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文章摘要
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
Received:April 02, 2014  Revised:April 02, 2014
DOI:
中文关键词: 恒压控制法  最大功率点跟踪  遗传算法  BP神经网络  干扰观察法
英文关键词: Constant pressure control  maximum power point tracking  Genetic algorithm  BP neural network  Perturb and Observe Algorithms
基金项目:中央高校基本科研业务费资助项目
Author NameAffiliationE-mail
linhongjiang* sichuandaxuedianqixinxixueyuan 928614547@qq.com 
zhou bu-xiang sichuandaxuedianqixinxixueyuan  
ran yi sichuandaxuedianqixinxixueyuan  
zhan chang-jie sichuandaxuedianqixinxixueyuan  
yang chang-yu sichuandaxuedianqixinxixueyuan  
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中文摘要:
      本文针对恒压控制法中采用BP神经网络预测最大功率点处电压存在较大误差的情况,提出了用遗传算法来优化BP神经网络,然后用优化后的算法来预测光伏系统最大功率点之处的电压,并以此值代替基于恒电压的光伏发电系统MPPT控制算法中的恒电压参数;同时结合恒电压控制法建立了基于GA-BP神经网络学习算法的改进恒压型光伏系统MPPT控制的仿真模型。最后通过算例仿真,仿真结果证明本文所提的基于GA-BPNN的光伏系统MPPT控制算法能够快速准确的进行光伏最大功率点跟踪,相比于BP神经网络算法、干扰观察法及FUZZY控制算法其稳定性更好,精度更高。 #$NL关键词: 恒压控制法;最大功率点跟踪;遗传算法;BP神经网络;干扰观察法
英文摘要:
      In the constant pressure control method, the author of this paper uses the BP neural network to predict the maximum power point voltage, there is a big error using genetic algorithm is proposed to optimize the BP neural network, and then use the optimized algorithm to predict the maximum power point of pv systems of voltage, and this value instead of photovoltaic power generation system based on constant voltage constant voltage parameters of the MPPT control algorithm; At the same time combined with constant voltage control method based on GA - BP neural network learning algorithm to improve constant-voltage type pv MPPT control system simulation model. Finally simulation through an example, the simulation results show that this article proposed the photovoltaic (pv) system based on GA - BPNN MPPT control algorithm can fast accurate photovoltaic maximum power point tracking, compared with the BP neural network algorithm, interference observation method and the FUZZY control algorithm, the stability is better, higher precision.#$NLKeywords: Constant pressure control;maximum power point tracking;Genetic algorithm;BP neural network;Perturb and Observe Algorithms
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