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http://dx.doi.org/10.5370/JEET.2013.8.3.421

Copula-ARMA Model for Multivariate Wind Speed and Its Applications in Reliability Assessment of Generating Systems  

Li, Yudun (School of Electrical Engineering, Chongqing University)
Xie, Kaigui (State Key Laboratory of Power Transmission Equipment & System Security, School of Electrical Engineering, Chongqing University)
Hu, Bo (School of Electrical Engineering, Chongqing University)
Publication Information
Journal of Electrical Engineering and Technology / v.8, no.3, 2013 , pp. 421-427 More about this Journal
Abstract
The dependence between wind speeds in multiple wind sites has a considerable impact on the reliability of power systems containing wind energy. This paper presents a new method to generate dependent wind speed time series (WSTS) based on copulas theory. The basic feature of the method lies in separating multivariate WSTS into dependence structure and univariate time series. The dependence structure is modeled through the use of copulas, which, unlike the cross-correlation matrix, give a complete description of the joint distribution. An autoregressive moving average (ARMA) model is applied to represent univariate time series of wind speed. The proposed model is illustrated using wind data from two sites in Canada. The IEEE Reliability Test System (IEEE-RTS) is used to examine the proposed model and the impact of wind speed dependence between different wind regimes on the generation system reliability. The results confirm that the wind speed dependence has a negative effect on the generation system reliability.
Keywords
Multivariate wind speed model; Copulas; Reliability evaluation; Dependence;
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Times Cited By KSCI : 1  (Citation Analysis)
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