Future power grids will incorporate a large number of distributed energy resources, which motivates research on real-time online algorithms that optimally control large networked systems. This poster introduces two algorithms for the real-time control of time-varying physical systems, based on recent development in time-varying optimization. The two algorithms take advantage of real-time feedback measurements of the system, are computationally efficient, and are theoretically guaranteed to have bounded suboptimality under certain conditions.

The confluence of two powerful global trends -- the rapid growth of cloud computing and data centers with skyrocketing energy consumption, and the accelerating penetration of renewable energy sources --