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Distributed Coordinated Control of Offshore Doubly Fed Wind Turbine Groups Based on the Hamiltonian Energy Method

Author

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  • Bing Wang

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
    School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China)

  • Qiuxuan Wu

    (School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China)

  • Min Tian

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Qingyi Hu

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

Abstract

To support doubly fed wind turbine (DFWT) groups in offshore wind farms, this paper proposes a distributed coordinated control based on the Hamiltonian energy theory. This strategy provides global stability to closed-loop systems and facilitates output synchronization. First, a model of a DFWT is realized as a port-controlled Hamiltonian system with dissipation (PCH-D), and the single-machine model is expanded into a multi-machine model of a wind turbine group. Then, by using the design methodology of distributed Hamiltonian systems, a distributed coordinated control is presented for a multi-machine PCH-D system. Furthermore, to investigate failures in wind turbine groups, they are divided into two cases: the separation of failed machines from the system, and the grid-connected operation of failed machines after a fault. These cases correspond to undirected and directed graphs, respectively. Finally, simulations prove that distributed coordinated control enhances the reliability and autonomy of wind turbine groups in offshore wind farms.

Suggested Citation

  • Bing Wang & Qiuxuan Wu & Min Tian & Qingyi Hu, 2017. "Distributed Coordinated Control of Offshore Doubly Fed Wind Turbine Groups Based on the Hamiltonian Energy Method," Sustainability, MDPI, vol. 9(8), pages 1-14, August.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:8:p:1448-:d:108535
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    References listed on IDEAS

    as
    1. Tzay-An Shiau & Ji-Kai Chuen-Yu, 2016. "Developing an Indicator System for Measuring the Social Sustainability of Offshore Wind Power Farms," Sustainability, MDPI, vol. 8(5), pages 1-14, May.
    2. Sergio Fragoso & Juan Garrido & Francisco Vázquez & Fernando Morilla, 2017. "Comparative Analysis of Decoupling Control Methodologies and H ∞ Multivariable Robust Control for Variable-Speed, Variable-Pitch Wind Turbines: Application to a Lab-Scale Wind Turbine," Sustainability, MDPI, vol. 9(5), pages 1-21, April.
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    Cited by:

    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. Ciprian Sorandaru & Sorin Musuroi & Flaviu Mihai Frigura-Iliasa & Doru Vatau & Marian Dordescu, 2019. "Analysis of the Wind System Operation in the Optimal Energetic Area at Variable Wind Speed over Time," Sustainability, MDPI, vol. 11(5), pages 1-16, February.
    3. Bing Wang & Min Tian & Tingjun Lin & Yinlong Hu, 2018. "Distributed Complementary Control Research of Wind Turbines in Two Offshore Wind Farms," Sustainability, MDPI, vol. 10(2), pages 1-21, February.
    4. Bing Wang & Zhen Tang & Weiyang Liu & Qiuqiao Zhang, 2020. "A Distributed Cooperative Control Strategy of Offshore Wind Turbine Groups with Input Time Delay," Sustainability, MDPI, vol. 12(7), pages 1-19, April.

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