Performance analyses of various commercial photovoltaic modules based on local spectral irradiances in Malaysia using genetic algorithm

Manjeevan Seera, Choo Jun Tan, Kok Keong Chong, Chee Peng Lim

    Research output: Contribution to journalArticleResearchpeer-review

    2 Citations (Scopus)


    A novel comprehensive methodology integrated with genetic algorithm (GA) has been formulated by accounting for local spectral irradiance and the specifications of commercial photovoltaic (PV) module. Despite having the same solar irradiance, variation in power conversion efficiency (PCE) of PV module can be significant in different site locations by referencing to that of standard AM1.5 spectrum. We have carried out a case study using GA for a combination of three site locations in Peninsular Malaysia and twelve types of commercial PV modules. Type-9 PV module operating in Bangi has recorded the lowest gain with 0.1%, while type-10 PV module operating in Bandar Sungai Long has shown the best gain of up to 27%. For solving multi-objective problems, MmGA and NSGAII have been applied to optimize three objectives concurrently including PCE, PV weight and PV panel area. From the simulation, type-1, type-6, and type-12 PV modules show the best in at least two objectives for the categories of m-Si, p-Si, and thin film, respectively.

    Original languageEnglish
    Article number120009
    Number of pages22
    Publication statusPublished - 15 May 2021


    • Annual energy yield
    • Commercial photovoltaic module
    • Genetic algorithm
    • Local spectral irradiance
    • Power conversion efficiency

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