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The Iranian electricity market is undergoing the first decade of restructuring. Effective competition in wholesale electricity market is a necessary feature of successful electricity industry restructuring. The paper examines the degree of competition in the Iranian electricity market during March to September 2009. The competitive benchmark analysis has been used to simulate producer’s behavior as a price taker firms and compare the competitive market results with actual market outcomes. The competitive benchmark has been calculated through generation costs of producers. Moreover, the possibility of execution market power has been considered by structural index. The finding indicates that the Iranian electricity market has a considerable potential to exercise power market and there were significant departure from competitive behavior during 2009.

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  Storing the electrical energy in large scale is impossible. So, it is necessary to identify the factors affecting the electricity demand. Researchers have used different methods to forecast the future demand of electricity, among them intelligent methods and fuzzy based methods are more popular. Since ANFIS structure is based on researcher’s experience about phenomenon, the created structure may not have the best result. Therefore, we used PSO-ANFIS structure.

  In this paper long term electricity demand is forecasted until the year 2025 by hybrid PSO-ANFIS algorithm. The results confirm the high power of the Adaptive Neural based Fuzzy Inference System in forecasting the electricity demand. Results also indicate that the forecasted electricity demand will be 401 billion KWh in 2025. The prediction performance of the proposed technique is more accurate than the ARIMA model.

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Efficiency analysis plays an important role in price regulation in the electricity distribution sector. This paper analyses efficiency and productivity of 38 electric distribution companies in Iran from year 1387 to 1389 (Iranian calendar year) by using slack based model (SBM). Super efficiency analysis is employed to rank full efficient companies. According to results, Tabriz, Ahwaz and north Khorasan companies have best performance among others. To examine importance of losses inclusion as input on super efficiency scores, statistical tests are utilized. Results indicate significant difference in super efficiency scores with and without accounting for losses. Average productivity index of total companies has declined by 4 percent under investigated period. Further, Panel data analysis applied to specify determinants of super efficiency of electricity distribution companies. According to results, Loss rate, network density and transformer load factor are the main determinants of super efficiency.

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The Iranian electricity industry has been restructured following the global experiences. The main objective of restructuring is transition from natural monopoly towards competition in order to improve efficiency. Currently, the Iranian electricity market is performing as imperfect competition and Pay-as-Bid (PAB) auctions are the major trade mechanism in this market. This paper proves that Supply Function Equilibrium (SFE) is an appropriate approach to analyze behavior of the Iranian electricity market. Isfahan electricity market has been considered as a case study in which SFE is applied (regarding marginal cost estimation as well as demand uncertainty). The derived SFE indicates that there is major difference between SFE and Nash equilibrium.

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The shares of state-owned or public companies are supplied in privatization plan. If the financial market be clear and efficient, it is expected that discovered price of supplied shares be efficient too. However, there is no guarantee for the fulfillment of this condition. Specially, implementation of those policies that, for example, a shock to exchange rate or the price of inputs (such as fuel), can affect market efficiency to discover efficient price of shares. In this study, the factors that cause the deviation of the actual share price have been identified, at first. After that a computable system has been designed by implementation error corrector filters. The input of this system is biased variable and corrected variable is the output. In this study, comparing previous studies, is generalized. So computable designed model can evaluates a wide range of factors. This system has been used to calculate the share of Tehran Regional Electricity Company. The outcomes show that the value of its shares is change from a negative amount (based on bias variables) to 2445 billion Rials (after passing based variable from correction filters). This difference, in addition of information asymmetry, maybe causes, in special in energy and electricity sectors, some opportunities to rent.

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In this study, the electrical energy consumption in Tehran before reduction subsidies and after targeting subsidies was examined with using a dataset collected from household subscribers Tehran Electricity Distribution Company from August 2000 to November 2012. After review and analysis values, a model was proposed for predicting power consumption. The proposed model was a combination of trigonometric coefficients and power factors. The best values were obtained by using a genetic algorithm.
Procedure of electrical energy consumption in Tehran after Implementation of subsidies reduction plan was compared with the predicted model of electrical energy consumption in Tehran before Implementation that plan. The results indicated that implementation of subsidies reduction plan reduced electrical consumption growth rates and also a little reduced consumption rate. The other results of this study contain consumption patterns in order to manage the future consumption level of electrical consumers in Tehran. Also the results showed that, because demand for electricity is inelastic to price and income in the short time, as a result price policies cannot be effective in controlling the electricity demand, then should use non-price and intensive policies to reduce the consumption of electricity.