Abstract
Perceptions of occupants to energy use, collected in questionnaire surveys, were used as input variable for building simulations. These perceptions are related to occupant interactions with lighting, plug loads, heating, cooling, windows opening and shading. The simulations were performed to a green-rated (GB) and a non-rated building, in Sydney Australia, with similar characteristics. The simulation models were calibrated according to measured annual energy data to incorporate the collected behaviours. Occupants' behaviours (OB) were quantified in terms of energy use, greenhouse gas emissions and costs. Results show that occupants have 25% more impact on the overall energy use in the non-rated building than in the GB. In the GB occupants have a major impact in the heating function while in the non-rated building they impact the lighting system. The GB is less subjected to the direct impact of OB if the majority of its systems are automatically controlled.
Abbreviations: AC: Air conditioning; ASHRAE: American Society of Heating, Refrigerating and Air-Conditioning Engineers; AUD: Australian dollars; BCA: Building Code of Australia; BEPS: Dynamic Building Energy Performance Simulations; COP: Coefficient of performance; EER: Energy efficiency ratio; HW: Hot water; GB: Green building; HVAC: Heating, ventilation, and air conditioning; IEQ: Indoor environmental quality; NRB: Non-rated building; NSW: New South Wales; OB: Occupant behaviour; occ: Occupants; SPLITS: A split system is an air conditioning systems split into one unit that is indoors and another one that is outdoors; WSU: Western Sydney University; VRF: Variable refrigerant flow system; yr: Year
Nomenclature
A | = | Occupants’ actions |
CV | = | Coefficient of variation of the root mean square error |
df | = | Degrees of freedom |
EB | = | Non-rated building (existing building) |
Er | = | Deviation value during the calibration process (%) |
ER | = | Deviation value due to occupant behaviour (%) |
Ereal | = | Average of measured energy use (kWh/yr) |
Ereal,i | = | Measured energy use during period i (kWh/yr) |
Esim,i | = | Energy during period i (kWh/yr) |
GHGemissions | = | Greenhouse gas emissions (tonCO2-eq) |
i | = | Period |
MBE | = | Mean bias error |
n1 | = | Number of subjects in group 1 |
n2 | = | Number of subjects in group 2 |
nm | = | Number of measurements |
p | = | Significance |
P(A) | = | Probability of occupants having a specific action |
P(A)NRB | = | Probability of occupants having a specific action in the green building |
P(A/Ei) | = | Probability of occupants’ interaction at an event i due to action A |
P(Ei) | = | Probability of the occurrence of the event i |
P(A)GB | = | Probability of occupants having a specific action in the non-rated building |
t | = | t student |
U | = | Overall heat transfer coefficient (W/m2-K) |
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 as-built information is the final data that represents what actually was built after the construction process
2 as-built information is the final data that represents what actually was built after the construction process
3 Based on Annex 66 final report
4 Based on a five-point scale (1, 2, 3, 4, and 5) where Unable = 1, Never =2, Sometimes = 3, Regularly =4 and Always = 5.
5 Includes classrooms
6 According to the results from the questionnaire survey, occupants only activated the shading system due to glare in 68% of the rooms with shading in the non-rated building and 61% of the rooms with shading in the green building
7 The percentage of occupants interacting with the air conditioning system is low due to the fact that this system is mainly managed by the management system. Only a few rooms have individual units such as Splits or Multisplits