Disturbance extracted methods for auxiliary power quality monitor-based voltage sag localization in distribution network
Author:
Funder
National Key Research and Development Program of China
Publisher
Elsevier BV
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology
Reference39 articles.
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2. Design and analysis of a flywheel energy storage system fed by matrix converter as a dynamic voltage restorer;Aydogmus;ENERGY,2022
3. Detection of voltage sag sources based on the angle and norm changes in the instantaneous current vector written in clarke’s components;B. Polajzěr;Int J Electr Power Energy Syst,2015
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1. An automatic recognition method for power quality disturbances based on CAB-Net;Journal of Physics: Conference Series;2024-08-01
2. Most influential feature form for supervised learning in voltage sag source localization;Engineering Applications of Artificial Intelligence;2024-07
3. A novel cause identification method of voltage sag for auxiliary power quality monitoring;Electric Power Systems Research;2024-01
4. Fault detection and classification using deep learning method and neuro‐fuzzy algorithm in a smart distribution grid;The Journal of Engineering;2023-10-26
5. Research on Voltage Sag Detection Algorithm based on Regional Transmission System;Frontiers in Computing and Intelligent Systems;2023-06-19
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