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Online Evaluation for the POI-Level Inertial Support to the Grid via Ambient Measurements

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Listed:
  • Genzhu Wu

    (School of Electrical Engineering, Xinjiang University, Urumqi 830046, China)

  • Weilin Zhong

    (School of Electrical Engineering, Xinjiang University, Urumqi 830046, China)

  • Muyang Liu

    (School of Electrical Engineering, Xinjiang University, Urumqi 830046, China)

  • Xiqiang Chang

    (School of Electrical Engineering, Xinjiang University, Urumqi 830046, China
    State Grid Xinjiang Electric Power Co., Ltd., Urumqi 830011, China)

  • Xianlong Shao

    (School of Electrical Engineering, Xinjiang University, Urumqi 830046, China)

  • Ruo Mo

    (School of Electrical Engineering, Xinjiang University, Urumqi 830046, China)

Abstract

As renewable energy sources like wind and solar power increasingly replace traditional energy sources and are integrated into the power grid, the issue of insufficient system inertia is becoming more apparent. This paper presents an online adaptive time window inertia constant identification method based on ambient measurements to identify the equivalent inertia constant of the time-varying inertia at Point of Interface ( POI ) level. The proposed method takes advantage of the online inertia estimation and the data-driven equivalent inertia constant identification techniques to simultaneously achieve online tracking and accuracy. With this regard, this paper first describes the inertia providers in modern system. Then, based on the frequency and power data measured by the Phasor Measurement Unit (PMU), this paper provides an improved data-driven equivalent inertia constant identification method. Subsequently, the paper proposes an ambient data smoothing method to cope with the numerical errors and provides, as a byproduct, an adaptive time window inertia constant identification. The adaptive time window is designed to enhance the accuracy of the method. Finally, the feasibility and accuracy of the proposed method of tracking synthetic inertia are validated by the simulation tests based on a grid in northwest China with high renewable energy penetration and a Virtual Power Plant (VPP). The experimental results show that the accuracy of this method is within 5 % .

Suggested Citation

  • Genzhu Wu & Weilin Zhong & Muyang Liu & Xiqiang Chang & Xianlong Shao & Ruo Mo, 2024. "Online Evaluation for the POI-Level Inertial Support to the Grid via Ambient Measurements," Energies, MDPI, vol. 17(20), pages 1-17, October.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5115-:d:1498905
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    References listed on IDEAS

    as
    1. Aleksey Suvorov & Alisher Askarov & Nikolay Ruban & Vladimir Rudnik & Pavel Radko & Andrey Achitaev & Konstantin Suslov, 2023. "An Adaptive Inertia and Damping Control Strategy Based on Enhanced Virtual Synchronous Generator Model," Mathematics, MDPI, vol. 11(18), pages 1-29, September.
    2. Li, Baolin & Wang, Jia & Nassani, Abdelmohsen A. & Binsaeed, Rima H. & Li, Zeyun, 2023. "The future of Green energy: A panel study on the role of renewable resources in the transition to a Green economy," Energy Economics, Elsevier, vol. 127(PB).
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