Flexible demand response programs modeling in competitive electricity markets

In recent years, extensive researches have been conducted on implementation of demand response programs (DRPs), aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, DRPs are divided into two main categories namely, incentive-based programs (IBPs) and time-based rate programs (TBRPs). Mathematical modeling of these programs helps regulators and market policy makers to evaluate the impact of price responsive loads on the market and system operational conditions. In this paper, an economic model of price/incentive responsive loads is derived based on the concept of flexible price elasticity of demand and customer benefit function. The mathematical model for flexible price elasticity of demand is presented to calculate each of the demand response (DR) program’s elasticity based on the electricity price before and after implementing DRPs. In the proposed model, a demand ratio parameter has been introduced to determine the appropriate values of incentive and penalty in IBPs according to the level of demand. Furthermore, the importance of determining optimum participation level of customers in different DRPs has been investigated. The proposed model together with the strategy success index (SSI) has been applied to provide an opportunity for major players of the market, i.e. independent system operator (ISO), utilities and customers to select their favorite programs that satisfy their desires. In order to evaluate the performance of the proposed model, numerical studies are conducted on the Iranian interconnected network load profile on the annual peak day of the year 2007.     

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.     

Impacts of day-ahead versus real-time market prices on wholesale electricity demand in Texas

The somewhat recent nodal market structure in Texas impacts wholesale day-ahead market (DAM) and real-time market (RTM) prices. However, comparative insights on consumer responses to both these prices have not received attention. This paper attempts to fill this void by developing a system-wide demand response model to better understand price elasticities under DAM and RTM pricing. These insights may also assist grid operators to develop improved short-term forecasts of electricity demand. Using a large dataset from the Electric Reliability Council of Texas and a hierarchical Bayesian population model, we offer new insights on how DAM and RTM pricing shapes demand for electricity, and the related consequences for maintaining a reliable electricity market.     

Modelling and forecasting Turkish residential electricity demand

This research investigates the relationship between Turkish residential electricity consumption, household total final consumption expenditure and residential electricity prices by applying the structural time series model to annual data over the period from 1960 to 2008. Household total final consumption expenditure, real energy prices and an underlying energy demand trend are found to be important drivers of Turkish residential electricity demand with the estimated short run and the long run total final consumption expenditure elasticities being 0.38 and 1.57, respectively, and the estimated short run and long run price elasticities being −0.09 and −0.38, respectively. Moreover, the estimated underlying energy demand trend, (which, as far as is known, has not been investigated before for the Turkish residential sector) should be of some benefit to Turkish decision makers in terms of energy planning. It provides information about the impact of past policies, the influence of technical progress, the impacts of changes in consumer behaviour and the effects of changes in economic structure. Furthermore, based on the estimated equation, and different forecast assumptions, it is predicted that Turkish residential electricity demand will be somewhere between 48 and 80 TWh by 2020 compared to 40 TWh in 2008.     

Demand response modeling considering Interruptible/Curtailable loads and capacity market programs

Recently, a massive focus has been made on demand response (DR) programs, aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, demand response programs are divided into two main categories namely, incentive-based programs and time-based programs. The focus of this paper is on Interruptible/Curtailable service (I/C) and capacity market programs (CAP), which are incentive-based demand response programs including penalties for customers in case of no responding to load reduction. First, by using the concept of price elasticity of demand and customer benefit function, economic model of above mentioned programs is developed. The proposed model helps the independent system operator (ISO) to identify and employ relevant DR program which both improves the characteristics of the load curve and also be welcome by customers. To evaluate the performance of the model, simulation study has been conducted using the load curve of the peak day of the Iranian power system grid in 2007. In the numerical study section, the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption are shown. In addition, by using strategy success indices the results of simulation studies for different scenarios are analyzed and investigated for determination of the scenarios priority.     

How is demand for natural gas determined across European industrial sectors?

This paper estimates the response of manufacturing sectors’ natural gas demand to price and output changes. The average response to future changes in absolute and relative prices of the manufacturing industry in an OECD country depends on the mix of manufacturing industries, particularly with respect to energy intensity and substitution opportunities in production. We estimate short and long run demand elasticities using a shrinkage estimator, which allows heterogeneous demand responses across industries for each country. Our results show that price and output elasticities are heterogeneous within the same manufacturing sector across countries. Furthermore, an output contraction due to e.g. demand shocks will generally have larger negative effects on gas demand than increases in natural gas prices.     

