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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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    1. Costoya, X. & deCastro, M. & Carvalho, D. & Gómez-Gesteira, M., 2020. "On the suitability of offshore wind energy resource in the United States of America for the 21st century," Applied Energy, Elsevier, vol. 262(C).
    2. Li, Pengfei & Hu, Weihao & Hu, Rui & Huang, Qi & Yao, Jun & Chen, Zhe, 2019. "Strategy for wind power plant contribution to frequency control under variable wind speed," Renewable Energy, Elsevier, vol. 130(C), pages 1226-1236.
    3. Deepak, M. & Abraham, Rajesh Joseph & Gonzalez-Longatt, Francisco M. & Greenwood, David M. & Rajamani, Haile-Selassie, 2017. "A novel approach to frequency support in a wind integrated power system," Renewable Energy, Elsevier, vol. 108(C), pages 194-206.
    4. Pradhan, Chittaranjan & Bhende, Chandrashekhar Narayan & Samanta, Anik Kumar, 2018. "Adaptive virtual inertia-based frequency regulation in wind power systems," Renewable Energy, Elsevier, vol. 115(C), pages 558-574.
    5. Zhang, Jian & Cui, Mingjian & He, Yigang, 2020. "Robustness and adaptability analysis for equivalent model of doubly fed induction generator wind farm using measured data," Applied Energy, Elsevier, vol. 261(C).
    6. Li, Yujun & Xu, Zhao & Zhang, Jianliang & Wong, Kit Po, 2018. "Variable gain control scheme of DFIG-based wind farm for over-frequency support," Renewable Energy, Elsevier, vol. 120(C), pages 379-391.
    7. Ochoa, Danny & Martinez, Sergio, 2018. "Frequency dependent strategy for mitigating wind power fluctuations of a doubly-fed induction generator wind turbine based on virtual inertia control and blade pitch angle regulation," Renewable Energy, Elsevier, vol. 128(PA), pages 108-124.
    8. Wang, Huaizhi & Ruan, Jiaqi & Ma, Zhengwei & Zhou, Bin & Fu, Xueqian & Cao, Guangzhong, 2019. "Deep learning aided interval state prediction for improving cyber security in energy internet," Energy, Elsevier, vol. 174(C), pages 1292-1304.
    9. Kheshti, Mostafa & Ding, Lei & Nayeripour, Majid & Wang, Xiaowei & Terzija, Vladimir, 2019. "Active power support of wind turbines for grid frequency events using a reliable power reference scheme," Renewable Energy, Elsevier, vol. 139(C), pages 1241-1254.
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