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Short-term optimal scheduling of cascade hydropower plants with reverse-regulating effects

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  • Su, Chengguo
  • Wang, Peilin
  • Yuan, Wenlin
  • Wu, Yang
  • Jiang, Feng
  • Wu, Zening
  • Yan, Denghua

Abstract

The joint operation mode of large hydropower plants and their reverse-regulating plants has been widely used in China's major river basins. Hence this paper establishes an optimization model for the short-term optimal scheduling of cascade hydropower plants with reverse-regulating effects. Two conflicting objectives that need to be considered for optimal operation are minimizing the peak-valley difference of the power grid and minimizing the outflow variation of the reverse-regulating plant. The complex hydraulic coupling between the main-regulating plant and reverse-regulating plant is of particular concern. A novel two-layer nested approach, coupling constraint method and a mixed-integer linear programming (MILP) approach, is therefore proposed to solve the model. The results for three case studies demonstrate that: 1) The proposed approach is computationally efficient, and the average time for a single calculation is about 12 min; 2) The peak-valley difference of power grid G in dry season and flood season is reduced by 26.0% and 15.7%, respectively, after optimization. The outflow variation of the reverse-regulating plant has been controlled at 300 and 350 m3/s, respectively. 3) The developed model produces a more realistic and executable scheduling scheme than the benchmark model which does not consider the complex hydraulic coupling between cascade plants.

Suggested Citation

  • Su, Chengguo & Wang, Peilin & Yuan, Wenlin & Wu, Yang & Jiang, Feng & Wu, Zening & Yan, Denghua, 2022. "Short-term optimal scheduling of cascade hydropower plants with reverse-regulating effects," Renewable Energy, Elsevier, vol. 199(C), pages 395-406.
    • Handle: RePEc:eee:renene:v:199:y:2022:i:c:p:395-406
    DOI: 10.1016/j.renene.2022.08.159
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    References listed on IDEAS

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    1. Su, Chengguo & Cheng, Chuntian & Wang, Peilin & Shen, Jianjian & Wu, Xinyu, 2019. "Optimization model for long-distance integrated transmission of wind farms and pumped-storage hydropower plants," Applied Energy, Elsevier, vol. 242(C), pages 285-293.
    2. J. Yazdi & A. Moridi, 2018. "Multi-Objective Differential Evolution for Design of Cascade Hydropower Reservoir Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4779-4791, November.
    3. Wang, Peilin & Yuan, Wenlin & Su, Chengguo & Wu, Yang & Lu, Lu & Yan, Denghua & Wu, Zening, 2022. "Short-term optimal scheduling of cascade hydropower plants shaving peak load for multiple power grids," Renewable Energy, Elsevier, vol. 184(C), pages 68-79.
    4. Liu, Benxi & Cheng, Chuntian & Wang, Sen & Liao, Shengli & Chau, Kwok-Wing & Wu, Xinyu & Li, Weidong, 2018. "Parallel chance-constrained dynamic programming for cascade hydropower system operation," Energy, Elsevier, vol. 165(PA), pages 752-767.
    5. Yuan, Wenlin & Xin, Wenpeng & Su, Chengguo & Cheng, Chuntian & Yan, Denghua & Wu, Zening, 2022. "Cross-regional integrated transmission of wind power and pumped-storage hydropower considering the peak shaving demands of multiple power grids," Renewable Energy, Elsevier, vol. 190(C), pages 1112-1126.
    6. Dai, Wei & Yang, Zhifang & Yu, Juan & Zhao, Ke & Wen, Shiyang & Lin, Wei & Li, Wenyuan, 2019. "Security region of renewable energy integration: Characterization and flexibility," Energy, Elsevier, vol. 187(C).
    7. Ding, Ning & Duan, Jinhui & Xue, Song & Zeng, Ming & Shen, Jianfei, 2015. "Overall review of peaking power in China: Status quo, barriers and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 503-516.
    8. Joe Naoum-Sawaya & Samir Elhedhli, 2013. "An interior-point Benders based branch-and-cut algorithm for mixed integer programs," Annals of Operations Research, Springer, vol. 210(1), pages 33-55, November.
    9. Yuan, Wenlin & Wang, Xinqi & Su, Chengguo & Cheng, Chuntian & Liu, Zhe & Wu, Zening, 2021. "Stochastic optimization model for the short-term joint operation of photovoltaic power and hydropower plants based on chance-constrained programming," Energy, Elsevier, vol. 222(C).
    10. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2017. "Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling," Energy, Elsevier, vol. 131(C), pages 165-178.
    11. Chen, Yongbao & Zhang, Lixin & Xu, Peng & Di Gangi, Alessandra, 2021. "Electricity demand response schemes in China: Pilot study and future outlook," Energy, Elsevier, vol. 224(C).
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    Cited by:

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    5. Lu, Na & Wang, Guangyan & Su, Chengguo & Ren, Zaimin & Peng, Xiaoyue & Sui, Quan, 2024. "Medium- and long-term interval optimal scheduling of cascade hydropower-photovoltaic complementary systems considering multiple uncertainties," Applied Energy, Elsevier, vol. 353(PA).

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