ST and LSSVR-based the fault location algorithm for the series compensated power transmission lines


Uyar M.

ENERGY EDUCATION SCIENCE AND TECHNOLOGY PART A-ENERGY SCIENCE AND RESEARCH, vol.30, no.1, pp.75-88, 2012 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 1
  • Publication Date: 2012
  • Journal Name: ENERGY EDUCATION SCIENCE AND TECHNOLOGY PART A-ENERGY SCIENCE AND RESEARCH
  • Journal Indexes: Science Citation Index Expanded
  • Page Numbers: pp.75-88
  • Keywords: Fault location, Series compensated lines, S-transform, Least square support vector regression, SUPPORT VECTOR MACHINES, NEURAL-NETWORK, TRANSFORM, WAVELET, CLASSIFICATION, PROTECTION, SYSTEM, ENERGY, DECOMPOSITION, DISTURBANCES

Abstract

This paper presents an approach based on S-Transform (ST) and Least Square Support Vector Regression (LSSVR) techniques for predicting the fault location in a compensated power transmission line with the fixed series capacitor. The entropy features of ST matrix are extracted for reducing the dimension of three-phase current signal measured from the sending end of the transmission line. Then, the extracted features are applied as input to LSSVR for determining fault location on series compensated line (SCL). The presented method has been tested using model of a 400kV, 320km transmission line, which is compensated, by a three-phase capacitor bank in the middle. The results show that the proposed method is capable of determining fault location on SCL under wide variations in operating conditions (i.e. fault resistance, fault inception angle, fault distance, percentage compensation level, source impedance and load angle).