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- Copyright © 2022 Anise Rouhani et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract
Hindawi International Transactions on Electrical Energy Systems Volume 2022, Article ID 4233407, 8 pages https://doi.org/10.1155/2022/4233407 Research Article Estimating the Short-term Price Elasticity of Residential Electricity Demand in Iran 1 1,2 3 Anise Rouhani , Habib Rajabi Mashhadi , and Mehdi Feizi Department of Electrical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran Center of Excellence in Soft Computing and Intelligent Information Processing (SCIIP), Ferdowsi University of Mashhad, Mashhad, Iran Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran Correspondence should be addressed to Habib Rajabi Mashhadi; h_mashhadi@um.ac.ir Received 25 March 2022; Revised 10 June 2022; Accepted 2 July 2022; Published 13 August 2022 Academic Editor: Salvatore Favuzza Copyright ©2022 AniseRouhaniet al.)is is anopen accessarticle distributedunder the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Excessive electricity consumption causes severe problems in the electricity sector and consequently in load curtailment. )is paper estimates the short-term price elasticity of electricity demand for the Iranian household sector by monthly panel dataset. )e estimated short-term price elasticity of electricity demand was − 0.048. We use abrupt change in electricity price due to targeting th subsidy on December 18 , 2010. )e 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 re- sponsiveness and reforming electricity pricing considering equality issues and tariff design. electricity price variations [2]. So, it is necessary to estimate 1. Introduction consumers’ reactions to these price changes to evaluate peak Economic development, improving living standards, and demand reduction in different pricing programs. According population growth rate raise electricity peak demand. Due to to the well-known demand law in economics, the demand the imbalance between electricity demand and supply in for electricity like any other commodity decreases with Iran, power generation investment needs to build different increasing price, provided all other factors are kept constant. types of power plants. Supplying Iran’s peak demand in a )e sensitivity of consumer’s demand to price changes is power system operation during critical peak hours, which measured by calculating the coefficient of price elasticity of occurs in summer, is a critical problem that increases demand. In fact, price elasticity is a relative measure of the electricity system operating costs and risks to supply rate of consumer response. security. Numerous studies have been performed to calculate the price elasticity of electricity demand in different sectors of )e household sector has a high share of electricity consumption in Iran. )is sector accounted for 32% of electricity consumption in several countries. For instance, consumption and was the second-largest consumer of Filipino estimated the own-price and cross-price elasticity of electricity in the country in 2019; while the industrial sector residential electricity demand during peak periods and off- with a share of 36% and the agricultural sector with a share of peak periods in Switzerland [3]. Some existing studies ob- 14% were in the first and third ranks [1]. )erefore, strategies tained the price elasticity of household electricity in India to reduce electricity consumption can be found by studying [4–7]. Filipino et al. estimated the price elasticity of the behavior of residential consumers. household electricity demand using disaggregate level survey Aalami et al. express residential consumers usually data in India and showed that income and price elasticity of change their normal consumption patterns related to electricity demand are lower than one [8]. 