Conference Editor

Jianshun Zhang; Edward Bogucz; Cliff Davidson; Elizabeth Krietmeyer

Keywords:

Building occupants and operators; Uncertainty; Building energy performance; Simulationbased analysis; Probabilistic models.

Location

Syracuse, NY

Event Website

http://ibpc2018.org/

Start Date

24-9-2018 3:30 PM

End Date

24-9-2018 5:00 PM

Description

Occupants play an important role in building energy performance, while building operators are the other side of the coin. This research quantifies the relative impact of probabilistic versus standard occupant models on building energy use. Energy performance of a highperformance reference small office building in Ottawa, Canada, is investigated using a simulation-based analysis. The impact of building users is studied by systematically altering occupant and operator-related domains, including occupants' presence and use of lights, window shades, operable windows, plug-in appliances, and thermostats. The results showed that the predicted natural gas energy use increased by a factor of about two compared to the reference occupant models. The predicted electricity energy use decreased about 49% compared to the reference occupant models. This deviation for the gas use resulted from modeling all six domains and for the electricity use resulted from simulating all six domains except for the window shade and operable window use using probabilistic models and operators’ adjusted thermostat setpoints with the air handling unit scheduling to be on all day. The maximum deviation of the predicted electricity energy use with occupants’ adjusted thermostat setpoints caused by the simultaneous probabilistic modeling of the four domains of occupants' presence and use of lighting, plug-in appliances, and thermostat. The lighting use domain showed the highest main effect on the energy use. The findings of the examination of occupant and operator-related modeling assumptions emphasizes the necessity to consider both operators' and occupants' impact on the predicted energy performance of the small building-scale model.

Comments

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DOI

https://doi.org/10.14305/ibpc.2018.hf-1.05

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

COinS
 
Sep 24th, 3:30 PM Sep 24th, 5:00 PM

Quantification of building energy performance uncertainty associated with building occupants and operators

Syracuse, NY

Occupants play an important role in building energy performance, while building operators are the other side of the coin. This research quantifies the relative impact of probabilistic versus standard occupant models on building energy use. Energy performance of a highperformance reference small office building in Ottawa, Canada, is investigated using a simulation-based analysis. The impact of building users is studied by systematically altering occupant and operator-related domains, including occupants' presence and use of lights, window shades, operable windows, plug-in appliances, and thermostats. The results showed that the predicted natural gas energy use increased by a factor of about two compared to the reference occupant models. The predicted electricity energy use decreased about 49% compared to the reference occupant models. This deviation for the gas use resulted from modeling all six domains and for the electricity use resulted from simulating all six domains except for the window shade and operable window use using probabilistic models and operators’ adjusted thermostat setpoints with the air handling unit scheduling to be on all day. The maximum deviation of the predicted electricity energy use with occupants’ adjusted thermostat setpoints caused by the simultaneous probabilistic modeling of the four domains of occupants' presence and use of lighting, plug-in appliances, and thermostat. The lighting use domain showed the highest main effect on the energy use. The findings of the examination of occupant and operator-related modeling assumptions emphasizes the necessity to consider both operators' and occupants' impact on the predicted energy performance of the small building-scale model.

https://surface.syr.edu/ibpc/2018/HF1/5

 

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