Neural-network based vector control of VSCHVDC transmission systems

Abstract

This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent City Research OnlineAbstract-The application of high-voltage dc (HVDC) using voltage-source converters (VSC) has surged recently in electric power transmission and distribution systems. An optimal vector control of a VSC-HVDC system which uses an artificial neural network to implement an approximate dynamic programming algorithm and is trained with Levenberg-Marquardt is introduced in this paper. The proposed neural network vector control algorithm is analyzed in comparison with standard vector control methods for various HVDC control requirements, including dc voltage, active and reactive power control, and ac system voltage support. Assessment of the resulting closed-loop control shows that the neural network vector control approach has superior performance and works efficiently within and beyond the constraints of the HVDC system, for instance, converter rated power and saturation of PWM modulation.

Multi-port Converter for Medium and High Voltage Applications

“…MTDC grids represent the initial step for realisation of future super grids to facilitate bulky powers transfer over long distances, with tight control over the directions and magnitudes of the power transfer in each DC line [1][2][3][4][5][6][7]. Such MTDC systems are anticipated to consist of more than one DC voltage levels [8][9][10][11][12][13].…”