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Intermittency of the wind power output is a main problem in wind energy extraction. To cope with this problem, pumped-storage units have been introduced. This paper investigates the combined optimization of a wind farm and a pumped-storage facility for the point of view of a generation company in a pool based electricity market. The optimization model is formulated as a two-stage stochastic programming problem with three random parameters: electricity price, wind generation, as well as units’ unavailability. In the proposed stochastic model, the optimal offering strategies for the day-ahead electricity market are the “here and now” decision variables while the optimal operation of the facilities are the recourse variables. In order to better show the effect of pumped-storage units on cost reduction and/or profit increment, a joint configuration is proposed and its results compared with uncoordinated operation.

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Following the restructuring in electricity industry and competitive market debut in iran, risk control is one of the requirements of the economic management and effective activity for major actors in electricity market. This paper introduced portfolio theory and the mean - variance approach and the conditional value-at-risk for risk management in electricity market which are two major risk management methods in financial issues and also the application of this method in electricity market of iran is presented. Although there are major differences between electricity and power markets and other markets, but the studies show that using more generalized financial models, Appropriate Approach can be achieved for risk management in a competitive market.

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Analysis of players behavior and electricity markets conditions through simulation can assist market decision-makers in appropriate designing and policy-making before actual implementation and can reduce costs and possible future problems. Considering ancillary service markets in addition to the energy market in simulations makes possible to compare and evaluate different market auction and commodity allocation models more efficiently. In this article, impacts of implementing different models of sequential and simultaneous allocation of energy, spinning reserve and replacement reserve on players behavior, possibility of price reversal, and payments in the markets are evaluated. In this regard, first, an approach based on the multi-agent system and the reinforcement learning algorithm is presented for simulating players behavior in the energy, spinning reserve and replacement reserve markets. Then, this approach is applied on a sample system including 17 generators, with various sizes and supply costs, under sequential and simultaneous allocation models. The analysis and evaluation results obtained about price reversal conditions and payments under different models will be useful for electricity markets policy- and decision-makers.

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As the electricity industry has changed and became more competitive, the electricity price forecasting has become more important. Investors need to estimate future prices in order to take proper strategy to maintain their market share and to maximize their profits. In the economic paradigm, this goal is pursued using econometric models. The validity of these models is judged by their forecasting errors. This paper is an effort to compare the forecasting power of Artificial Neural Network (ANN), Genetic Algorithm (GA) and ARIMA models for hourly electricity prices in Iran electricity market. According to the results, ANNs has the best forecasting performance followed by GA in the second place and ARIMA model in the third place.

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It is essential to enact restrictive laws and impose penalties for private sector participants when they play an important role in different sectors of production and trading of commodities. These laws and penalties reduce antitrust activities and protect participants against illegal activities. Therefore, the study and recognition of legal and economic issues related to the competition in different markets specially in some commodity markets which play crucial role in peoples’ lives is significantly important. Energy markets, particularly power markets are really important in humans’ lives and everyone must has access to enough sustainable energy to maintain a high standard of living.  In Iran, competition rights is a new topic that has been considered based on the Article 44 Constitution of the Islamic Republic of Iran. The study of competition rights experiences around the world and using them for designing and implementing efficient laws in Iran is very important. In this article, by adopting a legal and economical approach, we study and investigate principle issues of competition rights in Iran and other countries, particularly in power markets. Then, the main features of efficient organizations which are responsible for monitoring competition rights are mentioned. Finally, the competition rights challenges in Iran power market are investigated. This research also investigates some challenges in Iran power market including structural and legislation problems that should be solved with taking some steps in order to provide competitive environment for market participants. The results of this research demonstrate some structural and legislation problems of Iranian power market which highlights the importance of paying more attention to competiton rights. Establishment of the sectoral regulator in power industry not only resolves some drawbacks of current Iranian power market regulator but also leads to a comprehensive plan for Iranian power market reforms.     

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With the adoption of the General Policy Implementation Law, Article 44 of the Constitution, the power generation sector (state power plants) has been recognized as a transferable activity to the private sector.Previously, the government exercised its sovereignty over the property With the start of the process of transferring ownership of power plants to the private sector, the issue of how to apply the Ministry of Energy's sovereignty over the private sector to generate electricity industry in order to ensure the continuation of reliable and sustainable electricity production became important.Because, in accordance with Article 44 of the Constitution, the government's responsibility to ensure a secure and sustainable electricity supply as one of the important infrastructures of public services remains strong, and the development of privatization does not interfere with this. Therefore, the implementation of privatization policies should be done by amending the relevant legal regulations in such a way that the exercise of sovereignty over the electricity generation sector after the implementation of privatization policies will not face any problems.Using the descriptive and analytical method, the present study first deals with the necessity of applying governance in the production sector of electricity industry and then by studying the current situation and examining and pathology of governance practices, the strategies of governance in the private sector of electricity industry production are examined. Provides corrective data and suggestions.

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Privacy-preserving electricity markets have a key role in steering customers towards participation in local electricity markets by guarantying to protect their sensitive information. Moreover, these markets make it possible to statically release and share the market outputs for social good. This paper aims to design a market for local energy communities by implementing Differential Privacy (DP) that provably guarantees the privacy of market participants. Besides achieving a near-optimal solution and preserving the privacy of market participants, the proposed model maintains the utility of the market data for statistical releases. The required randomization for satisfying DP is embedded as Gaussian noise in each iteration of the gradient ascent algorithm underlying the optimization process of the market-clearing problem. In numerical studies, we investigate the impacts of the privacy loss parameter on the output distribution of the market-clearing quantities and payoffs of the market participants. In addition, we demonstrate the inherent trade-off between privacy protection and social welfare in the market under different privacy regimes.