Electricity Price Elasticity Research Articles

Electric vehicle usage, pollution damages, and the electricity price elasticity of driving

I study battery electric vehicle (BEV) usage and ownership characteristics with fundamental implications for the electrification of passenger transportation. Using data covering the entire BEV population in New York, I quantify BEV mileage and electricity consumption and highlight the important role of vehicle utilization in contributing to real-world pollution damages and their spatial variation. I then study the factors influencing how much BEVs are driven with a focus on estimating the electricity price elasticity of BEV mileage. Understanding how drivers respond to these changes in operating costs may help align the social and private costs of BEV driving and illustrates how electric utilities may affect transportation outcomes in the future. I find a 10% increase in residential electricity prices reduces mileage by 1%, but responsiveness falls as public charging stations—where prices are often decoupled from electricity costs—become available.

Optimal Planning of Hybrid Electricity–Hydrogen Energy Storage System Considering Demand Response

In recent years, the stability of the distribution network has declined due to the large proportion of the uses of distributed generation (DG) with the continuous development of renewable energy power generation technology. Meanwhile, the traditional distribution network operation mode cannot keep the balance of the source and load. The operation mode of the active distribution network (ADN) can effectively reduce the decline in operation stability caused by the high proportion of DG. Therefore, this work proposes a bi-layer model for the planning of the electricity–hydrogen hybrid energy storage system (ESS) considering demand response (DR) for ADN. The upper layer takes the minimum load fluctuation, maximum user purchase cost satisfaction, and user comfort as the goals. Based on the electricity price elasticity matrix model, the optimal electricity price formulation strategy is obtained for the lower ESS planning. In the lower layer, the optimal ESS planning scheme is obtained with the minimum life cycle cost (LCC) of ESS, the voltage fluctuation of ADN, and the load fluctuation as the objectives. Finally, the MOPSO algorithm is used to test the model, and the correctness of the proposed method is verified by the extended IEEE-33 node test system. The simulation results show that the fluctuation in the voltage and load is reduced by 62.13% and 37.06%, respectively.

Estimating the Price Elasticity of Natural Gas and Electricity in Pacific Northwest

This paper estimates the price elasticity of electricity and natural gas in the Pacific Northwest. Electricity and natural gas are substitutes; and demands of different classes of consumers for the energy are price-inelasticity. The results are when the price of retail electricity and natural gas changes, consumers would choose the cheaper one to make up for the increased cost of another energy price. Consumers’ demand for energy is mainly stable, they won’t affect a lot by the change in energy prices.

Estimating the Short-term Price Elasticity of Residential Electricity Demand in Iran

Excessive electricity consumption causes severe problems in the electricity sector and consequently in load curtailment. This paper estimates the short-term price elasticity of electricity demand for the Iranian household sector by monthly panel dataset. The estimated short-term price elasticity of electricity demand was −0.048. We use abrupt change in electricity price due to targeting subsidy on December 18th, 2010. The results show significant heterogeneity in electricity price elasticity between the various levels of consumption. Due to the heterogeneity of consumers’ electricity price elasticity, we can categorize residential consumers into four groups. Hence, policymakers are suggested to manage peak loads in the electricity network by estimating consumer responsiveness and reforming electricity pricing considering equality issues and tariff design.

Electric Vehicle Usage, Pollution Damages, and the Electricity Price Elasticity of Driving

Electric Vehicle Usage, Pollution Damages, and the Electricity Price Elasticity of Driving

Aggregation Optimization Method of Virtual Energy Storage for Electric Vehicles Considering User Elasticity

With the continuous development of electric vehicle charging facilities, the impact of electric vehicles on the power grid is growing. Considering the automatic demand response technology of smart grid, charging pile operators participate in the demand response plan and guide users to charge according to the price signal or incentive mechanism, which can ensure the safety of the power grid and reduce the negative effects of electric vehicles on the grid influence. Based on the theory of demand side response elasticity, this paper analyzes the whole process of electric vehicle users' participation in demand response and its influencing factors, classifies electric vehicle users based on demand response, and then quantitatively analyzes users' demand response from the perspective of electricity price elasticity and consumption psychology. Finally, the demand side response model with user participation is established. The application of the model can effectively improve the enthusiasm of electric vehicle users to participate in demand side response, and reduce the negative impact of electric vehicles on the power grid.

Price and income elasticities of electricity in China: Estimation and policy implications

AbstractChina has been reforming the energy sector, especially the electricity industry. One of the important aims is to reform the cross‐subsidies (the industrial sector has been subsidizing the residential sector for decades), which requires policy‐makers have a good understanding of price and income elasticities of electricity. However, few studies have estimated China's price and income elasticities of electricity, partly due to limited micro data. This study estimates price and income elasticities of electricity in China using AIDS (almost ideal demand system) demand model, which is consistent with consumer theory and more flexible than other regression models. The AIDS demand model is estimated using provincial‐level data from 2006 to 2016 and the estimation results show that the uncompensated price elasticity is −0.062, and the estimated income elasticity of residents is 0.889. To better understand the welfare implications of cross‐subsidies, which requires an estimate of the price elasticity of demand in the industrial sector. Based on the estimated price elasticity of electricity, we simulate the consumer surplus under different pricing mechanisms. Ramsey pricing, as expected, generated the larger consumer surplus than actual pricing mechanism, which would provide guidance for the price reform of China's power industry.

