Control and coordination of DC microgrids

As part of my research, I deal with the control and coordination of generators, loads and storage devices in DC microgrids. The aim is the efficient and secure control of the dynamic components in the microgrid.

In the coordination task, static operating points are usually calculated, which ensure optimal economy or minimum line losses. These operating points are tracked by real-time capable primary controllers. At the same time, these primary controllers regulate the voltages in the grid such that the dynamic microgrid is stabilized in desired equilibrium points (operating points).

In my research, I try to break up this hierarchical control architecture and rethink conventional controllers, e.g. grid-forming and grid-following controllers. The aim is to achieve optimal transient economy while simultaneously stabilizing the power grid. To achieve this, innovative data-driven controllers, e.g. reinforcement learning controllers, are used, which also take into account input and state constraints. The stability of such controllers can be proven analytically (e.g., by using dissipativity theory) or verified numerically.