Response 2010 Country report: Australia -Henney, A., EEE Ltd. by VaasaETT Ltd.

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Country Reports Australia By Alex Henney, EEE Ltd.

1 ÂŠ2010 ltd

VaasaETT

and

EEE

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CONTENTS

Page No. 3

KEY POINTS

INTRODUCTION 2.1 2.2 2.3

12 13 16 17

The National Electricity Market The retail markets Retailers

METERING

SMART METERING POLICIES IN VICTORIA, NEW SOUTH WALES, AND SOUTH AUSTRALIA

THE MINISTERIAL COUNCIL ON ENERGY’S STUDY ON SMART METERING

THE CONSULTANT’S STUDIES AND CONCLUSIONS

6.1 6.2 6.3 6.4 6.5 6.6 6.7 7

Recommended national minimum functionality The costs of smart metering are estimated to be between $2.7bn and $4.3bn (in NPV terms) The benefits of smart metering are estimated to be between $4.5bn and $6.7bn (in NPV terms) Smart metering, retailers and customers Smart metering is estimated to deliver net benefits of between $179m and $3.9bn nationally Non-smart meter direct load control may be a viable alternative in some jurisdictions Objectives Applying to the Rollout

31 32 33 35 37 42 43

IMPLEMENTING THE SMART METERING POLICY

Annex 1 Annex 2 Annex 3

49 52 54

Annex 4 Annex 5 Annex 6 Annex 7 Annex 8 Annex 9 Annex 10 Annex 11 Annex 12

Cross subsidies resulting from the net system load profile Victoria Advanced Metering Infrastructure Technology Trials Report The effect of costing wholesale prices on interval consumption rather than profiles and customer response to time-of-use and critical peak pricing from NSW studies Meter functionalities considered in NERA’s Phase 1 Overview Report on smart metering for the Ministerial Council on Energy Functionality – enabling direct load control via the smart meter infrastructure and facilitation of a connection with an IHD Standards and interoperability Costs, benefits, and net benefits Network benefits and operational costs Key points from the KPMG report on “Retailer Impacts” Customer impacts of smart metering Results from focus group studies Split benefits problem

63 65 71 73 85 89 98 112 114

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KEY POINTS

Australia has an area of 7.7m sq. kms (which is about 80% of the USA land mass excluding Alaska) while its population is only 21m; there are about 10m meter points. The government is federal in character, with a Commonwealth Government, 6 states and 2 territories; they are called jurisdictions. The focus of this study is Victoria, New South Wales (NSW), and South Australia, who were the founder members of the National Electricity Market; who were the first to open to full retail competition; and where 70% of the population live.

Traditionally small customers have had simple single register accumulating meters in Victoria, while in NSW and South Australia some customers have either two register meters or two meters; the second register/meter is used to record consumption for ripple controlled load of off-peak water heating. The meters are read quarterly. There are two types of profiles used for customers who switch 1) “net system load profile” which is calculated by aggregating the wholesale boundary energy and subtracting all the non-wholesale boundary interval energy, and 2) “controlled load profile” which is a modified version of the net system load profile split into two time periods. The same profiles are used for residential and small non-residential customers. The consumption of customers who have not switched is calculated by differencing.

A study in Victoria found that the residential customers whose consumption is 50% greater than the average user are paying a margin of Au$75 p.a., which is 50% more than they ‘should’; while customers whose consumption is 100% greater than the average user are paying a margin of Au$100 p.a., double what they ‘should’. Conversely, smaller than average users are typically paying too little. Furthermore the cross subsidies between those domestic customers that do not have air conditioning and those that do could be as much as $200 per customer per annum. Studies for EnergyAustralia and for Integral in NSW found that there are significant differences between calculating the cost of supply based on load profiles and interval metered half-hourly costs. State policies towards smart metering differ:• In July 2004 the Essential Services Commission of Victoria took a decision on a “Mandatory Rollout of Interval Meters for Electricity Customers”, which referred to manually read meters. But it reviewed the decision and, following a study by consultants in August 2006 which estimated there was a positive net present value (NPV) from a rollout, Victorian legislation was passed to give the relevant Minister the power to make Orders in connection with the state-wide rollout of 2.4m smart meters. These powers have been exercised to commence the rollout starting at mid 2009 to be 3

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completed by 2013. The DNOs have sought tenders for supply; four of the five will be using mesh radio for 96+% of the meters and GPRS for the balance • New South Wales: EnergyAustralia is in the process of rolling out manually read interval meters (which can be “smarted”) to all its customers starting with all new installations and existing installations that have a meter upgrade • South Australia has made no move to install smart meters. Rather it is concerned to shave the peak demand of the needle peak; South Australia and Victoria have among the world’s peakiest electricity load shapes – the last 10% of maximum demand occurs for less than 20 hours per year. This implies that those creating the peak are imposing significant costs on those with flatter load profiles. The regulator has funded the distribution network operator (DNO) to undertake a significant direct load control programme In February 2006, the Council of Australian Governments agreed to improve price signals for energy customers and investors, and committed to:“… the progressive national rollout of ‘smart’ electricity meters from 2007 to allow the introduction of time of day pricing and to allow users to better manage their demand for peak power but only where benefits outweigh costs for residential users”. In May 2007 the Ministerial Council on Energy (MCE) set up a working group, which commissioned NERA as lead consultant supplemented by CRA, KPMG, and Energy Market Consulting Associates to undertake a cost-benefit analysis of the case for introducing smart meters and direct load control. The analysis is probably the most thorough undertaken in any country; it cost Au$2½m, about US$1.6m, €1.2m, £1.1m. The consultants analysed the operational implications of four alternative scenarios:• Scenario 1: Distributor-led rollout – where each distribution network service provider is given the responsibility for owning and installing meters and associated metering data services within its area of operations as a monopoly service provider • Scenario 2: Retailer-led rollout – where retailers have responsibility for procuring the installation of meters and data management services within a competitive market for these services. • Scenario 3: Non-smart meter direct load control (DLC) device rollout – DNOs have responsibility for retrofitting direct load control devices on high energy using appliances such as airconditioners and pool pumps • Scenario 4: Centralised communications as part of a retailer-led rollout – where the entire Australian smart meter communications system is provided by either a new centralized agency or an existing market operator Detailed analysis concluded that the meters should have the following minimum functionalities. 4

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A notable effort was put into the cost-benefit analysis of providing an interface with a Home Area Network (HAN) and an in-home display. Preliminary findings from trials in NSW are that customers with an in-home display increased their response to a CPP tariff by 5% compared with customers who did not have such a display. This finding is consistent with studies in Canada and the UK. The conclusion was that it would have positive net benefits, even where it involves only a DLC capability underpinned by smart thermostats. The study also considered the standardization of protocols, but concluded more work was required.

