Franco BarnardM&V Project Engineer

Baseline Service Level Adjustments of ECM on Compressed Air Systems

16 August 2012

Baseline SLA of ECM on Compressed Air Systems

• Background – What is M&V?• Problem Statement• SLA Methodologies – Description, Assumptions, Advantages and

Disadvantages– SLA 1: Drilling time Energy (kWh) vs. Drilling time Air Flow (m3)– SLA 2: Monthly Compressor Energy (kWh) vs. Total Monthly Mine Energy (kWh)– SLA 3: Monthly Energy (kWh) vs. Monthly Production (Tons Hoisted)

• Results from the SLA Methodologies– SLA 1: Drilling time Energy (kWh) vs. Drilling time Air Flow (m3)– SLA 2: Monthly Compressor Energy (kWh) vs. Total Monthly Mine Energy (kWh)– SLA 3: Monthly Energy (kWh) vs. Monthly Production (Tons Hoisted)

• Summary & Conclusions• Further Work Needed

Points of Discussion

Background – What is M&V?

• M&V allows for the independent, unbiased performance assessment of any Energy Conservation Measure (ECM).

• M&V aims to quantify savings accurately and conservatively.

• To quantify the savings of an ECM, a Baseline (BL) and a BL Methodology needs to be developed.

• As part of the BL Methodology an independent parameter needs to be identified to perform routine adjustments (aka SLA).

• The SLA are done to reflect what the baseline would have been under current operational conditions.

Problem Statement

• Proper M&V is heavily dependent on data and data availability.

• Proper data on the compressed air systems in the mining industry can be very limited.

• SLA methodologies needs to be developed, regardless of the quality and quantity of data available to M&V.

• Unfortunately, the level of accuracy of M&V depends on the amount of money available for measurement instrumentation.

• With all of this in mind, the problem is to identify an appropriate independent parameter for the SLA.

SLA Methodologies

• The following SLA methodologies were identified and used on compressed air projects:

– SLA 1: Independent Parameter - Air Flow [Drilling time Energy Consumption (kWh) vs. Drilling time Air Flow (m3)]

– SLA 2: Independent Parameter – Total Mine Energy Consumption [Monthly Compressor Energy Consumption (kWh) vs. Total Monthly Mine Energy Consumption (kWh)]

– SLA 3: Independent Parameter – Production [Monthly Energy Consumption (kWh) vs. Monthly Production (Tons Hoisted)]

• For each of these SLA Methodologies certain assumptions were made.

• Each of them also have advantages and disadvantages associated with them.

SLA Methodologies – SLA 1

Independent Parameter - Air FlowDrilling time Energy Consumption (kWh) vs. Drilling time Air Flow

(m3)

• In this case the independent parameter was identified as the amount of compressed air being produced during the drilling times.

• The drilling times of a mine is mainly between 09:00am to 12:00pm during working days.

• The amount of electrical energy that was used during this was related to the amount of compressed air produced during the same time.

• A linear relation was obtained between these two parameters.

SLA Methodologies – SLA 1

SLA Methodologies – SLA 1

Independent Parameter – Air Flow

• Assumptions– The ECM would have no influence on the compressed air system during the

drilling times.• This was due to the fact that the mine was very sensitive to any changes that might

affect their production levels.

• Advantages of SLA 1– This SLA Methodology allows M&V to have a direct link to past operations under

current operational conditions.

• Disadvantages of SLA 1– If the ECM affects the compressed air system operations indirectly, this

methodology will no longer be accurate.

SLA Methodologies – SLA 2

Independent Parameter – Total Mine Energy ConsumptionMonthly Compressor Energy Consumption (kWh) vs. Total

Monthly Mine Energy Consumption (kWh)

• In this case the independent parameter was identified as the amount of energy consumed by the entire mine without the energy consumption of the compressed air system.

• The amount of electrical energy consumed by the mine was related to the amount of energy consumed by the compressed air system.

• The reason for choosing this independent parameter is because the compressed air system contributes to ±50% of the mine’s total energy consumption.

• Monthly amounts of energy were used to obtain a linear relation.

