A robust UPFC damping control scheme using PI and ANN based adaptive controllers
This paper proposes an ANN based adaptive damping control scheme for the unified power flow controller (UPFC) to clamp the low frequency electrochemical power oscillations. In this paper a novel damping control strategy based on the time-domain analysis of system transient energy function (TEF) is proposed and implemented by using well tuned conventional PI controllers to obtain the preliminary training data for the design of the proposed controllers. The multi-layered feed forward neural network with error back-propagation training algorithm is employed in this study. Models of UPFC and ANN controllers suitable for incorporating with the transient simulation programs are derived and tested on a revised IEEE nine-bus test system. Comprehensive simulation results demonstrate the great potential of using UPFC in damping control and the excellent performance of the proposed control scheme.
control artificial neural networks