The total costs of a national smart metering rollout are estimated as ranging from $2.7bn to $4.3bn in NPV terms over a 20 year period for a distributor-led rollout. The costs rise to over $5.9bn for a retailer-led rollout (upper bound). These estimates were developed through an extensive cost build up exercise, which included estimating the costs of:â&#x20AC;˘ Smart meters and their installation in each jurisdiction â&#x20AC;˘ Communications infrastructure â&#x20AC;˘ Meter data and communications management systems

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• Market operator systems to mange changes to market settlement information and new meteringrelated business to business transactions • Retailer systems to support the retailer activities expected to be undertaken as a result of the rollout of smart meters in each scenario • Distributor systems to support the distributor activities expected to be undertaken as a result of the rollout of smart meters in each scenario The benefits associated with a national rollout of smart metering were estimated to be between $4.5bn and $6.7bn in net present value (NPV) terms over the twenty year period of analysis under the distributorled rollout scenario. The value of the benefits falls under the alternative rollout scenarios to $4.1bn in the lower bound for both the retailer-led rollout and the centralized communications scenario. The majority of the benefit results from avoided meter costs associated with not having to replace the existing meter stock, and from business efficiency benefits for distributors (totaling approximately 39% to 44% and 41% to 55% of total benefits respectively):• The potential benefit from avoiding the need to replace the existing meter stock ranges from $1.7bn to $2.6bn • Distributor business efficiency benefits resulting from smart metering total between $2.1bn and $2.9bn in NPV terms over the twenty year period of the analysis. These benefits include:* * * * *

the avoided cost of routine manual meter reading the avoided cost of special meter reads (ie, when customers move into or out of premises) the avoided costs of manual disconnections and reconnections reductions in calls to faults and emergency lines avoided costs of customer complaints about voltage quality of supply

• Retailer benefits resulting from smart metering total between $98m and $196m in NPV terms over the twenty year period (or 4-6% of the total estimate of business efficiencies). These benefits include:*

* * *

a reduction in call centre costs as a result of fewer high bill enquiries. But call centre costs initially increase as customers query new tariff products that are introduced following a smart metering rollout a reduction in bad-debt and working capital requirements a reduction in hedging costs, due to interval data leading to improved forecasting; other cost reductions, including costs for data validation and settlement and management time

The final benefit category of benefits results from changes in the time of use and level of electricity demand by consumers which leads to:• The deferral of peak network augmentation • Reductions in retailers’ hedging costs as a result of reductions in peak wholesale prices 6

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• The deferral of peak generating capacity • Reductions in the level of unserved energy, generation operating costs and carbon emissions resulting from changes in the pattern of electricity market dispatch Nationally the demand response benefits range between $250m and $738m in NPV terms over the twenty year period of the analysis (excluding the demand response benefits that may arise from including an interface to a HAN). This represents between 6-12% of total benefits resulting from the introduction of smart metering. Including an interface to a HAN may increase the total demand response benefits by between a further $169m to $925m. Over the twenty year period of the cost-benefit analysis the total reduction in greenhouse cases is estimated to be between 597,000 tonnes and 12.3 million tonnes. National present value of benefits and costs (£m) for DNO rollout and DLC (Au$m)1

The national aggregated results mask differences in the underlying net benefits by jurisdiction, because both the costs and benefits vary according to the circumstances of each jurisdiction:-

As at February 2009 1Au$ = 0.66USD = 0.78€ = 0.88£.

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• A distributor-led rollout of smart metering in Queensland, New South Wales, Victoria and Western Australia would deliver positive net benefits on the basis of the estimated avoided meter costs and business efficiencies alone. The inclusion of an interface with HAN would likely further increase the net benefits, particularly if direct load control was targeted to maximize both participation and the resultant network deferral benefit • For South Australia a rollout of smart metering has a net positive benefit provided costs are at the low end of the range estimated because customer business efficiency benefits are lower in South Australia than the national average • On a per meter basis, meter costs are higher in rural and remote areas compared to urban areas. The national weighted average costs for meters with integrated communications is between $136 and $190 for meters compatible with the mesh radio network assumed for urban areas, but rises to $168 to $184 for meters compatible with power line carrier, which is assumed for customers in rural and remote areas under the DNO led rollout In determining the prospects for success in introducing more cost reflective time of use or critical peak pricing tariffs the consultants looked closely at the behaviour of retailers and of customers. From the retailers’ perspective:• The typical domestic electricity bill is about $1,000 per annum, on which the retailer makes about $50 per customer (before interest and tax), which leaves around $70 per customer for a retailer’s operating costs. One retailer stated that “If a customer calls you more than a couple of times a year, you have probably just lost your margin on that customer”. Another retailer explained that for this reason “retailers really do not want their customers to care” about the product • The thin retailer margins constrains the degree to which they are in a position to offer differential tariffs. Energy retailing is therefore a service which, for the mass market, involves a low degree of customization and customer contact. Retailers tend to operate mass marketing campaigns and make their competitive offers very similar to existing offers to overcome customer inertia (e.g. similar tariffs, but with a discount) • Most retailers were not keen on the introduction of smart meters linked with introducing new costreflective tariffs because “the key question a retailer will ask itself is: are more cost reflective tariffs going to increase the Au$50 margin I can make on the typical customer?”. Also the large retailers were not keen on spending Au$50-100m on new billing and customer service systems • “The typical view is that it is likely to be very difficult to sell retail products by focusing on tariffs as the customer does not understand them and is not interested in investing the time necessary to understand them. This is simply because their bills are not significant enough for them to care. One retailer stated “our salespeople never talk about tariffs when trying to win a customer – all they do is offer the same basic offer, but with some alternative benefit”. The retailer also stated that if you talk about tariffs “you are dead” in terms of making sales”

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From the customer’s perspective:• Residential customers do not spend much on electricity. It is a “low involvement” product, i.e. customers are not emotionally involved in it, and most require a saving of 10% to become interested in switching. But potential savings from switching are modest • A report by the Essential Services Commission of South Australia found there was “no evidence that small customers would accept more complicated structures with the introduction of smart metering. They have also found low take up rates in certain jurisdictions where smart meters are voluntary” • A consistent finding across focus groups was that participants were much more willing to consider a DLC tariff option compared to other alternatives. Participants viewed DLC options as providing them with a way to ‘do the right thing’ and reduce electricity consumption without needing to think about it and in that respect it not impacting their lifestyle. The fact that they would also reduce their electricity costs and receive a payment for adopting DLC was viewed as a bonus. In contrast to their willingness to consider DLC, the vast majority of participants did not see much benefit to them in adopting critical peak pricing (i.e. a tariff with a high peak price) (CPP). The government of South Australia is supporting DLC. A trial was undertaken in 2007/08 under the name “Beat-the-Peak” which uses a small device controlled remotely to switch off an air conditioner’s compressor for some minutes for the few hours of peak demand on days of high temperatures. There is a reduction in load of 10-20% when DLC is activated • There is a marked difference between the individual sense of responsibility to conserve energy and day to day behaviour related to saving electricity – at a day to day level the primary motivation for most customers to save electricity is to save money on the bill rather than actually saving or conserving energy • A study in NSW found that the cost of service for customers with interval meter was lower for approximately 50% of customers and higher for the other 50%; for 30% of customers it would be more than 10% higher than the current profiled-based cost and for 16% it would be more than 20% higher. Conversely, for 25% of customers the underlying cost of service would have been more than 10% less than the current profiled-based cost. The cost of service is naturally greater for those customers with a greater proportion of their consumption in higher-cost periods:*

it does not appear that seasonal ToU tariffs lead to a reduction in per-unit retail costs to customers, suggesting that there was little if any price-responsive load shifting

the usage of the CPP group is around 40% less at peak times, and results in savings of between $75 and $86 per customer. CPP tariff customers also used less energy than the control group. Consequently their annual bills were on average $92 (for CPP) and $139 less than for the control group

• Losing the cross subsidies that are implicit in profiles and increasing costs – hence prices - would limit the interest of some customers in moving to more cost reflective tariffs

