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, cilt.30, sa.1, ss.75-88, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 30 Sayı: 1
  • Basım Tarihi: 2012
  • Dergi Adı: ENERGY EDUCATION SCIENCE AND TECHNOLOGY PART A-ENERGY SCIENCE AND RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.75-88
  • Anahtar Kelimeler: 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
  • Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

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).