Integrations of Neural Networks and Transient Energy Functions for Designing Supplementary Damping Control of UPFC

Abstract

This article presents an integrated scheme for supplementary damping control of unified power flow controllers (UPFCs) in order to mitigate low-frequency oscillations in power systems. The entire control system consists of the primary control and the supplementary control. In the primary control, the passivity-based control is considered in the current control loop of two converters for achieving more prompt and accurate dynamical responses. In the supplementary control, the transient energy function (TEF) approach will be explored first for designing the damping control of UPFCs. This control action can be considered as an extension of droop control used in the synchronous generator. In order to further cope with unmodeled dynamics of power systems and provide the online dynamic adaptation ability, neural networks approximated control actions are designated for online weight adjustments of the TEF-based supplementary control. Numerical simulations on three benchmark systems have been performed to validate the proposed control method for providing the extra damping and suppressing power swings even under severe operating conditions.