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An Innovative Hunter-Prey-Based Optimization for Electrically Based Single-, Double-, and Triple-Diode Models of Solar Photovoltaic Systems

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  • Mostafa Elshahed

    (Electrical Engineering Department, Engineering and Information Technology College, Buraydah Private Colleges, Buraydah 81418, Saudi Arabia
    Electrical Power Engineering Department, Faculty of Engineering, Cairo University, Giza 12613, Egypt)

  • Ali M. El-Rifaie

    (College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait)

  • Mohamed A. Tolba

    (Reactors Department, Nuclear Research Center, Egyptian Atomic Energy Authority, Cairo 11787, Egypt
    Electrical Power Systems Department, National Research University “MPEI”, 111250 Moscow, Russia)

  • Ahmed Ginidi

    (Department of Electrical Power Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt)

  • Abdullah Shaheen

    (Department of Electrical Power Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt)

  • Shazly A. Mohamed

    (Electrical Engineering Department, Faculty of Engineering, South Valley University, Qena 83523, Egypt)

Abstract

The derivation of PV model parameters is crucial for the optimization, control, and simulation of PV systems. Although many parameter extraction algorithms have been developed to address this issue, they might have some limitations. This work presents an efficient hybrid optimization approach for reliably and effectively extracting PV parameters based on the hunter–prey optimizer (HPO) technique. The proposed HPO technique is a new population-based optimizer inspired by the behavior of prey and predator animals. In the proposed HPO mechanism, the predator attacks the prey that leaves the prey population. Accordingly, the position of a hunter is adjusted toward this distant prey, while the position of the prey is adjusted towards a secure place. The search agent’s position, which represents the best fitness function value, is considered a secure place. The proposed HPO technique worked as suggested when parameters are extracted from several PV models, including single-, double-, and triple-diode models. Moreover, a statistical error analysis was used to demonstrate the superiority of the proposed method. The proposed HPO technique outperformed other recently reported techniques in terms of convergence speed, dependability, and accuracy, according to simulation data.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:23:p:4625-:d:995444
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    References listed on IDEAS

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    Cited by:

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    4. Araby Mahdy & Abdullah Shaheen & Ragab El-Sehiemy & Ahmed Ginidi & Saad F. Al-Gahtani, 2023. "Single- and Multi-Objective Optimization Frameworks of Shape Design of Tubular Linear Synchronous Motor," Energies, MDPI, vol. 16(5), pages 1-27, March.
    5. Abdullah M. Shaheen & Ragab A. El-Sehiemy & Ahmed Ginidi & Abdallah M. Elsayed & Saad F. Al-Gahtani, 2023. "Optimal Allocation of PV-STATCOM Devices in Distribution Systems for Energy Losses Minimization and Voltage Profile Improvement via Hunter-Prey-Based Algorithm," Energies, MDPI, vol. 16(6), pages 1-20, March.
    6. 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.

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