2 International Transactions on Electrical Energy Systems )e electricity price in Iran is subsidized. )e subsidy is Chindarkar et al. indicate that setting a price is not appropriate for all different electricity consumption groups transfer payments by governments that can be done directly or indirectly to increase the consumers’ actual purchasing because the price elasticity of household electricity demand varies considerably in different states, different urban and power, the producers’ sale power, and greater equitable rural residential consumers, and different income groups income distribution. In addition, economic stability and [9]. Using an Indian household-level panel data, Balarama compensation for the effects of governmental policies en- et al. studied the price elasticity of electricity demand for hance the general well-being. )e Iranian Parliament passed different urban households in Bangladesh and showed in- the Iranian targeted subsidy plan or the subsidy reform plan equity among consumers due to price elasticity policies [10]. on January 05, 2010. )e governments have defined the subsidy plan as the “largest surgery” to the nation’s financial In addition, Vesterberg uses hourly power consumption data to compute the income elasticity of electricity demand system in half of a century and “one of the maximum es- sential undertakings in Iran’s current monetary history” for a Swedish region [11]. He finds that income elasticity has the highest value during peak hours for lighting and kitchen [20]. Due to the absence of smart meters in Iran, access to use, but an insignificant value for space heating. Zhou et al. defined demand as a function of income, price, and lifestyle, more frequent data on electricity consumption is still a and calculated the short-term price and income elasticity in challenge. However, in developed countries, with an esti- the urban area of China [12]. )e results show that income mation of price elasticity of electricity demand, price-based plays a small role in electricity consumption, but changes in electricity demand response programs are designed by the electricity prices have almost the same effect on different widespread application of smart meters to estimate the income levels. )e study by Filippini estimates the electricity demand curve conveniently [21]. )e purpose of this paper is to determine the short-term demand function of residential consumers during peak and off-peak periods using several economic models in Swiss price elasticity of electricity demand of residential con- sumers in Mashhad, the second-largest city of Iran, by [13]. He found that the short-term electricity of demand is less than one, and of long-term elasticity is more than one. monthly panel dataset, which corresponds to targeting subsidies time in Iran, and is one of the most important and He also stated that electricity demand could shift to the off- peak period due to rising electricity prices during the peak visible parts of the economic transformation plan that was period. carried out, which leads to an abrupt change in the electricity Some studies, e.g., [14], examined the short-term and price. For the first time, we focused on this period and long-term relationship between electricity demand and the calculated the price elasticity of electricity demand in Iran. factors affecting it. )e values of price and income elasticity Furthermore, this paper categorized the residential con- of residential electricity demand are also calculated in Sri sumers into four groups based on the price elasticity of electricity demand. Lanka. Athukorala et al. found that long-run electricity tariff reformation can play an important role in managing elec- Generally, the price elasticity of demand will vary according to the price of electricity and consumer behavior, tricity demand. Fan et al. achieved the annual price elasticity for flat rate programs in South Australia [15]; they con- and it can be used for demand response programs to reduce sidered the demand function dependence on population, the peak load. GSP (Gross State Production) temperature, and lagged price variables. Moreover, they determined how the price elas- 2. Background ticity changes at different times in a day or in different seasons. )e electricity prices of residential consumers in 30 coun- )e authors in [16, 17] show clearly that long-run tries are shown in Figure 1. As can be seen, the price of electricity demand is sensitive to changes in prices and electricity for residential consumers in Iran is much lower household revenues. )ey believe that electricity prices can than in other countries and is ranked the last among 32 be used as a tool to reduce electricity consumption. Bose countries. Countries such as Iran, Qatar, Russia, and Saudi et al. obtained the electricity demand function for different Arabia, due to their great crude oil and natural gas pro- sectors in India [7]. )e results indicated that the income duction output, have the lowest price of electricity in the elasticity of electricity demand for large industrial and world. In contrast, countries heavily dependent on fossil fuel