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KPMG concluded:“[it] would appear about half the customer base has been willing to switch to non-host retailers for savings of 5-10% of the value of their bill. Conversely, at least at this stage of the market’s development, up to half of the market appears to be unwilling to switch for such savings… Given this, it may well be difficult to interest most of these customers (i.e. customers who are disinclined to switch) to accept more cost-reflective tariffs that either:• Would save them a similar amount of money if they are currently flat load customers and stay the way, or • Might save them similar amounts of money, if they accept such a tariff and change their behaviour The customer focus groups canvassed participants’ views as to their willingness to adopt alternative tariff structures (including DLC). A consistent finding across all of the focus groups was that participants were much more willing to consider a DLC tariff option compared to other alternatives. In contrast to their willingness to consider DLC, the vast majority of participants did not see much benefit to them in adopting CPP. Available evidence suggests that it would be optimistic to assume that, just because smart meters will enable retailers to introduce more cost reflective tariffs reflecting each customer’s load profile, this will happen broadly across small customers in the foreseeable future. The technology lowers the barriers to retailers introducing such tariffs, but the benefits for many customers might be too small to make it worthwhile for retailers to market those products aggressively. They may also meet customer resistance to the tariff changes that might logically be made. The more likely outcome is that retailers offer more cost reflective tariffs to a significant minority of the market, perhaps up to half of it, and also offer Direct Load Control tariffs to a subset of these customers. It seems likely that the tariffs retailers offer will be different to what may be ‘ideal’ from the perspective of sending the most cost reflective prices signals possible to customers. This would be consistent with the need to produce offers to which customers are most receptive (i.e. are saleable in most competitive retail markets)”. NERA reiterated a view held by the Essential Services Commission of Victoria that “each of the smart meter scenarios assume that the rollout of smart meters is mandatory across all small customers. The reason for considering a mandatory rollout is due to the market failure arising from the benefits of smart meters accruing to both distributors and retailers [and customers], such that neither distributors nor retailers would invest optimally in a smart meter rollout on its own”. This view is shown clearly by the analysis of the costs and benefits by stakeholder for the DNO rollout as follows:-

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(Au$m) Minimum net benefit networks retailer customers market total nationwide

-226 -64 50 -59 -299

Maximum net benefit networks retailer customers market total nationwide

2,614 279 324 55 3,272

The split of benefits is fundamental to understanding the economics – and economic perspectives of smart metering and is the basis of the case for a mandated rollout, which is most sensibly achieved by a DNO.

The MCE recommended a DNO led rollout of smart meters in jurisdictions where benefits outweigh the costs, otherwise DLC should be implemented. Subsequently the MCE published proposals for amending the National Electricity Law “to provide that a Minister of a participating jurisdiction require a DNO to rollout smart meters, and conduct pilots and trials of smart meters”.

The National Stakeholder Steering Committee has been established by the MCE to define a national framework for the rollout of smart metering infrastructure including technical, and operational requirements and changes to regulatory rules and procedures in the National Electricity Market, Western Australia and Northern Territory. The Committee has prepared a National Smart Metering Programme work plan.

As noted above, Victoria has mandated a rollout of smart meters and it is just about to begin – mesh radio is the favoured communications technologies with GPRS as a fill in. The government of South Australia remains skeptical of the benefits of smart metering in addressing what it regards as its key problem, the needle peak, and remains committed to developing a range of peak reducing initiatives including direct load control for residential customers - “for customers a smart meter sitting on a wall does nothing”. The NSW government considers that smart metering is probably the way to go, but notes that the cost-benefit analyses have a wide range of outcomes, and problems remain with communications, in particular mesh technology. In 2012 officials will review the situation and the Minister will decide. 11

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INTRODUCTION

Australia has an area of 7.7m sq. kms (which is about 80% of the USA land mass excluding Alaska) while its population is only 21m. The majority live in the south eastern coastal region stretching from Adelaide in South Australia, through Melbourne in Victoria, Sydney in New South Wales, Brisbane in Queensland and up to Cairns.

The government is federal in character, with a Commonwealth

Government, and 6 states:• • • • • •

Victoria New South Wales Queensland South Australia Tasmania Western Australia

In addition there are 2 territories, Northern Territory and the Australian Capital Territory, which is the City of Canberra and environs. The various entities are termed “jurisdictions”.

The focus of this study is Victoria, New South Wales (NSW), and South Australia, who were the founder members of the National Electricity Market and were the first to open to full retail competition, and where 70% of the population live. The key characteristics of the states are:-

Victoria NSW South Australia

population (m)

no. of meter points (m)

4.7 6.7 1.5

2.4 3.3 0.8

electricity consumption (TWh) total residential 35.5 12.1 68.9 22.1 12.1 4.2

average res. Cons. (kWh p.a.) 5700 7500 6400

The government of Victoria led the way to competition and privatization. In 1993 it restructured the state and municipally owned electric industry into five generating companies, a separate transmission company, five DNOs, and set up a power pool for physical spot trading that commenced operation in 1994. All of the companies were privatized by 1999. In May 1997 the Victorian market was combined with New South Wales, and subsequently they became part of the National Electricity Market in December 1998, see below. The government of Victoria set a timetable for introducing competitive choice to customers in a phased manner culminating in full retail competition from January 2002. The state regulator is now the Essential Services Commission of Victoria.

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The government of New South Wales (NSW) restructured the state and municipally owned electricity industry in 1996, creating three generating companies, a separate transmission company, and six – subsequently rationalized to three – distributors2. It set up a market in 1997, which was a transition first to operating a joint market with Victoria, then joining the National Electricity Market in December 1998. The government set a timetable for introducing competitive choice to customers in a phased manner culminating in full retail competition from January 2002. The government has not privatized any of the companies. The state regulator is the Independent Pricing and Regulatory Tribunal (IPART).

The government of South Australia restructured the government owned electricity supply industry into three generation companies, a transmission company, one distribution network operator (DNO) and a retailer; all of the companies have been privatized.

South Australia joined the National Electricity

Market at its commencement in December 1998. Full retail competition for all customers was introduced at the beginning of 2003. The state regulator is the Essential Services Commission of South Australia (ESCOSA). 2.1

The National Electricity Market

The National Electricity Market Management Company (NEMMCO) was established to manage the operation of the power system through the now five participating states – Victoria, NSW, South Australia, Queensland, Tasmania – and the Australian Capital Territory, as a single control area, and to run a physical spot market, see exhibit 1. NEMMCO dispatches the plant in 5 minute intervals using the National Electricity Market dispatch engine, and operates a “real time” market which is a gross pool (i.e. all electricity flows through it) based on a last price auction. The National Electricity Market has regional pricing for both customers and generators based on the marginal price of supplying a “regional reference node”. The system is basically thermal, with large lignite plants in Victoria, hard coal in NSW and Queensland, and some gas plants in Victoria and South Australia, which also has lignite coal. There is a large hydro scheme in the Snowy Mountains in NSW, and hydro in Tasmania linked to Victoria via a 500MW interconnector. The market is an energy-only market from which the generators recover their capacity cost by spiking the price, which can increase to a cap of Au$10,000/MWh – the spot price can be very volatile in the short term.

The term distributor is used for the traditional role of combined network operator and franchise supplier. The term distribution network operator (DNO) is used for an undertaking that is purely a network company. In Australia they are termed a distribution network service provider (DNSP) but for consistency with the remainder of the Respond study they will be termed a DNO.

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Exhibit 1

The five states in the National Electricity Market

Source: NEMMCO Annual Report.

