Integrating Greenhouse Gas Emissions into Model Predictive Control of Heat Pump Water Heaters

Heat pump water heaters (HPWHs) are more energy-efficient than electric resistance water heaters and have inherent load-shifting potential due to their built-in storage tank. Most HPWHs currently employ rule-based control (RBC) strategies that track a temperature setpoint, regardless of the cost of electricity or marginal grid greenhouse gas (GHG) emissions. Economic model predictive control (MPC) can provide automated load flexibility for HPWHs as it can determine in real-time the optimal operation of the HPWH heat sources based on time-varying factors. For example, time-of-use (TOU) rates can be used by the MPC to minimize the cost of operating the HPWH. However, TOU rates do not directly reflect the actual grid GHG emissions associated with electricity generation. In this work, a method for incorporating the marginal grid GHG emissions signal into MPC is proposed. The resulting multi-objective MPC optimizes HPWH operation based on electricity cost and GHG emissions while maintaining user comfort. Simulation results demonstrate that the MPC approach can reduce operating costs and GHG emissions associated with HPWH operation with no comfort violations compared to a conventional RBC strategy for HPWHs.