Cost/ben enefit asses essment of the DRM DRM Pres esent entat - - PowerPoint PPT Presentation

Pres esent entat ation t ion to stak akeholder eholders* 30 30 October 2014 2014 Parkroy

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Cost/ben enefit asses essment of the DRM DRM

Typographical corrections and clarifications raised in presentation added

Agenda

• Overview of approach
• Approach to and results in the various components

– Counterfactual – Take-up – Wholesale market impacts – Network impacts – Costs

• Summary of results
• Scope items not being discussed today

– Distributional impacts* – Qualitative assessment of non-monetised economic benefits

1

* Slides on this topic have been added to this slidepack since the workshop

Total resource benefits and costs

Overview of approach

2

Establish counterfactual Estimate DRM take-up Simulate wholesale market impacts (CEMOS) Estimate network impacts

• Total supply system costs
• Wholesale market prices
• USE
• Emissions
• Generator profitability
• Augmentation capex

(LRMC)

• Revenue
• Network prices

Estimate costs Calculate estimated distributional impacts

Counterfactual – two cases developed to date

• AEMO 2014 NEFR on its own

– Includes explicit consideration of demand response, small PV and energy efficiency – Does not include consideration of other possible technology developments (EVs, storage)

• but very difficult to identify a generally accepted forecast of the penetration of these technologies
• AEMO plus CRNP

– Favourable draft determination published in August 2014 – AusNet Services’ Critical Day Peak Demand Tariff (first implemented in 2011)

• Creates a new tariff component for customers > 160 MWhpa: Critical Day Peak Demand
• CDPD is set by average demand over 20 hours (2-6 PM on 5 days in Dec – Mar nominated by the distributor)

– Provides a documented example of what can be achieved

• 7.3% reduction in peak demand for large customers ( >160 MWhpa), 5% for system as a whole
• Low implementation costs

– Generalised to all DNSPs and assumed to be implemented in 2016

3

Impact of CRNP on Wholesale Market Peak Demand (MW)

2016 2020 2025 2030 2035 NSW

• 351
• 402
• 469
• 666
• 551

VIC

• 137
• 118

QLD SA TAS

4

• Impact on wholesale market peak demand is significantly less than maximum impact of

CRNP

• This due to the fact that wholesale market increasingly peaks AFTER 6 PM (CRNP is

assumed to operate between 2 and 6 PM)

• Which in turn is due to

– Increasing penetration of rooftop PV in the first instance – But also to the impact of the CRNP itself

Timing of wholesale market peak demand – AEMO 2014 NEFR

2015 2016 2017 2018 2019 2020 2025 2030 2033 QLD 10POE 17:30 17:30 17:30 17:30 19:00 19:00 19:30 19:00 19:00 50POE 19:00 19:00 19:00 19:00 19:00 19:00 19:00 19:00 19:00 NSW 10POE 16:00 16:00 16:00 16:00 16:00 16:00 16:30 17:00 17:00 50POE 17:00 17:00 17:00 17:00 17:00 17:00 17:00 17:00 17:30 SA 10POE 17:30 18:30 18:30 18:30 18:30 18:30 18:30 18:30 18:30 50POE 20:00 20:00 20:00 20:00 20:00 20:00 20:00 20:00 20:00 VIC 10POE 16:30 16:30 16:30 16:30 17:00 17:00 17:00 17:00 17:30 50POE 17:00 17:00 17:00 17:30 17:30 19:30 19:30 19:30 19:30 TAS 10POE 08:30 08:30 08:30 08:30 08:30 18:30 18:30 18:30 18:30 50POE 18:30 18:30 18:30 18:30 18:30 18:30 18:30 18:30 18:30

5

Counterfactual – other potentially relevant policy settings considered but not included

• RIT-D

– No accepted forecasts of impacts – Likely to be lower than expected given reduced AEMO demand forecast and possibly CRNP

• Small Generator Aggregator Framework

– No small generators as yet operating under the Framework, and DRM would provide an essentially similar arrangement