commercial sectors is more than one, and for residential, imports for electricity generation are more vulnerable to agricultural, and small industrial sectors is less than one. market price fluctuations [22]. In fact, the cost of energy Habibollah et al. extracted the mathematical models production in Iran is much higher than what is paid by according to the price elasticity coefficient of demand in Iran consumers. )e prices paid by the consumers are very [18]. Using the mentioned models and evaluating different different from the actual prices due to government subsidies. scenarios on the country’s daily load curve, they calculated new According to Figure 2, residential consumers account for consumption curves, the amount of energy consumed and the 32.4% of the consumption share among the six sections of percentage of peak reduction. Likewise, Aalami et al. developed the total consumers [1]; due to the high volume of con- an economic model for demand response programs using the sumption of residential consumers and their significant concept of price elasticity of demand and customer benefit impact on the amount of peak electricity demand in Iran, function [19]. Furthermore, they used the proposed model to studying the behavior of residential consumers is of great investigate its effects on the energy market of Iran. importance. International Transactions on Electrical Energy Systems 3 Household electricity prices worldwide in September 2021, by select country (in U.S. dollars per kilowatt hour) 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 Denmark Germany Belgium United Kingdom Venuzuela Spain Ireland Rwanda Japan Italy Australia Kenya New Zealand France Poland South Africa Singapore Chile Israel Brazil United State South Korea China Mexico India Turkey Russia Nigeria Saudi Arabia Qatar Ethiopia Iran Figure 1: Household electricity prices worldwide in September 2021, by selected country. decreases, and vice versa; as a result, the amount of price elasticity of demand will be negative. Percentages of electricity use 2.2.PriceSlabSysteminIran. )e electricity pricing system in Iran is nonlinear. )e basic philosophy of this elec- tricity tariff is to protect low-income consumers. It is concerning how this pricing will impact the most vul- nerable consumers. Consequently, with tiered pricing, customers pay a lower rate up to particular usage and pay more for the additional electricity exceeding that threshold. )e day is broken into three periods of time. In the autumn, midpeak hours are typically around 5:00 am to 5: 00 pm. Midpeak is also known as the intermediate peak. Peak hours are between 5:00 pm and 9:00 pm. )e off-peak time band runs from 9:00 pm to 5:00 am. )ese periods are the same all weekdays, weekends, and public holidays. Prior to targeting subsidies, electricity prices were set for different consumption levels (11 steps) in midpeak, off-peak, and peak periods. According to the pricing mechanism, the first step Industrial Commercial was considered from 0 to 80kWh every month. In the peak Residential lighting period, there was an overpayment for different consumption Agriculture Public levels. Table 1 shows the price per different consumption levels Figure 2: Percentages of electricity use in different sectors of Iran. in the midpeak, off-peak, and peak period in the pricing system before the targeting subsidies, where c corresponds to 2.1.DefinitionofPriceElasticityofDemand. Price elasticity of the total consumption per month [23]. demand is the percentage of change in the amount of de- Table 2 shows the overpayment for peak and midpeak mand in proportion to the percentage of change in price, periods before targeting subsidies, but no overpayment is which is shown in the following equation: taken into account in the off-peak and first steps [23]. ΔQ P Iran’s Rial exchange rate against USD averaged 10365 (IRR/ elasticity � × . (1) USD) in December 2010, the maximum average electricity price ΔP Q per kilowatt-hour for the components of peak, midpeak, and In this formula, ∆Q is the change in electricity demand, off-peak periods was 773 Rials (7.46 cents), and the minimum and ∆P is the change in electricity price. If the price of monthly electricity price was 3398 Rials (32.78 cents). After the electricity increases, the amount of electricity demand Iranian targeted subsidy plan, seven different consumption 4 International Transactions on Electrical Energy Systems Table 1: Price and percentage of changes in marginal price before