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A survey on recent advances on dynamic state estimation for power systems.

Authors :
Qu, Bogang
Peng, Daogang
Shen, Yuxuan
Zou, Lei
Shen, Bo
Source :
International Journal of Systems Science. Dec2024, Vol. 55 Issue 16, p3305-3321. 17p.
Publication Year :
2024

Abstract

Recently, owing to the high penetration of renewable power generations, random access to dynamical loads and wide application of power-electronic devices, the modern power systems exhibit new features such as high dynamics, low inertia and weak voltage and frequency support. As a powerful tool in revealing the dynamical evolution of the modern power systems, the dynamic state estimation (DSE) scheme gains a surge of research enthusiasms. Note that in actual power systems, various styles of power generations and mixed measurements generated by the supervisory control and data acquisition (SCADA) system and the phasor measurement unit (PMU) pose higher demands on the DSE. In addition, the measurements with anomalies such as gross errors, outliers and incomplete information are often encountered due to the unreliable measurement facilities, constrained communication resources and cyber-threats. Such anomalies, if not tactfully handled, would largely impair the DSE performance. In this paper, a systematic and timely review with respect to DSE for power systems is provided. First, several typical models for power systems include quasi-steady model, synchronous-generator-based multi-machine model and renewable power generation model are introduced. Then the measurement facilities of power systems and their features as well as the measurements with anomalies are reviewed, respectively. Subsequently, the DSE schemes are recalled and discussed from the perspectives of framework, methodology, anomaly-resistant ability and application, respectively. Finally, some possible future research topics are outlined for the DSE of power systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00207721
Volume :
55
Issue :
16
Database :
Academic Search Index
Journal :
International Journal of Systems Science
Publication Type :
Academic Journal
Accession number :
181109646
Full Text :
https://doi.org/10.1080/00207721.2024.2427846