An Example Energy Accounting System

General Motors Corporation has a strong energy accounting system which uses an energy responsibility method. According to General Motors, a good energy accounting system is implemented in three phases: (1) design and installation of accurate metering, (2) development of an energy budget, and (3) publication of regular performance reports including variances. Each phase is an important element of the complete system.

1.6.3.1 The GM system

Phase 1—Metering. For execution of a successful energy accounting program, energy flow must be measured by cost center. The designing of cost center boundaries requires care; the cost centers must not be too large or too small. However, the primary design criterion is how much energy is involved. For example, a bank of large electric induction heat-treating furnaces might need separate metering even if the area involved is relatively small, but a large assembly area with only a few energy-consuming devices may require only one meter. Flexibility is important since a cost center that is too small today may not be too small tomorrow as energy costs change.

The choice of meters is also important. Meters should be accurate, rugged, and cost effective. They should have a good turndown ratio; a turndown ratio is defined as the ability to measure accurately over the entire range of energy flow involved.

Having the meters is not enough. A system must be designed to gather and record the data in a useful form. Meters can be read manually, they can record information on charts for permanent records, and/ or they can be interfaced with microcomputers for real-time reporting and control. Many energy accounting systems fail because the data collection system is not adequately designed or utilized.

Phase 2—Energy Budget. The unique and perhaps vital aspect of General Motors' approach is the development of an energy budget. The GM energy responsibility accounting system is somewhere between levels 3

and 4 of Figure 1-11. If a budget is determined through engineering models, then it is a standard cost system and it is at level 4. There are two ways to develop the energy budget: statistical manipulation of historical data or utilization of engineering models.

The Statistical Model. Using historical data, the statistical model shows how much energy was utilized and how it compared to the standard year(s), but it does not show how efficiently the energy was used. For example, consider the data shown in Table 1-5.

The statistical model assumes that the base years are characteristic of all future years. Consequently, if 1996 produced 600 units with the same square footage and degree days as 1995, 1000 units of energy would be required. If 970 units of energy were used, the difference (30 units) would be due to conservation.

We could use multiple linear regression to develop the parameters for our model, given as follows:

energy forecast= «(production level) + b(ft2) + c(degree days) (1-1)

We can rewrite this in the following form:

where X1= production (units) X3 = weather data (degree days) X2 = floor space (ft2) X4 = energy forecast (Btu)

Degree days are explained in detail in Chapter Two, section 2.1.1.2. Their use provides a simple way to account for the severity of the weather, and thus the amount of energy needed for heating and cooling a facility. Of course, the actual factors included in the model will vary between

Table 1-5 Energy Data for Statistical Modela

1995

1996

1997

Total energy (units)

1,000

1,100

1,050

Production (units)

600

650

650

Square feet

150,000

150,000

170,000

Degree days (heating)

6,750

6,800

6,800

aTaken, in part, from R.P. Greene, (see the Bibliography).

aTaken, in part, from R.P. Greene, (see the Bibliography).

companies and need to be examined carefully.

Multiple linear regression estimates the parameters in the universal regression model in Equation 1-1 from a set of sample data. Using the base years, the procedure estimates values for parameters a, b, and c in Equation 1-1 in order to minimize the squared error where squared error = ^ (X - X4)2

years with X4 = energy forecast by model Xi4 = actual energy usage

The development and execution of this statistical model is beyond the scope of this book. However, regardless of the analytical method used, a statistical model does not determine the amount of energy that ought to be used. It only forecasts consumption based on previous years' data.

The engineering model. The engineering model attempts to remedy the deficiency in the statistical model by developing complete energy balance calculations to determine the amount of energy theoretically required. By using the first law of thermodynamics, energy and mass balances can be completed for any process. The result is the energy required for production. Similarly, HVAC and lighting energy needs could be developed using heat loss equations and other simple calculations. Advantages of the engineering model include improved accuracy and flexibility in reacting to changes in building structures, production schedules, etc. Also, computer programs exist that will calculate the needs for HVAC and lighting.

Phase 3—Performance Reports. The next step is the publication of energy performance reports that compare actual energy consumption with that predicted by the models. The manager of each cost center should be evaluated on his or her performance as shown in these reports. The publication of these reports is the final step in the effort to transfer energy costs from an overhead category to a direct cost or at least to a direct overhead item. One example report is shown in Figure 1-14.

Sometimes more detail on variance is needed. For example, if consumption were shown in dollars, the variation could be shown in dollars and broken into price and consumption variation. Price variation is calculated as the difference between the budget and the actual unit price times the present actual consumption. The remaining variation would be due to

Actual

Budget

Variance

% variance

Department A

Electricity

2000

1500

+500

+33.3%

Natural gas

3000

3300

-300

-9.1%

Steam

3500

3750

-250

-6.7%

Total

8500

8550

-50

-0.6%

Department B

Electricity

1500

1600

-100

-6.2%

Natural gas

2000

2400

-400

-16.7%

Fuel oil

1100

1300

- 200

-15.4%

Coal

3500

3900

- 400

-10.2%

Total

8100

9200

- 1100

- 11.9%

Department C

Figure 1-14 Energy performance report (106Btu)

a change in consumption and would be equal to the change in consumption times the budget price. This is illustrated in Example 1.3. Other categories of variation could include fuel switching, pollution control, and new equipment.

