| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6860370 | International Journal of Electrical Power & Energy Systems | 2014 | 7 Pages |
Abstract
This paper studies probabilistic small-signal stability of power systems with wind farm integration, considering the stochastic uncertainty of system operating conditions. The distribution function of the real-part of system eigenvalue is computed by the method of probabilistic eigenvalue analysis. For improving probabilistic small-signal stability, PSS is adopted. A method for optimizing PSS based on participation factor and center frequency method is proposed. In order to evaluate the above proposed methods, the procedure is applied to a test system. The simulation results show that the stochastic variation of wind generation can induce a higher probability of system instability when compared with one that has no wind generation. With eigenvalues distributing in a wider range, it becomes difficult for PSS tuning. By applying the proposed optimized PSSs approach, probabilistic stability of system can be significantly improved.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
X.Y. Bian, X.X. Huang, K.C. Wong, K.L. Lo, Yang Fu, S.H. Xuan,
