An intelligent approach for predicting power quality in distribution power system

Author

El Haroon, Mohamed M. ; El-Magueed, Ahamed Abd ; El-fetoh, T.A.

Volume

2

fYear

2006

fDate

19-21 Dec. 2006

Firstpage

537

Lastpage

540

Abstract

This Paper presents a method for predicting power system voltage harmonics using Time-Delay Neural Network (TDNN). The TDNN method is based on the back propagation learning technique for feedforward neural networks. This approach has certain advantages over other conventional schemes, including the potential to track the harmonics in the time-varying power system environment. In order to demonstrate the effectiveness of TDNN, the performance is compared with the conventional methods.

Keywords

backpropagation; delays; distribution networks; feedforward neural nets; power supply quality; power system harmonics; time-varying systems; back propagation learning technique; distribution power system; feedforward neural networks; power quality prediction; power system voltage harmonics; time delay neural network; time varying power system; Artificial neural networks; Linear regression; Neural networks; Power quality; Power semiconductor switches; Power system analysis computing; Power system harmonics; Power system management; Power systems; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Systems Conference, 2006. MEPCON 2006. Eleventh International Middle East

Conference_Location

El-Minia

Print_ISBN

978-1-4244-5111-1

Type

conf

Filename

5372424