Last week, in the course of beginning a retrocommissioning process on a lab facility, I came across a bit of an anomaly and in the course of exploring it, discovered some useful resources. So, I thought I would share both with you in the next few posts.
The facility in question is a nominal 38,000 square foot lab facility on the Oregon Coast that was constructed in the mid 1980′s. Recently, the facility had undergone a partial renovation of its mechanical systems to replace existing aging machinery and improve efficiency.
Much to the Owner’s dismay, the site energy consumption in terms of btus increased rather than decreased as a result of the effort, as did the utility cost. To get a feel for the performance of the facility relative to its peers, I decided to benchmark it using two different publicly available benchmarking tools that include lab facilities in their data base.
Benchmarking provides a first pass, big picture contrast of a buildings energy performance relative to its peers. In their simplest form, benchmarking tools take a few fundamental inputs like total annual energy consumption and building square footage and generate some sort of energy intensity index like kilo-btus per square foot and then contrast that index with similar facilities. More sophisticated tools endeavor to normalize factors like occupancy, function, and climate to create a more meaningful contrast.
The first tool I utilized was the ORNL benchmarking tool, the results of which are presented below.
This benchmark is based on source energy; i.e. the energy that goes into the power plant vs. site energy. Based on the most recent utility data available, the Newport, Oregon facility has an Energy Use Intensity (EUI) of 629 kBtu/sf, as indicated by the red vertical dotted line in Figure 1. This places it at the low end of the national spectrum with approximately 72% of the facilities cataloged in the data base being more efficient.
Because the ORNL benchmarking tool is an older database and only contains labs contrasted on a nationwide basis, I also benchmarked the project facility against the Labs21 database, which is more recently developed and also allows buildings to be contrasted by climate zone and in terms of a number of different parameters such as electrical energy only, total site energy, cooling system energy, etc. The results of this benchmarking effort are depicted next both graphically and in a summary table. (Note that the red dotted lines indicate the project facilities rating relative to the left vertical axis on the graphs).
As can be seen from the table, the project facility benchmarks very favorably in terms of total energy consumption but is more in line with the median consumption figures when electrical energy is considered. I interpreted these results to indicate that conservation and optimization efforts focused on electrical targets will yield the biggest over-all improvements in efficiency.
There are at least two other benchmarking tools that can be accessed publicly. Energy Star allows the user to rate their building against similar facilities and paves the way for receiving an Energy Star rating. But it does not include a specific category for laboratory facilities, which is why I did not use it for my current project.
CalARCH is a benchmarking tool that was developed for the California building stock. It is very quick and easy to use and a good way to check a building in that region against its peers.
In the next post, I’ll take a look at the average daily consumption data and the clues it provided.
Senior Engineer – Facility Dynamics Engineering