Optimization of Capacity Allocation for Wind-Photovoltaic-Hydro Power Generation System Based on Particle Swarm Optimization Algorithm

Wind-photovoltaic-hydro hybrid power generation is an effective means to increase the power grid's ability to consume wind and solar energy, and the rational allocation of various power source capacities is the prerequisite for its effective application. The optimization model for the capacity allocation of wind-photovoltaic-hydro hybrid power generation systems aims to minimize the annual equivalent investment cost of the system as the objective function, with constraints such as capacity range, loss of power supply probability (LPSP), and power curtailment rate. To address the limitation of traditional particle swarm optimization (PSO) algorithms in tending to get stuck in local optima during model solving, an innovative PSO strategy is designed, which significantly improves the global search ability of the particles. Finally, the optimal ratio of wind and photovoltaic power generation capacities under a typical case system is studied, which verifies the effectiveness of the proposed model and the new algorithm, The impact of different LPSP on the calculation results is analyzed.