Price Elasticity Of Electricity Demand Research Articles

A temporal and spatial electric vehicle charging optimization scheme with DSO-EVA coordination framework

Burdens of increasing penetration of electric vehicles (EVs) on distribution systems have attracted wide attention to the research of EV charging coordination. Nevertheless, existing coordination lacks the joint consideration of the temporal-spatial flexibility of EVs, which could reduce load fluctuations when meeting the EV charging demands. Moreover, a thorough investigation is required for the coordination of the benefits to the distribution system operator (DSO), EV aggregator (EVA), and EVs. In this paper, a novel EV charging scheme considering the temporal-spatial features of EVs is proposed, achieving the coordination of DSO, EVA, and EVs in two steps. First, a mixed-integer second-order cone programming (MISOCP)-based EV charging schedule is developed for DSO. Second, the temporal-spatial features of EVs are exploited by EVA to track the charging schedule. Specifically, a dynamic charging price mechanism based on active power margin is proposed for public charging facilities and a specific load regulation is designed for private charging facilities. On this basis, the modified adaptive multi-objective particle swarm optimization (AMOPSO) algorithm is proposed, including adaptive flight parameter adjustment and termination mechanisms. Case studies demonstrate the proposed strategy can attenuate load variance and raise EVA revenue. Further, the impact analysis of penalty price and the price elasticity of electricity demand can provide references for stable distribution network operation, higher EVA revenue, and charging cost reduction.

Price elasticity of electricity demand in China– A new instrument variable based on marketization policy

Estimating the price elasticity of the demand for electricity is important in research on the economics of electricity. However, the conventional approach of using average electricity prices as explanatory variables introduces endogenous challenges, such as measurement errors and reverse causality. In this study, we provide a novel analysis of China's coal and electricity marketization process, investigating the impact of coal marketization on electricity prices. To overcome the endogeneity issue, we employ an instrumental variable (IV) method that leverages exogenous variations in average electricity prices induced by the coal marketization policy. The results indicate that the ordinary least squares (OLS) method underestimates the price elasticity of the demand for electricity by ignoring the fluctuations in coal prices. These results carry significant policy implications for countries considering energy marketization reforms as a solution to their energy challenges. Moreover, our research offers an innovative approach to address endogeneity, contributing to the methodological advancement of the field.

HOUSEHOLD-SPECIFIC SOCIAL NORMS, THE ELASTICITY OF ELECTRICITY DEMAND, AND CARBON EMISSION REDUCTIONS IN THE RESIDENTIAL SECTOR: EVIDENCE FROM A NATURAL EXPERIMENT IN RUSSIA

In this paper, I estimate the price elasticity of residential electricity demand using household-level panel data for Russia. The study takes advantage of the variation in tariffs across regions and over time, as well as the introduction of increasing block rate (IBR) schemes in a number of regions. I show that in those regions consumers appear to be aware of the block cut-offs, even though the latter are based on the prescribed social norms and are household and dwelling specific, to the point that there are up to a total of 31 different tier cut-offs. Based on these results, I estimate the price elasticity of electricity demand to be around −0.1. I also predict the associated changes in electricity consumption, CO2 emissions, and revenues if similar IBR policies are implemented countrywide.

Research on the Optimal Design of Seasonal Time-of-Use Tariff Based on the Price Elasticity of Electricity Demand

Building a new power system with renewable energy as its main component is a key measure proposed by China to address the climate change problem. Strengthening demand-side management (DSM) is an important way to promote the development of a new power system. As an important economic incentive measure in DSM, the current TOU tariff is faced with the problem of a weak incentive effect due to the small tariff difference between the peak and valley periods. Against this background, a novel hybrid three-stage seasonal TOU tariff optimization model is proposed in this paper. First, the K-means++ algorithm is adopted to select the typical days of the four seasons through load curve clustering. Then, the price elasticity of the electricity demand model is constructed to calculate the self-elasticity and cross-elasticity in four seasons. Finally, the seasonal TOU tariff optimization model is constructed to determine the optimal TOU tariff. Through the proposed model, the tariff in the peak period has increased by 8.06–15.39%, and the tariff in the valley period has decreased by 18.48–27.95%. The result shows that the load in the peak period has decreased by 4.03–8.02% and the load in the valley period has increased by 6.41–9.75% through the proposed model.

