Parametric building energy simulations are performedto quantify the range of annual HVAC energy savingsachievable through comfort-optimized adjustments toconventional heating and cooling setpoints in officebuildings. Savings potential is examined in context withoccupant subjective feedback, using pilot data from(N=45) real builing occupants collected with a novelmobile sensing platform from 2-week pilot studies infour (4) commerical buildings. Machine learningtechniques are used to generate probabilistic models ofthermal discomfort from physical and subjectivemeasures. Models are then interpreted to determine thelargest setpoint range achievable while maintainingthermal conditions that are acceptable to 80 percent ofbuilding occupants surveyed. Outcomes areextrapolated across three (3) building vintages (pre-1980, post-1980, and ASHRAE 90.1-compliant) andeight (8) California climate zones to determine thepotential range of energy savings achievable fromimplementing customized setpoints learned throughoccupant subjective feedback and concurrent thermalsensing.
Citation: ASHRAE/IBPSA-USA Bldg Simulation Conf, 2016
Product Details
- Published:
- 2016
- Number of Pages:
- 7
- Units of Measure:
- Dual
- File Size:
- 1 file , 1 MB
- Product Code(s):
- D-BSC16-37
