RBFN based MPPT algorithm for PV system with high step up converter

Abstract This paper proposes a neural network (NN) based maximum power point tracking (MPPT) algorithm for photovoltaic (PV) system with a high step–up converter design. The proposed methodology uses Radial Basis Function Network (RBFN) in NN algorithm for MPPT and the results are compared with classical perturb and observe (P&O) method and incremental conductance (INC) method. Also, to improve the voltage rating, a new modified Single Ended Primary Inductor Converter (SEPIC) is proposed and the results are validated with boost and SEPIC converter. The performance of the proposed algorithm is verified for various irradiance and temperature conditions.

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