Optimal Performance of Micro-grids Networks with Uncertainty using Game Theory Coalition Formulation Strategy

The demand for energy is constantly increasing, which is pushing the limitations of the current grid, increasing reliance on fossil fuels, and increasing CO2 emissions. These concerns have renewed interest in discovering ways to reduce power demand on the grid through renewable energy. However, the distribution characteristics of renewable energy make it difficult to integrate effectively into the traditional power grid. As power networks increase in scale, the drawbacks of the conventional grid, such as high cost and difficult operation, will become more apparent, and it will no longer meet increasing safety, reliability, and diversity. Therefore, applying efficient methods to improve the performance of micro-grids is necessary. In this paper the application of CRPSO algorithm based on the game theoretic formulation strategy was proposed to reduce the exchange of power between the macro station and micro-grids. The objective function of optimization involves minimizing the cost of power, loss, communication and load shedding. The advantages have caused the load of the micro-grids to be implemented as much as possible through the exchanges between the micro-grids and the cost of utilization and power supply of the loads to be minimized. Uncertainties in wind speed and solar radiation flux are also considered for the purpose of applying the random property of the distributed generation resources. The simulation results on the 33rd IEEE standard system in different scenarios indicate the desired performance of the proposed method.