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An MILP-based model for short-term peak shaving operation of pumped-storage hydropower plants serving multiple power grids

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  • Cheng, Chuntian
  • Su, Chengguo
  • Wang, Peilin
  • Shen, Jianjian
  • Lu, Jianyu
  • Wu, Xinyu

Abstract

China's power grids have constructed many large pumped-storage hydropower plants (PSHPs) to relieve their increasing peak shaving pressure. Unlike PSHPs in a single power grid, the PSHPs directly operated by the dispatch center of regional power grids are required to simultaneously provide peak regulation services for several subordinate provincial power grids. This makes the daily operation of these PSHPs very challenging for both system operators and researchers. Hence, this paper develops a Mixed-integer linear programming (MILP) based model for determining the optimal hourly scheduling of PSHPs serving several provincial power grids. The objective is to minimize the peak-valley difference of the residual load series of each power grid. The performance of individual units in the model will be considered, as well as the head effect for each unit in both generating mode and pumping mode. The study focuses mainly on the linearization of the commonly-used nonlinear objective function, constraints on the operation status of units, and turbine performance curves. These nonlinearities are then linearized with the aid of binary integer variables. The optimization results obtained from two real-world case studies are used to demonstrate that the proposed model is computationally efficient and shows good performance in relieving the peak regulation pressure of each power grid.

Suggested Citation

  • Cheng, Chuntian & Su, Chengguo & Wang, Peilin & Shen, Jianjian & Lu, Jianyu & Wu, Xinyu, 2018. "An MILP-based model for short-term peak shaving operation of pumped-storage hydropower plants serving multiple power grids," Energy, Elsevier, vol. 163(C), pages 722-733.
    • Handle: RePEc:eee:energy:v:163:y:2018:i:c:p:722-733
    DOI: 10.1016/j.energy.2018.08.077
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    References listed on IDEAS

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    9. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization," Renewable Energy, Elsevier, vol. 191(C), pages 459-492.
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    12. Yahia, Zakaria & Pradhan, Anup, 2020. "Simultaneous and sequential stochastic optimization approaches for pumped storage plant scheduling with random breakdowns," Energy, Elsevier, vol. 204(C).
    13. 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).
    14. Zhu, Zilong & Chen, Yaping & Wu, Jiafeng & Zhang, Shaobo & Zheng, Shuxing, 2019. "A modified Allam cycle without compressors realizing efficient power generation with peak load shifting and CO2 capture," Energy, Elsevier, vol. 174(C), pages 478-487.
    15. Zhang, Juntao & Cheng, Chuntian & Yu, Shen & Wu, Huijun & Gao, Mengping, 2021. "Sharing hydropower flexibility in interconnected power systems: A case study for the China Southern power grid," Applied Energy, Elsevier, vol. 288(C).
    16. 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.
    17. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Zhang, Yi & Zhao, Zhipeng & Lu, Jia, 2022. "Wasserstein metric-based two-stage distributionally robust optimization model for optimal daily peak shaving dispatch of cascade hydroplants under renewable energy uncertainties," Energy, Elsevier, vol. 260(C).
    18. 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.
    19. 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.
    20. Liao, Shengli & Liu, Zhanwei & Liu, Benxi & Cheng, Chuntian & Wu, Xinyu & Zhao, Zhipeng, 2021. "Daily peak shaving operation of cascade hydropower stations with sensitive hydraulic connections considering water delay time," Renewable Energy, Elsevier, vol. 169(C), pages 970-981.
    21. Liu, Yuan & Ji, Changming & Wang, Yi & Zhang, Yanke & Jiang, Zhiqiang & Ma, Qiumei & Hou, Xiaoning, 2023. "Effect of the quality of streamflow forecasts on the operation of cascade hydropower stations using stochastic optimization models," Energy, Elsevier, vol. 273(C).
    22. Xian Yang & Ye Cai & Yijia Cao & Shaowei Duan & Liang Tang & Zhijian Jia, 2022. "The Semi-Scheduling Mode of Multi-Energy System Considering Risk–Utility in Day-Ahead Market," Energies, MDPI, vol. 15(21), pages 1-15, November.

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