Abstract A hybrid maximum power point tracking method has been proposed for the photovoltaic system using a stochastic evolutionary search and a deterministic hill climbing algorithm. The proposed approach employs the particle swarm optimizer (PSO) to solve a dynamic optimization problem related to the control task in a PV system. The position of the best particle is updated by the hill climbing algorithm, and the position of the rest of the particles by the classic PSO rule. The presented method uses the re-randomization mechanism, which places five consecutive particles randomly, but in specified intervals. This mechanism helps track the maximum power point under partially shaded conditions.


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    Title :

    Hybrid MPPT Algorithm for PV Systems Under Partially Shaded Conditions Using a Stochastic Evolutionary Search and a Deterministic Hill Climbing


    Contributors:

    Published in:

    Publication date :

    2017




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English


    Classification :

    BKL:    53.35 Stromrichter, Transformatoren / 53.35$jStromrichter$jTransformatoren / 53.33 Elektrische Maschinen und Antriebe / 53.33$jElektrische Maschinen und Antriebe



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