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NEMMCO also operates the retail settlement including the profiling – there are two types of profiles 1) net system load profile, and 2) controlled load profile:• The basic net system load profile (or residual load profile) is used in the Australian Capital Territory, Victoria, and by one of the two distribution networks in Queensland. The profile is calculated by aggregating the wholesale boundary energy and subtracting all the non-wholesale boundary interval energy • For NSW, South Australia, and the other distribution network in Queensland the basic net system load profile is modified by subtracting an additional profile that represents the controlled load energy (e.g. the off-peak demand of water heating) The same profiles are used for residential and small non-residential customers. The consumption of customers who have not switched is calculated by simple differencing. A study by Trowbridge Deloitte found that the residential customers in Victoria whose consumption is 50% greater than the average user are paying a margin of Au$75 p.a. (which is 50% more than they ‘should’), while customers whose consumption is 100% greater than the average user are paying a margin of Au$100 p.a. (i.e. double what they ‘should’). Conversely, smaller than average users are typically paying too little, see Annex 1 for more detail. The Victorian Essential Services Commission has estimated that the cross subsidies between those domestic customers that do not have air conditioning and those that do, could be as much as $200 per customer per annum. There is a particular issue with subsidies to households with airconditioning:• The Victorian Essential Services Commission has estimated that the cross subsidies between those domestic customers that do not have air conditioning and those that do, could be as much as $200 per customer per annum • Work by EnergyAustralia for its network area suggests that the average non-air conditioning customer is paying $70 to much to the average air conditioning customer who is paying $86 too little3. Other work by EnergyAustralia suggests that for some load shapes it:“would expect energy costs (at least for retailers, if not customers) could double from their current level. This reflects the fact that, historically, in NSW, up to 50% of the energy costs is driven by price spikes. This differing exposure to price spikes is the key reason for variations in energy purchase costs between the three NSLPs”4.

EnergyAustralia, Increasing Block Network Tariff: Follow-up presentation to IPART’s Pricing Issues Consultation Group, 18 June 2003. This would appear to relate to energy costs only. 4 EnergyAustralia, Cost-benefit Analysis of Smart Metering and Direct Load Control: Phase One Report 7 November 2007. This does not necessarily imply that costs would double. The submission also notes that the differences in energy costs for the three NSW NSLP’s is substantial – typically more than 20%.

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• Charles River Associates in work for Integral Energy on the impact of air conditioning on its network concludes that the cross subsidy might be in the range of $80-110m p.a., which equates to between $110-151 per customer p.a.5 NEMMCO also maintains the retailer register and operates the customer switching system, the Metering and Settlement Administration Transfer Solution.

Following a report to the Council of Australian Governments the governance of the electricity market was reformed in 2004/5 as follows:•

The Ministerial Council on Energy (MCE) was created comprising the Energy Ministers from the Commonwealth Government and the state and territory governments

•

The Australian Energy Market Commission has responsibility for rule-making and market development. The Commission is accountable to, and subject to policy direction from, the MCE

•

The Australian Energy Regulator (AER) is responsible for market regulation. As well as regulating the wholesale market and transmission it is responsible for the economic regulation of distribution and retailing (other than retail pricing, which will remain with the competence of a state government until such time as it wishes to transfer responsibility to the AER)

2.2

The retail markets

The retail markets for small customers commenced with a regulated default tariff that in Victoria and South Australia was set to provide significant “headroom” for competing retailers to win customers from the incumbent retailer. In consequence the switching rate in these states was very high – by the end of 2007 about 40% had switched. Now the default tariffs have been ended, and retailers are free to offer any form of pricing structure they wish. In NSW, where the electric industry is largely state owned, the government did not allow the default tariffs to be set at relatively high level and so the switching rate has been much lower (about 20% by the end of 2007), and the default tariff remains in place.

Charles River Associates, Impact on Air Conditioning on Integral Energy’s Network, May 2003.

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2.3

Retailers

The main retailers in the three markets are as follows (I = the retailer created from the incumbent franchise, and C = a competitive retailer):-

Retailer

Origin Energy AGL Energy EnergyAustralia Integral Energy Country Energy TRUenergy Simply Energy ActewAGL Retail Red Energy Victoria Electricity Jackgreen (International) Powerdirect Australian Power & Gas

Ownership

Origin Energy AGL Energy NSW Government NSW Government NSW Government CLP Group (China Light & Power) International Power ACT Government & AGL Energy Snowy Hydro Infratil Jackgreen AGL Energy Australian Power & Gas

VIC

NSW

I I

C C I I I C

C I

C I C

C C C

C C C C C C

C C C C C

No. of customers (m) 2.09 1.93 1.25 0.82 0.78 0.65 0.35 0.15 0.07 0.07 0.03

Market share (%) 22 20 13 9 8 7 4 2 1 1 0

AGL and Origin Energy are large private Australian Energy companies; the NSW government owns EnergyAustralia, Integral Energy and Country Energy; TRUenergy is owned by the CLP Group, which is a large Hong Kong company; Simply Energy is owned by International Power, a large British power plant developer; Red Energy is owned by Snowy Hydro, which is owned by the Commonwealth Government and the governments of Victoria and NSW; Victoria Electricity is owned by the quoted New Zealand infrastructure company Infratil; Jackgreen was backed by Babcock & Brown, which has gone into administration; and Australian Power and Gas is backed by Cobra, a direct sales company. The two major private sector retailers and TRUenergy also have significant shares of the retail gas market, and are therefore more dominant in the retail energy market than this data suggests. A number of the smaller players have grown significantly in recent times.

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METERING

The DNOs maintain a register of all national meter identifiers (NMIs) and NEMMCO maintains a central register of all NMIs within its market. There are two types of meter for small customers6:• Type 5 is a manually read interval meter • Type 6 is a manually read accumulation meter The DNOs have a monopoly on the provision of types 5 and 6 meters. Traditionally small customers have had simple single register accumulating meters in Victoria and part of Queensland, while in NSW, South Australia, and parts of Queensland some customers have either two register meters or two meters. The second register/meter is used to record consumption for ripple controlled load of off-peak water heating. The types 5 and 6 meters are read quarterly.

Meters are owned and maintained by a “meter provider” and the data is read and delivered to NEMMCO for settlement by a “meter data provider” for manually read meters and by a “meter data agent” for meters with communications. There is a standard for data transfer for remotely read meters7. Part of the accreditation process of meter data agents is to confirm that they can handle data using the required format.

‘Small’ customers are those with a total annual consumption below 160 MWh for all jurisdictions with the exception of Queensland (100 MWh/year), Tasmania (150 MWh/year) and the Northern Territory (750 MWh/year). 7 Meter Data File Format Specification NEM12 & NEM13, NEMMCO, Effective Date 20th July 2005, http://www.nemmco.com/met_sett_sra/630-0032.pdf.

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SMART METERING POLICIES IN VICTORIA, AUSTRALIA

NEW SOUTH WALES, AND SOUTH

In July 2004 the Essential Services Commission of Victoria took a decision on a “Mandatory Rollout of Interval Meters for Electricity Customers”8, which referred to manually read meters. According to the Commission:“Interval meters enable retailers and customers to measure real time electricity consumption and to send and respond to the cost-related price signals…The responses of electricity demand to costrelated prices should contribute to:• • • •

smoothing the peaks in the electricity load profile, thus reducing the volatility of energy prices improving the efficiency of the operation of the electricity wholesale market improving the balance between supply and demand in the wholesale market lowering the cost of energy by delaying investments in new infrastructure to satisfy the future growth of, and peaks in, the demand for electricity

These potential improvements in wholesale market efficiency are particularly relevant for Australia’s ‘energy only’ wholesale market, which has weather driven needle peaks in demand and relatively low forecast reserve plant margins. These features are especially relevant in the Victorian and South Australian regions of the market. In addition to the demand management benefits, interval meters should:• • • •

Increase the accuracy of settlement and ensure equity among customers Provide a digital platform for the innovation of customer services Reduce disputes associated with, and the need for, estimated data Improve customer transfer efficiency because a manual meter reading would not be needed”

The Commission assessed that the benefits exceeded the costs, and justified a mandated rollout because:• “Market forces alone would fail to deliver a timely interval meter rollout on a scale sufficient to provide economies in meter manufacture, installation and reading • Regulatory intervention would be required to achieve the economic benefits that would result from a more timely and larger scale rollout” And because of split benefits:• “Individual market participants could not capture the full benefits that would accrue to the market from their decisions to install interval meters”

http://www.esc.vic.gov.au/NR/rdonlyres/8FCF80D2-F7EB-4071-9C7FA0721A95B004/0/IMRO_FinalDecisionFinal9July04.pdf.

