of the monthly usage records suggest that our Ukrainian consumers were aware of the increasing block pricing system and responded to marginal prices, with bunching observed at the then-current as well as future block cutoffs. The price elasticity of electricity demand is approximately -0.2 to -0.5, with the bulk of our estimates around -0.3. The elasticity becomes up to 50% more pronounced over the first three months since prices change. We find only limited evidence that persons who are attentive about their consumption levels, their bills, or the tariffs are more responsive to the price changes. The tariff increases do help reduce CO2 emissions, but at a high cost per ton.

Response to Extreme Energy Price Changes: Evidence from Ukraine

Large but temporary price increases are sometimes deployed on days when the demand for electricity is extremely high due to exceptionally warm or cold weather. But what happens when the extreme price changes are permanent? Between January 2013 and April 2016, natural gas and electricity prices in Ukraine increased dramatically (up to 300% of the initial rates). We exploit variation in tariffs over time and across customers to estimate the price elasticity of electricity demand using a panel dataset with monthly meter readings from households in Uzhhorod in Ukraine. The price elasticity of electricity demand is -0.2 to -0.5, with the bulk of our estimates around -0.3. The elasticity becomes up to 50% more pronounced over the first three months since prices change. We find only limited evidence that persons who are attentive about their consumption levels, their bills, or the tariffs are more responsive to the price changes.

О ценовой эластичности спроса на электроэнергию

The paper provides the econometric estimates of short-run and long-run price elasticities of electricity demand for different categories of customers. Both for residential and for non-residential sectors the estimates (in absolute value) of short-run price elasticity are low, while the estimates of long-run price elasticity are high. Consequently, long-run projections of electricity demand under expectations of increase of energy prices should take into account the long-run price elasticity. The estimates of short-run price elasticity for non-residential sector can be used in models of imperfect competition in the electricity market, under a number of assumptions, such as the absence or weak attention of the regulator, when possible strategies of economic agents (such as electricity suppliers in the spot market) may depend on the short-run price elasticity of demand.

An experimental investigation of price elasticity in electricity markets using a response surface methodology

For the purposes of government policy concerning energy security, optimal taxation, and climate change, precise estimates of the effective factors in price elasticity of electricity demand are of principal importance. In this regard, this paper explores the effect of different factors including proportion of income spent-level, consumer academic-level, demand-types, demand time, possibility of postponing demand-level, price-level, demand-level, and awareness of participation benefits-level on price elasticity of electricity demand for Iran power system. To achieve this, a nonlinear-empirical model based on response surface methodology is proposed. Thereafter, these factors were prioritized based on their effect on price elasticity. Analysis results reveal that proportion of income spent-level has the most significant effect on the price elasticity of electricity demand while consumer academic-level has the least effect. These results could be applied by policy makers as a tool in making decisions on how to set the price of electricity.

Application of artificial neural networks and fuzzy logic to long-term load forecast considering the price elasticity of electricity demand

Application of artificial neural networks and fuzzy logic to long-term load forecast considering the price elasticity of electricity demand

The Price Elasticity of Electricity Demand in the United States: A Three-Dimensional Analysis

In this paper we employ a dataset of three dimensions—state, sector, and year—to estimate the short- and long-run price elasticities of state-level electricity demand in the United States. Our sample covers the period 2003-2015. We contribute to the literature by employing instrumental variable estimation approaches, using the between estimator, and pursuing panel specifications that enable us to control for multiple dimensions of fixed effects. We conclude that state-level electricity demand is very price inelastic in the short run, with a same-year elasticity of -0.1.

Revisiting income and price elasticities of electricity demand in Pakistan

In view of a more than decade-long power crisis in Pakistan, several studies have estimated income and price elasticities of electricity demand. These estimates are based on electricity consumption data that do not reflect actual demand due to an electricity supply shortfall of up to 6000 megawatts (MW). Moreover, previous studies accounted for power consumption data of only one of the two electric power companies, Pakistan Electric Power Company (P.E.P.C.O.), ignoring the other company K-Electric, with a share of over 15% in country’s electricity consumption. This study attempts to revisit electricity demand elasticities in Pakistan at the aggregate and sectoral level by including both P.E.P.C.O. and K-Electric and adjusting the consumption series for load shedding to reflect actual electricity demand. By employing an Autoregressive Distributive Lag model, the study finds electricity demand to be income elastic at aggregate level and in the agriculture sector in the long run, and relatively inelastic in the industrial sector. However, unlike previous studies, the electricity demand is price inelastic at all levels, which is an expected outcome in an economy facing electricity shortages. The coefficients of short-run income and price elasticities are smaller than their long-run counterparts. No evidence of cointegration is found for the commercial sector.

