3_steps to Develop a Baseline

STEPS TO DEVELOP A BASELINE

Prepared by Dušan Gvozdenac and Miroslav Kljajić

Project: Regional training on planning and monitoring energy efficiency measures in the constructing sector Podgorica, Tiranë, Sarajevo i Banja Luka, October – December, 2013.

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Developing an energy use and energy intensity baseline is a valuable way to get started with energy management. Baselines create a benchmark for comparing energy performance from year to year. Baselining is the act of measuring energy use and energy intensity at a determined level of detail for the purpose of establishing a benchmark for future comparison to itself. Energy intensity is defined as the energy used per unit of output.

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Any energy system no matter what its size and intensity of energy consumption are requires providing answers to the following questions:

• Why is it necessary to establish the level of energy consumption before an energy efficiency measure is implemented at the site?

• How to establish an energy baseline for an energy efficiency measure?

• How to use opportunity baseline to estimate and measure energy savings?

• How to incorporate factors affecting current and future energy use into reliable baselines?

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ESTABLISHING AN ENERGY BASELINE Energy baselines are defined in ISO 50001 as ‘quantitative references providing a basis for comparison of performance’ that apply to a specific time period and provide a reference for comparison before and after the implementation of energy improvements. There are three main methods for establishing an energy baseline for opportunities:

• regression analysis, • modeling/simulation, • short-term metering.

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Forecasting future energy baselines

Energy Baseline

Adjusted Energy Baseline

without opportunity

implementation

ADJUSTMENT

Based on Historical Energy Data and

Factors

Based on Future Energy Data and

Factors

En

erg

y

Adjusting the current energy baseline to account for factors which influence energy consumption

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Factor Influence on energy consumption

Adjustment required

Tip

Multiple product lines

Some products are more energy intensive than others.

Set separate baselines for each product.

Compare performance with appropriate baseline when evaluating opportunities and measuring savings.

Production rate Fixed energy overheads are spread over production, so energy intensity changes with production.

Index energy baseline to production rate.

Optimization of assets is a key method to improve energy efficiency while improving business outcomes.

Raw materials

Changes to raw material can increase or decrease energy consumption (e.g. a mineral processing plant using more energy when processing gold due to hardness).

Set separate baselines for each raw material.

Compare performance with appropriate baseline when evaluating opportunities and measuring savings.

Ambient conditions

Temperature Relative humidity (RH)—affects performance of wet cooling towers and gas turbines

Degree days % RH

Degree day data is available for each geographical region (refer to the Bureau of Meteorology website for more information: <www.bom.gov.au>).

Occupancy Increasing number of guests/patients/employees increases energy consumption.

Index to occupancy levels or rooms in use.

Find appropriate measure (e. g. number of people, floor area or number of rooms). Optimizations of services according to occupancy rates can deliver significant savings.

Energy consumption rates

Steep gradients increase vehicle fuel consumption.

Set baselines for common routes or for a range of gradients.

Compare performance with appropriate baseline when evaluating opportunities and measuring savings.

Adjusting for energy influencing factors

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Example A manufacturing company plans to increase production. To forecast the energy baseline, the current energy baseline was adjusted for the production increase (following Figure). The dashed line shows the forecast energy baseline, had the production level not been adjusted for an increase.

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Energy Baseline

Time

En

erg

y U

se

Baseline Period Reporting Period

Adjustment

Icreased Production

Opportunity Implementation

Forecasting the energy baseline

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Using an energy baseline - EXAMPLE

A minerals processing site has identified an energy efficiency opportunity. Implementing the opportunity will influence energy use across the site, so the baseline boundary has been set around the mineral processing site.

Baseline. On average, each year the mineral site processes 180,000 tons of mineral, consumes 30.06 GWh of electricity and operates for annually 8,000 hours. From this, the baseline energy intensity was calculated:

30.06 GWhSite baseline energy intensity = 167 kWh / t

180,000 t

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The current energy consumption of 30.06 GWh can be adjusted to take into account the forecast changes in production by multiplying the current energy intensity (167 kWh/t) by the production forecast. This adjustment creates the forecast energy baseline which will later be used by the company to estimate energy savings.

Units Current Forecast (without opportunity implementation)

Annual production forecast

tons 180,000 189,000

Energy intensity kWh/t 167 167

Energy consumption GWh 30.06 31.56

There is a 5% difference between the current energy baseline and the forecast energy baseline due to the forecast production change.

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CALCULATION OF HEATING DEGREE-DAYS Heating Degree-Days (HDD) for a particular climate is obtained by subtracting each day's mean outdoor dry bulb temperature from the balance point temperature. This result is the number of HDDs for that day. For example, if mean daily outdoor dry bulb temperature of a place is 10.0 oC and the balance point temperature is 18.3 oC, then the HDD of the place for that particular day is (18.3 – 10) = 8.3 oC. If the mean outdoor dry bulb temperature is equal to or higher than the balance temperature, then the HDD will be equal to 0.

