TY - JOUR
T1 - Use of model predictive control and weather forecasts for energy efficient building climate control
AU - Oldewurtel, Frauke
AU - Parisio, Alessandra
AU - Jones, Colin N.
AU - Gyalistras, Dimitrios
AU - Gwerder, Markus
AU - Stauch, Vanessa
AU - Lehmann, Beat
AU - Morari, Manfred
PY - 2012/2
Y1 - 2012/2
N2 - This paper presents an investigation of how Model Predictive Control (MPC) and weather predictions can increase the energy efficiency in Integrated Room Automation (IRA) while respecting occupant comfort. IRA deals with the simultaneous control of heating, ventilation and air conditioning (HVAC) as well as blind positioning and electric lighting of a building zone such that the room temperature as well as CO2 and luminance levels stay within given comfort ranges. MPC is an advanced control technique which, when applied to buildings, employs a model of the building dynamics and solves an optimization problem to determine the optimal control inputs. In this paper it is reported on the development and analysis of a Stochastic Model Predictive Control (SMPC) strategy for building climate control that takes into account the uncertainty due to the use of weather predictions. As first step the potential of MPC was assessed by means of a large-scale factorial simulation study that considered different types of buildings and HVAC systems at four representative European sites. Then for selected representative cases the control performance of SMPC, the impact of the accuracy of weather predictions, as well as the tunability of SMPC were investigated. The findings suggest that SMPC outperforms current control practice.
AB - This paper presents an investigation of how Model Predictive Control (MPC) and weather predictions can increase the energy efficiency in Integrated Room Automation (IRA) while respecting occupant comfort. IRA deals with the simultaneous control of heating, ventilation and air conditioning (HVAC) as well as blind positioning and electric lighting of a building zone such that the room temperature as well as CO2 and luminance levels stay within given comfort ranges. MPC is an advanced control technique which, when applied to buildings, employs a model of the building dynamics and solves an optimization problem to determine the optimal control inputs. In this paper it is reported on the development and analysis of a Stochastic Model Predictive Control (SMPC) strategy for building climate control that takes into account the uncertainty due to the use of weather predictions. As first step the potential of MPC was assessed by means of a large-scale factorial simulation study that considered different types of buildings and HVAC systems at four representative European sites. Then for selected representative cases the control performance of SMPC, the impact of the accuracy of weather predictions, as well as the tunability of SMPC were investigated. The findings suggest that SMPC outperforms current control practice.
KW - Building climate control
KW - Chance-constrained control
KW - Energy efficiency
KW - Stochastic model predictive control
UR - http://www.scopus.com/inward/record.url?scp=84855234478&partnerID=8YFLogxK
U2 - 10.1016/j.enbuild.2011.09.022
DO - 10.1016/j.enbuild.2011.09.022
M3 - Article
AN - SCOPUS:84855234478
SN - 0378-7788
VL - 45
SP - 15
EP - 27
JO - Energy and Buildings
JF - Energy and Buildings
ER -