Identification of coherent generators based on clustering methods. (July 2020)

• Record Type: Journal Article
• Authors: Wu, Peng; Xing, Lin; Zhang, Ji; Xi, Peng
• Is Part Of: Journal of physics. Volume 1601:Number 3(2020)
• Publication Date: 2020-07
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1601/3/032043
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The identification of coherent generators is very important for the stability analysis and control of power system. So far, there are three main identification methods of coherent generators which have cetain disadvantages. In this paper, two new algorithms based on clustering are proposed for the identification of coherent generators. Algorithm 1 is the optimal classification of generators based on given swing curves. By introducing the validity index into the algorithm, the optimal classification of the given generator swing curves can be obtained. Algorithm 2 is identification of coherent generators under specific faults. This algorithm firstly calculates the critical clear time of the system. Since the swing curves obtained at the critical clear time(critical curves) contain the complete information reflecting the swing and oscillation between generators, they can be used as reliable samples for clustering. Examples show that the two algorithms are effective.