Demand elasticities in OECD: Dynamical aspects

Four models with different lag structures are used to express final energy demand in OECD from 1960–1982 as a function of real GDP and average energy price. The income and long-run price elasticities are not significantly dependent on the model specification, but the Koyck lag scheme, estimated in its distributed lag form, is found to give the most satisfactory results. The statistical properties of the data together with evidence of trends in the elasticities both suggest that the period of falling real prices prior to 1971 is not comparable to the present period. For the period after 1971, an income elsticity of 1.02 and a long-run price elasticity of -0.37 are obtained.     

Turkish aggregate electricity demand: An outlook to 2020

This paper investigates the relationship between Turkish aggregate electricity consumption, GDP and electricity prices in order to forecast future Turkish aggregate electricity demand. To achieve this, an aggregate electricity demand function for Turkey is estimated by applying the structural time series technique to annual data over the period 1960 to 2008. The results suggest that GDP, electricity prices and a UEDT (Underlying Energy Demand Trend) are all important drivers of Turkish electricity demand. The estimated income and price elasticities are found to be 0.17 and −0.11 respectively with the estimated UEDT found to be generally upward sloping (electricity using) but at a generally decreasing rate. Based on the estimated equation, and different forecast assumptions, it is predicted that Turkish aggregate electricity demand will be somewhere between 259 TWh and 368 TWh in 2020.     

Gasoline demand in Saudi Arabia: are the price and income elasticities constant?

ABSTRACT

The paper investigates gasoline consumption in case of oil-exporting country applying Time-varying Coefficient Cointegration approach to the data from 1980 to 2017. Empirical estimations show that long-run income and price elasticities are not constant and are responsive to price and income fluctuations in the period considered. The income elasticity of gasoline demand increased until 2014, peaking at 0.151, following growth in disposable income, before declining to 0.136 in 2017. However, consumers do not stop driving when their disposable incomes fall, resulting in a less elastic response of gasoline demand to income. Price elasticities sit in the range of ?0.31 to ?0.05, becoming less elastic when prices are low and vice versa.

The findings of the study may be useful in successful implementation of energy price reforms and implementation of environmental policies.     

The price elasticity of the residential demand for electricity in the Vepco service area

In this study, we derive seasonal estimates of price elasticities of the residential demand of electricity in the Vepco service area from a detailed integrated economietic and end-use model that does not constrain the demand function to constant elasticities with respect to the explanatory variables. The elasticity coefficients derived from the model conform to expectations based on theoretical considerations.We also examine the structural stability of the demand function for residential electricity in the Vepco service area during 1969: 2–1980: 4. Two shifts are detected, one at the beginning of 1976 and the other at the end of 1978. The first shift is attributed to the delayed reaction of Vepco residential customers to the oil embargo and the subsequent increases in energy prices; the second relates to increased energy consciousness brought about by continued high prices of energy and also by encouragement from the federal government to conserve.     

An analysis of gasoline demand elasticities at the national and local levels in Mexico

The majority of evidence on gasoline demand elasticities is derived from models based on national data. Since the largest growth in population is now taking place in cities in the developing world it is important that we understand whether this national evidence is applicable to demand conditions at the local level. The aim of this paper is to estimate and compare gasoline per vehicle demand elasticities at the national and local levels in Mexico. National elasticities with respect to price, income, vehicle stock and metro fares are estimated using both a time series cointegration model and a panel GMM model for Mexican states. Estimates for Mexico City are derived by modifying national estimates according to mode shares as suggested by Graham and Glaister (2006), and by estimating a panel Within Groups model with data aggregated by borough. Although all models agree on the sign of the elasticities the magnitudes differ greatly. Elasticities change over time and differ between the national and local levels, with smaller price responses in Mexico City. In general, price elasticities are smaller than those reported in the gasoline demand surveys, a pattern previously found in developing countries. The fact that income and vehicle stock elasticities increase over time may suggest that vehicles are being used more intensively in recent years and that Mexico City residents are purchasing larger vehicles. Elasticities with respect to metro fares are negligible, which suggests little substitution between modes. Finally, the fact that fuel efficiency elasticities are smaller than vehicle stock elasticities suggests that vehicle stock size, rather than its composition, has a larger impact on gasoline consumption in Mexico City.     

