Rayleigh Distribution-Based Novel and Efficient MPPT Algorithm for Rooftop PV System with Competence to Distinguish Different Dynamics

The dynamic environment conditions entail the need for the MPPT technique for the Solar Photovoltaic (SPV) System, which ensures optimal utilization of available solar energy. In this article, Rayleigh distribution-based Particle Swarm Optimization (RDPSO) method has been proposed for maximum power extraction from PV panels. The proposed approach has been developed to enhance the exploration and exploitation characteristics of PSO for the quick detection of GMPP with high efficacy. Teaser-Kaiser energy Operator (TKEO) has been used to mitigate redundancy in search space, improving convergence speed. In addition, a novel technique has been proposed to identify PV system dynamics caused by variations in irradiation level, shading conditions, and load fluctuations. In rooftop PV systems fluctuations in consumers' loads are frequent events. The initialization of the heuristic method owing to load variations creates additional stress on the system and impacts the overall performance and life span of the connected equipment. Therefore, the proposed method has the proficiency to respond quickly to load variations without re-initializing the heuristic method. The performance of the proposed method has been validated for different dynamic conditions. The outcomes proved that the presented method is having high convergence speed for different dynamic conditions along with minimal fluctuation in power during the search process.