Fault Location in a VSC-HVDC Link Using Neural Networks

Abstract

High-voltage direct current (HVDC) using voltage source converter (VSC) in transmission systems applications are currently a competitive alternative to the traditional AC transmission systems, especially for offshore wind power applications. The increases of rated power and distance to the shore have made VSC-HVDC transmission systems economically more efficient than the conventional solution based on an AC lines. Locating a fault in a submarine DC line must be fast and accurate because of the high cost of the submarine repairs as well as the operation cost (not-supplied energy). This paper proposed a fault location methodology based on artificial neural networks (ANN) for VSC-HVDC transmission system. The methodology only uses instantaneous values of electrical quantities (voltage and current) at one of the VSC terminal eliminating the problem of synchronisation. The proposed methodology has been tested and demonstrated using a typical VSC-HVDC test network, and simulation results show the appropriate performance of the methodology.