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Analysis of the impact ofthe Victorian Energy Efficiency Target schemeon energy consumption and Victorian energy markets

DISCLAIMER

This report has been prepared for the Department of State Development, Business and Innovation (DSDBI) as an input to its review of the Victorian Energy Efficiency Target (VEET). The analysis and information provided in this report is derived in whole or in part from information prepared by a range of parties other than Oakley Greenwood (OGW), and OGW explicitly disclaims liability for any errors or omissions in that information, or any other aspect of the validity of that information. We also disclaim liability for the use of any information in this report by any party for any purpose other than the intended purpose.

DOCUMENT INFORMATION

Project Impact analysis of the VEET 2009 - 2012

Client Department of State Development, Business and Innovation

Status Final Report

Report prepared by

Lance Hoch ([email protected])Rohan Harris ([email protected])Greg Thorpe ([email protected])

Date 6 December 2013

by

Impact analysis of the VEET 2009 - 201227 September 2013

Draft Final Report

Table of CONTENTS

1. Executive summary11.1. Project background and purpose 11.2. Approach 11.3. Findings and caveats 2

1.3.1. Findings 21.3.2. Caveats 6

2. Introduction 82.1. Overview of the Victorian Energy Efficiency Target (VEET) scheme 82.2. Purpose of this study 82.3. Overview of the methodological approach requested in the ToR 82.4. Findings concerning the efficacy of the approaches undertaken 9

2.4.1. The bottom-up approach 92.4.2. The top-down approach10

2.5. Organisation of this report 12

3. Key assumptions 133.1. General assumptions regarding the VEET and other factors 133.2. Assumptions regarding VEET impacts on the transmission and distribution com-

ponents of the retail bill 143.3. Assumptions regarding the VEET’s impact on the retail component of the bill

153.4. Key assumptions made in the analysis of the distributional impacts of the VEET

153.5. Key assumptions made in the analysis of the net economic benefits of the VEET

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4. Impact of the VEET on energy consumption 164.1. Purpose and overview of the bottom-up approach 164.2. Bottom-up energy consumption impacts 16

5. Impact of the VEET on energy markets 195.1. Purpose and overview of this task 195.2. Impact on wholesale electricity market and wholesale component of the retail

bill195.2.1. Overview of the approach used 195.2.2. Model configuration 205.2.3. Key inputs to the modelling 21

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5.2.4. Estimation of the peak demand and load shape impacts of the VEET 275.2.5. Results of the CEMOS analysis 28

5.3. Impact on transmission and distribution components of the retail bill 325.3.1. How energy efficiency affects network prices 325.3.2. Calculating the impact of the VEET on the transmission component of the re-tail bill 335.3.3. Calculating the impact of the VEET on the distribution component of the re-tail bill 335.3.4. Findings 35

5.4. Impact on retail operating costs and margin 375.4.1. Nature of the costs incurred by retailers 375.4.2. Findings 37

6. Distributional impacts of the VEET 406.1. Purpose and overview of this task 406.2. Findings 41

6.2.1. Costs of the scheme as allocated to participants and non-participants 416.2.2. Benefits of the scheme accruing to participants and non-participants 436.2.3. Net benefits accruing to participants and non-participants in Victoria 45

6.3. Net economic benefits (electricity sector total resource cost perspective) 45

7. Conclusions, caveats and recommendations 487.1. Conclusions 487.2. Caveats 52

Appendix A : Terms of Reference 54Project description 54

I. Measure the impact of VEET on energy consumption 54II. Evaluate the effect of VEET on energy markets 55III. Assess the distributional impacts of VEET 55

Scope 55Project tasks and deliverables 56

Appendix B : Findings of the top-down approach 57B.1 Purpose and overview of the top-down approach 57B.2 Change in average consumption 57B.3 Weather correction 60B.4 Price impacts 61B.5 Policy impacts 64B.6 Results of the top-down analysis 68B.7 An alternative use for the top-down approach 71

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Appendix C : Allocation of VEET measure annual savings to seasons and times of day to create load shape impacts for use in the market modelling 73

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Table of FIGURES

Figure 1: Delivered gas prices ($/GJ).....................................................................................................25

Figure 2: AEMO’s estimated reductions in residential and commercial consumption in the NEM.........59

Table of TABLES

Table 1: Average VEET benefits & costs per participant and non-participant in Victoria ($2012, 2009 – 20)............................................................................................................................................................ 5

Table 2: VEET economic benefits and costs – TRC perspective ($2012 million, 2009 – 20)...................6

Table 3: Comparison of policy impacts from the top-down approach with the bottom-up impact estimate of the VEET (GWh)................................................................................................................................ 12

Table 4: Overview of energy consumption impacts from 2009 through 2012 of VEET activity measures installed between 2009 and 2012...........................................................................................................17

Table 5: VEET savings by activity measure and end use.......................................................................18

Table 6: 2012 ESOO energy and summer peak demand forecast – Victoria.........................................23

Table 7: Forecast energy reductions (GWh, sent-out) due to national and state-level energy efficiency programs and policies............................................................................................................................ 24

Table 8: Forecast summer maximum demand reductions (MW) due to national and state-level energy efficiency programs and policies............................................................................................................24

Table 9: Carbon price schedule.............................................................................................................26

Table 10: Impacts of the VEET on the wholesale electricity market (FY)...............................................29

Table 11: Impacts of the VEET on the wholesale electricity market (CY)...............................................30

Table 12: VEET impact on use of fuels for generation 2009 – 2020, GWh............................................31

Table 13: VEET impact on amount and type of generation capacity 2020 (MW)...................................31

Table 14: VEET impact on generation production costs ($millions2012)...............................................32

Table 15: Network revenue reductions ($million 2012)..........................................................................35

Table 16: Comparison of VEET impacts (MW) with total forecast network non-coincident peak demand............................................................................................................................................................... 36

Table 17: Certificate price ($nominal).....................................................................................................38

Table 18: Number of certificates created (‘000s)....................................................................................38

Table 19: Retailer costs ($million 2012).................................................................................................39

Table 20: Annual and total cost of the VEET per average customer for each customer class ($2012). .42

Table 21: Proportion of customers on standing offers and market offers...............................................43

Table 22: Annual and total benefit of the VEET per average customer for each customer class ($2012)............................................................................................................................................................... 44

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Table 23: Annual and total benefit of the VEET accruing to non-Victorian customers in aggregate ($2012)................................................................................................................................................... 45

Table 24: Distributional impacts – net annual and total financial benefit of the VEET per average cus-tomer for each customer class ($2012)..................................................................................................45

Table 25: Economic benefits of the VEET – electricity sector total resource cost perspective ($2012, millions).................................................................................................................................................. 46

Table 26: Economic costs of the VEET – electricity sector total resource cost perspective ($2012, mil-lions)....................................................................................................................................................... 46

Table 27: Net economic benefits of the VEET – electricity sector total resource cost perspective ($2012, millions).................................................................................................................................................. 46

Table 28: Impact of VEET on wholesale electricity price, by jurisdiction ($2012/MWh)..........................49

Table 29: Average VEET benefits & costs per participant and non-participant in Victoria ($2012, 2009 – 20).......................................................................................................................................................... 50

Table 30: VEET economic benefits and costs – TRC perspective ($2012 millions, 2009 – 20).............52

Table 31: Average annual consumption per residential customer..........................................................58

Table 32: Average change in residential consumption – pre- and post-weather correction...................61

Table 33: Estimated cumulative residential price changes.....................................................................63

Table 34: Estimated per-annum price elasticity impacts........................................................................64

Table 35: Total per annum impact of policy drivers on residential consumption relative to 2008 levels (GWh)..................................................................................................................................................... 65

Table 36: Breakdown of the residential energy reduction impact of each policy measure, by distribution area (GWh)............................................................................................................................................ 65

Table 37: Policy impacts (GWh).............................................................................................................66

Table 38: Clean Energy Council estimates of cumulative Solar PV output (GWh).................................67

Table 39: Clean Energy Council estimates of installed capacity of Solar PV (GWh)..............................68

Table 40: Year-on-year increase in installed capacity (MW) and output (GWh).....................................68

Table 41: Residual impact possibly attributable to VEET scheme.........................................................68

Table 42: Sensitivity associated with using alternative elasticity estimates............................................70

Table 43: Residual impact attributable to the VEET Scheme with different elasticities..........................70

Table 44: Comparison of VEET scheme with key policy impacts...........................................................72

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1. Executive summary1.1. Project background and purpose

The Victorian Energy Efficiency Target (VEET) scheme (promoted publicly as the "Energy Saver Incentive" or "ESI") is a market-based scheme designed to promote the uptake of energy efficiency improvements in residential and non-residential premises. The scheme works by setting a greenhouse gas (GHG) abatement target that is to be met through the uptake of prescribed energy efficiency activities for which certificates are granted. Each certificate represents an energy saving equivalent to one tonne of GHG abatement. Large energy retailers operating in Victoria are required to surrender certificates annually in amounts proportional to their energy sales.The purpose of this study was to identify costs and benefits of the VEET scheme in terms of the measures installed since its inception in 2009 through the end of 2012. Specifically, this review was undertaken to assess the impact that the reduction in energy consumption that has resulted from the measures installed under the program during that time has had on wholesale energy costs and retail energy prices, and how this has affected the bills of customers that have participated in the scheme and customers that have not done so.

1.2. ApproachThe ToR requested that both a top-down and a bottom-up approach be used in estimating the impacts of the VEET on energy consumption that would subsequently be used to assess the impact of the scheme on wholesale and retail energy prices and the bills of program participants and non-participants.DSDBI provided the bottom-up energy consumption impacts of the annual and lifetime electricity and gas consumption impacts associated with each of the energy efficiency measures that had been eligible for installation under the scheme in the years 2009 through 2012 that were to be used in the bottom-up analysis. These estimates included revisions that were informed by fieldwork that developed real-world information about the persistence of several of the measures that were installed under the scheme, and a subsequent extensive review of the algorithms that had been used in the setting the amount of certificates to be awarded for each of the eligible VEET measures. These activities resulted in a substantial reduction in the energy savings assumed to have been saved by several of the measures and therefore the scheme as a whole.

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The top-down approach that was undertaken did not rely on any assumptions about the efficacy of the measures installed under the VEET, and was undertaken to provide a measure of the scheme’s impact that could be seen as being entirely external to and independent of any assumptions about the scheme itself. The top-down approach involved assessing the impact of a number of factors that would have contributed to differences between the amount of energy actually consumed in the years 2009 through 2012 from the amount that had been forecast to be consumed before the scheme was introduced. These included weather differences, price elasticity, and the impact of other energy efficiency policies and programs. Any residual difference between forecast and actual consumption after accounting for these factors would represent an estimate of the impact of the VEET.The results of both the bottom-up and the top-down analyses were then to be used in assessing the impact of the VEET on wholesale and retail energy prices and the bills of customers that had participated in the VEET and those that had not. Unfortunately, the top-down approach did not provide a feasible estimate of the impact of the VEET. The basic problem was that the raw, non-weather-corrected electricity consumption data for the base and evaluation period that was sourced from the Victorian distribution businesses indicated that the change in consumption for residential and small non-residential customers varied significantly across the distribution businesses. Three of the businesses reported reductions over the period that ranged from 5.1% to 8.9%. The other two businesses reported much smaller reductions over the period, at 1.6% and 1.8% respectively. After accounting for the effects of the factors discussed above, the result of the top-down analysis was that the impact of the VEET for the two distribution businesses with very low reductions in consumption was that the VEET had served to increase consumption by between 5% and 6%. There were also concerns regarding the results of the top-down approach for the other three distribution businesses. As a result, use of the top-down approach as the basis for estimating the impact of the VEET scheme was not deemed to be appropriate, it was not used as an input to the assessment of the scheme’s impacts on wholesale and retail energy prices. However, the results of the top-down approach can still provide a valuable, high-level sense-check to the bottom up estimates of the impact of the VEET. Specifically, DSDBI can cross-check the results of the bottom up approach against the estimated impact of other policy drivers as derived in the top-down approach. The relativity of their impacts can serve as a useful cross-check of the sensibleness of the bottom-up estimates.

1.3. Findings and caveats

1.3.1. FindingsThese findings should be considered in light of the caveats discussed in section 7.2 below.

99.3% of all scheme savings were produced by just nine of the 28 eligible measures.

And these addressed just four end uses:

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lighting (64.7%) – which involved the replacement of GLS (incandescent) lamps with high efficiency lighting; water heating (17.3%) – which predominately included the replacement of electric storage water heating equipment with gas or LPG storage, instantaneous or gas-boosted solar water heating;standby power (13.8%) – which comprised the installation of control units that automatically reduce the amount of time appliances in the home such as home entertainment units and computers spend in standby mode; and space heating (3.6%) -- which predominately included the replacement of electric resistance space heating with ducted gas heating.

As a result, the rest of the analysis concerned only these nine measures.Business customers accounted for only 0.1% of the savings produced by these measures. Therefore, the impacts on business customers were not considered further in the analysis.

The VEET produced material energy savings – mostly reducing the use of coal – but did not impact peak electricity demand to any material extent.

The electricity savings produced by the measures installed under the VEET in the years 2009 through 2012 are material, amounting to just over 5,400 GWh cumulatively by the end of 2020. The 424,965 MWh saved in 2012 alone equates to approximately 2.2% of Victoria’s residential and SME electricity consumption in that year.Virtually all of the energy saved (99.3%) comes from reduced use of coal for electricity generation, which is consistent with the scheme’s objective of reducing carbon emissions. This high impact on coal in part reflects the times of day that the measures eligible for installation under the VEET from 2009 through 2012 affect electricity use. Just under 65% of the savings come from the replacement of standard light globes with high-efficiency alternatives. Clearly, most of these savings will occur in evening hours. Another 15% comes from energy efficiency measures installed on off-peak water heaters, where virtually all of the savings will accrue at night.However, this time distribution of electricity savings – with most of its impact in the evening – means that the scheme’s impact on electricity peak demand, which tends to occur in the afternoon or early evening of hot summer weekdays, is correspondingly small. The analysis undertaken in this study suggests that the scheme’s impact on peak demand reaches its highest point at 41 MW in 2013, representing just 0.4% of the peak demand in Victoria that year.

Impacts on gas were both smaller and in the opposite direction as compared to those for electricity.

Overall, gas consumption increased by over 134,000 GJ due to the program through 2020. This is not surprising given that a number of the most popular measures offered under the VEET during the years 2009 through 2012 involved changing out electricity equipment for gas-fired equipment. For example, 39% of the more than 45,000 installations that concerned water heating equipment involved the replacement of electric water heating equipment by gas-fired equipment.

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Even so, the increase was not material: the increase in gas consumption of 110,600 GJ due to the scheme in 2012 represents only about 0.1% of Victoria’s residential gas consumption in that year. For this reason, the impacts on gas were not considered further in the analysis. As a result, the benefits to participants developed in this analysis are slightly overstated, as they do not include the increased cost of gas that participants would have incurred due to those measures that substituted gas for electricity use.

The reduction in electricity generation will have reduced electricity sector production costs, and because of that, wholesale electricity prices.

Based on the results of the analyses undertaken, the VEET will produce savings in electricity system production costs with a net present value of just over $103 million (in 2012 dollars) by 2020. These savings will almost wholly result from reduced fuel costs and reductions in other variable operating and maintenance expenses.Those savings – and a slight impact on the bidding behaviour of generators due to the increased competition to meet reduced demand – result in downward pressure on wholesale electricity prices in Victoria and the other NEM jurisdictions. In Victoria, the VEET reduces wholesale market prices by $0.30/MWh (approximately 0.8%) on average over the study period. Average reductions over the study period in the other NEM jurisdictions range from a low of $0.03/MWh in South Australia to a high of $0.08/MWh in New South Wales.

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The VEET will have produced material net financial benefits for program participants, EREP sites and all electricity users outside Victoria. However, customers in Victoria that did not participate in the VEET (other than EREP sites) will have experienced net financial costs.

All customers in the NEM benefits from the downward pressure exerted by the VEET on wholesale electricity prices, but VEET participants accrue additional benefits due to the reduced electricity consumption produced by the measures installed under the VEET – so they have a lower price and a lower volume. This combination is more than enough to overcome the increases that result from networks in Victoria needing to increase unit prices to recover their revenue requirements across reduced sales, and retailers needing to recover the costs of creating or purchasing certificates to meet their obligations under the VEET. The prices of EREP sites within Victoria and all non-Victorian electricity users are not subject to these cost-recovery price increases.Non-participants in Victoria who share in the costs of the VEET (i.e., all customer classes except very large customers who were liable under the EREP program) experience net costs. This is because the increases in their bills due to increased network unit prices and increased retail charges to recover the costs of complying with the VEET outweigh the impact of the reductions in wholesale electricity prices engendered by the scheme.EREP sites in Victoria and customers in other NEM jurisdictions are not subject to these increases in network and retail costs, and therefore experience net benefits due to lower wholesale electricity price.Table 1 on the next page summarises the present value of the benefits and costs experienced by the average VEET participant and various classes of non-participant in Victoria1 between 2009 and 2020. The reductions in wholesale electricity price induced by the VEET in other NEM jurisdictions also produces $64 million ($2012) in net benefits for non-Victorian electricity users over that same time period.

1 The figures in the table represent the benefits and costs that accrue to the average customer within each of the customer classes shown. The scale of the impact on different customer classes reflects the amount of electricity consumed by the average customer within each class. This is why the impact on EREP customers – who are the largest electricity consumers in the state – is so much larger than for any of the other customer classes.

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Table 1: Average VEET benefits & costs per participant and non-participant in Victoria ($2012, 2009 – 20)

Customer class

Benefits Costs

Net benefit

Wholesale price

reduction

Reduced usage

Total benefit

Increased

network price

Retailer recovery

of program

costs

Total cost

Residential participants

$12.06 $824.66 $836.72 $79.50 $86.23 $165.73 $670.99

Residential non-participants

$13.13 NA $12.00 $89.25 $92.50 $181.75 -$169.75

Small commercial customers

$61.19 NA $55.89 $0.00 $129.52 $129.52 -$73.63

Medium commercial and small industrial customers

$313.99 NA $286.94 $0.00 $646.67 $646.67 -$359.73

EREP customers

$151,185.00 NA $138,065.

00 $0.00 $0.00 $0.00 $138,065.00

Source: OGW analysis

Overall, the program has a negative net economic benefit from the total resource cost perspective of the electricity sector; that is, its costs outweigh the benefits it has provided.

The financial benefits and costs summarised above for VEET participants and non-participants include a significant amount of transfers. For example, some of the benefit experienced by program participants are subsidised by costs incurred by non-participants and some of the benefits experienced by program participants and non-participants come at the expense of reduced net revenue achieved by the shareholders of various parts of the electricity supply chain.

