Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.


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    Titel :

    Multiple Peaks Tracking Algorithm using Particle Swarm Optimization Incorporated with Artificial Neural Network


    Beteiligte:
    Mei Shan Ngan (Autor:in) / Chee Wei Tan (Autor:in)

    Erscheinungsdatum :

    29.10.2011


    Anmerkungen:

    oai:zenodo.org:1328039
    International Journal of Electrical, Electronic and Communication Sciences 4.0(10)



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629




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