Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/22954
Title: | Detection of Oscillatory Modes in Power Systems using Empirical Wavelet Transform | Authors: | Khurram, Ambreen Gusnanto, Arief Aristidou, Petros |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Oscillatory instability;Inter-area oscillations;Empirical Wavelet Transform;Hilbert Transform;PMU | Issue Date: | Jul-2021 | Source: | IEEE Madrid PowerTech, 2021, 28 June - 2 July, Madrid, Spain | Conference: | PowerTech | 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. | URI: | https://hdl.handle.net/20.500.14279/22954 | ISBN: | 9781665435970 | DOI: | 10.1109/PowerTech46648.2021.9494761 | Rights: | © IEEE Attribution-NonCommercial-NoDerivatives 4.0 International |
Type: | Conference Papers | Affiliation : | University of Leeds Cyprus University of Technology |
Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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