A scalable control design for grid-forming inverters in microgrids

TL;DR

This paper presents a scalable, passivity-based control design for grid-forming inverters in microgrids, enhancing stability, power sharing, and performance in islanded operation through decentralized conditions and advanced modeling.

Contribution

It introduces a novel decentralized control method for grid-forming inverters using passivity theory, applicable to complex models and ensuring plug-and-play stability.

Findings

Guarantees stable plug-and-play microgrid operation.

Improves power sharing compared to non-droop methods.

Enhances stability and performance in realistic simulations.

Abstract

Microgrids are increasingly recognized as a key technology for the integration of distributed energy resources into the power network, allowing local clusters of load and distributed energy resources to operate autonomously. However, microgrid operation brings new challenges, especially in islanded operation as frequency and voltage control are no longer provided by large rotating machines. Instead, the power converters in the microgrid must coordinate to regulate the frequency and voltage and ensure stability. We consider the problem of designing controllers to achieve these objectives. Using passivity theory to derive decentralized stability conditions for the microgrid, we propose a control design method for grid-forming inverters. For the analysis we use higher-order models for the inverters and also advanced dynamic models for the lines with an arbitrarily large number of states. By satisfying the decentralized condition formulated, plug-and-play operation can be achieved with guaranteed stability, and performance can also be improved by incorporating this condition as a constraint in corresponding optimization problems formulated. In addition, our control design can improve the power sharing properties of the microgrid compared to previous non-droop approaches. Finally, realistic simulations confirm that the controller design improves the stability and performance of the power network.