targeting subsidies. Electricity price in mid-peak period Electricity price in peak period Consumption steps Electricity price in off-peak period (Rial/kWh) (Rial/kWh) (Rial/kWh) 0–80 0 0 0 81–150 80.94 202.35 20.24 151–200 93.74 − (1276.30/c) 234.35 − (3190.75/c) 23.44 − (319.08/c) 201–250 112.75 − (3331.13/c) 281.88 − (8327.83/c) 25.63 − (757.08/c) 251–300 124.3 − (6218.63/c) 310.75 − (15546.58/c) 28.25 − (1413.33/c) 301–400 375.1 − (81458.63/c) 937.75 − (203646.58/c) 85.25 − (18513.33/c) 401–500 375.1 − (81458.63/c) 937.75 − (203646.58/c) 85.25 − (18513.33/c) 501–600 375.1 − (81458.63/c) 937.75 − (203646.58/c) 85.25 − (18513.33/c) 601–800 965.8 − (435878.63/c) 2414.5 − (1089696.58/c) 219.5 − (99063.33/c) 801–966 965.8 − (435878.63/c) 2414.5 − (1089696.58/c) 219.5 − (99063.33/c) >966 514.80 1287.00 117.00 Table 2: Overpayment for different periods before targeting subsidies. Consumption Electricity price in off- Overpayment in midpeak period (Rial/kWh) Overpayment in peak period (Rial/kWh) steps peak period (Rial/kWh) 0–80 — — — 81–150 — — —- 151–200 — — — 2 2 201–250 22.55 − (5176.23/c) + (133245.2/c ) 56.38 − (12940.57/c) + (333113.0/c ) — 2 2 251–300 49.72 − (13674.45/c) + (559676.7/c ) 124.30 − (34186.13/c) + (1399191.8/c ) — 2 2 301–400 225.06 – 105140.18/c + 12218794.5/c 562.65 – 262850.45/c + 30546986.3/c — 2 2 401–500 375.10 − (197739.63/c) + (25252175.3/c ) 937.75 − (494349.08/c) + (63130438.3/c ) — 2 2 501–600 562.65 − (332243.95/c) + (45616832.8/c ) 1406.63 − (830609.86/c) + (114042082.0/c ) — 601–800 1448.7 – 1194665.95/c + 244092032.8/c 3621.75 − (2986664.86/c) + (610230082.0/c ) — 2 2 801–966 1931.60 − (1798925.26/c) + (418443484.8/c ) 4829.0 − (4497313.15/c) + (1046108712.0/c ) — >966 1029.60 − (494208.00/c) 2574.00 − (1235520.00/c) — Table 3: Price and percentage of changes in marginal price after targeting subsidies. Consumption steps Electricity price (Rial/kWh) Percentage of changes in marginal price 0–100 270 — More than 100 to 200 320 18.51% More than 200 to 300 720 125% More than 300 to 400 1300 80.55% More than 400 to 500 1500 15.38% More than 500 to 600 1900 26.66 More than 600 2100 10.52 2.3. Electricity Bill Structure. A typical household electricity steps have been considered (see Table 3). )e first step is 0–100kWh monthly with 270Rial/kWh (2.60cent/kWh), and bill includes the following information: the second step is 100–200kWh per month with 320Rial/kWh (1) Consumer Information: name and family, postal (3.09cent/kWh). In the next steps, consumers will face higher code, address, the number of households, being marginal prices. According to this pricing mechanism, an single-phase or three-phase, and the amperes value. overpayment is considered in the peak period, and a discount is (2) Consumption information: information measured in determined in the off-peak period. )e maximum electricity peak, midpeak, and off-peak periods in the previous price, without taking the overpayment and the discount into and the current month, consumption steps and account, is 1300Rial/kWh (12.54 cent/kWh). prices in each step, and the formula to calculate the Table 3 illustrates the price and percentage of changes in the consumption cost, overpayment peak, and off-peak marginalpriceineachstepofthepricesystemafterthetargeting discount. subsidies. )e price increases gradually, third step contains the highest percentage of marginal price changes, and the seventh (3) Consumption history: 60-day consumption infor- step includes the lowest percentage of marginal price changes. mation of the last year and current year. International Transactions on Electrical Energy Systems 5 (4) Overpayment peak and off-peak discount: electricity short-term price elasticity of residential electricity demand. consumption is divided into two or three time pe- In December and January, the autumn months in Iran, riods during the day. A two-rate electricity meter temperatures are low, and electricity consumption is low due measures energy consumption during peak and off- to the lack of air conditioning. Because these consumers peak periods in kWh. A three-rate electricity meter have three-rate electricity meters, consumption information measures energy consumption during peak, mid- was used in the off-peak, mid-peak, and peak periods to peak, and off-peak periods in kWh. Consumers estimate the price elasticity of electricity demand. would face a penalty for usage during peak hours and Tables 4 and 5 summarize the descriptive statistics of the a discount during