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Parameter Identification of a Governing System in a Pumped Storage Unit Based on an Improved Artificial Hummingbird Algorithm

Author

Listed:
  • Liying Wang

    (School of Water Conservancy and Hydropower, Hebei University of Engineering, Handan 056038, China)

  • Luyao Zhang

    (School of Water Conservancy and Hydropower, Hebei University of Engineering, Handan 056038, China)

  • Weiguo Zhao

    (School of Water Conservancy and Hydropower, Hebei University of Engineering, Handan 056038, China)

  • Xiyuan Liu

    (School of Water Conservancy and Hydropower, Hebei University of Engineering, Handan 056038, China)

Abstract

Parameter identification is an important method to establish the governing system of a pumped storage unit. Appropriate parameters will make the governing system obtain better control performance. Therefore, in this study, an improved artificial hummingbird algorithm (IAHA) is proposed for the parameter identification of the governing system in a pumped storage unit. The algorithm integrates two key strategies to improve the optimization ability of the algorithm. First, the Chebyshev chaotic map is employed to initialize the artificial hummingbirds, which in turn increases and enhances the global search capability of the initial population. Second, the Levy flight is introduced in the guided foraging phase to expand the search space and avoid premature convergence. The performance of the proposed IAHA algorithm is compared with that of four other algorithms on 23 standard test functions, and the results show that IAHA has higher accuracy and faster convergence than the other four algorithms. Finally, IAHA was applied to the parameter identification of the governing system of a pumped storage unit to verify the effectiveness of the algorithm in tracking real-world problems.

Suggested Citation

  • Liying Wang & Luyao Zhang & Weiguo Zhao & Xiyuan Liu, 2022. "Parameter Identification of a Governing System in a Pumped Storage Unit Based on an Improved Artificial Hummingbird Algorithm," Energies, MDPI, vol. 15(19), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:6966-:d:922754
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    References listed on IDEAS

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    1. Hu, Gang & Dou, Wanting & Wang, Xiaofeng & Abbas, Muhammad, 2022. "An enhanced chimp optimization algorithm for optimal degree reduction of Said–Ball curves," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 197(C), pages 207-252.
    2. Ali, M. & El-Hameed, M.A. & Farahat, M.A., 2017. "Effective parameters’ identification for polymer electrolyte membrane fuel cell models using grey wolf optimizer," Renewable Energy, Elsevier, vol. 111(C), pages 455-462.
    3. Tan Ding & Li Chang & Chaoshun Li & Chen Feng & Nan Zhang, 2018. "A Mixed-Strategy-Based Whale Optimization Algorithm for Parameter Identification of Hydraulic Turbine Governing Systems with a Delayed Water Hammer Effect," Energies, MDPI, vol. 11(9), pages 1-29, September.
    4. Liying Wang & Kaidi Zhang & Weiguo Zhao, 2022. "Nonlinear Modeling of Dynamic Characteristics of Pump-Turbine," Energies, MDPI, vol. 15(1), pages 1-17, January.
    5. Tian Tian & Changyu Liu & Qi Guo & Yi Yuan & Wei Li & Qiurong Yan, 2018. "An Improved Ant Lion Optimization Algorithm and Its Application in Hydraulic Turbine Governing System Parameter Identification," Energies, MDPI, vol. 11(1), pages 1-15, January.
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