Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/22954
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Khurram, Ambreen | - |
dc.contributor.author | Gusnanto, Arief | - |
dc.contributor.author | Aristidou, Petros | - |
dc.date.accessioned | 2021-09-01T12:01:36Z | - |
dc.date.available | 2021-09-01T12:01:36Z | - |
dc.date.issued | 2021-07 | - |
dc.identifier.citation | IEEE Madrid PowerTech, 2021, 28 June - 2 July, Madrid, Spain | en_US |
dc.identifier.isbn | 9781665435970 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/22954 | - |
dc.description.abstract | In electric power systems, detecting inter-area oscillations is crucial to the system operators for maintaining the security of the grid - especially in the case of unstable oscillatory behaviour. However, extracting information from unstable, noisy, signals is complicated with conventional signal processing tools suffering from insufficient adaptability. In this paper, we propose a method based on Empirical Wavelet Transform (EWT) to estimate in real-time the dominant inter-area modes in electricity grids. EWT extracts the inherent modulation information by decomposing the signal into its mono components under an orthogonal basis. The instantaneous amplitude and instantaneous frequency is estimated by applying Hilbert transform from the narrow band components of the decomposed EWT signal. The performance of the proposed method is demonstrated using the Nordic test system. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.rights | © IEEE | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Oscillatory instability | en_US |
dc.subject | Inter-area oscillations | en_US |
dc.subject | Empirical Wavelet Transform | en_US |
dc.subject | Hilbert Transform | en_US |
dc.subject | PMU | en_US |
dc.title | Detection of Oscillatory Modes in Power Systems using Empirical Wavelet Transform | en_US |
dc.type | Conference Papers | en_US |
dc.collaboration | University of Leeds | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.subject.category | Electrical Engineering - Electronic Engineering - Information Engineering | en_US |
dc.country | United Kingdom | en_US |
dc.country | Cyprus | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.relation.conference | PowerTech | en_US |
dc.identifier.doi | 10.1109/PowerTech46648.2021.9494761 | en_US |
dc.identifier.scopus | 2-s2.0-85112364880 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/85112364880 | - |
cut.common.academicyear | 2020-2021 | en_US |
item.openairecristype | http://purl.org/coar/resource_type/c_c94f | - |
item.openairetype | conferenceObject | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | none | - |
item.languageiso639-1 | en | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-4429-0225 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
CORE Recommender
SCOPUSTM
Citations
5
3
checked on Mar 14, 2024
Page view(s) 5
259
Last Week
1
1
Last month
5
5
checked on Nov 21, 2024
Google ScholarTM
Check
Altmetric
This item is licensed under a Creative Commons License