Perception and decision-making for demand response based on dynamic classification of consumers

Demand response plays a significant role in improving electricity market efficiency and keeping power system stability. Load aggregators can provide reliable resource for power balance and auxiliary services by integrating dispersed responsive loads. In order to meet the aggregators’ requirement of timeliness and accuracy in the real-time demand response market, a method of perception and decision-making for demand response based on dynamic classification of consumer is proposed. The price elasticity of electricity demand is calculated based on continuously updated trading experience and applied as a classification criterion. Consumers are dynamically classified by self-organizing maps algorithm to perceive consumers’ responsive ability. Furthermore, the interaction model of aggregator and consumers in market environment is constructed, and deep reinforcement learning is applied to solve the trading strategy in the uncertain market with incomplete information. Simulations show that the results of trading partner and reward price gained by the proposed method are appropriate. Therefore, the deviation between response quantity and the bid-winning volume is effectively controlled, and the transaction revenue of the aggregator is improved.

Electricity Demand Elasticity, Mobility, and COVID-19 Contagion Nexus in the Italian Day-Ahead Electricity Market

The magnitude of the impact of the pandemic on key variables, such as electricity demand, mobility of people and number of COVID-19 hospitalization cases, has been unprecedented. Existing economic models have not estimated the impact of sucokh events. This paper fills this gap, investigating the nexus among electricity demand elasticity, shifting behaviors of mobility and COVID-19 contagion with econometric estimation techniques. Firstly, using the single bids to purchase recorded in the Italian day-ahead wholesale electricity market in 2020, we estimate hourly electricity demand and price elasticity directly from short-run consumer behavior. Then, we analyze the effects of the main aspects of the pandemic, the health situation and the mobility contraction at the national level, on the estimated price elasticities. The period of heavy lockdown between 10 March and 3 June recorded a reduction in the price elasticity of electricity demand. However, when the pandemic broke out again at the beginning of October, elasticity increased, highlighting how companies and economic activities had adopted countermeasures to avoid the arrest of the economy and, consequently, the sharp contraction in electricity demand.

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.

“Wild” tariff schemes: Evidence from the Republic of Georgia

Consumers often struggle to grasp complicated pricing plans, including increasing block rate (IBR) schemes, which have been used for decades by utilities in many parts of the world. The assumption that they encourage conservation has, however, recently been challenged (Ito, 2014). We take advantage of the unique IBR tariffs for electricity in the Republic of Georgia—where “overage” is penalized more heavily than in conventional IBRs—to ask whether consumers respond to price, and to which price specifically.Based on the data from several waves of the Georgia Household Budget Survey, we find evidence of “notches,” namely missing probability mass on the right of the lowest block cutoff and a spike in the frequency of monthly consumption to the left of it. This is in contrast with the “bunching” pattern predicted by Borenstein (2009) when demand is not completely inelastic, and with the empirical evidence in Borenstein (2009) and Ito (2014).During our study period (2012–2019), the tariffs were revised—both downwards and upwards—to a different extent in different blocks and at different times across the regions of the country. We devise difference-in-difference study designs that exploit such natural experiments, finding that consumption did increase when the tariffs were reduced and fell when they were raised. Ours is one of the few studies that exploits quasi experimental conditions to examine whether the response to price changes is symmetric. We find that it is, in that the implied price elasticity of electricity demand is in both cases −0.3.Finally, we fit an electricity demand function, which results in an even stronger price elasticity (−0.5). Households seem to respond to the actual, average price (here equal to the marginal price) rather than to expected price. Our estimates of the price elasticity bode well for a carbon tax, an energy tax, or simple tariff increases to help curb imports of gas-fired electricity from neighboring countries.

Household electricity demand in Latin America and the Caribbean: A meta-analysis of price elasticity

Studying the price elasticity of demand is essential when considering rate policies in the electricity sector. This research aims to perform a meta-analysis and a meta-regression of the price elasticity of electricity demand for the residential sector in Latin American and Caribbean countries. Results show that the true value of the short-term price elasticity is between −0.197 and −0.468 and, for the long-term, is between −0.252 and −0.331. Findings differ substantially when studies are classified by their quality in econometric procedures. The long-term price elasticity seems to be lower than estimates found for other regions.

