Detrending and characterizing system frequency oscillations using an adapted Zhou algorithm
dc.contributor.author | Bowen, Aidan | |
dc.contributor.author | Hayes, Barry P. | |
dc.date.accessioned | 2022-11-23T16:08:28Z | |
dc.date.available | 2022-11-23T16:08:28Z | |
dc.date.issued | 2022-10-18 | |
dc.date.updated | 2022-11-23T16:01:30Z | |
dc.description.abstract | Electro-mechanical oscillations between interconnected synchronous generators and oscillations in system frequency are an inherent part of the operation of large power systems. Very Low Frequency (VLF) oscillations are usually classified as oscillations in the 0.01-0.1 Hz range. With the move towards variable renewable energy sources and low-inertia power systems, VLF oscillations are being observed with increasing regularity in many small and island grids. If left undamped, these can present a threat to system stability. However, finding the root cause and source(s) of VLF oscillations is an extremely challenging task for network operators. Recent work has identified a need for improved tools for identifying and characterising VLF oscillations, in order to determine the combination of system conditions that can be used as predictors for VLF events. A suitable small signal model is also required in order to enable verification of the root cause of VLF events and study of mitigation measures. Accordingly, this paper presents a new approach for detrending and characterizing system frequency oscillations using an adapted Zhou algorithm. The paper also describes a method for applying this algorithm for the detection/location of oscillations, and for their detrending and characterization. Finally, an approach for relating detected oscillation events to power system operating conditions for diagnostic purposes is described. The effectiveness of the proposed approach is demonstrated using a single frequency power system model, and using system frequency oscillations recorded from the Irish power system. | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Accepted Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Bowen, A. and Hayes, B. P. (2022) 'Detrending and characterizing system frequency oscillations using an adapted Zhou algorithm', 2022 57th International Universities Power Engineering Conference (UPEC), Istanbul, Turkey, 30 August - 2 September. doi: 10.1109/UPEC55022.2022.9917945 | en |
dc.identifier.doi | 10.1109/UPEC55022.2022.9917945 | en |
dc.identifier.endpage | 6 | en |
dc.identifier.isbn | 978-1-6654-5505-3 | |
dc.identifier.isbn | 978-1-6654-5506-0 | |
dc.identifier.startpage | 1 | en |
dc.identifier.uri | https://hdl.handle.net/10468/13878 | |
dc.language.iso | en | en |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en |
dc.rights | © 2022, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en |
dc.subject | Common mode oscillations | en |
dc.subject | Damping | en |
dc.subject | Detrending | en |
dc.subject | Low inertia systems | en |
dc.subject | Nonstationary | en |
dc.subject | Power system monitoring | en |
dc.subject | Power system oscillations | en |
dc.subject | Power system stability | en |
dc.subject | Signal processing | en |
dc.subject | Very low frequency oscillations | en |
dc.subject | Wide area monitoring | en |
dc.title | Detrending and characterizing system frequency oscillations using an adapted Zhou algorithm | en |
dc.type | Conference item | en |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Detrending_Characterizing_Bowen_Hayes_UPEC2022_FINAL.pdf
- Size:
- 1.41 MB
- Format:
- Adobe Portable Document Format
- Description:
- Accepted Version
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 2.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: