Localización de faltas en enlaces de tipo VSC-HVDC usando redes neuronales

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 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.