IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i4p1609-d1591947.html
   My bibliography  Save this article

A Novel Optimization Approach Using Chaos Game Optimization Algorithm for Parameters Estimation of Photovoltaic Cells

Author

Listed:
  • Galal Borham Wereda

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Ibrahim Mohamed Diaaeldin

    (Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Othman A. M. Omar

    (Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Mahmoud A. Attia

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Ahmed O. Badr

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

Abstract

The utilization of solar photovoltaics (PV) in electricity generation is progressively increasing due to its environmental benefits, such as reducing power transmission costs and mitigating global warming. This research aims to enhance the effectiveness of the extracted PV parameters. To estimate the parameters of the PV model, a recent optimization algorithm called the Chaos Game Optimization algorithm (CGO) is employed to precisely choose PV parameters. In this work, PV cells are modeled using two different models, including the single-diode model (SDM) and the double-diode model (DDM). The CGO algorithm outperformed nine well-known optimization algorithms based on the root–mean squares of error (RMSE) with a percentage of up to 97% for the single-diode model (SDM) and up to 92.92% for the double-diode model (DDM).

Suggested Citation

  • Galal Borham Wereda & Ibrahim Mohamed Diaaeldin & Othman A. M. Omar & Mahmoud A. Attia & Ahmed O. Badr, 2025. "A Novel Optimization Approach Using Chaos Game Optimization Algorithm for Parameters Estimation of Photovoltaic Cells," Sustainability, MDPI, vol. 17(4), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:4:p:1609-:d:1591947
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/4/1609/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/4/1609/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aissa Meflah & Fathia Chekired & Nadia Drir & Laurent Canale, 2024. "Accurate Method for Solar Power Generation Estimation for Different PV (Photovoltaic Panels) Technologies," Resources, MDPI, vol. 13(12), pages 1-18, November.
    2. Jianping Zhao & Damin Zhang & Qing He & Lun Li, 2023. "A Hybrid-Strategy-Improved Dragonfly Algorithm for the Parameter Identification of an SDM," Sustainability, MDPI, vol. 15(15), pages 1-35, July.
    3. Jordehi, A. Rezaee, 2016. "Parameter estimation of solar photovoltaic (PV) cells: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 354-371.
    4. Pillai, Dhanup S. & Rajasekar, N., 2018. "Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3503-3525.
    5. Zaiyu Gu & Guojiang Xiong & Xiaofan Fu, 2023. "Parameter Extraction of Solar Photovoltaic Cell and Module Models with Metaheuristic Algorithms: A Review," Sustainability, MDPI, vol. 15(4), pages 1-45, February.
    6. Singh, G.K., 2013. "Solar power generation by PV (photovoltaic) technology: A review," Energy, Elsevier, vol. 53(C), pages 1-13.
    7. Ailing Wang & Qiongfang Lin & Chunlu Liu & Liu Yang & Shaonan Sun, 2024. "Sustainable Energy Development: Reviewing Carbon Emission Reduction in Photovoltaic Power Systems," Sustainability, MDPI, vol. 16(23), pages 1-22, November.
    8. Chin, Vun Jack & Salam, Zainal & Ishaque, Kashif, 2015. "Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review," Applied Energy, Elsevier, vol. 154(C), pages 500-519.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. En-Jui Liu & Yan-Hao Huang & Wei-Lun Lin & Chen-Kai Wen & Chun-I Lin, 2025. "Rapid, Precise Parameter Optimization and Performance Prediction for Multi-Diode Photovoltaic Model Using Puma Optimizer," Energies, MDPI, vol. 18(11), pages 1-31, May.
    2. Pedroza-Díaz, Alfredo & Rodrigo, Pedro M. & Dávalos-Orozco, Óscar & De-la-Vega, Eduardo & Valera-Albacete, Álvaro, 2025. "Review of explicit models for photovoltaic cell electrical characterization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    3. Shufu Yuan & Yuzhang Ji & Yongxu Chen & Xin Liu & Weijun Zhang, 2023. "An Improved Differential Evolution for Parameter Identification of Photovoltaic Models," Sustainability, MDPI, vol. 15(18), pages 1-28, September.
