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Downsizing Lab Energy Systems

Downsizing Lab Energy Systems

HVAC and piped-utility systems in labs can be as much as 300% too big. Here's how to cut them down to size.


By By Jeff Yoders, Associate Editor | August 11, 2010
This article first appeared in the 200603 issue of BD+C.

Laboratories are the third-most energy-intensive building type. A single fume hood can consume as much energy as three single-family homes. But different types of labs can exhibit wide variations in energy needs, which often discourage designers from trying to make their laboratories energy efficient.

Moreover, many lab designers use either estimates based on rated data, or design benchmarks from prior projects. Consequently, peak equipment loads are frequently overestimated by anywhere from 40 to 300%, according to a Syska Hennessy Group study.

"There has to be a way of looking at this and analyzing it with some mathematics that makes sense," said John "Jay" Martin, PE, a design engineer in the San Diego office of Syska Hennessy.

"When it comes to planning and sizing HVAC and piped-utility systems, the current methods are no better than guesses," said Martin, who has overseen hundreds of laboratory projects in his more than 30 years as a mechanical engineer.

One source of error is benchmarking databases. These are collections of heat gain values categorized by laboratory space type over a number of different projects or project types, as compiled by laboratory consultants and programmers. These numbers are used to size new laboratory HVAC systems. In a 2004 study, Martin estimated the cost of over-sizing HVAC systems due to benchmarking was at least $7.50/sf, possibly double or triple that.

"The problem lies in the fact that the calculation of the heat gain generated in any laboratory space by these databases is extremely flawed," said Martin.

Benchmarking frequently results in oversized HVAC systems because the databases use peak demand data—and assume that all systems will be used simultaneously in the laboratory. The engineers then guess at a value higher than the quoted average of the peak demand numbers that will satisfy the spaces with the highest heat gain. This leads to a situation where laboratory spaces that don't need maximum ventilation and conditioning are being designed for the peak load.

One promising method to help fight oversizing lab systems is probability-based analysis, or PBA.

PBA derives diversity factors of space loads, rather than maximum peak loads, using the centuries-old mathematic application of probability. "PBA is actually hundreds of years old," Martin explained. "This is really nothing new."

More than 70 years ago, in fact, Dr. Roy B. Hunter used PBA to determine peak water flow demand in plumbing systems. Hunter's curves determined the probability of any of a number of fixtures to demand water at any given time.

PBA does the same thing for laboratory spaces. By using Hunter's equation, engineers can create curves that show the aggregate probability of use for each heat source in a space. PBA and building load measurements can then be used together, providing two reference points for rightsizing.

PBA can calculate the diversity factors of different levels of aggregation—for example, as the number of pieces of lab equipment goes up, so, too, does the number of variables. It has been used in the design of a number of labs, including the new UCLA Life Sciences Center. The extra cost of PBA, according to Martin, is $.50/sf, compared to the average $7.50/sf he estimates current oversizing is costing lab owners.

Metering is another tool being used to rightsize laboratory buildings. UC Riverside measured equipment loads at two of its laboratories in order to use the data as a basis for sizing HVAC systems in the design of new facilities there.

"Metering is certainly a step in the right direction, but the question then becomes, how long are you going to meter?" Martin asked. "What we really need is proven scientific methods to base sizing on, and that's what PBA is."

For more on PBA, read Jay Martin's "A Case for Probability Based Analysis":www.bdcnetwork.com/contents/pdfs/bdc0603PBAWhitepaper.pdf.

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