UPFC Supplementary Damping Control Synthesis: A Forward Neural Networks Approximated Energy Function Approach

Abstract

This paper aims to develop supplementary damping control actions of UPFCs by using forward neural networks (FNN) approximated energy function methods. The energy function based approach will first be considered for designing the supplementary damping control based on the network-preserving model. In order to provide more flexible solution, we proposed the Energy Function based Forward Neural Network Supplementary Damping (EFFNNSD) controller of UPFCs. The EFFNNSD can approximate the supplementary control action based on energy function methods. The EFFNNDS not only retain the idea of energy function methods, but also has powerful on-line learning ability for damping control adjustments. Numerical simulations on two benchmark systems have been performed to validate the proposed control for providing the extra damping and suppressing power swings even under severe operating conditions.