A Distributed Scheme for Voltage and Frequency Control and Power Sharing in Inverter Based Microgrids

TL;DR

This paper introduces a novel distributed control scheme for inverter-based microgrids that ensures voltage and frequency regulation, active power sharing, current limiting, and scalability, with proven stability and demonstrated effectiveness through simulations.

Contribution

It presents a new control architecture combining inner current limiting, a distributed secondary control, and a double-loop voltage control with stability analysis considering line conductances.

Findings

Improved stability properties with angle droop-like frequency control.

Effective active power sharing and voltage regulation demonstrated.

Control scheme validated through detailed nonlinear simulations.

Abstract

Grid-forming inverter-based autonomous microgrids present new operational challenges as the stabilizing rotational inertia of synchronous machines is absent. The design of efficient control policies for grid-forming inverters is, however, a non-trivial problem where multiple performance objectives need to be satisfied, including voltage/frequency regulation, current limiting capabilities, as well as active power sharing and a scalable operation. We propose in this paper a novel control architecture for frequency and voltage control which allows current limitation via an inner loop, active power sharing via a distributed secondary control policy and scalability by satisfying a passivity property. In particular, the frequency controller employs the inverter output current and angle to provide an angle droop-like policy which improves its stability properties. This also allows to incorporate a secondary control policy for which we provide an analytical stability result which takes line conductances into account (in contrast to the lossless line assumptions in literature). The distinctive feature of the voltage control scheme is that it has a double loop structure that uses the DC voltage in the feedback control policy to implement a power balancing strategy to improve performance. The performance of the control policy is illustrated via simulations with detailed nonlinear models in a realistic setting.