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The total resource cost (TRC) perspective assesses the economic benefits and costs of the VEET (or any supply or demand side option) from the perspective of the electricity supply and demand chain overall. Essentially, it measures the total cost of different means – including energy efficiency improvements – for meeting end-use electricity requirements. In this way the TRC can be used to assess the VEET (or any demand-side option) as simply another resource option for meeting customer energy requirements. In the TRC, the costs of the VEET as a resource option include the total costs of the program, including all costs incurred by participants, and the electricity supply chain in developing and implementing the program. The benefits of the VEET as considered by the TRC are all costs that are avoided across the electricity supply chain due to the program, valued at their marginal costs.The TRC differs from the societal perspective in that it does not include consideration of externalities (such as, but not necessarily limited to, environmental impacts, employment impacts or impacts on energy supply security), or costs incurred by government or other bodies in developing, implementing, administering or evaluating the program that are not recovered through electricity price mechanisms. In the present instance, the fact that the electricity price used includes a carbon price means that at least some proportion of the environmental externality will be included in the TRC.Table 2 presents the benefits and costs of the VEET from the TRC perspective (including carbon costs).Table 2: VEET economic benefits and costs – TRC perspective ($2012 million, 2009 – 20)

Benefits Costs

Net benefit

Reduced fuel and variable

O&M costs

Reduced fixed

production costs

Total benefit

Participant costs

Certificate costs

Scheme complianc

e costs

Total cost

$103.13 $0.01 $103.14Not con-

sidered$268.23 $12.54 $280.77 -$177.63


1.3.2. Caveats

The energy savings of the VEET are not measured results – they have been have been derived from engineering estimates augmented by post-installation surveys to revise persistence assumptions.

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DSDBI and Sustainability Victoria have made a thorough review and refinement of the algorithms originally used to estimate the energy consumption impacts of the VEET measures. The algorithms themselves are quite sophisticated and take into account all of the factors that could reasonably be thought to affect scheme savings. The decision to commission fieldwork on the persistence of several measures – particularly standby power controllers – has also served to significantly refine and revise the estimated energy savings of the scheme.However, there has been no attempt to measure the actual, real-world impacts of the measures. As a result, these estimates may over- or under- estimate actual, real-world energy savings and other impacts of the scheme.

There is significant uncertainty regarding the time distribution of VEET measure savings

There is no direct data on the time distribution of the energy impacts of the measures installed under the VEET. For the purpose of this study, these impacts have been estimated based on the professional experience of OGW.In addition, it has been assumed, based on the data provided by DSDBI and Sustainability Victoria, that the water heating and shower rose measures (which account for approximately 17.3% of all VEET savings) have been installed only on off-peak water heaters, and therefore have no impact at times of generation system peak demand. To the extent that the measures may have had larger impacts on peak demand, program benefits would be larger.

Network benefits have not been considered

While we believe that this is unlikely to materially affect the overall assessment of the costs and benefits of the measures installed from 2009 through 2012, due to their likely impacts on peak demand and geographic spread, it is an issue that may warrant consideration in future evaluations to the extent that the measures to be assessed as part of such evaluations are likely to have larger impacts on peak demand.

The economic cost of the program has probably been overstated

This is because we did not have any information on the actual cost of ‘producing’ the certificates (which would include the cost of the measures, less any contribution from participants; the cost of installing the measures, the cost of being accredited under the VEET; and the overhead costs of the certificate-creating enterprise). Rather, we used the market-clearing price of certificates as the proxy for these costs, as it was available and information on those costs was not. It is important to recognise, however, that the market clearing price in theory, represents the marginal cost to the marginal producer that is required to clear the market for certificates. The use of the market clearing price as the basis for establishing the overall costs of the VEET will therefore over-state costs, in so far as it also includes the producer surplus that certificate creators generate from the scheme. However, we do not consider this to be a material issue, given the high volume, low margin nature of the products offered under the scheme (which impact on the slope of the supply curve, and hence, the level of producer surplus).

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2. Introduction2.1. Overview of the Victorian Energy Efficiency Target

(VEET) schemeThe Victorian Energy Efficiency Target (VEET) scheme (promoted publicly as the "Energy Saver Incentive" or "ESI") is a market-based scheme designed to promote the uptake of energy efficiency improvements in residential and non-residential premises. It was established under the Victorian Energy Efficiency Target Act 2007 (the Act) and commenced on 1 January 2009.The scheme works by setting a greenhouse gas (GHG) abatement target that is to be met through the uptake of prescribed energy efficiency activities. These activities are specified in the scheme regulations and, when undertaken by scheme-accredited parties, result in the creation of Victorian energy efficiency certificates (VEECs); each VEEC represents one tonne of GHG abatement). The scheme also places a liability on large energy retailers that operate in Victoria to acquire and surrender VEECs in an amount that is proportional to their individual share of the sales of electricity and gas to residential customers within the state, and that in aggregate will meet the overall abatement target set by the scheme.During its first three-year phase (2009 through 2011) the VEET scheme was aimed at energy efficiency uptake in the residential sector with a target of 2.7 million VEECs per annum (or 2.7 million tonnes of GHG abatement per annum). In its second phase, (starting on 1 January 2012) the target was raised to 5.4 million VEECs per annum and the scheme activities made available to small and medium enterprises as well as the residential sector. The VEET scheme is legislated to continue in three-year phases until 1 January 2030, with the target to be reset in the VEET regulations before each three-year phase.

2.2. Purpose of this studyThe purpose of this study is to identify costs and benefits of the VEET scheme in terms of the measures installed since its inception in 2009 through the end of 2012. At the time the Terms of Reference (ToR) for this study were being prepared, the scheme had completed just over four full years of operation. This review was undertaken to assess the impact that the reduction in energy consumption that has resulted from the measures installed in Victorian residences and businesses under the program during that time on wholesale energy costs and retail energy prices, and how this has affected the bills of customers that have participated in the scheme and customers that have not done so.

2.3. Overview of the methodological approach requested in the ToRThe ToR requested that both a top-down and a bottom-up approach be used in estimating the impacts of the VEET on energy consumption that would subsequently be used to assess the impact of the scheme on wholesale and retail energy prices and the bills of program participants and non-participants.

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The bottom-up energy consumption impacts were provided by DSDBI. These impacts were developed by DSDBI through the following steps:

with input from Sustainability Victoria, DSDBI had re-visited the algorithms used to originally set the number of VEECs (and therefore the electricity and gas consumption impacts) associated with each of the energy efficiency measures eligible for installation under the scheme in the years 2009 through 2012, andwith input from external consultants, DSDBI had conducted a number of follow-up studies concerning the persistence of some of the measures that had been eligible for installation under the VEET from 2009 through 2012.

Using the results of these two undertakings, DSDBI developed a revised estimate of the annual and lifetime electricity and gas consumption impacts associated with each of the energy efficiency measures that had been eligible for installation under the scheme in the years 2009 through 2012. These estimates were provided to OGW.However, the ToR also requested that the VEET scheme’s impact on energy consumption be estimated through an alternative, top-down approach. This would provide an approach that did not rely on any assumptions about the efficacy of the measures installed under the VEET, and could therefore be seen as potentially providing an independent, external measure of the scheme’s impacts. The top-down approach was to be undertaken through extrapolation of the observed deviation between the amount of energy actually consumed in the years 2009 through 2012 from the amount that had been forecast to be consumed before the scheme was introduced. Under the top-down approach the impacts of all key variables that may have contributed to this deviation were to be calculated, with the residual assumed to represent the impact of the VEET. Variables identified in the ToR for inclusion in the top-down approach included (though were not necessarily to be limited to):

price elasticities of electricity and gas consumption;economic activity (potentially disaggregated for specific industries);take-up of rooftop solar PV;the impacts of other energy efficiency schemes; andweather.

The results of both the bottom-up and the top-down analyses were then to be used in assessing the impact of the VEET on wholesale and retail energy prices and the bills of customers that had participated in the VEET and those that had not.Appendix A contains the full ToR.

2.4. Findings concerning the efficacy of the approaches un-dertaken

2.4.1. The bottom-up approachThe bottom-up approach was implemented relatively straightforwardly. It involved:

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assessing the load profile impacts of each of the measures installed under the VEET from 2009 through 2012 by apportioning the estimated energy savings of each measure to different hours of the day for weekend and weekdays by season;using the results to create a ‘with VEET’ and ‘without VEET’ load profile for the years 2009 through 2020; running each of those load profiles through the CEMOS electricity market simulation model; comparing the outputs of the two runs with regard to key variables such as wholesale market energy price, generation by fuel type, and plant by capacity type.

The change in consumption and wholesale energy price was then used to calculate the change in retail electricity price and the impact of the program on the bills of customers that had participated in the VEET and those that hadn’t.These undertakings are discussed in detail in sections 4 through 6 of this report.

2.4.2. The top-down approachThe top-down approach was premised on deconstructing the changes in residential and small non-residential energy consumption at the distribution network area level over the 1 January 2009 to 31 December 2012 period. It involved the following four tasks:

identifying the raw, non-weather corrected, change in average residential (and small commercial) consumption over the period 2008 to 2012 (‘the base and evaluation period’);weather correcting that consumption; determining the contribution that pricing and other policy measures had had on the observed changes in consumption after the effects of weather had been removed, anddetermining the residual amount of the change over the evaluation period that was not attributable to weather impacts, pricing or policy impacts, and assuming that this represented the impact of the VEET scheme.

The raw, non-weather-corrected electricity consumption data for the base and evaluation period was sourced from the Victorian distribution businesses. These data indicated that the change in consumption for residential and small non-residential customers varied significantly across the distribution businesses. Three of the businesses reported reductions over the period that ranged from 5.1% to 8.9%. The other two businesses reported much smaller reductions over the period, at 1.6% and 1.8% respectively. The larger reductions reported by three of the businesses were broadly similar to those reported by AEMO in its 2013 National Electricity Forecasting Report2.

2 Available at http://www.aemo.com.au/Electricity/Planning/Forecasting/National-Electricity-Forecasting-Report-2013. AEMO’s data indicated that average per capita consumption of residential and small commercial customers had reduced by about 7.2% between 2008/09 and 2011/12.

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This relatively large difference between the changes in consumption reported by the two groups of distribution businesses created a difficulty for the remainder of the top-down analysis. It implied that there would need to be a significant difference in one or more of the following other factors between the distribution businesses characterised by higher and lower reductions in residential consumption:

the relative take-up of the VEET measures across the five distribution areas,the effects of weather across the five distribution areas, and/or the impacts of pricing (i.e., price elasticity) or policy measures other than the VEET.

The first factor was deemed unlikely to have been significantly different across the distribution businesses based on an examination of VEET program records. Weather data specific to each of the distribution businesses was not available, so it is not possible to say with certainty whether that factor might have accounted for any of the apparent differences in consumption change between the two groups of distributors, but the magnitude of the change and the fact that differences of this magnitude were observed between adjoining distribution systems makes this seem unlikely. That leaves the impacts of policy measures other than the VEET and the impact of price increases, neither of which seem likely to account for the strongly geographic-based differences observed.In the absence of an explanatory variable for the differences in the change in residential consumption over the 2008-2012 period, the top-down approach was not able to provide a feasible estimate of the amount of change in energy consumption that should be attributable to the VEET for two of the distribution systems. For those businesses, the top-down approach period indicated that the residual change which should be attributable to the VEET – after correcting the observed changes in energy consumption for the effects of weather, price elasticity, and the several other policy interventions at play during that time period (including minimum energy performance standards and the take-up of rooftop PV systems) – was a net increase in energy consumption of between 5% and 6%. This is not likely to be accurate.For the other three distribution areas the top-down approach indicated that the residual change in consumption – notionally the impact of the VEET scheme – was a reduction in the range of 0.2% to 1.8%.Even for these businesses, however, there are factors that argue against putting much faith in the top-down result it as an estimate of the impacts of the VEET. These include:

The fact that (a) the actual price elasticity of the residential customer sector is not known with any real precision and (b) the results of the top-down approach are very sensitive to the price elasticity value used. Sensitivity analysis showed that a change in elasticity factor from the -0.15 used in the analysis to -0.25 changed the residual energy consumption that might be attributed to the VEET by something in the order of 2.5% to almost 3%.

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The fact that (c) the likely impact of the VEET is a relatively small percentage of the residential electricity consumption, and (d) the residual of the top-down approach (which would provide an approximation of the impact of the VEET) is the result of a number of corrections and attributions. It must be remembered that each of these will be subject to some margin of error. As a result, the residual itself will be subject to a margin of error and that error band could easily be a significant proportion of the likely impact of the VEET itself.

Based on these considerations, use of the top-down approach as the basis for estimating the impact of the VEET scheme was not deemed to be appropriate, and as a result, it was not used as an input to the assessment of the scheme’s impacts on wholesale and retail energy prices. However, the results of the top-down approach can still provide a valuable, high-level sense-check to the bottom up estimates of the impact of the VEET. Specifically, DSDBI can cross-check the results of the bottom up approach against the estimated impact of other policy drivers as derived in the top-down approach. The relativity of their impacts can serve as a useful cross-check of the sensibleness of the bottom-up estimates.As an example, Table 3 on the following page provides a comparison of the impacts of the different policy drivers that were considered within the top-down approach and those of the VEET.

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Table 3: Comparison of policy impacts from the top-down approach with the bottom-up impact estimate of the VEET (GWh)

Policy 2009 2010 2011 2012

MEPS – Lighting 15.35 34.80 66.63 108.19MEPS - AC Res 0.11 0.23 0.35 4.95Insulation 14.84 59.35 59.35 59.35Solar Water Heater 9.62 22.42 39.34 59.69Solar PV 12.91 65.22 220.08 338.40VEET scheme 66.19 220.68 266.07 447.33VEET scheme impact as a proportion of all other policy impacts

125.29% 121.24% 68.97% 78.40%


As can be seen, the bottom-up analysis suggests that the VEET scheme has had a larger impact on residential electricity consumption than solar PV in every year from 2009 through 2012. Further, in the first two years, the VEET appears to have had a larger impact than all of the policy initiatives considered combined.Although it is not possible to use the figures above to reach a conclusion regarding the reasonableness of the bottom-up estimates of the impact of the VEET, the comparison can provide a useful check-point for those estimates. To the extent that the comparison suggests that the current estimates of VEET impacts may be optimistic, DSDBI may wish to consider further modifications to the manner in which program impacts are estimated.Appendix B contains the findings of the top-down approach.

2.5. Organisation of this reportThe remainder of this report is organised as follows:

Section 3 presents a list of the key assumptions that were made in each part of the analyses undertaken;Section 4 provides an overview of the energy consumption impacts of the measures installed under the VEET from 2009 through 2012 as provided by DSDBI as an input to this study;Section 5 presents the results of the analysis of the impacts of the VEET on wholesale and retail energy prices;Section 6 discusses the distributional impacts of the VEET in terms of its impacts on the bills of participants and non-participants, and the net economic benefits of the scheme as a whole;Section 7 presents the conclusions and recommendation of the study;Appendix A contains the terms of reference for the study;Appendix B presents the findings of the top-down approach; and

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Appendix C contains the allocation of VEET measure impacts to seasons, day types and times of day.

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3. Key assumptionsThis section of the report presents the key assumptions used in each of the various parts of the analyses undertaken within the study.

3.1. General assumptions regarding the VEET and other factorsThe following general assumptions were made and have impacts on various parts of the analysis:

VEET impacts can be acceptably represented on an average participant basis, rather than calculating the benefits and costs associated with each unique bundle of measures installed.VEET measures are installed at an essentially equal rate year-round, so that it can be assumed that half of the measures will be installed by June and the other half by December. The gas consumption impacts of the VEET in 2009 through 2012 – at approximately 0.1% of residential gas consumption in Victoria – were not significant enough to warrant consideration of their impacts on gas prices in the wholesale or retail markets. As a result, the impacts of VEET measures on the gas consumption and gas bills of VEET participants have not been included in the analysis, and therefore, participant costs will have been marginally under-estimated and participant net benefits marginally over-estimated. We believe the magnitude of these under- and over-estimates to be immaterial. While the costs incurred by gas retailers have been included in the analysis, all costs have been assumed to have been recovered through electricity prices. This will tend to slightly over-state the impact of the program on electricity tariffs; in actual fact, some program costs may have been recovered in gas prices (though, given the relative levels of activity in electricity and gas, the amount recovered in gas prices can reasonably be assumed to have been quite small).VEET program impacts in general can be adequately represented by the 9 measures (of 28 in total) that account for 99.3% of the electricity savings attributable to all measures implemented in the 2009-12 period. Virtually all of these savings occurred in residential facilities. Savings in business facilities – who only became eligible to participate in the VEET in 2012, the last year included in this study – accounted for less than 0.2% of total VEET electricity savings and less than 0.2% of the savings of the 9 measures used to represent the overall program. Where data provided by DSDBI stated that a VEET measure was applied to off-peak water heating, we assumed that all impacts affected only those hours when off-peak circuits are energised. No allowance was made for ‘drift’ in timers or controls, or for consumer bypass of the control.

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Some measures have useful lives that extend beyond the end of the study period (2020). The use of a longer study period would have shown higher benefits, though these benefits would contribute relatively less to the net present value of the scheme due to discounting.In addition, it was assumed that the benefits of the scheme were limited to the useful life of the measures installed under the scheme. No assumption was made that participating households would permanently reduce their consumption in the end-uses affected by the scheme after the useful life of the initial measure(s) installed.It should also be noted that because our calculation of the benefits obtained by participants in the VEET scheme used the single rate tariff, program savings associated with water-heating measures will be somewhat over-valued (because the off-peak tariff rate is lower than that in the single tariff). Similarly, the network revenue reductions associated with these measures – which affect the distributional impacts of these measures on non-participants – will also have been over-estimated.Weighted average TUoS and DUoS charges at the state level are acceptable approximations of the charges that would apply to VEET participants and non-participantsA discount rate of 7% was used to undertake all net present value calculations. This is the same value used in the original Regulatory Impact Statement (RIS) for the VEET,All dollar figures are reported in present value 2012 terms unless stated otherwise.All results are reported on a calendar year basis unless state otherwise.

3.2. Assumptions regarding VEET impacts on the transmis-sion and distribution components of the retail billWith regard to the impact of the VEET on the transmission and distribution portions of the retail bill, it was assumed that:

Network-use-of-system (NUoS) charges to residential consumers continue to be levied through 2020 on the same tariff structure as at present.The transmission (TUoS) portion of NUoS charges to residential consumers continue to be levied in relative proportion to applicable distribution (DUoS) charges.The VIC network businesses continue to operate under a Weighted Average Price Cap (WAPC) form of price regulation through 2020, and the VIC transmission business operates under a Revenue Cap form of price control through 2020.The VIC distribution businesses did not take the impacts of the VEET into account when they forecast sales volumes for the 2006-10 period, but will have done so with regard to residential sales (but not non-residential sales) in the 2011-15 and 2016-20 regulatory periods.The actual reductions in sales volumes experienced by the VIC distribution businesses in 2011 and 2012 were exactly equal to the reduction in sales that was forecast by those businesses.

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The VEET did not have any impact on DB capital costs from 2009 or 2010. This assumption was based on the relatively small impact on peak demand that was identified as having resulted from the VEET, and the relatively wide geographic spread of take-up of the scheme.The distribution businesses did not forecast that the VEET would have any impact on capital costs in the 2011-15 period, and that they will not forecast that it will have any such impact on network costs in the 2016-2020 regulatory period either.The distribution businesses will seek to recover revenue shortfalls due to lower than forecast sales volumes from those customer classes whose consumption lagged forecasts.This revenue shortfall is approximated by multiplying the variable prices that would have applied to that lost consumption (TUoS and DUoS) by the amount of energy not consumed as a result of the VEET scheme.

