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Power Oscillation Source Location Based on the Combination of Energy Function and Normal Distribution in a Fully Data-Driven Approach

Authors :
Shujia Guo
Xu Liu
Chao Jiang
Jing Cong
Source :
Energies, Vol 17, Iss 20, p 5237 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

With the deepening of national efforts toward green energy transformation, the power system is evolving into one characterized by “double high”—a high proportion of new energy integration and a high level of power electronic systems. This results in a more complex system topology, necessitating improvements in various prevention and control measures. Traditional model-based methods for locating power oscillation disturbance sources in power systems are no longer sufficient to meet the operational demands of modern power systems. With the rapid development of wide-area measurement systems (WAMS), there is growing interest in disturbance source localization using system response data. System dynamics provide a wealth of easily extractable data that can accurately reflect the power system’s behavior under normal conditions. This paper proposes a numerical method for locating disturbance sources, combining energy functions with normal distribution identification, based on power oscillation mechanisms and system response data. The method identifies potential disturbance sources, including small random load fluctuations and large forced power oscillations. The innovation lies in the introduction of a 3 Sigma value criterion to pinpoint the disturbance source location, addressing the limitations of traditional energy function methods that require manual intervention. By quantifying the localization of power oscillation disturbance sources, this method significantly improves both efficiency and accuracy.

Details

Language :
English
ISSN :
19961073
Volume :
17
Issue :
20
Database :
Directory of Open Access Journals
Journal :
Energies
Publication Type :
Academic Journal
Accession number :
edsdoj.81f7b6a2ba34e7ca5244966aa933e69
Document Type :
article
Full Text :
https://doi.org/10.3390/en17205237