The Impact of China's Electricity Deregulation on Coal and Power Industries: Two-Stage Game Modeling Approach

The regulated price mechanism in China’s power industry has attracted much criticism because of its incapability to optimize the allocation of resources. To build an “open, orderly, competitive and complete” power market system, the Chinese government launched an unprecedented marketization reform in 2015 to deregulate the electricity price. This paper examines the impact of the electricity price deregulation in the industry level. We first construct two-stage dynamic game models by taking the coal and coal-fired power industries as the players. Using the models, we compare analytically the equilibriums with and without electricity regulation, and examine the changes in electricity price, electricity generation, coal price and coal traded quantity. The theoretical analyses show that there are three intervals of the regulated electricity sales prices which influence the impact of electricity price deregulation. Next, we collect empirical data to estimate the parameters in the game models, and simulate the influence of electricity deregulation on the two industries in terms of market outcome and industrial profitability. Our results suggest that the actual regulated electricity price falls within the medium interval of the theoretical results, which means the price deregulation will result in higher electricity sales price but lower coal price, less coal traded amount and less electricity generation amount. The robustness analysis shows that our results hold with respect to the electricity generation efficiency and price elasticity of electricity demand.

Estimating the price (in)elasticity of off-grid electricity demand

Community-scale power infrastructure may be the only electrification option for tens of millions households that remain out of reach from centralized power grids. The responsiveness of household electricity demand to price is a crucial design input for off-grid systems. While the price elasticity of electricity demand of grid-connected consumers has been abundantly studied, few studies focus on off-grid communities where substantial econometric challenges arise, including the absence of metered consumption data and electricity prices that are simultaneously determined by cost and demand considerations. This study attempts to address these challenges for the case of off-grid micro hydropower consumers. It makes two core contributions: First, we propose the surface area of the contributing hydrologic catchment as a new instrumental variable to estimate elasticity using a cross sectional dataset of existing micro hydropower infrastructure. Second, we provide a first price-elasticity estimate (−0.15) for off-grid electricity demand in Nepal. We surmise that the small (in absolute value) elasticity value found in this study arises from the low levels of consumption observed off-the-grid. We use a Monte Carlo analysis to show that failing to account for this disparity can lead to substantial financial losses caused by suboptimal power infrastructure design.

Response to Extreme Energy Price Changes: Evidence from Ukraine

Large but temporary price increases are sometimes deployed on days when the demand for electricity is extremely high due to exceptionally warm or cold weather. But what happens when the extreme price changes are permanent? Between January 2013 and April 2016, natural gas and electricity prices in Ukraine increased dramatically (up to 300% of the initial rates). We exploit variation in tariffs over time and across customers to estimate the price elasticity of electricity demand using a panel dataset with monthly meter readings from households in the city of Uzhhorod in Ukraine. We ask three research questions. First, what is the price elasticity of consumption implicit in the response (if any) to these large electricity price changes? Second, is there evidence of heterogeneity in the price elasticity of electricity demand driven by dwelling or household characteristics, or by consumer understanding of block pricing and/or own consumption levels? Third, how quickly do household adjust their consumption after a price change? Histograms of the monthly usage records suggest that our Ukrainian consumers were aware of the increasing block pricing system and responded to marginal prices, with bunching observed at the then-current as well as future block cutoffs. The price elasticity of electricity demand is approximately -0.2 to -0.5, with the bulk of our estimates around -0.3. The elasticity becomes up to 50% more pronounced over the first three months since prices change. We find only limited evidence that persons who are attentive about their consumption levels, their bills, or the tariffs are more responsive to the price changes. The tariff increases do help reduce CO2 emissions, but at a high cost per ton.

An integrated model for assessing electricity retailer’s profitability with demand response

This paper introduces a model that integrates a Unit Commitment (UC) model, which performs the simulation of the day-ahead electricity market, combined with an econometric model that estimates the income and price elasticities of electricity demand. The integrated model is further extended to estimate the retailers’ profitability with demand responsive consumers. The applicability of the proposed model is illustrated in the Greek day-ahead electricity market. The model is designed to identify the effects of demand responsiveness to the fluctuations of spot prices, based on their short-term price elasticities. It provides price signals on the profitability of retailers/demand aggregators, when forming their tariffs. We argue that the non-linearity between demand response and evolution of wholesale price, inherits risk for retailers. This finding could lead even to losses for some time periods, affecting strongly their viability. The model provides useful insights into the risk of retailers from their price responsive customers and therefore acts as a pivotal study to policy makers and government officials (i.e. regulators, transmission and distribution system operators) active in the electricity market.

Industrial and residential electricity demand dynamics in Japan: How did price and income elasticities evolve from 1989 to 2014?

