Research on Capacity Configuration of Source Network and Storage System Utilizing the Improved Particle Swarm Optimization Algorithm

With the development of renewable energy technology, The source network load storage system has turned into an important solution for guaranteeing the reliability and stability of the power system. Reasonable capacity allocation can optimize investment costs, ensure the dependability of power supply of the system and reduce the waste of renewable energy, which is crucial to improving system performance and economic benefits. A particle swarm optimization(PSO)algorithm that has been improved is put forward, combined with variable inertia weight to enhance the search ability and convergence speed of the algorithm, a complex problem is multi-objective optimization is adopted to find the premise of ensuring the power supply reliability and reducing the amount of wind and light abandon with the lowest investment cost. The proposed algorithm is applied to the small island test system for source network load storage and compared with the typical optimization algorithm. The simulation results show that the multi-objective optimization method based on the improved PSO algorithm can not only effectively realize the capacity configuration of the source network storage system, but also significantly improve the quality of the convergence speed and reconciliation, which provides a new optimization tool for the power system planning and operation.