LAUSR

Abstract The aim of this paper is to develop a methodology based on pattern recognition of DC voltage signals for fault location in HVDC transmission systems. By using the shape similarity amongst voltage signals, an ANN is trained as a pattern recognizer to correlate post-fault DC voltage to fault distances on a DC line. The CIGRE HVDC benchmark system was used for developing and testing purposes. The HVDC system is modeled and simulated in PSCAD, while the ANN is trained and implemented in MATLAB™. The proposed methodology was developed and tested considering different operational conditions of the adopted HVDC system. After an exhaustive evaluation process considering different fault locations and fault resistances, the method presented here showed a very accurate and robust behavior.