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MPPT-Based Chaotic ABC Algorithm for a Photovoltaic Power System Under Partial Shading Conditions

Author

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  • Chian-Song Chiu

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 320, Taiwan)

  • Yu-Ting Chen

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 320, Taiwan)

Abstract

This paper presents a novel maximum power point tracking (MPPT) method designed for a photovoltaic (PV) power system operating under partial shading conditions. Partial shading conditions induce multiple power peak characteristics into the power–voltage curve of the PV power system, such that conventional MPPT methods often lead local maximum power and result in suboptimal energy harvesting. To solve this problem, this paper proposes a chaotic artificial bee colony (CABC) algorithm hybridized with a chaotic searching behavior. The incorporation of the chaotic mapping enhances the exploration capability of bees (i.e., faster convergence time) and escapes local optima. To demonstrate its superior performance, the CABC algorithm is rigorously evaluated through simulations under two distinct partial shading scenarios, while making comparisons with the standard ABC algorithm and traditional MPPT methods. Therefore, the potential of this novel approach enhances MPPT accuracy, efficiency, and reliability in a partially shaded PV power system.

Suggested Citation

  • Chian-Song Chiu & Yu-Ting Chen, 2025. "MPPT-Based Chaotic ABC Algorithm for a Photovoltaic Power System Under Partial Shading Conditions," Energies, MDPI, vol. 18(7), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1710-:d:1623322
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    References listed on IDEAS

    as
    1. Kishore, D.J. Krishna & Mohamed, M.R. & Sudhakar, K. & Peddakapu, K., 2023. "Swarm intelligence-based MPPT design for PV systems under diverse partial shading conditions," Energy, Elsevier, vol. 265(C).
    2. Md Tahmid Hussain & Adil Sarwar & Mohd Tariq & Shabana Urooj & Amal BaQais & Md. Alamgir Hossain, 2023. "An Evaluation of ANN Algorithm Performance for MPPT Energy Harvesting in Solar PV Systems," Sustainability, MDPI, vol. 15(14), pages 1-36, July.
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    4. Musong L. Katche & Augustine B. Makokha & Siagi O. Zachary & Muyiwa S. Adaramola, 2023. "A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems," Energies, MDPI, vol. 16(5), pages 1-23, February.
    5. Rodrigo Bairros Watanabe & Oswaldo Hideo Ando Junior & Paulo Gabriel Martins Leandro & Fabiano Salvadori & Marlon Felipe Beck & Katiane Pereira & Marcelo Henrique Manzque Brandt & Fernando Marcos de O, 2022. "Implementation of the Bio-Inspired Metaheuristic Firefly Algorithm (FA) Applied to Maximum Power Point Tracking of Photovoltaic Systems," Energies, MDPI, vol. 15(15), pages 1-15, July.
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