Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77613
Title: Reducing model complexity of DFIG-based wind turbines to improve the efficiency of power system stability analysis
Authors: Bu, SQ 
Zhang, X
Xia, SW 
Xu, Y
Zhou, B
Lu, X 
Keywords: Computational efficiency
Damping torque contribution
Dynamic model component
Reduced model
Wind power generation
Issue Date: 2017
Publisher: Elsevier
Source: Energy procedia, 2017, v. 142, p. 971-976 How to cite?
Journal: Energy procedia 
Abstract: 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.
Description: 9th International Conference on Applied Energy, ICAE 2017, Cardiff, United Kingdom21-24 Aug 2017
URI: http://hdl.handle.net/10397/77613
EISSN: 1876-6102
DOI: 10.1016/j.egypro.2017.12.155
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

3
Citations as of Sep 18, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.