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Utility bill tracking and analysis is at the center of rigorous energy management practice. Reliable energy management decisions can be made based upon analysis from an effective utility bill tracking system. From your utility bills you can determine:

– whether you are saving energy or increasing your consumption,
– which buildings are using too much energy,
– whether your energy management efforts are succeeding,
– whether there are utility billing or metering errors, and
– when usage or metering anomalies occur (ie. when usage patterns change)

Any energy management program is incomplete if it does not track utility bills. Equally, any energy management program is rendered less effective when its utility tracking system is difficult to use or does not yield valuable information. In either case, fruitful energy savings opportunities are lost.

Many practical energy managers make the smart choice and invest in utility bill tracking software, but then fail to recover their initial investment in energy savings opportunities. How could this be?

This paper introduces three simple and useful procedures that can be performed with utility bill tracking software. Just performing and acting upon the first two types of analysis will likely save you enough money to pay for your utility bill tracking system in the first year. The three topics are Benchmarking, Load Factor Analysis, and Weather Normalization as shown in Table 1.

BENCHMARKING
Let’s suppose you were the new energy manager in charge of a portfolio of school buildings for a district. Due to a lack of resources, you cannot devote your attention to all the schools at the same time. You must select a handful of schools to overhaul. To identify those schools most in need of your attention, one of the first things you might do is find out which schools were using too much energy. A simple comparison of Total Annual Utility Costs spent would identify those buildings that spend the most on energy, but not why.

Benchmarking Different Categories of Buildings
When benchmarking, it is also useful to only compare similar facilities. For example, if you looked at a school district and compared all buildings by $/SQFT, you might find that the technology centers administration buildings were at the top of the list, since administration buildings and technology centers often have more computers and are more energy intensive than elementary schools and preschools. These results are expected and not necessarily useful. For this reason, it might be wise to break your buildings into categories, and then benchmark just one category at a time.

Different Datasets
You can benchmark your buildings against each other (as we did in our example) or against publicly available databases of similar buildings in your area. Energy Star’s Portfolio Manager allows you to compare your buildings against others in your region. Perhaps those buildings in your portfolios that looked the most wasteful are still in the top 50th percentile of all similar buildings in your area. This would be useful to know.