modelling report - energy web viewemma fagan. gordon weiss. 23/02/2015. version 2: revised ... in...

25 March 2015| REF: J/N 123192

Department of Economic Development, Jobs, Transport and ResourcesVEET Energy Saver Incentive SchemeBusiness Sector Energy Efficiency Modelling

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BUSINESS SECTOR ENERGY EFFICIENCY MODELLING

Project details

Department of Economic Development, Jobs, Transport and Resources

Energetics Contact

Kathryn Lucas-Healey Gordon Weiss

Description Prepared By Reviewed By Approved By Approval Date

Version 1: Initial Draft Gordon Weiss Emma Fagan Gordon Weiss 23/02/2015

Version 2: Revised version Emma Fagan Gordon Weiss Gordon Weiss 25/03/2015

About Energetics

Energetics is a specialist energy and carbon management consultancy. Our experts help clients to

Be leaders. Develop and implement strategyBe informed. Make data-driven decisionsBe efficient. Drive business improvement and realise savingsBuy better. Leverage energy supply and carbon markets

2014

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2013

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Finalist: Leading in Sustainability Banksia Award

2012

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2011

Winner: BRW Client Choice Award for Best Value

Finalists: BRW Client Choice Awards for Exceptional Service, Most Innovative, Outstanding Client Care and Best Consulting Engineering Firm (revenue <$50 Million)

© Energetics Pty Ltd 2023 123192\Documents\1948791\1

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Copyright

© 2015 Energetics. All rights reserved.

"Energetics" refers to Energetics Pty Ltd and any related entities.

This report is protected under the copyright laws of Australia and other countries as an unpublished work. This report contains information that is proprietary and confidential to Energetics and subject to applicable Federal or State Freedom of Information legislation, shall not be disclosed outside the recipient's company or duplicated, used or disclosed in whole or in part by the recipient for any purpose other than for which the report was commissioned. Any other use or disclosure in whole or in part of this information without the express written permission of Energetics is prohibited.

Disclaimer

The information contained in this document is of a general nature only and does not constitute personal financial product advice. In preparing the advice no account was taken of the objectives, financial situation or needs of any particular person. Energetics is authorised to provide financial product advice on derivatives to wholesale clients under the Corporations Act 2001 AFSL No: 329935. In providing information and advice to you, we rely on the accuracy of information provided by you and your company. Therefore, before making any decision, readers should seek professional advice from a professional adviser to help you consider the appropriateness of the advice with regard to your particular objectives, financial situation and needs.

Australian Financial Services License (AFSL # 329935).


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Table of contents

TABLE OF CONTENTS

1. Background.................................................................................................................................. 1

2. Modelling the VEET scheme........................................................................................................3

2.1. Consideration of non-financial barriers.........................................................................................5

3. Assumptions and parameters......................................................................................................6

4. Defining the measures.................................................................................................................9

4.1. Large commercial and SME sectors...........................................................................................10

4.2. Large industrial sector................................................................................................................14

5. Outcomes: Results of the modelling..........................................................................................17

5.1. Business sector results...............................................................................................................17

5.2. Results for certificate price scenarios.........................................................................................18

Appendix A. Key assumptions.......................................................................................................25

Retail energy prices.......................................................................................................................... 25

Savings and cost of lighting upgrades..............................................................................................25

Payback thresholds........................................................................................................................... 28

Appendix B. Industrial and mining measures................................................................................30

Appendix C. Details of the measures............................................................................................32

Contact details.................................................................................................................................... 33

LIST OF FIGURES

Figure 1: Calculation of incentive level...................................................................................................3

Figure 2: Measure uptake for smaller measures – take up curves as a function of incentive percentage............................................................................................................................................................... 4

Figure 3: Measure uptake for larger measures – take up curves as function of payback.......................4

Figure 4: Measures adopted...................................................................................................................4

Figure 5: Three year target with large business exclusion....................................................................17

Figure 6: Seven year target with large business exclusion...................................................................17

Figure 7: Seven year target without large business exclusion..............................................................18

Figure 8: Large commercial site energy consumption..........................................................................27

LIST OF TABLES

Table 1: Changes from previous VEET modelling..................................................................................2


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Table 2: Key assumptions and parameters in the model........................................................................6

Table 3: Parameters defining each measure..........................................................................................9

Table 4: Example of a measure..............................................................................................................9

Table 5: List of stationary energy savings measures by commercial market segment.........................12

Table 6: List of stationary energy savings measures by industrial market segment.............................14

Table 7: Extract from ClimateWorks database.....................................................................................16

Table 8: Three year scenario certificate prices.....................................................................................18

Table 9: Five year scenario certificate prices.......................................................................................19

Table 10: Certificates generated in the three year VEET scenario.......................................................19

Table 11: Certificates generated in five year VEET scenario...............................................................19

Table 12: Certificates generated by measure in 5.4 million certificates, five year VEET scenario........20

Table 13: Model retail energy prices.....................................................................................................25

Table 14: Savings per lighting installation............................................................................................26

Table 15: Energy consumption by building class..................................................................................27

Table 16: Derivation for commercial lighting upgrades in Victoria........................................................28

Table 17: Industrial and mining measure parameters...........................................................................30


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1. Background

On 1 January 2009 the Victorian Energy Saver Incentive (ESI) scheme was launched to promote the uptake of energy efficiency improvements in residential premises. The scheme is established in the Victorian Energy Efficiency Target Act 2007 (the Act). The objectives of the Act are to:

• reduce greenhouse gas (GHG) emissions

• encourage the efficient use of electricity and gas

• encourage investment, employment and technology development in industries that supply goods and services which reduce the use of electricity and gas by consumers.

The scheme is based on three year phases.

Phase 1 had an annual target of reducing lifetime GHG emissions by 2.7 million tonnes per annum in the residential sector, which was doubled to 5.4 million per annum for Phase 2 for the period to 2015, and expanded to include business and other non-residential sectors.

This objective of this review is to develop an appropriate target for Phase 3 of the VEET scheme.

In 2013 Energetics developed modelling as well as a number of scenarios examining business sector energy efficiency activities (as provided in VEET Energy Model Input Final Assumptions Report 1 [the 2013 Assumption Report] and related spreadsheets). Sustainability Victoria modelled the residential sector energy efficiency activities.

In this report, Energetics updates the modelling of business sector energy efficiency activities to ensure that it is accurate and current. We also present a number of target scenarios to incorporate into a model of the energy market, including energy efficiency measures pursued by the parts of the Victorian business sector that buy energy from energy retailers rather than the wholesale market.

Constraints and limitations

There are a number of factors that may influence the growth of the VEET scheme in Victoria that have not been included in this model. Non-market barriers such as split incentives and limited knowledge and access to information about the benefits of energy efficiency activities, cannot be modelled accurately.

