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This paper presents two new methodologies for optimal placement of distributed generation (DG) in a locational marginal price (LMP) based on wholesale electricity market. A Gravitational Search Algorithm (GSA) is proposed for simultaneous power quality improvement, optimal placement and sizing of fixed capacitor banks in radial distribution networks with nonlinear loads and distributed generation (DG) imposing voltagecurrent harmonics. In distribution systems, nonlinear loads and DGs are often considered as harmonic sources. For optimizing capacitor placement and sizing in the distribution system, objective function includes the cost of power losses, energy losses and capacitor banks. In this study, new fitness function is used to solve the constrained optimization problem with discrete variables. Simulation results for modified 12 IEEE are presented and solutions for the proposed method are compared with previous methods. The proposed methods complyengineering aspects of system operation and economic aspects of market operation and act as good indicators for the placement of DG, especially in a market environment. In order to provide a scenario for DGs available, several cost characteristics are assumed. For each DG cost characteristic, an optimal placement and size are identified for each of the objectives. Results show that proposed GSA method could be effectively used for optimal capacitor placement and sizing in distorted distribution systems.

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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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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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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.

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One of the recent developments in power systems in order to increase the competitive environment and gain technical advantages is the expansion of electrical connections among various countries and the development of regional electricity markets. In this situation, the participation of market players is provided in international electricity markets in addition to local markets. In this article, considering the geographical location of Iran, the state of restructuring, the challenges of the production sector, and the increase of energy exchanges, the issue of developing a regional market with neighboring countries centered on Iran has been evaluated. For this purpose, firstly, the electricity industry structure of twelve neighboring countries of Iran with water and land borders has been analyzed and compared. Then, 18 important criteria for determining regional market development priorities have been identified and introduced. In the following, coefficients for different criteria have been assigned with expert survey and entropy methods, and by using SAW, TOPSIS, and Vikor multi-criteria decision-making methods, the priority of countries in connecting to the regional market has been determined. Finally, a comprehensive model for creating a regional market centered on Iran in a twenty-year time horizon has been proposed. The proposed model is divided into five phases with periods of three to five years for market development.