    4. Li, Shuijia & Gong, Wenyin & Gu, Qiong, 2021. "A comprehensive survey on meta-heuristic algorithms for parameter extraction of photovoltaic models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    5. Sofia Boulmrharj & Mohammed Khaidar & Mohamed Bakhouya & Radouane Ouladsine & Mostapha Siniti & Khalid Zine-dine, 2020. "Performance Assessment of a Hybrid System with Hydrogen Storage and Fuel Cell for Cogeneration in Buildings," Sustainability, MDPI, vol. 12(12), pages 1-21, June.
    6. Ebrahimi, S. Mohammadreza & Salahshour, Esmaeil & Malekzadeh, Milad & Francisco Gordillo,, 2019. "Parameters identification of PV solar cells and modules using flexible particle swarm optimization algorithm," Energy, Elsevier, vol. 179(C), pages 358-372.
    7. Habib Satria & Rahmad B. Y. Syah & Moncef L. Nehdi & Monjee K. Almustafa & Abdelrahman Omer Idris Adam, 2023. "Parameters Identification of Solar PV Using Hybrid Chaotic Northern Goshawk and Pattern Search," Sustainability, MDPI, vol. 15(6), pages 1-24, March.
    8. Nawal Rai & Amel Abbadi & Fethia Hamidia & Nadia Douifi & Bdereddin Abdul Samad & Khalid Yahya, 2023. "Biogeography-Based Teaching Learning-Based Optimization Algorithm for Identifying One-Diode, Two-Diode and Three-Diode Models of Photovoltaic Cell and Module," Mathematics, MDPI, vol. 11(8), pages 1-30, April.
    9. Pillai, Dhanup S. & Rajasekar, N., 2018. "Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3503-3525.
    10. Li, Yuanliang & Ding, Kun & Zhang, Jingwei & Chen, Fudong & Chen, Xiang & Wu, Jiabing, 2019. "A fault diagnosis method for photovoltaic arrays based on fault parameters identification," Renewable Energy, Elsevier, vol. 143(C), pages 52-63.
    11. Wang, Gang & Zhao, Ke & Qiu, Tian & Yang, Xinsheng & Zhang, Yong & Zhao, Yong, 2016. "The error analysis of the reverse saturation current of the diode in the modeling of photovoltaic modules," Energy, Elsevier, vol. 115(P1), pages 478-485.
    12. Manish Kumar Singla & Jyoti Gupta & Parag Nijhawan & Parminder Singh & Nimay Chandra Giri & Essam Hendawi & Mohamed I. Abu El-Sebah, 2023. "Parameter Estimation Techniques for Photovoltaic System Modeling," Energies, MDPI, vol. 16(17), pages 1-16, August.
    13. Chen, Zhicong & Yu, Hui & Luo, Linlu & Wu, Lijun & Zheng, Qiao & Wu, Zhenhui & Cheng, Shuying & Lin, Peijie, 2021. "Rapid and accurate modeling of PV modules based on extreme learning machine and large datasets of I-V curves," Applied Energy, Elsevier, vol. 292(C).
    14. Wang, Shinong & Luo, Huan & Ge, Yuan & Liu, Shilin, 2021. "A new approach for modeling photovoltaic modules based on difference equation," Renewable Energy, Elsevier, vol. 168(C), pages 85-96.
    15. Jeehong Kim & Seok-ho Lee & Kil To Chong, 2022. "A Study of Neural Network Framework for Power Generation Prediction of a Solar Power Plant," Energies, MDPI, vol. 15(22), pages 1-19, November.
    16. Cornejo, Lorena & Martín-Pomares, Luis & Alarcon, Diego & Blanco, Julián & Polo, Jesús, 2017. "A through analysis of solar irradiation measurements in the region of Arica Parinacota, Chile," Renewable Energy, Elsevier, vol. 112(C), pages 197-208.
    17. Singh, Rashmi & Sharma, Madhu & Rawat, Rahul & Banerjee, Chandan, 2018. "An assessment of series resistance estimation techniques for different silicon based SPV modules," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 199-216.
    18. Slawomir Gulkowski, 2023. "Modeling and Experimental Studies of the Photovoltaic System Performance in Climate Conditions of Poland," Energies, MDPI, vol. 16(20), pages 1-16, October.
    19. Dong, Xiao-Jian & Shen, Jia-Ni & Ma, Zi-Feng & He, Yi-Jun, 2022. "Simultaneous operating temperature and output power prediction method for photovoltaic modules," Energy, Elsevier, vol. 260(C).
    20. Ridha, Hussein Mohammed & Gomes, Chandima & Hazim, Hashim & Ahmadipour, Masoud, 2020. "Sizing and implementing off-grid stand-alone photovoltaic/battery systems based on multi-objective optimization and techno-economic (MADE) analysis," Energy, Elsevier, vol. 207(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:4:p:1609-:d:1591947. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.