There are also policies in Australia that may impact the pool of opportunities potentially taken up under the VEET, particularly the Emissions Reduction Fund (ERF). While the influence of the ERF is difficult to estimate before it begins, we see possible outcomes where engagement with the VEET scheme is preferred. One such example arises where ERF assessment methodologies overlap with the VEET. Project proponents may choose the VEET scheme as payment for emissions reductions is made up front unlike the delivery model offered under the ERF. The lack of entry-level abatement thresholds in the VEET may also make the scheme more attractive.

Ultimately market conditions and the price of both ACCUs and VEECs will determine how the pool of opportunities offered under the VEET, may be impacted by the ERF.

1 “VEET Energy Model Input: Final assumptions report”, Energetics, 18 November 2013


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Changes from the 2013 model

The business sector energy efficiency modelling described in this report built on work done for the 2013 Assumption Report. A number of changes have been made to the earlier model and these are outlined in Table 1 below.

Table 1: Changes from previous VEET modelling

Changes Reference in this report

Measures for the large industrial sector are included Section 4.2

A number of measures pertaining to the large commercial and SME sectors have been removed or combined

Section 4.1

Several measures pertaining to the large commercial and SME sectors have been amended

Table 5

The electricity and natural gas prices are updated Appendix A

The year by year decay of the savings due to a measure has been changed

The value was changed from 0% to 3%.

Discount rate The value for project based assessment (PBA) measures was changed from 20% to 10%.

Detail in Section 2.


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2. Modelling the VEET scheme

This report focuses on commercial energy efficiency measures and the assumptions used to model their impact. The following section provides an overview of the functionality of the model.

Figure 1 to Figure 4 outline the process used to determine the number of certificates created for different certificate prices. Each energy efficiency measure was defined according to adjustable parameters such as the total pool of efficiency opportunities, the costs of implementation and the average electricity and gas savings that will result. The model also includes adjustable parameters. Examples include a certificate price ($/certificate2), a greenhouse gas (GHG) emissions factor and any administrative fees associated with the creation of certificates.

The total number of certificates created depends on the annual GHG emissions savings, the duration of the energy efficiency measure and the GHG emissions factor applied.

The incentive for participants is a function of the number of certificates created, multiplied by the value of each certificate. The latter is net of any fees associated with the administration of the scheme.

The model calculates the uptake of measures based on the incentive to participate. One of two approaches is used. For the less costly measures most suited to SME markets, the uptake is calculated based on a simple relationship between the size of the incentive and the cost of the energy efficiency measure. Figure 2 shows the uptake of simpler measures such as replacing an old appliance. There is a default take-up curve plus one for low cost appliances and one for new technologies (where there can be resistance to early adoption).

Figure 1: Calculation of incentive level

The 5% fee used within the model reflects the observed administrative cost reported in the assessment of the ACT Government EEIS.

In determining the deemed savings for a project, the calculated emissions savings are discounted by 10% for each year of a project’s life up to 10 years. This differs from the 20% discount rate used in prior VEET modelling. This discount provides a balance between what is an adequate incentive for project proponents to drive energy saving measures and the need to ensure that certificates are only created for genuine savings. The change in the discount rate is material and has resulted in an effective project life of 5.5 years when generating VEECs as opposed to three years when using a 20% discount rate. It also results in a savings persistence of ten years rather than five.

The treatment of $0 certificate prices and the impact of the results are discussed in detail in section 2.1.

2 One certificate is intended to be equivalent to 1 tonne of lifetime greenhouse gas abatement.


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Figure 2: Measure uptake for smaller measures – take up curves as a function of incentive percentage

If the commercial GHG emissions abatement measure is more costly and generally applicable to larger businesses then it is more appropriate to use an approach based on the payback. Figure 3 shows the calculation. The payback threshold, which establishes when the energy efficiency measure will be taken up, is a distribution function that reflects the range of thresholds for different participants.

Figure 3: Measure uptake for larger measures – take up curves as function of payback

Finally, the actual number of instances that the energy efficiency measure is adopted is expressed as the uptake rate times the total pool of opportunity. Total uptake figures are managed by a constraint that limits the maximum annual uptake to reflect the fact that the market has limited capacity to deliver any one measure within a fixed period of time. See Figure 4 for an overview on how this functionality works.

Figure 4: Measures adopted


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2.1. Consideration of non-financial barriers

Note that the assessments of payback periods within the model were undertaken on a purely financial basis. There are a range of non-financial barriers that may also limit the interest in energy efficiency projects. The impact of non-financial barriers is modelled through the use of payback periods that have actually been seen in the market, rather than payback periods that would be implied by realistic financial returns. As discussed in Section 3, the actual paybacks required by the market are as low as 1.75 years whereas projects with paybacks as high as 10 years would show a positive financial return.

The data that defines the take-up of a measure comes from a number of independent sources – observed take-up of measures, reported costs to implement energy efficiency measures, savings based on a basket of specific activities within a broad measure and forecasts of energy prices. For instance, the measure “lighting upgrade” covers a broad range of potential activities that depend upon the existing form of lighting and the replacement technology. It is possible that some measures will be cost effective to some participants even if no incentive is in place. This is best considered as a component of the business-as-usual case.

The business-as-usual take-up that is predicted by the model was deducted from the take-up at various positive incentives (external to the VEET program) in order to give a true indication of the take-up driven by the incentive. As an example, if a measure saw 500 certificates generated at a $0 certificate price, and 10,000 generated a $15 certificate price, these 500 certificates are deducted from the 10,000 certificates to give the actual impact of the incentive.

Note though that in the ‘real world’, factors such as an un-modelled increase in energy prices or a significant drop in implementation cost will result in the measure becoming more cost effective and therefore we would see take-up without any incentive. Similarly, a fall in energy prices or increase in implementation costs will mean that measures are less attractive.


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3. Assumptions and parameters

Table 2 outlines a number of key assumptions and parameters that define the overall properties of the model. Some of these assumptions and parameters relate to the structure of the model and others relate to the performance of the abatement measures.

Table 2: Key assumptions and parameters in the model

Item Details

Business-as-usual

Where activities involve the upgrade of equipment at the point of replacement (e.g. installing a high efficiency motor at the time the motor needs replacing), the business–as-usual (BAU) case assumes that a unit compliant with the Minimum Energy Performance Standards (MEPS) is installed.

In other cases, the savings associated with the measure represent a weighted average of savings for measures reported in the Commonwealth Energy Efficiency Opportunities (EEO) program and other energy audits.

In confidence, commercial data has also been used to derive installation costs and savings potentials for some measures, most notably commercial lighting.

Averaging different items

Energy savings for each measure where the averages of a number of uses of the measure are reported in EEO and other energy assessments. The aggregation of different instances of the measure will include the use of different pieces of equipment. The extensive, publicly available EEO dataset, which was used to derive the average savings for an energy efficiency measure, was assumed to be representative of the total pool of opportunities in the wider economy.

