جستجوی مقالات مرتبط با کلیدواژه "تقاضای برق" در نشریات گروه "اقتصاد"

The purpose of this study is to evaluate the impact of demand management policies on electricity consumption saving in the household sector in Iran during 2010-2017. The results confirm that household electricity demand is an inverse function of electricity price, household dimension, cooling requirement, and gas price in the second 5 months of the year and energy intensity index. Household electricity demand is also a direct function of gas prices in the summer, heating needs and income. According to the results, the average short-term and long-term price elasticity of electricity demand in Iran are estimated at -0.03 and -0.13, respectively. Electricity consumption in the previous period was the most influential variable in the trend of electricity consumption during the studied years in the domestic sector in Iran. Given the diversity of climate and the need for heating and cooling, which is one of the involuntary factors leading Iranian citizens to increase energy consumption, it is necessary to pay attention to non-price policies in the home and building sector

Estimating electricity demand elasticity in different sectors has been an essential research topic. Considering the fact that pricing electricity in various countries does not follow the same rules, many econometrics methods have been developed to estimate this crucial parameter. Electricity demand elasticity is defined as the percent change in electricity consumption in response to one percentage change in electricity price. Having a correct estimate of this parameter would help policymakers to price electricity properly in order to reach desirable goals in electricity consumption optimization and many other aspects of electricity consumption. In Iran, Tavanir which is a subsidiary of the Ministry of Energy, announces the price schedule of electricity in different months and regions. Examining the price schedules in different counties would make it clear that there are neighboring counties in which the imposed tariffs are not the same. In this research, using the fact that there are different tariffs imposed in some neighboring countries, the regression discontinuity design is exploited to identify the household electricity demand price elasticity causally. The findings of this research suggest that on average, increasing the electricity price by one percentage would lead to the decrease of electricity consumption by around 0.4 to 0.7 percent.

The energy sector has always been considered as one of the key and influential sectors in the country's economy and the analysis of the interaction effects of this sector or other productive sectors and the impact of decisions and policies related to those sectors and various economic factors such as households is very It is important. In the Iranian economy, energy carriers, especially electricity, are subject to subsidies and The government provides electricity to the people at a price far below cost. Therefore, it always incurs heavy costs for providing hidden subsidies. according to the Law on Targeted Subsidies, the government is obliged to liberalize the prices of various energy carriers, including electricity, in stages, and this liberalization has always acted as a shock, and this shock will have several effects on electricity demand. Therefore, the purpose of this study is to estimate the short-term and long-term effects of electricity prices on household electricity demand in the provinces of Iran.

This study uses experimental data to study and estimate the response of household electricity demand to electricity prices in the provinces of Iran based on the ARDL panel method in the period 1991 to 2014. For this purpose, the household electricity demand function is a function of the average current price of electricity, the average current price of natural gas as a substitute, the number of hot days of the year and the average household income. In order to investigate the effect of electricity price shocks, the electricity price variable has been divided into two variables, electricity price shock and electricity price trend, using the Hodrick Prescott filter.

The results of model fit show that price shock elasticity is in the short run (-0.06) and in the long run the price elasticity is (-0.38). The price elasticity is in the short run (-5.39) and in the long run (-52.40). In addition, the findings show that the consumption of the previous period always has a positive and significant effect on electricity consumption of the current period. as one unit of increase in electricity consumption in the previous period, causes an increase of 0.32 units of electricity consumption in the current period. Gas price as a substitute commodity also has a positive and significant effect on electricity consumption in the household sector in the same period, the variable coefficient of electricity price (trend) has a negative and significant effect on electricity consumption in the current period in the household sector.

This study shows that in Iran, electricity for home consumers is a short-term commodity and a long-term commodity in the long run. and the short-run and long-run income trend suggests that electricity is a normal commodity among home consumers. Cross-tensile examination of the gas indicates that the gas is a traction product and a substitute for electricity. Examination of the effect of temperature also shows that this variable will have a positive effect on power consumption. The error correction study also shows that in each period, 69% of the imbalance in household electricity demand is moderated and moves to the long run. Examination of the error correction factor also shows that in each period, 69% of the imbalance in household electricity demand is adjusted and moves towards a long-term value. The study of the effect of air temperature also shows that with increasing air temperature, the amount of electricity consumption in the residential sector increases. The results also show that the percentage of urban population has a positive effect on electricity consumption in the household sector but is not statistically significant.

This paper aims to model total electricity demand (incremental) in order to estimate price and income elasticities using provincial data and the spatial panel data method. Electricity demand at the province level is influenced by climatic zones, which can be divided into temperate, cold and sub-tropical. This paper uses time series data for electricity demand in Iran’s 28 provinces, taking into account climatic factors as well as income and price elasticities.  We use Elhorst methodology and likelihood-ratio test to compare spatial patterns in order to select the best method compatible with the theoretical model. The results indicate a  price elasticity of electricity demand (-0.08), cross elasticity of electricity demand (-0.6565), income elasticity (0.11) and elasticity of demand to temperature changes (1.9). In other words, electricity demand is minimally sensitive to changes in electricity prices and natural gas prices and income, but sensitive to changes in temperature (elastic). Our cross elasticities and income elasticity indicate that electricity and natural gas are substitutes for each other and can be considered essential goods based on their income elasticity.

The aim of this study is to present two time-series forecasting models and combine these models to provide a short-term prediction for hourly electricity demand, using daily electricity consumption data for the period 2006-2011. The first model is based on the decomposition of the electricity load into deterministic and stochastic components and the second model is based on the assumption that the electricity load is a stochastic time series. Once the hourly demand for electricity load is predicted using the above-mentioned models, the performance of the combined model is compared with the two time-series models and also with the dispatching unit model (a multi-variable model in which the weather variable is also included). The results show that the use of the combined model leads to an increase in prediction accuracy over the two time-series models. Moreover, the accuracy of the combined model is as good as the dispatching unit model for most of the time during the day, and even better during the consumption peak hours.

Following the rise of the fuels that power plants consume in the deregulated market، an increase in the electricity prices would be expected. This article tries to study the effects of power plants’ fuel prices adjustment on the amount of increase in electricity prices in the market. The components of the deregulated power market were modeled in the systems dynamics method with the aim of finding a reasonable answer to the question of this research. The model encompasses three parts، namely demand، price and production run through powersim software. The change in the prices of fuels delivered to power plants is considered as the policy variable of the model. The results of running the model illustrated that it is anticipated that the price of electricity will reach 409 rials in a kilowatt per hour by the end of the period providing that the power plants’ fuel prices are not adjusted. If the prices of fuels delivered to power plants are adjusted، the power market prices will reach 556 and 585 rials in a kilowatt per hour by the end of the period، assuming that the price growth may be by 5 or 8 percent، respectively. In the final part of the paper، the effect of economic growth increase as well as that of value added taxation on power market is analyzed in the framework of a suggestion model. Therefore، in such a case، assuming a 6 and 8 percent price growth، the prices of power market will reach 611 and 641 rials in a kilowatt per hour by the end of the period.