Global MPPT Strategy for PV Systems under Partial Shading Inspired by Wave Function Collapse Algorithm

Abstract

The photovoltaic (PV) systems operate under Partial Shading Conditions (PSC), which severely degrade the PV system performance as number of local maxima appears in power-voltage (P-V) characteristic curve causing to generate the local maximum points in conventional control algorithms. Considering shading’s profound effect on energy production and system reliability, this paper recommends a new Maximum Power Point Tracking (MPPT) strategy based on the Wave Function Collapse (WFC) algorithm. The proposed approach adopts a probabilistic state-selection scheme, conducive to select the proper navigating steps in the search space for GMPP. The competition between exploration and exploitation is adaptively balanced in this algorithm, which enables it to perform stably at different irradiance levels and levels of noise. Extensive simulation results for a wide range of PSC scenarios show that, in comparison to the classical Perturb and Observe (P&O) and Particle Swarm Optimization (PSO), WFC-based MPPT approach enables a swifter tracking effort as well as a better energy harvesting efficiency. The results show that the proposed approach is strong in solving the drawbacks of metaheuristic and classical trackers under dynamic environmental environment limitations.