Average annual energy savings (MJ/yr)

Commercial buildings and SMEs: An average was calculated for annual energy savings for commercial buildings and SMEs, based on the fraction of the total energy used by the building or facility resulting from the implementation of the energy efficiency measure.

The baseline and measures developed for the modelling of the National Energy Savings Initiative [the NESI dataset] also included the average amount of energy used by each type of building. The product of these two values gives the average annual energy savings.

Industrial facilities: We used the “Percentage of total energy used by a facility that is saved by the measure” reported in the industrial component of the NESI dataset.3

Measure life (Years)

This is the estimated length in years that the measure is expected to deliver energy savings once installed. Sources included the Carbon Trust persistence factor data base, the Low Carbon Australia persistence factor data base, EES residential baseline study, RIS: NAEEEC Report 2003/10 Minimum Energy Performance Standards and Alternative Strategies for Linear Fluorescent Lamps, the BIS Shrapnel Household Appliances 2006 and Energetics commercial in-confidence figures.

VEET GHG coefficients

Provided by the Victorian Government and used consistently across all VEET modelling, the values applied were 0.963 tCO2-e/MWh for electricity and 0.0573 tCO2-e/GJ for natural gas.

Pool of opportunities

The following approach was used to estimate the number of opportunities for large commercial and SME buildings:

The total energy consumption for each type of building or SME facility was estimated using the energy reported by ANZSIC sector, measures of building size and activity as reported to the ABS (e.g. employee numbers, sales volume, patient numbers, student numbers) and measures of energy intensity within various types of buildings.

3 Inputs to Energy Savings Initiative modelling from Industrial Energy Efficiency Data Analysis Project: http://www.industry.gov.au/Energy/Documents/energy-efficiency/energy-savings/consultant/Industrial_data_subsector_grouping_level_dataset.xls (Accessed March 2015)


http://www.industry.gov.au/Energy/Documents/energy-efficiency/energy-savings/consultant/Industrial_data_subsector_grouping_level_dataset.xls

http://www.industry.gov.au/Energy/Documents/energy-efficiency/energy-savings/consultant/Industrial_data_subsector_grouping_level_dataset.xls

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Item Details

The average energy used by each type of building or facility was assessed by either:

o aggregating a set of representative assessments of a specific building type to directly estimate the average, or

o estimating the total number of buildings in a specific category and then dividing the total energy used by those buildings by the total number of buildings.

Using our estimate for the total energy used by each type of building in Victoria, and our estimate of the average energy used by a building, we estimated the number of buildings of each type in Victoria.

Using our estimate for the fraction of all buildings or facilities where a measure was applicable (eg an upgrade to a boiler is only applicable to a building with a boiler) and our estimate for the fraction of buildings where a particular measure has already been adopted, we adjusted the estimate of each type of building or facility in Victoria to give the number of buildings or facilities where a particular measure is still able to be implemented. This is the pool of opportunities.

The modelling of measures applicable to the large industrial sector used a different approach. The large industrial sector covered mining and industry excluding non-ferrous metals. The latter were excluded as non-ferrous metal production is dominated by metal (aluminium) smelting which takes its electricity directly from the wholesale market. The pool of opportunity for the industrial measures covers the energy used by the large industrial sector as determined during the modelling of the national energy savings initiative. This basically covered the entities that were obligated under the NGER program.

More detail on calculating the pool of opportunity can be found in the report on the Commercial and SME Energy Efficiency Data on the NESI Consultants Reports webpage.4

Maximum uptake rate/year

Where a measure is only applicable at the point of replacement of the equipment, the maximum uptake rate is the total pool of opportunity divided by the life of the equipment ie the turnover of stock.

In other cases, it was based on our estimate of what is achievable and reasonable. This is the part of the model where there is the greatest uncertainty

Note that where measures were assessed using a project based method, the maximum take-up in the first year was set to zero to account for the time needed to undertake the assessment and the internal processes to approve and then implement the measure.

Discount rate In determining the average number of certificates for a project, the calculated emissions savings are discounted by 10% for each year of a project’s life up to 10 years. This differs from the 20% discount rate used in prior VEET modelling.

Average number of certificates

Where a commercial measure uses a default abatement factor5 to determine the number of certificates, the number of certificates is equal to the energy savings times the emissions factors times the measure lifetime.

For measures that are assessed by a project based methodology, the number of certificates is equal to the energy savings times the emissions factors times 5.5. The latter term represents 100% of the emissions savings in the first year plus 90% of the emissions savings in the second year plus 80% of the emissions savings in the third year, and so on.

Additionality The measures have accounted for regulatory additionally though the definition of the energy savings due to the measure e.g. the savings due to the installation of an appliance subject to minimum energy performance standards (MEPS) is taken to be the savings above the MEPS

4 http://www.industry.gov.au/Energy/Documents/energy-efficiency/energy-savings/consultant/Commercial_and_SME_EnergyEfficiencyDataReport.pdf (Accessed March 2015)

5 Default abatement factors are used to calculate the number of abatement certificates that may be created from the installation of common equipment such as compact fluorescent lamps, refrigerated display cabinets and certain electric motors. Calculation of certificates using default abatement factors is simple as the number of certificates is linked to the size of the appliance and not the characteristic of the particular installation.


http://www.industry.gov.au/Energy/Documents/energy-efficiency/energy-savings/consultant/Commercial_and_SME_EnergyEfficiencyDataReport.pdf


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Item Details

level not the market average energy performance (assuming the latter is the lower).

Rebound Rebound in this instance refers to the implementation of a more energy efficient technology driving a slight increase in the use of the more efficient equipment compared to the previous, less efficient technology (generally related to the energy cost saving differential). With deemed abatement this may result in slightly less GHG abatement than anticipated.

The model accounts for rebound by reducing the savings due to an implemented measure from year to year.6 Our default factor, based on Energetics experience is to reduce the energy savings by 3% each year and this value was used in the model of the VEET scheme.

Average payback The average payback is calculated by the model, taking into account the capital cost, incentive payments and the energy savings.

Payback installation hurdle

Our default payback thresholds are to include any measure that offers a payback within three years for measures in large businesses and 1.75 years for the SME sector. Where the take-up is assessed using the payback threshold, 50% of the available instances of the measure will be taken up when the average payback is equal to the threshold.

Lifetime energy saved

The lifetime savings for a particular instance of a measure is equal to the sum of annual savings over the lifetime of the measure.

The total energy saved is the aggregate of energy saved for each instance of each measure, taking into account the calendar year when the instance was implemented. Discounts to these savings are applied to measures incentivised using project based assessment methodologies (see Maximum uptake rate/year).

Annual GHG emissions saved

This model used an emissions factor equivalent to the VEET GHG coefficient to calculate annual GHG emissions reduction on a measure by measure basis and in totality.

Lifetime GHG emissions saved

This is the sum of annual GHG savings across all measures and all years. Lifetime GHG emissions reductions are also calculated using an emissions factor equivalent to the VEET GHG coefficient.

