MO-PSO Based Bi-level Multi-objective Optimal Configuration of Energy Storage System in Distribution Network

This paper considers the planning effectiveness and operational efficiency of battery energy storage systems (BESSs). A multi-objective particle swarm optimization (MOPSO) algorithm is proposed to solve the optimal solution of BESSs charging and discharging operation strategy; the outer layer aims to minimize the investment and operation cost of BESSs, voltage fluctuation and load fluctuation of distribution network. MOPSO algorithm solves the Pereto non-dominated solution set of the location-determined-volume planning scheme. The proposed algorithm achieves a balance between local exploration and global search, and effectively obtains high-quality solutions. Finally, the simulation results based on the IEEE-33 node system show that compared with the traditional multi-objective optimization algorithm, the proposed algorithm can obtain a more widely distributed and uniform Pareto front, which not only realizes the optimal investment benefit of BESSs, but also realizes the distribution of power distribution. The grid voltage quality and power stability are also significantly better than other algorithms.