DocumentCode :
24422
Title :
Contactless Measurement of Substation Busbars Voltages and Waveforms Reconstruction Using Electric Field Sensors and Artificial Neural Network
Author :
Borkowski, Dariusz ; Wetula, Andrzej ; Bien, Andrzej
Author_Institution :
AGH Univ. of Sci. & Technol., Krakow, Poland
Volume :
6
Issue :
3
fYear :
2015
fDate :
May-15
Firstpage :
1560
Lastpage :
1569
Abstract :
This paper presents a method for contactless measurement of instantaneous voltage and waveform reconstruction for use in a medium voltage (MV) indoor substation. Voltage waveforms are reconstructed by artificial neural network (ANN) using the signals originating from electric field sensors located under MV bus. The method is validated by the experiment in a typical indoor MV substation. Depending on the selection of ANN architecture and data used for training the root mean squared error of waveforms, reconstruction as low as 0.3% to 2.1% can be achieved in a steady state. The practical advice on the application of the proposed measurement method in a production environment is also given.
Keywords :
busbars; electric fields; electric sensing devices; mean square error methods; neural nets; power engineering computing; substations; ANN architecture; MV bus; artificial neural network; contactless measurement; electric field sensors; medium voltage indoor substation; production environment; root mean squared error; substation busbars voltages; voltage waveforms; waveforms reconstruction; Artificial neural networks; Capacitive sensors; Neurons; Substations; Training; Voltage measurement; Artificial neural networks (ANN); contactless voltage measurement; electric field (EF) sensors; waveform reconstruction;
fLanguage :
English
Journal_Title :
Smart Grid, IEEE Transactions on
Publisher :
ieee
ISSN :
1949-3053
Type :
jour
DOI :
10.1109/TSG.2014.2363294
Filename :
6945326
Link To Document :
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