Certificate administrative fee

A further 5% of the certificate price is deducted to account for the cost incurred by the Accredited Person or third party involved in installing a measure.

Note that costs incurred for the undertaking of a feasibility study prior to implementing the measure are included in the implementation cost of the measure.

Average cost The average cost is equal to the cost of applying the measure to the entire building or facility (equipment + installation + feasibility studies).

The average costs for large commercial and SME measures were derived from the NESI dataset, unless otherwise indicated in Table 5. Large industrial measures were derived from the industrial component of the NESI dataset.3

Uptake rate function

The uptake of a measure is determined by the ratio of the size of the incentive and the cost of the measure. See Figure 2 for an illustration of an uptake rate function.

6 Note that the year by year reduction in energy savings is independent of the discounting of calculated emissions savings when determining the number of certificates for project based measures.


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4. Defining the measures

The energy efficiency measures that were included in the modelling of the extension of the VEET scheme are based on opportunities in the large industrial, large commercial and SME sectors. They were developed with reference to Australian and international literature, as well as Energetics’ extensive field experience in conducting energy audits nationwide across most building types.

Each measure was defined by a collection of parameters. Table 3 and Table 4provide details of those parameters and an example of one activity. Measures were also split between industrial facilities, commercial buildings and buildings appropriate to the SME sector.

Table 3: Parameters defining each measure

Item Meaning

Measure name A descriptive name for the measure.

Building type or sector Ten types of large commercial buildings, four types of small buildings, industrial facility. mining facility

Size of opportunity Number of nominal buildings or nominal facilities where the opportunity exists

Lifetime Estimate of a particular opportunity useful lifetime

Installed cost Average cost to implement all instances of the opportunity in the building type or the facility

Electricity savings (GJ/p.a.)

Average annual savings from implementing all instances of the opportunity in the building type or facility

Gas savings (GJ/p.a.) Average annual savings from implementing all instances of the opportunity in the building type or facility

T/U function Used to determine the uptake of a measure, the options were one of three potential take-up functions or the use of payback in years. There is a default take up curve plus one for low cost appliances and one for new technologies (where there can be resistance to early adoption).

T/U rate % size year 1, 2, 3 and 4 and beyond

Maximum limit on uptake: maximum percentage of buildings or facilities that can be upgraded in any year of the program

P/B Threshold Three years for large buildings, the industrial sector and the mining sector. 1.75 for the SME sector.

Incentive method Default abatement factor or project based assessment

Table 4: Example of a measure

Item Meaning

Measure Name Lighting upgrade

ID 18


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Item Meaning

Sector SME industrial

End use Lighting

Measure type SME-existing

Size of opportunity (units) 126300

Units Buildings

Applicable energy tariff Franchise

Lifetime of abatement savings (years) 10

Total Installed cost ($/unit) 4509.855

Electricity savings (GJ/unit p.a.) 25.67172

Mains Gas savings (GJ/unit p.a.) 0

T/U function Payback

T/U rate % size year 1 0.15



T/U rate % size year 4 onwards 0.15

Payback Threshold 1.75

Payback SD 0.291667

Incentive method DAF

4.1. Large commercial and SME sectors

A number of considerations were taken into account in calculating potential energy savings attributable to each measure for each building type:

The lifetime of a measure: Lifespan estimates were made for each measure with reference to industry sources7, complemented by Energetics’ industry knowledge.

The minimum energy performance standards (MEPS) applicable to equipment or typical baseline energy use by equipment in the sample base.

The energy consumed by high efficiency (HE) alternative technologies to existing installations.

The energy use baseline per building type.

7 See Table 2.


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The energy savings potential for each of the measures was expressed as a percentage of the total energy use by the building type. The marginal or incremental cost per measure relative to the energy usage of the building type was also calculated based on the capital and implementation cost estimates from the audit datasets.

The savings potential was assessed for individual measures that were intended as input into the NESI dataset. We did not take into account the interaction of measures8 nor mutually exclusive measures9. However, there were only limited instances identified where measures interact with other measures.

The energy efficiency measures included in the model were derived from a similar data set used for the modelling of the NESI dataset. For commercial and SME applications 38 different measures across twelve broad classes were modelled. Each measure applied to one or more of ten types of large commercial building and four types of small to medium enterprises. Types of buildings within the model include commercial offices, schools, large and small retail outlet, hotels and restaurants.

The list of potential energy savings opportunities in the commercial and SME sectors was supported with reference to Australian and international literature, as well as Energetics’ extensive field experience in conducting energy audits nationwide across most building types.

Certain adjustments were made to the list of measures from the earlier work. The key adjustments are outlined below:

Measures covered by Schedule 1 to Schedule 30 of the VEET Regulations were removed as they will be covered by the modelling of the residential sector.

Several groups of measures involved the same improvement implemented in different building types. Further, these measures had the same implementation cost per MJ. These measured were combined into one measure spanning all buildings covered by the separate measures with no change in the overall result but with the benefit of less complexity.

With the exception of certain forms of window treatment, building shell measures are not cost effective. Window treatments are covered by the residential component of the VEET scheme and so applying treatments on SME premises has been transferred to the residential model. We validated the remaining window treatment measures that applied to large commercial buildings. These measures were combined into a single measure applicable to large commercial buildings. These changes have made no material impact on the results generated by the model.

Measures involving the installation of evaporative air conditioners were removed as the commercial sector has seen a steady decline in the installation of evaporative air conditioners10. This amendment also had no material impact on the results generated by the model.

Based on experiences with other energy efficiency trading schemes (e.g. the ESS), upgrades to commercial lighting are expected to be one of the measures that has a large take-up. Therefore have a robust description for this measure is highly desirable in this

8 This refers to a situation where the effectiveness of one measure is impacted by the adoption of a second or third measure. For example, the replacement of inefficient lighting in an office could lead to increased energy use for heating due to more heat being lost in the ambient atmosphere by the inefficient lighting.

9 This refers to a situation where the implementation of one measure, precludes the adoption of another.

10 Institute for Sustainable Systems and Technologies, “ Technical research on evaporative air conditioners and feasibility of rating their energy performance”, (accessed March 2015)


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Report. The lighting measures outlined in the 2013 Assumption Report were taken from the NESI dataset. Better data regarding the savings and costs of commercial lighting upgrades is now available. This was used to validate and revise the lighting measures. In particular, all lighting measures were combined into two aggregated measures: one for large commercial buildings and one for SME buildings. These amendments have resulted in a more accurate calculation of the likely certificates to be generated under the lighting upgrade measure. A more comprehensive description of the lighting measures can be found in Appendix A.

There has been almost no take-up of high efficiency (HE) motors in the ESS. The technical potential for the measure “HE motors in small offices” in the NESI dataset is much higher than can be justified as small offices do not use pumps other than small pumps in generally packaged HVAC systems. Based on revised assessment for the HE motor market in the commercial business sector in Victoria this measure was removed from the current model. This removal does not impact on the treatment of HE motors in other business sectors such as warehouses, shopping centres and universities.