off-peak hours. key variables. In peak periods, the average electricity con- sumption in December and January is 42.08kWh and 40.81kWh, respectively. )e maximum values of monthly 2.4. -e Final Electricity Bill. )e final monthly electricity electricity consumption in December and January in peak bill, Bill paid by household i in month t, is calculated. In the it periods are 335.09kWh. In peak periods, the average elec- final bill calculated for each household, the amounts of the tricity prices charged to households in December and peak period penalty and off-peak period discount are January are 240.69Rial/kWh and 662.77Rial/kWh, respec- considered. )e average price charged to household i in tively. )e maximum values of electricity prices in December month t is calculated through the following formula: and January in peak periods are 793.52Rial/kWh and 1613.50Rial/kWh, respectively. )e minimum values of Bill it P � . (2) it electricity prices in December and January in peak periods it are 43.67Rial/kWh and 463.42Rial/kWh, respectively. According to the above formula, q (kWh) is the total )e comparison of the average electricity consumption it consumption of household i in montht and P (Rial/kWh) is values in these two months shows that the average electricity it the average electricity price charged to household i in consumption values in January compared to December in all montht. periods have decreased, while the average electricity prices in January compared to December have increased. It is noteworthy that after changing the tariff, the average electricity price charged to households is calculated during peak and off-peak periods by considering overpayment and 4. Results discounted in these periods. )e price elasticity of electricity demand is used to assess consumer behavior. As residential consumers’ load profiles 2.5. Regression Price Elasticity. Using the data panel, we vary with the price, their price elasticity of demand can be applied the fixed effect regression model to estimate the price used to develop demand response programs to control and elasticity of residential electricity demand to avoid omitted reduce peak loads in power systems. Due to the high pro- variable bias, remove the effect of those time-invariant portion of residential consumers in Iran, it is crucial to know household characteristics, and control unobserved hetero- their consumption behavior in the face of electricity price geneity in the Equation as follows: changes because they have the significant potential to manage peak loads in the network. Unfortunately, esti- ln q � α + β ln p + ε . (3) it i it it mating the elasticity of electricity demand in developing In the above equation, q is the monthly consumption of countries is difficult due to the lack of data and abrupt it household i in period t and p is the average electricity price changes in electricity prices. However, we used the period of it th charged to household i in period t, and α will be the fixed targeting subsidies on December 18 , 2010, and calculated effects in the model. We employed the log-log model, so the the short-term price elasticity of residential electricity de- coefficient β will also be the average price elasticity of res- mand for the first time. idential electricity demand. ε is the error term and the term In this paper, the elasticity of electricity demand has been it α represents the unobserved time-invariant individual ef- calculated according to the available data from the electricity fect. We estimated the short-run price elasticity by assuming consumption of 2,651 residential consumers with three-rate that climatic conditions, household size, and household electricity meters in Mashhad in December and January. income do not vary over the study period. Data analysis was performed in a multistep process during which the collected data were processed. As seen in Table 6, mean, mid, maximum value, mini- 3. Data and Methodology mum value, and standard deviation are listed for each of the We collected the dataset from one of the largest cities in Iran, research variables, respectively. When taking into account all Mashhad. )e electricity tariff was changed by the Iranian customers without classifying them, we estimate the average th targeted subsidy plan in Iran on December 18 , 2010. We short-term price elasticity of electricity demand to be − 0.048. studied how this tariff change affected the electricity con- )e results of the regression are shown in Table 7. sumption of residential