Reducing model complexity of DFIG-based wind turbines to improve the efficiency of power system stability analysis

Siqi Bu, X. Zhang, S. W. Xia, Y. Xu, B. Zhou, X. Lu

Research output: Journal article publicationConference articleAcademic researchpeer-review

8 Citations (Scopus)


Published by Elsevier Ltd. The growing number of doubly-fed induction generator (DFIG) based wind farms has significantly increased the model complexity and simulation burden for power system stability analysis. In this paper, a novel method to assess the modeling adequacy of DFIGs for small-signal stability analysis is introduced. By evaluating the damping torque contribution to stability margin from different DFIG dynamic model components, the proposed method provides a quantitative index to show the participation level of each DFIG model component in affecting power system damping performance. In addition, five DFIG model reduction schemes are established, and a novel strategy to reduce individual DFIG model complexity based on the participation level is proposed. The effectiveness of the proposed strategy has been demonstrated in the New England test system. It can be concluded that the proposed DFIG model reduction for dynamic studies is undoubtedly beneficial to system planner and operator, in the way of improving computational efficiency when analyzing large-scale power systems with the increasing penetration of wind energy.
Original languageEnglish
Pages (from-to)971-976
Number of pages6
JournalEnergy Procedia
Publication statusPublished - 1 Jan 2017
Event9th International Conference on Applied Energy, ICAE 2017 - Cardiff, United Kingdom
Duration: 21 Aug 201724 Aug 2017


  • Computational efficiency
  • Damping torque contribution
  • Dynamic model component
  • Reduced model
  • Wind power generation

ASJC Scopus subject areas

  • General Energy


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