Numerical Simulation and Analysis of Grey Wolf Optimization Based Maximum Power Point Tracking Under Complex Operational Conditions

Abstract

Efficiently harnessing solar energy is pivotal in the pursuit of sustainable energy sources. Maximum Power Point Tracking (MPPT) techniques are essential for optimizing the performance of photovoltaic (PV) systems, especially under challenging operational conditions. This study presents a comprehensive numerical simulation and analysis of a novel Grey Wolf Optimization (GWO) based MPPT algorithm tailored to address complex operational scenarios, including partial shading, temperature fluctuations, and varying solar irradiance. The research begins with an in-depth exploration of the GWO algorithm, a nature-inspired optimization technique. The GWO algorithm's integration with MPPT in PV systems is thoroughly investigated. A precise mathematical model, based on the single-diode five-parameter model, is employed to emulate the nonlinear characteristics of PV panels. Numerical simulations are conducted using MATLAB/Simulink with real-world data inputs, replicating diverse operational conditions. Comparative assessments are made against traditional MPPT methods like Perturb and Observe (P&O) and Incremental Conductance (IncCond). Key performance metrics, including tracking efficiency, convergence speed, steady-state oscillations, and energy yield, are rigorously evaluated. The results demonstrate the superiority of the GWO-based MPPT algorithm in complex operational conditions, with higher tracking efficiency, faster convergence, and reduced steady-state oscillations compared to conventional approaches. This algorithm particularly excels in scenarios with partial shading and rapidly changing solar irradiance. Additionally, a sensitivity analysis is conducted to fine-tune the GWO algorithm's control parameters, enhancing its adaptability to various PV system configurations. In conclusion, this study underscores the potential of Grey Wolf Optimization as an effective tool for enhancing MPPT performance in PV systems under challenging operational conditions. The findings have significant implications for the advancement of renewable energy technologies and their seamless integration into the grid, making this research valuable for engineers and researchers in the field.