• Connecting Embedded Generators

– If enacted, likely to improve the investment environment and reduce time required for connection – Magnitude of impact is difficult to assess, and will affect both the base and DRM cases

• Bidding in Good Faith

– No position taken as yet by the AEMC; implementation can only improve DRM case

• Competition in metering and related services

– Little impact: metering & metering services already competitive for DRM segments

• Multiple Trading Relationships (MTR)

– Provides similar functionality (ability for customer to have commercial relationships with two market entities); DRM requires baseline calculations and payment at spot price for DR – Potential for some ‘sharing’ of implementation costs

6

DISCUSSION

7

Take-up – summary of approach

• Industrial sector

– ClimateWorks data in Industrial demand side response potential (Feb 2014) served as primary source – Adjusted to NEM (ABARE data) and extrapolation further adjusted to reflect ratio of large, medium and small enterprises by industrial sector within each state

• Commercial sector

– ABARE Table F to estimate of the energy consumption by ANZSIC Division and sub-sector level for aggregated large, and medium to large sites by state – Assumed peak demand would be 150% of the average, based on non 24/7 operation – Used industry knowledge and literature to identify potential for DR and estimate likely take-up

• Standby generation

– Industrial – used the levels of standby identified in ClimateWorks data (with same adjustments as above, ) – Commercial – literature review to obtain an indication of levels of standby available (e.g., NSW DEUS survey)

• Further adjustments for

– Amount of DR already in the market – Impact of DRM on availability of DR at various spot prices – Impact of CRNP

8

Take-up – approach detail

Industrial sector

• ClimateWorks data in Industrial demand side response potential (Feb 2014) served as

primary source

– Provides solid insights into the potential practices of industry, but some limitations – Interviews undertaken to assess potential in total, not DR specifically – So size of opportunity, associated costs issues and the impact of notification periods are not entirely applicable to the DRM – Augmented with information obtained from responses to Consultation Paper and follow-up discussions with stakeholders

• Adjustments included:

– ABARE data - to remove WA and NT from each of the industrial sector – ABS data on employee numbers and turnover - to evaluate the ratios of large, medium, and small facilities by industry sector within each state, which affects the types of end-use processes present and therefore the likely potential for DR

• This was used to refine the extrapolation of DR potential from the very large enterprises interviewed by

ClimateWorks to each industry sector

• Some conservatism here as certain types of DR were not necessarily applied to all of the sectors in which
• ne would expect them to be applicable

9

Take-up – approach detail (2)

Commercial sector (ANZSIC Divisions F, G, H, J, K, L, M, N, O, P, Q, R, S)

• ABARE Table F data - to obtain an estimate of the energy consumption by state
• Applied info from NSW/VIC at sub-sector level to obtain estimates of energy

consumption for aggregated large sites and medium to large sites

• Estimate average demand for each sectors

– Assumed peak demand would be 150% of the average, based on non 24/7 operation – Average calculated by the following assumptions:

• for large facilities - 90% of total consumption occurs during the working week, 10 hrs/day and 250 days/yr
• for medium sized facilities - all consumption occurs during the regular working week
• Identified typical energy use in key end-uses and their contribution to peak demand
• Used industry knowledge and literature to

– identify potential for DR – estimate the probability of participation to obtain estimated DR take-up

• Base DRM case includes only large commercial facility DR potential/take-up

10

Take-up – approach detail (3)

Standby generation

• Commercial sector

– Literature review to obtain an indication of levels of standby available (e.g., NSW DEUS survey) – Used population / industry splits to estimate likely levels of standby generation by state and sub- sector – Note: available surveys never had more than 80% response rates and this was not extrapolated – may be a source of some minor conservatism – Base case assumed 40% participation rate

• Industrial sector

– Used the levels of standby identified in ClimateWorks data (with same adjustments as above) – Split between states using same ratios as in commercial – Projected participation rates same as for commercial

