The biggest errors occur in modeling estimates of energy use in older homes; usually post-retrofit energy use is pretty close to modeled estimates, but pre-retrofit use is dramatically overestimated because of poor assumptions, biased inputs, and bad algorithms.”
Poor assumptions. Models and auditors underestimate the efficiency of existing heating equipment, they often assume 60% efficiency for old furnaces.
Low R-value estimates for existing walls (R-3.5) and attics. Many defaults are biased; they assume R-3.5 for an old wall when many old walls actually perform at R-5 or R-6. Energy models often underestimate the effects of a high framing factor, thick sheathing, and multiple layers of old siding, all of which impr
ove a wall’s R-value.
Low R-value estimates for existing single-pane windows. We assume that old single-pane windows are R-1, when they are probably closer to R-1.35 or R-1.4. When calculating the outside surface film coefficient, they assume worst-case conditions — in other words, that the wind is always blowing away heat from the window. They do it that way because the design load is always calculated for the coldest, windiest day of the year (even though the coldest day usually isn’t windy). If an auditor calculates single-pane windows at R-1, he’s assuming that the wind is blowing continuously nonstop all winter long. But in a real house, the wind speed is often close to zero up against the window.
Low or absent estimates for thermal regain. Energy models underestimate thermal regain from basements and crawlspaces. Most models get big things wrong, like how basements and crawlspaces work. Vented crawl spaces usually aren’t at the outdoor temperature. When the outdoor temperature is 10 degrees, a vented crawl space can be at 50 degrees. Why is it that when we insulate a basement ceiling, we get minimal savings — maybe zero savings, or maybe $20 a year?
Well, if you have a furnace and ductwork in the basement, you are regaining a lot of the heat given off by the furnace and ducts, due to the directional nature of air leakage in the wintertime. The stack effect brings basement air upstairs. The basement is pretty warm, so the air leaking into the house is warmer than the models predict. A similar effect happens in attics: because of the stack effect, most of the air leaving the house leaves through the attic. In a leaky house, you might have 200 cfm of air flow being dumped into the attic. That makes the attic warmer than the models predict. If the attic is 50 degrees, the heat loss through the ceiling insulation is less than the model assumes.
Also check for foundation heat loss, infiltration, wall heat loss, attic heat loss, framing factors, edge effects, window heat loss, window heat gain, exterior shading, interior shading, the effect of insect screens, air films, HVAC equipment performance, duct efficiency and regain, AC refrigerant charge, and air flows over HVAC coils. There are many unknowns: soil conductivity and ground temperatures are unknown. Wind speed is unknown. Leak locations are unknown.
Experience says that better results can be predicated by asking the right set of questions, than running complex computer models.
(the questions posed above are by no means exclusive, comments from readers of this blog are appreciated)