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The government decided to look at the issue again, and in 2005 commissioned from CRA and Impaq Consulting an “Advanced Interval Meter Communications Study”9 to investigate whether it would be cost-effective to add communications, and whether a faster rollout would be beneficial. The study evaluated the costs and benefits of four different technologies for advanced meter communications:• Wireless networks, based on cell phone technology (GPRS or Code Division Multiple Access) • Distribution line carrier (DLC), which injects the communications signal downstream of the distribution transformer into the low voltage hence is suitable for urban areas where there are many customers connected to the same low voltage transformer • Mesh radio • Power line carrier (PLC), which injects the communication signal at medium voltage and is designed to be able to pass through the distribution transformer. Hence it is suitable for rural areas where there are few customers on a single low voltage line but many customers on the same medium voltage feeder. The DLC and mesh radio technologies are not suitable for use in remote rural areas because the density of customers is too low.

The consultants estimated the benefits, costs and net benefits for various technologies relative to the costs and benefits of the rollout of manual interval meters. A rollout schedule at the same rate as originally planned of a DLC private network solution has marginally negative net benefits, but a faster rollout using DLC, mesh radio, or PLC (but not wireless) should provide net present value benefits (NPV), see exhibit 2. Exhibit 2

Cost-benefit analysis results of accelerated rollout (NPV in 2005 prices over the 18 year life of the investment) Communications technology wireless DLC Mesh radio PLC

Benefits (Au$m)

) ) 432 ) )

Costs (Au$m)

954 353 406 371

Net benefits (Au$m) -523 79 26 61

Advanced Interval Meter Communications study, 23 December 2005. http://www.dpi.vic.gov.au/dpi/dpinenergy.nsf/93a98744f6ec41bd4a256c8e00013aa9/11dfde71ea29720aca257395001ec7eb/$F ILE/AMI_Study.pdf

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The most significant benefit derives from the avoided cost of manually read normal cycle reads, which accounts for about 45% of the total benefits. The consultants recommended that the rollout of manual meters be cancelled and that the Victorian government and electricity supply industry should undertake an accelerated rollout of interval metering with advanced communications across Victoria.

To that end the government should facilitate the

development, in conjunction with the industry and the Essential Services Commission, of a common functional specification that will be mandated for smart meters. The government accepted the recommendations, and in August 2006 Victorian legislation was passed to give the relevant Minister the power to make Orders in connection with the state-wide rollout of 2.4m smart meters. These powers have been exercised to commence the rollout starting mid 2009 and to be completed by 2013. The government set up a stakeholder group to organize a series of trials of different communications technologies, which reported in November 2007, see Annex 2. The conclusions were that:• There are power line systems available suitable for further investigation for the Victorian rollout. There were concerns, however, regarding the potential “headroom” should future communications bandwidth requirements increase significantly • The distributor line trials broadly concluded that although available communications bandwidth may potentially be adequate to meet the requirements of the Functionality Specification, there remain a number of concerns regarding headroom for any future growth in communications bandwidth requirements • The mesh radio technology trials generally concluded that the technology has sufficient inherent communications bandwidth to meet the requirements of the functionality specification • GPRS has sufficient inherent bandwidth to meet the requirements prescribed by the functionality specification In October 2007 the government mandated10:• • • •

smart meters for all customers the meters to be the responsibility of the DNOs communications technology is a decision of the DNO minimum functionality specification of:-

Advanced Metering Infrastructure Minimum AMU Functionality Specification (Victoria), October 2007, Department of Primary Industries.

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* * * * * * * * * * * * * *

Remotely measure half-hourly consumption (Remote Routine and special reads) with a capability of being read at least once every 24 hours Controlled load or dedicated circuit management (storage hot water) Remote connect and disconnect of customer’s entire load at meter Remote time clock synchronisation Remotely measure separate exports and imports of energy Remote setting of times for controlled load switching Remote firmware upgrades Supply capacity control for entire customer’s load Measure power factor Meter loss-of-supply and outage detection Recording of meter settings, status indicators, events “Open” ZigBee interface to home area network Control of “other load” (eg air conditioner at time of summer peak) Tamper detection

Since the DNOs will be responsible for the initial rollout of meters and for the initial meter data provider, consequently there will be a number of bespoke communications systems (rather than open systems) for communications to the meter, but the market will still receive its data in the standard format. The data protocol being used is the existing one for remotely read meters, which will in due course be extended to accommodate additional functionalities. After the initial rollout competition for smart meters may be available, which would mean that retailers could choose their own metering provider (for installation etc) and meter data agent (for data collection). But again this will not impact the use of standard protocols in the delivery of data. The Essential Services Commission undertook a consultation on the price regulation of the meters11 and subsequently:• A revised framework and approach and draft information templates were issued on 4 December 2008 • Responsibility for regulatory oversight of the rollout was transferred from the ESC to the Australian Energy Regulator (AER) on 1 January 2009 • On 30 January 2009, the AER released its final decision on the framework and approach applying to distributors' budget applications for AMI expenditure for 2009-2011 and charges applications for 2010 and 2011 The five DNOs have been out to tender for meters and communications. The meters have the capacity to link into a home area network (but do not have to include an in-home display) and so (subject to 11

Advanced metering infrastructure price review, Consultation paper no. 1; framework and approach, August 2007, http://www.esc.vic.gov.au/NR/rdonlyres/F60D6221-0299-4315-B27F818A8911B34D/0/AMIConsultationPaperNo1FrameworkandApproach20070625.pdf

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complexity) will be able to effect direct load control. Reportedly four of the DNOs are using mesh radio for 96+% of meter points and GPRS for the balance. The results of the tenders will be made public by the end of April. The DNOs have to install 5% by June 2010 and complete the rollout by 2013.

New South Wales: EnergyAustralia is in the process of rolling out manually read interval meters (which can be smarted) to all its customers starting with all new installations and existing installations which have a meter upgrade. By November 2008 it had installed about 400,000 meters into the mass market sector. The distribution division is driving the rollout, which it has justified in terms of the benefits to the network business from deferred capital expenditure.

To support the rollout, EnergyAustralia has

introduced time of use network tariffs, which for smaller users have the following charges (excluding general sales tariff, GST):• A peak price of 12.8c/kWh for 2pm-8pm on working weekdays • A shoulder price of 2.4c/kWh for 7am-2pm and 8pm-10pm on working weekdays • An off-peak price of 0.6c/kWh all other times The relativities are thus peak/off-peak 21 times, peak/shoulder 5.3 times The retail business also has a regulated retail PowerSmart Home tariff for customers with interval meters with the following charges (excluding GST):• A peak price of 25.1c/kWh for 2pm-8pm on working weekdays • A shoulder price of 8.9c/kWh for 7am-2pm and 8pm-10pm on working weekdays and 7am-10pm on weekends and public holidays • An off-peak price of 5.1 c/kWh all other times The relativities are thus peak/off-peak 4.9 times, peak/shoulder 2.8 times. According to EnergyAustralia:“A survey of 3,000 PowerSmart Home customers shows that 94% of customers have found their bills are the same or cheaper than what they would have paid under the traditional flat pricing system,often without changing the way they use electricity. In fact, customers saved an average of 10% compared to what they would have paid under flat pricing, while some customers were able to save more than 30%. Of the small number of customers whose bill was higher, the increase was mostly less than 5%”. EnergyAustralia and Integral Energy have undertaken analyses of the changes in costs to serve resulting from switching to half-hourly costing and the demand response from ToU and critical peak pricing tariffs, 23