11

Take-up – approach detail (4)

Estimate take-up by state and price point

• Subtract DR already being exercised as identified in AEMO NEFR
• Allocate to state level based on earlier analysis of ABARE data
• Judgementally changed proportions of available DR at various spot prices from AEMO to

sculpt DR potential estimated above

12

Trigger spot price ($/MWh) Cumulative % of total DR potential that will respond

AEMO Assumed for DRM case $300 19% 25% $500 22% 30% $1,000 23% 40% $7,500 59% 80% MPC 100% 100%

Take-up – approach detail (5)

Assumption underlying price-point participation adjustments

• AEMO data is pre-DRM
• Reflects a mix of DR based on spot exposure and participation in retailer programs in

which

– DR provider percentage of arbitrage has generally been about 50%, and – Dispatch calls have not always been made at strike prices nominated by DR provider

• Judgemental estimates informed by following observations/assumptions:

– Most customers are not interested in spot exposure, so majority of growth will come from participation of customers who want to play through DRM – DRAs will offer higher levels of arbitrage to DR providers, and call for dispatch more regularly, which will serve to increase the % of total DR potential that will become available at each of the AEMO price points, as shown above

13

Take-up – approach detail (6)

Adjustment for CRNP (in that case)

• Subtracted impact of CRNP from DR available before 6PM

Adjustment for time of wholesale market peak demand

• Single-shift industrial operations are unlikely to provide DR after 6PM as many of their
• perations will be winding down by 4PM
• 2- and 3-shift industrial operations in industrial and mining will contribute to DR even as

peak shifts to hours after 6PM

• Commercial buildings split based on likely usage patterns by sub-sector, e.g. most
• ffices will have very little load to reduce after 6PM, whereas more continuous operations

such as data centres or hospitals will be able to participate both before and after 6PM

• Analysis and allocation of DR by sector re-analysed to account for potential drop in DR

as peak times shift later in the day

14

Take-up – results (MW)

2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 NSW 312 312 375 439 503 566 628 689 751 812 VIC 231 231 278 325 373 420 465 511 556 602 QLD 238 238 286 335 383 432 479 526 573 620 SA 72 72 87 102 116 131 145 160 174 188 TAS 71 71 85 100 114 129 143 157 171 185 NEM 923 923 1112 1300 1489 1678 1860 2042 2225 2407

15

2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 NSW 217 217 257 297 337 377 415 454 492 531 VIC 156 156 184 212 289 369 422 511 556 602 QLD 238 238 286 335 383 432 479 526 573 620 SA 72 72 87 102 116 131 145 160 174 188 TAS 71 71 85 100 114 129 143 157 171 185 NEM 753 753 899 1045 1240 1438 1604 1807 1966 2125 AEMO 2014 AEMO 2014 plus CRNP

• Each

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DISCUSSION

16

Wholesale market impacts – approach

• Starting point was 2014 AEMO National Electricity Forecast (NEFR) – provided:

– Forecast annual sent-out electricity requirements, peak demand and LDCs – Current and committed generation plant and transmission interconnections – Costs and operating characteristics of candidate conventional and renewable plant

• No carbon cost
• We were instructed to keep conventional coal options in the candidate list (to be

consistent with RET Review)

• Key issue was to ensure that wholesale prices are plausible

– Required balancing the amount of coal, gas and renewable generation in the market – Guideline was to ensure a reasonable price path (i.e., one that provides a realistic level of revenue/profitability) for all operating generators – This required withdrawal of coal and gas capacity and a floating (i.e., reduced) level of renewable generation given the current load forecast – Full LRET quota is NOT met

17

Wholesale market impacts – approach to modelling DRM

• Assumed most of the DR to be provided under the DRM will come from DRAs
• DRA bidding behaviour assumed to be rational – that is, they will not knowingly
• ver-dispatch in such a way that it crashes price
• DR itself modelled as a series of plants with:

