C-Vine Pair Copula Based Wind Power Correlation Modelling in Probabilistic Small Signal Stability Analysis

被引:0
|
作者
Jin Xu [1 ,2 ]
Wei Wu [2 ]
Keyou Wang [1 ,2 ]
Guojie Li [1 ,2 ]
机构
[1] IEEE
[2] the Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao Tong University
基金
中国国家自然科学基金;
关键词
Monte Carlo simulation; pair copula; small signal stability; wind power correlation;
D O I
暂无
中图分类号
TM614 [风能发电]; TM712 [电力系统稳定];
学科分类号
0807 ; 080802 ;
摘要
The increasing integration of wind power generation brings more uncertainty into the power system. Since the correlation may have a notable influence on the power system,the output powers of wind farms are generally considered as correlated random variables in uncertainty analysis. In this paper, the C-vine pair copula theory is introduced to describe the complicated dependence of multidimensional wind power injection, and samples obeying this dependence structure are generated. Monte Carlo simulation is performed to analyze the small signal stability of a test system. The probabilistic stability under different correlation models and different operating conditions scenarios is investigated. The results indicate that the probabilistic small signal stability analysis adopting pair copula model is more accurate and stable than other dependence models under different conditions.
引用
收藏
页码:1154 / 1160
页数:7
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