3.3. Assumptions regarding the VEET’s impact on the retail component of the billWith regard to the impact of the VEET on the retail component of the retail bill, it was assumed that:

Retailers will seek to recover in full any costs incurred due to the program.Retailers will seek to recover these costs from those customer classes that were eligible to participate in the program (and not from other customer classes).Retailers will seek to recover operating costs associated with the program in the same (or succeeding) year in which they are incurred.Retailers will seek to recover capital costs associated with the program as soon as possible. For the purpose of the analyses undertaken, it was assumed that all such costs would be recovered within three years.The published information on monthly certificate prices multiplied by the number of certificates surrendered in that month represents an acceptable (though likely over-estimated) proxy for the cost incurred by retailers for certificate creation.Retailers will recover costs incurred through increases on variable charges rather than through an increase in a fixed charge.VEET participants have taken up market offers in the same proportion as VIC residential customers overall.The variable charge paid by residential customers on market contracts can be suitably represented by the straight arithmetic average variable charge across all market offers.The variable charge paid by residential customers on standing offer contracts can be suitably represented by the variable charge in the standing offer of the host retailer in each of the distribution service areas.

3.4. Key assumptions made in the analysis of the distribu-tional impacts of the VEETIn calculating the distributional effects of the VEET it was assumed that:

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All costs related to the VEET (whether actual costs or reduced revenues) will be recovered proportionally from those customer classes eligible to participate, in proportion to the relative sales volumes of those classes.Changes to wholesale energy price are reflected instantly and in full in the retail prices charged by retailers to customers, and that this applies to customers in all customer classes, regardless of their eligibility to participate in the VEET, or whether they are located within or outside Victoria.The overall impact of the VEET was not large enough in absolute terms to change the costs incurred by retailers for financial hedging of their residential load.

3.5. Key assumptions made in the analysis of the net eco-nomic benefits of the VEETIn calculating the net economic benefits of the VEET from the perspective of the electricity sector as a whole, we have not sought to quantify the allocative efficiency benefits stemming from changes in the bidding behaviour of market participants (though, in fact, we believe these benefits to be immaterial in the case of the VEET).

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4. Impact of the VEET on energy consumption4.1. Purpose and overview of the bottom-up approach

The bottom-up approach used information regarding the annual electricity and gas consumption impacts and useful lives of each of the measures that were eligible to be installed under the VEET from 2009 through 2012, and the number of each measure that were actually installed in each of those years. This information was provided by DSDBI with assistance from Sustainability Victoria and external consultants. The information provided by DSDBI accounted for each of the following factors in relation to each measure installed under the VEET from 2009 through 2012:

Gross energy impacts per typical installation, including consideration of:the useful life and size of the equipment being replaced and installedthe impact of both energy reductions and increases where the measure included fuel switching (for example, where there was a switch from the use of electric end-use equipment to gas-fired equipment);

The number of installations per year within each of four regions, which allowed for climate based variations in energy savings; andA global discount factor, which took into consideration the following factors:

compliance, which accounts for the fact that no program achieves 100% compliance with its rules, and the fact that not all measures will be used for the full course of their useful lives (persistence)additionality, which attempted to account for the level of take-up of each measure that would have occurred under business as usual conditions (i.e., the level of take-up that would have been expected in the absence of the VEET scheme, but including the influence of other policy measures that are in place)rebound, which takes into account the potential for some customers to increase their amenity or comfort due to the reduction of their energy bill, in which case, energy savings will not be as high as might otherwise have been achieved.

OGW was not asked to critically review the bottom-up savings estimates.

4.2. Bottom-up energy consumption impactsTable 4 on the following page summarises the energy consumption impacts of the VEET activity measures that were installed between 2009 and 2012 as reported in the bottom-up analysis provided to OGW by DSDBI and Sustainability Victoria. Note that in the table, negative values connote reductions in consumption, while positive numbers indicate that consumption increased.

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Table 4: Overview of energy consumption impacts from 2009 through 2012 of VEET activity measures installed between 2009 and 2012

Fuel Customer segment

Annual consumption impact Cumulative impact

2009-202009 2010 2011 2012

Electricity (MWh)

Residential -66,188 -220,683 -266,070 -445,515 -5,350,596

Business -1 -1,811 -37,969

Total electricity -66,188 -220,683 -266,071 -447,326 -5,388,566

Gas (GJ) Residential -19,218 -15,286 10,005 108,189 96,654

Business 3 2,415 37,563

Total gas -19,218 -15,286 10,007 110,604 134,217

Source: OGW analysis of DSDBI/Sustainability Victoria bottom-up results

The table provides two important insights:Overall, gas consumption increased due to the program. This is not surprising given that a number of the most popular measures offered under the VEET during the years 2009 through 2012 featured changing out electricity equipment for gas-fired equipment. For example, 39% of the more than 45,000 installations that concerned water heating equipment involved the replacement of electric water heating equipment by gas-fired equipment. Clearly, the impact of these change-outs will have been to increase gas consumption. By contrast, only 19.8% of the water heating installations involved measures that would have reduced gas consumption. In addition to the impact of the VEET on gas being an increase, the absolute magnitude of the impact was materially smaller than the scheme’s impact on electricity. The increase of 110,600 GJ in 2012 represents approximately 0.1% of Victoria’s residential gas consumption in that year. By contrast, the reduction in electricity consumption in 2012 of 447,326 MWh represented approximately 2.3% of Victoria’s residential and SME electricity consumption in that year.

Business customers accounted for an exceedingly small portion of the program impacts – less than 0.2% of the impacts on electricity consumption and less than 3% of the impacts on gas consumption.

Further, inspection of the 28 individual activity measures that were offered under the VEET in the years 2009 through 2012 reveals that 9 of them accounted for 99.3% of all electricity saved (see Table 5 below), and that this occurred in just four end uses:

lighting (64.7%)

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water heating (17.3%)standby power (13.8%)space heating (3.6%).

Table 5: VEET savings by activity measure and end use

Measure No

Measure descriptionMeasure savings 2009-12 (MWh)

% total VEET electricity savings2009-12

1A Replace electric storage water heater with gas or LPG storage water heater 16,191 1.6%

1B Replace electric storage water heater with gas or LPG instantaneous water heater 29,053 2.9%

1C Replace existing electric water heater with electric boosted solar or heat pump water heater

71,404 7.1%

1D Replace existing electric water heater with gas or LPG boosted solar water heater 34,235 3.4%

17 Install low-flow shower rose 21,569 2.2%Subtotal – water heating measures 172,270 17.3%

29 Install (one or more) stand-by power controllers (SPCs) 138,068 13.8%

Subtotal – standby power control 138,068 13.8%

6 Replace large central electric resistance space heating with high efficiency ducted gas heating system

35,629 3.6%

Subtotal – high efficiency space heating 35,629 3.6%

16A & 21A

Replace GLS lamp with a low energy lamp 617,515 64.7%

Subtotal – high efficiency lighting 617,515 64.7%

All others All others 7,241 0.7%Total VEET savings 1,000,255 100.0%Sub-total of measures assessed in this study 993,014 99.3%

Source: OGW analysis of Sustainability Victoria bottom-up results

Based on these findings and in consultation with DSDBI, it was decided that the assessment to be undertaken later in the study of the impact of the VEET on the wholesale energy market and the bills of customers who participated and did not participate in the program would:

address electricity only, anduse the 9 residential measures that account for 99.3% of all electricity savings achieved under the program to stand for the program as a whole.

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5. Impact of the VEET on energy markets5.1. Purpose and overview of this task

The overall purpose of this task was to assess the impact of the VEET on the prices paid for energy by electricity and gas customers. This was undertaken by assessing the impact of the VEET on:

wholesale energy production costs and prices via a market simulation model,transmission and distribution system costs and prices through the assessment of the impact of the throughput volume changes caused by the VEET on network revenue, and any impact of the VEET on network capital requirementsretail operating costs, including costs incurred in complying with the program.

The outputs of these separate analyses were combined to assess the overall impact of the VEET on retail energy prices.Based on the results of the bottom-up and top-down analyses it was decided in consultation with DSDBI that:

only the results of the bottom-up analysis would be used3, and the analysis would focus on the electricity market only4.

5.2. Impact on wholesale electricity market and wholesale component of the retail bill

5.2.1. Overview of the approach usedThe impact of the VEET over the period of interest (2009 through 2020) was analysed through the use of the CEMOS market simulation model.CEMOS is a linear optimisation model set up to examine the NEM in either of two modes: least cost analysis or market behaviour analysis. In the former, the model provides information on the costs of supplying the assumed demand at least cost. In the latter, the price that would be assumed to pertain in a competitive, privatised market is the key output, although the (resource) cost incurred in meeting demand is also reported, along with information on all other relevant operating parameters of the generation system.In this study we used the market behaviour configuration which includes a Cournot-Nash profit maximising algorithm to determine generator bidding behaviour. The Cournot-Nash algorithm takes account of generation portfolios and determines the price that should be set for each generator such the price-volume trade-off is optimised and any generator that offers a higher price will lose more revenue due to reduced dispatch volume than it gains from a higher market price and similarly chasing higher volume by offering a lower price will also result in lower revenue due to reduced market price. CEMOS has been used in market bidding mode to examine:

3 See section 2.4.2 for the reasons why it was decided not to undertake the top-down analysis.

4 See section 4.2 for an explanation of why it was decided not to assess the impacts of the VEET on the gas market.

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the impact of carbon pricing and the renewable energy target for AEMC; the peak demand reduction that may have resulted from NSW’s Energy Savings Scheme, and any consequent reductions in wholesale electricity price, for the NSW Office of Environment and Heritage;the impact that the first two to three years of operation of the VEET, ESS and REES had on wholesale electricity market prices, generation system capacity requirements, fuel usage and carbon emissions, for the AEMC; andthe potential impact of four demand-side program options on the wholesale energy market of the NEM which was undertaken as part of a multi-market study commissioned by the International Energy Agency.

CEMOS has also been used to provide advice to private clients on generation asset market entry, merger and acquisition proposals. CEMOS uses the most recent publicly available data on forecast demand, and the costs, operating characteristics and capacities of existing and committed generation and transmission across the NEM, and the costs, operating characteristics and capacities of candidate generation facilities.Model outputs include:

Wholesale price by NEM price region (jurisdiction) and for the NEM as a wholeFor individual generators, portfolios and the generation sector as a whole:

capacity and fuel mix over time, including entry and exitdispatchfuel useemissionsspot market revenue.

5.2.2. Model configurationBecause this study required assessment of the impacts of the VEET in both a historical period (2009 through 2012) and a future period (2013 through 2020) CEMOS had to be configured in two slightly different approaches.

Historical period configurationIn the historical period actual outturn results are available – for example, the prices that actually resulted in the wholesale market. These prices include the impact of the VEET. Therefore, to estimate what prices would have been in the absence of the scheme, the impacts of the program on the demand profile need to be added back to the consumption in those years.

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However, it must be recalled that the price that eventuated in those years was the result of not only the VEET, but also a number of other factors. Those factors include actual weather (as opposed, for example, to the weather that would have been assumed in forecasts of price for those years, as encapsulated in the 10- 50- and 90-POE5 scenarios that are used in most forward-looking market simulations), and any actual forced outage that occurred (as opposed to the forced outage rates that would be assumed in any forward-looking assessment). It is impractical (and within the time and budgetary resources that were available for this assignment, impossible) to load into the model (a) the actual price stack (supply curve) for all generators across the NEM (that is, the prices that the generators actually offered each half hour over the course of the historical years in response to the actual conditions that pertained in those years) plus (b) the operating constraints that impacted AEMO’s calculation of dispatch and pricing for each half hour over the four years of interest. Put another way this means it is not practical to simply substitute the calculated ‘without VEET’ estimated demand into the model to determine the prices and dispatch that would have prevailed without the VEET and compare that outcome to the actual. However, it is practical to use the model to determine modelled prices in both the ‘with VEET’ and ‘without VEET’ cases. While the ‘with VEET’ result of this process may not match the actual half hour prices that actually occurred in the historical years, the difference between the modelled prices of the ‘with’ and ‘without’ cases will provide a useable approximation of the difference that would have occurred in practice. This approach was pragmatically achievable within the available time and at a reasonable cost. It also avoided the need to explicitly assess changes in generator bidding behaviour for the particular market conditions that prevailed – for example if in the ‘with VEET’ case generators had “parked” capacity in the bid stack at a high price but were prepared to rebid if the affected capacity was called by AEMO, which is something that would need to be considered if actual half hour by half hour bid stacks were to be used.

Future period configurationThe model was run for the forecast period of 1 January 2013 to 31 December 2020 using publicly available, current information regarding forecast energy consumption and peak demand; the costs, operating characteristics and capacities of existing and committed generation facilities across the NEM; and the costs, operating characteristics and capacities of candidate generation technologies. Further detail regarding the key input data used in the assessment of the VEET’s impact on the wholesale electricity market and prices is presented in the following section.

5.2.3. Key inputs to the modellingThe key inputs used by the CEMOS model include:

the energy and demand forecast

5 POE stands for ‘probability of exceedence’, which is defined by AEMO as “The probability, as a percentage, that a maximum demand level will be met or exceeded (for example, due to weather conditions) in a particular period of time. For example, for a 10% POE maximum demand for any given season, there is a 10% probability that the corresponding 10% POE projected maximum demand level will be met or exceeded. This means that the10% POE projected maximum demand level for a given season is expected to be met or exceeded, on average, 1 year in 10.”

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the costs and performance of existing, committed and new entrant generation planforecast fuel pricesthe carbon pricethe transmission network configuration.

The sources of information used for each of these inputs are discussed below.

Energy and demand forecastsIn the 2009 through 2012 period the demand that actually resulted includes the impact of the VEET. Essentially, the actual energy consumption and peak demand is the result, in part, of the VEET. To estimate what energy consumption and peak demand would have been in the absence of the scheme, we added back the impacts of the VEET as determined in the bottom-up analysis provided by DSDBI and Sustainability Victoria to the outturn demand in the years 2009 through 2012.AEMO’s Electricity Statement of Opportunities (ESOO) served as the starting point for the energy and demand forecasts for the forecast period years of 2013 through 2020. However, the 2012 ESOO explicitly took into consideration the effects of a number of energy efficiency policies and programs that have been implemented at the national and state levels, as detailed in AEMO’s 2012 National Electricity Forecast Report (NEFR). National level policies and programs whose impacts were taken into consideration included the Clean Energy Future package, the national Renewable Energy Target (RET) scheme, Mandatory Disclosure (Energy Efficiency Disclosure Act 2010), Minimum Energy Performance Standards (MEPS), the Energy Efficiency Opportunities Program, and the Home Insulation Program (2009-10). At the state level, the “key policy considered in developing forecasts for energy efficiency for Victoria” in the 2012 NEFR was the VEET. The 2012 NEFR provided an estimate of the impact of these national and state-level policies and programs on electricity consumption and peak seasonal demand for each of the states. This estimate included but did not separately identify the impact of the VEET including its expansion from 2012 onwards. As a result, the following steps were undertaken to establish the ‘with’ and ‘without’ energy and demand forecasts for the impact of the measures installed under the VEET between 2009 and 2012:

For the ‘with VEET’ case:Step 1: the 2012 NEFR forecast impact of energy efficiency policies and programs in Victoria – including the VEET scheme – was added back in to the energy consumption and peak demand forecast of the 2012 ESOO, and then Step 2: the energy and demand impacts that the measures installed under the VEET in the 2009 – 2012 period were forecast to have in the years 2013

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through 2020 were subtracted from the energy and demand values calculated in Step 16,7.

The net effect of the two steps above was to remove all forecast impacts of the VEET including the measures installed in 2009-12 plus all expected expansions of the program and then to include in the forecast only the continuing impacts of the measures that were actually installed in the years 2009-12.

For the ‘without VEET’ case, Step 1 above was also undertaken, but step 2 was not. This essentially removed all anticipated impacts of the VEET on energy consumption and peak demand from the forecast.

the forecast impact of the VEET scheme in the 2012 NEFR was added back in to the energy consumption and peak demand forecast of the 2012 ESOO.

It is recognised that this approach also removed the impacts in Victoria of the six policies and programs that were implemented at the national level, but as in the case of the modelling of historical period, the difference between the model outputs of the ‘with’ and ‘without’ cases over the 2013 through 2020 period will provide a useable approximation of the impact of the VEET during that time. As noted above, this approach was necessary because the 2012 NEFR did not include explicit forecasts of the impacts of the individual policies and programs implemented at the national or state levels. Table 6 through Table 8 present:

the 2012 ESOO energy and peak demand forecasts for Victoria;the 2012 NEFR forecasts regarding the energy and peak demand impacts of the energy efficiency programs and policies in Victoria and the other NEM jurisdictions for the years 2013 – 2020

The allocation of the energy savings produced by the measures installed under the VEET in the years from 2009 through 2012 to assess their impact on the overall load profile and peak demand is discussed in section 5.2.4 below.The final ‘with VEET’ and ‘without VEET’ energy and demand forecasts that were used in the analysis of the impact of the VEET measures installed between 2009 and 2012 on the wholesale market and wholesale electricity prices in the years 2013 through 2020 are presented in section 5.2.5.

6 Note that this entailed estimating the load profile and particularly the peak demand impacts of the measures installed under the VEET in the years from 2009 through 2012 from the energy consumption reduction estimates included in the bottom-up analysis provided by DPI and Sustainability Victoria. The process for doing this is described in section 5.24 below.

7 Step 2 also involved adjusting the energy and demand reductions forecast to result over the 2013 – 2020 period from the measures installed under the VEET in the 2009 – 2012 for transmission and distribution losses. This is because the savings were estimated at the end-use level, whereas the market simulation model operates at the generation sent-out level. An average transmission/distribution loss factor of 7.5% was used for this adjustment. Step 1 did not need to be adjusted in this way as the NEFR presented its estimates of the impacts of energy efficiency policies in ‘sent-out’ terms.

