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Optimization of Guide Vane Closing Schemes of Pumped Storage Hydro Unit Using an Enhanced Multi-Objective Gravitational Search Algorithm

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  • Jianzhong Zhou

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Key Laboratory of Digital Valley Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yanhe Xu

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Key Laboratory of Digital Valley Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yang Zheng

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Key Laboratory of Digital Valley Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yuncheng Zhang

    (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Key Laboratory of Digital Valley Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

The optimization of guide vane closing schemes (OGVCS) of pumped storage hydro units (PSHUs) is a cooperative control and optimal operation research field in renewable energy power generation technology. This paper presents an OGVCS model of PSHUs considering the rise rate of the unit rotational speed, the specific node pressure of each hydraulic unit, as well as various complicated hydraulic and mechanical constraints. The OGVCS model is formulated as a multi-objective optimization problem to optimize conflicting objectives, i.e., unit rotational speed and water hammer pressure criteria. In order to realize an efficient solution of the OGVCS model, an enhanced multi-objective bacterial-foraging chemotaxis gravitational search algorithm (EMOBCGSA) is proposed to solve this problem, which adopts population reconstruction, adaptive selection chemotaxis operator of local searching strategy and elite archive set to efficiently solve the multi-objective problem. In particular a novel constraints-handling strategy with elimination and local search based on violation ranking is used to balance the various hydraulic and mechanical constraints. Finally, simulation cases of complex extreme operating conditions (i.e., load rejection and pump outage) of a ‘single tube-double units’ type PSHU system are conducted to verify the feasibility and effectiveness of the proposed EMOBCGSA in solving OGVCS problems. The simulation results indicate that the proposed EMOBCGSA can provide a lower rise rate of the unit rotational speed and smaller water hammer pressure than other methods established recently while considering various complex constraints in OGVCS problems.

Suggested Citation

  • Jianzhong Zhou & Yanhe Xu & Yang Zheng & Yuncheng Zhang, 2017. "Optimization of Guide Vane Closing Schemes of Pumped Storage Hydro Unit Using an Enhanced Multi-Objective Gravitational Search Algorithm," Energies, MDPI, vol. 10(7), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:911-:d:103475
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    References listed on IDEAS

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    2. Jiawei Ye & Wei Zeng & Zhigao Zhao & Jiebin Yang & Jiandong Yang, 2020. "Optimization of Pump Turbine Closing Operation to Minimize Water Hammer and Pulsating Pressures During Load Rejection," Energies, MDPI, vol. 13(4), pages 1-18, February.
    3. Wuyi Wan & Boran Zhang & Xiaoyi Chen, 2018. "Investigation on Water Hammer Control of Centrifugal Pumps in Water Supply Pipeline Systems," Energies, MDPI, vol. 12(1), pages 1-20, December.
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    6. Zanbin Wang & Chaoshun Li & Xinjie Lai & Nan Zhang & Yanhe Xu & Jinjiao Hou, 2018. "An Integrated Start-Up Method for Pumped Storage Units Based on a Novel Artificial Sheep Algorithm," Energies, MDPI, vol. 11(1), pages 1-29, January.
    7. Mohammad Mahmoudi-Rad & Mohammad Najafzadeh, 2023. "Effects of Surge Tank Geometry on the Water Hammer Phenomenon: Numerical Investigation," Sustainability, MDPI, vol. 15(3), pages 1-19, January.
    8. Nuria Novas & Alfredo Alcayde & Isabel Robalo & Francisco Manzano-Agugliaro & Francisco G. Montoya, 2020. "Energies and Its Worldwide Research," Energies, MDPI, vol. 13(24), pages 1-41, December.
    9. Jianzhong Zhou & Zhigao Zhao & Chu Zhang & Chaoshun Li & Yanhe Xu, 2017. "A Real-Time Accurate Model and Its Predictive Fuzzy PID Controller for Pumped Storage Unit via Error Compensation," Energies, MDPI, vol. 11(1), pages 1-24, December.
    10. Michał Kubrak & Agnieszka Malesińska & Apoloniusz Kodura & Kamil Urbanowicz & Paweł Bury & Michał Stosiak, 2021. "Water Hammer Control Using Additional Branched HDPE Pipe," Energies, MDPI, vol. 14(23), pages 1-18, November.
    11. Ivan Lorencin & Nikola Anđelić & Vedran Mrzljak & Zlatan Car, 2019. "Genetic Algorithm Approach to Design of Multi-Layer Perceptron for Combined Cycle Power Plant Electrical Power Output Estimation," Energies, MDPI, vol. 12(22), pages 1-26, November.
    12. Gonggui Chen & Xingting Yi & Zhizhong Zhang & Hangtian Lei, 2018. "Solving the Multi-Objective Optimal Power Flow Problem Using the Multi-Objective Firefly Algorithm with a Constraints-Prior Pareto-Domination Approach," Energies, MDPI, vol. 11(12), pages 1-18, December.
    13. Wuyi Wan & Boran Zhang, 2018. "Investigation of Water Hammer Protection in Water Supply Pipeline Systems Using an Intelligent Self-Controlled Surge Tank," Energies, MDPI, vol. 11(6), pages 1-16, June.
    14. Daqing Zhou & Huixiang Chen & Jie Zhang & Shengwen Jiang & Jia Gui & Chunxia Yang & An Yu, 2019. "Numerical Study on Flow Characteristics in a Francis Turbine during Load Rejection," Energies, MDPI, vol. 12(4), pages 1-15, February.
    15. Wuyi Wan & Boran Zhang & Xiaoyi Chen & Jijian Lian, 2019. "Water Hammer Control Analysis of an Intelligent Surge Tank with Spring Self-Adaptive Auxiliary Control System," Energies, MDPI, vol. 12(13), pages 1-19, July.
    16. Shuai Liu & Zhong-Kai Feng & Wen-Jing Niu & Hai-Rong Zhang & Zhen-Guo Song, 2019. "Peak Operation Problem Solving for Hydropower Reservoirs by Elite-Guide Sine Cosine Algorithm with Gaussian Local Search and Random Mutation," Energies, MDPI, vol. 12(11), pages 1-24, June.

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