An adaptive neuro-fuzzy inference system employed cuk converter for PV applications

Abstract

An Adaptive Neuro-Fuzzy Inference System based Intelligent Algorithm for Photovoltaic (PV) application proposed in this paper. Under the nonlinear behavior of the surroundings, the proposed algorithm achieves optimal power point (OPP) without prior system knowledge. Compared with other intelligent methodologies, the proposed algorithm has low implementation cost, as it does not need any sensors to measure solar irradiance. The proposed algorithm provides proper training to the PV system under varying PV insolation. Modeled Cuk converter employed PV system is validate by simulated responses present in the paper. Inverter with Fuzzy logic control (FLC)-dSPACE board is also implement for sinusoidal current injection to the utility grid. © 2019 IEEE.