Optimal configuration for power grid battery energy storage systems based on payload fluctuation guided multi-objective PSO

This article proposes a payload fluctuation guided multi-objective particle swarm optimization algorithm (PFGMOPSO) based optimal configuration strategy for power grid battery energy storage systems (BESS). This method comprehensively considers the stability and economy of distribution network operation, and establishes an optimization configuration model for BESS location and capacity by selecting node voltage fluctuations, BESS investment costs, and system active power losses as the objective functions. In response to the disadvantage of poor population diversity in traditional MOPSO algorithms, two main improvements have been made: 1) An optimal particle selection strategy has been proposed to increase population diversity; 2) the fluctuation of payload is selected as the parameter to guide particle motion, making particles move in the optimal direction and effectively utilizing system parameters to improve the convergence speed of the algorithm. Based on the IEEE33 node distribution network system, four configuration scenarios are analyzed with system simulation. With the proposed scheme, the optimal configuration area, capacity, and power of the energy storage system were selected, effectively improving the system node voltage fluctuations and line losses. Finally, a simulation comparison was conducted between the traditional MOPSO and the proposed PFG-MOPSO algorithm, which verifies the superiority of the proposed method.