by: John Avina, June 8, 2009
ABSTRACT
Utility Bill Tracking systems are at the center of an effective energy management program. However, some organizations spend time and money putting together a utility bill tracking system and never reap any value. This paper presents three utility bill analysis techniques which energy managers can use to arrive at sound energy management decisions and achieve cost savings.
INTRODUCTION
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.
As seen in Figure 1, Santa Rosa Elementary School (ES), San Simeon ES and San Gabriel ES cost the most to operate, while San Luis Obispo ES and Creston ES cost the least. But these three schools may not be the best schools to work on first. Most likely the buildings that spend the most on energy are the largest buildings in the portfolio. It would be wiser to find those buildings that spend the most per square foot per year. This process is referred to as benchmarking, and is presented in Figure 2.
Figure 2 shows the same schools, but the costs are divided by square footage (SQFT). Santa Rosa and San Simeon ES are still the best targets, but San Gabriel ES is actually one of the more efficient schools. Instead San Luis Obispo ES is the third most wasteful school on a $/SQFT basis. From this, we can also see that the most inefficient schools cost about 30% more to operate than the most efficient schools.
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.
Occasionally, management decides that their organization needs to save some arbitrary percentage (5%, 10%, etc.) on utility costs each year. Depending upon the goal, this can be quite challenging, if not impossible. Energy managers can use benchmarking to guide management in setting realistic energy management goals, as shown in Figure 3. For example, our school district energy manager might decide to create a goal that the three most energy consuming schools use only $0.80/SQFT. Since this is about as much as the lowest energy consuming schools are currently using, this could be an attainable goal.
If you can find a dataset, you may also be able to benchmark your buildings against a set of similar buildings in your area and see the range of possibilities for your buildings. In any case, benchmarking will focus your energy management efforts and provide realistic goals for the future.
Rules of Thumb
New energy managers often search for a “rule of thumb” to use for benchmarking. An example could be: “If your building uses more than $2/SQFT/Year then you have a problem.” Unfortunately, this won’t work. Different types of buildings have different energy intensities. Moreover, different building locations will require differing amounts of energy for heating and cooling. In San Francisco, where temperatures are consistently in the 60s, there is almost no cooling requirement for many building types; whereas in Miami, buildings will almost always require cooling. Different building types, with their characteristic energy intensities, different weather sites, and different utility rates all combine to make it hard to have rules of thumb for benchmarking. However, energy managers whose portfolios are all close by, can develop their own rules of thumb. These rules will most likely not be transferable to other energy managers in different locations, with different building types, or using different utility configurations.
Benchmarking Buildings in Different Locations
There are some complications associated with benchmarking. Suppose you were the energy manager of a chain store, and you had buildings in different national locations. Then benchmarking might not be useful in the same sense. Would it be fair to compare a San Diego store to a Chicago store, when it is always the right temperature outside in San Diego, and always too hot or too cold in Chicago? The Chicago store will constantly be heating or cooling, while the San Diego store might not have many heating or cooling needs. Comparing at $/SQFT might help decide which store locations are most expensive to operate due to high utility rates and different heating and cooling needs.
Some energy analysts benchmark using kBtu/SQFT to remove the effect of utility rates (replacing $ with kBtu). Some will take it a step further using kBtu/SQFT/HDD to remove the effect of weather (adding HDD), but adding HDD (or CDD) is not a fair measurement, as it assumes that all usage is associated with heating. This measurement also does not take into account cooling (or heating) needs. Many thoughtful energy managers shy away from benchmarking that involves CDD or HDD.
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June 14th, 2011 
