Artificial intelligent based fault location technique for EHV series-compensated lines

Author

Joorabian, M.

Author_Institution

Sch. of Electr. Eng., Shahid Chamran Univ., Ahwaz, Iran

Volume

2

fYear

1998

fDate

3-5 Mar 1998

Firstpage

479

Abstract

This paper proposes the use of fuzzy neural networks (FNN) to solve the fault location problem for series-compensated lines. The technique is based on a hybrid intelligent model that integrates artificial neural networks (ANN) and a fuzzy logic system (FLS). The frequency components of the instantaneous three phase voltages and currents derived at the fault locator-end of the line are used to train an ANN to classify the fault type, and a separate FNN is used to accurately locate a fault on EHV series-compensated lines

Keywords

fault location; fuzzy logic; fuzzy neural nets; fuzzy systems; learning (artificial intelligence); power system analysis computing; power transmission lines; ANN training; EHV series-compensated lines; artificial intelligence; artificial neural networks; fault location technique; fault locator; fault type classification; frequency components; fuzzy logic system; fuzzy neural networks; hybrid intelligent model; instantaneous three phase currents; instantaneous three phase voltages; Artificial intelligence; Artificial neural networks; Capacitors; Circuit faults; Fault location; Fuzzy logic; Fuzzy neural networks; Power system relaying; Power transmission lines; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Energy Management and Power Delivery, 1998. Proceedings of EMPD '98. 1998 International Conference on

Print_ISBN

0-7803-4495-2

Type

conf

DOI

10.1109/EMPD.1998.702709

Filename

702709