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Table 6: 2012 ESOO energy and summer peak demand forecast – Victoria

Year (FY) Final Victoria energy requirements (GWh)

Victoria summer peak demand (MW)

2009-10 48,033 10,1442010-11 47,754 9,9782011-12 46,871 9,1902012-13 47,510 9,6902013-14 49,043 9,9212014-15 50,243 10,1242015-16 51,457 10,2842016-17 52,469 10,4302017-18 53,461 10,5702018-19 54,581 10,7442019-20 55,608 10,8912020-21 56,469 11,036

Source: AEMO, 2012 ESOO

Table 7: Forecast energy reductions (GWh, sent-out) due to national and state-level energy efficiency programs and policies

Year (FY) NSW/ACT QLD SA TAS VIC

2012-13 1,092 636 292 90 1,065

2013-14 1,623 954 438 133 1,560

2014-15 2,154 1,271 558 174 1,938

2015-16 2,685 1,586 676 216 2,307

2016-17 3,219 1,900 795 258 2,667

2017-18 3,757 2,217 908 298 3,022

2018-19 4,299 2,538 1,020 337 3,374

2019-20 4,844 2,862 1,126 375 3,722

2020-21 5,214 2,975 1,152 387 3,855

Source: AEMO, 2012 NEFR

Table 8: Forecast summer maximum demand reductions (MW) due to national and state-level energy efficiency programs and policies

Year (FY) NSW/ACT QLD SA TAS VIC

2012-13 104 88 25 7 119

2013-14 155 132 38 10 173

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2014-15 206 176 50 13 211

2015-16 257 219 61 17 248

2016-17 308 263 73 20 285

2017-18 358 306 85 23 322

2018-19 409 350 96 27 358

2019-20 459 393 108 30 395

2020-21 473 409 111 31 409

Source: AEMO, 2012 NEFR

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Costs and performance of existing, committed and new entrant generation planThe inputs to the modelling concerning the costs and performance of existing, committed and new entrant generation plant were taken from material published by AEMO. AEMO publishes data on the capacity and many other parameters needed to undertake modelling of the NEM, for example as part of its National Transmission Planning role. As the AEMO material is quite extensive, it is not repeated here but can be viewed at the following websites:

Information on generation ownership and capacity by unit for existing and committed plant can be accessed at http://www.aemo.com.au/Electricity/Planning/Related-Information/Generation-Information

Information on the technical operating parameters, emission factors and new entrant technology costs can be accessed at http://www.aemo.com.au/Electricity/Planning/National-Transmission-Network-Development-Plan/Assumptions-and-Inputs

Information on the construction costs of new entrant generation plant can be accessed at http://www.aemo.com.au/Electricity/Planning/National-Transmission-Network-Development-Plan/~/media/Files/Other/planning/WorleyParsons_Cost_of_Construction_New_Generation_Technology_2012%20pdf.ashx

Note that where the data in these sources varies across different planning scenarios we have used the information for Scenario 3 or the Planning Scenario.

Fuel pricesAEMO also publishes fuel price information and forecasts. We have used the information available in Table 7 at http://www.aemo.com.au/Electricity/Planning/National-Transmission-Network-Development-Plan/Assumptions-and-Inputs for coal prices.For gas we have slightly modified those costs based on our own internal analysis. Figure 1 below shows the gas costs used in the modelling using a representative plant within each state. It should be noted that the costs for each plant are adjusted to include the cost of transportation, based on the plant’s location, and all OCGT plant costs for gas are increased by 25% to account for the lower utilisation of these plants.

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http://www.aemo.com.au/Electricity/Planning/National-Transmission-Network-Development-Plan/Assumptions-and-Inputs


http://www.aemo.com.au/Electricity/Planning/National-Transmission-Network-Development-Plan/~/media/Files/Other/planning/WorleyParsons_Cost_of_Construction_New_Generation_Technology_2012%20pdf.ashx





http://www.aemo.com.au/Electricity/Planning/Related-Information/Generation-Information

http://www.aemo.com.au/Electricity/Planning/Related-Information/Generation-Information


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Figure 1: Delivered gas prices ($/GJ)


Carbon priceThe carbon price was assumed to commence in 2013-14 and continue along the fixed path that was established by the Labour government through June 2015, when it was assumed that Australia’s fixed carbon price would be replaced with a scheme aligned with the European emissions trading scheme. We assumed that carbon costs were forecast to fall to around $10/tonne in 2015-16, and then rise annually at 4% real. The $10 figure was derived based on the assumption at the time that the Australian scheme would be opened up to international trade and that the current European price would increase moderately by that time. The 4% annual escalation rate is the same annual escalation rate that Treasury has used in all of its previous forecasts regardless of the starting price. Table 9: Carbon price schedule

Year Carbon price(2012$/tonne)

2012-13 $23.00

2013-14 $24.15

2014-15 $25.12

2015-16 $10.00

2016-17 $10.40

2017-18 $10.82

2018-19 $11.25

2019-20 $11.70

2020-21 $12.17

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Source: OGW

Transmission network configurationThe modelling is based on the inter-regional transmission configuration and announced future augmentations contained in the 2012 ESOO. It is assumed that intra-regional networks are augmented as economic and as needed to ensure network performance standards are met. Model outputs for operation at high transfer levels are reviewed for high price differences that would be indicative of a possible economic case for augmentation of inter-regional networks.

5.2.4. Estimation of the peak demand and load shape impacts of the VEETIn order to assess the impacts of the VEET on the wholesale electricity market and wholesale electricity prices it was necessary to determine how the programs affect the load profile that the generation sector will be required to meet. The load shape is defined by three parameters: total peak demand, total demand, and the amount of electricity required over each hour of the year8. The bottom-up analysis provided by DSDBI and Sustainability Victoria did not provide any estimate of either the peak demand or load shape impacts of the energy efficiency measures that were installed – it only provided their annual energy savings. To assess the impacts of the technologies and programs, peak demand and load shape impacts had to be estimated.Three sources of information were identified for this process: a set of Conservation Load Factors (CLF)9 assembled by the Institute for Sustainable Future and Energetics10, a set of peak demand factors11, developed by SKM MMA12, and a subsequent set of CLFs developed by SKM MMA13, presumably using their peak demand factors as input. All three of these sets of factors were commissioned by the Commonwealth Department of Climate Change and Energy Efficiency.

8 Strictly speaking the third of these includes the first two.

9 The CLF of an energy saving technology is its average reduction in load, divided by its peak reduction in load, specifically: (annual savings in MWh / 8760 hrs in a year) / system coincident peak reduction in MW.

10 Institute for Sustainable Futures and Energetics, Building Our Savings: Reduced Infrastructure Costs from Improving Building Energy Efficiency, July 2010.

11 Defined by SKM MMA as the coincident peak demand impacts of the measure (in kW) divided by its annual consumption reduction impacts (in MWh).

12 SKM MMA, Energy Market Modelling of National Energy Savings Initiative Scheme – Assumptions Report, December 2011.

13 SKM MMA, Assessment of Economic Benefits from a National Energy Savings Initiative, March 2013.

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Each of these factors were applied to the annual energy consumption reductions of the VEET measures that were provided in the bottom-up analysis to derive an estimate of the peak demand impact of each measure. Review of the results revealed that the peak demand factor and the CLF produced materially different results for specific technologies, and that the direction of the difference was not consistent across technologies. As a result, we closely examined the peak demand impact for each technology that resulted from the application of each of the factors, and selected the factor that we believed was the most accurate, based on our experience with demand-side measures. However, even after a factor was selected to derive the peak demand of each measure from its annual consumption there remained the need to distribute the annual savings over the course of the year – that is, to estimate the impact of each measure on the system load shape.This was done based on the nature of each measure, its annual energy consumption reduction, and its peak demand impact as determined by the following steps:

annual energy consumption reductions were allocated to three seasons, summer (3 months: December through February), winter (3 months: July through August), and shoulder (6 months: March through June and September through November); seasonal energy reductions were allocated to each of four blocks of time on both weekdays and weekend days within each of the seasons; and within the seasonal allocation, the level of energy reductions allocated to the 3PM to 7PM weekday block was checked for the degree to which it approximated the selected CLF or peak demand factor.

Appendix C presents further detail about and the results of this process for each type of energy efficiency technology installed under the VEET.

5.2.5. Results of the CEMOS analysis

Impact of the VEET on average wholesale electricity priceTable 10 on the following page presents the figures that were used in the modelling for the energy requirements and peak demand in the ‘without VEET’ and ‘with

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VEET’ scenarios, along with the output of the CEMOS modelling showing the impact of the VEET on the time-weighted wholesale electricity price in Victoria14. Not surprisingly, results show that the VEET reduces energy consumption, starting at about 0.1% of total NEM consumption and rising to about 1.0% by 2013-14 and then staying at approximately that level for the remainder of the study period.By contrast, the program’s impact on summer peak demand and average wholesale price in Victoria is significantly smaller. Summer peak demand reductions in Victoria due to the VEET range between 0.1% and 0.4%, and reductions in Victoria’s time-weighted average wholesale electricity price averaged 0.7%, but varied significantly from year to year, ranging from a low of 0.2% to 2.4%. In 7 of the 12 years wholesale price reductions were found to be 0.5% of less, and in only two years was it more than 1.0%.It should be noted that the impacts in Table 10 are presented in terms of financial years, which is how the AEMO data that is used as input to market simulation modelling is provided. By contrast, the VEET program is run by calendar years. Therefore, the CEMOS outputs were re-organised to a calendar year basis to better align with the VEET bottom-up analysis and other records. Those calendar year impacts are presented in Table 11 following Table 10 below.

14 In this study we have assessed the impact of the VEET on the time-weighted price (TWP) at the Victorian reference point. TWP is calculated as the simple arithmetic average of all 17,520 half-hourly prices in the year. Other studies have used the load-weighted price, which is calculated as the product of the load and price that pertained in each half hour of the year, summed across all half hours and divided by the total consumption in the market over the course of the year. Neither approach is strictly speaking correct for use in the assessment of the impact of the VEET on the wholesale price applicable to any particular customer class. To calculate that impact correctly would require the following procedure: (1) identify wholesale market price in each half hour prior to the VEET and after implementation of the VEET, (2) for VEET participants, calculate the load weighted price of their load profile prior to installation of the VEET measures and then the load weighted price of their load profile after installation of the measures, with the difference in those two prices being the impact of the program on the average cost of wholesale electricity to serve them, and (3) for the market as a whole or for any particular segment of the market (for example ,residential non-participants, other non-participants, etc.), calculate the load weighted price of the load profile of that segment based on the before and after VEET half-hourly prices. To our knowledge, this approach has never been used, and was beyond the resources of the present project. We chose to use the time weighted price because the load profile of the impacts of the VEET, based on the nature of the measures installed, was significantly skewed away from midday hours, and therefore would be likely to be characterised by prices that would be closer to the time weighted average rather than the load weighted average, given that the load weighted average will be more affected by periods of higher price.

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Table 10: Impacts of the VEET on the wholesale electricity market (FY)

Without VEET With VEET Change

FY

Total electricity sent out – Victoria (GWh)

Victoria peak demand (MW)

Average (time weighted) price – Victoria ($/MWh)







2009-10 48,085 9,504 $30.08 48,033 9,498 $29.94 -52 -6 -$0.142010-11 47,946 9,365 $29.88 47,754 9,343 $29.36 -192 -22 -$0.522011-12 47,143 8,630 $19.64 46,871 8,605 $19.35 -272 -25 -$0.292012-13 47,936 9,108 $47.26 47,510 9,073 $46.80 -426 -35 -$0.462013-14 49,572 9,451 $50.84 49,003 9,410 $50.43 -569 -41 -$0.412014-15 50,790 9,677 $52.66 50,202 9,638 $52.35 -588 -40 -$0.312015-16 51,994 9,861 $33.85 51,417 9,823 $33.76 -577 -38 -$0.092016-17 53,002 10,033 $33.23 52,429 9,995 $33.15 -573 -38 -$0.082017-18 53,992 10,199 $42.43 53,421 10,161 $41.47 -571 -38 -$0.962018-19 55,112 10,395 $36.82 54,542 10,357 $36.75 -570 -38 -$0.072019-20 56,137 10,567 $36.28 55,568 10,529 $36.14 -569 -38 -$0.142020-21 56,996 10,717 $37.03 56,430 10,678 $36.92 -566 -38 -$0.11

Source: OGW CEMOS modelling

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Table 11: Impacts of the VEET on the wholesale electricity market (CY)

CY Consumption impact -- Victoria (GWh)

Peak demand impact – Victoria (MW)

Wholesale electricity price impact – Victoria ($/MWh)

2009 -66 -6.00 -$0.08

2010 -220 -21.00 -$0.33

2011 -265 -25.00 -$0.40

2012 -442 -35.00 -$0.37

2013 -559 -41.00 -$0.43

2014 -542 -40.00 -$0.36

2015 -535 -38.00 -$0.20

2016 -532 -38.00 -$0.09

2017 -531 -38.00 -$0.52

2018 -531 -38.00 -$0.51

2019 -529 -38.00 -$0.10

2020 -526 -38.00 -$0.12


Impact of the VEET on wholesale market fuel usage, capacity by plant type and production costsChanges in wholesale electricity price result from changes in production costs – which can include changes in the amount or price of fuels used to generate the electricity required by customers, changes in the amount or type of electricity generation capacity needed to meet peak demand -- and/or the bidding behaviour of generators.Table 10 and Table 11 above provided information on the impacts of the VEET in terms of end-use electricity and peak demand requirements. This section shows the impact on the wholesale electricity market of the difference between the electricity and peak demand requirements of the ‘without VEET’ and ‘with VEET’ scenarios.Table 12 on the following page compares the amount of electricity generated in the two scenarios by fuel type. As can be seen, the VEET results in 5,415 GWh less electricity being generated over the 2009 through 2020 period. Almost all of these savings come from coal-fired generation, in large part due to the times of day at which the measures installed under the VEET have their greatest impact. For example, both the lighting measures and the off-peak water heating measures will have the majority of their impacts at night, when coal is more likely to be the marginal fuel. Given the fact that the scheme sought to reduce carbon emissions, the fact that its impacts have overwhelming been on coal is a very good thing.

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Table 12: VEET impact on use of fuels for generation 2009 – 2020, GWh

Generation fuel type Without VEET (GWh) With VEET (GWh) Change due to

VEET (GWh)

Wind 122,837.5 122,798.7 -38.8

Biomass 27,789.6 27,789.8 0.2

Hydro 182,481.6 182,481.6 0.0

Subtotal renewables 333,108.7 333,070.2 -38.5

Gas – CCGT 92,032.7 92,034.1 1.4

Gas – OCGT 35,366.3 35,347.2 -19.1

Gas – cogeneration 35,689.0 35,689.0 0.0

Subtotal gas 163,088.0 163,070.3 -17.6

Other (oil & steam gas) 23,237.1 23,224.9 -12.2

Sub-critical black coal 1,100,759.6 1,096,949.8 -3,809.9

Sub-critical brown coal 604,147.3 602,671.3 -1,476.0

Super-critical black coal 251,324.4 251,263.3 -61.1

Subtotal – coal 1,956,231.3 1,950,884.3 -5,347.0

Total 2,475,665.1 2,470,249.7 -5,415.4


Table 13 provides information on how the VEET has impacted the total amount of generation capacity required in the NEM, and the proportion of total capacity represented by different plant types.Table 13: VEET impact on amount and type of generation capacity 2020 (MW)

Plant capacity type Without VEET (MW) With VEET (MW) Change due to

VEET (MW)

Wind 8,358 8,358 0

Biomass 800 800 0

Hydro (including small hydro) 7,923 7,923 0

Gas – CCGT 2,244 2,244 0

Gas – OCGT 5,663 5,663 0

Gas – cogeneration 492 492 0

Other (oil & steam gas) 2,367 2,367 0

Sub-critical black coal 16,705 16,705 0

Sub-critical brown coal 7,098 7,098 0

Super-critical black coal 2,917 2,917 0

Total 54,567 54,567 0

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Table 13 shows that the VEET does not change either the amount of capacity required to meet peak demand in 2020, or the proportion of capacity provided by each of the different plant types. This is not surprising given that the VEET was estimated to have only a minimal (about 40 MW) impact on peak demand (which is also not surprising given the nature of the measures that were installed). This impact on peak demand is not large enough to change the amount or type of additional capacity required in the NEM, or the timing with which it is needed.As a result, the impact of the VEET on electricity sector production costs are almost wholly the result of reduced fuel costs and other variable operating and maintenance expenses. As shown in Table 14, the net present value of these cost savings through 2020 is just over $103 million in 2012 dollars.Table 14: VEET impact on generation production costs ($millions2012)

Year Without VEET With VEETChange due to VEET

2009-10 4,924.8 4,924.0 - 0.9

2010-11 4,855.2 4,851.8 - 3.4

2011-12 4,844.0 4,839.9 - 4.1

2012-13 9,010.5 8,995.2 - 15.3

2013-14 9,697.1 9,675.3 - 21.8

2014-15 10,190.2 10,164.6 - 25.6

2015-16 7,538.4 7,522.6 - 15.8

2016-17 8,257.6 8,241.2 - 16.4

2017-18 8,916.3 8,899.1 - 17.2

2018-19 9,415.8 9,399.7 - 16.1

2019-20 9,912.2 9,896.1 - 16.1

2020-21 10,294.3 10,278.2 - 16.1

NPV 61,792.5 61,689.4 - 103.1


5.3. Impact on transmission and distribution components of the retail bill

5.3.1. How energy efficiency affects network pricesThe extent to which a change in energy consumption associated with a Government policy such as the VEET scheme impacts upon network charges is primarily a function of two issues:

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the form of price control under which transmission and distribution businesses operate; andwhether the impact of that policy was forecast by the regulated business as part of their pricing submission.

In the case of the former, regulated businesses operate under either a Revenue Cap or a Weighted Average Price Cap (WAPC) form of price control. If a business operates under a Revenue Cap, it means that its revenues are capped for the entire regulatory control period, no matter what level of sales occurs. Under a WAPC, a business’ revenue is a function of its sales volume.In the case of the latter (a WAPC), if, as part of its pricing submission, a business forecasts the impact of an energy efficiency policy, it will lead (all other things being equal) to a lower energy forecast than would have pertained otherwise. This, in turn, will result in higher overall unit prices.

5.3.2. Calculating the impact of the VEET on the transmission com-ponent of the retail billThe Victorian transmission business has historically operated, and continues to operate, under a Revenue Cap form of price control. Therefore, its unit prices will automatically increase/decrease to compensate for the loss/gain of revenue that stems from any reduction/increase in energy throughput that results from the VEET. For residential customers, transmission charges are included in the Network Use of System (NUoS) charge that the distribution business charges to the retailer, and that are included in the retailer’s bill to the customer. To calculate the impact of the VEET scheme on the transmission component (TUoS) of the final NUoS charges, we have simply multiplied the VEET scheme’s estimated impact on energy consumption by the transmission component of the flat rate residential NUoS charge levied by each distribution business in each year. Because the impacts of the VEET scheme were modelled at a state-wide level while TUoS prices vary by distribution business, we have determined a weighted-average TUoS price across the State, based on the proportion of residential usage of each of the distribution businesses. It is this weighted residential average TUoS price that has been multiplied by the VEET scheme impacts in each year to determine the additional revenue that will need to be recovered from the remaining throughput of residential consumers in order to ensure that the transmission business recovers its overall revenue requirement. We have not sought to incorporate into the calculation any time value of money effects.

5.3.3. Calculating the impact of the VEET on the distribution com-ponent of the retail billEach of the Victorian distribution businesses has historically, and continues to, operate under a WAPC. This means that any forecast reduction in sales would flow through to higher unit prices15. The first task was to establish whether or not the distribution businesses forecast (or were likely to have forecast) the impacts of the VEET scheme as part of their regulatory submissions for the 2006-2010 regulatory period.

15 This may be offset by lower capital and operating costs, if the scheme impacts upon a network business’ cost drivers. This issue is discussed later in this section of the report.