The list of measures for energy savings for the large commercial and SME sectors is presented in Table 5. In several cases the capital costs from the earlier modelling were increased by 15% to capture the cost of the feasibility study. Previously this was included in the administration fee. This is described as “the 15% loading” in the table.

Table 5: List of stationary energy savings measures by commercial market segment

Measure Name Sector Basis and comments DAF/PBA11

Air Compressors: Improved operation of compressed air systems

SME Industrial

The measure was taken from the NESI SME dataset. There was some take-up of air compressor measures in the ESS. The need for a relatively high certificate price will limit actual take-up.

PBA

Appliances & Equipment: Variable speed drives (VSDs)

SME Industrial

The measure was taken from the NESI SME dataset. Several similar VSD measures applicable to the SME sector were included in the earlier modelling. Further, some related measures are included in the current dataset. Therefore as VSDs are largely an industrial piece of equipment, this measure is restricted to just the industrial SME sector.The poor take-up of these apparently cost effective measures appears to be because take-up was modelled by an uptake curve rather than payback. Payback is used in the current modelling.

PBA

Appliances & Equipment: Replace a MEPS compliant motor with a HE motor

Shopping Centre

These were derived from the NESI dataset. The 15% loading has been applied.

Note that there has been almost no take-up of high efficiency motors in the ESS.

DAF


Warehouse (NR)

DAF

HVAC: Replace a MEPS compliant

University / TAFE

DAF

11 DAF means a default abatement factor. PBA means project based assessment.


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Measure Name Sector Basis and comments DAF/PBA

motor with a HE motor

Boilers, Furnaces & Ovens: Upgrade Hospitality The measure was taken from the NESI large

commercial dataset.PBA

Boilers, furnaces and ovens: Replace boiler

Large commercial

This combined measure was derived from the NESI large commercial dataset. The 15% loading has been applied.

PBA

Building shell: Window treatment

Large commercial

The treatment of building shell measures was discussed above.

PBA

HVAC: HVAC controls Hospitality

The measures were taken from the NESI datasets.

PBA

HVAC: HVAC controls

SME Industrial

PBA

HVAC: High efficiency standalone AC

SME

The measure was derived from the NSEI SME dataset. The large installation cost of these measures suggests that they would be better modelled using payback to determine take-up. A 5% loading was added to the installation cost to allow for any feasibility studies.

DAF


Large office The measures were taken from the NESI large commercial dataset. The test for take-up was changed to the payback as it better reflects the type of measure and the large installed cost. A 5% allowance for the feasibility study has been added.

DAF


Shopping Centre

DAF

HVAC: HVAC controls

Large commercial

A review of data from sources available to Energetics suggested that the indicated installation cost per GJ of electricity saved was too low, and should be at least $150/GJ. The 15% loading has been applied.

PBA

HVAC: Replace cooling tower Large office The measure was taken from the NESI large

commercial dataset.PBA

HVAC: Upgrade chiller

Large commercial

This measure was derived from the NESI large commercial dataset. The 15% loading has been applied.

PBA

HVAC: Variable speed drives and control for fans

Large commercial

This measure was derived from the NESI large commercial dataset. The 15% loading has been applied.

PBA

Lighting upgrade SME Industrial

Lighting measures were discussed above.

DAF

Lighting upgrade Large commercial

DAF

Pumps: Upgrade to HE pumps Hospitality


DAF

Pumps: Upgrade to HE pumps

SME Industrial

DAF


14


Measure Name Sector Basis and comments DAF/PBA

Pumps: Variable speed drives for pumps

Hospital


PBA

Pumps: Variable speed drives for pumps

SME Industrial

PBA

4.2. Large industrial sector

In addition to the calculation of potential energy savings from the commercial and SME sectors, additional work was undertaken to calculate energy savings (electricity and natural gas savings) from the large industrial sector in Victoria. These sites have been included following the sunsetting of the Environment and Resource Efficiency Plans (EREP) program. To date large industrial and commercial sites had been excluded from the coverage of the VEET scheme due to the operation of the EREP scheme.

In total 26 measures were considered covering both the broad industrial sector and the mining sector. Note that all measures are based on a PBA assessment of savings.

The bulk of the data used to derive the measures applicable to the large industrial sector has been extracted from work done by ClimateWorks as part of the modelling of the NESI12. The list of measures as included in the VEET model is shown in Table 6:

Table 6: List of stationary energy savings measures by industrial market segment

Measure Industry Mining

Measures that save electricity

Upgrade: Co-generation or Tri-generation

Upgrade: Comminution (crushing and grinding) and blasting systems

Upgrade: Compressed air systems

Upgrade: Conveyors

Upgrade: Furnace/Kilns

Upgrade: Gas compression equipment

Upgrade: IT, communications and other electronic equipment

Upgrade: Lighting systems

Upgrade: Non-transport machinery

Upgrade: Other Building services

Upgrade: Other equipment

12 “Inputs to the Energy Savings Initiative modelling from the Industrial Energy Efficiency Data Analysis Project”, ClimateWorks Australia, July 2012


15


Measure Industry Mining

Upgrade: Pumping systems

Upgrade: Refrigeration

Upgrade: Stationary materials handling systems

Upgrade: Various industrial systems

Upgrade: Ventilation systems, fans and blowers

Upgrade: Waste treatment, disposal and remediation

Measures that save natural gas

Upgrade: Boiler systems

Upgrade: Conveyors

Upgrade: Dryers

Upgrade: Furnace/Kilns

Upgrade: Gas compression equipment

Upgrade: Other process heating equipment

Upgrade: Ovens

Upgrade: Thermal electricity generation

Upgrade: Various industrial systems

The data for individual measures was aggregated by “Technology/ process” and “Fuel category” across the major industry classifications – “Mining” and “Industry”. Subsector groupings associated with manufacturing of metals was excluded as they largely reflect energy used by the aluminium smelters which is not covered by the VEET. The final set of aggregated measures described the expected savings as a percentage of total electricity or gas used at a facility and the average capital cost per GJ of energy saved for particular technology or process. The aggregation did not include measures with paybacks in the 0-2 year range as reported by ClimateWorks as they are likely to be taken up by businesses without any additional incentives afforded through the VEET.

The model also estimated the energy used by the large industrial sector. Information on energy use in Australian categorised by fuel type and by ANZSIC sector is available from the Office of the Chief Economist13. The energy used in Victoria for each ANZSIC sector was estimated by assuming the fraction of energy used by each ANZIC sector in Victoria is the same as the corresponding national fraction. The electricity and natural gas consumed by Victoria was also available in the 2014 energy statistics.

