An event-triggered model predictive control for energy efficiency and thermal comfort optimization in buildings

Abstract

Model predictive control (MPC) is a promising optimal control technique for building automation. However, the high computation load to solve the optimization problem of MPC is challenging its implementation for real-time building control. Typical MPC systems employ the time-triggered mechanism (TTM), which conducts the optimization periodically at each control interval regardless of the necessity. This study proposes an event-triggered mechanism (ETM) for MPC, which conducts the optimization only when there is a triggering event that necessitates it. Contrasting to the conventional ETM that bases only on the current information, the proposed ETM bases on the cost function considering the past, current and future information. An event-triggered model predictive control (ETMPC) system is developed using the proposed ETM. In a simulation environment, the ETMPC system is implemented to control an air-conditioning system. The ETMPC is compared to a MPC employing TTM and a conventional thermostat. The ETMPC improved the computation efficiency by 77.6% - 88.2% as compared to the MPC while achieving similar energy performance as the MPC does (both achieved more than 9% energy savings over the thermostat). The ETMPC only degraded the thermal comfort performance slightly as compared to the MPC but is still much better than the thermostat.