TY - JOUR
T1 - Occupant feedback based model predictive control for thermal comfort and energy optimization
T2 - A chamber experimental evaluation
AU - Chen, Xiao
AU - Wang, Qian
AU - Srebric, Jelena
N1 - Funding Information:
This work was supported by National Science Foundation under NSF grant EFRI-1038264/EFRI-1452045 . We would also like to thank Dr. Yang-Seon Kim for her help in developing a heat balance chamber model under the EnergyPlus simulation environment. Though the resulting model was not used in this work since the results did not agree with experimental measurements, her work motivated us to develop the empirical chamber model used in this paper.
Publisher Copyright:
© 2015 Elsevier Ltd.
PY - 2016/2/15
Y1 - 2016/2/15
N2 - In current centralized building climate control, occupants do not have much opportunity to intervene the automated control system. This study explores the benefit of using thermal comfort feedback from occupants in the model predictive control (MPC) design based on a novel dynamic thermal sensation (DTS) model. This DTS model based MPC was evaluated in chamber experiments. A hierarchical structure for thermal control was adopted in the chamber experiments. At the high level, an MPC controller calculates the optimal supply air temperature of the chamber heating, ventilation, and air conditioning (HVAC) system, using the feedback of occupants' votes on thermal sensation. At the low level, the actual supply air temperature is controlled by the chiller/heater using a PI control to achieve the optimal set point. This DTS-based MPC was also compared to an MPC designed based on the Predicted Mean Vote (PMV) model for thermal sensation. The experiment results demonstrated that the DTS-based MPC using occupant feedback allows significant energy saving while maintaining occupant thermal comfort compared to the PMV-based MPC.
AB - In current centralized building climate control, occupants do not have much opportunity to intervene the automated control system. This study explores the benefit of using thermal comfort feedback from occupants in the model predictive control (MPC) design based on a novel dynamic thermal sensation (DTS) model. This DTS model based MPC was evaluated in chamber experiments. A hierarchical structure for thermal control was adopted in the chamber experiments. At the high level, an MPC controller calculates the optimal supply air temperature of the chamber heating, ventilation, and air conditioning (HVAC) system, using the feedback of occupants' votes on thermal sensation. At the low level, the actual supply air temperature is controlled by the chiller/heater using a PI control to achieve the optimal set point. This DTS-based MPC was also compared to an MPC designed based on the Predicted Mean Vote (PMV) model for thermal sensation. The experiment results demonstrated that the DTS-based MPC using occupant feedback allows significant energy saving while maintaining occupant thermal comfort compared to the PMV-based MPC.
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U2 - 10.1016/j.apenergy.2015.11.065
DO - 10.1016/j.apenergy.2015.11.065
M3 - Article
AN - SCOPUS:84951201719
SN - 0306-2619
VL - 164
SP - 341
EP - 351
JO - Applied Energy
JF - Applied Energy
ER -