Price Elasticity of Electricity Demand in China

Price Elasticity of Electricity Demand in China

The price elasticity of electricity demand when marginal incentives are very large

Using unique data on Swedish households, we measure the price elasticity of electricity demand for households facing a mandatory non-linear distribution tariff, where households are charged based on their maximum consumption during a month, and where the marginal incentives are very large. We estimate the price elasticity using both 2SLS and bunching estimators, and we find that the price elasticity is smaller than what many previous studies on electricity demand have found.We show that the 2SLS estimates are not robust to changes to the set of controls or to the sample definition, while the bunching estimates suggest that the price elasticity of electricity demand is small in response to the large marginal incentives.Furthermore, we illustrate why charging households based on maximum consumption during a month leads to weak incentives in the end of the month, and discuss alternative tariff designs.

Impact of Revised Time of Use Tariff on Variable Renewable Energy Curtailment on Jeju Island

Jeju Island announced the “Carbon Free Island (CFI) Plan by 2030” in 2012. This plan aims to replace conventional generators with distributed energy resources (DERs) up to a level of 70% by 2030. Akin to Jeju Island, as DERs have been expanded in islanded power systems, variable renewable energy (VRE) has become a significant component of DERs. However, VRE curtailment can occur to meet power balance, and VRE curtailment generally causes energy waste and low efficiency, so it should be minimized. This paper first presents a systematic procedure for estimating the annual VRE curtailment for the stable operation of the islanded power systems. In this procedure, the VRE curtailment is estimated based on the power demand, the grid interconnection, the capacity factor of VRE, and conventional generators in the base year. Next, through the analysis of the hourly net load profile for the year in which the VRE curtailment is expected to occur, a procedure was proposed to find the season and hour when VRE curtailment occurs the most. It could be applied to revised Time-of-Use (ToU) tariff rates as the most cost-effective mitigation method of VRE curtailment on the retail market-side. Finally, price elasticity of electricity demand was presented for applying the revised ToU tariff rate scenarios in a specific season and hour, which found that VRE curtailment occurred the most. Considering self- and cross-price elasticity of electricity, revised ToU tariff rate scenarios were used in a case study on Jeju Island. Eventually, it was confirmed that VRE curtailment could be mitigated when the revised ToU tariff rates were applied, considering the price elasticity of demand.

Price Elasticity and Beyond: The Determinants of Residential Electricity Consumption in New York

The price elasticity of electricity demand has been the focus of an important literature, because of the potential impact it has on energy and economic policy. We contribute to it by looking at the state of New York case in an innovative way. We construct a three-dimensional (utility × county × year) panel dataset of electricity sales to residential consumers from 21 electric utilities in all 62 counties of state of New York over the years of 1994 to 2013 to estimate the price elasticity of residential electricity average demand (per household). Such data enables us to account for differences within a large jurisdiction, without having to rely on household-level data, which are difficult to obtain, especially over different years. We find that the short-run and intermediate-run price elasticity of demand are respectively in the vicinity of -0.04 and -0.07 and that the long-run elasticity is around -0.60. We also investigate how the price elasticity varies in different contexts, as described by time period, price level, income level, weather indicators, and other variables. We find that once we take into account the heterogeneity of contexts, the multiplicity of significant price elasticities of demand make it difficult to have a valid, global, interpretation of the impact of a price change upon households. There is such an heterogeneity of price elasticities across the different contexts that one should be cautious on its use for policy, as a single value may not represent any consumer at all.

Measuring Demand Elasticity in the Italian Power Market: a Bayesian Experiment under dual pricing scheme

This study run experiment aiming to provide a flexible and analytically elegant framework to reliably estimate the price elasticity of electricity demand. Inference pertains to the demand at hourly level in the Italian wholesale electricity market and uses individual demand bid data. Individuals' bids represent the ex-ante willingness to pay and thus allows for constructing a market demand grounded in the consumer behavior theory, by exploiting the duality approach. Bayesian econometric estimation is applied, relaxing homoskedasticity assumptions of the traditional linear regression model. It allows to identify robust results, showing that elasticity varies significantly among hours of the day, zone segmentation as well as the level of equilibrium price. Bayesian inference provides also the opportunity to include prior information sourced from previous studies and the institutional struc- ture governing the agents' behavior. This prior information involves some degree of uncertainty, for this reason Bayesian approach assigns it a probability distribution. Using Bayes rule, prior information are then updated according to the observed data. Results validate the market reform designed to foster competition and increase wel- fare even through the time-varying pricing schemes that trigger the consumers' price reaction.

