16.01.2014 Views

Metrics and Benchmarks for Energy Efficiency in Laboratories - I2SL

Metrics and Benchmarks for Energy Efficiency in Laboratories - I2SL

Metrics and Benchmarks for Energy Efficiency in Laboratories - I2SL

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

LABS FOR THE 21ST CENTURY<br />

3<br />

Basel<strong>in</strong>e <strong>for</strong> percentage reduction: There are two commonly<br />

used ways to express percentage reduction:<br />

1. percentage reduction relative to total loads (<strong>in</strong>clud<strong>in</strong>g<br />

process loads)<br />

2. percentage reduction relative to “regulated loads”<br />

(exclud<strong>in</strong>g process loads)<br />

Appendix G of the 2004 version specifies the first<br />

approach (i.e., based on total loads). Earlier versions of<br />

LEED-NC (prior to 2.2) followed the second approach.<br />

This often created confusion about what was <strong>in</strong>cluded or<br />

excluded <strong>in</strong> the percentage calculation, <strong>and</strong> was especially<br />

problematic <strong>in</strong> laboratory build<strong>in</strong>gs. For example, fume<br />

hoods were sometimes <strong>in</strong>cluded because they were part<br />

of the HVAC system, <strong>and</strong> other times excluded because<br />

they were considered a process load. Figure 1 compares<br />

different options <strong>for</strong> calculat<strong>in</strong>g percentage reduction <strong>for</strong><br />

the Science <strong>and</strong> Technology Facility at the National<br />

Renewable <strong>Energy</strong> Laboratory, which received a LEED-<br />

NC Plat<strong>in</strong>um rat<strong>in</strong>g. The difference between the options<br />

underscores the need to clearly def<strong>in</strong>e how it is calculated<br />

<strong>and</strong> compared with other facilities.<br />

While percentage reduction of total load is the primary<br />

metric that should be used, it is also useful to track percentage<br />

reduction of regulated loads, s<strong>in</strong>ce it provides a<br />

measure of the efficiency of features that designers have<br />

significant control over. This is particularly true <strong>in</strong> laboratories,<br />

where process loads can vary significantly across<br />

different projects <strong>and</strong> design estimates are often grossly<br />

<strong>in</strong>accurate.<br />

Annual <strong>Energy</strong> Consumption (kBtu/sf)<br />

100<br />

50<br />

0<br />

Sav<strong>in</strong>gs %<br />

Sav<strong>in</strong>gs<br />

Electricity<br />

Gas<br />

400<br />

350<br />

300<br />

250<br />

200<br />

150<br />

Budget<br />

Model<br />

(90.1-1999<br />

ECB)<br />

0<br />

80<br />

204<br />

58%<br />

Proposed<br />

Model<br />

(90.1-1999<br />

ECB) &<br />

Sav<strong>in</strong>gs<br />

58%<br />

164<br />

70<br />

50<br />

Budget<br />

Model<br />

(Labs21<br />

1999<br />

ECB)<br />

0<br />

87<br />

222<br />

61%<br />

Proposed<br />

Model<br />

(90.1-1999<br />

ECB) &<br />

Sav<strong>in</strong>gs<br />

61%<br />

188<br />

70<br />

50<br />

Basel<strong>in</strong>e<br />

Model<br />

(90.1-2004<br />

App. G)<br />

0<br />

128<br />

233<br />

45%<br />

Proposed<br />

Model<br />

(90.1-2004<br />

App. G) &<br />

Sav<strong>in</strong>gs<br />

Figure 1. Different options to calculate percentage<br />

reduction—results <strong>for</strong> the Science <strong>and</strong> Technology<br />

Facility at the National Renewable <strong>Energy</strong> Laboratory.<br />

Source: NREL/AEC.<br />

45%<br />

161<br />

150<br />

50<br />

Metric <strong>for</strong> percentage reduction: ASHRAE 90.1 requires<br />

that energy cost be used as the metric <strong>for</strong> calculat<strong>in</strong>g percentage<br />

reduction. EPACT 2005, on the other h<strong>and</strong>, uses site<br />

energy as the metric <strong>for</strong> sav<strong>in</strong>gs calculation. The percentage<br />

reduction <strong>for</strong> site energy, source energy, <strong>and</strong> cost will be different<br />

depend<strong>in</strong>g on the rate structure <strong>and</strong> fuel mix. If projects<br />

seek to set <strong>and</strong> track energy <strong>and</strong> emissions goals, it is<br />

important to track percentage reduction results us<strong>in</strong>g both<br />

cost <strong>and</strong> source energy metrics. (This is a m<strong>in</strong>imal additional<br />

burden s<strong>in</strong>ce most energy model<strong>in</strong>g tools provide both<br />

metrics <strong>in</strong> their output.) Traditionally, energy cost has<br />

served as a reasonably good proxy <strong>for</strong> source energy.<br />

However, recent <strong>and</strong> anticipated volatility <strong>in</strong> the natural gas<br />

<strong>and</strong> electricity markets may make this assumption <strong>in</strong>valid.<br />

Model<strong>in</strong>g assumptions sensitivity analysis: <strong>Energy</strong><br />

model<strong>in</strong>g always requires mak<strong>in</strong>g a host of assumptions,<br />

either because some parameters are unknown, or because<br />

the model<strong>in</strong>g tool does not directly support certa<strong>in</strong> build<strong>in</strong>g<br />

features. As a result, many build<strong>in</strong>g owners <strong>and</strong><br />

designers are concerned about the validity of model<strong>in</strong>g<br />

results. The follow<strong>in</strong>g recommendations can help to mitigate<br />

this issue:<br />

• Select experienced modelers: <strong>Energy</strong> model<strong>in</strong>g is a<br />

highly specialized skill, <strong>and</strong> owners <strong>and</strong> designers<br />

should select modelers that have experience with<br />

laboratories.<br />

• Underst<strong>and</strong> key assumptions: Modelers should<br />

document the key assumptions <strong>and</strong> review them<br />

with designers to ensure that they are valid.<br />

• Test the sensitivity of key assumptions: Modelers<br />

should run parametric variations on the key<br />

assumptions <strong>and</strong> document the sensitivity of the<br />

results to variations <strong>in</strong> the assumptions.<br />

2.2 <strong>Metrics</strong> based on empirical per<strong>for</strong>mance<br />

While metrics based on ASHRAE 90.1 are useful <strong>for</strong><br />

explor<strong>in</strong>g design alternatives, many owners <strong>and</strong> designers<br />

are uncom<strong>for</strong>table with the wide variability <strong>in</strong> model<strong>in</strong>g<br />

results. Some projects are now look<strong>in</strong>g to def<strong>in</strong>e an<br />

explicit energy use target that the design should meet—<br />

which also serves as a reality check <strong>for</strong> the modeled<br />

results. In the case of office build<strong>in</strong>gs, <strong>for</strong> example, owners<br />

can specify that they should be designed to earn an<br />

<strong>Energy</strong> Star label. However, <strong>Energy</strong> Star does not have a<br />

comparable rat<strong>in</strong>g system <strong>for</strong> laboratories. For labs, there<br />

are two options <strong>for</strong> sett<strong>in</strong>g a target:<br />

• For organizations that have energy use data on<br />

a portfolio of laboratory build<strong>in</strong>gs, targets could<br />

be set based on the range of energy use <strong>in</strong>tensity<br />

across the portfolio.

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!