UC Davis

As California continues to decarbonize the electrical grid and more customers electrify, load flexibility among heat pumps is becoming critical for maximizing the use of carbon-free electricity sources, stabilizing the electricity grid, and minimizing operating costs to end-users. The transition to all-electric housing has many concerned about potential increases in utility costs. Load flexibility controls offer a way to mitigate the impact of electrification on customers by shifting consumption to times of day with lower rates without compromising their comfort. Heat pump water heaters (HPWHs) are currently controlled using rule-based logic to maintain a programmed water temperature setpoint. This type of control usually does not provide any flexibility to when the heat pump operates. Economic model predictive control (MPC) is an advanced control technique that can provide automated load flexibility due to its ability to account for time-varying electric tariffs and available energy storage. A new configurable control framework is motivated and described to address the challenges of configuring economic MPC for deployment. This framework utilizes a graph-based system representation of the physical system that automatically instantiates the underlying economic MPC problem from the system representation and requires minimum MPC expertise. In this work, the MPC framework is described and applied to a simulated HPWH. The closed-loop simulation results are compared to the results obtained from simulations of an HPWH under a rule-based control approach.