NDLI: Classification of low voltage distribution networks by means of Voltage Distortion

Content Provider	IEEE Xplore Digital Library
Author	Schegner, P. Meyer, J. Lobos, T. Waclawek, Z. Muehlwitz, M. Hopfner, I.S.
Copyright Year	2005
Description	Author affiliation: Tech. Univ. Dresden, Dresden (Schegner, P.; Meyer, J.)
Abstract	Determination of power quality becomes more and more important in the future. Low voltage networks are usually large and very complex. Therefore the calculation of power quality parameters by modeling as equivalent network is hardly possible in practice. That's why new methods for efficient and exact estimation of power quality parameters in low voltage networks are necessary. The presented method is based on the fact that networks of similar structure have a similar behavior in power quality. The Points of Common Coupling (PCC) are divided into different classes, where each class consists of PCC's with similar characteristics. This way the method allows the estimation of power quality levels based on the class a PCC is assigned to. The paper demonstrates the method for the 5th voltage harmonic as an example power quality parameter. The above-mentioned classification of substations is based on probabilistic neural networks.
Starting Page	1
Ending Page	6
File Size	1162741
Page Count	6
File Format	PDF
ISBN	9785932080344
DOI	10.1109/PTC.2005.4524821
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-27
Publisher Place	Russia
Access Restriction	Subscribed
Rights Holder	Energy Systems Institute
Subject Keyword	Low voltage Power quality Neural networks Power system harmonics Substations Power measurement Time measurement Harmonic distortion Electronic equipment Costs neural network applications Power distribution power quality harmonic distortion power system identification
Content Type	Text
Resource Type	Article

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