A microgrid is a standalone power grid requiring generation capabilities (often generators, batteries, or renewable resources) plus control methods to maintain power flow. Electronics, appliances, and heating or cooling are all responsible for consuming that power. In this project, Laura Brown and other Michigan Tech researchers are investigating a control system for such microgrids that are autonomous—able to work in isolation—and agile, flexible to rapid changes in the configuration of the electric grid to incoming sources and consumers of power.
The world of microgrids is layered, each layer with a different purpose and speed. For stable power, the controls for the microgrid are considered hierarchically: low-level control responds to fastest events, and maintains regulation of stable voltages and currents in the system; the upper layer of control is responsible for power distribution, optimization, and long-term planning and prediction of resource availability and use. Brown’s work focuses on this high-level analysis in resource prediction at several timescales—in the next few minutes, next hours, next days. What if a generator is out of service for maintenance—what can be done? Brown uses artificial intelligence, machine learning, and experts in other domains to turn off non-critical resources or add new power sources.
The United States Department of Defense and the Army Research Lab seek the expertise of interdisciplinary Michigan Tech researchers to solve, prevent, and adapt to these potential real-world scenarios.