Particle Swarm Optimization with Targeted Position-Mutated Elitism (PSO-TPME) for Partially Shaded PV Systems

In partial shading situations, the power–voltage (P–V) characteristics of photovoltaic (PV) systems become more complex due to many local maxima. Hence, traditional maximum power point tracking (MPPT) techniques fail recognize global (MPP), resulting in a significant drop produced power. Global optimization strategies, such as metaheuristic approaches, efficiently address this issue. This work implements recent “particle swarm through targeted position-mutated elitism” (PSO-TPME) with reinitialization mechanism on PV system under conditions. The fast-converging and exploration capabilities PSO-TPME make it appealing for online optimization. also offers flexibility tuning particle classifier, elitism, mutation level, probability. analyzes several parameter settings MPPT partially shaded systems. Simulations varying patterns show that PSO-TPME, balanced exploitation–exploration settings, outperforms PSO terms convergence speed amount captured energy during convergence. Furthermore, simulations conditions fast-varying, smooth, step-changing irradiance demonstrated proposed technique is capable dealing these severe conditions, capturing than 97.7% 98.35% available energy, respectively.