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and a consultant further analysed data from the trials, see annex 3. The key findings from the various studies were that:• The cost of service for customers with interval meter was lower for approximately 50% of customers and higher for the other 50%; for 30% of customers it would be more than 10% higher than the current profiled-based cost and for 16% it would be more than 20% higher. Conversely, for 25% of customers the underlying cost of service would have been more than 10% less than the current profiled-based cost. The cost of service is naturally greater for those customers with a greater proportion of their consumption in higher-cost periods. • There was no significant proportional bias in changes for low income customers benefiting from assistance programmes • It does not appear that seasonal ToU tariffs lead to a reduction in per-unit retail costs to customers, suggesting that there was little if any price-responsive load shifting • Customers on critical peak pricing (CPP) tariffs (with and without IHDs) appear to have a lower perunit customer cost ($5 - 6/MWh respectively, or around 4%) compared with a control group, which is a direct result of load reduction in the higher-cost CPP periods. The usage of the CPP group is around 50 kWh less in aggregate than the control group over the fourteen CPP periods that were called in the study period:*

the CPP customers exhibited a reduction in energy use in peak periods of 37% and in total of 2.4%

the CPP IHD customers exhibited a reduction in energy use in peak periods of 41% and in total of 3.6%

CPP tariff customers also used less energy than the control group. Consequently their annual bills were on average $92 (for CPP) and $139 (for CPP with an IHD) less than for the control group

EnergyAustralia and the other two DNOs are also installing smart meters with communications on a pilot basis.

In South Australia the government and ESCOSA have made no move to install smart meters. They are concerned to shave the peak demand of the needle peak which occurs in Victoria and South Australia every few summers when there is a heat wave for a few days and air conditioning – particularly in residences – increases demand significantly. Victoria and South Australia have some of the world’s peakiest electricity load shapes – the last 10% of maximum demand occurs for less than 20 hours per year – and thus very low asset utilization of peaking plant. This implies that those creating the peak are imposing significant costs on those with flatter load profiles. The Commission is anxious to avoid the

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cost of augmenting the distribution network, which is within its sphere of responsibility12. However “The Commission’s conclusion was that there was insufficient certainty of the demand reduction associated with such a tool (viz a smart meter) as to permit ETSA Utilities to defer network augmentation. The Commission therefore determined that it would be inappropriate to fund a wide scale rollout of interval meters to all customers of ETSA Utilities during the 2005 – 2010 regulatory period…the Commission approved an amount of $20.4 million over the 2005-2010 regulatory period to trial network demand management initiatives in the following areas:• • • • • • •

Power factor correction Direct load control of the compressors of air conditioning systems Voluntary and curtailable load control Demand management organization within ETSA Utilities Standby generation Critical peak pricing Aggregation”

There is a portfolio of projects which include direct load control of large commercial and industrial sites, standby generators, and direct load control of residences13.

A direct load control trial was undertaken over the 2006/07 summer period involving 1100 residential and commercial customers. As part of the trial customers in the trial area were offered a $100 incentive payment to have their air-conditioner cycled off for 15 minutes of each 30 minute period. The trial was extended in 2007/08 under the name “Beat-the-Peak”, which uses a small device controlled remotely by ETSA Utilities to switch off an air conditioner’s compressor for some minutes for the few hours of peak demand on days of high temperatures (the air conditioner fan stays on to circulate cool air). There is a discernable decrease in load when DLC is activated; the average reduction for two housing estates is shown in exhibit 3.

ETSA Utilities Demand Management Program Progress Report, June 2007. http://www.escosa.sa.gov.au/webdata/resources/files/070628-R-DemandManagementProgress_Report-_Final_.pdf. The Commission has issued “Demand Management for Electricity Distribution Networks, Electricity Industry Guideline No. 12”, http://www.escosa.sa.gov.au/webdata/resources/files/070628-O-Guideline12-DemandManagementV2_Final.pdf. “This Guideline outlines the way in which the Essential Services Commission of South Australia requires ETSA Utilities to meet its obligations to report and consult on its system constraints and Demand Management plans”. 13

Annual demand management compliance report (Issue 1.0 – August 2008), ETSA Utilities, http://www.etsautilities.com.au/public/download.jsp?id=7216.

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Exhibit 3

Average load savings per participant in the DLC trials Location

Glenelg Mawson Lakes

Average A/C capacity (kW) 3.08 5.07

Average kW reduction per A/C (kW) 0.45 1.34

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THE MINISTERIAL COUNCIL ON ENERGY’S STUDY ON SMART METERING

In February 2006, the Council of Australian Governments agreed to improve price signals for energy customers and investors, and committed to:“… the progressive national roll out of ‘smart’ electricity meters from 2007 to allow the introduction of time of day pricing and to allow users to better manage their demand for peak power but only where benefits outweigh costs for residential users, and in accordance with an implementation plan that has regard to costs and benefits and takes account of different market circumstances in each State and Territory”. At its meeting of 25 May 2007 the Ministerial Council on Energy set up a working group, which commissioned NERA as lead consultant supplemented by CRA, KPMG, and Energy Market Consulting Associates to undertake a cost-benefit analysis of the case for introducing smart meters and direct load control (DLC). The work has been undertaken in two phases:• Phase 1 addressed the question: What functionalities should be included in a minimum national functionality for a rollout of smart meters? The consultants completed Phase 1 in September 2007 • Phase 2 addressed the further question of whether the costs of rolling-out smart meters (or of undertaking an alternative demand management scenario) exceed the benefits, given the particular circumstances of different jurisdictions. The consultants completed Phase 2 in February 2008 The Standing Committee of Officials of the MCE published a “Consultation Regulatory Impact Statement on the Cost-Benefit of Options for National Smart Meter Rollout” in April 2008 followed by a final “Regulatory Impact Statement for Decision” in June 2008. The MCE issued a Smart Meter Decision Paper on 13 June 2008 followed by consultation for changing the National Electricity Law. “Smart meters are electricity meters that are capable both of measuring and recording energy consumption in short intervals, and of two-way communication, enabling energy providers to read and control features of the meter remotely. There are three main potential motivations for a smart metering rollout:1.

First, to provide a capability to manage network demand where jurisdictions face significant maximum demand growth, in order to delay the need for expensive investment in network capacity and peak generation.

Second, to achieve business efficiencies from the avoidance of costs, or better delivery of existing services (including the development of innovative new products and increased retail competition).

Third, to reduce greenhouse gas emissions. 27

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These three motivations are all reflected in the list of objectives that the MCE has required a smart meter rollout to be assessed against.

For a non-smart meter rollout of direct load control (DLC) infrastructure, only the first and third of these drivers apply. There are no business efficiency benefits associated with a DLC rollout. In relation to the third driver we note that the impact of a smart metering rollout on greenhouse gas emissions will depend critically on how demand changes as a result of changes in customer behaviour and particularly on the extent to which demand is reduced rather than simply shifted from peak to off-peak timesâ&#x20AC;?.

NERA reiterated a view held by the Essential Services Commission of Victoria that â&#x20AC;&#x153;each of the smart meter scenarios assume that the rollout of smart meters is mandatory across all small customers. The reason for considering a mandatory rollout is due to the market failure arising from the benefits of smart meters accruing to both distributors and retailers, such that neither distributors nor retailers would invest optimally in a smart meter rollout on its ownâ&#x20AC;?. Annex 12 analyses the issue of split benefits in more detail.