Empirical Study of Relationship Between Price Elasticity of Electric Demand and Seasonal Effects

Purpose - This study investigates the estimation results of price elasticity in previous studies and examines the relationship between temperature effects, or seasonal effect, for the demand function of electricity and price elasticity of electricity demand. Design/Methodology/Approach - We use the monthly data of electricity demand and price from Jan, 1981to Dec, 2018 in KESIS and KEPCO. Estimates of demand functions for electricity using Stata 14 might be biased because of identification problems. It is necessary to analyze whether control of temperature or seasonal effects utilized in many studies significantly deal with the identification of demand functions for electricity. Findings - Past literature showed that controlled temperature or seasonal effects have tended to be more sensitive to price elasticity of electricity than those that did not. Moreover, except for industrial power, estimates of long-term price elasticity on electricity demand is more sensitive when temperature or seasonality is controlled. Research Implications - The results imply that price elasticity estimates are likely to be downward biased in demand function model on electricity with only price and income as variables and these also highlight that control of temperature and seasonality is one of the ways to identify demand.

How much household electricity consumption is actually saved by replacement with Light-Emitting Diodes (LEDs)?

Many countries have promoted the replacement of conventional lamps with next-generation lamps to reduce electricity usage for lighting. In Japan, the majority of the lamps sold at home appliance mass merchant shops have been changed from incandescent lamps to energy-saving lamps. All conventional lamps are planned to be replaced with light-emitting diodes (LEDs) by 2020. Although the energy-saving effect of LEDs has been stressed in many engineering studies, the amount of electricity that is actually saved by the installation of LEDs has not been examined. Using microlevel data from the Survey on Carbon Dioxide Emission from Households (SCDEH), we compare monthly electricity usage between households using conventional lamps and those using LEDs. Our empirical results demonstrate that households have reduced their electricity usage by 1.96% through past LEDization. Households can reduce their electricity usage by an additional 6.99% when LEDization is completed. The empirical results further demonstrate that middle-income households have higher price elasticity of electricity demand and are more likely to receive greater benefit from LED installation.

Price elasticities of residential electricity demand: Estimates from household panel data in Bangladesh

Abstract We collect a household level panel dataset to estimate the price elasticities of electricity demand for different types of urban households in Bangladesh. We use an instrumental variable estimation strategy which exploits exogenous variation in average electricity prices induced by a value-added-tax shock. The results indicate significant heterogeneity in price elasticities by electricity consumption levels. We conduct a number of simulations under alternative policy scenarios to illustrate how incorporating the heterogeneous nature of price elasticities into pricing policy can help decrease electricity demand-supply mismatch and inequality in electricity consumption. The results have important policy implications for developing countries aiming to address major energy issues by implementing tariff reforms.

Analyzing the energy system impacts of price-induced demand-side-flexibility with empirical data

This paper assesses the potential effects on the energy system from a full roll out of a smart phone app designed to connect household electricity consumers with their consumption and price data. The effects of the app in allowing greater demand-side flexibility from household consumers is estimated based on data from an 18-month field trial involving 1557 Austrian households. These estimates are given as hourly price elasticities of electricity demand and hourly energy efficiency treatment effects from consumer engagement with the app. In a novel methodological coupling, the econometric estimates are input into the Balmorel energy system model, which is used to analyze future scenarios of full renewable energy deployment in the Austrian energy system. The results demonstrate that the impact of the flexible residential demand for electricity is small but significant to future system costs. The total discounted system cost increases by 20–24% in the renewable energy scenarios, compared to a business as usual scenario, due to heavy investments in renewable generation. However, system cost is reduced by 4–7% in renewable energy scenarios where the observed demand-side flexibilities are considered. The results are subject to several methodological caveats, but they give a clear signal that ICT-enabled demand side flexibility can be an important cost-saving element that should be integrated into the future energy system and considered in system-level models.

Price Elasticity of Electricity Demand in France

[eng] Competition and climate becoming more important for electricity production and consumption, market operators are increasingly interested in reliable forecasts of electricity prices and consumption for planning their investments and regulating policies. Key for good forecasts is understanding the consumers’ reaction to price changes, synthesized by the concept of elasticity. Using a unique dataset of millions of bi-annual meter readings of electricity consumption in France from 2007 to 2015, we estimate the price elasticity of electricity expenditure of private households. We propose three specifications: a canonical one that regresses electricity consumption on a price per kilowatt/hour, where we find an elasticity equal to -0.8, a result remarkably in line and corroborating previous literature; a specification that follows Filippini’s (1995) model of an Almost Ideal Demand System (AIDS), in which we substantially replicate his results; and finally, an extension of the latter that allows elasticities to be season-dependent that shows the demand of electricity being more elastic in summer.

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.