Photovoltaic (PV) power generation system as an auxiliary energy device can provide electricity for ships. In addition, it contributes to reducing carbon emissions of ships and improving ships' greenness. However, the ship's PV power generation system is sensitive to be affected by the external environment. PV arrays break down occasionally during system operation, which can affect the stability of the ship's electrical system. Therefore, it is great significance to carry out the fault diagnosis research on PV power generation systems. In this paper, the ship PV power generation system simulation model is established based on the performance parameters of a barge PV power generation system. The simulation model is established in Matlab/Simulink. The characteristics of 13 faults were simulated, such as Open-circuit, Short-circuit, different degrees of Shadow shielding, and cross faults of PV arrays components. In this paper, the Cuckoo Search-Probabilistic neural network (CS-PNN) algorithm is proposed. The accuracy is verified by fault simulation data and experimental data. The result shows this method can diagnose the fault types of the PV power generation system of ships. It is very effective that can provide a guarantee for the safe and stable operation of ships.


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    Titel :

    Research on fault diagnosis of ship photovoltaic power generation system


    Beteiligte:
    Xu, Yi (Autor:in) / Gao, Song (Autor:in) / Yan, Xinping (Autor:in)


    Erscheinungsdatum :

    22.10.2021


    Format / Umfang :

    1915868 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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