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Coyote optimization algorithm for parameters extraction of three-diode photovoltaic models of photovoltaic modules

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  • Qais, Mohammed H.
  • Hasanien, Hany M.
  • Alghuwainem, Saad
  • Nouh, Adnan S.

Abstract

This paper exhibits a novel application of the coyote optimization algorithm (COA) in order to extract the nine unknown parameters of the three-diode photovoltaic (PV) model of PV modules. The main target of this study is to obtain a very highly precise PV model, which can be efficiently applied to represent the PV system in the simulation of dynamic power systems. The optimization problem is formulated to take into consideration the root mean squared current error between the calculated model current and the experimental current of the PV module. The COA is applied to minimize this fitness function. In this study, the COA-PV model is validated by the numerical results which are performed at different environmental conditions such as temperature and irradiation variation conditions. Moreover, its effectiveness is executed by making a comparison between its numerical and experimental results for some commercial PV modules in the market like the KC200GT and MSX-60 modules. With the adoption of the COA, a highly precise three-diode PV model can be established. This represents a novel contribution to the field of PV systems and its modeling.

Suggested Citation

  • Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad & Nouh, Adnan S., 2019. "Coyote optimization algorithm for parameters extraction of three-diode photovoltaic models of photovoltaic modules," Energy, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:energy:v:187:y:2019:i:c:s0360544219316950
    DOI: 10.1016/j.energy.2019.116001
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    Cited by:

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    6. Bushra Shakir Mahmood & Nazar K. Hussein & Mansourah Aljohani & Mohammed Qaraad, 2023. "A Modified Gradient Search Rule Based on the Quasi-Newton Method and a New Local Search Technique to Improve the Gradient-Based Algorithm: Solar Photovoltaic Parameter Extraction," Mathematics, MDPI, vol. 11(19), pages 1-40, October.
    7. Zhang, Yiying & Ma, Maode & Jin, Zhigang, 2020. "Comprehensive learning Jaya algorithm for parameter extraction of photovoltaic models," Energy, Elsevier, vol. 211(C).
    8. Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad, 2020. "Parameters extraction of three-diode photovoltaic model using computation and Harris Hawks optimization," Energy, Elsevier, vol. 195(C).
    9. Abd-ElHady Ramadan & Salah Kamel & Tahir Khurshaid & Seung-Ryle Oh & Sang-Bong Rhee, 2021. "Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer," Sustainability, MDPI, vol. 13(12), pages 1-16, June.
    10. Samuel R. Fahim & Hany M. Hasanien & Rania A. Turky & Shady H. E. Abdel Aleem & Martin Ćalasan, 2022. "A Comprehensive Review of Photovoltaic Modules Models and Algorithms Used in Parameter Extraction," Energies, MDPI, vol. 15(23), pages 1-56, November.
    11. Shaheen, Abdullah M. & Ginidi, Ahmed R. & El-Sehiemy, Ragab A. & El-Fergany, Attia & Elsayed, Abdallah M., 2023. "Optimal parameters extraction of photovoltaic triple diode model using an enhanced artificial gorilla troops optimizer," Energy, Elsevier, vol. 283(C).
    12. Adeel, Muhammad & Hassan, Ahmad Kamal & Sher, Hadeed Ahmed & Murtaza, Ali Faisal, 2021. "A grade point average assessment of analytical and numerical methods for parameter extraction of a practical PV device," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    13. 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).
    14. Long, Wen & Jiao, Jianjun & Liang, Ximing & Xu, Ming & Tang, Mingzhu & Cai, Shaohong, 2022. "Parameters estimation of photovoltaic models using a novel hybrid seagull optimization algorithm," Energy, Elsevier, vol. 249(C).
    15. El-Dabah, Mahmoud A. & El-Sehiemy, Ragab A. & Hasanien, Hany M. & Saad, Bahaa, 2023. "Photovoltaic model parameters identification using Northern Goshawk Optimization algorithm," Energy, Elsevier, vol. 262(PB).
    16. Habib Kraiem & Ezzeddine Touti & Abdulaziz Alanazi & Ahmed M. Agwa & Tarek I. Alanazi & Mohamed Jamli & Lassaad Sbita, 2023. "Parameters Identification of Photovoltaic Cell and Module Models Using Modified Social Group Optimization Algorithm," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    17. Ali, E.S. & Elazim, S.M. Abd & Balobaid, A.S., 2023. "Implementation of coyote optimization algorithm for solving unit commitment problem in power systems," Energy, Elsevier, vol. 263(PA).
    18. Ahmed Ginidi & Sherif M. Ghoneim & Abdallah Elsayed & Ragab El-Sehiemy & Abdullah Shaheen & Attia El-Fergany, 2021. "Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    19. 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).

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