consumers. We used the data panel )e price elasticity of electricity demand can be applied to of 2,651 consumers living in Mashhad. According to the different pricing programs to decrease peak electricity demand. Iranian targeted subsidy plan data, we used the consumption An appropriate electricity pricing program design requires information for December and January to estimate the knowing how the price elasticity of peak electricity demand 6 International Transactions on Electrical Energy Systems Table 4: Descriptive statistics. Midpeak period Peak period Off-peak period Midpeak period Peak period Off-peak period electricity electricity electricity electricity electricity electricity consumption in consumption in consumption in consumption in consumption in consumption in December (kWh) ِ December (kWh) December (kWh) January (kWh) January (kWh) January (kWh) Mean 87.22 42.08 54.36 85.02 40.81 53.07 Median 75.06 36.37 45.41 73.29 35.18 43.85 Maximum 805.07 335.09 1293.77 975.06 335.09 1293.77 Minimum 7.87 0.21 0 7.87 0.21 0 Std. Dev 58.59 27.36 46.64 58.66 26.55 47.21 Skewness 3.65 3.14 9.46 4.27 3.26 9.90 Kurtosis 31.79 23.29 206.87 44.18 25.7 209.4 Jarque-bera 97409.6 49843.9 4630728 195369.7 61648.6 4749913 Probability 0 0 0 0 0 0 Sum 231230.3 111558.2 144113.8 225377.1 108195.2 140690.3 Sum sq. Dev 9097728 1982991 5766037 9117728 1867539 5907612 Observation 2651 2651 2651 2651 2651 2651 Note. Table 3 provides descriptive statistics for our household-level panel data. )is table illustrates descriptive statistics for the variables of the monthly electricity consumption of households in midpeak, peak, and off-peak periods of December and January. Table 5: Descriptive statistics. Average electricity Average electricity Average electricity Average electricity Average electricity Average electricity price during price during peak price during off- price during price during off- price during peak midpeak period in period in peak period in midpeak period in peak period in period in January December (Rial/ December (Rial/ December (Rial/ January (Rial/ January (Rial/ (Rial/kWh) kWh) kWh) kWh) kWh) kWh) Mean 103.78 240.69 28.14 362.77 662.77 212.77 Median 88.08 220.05 22.3 317.97 617.97 167.97 Maximum 793.52 793.52 120.1 1313.5 1613.50 1163.50 Minimum 33.67 43.67 20.78 163.42 463.42 13.42 Std. Dev 69.82 126.12 14.68 133.13 133.13 133.13 Skewness 6.09 2.23 2.70 3.66 3.66 3.66 Kurtosis 50.37 10.38 10.9 19.69 19.69 19.69 Jarque-bera 264264.2 8214.6 10149.1 36683.07 36683.07 36683.07 Probability 0 0 0 0 0 0 Sum 275116.6 638062.8 74613.5 961705.3 1757005 564055.3 Sum sq. Dev 12919131 42153584 571419.8 46967913 46967913 46967913 Observation 2651 2651 2651 2651 2651 2651 Note. Table 5 illustrates descriptive statistics for the variables of the average electricity price charged to households in midpeak, peak, and off-peak periods of December and January. changes between consumers. Hence, to examine the hetero- )ey have to significantly reduce their additional electricity geneity of price elasticities in the peak period, we classified consumption to maintain other needs when their average households into seven groups based on monthly consumption price rises. On the other hand, consumers in the last steps are to explore the heterogeneous consumption pattern. affluent and do not care about the rise in average price. Figure 3 shows the average elasticity during the peak Additionally, the principal reason for the lower price elas- period per consumption step. Results indicate that most ticity of electricity demand in our case study is that con- sumers did not need to use the air conditioner due to low households are willing to reduce electricity demand when they face higher average prices of electricity. However, there temperature. is significant heterogeneity in electricity price elasticity Finally, in Iran, there are two categories for residential between the various consumption levels. Furthermore, the electricity consumption: low-usage consumers use less than maximum average elasticity is in the sixth step, and the the consumption pattern that is the monthly electricity minimum average elasticity is in the first step. Because low- consumption, which is determined based on climate zones usage households are often low-income households re- and seasonal temperature changes, and high-usage con- quiring a minimum kWh for basic needs, they cannot sumers use more than the consumption pattern. change their consumption when the average price increases. According