A Hybrid MPPT algorithm based on trisection search and IPSO

This paper introduces an innovative algorithm for maximum power point tracking (MPPT). with a trisection search method is proposed in this paper. The proposed method resolves the drawbacks of conventional MPPT techniques like Perturb & Observe (P&O), especially under partial shading conditions that result in the presence of multiple local maxima on the power curve. Traditional methods often face significant challenges in locating and maintaining the global maximum power point (GMPP), while heuristic methods like Particle Swarm Optimization (PSO) suffer from slow convergence. The proposed IPSO with Trisection Search (IPSO-TS) algorithm combines the global search capability of IPSO with the rapid convergence of the trisection search method, enabling efficient tracking of the GMPP and providing improved performance in both simple and complex irradiance conditions. MATLAB simulations demonstrate the robustness and stability of the algorithm across various scenarios, achieving energy savings of approximately 50% compared to the IPSO algorithm and around 33% compared to EAGPSO during the tracking process. DOI: 10.61416/ceai.v27i3.9466

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Journal
Journal of Control Engineering and Applied Informatics
Published
2025-09-25
DOI
https://doi.org/10.61416/ceai.v27i3.9466
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
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article

A Hybrid MPPT algorithm based on trisection search and IPSO

Lidong Liu, Yulun Wu
Journal of Control Engineering and Applied Informatics
Metaheuristic Optimization Algorithms Research
article

A Hybrid MPPT algorithm based on trisection search and IPSO

Lidong Liu, Yulun Wu
article en

Abstract

This paper introduces an innovative algorithm for maximum power point tracking (MPPT). with a trisection search method is proposed in this paper. The proposed method resolves the drawbacks of conventional MPPT techniques like Perturb & Observe (P&O), especially under partial shading conditions that result in the presence of multiple local maxima on the power curve. Traditional methods often face significant challenges in locating and maintaining the global maximum power point (GMPP), while heuristic methods like Particle Swarm Optimization (PSO) suffer from slow convergence. The proposed IPSO with Trisection Search (IPSO-TS) algorithm combines the global search capability of IPSO with the rapid convergence of the trisection search method, enabling efficient tracking of the GMPP and providing improved performance in both simple and complex irradiance conditions. MATLAB simulations demonstrate the robustness and stability of the algorithm across various scenarios, achieving energy savings of approximately 50% compared to the IPSO algorithm and around 33% compared to EAGPSO during the tracking process. DOI: 10.61416/ceai.v27i3.9466

Journal of Control Engineering and Applied InformaticsVol. 27(3)
Jangan University (KR)
Openalex Percentile: Top 86%
Metaheuristic Optimization Algorithms Research
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A Hybrid MPPT algorithm based on trisection search and IPSO — Lidong Liu, Yulun Wu · Journal of Control Engineering and Applied Informatics (2025) | TGRS Research Map | TGRS