DocumentCode :
3130543
Title :
Neural network based shunt active filter for harmonic and reactive power compensation under non-ideal mains voltage
Author :
Gupta, Nitin ; Singh, S.P. ; Dubey, S.P.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., Roorkee, India
fYear :
2010
fDate :
15-17 June 2010
Firstpage :
370
Lastpage :
375
Abstract :
This paper presents a new method for harmonic and reactive power compensation with power factor improvement using an artificial neural network (ANN) and a new control algorithm for active power filter (APF) for power quality conditioning for variable load under non-ideal mains voltage conditions. The neural network controller comprises two similar adaptive linear neurons (ADALINE), and it has been designed to extract fundamental frequency components from non-sinusoidal and unbalanced currents instead of conventional low pass filter. Reactive power compensation is done without sensing load currents, which gives simplicity in control with less number of current sensors. The performance of the APF with the proposed neural network compensation algorithm is found to be considerably effective and adequate to compensate harmonics and reactive power. The results show excellent behaviors and performances.
Keywords :
neurocontrollers; power harmonic filters; power supply quality; reactive power; active power filter; adaptive linear neurons; harmonic compensation; neural network; non-ideal mains voltage; reactive power compensation; shunt active filter; Active filters; Artificial neural networks; Neural networks; Power harmonic filters; Power quality; Power system harmonics; Programmable control; Reactive power; Reactive power control; Voltage control; Active filter; Instantaneous reactive power theory; harmonic compensation; low pass filter; neural network; point of common coupling; power qaulity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on
Conference_Location :
Taichung
Print_ISBN :
978-1-4244-5045-9
Electronic_ISBN :
978-1-4244-5046-6
Type :
conf
DOI :
10.1109/ICIEA.2010.5516896
Filename :
5516896
Link To Document :
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