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Author:

Li, Xuan (Li, Xuan.) | Xu, Ying (Xu, Ying.) | Li, Fengmo (Li, Fengmo.) | Kang, Qiao (Kang, Qiao.) | Li, Zhuling (Li, Zhuling.) | Long, Cheng (Long, Cheng.)

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Abstract:

Because the wind farm grid-connected analysis model cannot satisfy the requirements of simulation speed and accuracy simultaneously, it is not conducive to research the interaction between large-scale wind farms and power system. Therefore, establishing a wind farm equivalent model, which can accurately represent the operation characteristics, is very important to research the stable operation of power system. In the paper, the method of combining principal component analysis (PCA) and DBSCAN is adopted to establish the aggregated model of permanent magnet synchronous generator (PMSG) offshore wind farm, and the MATLAB/Simulink is employed to do the simulation verification. The result shows that the proposed model can accurately represent the dynamic response of the wind farm. Meanwhile, the model has good equivalent effect under the conditions of wind speed fluctuation and short circuit fault. © 2021 IEEE.

Keyword:

Clustering algorithms Electric machine theory Electric power system interconnection Electric utilities MATLAB Offshore oil well production Offshore wind farms Permanent magnets Synchronous generators Wind

Author Community:

  • [ 1 ] [Li, Xuan]State Grid Economic and Technological Research Institute Co. Ltd., Dc Technical Consulting Center, Beijing, China
  • [ 2 ] [Xu, Ying]State Grid Economic and Technological Research Institute Co. Ltd., Dc Technical Consulting Center, Beijing, China
  • [ 3 ] [Li, Fengmo]State Grid Economic and Technological Research Institute Co. Ltd., Dc Technical Consulting Center, Beijing, China
  • [ 4 ] [Kang, Qiao]State Grid Economic and Technological Research Institute Co. Ltd., Dc Technical Consulting Center, Beijing, China
  • [ 5 ] [Li, Zhuling]Xi'an Jiaotong University, School of Electrical Engineering, Xi'an, China
  • [ 6 ] [Long, Cheng]Xi'an Jiaotong University, School of Electrical Engineering, Xi'an, China

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Year: 2021

Page: 761-766

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 8

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