Low Frequency Oscillation Modal Parameter Identification Based on NExT-ERA and Fuzzy Clustering
- Resource Type
- Article
Text
- Authors
- Gao Jie; Wang Jia; Zhou Yang
- Source
- International Journal of Control and Automation, 01/30/2016, Vol. 9, Issue 1, p. 309-322
- Subject
- low frequency oscillation
modal analysis
ambient excited
Natural Excitation Technique
Eigensystem Realization Algorithm
fuzzy clustering.
- Language
- 영어(ENG)
- ISSN
- 2005-4297
Using ambient excited data under PMU measurements to identify the low frequency oscillation mode and oscillation modes parameter information corresponding, has good prospects in power system analysis and control. This article discusses the applicability by using the natural excitation technique (NExT) in conjunction with the eigensystem realization algorithm for low frequency oscillation modes identification, then introduced fuzzy C-means clustering algorithm to picked up the authenticity of the identified modal results automatically and improving the recognition accuracy. On the IEEE-11 and IEEE-68 bus test system numerical example shows that the proposed method has higher modal recognition ability and efficiency, and can meet the needs of online applications.