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Short-term optimal scheduling of cascade hydropower plants shaving peak load for multiple power grids

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

Abstract

Cascade hydropower plants which have good regulation performance and are managed by the dispatching center of regional power grids are usually required to simultaneously shave the peak load for multiple provincial power grids, which is an important way of relieving the growing peak shaving pressure on power grids in central and eastern China. This paper establishes an optimization model for the short-term generation scheduling of cascade hydropower plants in regional power grids. In this model, minimizing the peak-valley load difference of multiple power grids is adopted as the objective function. In addition to conventional hydraulic constraints, the operation constraints of individual hydropower units, electrical constraints and head effect on the power generation are all considered to obtain precise scheduling. The original nonlinear and non-convex model is converted into a standard mixed-integer linear programming (MILP) formulation through several linearization strategies. The results for the real-world case study indicate that: 1) the proposed model is computationally efficient with a calculation time of 326 s; 2) the peak-valley differences of the Shanghai Power Grid and Zhejiang Power Grid decreased by 9.71% and 2.29%, respectively; 3) compared with actual operation, the proposed model shows better performance in peak shaving for multiple provincial power grids.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:184:y:2022:i:c:p:68-79
    DOI: 10.1016/j.renene.2021.10.079
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    References listed on IDEAS

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    2. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Yan, Zhiyu, 2022. "A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems," Renewable Energy, Elsevier, vol. 196(C), pages 204-219.
    3. Zhou, Siyu & Han, Yang & Zalhaf, Amr S. & Chen, Shuheng & Zhou, Te & Yang, Ping & Elboshy, Bahaa, 2023. "A novel multi-objective scheduling model for grid-connected hydro-wind-PV-battery complementary system under extreme weather: A case study of Sichuan, China," Renewable Energy, Elsevier, vol. 212(C), pages 818-833.
    4. 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).
    5. Fang, Zhou & Liao, Shengli & Cheng, Chuntian & Zhao, Hongye & Liu, Benxi & Su, Huaying, 2023. "Parallel improved DPSA algorithm for medium-term optimal scheduling of large-scale cascade hydropower plants," Renewable Energy, Elsevier, vol. 210(C), pages 134-147.
    6. 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.
    7. Wang, Jin & Zhao, Zhipeng & Zhou, Jinglin & Cheng, Chuntian & Su, Huaying, 2024. "Developing operating rules for a hydro–wind–solar hybrid system considering peak-shaving demands," Applied Energy, Elsevier, vol. 360(C).
    8. Liao, Shengli & Yang, Hualong & Liu, Benxi & Zhao, Hongye & Liu, Huan & Ma, Xiangyu & Wu, Huijun, 2022. "Daily peak-shaving model of cascade hydropower serving multi-grids considering an HVDC channel shared constraint," Renewable Energy, Elsevier, vol. 199(C), pages 112-122.
    9. Liu, Benxi & Liu, Tengyuan & Liao, Shengli & Wang, Haidong & Jin, Xiaoyu, 2023. "Short-term operation of cascade hydropower system sharing flexibility via high voltage direct current lines for multiple grids peak shaving," Renewable Energy, Elsevier, vol. 213(C), pages 11-29.

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