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Research on Two-Stage Regulation Method for Source–Load Flexibility Transformation in Power Systems

Author

Listed:
  • Chunyang Hao

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Yibo Wang

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Chuang Liu

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Guanglie Zhang

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Hao Yu

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Dongzhe Wang

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Jingru Shang

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

Abstract

Under the premise of continuously increasing the grid-connected capacity of new energy, the fluctuation and anti-peak shaving characteristics of wind power have always constrained the development of green power systems. Considering the characteristics of power system flexibility resources, this paper introduces a two-stage regulation approach for power systems with enhanced source–load flexibility. In the day-ahead stage, an advanced peak regulation transformation is employed, leveraging the combined heat storage device of conventional thermal power units to enhance their peak regulation capability. Additionally, the Energy Intensive Load (EIL) is integrated into the regulation system. A two-level coordinated optimization model is developed, incorporating wind power integration and dispatching power allocation, with the aim of optimizing wind power integration and achieving the optimal allocation of dispatching power. In the intra-day stage, the connection of wind plants and energy storage devices is utilized to minimize the wind power fluctuations and improve the control ability over wind power variations. Compared with traditional methods, the wind power consumption in Scenario 1 and Scenario 2 increases by 2741.1 MW/h and 2478.5 MW/h respectively. Furthermore, the inclusion of an energy storage device in the intra-day stage significantly reduces the wind power fluctuations, maintaining a stable fluctuation rate within ±1%. Therefore, this method can effectively improve the level of wind power consumption and reduce the impact of real-time fluctuations on the power system.

Suggested Citation

  • Chunyang Hao & Yibo Wang & Chuang Liu & Guanglie Zhang & Hao Yu & Dongzhe Wang & Jingru Shang, 2023. "Research on Two-Stage Regulation Method for Source–Load Flexibility Transformation in Power Systems," Sustainability, MDPI, vol. 15(18), pages 1-23, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13918-:d:1243183
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    References listed on IDEAS

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    1. Ikegami, Takashi & Urabe, Chiyori T. & Saitou, Tetsuo & Ogimoto, Kazuhiko, 2018. "Numerical definitions of wind power output fluctuations for power system operations," Renewable Energy, Elsevier, vol. 115(C), pages 6-15.
    2. Zeng, Yuan & Zhang, Ruiwen & Wang, Dong & Mu, Yunfei & Jia, Hongjie, 2019. "A regional power grid operation and planning method considering renewable energy generation and load control," Applied Energy, Elsevier, vol. 237(C), pages 304-313.
    3. Zhao, Xiaoli & Chen, Haoran & Liu, Suwei & Ye, Xiaomei, 2020. "Economic & environmental effects of priority dispatch of renewable energy considering fluctuating power output of coal-fired units," Renewable Energy, Elsevier, vol. 157(C), pages 695-707.
    4. Qiang Zhou & Jianmei Zhang & Pengfei Gao & Ruixiao Zhang & Lijuan Liu & Sheng Wang & Lin Cheng & Wei Wang & Shiyou Yang, 2023. "Two-Stage Robust Optimization for Prosumers Considering Uncertainties from Sustainable Energy of Wind Power Generation and Load Demand Based on Nested C&CG Algorithm," Sustainability, MDPI, vol. 15(12), pages 1-23, June.
    5. Tang, Hong & Wang, Shengwei, 2023. "Game-theoretic optimization of demand-side flexibility engagement considering the perspectives of different stakeholders and multiple flexibility services," Applied Energy, Elsevier, vol. 332(C).
    6. Sasaki, Kento & Aki, Hirohisa & Ikegami, Takashi, 2022. "Application of model predictive control to grid flexibility provision by distributed energy resources in residential dwellings under uncertainty," Energy, Elsevier, vol. 239(PB).
    7. Yao, Leyi & Liu, Zeyuan & Chang, Weiguang & Yang, Qiang, 2023. "Multi-level model predictive control based multi-objective optimal energy management of integrated energy systems considering uncertainty," Renewable Energy, Elsevier, vol. 212(C), pages 523-537.
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    Cited by:

    1. Xiaoqing Wang & Xin Du & Haiyun Wang & Sizhe Yan & Tianyuan Fan, 2024. "Research on Coordinated Optimization of Source-Load-Storage Considering Renewable Energy and Load Similarity," Energies, MDPI, vol. 17(6), pages 1-16, March.

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