Model Predictive Control of regulation services from commercial buildings to the smart grid

We first demonstrate that the demand-side flexibility of the Heating Ventilation and Air Conditioning (HVAC) system of a typical commercial building can be exploited for providing frequency regulation service to the power grid using at-scale experiments. We then show how this flexibility in power consumption of building HVAC system can be leveraged for providing regulation service. To this end, we consider a simplified model of the power grid with uncertain demand and generation. We present a Model Predictive Control (MPC) scheme to direct the ancillary service power flow from buildings to improve upon the classical Automatic Generation Control (AGC) practice. We show how constraints such as slow and fast ramping rates for various ancillary service providers, and short-term load forecast information can be integrated into the proposed MPC framework. Finally, we provide extensive simulation results to illustrate the effectiveness of the proposed methodology for enhancing grid frequency regulation.