Gholami, Mustafa, Gharehpetian, Gvrvg, Mohammadi, Mohammad (2013). Online Static Security Margin Improvement based on Wind Farms. , 12(4), 1-11.
Mustafa Gholami; Gvrvg Gharehpetian; Mohammad Mohammadi. "Online Static Security Margin Improvement based on Wind Farms". , 12, 4, 2013, 1-11.
Gholami, Mustafa, Gharehpetian, Gvrvg, Mohammadi, Mohammad (2013). 'Online Static Security Margin Improvement based on Wind Farms', , 12(4), pp. 1-11.
Gholami, Mustafa, Gharehpetian, Gvrvg, Mohammadi, Mohammad Online Static Security Margin Improvement based on Wind Farms. , 2013; 12(4): 1-11.

Online Static Security Margin Improvement based on Wind Farms

The Modares Journal of Electrical Engineering
Article 1, Volume 12, Issue 4, 2013, Pages 1-11    PDF (141.36 K)
Authors
Mustafa Gholami1; Gvrvg Gharehpetian* 1; Mohammad Mohammadi2
1Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran
2Dept. of Power and Control Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Fars
Abstract
Due to the high penetration of wind farms in the networks, they can have a significant role in the control of power systems. In this paper, wind farms (WFs) are used to improve the static security margins of the power system. Generation rescheduling is one of the remedies to improve the static security margins of the power system. In this paper, the generation rescheduling is presented based on wind farms. To assess the security of the power system, the net active and reactive (generation minus demand) powers of all buses are selected as features. The numbers of the features are reduced based on one of the famous methods of the feature extraction methods named Principle Component Analysis (PCA). The feature extraction method is used to save all features effects on the security of the power system. In this paper, to find the most optimum way to improve the static security margins, two optimization problems are introduced for the two strategies presented. The proposed method is implemented on the IEEE 39-bus network and the results show its effectiveness on the static security margin. It should be mentioned that the proposed method can deal with correlated random variables. Nataf transformation is used to build more accurate and more realistic database to train the classifier to assess the static security margins of the power system. The real data of Iran's grid are used to validate the Nataf transformation
Keywords
Static Security Assessment; Decision Tree; Preventive Control; Wind Farms
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