The Influence Of Unmeasured Occupancy Disturbances On The Performance Of Black-Box Thermal Building Models

Previous studies have identified a significant potential in using economic model predictive control for space heating. This type of control requires a thermodynamic model of the controlled building that maps certain controllable inputs (heat power) and measured disturbances (ambient temperature and solar irradiation) to the controlled output variable (room temperature). Occupancy related disturbances, such as people heat gains and venting through windows, are often completely ignored or assumed to be fully known (measured) in these studies. However, this assumption is usually not fulfilled in practice and the current simulation study investigated the consequences thereof. The results indicate that the predictive performance (root mean square errors) of a black-box state-space model is not significantly affected by ignoring people heat gains. On the other hand, the predictive performance was significantly improved by including window opening status as a model input. The performance of black-box models for MPC of space heating could therefore benefit from having inputs from sensors that tracks window opening.