An efficient MPPT framework with an improved JAYA algorithm for fast and reliable tracking in partially shaded PV systems

This paper presents a maximum power point tracking framework for photovoltaic systems operating under partial shading conditions (PSCs). The proposed framework consists of three stages. The First Peak Detection stage identifies the first peak and estimates the locations of subsequent peaks. The Global Maximum Power Point Searching stage employs a customized metaheuristic algorithm integrated with Voltage Interval Reduction and Local Maximum Power Point Identification and Skipping mechanisms to confine the search space and eliminate redundant evaluations and mitigate transient power drops. Finally, the convergence evaluation and decision stage concludes the GMPPS. Furthermore, an Improved JAYA (IJAYA) algorithm is proposed, incorporating particle-based update strategy and an adaptive parameter strategy based on iteration count and particle power information to enhance convergence performance and reduce particle overlap. Experimental validation under four PSC scenarios demonstrates that the framework-based IJAYA (FW-IJAYA) outperforms search space reduction (SSR) and FW-SSR with average tracking time and tracking efficiency being 1.125s and 92.84%, respectively.