Contactless voltage detector development to be used as individual protection equipment applicable to 13,8kV distribution power lines

Pinho, Antonio Carlos; Lourenco, Alessandro Pinto; Dallacosta, Ezequiel; Bressan, Marcos Artur

doi:10.1109/induscon.2010.5739928

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2015

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The method shown in [8] can be used for detection of the voltage in single phase cable e.g., in a coal mine. In [9], voltage detectors are proposed for use by utility staff during the maintenance of overhead lines for security purposes.…”

Section: Introductionmentioning

confidence: 99%

Contactless Measurement of Substation Busbars Voltages and Waveforms Reconstruction Using Electric Field Sensors and Artificial Neural Network

Borkowski

Wetula

Bień

2015

IEEE Trans. Smart Grid

View full text Add to dashboard Cite

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. Index Terms-Artificial neural networks (ANN), contactless voltage measurement, electric field (EF) sensors, waveform reconstruction.

show abstract

Section: Introductionmentioning

confidence: 99%