– SRMC specified at the various trigger prices – zero minimum generation which makes the plant fully flexible subject to trigger price and capacity – minimum run time of 30 minutes – maximum number of hours per event to be 8 hours

• note that no high price event of 8 hours occurred in the base case

– maximum of 80 hours of dispatch per year

• note that no more than 9 hours (first 5 load blocks) were found with prices at or above trigger

points in most years, though in some they persisted for 15 hours (first 6 blocks)

–

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Wholesale market impacts – approach details

• Load block approach (consistent with AEMO long term planning in virtually all other

NEM simulation models)

• Model run to 2040 and results reported to 2035 to manage any possible end effects

(something AEMO now notes in their work)

• Game theoretic analysis with Monte Carlo on generator outages
• High and typical load represented by separate runs for 10POE and 50POE (DRM

effectively only occurs in 10POE runs where price is high)

• Close attention to different availability of DRM in the 10POE and 50POE cases due to

changes in timing of peaks as noted in AEMO 2014 NEFR and further impacted by CRNP

• Conservative treatment of price spikes not aligned with high demand which are seen in

practice but are very subjective to include in modelling

– May disappear or at least be affected by things like good-faith rebidding, etc. – Hence, model only sees high prices when demand is high (note Monte Carlo process picks up high prices due to generator outages a little away from peak but not further away (e.g., at 4AM)

19

Cases analysed

Case Without DRM With DRM BAU AEMO 2014 NEFR Base DRM CRNP AEMO 2014 w/ CRNP Base DRM w/ CRNP Price volatility AEMO 2014 w/ CRNP @ 10POE prices Base DRM w/ CRNP @ 10POE prices Illustrative capex requirement case* Energy and peak demand growth rates from 1999-2009 Base DRM

20

• Note that the ‘Illustrative capex requirement’ case was developed strictly for illustrative

purposes – to identify a set of conditions under which the DRM provides significant

• benefit. It assumes:

– average annual growth rates in both peak demand and overall electricity consumption similar to those experienced in the period 1998 -2008 – that the significant over-supply of generation no longer exists and installed capacity levels are more like longer term averages

• It should be noted that while these conditions are plausible (i.e., they have existed in the

recent past) they are not conditions that are expected to exist within the near- to mid- term

* Previously termed ‘High demand growth’ case

Wholesale market impacts – results

Impact item (2017 thru 2035, NPV @ 7.5%) AEMO 2014 NEFR AEMO forecast plus CRNP Change in generation sector capacity & FOM costs (NPV) NIL NIL Change in generation sector fuel and VOM costs (NPV) $2.6 million NIL + Change in total generation sector costs (NPV) $2.6 million NIL + Reduction in installed capacity as at 2035 0 MW 0 MW Reduction in generation 136 GWh 57 GWh Average annual change in NEM wholesale price ($/MWh) $0.73 $0.26 GHG emission reductions 259,000 tonnes 182,000 tonnes Average annual reduction in unserved energy 0.02 GWh 0.01 GWh

21

• These results are not surprising given the nature of the AEMO forecast

– Over-supply squeezes out gas to minimum take or pay (cogen and some take-or-pay still needed to back contract positions) – Market becomes incremental on coal – leading to very low prices – All additional demand growth taken up by renewables and return of out-of service plants

Wholesale market impacts – results (2)

Impact item (2017 thru 2035, NPV @ 7.5%) Price volatility Illustrative capex requirement case* Change in generation sector capacity & FOM costs (NPV) NIL $63 million (10 yrs) $1.1 billion (19 yrs) Change in generation sector fuel and VOM costs (NPV) $1.9 million minor Change in total generation sector costs (NPV) $1.9 million $63 million (10 yrs) $1.1 billion (19 yrs) Reduction in installed capacity (as at 2035) 0 MW 1,968 MW (10th yr) 1,980 MW (19th yr) Reduction in generation 57 GWh 296 GWh (10th yr) 437 GWh (19th yr) Average annual change in NEM spot price ($/MWh) $0.42 $0.79 (10 yrs) $1.56 (19 yrs) GHG emission reductions (tonnes) 777,000 tonnes 467,000 (10 yrs) 1.5 million (19 yrs) Average annual reduction in unserved energy 0.02 GWh 0.4 GWh

