Optimal Battery Energy Storage Placement in PV-connected Network Considering Uncertainty

Abstract

The recent distribution network has been widely equipped with renewable energy resources. In such conditions, photovoltaic (PV)-connected systems have a significant challenge concerning mismatching the supply and demand. Battery energy storage systems (BESS) are a proper solution to overcome this issue. In this paper, an optimal placement framework to determine the best site and size of BESS in PV connected systems is presented. Meanwhile, the uncertainty of the system is caught through the K-means data clustering algorithm, and day-ahead data is provided. Since the proposed approach leads to a mixed-integer nonlinear programming (MINLP) problem, particle swarm optimization (PSO) as an evolutionary method is employed to solve the problem. A modified 51-bus distribution test system is employed to verify the proposed method. Simulation results determine the optimal site and size of batteries in the system. Moreover, the impact of cooperation of PV and BESS in the system load shedding is considered as well. Finally, a sensitivity analysis on the level of load shedding is performed and discussed.