Dynamic Energy Management with Scenario-Based Robust MPC

M. Wytock, N. Moehle, and S. Boyd

Proceedings of the American Control Conference, pages 2042-2047, May, 2017. Longer paper will be posted soonish.

We present a simple, practical method for managing the energy produced and consumed by a network of devices. Our method is based on (convex) model predictive control. We handle uncertainty using a robust model predictive control formulation that considers a finite number of possible scenarios. A key attribute of our formulation is the encapsulation of device details, an idea naturally implemented with object-oriented programming. We introduce an open-source Python library implementing our method and demonstrate its use in planning and control at various scales in the electrical grid: managing a smart home, shared charging of electric vehicles, and integrating a wind farm into the transmission network.