Estimating Demand Response Potential of Buildings Using a Predictive HVAC Model

Increasing penetration of intermittent renewable electricity into the grid, coupled with development of new communication and control strategies, is creating challenges and opportunities for demand response (DR) to balance the grid. This paper presents a model characterization of a controllable buildings Variable Air Volume HVAC (VAV HVAC) system capable of implementing control strategies that provide flexibility to the grid. A Model Predictive Controller (MPC) capable of reliably varying the modeled power by ±20%, or up to ±2 GW on a national scale, every five minutes without compromising occupants comfort was built. A climate analysis was performed in order to assess the availability of controllable resources in sixteen cities. It is found that this control strategy could be implemented up to 99% of the time in the hottest regions, but as low as 10% of the time in the coldest.