Market-induced carbon leakage in China’s certified emission reduction projects

The topic of climate change has aroused increasingly widespread concern around the world. Under the agreement at the 21st Conference of the Parties of the United Nations Framework Convention on Climate Change (UNFCCC), covened in Paris, France (Paris Agreement), which requires all Parties to undertake emission reductions, the developing countries who were once exempted from emission reduction obligations are now becoming more and more important. This study focuses on mitigation actions in China, the largest carbon emitter, as well as the largest developing country in the world. Specifically, we examine Chinese Certified Emission Reduction (CCER) projects. The objective is to compare the reduction efficiency of three types of projects: simple abatement and completely renewable energy alternative projects at the supply side and demand side projects. From market-induced carbon leakage point of view, a dual market equilibrium model was built, with results showing that the key factors affecting the leakage rates are price elasticities of both demand and supply sides and market share parameters. In most cases, renewable energy alternative projects show the least leakage rate while demand side projects show the highest. Sensitivity analysis finds that leakage rates for the three types of projects are more sensitive to price elasticity parameters than market share parameters. Moreover, factors $$ {E}_c^{de} $$ (electricity price elasticity of coal demand from coal-fired generation) and $$ {E}_e^d $$ (electricity price elasticity of electricity demand) affect not only the leakage rate of each project but also the comparative results between them. Although our study is based on China, the theoretical analysis is applicable in other regional voluntary emission reduction markets around the world. So, a systematic approach to comprehensively analyze the issue is summarized, based on which, we recommend two mitigation strategies to cope with the issue in offset projects in order to give managerial insights for the government. Firstly, the calculated leakage rates for different types of projects provide a new perspective to evaluate various offset projects, thus helping consider project types for priority validation. Secondly, we suggest to establish an accurate and classified discount coefficient system according to the project types to deal with the issue; the sensitivity analysis is helpful to find the most influential factors. A top-down approach to implement the strategy is proposed.

Optimal Allocation of Energy Storage System Considering Price-Based Demand Response and Dynamic Characteristics of VRB in Wind-PV-ES Hybrid Microgrid

Studying the influence of the demand response and dynamic characteristics of the battery energy storage on the configuration and optimal operation of battery energy storage system (BESS) in the Wind-Photovoltaic (PV)-Energy Storage (ES) hybrid microgrid. A demand response model that is based on electricity price elasticity is established based on the time-of-use price. Take the capital-operating cost and direct economic benefit of the BESS and the loss of abandoned photovoltaic and wind power as the optimization objective, an optimal configuration method that considers the dynamic characteristics of the BESS and the maximum absorption of photovoltaic and wind power is proposed while using particle swarm optimization to solve. The results show that the configuration results considering the demand side response of the microgrid BESS can obtain better economy and reduce the storage capacity requirement, and the result shows that the efficiency of BESS relates to the load of the system, the distributed generation (DG) characteristics, and the dynamic characteristics of BESS. Meanwhile, the capacity and power of the energy storage configuration increase as the DG permeability increases due to the reverse load characteristic of the wind power.

A time varying approach on the price elasticity of electricity in India during 1975–2013

Poor cost recovery rates and large subsidization of the agriculture and households by industrial and commercial users are two of the characteristics of the power sector in India. The paper applies a variety of linear and nonlinear unit root tests and a Kalman filter approach which can host time varying elasticities, to estimate the effects of various macroeconomic factors on the price elasticity for electricity in India during 1975–2013. The estimated price elasticity is −0.21 and the income elasticity is 0.41. The study finds that the electricity demand is affected by macroeconomic parameters such as trade and foreign direct investment. The findings of the study have implications to the policy makers and private investors who wish to invest in electricity supply utilities and infrastructure. The value of the estimated elasticity in the study is relatively smaller as compared to the previous studies reflecting, among other things, the fact that electricity demand is supply driven in India.

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.

Bus load forecasting method considering user interaction response in electricity market environment

To improve the accuracy of bus load forecasting under the environment of electricity market, a bus load forecasting framework considering user interaction response is proposed. Since bus load components are complex and the response of each load to real-time electricity price is different, the identification and proportion calculation model of bus load components is firstly established. Secondly, the interactive response models of each load to real-time electricity price are established from the perspective of overall price elasticity and time-price difference elasticity. Thirdly, four different forecasting strategies are proposed with considering of electricity price elasticity, and the sequence of interaction analysis and load forecasting. Finally, a case study is carried out to verify the effectiveness of the proposed forecasting framework using the actual bus load data of a certain area in Guangdong Province.

Modelling of multi-timescale demand response for power markets

Demand response as an important part of smart grid makes the consumers participate in market operation that can lead to the benefit of both the utility and the consumers. In this paper, a multi-timescale demand response model that accounts for short-term and long-term demand characteristics is established. The short-term demand response and long-term demand response are combined by the electricity price elasticity matrix. The objective of optimisation is to minimise the peak-valley load difference in the total load, and particle swarm optimisation is adopted as the optimisation algorithm. The simulation results of IEEE-30 node distribution network show the feasibility and effectiveness of the proposed demand response model and pricing strategy. The research of this paper will provide technical support for the application of demand response mechanism after the new electric power reform.

The Effect of Electricity Prices on Residential Solar Photovoltaic Panel Adoption: Fukushima as a Natural Experiment

There are a range of private financial benefits of residential solar photovoltaic (PV) installation, such as a reduced electricity bill, tax incentives and a feed-in tariff for generated electricity. To empirically analyze how rising electricity prices affect household adoption decisions, we use the 2011 Fukushima nuclear disaster as a natural experiment. The shutdown of nuclear power plants across Japan led to a sizable increase in electricity prices that varied by region, allowing us to identify the effect of electricity prices on household PV system adoption. We find that higher electricity prices are significantly more influential on PV adoption on existing homes than on newly-built homes. Our estimated electricity price elasticity of PV systems ranges from 0.9 to 1.2 for existing homes and is much smaller and statistically insignificant for newly-built homes. We discuss behavioral mechanisms explaining this difference and implications for policies stimulating residential adoption of renewables.

Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response

In order to solve the influence of uncertain photovoltaic power (PV) on the stable operation of microgrid (MG), demand response (DR) and battery energy storage system (BESS) need to be introduced simultaneously into the operation optimal scheduling of PV-based microgrid (PV-MG). Therefore, it is of great significance for commercial investment decisions of PV-MG to consider the influence of DR on BESS optimal sizing. Under the peak-valley time-of-use (TOU) price, this paper builds cross-time DR models based on price elasticity matrix. Furthermore, through the introduction of DR and BESS into PV-MG scheduling optimization, the MG investment and benefit model is proposed. Considering the constraint condition such as co-ordination of supply and demand, electricity price elasticity and energy loss of storage system, the improved non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-objective optimal allocation model of the BESS with the target of maximum PV consumptive rate and annual net profits. The optimization method was applied to a PV-MG in Guangdong. Through the regulation and control effect of demand response and BESS on load distribution, the uncertainties PV power can be suppressed so as to improve the PV system consumptive level, which is of great guiding significance for BESS optimal sizing under this situation.

Household Energy Demand in Urban China: Accounting for Regional Prices and Rapid Income Change

Understanding the rapidly rising demand for energy in China is essential to efforts to reduce the country’s energy use and environmental damage. In response to rising incomes and changing prices and demographics, household use of various fuels, electricity and gasoline has changed dramatically in China. In this paper, we estimate both income and price elasticities for various energy types using Chinese urban household micro-data collected by National bureau of Statistics, by applying a two-stage budgeting AIDS model. We find that total energy is price and income inelastic for all income groups after accounting for demographic and regional effects. Our estimated electricity price elasticity ranges from -0.49 to -0.57, gas price elasticity ranges from -0.46 to -0.94, and gasoline price elasticity ranges from -0.85 to -0.94. Income elasticity for various energy types range from 0.57 to 0.94. Demand for coal is most price and income elastic among the poor, whereas gasoline demand is elastic for the rich.

Sectoral electricity elasticities in South Africa: Before and after the supply crisis of 2008

In this paper, we estimate the price elasticity of electricity for various industrial sectors of the South African economy from 2002 to 2011. The data used include sectoral electricity consumption data and electricity tariff data, both courtesy of Eskom as well as output data based on national statistics. The most important contribution this paper makes is that it includes the period after the sharp rises in electricity tariffs in 2007/2008 following a period of load-shedding and insecurity in electricity supply. Previous studies have included data only until 2007 and, for the most part, have found statistically insignificant, positive elasticities. However, for the period post-2007, we found statistically significant and negative elasticities for 9 of the 11 sectors considered. Our results show that the majority of industrial sectors have become much more sensitive to changes in the price of electricity following 2007/2008, indicating to policymakers that tariff restructuring might influence consumer behaviour significantly.

The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application

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.

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. 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.

Analysis of Electricity Subsidies Removing in Iran on Air Pollution by Using of VECM

In Iran, the government pays subsidy on electricity consumption. So, the price of electricity in Iran is lower than its actual levels. Payment of subside on electricity consumption, increase the consumption of this energy carrier and also increase environment pollution as a result. This paper analyzes the short-term and long-term impacts of removing of electricity subsidies on environment pollution. To do so, the dynamic relation between electricity consumption and its price is estimated by using of an vector error correction model. The short – run and long – run price elasticity of electricity, show the impact of increase in electricity price due to removing of electricity subsidies, on its consumption and environment pollution in the short – and long run. The short-run and long-run price elasticity of electricity is –0.03 and –0.14 respectively. So, a 1% increase in prices of electricity due to removing of electricity subsidies, will decrease the electricity consumption and its environmental pollution about 0.03% and 0.14% in the short and long-run respectively.