A Review of Methods for Locating a Disturbance in Electrical Networks Based on Synchronized Phasor Measurements and Machine Learning Algorithms
Abstract
The introduction of renewable energy sources, power electronics-based control devices, and intelligent analysis and control systems into electrical networks has entailed a change in the dynamics of transients in electric power systems. The increase in the speed of transients caused by a decrease in the total inertia of power systems places new demands on the response speed of emergency automation and relay protection devices. One of the promising approaches through which a significantly shorter algorithmic delay of power system control and protection devices can be obtained is the use of machine learning algorithms to synthesize the control law and locate the disturbance. The article presents an analysis of works addressing adaptive techniques for locating disturbances in distribution and backbone electrical networks based on the use of machine learning algorithms and synchronized phasor measurements. Various studies of machine learning algorithms, accuracy, and computational delay are compared. Based on the conducted meta-analysis, promising areas of research on the disturbance location problem have been identified.
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Исследование выполнено за счет гранта Российского научного фонда № 23-79-01024, https://rscf.ru/project/23-79-01024/
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The research was financially supported by the Russian Science Foundation, grant No. 23-79-01024, https://rscf.ru/project/23-79-01024/