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Coordinated Control of Wind Turbine and Energy Storage System for Reducing Wind Power Fluctuation

Author

Listed:
  • Chunghun Kim

    (Department of Electrical Engineering, Hanyang University, Seoul 133-791, Korea)

  • Eduard Muljadi

    (National Renewable Energy Laboratory, Golden, CO 80401, USA)

  • Chung Choo Chung

    (Department of Electrical Engineering, Hanyang University, Seoul 133-791, Korea)

Abstract

This paper proposes a method for the coordinated control of a wind turbine and an energy storage system (ESS). Because wind power (WP) is highly dependent on wind speed, which is variable, severe stability problems can be caused in power systems, especially when the WP has a high penetration level. To solve this problem, many power generation corporations or grid operators have begun using ESSs. An ESS has very quick response and good performance for reducing the impact of WP fluctuation; however, its installation cost is high. Therefore, it is important to design the control algorithm by considering both the ESS capacity and WP fluctuation. Thus, we propose a control algorithm to mitigate the WP fluctuation by using the coordinated control between the wind turbine and the ESS by considering the ESS capacity and the WP fluctuation. Using de-loaded control, according to the WP fluctuation and ESS capacity, we can expand the ESS lifespan and improve grid reliability by avoiding the extreme value of state of charge (SoC) (i.e., 0 or 1 pu). The effectiveness of the proposed method was validated via MATLAB/Simulink by considering a small power system that includes both a wind turbine generator and conventional generators that react to system frequency deviation. We found that the proposed method has better performance in SoC management, thereby improving the frequency regulation by mitigating the impact of the WP fluctuation on the small power system.

Suggested Citation

  • Chunghun Kim & Eduard Muljadi & Chung Choo Chung, 2017. "Coordinated Control of Wind Turbine and Energy Storage System for Reducing Wind Power Fluctuation," Energies, MDPI, vol. 11(1), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:11:y:2017:i:1:p:52-:d:124524
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    References listed on IDEAS

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    1. Wei Wang & Chengxiong Mao & Jiming Lu & Dan Wang, 2013. "An Energy Storage System Sizing Method for Wind Power Integration," Energies, MDPI, vol. 6(7), pages 1-13, July.
    2. Xisheng Tang & Yushu Sun & Guopeng Zhou & Fufeng Miao, 2017. "Coordinated Control of Multi-Type Energy Storage for Wind Power Fluctuation Suppression," Energies, MDPI, vol. 10(8), pages 1-16, August.
    3. Calif, Rudy & Schmitt, François G. & Huang, Yongxiang, 2013. "Multifractal description of wind power fluctuations using arbitrary order Hilbert spectral analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4106-4120.
    4. Jin-Sun Yang & Jin-Young Choi & Geon-Ho An & Young-Jun Choi & Myoung-Hoe Kim & Dong-Jun Won, 2016. "Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation," Energies, MDPI, vol. 9(12), pages 1-13, November.
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    Cited by:

    1. Zhe Jiang & Xueshan Han & Zhimin Li & Mingqiang Wang & Guodong Liu & Mengxia Wang & Wenbo Li & Thomas B. Ollis, 2018. "Capacity Optimization of a Centralized Charging Station in Joint Operation with a Wind Farm," Energies, MDPI, vol. 11(5), pages 1-18, May.
    2. Danny Ochoa & Sergio Martinez, 2018. "Proposals for Enhancing Frequency Control in Weak and Isolated Power Systems: Application to the Wind-Diesel Power System of San Cristobal Island-Ecuador," Energies, MDPI, vol. 11(4), pages 1-25, April.

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