A Comparative Study of MPPT Algorithms for Solar Photovoltaic Systems Under Partial Shading Conditions in South East Nigeria

Background: Partial shading from trees, buildings, and cloud edge effects creates multiple power peaks in PV module I-V characteristics, causing conventional MPPT algorithms to track false maxima and significantly reduce energy yield. Improved MPPT methods for Nigerian shading conditions are needed. Aim: This study comparatively evaluated the performance of perturb-and-observe, incremental conductance, particle swarm optimisation, and grey wolf optimiser MPPT algorithms under partial shading conditions representative of South East Nigeria. Methods: A hardware-in-the-loop simulation platform was developed using MATLAB Simulink and a dSPACE real-time simulator. Shading patterns were derived from field measurements at five South East Nigeria sites. Tracking efficiency, convergence speed, and steady-state oscillation were the key performance metrics. Results: Particle swarm optimisation and grey wolf optimiser consistently tracked the global power maximum under partial shading, achieving mean tracking efficiencies of 98.2% and 98.7% respectively. Perturb-and-observe and incremental conductance were trapped at local maxima in 37% and 29% of shading scenarios. Conclusion: Bio-inspired MPPT algorithms provide significantly superior performance under partial shading conditions. Their implementation in commercial solar charge controllers and inverters serving South East Nigerian markets is strongly recommended. Keywords: MPPT, partial shading, solar PV, particle swarm optimisation, South East Nigeria.