DocumentCode :
2503601
Title :
An artificial neural-net based method for predicting distribution transformer’s total harmonic distortions
Author :
Türker, Turhan ; Yörükeren, Nuran ; Sengül, Mehlika ; Alboyaci, Bora
Author_Institution :
Energy Sector Power Distrib. Div., Siemens Turkey, Istanbul
fYear :
2008
fDate :
1-3 Dec. 2008
Firstpage :
1194
Lastpage :
1197
Abstract :
This paper presents a new method for predicting distribution transformerpsilas total current and total voltage harmonic distortion with artificial neural network. The method is based on the backpropagation learning technique. This paper shows the proposed method is promising in total harmonic distortion prediction. For better system planning it is necessary to analyze and predict the behavior of harmonics. By predicted values system planners take an appropriate strategy to decrease significant harmonics in distribution systems.
Keywords :
backpropagation; harmonic distortion; neural nets; power engineering computing; power system harmonics; power transformers; artificial neural-net based method; backpropagation learning technique; distribution transformer prediction; system planning; total voltage harmonic distortion; Artificial neural networks; Backpropagation; Distortion measurement; Harmonic distortion; Power system faults; Power system harmonics; Power system measurements; Power system planning; Switched-mode power supply; Total harmonic distortion; Artificial neural network; Distribution transformer; System planning; Total harmonic distortion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International
Conference_Location :
Johor Bahru
Print_ISBN :
978-1-4244-2404-7
Electronic_ISBN :
978-1-4244-2405-4
Type :
conf
DOI :
10.1109/PECON.2008.4762657
Filename :
4762657
Link To Document :
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