This study estimates the price and income elasticities of industrial and residential electricity demand in Japan with the annual data from 1989 to 2014. A time varying parameter (TVP) model with the Kalman filter is applied to monitor the evolution of consumer behaviors in the “post-bubble” period given the exogenous shock (financial crisis in 2008) and the structural breaks (electricity deregulation and Fukushima Daiichi crisis). The TVP model can provide a robust estimation of elasticities and can detect the outliers and the structural breaks. The results suggest that both industrial and residential consumers become less sensitive to price after the electricity deregulation and the financial crisis, and more sensitive to price after the Fukushima Daiichi crisis. Especially the industrial sector is less sensitive to price after the retail deregulation. By contrast, the income elasticities of industrial and residential sector consumers are stable during the examined period. Results also indicate that a negative relationship exists between the price elasticity of electricity demand and the price level of electricity after the electric sector deregulation. Some insights on the further electric sector reform and the environmental taxation in Japan are also provided.

Gas and electricity demand in Spanish manufacturing industries: An analysis using homogeneous and heterogeneous estimators

A comparative analysis of electricity and gas demand in the industrial sector over a long period of time appears to be absent in the literature. In fact, unlike electricity demand, natural gas demand in the industrial sector has not been well researched. Our paper aims to cover this gap. It analyses electricity and gas consumption patterns by the Spanish manufacturing sector, between 1995 and 2010. A novel and innovative quantitative approach based on, both, homogenous and heterogeneous estimators was used for this purpose. The results of the no-spurious estimations (the Augmented Mean Group Estimator) show that the price elasticity of gas demand is significantly negative and within the −0.44 to −0.48 range. In contrast, the price elasticity of electricity demand is not statistically significant. The income elasticities show the opposite pattern: those of natural gas are not statistically significant, whereas the income elasticities for electricity are statistically significant and within the 0.22 to 0.29 range. Compared to previous findings, our preferred estimation shows some variation regarding price elasticities of natural gas demand.

The Price Elasticity of Electricity Demand in the United States: A Three-Dimensional Analysis

In this paper we employ a dataset of three dimensions - state, sector, and year - to estimate the short- and long-run price elasticities of state-level electricity demand in the United States. Our sample covers the period 2003-2015. We contribute to the literature by employing instrumental variable estimation approaches, using the between estimator, and pursuing panel specifications that are able to control for multiple dimensions of fixed effects. We conclude that state-level electricity demand is very price inelastic in the short run, with a same-year elasticity of -0.1. The long-run elasticity is near -1, larger than often believed. Among the sectors, it is industry that has the largest long-run price elasticity of demand. This appears to in part be due to electricity-intensive industrial activities clustering in low-price states.

Response to Extreme Energy Price Changes: Evidence from Ukraine

Large but temporary price increases are sometimes deployed on days when the demand for electricity is extremely high due to exceptionally warm or cold weather. But what happens when the extreme price changes are permanent? Between January 2013 and April 2016, natural gas and electricity prices in Ukraine increased dramatically (up to 300% of the initial rates). We exploit variation in tariffs over time and across customers to estimate the price elasticity of electricity demand using a panel dataset with monthly meter readings from households in the city of Uzhhorod in Ukraine. We ask three research questions. First, what is the price elasticity of consumption implicit in the response (if any) to these large electricity price changes? Second, is there evidence of heterogeneity in the price elasticity of electricity demand driven by dwelling or household characteristics, or by consumer understanding of block pricing and/or own consumption levels? Third, how quickly do household adjust their consumption after a price change? Histograms of the monthly usage records suggest that our Ukrainian consumers were aware of the increasing block pricing system and responded to marginal prices, with bunching observed at the then-current as well as future block cutoffs. The price elasticity of electricity demand is approximately -0.2 to -0.5, with the bulk of our estimates around -0.3. The elasticity becomes up to 50% more pronounced over the first three months since prices change. We find only limited evidence that persons who are attentive about their consumption levels, their bills, or the tariffs are more responsive to the price changes. The tariff increases do help reduce CO2 emissions, but at a high cost per ton.

The influence of nonlinear pricing policy on residential electricity demand—A case study of Anhui residents

In this paper, we propose a power structure of economic models of price responsive loads, based on price elasticity of electricity demand, perceived price and customer benefit function. Taking Anhui province as an example, we estimate the influences of block pricing policy and TOU-block pricing policy (the combination of blocking pricing policy and time-of-use (TOU) pricing policy) on residential electricity demand and electricity expenses. We find that the present block pricing policy may help lower the residential electricity consumption at about 1.4%–3.0% per year, which indicates that the effect of energy conservation is not obvious; while the TOU-block pricing policy may help lower the yearly electricity consumption at less than 1%, which implies that, compared with block pricing, the TOU-block pricing policy plays a weaker role in reducing electricity consumption. Moreover, block pricing policy results in a yearly increase of 2.34%–4.28% power expenses on urban residents, while TOU-block pricing policy may lower the corresponding expense at 8.17%–14.30%, which shows that block pricing policy plays a limited role in increasing the electricity expense of urban residents. In addition, the TOU-block pricing policy may effectively alleviate the effect of block pricing on urban residents' electricity expense. Generally speaking, we see limited prospect in the goal attainment of the present TOU-block pricing policy.