| 基于神经网络应用的光伏阵列最大功率点跟踪 |
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| 引用本文： | 崔岩,王丽霞. 基于神经网络应用的光伏阵列最大功率点跟踪[J]. 系统仿真技术, 2009, 5(4): 241-246 |
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| 作者姓名： | 崔岩 王丽霞 |
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| 作者单位： | 汕头大学电子工程系,广东,汕头,515063 |
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| 摘 要： | 针对光伏电池输出特性的非线性,提出了1种跟踪光伏阵列最大功率点的新方法,该方法应用反向传播（back propagation）和径向基（RBF）神经网络理论跟踪光伏阵列最大功率点,在变化的环境条件下,使用MATLAB软件对这2种神经网络进行仿真,训练及测试,仿真表明,RBF神经网络比BP神经网络更快捷、更准确地跟踪了光伏阵列的最大功率点。
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| 关 键 词： | 光伏方阵 最大功率点跟踪 径向基神经网络 反向传播神经网络 |
Based on Application of Neural Networks Photovoltaic-Array Maximum Power-point Tracking |
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| CUI Yan,WANG Lixia. Based on Application of Neural Networks Photovoltaic-Array Maximum Power-point Tracking[J]. System Simulation Technology, 2009, 5(4): 241-246 |
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| Authors: | CUI Yan WANG Lixia |
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| Affiliation: | (Department of Electronic Engineering,Shantou University,Shantou 515063,China) |
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| Abstract: | Aimed at nonlinear Photovoltaic battery,this paper puts forward a new type of tracking photovoltaic arrays maximum power point,back propagation（BP）and radial basis fuction（RBF） neural network theory are applicatied in tracking photovoltaic arrays maximum power point.under changing environmental circumstances,by using the MATLAB software,simulating,training and testing the two neural network,the results showed：RBF neural network is faster and more accurate tracking of photovoltaic arrays maximum power point than the BP neural network. |
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| Keywords: | photovoltaic array maximum power point tracking radial basis fuction neural network back propagation neural network |
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