Work on the NESI yielded the fraction of each fuel type used by large and SME business. This data was used to estimate the electricity and gas used by large industry and large mining in Victoria. These

13 2014 energy statistics data (http://www.industry.gov.au/industry/Office-of-the-Chief-Economist/Publications/Pages/Australian-energy-statistics.aspx#)


16


values were within 10% of the reported EREP amounts, which suggests that the majority of facilities obligated under the EREP program are also the sites that report under NGER. The requirement to report under NGER was the criteria to separate large businesses from SMEs in the NESI dataset modelling.

An example of a specific measure by sub-sector and fuel type is outlined below in Table 7.

Table 7: Extract from ClimateWorks database

Item Typical value

Subsector grouping C11 - Food Product Manufacturing

Technology/ process Dryers

Fuel category Gas

Payback range >4 years

Energy savings (% subsector grouping - fuel category energy use)

4.23%

Capital costs ($/GJ) $41.60

Appendix A provides additional information about the industrial measures including the amount of energy they save and the cost to implement the measures.


17


5. Outcomes: Results of the modelling

5.1. Business sector results

Figure 5 to Figure 7 below show the results of the modelling of the business sector of the VEET scheme. It considers three or five year timeframes of the VEET scheme, and forecasts the take-up of certificates at varying certificate prices. Note that neither Figure 5 nor Figure 6 include the possible generation of certificates from large business (as outlined in section 4.2).

Figure 5: Three year target with large business exclusion

Figure 6: Five year target with large business exclusion


18


Figure 7 below includes large business in the modelling of total certificates created leading to the higher level of certificates created, particularly in years 2018 and 2019. The approach taken to include large industrial sector energy users is outlined further in section 4.2.

Figure 7: Five year target without large business exclusion

As demonstrated in both Figure 6 and Figure 7 some drop off is assumed at a higher certificate price. This results from a higher certificate price driving increased participation in the earlier years, and limiting the pool of opportunity for participation in the later years. This is particularly so where large business’ are excluded. As Figure 6 demonstrates there is a levelling off after a certain certificate price.

5.2. Results for certificate price scenarios

The generation of certificates for each specific measure was based on two different scenarios – a three year scenario and a five year scenario – with yearly certificate prices modelled against three different VEET targets. Table 8 and Table 9 below consider the certificate prices that were used to model the results in each scenario against each certificate target.

Table 8: Three year scenario certificate prices

Certificate Target 2016 2017 2018

5,400,000 19.53 30.73 27.04

5,800,000 23.30 37.04 28.56

6,200,000 30.77 44.15 30.26


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Table 9: Five year scenario certificate prices

Certificate Target 2016 2017 2018 2019 2020

5,400,000 19.53 30.73 27.04 25.86 51.30

5,800,000 23.30 37.04 28.56 28.41 54.47

6,200,000 30.77 44.15 30.26 30.75 57.65

Based on these certificates the following total certificate prices were generated. These totals incorporate all measures and assumptions outlined within this Report.

Table 10 provides an overview of the total certificates created at each certificate target over the three year VEET scenario.

Table 10: Certificates generated in the three year VEET scenario

Certificate Target 2016 2017 2018

5,400,000 1,139,016 2,257,823 2,937,394

5,800,000 1,169,056 2,400,504 3,335,132

6,200,000 1,195,707 2,582,105 3,402,405

Table 11 provides an overview of the total certificates created at each certificate target over the five year VEET scenario. Note that the remainder of the certificates generated in each of the scenarios outlined in Table 10 and Table 11 arise from the residential sector.

Table 11: Certificates generated in five year VEET scenario

Certificate Target 2016 2017 2018 2019 2020

5,400,000 1,139,016 2,257,823 2,937,394 3,136,295 4,074,539

5,800,000 1,169,056 2,400,504 3,335,132 3,581,499 3,533,575

6,200,000 1,195,707 2,582,105 3,402,405 3,699,273 3,767,856

Table 12 gives a complete breakdown of certificated generated for each measure over the five year period for an indicative target of 5.4 million certificates.


20


Table 12: Certificates generated by measure in 5.4 million certificates, five year VEET scenario14

Measure Name Sector End use 2016 2017 2018 2019 2020

Air Compressors: Improved operation of compressed air systems

SME Industrial Air Compressors 0 0 0 0 0

Appliances & Equipment: Variable speed drives SME Industrial Appliances and equipment 2,930 8,723 6,791 9,197 179,859


Shopping Centre Appliances and equipment 3,793 3,793 3,793 3,793 3,793


Warehouse (NR) Appliances and equipment 2,630 2,630 2,630 2,630 2,630

Boilers, Furnaces & Ovens: Upgrade Hospitality Boilers, furnaces and ovens 0 319 246 359 11,482

Boilers, furnaces and ovens: Replace boiler Large commercial Boilers, furnaces and ovens 52,354 56,867 51,282 13,263 0

Building shell: Window treatment Large commercial Building shell upgrade 1 1 2 4 331

HVAC: HVAC controls Hospitality HVAC 0 0 0 0 0

HVAC: HVAC controls SME Industrial HVAC 0 0 0 0 0

HVAC: High efficiency stand alone AC SME HVAC 0 0 0 0 0

HVAC: High efficiency stand alone AC Large office HVAC 0 0 0 0 0

HVAC: High efficiency stand alone AC Shopping Centre HVAC 0 0 0 0 0

HVAC: HVAC controls Large commercial HVAC 0 27,334 35,821 17,783 0

14 In the context of this Report “small offices” and “small trade” captures tenancies in large commercial buildings and large shopping centres


21



HVAC: Replace a MEPS compliant motor with a HE motor

University / TAFE HVAC 2,926 2,926 2,926 2,926 2,926

HVAC: Replace cooling tower Large office HVAC 0 0 0 0 0

HVAC: Upgrade chiller Large commercial HVAC 0 0 0 0 0

HVAC: Variable speed drives and control for fans Large commercial HVAC 37,466 124,038 120,934 28,948 0

Lighting upgrade SME Lighting 748,040 1,513,131 1,918,612 1,958,276 1,392,327

Lighting upgrade Large commercial Lighting 0 0 0 0 0

Pumps: Upgrade to HE pumps Hospitality Pumps 0 9,761 9,337 7,351 9,761

Pumps: Upgrade to HE pumps SME Industrial Pumps 133,575 133,575 133,575 133,575 133,575

Pumps: Variable speed drives for pumps Hospital Pumps 0 0 0 0 0

Pumps: Variable speed drives for pumps SME Industrial Pumps 77,181 158,295 132,213 141,710 158,953

Refrigeration: RDC upgrade Hospitality Refrigeration 21,120 21,120 21,120 21,120 21,120

Refrigeration: RDC upgrade Small trade Refrigeration 32,871 32,871 32,871 32,871 32,871

Refrigeration: HE commercial refrigeration Large retail (R) Refrigeration 5,576 8,254 7,193 4,855 2,126

Refrigeration: HE commercial refrigeration SME Industrial Refrigeration 6,574 11,324 10,333 14,745 51,917

Refrigeration: Replace a low efficiency fan motor with an electronically commutated motor

