Enhancing Microgrid Flexibility, Stability, and Economy with Inverter-based Resources

Microgrids face both challenges and opportunities due to the wide integration of inverter-based resources (IBRs) and advanced control techniques. On the one hand, IBRs enable the optimal use of renewable energies, which are environmentally friendly; On the other hand, IBRs introduce fast dynamics and high non-linearities to microgrids, degrading their stability and complicating the design of effective controllers. It remains an open question of how to maximize the benefits of IBRs for microgrids while overcoming the limitations. Hence, this dissertation addresses these issues by proposing new device-level control algorithms for IBRs, deriving analytical stability criteria, and integrating device-level controller design into the grid-level economic operation of microgrids.

Firstly, an adaptive PQ control method with trajectory tracking capability is developed to improve the controllability and flexibility of the IBRs in microgrids, combining model-based analysis, physics-informed reinforcement learning, and power hardware-in-the-loop experiment. Exponential response time constants can be freely assigned to IBRs to follow any predefined trajectory without complicated gain tuning.

Secondly, a decentralized and coordinated voltage and frequency (V-f) control framework is proposed for islanded microgrids, with full consideration of the limited capacity of distributed energy resources (DERs) and V-f dependent load. The control framework is composed of a power regulator and a V-f regulator, which generate the supplementary signals for the primary controller.

Thirdly, a systematic controller design approach that ensures stability and domain of attraction (DOA) is developed for islanded microgrids. The stability conditions, i.e., certified stability, certified DOA, and their combination, are derived to rigorously guarantee whether a designated range is a subset of DOA. A systematic method for identifying the candidate control parameter set is further developed by integrating the analytical stability conditions.

Lastly, the concept of virtual inertia scheduling (VIS) is proposed to efficiently handle the high penetration of IBRs. VIS is an inertia management framework targeting security-constrained and economy-oriented inertia scheduling and generation dispatch of microgrids with a large scale of DERs. It schedules the power setting points of synchronous generators and IBRs, as well as the control modes and control parameters of IBRs, to provide secure and cost-effective inertia support.