Modal Decomposition of the Linear Swing Equation in Networks with Symmetries

TL;DR

This paper introduces a modal decomposition method to analyze how symmetries in power grid networks influence the transient and steady-state dynamics of the swing equation, providing insights into peak flows and perturbation propagation.

Contribution

It presents a novel modal decomposition technique that characterizes the effects of network symmetries on swing equation dynamics in both homogeneous and heterogeneous systems.

Findings

Symmetries significantly affect transient responses and peak flows.

The method applies to large, real-world power grid networks.

Small perturbations propagate differently in symmetric networks.

Abstract

Symmetries are widespread in physical, technological, biological, and social systems and networks, including power grids. The swing equation is a classic model for the dynamics of powergrid networks. The main goal of this paper is to explain how network symmetries affect the swing equation transient and steady state dynamics. We introduce a modal decomposition that allows us to study transient effects, such as the presence of overshoots in the system response. This modal decomposition provides insight into the peak flows within the network lines and allows a rigorous characterization of the effects of symmetries in the network topology on the dynamics. Our work applies to both cases of homogeneous and heterogeneous parameters. Further, the model is used to show how small perturbations propagate in networks with symmetries. Finally, we present an application of our approach to a large power grid network that displays symmetries.