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A Mixed-Strategy-Based Whale Optimization Algorithm for Parameter Identification of Hydraulic Turbine Governing Systems with a Delayed Water Hammer Effect

Author

Listed:
  • Tan Ding

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Li Chang

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Chaoshun Li

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Chen Feng

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Nan Zhang

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

For solving the parameter optimization problem of a hydraulic turbine governing system (HTGS) with a delayed water hammer (DWH) effect, a Mixed-Strategy-based Whale Optimization Algorithm (MSWOA) is proposed in this paper, in which three improved strategies are designed and integrated to promote the optimization ability. Firstly, the movement strategies of WOA have been improved to balance the exploration and exploitation. In the improved movement strategies, a dynamic ratio based on improved JAYA algorithm is applied on the strategy of searching for prey and a chaotic dynamic weight is designed for improving the strategies of bubble-net attacking and encircling prey. Secondly, a guidance of the elite’s memory inspired by Particle swarm optimization (PSO) is proposed to lead the movement of the population to accelerate the convergence speed. Thirdly, the mutation strategy based on the sinusoidal chaotic map is employed to avoid prematurity and local optimum points. The proposed MSWOA are compared with six popular meta-heuristic optimization algorithms on 23 benchmark functions in numerical experiments and the results show that the MSWOA has achieved significantly better performance than others. Finally, the MSWOA is applied on parameter identification problem of HTGS with a DWH effect, and the comparative results confirm the effectiveness and identification accuracy of the proposed method.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2367-:d:168484
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    References listed on IDEAS

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    Cited by:

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    2. Paweł Ocłoń & Maciej Ławryńczuk & Marek Czamara, 2021. "A New Solar Assisted Heat Pump System with Underground Energy Storage: Modelling and Optimisation," Energies, MDPI, vol. 14(16), pages 1-15, August.
    3. 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.
    4. Jun Zhang & Denghua Zhong & Mengqi Zhao & Jia Yu & Fei Lv, 2019. "An Optimization Model for Construction Stage and Zone Plans of Rockfill Dams Based on the Enhanced Whale Optimization Algorithm," Energies, MDPI, vol. 12(3), pages 1-29, February.

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