We see a lot of houses. We have a lot of data on houses. For a while now, I have been wondering whether or not I’d be able to find some meaningful relationships with this data. I am not even sure what I would use it for, but I have taken some time to compile the data and pull some numbers that I thought were interesting. More than anything, the data just shows typical values for ‘regular houses’ in the Chicagoland area.
DISCLAIMER: This isn’t a scientific research study in any way, shape, or form - there are many things that you may point out that would make this little ‘research project’ invalid. I randomly selected 98 properties that we have done some sort of analysis for over the years. These properties were a mixture of single-family homes, condos, and townhomes. All of them were in the general Chicagoland area and were not built/designed to be high performance.
Here is a quick glimpse at some of the home size statistics from our sample:
Size (Square Feet): 9,058/1,155/3,963
Volume (Cubic Feet): 86,866/11,459/34,305
Enclosure Area (Square Feet): 21,723/2,079/7,565
Shell Area/Volume: 0.35/0.15/0.23
The SA/VOL is a ratio of the surface area of a building to its volume. Generally, ‘efficient’ shapes have large volumes with low surface areas, therefore making this ratio as small as possible. In European countries, this metric is often a key design consideration. Most homes in Chicago will have a SA/VOL ratio of 0.2-0.23 because of long, slender lots (typically 20’ wide and 55’ long).
Now lets talk about some consumption statistics and how they relate to home size:
Square Feet per Ton of Air Conditioning Installed: 1886/390/878
SF/Ton AC: The number of square feet of the home divided by installed capacity of the cooling equipment. 1 Ton is approximately equally to 12,000 Btu/hr.
% Air Conditioning Installed Compared to Amount Actually Needed in Home: 177%/-54%/21%
% AC Size Discrepancy: The % difference between the capacity of the installed cooling equipment and the calculated amount needed from an energy modeling software.
Square Feet per kBtu per hour of Heating Installed: 95/13/31
SF/kBtu Heating: The number of square feet of the home divided by installed OUTPUT capacity of the heating equipment.
% Heating Installed Compared to Amount Actually Needed in Home: 157%/-47%/34%
% Heating Size Discrepancy: The % difference between the OUTPUT capacity of the installed heating equipment and the calculated amount needed from an energy modeling software.
Annual kiloWatt hours per Square Foot: 9.39/0.68/4.01
Annual kWh/SF: The actual electrical consumption over a year long period divided by the area of the home.
It should be noted that square footage, installed equipment capacities, and annual kWh are actual measured values, or determined through inspection. The % discrepancy between installed equipment and calculated loads is based off an energy model, so these values have inherent errors in them because of this. Regardless, the results are pretty typical with standard construction – heating and cooling equipment is usually oversized for the needs of a given home (positive % indicates oversized, and negative % indicates undersized).
Lastly, I’d like to point out the variability in annual electrical consumption in relation to home size.
Electrical consumption is largely based on occupant behavior, installed gadgetry, and family size. Typically, the phone calls we’d receive regarding large electrical bills were pretty simply explained by a few big consumers like pool/hot tub heaters, pumps, electric radiant heat, and entertainment systems.
In closing, the information provided here gives you an idea of standard homes in Chicago. I am not a fan of ‘rules of thumb,’ so the above metrics aren’t intended for any form of comparison against new homes. The overall idea is always to engineer a perfect home, install all components to specification, and test them once they are in place. Or as Corbett Lunsford would say it, ‘Control is the goal.”