Scheduling of Software-Defined Microgrids for Optimal Frequency Regulation

TL;DR

This paper presents an optimal scheduling framework for software-defined microgrids with high inverter-based resources, aiming to enhance frequency stability through dynamic virtual inertia and damping control, considering practical side effects.

Contribution

It introduces a novel scheduling method that dynamically optimizes virtual inertia and damping in microgrids, explicitly modeling control delays and failures for improved frequency regulation.

Findings

Effective frequency stability improvement demonstrated in case studies.

Significant economic benefits shown through the proposed strategy.

Explicit modeling of delays and failures enhances reliability of control.

Abstract

Integrated with a high share of Inverter-Based Resources (IBRs), microgrids face increasing complexity of frequency dynamics, especially after unintentional islanding from the maingrid. These IBRs, on the other hand, provide more control flexibility to shape the frequency dynamics of microgrid and together with advanced communication infrastructure offer new opportunities in the future software-defined microgrids. To enhance the frequency stability of microgrids with high IBR penetration, this paper proposes an optimal scheduling framework for software-defined microgrids to maintain frequency stability by utilizing the non-essential load shedding and dynamical optimization of the virtual inertia and virtual damping from IBRs. Moreover, side effects of these services, namely, the time delay associated with non-essential load shedding and potential IBR control parameter update failure are explicitly modeled to avoid underestimations of frequency deviation and over-optimistic results. The effectiveness and significant economic value of the proposed simultaneous and dynamic virtual inertia and damping provision strategy are demonstrated based on case studies in the modified IEEE 33-bus system.