DocumentCode :
1610362
Title :
A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Author :
Sabo, Aliyu ; Abdul Wahab, Noor Izzri ; Mohd Radzi, Mohd Amran ; Mailah, Nashiren Farzilah
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. Putra Malaysia, Serdang, Malaysia
fYear :
2013
Firstpage :
348
Lastpage :
352
Abstract :
Proliferation of nonlinear loads /devices in power systems generates a major concern to power system engineers, courtesy of its severe contamination effects (polluting the distribution networks with current harmonics). This paper depicts artificial intelligence (AI) application on resolving the power quality problem mentioned above by using the parallel active power filter (APF) strategy in two-wire distribution systems. The proposed AI adopted is an artificial neural network (ANN) responsible to detect current harmonics for the active power filtering process. The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. The proposed scheme is achieved via simulation studies (under MATLAB SIMULINK environment) and results obtained are discussed to verify its performance.
Keywords :
active filters; artificial intelligence; distribution networks; harmonic distortion; neural nets; power engineering computing; power harmonic filters; AI; ANN; APF strategy; SAPF; artificial intelligence; artificial neural network; current harmonics detection; current harmonics reduction; mathematical algorithm; nonlinear devices; nonlinear loads; parallel active power filter; power quality; shunt active power filter control; two-wire distribution system; Active filters; Artificial neural networks; Conferences; Harmonic analysis; Power harmonic filters; Switches; Harmonic; Neural Network; Power; Shunt Active Power Filter; Total Harmonic Distortion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Clean Energy and Technology (CEAT), 2013 IEEE Conference on
Conference_Location :
Lankgkawi
Print_ISBN :
978-1-4799-3237-5
Type :
conf
DOI :
10.1109/CEAT.2013.6775654
Filename :
6775654
Link To Document :
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