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Low voltage ride through enhancement of a permanent magnet synchronous generator based wind energy conversion system in an islanded microgrid: A dynamic matrix controlled virtual DC machine

Author

Listed:
  • Bo, Long
  • Chen, ZhiHao
  • Li, XingYu
  • Rodriguez, Jose
  • To Chong, Kil

Abstract

In an isolated microgrid, the wind energy conversion system based on direct-drive permanent magnet synchronous generator may experience fluctuations in the DC bus voltage due to wind variations and grid voltage drop, thereby compromising system reliability. To address this issue, the scheme of the supercapacitor energy storage system is proposed. The existing double closed-loop PID control, which cannot provide inertia support, has shortcomings such as difficult parameter setting and slow dynamic response. To solve this problem, the dynamic-matrix-control based predictive control for a virtual DC machine method is proposed. Firstly, the concept of virtual DC machine control is firstly introduced in supercapacitor energy storage system. Secondly, according to the unit step response of virtual DC machine, the prediction model of virtual DC machine is established. Finally, the desired torque increment reference of virtual DC machine is calculated by the dynamic-matrix-control controller to change the input torque reference. Hardware-in-the-loop experiment verifies the effectiveness of the proposed method: Compared with traditional double closed-loop PID control, the maximum voltage fluctuation is reduced by 67.9 % under random wind fluctuation and the inhibition effect on DC voltage surge and plunge when fault occurs in the power grid is increased by 61.4 % and 57.9 %.

Suggested Citation

  • Bo, Long & Chen, ZhiHao & Li, XingYu & Rodriguez, Jose & To Chong, Kil, 2024. "Low voltage ride through enhancement of a permanent magnet synchronous generator based wind energy conversion system in an islanded microgrid: A dynamic matrix controlled virtual DC machine," Renewable Energy, Elsevier, vol. 228(C).
  • Handle: RePEc:eee:renene:v:228:y:2024:i:c:s0960148124007481
    DOI: 10.1016/j.renene.2024.120680
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