Multi-Objective Joint Planning Method of Distributed Photovoltaic and Battery Energy Storage System Based on NSGA-III Algorithm

In the context of the aggravating of the energy crisis, the penetration rate of distributed photovoltaic (DPV) in the distribution network (DN) is getting higher and higher. In view of the adverse effects caused by DPV access to the DN, this paper proposes a multi-objective joint planning method of DPV and distributed battery energy storage system (DBESS). First, considering time of use (TOU) price and the security and economic indicators of DN, the annual average comprehensive cost, voltage fluctuation and network loss of the DN are taken as the optimization objectives, and taking the location and installed capacity of DPV and DBESS as decision variables based on the results of cluster division, a multi-objective joint planning model of DPV and DBESS is constructed considering the optimal operation of DBESS. Then, an optimization framework based on the third-generation Non-dominant Sequencing Genetic Algorithm (NSGA-III) is further built to solve the model, and the objectives and variables of different planning time scale are processed separately by means of embedding power flow calculation and hybrid coding method. Finally, the effectiveness of the proposed method is verified on the IEEE-33 node benchmark system.