The computation is a good starting point but it is unclear how to apply it as a decision tool. There are too many unknowns. I am not disputing the usefulness of your computation, just sharing our experience while researching our own purchase. A limited set of generalized data is a good starting point but being limited and being generalized makes the data less useful for making specific decision.

The efficiency, sizing and implementation of the cooling and heating systems are unknown. The insulation value of the home (wall, ceiling, floor) is unknown. The angle of the home in relation to seasonal sun angle is unknown. The seasonal strike angle of the sun on various windows is unknown. The amount of shade, reflective and absorbent surfaces is unknown. The local climate is unknown. The color of the house and roof is unknown. There are several more.

Six years ago while doing our research, I went through the same process as you did. Thankfully, we had time to add applicable details specific to our house and its microclimate. After identifying the unknowns, we were able to refine our analysis to be much more realistic.

For example, we live in an area that is considered "mild" by CA standard. Summer fog, winter warmth. Someone at NOAA or NWS using regional data decided to draw the zone boundary in that manner. It is wrong. Our microclimate is mostly intensely hot summer with some fog and our winter can have nasty pelting hail stones and snow or often wind-driven rain and gusts to 45-MPH. None of that fits the definition of "mild". It can get downright cold here by CA coastal standard and downright oven-hot by the same standard. UNless we apply our local parameters to the analysis, we would have made the wrong choices.

The singular focus on windows ROI is also insufficient. Efficiency often involves integration of various components such as AC/Heating solutions, insulation and even landscaping. It may also involve the type of windows we select.

An example is our older AC and heating system. It was extremely inefficient and could not keep up with the normal heat and cold of our microclimate. It was not the energy cost that drove us to replace our windows, it was the incredible indoor heat and cold due to such inefficiency. Low-E and Argon took care of the seasonal norm and increased our comfort level instantly. Unfortunately, we still had to deal with seasonal extremes. Thankfully, instead of having to replace with a more expensive AC and heating unit, we switched to zoned radiant heat and whole-house natural cooling. These lower cost but highly efficient solutions were possible because of windows with Low-E and Argon. So understanding of our local climate helped us select a better solution set that integrated windows with radiant heat and natural cooling.

As part of our natural cooling system, we use Casement windows at strategic locations to direct cool breezes into the house. On hot summer days, cold night air accumulates indoor overnight to further reduce our needs to run our AC during the day.

In conclusion, I will suggest taking a systemwide approach by including meaningful specific factors in the computation and then examine whether window type and other non-window components can be effective partners in reducing energy needs, increasing comfort level and hopefully, save a few dollars each month. Just focusing on low-e and argon is insufficient.

Respectfully,
Cal.

swampwiz,

Think of your home as a set of interconnecting elements that function in harmony (or not in some cases) to give you the environment that you desire.

While there is certainly value in looking at the different elements individually, as Calbay noted in his post, and I agree, "...it is unclear how to apply it as a decision tool. There are too many unknowns."

Also, I would suggest that since your premise is window performance, starting out by discussing "constant: BTU = .00024 KW-hr", "cost for power:", Coefficient Of Performance of an air source heat pump, etc. detracts from the basic idea of measuring or comparing window performance. These are variables that don't directly affect window performance, at least not as I read your intent.

I am not suggesting that you don't need that additional information, but I am suggesting that you need to establish a baseline (in this case basic window performance) before you begin adding variables that are affected by, or affect that baseline. In your post you added variation, including at least one unsupported assumption, before you introduced measured or calculated window performance.

In your post you suggested comparing a 10 sqft window with U-factor variations of .5, .3. and .25.

The formula for calculating Btu from U value is Btu = U x # hours x ft² x Delta T (temperature difference - which I am going to assume 50° for these examples).

So, if Btu = .50 x 1 hr x 10 ft² x 50°
then Btu = 250

If Btu = .30 x 1 hr x 10 ft² x 50°
Btu = 150
and
If Btu = .25 x 1 hr x 10 ft² x 50°
Btu = 125

These are really simple examples of the difference in Btu loss and window performance rating, it is possible to interpolate the value of improved performance when our only variable (so far) is the U-value (or U-factor) difference which is based on clear/clear (.050), clear/LowE (.030), clear/argon/LowE (.025).

But your house isn't confined to windows. It has walls and things as well.

Assuming for the sake of simple math that a house has 1000 sqft of exposed wall (125 linear feet x 8') and that 15% of the wall area is windows - we can calculate overall wall performance by changing window performance.

By definition, while R-value defines thermal resistance of a material, U-value measures thermal transfer thru a material.

The formula for computing U-value is: Btu / (hr x degrees F x sqft)

and the formula for computing R-value is: (hr x degrees F x sqft) / Btu

and the formula for computing heat transfer is: (BTU/hr) = (area / R) * ÄT

With ÄT again representing the temperature difference between what is inside and what is outside the house.

Using the formula U=1/R, we can convert U.50 to R2, U.30 to R3.33, and U.25 to R4.

However, this time we will assume a less severe environment so that ÄT = 25°

If ÄT = 25°, then (10 sqft / R 2) = 5 * 25° = 125 BTU/hr loss or gain
If ÄT = 25°, then (10 sqft / R 3.33) = 3 * 25° = 75 BTU/hr
If ÄT = 25°, then (10 sqft / R 4) = 2.5 * 25° = 62.5 BTU/hr

Keeping in mind that the Btu losses or gains are based on one square foot for one hour and the example has 150 square feet if windows. Combined they equal:

125 Btu x 150 sqft = 18750 Btu
75 Btu x 150 sqft = 11250 Btu
62.5 Btu x 150 sqft = 9375 Btu

I am also assuming a typical 2x4 wall with R-13 fiberglass insulation. The overall wall insulation value excluding windows will calculate out to a bit below R-10, but I am also assuming R-10 for simplicity (and laziness on my part).

Wall = R10 or U.1
Window = U.5
Window = 15% of wall
Wall area = 850 sqft and window area = 150 sqft
Wall = 850 sqft x U.1 = 85
Window = 150 sqft x U.50 = 75
85 + 75 = 160/1000sqft = U.16 or overall wall R value including windows of 6.25.

Wall = R10 or U.1
Window = U.3
Window = 15% of wall
Wall area = 850 sqft and window area = 150 sqft
Wall = 850 sqft x U.1 = 85
Window = 150 sqft x U.30 = 50
85 + 50 = 135/1000sqft = U.135 or overall wall R value including windows of 7.41.
Wall = R10 or U.1
Window = U.25
Window = 15% of wall
Wall area = 850 sqft and window area = 150 sqft
Wall = 850 sqft x U.1 = 85
Window = 150 sqft x U.25 = 37.5
85 + 37.5 = 122.5/1000sqft = U.123 or overall wall R value including windows of 8.1.

And assuming that I didnt make any errors in my arithmetic,

Improving window performance from U.5 to U.3 results in an overall wall performance improvement of 18.56% in this example

Improving window performance from U.3 to U.25 results in an overall wall performance improvement of 9.31% in this example

And improving window performance from U.5 to U.25 results in an overall wall performance improvement of 28.46% in this example

And finally, in my opinion, now would be time to begin discussing "constant: BTU = .00024 KW-hr", "cost for power:", Coefficient Of Performance of an air source heat pump, and any other variables that are affected by window performance rather versus effect window performance.

And as a final, final aside, Btu actually = .0002931 Kwh, and there are large portions of the country, primarily California and New York and parts of New England, that have already exceeded the $.12 Kwh.