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Estimation of Parameters of Triple Diode Photovoltaic Models Using Hybrid Particle Swarm and Grey Wolf Optimization

Author

Listed:
  • Hazem Hassan Ellithy

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

  • Adel M. Taha

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

  • Hany M. Hasanien

    (Electrical Power and Machines 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)

  • Adel El-Shahat

    (Energy Technology Program, School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA)

  • Shady H. E. Abdel Aleem

    (Department of Electrical Engineering, Valley High Institute of Engineering and Technology, Science Valley Academy, Qalyubia 44971, Egypt)

Abstract

The quality of the photovoltaic (PV) cell model impacts many simulation studies for PV systems, such as maximum power point tracking and other assessments. Moreover, due to limited information found in the datasheets of the PV cells, several parameters of the model are unavailable. Thus, this paper introduces a novel approach using a hybrid Particle Swarm and Grey Wolf Optimization algorithm to figure out these parameters under different environmental conditions. The proposed algorithm is used with two types of PV cells–Kyocera KC200GT and Canadian solar cell CS6K-280M–and can be used with any commercial type of PV module needing only parameters in the datasheet. The absolute error of the model’s simulation results is compared to the actual results collected from sites in Egypt, in an attempt to investigate the effectiveness of the suggested approach.

Suggested Citation

  • Hazem Hassan Ellithy & Adel M. Taha & Hany M. Hasanien & Mahmoud A. Attia & Adel El-Shahat & Shady H. E. Abdel Aleem, 2022. "Estimation of Parameters of Triple Diode Photovoltaic Models Using Hybrid Particle Swarm and Grey Wolf Optimization," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9046-:d:870066
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    References listed on IDEAS

    as
    1. Omnia S. Elazab & Hany M. Hasanien & Ibrahim Alsaidan & Almoataz Y. Abdelaziz & S. M. Muyeen, 2020. "Parameter Estimation of Three Diode Photovoltaic Model Using Grasshopper Optimization Algorithm," Energies, MDPI, vol. 13(2), pages 1-15, January.
    2. Narinder Singh & S. B. Singh, 2017. "Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance," Journal of Applied Mathematics, Hindawi, vol. 2017, pages 1-15, November.
    3. 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).
    4. Ishaque, Kashif & Salam, Zainal & Mekhilef, Saad & Shamsudin, Amir, 2012. "Parameter extraction of solar photovoltaic modules using penalty-based differential evolution," Applied Energy, Elsevier, vol. 99(C), pages 297-308.
    5. Wu, Lijun & Chen, Zhicong & Long, Chao & Cheng, Shuying & Lin, Peijie & Chen, Yixiang & Chen, Huihuang, 2018. "Parameter extraction of photovoltaic models from measured I-V characteristics curves using a hybrid trust-region reflective algorithm," Applied Energy, Elsevier, vol. 232(C), pages 36-53.
    6. Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad, 2019. "Identification of electrical parameters for three-diode photovoltaic model using analytical and sunflower optimization algorithm," Applied Energy, Elsevier, vol. 250(C), pages 109-117.
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