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Optimal Energy Storage Operation Chart and Output Distribution of Cascade Reservoirs Based on Operating Rules Derivation

Author

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  • Yuxin Zhu

    (Huazhong University of Science & Technology)

  • Jianzhong Zhou

    (Huazhong University of Science & Technology)

  • Yongchuan Zhang

    (Huazhong University of Science & Technology)

  • Zhiqiang Jiang

    (Huazhong University of Science & Technology)

  • Benjun Jia

    (China Yangtze Power Co., Ltd.)

  • Wei Fang

    (Huazhong University of Science & Technology)

Abstract

An energy storage operation chart (ESOC) is one of the most popular methods for conventional cascade reservoir operation. However, the problem of distributing the total output obtained from the ESOC has not yet been reasonably solved. The discriminant coefficient method is a traditional method for guiding the output distribution by determining the order of reservoir supply or storage; however, it cannot quantify the water used in operation. Thus, this study develops a new output distribution model using a polynomial fitting method and an artificial neural network to express the functional relationship derived from the deterministic optimization results of long-term runoff series to maximize power generation. Cascade reservoirs of the lower reaches of the Jinsha River in China were selected for the case study. Compared to the discriminant coefficient method, the proposed method can rationally distribute the total output, thus avoiding the problem of concentrated deserting water in downstream reservoirs that occurs in the discriminant coefficient method. In general, this study proposes an effective alternative method to guide cascade reservoir operation.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:14:d:10.1007_s11269-022-03333-8
    DOI: 10.1007/s11269-022-03333-8
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    References listed on IDEAS

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    1. 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.
    2. Jiang, Zhiqiang & Li, Anqiang & Ji, Changming & Qin, Hui & Yu, Shan & Li, Yuanzheng, 2016. "Research and application of key technologies in drawing energy storage operation chart by discriminant coefficient method," Energy, Elsevier, vol. 114(C), pages 774-786.
    3. Suiling Wang & Zhiqiang Jiang & Yi Liu, 2022. "Dimensionality Reduction Method of Dynamic Programming under Hourly Scale and Its Application in Optimal Scheduling of Reservoir Flood Control," Energies, MDPI, vol. 15(3), pages 1-17, January.
    4. Jia Chen, 2021. "Long-Term Joint Operation of Cascade Reservoirs Using Enhanced Progressive Optimality Algorithm and Dynamic Programming Hybrid Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2265-2279, May.
    5. Meral Buyukyildiz & Gulay Tezel & Volkan Yilmaz, 2014. "Estimation of the Change in Lake Water Level by Artificial Intelligence Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4747-4763, October.
    6. Chun-Tian Cheng & Wen-Chuan Wang & Dong-Mei Xu & K. Chau, 2008. "Optimizing Hydropower Reservoir Operation Using Hybrid Genetic Algorithm and Chaos," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(7), pages 895-909, July.
    7. Elnaz Sharghi & Vahid Nourani & Hessam Najafi & Amir Molajou, 2018. "Emotional ANN (EANN) and Wavelet-ANN (WANN) Approaches for Markovian and Seasonal Based Modeling of Rainfall-Runoff Process," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3441-3456, August.
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    Cited by:

    1. Xinyu Wu & Yuan Lei & Chuntian Cheng & Qilin Ying, 2023. "An Optimal Operation Method for Parallel Hydropower Systems Combining Reservoir Level Control and Power Distribution," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1729-1745, March.
    2. Burhan Yildiz & Mehtap Kose Ulukok & Vali Bashiry, 2023. "Bi-Attempted Base Optimization Algorithm on Optimization of Hydrosystems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3585-3597, July.

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