Fostering economic demand response in the Midwest ISO

The Midwest Independent System Operator (MISO) runs the power grid in 14 states and one Canadian province and has a peak demand of some 116,000 MW. Its operational area is richly supplied with reliability-triggered demand response programs such as direct load control of residential appliances and curtailable/interruptible rates for commercial and industrial customers. However, economic demand response programs are lacking. This paper discusses three different ways in which such programs can be introduced in the wholesale energy markets run by MISO. These include, first, an approach in which utilities and load serving entities move retail customers to dynamic pricing and other time-based pricing rates; second, an approach in which these same entities and possibly third-parties bid price responsive demand curves into the wholesale market; and third, an approach in which demand response is bid as a supply resource into the wholesale market.     

An analysis of the welfare and distributive implications of factors influencing household electricity consumption

The deep economic crisis and the sharp rise in electricity prices have reduced electricity demand by Spanish households. This paper aims to analyse the responsiveness of household electricity demand and the welfare effects related to both factors in the 2006–2012 period by applying a demand model estimated with the quantile regression method. The results show that the electricity consumption of medium-high income households is particularly responsive to price increases, whereas that of medium-low income households is more responsive to changes in income. The retail electricity price increases and the economic crisis have led to lower and steeper U-shape price elasticities of demand and higher and steeper N-shape income elasticities of demand. The joint impact of those two factors on the welfare of lower-income households is higher in relative terms (i.e., as a share of household income) than for other income groups. These results suggest that the economic crisis and increases in retail electricity prices have had detrimental welfare effects, especially on the lower-income segment of the population. They should be considered when financing climate and energy policies through the electricity bill and provide a rationale to take such support, which pushes the retail electricity price upwards, out of the electricity bill.     

Generators' bidding behavior in the NYISO day-ahead wholesale electricity market

This paper proposes a statistical and econometric model to analyze the generators' bidding behavior in the NYISO day-ahead wholesale electricity market. The generator level bidding data show very strong persistence in generators' grouping choices over time. Using dynamic random effect ordered probit model, we find that persistence is characterized by positive state dependence and unobserved heterogeneity and state dependence is more important than unobserved heterogeneity. The finding of true state dependence suggests a scope for economic policy intervention. If NYISO can implement an effective policy to switch generators from higher price groups to lower price groups, the effect is likely to be lasting. As a result, the market price can be lowered in the long-run. Generators' offered capacity is estimated by a two-stage sample selection model. The estimated results show that generators in higher-priced groups tend to withhold their capacity strategically to push up market prices. It further confirms the importance of an effective policy to turn generators into lower price groups in order to mitigate unexpected price spikes. The simulated market prices based on our estimated aggregate supply curve can replicate most volatility of actual DA market prices. Applying our models to different demand assumptions, we find that demand conditions can affect market prices significantly. It validates the importance of introducing demand side management during the restructure of electricity industry.     

World crude oil and natural gas: a demand and supply model

This paper examines world markets for crude oil and natural gas over the period 1918–1999; it analyzes the time-series properties of output and prices and estimates demand and supply elasticities during 1918–1973 and 1973–1999. Oil and gas prices were stable during the first period; they became volatile afterwards, reflecting deep changes in the market structure following the oil shock in 1973. Demand price elasticities were too low; however, demand income elasticities were high. Supply price elasticities were also too low. The elasticity estimates help to explain the market power of the oil producers and price volatility in response to shocks, and corroborate elasticity estimates in energy studies.     

Sectoral energy demand in Canadian manufacturing industries

Several studies have been undertaken which analyse the price elasticities of demand for energy in the aggregate manufacturing sectors of different countries. This paper investigates the impact of changing energy prices on factor demands in each of the many subsectors of manufacturing in Canada. Translog cost functions are estimated and the energy price elasticities of demand are derived. These elasticities enable us to pinpoint those sectors that will have the most difficulty in adapting to high energy prices.     

