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Wind Farm Dynamic Equivalent Modeling Method for Power System Probabilistic Stability Assessment.

Authors :
Wang, Peng
Zhang, Zhenyuan
Huang, Qi
Lee, Wei-Jen
Source :
IEEE Transactions on Industry Applications. May-Jun2020, Vol. 56 Issue 3, p2273-2280. 8p.
Publication Year :
2020

Abstract

The uncertainty of power system is intensified by the integration of large-scale renewable energy resources such as wind farm (WF). Considering the impact of system uncertainties, the probabilistic stability analysis methods have been used in the stability assessments of power system with the WF integration. However, in traditional probabilistic analysis methods, WF is normally considered as PQ bus or aggregated as one single-machine equivalent model regardless of wake effect, which might reduce the accuracy of probabilistic stability studies. In this article, a dynamic equivalent modeling method of WF for probabilistic stability assessments is proposed. The wake effect is considered in the modeling process and a practical four-machine clustering method is used in wind turbines clustering. Besides, the fisher discriminant analysis (FDA) is adopt to combine the similar WTs clustering results reasonably. Then, the WF is aggregated to a multi-machine equivalent model by capacity weighted method. Also, the established WF probabilistic model can be directly used in time-domain simulation based on Monte Carlo simulation and FDA. Finally, the efficiency of the proposed method is verified in an actual WF in China. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00939994
Volume :
56
Issue :
3
Database :
Academic Search Index
Journal :
IEEE Transactions on Industry Applications
Publication Type :
Academic Journal
Accession number :
142930052
Full Text :
https://doi.org/10.1109/TIA.2020.2970377