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THE CONSULTANTS’ STUDIES AND CONCLUSIONS14

The consultant analysed the operational implications of four alternative scenarios:• Scenario 1: Distributor-led rollout – where each distribution network service provider is given the responsibility for owning and installing meters and associated metering data services within its area of operations as a monopoly service provider • Scenario 2: Retailer-led rollout – where retailers have responsibility for procuring the installation of meters and data management services within a competitive market for these services. The key feature of the retailer-led scenario is the scope for competitive provision of communications and data management services, and metering provision within an area of operations. The competitive pressure in the meter data aggregator and meter provider markets should provide stronger incentives for service provision to retailers compared with a regulated service provision requirement where these services are provided by a distributor. Ultimately a retailer could choose to source metering services from an alternative provider if expectations are not satisfied. It is this competitive pressure that is anticipated to provide lower costs for service provision • Scenario 3: Non-smart meter direct load control (DLC) device rollout – which does not involve the installation of smart meters. DNOs have responsibility for retrofitting direct load control devices on high energy using appliances such as airconditioners and pool pumps • Scenario 4: Centralised communications as part of a retailer-led rollout – where the entire Australian smart meter communications system is provided by either a new centralized agency or an existing market operator. This scenario involves an obligation for a retailer to provide a smart meter to all of its customers by 31 December 2014. It is assumed that retailers would procure meters from competitive meter providers, with a single centralised communications and data aggregating system being provided by a third party. All meter providers would be required to ensure that their meters were capable of being read by the centralized communications and data aggregating infrastructure The three smart meter rollout scenarios differ in:• The allocation of the roles and responsibilities throughout the metering chain • The ownership of the meters (which has implications for customer churn where there is retail competition) • The scope for competition in metering services • Communications infrastructure required to provide services The differences are summarised in exhibit 4 below.

http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Meters%20-%20Stream%201%20-%20Overview%20%20Phase%201%20-%20NERA20071004120410.pdf.

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Exhibit 4

Comparison of smart meter scenarios

The key reports of Phase 2 are15:• Executive Summary of NETA’s Report on Smart Meters Phase 2 – Cost-benefit Analysis • Smart Metering – CBA Phase 2 – Stream 3 – Retail – KMPG (March 2008) 15

http://www.mce.gov.au/assets/documents/mceinternet/Executive_Summary_of_NERA%27s_Phase2Report20080915085044.p df, http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Metering%20CBA%20Phase%202%20Stream%203%20%20retail%20-%20KPMG%202008030320080304152737.pdf, http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Metering%20CBA%20Phase%202%20Stream%204%20%20consumers%20-%20NERA%202008022920080304153026.pdf, http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Metering%20CBA%20Phase%202%20Stream%204a%20%20consumer%20focus%20groups%20-%20NERA%202008022220080304153216.pdf, http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Metering%20CBA%20Phase%202%20Stream%202%20%20Networks%20-%20CRAI%202008020320080304152554.pdf.

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• Smart Metering – CBA Phase 2 – Stream 4 – Consumers – NERA (March 2008) • Smart Metering – CBA Phase 2 – Stream 4a – Consumers Focus Groups – NERA (March 2008) • Smart Metering – CBA Phase 2 – Stream 2 – Networks – CRA (March 2008) 6.1 Recommended national minimum functionality The analysis of costs and benefits for the smart meter scenarios were based on the recommended national minimum functionality. Most of the functionality was analysed in Phase 1 of the study, see Annex 4, plus an interface with a home area network should be included, which would facilitate provision of an in home display by retailers. (This functionality (16) was examined in detail together with the alternative option, functionality 15), see Annex 5. The benefits that may be expected to result from the inclusion of this functionality relate to both:• The ability to facilitate direct load control of appliances via the smart metering infrastructure • The potential to enhance customer demand response to ToU tariffs and CPP and to achieve greater demand conservation overall via the future provision of an in home display (IHD) Analysis suggests that the inclusion of functionality 16 would have positive net benefits, even where it involves only a DLC capability underpinned by smart thermostats and where it did not also involve provision of an IHD. It is also expected to have a positive net benefit where it involves DLC capability and where it involves the provision of an IHD. Furthermore the decision relates only to whether the meters that are rolled out include an interface with a HAN. How that interface is ultimately used will be determined by the commercial considerations of both retailers and distributors. That is, whether the interface is used to provide DLC capability and, if so, whether it is provided via a smart thermostat or via an open-system in-home communications device (eg, Zigbee). This is not determined as part of the minimum national functionality but will be a subsequent business decision. Similarly, whether consumers are provided with IHDs will depend on businesses’ consideration of whether they expect to achieve an enhanced demand response or could realize other benefits from an IHD.

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Exhibit 5

Final functionalities recommended for inclusion in a minimum national meter specification

The study also considered the standardization of protocols, but concluded more work was required, see Annex 6. 6.2 The costs of smart metering are estimated to be between $2.7bn and $4.3bn (in NPV terms) The total costs of a national smart metering rollout are estimated as ranging from $2.7bn to $4.3bn in NPV terms16 over a 20 year period for a distributor-led rollout. The costs rise to over $5.9bn for a retailer led rollout (upper bound). These estimates have been developed through an extensive cost build up exercise, which includes estimating the costs of:â&#x20AC;˘ Smart meters and their installation in each jurisdiction â&#x20AC;˘ Communications infrastructure â&#x20AC;˘ Meter data and communications management systems 16

A 20 year time period was assumed for the cost-benefit analysis with all existing meters replaced by 31 December 2014, but the profiles of replacement were dependent upon the jurisdictional circumstances. The analysis used a real pre-tax discount rate of 8% for all costs and benefits of the smart meter rollout, and sensitivity testing with discount rates of 6.5% and 9.5%. The lower rate approximates the real pre-tax weighted average cost of capital commonly used by energy regulators in Australia.

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• Market operator systems to manage changes to market settlement information and new meteringrelated business to business transactions • Retailer systems to support the retailer activities expected to be undertaken as a result of the rollout of smart meters in each scenario • Distributor systems to support the distributor activities expected to be undertaken as a result of the rollout of smart meters in each scenario In addition, an allowance has been made for programme management costs relating to the smart metering infrastructure rollout. The costs differed between each scenario due to:• Differences in the assumed communications infrastructure considered by EMCa to be appropriate to support each scenario • Differences in the non-communications infrastructure, eg, the number of meter data management systems required • Differences in meter costs between scenarios Additional information about costs is provided in Annexes 7 and 8. 6.3 The benefits of smart metering are estimated to be between $4.5bn and $6.7bn (in NPV terms)17 The benefits associated with a national rollout of smart metering have been estimated to be between $4.5bn and $6.7bn in NPV terms over the twenty year period of analysis, under the distributor-led rollout scenario. The value of the benefits falls under the alternative rollout scenarios, to $4.1bn in the lower bound for both the retailer-led rollout and the centralized communications scenario.

The majority of the benefits result from avoided meter costs associated with not having to replace the existing meter stock and business efficiency benefits for distributors (totaling approximately 39% to 44% and 41% to 55% of total benefits respectively). Demand response benefits represent only between 6% and 12% of total estimated benefits (excluding the potential demand response benefits associated with including an interface to the HAN):-

The cost-benefit analysis focused only on the first round impact of a smart meter rollout or DLC alternative. That is, the costs associated with the rollout and the benefits that flow from it are assessed at the point at which they are first incurred (for costs) or first accrue (for benefits). For example, under Scenario 1 the costs of the smart meters are initially borne by the distributors, and business efficiency benefits from no longer having to manually read meters also accrue to the distributor in the first instance. In the longer term, however, both the costs of the rollout and many of the benefits can be expected to flow through to customers.

