Short Answer: Household hourly energy use of non-weather sensitive (NWS)
end-uses such as water heaters, clothes dryers, ovens, etc. vary in a random
way across days and weeks. These variations can result in unexpectedly high
individual peak hourly loads compared to estimates based on assumed uniform
patterns applied in engineering-based models such as those provided by NREL.
Longer Answer: End-use loads in engineering-based databases
(e.g. DOE, NREL) typically apply uniform load profiles for individual end uses
for each day or day type (e.g., weekday, weekend) which implies for instance,
that households wash and dry clothes at the same time on “washing days,” that
meals are cooked at the same time every day and so on. These assumptions lead
to a flattening of load profiles that underestimate peaks and valleys
resulting from the actual random nature of all appliances energy use. This variation
plays an important role in solar, battery, smart grid, micro-grid and other
product development, application, and analysis. Realistic NWS kW loads are
based on actual metered data as applied in the MAISY RECS Database rather
than hypothetical "average" uniform load profiles.