Certain investigations of ANFIS assisted CPHO algorithm tuned MPPT controller for PV arrays under partial shading conditions

Abstract

This paper conceptualizes development of solar energy harvesting in partial shading situations. Two methods, namely Photovoltaic (PV) system topology design and Maximum Power Point Tracking (MPPT) techniques, can well reduce partial shading effects. An active hybrid MPPT controller suggested harvesting PV power called the Adaptive Neuro-Fuzzy Inference System (ANFIS) assisted Crowded Plant Height Optimisation (CPHO) algorithm. In the multi-string PV system configuration, the DC–DC boost converter is operated between the PV string and inverter to maximise the power yield. The duty ratio of converter must be adjusted and kept at an optimal level to obtain maximum power from the PV array. During uniform irradiance condition, the CPHO tuned MPPT controller itself gives the optimal duty cycle. Under partial shading circumstances, the PV array power versus voltage characteristics has several peaks. Hence optimal duty cycle can be obtained in two stages. In the first stage, ANFIS performs estimation of Global Maximum Power Point (GMPP), among multiple Local Maximum Power Point (LMPP) peaks and tracks close to a peak power point. The second stage CPHO algorithm fine-tunes and attains the exact point of GMPP. Hence, the suggested hybrid MPPT controller detects the GMPP more accurately and settles down the oscillations of the duty cycle in a fast manner. The performance enlivened by getting optimal duty cycle, and this proposed approach fortified through the MATLAB/Simulink platform.