Maximum Power Point Tracking of Series-Parallel Connected Bifacial PV Modules

Bifacial photovoltaic (BiPV) modules capture solar energy from their front and rear surfaces, posing unique challenges due to their exposure to non-uniform irradiance and temperature variations. In the pursuit of optimizing the energy output of BiPV systems, this paper focuses on investigating the effectiveness of the maximum power point tracking (MPPT) methods of series-parallel (SP) connected BiPV modules using advanced metaheuristic algorithms like the genetic algorithm (GA), particle swarm optimization (PSO), and gray wolf optimizer (GWO). The efficiency of the selected techniques is compared to each other in tracking the maximum power point (MPP) of a (2 × 2) BiPV array feeding a DC/DC converter under three different cases. Through detailed simulations, the results demonstrate that these algorithms can significantly enhance the energy yield of BiPV arrays of SP configurations. The findings indicate that selecting an optimization strategy is essential to increasing the overall effectiveness of BiPV systems. Each methodology provides unique benefits depending on the operating circumstances.