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Based on the information available to us, we conclude that this is unlikely to have been the case. For example, distribution businesses would have finalised their regulatory submissions for the 2006-2010 regulatory period, in late 2004. The VEET scheme commenced some four years later on 1 January 2009, with its establishment Act (the Victorian Energy Efficiency Target Act) being promulgated in 2007. Both of these dates are well after distributors would have submitted their regulatory proposals. Therefore, we have assumed for the purposes of modelling the impact of the VEET scheme on retail prices, that the impact of the VEET on distribution prices over this period has been zero. Note that this implicitly means that it is the shareholders of the distribution businesses who have borne the financial impact of reduced sales associated with the VEET scheme over this period. For the purposes of identifying the impact on distribution prices in 2011 and 2012, we:

assessed the distribution business’ pricing submissions, as well as the AER’s review of those pricing submissions, to assess the extent to which the businesses forecast the impact of the VEET scheme and the AER accepted those forecasts. Based on the evidence available16, we are confident that the businesses:

made some allowance for the impact of the VEET scheme in their residential energy sales forecasts for the period 2011-2015; anddid not make any allowance for the impact of the VEET scheme in their commercial energy sales forecasts for the period 2011-2015.

determined a weighted average DUoS variable price for residential customers for the distribution businesses (based on each distribution business’ contribution to state-wide residential consumption, and their flat rate DUoS tariff that has the most number of residential customers), and multiplied this weighted average price by the estimated energy impacts of the VEET scheme17.

One other key simplifying assumption that we made was that the actual impacts of the VEET scheme in 2011 and 2012 were exactly the same as what the distribution businesses had forecast them to be in those years. In reality, if the actual VEET scheme impacts in either or both of those years differed from the forecast impacts, the revenue impact of the difference would have been borne by the shareholders of the distribution businesses – via either increased returns (if the forecast reduction in sales was higher than what actually occurred) or decreased returns (if the actual reduction in sales were greater than what was forecast).

16 See Table 4 and Table 5 on page 22 of the ACiL Tasman report –VIC DBs and Victorian Electricity Distribution Price Review: Review of electricity sales and customer numbers forecasts, for AER, 21 April 2010, which indicates that distribution businesses made an allowance for the impacts of the VEET scheme on residential consumption, but did not make an allowance for the impacts of the scheme on commercial consumption.

17 In practice, the unit prices that would have occurred in the absence of the VEET scheme would have been slightly lower, given the higher volumes that would have been forecast in the absence of the VEET scheme. However, calculation of those prices would require re-running the tariff models of each distribution company which would be a complex task well beyond the time and budgetary resources of this assignment. In addition, given the overall magnitude of the impacts of the VEET scheme relative to total consumption, the added accuracy of such iteration is likely to be very small, and therefore, we have used the simplified approach presented above.

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5.3.4. FindingsThe following table outlines the total estimated reduction in network revenue (both TUoS and DUoS) that would have needed to have been recovered over the 2009 through 2012 period from all residential customers (both participants and non-participants) as a result of the implementation of the VEET scheme, based on the considerations above.Table 15: Network revenue reductions ($million 2012)

Network revenue impact 2009 2010 2011 2012

Network revenue impact -$0.65 -$2.83 -$17.49 -$32.46


Note that the reason for the large increase in network revenue reductions in 2011 is because this is the first year that the impact on distribution prices is included (in 2009 and 2010, only the impact on transmission prices is included). The reason for the large increase in 2012 is because of the large increase in volumes assumed to be saved by the VEET scheme in this year, relative to previous years.One final caveat to note is that theoretically, the VEET scheme may impact on peak demand and energy at risk, both of which are cost drivers for network businesses. The scope of work did not require us to assess either:

the forecast impact that the distribution businesses expected the scheme to have on network capital costs, via a review of the augmentation plans/demand forecasts that the businesses submitted as part of their 2011 EDPR submissions; orthe actual impact of the scheme on network costs in 2009 and 2010.

We do not consider that this exclusion will materially impact on the overall results, given the scheme is estimated to have had only a relatively small impact on peak demand – with this estimated to be around 0.4% of total network demand in Victoria, as determined in the CEMOS modelling (see section 5.2.5). Table 16 on the following page shows the VEET’s impact on peak demand, relative to estimates made by the AER as to the overall coincident peak demands that were expected to be placed on the Victorian distribution networks over the 2011 to 2015 period.

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Table 16: Comparison of VEET impacts (MW) with total forecast network non-coincident peak demand18

Policy 2011 2012 2013 2014 2015

Citipower (MW) 1,510 1,552 1,593 1,634 1,677

Powercor (MW) 2,481 2,557 2,652 2,747 2,848

Jemena (MW) 1,099 1,130 1,161 1,192 1,212

SP AusNet (MW) 1,874 1,959 2,046 2,130 2,219

United Energy (MW) 2,359 2,424 2,495 2,576 2,591

VEET state-wide impact (MW) - 24 - 33 - 38 - 36 - 36

VEET state-wide impact as a proportion of total forecast demand

0.26% 0.34% 0.38% 0.35% 0.34%

Source: AER – “Final decision - Victorian electricity distribution network service providers Distribution determination 2011–2015”, October 2010, page XVII-XVIII, and OGW modelling

As shown, the impacts of the VEET on summer peak demand state-wide are quite small relative to the expected peak demand of any one of the distribution business. Further to the above, we note the scheme’s impact on a distribution business’ augmentation program will be a function of:

the location of the peak demand impacts stemming from the VEET scheme; whether those impacts coincide with when that particular part of the distribution system peaks;the extent to which there are capacity constraints in that part of the system that are driving the need to undertake augmentations in the future;whether the peak demand reductions are sufficient to defer the need for the augmentation; andwhether the peak demand reductions are recognised by the distribution and are in place or anticipated to be in place prior to the time the augmentation is expected to be needed to ensure reliability of supply.

All in all, this sort of assessment is complex and must be undertaken on a location-specific basis. As such it was well beyond the scope of this assignment. Notwithstanding this, we would make a general observation that much of a distribution network business’ augmentation is likely to be driven by demand increases occurring in the growth corridors that it serves. For example, in its most recent electricity distribution pricing submission, SP AusNet stated that19:

18 That is, the sum of non-coincident zone substation peak demands (MW) for each distribution business.

19 SPI Electricity Pty Ltd, “Electricity Distribution Price Review 2011-2015 Regulatory Proposal - Public Version”, November 2009, page 9

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“Maximum demand for the SP AusNet network is expected to continue to increase on average by 4.4% per annum over the forthcoming regulatory period, principally as a result of further development in the northern and south-eastern growth corridors, and continued growth in air conditioner penetration.” [Emphasis added]

It is likely that customers in these areas are less likely to take up activities under the VEET scheme, due to the fact that, as growth corridors, they will have a substantially higher proportion of newly constructed houses, which are therefore likely to have newer appliances, which are likely to be higher than average in energy efficiency, and in any case for which an early change-out under the VEET would be unlikely to be financially justifiable.

5.4. Impact on retail operating costs and margin

5.4.1. Nature of the costs incurred by retailersThe impact of the VEET on retailers’ internal costs comprises the following:

costs incurred in creating or purchasing certificates, including transaction costs associated with identifying and negotiating with certificate sellers in those cases where the retailer purchases certificatescosts associated with complying with the obligations of the scheme, including the costs incurred in first developing systems and procedures to ensure that the retailer can conform to the requirements of the VEET, and then, subsequently, the on-going costs associated with scheme requirements in terms of recordkeeping and reporting.

We assumed, for the purposes of this assignment, that: the retailers will seek to recover these costs in full, and they will seek to do so from the customer classes that are eligible to participate in the VEET in any particular year.

We consider both assumptions to be non-controversial, as both are consistent with the outcomes that would be expected to occur in a perfectly competitive market. For example, any move to recover the costs of the scheme from customers that are ineligible to participate in the scheme would, in theory, lead to prices for those customers deviating from what would otherwise be the efficient level for that price. In a perfectly competitive market, any retailer that adopted this approach would lose market share, to other retailers operating in that segment of the market. This, in turn, would reduce their ability to recover the costs of the scheme, which was the original objective. In addition, if a retailer chose to not recover the costs of the scheme in full, they would lower their financial, potentially risking their long-term financial viability.

5.4.2. FindingsDSDBI provided information on the average monthly cost of certificates from the Essential Services Commission, along with the results of the bottom-up analysis. The average certificate price was then multiplied by the number of certificates that were created in that month, to provide an approximation of the overall certificate costs for each calendar year.

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It should be noted that this price represents the marginal price of certificates – that is, it is the price that ‘clears’ the market under the VEET scheme. It is unlikely to represent the actual cost to the certificate creators (including retailers) of producing those certificates, and because of this should be seen as the upper-end estimate of the costs incurred by retailers in meeting their certificate obligations under the program. Table 17 and Table 18 on the following page show, respectively, the certificate prices that pertained in each month of 2009 through 2012, and the number of certificates that were created in each of those months.Table 17: Certificate price ($nominal)

Yr Jan Feb Mar April May June July AugSep

tOct Nov Dec

2009 $12.50 $12.50 $12.5

0$12.50

$12.50

$12.50

$12.50

$12.50

$12.50

$12.60

$12.65

$12.16

2010 $11.94 $11.90 $10.6

5$10.25 $9.95 $9.28 $9.35 $10.3

3$11.00

$11.00

$11.70

$14.25

2011 $14.90 $16.05 $16.3

0$20.00

$20.60

$24.00

$25.00

$25.00

$25.63

$33.10

$40.88

$39.98

2012 $33.73 $23.75 $22.0

4$22.32

$23.75

$24.19

$21.30

$21.04

$22.45

$21.88

$20.00

$20.02

Source: ESC

Table 18: Number of certificates created (‘000s)

Yr Jan Feb Mar April May June July Aug Sept Oct Nov Dec

2009 102.3 185.7 208.2 243.4 437.1 464.9 577.9 450.5 423.8 458.9 417.7 260.9

2010 205.6 204.3 281.9 310.2 344.0 199.1 130.6 96.9 105.7 87.3 75.5 58.7

2011 36.5 50.8 57.9 55.3 72.9 80.1 80.4 86.4 167.7 300.2 490.7 734.2

2012 592.9 594.6 548.4 497.8 668.4 599.4 722.6 794.0 693.9 703.2 638.2 517.4

Source: ESC

We also included within our analysis the estimated administrative and infrastructure costs associated with the scheme.

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The administrative costs associated with the VEET that are incurred by the retailers are not publicly available. Therefore, we used the information provided in a report published by the Department of Climate Change and Energy Efficiency (DCCEE) entitled Analysis of Compliance Costs for a National Energy Savings Initiative20, which includes information on these costs that was developed through interviews with a subset of retailers with obligations under the VEET (including all three of the largest retailers), and certificate creators. Where infrastructure costs were incurred, we assumed that these were amortised over the period 2009 to 2012. It should be noted that the costs incurred by the ESC in administering the scheme have not been included in these calculations, as it is our understanding, based on information provided by the ESC for the DCCEE report, that these costs are recovered from a $1 charge included in the cost of registering each certificate and the fees paid by certificate creators in registering to be approved to install specific VEET measures. The estimated administrative and infrastructure costs associated with the scheme are outlined in Table 19 below.Table 19: Retailer costs ($million 2012)

Retailer costs 2009 2010 2011 2012

VEET Certificate costs $57.16 $23.48 $75.53 $173.88

Compliance costs $3.85 $2.17 $2.34 $6.73

Source: OGW analysis of certificate price and volume data provided by the ESC and information on compliance costs incurred by liable retailers in the DCCEE report, Analysis of Compliance Costs for a National Energy Savings Initiative.

20 NERA Economic Consultants and Oakley Greenwood, Analysis of Compliance Costs for a National Energy Savings Initiative, Final Report for the Department of Climate Change and Energy Efficiency, December 2012) available at www.ret.gov.au/energy/efficiency/savings/nesi_consultant/Pages/index.aspx.

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6. Distributional impacts of the VEET6.1. Purpose and overview of this task

The purpose of this task was to assess the impact of the VEET on the bills of customers who had participated in the VEET and those that had not. To do so, we defined the following groups of participants and non-participants:

program participants, who were limited to residential customers that had measures installed under the VEET between 2009 and 2012 inclusive; we did not consider the impacts on small business customers that participated in those years (2001 and 2012 only) due to the very small number of these customers;non-participants, who were further disaggregated as follows:

residential non-participants – residential customers within Victoria that were eligible to participate but did not do so in the 2009 – 2012 period;small non-residential non-participants – small, non-residential customers within Victoria who became eligible to participate in the scheme in 2011, and who have been allocated a proportional share of program costs in government policy;medium commercial and small industrial customers – medium-sized non-residential customers within Victoria who became eligible to participate in the scheme in 2011, and who have been allocated a proportional share of program costs in government policy;large commercial and industrial customers – large commercial and industrial customers within Victoria – specifically, those large customers that are liable under the EREP program21, and who, because of that, were specifically exempted in government policy from being allocated a share of the VEET costs; andall customers in other NEM jurisdictions – these customers were not eligible to participate in the VEET or recovery of its costs, but could be impacted by any change brought about by the program in wholesale electricity prices in their jurisdictions.

Then, to calculate the impact of the VEET on the bills of each of those groups of customers, we split our analysis into two discrete calculations regarding:

the financial costs of the scheme, which is borne by both participants and non-participants, and comprise:

network costs (which accrue to residential customers only); andretail costs (which accrue to residential customers only, except for 2012 when small and medium sized non-residential customers also share in these costs).

the financial benefits of the scheme, which accrue to both participants and non-participants, and include:

21 The Environment and Resource Efficiency Plans program that was implemented by the Victoria Environment Protection Agency (see http://www.epa.vic.gov.au/our-work/programs/past-programs/erep-program).

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reductions in the wholesale energy price as a result of the VEET scheme (which accrue to participants and non-participants in Victoria, as well as non-participants from other NEM States); and reductions in electricity usage, and the consequent impact on bill amounts (which accrue to participants only).

6.2. Findings

6.2.1. Costs of the scheme as allocated to participants and non-par-ticipants To derive the costs of the scheme, we:

ascertained the number of unique participants that have taken part in the scheme by:

determining the ratio of unique participants to total participants based on data on these items provided by DSDBI for the VEET from 2009 through June 2013; andapplying that ratio to the total number of participants in each program year (as reported in the bottom-up analysis provide by DSDBI and Sustainability Victoria) to estimate the number of unique participants in each year from 2009 through 2012;

determined the average usage per participant (who, based on the information from the bottom-up analysis, are all assumed to be residential customers) by:

dividing the estimated impact of the VEET scheme in each year by the cumulative number of participants partaking in the scheme in that year (from the step above) to work out the average yearly reduction in consumption that each participant would achieve as a result of participating in the scheme; anddeducting that reduction in consumption from what the overall average residential consumption in each year would have been, had the VEET scheme not existed, to determine the post-VEET average consumption per participant; and

determined the average usage of residential non-participants in each year by back-solving, so that when that average was combined with our average usage per participant (previous step), the state-wide average equated to the state-wide average consumption of residential customers over the evaluation period that was provided by the distribution businesses, and the difference between the participant and non-participant average consumption equated to the per customer impact of the VEET scheme.

Then, to attribute network costs between residential participants and non-participants, as well as to other non-participants (e.g., small to medium sized non-residential customers), we:

multiplied the respective average usages of the residential participants and residential non-participants by the weighted average network price to determine the increase in the bills of both groups that were caused by higher network costs; but

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did not allocate any of the network costs to any other customer class, as not only did these customers not participate in the scheme (except for 2012, where some were, in theory, eligible to participate, although in actuality, only a very small number did participate), but distribution businesses did not forecast any reduction in consumption from these customer classes as a result of the scheme22. It is assumed that because of this, any increase in network costs would only be recovered via increases in residential tariffs.

To attribute retail costs between residential participants and non-participants, as well as to other non-participants (e.g., small to medium sized non-residential customers in Victoria), we:

attributed the retail costs associated with the scheme to residential customers for the period 2009 through 2011 (as only residential customers were eligible for participation in the scheme during this period);

this was done by dividing the total retail costs in that year, by the total residential consumption (which was provided by the distribution businesses), and then multiplying this cost per kWh by the respective average usages for the residential participants and non-participants23; and

attributed the retail costs associated with the scheme in 2012 to all customers (excluding EREP customers24) by allocating those retail costs based on the relative consumption of each customer class.

The following table outlines the costs (per customer) attributable to each customer class.Table 20: Annual and total cost of the VEET per average customer for each customer class ($2012)

Customer class Component 2009 2010 2011 2012NPV

2009-2020

Residential participantsNetwork costs $0.29 $1.17 $7.22 $13.60 $79.50

Retail costs $26.80 $10.59 $32.14 $33.69 $86.23

22 See Table 5 on page 22 of the ACiL Tasman report –“VIC DBs and Victorian Electricity Distribution Price Review: Review of electricity sales and customer numbers forecasts, for AER”, 21 April 2010, which indicates that distribution businesses made no allowance for the impacts of the VEET Scheme on commercial consumption.

23 It should be noted that this approach implicitly assumes that these costs are apportioned on per kWh basis. In practice, retailers may seek to recover these costs simply on a per customer basis. If this were to occur, it would, ceteris paribus, lead to a slight increase in costs apportioned to participants, and a slight decrease in the costs apportioned to non-participants, because in the present approach, non-participants are assumed to have a higher average consumption than participants, and thus, under our proposed methodology, they attract a slightly larger proportion of overall costs relative to if the apportionment was done on a per-customer basis. Overall, we do not consider this issue to be material, particularly given that the difference in the average consumption of participants and non-participants is not significant.

24 DSDBI explicitly excluded EREP customers from being allocated a portion of VEET as a matter of policy. This was communicated to the liable retailers and the EREP customers. Consistent with this, we have excluded EREP customers from VEET program cost allocation.

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Network costs $0.30 $1.29 $7.90 $14.61 $89.25

Retail costs $27.85 $11.65 $35.15 $36.19 $92.50


Network costs $0.00 $0.00 $0.00 $0.00 $0.00

Retail costs $0.00 $0.00 $0.00 $169.77 $129.52


Network costs $0.00 $0.00 $0.00 $0.00 $0.00

Retail costs $0.00 $0.00 $0.00 $847.65 $646.67

EREP customersNetwork costs $0.00 $0.00 $0.00 $0.00 $0.00

Retail costs $0.00 $0.00 $0.00 $0.00 $0.00


6.2.2. Benefits of the scheme accruing to participants and non-par-ticipantsTo derive the benefits of the scheme, we first calculated the reduction in electricity bills accruing to participants of the scheme through the following steps:

First, deriving the average variable price in the host retailer’s standing offer and the average variable price across the various market offer prices available within each distribution area in each year25. This was based on information from St Vincent de Paul26 price data, which is available on a six-monthly basis, going back to July 2010. For the purposes of calculating 2011 and 2012 figures, we used an average of the January and June prices applicable to that year. For the purposes of calculating the 2010 prices, we used the average of the July 2010 figures, and an estimate of the January 2010 figures which was back-cast based on the proportionate increase between January and July 2011. The 2009 figure was back-cast, based on known growth rates in market and standing offer retail prices between 2010 and 2012 (i.e., the growth rate between 2009 and 2010 is assumed to be the same as the annualised growth rate between 2010 and 2012).We then derived a state-wide weighted average market offer variable price and average standing offer variable price, by simply weighting each distribution business’ average market and average standing offer variable prices by its contribution to total residential consumption.

