Back to Search Start Over

Improved Subsynchronous Oscillation Parameter Identification Based on Eigensystem Realization Algorithm.

Authors :
Chen, Gang
Zeng, Xueyang
Liu, Yilin
Zhang, Fang
Shi, Huabo
Source :
Applied Sciences (2076-3417); Sep2024, Vol. 14 Issue 17, p7841, 13p
Publication Year :
2024

Abstract

Subsynchronous oscillation (SSO) is the resonance between a new energy generator set and a weak power grid, and the resonance frequency is usually the sub-/super-synchronous frequency. The eigensystem realization algorithm (ERA) is a classic algorithm for extracting modal parameters based on matrix decomposition. By leveraging the ERA's simplicity and low computational cost, an enhanced methodology for identifying the key parameters of SSO is introduced. The enhanced algorithm realizes SSO angular frequency extraction by constructing an angular frequency fitting equation, enabling efficient identification of SSO parameters using only a 200 ms synchrophasor sequence. In the process of identification, the fitting-based ERA effectively addresses the limitation of the existing ERA. The accuracy of SSO parameter identification is improved, thereby realizing that SSO parameter identification can be carried out using a 200 ms data window. The fitting-based ERA is verified using synthetic and actual data from synchrophasor measurement terminals. The research results show that the proposed algorithm can accurately extract fundamental and subsynchronous or supersynchronous oscillation parameters, effectively realizing dynamic real-time monitoring of subsynchronous oscillations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
17
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
179650364
Full Text :
https://doi.org/10.3390/app14177841