Title :
New Research on Harmonic Detection Based on Neural Network for Power System
Author :
Ying, Chen ; Qingsheng, Lin
Author_Institution :
Sch. of Inf. Eng., Nanchang Univ., Nanchang, China
Abstract :
Analysis and control for power quality by neural network is a new research field in electrical power system. Rapid and reliable extract the harmonic components determine the overall performance of Active Power Filter (APF). This paper presents a new three-layer feedforward neural network based on error back-propagation algorithm that the training sample without time delay, which can detecting harmonics for power system in real-time. With the simulation study using Matlab, the simulation results illustrate that the harmonic detection method based on neural network is feasible, which can quickly detecting the harmonics for non-linear load.
Keywords :
backpropagation; feedforward neural nets; harmonics suppression; power system control; Matlab simulation; active power filter; error backpropagation algorithm; feedforward neural network; harmonic detection method; power quality; power system; Active filters; Control system analysis; Control systems; Neural networks; Power harmonic filters; Power quality; Power system analysis computing; Power system harmonics; Power system reliability; Power system simulation; APF; BP algorithm; detection; feedforward neural network; harmonics;
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
DOI :
10.1109/IITA.2009.146