22

* Previously termed ‘High demand growth’ case

Observations

• Present market conditions are not favourable to DR in general

– Supply overhang results in

• Very few hours of high prices
• No ability for DR to defer the need for additional plant as all additional demand growth taken up by

renewables and return of out-of service plants

• Increased price volatility increases the scope for DR to participate in the market,

– But generation over-supply still results in virtually no benefit from the DRM due to inability to defer plant

• But DRM is very likely to have significant benefits under conditions that require

sustained additional generation capex

– For example, the high growth rates that characterised the mid 90s to mid to late 00s – Strong growth in peak demand allows DR to provide an alternative to peaking generation – In practice, the timing and extent of capex requirements will be influenced by demand growth and decisions about retirement (rather than cold storage) of existing plant and costs to restart units that have been out of service for an extended period

23

DISCUSSION

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Network benefits – summary of approach

• Estimated spread of DR impact at state level at times before and after regional peak

demand

– assumed normal distribution of impact +/- 1.5 hours of peak

• Further adjusted DR estimates to reflect:

– the timing of peak demand at different voltage levels within the network – proportion of load of DRM eligible customers that is served at each voltage level – proportion of the DR that will impact each specific network business in each State (based on proportion of state-wide electricity consumption of non-residential customers within each DNSP)

• Multiplied the resulting DR at each voltage level in each network by the voltage-specific

LRMC for each network business

– LRMC figures were based on published information wherever possible, unpublished information that we are aware of, or (where nothing was available) the estimates of other similar businesses

• Discounted the LRMC figures from year 3 onwards by 5%

– To reflect the fact that CRNP is likely to lower network business’ demand forecasts, delaying the need for capex, and therefore reducing their LRMC of supply

• Adjustment also made to reflect proportion of network that peaks in the same season as

the wholesale market

25

Network benefits – approach detail

• Estimate spread of DR impact at state level at times before and after regional peak

demand (based on outturn system peak demand timing) using the following assumption:

– 100% of that year’s DR assumed to occur at time of system peak in that region – 75% half hour before and after this time – 50% one hour before and after this time – 25% one and a half hours before and after this time. – 0% outside of that +/- 1.5 hours on either side of peak demand in the jurisdiction

• Further adjust DR estimates to reflect the timing of peak demand at different voltage

levels within the network

• Generalised peak-period times were assumed as follow:

– Sub transmission – 3 to 6 PM AEST – High voltage – 3 to 5:30 PM AEST – Low voltage – 4:30pm to 7:30 PM AEST

26

Network benefits – approach detail (2)

• Example: if the wholesale system is expected to peak at 6PM (AEST) in Victoria

– DR affecting LV LV networks in Victoria would be the average of

• 100% * DR (the 6PM ‘peak’ figure)
• 75% * DR (for 5:30PM) + 75% * DR (for 6:30PM)
• 50% * DR (for 5PM) + 50% * DR (for 7PM)
• 25% * DR (for 4:30PM) and 25% * DR (for 7.30PM)

– This reflects the fact that not all parts of that part of the LV network (in this example) will peak exactly when 100% of the DR estimate is likely to be available (which coincides with when the wholesale system peaks) – If the wholesale system peaked half an hour later (at 6.30PM) in the above example, the 4.30PM figure would have 0% * DR applied to it – because it is outside the +/- 1.5 hour window

27

Network benefits – approach detail (3)

• Step above is undertaken for each of the various voltage levels using the following

proportions which were developed based on data provided by a number of DNSPs:

– Transmission 100% in all cases – Sub-transmission ~25% – High voltage ~10% – Low voltage ~65%

