Adaptive Optimization Method of Photovoltaic Power Generation Model Parameters Based on CGAPSO Algorithm

Accurately constructing the fault simulation model of new energy sources and determining the parameters is the key to the study of transient stability, which needs to rely on the actual test data to identify the parameters. However, the existing algorithms mostly rely on single condition data, which leads to poor adaptability of model conditions and large simulation deviation under non-specific conditions. Therefore, the parameter set optimization algorithm is urgently needed to improve the adaptability of the model and the accuracy of simulation. In this paper, a parameter optimization method of photovoltaic power generation model based on cgapso (cellular genetic particle swarm optimization) is proposed. The psd-bpa software is used as the test platform, and the effectiveness of the method is verified through the information sharing decision parameter set between modules.