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Refined Scheduling Based on Dynamic Capacity Model for Short-term Hydropower Generation

Author

Listed:
  • Rongqi Zhang

    (North China Electric Power University)

  • Shanghong Zhang

    (North China Electric Power University)

  • Xiaoxiong Wen

    (North China Electric Power University)

  • Zhu Jing

    (Changjiang Design Group Co., Ltd.)

Abstract

Existing studies on reservoir hydropower generation scheduling mostly use the static reservoir capacity method, which introduces large errors in scheduling calculations for river-type reservoirs. As a typical river-type reservoir, the Three Gorges Reservoir in China uses the dynamic reservoir capacity method for improved scheduling of the hydropower generation scheduling process. This study investigated the short-term power generation scheduling of the Three Gorges Reservoir, and established a dynamic capacity short-term hydropower generation scheduling model based on a one-dimensional unsteady flow model. Considering the measured actual water level before the dam and the inflow process, model simulation schemes were established according to the dispatching regulations, and 94,479 scheduling schemes were generated. Different schemes were simulated using the dynamic capacity hydropower scheduling model (DCHSM) to derive the maximum power generation scheme. Then, this scheme was compared with the optimal scheme of the static capacity hydropower scheduling model. Results revealed that use of the optimal scheme of the static capacity hydropower scheduling model could generate power output of 1.765 billion kWh, while the maximum power output of the DCHSM scheme was calculated at 1.792 billion kWh. In comparison with the actual power of 1.777 billion kWh, use of the DCHSM could increase power output by approximately 0.90%. The calculated power output process has reasonable agreement with the actual scheduling process and, contributes to refinement of reservoir scheduling. The findings of this study could provide technical support for refined short-term scheduling of river-type reservoirs.

Suggested Citation

  • Rongqi Zhang & Shanghong Zhang & Xiaoxiong Wen & Zhu Jing, 2023. "Refined Scheduling Based on Dynamic Capacity Model for Short-term Hydropower Generation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 21-35, January.
  • Handle: RePEc:spr:waterr:v:37:y:2023:i:1:d:10.1007_s11269-022-03352-5
    DOI: 10.1007/s11269-022-03352-5
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    References listed on IDEAS

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    1. Avesani, Diego & Zanfei, Ariele & Di Marco, Nicola & Galletti, Andrea & Ravazzolo, Francesco & Righetti, Maurizio & Majone, Bruno, 2022. "Short-term hydropower optimization driven by innovative time-adapting econometric model," Applied Energy, Elsevier, vol. 310(C).
    2. Changming Ji & Chuangang Li & Boquan Wang & Minghao Liu & Liping Wang, 2017. "Multi-Stage Dynamic Programming Method for Short-Term Cascade Reservoirs Optimal Operation with Flow Attenuation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4571-4586, November.
    3. Yuan, Wenlin & Zhang, Shijie & Su, Chengguo & Wu, Yang & Yan, Denghua & Wu, Zening, 2022. "Optimal scheduling of cascade hydropower plants in a portfolio electricity market considering the dynamic water delay," Energy, Elsevier, vol. 252(C).
    4. Hamidreza Rahimi & Saiyu Yuan & Xiaonan Tang & Chunhui Lu & Prateek Singh & Fariba Ahmadi Dehrashid, 2022. "Study on Conveyance Coefficient Influenced by Momentum Exchange Under Steady and Unsteady Flows in Compound Open Channels," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2179-2199, May.
    5. Feng, Suzhen & Zheng, Hao & Qiao, Yifan & Yang, Zetai & Wang, Jinwen & Liu, Shuangquan, 2022. "Weekly hydropower scheduling of cascaded reservoirs with hourly power and capacity balances," Applied Energy, Elsevier, vol. 311(C).
    6. Liao, Shengli & Liu, Huan & Liu, Zhanwei & Liu, Benxi & Li, Gang & Li, Shushan, 2021. "Medium-term peak shaving operation of cascade hydropower plants considering water delay time," Renewable Energy, Elsevier, vol. 179(C), pages 406-417.
    7. Lei, Kaixuan & Chang, Jianxia & Wang, Yimin & Guo, Aijun & Huang, Mengdi & Xu, Bo, 2022. "Cascade hydropower stations short-term operation for load distribution considering water level synchronous variation," Renewable Energy, Elsevier, vol. 196(C), pages 683-693.
    8. Juran Ahmed & Arup Sarma, 2005. "Genetic Algorithm for Optimal Operating Policy of a Multipurpose Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(2), pages 145-161, April.
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