New Combined Method for Fault Detection, Classification, and Location in Series-compensated Transmission Line

Abstract In this article, a new full-scheme distance protection for a series-compensated transmission line is proposed. The new combination of hyperbolic S-transform and learning machines is applied for fault detection, classification, and location, which are the three main aspects of distance relays. The hyperbolic S-transform is used for extracting useful features from the current and voltage signals sample of the power system from one terminal. The extracted features are employed for distance protection using support vector classification and support vector regression methods. The proposed method is evaluated by the different series capacitor location in the transmission line, where a metal oxide varistor protects the series capacitor against over-voltages. Extensive simulation experiments show that the proposed protection scheme provides accurate tripping logic with good accuracy of fault location. Also, the non-tripping decision for external faults that occurred on adjacent uncompensated transmission line is embedded in the proposed scheme. The various operating conditions of the series-compensated transmission line are simulated in the PSCAD/EMTDC (Winnipeg, Manitoba, Canada) environment. The obtained results of support vector classification and support vector regression confirm that the new extracted features from the time-frequency hyperbolic S-transform-matrix are very effective and reliable.