DocumentCode :
2526859
Title :
Implementation of the neural network for tracing of spot welders
Author :
Khodaparast, Jalal ; Dastfan, Ali
Author_Institution :
Dept. of Electr. & Robotic Eng., Shahrood Univ. of Technol., Shahrood, Iran
fYear :
2012
fDate :
17-20 June 2012
Firstpage :
630
Lastpage :
636
Abstract :
Detection of flicker sources is the first step to mitigate the effect of flicker in power system. In this literature, existence of several flicker sources is studied and proposes a technique for detecting all existing tones in voltage envelope. This technique is based on the d-q transformation. Half wave rectifier is improved by using d-q transformation, to calculate amplitudes of all flicker tones. These amplitudes are considered as index of flicker sources detection. And in this paper, in order to reduce the number of measurement devices a neural network is train by using acquired indexes to identify the place of flicker sources. For validation, the 6-bus network is simulated and algorithm for flicker sources detection is tested. The simulations results show that by using the proposed algorithm, all flicker sources in a power system can be detected correctly.
Keywords :
neural nets; power engineering computing; power supply quality; spot welding; 6-bus network; d-q transformation; flicker effect; flicker sources; flicker sources detection; half wave rectifier; neural network; power quality disturbances; power system; spot welders; Indexes; Power quality; Flicker Sources Detection; Flicker Tones; Improved Half Wave Rectifier; Inter-harmonic; Neural Network; Power Quality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Harmonics and Quality of Power (ICHQP), 2012 IEEE 15th International Conference on
Conference_Location :
Hong Kong
ISSN :
1540-6008
Print_ISBN :
978-1-4673-1944-7
Type :
conf
DOI :
10.1109/ICHQP.2012.6381267
Filename :
6381267
Link To Document :
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