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Frequency constrained unit commitment considering reserve provision of wind power

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  • Jiang, Boyou
  • Guo, Chuangxin
  • Chen, Zhe

Abstract

Large-scale wind power integration not only requires extra flexibility for power system operation but also leads to declining system inertia and raises concerns regarding frequency stability. Pertinent studies have substantiated the capability of wind turbines (WTs) to provide reserves via pitch angle control (PAC) and rotor speed control (RSC). In this study, a comprehensive modeling approach is employed for the first time to capture WTs’ reserve capacities while accounting for the exogenous uncertainty associated with wind speed and the decision-dependent uncertainty regarding the control decisions including pitch angle and rotor speed. Subsequently, a two-stage frequency constrained stochastic unit commitment model incorporating WTs’ reserve provision is formulated to jointly optimize the unit commitment, generation, and reserves from both conventional generating units (CGUs) and WTs. To enhance computational tractability, a deep neural network based framework is adopted in combination with piece-wise linearization to linearize the nonlinear terms regarding PAC and RSC. Furthermore, two solution acceleration strategies tailored to the model’s characteristics are proposed. Case studies show that (i) the proposed model effectively develops the reserve potential of WTs, leading to a reduction in reserve cost and wind curtailment; (ii) the proposed acceleration strategies significantly improve the solution efficiency, reducing the solution time by 62.88% and 15.71% in the IEEE 9-bus and 118-bus systems, respectively.

Suggested Citation

  • Jiang, Boyou & Guo, Chuangxin & Chen, Zhe, 2024. "Frequency constrained unit commitment considering reserve provision of wind power," Applied Energy, Elsevier, vol. 361(C).
  • Handle: RePEc:eee:appene:v:361:y:2024:i:c:s0306261924002812
    DOI: 10.1016/j.apenergy.2024.122898
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    References listed on IDEAS

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    1. Yang, Yang & Peng, Jimmy Chih-Hsien & Ye, Zhi-Sheng, 2023. "Distributionally robust frequency dynamic constrained unit commitment considering uncertain demand-side resources," Applied Energy, Elsevier, vol. 331(C).
    2. Harsha Nagarajan & Mowen Lu & Site Wang & Russell Bent & Kaarthik Sundar, 2019. "An adaptive, multivariate partitioning algorithm for global optimization of nonconvex programs," Journal of Global Optimization, Springer, vol. 74(4), pages 639-675, August.
    3. Jiang, Sufan & Wu, Chuanshen & Gao, Shan & Pan, Guangsheng & Liu, Yu & Zhao, Xin & Wang, Sicheng, 2022. "Robust frequency risk-constrained unit commitment model for AC-DC system considering wind uncertainty," Renewable Energy, Elsevier, vol. 195(C), pages 395-406.
    4. Yin, Yue & Liu, Tianqi & Wu, Lei & He, Chuan & Liu, Yikui, 2021. "Frequency-constrained multi-source power system scheduling against N-1 contingency and renewable uncertainty," Energy, Elsevier, vol. 216(C).
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