Large retail (R) Refrigeration 11,979 24,062 40,173 3,818 0

Ventilation / fans: Car park ventilation control Large office Ventilation and fans 0 0 0 0 0

Ventilation / Fans: Improve fan efficiency SME Ventilation and fans 0 0 0 0 0


22



Water heating: Solar or heat pump water heater Hospital Water heating 0 2 1 3 1,711

Water heating: Solar or heat pump water heater Large retail (R) Water heating 0 1 0 1 595

Upgrade: Co-generation or Tri-generation Industry Co-generation or Tri-generation 0 0 0 0 0

Upgrade: Compressed air systems Industry Compressed air systems 0 0 0 0 0

Upgrade: Conveyors Industry Conveyors 0 0 7 20 16

Upgrade: Furnace/Kilns Industry Furnace/Kilns 0 0 6 53 0

Upgrade: Gas compression equipment Industry Gas compression equipment 0 0 0 6,147 0

Upgrade: IT, communications and other electronic equipment

Industry IT, communications and other electronic equipment

0 0 0 0 3

Upgrade: Lighting systems Industry Lighting systems 0 0 0 0 0

Upgrade: Non-transport machinery Industry Non-transport machinery 0 7 7 13 268

Upgrade: Other Building services Industry Other Building services 0 9,922 55,158 138,227 68,859

Upgrade: Other equipment Industry Other equipment 0 9 57 64 147

Upgrade: Pumping systems Industry Pumping systems 0 4,766 19,257 21,719 61,626

Upgrade: Refrigeration Industry Refrigeration 0 7 7 18 1,313

Upgrade: Stationary materials handling systems Industry Stationary materials handling systems

0 0 0 0 0

Upgrade: Various industrial systems Industry Various industrial systems 0 40,998 38,147 60,835 855,519


23



Upgrade: Ventilation systems, fans and blowers Industry Ventilation systems, fans and blowers

0 523 6,409 10,152 14,660

Upgrade: Waste treatment, disposal and remediation

Industry Waste treatment, disposal and remediation

0 8 8 11 107

Upgrade: Comminution (crushing and grinding) and blasting systems

Mining Comminution (crushing and grinding) and blasting systems

0 0 0 4,026 0

Upgrade: Compressed air systems Mining Compressed air systems 0 0 0 4,015 0

Upgrade: Conveyors Mining Conveyors 0 5 5 12 265

Upgrade: Lighting systems Mining Lighting systems 0 9 35 45 85

Upgrade: Other Building services Mining Other Building services 0 7,108 29,528 35,558 73,519

Upgrade: Other equipment Mining Other equipment 0 0 0 0 0

Upgrade: Pumping systems Mining Pumping systems 0 0 0 0 0

Upgrade: Stationary materials handling systems Mining Stationary materials handling systems

0 0 0 0 0

Upgrade: Boiler systems Industry Boiler systems 0 0 155,370 395,601 838,602

Upgrade: Dryers Industry Dryers 0 19,353 58,171 39,633 94,291

Upgrade: Furnace/Kilns Industry Furnace/Kilns 0 0 0 0 0

Upgrade: Other process heating equipment Industry Other process heating equipment

0 0 0 0 0


24



Upgrade: Ovens Industry Ovens 0 0 0 0 0

Upgrade: Various industrial systems Industry Various industrial systems 0 36,060 45,336 22,905 59,248

Upgrade: Boiler systems Mining Boiler systems 0 0 0 0 0

Upgrade: Conveyors Mining Conveyors 0 0 0 0 0

Upgrade: Furnace/Kilns Mining Furnace/Kilns 0 22 32 13 34

Upgrade: Gas compression equipment Mining Gas compression equipment 0 0 0 0 0

Upgrade: Other process heating equipment Mining Other process heating equipment

0 0 0 0 0

Upgrade: Thermal electricity generation Mining Thermal electricity generation 0 0 0 0 0


25


Appendix A. Key assumptions

Retail energy prices

These feed directly into the payback calculation that determines the take-up of measures, and a small change in the retail price can have a significant impact on the cost effectiveness of measures e.g. a 10% change in the electricity price to SMEs is roughly equivalent to a change in certificate price of $20/tonne. The electricity prices must be marginal prices, representing the cost of the electricity that is actually saved due to the measures.

The retail prices out to 2024 in the model are in Table 13.

Table 13: Model retail energy prices

Sector and fuel 2016 2017 2018 2019 2020 2021 2022 2023 2024

Franchise (SME) customers

Electricity ($/MWh) 207.22 200.63 203.88 209.36 214.39 210.79 214.28 217.49 221.29

Natural gas ($/GJ) 11.17 11.98 12.42 11.95 11.07 10.27 9.55 9.59 9.62

Contract (large) customers

Electricity ($/MWh) 158.52 151.90 154.85 159.95 164.63 160.91 164.08 166.98 170.45

Natural gas ($/GJ) 10.77 11.58 12.02 11.55 10.67 9.87 9.15 9.19 9.22

Savings and cost of lighting upgrades

These are expected to be the measures with the highest uptake in the SME and commercial sectors, and so accurate modelling of these measures will increase confidence in the outcomes of the modelling. Key data items are the cost of implementation per unit of energy saved, savings per instance of a measure and the number of measures that can be implemented.

Implementation costs

Energetics analysed the actual implementation cost and savings achieved for a large number of commercial lighting upgrades for confidential and non-confidential sources. We found that implementation costs ranged from $32/GJ saved up to $278/GJ saved. Averages, weighted by the number and size of projects were $175/GJ for the SME sector and $135/GJ for the large commercial sector. These results reflected a typical basket of lighting measures that are actually being implemented in the respective sectors.


26


For comparison, the simple average of lighting measures in the earlier VEET modelling was $156/GJ. The NSW OEH recently published a technology report on energy efficient lighting15. This report included typical savings and costs for commercial lighting upgrades. The cost of various low cost upgrades ranged for $64/GJ (replacing a 60W dichroic halogen lamp with a 25W IRC lamp) through to $237/GJ (replacing a twin 36 W T8 recessed linear fluorescent luminaire with a single 36 W T8 reflector). The simple average of these lighting upgrades was around $150/GJ.

These comparisons suggest that using values of $175/GJ for the SME sector and $135/GJ for the large commercial sector is not unreasonable.

Savings per instance of a measure

The savings per instance of a measure is required to determine the number of instances that can be implemented. The average savings per installation across a range of actual lighting upgrades in our databases is in Table 14.

Table 14: Savings per lighting installation

Sector Average use per site (MWh)

Savings as % of site consumption

Savings/instance (MWh)

Large commercial 5000 2.71% 136

SME 86 8.33% 7.1

The OEH technology report on energy efficient lighting quotes the annual energy savings for the upgrading of 100 lights of different types, with the annual savings ranging from 5.2 MWh to 80 MWh. Lighting upgrades typical of SMEs saved the order of 10 MWh per 100 lights. The figure of 7.1 MWh per instance in the table implies that a typical SME lighting upgrade involves around 70 to 100 lights. This seems reasonable.

