林虹江,周步祥,冉伊,詹长杰,杨昶宇.基于遗传优化BP神经网络算法的光伏系统最大功率点跟踪研究[J].电测与仪表,2015,52(5):. linhongjiang,zhou bu-xiang,ran yi,zhan chang-jie,yang chang-yu.Maximum Power Point of Photovoltaic Generation System based on Genetic Optimization BP Neural Network Algorithm of Tracking Studies[J].Electrical Measurement & Instrumentation,2015,52(5):.
基于遗传优化BP神经网络算法的光伏系统最大功率点跟踪研究
Maximum Power Point of Photovoltaic Generation System based on Genetic Optimization BP Neural Network Algorithm of Tracking Studies
In the constant pressure control method, the author of this paper uses the BP neural network to predict the maximum power point voltage, there is a big error using genetic algorithm is proposed to optimize the BP neural network, and then use the optimized algorithm to predict the maximum power point of pv systems of voltage, and this value instead of photovoltaic power generation system based on constant voltage constant voltage parameters of the MPPT control algorithm; At the same time combined with constant voltage control method based on GA - BP neural network learning algorithm to improve constant-voltage type pv MPPT control system simulation model. Finally simulation through an example, the simulation results show that this article proposed the photovoltaic (pv) system based on GA - BPNN MPPT control algorithm can fast accurate photovoltaic maximum power point tracking, compared with the BP neural network algorithm, interference observation method and the FUZZY control algorithm, the stability is better, higher precision.#$NLKeywords: Constant pressure control；maximum power point tracking；Genetic algorithm；BP neural network；Perturb and Observe Algorithms