25 It should be noted that where a multi-tier block tariff was the common standing offer/market offer (which is relevant for Citipower and Powercor), we used the second tier of that block, as most customers accrue at least some usage at this marginal price, and it is therefore reasonable to assume that it represents the marginal benefit associated with any reduction in consumption as a result of participation in the VEET,

26 Available at http://www.vinnies.org.au/energy-reports-vic . We have not sought to validate this data

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We then worked out an average retail price, based on weighting the average standing offer and market offer prices by the estimated number of customers on market offers versus standing offers. For the years 2008, 2010 and 2012, this information was provided by DSDBI27. We then interpolated results for the intervening years of 2009 and 2011. This indicated that the proportion of small customers on a standing offer has reduced from around 46% in June 2008 to 25% in June 2012 (see Table 21 below).Then, after correcting for the effects of inflation, we multiplied this weighted average price ($2012) by the total volumes estimated to be saved under the VEET scheme to determine the overall reduction in participants’ bills as a result of participating in the scheme. We then divided this number by the estimated cumulative number of unique participants in each year to determine the per-participant benefit in each year.

Table 21: Proportion of customers on standing offers and market offers

Retail price Standing offer Market offer Source

June 2008 46% 54% ESCJune 2009 40.5% 59.5% InterpolatedJune 2010 35% 65% ESCJune 2011 30.0% 70.0% InterpolatedJune 2012 25% 75% DSDBI

Source: OGW analysis of DSDBI data

In addition, we calculated the benefits that accrue to residential participants and non-participants, as well as to other non-participants (e.g., small to medium sized non-residential customers within Victoria, large non-residential customers within Victoria, and all electricity customers in the other NEM States), of the reduced wholesale price that results from the measures installed under the VEET. This was calculated by:

multiplying the respective average usages for the residential participants and residential non-participants within Victoria by the time-weighted average wholesale price reduction in Victoria (details of which have been provided in section 5.2.5) to determine the benefits that participants and non-participants would accrue from the reduction in wholesale price stemming from the scheme28; andmultiplying the average usage for each of the non-residential customer classes within Victoria by the time-weighted average wholesale price reduction in Victoria to determine the benefits that would accrue to each group of non-participants from the reduction in wholesale price stemming from the scheme; and

27 Email from David Blowers to Lance Hoch dated 14 August 2013.

28 Implicitly, this assumes that any reduction in the wholesale price of electricity flows directly through to retail tariffs. This is consistent with the assumption that the electricity market is perfectly competitive.

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multiplying the estimated electricity consumption in each other NEM jurisdiction, inclusive of an estimate of losses, by the change in the time-weighted wholesale price in the respective jurisdiction.

The following table shows the per-customer benefits accruing to each category of Victorian customer.Table 22: Annual and total benefit of the VEET per average customer for each customer class ($2012)

Customer class

Component

2009 2010 2011 2012NPV

2009-2020

Residential participant

Wholesale price $0.45 $1.72 $2.04 $1.90 $12.06

Reduction in consumption

$13.20 $48.39 $58.09 $114.74 $824.66


Wholesale price $0.47 $1.89 $2.23 $2.04 $13.13


Wholesale price $2.11 $8.79 $10.49 $9.58 $61.19


Wholesale price $13.18 $49.71 $53.47 $47.83 $313.99

EREP customers

Wholesale price $5,067 $21,174 $25,955 $23,796 $151,185


The following table shows the benefits accruing to non-Victorian customers.Table 23: Annual and total benefit of the VEET accruing to non-Victorian customers in aggregate ($2012)

2009 2010 2011 2012NPV

2009-2020

Benefits to electricity users in other states via lower wholesale prices

$3,789,343 $6,875,265 $3,963,84

2 $

2,704,142 $63,999,2

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6.2.3. Net benefits accruing to participants and non-participants in VictoriaThe following table demonstrates the net (per customer) benefits accruing to each category of customer in Victoria.Table 24: Distributional impacts – net annual and total financial benefit of the VEET per average customer for each customer class ($2012)

Customer class 2009 2010 2011 2012NPV

2009-2020

Residential participants -$13.44 $38.35 $20.77 $69.36 $670.99

Residential non-participants -$27.68 -$11.05 -$40.82 -$48.75 -$168.63

Small commercial customers $2.11 $8.79 $10.49 -$160.19 -$68.32

Medium commercial and small industrial customers $13.18 $49.71 $53.47 -$799.82 -$332.68

EREP customers $5,067 $21,174 $25,955 $23,796 $151,185


6.3. Net economic benefits (electricity sector total resource cost perspective)The previous sections assessed the financial outcomes of the program from the perspective of customers that participated in the VEET and several classes of customers that did not participate. The economic benefits and costs of the program from the total resource cost perspective of the electricity sector – which can be defined as including the total net cost borne by electricity providers and users in meeting electricity needs – are somewhat different:

Economic benefits, which from the perspective of the electricity sector as a whole, are represented by reductions in electricity production costs, which include:

reductions in electricity variable costs: fuel costs, variable operation and maintenance costs, and carbon costs (which internalises what is generally treated as an externality); and reductions in capital costs and fixed operation and maintenance costs.

Economic costs, which from the perspective of the electricity sector as a whole, are represented by any increased costs of producing and delivering electricity, which in the case of the VEET are represented by:

the cost of the program itself, and any costs incurred by program participants (which in the present analysis have been assumed to be zero).

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Table 25 through Table 27 present the economic benefits, costs and net benefits of the VEET from the electricity sector total resource cost perspective.Table 25: Economic benefits of the VEET – electricity sector total resource cost perspective ($2012, millions)

Economic benefit 2009 2010 2011 2012NPV

2009-2020

Reduced variable production costs $0.86 $3.40 $4.11 $15.32 $103.13

Reduced fixed production costs $0.00 $0.00 $0.00 $0.00 $0.01

Total reduction in production costs $0.86 $3.40 $4.11 $15.32 $103.14


Table 26: Economic costs of the VEET – electricity sector total resource cost perspective ($2012, millions)

Economic costs 2009 2010 2011 2012NPV

2009-2020

VEET certificate costs $57.16 $23.48 $75.53 $173.88 $268.23

Compliance costs $3.85 $2.17 $2.34 $6.73 $12.54

Total costs $61.01 $25.66 $77.87 $180.60 $280.77


Table 27: Net economic benefits of the VEET – electricity sector total resource cost perspective ($2012, millions)

2009 2010 2011 2012NPV

2009-2020

Net economic benefit -$60.15 -$22.26 -$73.76 -$165.28 -$177.63


In addition to the above, we note that the VEET scheme could also lead to an additional economic benefit, being an improvement in allocative efficiency. In simple terms, allocative efficient outcomes occur if the price for a particular service accurately reflects the costs to society of providing that service. Where prices deviate from costs, the socially optimum level of production and consumption will not occur, and thus, a “deadweight loss” will result.

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If, in the absence of the VEET scheme, the pricing outcomes within the wholesale market deviated from cost reflective levels (i.e., were higher than cost-reflective levels), this would result in some customers consuming less electricity than they otherwise would have purchased. This is likely to reduce either the productivity or amenity enjoyed by these consumers, and thus their consumer surplus. There will also be a loss in producer surplus, due to the fact that the generators will not sell as many units of electricity as they would have under perfect competition. If, however, the adoption of the VEET scheme leads to generators adopting more efficient bidding behaviour, so that the wholesale price better reflects the cost of supply, then improvements in allocative efficiency will ensue. Notwithstanding the conceptual merits of including this economic benefit within our analysis, it is our view that, in the case of the VEET, it is not likely to be material when compared with the productive efficiency benefits that have been outlined above. We say this for two reasons:

The results of our market modelling indicate that there are only small changes in bidding behaviour as a result of the VEET scheme; andThis small change in the wholesale price does not directly translate into a loss in allocative efficiency because:

the majority of the revenue that is generated from that change in wholesale price simply represents a transfer from consumer to producer surplus (i.e., producers increase their profits, with this being ‘funded’ directly by consumers), which is not an economic cost; and the loss in allocative efficiency is further reduced as it is a function of, amongst other things, the elasticity of demand (which reflects the slope in the demand curve).

As a result, we do not feel that the omission of the potential for the VEET to increase allocative efficiency makes a material difference in the estimation of the scheme’s net economic benefits.

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7. Conclusions, caveats and recommendations7.1. Conclusions

The section presents the conclusions that can be drawn regarding the key questions to be addressed in this study based on the analyses undertaken. These conclusions should be considered in light of the assumptions listed in section 3 above, and the caveats discussed in section 7.2 below.

The VEET produced material energy savings – mostly reducing the use of coal – but did not impact peak electricity demand to any material extent.

The electricity savings produced by the measures installed under the VEET in the years 2009 through 2012 are material, amounting to just over 5,400 GWh cumulatively by the end of 2020. The 427,965 MWh saved in 2012 alone equates to approximately 2.2% of Victoria’s residential and SME electricity consumption in that year.Virtually all of energy saved (99.3%) comes from reduced use of coal for electricity generation, which is consistent with the scheme’s objective of reducing carbon emissions. This high impact on coal in part reflects the times of day that the measures eligible for installation under the VEET from 2009 through 2012 affect electricity use. Just under 65% of the savings come from the replacement of standard light globes with high-efficiency alternatives. Clearly, most of these savings will occur in evening hours. Another 15% comes from energy efficiency measures installed on off-peak water heaters, where virtually all of the savings will accrue at night.However, this time distribution of electricity savings – with most of its impact in the evening – means that the scheme’s impact on electricity peak demand – which tends to occur in the afternoon or early evening of hot summer weekdays – is correspondingly small. The analysis undertaken in this study suggests that the scheme’s impact on peak demand reaches its highest point at 41 MW in 2013, representing 0.4% of the state’s peak demand in that year.

Impacts on gas were both smaller and in the opposite direction.

Overall, gas consumption increased by over 134,000 GJ due to the program through 2020. This is not surprising given that a number of the most popular measures offered under the VEET during the years 2009 through 2012 involved changing out electricity equipment for gas-fired equipment. For example, 39% of the more than 45,000 installations that concerned water heating equipment involved the replacement of electric water heating equipment by gas-fired equipment. Even so, the increase was not material: the increase in gas consumption of 110,600 GJ due to the scheme in 2012 represents only about 0.1% of Victoria’s residential gas consumption in that year.For this reason, the impacts on gas were not considered further in the analysis. As a result, the benefits to participants developed in this analysis are slightly overstated, as they do not include the increased cost of gas that participants would have incurred due to those measures that substituted gas for electricity use.

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The reduction in electricity generation will have reduced electricity sector production costs, and because of that, wholesale electricity prices.

Based on the results of the analyses undertaken, the VEET will produce savings in electricity system production costs with a net present value of just over $103 million (in 2012 dollars). These savings will almost wholly result from reduced fuel costs and reductions in other variable operating and maintenance expenses.Those reduced savings – and a slight impact on the bidding behaviour of generators due to the increased competition to meet reduced demand – result in downward pressure on wholesale electricity prices in Victoria and the other NEM jurisdictions, as shown in Table 28 below. As would be expected, the impact is almost always greatest in Victoria, with impacts in the other jurisdictions generally (but not always) materially lower. However, even in Victoria these decreases represent less than a 1% reduction from the wholesale price that would have pertained in the ‘without VEET’ scenario (the average change across all of the years is -0.8%), and the reduction exceeds -1.0% in only two years.Table 28: Impact of VEET on wholesale electricity price, by jurisdiction ($2012/MWh)

CY VictoriaQueensland

New South Wales

South Australia

Tasmania NEM

2009 -$0.08 -$0.01 -$0.02 -$0.09 -$0.10 -$0.06

2010 -$0.33 -$0.02 -$0.03 -$0.25 -$0.10 -$0.14

2011 -$0.40 -$0.01 -$0.02 -$0.18 -$0.00 -$0.12

2012 -$0.37 -$0.01 -$0.02 -$0.06 -$0.01 -$0.09

2013 -$0.43 -$0.02 -$0.03 -$0.23 -$0.03 -$0.15

2014 -$0.36 -$0.05 -$0.08 -$0.20 -$0.01 -$0.14

2015 -$0.20 -$0.07 -$0.12 $0.06 $0.00 -$0.07

2016 -$0.09 -$0.06 -$0.11 $0.08 $0.03 -$0.03

2017 -$0.52 -$0.06 -$0.14 -$0.30 -$0.28 -$0.26

2018 -$0.51 -$0.06 -$0.13 -$0.01 -$0.32 -$0.21

2019 -$0.10 -$0.06 -$0.11 $0.56 -$0.01 $0.05

2020 -$0.12 -$0.06 -$0.13 $0.30 -$0.02 -$0.01

Average -$0.29 -$0.04 -$0.08 -$0.03 -$0.07 -$0.10


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The VEET will have produced material net financial benefits for program participants, EREP sites and all electricity users outside Victoria. However, customers in Victoria that did not participate in the VEET (other than EREP sites) will have experienced net financial costs.

While all customers in the NEM will benefit from the downward pressure exerted by the VEET on wholesale electricity price, this effect, as noted in Table 28 above, is strongest in Victoria.VEET participants accrue additional benefits due to the reduction in their consumption produced by the measures installed under the VEET – so they have a lower price and a lower volume. This combination is more than enough to overcome the increases that result from networks in Victoria needing to increase unit prices to recover their revenue requirements across reduced sales, and retailers needing to recover the costs of creating or purchasing certificates to meet their obligations under the VEET. The prices of EREP sites within Victoria and all non-Victorian electricity users are not subject to these cost-recovery price increases.Non-participants in Victoria who share in the costs of the VEET (all customer classes except very large customers who were liable under the EREP program) experience net costs. This is because the increases in their bills due to increased network unit prices and increased retail charges to recover their costs of complying with the VEET outweigh the impact of the reductions in wholesale electricity prices engendered by the scheme.EREP sites in Victoria and customers in other NEM jurisdictions are not subject to these increases in network and retail costs, and therefore experience net benefits due to lower wholesale electricity price.Table 29 summarises the present value of the benefits and costs experienced by the average VEET participant and various classes of non-participant in Victoria29 between 2009 and 2020. As shown in Table 23 above, the reductions in wholesale electricity price induced by the VEET in other NEM jurisdictions also produces over $62 million ($2012) in net benefits for non-Victorian electricity users in that same time period.Table 29: Average VEET benefits & costs per participant and non-participant in Victoria ($2012, 2009 – 20)

Customer class

Benefits Costs

Net benefit

Wholesale price

reduction

Reduced usage

Total benefit

Increased

network price

Retailer recovery

of program

costs

Total cost

Residential participan

$12.06 $824.66 $836.72 $79.50 $86.23 $165.73 $670.99

29 The figures in the table represent the benefits and costs that accrue to the average customer within each of the customer classes shown. The scale of the impact on different customer classes reflects the amount of electricity consumed by the average customer within each class. This is why the impact on EREP customers – who are the largest electricity consumers in the state – is so much larger than for any of the other customer classes.

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tsResidential non-participants

$13.13 NA $12.00 $89.25 $92.50 $181.75 -$169.75


$61.19 NA $55.89 $0.00 $129.52 $129.52 -$73.63


$313.99 NA $286.94 $0.00 $646.67 $646.67 -$359.73

EREP customers

$151,185.00 NA $138,065.

00 $0.00 $0.00 $0.00 $138,065.00


Overall, the program has a negative net economic benefit from the total resource cost perspective of the electricity sector; that is, its costs outweigh the benefits it has provided.

The financial benefits and costs summarised above for VEET participants and non-participants include a significant amount of transfers. For example, some of the benefit experienced by program participants are subsidised by costs incurred by non-participants and some of the benefits experienced by program participants and non-participants come at the expense of reduced net revenue achieved by the shareholders of various parts of the electricity supply chain.The total resource cost (TRC) perspective can be used to assess the economic benefits and costs of the VEET (or any supply or demand side option) from the perspective of the electricity supply and demand chain overall. Essentially, it measures the total cost of different means –including energy efficiency improvements – for meeting end-use electricity requirements. In this way the TRC can be used to assess the VEET (or any demand-side option) as simply another resource option for meeting customer energy requirements. In the TRC, the costs of the VEET as a resource option include the total costs of the program, including all costs incurred by participants, and the electricity supply chain in developing and implementing the program. The benefits of the VEET as considered by the TRC are all costs that are avoided across the electricity supply chain due to the program, valued at their marginal costs.

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The TRC differs from the societal perspective in that it does not include consideration of externalities (such as, but not necessarily limited to, environmental impacts, employment impacts or impacts on energy supply security), or costs incurred by government or other bodies in developing, implementing, administering or evaluating the program that are not recovered through electricity price mechanisms. In the present instance, the fact that the electricity price used includes a carbon price means that at least some proportion of the environmental externality will be included in the TRC.As discussed in section 5.2.5, the VEET’s effects on the costs of the electricity generation sector (which comprise the benefits of the TRC metric) occur almost entirely in reducing the need for coal for electricity generation. Minor cost reductions also occur in the reduced need for other fuels and other variable operating and maintenance expenses within the generation sector. Analysis of the load shape impacts of the measures installed under the VEET in the years 2009 through 2012 indicates that the program did not have any impacts on the amount or type of electricity generation capacity needed in the generation sector, and therefore will not affect capital cost requirements of the generation sector. The very small impact of the VEET on peak demand – and the fact that these impacts will be relatively widely spread across the state also suggests that it is unlikely that the scheme will have had any material impact on the capital requirements of the state’s transmission or distribution networks.The costs of the VEET from the TRC perspective include:

Any costs incurred by scheme participants for the measures installed – These costs have not been considered in this analysis, which serves to understate the cost side of the TRC, though it is important to note that several of the measure that were installed under the program were provided free of charge to scheme participants;The costs incurred by retailers in either creating or purchasing VEECs are required to meet their obligations under the scheme – We have used the price at which certificates traded in each month as the proxy for these costs; however, it should be noted that this price represents the marginal price of certificates – that is, it is the price that ‘clears’ the market under the VEET scheme. It is unlikely to represent the actual cost to the certificate creators (including retailers) of producing those certificates. Therefore, this will tend to overstate the cost side of the TRC;Any other costs incurred by retailers in complying with the scheme – The costs considered in this regard included costs incurred in developing the infrastructure required to administer the program and the on-going costs of scheme implementation and documentation.

Table 30 presents the benefits and costs of the VEET from the TRC perspective (including carbon costs).

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Table 30: VEET economic benefits and costs – TRC perspective ($2012 millions, 2009 – 20)

Benefits Costs

Net benefit

Reduced fuel and variable

O&M costs

Reduced fixed

production costs

Total benefit

Participant costs

Certificate costs

Scheme complianc

e costs

Total cost

$103.13 $0.01 $103.14Not con-

sidered$268.23 $12.54 $280.77 -$177.63


7.2. Caveats

The energy savings of the VEET are not measured results – they have been have been derived from engineering estimates augmented by post-installation surveys to revise persistence assumptions.

DSDBI and Sustainability Victoria have made a thorough review and refinement of the algorithms originally used to estimate the energy consumption impacts of the VEET measures. The algorithms themselves are quite sophisticated and take into account all of the factors that could reasonably be thought to affect scheme savings. The decision to commission fieldwork on the persistence of several measures – particularly standby power controllers – has also served to significantly refine and revise the estimated energy savings of the scheme.However, there has been no attempt to measure the actual, real-world impacts of the measures. As a result, these estimates may over- or under- estimate actual, real-world energy savings and other impacts of the scheme.

