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基于神经网络的光伏发电最大功率点跟踪算法
引用本文:苏海滨,卞晶晶,刘强,卜自珍. 基于神经网络的光伏发电最大功率点跟踪算法[J]. 华北水利水电学院学报, 2010, 31(6): 80-83
作者姓名:苏海滨  卞晶晶  刘强  卜自珍
作者单位:[1]华北水利水电学院,河南郑州450011 [2]河南省朝阳建筑设计有限公司,河南郑州450011 [3]北京市密云水利局勘察设计所,北京101500
摘    要:由于光伏阵列电压和电流的非线性,光伏发电输出能量存在最大功率点.为提高光伏发电系统的发电效率,提出了一种基于神经网络和Cuk变换器对光伏阵列最大功率点跟踪的算法.神经网络输入变量为温度和光照强度,学习算法采用梯度下降法,输出量为电压信号,用于调节Cuk变换器的开关占空比.仿真结果表明,该算法最大功率点跟踪控制精度较高,响应迅速,且系统适应性良好.

关 键 词:光伏发电  最大功率点跟踪  神经网络

A Tracking Method of the Maximum Power Point for Photovltatic Power Generation Based on Neural Network
SU Hai-bin,BIAN Jing-jing,LIU Qiang,BU ZI-zhen. A Tracking Method of the Maximum Power Point for Photovltatic Power Generation Based on Neural Network[J]. Journal of North China Institute of Water Conservancy and Hydroelectric Power, 2010, 31(6): 80-83
Authors:SU Hai-bin  BIAN Jing-jing  LIU Qiang  BU ZI-zhen
Affiliation:1.North China Institute of Water Conservancy and Hydroelectric Power,Zhengzhou 450011,China; 2.Chaoyang Architectural Design Co.,Ltd.Company,Zhengzhou 450011,China; 3.Beijing Miyun Water Authority Survey and Design Office,Beijing 101500,China)
Abstract:Because of the photovoltaic array voltage and current are non-linear,there is a maximum power point of PV output energy.To improve the efficiency of electricity generating systems of PV,on the basis of the the neural network and Cuk converters,a tracking algorithm is presented for the maximum power point of photovoltatic arrays.Input variables of neural network are temperature and irradiance.Learning algorithm uses Gradient descent learning algorithm.Output is a voltage signal for regulating the Cuk converter switch duty ratio.Simulation results show that this method for the maximum power point tracking control can achieve relatively high precision error,fast response,and the system adaptability is good.
Keywords:photovoltaic power generation  the maximum power point tracking  neural network
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