TY  - CONF
  - Alie El-Din Mady, Gregory M. Provan, Conor Ryan and Kenneth N. Brown
  - Conference of Association for the Advancement of Artificial Intelligence (AAAI)
  - Stochastic Model Predictive Controller for the Integration of Building Use and Temperature Regulation
  - 2011
  - July
  - Validated
  - 1
  - ()
  - San Francisco, CA, USA
  - 07-AUG-11
  - 11-AUG-11
  - The aim of a modern Building Automation System (BAS) is to enhance interactive control  strategies for energy efficiency and enhanced user comfort. In this context, we develop a novel control algorithm that uses a stochastic building occupancy model to improve mean energy efficiency while minimizing expected discomfort. We compare by simulation our Stochastic Model Predictive Control (SMPC) strategy to the standard heating control method to empirically demonstrate a 4.3% reduction in energy use and 38.3% reduction in expected discomfort.
  - SFI 06-SRC-I1091
DA  - 2011/07
ER  - 

@inproceedings{V99731673,
   = {Alie El-Din Mady, Gregory M. Provan, Conor Ryan and Kenneth N. Brown},
   = {Conference of Association for the Advancement of Artificial Intelligence (AAAI)},
   = {{Stochastic Model Predictive Controller for the Integration of Building Use and Temperature Regulation}},
   = {2011},
   = {July},
   = {Validated},
   = {1},
   = {()},
   = {San Francisco, CA, USA},
  month = {Aug},
   = {11-AUG-11},
   = {{The aim of a modern Building Automation System (BAS) is to enhance interactive control  strategies for energy efficiency and enhanced user comfort. In this context, we develop a novel control algorithm that uses a stochastic building occupancy model to improve mean energy efficiency while minimizing expected discomfort. We compare by simulation our Stochastic Model Predictive Control (SMPC) strategy to the standard heating control method to empirically demonstrate a 4.3% reduction in energy use and 38.3% reduction in expected discomfort.}},
   = {SFI 06-SRC-I1091},
  source = {IRIS}
}