Table 5 Summary of referenced end-use modeling methods, including how these models are extended in this paper.
From: High resolution synthetic residential energy use profiles for the United States
End-use | Relevant models | Our approach |
|---|---|---|
HVAC | Muratori et.al.41, Subbiah et.al.44, Thorve et.al.27, Tsuji et.al.43 | Our model is based on the approach adopted in Subbiah et.al.44 and Thorve et.al.27. These models were specific to Virginia state. The method employed in these works as well as ours is a physics model. This model is also documented in NREL Technical Reports. Additional details about thermostat settings, building characteristics such as insulation are obtained from RECS survey, EIA website, and NREL Technical Reports. |
DHW | Hendron et.al.48 and Maguire et.al.50 present a general stochastic method to reproduce sample hot water draws based on two water usage surveys conducted in the U.S. The analyses concludes by reporting distributions related to hot water usage events such as showering, using dishwasher, and using clothes washer. Some of these results are summarized in Table 4 and used in our model. Hot and cold water temperatures for specific end-uses are obtained from NREL surveys. The above model does not consider the setting of specific household schedules. This context of household occupancy and occurrence of events is added to an existing model in literature presented in Thorve et.al.27 in order to schedule these hot water usage events. | |
light | Richardson et.al.57, Stokes et.al.56, Paatero & Lund et.al.58 | We mainly improve upon the stochastic lighting model developed for U.K. household by Richardson et.al. by adding context of U.S. households such as household size, household occupancy, annual lighting consumption in the U.S. for different household sizes, calibration of γ for U.S. households, and proportion of light bulbs in the U.S. households and their power ratings. The probability of switch-on event is modeled from Paatero & Lund et.al.58 and Richardson et.al.57. Duration of switch-on event is taken from Stokes et.al.56. Power ratings for different categories of lighting units in U.S. is obtained from a study conducted by Bonneville Power Administration59. Proportion of lighting units in U.S. households and annual lighting consumption by household size is derived from RECS survey. Irradiance data for the U.S. is obtained from NREL. |
refr | — | A linear regression model is developed to predict daily refrigerator usage for a household based on outside temperature and climate zones. |
misc, act | All the three referenced models have inspired the design of activity models involving use of appliances. The actual activity occurrence is obtained from the individual/household occupancy schedule. Duration and power usage distributions of appliances is modeled from NIST datasets62,63,64 and other datasets65,66,67,68. The start time is chosen randomly within the duration reported by ATUS individuals and the power ratings and duration of the activity/appliance is selected from the above mentioned distributions. |
