A Comfort-Aware Energy Efficient HVAC System Based on the Subspace Identification Method

A proactive heating method is presented aiming at reducing the energy consumption in a HVAC system while maintaining the thermal comfort of the occupants. The proposed technique fuses time predictions for the zones’ temperatures, based on a deterministic subspace identification method, and zones’ occupancy predictions, based on a mobility model, in a decision scheme that is capable of regulating the balance between the total energy consumed and the total discomfort cost. Simulation results for various occupation-mobility models demonstrate the efficiency of the proposed technique.

[1]  Evangelos Zervas,et al.  A Subspace Identification Method for Detecting Abnormal Behavior in HVAC Systems , 2015 .

[2]  S. J. Mason.  Feedback Theory-Further Properties of Signal Flow Graphs , 1956, Proceedings of the IRE.

[3]  Bing Dong,et al.  A real-time model predictive control for building heating and cooling systems based on the occupancy behavior pattern detection and local weather forecasting , 2013, Building Simulation.

[4]  Samuel J. Mason,et al.  Feedback Theory-Some Properties of Signal Flow Graphs , 1953, Proceedings of the IRE.

[5]  Brandon Hencey,et al.  Predictive HVAC control using a Markov occupancy model , 2014, 2014 American Control Conference.

[6]  Miguel Á. Carreira-Perpiñán,et al.  OBSERVE: Occupancy-based system for efficient reduction of HVAC energy , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[7]  Hojung Cha,et al.  Occupancy Prediction Algorithms for Thermostat Control Systems Using Mobile Devices , 2013, IEEE Transactions on Smart Grid.

[8]  Bourhan Tashtoush,et al.  Dynamic model of an HVAC system for control analysis , 2005 .

[9]  Stefan Achleitner,et al.  POEM: power-efficient occupancy-based energy management system , 2013, IPSN.

[10]  Rajesh Gupta,et al.  Sentinel: occupancy based HVAC actuation using existing WiFi infrastructure within commercial buildings , 2013, SenSys '13.

[11]  Prabir Barooah,et al.  Energy-efficient control of under-actuated HVAC zones in commercial buildings , 2015 .

[12]  R. Pyke.  Markov Renewal Processes with Finitely Many States , 1961 .

[13]  H. Daniels.  Saddlepoint Approximations in Statistics , 1954 .

[14]  Bart De Moor,et al.  Subspace Identification for Linear Systems: Theory ― Implementation ― Applications , 2011 .

[15]  宮森 悠.  ライブラリー Annual Energy Outlook 2000 , 2000 .

[16]  A. Walter.  Notes on the utilization of records from third order climatological stations for agricultural purposes , 1967 .