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

Shujia Guo (), Xu Liu, Chao Jiang and Jing Cong
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Shujia Guo: School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China
Xu Liu: State Grid Pinghu Power Supply Company, Jiaxing 314299, China
Chao Jiang: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Jing Cong: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China

Energies, 2024, vol. 17, issue 20, 1-25

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.

Keywords: disturbance source location; system response data; energy function; normal distribution; 3 Sigma (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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