** Customized Home Energy Report**
Energy consumption cannot be meaningfully modeled without considering the number of occupants in a home.
When your client is a home buyer, you enter the number and age of people moving into the home. If your client is the seller, you enter number and age of current occupants.
The Home Energy Report™ is customizable by entering your client’s information. (See screenshot above.)
Write a customizable Home Energy Report for your client now at http://www.nachi.org/home-energy-inspection.htm.
The number and age of occupants drives a formula that estimates the amount of hot water use in the household, and thus the hot water heating energy demand.
Holding the number of occupants constant, results in an insensitivity of energy use across a wide range of conditions, leading to over-predictions for homes with low occupancy (but mitigated by the fact that a default of, say, three people can only overestimate the actual conditions by two people) and significant under-predictions for homes with high occupancy.
The number of occupants will directly affect the amount of calculated domestic hot water consumption for the household. That includes regular fixtures, dishwasher and clothes washer hot water use. In addition, we allow miscellaneous electric loads (MELs) and lighting to be proportional to floor area or numbers of bedrooms.
Scaling televisions by number of bedrooms captures the effects of occupancy more effectively than would simply linking television use to house size. The remaining plug loads are scaled by floor area.
A secondary impact from the bedrooms/occupancy calculation is a better scaling of the internal gains (which, in turn, effect heating and cooling energy use) due to the number of occupants.
Testing of these refinements in the model (in comparison to measured energy use for large numbers of homes) showed much better predictions for total home energy than was the case with fixed occupancy and no dependence of MELs or lighting on floor area.
Accuracy Within 1%
The National Renewable Energy Laboratory (NREL) in a 2012 publication showed that when averaged across groups of homes, the tool predicts energy use within 1% of actual consumption when physical characteristics and occupant behavior are accurately documented.