Dr Yunfei Chen yunfei.chen@durham.ac.uk
Professor
Dr Yunfei Chen yunfei.chen@durham.ac.uk
Professor
Ziyu Fan ziyu.fan@durham.ac.uk
Post Doctoral Research Associate
David Gregory
Xiaoyao Zhou
Ronak Rabbani
With the increasingly high penetration of renewable energy sources and the more integration of flexible loads, the power system is currently experiencing significant changes. While these changes aim to meet the growing needs of modern society, they also lead to the occurrence of more and more power oscillation events. These oscillations could be harmful to the operation of the power system, even causing power outages in poorly damped power systems. Hence, it is important to locate the source of these oscillations in the complicated power system, as control strategies or actions can be taken to mitigate them. To locate the source of oscillations accurately, many efficient techniques for oscillation source localization have been developed in the past decade using different physical properties of the power system and different methods. This survey focuses on these techniques to localize the source of oscillation in power systems. They can be categorized according to the physical metrics used, such as energy, mode shape, traveling wave, and damping torque. They can also be classified according to the specific methods used, such as data-driven, machine/deep learning, and transforms. The principles of these techniques, as well as their advantages and disadvantages, are discussed. Based on this survey, future research challenges on oscillation localization are outlined. The survey aims to provide a comprehensive review of the most existing techniques for oscillation source localization in the literature so that researchers and engineers can identify the most appropriate technique for their respective domains and applications.
Chen, Y., Fan, Z., Gregory, D., Zhou, X., & Rabbani, R. (2025). A Survey of Oscillation Localization Techniques in Power Systems. IEEE Access, 13, 28836-28860. https://doi.org/10.1109/ACCESS.2025.3540318
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 3, 2025 |
Online Publication Date | Feb 10, 2025 |
Publication Date | Feb 14, 2025 |
Deposit Date | Apr 7, 2025 |
Publicly Available Date | Apr 7, 2025 |
Journal | IEEE Access |
Electronic ISSN | 2169-3536 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 13 |
Pages | 28836-28860 |
DOI | https://doi.org/10.1109/ACCESS.2025.3540318 |
Public URL | https://durham-repository.worktribe.com/output/3782407 |
Published Journal Article
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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