Abstract

To address the problem that the MPPT strategy of PV system based on BP neural network has large errors when the light intensity changes suddenly, an improved particle swarm optimization is proposed for the optimization of weights and thresholds of BP neural network, and a simulation model of MPPT control of PV system based on PSO-BP neural network algorithm is established. The test and simulation results show that the optimized BP neural network converges faster and the prediction accuracy is improved.

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