The figure of 5000 MWh for large commercial sites was derived from values reported in the NESI dataset. The following chart was taken from the NESI Consultants Report Webpage16 (refer Figure 8).

15 http://www.environment.nsw.gov.au/resources/business/140017-energy-efficient-lighting-tech-rpt.pdf (Accessed March 2015)

16 http://www.industry.gov.au/Energy/Documents/energy-efficiency/energy-savings/consultant/Commercial_and_SME_EnergyEfficiencyDataReport.pdf (Accessed March 2015).




http://www.environment.nsw.gov.au/resources/business/140017-energy-efficient-lighting-tech-rpt.pdf

27


University / Ter...

Hospital

CB

D H

otel / SA

Large office

Warehouse (R

)

Large retail (R)

Warehouse ...

Shopping centre

Large retail (NR

)

School

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,00013,676

8,479

5,439 5,265 5,179

3,440 3,161 2,7291,908

1,045

Annu

al e

lect

ricity

con

sum

ptio

n (M

Wh)

Figure 8: Large commercial site energy consumption

Potential instances of lighting upgrades

The potential number of instances of lighting upgrades comes from a consideration of the energy used by the SME and large commercial sectors. Estimates of the energy used by these sectors come from the NESI dataset modelling, refer Table 15.

Table 15: Energy consumption by building class

Energetics Building Class Electricity consumption by building class in Victoria (PJ)

Sector

CBD Hotel / SA 0.76 Large Com

School 0.98 Large Com

University / Tertiary 2.70 Large Com

Hospital 1.39 Large Com

Large retail (R) 3.57 Large Com

Large Retail (NR) 1.25 Large Com

Warehouse (R) 0.49 Large Com

Warehouse (NR) 2.13 Large Com

Large office 3.96 Large Com

Shopping Centre 2.75 Large Com

Street lighting 1.24 Large Com


28


Energetics Building Class Electricity consumption by building class in Victoria (PJ)

Sector

Non-CBD hotel/hostel/resort 2.05 SME

Restaurant 5.53 SME

Small retailing facilities 8.13 SME

Small office 17.81 SME

SME Manufacturing 22.12 SME

SME Industrial (other / NMF) 0 SME

Knowing the energy used by the sectors in Victoria and the average energy used per site means that the number of potential sites can be estimated. Many of the sites will already have undertaken lighting upgrades and so must be removed from the set of potential sites. Based on analysis done during the NESI dataset modelling, we estimated that 40% of large buildings and 30% of small buildings already had upgraded lights.

The derivation of the potential for commercial lighting upgrades in Victoria is in Table 16.

Table 16: Derivation for commercial lighting upgrades in Victoria

Sector Total electricity use in Victoria

(GWh)

Average use per site

(MWh)

Estimated penetration to

date

Technical potential

(Instances)

Potential certificates

Large commercial 5,893 5000 40% 710 966,000

SME 15,455 86 30% 126300 9,016,000

The final column in the figure is the number of certificates that would be generated if all possible measures were implemented. It assumes a 10 year lifetime for the measures. The uptake of commercial lighting in the ESS generated around 1 million certificates in the first year, rising to 3 million in the third year. Assuming that the market in Victoria is similar to that in NSW, we constrained the uptake in the first three years of the modelled scheme to 10%, 20% and 30% of the maximum.

Payback thresholds

A review of the prevailing thresholds applied to energy efficiency investment by Australian businesses was carried out as part of the NESI dataset modelling. This review suggested that SMEs generally require paybacks of between one to 2.5 years, whilst large commercial entities may respond positively to paybacks of between one to four years, depending on economic conditions in each case. The payback threshold for large commercial entities is three years during average economic conditions. During times of weak economic growth the payback threshold approaches one year and in good times it increases to four years. There was a large variation in the average payback period of opportunities between measures and end-use categories.


29


We used 1.75 years for the payback threshold for the SME sector. A figure of 3 years was used for the large commercial and industrial sectors.


30


Appendix B. Industrial and mining measures

Table 17: Industrial and mining measure parameters

Measure Total energy used by all facilities in Victoria

where the measure applies (TJ)

Percentage of total energy used by a

facility that is saved by the measure

Cost to implement the measure ($/GJ

saved)

Measures applicable to industry that save electricity

Co-generation or Tri-generation 12,986 18.3% $50.87

Comminution (crushing and grinding) and blasting systems

12,986 0.4% $8.95

Compressed air systems 38,957 0.1% $45.50

Conveyors 12,986 0.0% $1.50

Furnace/Kilns 12,986 0.0% $1.60

Gas compression equipment 38,957 0.1% $35.40

IT, communications and other electronic equipment

12,986 0.0% $31.67

Lighting systems 12,986 0.1% $12.91

Non-transport machinery 25,971 0.0% $33.96

Other Building services 38,957 0.3% $65.77

Other equipment 12,986 0.0% $1.70

Pumping systems 38,957 0.3% $66.71

Refrigeration 38,957 1.0% $102.12

Stationary materials handling systems 12,986 0.0% $28.62

Various industrial systems 103,885 7.0% $246.66

Ventilation systems, fans and blowers 38,957 0.1% $62.44

Waste treatment, disposal and remediation

12,986 0.0% $28.22

Measures applicable to mining that save electricity

Comminution (crushing and grinding) and blasting systems

11,171 0.2% $63.38

Compressed air systems 11,171 0.2% $63.77


31


Measure Total energy used by all facilities in Victoria

where the measure applies (TJ)

Percentage of total energy used by a

facility that is saved by the measure

Cost to implement the measure ($/GJ

saved)

Conveyors 16,756 0.3% $186.96

Lighting systems 5,585 0.0% $5.71

Other Building services 22,341 0.3% $105.73

Other equipment 16,756 1.0% $89.47

Pumping systems 11,171 0.0% $87.42

Stationary materials handling systems 5,585 0.0% $39.09

Measures applicable to industry that save natural gas

Boiler systems 217,643 3.1% $24.65

Dryers 108,821 1.8% $17.81

Furnace/Kilns 54,411 0.0% $0.10

Other process heating equipment 108,821 0.5% $19.05

Ovens 54,411 0.1% $7.03

Various industrial systems 272,054 2.9% $48.38

Measures applicable to mining that save natural gas

Boiler systems 10,734 0.1% $3.85

Conveyors 10,734 0.0% $38.79

Furnace/Kilns 10,734 0.3% $1.63

Gas compression equipment 10,734 0.9% $128.26

Other process heating equipment 10,734 0.3% $8.93

Thermal electricity generation 10,734 0.1% $3.72


32


Appendix C. Details of the measures

An extract from the VEET model that includes the descriptions of all the measures in the model is attached. See “Measures.xlsx”.


33


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