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Degree days are essentially the summation of temperature differences over time. Hence, they capture both extremity and duration of outdoor temperatures. The temperature difference is set as difference between a reference temperature and outdoor air temperature. The reference temperature is known as the base temperature which is a balance point temperature, i.e. the outdoor temperature at which the heating or cooling systems do not need to run in order to maintain comfort conditions.

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Mean daily outdoor temperature can be calculated simply as arithmetic mean of minimum and maximum temperatures of a particular day or using the following approximate formula:

7 14 21m

t +t +2 tt =

4

where t7, t14 and t21 are outdoor temperatures measures at 7:00, 14:00 and 21:00 hours, respectively.

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CALCULATION OF COOLING DEGREE-DAYS Cooling Degree-Days (CDD) for a particular climate is obtained by subtracting each day's mean outdoor dry bulb temperature from the balance point temperature; the result is the number of CDDs for that day. For example, if the maximum and minimum outdoor dry bulb temperatures of a place are 32.2 and 15.5 oC respectively, and the balance point temperature is 15.5 oC then, the CDD of the place for that particular day will be [(32.2+15.5)/2] – 15.5 = 8.4 oC. Here, the mean outdoor temperature is calculated based on maximum and minimum daily temperatures. If the mean outdoor dry bulb temperature is equal to or lower than the balance point temperature then, the CDD will be equal to 0.

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Reading Date

Days Month

Consumption [kWh]

Demand [kW]

Daily Consumption [kWh/day]

HDD [oC]

CDD [oC]

Temp [oC]

Jul-17 30 S 762,300 950 25,410.0 0.0 84.5 19.7

Aug-16 30 S 665,280 930 22,176.0 0.0 134.3 21.5

Sep-16 31 S 623,700 990 20,119.4 8.2 91.4 19.3

Oct-1 30 W 568,260 950 18,942.0 43.7 18.7 14.9

Nov-15 30 W 623,700 772 20,790.0 190.3 0.0 8.7

Dec-16 31 W 457,380 722 14,754.2 423.4 0.0 1.3

Jan-15 30 W 665,280 752 22,176.0 618.4 0.0 -5.6

Feb-14 30 W 540,540 792 18,018.0 556.9 0.0 -3.6

Mar-14 28 W 526,680 761 18,810.0 509.2 0.0 -3.2

Apr-15 32 W 498,960 712 15,592.5 290.1 0.1 6.0

May-15 30 W 693,000 970 23,100.0 102.3 3.2 12.1

Jun-16 32 S 595,980 970 18,624.4 17.6 49.5 17.3

Electric Meter

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Reading Date

Days Month

Consumption [m3]

Daily Consumption [m3]/day

HDD [°C]

CDD [°C]

Temp [°C]

Jul 09 28 S 70,047 2,501.7 6.6 95.7 18.2

Aug 13 35 S 84,010 2,400.3 0.0 218.0 21.2

Sep 10 28 S 64,959 2,320.0 0.0 163.0 20.8

Oct 15 35 W 96,573 2,759.2 51.3 41.1 14.7

Nov 01 28 W 110,836 3,958.4 159.6 1.0 9.3

Dec 10 28 W 159,144 5,683.7 353.6 0.0 2.4

Jan 14 35 W 253,199 7,234.3 690.8 0.0 -4.7

Feb 11 28 W 200,452 7,159.0 516.5 0.0 -3.4

Mar 11 28 W 191,339 6,833.5 535.3 0.0 -4.1

Apr 15 35 W 160,532 4,586.6 333.1 2.6 5.6

May 13 28 W 79,885 2,853.0 99.5 14.0 11.9

Jun 10 28 S 61,002 2,178.6 20.1 75.7 17.0

Natural Gas Meter

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Monthly Electricity Consumption versus HDD/day (Heating Season)

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Monthly Electricity Consumption versus CDD/day (Cooling Season)

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Monthly Electricity Consumption versus Mean Monthly Outdoor Temperature

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Monthly Electricity Demand versus Mean Monthly Outdoor Temperature

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Monthly Natural Gas Consumption versus HDD/day (Heating Season)

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Monthly Natural Gas Consumption versus CDD/day (Cooling Season)

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Baseline Conditions • Lighting—was operated manually in all areas. Corridor lights

were usually shut off at 10 p.m. each evening. • Laundry—was operated in a daily 8-hour shift, 7 days a week

and no bedding outside the hospital was included. • Kitchen—was operated in a 12-hour shift, 7 days a week, with

no extra meal preparation. • Fan schedule—the attached schedule indicates the ventilation

fan schedule during the baseline period. • Miscellaneous—there were 13 personal computers, 4 laser

printers, 8 dot matrix printers and 4 copiers on the site as detailed in the attached equipment survey.

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Natural Gas Meter The linear regression results in good correlation between energy use and heating degree-days. The following will be used for determining savings:

cp b

b

p c c

daysE E (for summer months)

days

E 2,295 days 251.84 HDD (for w int er months)

The formula for savings is then

s p cE E E Ep = projected energy consumption Eb = energy consumption in a baseline month Ec = current monthly energy consumption Es = monthly energy savings daysb = number of reading days in a baseline month daysc = number of reading days in a current month HDDc = number of heating degree days in current month