• Adjustment is then made for the estimated proportion of that DR that will impact each

specific network business in each State (based on proportion of state-wide electricity consumption of non-residential customers within each DNSP)

• The resulting DR at each voltage level in each DNSP is then multiplied by the voltage-

specific LRMC for each network business

– LRMC figures were based on published information wherever possible, unpublished information that we are aware of, or (where nothing was available) the estimates of other similar businesses – Estimates were cross-checked against a calculation based on reported MW/Augmentation costs in regulatory submissions

• Discounted the LRMC figures from year 3 onwards by 5%

– Reflect the fact that CRNP is likely to lower network business’ demand forecasts, delaying the need for capex, and therefore, reducing their LRMC of supply

• Adjustment also made to reflect proportion of network that peaks in the same season as

the wholesale market

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Network benefits – results (AEMO forecast plus CRNP)

29

TOTAL 7.5% 10% 20 years $117.8m $93m 15 years $91.6m $75.5 Distribution 7.5% 10% 20 years $101.4m $80.1m 15 years $78.9m $65m Transmission 7.5% 10% 20 years $16.4m $12.9m 15 years $12.7m $10.4m

Network benefits – results (AEMO forecast alone)

30

TOTAL 7.5% 10% 20 years $178.4m $141.8M 15 years $138.5m $115M Distribution 7.5% 10% 20 years $147.3m $117.1m 15 years $114.4m $95m Transmission 7.5% 10% 20 years $31.1m $24.7m 15 years $24.1m $20m

Observations

• The approach used significantly improves on the type of static analysis commonly

undertaken

– Adjusts for potential differences in timing between network peaks (including the fact that much of the CRNP will affect higher voltage levels) and seasonality – But as a top-down approach cannot accurately account for current headroom and growth rates (as is done in the wholesale market simulation modelling)

• Network benefits are very high relative to wholesale market benefits in the BAU and

CRNP cases

– Begs the question of why a market mechanism would be undertaken to provide network benefits

• Network benefits have not been calculated as yet in the High demand case

– But are much less critical to the outcome

31

DISCUSSION

32

Available cost estimates – ERAA/Seed Advisory

• Estimate provided by Seed Advisory from ERAA member survey was $120 million

($2012-13; NPV at 7.1% pa over a 10-year horizon)

– Includes $8 million in AEMO costs and $112 million for only 9 retailers based on responses to an ERAA member survey – Cost estimates developed from AEMO Detailed Design documents – referred to by some as a ‘concept document’ – Cost estimation process used a conservative methodology – calculated cost of each component at the lower $ value of the range selected by the respondent – While responses will entail a significant margin of error, overall result may well be conservative

• One area of concern:

– Some retail respondents estimated that IT build/ implementation costs and on-going program administration costs would both be ‘very large’ – At face value, this does not seem logical

33

It is important to note the implications of the 10-year timeframe

• The benefits presented above are calculated on 19 years
• The IT systems for administering the DRM would need to be refreshed over that longer

timeframe, and those costs will need to be included in the final benefit/cost calculation

Available cost estimates – independent expert opinion

• OGW approached 3 parties involved in IT system development/alteration for the

electricity industry to see if we could obtain an independent estimate of the costs likely to be incurred by retailers in implementing and administering the DRM

• Their views:

– At this point in the design and specification of the DRM, IT build estimates would be expected to be in the order of +/– 50% at best – Better estimates require a draft Rule to be made and an industry ‘build pack’ to be developed – Even then, it would still require a considerable time and effort to develop a cost estimate that was within +/-20% – And costs could vary considerably depending on

• the system landscape of the individual retailer, and
• the fact that most/all retailers have other systems in addition to their core system that need to act in concert

– Market-facing systems in particular (MSATS, etc.) would be a major driver of development and testing costs

• Could not provide an alternative cost estimate
• Based on the level of detail currently available, the estimates provided by the retailers

and distributors that responded to the ERAA survey appear reasonable

34

Cost estimates – major drivers

• The scope of the changes required to implement the AEMO detailed design

document is the major driver for cost

• Based on scope, the understanding of retailers is that a number of the existing

