Wind Power System Risk Assessment Based on Fuzzy Clustering and Copula Function Modeling - Energy and Power Engineering

EPE > Vol.9 No.4, April 2017

Energy and Power Engineering

Volume 9, Issue 4 (April 2017)

ISSN Print: 1949-243X ISSN Online: 1947-3818

Google-based Impact Factor: 0.66 Citations

Wind Power System Risk Assessment Based on Fuzzy Clustering and Copula Function Modeling ()

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Download as PDF (Size: 1450KB) PP. 352-364

DOI: 10.4236/epe.2017.94B041 2,549 Downloads 3,222 Views Citations

Author(s)

Mingshun Liu¹, Lijin Zhao¹, Liang Huang¹, Wenhao Han², Changhong Deng², Zhijun Long²

Affiliation(s)

¹Guizhou Power Grid Co., Ltd., Guiyang, China.
²School of Electrical Engineering, Wuhan University, Wuhan, China.

ABSTRACT

According to the characteristics of the correlation of multiple wind farm output, this paper put forwards a modeling method based on fuzzy c-means clustering and the copula function, and correlation wind farms are inserted into IEEE-RTS79 reliability system for risk assessment. By the probabilistic load flow calculated by Monte Carlo simulation method, the probability of the accident is derived, and bus voltage and branch power flow overload risk index are defined in this paper. The results show that this method can realize the modeling of the correlation of wind power output, and the risk index can identify the weakness of the system, which can provide reference for the operation and maintenance personnel.

KEYWORDS

Correlation, Fuzzy Clustering, Copula Function, Risk Assessment

Share and Cite:

Liu, M. , Zhao, L. , Huang, L. , Han, W. , Deng, C. and Long, Z. (2017) Wind Power System Risk Assessment Based on Fuzzy Clustering and Copula Function Modeling. Energy and Power Engineering, 9, 352-364. doi: 10.4236/epe.2017.94B041.

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