When it comes to energy use, how does your facility stack up against comparable firms subject to the same general climate?

That question is often the first heard from facility managers and operators when they wonder how to control utility costs. This column has covered some sophisticated energy issues over the last four years, and it's time to take a few steps back to focus on some of the basics, one of which is benchmarking energy usage.

Benchmarking 101

Benchmarking does not show how much energy could be saved. Instead, it provides an indication of how different a facility's energy usage may be from the average of others like it. It may, however, provide a hint that savings may be possible by changing a facility's systems and/or operations.

It's often difficult to compare one building to another, even in the same city. While some general guidelines are available, their use may be limited due to variety of factors, such as operating hours, unusual HVAC equipment (e.g., thermal storage), and energy-intensive systems not related to building operations (e.g., data centers, trading floors). Merely upgrading lighting and adding VSDs on fans could reduce electrical usage by 20% to 30%, relative to an identical structure that has not done so. With that realization in mind, what information is available to at least show where we rank next to similar facilities?

Benchmarking Resources

At one end of the data spectrum are private databases of energy use (e.g., Jackson Associates,www.maisy.com) containing both basic and sophisticated energy use data (e.g., hourly load profiles) for a variety of building types. At the other end, are simplified surveys such as BOMA's Experience Exchange Report (clickhere). The latter provides the cost per square foot for different types of utilities used by commercial real estate buildings in many cities.

In between are several government-sponsored options, including the Commercial Building Energy Consumption Survey (CBECS). CBECS is one of the better no-cost databases, although one must be sure to make appropriate weather corrections, the process for which is outlined in the documentation. Find it at www.eia.doe.gov/emeu/cbecs/contents.html.

Practical experience using CBECS indicates that it tends to underestimate energy intensity (e.g., kWh/sq ft/yr, Btu/sq ft/yr) for some building types (e.g., colleges) while overestimating it when its sample is much smaller (e.g., laboratories). Fortunately, it also provides useful statistical qualifiers (e.g., standard deviations) that provide a range around the single numbers found in its columns. Its data is based on a combination of extensive surveys and computer simulations performed by the DOE.

Another "free" option (i.e., supported by your taxes) is the Energy Star Portfolio Manager (PM). Developed over several years by the EPA, it is designed to encourage energy conservation (and thus lower fossil fuel emissions). Via a webpage, the PM process allows a building operator to enter information regarding energy use and the building's operations. Using data from several benchmarking sources, the PM will then provide a score that shows where the facility ranks relative to similar (but energy-efficient) facilities. Find it at www.energystar.gov/index.cfm?c=evaluate_performance.bus_portfoliomanager.

PM has been evolving over the past few years to include more building types and greater latitude in describing buildings (e.g., percent of area used as a data center). While working relatively well for simple buildings (e.g., K-12 schools), it may run into trouble when assessing the usage of new buildings constructed under more stringent energy and health codes (e.g., outside air requirements) than most existing buildings, the bulk of which were erected before the first energy crisis in 1973.

The ideal benchmark for most buildings is a good computer simulation that takes into account existing systems, operating hours, internal equipment, etc., at a given facility. It calculates energy use if everything was working as expected. The difference from actual usage may reveal problems and opportunities for cutting energy costs. Once completed, such a model is also very handy toward determining savings if one or more systems or operating parameters were to change. A variety of such models exist, ranging from very detailed programs (such as DOE-2) to Carrier Corporation's venerable Hourly Analysis Program (HAP). For several DOE-sponsored options, go to www.eere.energy.gov/buildings/energy_tools-/doe_tools.html.

Before going down the computer simulation path, it is advisable to understand the limits and opportunities of such efforts. The best book on the subject is Jim Walt's Computerized Building Energy Simulation Handbook (available at www.aeecenter.org/books/). ES