On-grid optimal MPPT for fine-tuned inverter based PV system using golf optimizer considering partial shading effect

Abstract

Improving photovoltaic systems to better withstand variations in temperature and irradiance, lessen steady-state ripples, maintain high efficiency, require less tracking time, and have minimal complexity is becoming increasingly important. The PV array's overall power output is negatively impacted by partial shading because the shaded cells produce less power and consume less power overall, which lowers efficiency and creates localized hotspots. Although bypass diodes may be used to counteract these impacts by rerouting current around cells that are shaded, they can result in several peaks, which complicates maximum power point tracking (MPPT). To manage several peaks and optimize power output, metaheuristic algorithms are compulsory. A recently developed game-based optimization methodology known as Golf Optimization Approach (GOA) is used in this study to find a way to MPPT in a grid-connected photovoltaic (PV) system under partial shading conditions (PSCs). Additionally, the same suggested approach is applied to get optimal parameters for the inverter with the goal of optimizing its voltage and current regulators. It aims to evaluate a plan to lower the output voltage and current's total harmonic distortion and DC voltage error. The proposed technique is contrasted to other tracking approaches such as the traditional Perturb & Observe (P&O), Gray Wolf Optimization (GWO), and Sea-gull Optimization Approach (SOA). Simulation is performed in MATLAB R2022b/SIMULINK environment. The obtained outcomes demonstrate the ability of the suggested technique to enhance the utility grid's power quality and improve the tracking system under various partial shading effects and temperature alterations. The proposed technique achieves a tracking efficiency of 99.8 %, surpassing the effectiveness of both of the previous methods which are at 97.2 % and 96.7 %.