SLA Methodologies – SLA 2

SLA Methodologies – SLA 2

Independent Parameter – Total Mine Energy Consumption• Assumptions

– It was assumed that no other ECM would have been done during the same time as the compressed air project.

– It was also assumed that the amount of compressed air needed on the underground operations would not change.

• Advantages of SLA 1– Due to the fact that the compressed air system contributes to ±50% of the mine’s total

energy consumption, small ECM would have a negligible effect on accuracy of SLA 2.

• Disadvantages of SLA 1– If large ECM measures are done on other systems of the mine it would cause SLA 2 to

be come inaccurate. This could also include the expansion/downsizing of mining operations.

– The savings calculations might be inaccurate on a daily basis. But over the course of a month accuracy of SLA 2 should not be a problem.

– These two parameters might be auto-correlated and not independent.

SLA Methodologies – SLA 3

Independent Parameter - ProductionMonthly Energy Consumption (kWh) vs. Monthly Production (Tons

Hoisted)

• In this case the independent parameter was identified as the Production of the mine. In other words the amount of tons of raw material hoisted on a monthly basis.

• The amount of tons hoisted was related to the amount of energy consumed by the compressed air system.

• Monthly amounts of energy and production were used.

• A linear relation was obtained between these two parameters.

SLA Methodologies – SLA 3

SLA Methodologies – SLA 3

Independent Parameter – Production

• Assumptions– The compressed air system has the greatest influence on the production of the

mine than any other of the operations at the mine.

• Advantages of SLA 1– Mine’s monitor their production closely and the production levels of mines are

quite easily accessible. Thus, no additional metering would be necessary.

• Disadvantages of SLA 1– The fit of the linear relation for SLA 3 is not very good. This might result in

inaccurate saving being reported on a monthly basis. However, over a period of 3 months or more, SLA 3 is very accurate.

Results – SLA Methodologies

• Each of the SLA Methodologies were evaluated with two statistical parameters. – The Coefficient of Determination was calculated (R-squared)– ASHRAE determination bias. (Should be smaller than 0.005%)

• The results for the parameters mentioned above are in the table below.

Results – SLA 1 – Air Flow

Results – SLA 1 – Air Flow

Results – SLA 1 – Air Flow

Results – SLA 2 - Total Mine Energy Consumption

Results – SLA 2 - Total Mine Energy Consumption

Results – SLA 3 - Production

Results – SLA 3 - Production

Summary & Conclusions

• SLA 1 Methodology

– SLA 1 has a very good R-squared value (0.75) but it does not comply with the ASHRAE determination bias limit of 0.005%. However, at 0.0293% it does come quite close.

– This methodology is very situation specific. This means that it may only be used for projects where the ECM is not expected to affect the consumption of compressed air during the drilling times.

– SLA 1 must also be closely monitored, so that the baseline SLA methodology can be updated when the consumption of compressed air starts to become affected.

Summary & Conclusions

• SLA 2 Methodology

– SLA 2 has a very good R-squared value (0.74) and it does comply with the ASHRAE determination bias limit of 0.005% (0.00003%).

– This methodology has not been definitively proven to be reliable or accurate. It should firstly be established whether there exists auto-correlations between the two parameters.

– SLA 2 should rather be avoided unless it can be proven that the independent parameter is in fact independent.

• The Durbin-Watson test is one test that can be used for clarification.

Summary & Conclusions

• SLA 3 Methodology

– SLA 3 does not have a very good R-squared value (0.01) but it does comply with the ASHRAE determination bias limit of 0.005% (0.0012%).

– Compressed air systems in the mining industry consumes a very large amount of the mines total energy consumption. This means that it should have a large effect on the production levels of a mine.

– Production data is readily available from most mines. This makes it a very easy way of evaluating the performance of an ECM on compressed air systems.

– It is recommended that SLA 3 be used as far as possible when evaluating ECM on compressed air systems.

Further Work Needed

• Get enough data to test these methodologies on the same project. This would show the accuracy of each SLA Methodology very clearly.

• Investigate in full is any auto-correlations exist between the parameters chosen for SLA 2. The Durbin-Watson test is one test that could be used to clarify this matter.

Thank you.