Applications of neural networks for the power quality factors measurement - i.e. voltage fluctuations

Szlosek, Marcin; Hanzelka, Zbigniew

doi:10.1109/epqu.2009.5318836

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2015

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“…Thanks to the small footprint required by the sensors as well as low price of needed equipment the method can become an common part of smart grids, which utilize a great number of measurement data in order to reliably control the power quality [26], [27] or identify the state of the grid [28].…”

Section: Discussionmentioning

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

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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.

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Section: Discussionmentioning

confidence: 99%