Week 7: Analyzing Building Performance
1) Building occupant satisfaction and sustainability are two related areas of design that can often find themselves in direct coordination or conflict. Occupancy satisfaction is often linked to comfort and amenities and these can be shared with sustainability. For example, natural light is considered a positive for occupant satisfaction as it has been proven that natural light can contribute to human happiness. Natural light is also a positive in the building field, as it can help aid in passively heating a building.
Water usage comes to mind on the opposite end of the spectrum. For example, low flow fixtures, such as shower heads are great for water conservation. However, I think you would be hard pressed to find a large percentage of people that would prefer a low flow/low pressure head over a standard shower head. Another loosely related example would be that of air conditioning in cars. On a 70 degree day, the vast majority of drivers I would conjecture still rely on air conditioning as opposed to passively cool the car by opening their window. In this case occupant satisfaction is winning out over sustainability.
2) Benchmarks and targets are critical for analyzing actual building performance data because traditional goal setting for new buildings typically focuses on using a percentage less energy than the current codes or standards. It can be problematic as it only addresses a fraction of the energy-using systems in the building and is based upon assumptions about building usage without taking into account actual operating conditions and building management practices.
3) Some of the limitations of traditional energy models when it comes to predicting actual building performance includes:
Water usage comes to mind on the opposite end of the spectrum. For example, low flow fixtures, such as shower heads are great for water conservation. However, I think you would be hard pressed to find a large percentage of people that would prefer a low flow/low pressure head over a standard shower head. Another loosely related example would be that of air conditioning in cars. On a 70 degree day, the vast majority of drivers I would conjecture still rely on air conditioning as opposed to passively cool the car by opening their window. In this case occupant satisfaction is winning out over sustainability.
2) Benchmarks and targets are critical for analyzing actual building performance data because traditional goal setting for new buildings typically focuses on using a percentage less energy than the current codes or standards. It can be problematic as it only addresses a fraction of the energy-using systems in the building and is based upon assumptions about building usage without taking into account actual operating conditions and building management practices.
3) Some of the limitations of traditional energy models when it comes to predicting actual building performance includes:
- codes and standards only address a fraction of energy-using systems in the building
- models are only as good as the assumptions about operating conditions are, which many times can be largely inaccurate
- Sub-systems left out - ie. "plug" loads
- does not take into account specialty equipment tailored to the site or building
In conclusion, it seems there is a lack of industry knowledge/data to be used when creating models. This lack of data speaks more to the fact that the solution is not one-size fits all and not to a lack of effort. For example two identical university biology labs, one in Arizona and one in Maine will have very different energy usage profiles. This raises the questions about how best to categorize the information and use it in an effective manner. Variables like climate, weather, materials, usage, hours of operation, etc., combined with the fact that technology is changing quite rapidly lead to difficulty in standardizing information and providing conclusive results.
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