This blog is the second installment in a short series drawn from our September Energy Leader Webinar: Tips for Getting Buy-In for Your Energy Project. The webinar purpose was simple: to help participants get more projects approved and more energy saved.
Webinar speakers were Steve Heinz, founder and CEO of EnergyCAP, Inc., and Dr. Eric Woodroof, founder and principal of Profitable Green Solutions. Today we’ll share some of the insights we gleaned from Steve’s portion of the presentation.
Steve has been focused on energy management information for the last 40 years, and he’s helped a lot of clients get more value out of their energy data using EnergyCAP software for utility bill management. One of the ways to obtain value from utility bill data is to use that data to get buy-in from management for energy projects.
There are two ways utility bill data can be used to obtain project buy-in—before a project begins, and after a previous project is completed.
Before the project begins—even before it’s been conceived—energy data can be tremendously helpful in identifying inefficient buildings through some sort of benchmarking process.
It could be an internal process that you set up. Suppose you have a chain of box stores and all are similarly staffed with similar merchandise, store hours, even building design. That’s a benchmarking project begging to happen.
You get your utility information into an energy management tracking database like EnergyCAP, and now you are comparing energy data from all 30 locations with weather-normalized calendarized charts and graphs, and you’ve got anomalies leaping off your computer screen.
All sorts of questions can come from data: Why is Building A operating at twice the unit cost of electricity per square foot of Building B? Why is Building T using six times as much water as any other similar facility? And each question suggests a project, and because you are benchmarking, it also suggests the scope of possible savings: “Gee, if I brought Building T in line with water use at other similar facilities, we could save $XXXXX.XX annually.”
This type of benchmarking is organizational benchmarking. It’s internal to your organization, and you determine the benchmarking group members.
But if you have the utility data, you may also be able to use national benchmarking, perhaps with your industry/trade association, or even with a government-sponsored benchmarking initiative like ENERGY STAR.
The value of benchmarking, done either way, is that it can help to increase the confidence of your decision makers that certain buildings are worthy of energy management investments. Your energy data can provide a corroborating piece of information that is confirming project feasibility.
Of course, benchmarking alone is not granular enough to reveal exactly what project should be done in each building, or even what a project is likely to cost. It’s not the purpose of benchmarking to zero in on the fine details. The purpose of benchmarking is to identify which buildings require further scrutiny, and which hold the most promise for valuable returns from your energy management project—whatever you determine it should be.
For instance, within EnergyCAP software, we have built an automated interface that streams customer utility data directly to the ENERGY STAR Portfolio Manager—their online app for obtaining energy efficiency ratings.
If you had to enter your utility data in the app manually, it would take a lot of time and effort. As an ENERGY STAR partner, we can do it for you, and many of our clients use that functionality for national benchmarking. Each month, EnergyCAP can upload the latest set of utility bills to ENERGY STAR. ENERGY STAR will return a 1-100 point building energy efficiency rating based on a comparison with their national database filtered to include buildings that are the most similar to each rated building. And if you can score 75 or above, you can apply for an ENERGY STAR certificate recognizing that achievement. ENERGY STAR is a national benchmark that can provide a corroborating data point to help confirm that a building is operating relatively efficiently or inefficiently based on a national peer comparison.
The key with good benchmarking is to get your building into a good peer group. It doesn’t make any sense to benchmark the energy performance of a high school against an elementary school, or a middle school against a football stadium.
In EnergyCAP, you select a building PRIMARY USE for each building in the system. Then EnergyCAP automatically creates a peer group of buildings based on that database field. Then the software will rank each buildings from worst to best in terms of several metrics, including annualized cost per square foot, for example. In the image below, you can see a vertical bar representing the average value for all of the buildings being benchmarking. This type of visualization makes it very, very obvious which buildings are “above average,” and not in a good way!
As an energy manager, you might look at this peer group of high schools with a knowledgeable eye and supply an answer for the obvious question: Why is one building operating at a cost of nearly $2.00 per square foot per year when the average is only $1.32?
Perhaps it’s an older building. Perhaps it has a history of inefficient operation. Or perhaps the data might be a surprise to you, and suggest a potential energy project.
Suppose you have two buildings that are very similar. They were built in about the same era. They’re occupied about the same hours of the day and of the week. We might expect them to operate with the same efficiency, but suppose that the data reveals that they’re not? What if they are significantly different—about 50 percent higher for the first? You might need to take a look at that. It could be a data problem. It could be an operational problem that can be corrected, or it could be an energy efficiency problem that requires retrofit to equipment.
Another benchmark that many people overlook is peak demand, expressed in watts per square foot. We have found that a typical peer group of buildings will generally be pretty closely packed in terms of demand. In the example below, The average is about 3.5 to 4.0 watts per square foot for peak demand. Peer groups of buildings tend to have the same energy intensity, but in the example below, you see one building that’s almost four times higher than that.
This indicates a real problem with peak demand. And given the long-term impact that demand can have on your energy bill, especially if your rate schedule has a demand ratchet, trimming your peak demand can be a very valuable money saver. We recommend that you look carefully at benchmarking metrics for electricity demand!
Another valuable benchmarking metric that can be determined using utility bill data is weather-related energy use for a building, expressed in BTUs per square foot. Again, you’d expect similar buildings to have roughly the same weather sensitivity. In other words, one cooling degree day, one additional degree above a balance point should cause about the same amount of energy to be consumed in typical buildings, assuming that they’re operated similarly, and construction is relatively the same. So when you see a building that’s an outlier, like this example, it indicates something that requires investigation—a potential energy management project.
As you can see, benchmarking with historical utility bill data can provide valuable direction for energy management project conception and planning.