B2B and B2M processes will need to be changed, and new ones created

• Changes of this nature will require the definition and implementation of a new

schema

– Will also require consequential changes across much of a typical retailer’s system landscape (which has become quite complex in many instances)

• For example: changes would be required to gateways (B2B, B2M), NMI discovery processes,

core metering, billing and customer/site management systems, settlement and general ledger, reporting and compliance systems

– Significant testing and formal project governance would also be required given the number of systems involved – Changes to scope would result in a change to the cost estimates

35

Considerations moving forward – coordination of system changes

• A number of the current Rule changes being considered have overlapping system

functionality requirements

– DRM, MTR, Embedded Networks and (to a lesser degree) Metrology Contestability

• This offers the potential for shared costs which is not being recognised in the analysis of

each Rule change on its own

• However, making changes to systems to meet the requirements of all requirements could

potentially result in a large, complex and risky project

• Sequencing of changes may result in savings and reduced risk (needs further discussion

and analysis by industry)

• However, it should also be noted that extending the scope of the DRM to include small

retail customers is likely to increase the cost of implementation by “an order of magnitude” (though MTR is envisaged to apply to residential sector)

36

Considerations moving forward – alternative approaches

• The B2B and B2M arrangements currently in place are relatively costly to change to

incorporate new functionality

• Using manual processes, even for a small number of consumers, is difficult given the

degree of integration in place between systems

– Data about the DRM would be need to be manually entered into a number of systems

• Where existing B2B / B2M arrangements result in a barrier to implementing initiatives

due to cost or risk, the potential for using a mechanism other than the existing B2B / B2M arrangements should be investigated

• In considering future market systems architectures, flexibility to accommodate change

should be a key consideration

37

DISCUSSION

38

Distributional impacts – summary of approach

• The primary inputs to the calculation of distributional impacts were:

– Reductions in wholesale price – Impacts on network capital costs – Cost of the program

• Other key inputs assumptions to the assessment of distributional impacts were as follows:

– All customers were assumed to benefit from the wholesale price reductions available at the applicable regional node – Variations were undertaken in the allocation of benefits to different customer classes, but the distribution business was assumed to retain 30% of the benefit in all cases (consistent with the AER’s capital expenditure incentive guideline) – Variations were also undertaken in the allocation of DRM costs to different customer classes – The impact of the reduction in throughput due to the exercise of demand response under the DRM

• n network tariffs was not calculated; nor was the impact of that reduced consumption included in the

analysis of DR providers’ benefits

• This was not felt to be a material omission given the relatively small amount of consumption reduction involved.

– Consistent with the Standard Practice Manual for the Economic Analysis of Demand Side Management Programs and Projects, DR providers’ costs were not included in this analysis

• A calculation of distributional impacts that includes an estimate of DR providers’ costs will be provided in the full

version of the final report

39

Distributional impacts – overview of results

• Three different variations of the distributional impacts analysis in the AEMO forecast plus

CRNP were undertaken.

• The three variations differed in how the costs of the DRM (assumed to be $120 million in

NPV terms) and its benefits were allocated between customer classes

– Recall that the $120 million is probably a low estimate – it does not include any software refresh costs over the 20-year period, and is based on the costs estimated by only nine retailers

• All three runs showed positive results for:

– Customers eligible to participate in the DRM

• Primary benefit is the wholesale market payments at spot price when they provide DR
• Benefits are in the thousands of dollars (NPV) over the period

– Commercial customers and residential customers in all DNSP service areas in the NEM

• Benefits are the sharing of the network cost reductions due to lower peak demand, and the impact of the

reduction in the wholesale electricity price

• Benefits are generally only in the tens of dollars
• Indicates that this scenario of the DRM is:

– Unlikely to result in increased costs for any customer class, and – Likely to help those who participate save money on their bills.

