Influence of Different Optimization Aalgorithms on Prediction Accuracy of Photovoltaic Output Power Based on BP Neural Network

Aiming at the problem that back propagation (BP) neural network is easy to fall into local extremum, based on the short-term prediction of photovoltaic output power using the BP neural network, this paper studies the influence of genetic algorithm (GA) and particle swarm optimization (PSO) algorithm respectively to optimize the structure of the BP neural network on the prediction accuracy of photovoltaic output power. The effectiveness of the proposed method is verified by the simulation of the actual operation data of a photovoltaic power station. The simulation results show that different optimization algorithms have a significant impact on the prediction accuracy of photovoltaic output power.