Distributed model predictive control for building demand side management

Demand side management is widely acknowledged as an important source of flexibility and then an essential element to balance supply and demand more effectively. A fundamental challenge is to enable buildings to participate in demand side services without violating indoor comfort. In this paper, we present a distributed Model Predictive Control (MPC) approach to demand side management in buildings. The proposed MPC scheme encompasses heating/cooling systems, onsite generation and storage technologies, which are integrated into a unified management framework along with standard objectives (e.g., heating/cooling). The distributed algorithm, based on an active-set method, allows adjustments of multiple setpoints and enables the building to participate in balancing programs while minimising the energy use without violating the indoor comfort. Numerical results with real data from one university building show the promising performance and computational tractability of the proposed approach, which can enable practical implementations on building platforms.