Structural change and Thailand energy demand

This paper examines the impact of changes in the structure of the economy, radical changes in economic policy and oil price shocks on the relation between Thailand energy demand and its macroeconomic determinants. The impact of these structural changes on the relationship between energy consumption, income, energy prices and structural variation is examined through unit root and cointegration tests, the cointegration relationship and the error correction model. Methods which endogenize the location of an a priori unknown break point are employed to assess the impact of structural change. In general, the recognition of structural change has lead to some unique insights. In particular, the results of some of the conventional unit root and cointegration tests are reversed once structural changes are recognized. Estimates from the cointegrating regression imply long-run income, price, and structural variation elasticities of 0.568, −0.600 and 1.046, respectively. In comparison, estimates from the error correction model suggest a higher short-run income elasticity (0.788) but lower short-run price and structural variation elasticities (−0.522 and 0.491, respectively). One of the important implications of the estimates pertains to the low price elasticity for aggregate energy demand which implies that the over-pricing of energy as a policy instrument is not likely to be very influential for restraining future energy demand. Additionally, taxes on energy prices are unlikely to achieve government goals for energy conservation and environmental improvement, although they may well be efficient for raising revenue. Copyright © 2006 John Wiley & Sons, Ltd.     

Electricity demand elasticities and temperature: Evidence from panel smooth transition regression with instrumental variable approach

This study applies a non-linear model, i.e. the recently developed panel smooth transition regression (PSTR) model, and takes into account the potential endogeneity biases to investigate the demand function of electricity for 24 OECD countries from the period 1978–2004. Our empirical results demonstrate that there is a strongly non-linear link among electricity consumption, real income, electricity price, and temperature, a result that is new to the literature. As real income rises, electricity consumption rapidly increases first, and after the level of real income exceeds approximately US$2500, its increasing rate turns slow down. An increase in electricity price has a negative or no influence on electricity consumption. Evidence of a U-shaped relationship between electricity consumption and temperature is supported, and the threshold value of temperature is approximately 53 °F, which is endogenously determined. Furthermore, the estimated elasticities of time dynamic indicate that electricity demand is income inelastic, price inelastic, and temperature inelastic. As time goes on, the absolute elasticities of electricity demand gradually decrease with respect to real GDP and electricity price, whereas they gradually increase with respect to temperature, suggesting that the impact of temperature on electricity demand is becoming more important in recent years.     

Short-run and long-run elasticities of import demand for crude oil in Turkey

The aim of this study is to attempt to estimate the short-run and the long-run elasticities of demand for crude oil in Turkey by the recent autoregressive distributed lag (ARDL) bounds testing approach to cointegration. As a developing country, Turkey meets its growing demand for oil principally by foreign suppliers. Thus, the study focuses on modelling the demand for imported crude oil using annual data covering the period 1980–2005. The bounds test results reveal that a long-run cointegration relationship exists between the crude oil import and the explanatory variables: nominal price and income, but not in the model that includes real price in domestic currency. The long-run parameters are estimated through a long-run static solution of the estimated ARDL model, and then the short-run dynamics are estimated by the error correction model. The estimated models pass the diagnostic tests successfully. The findings reveal that the income and price elasticities of import demand for crude oil are inelastic both in the short run and in the long run.     

MPC-based interval number optimization for electric water heater scheduling in uncertain environments

In this paper, interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling. First of all, interval numbers are used to describe uncertain parameters including hot water demand, ambient temperature, and real-time price of electricity. Moreover, the traditional thermal dynamic model of electric water heater is transformed into an interval number model, based on which, the day-ahead load scheduling problem with uncertain parameters is formulated, and solved by interval number optimization. Different tolerance degrees for constraint violation and temperature preferences are also discussed for giving consumers more choices. Furthermore, the model predictive control which incorporates both forecasts and newly updated information is utilized to make and execute electric water heater load schedules on a rolling basis throughout the day. Simulation results demonstrate that interval number optimization either in day-ahead optimization or model predictive control format is robust to the uncertain hot water demand, ambient temperature, and real-time price of electricity, enabling customers to flexibly adjust electric water heater control strategy.