Determination the Switching State of Compensatory Equipment Based on Monitor Data Analysis
Paper number
713Conference name
CIRED 2019Conference date
3-6 June 2019Conference location
Madrid, SpainPeer-reviewed
YesMetadata
Show full item recordAuthors
Wang, Ying, College of Electrical Engineering and Information Technology- Sichuan University, ChinaDeng, 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.Publisher
AIMDate
2019-06-03Published in
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/126http://dx.doi.org/10.34890/254