Determination the Switching State of Compensatory Equipment Based on Monitor Data Analysis
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Paper number
713
Working Group Number
Conference name
CIRED 2019
Conference date
3-6 June 2019
Conference location
Madrid, Spain
Peer-reviewed
Yes
Short title
Convener
Authors
Wang, Ying, College of Electrical Engineering and Information Technology- Sichuan University, China
Deng, Ling-Feng, Sichuan University, China
Xiao, Xianyong, College of Electrical Engineering and Information Technology Sichuan University, China
Hu, Chong, Anhui Electric Power Research Institute, China
Wang, Xin, CEIEC Shenzhen Electric Technology Inc, China
Deng, Ling-Feng, Sichuan University, China
Xiao, Xianyong, College of Electrical Engineering and Information Technology Sichuan University, China
Hu, Chong, Anhui Electric Power Research Institute, China
Wang, Xin, CEIEC Shenzhen Electric Technology Inc, China
Abstract
The power supply companies have codes to limit the power quality disturbance from the disturbance source, for example, wind park or arc furnace. To equip the power quality compensatory equipment is the straight way to limit it. However, it is difficult for power supply company to manage the power quality compensatory equipment on the user side. This paper presents an algorithm, based on power quality monitoring data on the grid side, to determine the operation status of the compensatory equipment on the user side for power grid companies. In this paper, the probabilistic neural network is used to classify the operation status of the compensatory equipment, by taking the voltage deviation, three-phase voltage unbalance, total harmonic distortion rate and long-term voltage flicker as the input data of the network, so as to realize the determination of the operation status of the compensatory equipment. The correctness and reliability of the proposed method is verified by the recorded power quality data from a substation in Anhui Power Grid in China.
Table of content
Keywords
Publisher
AIM
Date
2019-06-03
Published in
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/126
http://dx.doi.org/10.34890/254
http://dx.doi.org/10.34890/254
ISSN
2032-9644
ISBN
978-2-9602415-0-1