Data-Driven Distributed Voltage Control for Microgrids: A Koopman-based Approach

TL;DR

This paper introduces a novel distributed voltage control method for microgrids using Koopman operator theory, enabling linear modeling of nonlinear dynamics for improved voltage regulation based solely on local data.

Contribution

It develops a Koopman-based data-driven control strategy integrated with MPC for distributed voltage regulation in microgrids, accounting for system changes and constraints.

Findings

Effective voltage regulation under varying load and network conditions.

Distributed control based on local measurements achieves system stability.

Incorporates reactive power constraints and minimizes control costs.

Abstract

This paper presents a distributed data-driven control to regulate the voltage in an alternate current microgrid (MG). Following the hierarchical control frame for MGs, a secondary control for voltage is designed with a data-driven strategy using the Koopman operator. The Koopman operator approach represents the nonlinear behavior of voltage as a linear problem in the space of observables or lifted space. The representation in the lifted space is used together with linear consensus to design a model predictive control (MPC). The complete algorithm is proved in an MG model including changes in load, transmission lines, and the communication graph. The data-driven model regulates voltage using a distributed approach based only on local measurements, and includes reactive power constraints and control cost minimization.