There is significant uncertainty regarding the time distribution of VEET measure savings

There is no direct data on the time distribution of the energy impacts of the measures installed under the VEET. For the purpose of this study, these impacts have been estimated based on the professional experience of OGW.In addition, it has been assumed, based on the data provided by DSDBI and Sustainability Victoria, that the water heating and shower rose measures (which account for approximately 17.3% of all VEET savings) have been installed only on off-peak water heaters, and therefore have no impact at times of generation system peak demand. To the extent that the measures may have had larger impacts on peak demand, program benefits would be larger.

Network benefits have not been considered

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While we believe that this is unlikely to effect the overall assessment of the costs and benefits of the measures installed from 2009 through 2012, due to their likely impacts on peak demand and geographic spread, it is an issue that may warrant consideration in future evaluations to the extent that the measures to be assessed as part of such evaluations are likely to have larger impacts on peak demand.

The economic cost of the program has probably been overstated

As noted in the previous section, the magnitude of the economic cost of the VEET is likely to be over-stated in the TRC metric as calculated in this analysis. This is because we did not have any information on the actual cost of ‘producing’ the certificates (which would include the cost of the measures, less any contribution from participants; the cost of installing the measures, the cost of being accredited under the VEET; and the overhead costs of the certificate-creating enterprise). Rather, we used the market-clearing price of certificates as the proxy for these costs, as it was available and information on those costs was not. It is important to recognise, however, that the market clearing price in theory, represents the marginal cost to the marginal producer that is required to clear the market for certificates. The use of the market clearing price as the basis for establishing the overall costs of the VEET will therefore over-state costs, in so far as it also includes the producer surplus that certificate creators generate from the scheme. However, we do not consider this to be a material issue, given the high volume, low margin nature of the products offered under the scheme (which impact on the slope of the supply curve, and hence, the level of producer surplus).

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Appendix A: Terms of ReferenceProject descriptionThe purpose of this project is to identify costs and benefits of the VEET scheme since its inception in 2009.The project will focus on modelling the impact that the scheme has had on energy consumption and how this has impacted the energy market in relation to wholesale costs and retail prices. In modelling the effect of the VEET scheme on energy consumption and the energy market, three to four separate methodologies should be used to ensure the robustness of results.The project has three components:

I. Measure the impact of VEET on energy consumptionThe supplier will develop and run three to four methodologies (outlined below) to assess the impact of VEET on energy consumption between 1 January 2009 and 31 December 2012. The results of this modelling will quantify the energy savings from the VEET scheme to date.The methodologies are:

a) Bottom up approach – the VEET scheme’s impact on energy consumption will be calculated from the energy savings attributed to the creation of VEECs. DPI have their own technology cost curve model that calculates the energy savings from the scheme in this way. The results will be provided to the contracted supplier to determine the impact on wholesale costs and retail prices in the second component of the project. DPI will liaise with the ESC to provide information on certificate creation over the period 1 January 2009 to 31 December 2012.In the case of this methodology, energy savings will also be forecast into the future until 1 January 2020 and provided to the supplier.

b) Top down approach – the VEET scheme’s impact on energy consumption will be extrapolated from the deviation of actual energy consumption from that forecast before the scheme was introduced. The supplier will be required to provide a reasoned estimate for this deviation in consumption which includes an analysis (and justification) of all key factors that have influenced energy demand over the period. The methodology will calculate the impacts of all key variables that may have contributed to this deviation, with the residual accounting for the impact of the VEET scheme. Variables should include, but not be limited to:o price elasticities of electricity and gas consumption;o economic activity (potentially disaggregating for specific industries);o take-up of solar PV;o other energy efficiency schemes; ando weather.

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c) Econometric – undertake econometric analysis to determine the impact of the VEET scheme on energy consumption. The dependent variable should relate to energy consumption for the period 1 January 2009 to 31 December 2012. Independent variables should include a measure for the VEET scheme (potentially a derivation on the number of certificates created), the variables specified above and those identified by the supplier.

d) Alternative methodology - the supplier has the option of suggesting an additional methodology for calculating the impact of the VEET scheme on energy consumption.

II. Evaluate the effect of VEET on energy marketsThe outcomes of the methodologies will create three to four energy consumption scenarios that will be used as inputs into electricity and gas market models to determine the scheme’s impact on wholesale costs and retail prices for the first four years of the scheme. The outcomes of the first methodology (the bottom up approach) will also allow the impact on future wholesale costs and retail prices of future energy savings from VEET activities that have occurred in the first four years of the scheme to be estimated.That is, for all three (or four) methodologies the costs and benefits of the scheme in relation to wholesale costs and retail prices should be calculated for the period, 1 January 2009 to 31 December 2012. While for the first methodology (the bottom up approach) the costs and benefits of the scheme in relation to wholesale costs and retail prices should also be calculated for the period 1 January 2009 to 1 January 2020.The differing nature of the methodologies will mean that the set of assumptions underpinning each model may be different. Each of the key assumptions must be documented and agreed with DPI prior to running the models.

III. Assess the distributional impacts of VEETIn part using the outputs from the previous project components, the supplier will identify the average annual changes to household energy bills for participants and nonparticipants in the scheme for each of the methodologies. It will also identify the average change to energy bills for residential households, SME’s and large businesses.

ScopeThe project scope will consider the impact of the VEET scheme on:

the electricity market; and the gas market.

The project will consider a range of costs and benefits relating to, but not limited to:

changes in retail electricity and gas prices; changes in wholesale electricity and gas prices; changes in generation expenditure; changes to generator profits (including changes to carbon tax liabilities);

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changes to retailer profits; changes in gas and electricity bills for participants and non-participants; scheme administration; transaction costs for retailers; transaction costs for accredited providers and up front purchase costs to participants.

The project will consider the distributional effects of the scheme according to: Participants and non-participants; and Residential and business (SMEs and large businesses) energy consumers.

Project tasks and deliverablesThe supplier must develop a set of cost benefit analyses that identify the impact of the VEET scheme on energy markets since its inception on 1 January 2009.The successful supplier will be required to undertake the following tasks:

develop and run three or four methodologies for calculating the effect the VEET scheme has had on energy consumption (supporting analysis should consider the advantages and/or limitations associated with the methodologies, including data availability and ease of replication);

undertake modelling, using inputs from the three to four separate energy consumption methodologies, that identifies the costs and benefits of the VEET scheme activities through its impact on the electricity and gas markets, particularly regarding wholesale costs and retail prices;

calculate the average change in household energy bills for participants and nonparticipants;

calculate the average change in energy bills for residential and business consumers;

field questions from policy staff and present findings as necessary; and prepare an interim and final report addressing key issues and findings.

The successful supplier will be required to provide the following deliverables: a set of methodologies which may be used by DPI for future analysis; a list of assumptions; a final report addressing key issues, findings and recommendations; and a presentation of the final report to the VEET review Steering Committee.

The final report should include an analysis of the individual methodologies used, outlining the advantages and limitations of each methodology. The supplier should specify in the report its preferred methodology, if it has one. The final report should contain individual sections regarding the impact of the VEET scheme on:

energy consumption; wholesale costs; retail prices; and

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participants and non-participants.

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Appendix B: Findings of the top-down approachB.1 Purpose and overview of the top-down approach

The ToR explained the purpose of and approach to be taken to the top-down analysis as follows:

The VEET scheme’s impact on energy consumption will be extrapolated from the deviation of actual energy consumption from that forecast before the scheme was introduced. The supplier will be required to provide a reasoned estimate for this deviation in consumption which includes an analysis (and justification) of all key factors that have influenced energy demand over the period.

The methodology will calculate the impacts of all key variables that may have contributed to this deviation, with the residual accounting for the impact of the VEET scheme. Variables should include, but not be limited to:

price elasticities of electricity and gas consumption;

economic activity (potentially disaggregating for specific industries);

take-up of solar PV;

other energy efficiency schemes; and

weather.

Our approach was premised on deconstructing the changes in energy consumption over the 1 January 2009 to 31 December 2012 period. It involved 4 tasks:

identifying the raw, non-weather corrected, change in average residential (and small commercial) consumption over the period 2008 to 2012 (‘the evaluation period’);weather correcting that consumption; determining the contribution that other pricing and policy measures have had on that change; anddetermining the residual amount of the change over the evaluation period that is not attributable to weather impacts, pricing or policy impacts, and assuming that this is attributable to the VEET scheme.

Each of these tasks is discussed in more detail below.

B.2 Change in average consumptionWe obtained information directly from the Victorian distribution businesses as to the estimated non-weather corrected electricity consumption (for both residential and small commercial customers) for each year since 2008, as well as the estimated number of customers in each customer class. The combination of the two allowed us to estimate how the total average consumption for residential and small commercial customers has changed since 2008.

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This is the fundamental building block in the top-down approach, as the overarching methodology relies on assessing the contributions to this overall change, with any residual (unaccounted for) change over the period being ascribed to the VEET scheme.The residential data provided to us by the distribution businesses has been reproduced in the following table, but without disclosure of which data belongs to which distribution business, as this information is considered commercial-in-confidence. Table 31: Average annual consumption per residential customer

Distribution business

Year (kWh) Average YoY

change

Change between 2008

and 20122008 2009 2010 2011 2012

Distco 1 5,183 5,225 5,367 4,902 4,918 -1.303% -5.111%

Distco 2 4,703 4,788 4,920 4,795 4,623 -0.427% -1.696%

Distco 3 6,051 6,137 5,937 5,580 5,509 -2.322% -8.970%

Distco 4 6,272 7,116 6,293 6,286 6,158 -0.460% -1.828%

Distco 5 5,340 5,309 5,262 4,977 4,908 -2.087% -8.092%

Source: Victoria distribution businesses

The above data indicates the raw change in average reported volumes for residential customers over the evaluation period has materially differed between distribution businesses. For example, the absolute change between 2008 and 2012 figures (non-weather corrected) varies between -1.69% for Distco 2 up to -8.9% for Distco 3. This is reflected in the annual year-on-year changes, which vary, for the same two businesses, between -0.42% to -2.32%.It is noted that the reductions reported by three of the five distribution businesses are broadly similar to those reported by AEMO in its 2013 National Electricity Forecasting Report30. Specifically, AEMO published a graph that indicated that average per capita consumption of residential and commercial customers had reduced from around 7,000 kWh in 2008/09 to around 6,500 kWh, or around 7.2%.

30 Available at http://www.aemo.com.au/Electricity/Planning/Forecasting/National-Electricity-Forecasting-Report-2013.

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Figure 2: AEMO’s estimated reductions in residential and commercial consumption in the NEM

Source: AEMO, National Electricity Forecasting Report for the National Electricity Market”, 2013 – page vii

Notwithstanding the above, the significant variation between Distco 2 and Distco 4 and the other three distribution businesses calls into question the likelihood of being able to accurately use the top-down approach at a distribution business level. For the approach to still have credence, one of two possible outcomes would need to eventuate:

the influence of weather on different businesses (particularly Distco 4 and Distco 2, relative to the other businesses) would need to be significantly different, so that after weather correcting, the overall change across the distribution businesses were much closer aligned; or the impacts of policy and pricing would need to vary markedly across the businesses (again, particularly Distco 4 and Distco 2, relative to the other businesses), so again, the overall change across the distribution businesses were much closer aligned.

There are two other theoretically feasible explanations that may also contribute to such an outcome occurring – namely, that the VEET scheme has a markedly different impact on different distribution business, and / or there is an unidentified explanatory variable that is driving up average consumption in the Distco 2 and Distco 4 distribution areas, relative to the other three distribution areas. Both of these are considered to have a very low probability of occurrence – mainly because there is no reason to believe that demographic characteristics will vary sufficiently across Victoria to result in material geographic variations in take up of the VEET, and /or penetration of other electricity consuming appliances.

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The influence of weather as well as the impacts of pricing and policy are investigated in further detail below.

B.3 Weather correctionOGW undertook an analysis of the relationship between weather and the electricity consumption that is measured by the Net System Load Profile (NSLP).31 The NSLP is calculated and published by the Australian Energy Market Operator (AEMO) for each Victorian Distribution Network’s area. The NSLP is based on a mathematical process that approximates half hourly basic meter readings. This process is designed as a substitute for the functionality of an interval meter for the purposes of allowing a Type 6 meter reading to be settled on the wholesale market. For Victoria, the NSLP is calculated by aggregating all injections into the transmission system from (i.e., total sent out generation) and subtracting off all the non-wholesale interval energy (Metering Installation Types 1, 2, 3, 4, 5 and 7)32. The NSLP does not cover all of a distribution business’ consumption, nor even its total residential and small commercial consumption. Therefore, rather than using the NSLP to calculate the total overall load for a particular distribution area, we used it to derive how that load shape responds to changes in weather, as well as how that load shape has changed over time. An implicit assumption in doing this is that the NSLP is a reasonable representation of an average residential / small commercial customer, including how the underlying customers respond to outturn weather events. We have no reason to believe that this is not the case.To calculate the weather dependency of load in each distribution business’ area we ascribed a Heating Degree Day (HDD) or Cooling Degree Day (CDD) value to each day from 2008 to 2012, based on the actual weather outcomes that occurred on those days. Weather data and HDD and CDD counts were supplied by SP AusNet. The same HDD/CDDs were applied when calculating the weather dependency of each distribution business’ energy consumption.We then undertook a regression analysis to assess the statistical relationship between our dependent variable, namely consumption from the NSLP – split out into 4 different time intervals of the day, and by season - and Effective Degree Days (EDDs), which was computed as the sum of our two explanatory variables (HDDs and CDDs). We used the results of the above analysis to create a distribution business specific algorithm that has an intercept (which reflects total base consumption in the NSLP, which is the consumption that is not affected by weather), and a coefficient representing the change in energy consumption contained within the NSLP (in that time interval/season/year), given a change in EDDs explanatory variable.

31 Ideally, a statistically significant sample of interval meter data, stratified by customer type and region, would have been used as the basis for this analysis. However, such a dataset was not available within the time and budget available for this assignment.

32 It should be noted that customers with solar panels and AMI meters will be retained within the NSLP, until their meter has been converted from a Type 6 to a Type 5 meter. Advice received from the distribution businesses is that this is unlikely to have materially impacted any of the evaluation years, except 2012 (and even then only for some distribution businesses).

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This information then allowed us to calculate two different loads (and consequently, load shapes):1. A pre-VEET scheme per customer load, which is simply the average

consumption in that year; and2. A new average load for each year of the evaluation, based on the actual

coefficients for each year of the evaluation period, but utilising the EDDs from 2008.

In the second calculation, by using the algorithms for each year, in combination with the EDDs from the 2008 year, we are effectively weather-correcting that consumption; that is, we have removed weather as a driver for the difference in average consumption and load shape between the 2008 year and future years. Therefore, any difference between in the consumption derived above represents an estimate of the non-weather related impact on average consumption (and load shape). The impact of this analysis on the average change in consumption for each distribution business is shown in the table below.Table 32: Average change in residential consumption – pre- and post-weather correction


Pre weather correction Post weather correction

Average YoY change

Change between 2008

and 2012

Average YoY change

Change between 2008

and 2012

Distco 1 -1.303% -5.111% -1.63% -6.360%

Distco 2 -0.427% -1.696% -0.83% -3.281%

Distco 3 -2.322% -8.970% -2.73% -10.465%

Distco 4 -0.460% -1.828% -0.78% -3.078%

Distco 5 -2.087% -8.092% -2.47% -9.518%


The far right column in the above table is effectively the non-weather related change in consumption between 2008 and 2012. In the following sections, we outline how we have gone about further decomposing that change into price impacts, solar impacts and the impact of other energy efficiency schemes. The residual, after the impact of those factors have been determined, is assumed to be the impact of the VEET scheme.

B.4 Price impactsFor the purposes of deriving the price elasticity impacts, we first undertook a literature review to assess the relevant range of own-price elasticity estimates pertaining to electricity consumption. In doing this, we reviewed the outcomes of a number of documents, including:

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Electricity Statement of Opportunities for the National Electricity Market (2011), which indicated that AEMO uses a long run price elasticity of -0.38 for Victoria, but with this varying down to -0.16 for NSW33; A report from NIEIR published in 2007, which estimates a price elasticity of -0.25 for residential customers, -0.35 for commercial customers and -0.38 for industrial customers34; andTwo studies quoted by Faruqui and George (the Salt River Project, by Kirdeide, and the ‘Puget Sound Energy’ project) which examined the price elasticity of demand for electricity in the United States. The former study was associated with coincident peak demand, not just peak period energy consumption. This study determined a value of –0.28 of peak demand based on Time of Use prices applied across 100,000 customers. The second study, which included the billing histories of around 240,000 customers, reported an own-price elasticity of demand between -0.20 and -0.33 for both the on-peak and off-peak periods35.

We further note that SP AusNet, in its previous regulatory submission, utilised an estimate of the short-run own-price elasticity of demand -0.15, which, was accepted by the Australian Energy Regulator.Our first observation is that there is no single, “recognised” source or estimate of the elasticity of demand for electricity in Australia. The closest would be the AEMO assumption. However, our second observation is that many of these studies, including AEMO, quote “long-run” elasticities, and furthermore, they are based on empirical data that has been collected over a period that feature contextual differences that are likely to impact the extent to which the outcomes produced from those studies are relevant to the Victorian context over the current evaluation period.Short-run elasticity is generally lower than long-run elasticity, as consumers generally only change appliances at the end of the useful life of their appliances, but may reduce use of existing appliances rapidly in the face of a price change. It is for this reason (amongst others) that SP AusNet used what was then considered a materially lower figure of -0.15.

33 AEMO – “Electricity Statement of Opportunities for the National Electricity Market”, 2011, page 3-59.

34 NIEIR , “The own price elasticity of demand for electricity in NEM regions” June 2007

35 Faruqui, A & George, S (2002), “The value of dynamic pricing in mass markets‟, The Electricity Journal, July, p. 48.

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Following on from the above commentary, we also note that the extent to which consumers respond to higher prices through lower consumption will be a function of the contextual factors affecting the industry at a point in time, including the overall magnitude of the change in price, current price levels, and the technology available for responding to those price signals. For example, the period over which many of the empirical studies above were undertaken featured much smaller prices rises, as well as being on a much smaller overall bill (and the relative size of that bill to a household’s total income is likely to be smaller). It is not practicable to identify the impact on own-price elasticity of demand for electricity; however, we are confident that the demand curve is not linear over all price and bill ranges. As a result, we think it is possible that the materially larger changes in price that have occurred over several successive years in the recent past will have influenced consumer price elasticity. It is possible that customers who respond to price changes are more likely than the average customer to respond by installing solar panels. If this is the case there is a risk of over-estimating the impact of price changes due to double counting the volume impacts of behavioural change based on older (pre extensive penetration of solar) elasticity values and the effect of the increased uptake solar panels. We emphasise we have not been in a position to test this hypothesis but nevertheless consider it prudent to adopt an elasticity at the low end of values available from our literature review36. For the purposes of our base case modelling37, we have used an estimated elasticity of -0.15, which means that for every 10% increase in price, we have assumed a 1.5% reduction in energy consumption. In determining the price coefficient, we have tested three “price drivers”, namely:

The change in the “variable component” of the single rate standing offer charge (of the host retailer) applicable to each distribution business’ customers over the evaluation period; The change in the “average bill” of those customers on a single rate standing offer (based on the host retailer’s standing offer) in each distribution business’ area; andThe change in the “average bill” using the average single rate market offer available in each distribution business’ area, in each of year of the evaluation period.

