Abstract PV fouling detecting system based on neural network and fuzzy logic is proposed. Comparing with traditional methods, the proposed method is rapid adaptive and universal to all PV power station. Neural network is used to predict the maximum power point (MPP) of a PV module under any lighting conditions. Then fuzzy logic rule is used to identify the fouling condition according to the result from neural network prediction. The experiment shows that the neural network can precisely predict the MPP under any lighting environment and the fuzzy logic rules can precisely identify the fouling condition of PV modules.


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    Title :

    PV Fouling Detecting System Based on Neural Network and Fuzzy Logic


    Contributors:
    Chen, Xuejuan (author) / Wu, Chunhua (author) / Li, Hongfa (author) / Feng, Xiayun (author) / Li, Zhihua (author)


    Publication date :

    2014-01-01


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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