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Advanced adaptive frequency support scheme for DFIG under cyber uncertainty

Author

Listed:
  • Wang, Huaizhi
  • Liu, Yangyang
  • Zhou, Bin
  • Voropai, Nikolai
  • Cao, Guangzhong
  • Jia, Youwei
  • Barakhtenko, Evgeny

Abstract

In recent years, the development of information and communication technology has promoted the transformation of traditional electrical power grid into a deeply-intertwined cyber physical power system (CPPS). However, it also introduces cyber uncertainties that have a significant impact on the economic operation and real-time control of CPPS. This paper aims to solve the control problem of frequency support of wind farms in a cyber uncertainty environment, and proposes an advanced adaptive frequency support scheme for doubly-fed induction generator (DFIG). In the proposed scheme, both the minimum rotor speed and the deloaded operating level of wind turbines are required to be determined at first. Then, an advanced adaptive droop control method is proposed with consideration of cyber uncertainty to improve the response speed of wind turbines for frequency support. Finally, the stability of the proposed scheme is theoretically proved. The proposed scheme combines deloading control and inertial control, so that the controller can not only make up for the impact of cyber uncertainty on frequency regulation, but also can adaptively determine the participation factor of each wind turbine. The effectiveness of this control scheme is highlighted on a simulation platform built on Matlab/Simulink. The obtained results demonstrate that the proposed control scheme is capable for improving the frequency nadir and preventing secondary frequency dips.

Suggested Citation

  • Wang, Huaizhi & Liu, Yangyang & Zhou, Bin & Voropai, Nikolai & Cao, Guangzhong & Jia, Youwei & Barakhtenko, Evgeny, 2020. "Advanced adaptive frequency support scheme for DFIG under cyber uncertainty," Renewable Energy, Elsevier, vol. 161(C), pages 98-109.
    • Handle: RePEc:eee:renene:v:161:y:2020:i:c:p:98-109
    DOI: 10.1016/j.renene.2020.06.085
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    References listed on IDEAS

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    Cited by:

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