Note that we have used the figures reported for each distribution business in the ESC’s Energy Retailers Comparative Performance Report - Pricing and the Competitive Market for each year of the evaluation period in calculating the change in total bill, whether based on the single-rate standing offer or the single-rate market offers.The relative price impacts of each alternative are outlined in the table below.

36 There is also a possibility that customers installing solar will be sensitised to all factors that impact their bill and thus exhibit higher demand elasticity.

37 Sensitivity analysis of the elasticity factor was also undertaken and is discussed later in this section. See Tables 42 and 43.

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Table 33: Estimated cumulative residential price changes


Change in variable charge

in the host retailer’s

standing offer

Change in average bill based on

standing offer

Change in average bill based on market offer*

Distco 1 27.40% 33.77% 25.68%

Distco 2 35.93% 53.90% 41.79%

Distco 3 40.88% 44.43% 33.83%

Distco 4 44.98% 52.21% 33.77%

Distco 5 43.37% 51.81% 24.88%


As can be seen from the table above, there is not a substantial difference in the results of each of the possible approaches, although, in almost all cases, the estimated impact based on using the average “market offer” approach is the lowest.For the purposes of our modelling, we have been conservative and used the change in the average bill using the “average market offer” for each distribution business. The rationale for this is simply that the majority of residential customers in Victoria are on market offers, and therefore, it is likely to be most representative of overall bill change. A potential drawback of using this approach is that it focuses on the change in the total bill, not the change in the component of the bill that the consumers can actually influence via changes in their consumption behaviour (i.e., the variable charge). That said, there is also a school of thought that suggests that consumers may be as responsive to the change in the average bill as they are to the change in the marginal price. On balance, however, we have chosen the lower elasticity factor because it is more conservative. The following table shows the per annum price elasticity impact based on the combination of our assumed price elasticity (of -0.15) and our price coefficient (average bill change based on market offer).Table 34: Estimated per-annum price elasticity impacts


2009 2010 2011 2012Total

cumulative change

Distco 1 -0.80% -1.48% 0.04% -1.33% -3.53%

Distco 2 -1.56% -1.92% -0.53% -1.50% -5.40%

Distco 3 -1.37% -1.25% -0.20% -1.76% -4.50%

Distco 4 -0.50% -1.56% -0.62% -1.88% -4.50%

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Distco 5 -0.14% -1.32% -0.43% -1.58% -3.43%


B.5 Policy impactsFor the purposes of testing the policy impacts, we reviewed a number of different policies that we considered were likely to have impacted residential energy consumption, relative to 2008 (pre-VEET) levels. The specific policies considered are outlined below:

Minimum Energy Performance Standards – Lighting: This was a policy aimed at phasing out inefficient light bulbs (replacing 75W incandescent globes with 15W compact fluorescent globes). The scheme was first announced in 2007.Minimum Energy Performance Standards – Residential Air-conditioning: Since 1 October 2004, all single phase air conditioners manufactured in or imported into Australia and New Zealand must comply with MEPS requirements. MEPS requirements are set out in AS/NZS 3823.2-2011. On 1 October 2011, this policy was made more stringent.Solar Hot Water & Solar PV: The Small Scale Renewable Energy Scheme (SRES) is a federal scheme administered by the Clean Energy Regulator that encourages the adoption of small-scale technologies, such as Solar Hot Water (SHW) and Solar PV. When these technologies are installed they can be registered with the Clean Energy Regulator to receive a certificate which can be used to claim a rebate that subsidises the cost of the system. The Federal scheme has been in place since 2001 and is supplemented by state based schemes, such as those that provide feed-in-tariffs for Solar PV. For SHW, the Victorian Government offers five different rebate programs that can provide funds totalling up to $3300 per installation (the VEET is one of these programs). Every month, the Clean Energy Regulator publishes figures for all certificates claimed since 2001, providing accurate detail on the number and timing of the deployment of Solar PV and SHW systems in Australia, by postcode. This data was used in the modelling undertaken for this study.Insulation: This Commonwealth Government scheme provided rebates for households who installed insulation in their homes, with the intent of driving down space heating and cooling energy usage by 35%. We have assumed no insulation was installed under this scheme after 2010.

The following table outlines the estimated combined cumulative impact of these policies on energy consumption in each of the distribution areas, relative to 2008 levels.Table 35: Total per annum impact of policy drivers on residential consumption relative to 2008 levels (GWh)


Unit 2009 2010 2011 2012

Distco 1 GWh 3.90 12.72 18.88 26.04

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Distco 2 GWh 4.97 16.90 29.86 42.68

Distco 3 GWh 19.58 63.91 144.97 219.16

Distco 4 GWh 11.13 41.91 100.16 151.22

Distco 5 GWh 13.26 46.57 91.88 131.48


The following table breaks down the aforementioned impacts by policy type for each distribution area.Table 36: Breakdown of the residential energy reduction impact of each policy measure, by distribution area (GWh)

Distribution business Policy 2009 2010 2011 2012

Distco 1

MEPS - Lighting 1.77 4.02 7.69 12.49

MEPS - AC Res 0.01 0.03 0.04 0.59

Insulation 1.71 6.85 6.85 6.85

Solar Water Heater 0.09 0.23 0.43 0.76

Solar PV 0.32 1.59 3.86 5.33

Distco 2

MEPS - Lighting 1.86 4.23 8.09 13.14

MEPS - AC Res 0.01 0.03 0.04 0.59

Insulation 1.80 7.20 7.20 7.20


Solar PV 0.88 4.46 12.76 18.94

Distco 3

MEPS - Lighting 4.10 9.30 17.81 28.92

MEPS - AC Res 0.03 0.06 0.10 1.36

Insulation 3.97 15.87 15.87 15.87


Solar PV 4.37 22.06 81.96 129.08

Distco 4

MEPS - Lighting 3.74 8.47 16.22 26.35

MEPS - AC Res 0.03 0.05 0.08 1.18

Insulation 3.61 14.45 14.45 14.45


Solar PV 3.75 18.93 69.40 109.24

Distco 5 MEPS – Lighting 3.87 8.78 16.81 27.29

MEPS - AC Res 0.03 0.06 0.09 1.22

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Insulation 3.75 14.98 14.98 14.98


Solar PV 3.60 18.16 52.12 75.80

*Figures may not match Table 35 due to rounding.


The following table shows the total contribution across Victoria of each policy driver.Table 37: Policy impacts (GWh)

Policy 2009 2010 2011 2012

MEPS – Lighting 15.35 34.80 66.63 108.19

MEPS - AC Res 0.11 0.23 0.35 4.95

Insulation 14.84 59.35 59.35 59.35


Solar PV 12.91 65.22 220.08 338.40

Figures may not match Table 35and Table 36due to rounding.


In addition to the above, we also sought to cross-check our results against other readily available public information, in particular, for solar PV, which has by far and away the largest impact on energy consumption of all of the policy drivers investigated. In particular, we note that our figures broadly match those provided by other credible sources, including AEMO, and the Clean Energy Council. For example, in its report Rooftop PV Information Paper (2012), AEMO stated that38:

“Over 2011 and the first two months of 2012, rooftop PV systems in Victoria are estimated to have generated 260 GWh…”

Given that this covers 14 months, this equates closely to our forecast of 220GWh outlined in the above table (which is for 12 months).The Clean Energy Council, in its Renewable Energy in Victoria Report (2012), contains the following information with regard to the amount of energy it estimates has been produced by solar PV cells since 2009. Table 38: Clean Energy Council estimates of cumulative Solar PV output (GWh)

Fuel type Unit 2009 2010 2011 2012

Bioenergy GWh 554 605 633 651

Hydro GWh 506 748 813 950

38 AEMO, “Rooftop PV Information Paper - National Electricity Forecasting”, 2012. Page 16

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Solar GWh 18 61 225 550

Wind GWh 1028 1217 1280 1674

Total GWh 2106 2632 2951 3825

Source: Clean Energy Council -“Renewable Energy in Victoria – Report 2012”, page 5

We note that for the first three years of our evaluation period, the Clean Energy Council’s figures (for solar) are very similar to our figures (e.g., 2011 figures are within 2.5% of each other). For 2012, they differ materially, and we are unable to explain the driver for this difference although we note that the Clean Energy Council provides the following caveat in its report: “the most recent 12 months data at the time of publication is subject to review based on future STC creation”. This indicates that this difference may be driven by the timing of the creation of the small-scale technologies certificates (STCs), and when we undertook our analysis relative to the timing of the Clean Energy Council’s analysis. Notwithstanding the above caveat, the 2012 solar PV output (GWh) provided by the Clean Energy Council appears to be somewhat of an anomaly, given that the figure reported suggests that the installed capacity of solar is around 55% more in 2012 versus 2011 (417MW vs. 270MW), yet the production that it reports as being derived from that installed capacity is 145% more (550GWh vs. 220GWh). Table 39: Clean Energy Council estimates of installed capacity of Solar PV (GWh)

Fuel Type Unit 2009 2010 2011 2012

Bioenergy MW 121 124 128 129

Hydro MW 802 802 802 803

Solar MW 20.1 75.1 270 417

Wind MW 428 428 4332 519

Total MW 1372 1429 1633 1869

Source: Clean Energy Council -“Renewable Energy in Victoria – Report 2012”, page 4

Table 40: Year-on-year increase in installed capacity (MW) and output (GWh)

Fuel Type Unit 2009 2010 2011 2012

Increase in Installed Capacity MW NA 373.63%

359.52% 154.44%

Increase in Energy Output GWh NA 338.89%

368.85% 244.44%

Source: Clean Energy Regulator

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Overall, the relationship between installed capacity and energy outputs from solar panels in 2012 is inconsistent with the relationship that holds in previous years, whereby output (GWh) increases at a similar rate to installed capacity. Finally, we note that if the percentage increase in installed capacity reported by the Clean Energy Council between 2011 and 2012 (54.44%), were applied to our 2011 output (266 GWh), we get a figure of 341 GWh, which is very similar to what we have estimated (338 GWh).

B.6 Results of the top-down analysisBased on the information outlined in the previous sections, the following table consolidates the total impact of each of the identified drivers, and consequently, the residual impact that could possibly be ascribed to the VEET scheme.Table 41: Residual impact possibly attributable to VEET schemeDistribution business Component 2008 to 2012

Distco 1

Price -3.53%

Policies -1.92%

Total -5.45%

Reported Volumes (weather corrected) -6.36%

Unaccounted for Amount -0.91%

Distco 2

Price -5.40%

Policies -3.23%

Total -8.63%


Unaccounted for Amount 5.35%

Distco 3

Price -4.50%

Policies -5.76%

Total -10.26%



Distco 4 Price -4.50%

Policies -4.37%

Total -8.87%


Unaccounted for Amount 5.79%

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Distco 5

Price -3.43%

Policies -4.25%

Total -7.68%




As can be seen from the results outlined in the table above, the top-down approach does not result in a feasible estimate of the amount that could be attributable to the VEET Scheme for the two distribution businesses (Distco 2 and Distco 4) whose raw (non-weather corrected) consumption figures indicated that there has been only a relatively small change in the average residential consumption over the evaluation period. Their unaccounted-for reductions (and therefore VEET scheme amounts) are over 5%; that is, the VEET scheme has contributed to an increase in average consumption over the period of over 5%.For the other three businesses, the top-down approach provides what would appear to be a reasonable estimate of the unaccounted-for amount. More specifically, as would be expected, it explains the majority of the overall change in average consumption over the period, with the residual for Distco 5 being -1.83%, the residual for Distco 3 being -0.20% and for Distco 1 being -0.91%. In this scenario, the unaccounted for amount could, theoretically, be used as a proxy estimate of the impact of the VEET scheme. However, we would caution against utilising these estimates for the purposes of undertaking any of the consequential modelling of the impact of the VEET 39 on wholesale, network or retail prices, or to identify the distribution impacts, for a number of reasons, over and above the substantive issues pertaining to Distco 2 and Distco 4. In particular, the top down approach is very sensitive to the assumed elasticity of demand. For example, the table below demonstrates the impact on the expected cumulative change in consumption over the evaluation period, if a -0.20 elasticity estimate were to be used, or a -0.25 elasticity were used, instead of a -0.15 estimate.Table 42: Sensitivity associated with using alternative elasticity estimates


Cumulative total change

(-0.15 elasticity)


(-0.20 elasticity)


(-0.25 elasticity)

Distco 1 -3.53% -4.69% -5.84%

Distco 2 -5.40% -7.15% -8.88%

Distco 3 -4.50% -5.98% -7.43%

39 This includes the development of the econometric analysis originally requested in the ToR.

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Distco 4 -4.50% -5.97% -7.42%

Distco 5 -3.43% -4.56% -5.68%


This is further illustrated in a comparison of the total results, under each of the elasticity assumptions.Table 43: Residual impact attributable to the VEET Scheme with different elasticities

Distribu-tion busi-ness

Component -0.15 Elasti-city

-0.20 Elasti-city

-0.25 Elasti-city

Distco 1

Price -3.53% -4.69% -5.84%

Policies -1.92% -1.92% -1.92%

Total -5.45% -6.61% -7.76%

Reported Volumes (weather corrected) -6.36% -6.36% -6.36%

Unaccounted for Amount -0.91% 0.25% 1.40%

Distco 2

Price -5.40% -7.15% -8.88%

Policies -3.23% -3.23% -3.23%

Total -8.63% -10.38% -12.11%


Unaccounted for Amount 5.35% 7.10% 8.83%

Distco 3

Price -4.50% -5.98% -7.43%

Policies -5.76% -5.76% -5.76%

Total -10.26% -11.73% -13.18%


Unaccounted for Amount -0.20% 1.27% 2.72%

Distco 4

Price -4.50% -5.97% -7.42%

Policies -4.37% -4.37% -4.37%

Total -8.87% -10.34% -11.79%


Unaccounted for Amount 5.79% 7.26% 8.71%

Distco 5 Price -3.43% -4.56% -5.68%

Policies -4.25% -4.25% -4.25%

Total -7.69% -8.81% -9.94%

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Unaccounted for Amount -1.83% -0.70% 0.42%


In conclusion, the results are particularly sensitive to the elasticity of demand assumptions that are adopted. This is because of the overall magnitude of the price increase over the evaluation period, with the even the lowest price rise leading to a 3.7% reduction in consumption over the period (assuming our base case assumption of price elasticity at -0.15).This is compounded by the uncertain nature of this estimate, as discussed above.

B.7 An alternative use for the top-down approachDespite it being inappropriate to use as the basis for estimating the impact of the VEET for each distribution business, the information derived from the top-down approach can serve as a high-level sense check to bottom up estimates of the impact of the VEET.In particular, DSDBI can cross-check the results of the bottom up approach against the estimated impact of other policy drivers to assess the relativity of the different policy initiatives, including the VEET scheme. This may allow it to draw some conclusions about the overall results produced via the adoption of the bottom up approach.The following table provides a comparison of the different policy drivers that OGW has estimated as part of this assignment, and the estimated impact that the VEET scheme has had on energy consumption over the same period.

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Table 44: Comparison of VEET scheme with key policy impacts

Policy 2009 2010 2011 2012

MEPS – Lighting 15.35 34.80 66.63 108.19

MEPS - AC Res 0.11 0.23 0.35 4.95

Insulation 14.84 59.35 59.35 59.35


Solar PV 12.91 65.22 220.08 338.40

VEET scheme 66.19 220.68 266.07 447.33

VEET scheme impact as a proportion of total other policy impacts

125.29% 121.24% 68.97% 78.40%


As shown, the bottom-up analysis suggests that the VEET scheme has had a larger impact on residential electricity consumption than solar PV in all of the years. Further, in the first two years, the VEET had a larger impact than all of the policy initiatives considered combined.Although it is not possible to use the figures above to reach a conclusion regarding the reasonableness of the bottom-up estimates of the impact of the VEET, the comparison can provide a useful check-point for those estimates. To the extent that the comparison suggests that the current estimates of VEET impacts may be optimistic, DSDBI may wish to consider further modifications to the manner in which program impacts are estimated.

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Appendix C: Allocation of VEET measure annual savings to seasons and times of day to create load shape impacts for use in the market modelling

% Saved by season

Measure

Summer months(Dec - Feb)

Shoulder months (Mar - May, Sep - Nov)

Winter months (Jun- Aug)

Replace electric off-peak storage water heating with gas/LPG storage, instantaneous or boosted solar water heating 20% 50% 30%Replace electric off-peak storage water heating with elec-tric boosted solar or heat pump water heater 20% 50% 30%Replace electric central resistance heating with high effi-ciency ducted gas heater 0% 30% 70%

Relace GLS lamps with low energy lamps 15% 50% 35%Install shower rose for use with electric off-peak storage water heater 25% 45% 30%

Install standby power controllers 25% 50% 25%

% Saved by time of dayMeasure Summer months (Dec - Feb)

7A - 3P 3P - 7P

7P - 11P

11P - 7A

Replace electric off-peak storage water heating with gas/LPG storage, instantaneous or boosted solar water heating 0% 0% 0% 100%Replace electric off-peak storage water heating with elec-tric boosted solar or heat pump water heater 0% 0% 0% 100%Replace electric central resistance heating with high effi-ciency ducted gas heater NA NA NA NA

Relace GLS lamps with low energy lamps 9% 27% 56% 7%Install shower rose for use with electric off-peak storage water heater 0% 0% 0% 100%Install standby power controllers 36% 9% 9% 45%

% Saved by time of day

MeasureShoulder months Mar - May & Sep

- Nov)

7A - 3P 3P - 7P

7P - 11P

11P - 7A

Replace electric off-peak storage water heating with gas/LPG storage, instantaneous or boosted solar water heating 0% 0% 0% 100%Replace electric off-peak storage water heating with elec-tric boosted solar or heat pump water heater 0% 0% 0% 100%Replace electric central resistance heating with high effi-ciency ducted gas heater 27% 16% 38% 19%Relace GLS lamps with low energy lamps 10% 28% 55% 7%Install shower rose for use with electric off-peak storage water heater 0% 0% 0% 100%Install standby power controllers 36% 9% 9% 45%

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% Saved by time of dayMeasure Winter months (Jun- Aug)

7A - 3P 3P - 7P

7P - 11P

11P - 7A

Replace electric off-peak storage water heating with gas/LPG storage, instantaneous or boosted solar water heating 0% 0% 0% 100%Replace electric off-peak storage water heating with elec-tric boosted solar or heat pump water heater 0% 0% 0% 100%Replace electric central resistance heating with high effi-ciency ducted gas heater 24% 22% 33% 20%Relace GLS lamps with low energy lamps 13% 32% 48% 7%Install shower rose for use with electric off-peak storage water heater 0% 0% 0% 100%Install standby power controllers 36% 9% 9% 45%

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