Robust estimation method for power system dynamic synchronization with sensor gain degradation

Wang, Yi, Zhang, Jiawei, Wang, Yaoqiang, Li, Zhongwen, Wang, Kewen and Liang, Jun ORCID: https://orcid.org/0000-0001-7511-449X 2025. Robust estimation method for power system dynamic synchronization with sensor gain degradation. ISA Transactions: The Journal of Automation 156 , pp. 123-141. 10.1016/j.isatra.2024.10.031 Item availability restricted.

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Abstract

Efficient and accurate real-time estimation of power system synchronization is quite important for its safety control and operation. However, signal sensing failure, electromagnetic interference, system delay, etc., will cause the sensor gain degradation. To furnish a dependable method for dynamic estimation in power grid synchronization amid sensor gain degradation, this research presents a robust estimation system capable of monitoring and tracking the frequency, voltage phase angles, and magnitudes. Firstly, the random degradation of measurement data is characterized by a discrete distribution within the range [0,1]. Secondly, the state space model of sensor gain degradation is established. Subsequently, a novel modified fault-tolerant extended Kalman filter (MFTEKF) is developed under the recursive estimator framework. Finally, extensive experimental results definitively demonstrate that the proposed MFTEKF can accurately monitor the dynamic characteristics of the power grid.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	0019-0578
Funders:	National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Henan, Postdoctoral Research Project of Henan Province
Date of First Compliant Deposit:	2 December 2024
Date of Acceptance:	25 October 2024
Last Modified:	05 Feb 2025 12:15
URI:	https://orca.cardiff.ac.uk/id/eprint/174335

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