Model-predictive control for non-domestic buildings: A critical review and prospects

Model-predictive control (MPC) has recently excited much interest as a new control paradigm for non-domestic buildings. Since it is based on the notion of optimization, MPC is, in principle, well placed to deliver significant energy savings and reductions in CO2 emissions compared with existing rule-based control systems. The prospects for buildings MPC are critically reviewed, in particular, the central role of the predictive mathematical model that lies at its heart. The emphasis is on practical implementation rather than control-theoretic aspects, and covers the role of occupants as well as the form of the predictive model. The most appropriate structure for such a model is still an open question, which is considered alongside the development of the initial model, and the process of updating the model during the building's operational life. The importance of sensor placement is highlighted alongside the possibility of updating the model with occupants' comfort perception. It is concluded that there is an urgent need for research on the automated creation and updating of predictive models if MPC is to become an economically viable control method for non-domestic buildings. More evidence through operating full-scale buildings with MPC is required to demonstrate the viability of this method.;Model-predictive control (MPC) has recently excited much interest as a new control paradigm for non-domestic buildings. Since it is based on the notion of optimization, MPC is, in principle, well placed to deliver significant energy savings and reductions in CO 2 emissions compared with existing rule-based control systems. The prospects for buildings MPC are critically reviewed, in particular, the central role of the predictive mathematical model that lies at its heart. The emphasis is on practical implementation rather than control-theoretic aspects, and covers the role of occupants as well as the form of the predictive model. The most appropriate structure for such a model is still an open question, which is considered alongside the development of the initial model, and the process of updating the model during the building's operational life. The importance of sensor placement is highlighted alongside the possibility of updating the model with occupants' comfort perception. It is concluded that there is an urgent need for research on the automated creation and updating of predictive models if MPC is to become an economically viable control method for non-domestic buildings. More evidence through operating full-scale buildings with MPC is required to demonstrate the viability of this method.;Model-predictive control (MPC) has recently excited much interest as a new control paradigm for non-domestic buildings. Since it is based on the notion of optimization, MPC is, in principle, well placed to deliver significant energy savings and reductions in CO2 emissions compared with existing rule-based control systems. The prospects for buildings MPC are critically reviewed, in particular, the central role of the predictive mathematical model that lies at its heart. The emphasis is on practical implementation rather than control-theoretic aspects, and covers the role of occupants as well as the form of the predictive model. The most appropriate structure for such a model is still an open question, which is considered alongside the development of the initial model, and the process of updating the model during the building's operational life. The importance of sensor placement is highlighted alongside the possibility of updating the model with occupants' comfort perception. It is concluded that there is an urgent need for research on the automated creation and updating of predictive models if MPC is to become an economically viable control method for non-domestic buildings. More evidence through operating full-scale buildings with MPC is required to demonstrate the viability of this method.;