| 基于GA-RBF神经网络的光伏电池MPPT研究 |
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| 引用本文： | 姚雪梅,夏东伟,李建.基于GA-RBF神经网络的光伏电池MPPT研究[J].青岛大学学报(工程技术版),2009,24(2):10-14. |
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| 作者姓名： | 姚雪梅 夏东伟 李建 |
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| 作者单位： | 青岛大学自动化工程学院,山东,青岛,266071 |
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| 摘 要： | 讨论了光伏电池非线性输出特性,在此基础上,结合径向基函数神经网络的特点,提出了基于遗传算法优化的径向基函数神经网络方法,并将该方法用到了电池的最大功率点跟踪预测中。仿真及实验结果表明,与传统的径向基函数神经网络相比,该方法克服了网络参数选择的随机性,具有更高的精度和适应能力。
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| 关 键 词： | 光伏电池 最大功率点跟踪 遗传算法 RBF神经网络 |
Research of Maximum Power Point Based on GA-RBF Neural Network |
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| YAO Xue-mei,XIA Dong-wei,LI Jian.Research of Maximum Power Point Based on GA-RBF Neural Network[J].Journal of Qingdao University(Engineering & Technology Edition),2009,24(2):10-14. |
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| Authors: | YAO Xue-mei XIA Dong-wei LI Jian |
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| Affiliation: | School of Automation Engineering;Qingdao University;Qingdao 266071;China |
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| Abstract: | Non-linear output characteristics of PV array are discussed,and then a radial base function neural network optimized by genetic algorithm is applied to maximum power point tracking for PV array.Simulation and test results demonstrate that the proposed method can not only perfectly resolve the problem of random selection of RBF cluster center number and width value,but also have better accuracy and adaptability than traditional RBF method. |
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| Keywords: | PV array MPPT GA RBF neural network |
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