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