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Optimal Inertia Reserve and Inertia Control Strategy for Wind Farms

Author

Listed:
  • Youming Cai

    (Wind Power Research Center, School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)

  • Zheng Li

    (School of Information Science and Technology, Donghua University, Shanghai 201620, China)

  • Xu Cai

    (Wind Power Research Center, School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)

Abstract

It is important to reduce the impact of the high penetration of wind power into the electricity supply for the purposes of the security and stability of the power grid. As such, the inertia capability of wind farms has become an observation index. The existing control modes cannot guarantee the wind turbine to respond to the frequency variation of the grid, hence, it may lead to frequency instability as the penetration of wind power gets much higher. For the stability of the power grid, a simple and applicable method is to realize inertia response by controlling wind farms based on a high-speed communication network. Thus, with the consideration of the inertia released by a wind turbine at its different operating points, the inertia control mechanism of a doubly-fed wind turbine is analyzed firstly in this paper. The optimal exit point of inertia control is discussed. Then, an active power control strategy for wind farms is proposed to reserve the maximum inertia under a given power output constraint. Furthermore, turbines in a wind farm are grouped depending on their inertia capabilities, and a wind farm inertia control strategy for reasonable extraction of inertia is then presented. Finally, the effectiveness of the proposed control strategy is verified by simulation on the RT-LAB (11.3.3, OPAL-RT TECHNOLOGIES, Montreal, Quebec, Canada) platform with detailed models of the wind farm.

Suggested Citation

  • Youming Cai & Zheng Li & Xu Cai, 2020. "Optimal Inertia Reserve and Inertia Control Strategy for Wind Farms," Energies, MDPI, vol. 13(5), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1067-:d:326700
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    References listed on IDEAS

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    1. Bing Wang & Zhen Tang & Xiang Gao & Weiyang Liu & Xianhui Chen, 2019. "Distributed Control Strategy of the Leader-Follower for Offshore Wind Farms under Fault Conditions," Sustainability, MDPI, vol. 11(8), pages 1-20, April.
    2. Fernandez, L.M. & Garcia, C.A. & Jurado, F., 2008. "Comparative study on the performance of control systems for doubly fed induction generator (DFIG) wind turbines operating with power regulation," Energy, Elsevier, vol. 33(9), pages 1438-1452.
    3. Tonglin Fu & Chen Wang, 2018. "A Hybrid Wind Speed Forecasting Method and Wind Energy Resource Analysis Based on a Swarm Intelligence Optimization Algorithm and an Artificial Intelligence Model," Sustainability, MDPI, vol. 10(11), pages 1-24, October.
    4. Lingzhi Wang & Jun Liu & Fucai Qian, 2019. "Frequency Distribution Model of Wind Speed Based on the Exponential Polynomial for Wind Farms," Sustainability, MDPI, vol. 11(3), pages 1-13, January.
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    Cited by:

    1. Cheng Chi & Hai Zhao & Jiahang Han, 2022. "Study on Quantitative Evaluation Index of Power System Frequency Response Capability," Energies, MDPI, vol. 15(24), pages 1-13, December.

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