However, had energy consumption not been reduced, the total energy cost would have been:

The total cost avoidance therefore was:

which is the drop in consumption times the actual price or

(2125 - 2000) 4.5 + (6400 - 4808) 3.12 + (2571 - 2242) 4.46 = $6997

This problem of increased energy costs despite energy management savings can arise in a number of ways. Increased production, plant expansion, or increased energy costs can all cause this result.

Example 1.3

The table shown in Figure 1-15 portrays a common problem in energy management reporting. The energy management program in this heat treating department was quite successful. When you examine the totals, you see that the total consumption (at old prices) was reduced by $5631. The total energy cost, however, went up by $500, which was due to a substantial price variation of $6131. Consequently, total energy costs increased to $34,000.

$

Unit price (budget)

Unit price (actual)

A - Ba variance

(D - C)Ab price variance

- F or (Bb - Ab)C consumption variance

Department

(source) Heat treating (electricity)

106 Btu

106 Btu

$/106Btu

$/106 Btu

$9,000 2,000

$8,500 2,125

$4.00

$4.50

+$500

+$1000

-$500

(natural gas)

15,000 4,808

16,000 6,400

2.50

3.12

-1000

+2980

-3980

(steam)

10,000 2,242

9,000 2,571

3.50

4.46

+1000

+2151

-1151

(total)

$34,000

$33,500

+$500

+$6131

-$5631

aMeasured in $ bMeasured in 106 Btu

Energy cost

Figure 1-15

in dollars by department with variance analysis.

Dl n

1.7 ENERGY MONITORING, TARGETING AND REPORTING

1.7.1 Introduction

Energy Monitoring, Targeting and Reporting (MT&R) is a powerful management technique for

• analyzing the historical energy performance of industrial, commercial, and institutional facilities

• setting energy reduction targets

• controlling current energy performance

• and, projecting future energy budgets.

It is a technique that has proven its effectiveness in achieving energy cost savings in the range five to fifteen percent as a direct consequence of effective performance monitoring, and in creating the management information needed to identify and implement energy efficiency measures. Further, it provides a framework for savings verification when measures are implemented.

The working definitions that commonly apply are the following:

• Energy Monitoring is the regular collection and analysis of information on energy use. Its purpose is to establish a basis of management control, to determine when and why energy consumption is deviating from an established pattern, and to provide a basis for taking management action where necessary.

• Targeting is the identification of levels of energy consumption towards which it is desirable, as a management objective, to work.

• Reporting closes the loop, by putting the management information generated in a form that enables ongoing control of energy use, the achievement of reduction targets, and the verification of savings.

MT&R is built around one key statistical technique: CUSUM (Cumulative Sum of Differences) analysis of the variance between energy consumption predicted by an energy performance model (EPM), and the actual measured consumption. Ancillary functions that are derived from

*This section was written by Mr. Doug Tripp, P. Eng., Executive Director, Canadian Institute for Energy Training,; and Mr. Stephen Dixon, President, TdS Dixon Inc.

the CUSUM analysis are a target-setting methodology, and the application of energy control charts for real-time management of performance. The key steps in an effective MT&R process are:

• measurement of energy consumption over time

• measurement of the independent variables that influence energy consumption (weather, production, occupancy) over corresponding time intervals

• development of a relationship (the energy performance model) between energy and the independent variables

• historical analysis of energy performance using CUSUM, and application of the CUSUM trend into the future

• definition of reduction targets

• frequent comparison of actual consumption to targets

• reporting of consumption and target variances

• taking action to address variances and ensure targets are met.

The achievement of energy cost savings is the primary objective of MT&R, but there are other benefits as well, including:

• improved budgeting and forecasting

• improved product/service costing

• tracking and verification of energy efficiency retrofits

• opportunities for improved operation and maintenance practices.

1.7.1.1 MT&R and Continuous Improvement

Monitoring and target setting have elements in common and they share much of the same information. As a general rule, however, monitoring comes before target setting because without monitoring you cannot know precisely where you are starting from or decide if a target has been achieved. The reporting phase not only supports management control, but also provides for accountability in the relationship between performance and targets.

MT&R is consistent with other continuous improvement techniques applied in organizations, and should be viewed as an ongoing, cyclical process, as Figure 1-15 suggests.

The cycle begins with any measured energy data presently available, typically energy bills or invoices. Once assembled the data can be analyzed to reveal patterns, trends and consumption statistics. The reporting of the information resulting from this analysis can be used to prompt actions that produce results, typically the reduction of consumption and costs. Subsequent measurements and analysis reveal the actual result of the actions. The process then enters another cycle of measurement, analysis and action.

1.7.1.2 Energy Cost Center

The organizational basis for MT&R is the energy cost center (ECC). An ECC is a unit for which energy use may be measured along with other factors that influence the energy consumption. For example, the ECC might be a single building in a portfolio of properties, a production unit or department in a plant, or a major energy consuming system such as the heating plant.

Basic criteria for the designation of an ECC are:

• energy consumption can be measured in isolation

• the cost of measurement can be justified by potential savings

• the ECC must correspond to existing business structures

• someone must be accountable for the ECC

• a factor of influence must be measurable.

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