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Flexible Kinetic Energy Release Controllers for a Wind Farm in an Islanding System

Author

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  • Yi-Wei Chen

    (Department of Electrical Engineering, National Taiwan University, EE Building 2, No. 1, Sec. 4, Roosevelt Rd., Taipei 106, Taiwan)

  • Yuan-Yih Hsu

    (Department of Electrical Engineering, National Taiwan University, EE Building 2, No. 1, Sec. 4, Roosevelt Rd., Taipei 106, Taiwan)

Abstract

To improve frequency nadir following a disturbance and avoid under-frequency load shedding, two types of flexible kinetic energy release controllers for the doubly fed induction generator (DFIG) are proposed. The basic idea is to release only a small amount of kinetic energy stored at the DFIG in the initial transient period (1–3 s after the disturbance). When the frequency dip exceeds a preset threshold, the amount of kinetic energy released is increased to improve the frequency nadir. To achieve the goal of flexible kinetic energy release, a deactivation function based integral controller is first presented. To further improve the dynamic frequency response under parameter uncertainties and external disturbances, a second flexible kinetic energy release controller is designed using a proportional-integral controller, with the gains being adapted in real-time with the particle swarm optimization algorithm. Based on the MATLAB/SIMULINK simulation results for a local power system, it is concluded that the frequency nadir can be maintained around the under-frequency load shedding threshold of 59.6 Hz using the proposed controllers.

Suggested Citation

  • Yi-Wei Chen & Yuan-Yih Hsu, 2020. "Flexible Kinetic Energy Release Controllers for a Wind Farm in an Islanding System," Energies, MDPI, vol. 13(22), pages 1-15, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:6135-:d:449504
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    References listed on IDEAS

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    1. 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.
    2. Hafiz, Faizal & Abdennour, Adel, 2016. "An adaptive neuro-fuzzy inertia controller for variable-speed wind turbines," Renewable Energy, Elsevier, vol. 92(C), pages 136-146.
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    Cited by:

    1. Lasantha Meegahapola & Siqi Bu, 2021. "Special Issue: “Wind Power Integration into Power Systems: Stability and Control Aspects”," Energies, MDPI, vol. 14(12), pages 1-4, June.

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