# Data-Driven Wide-Area Control Design of Power System Using the Passivity Shortage Framework

## TL;DR

This paper introduces a data-driven, passivity-based wide-area control method for power systems that effectively dampens inter-area oscillations by decomposing the system into passivity-short subsystems and optimizing stability parameters.

## Contribution

It develops a novel modular control design framework using passivity shortage theory and data-driven matrix inequalities, enabling adaptive and effective oscillation damping in large-scale power systems.

## Key findings

- Effective damping of inter-area oscillations demonstrated in simulations
- Control design is modular and adapts to operating conditions
- Utilizes data-driven matrix inequalities for stability parameter optimization

## Abstract

A novel wide-area control design is presented to mitigate inter-area power frequency oscillations. A large-scale power system is decomposed into a network of passivity-short subsystems whose nonlinear interconnections have a state-dependent affine form, and by utilizing the passivity shortage framework a two-level design procedure is developed. At the lower level, any generator control can be viewed as one that makes the generator passivity-short and $L_2$ stable, and the stability impact of the lower-level control on the overall system can be characterized in terms of two parameters. While the system is nonlinear, the impact parameters can be optimized by solving a data-driven matrix inequality (DMI), and the high-level wide-area control is then designed by solving another Lyapunov matrix inequality in terms of the design parameters. The proposed methodology makes the design modular, and the resulting control is adaptive with respect to operating conditions of the power system. A test system is used to illustrate the proposed design, including DMI and the wide-area control, and simulation results demonstrate effectiveness in damping out inter-area oscillations.