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Metaheuristic-Based Optimization of Nonlinear PI Controllers for Maximum Power Extraction in PV Systems.

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Bibliographic Details
Title: Metaheuristic-Based Optimization of Nonlinear PI Controllers for Maximum Power Extraction in PV Systems.
Authors: Khellaf, Loubna1 (AUTHOR) l.khellaf@etu.ensti-annaba.dz, Djellal, Adel1 (AUTHOR), Mayache, Hichem1 (AUTHOR)
Source: Journal Européen des Systèmes Automatisés. Aug2025, Vol. 58 Issue 8, p1561-1573. 13p.
Subject Terms: Photovoltaic power systems, Metaheuristic algorithms, Particle swarm optimization, Scientific method, Energy harvesting, Genetic algorithms, Mathematical optimization, PID controllers
Abstract: Despite the promising potential of photovoltaic energy and its wide range of uses, it still has shortcomings today, mainly due to its highly sensitive nature to environmental factors, resulting in low efficiency and energy loss. Therefore, the implementation of a robust control strategy for photovoltaic systems becomes essential in order to efficiently track the maximum power point (MPP) and deliver the best possible performance. This study proposes the implementation of a non-linear Proportional-Integral (NPI) controller in a PV system with a resistive load. The NPI controller is designed by integrating a non-linear gain function based on Popov's stability criterion into the classical PI structure, aligning with the nonlinear characteristics of PV systems. Furthermore, intelligent control techniques, in particular these metaheuristic algorithms: Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Grey Wolf optimizer (GWO), were utilized to fine-tune both non-linear PI and classic PI controllers. The performance of the proposed approach is assessed using key metrics such as Mean Square Error (MSE), overshoot, settling time, and efficiency, demonstrating its effectiveness in enhancing PV system operation. [ABSTRACT FROM AUTHOR]
Database: Supplemental Index
Description
Abstract:Despite the promising potential of photovoltaic energy and its wide range of uses, it still has shortcomings today, mainly due to its highly sensitive nature to environmental factors, resulting in low efficiency and energy loss. Therefore, the implementation of a robust control strategy for photovoltaic systems becomes essential in order to efficiently track the maximum power point (MPP) and deliver the best possible performance. This study proposes the implementation of a non-linear Proportional-Integral (NPI) controller in a PV system with a resistive load. The NPI controller is designed by integrating a non-linear gain function based on Popov's stability criterion into the classical PI structure, aligning with the nonlinear characteristics of PV systems. Furthermore, intelligent control techniques, in particular these metaheuristic algorithms: Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Grey Wolf optimizer (GWO), were utilized to fine-tune both non-linear PI and classic PI controllers. The performance of the proposed approach is assessed using key metrics such as Mean Square Error (MSE), overshoot, settling time, and efficiency, demonstrating its effectiveness in enhancing PV system operation. [ABSTRACT FROM AUTHOR]
ISSN:12696935
DOI:10.18280/jesa.580803