Scheduling and siting of storages considering power peak shaving and loss reduction by exchange market algorithm

Abstract

The large-scale integration of grid-scale energy storage systems (ESSs) motivates the development of techniques for determining the optimal ratings and locations of storage devices. To achieve the best optimal results, exchange market algorithm (EMA) is used. EMA is a new meta-heuristic method for solving the optimizing problems. This optimization algorithm is inspired by the procedure of trading the shares on the stock market. Evaluation of how the stocks are traded on the stock market by elites has formed this algorithm. This paper proposes a method for identifying the sites where ESSs should be located to perform most effectively. It has been tested on a standard 33 bus radial distribution system. A method for determining the optimal operation of ESSs to obtain the least power loss is proposed. The main purpose of the operation strategy is to minimize the peak generation in which the power plants generate with the least oscillation. To validate the effectiveness of this method different scenarios are investigated. In order to proof this optimization method, several comparisons have been done. Finally, the storages optimal charge and discharge rate, location, and power loss improvement are presented. The results show the ability of the EMA in finding the global optimum point of the storage and their hourly charging rate.