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Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells

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  • Rongjie Wang

    (Marine Engineering Institute, Jimei Univeristy, 176 Shigu road, Jimei District, Xiamen 361021, China
    Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering, 176 Shigu road, Jimei District, Xiamen 361021, China)

  • Yiju Zhan

    (School of Engineering, Sun Yat-sen University, Panyu District, Guangzhou 510006, China)

  • Haifeng Zhou

    (Marine Engineering Institute, Jimei Univeristy, 176 Shigu road, Jimei District, Xiamen 361021, China)

Abstract

The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a single diode model and double diode model using this improved artificial bee colony. Experimental results clearly demonstrate the effectiveness of the proposed method and its superior performance compared to other competing methods.

Suggested Citation

  • Rongjie Wang & Yiju Zhan & Haifeng Zhou, 2015. "Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells," Energies, MDPI, vol. 8(8), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:8:p:7563-7581:d:53154
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    References listed on IDEAS

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    1. Chakraborty, Uday K. & Abbott, Travis E. & Das, Sajal K., 2012. "PEM fuel cell modeling using differential evolution," Energy, Elsevier, vol. 40(1), pages 387-399.
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    Cited by:

    1. Nunes, H.G.G. & Pombo, J.A.N. & Mariano, S.J.P.S. & Calado, M.R.A. & Felippe de Souza, J.A.M., 2018. "A new high performance method for determining the parameters of PV cells and modules based on guaranteed convergence particle swarm optimization," Applied Energy, Elsevier, vol. 211(C), pages 774-791.
    2. Lin, Xiankun & Wu, Yuhang, 2020. "Parameters identification of photovoltaic models using niche-based particle swarm optimization in parallel computing architecture," Energy, Elsevier, vol. 196(C).
    3. Houssem Ben Aribia & Ali M. El-Rifaie & Mohamed A. Tolba & Abdullah Shaheen & Ghareeb Moustafa & Fahmi Elsayed & Mostafa Elshahed, 2023. "Growth Optimizer for Parameter Identification of Solar Photovoltaic Cells and Modules," Sustainability, MDPI, vol. 15(10), pages 1-26, May.
    4. Hassan Shaban & Essam H. Houssein & Marco Pérez-Cisneros & Diego Oliva & Amir Y. Hassan & Alaa A. K. Ismaeel & Diaa Salama AbdElminaam & Sanchari Deb & Mokhtar Said, 2021. "Identification of Parameters in Photovoltaic Models through a Runge Kutta Optimizer," Mathematics, MDPI, vol. 9(18), pages 1-22, September.
    5. Muhammad Ali Mughal & Qishuang Ma & Chunyan Xiao, 2017. "Photovoltaic Cell Parameter Estimation Using Hybrid Particle Swarm Optimization and Simulated Annealing," Energies, MDPI, vol. 10(8), pages 1-14, August.
    6. Alena Vagaská & Miroslav Gombár & Ľuboslav Straka, 2022. "Selected Mathematical Optimization Methods for Solving Problems of Engineering Practice," Energies, MDPI, vol. 15(6), pages 1-22, March.
    7. Varaha Satra Bharath Kurukuru & Ahteshamul Haque & Mohammed Ali Khan & Subham Sahoo & Azra Malik & Frede Blaabjerg, 2021. "A Review on Artificial Intelligence Applications for Grid-Connected Solar Photovoltaic Systems," Energies, MDPI, vol. 14(15), pages 1-35, August.
    8. Rizk-Allah, Rizk M. & El-Fergany, Attia A., 2021. "Emended heap-based optimizer for characterizing performance of industrial solar generating units using triple-diode model," Energy, Elsevier, vol. 237(C).
    9. Tong Kang & Jiangang Yao & Min Jin & Shengjie Yang & ThanhLong Duong, 2018. "A Novel Improved Cuckoo Search Algorithm for Parameter Estimation of Photovoltaic (PV) Models," Energies, MDPI, vol. 11(5), pages 1-31, April.
    10. Mostafa Elshahed & Ali M. El-Rifaie & Mohamed A. Tolba & Ahmed Ginidi & Abdullah Shaheen & Shazly A. Mohamed, 2022. "An Innovative Hunter-Prey-Based Optimization for Electrically Based Single-, Double-, and Triple-Diode Models of Solar Photovoltaic Systems," Mathematics, MDPI, vol. 10(23), pages 1-22, December.

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