Improved JAYA algorithm speeds maximum power point tracking in shaded PV systems

This paper presents a maximum power point tracking framework for photovoltaic systems operating under partial shading conditions, built around an improved JAYA algorithm.

The framework operates in three stages. The first, First Peak Detection, identifies the first peak and estimates the locations of subsequent peaks. The second stage, Global Maximum Power Point Searching, employs a customized metaheuristic algorithm integrated with Voltage Interval Reduction and Local Maximum Power Point Identification and Skipping mechanisms to confine the search space, eliminate redundant evaluations and mitigate transient power drops. A final convergence evaluation and decision stage concludes the search.

The algorithm at the heart of the second stage is an improved version of JAYA, a population-based metaheuristic. The improvement combines a particle-based update strategy with an adaptive parameter strategy that draws on both the iteration count and the power information of individual particles. According to the authors, the improved JAYA algorithm incorporates a 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 covered four partial shading scenarios. Across these tests, the framework-based IJAYA configuration, abbreviated FW-IJAYA, achieved an average tracking time of 1.125 seconds and an average tracking efficiency of 92.84 percent. The comparison baselines were the search space reduction method, known as SSR, and its framework-integrated counterpart, FW-SSR. Experimental validation under four partial shading scenarios demonstrates that FW-IJAYA outperforms SSR and FW-SSR, with average tracking time and tracking efficiency of 1.125 seconds and 92.84 percent, respectively.

The work is published as open access research in Discover Applied Sciences, shared early under a citable permanent DOI ahead of the final Version of Record. The authors are Dhia Elhak Rouabah, Maaspaliza Azri and Mohd Zulkifli Ramli, with Abdelhak Lekbir among the contributing authors.

Subject of Research: A three-stage maximum power point tracking framework with an improved JAYA algorithm for partially shaded photovoltaic systems

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

Article References: Rouabah, D. E., Azri, M., Ramli, M. Z., & Lekbir, A. (2026). An efficient MPPT framework with an improved JAYA algorithm for fast and reliable tracking in partially shaded PV systems. Discover Applied Sciences. https://doi.org/10.1007/s42452-026-09852-y

Image Credits: AI Generated

DOI: 10.1007/s42452-026-09852-y

Keywords: photovoltaics, MPPT, partial shading, JAYA algorithm, metaheuristic optimization, global maximum power point, solar energy, power electronics, tracking efficiency, search space reduction, efficient, framework