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Optimization of Energy Storage Operation Chart of Cascade Reservoirs with Multi-Year Regulating Reservoir

Author

Listed:
  • Yi Liu

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

  • Zhiqiang Jiang

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

  • Zhongkai Feng

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

  • Yuyun Chen

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

  • Hairong Zhang

    (Department of Water Resources Management, China Yangtze Power Company Limited, Yichang 443133, China)

  • Ping Chen

    (Yalong River Hydropower Development Company Ltd., Chengdu 610051, Sichuan, China)

Abstract

In view of the problems that have not been solved or studied in the previous studies of cascade Energy Storage Operation Chart (ESOC), based on a brief description of the composition, principle, drawing methods, and simulation methods of ESOC, the following innovative work has been done in this paper. Firstly, considering the inconsistency of inflow frequency of upstream and downstream watershed in selecting the typical dry years, a novel optimization model for selecting the overall inflow process considering the integrity of watershed was proposed, which aimed at minimizing the sum of squares of inflow frequency differences. Secondly, aiming at the influence of output coefficients (including number and values) on the results of ESOC, this paper proposed a new method to construct the initial solution of output coefficients and established an optimization model of output coefficients based on progressive optimality algorithms. Thirdly, to the optimization of ESOC with multi-year regulating reservoir, a discrete optimization model of drawdown level was constructed based on the idea of ergodic optimization. On these bases, taking the seven reservoirs in the Yalong River basin of China as an example, the typical dry years considering the inflow frequency inconsistency, the optimal output coefficients of ESOC and the optimal end-of-year drawdown level of a multi-year regulating reservoir (Lianghekou) were obtained, and compared with the previous research results, the ESOC optimized in this paper can increase the total power generation of the cascade system by 9% under the condition that the guaranteed rate did not change much. Furthermore, the difference of the optimal end-of-year drawdown levels between the cascade joint operation and single reservoir operation was discussed for the Lianghekou reservoir at the end of the case study. The obtained results were of great significance for guiding the actual operation of cascade reservoirs.

Suggested Citation

  • Yi Liu & Zhiqiang Jiang & Zhongkai Feng & Yuyun Chen & Hairong Zhang & Ping Chen, 2019. "Optimization of Energy Storage Operation Chart of Cascade Reservoirs with Multi-Year Regulating Reservoir," Energies, MDPI, vol. 12(20), pages 1-20, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3814-:d:274552
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    Cited by:

    1. Zhiqiang Jiang & Peibing Song & Xiang Liao, 2020. "Optimization of Year-End Water Level of Multi-Year Regulating Reservoir in Cascade Hydropower System Considering the Inflow Frequency Difference," Energies, MDPI, vol. 13(20), pages 1-20, October.
    2. Ailing Xu & Li Mo & Qi Wang, 2022. "Research on Operation Mode of the Yalong River Cascade Reservoirs Based on Improved Stochastic Fractal Search Algorithm," Energies, MDPI, vol. 15(20), pages 1-19, October.
    3. Yuxin Zhu & Jianzhong Zhou & Yongchuan Zhang & Zhiqiang Jiang & Benjun Jia & Wei Fang, 2022. "Optimal Energy Storage Operation Chart and Output Distribution of Cascade Reservoirs Based on Operating Rules Derivation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5751-5766, November.
    4. Alireza Taheri Dehkordi & Mohammad Javad Valadan Zoej & Hani Ghasemi & Ebrahim Ghaderpour & Quazi K. Hassan, 2022. "A New Clustering Method to Generate Training Samples for Supervised Monitoring of Long-Term Water Surface Dynamics Using Landsat Data through Google Earth Engine," Sustainability, MDPI, vol. 14(13), pages 1-24, June.

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