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Research on a Small Signal Stability Region Boundary Model of the Interconnected Power System with Large-Scale Wind Power

Author

Listed:
  • Wenying Liu

    (Electrical and Electronic Engineering Institute, Mailbox 435, North China Electric Power University, No. 2 Beinong Road, Changping District, Beijing 102206, China)

  • Rundong Ge

    (Electrical and Electronic Engineering Institute, Mailbox 435, North China Electric Power University, No. 2 Beinong Road, Changping District, Beijing 102206, China)

  • Quancheng Lv

    (Electrical and Electronic Engineering Institute, Mailbox 435, North China Electric Power University, No. 2 Beinong Road, Changping District, Beijing 102206, China)

  • Huiyong Li

    (Electrical and Electronic Engineering Institute, Mailbox 435, North China Electric Power University, No. 2 Beinong Road, Changping District, Beijing 102206, China)

  • Jiangbei Ge

    (Electrical and Electronic Engineering Institute, Mailbox 435, North China Electric Power University, No. 2 Beinong Road, Changping District, Beijing 102206, China)

Abstract

For the interconnected power system with large-scale wind power, the problem of the small signal stability has become the bottleneck of restricting the sending-out of wind power as well as the security and stability of the whole power system. Around this issue, this paper establishes a small signal stability region boundary model of the interconnected power system with large-scale wind power based on catastrophe theory, providing a new method for analyzing the small signal stability. Firstly, we analyzed the typical characteristics and the mathematic model of the interconnected power system with wind power and pointed out that conventional methods can’t directly identify the topological properties of small signal stability region boundaries. For this problem, adopting catastrophe theory, we established a small signal stability region boundary model of the interconnected power system with large-scale wind power in two-dimensional power injection space and extended it to multiple dimensions to obtain the boundary model in multidimensional power injection space. Thirdly, we analyzed qualitatively the topological property’s changes of the small signal stability region boundary caused by large-scale wind power integration. Finally, we built simulation models by DIgSILENT/PowerFactory software and the final simulation results verified the correctness and effectiveness of the proposed model.

Suggested Citation

  • Wenying Liu & Rundong Ge & Quancheng Lv & Huiyong Li & Jiangbei Ge, 2015. "Research on a Small Signal Stability Region Boundary Model of the Interconnected Power System with Large-Scale Wind Power," Energies, MDPI, vol. 8(4), pages 1-25, March.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:4:p:2312-2336:d:47274
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    References listed on IDEAS

    as
    1. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    2. Kang, Junjie & Yuan, Jiahai & Hu, Zhaoguang & Xu, Yan, 2012. "Review on wind power development and relevant policies in China during the 11th Five-Year-Plan period," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 1907-1915.
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    Citations

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    Cited by:

    1. Jian Zuo & Yinhong Li & Dongyuan Shi & Xianzhong Duan, 2017. "Simultaneous Robust Coordinated Damping Control of Power System Stabilizers (PSSs), Static Var Compensator (SVC) and Doubly-Fed Induction Generator Power Oscillation Dampers (DFIG PODs) in Multimachin," Energies, MDPI, vol. 10(4), pages 1-23, April.
    2. Bingtuan Gao & Chaopeng Xia & Ning Chen & Khalid Mehmood Cheema & Libin Yang & Chunlai Li, 2017. "Virtual Synchronous Generator Based Auxiliary Damping Control Design for the Power System with Renewable Generation," Energies, MDPI, vol. 10(8), pages 1-21, August.
    3. Rundong Ge & Wenying Liu & Huiyong Li & Jianzong Zhuo & Weizhou Wang, 2015. "Research on the Multi-Period Small-Signal Stability Probability of a Power System with Wind Farms Based on the Markov Chain," Sustainability, MDPI, vol. 7(4), pages 1-18, April.
    4. Paul Stewart & Chris Bingham, 2016. "Electrical Power and Energy Systems for Transportation Applications," Energies, MDPI, vol. 9(7), pages 1-3, July.
    5. Rui Quan & Wenxia Pan, 2017. "A Low-Order System Frequency Response Model for DFIG Distributed Wind Power Generation Systems Based on Small Signal Analysis," Energies, MDPI, vol. 10(5), pages 1-15, May.

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