Probabilistic Small Signal Stability Evaluation of Power Systems with High Penetration of Wind Farms

被引:4
|
作者
Madadi, S. [1 ]
Mohammadi-Ivatloo, B. [1 ,2 ]
Tohidi, S. [1 ]
机构
[1] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran
[2] Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam
关键词
Probabilistic small signal stability; fuzzy clustering method; self organized map; k-means clustering approaches; wind farms; DESIGN;
D O I
10.1016/j.compeleceng.2020.106683
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Wind farms are increasingly installed in power systems. Such power generation units increase stochastic power system variables, affecting power systems stability. Therefore, the impact of stochastic generation on power systems stability should be carefully taken into account, an aim which can be realized by probabilistic evaluation. This paper presents hybrid methods for the evaluation of probabilistic small-signal stability (PSSS) in power systems. These methods are based on clustering approaches and Monte Carlo simulation (MCS) which is employed in a probabilistic problem to achieve acceptable results. There are two steps for evaluation of PSSS in the hybrid methods. Clustering methods divide stochastic sets into small sets; the member of small sets is employed to calculate eigenvalues similar to MCS. Consequently, this method is faster than MCS. Two case studies are employed based on the IEEE 9-bus and 39-bus test systems for the evaluation of the proposed method. It is shown that the proposed methods yield accurate results and are faster than MCS. (c) 2020 Elsevier Ltd. All rights reserved.
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页数:18
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