40

Distributional impacts – AEMO plus CRNP scenario

41

NPV of Benefits (costs) Per Residential Customer Citipower Ausgrid SP AusNet Endeavour Energex Ergon Essential Jemena Powercor SAPN United Reduced wholesale prices $7.10 $17.95 $7.74 $20.00 $12.39 $15.25 $19.37 $6.67 $7.82 $8.58 $6.99 Allocation of costs

• $8.65
• $10.81
• $9.43
• $12.05
• $11.23
• $13.83
• $11.67
• $8.12
• $9.52
• $9.66
• $8.51

Revenue generated by DR providers $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 Network Benefits $21.23 $4.29 $5.57 $4.69 $5.08 $9.01 $9.23 $12.35 $9.26 $8.21 $7.98 TOTAL $19.68 $11.42 $3.89 $12.63 $6.23 $10.43 $16.93 $10.89 $7.56 $7.13 $6.46 NPV of Benefits (costs) Per Commercial Customer Citipower Ausgrid SP AusNet Endeavour Energex Ergon Essential Jemena Powercor SAPN United Reduced wholesale prices $56.53 $57.50 $36.85 $85.40 $39.88 $15.93 $66.15 $33.30 $31.99 $29.49 $35.92 Allocation of costs

• $68.85
• $34.64
• $44.88
• $51.45
• $36.17
• $14.45
• $39.85
• $40.55
• $38.96
• $33.17
• $43.74

Revenue generated by DR providers $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 Network Benefits $21.23 $4.29 $5.57 $4.69 $5.08 $9.01 $9.23 $12.35 $9.26 $8.21 $7.98 TOTAL $8.91 $27.14

• $2.46

$38.63 $8.79 $10.49 $35.52 $5.09 $2.29 $4.52 $0.16 NPV of Benefits (costs) Per DR Customer Citipower Ausgrid SP AusNet Endeavour Energex Ergon Essential Jemena Powercor SAPN United Reduced wholesale prices $2,401.36 $1,157.31 $1,814.13 $5,668.11 $2,177.97 $1,951.13 $4,290.92 $1,786.71 $2,911.40 $1,994.81 $1,226.74 Allocation of costs $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 Revenue generated by DR providers $638.94 $4.66 $638.94 $4.66 $945.44 $945.44 $4.66 $638.94 $638.94 $708.80 $638.94 Network Benefits $4,016.96 $232.22 $1,623.16 $730.01 $612.00 $850.45 $1,675.77 $2,049.15 $2,543.30 $1,648.65 $1,261.32 TOTAL $7,057.26 $1,394.18 $4,076.23 $6,402.78 $3,735.41 $3,747.02 $5,971.35 $4,474.80 $6,093.64 $4,352.27 $3,127.01

Assumes

• all DRM costs allocated across the residential & commercial customer classes in proportion to their consumption

volume

• all customers equally share in 70% of the network benefits (the other 30% are retained by the network business)

Distributional impacts – a note on customer class definitions

• Definition of the customer classes used was constrained by the nature of the information

available from distribution companies regarding their sales

– Customers on demand tariffs have been taken as the customers eligible for the DRM; this will:

• Undercount that population as it is unlikely to include many customers between 100 and 160 Mwhpa
• Under-estimate the income benefits to those who participate in the DRM because it spreads the DR spot

price income across all such customers

– Non-residential customers that are not on demand tariffs have been defined as commercial; this is likely to undercount those customers – Residential customers have been classified as residential

• Note that:

– The pool revenue income earned by the DR providers under the DRM represents a gross wealth transfer from generators to DR providers – The net wealth transfer, assuming generators are not subject to take-or-pay fuel contracts, is equivalent to the gross wealth transfer less the cost not spent on fuel for the amount of generation displaced by DR

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Oakley Greenwood Pty Ltd GPO Box 4345 Melbourne 3001 +613 9016 2550 lhoch@ h@oak akleygreenwoo

• od.

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