Identification of voltage sag source based on Improved GRA. Issue 1 (1st April 2022)

• Record Type: Journal Article
• Authors: Li, Ma; Dong, Pengyuan
• Is Part Of: Journal of physics. Volume 2258:Issue 1(2022)
• Publication Date: 2022-04-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2258/1/012075
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Accurate identification of fault source causing voltage sag is of great significance to the governance and further research of voltage sag. In this paper, a voltage sag source identification method based on improved grey correlation analysis (GRA) is proposed. In view of the deficiency that the traditional GRA only considers the similarity, the proposed method considers the geometric area and slope of sequence into the calculation of correlation coefficient, so that the improved GRA has attributes of both sequence similarity and data closeness. Eight features are extracted from six common types of sag waveforms to form standard and test sequence; The improved GRA is used to calculate the correlation degree between the test and standard sequences, then the identification of sag source can be realized. Simulation model is built in MATLAB. Results show that this proposed method can effectively identify the voltage sag source. Compared with the traditional GRA, this method has higher identification accuracy and stronger identification ability.