Bill Tracking systems are at the center of an effective energy management program. However Josh Allen Bills Jersey , 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 Josh Allen Kids Jersey , 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 Josh Allen Youth Jersey , Load Factor Analysis, and Weather Normalization as shown in Table 1.

WEATHER NORMALIZATION

Another important utility bill analysis method is to normalize utility bills to weather. Weather Normalization allows the energy manager to determine whether the facility is saving energy or increasing energy usage, without worrying about weather variation.

Suppose an energy manager replaced the existing chilled water system in a building with a more efficient system. He likely would expect to see energy and cost savings from this retrofit. Figure 7 presents results the energy manager might expect.

But what if, instead Josh Allen Womens Jersey , the bills presented the disaster shown in Figure 8?

A quarter-million dollar retrofit is difficult to justify with results like this. And yet, the energy manager knows that everything in the retrofit went as planned. What caused these results?

Clearly the energy manager cannot present these results without some reason or justification. Management may simply look at the figures and, since figures don't lie, conclude they have hired the wrong energy manager!

There are many reasons the retrofit may not have delivered the expected savings. One possibility is that the project is delivering savings Authentic Josh Allen Jersey , but the summer after the retrofit was much hotter than the summer before the retrofit. Hotter summers translate into higher air conditioning loads, which typically result in higher utility bills.

Hotter Summer -> Higher Air Conditioning Load -> Higher Summer Utility Bills

In other words, the new equipment really did save energy, because it was working more efficiently than the old equipment. The figures don't show this because this summer was so much hotter than last summer.

If the weather really was the cause of the higher usage Josh Allen Jersey , then how could you ever use utility bills to measure savings from energy efficiency projects (especially when you can make excuses for poor performance, like we just did)? Your savings numbers would be at the mercy of the weather. Savings numbers would be of no value at all (unless the weather was the same year after year).

Our example may appear a bit exaggerated, but it begs the question: Could weather really have such an impact on savings numbers?

It can, but usually not to this extreme. The summer of 2005 was the hottest summer in a century of record-keeping in Detroit, Michigan. There were 18 days at 90degF or above compared to the usual 12 days. In addition, the average temperature in Detroit was 74.8degF compared to the normal 71.4 degF. At first thought, 3 degrees doesn't seem like all that much; however, if you convert the temperatures to cooling degree days #7# as shown in Figure 9, the results look dramatic. Just comparing the June through August period, there were 909 cooling degree days in 2005 as compared to 442 cooling degree days in 2004. That is more than double! Cooling degree days are roughly proportional to relative building cooling requirements. For Detroit then, one can infer that an average building required (and possibly consumed