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Parameter Identification of Photovoltaic Cell Model Based on Enhanced Particle Swarm Optimization

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  • Rongjie Wang

    (Marine Engineering Institute, Jimei University, Xiamen 361021, China
    Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering, Xiamen 361021, China)

Abstract

Photovoltaic (PV) cell (PVC) modeling predicts the behavior of PVCs in various real-world environmental settings and their resultant current–voltage and power–voltage characteristics. Focusing on PVC parameter identification, this study presents an enhanced particle swarm optimization (EPSO) algorithmto accurately and efficiently extract optimal PVC parameters. Specifically, the EPSO algorithm optimizes the minimum mean squared error between measured and estimated data and, on this basis, extractsthe parameters of the single-, double-, and triple-diode models and the PV module. To examine its effectiveness, the proposed EPSO algorithm is compared with other swarm optimization algorithms. The effectiveness of the proposed EPSO algorithm is validated through simulation. In addition, the proposed EPSO algorithm also exhibits advantages such as an excellent optimization performance, a high parameter estimation accuracy, and a low computational complexity.

Suggested Citation

  • Rongjie Wang, 2021. "Parameter Identification of Photovoltaic Cell Model Based on Enhanced Particle Swarm Optimization," Sustainability, MDPI, vol. 13(2), pages 1-23, January.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:840-:d:481351
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    References listed on IDEAS

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    6. 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.
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    Cited by:

    1. 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.
    2. Husheng Wu & Qiang Peng & Meimei Shi & Lining Xing & Shi Cheng, 2022. "Drunkard Adaptive Walking Chaos Wolf Pack Algorithm in Parameter Identification of Photovoltaic Module Model," Energies, MDPI, vol. 15(17), pages 1-24, August.

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