This article proposes a fault identification method, based on the complementary analysis of the light and dark current–voltage (I–V) characteristics of the photovoltaic (PV) module, to distinguish between four important degradation modes that lead to power loss in PV modules: (i) degradation of the electrical circuit of the PV module (cell interconnect breaks; corrosion of the junction box, module cables, and connectors); (ii) mechanical damage to the solar cells (cell microcracks and fractures); (iii) potential‐induced degradation (PID) sustained by the module; and (iv) optical losses affecting the module (soiling, shading, and discoloration). The premise of the proposed method is that different degradation modes affect the light and dark I–V characteristics of the PV module in different ways, leaving distinct signatures . This work focuses on identifying and correlating these specific signatures present in the light and dark I–V measurements to specific degradation modes; a number of new dark I–V diagnostic parameters are proposed to quantify these signatures. The experimental results show that these dark I–V diagnostic parameters, complemented by light I–V performance and series‐resistance measurements, can accurately detect and identify the four degradation modes discussed. Copyright © 2015 John Wiley & Sons, Ltd. This article proposes a fault identification method, based on the complementary analysis of the light and dark current–voltage characteristics of the photovoltaic module, to distinguish between four important degradation modes that lead to power loss in photovoltaic modules: (i) degradation of the electrical circuit of the PV module (cell interconnect breaks; corrosion of the junction box, module cables, and connectors); (ii) cell microcracks and fractures; (iii) potential‐induced degradation; and (iv) optical losses affecting the module (soiling, shading, and discoloration).


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    Title :

    Fault identification in crystalline silicon PV modules by complementary analysis of the light and dark current–voltage characteristics



    Published in:

    Publication date :

    2016




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    53.36 Energiedirektumwandler, elektrische Energiespeicher