to the price elasticity of electricity demand for However, the consumers in the sixth step have the highest different consumption groups in Figure 3, we find that price electricity of demand and often have a medium lifeline. clustering consumers into two groups (low-usage and high- International Transactions on Electrical Energy Systems 7 Table 6: Descriptive statistics of variables. Variable names Logarithm of monthly electricity consumption (kWh) Logarithm of average electricity price (Rial/kWh) Mean 3.87 5.12 Mid 3.88 5.34 Maximum 7.17 7.39 Minimum − 2.99 2.59 Std. Dev 0.69 1.09 Observations 15906 15906 Table 7: Results of regression. Variable Coefficient Standard error t-statistic Probability Ln (price) − 0.048 0.002 − 21.84 0.0000 c 4.12 0.012 353.32 0.0000 Weighted statistics R-squared 0.81 S.E of regression 0.43 Adjusted R-squared 0.77 Sum. Squared residue 2422.7 F-statistic 21.4 Prob (F-statistic) 0.000000 Note. Table 7 shows the results of the regression. F-statistic, t-statistics, and the corresponding p-value are reported. R-squared is 0.81, which indicates that the independent variables explained about 81% of the variation that occurred in dependent variables in a regression model. AVERAGE ELASTICITY IN PEAK PERIOD PER CONSUMPTION STEPS 0-100 100-200 200-300 300-400 400-500 500-600 >600 -0.01 -0.02 -0.03 -0.04 -0.05 -0.06 -0.07 -0.08 -0.09 CONSUMPTION STEPS Figure 3: Average elasticity in peak period between different consumption steps. usage consumers) is incorrect. Consumers in the sixth and calculate the price elasticity of electricity demand. Unfor- fifth steps have a medium lifeline with the highest re- tunately, the electricity price in Iran is very different from the sponsiveness. Consumers in the first step have the lowest actual price due to government subsidies, and consumers’ responsiveness to price changes. Due to the heterogeneity of reaction to price rise is slight. )erefore, electricity pricing in consumer’s electricity price elasticity, it is better to change Iran is needed to reform. the classification into four groups: vulnerable consumers Using the targeting subsidies shock that occurred on th (with monthly consumption lower than100 kWh), low-us- December 18 , 2010, we used the panel data of 2,651 res- age consumers (with monthly consumption between 100 idential consumers with a fixed effect regression model. )e and 400 kWh), medium-usage consumers (with monthly estimated short-term price elasticity of electricity demand consumption between 400 and 600 kWh), and high-usage was -0.048. We have examined the price elasticity of elec- consumers (with monthly consumption more than 600 tricity demand of residential consumers with different kWh). consumption levels. We find significant heterogeneity in electricity price elasticity between the various levels of consumption. Low-consumption consumers are pro- 5. Conclusion portionately inelastic; however, medium-consumption consumers are the most responsive to price increases. Fi- In this study, we have investigated the residential electricity nally, the high consumption consumers are more flexible demand and examined how price changes affect electricity than the low consumption consumers but not as responsive consumption in a household in Mashhad; one of the largest as the medium-consumption consumers. cities in Iran. Knowledge of consumer behavior is crucial, as )is study provides more information about the behavior residential consumers create a significant potential for load of residential consumers to policymakers to reform electricity reduction due to the high share of their consumption among prices. Mainly, it can be used in critical peak pricing programs all consumers. )erefore, it is extremely important to AVERAGE ELASTICITY 8 International Transactions on Electrical Energy Systems [15] S. Fan and R. J. Hyndman, “)e price elasticity of electricity to manage peak loads. Because of different price elasticities, we demand in South Australia,” Energy Policy, vol. 39, no. 6, need to design the tariff according to the level of consumption pp. 3709–3719, 2011. to decrease inequality between consumers. [16] F. Jamil and E. Ahmad, “Income and price elasticities of electricity demand: aggregate and sector-wise analyses,” En- Data Availability ergy Policy, vol. 39, pp. 5519–5527, 2011. [17] K.-M. 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Journal
International Transactions on Electrical Energy Systems – Hindawi Publishing Corporation
Published: Aug 13, 2022