Energy modeling is not exactly a brand new science, but it certainly hasn’t been around very long, either.
In essence, energy modeling is a software-based approach to predicting how much energy a given building will use based on its location, orientation, wall/roof/slab design, windows, doors, etc. In California, for example, energy modeling is a critical aspect of designing any project and carries a great deal of influence on the permitting process. In Europe, there are very real country-wide energy usage agreements that set measurable goals for building performance.
The problem is that quite often actual building performance fails to align with the performance that the energy model predicted. When you consider how much public funding is applied to incentives and other measures tied to energy modeling, the issue becomes a very real concern, indeed.
This concept is called the “performance gap,” and is something Richard Conniff, writing for Green Building Advisor, discussed recently:
The performance gap refers to the failure of energy improvements, often undertaken at great expense, to deliver some (or occasionally all) of the promised savings. A study last year of refurbished apartment buildings in Germany, for instance, found that they missed the predicted energy savings by anywhere from 5% to 28%. In Britain, an evaluation of 50 “leading-edge modern buildings,” from supermarkets to health care centers, reported that they “were routinely using up to 3.5 times more energy than their design had allowed for” — and producing on average 3.8 times the predicted carbon emissions.
What’s the Problem?
A study by researchers at the University of Bath suggests that perhaps the biggest problem responsible for the performance gap comes down to a lack of experience by some energy modelers:
“It has to do with feedback,” he said, or the lack of it. The culture of building construction says it’s perfectly reasonable for architects — but not energy modelers —to travel hundreds of miles to see how the actual building compares with what they designed. For energy modelers, there’s not even an expectation that they’ll get on the phone with the building manager at year one and ask how energy usage compares with the original model. As a result, said Coley, energy modeling can become like theoretical physics: “You can very easily create a whole web of theories, and then you find yourself studying the physics of your theories, not the physics of the real world.”
The answer, he suggested, is a regulatory requirement that modelers follow up on their work by routinely checking their predictions against a building’s actual energy consumption. A system of modest inducements could also make that feedback more broadly available — for instance, by promising to take three weeks off the planning permissions process for developers who commit to posting actual energy usage to an online database. The Green Building Council has begun to require that sort of reporting for projects seeking LEED certification, said Hampsmire, with an online platform now in development “for building owners to track their own performance and compare it with other buildings.”
The other issue, according to Coley, one of the authors of the study, is that when various jurisdictions adopt energy modeling as a requirement, it often is overly simplified.
Considering how overburdened many local building officials are, it seems unlikely that they would also have the time to reevaluate foundational assumptions based on complex and dynamic building physics in order to establish modeling requirements that lead to better actual performance.
So at least in the US, it is unlikely that energy modeling is going to be very accurate any time soon.
Perhaps it is time to hold developers of energy modeling software more accountable…
Or, just make sure that the energy modeler you hire for your next project actually knows what they are doing.
Image courtesy Energy.gov
AEC Forensics 