A Distributed Model Predictive Control Framework for Grid-Friendly Distributed Energy Resources

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