A Distributed Model Predictive Control Framework for Grid-Friendly Distributed Energy Resources
Lalitha Subramanian, Vincent Debusschere, Hoay Beng Gooi, Nourédine Hadjsaïd
Abstract
This work develops a distributed fast-frequency control framework for application in self-consuming energy communities. We propose a distributed consensus optimization of inertia coefficients based on the individual resource constraints of grid-friendly distributed energy resources (ders), which relies on the presence of a peer-to-peer communication infrastructure. In the proposed control strategy, the inertia coefficients of the individual ders are optimally tuned in real-time by a faster control loop to improve the frequency response metrics such as nadir frequency, peak overshoot, and the settling time of the frequency transient with the help of local model predictive controllers. The coordination among the ders are simulated on the cigre benchmark microgrid and the control is validated on a power hardware-in-the-loop platform.