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• The potential benefit from avoiding the need to replace the existing meter stock ranges from $1.7bn to $2.6bn • Distributor business efficiency benefits resulting from smart metering, total between $2.1bn and $2.9bn in NPV terms over the twenty year period of the analysis. These benefits include:* * * * *

the avoided cost of routine manual meter reading the avoided cost of special meter reads (ie, when customers move into or out of a premise) the avoided costs of manual disconnections and reconnections reductions in calls to faults and emergency lines avoided costs of customer complaints about voltage quality of supply

• Retailer benefits resulting from smart metering total between $98m and $196m in NPV terms over the twenty year period of the analysis (or 4-6% of the total estimate of business efficiencies). These benefits include:*

* * *

The final benefit category results from changes in the time of use and level of electricity demand by customers, which leads to:• • • •

The deferral of peak network augmentation Reductions in retailers’ hedging costs as a result of reductions in peak wholesale prices The deferral of peak generating capacity18 Reductions in the level of unserved energy, generation operating costs and carbon emissions resulting from changes in the pattern of electricity market dispatch

The demand response benefits are calculated based on assumptions in relation to the ToU tariffs and CPP products that may be offered following a smart meter rollout and the likely take-up rate of those products19 and estimates of the demand response resulting from the introduction of these tariffs, which have been developed by NERA20. CRA have taken these estimates of demand response and estimated

CRA concluded that the relatively small size of the overall system demand reductions that have been estimated to follow a rollout of smart meters or a DLC alternative would not be sufficient to defer generation investment in practice. However, CRA have estimated benefits in relation to a reduction in unserved energy, resulting from the demand reduction. CRA Workstream 5 Market Impact Consultation Report (February 2008), section 4.2.

19 20

KPMG, Workstream 3 Retail Impacts Consultation Report (February 2008), Appendix A. NERA, Workstream 4 Consumer Impacts Consultation Report (February 2008), section 5.

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both the potential value of the network deferral benefits that may occur and the impact on the electricity market.

Nationally the demand response benefits range between $250m and $738m in NPV terms over the twenty year period of the analysis (excluding the demand response benefits that may arise from including an interface to a HAN). This represents between 6-12% of total benefits resulting from the introduction of smart metering. Including an interface to a HAN may increase the total demand response benefits by between a further $169m to $925m. Over the twenty year period of the cost-benefit analysis the total reduction in greenhouse cases is estimated to be between 597,000 tonnes and 12.3 million tonnes.

There are a number of additional benefits that were not quantified in the study due mainly to a lack of information, namely:• • • • • •

Reduction in cost of load research Reduction in technical losses Reduction in the cost of network planning and operation Avoided costs of validation and exception management for routine and special meter readings Reduction in end of line monitoring Reduction in the cost of recording and reporting minutes off supply to regulators

If these benefits could be quantified they could increase the overall benefits of smart metering by 1020%. 6.4

Smart metering, retailers and customers

As part of the project, KPMG undertook a study on “Retailer Impacts” which includes not only information that is relevant to considering smart meters, but also information of relevance to retailing in general. Further extracts are included in Annex 9. The study points out that:• Residential customers do not spend much on electricity, and are not interested in it. Potential savings from switching are modest. “The experience across these markets varies, but there would appear to be several important similarities that are relevant to whether retailers might introduce more cost reflective tariffs across the board to unwind the load profile cross subsidy…it would appear about half the customer base has been willing to switch to non-host retailers for savings of 5-10% of the value of their bill. Conversely, at least at this stage of the market’s development, up to half of the market appears to be unwilling to switch for such savings” • Retailer margins are slim, and most were not keen on the introduction of smart meters linked with introducing new cost-reflective tariffs because “the key question a retailer will ask itself is: are more cost reflective tariffs going to increase the Au$50 margin I can make on the typical customer?”. Also 35

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the large retailers were not keen on spending Au$50-100m on new billing and customer service systems • The thin retailer margins constrains the degree to which they are in a position to offer differential tariffs. Energy retailing is therefore a service which, for the mass market, involves a low degree of customization and customer contact. Retailers tend to operate mass marketing campaigns and make their competitive offers very similar to existing offers to overcome customer inertia (e.g. similar tariffs, but with a discount) • “The typical view is that it is likely to be very difficult to sell retail products by focusing on tariffs as the customer does not understand them and is not interested in investing the time necessary to understand them. This is simply because their bills are not significant enough for them to care. One retailer stated “our salespeople never talk about tariffs when trying to win a customer – all they do is offer the same basic offer, but with some alternative benefit”. The retailer also stated that if you talk about tariffs “you are dead” in terms of making sales A number of variables, both from a retailer’s and customer’s perspective, are likely to influence the take up of these tariffs generally and by jurisdiction. For customers the key variables are likely to include:• The initial impact, if any, on the customer’s bill. From KPMG’s view it would be reasonable to assume that:*

for bill savings of greater than (say) 10% a majority of customers will be prepared to move and thus create a competitive threat to the incumbent retailers

for bill savings of between (say) 5-10% a significant majority of customers will be prepared to move

for bill savings of between (say) 0-50% a minority of customers will be prepared to move

• The customer’s willingness to take more price risk • The customer’s willingness to switch for savings or prospective savings dependent on behavioural change • The complexity of the offers and how easy it is for the customer to respond • How the information about usage is communicated to customers • Environmental concerns The customer focus groups canvassed participants’ views as to their willingness to adopt alternative tariff structures (including DLC), see Annex 11. A consistent finding across all of the focus groups was that participants were much more willing to consider a DLC tariff option compared to other alternatives. Participants viewed DLC options as providing them with a way to ‘do the right thing’ and reduce electricity consumption without needing to think about it and in that respect it not impacting their 36

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lifestyle. The fact that they would also reduce their electricity costs and receive a payment for adopting DLC was viewed as a bonus. In contrast to their willingness to consider DLC, the vast majority of participants did not see much benefit to them in adopting CPP. KPMG think it is reasonable to expect that:• Some non-incumbent retailers will target those customers who will save significant amounts (i.e. above 10%) of money under more cost reflective offers and actively sell these tariffs to them • Incumbent retailers to watch market developments closely and be prepared to start offering more cost reflective tariffs to these customers relatively quickly if it became apparent that they risked losing a significant number of their (newly) more attractive customers • Even if they were prepared to accept price risk, with the intention of saving money by altering their behaviour, the additional savings are likely to be relatively modest for the typical customer (perhaps about $50 p.a.) Given the added complexity of such offers it seems reasonable to conclude that the savings would have to be larger than those outlined above to encourage significant take up. It is possible this might change as these markets mature further, but it seems that this may take some time given the maturity of some of these markets and the higher savings these remaining customers may need to switch”. Further details on customer impacts is provided in Annex 10. 6.5 Smart metering is estimated to deliver net benefits of between $179m and $3.9bn nationally Exhibit 6 summarises the overall net benefit nationally across all of the jurisdictions in Australia resulting from the analysis for each of the alternative rollout scenarios. The maximum net benefits of smart metering (excluding the costs and benefits that may accrue from the interface with a HAN) are estimated to arise from a distributor-led rollout of smart metering (Scenario 1), with a range of between $179m and $3.9bn in NPV terms over a twenty year period. For the alternative rollout scenarios 2 and 4, the net benefit of smart metering is negative in the lower bound, reflecting both the higher costs associated with those scenarios and the lower level of expected benefits.

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Exhibit 6

NPV benefits and costs ($m) national (excluding HAN)

Exhibit 7

NPV of benefits and costs ($m) â&#x20AC;&#x201C; national scenario 1 (excluding HAN)

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In exhibit 7 the solid component of each of the bars represents the lowest end of the range estimated for the smart metering infrastructure (SMI)21 costs, avoided meter costs, business efficiencies or demand response. The potential additional cost or benefit for each of the categories (as reflected by the upper end of the estimation range in each case) is indicated by the hatched areas. The total magnitude of the additional benefits (i.e. the top end of the ranges) is indicated by the height of the uppermost hatched areas in the demand response bars. The exhibit shows that:â&#x20AC;˘ On the basis of the low cost estimate a smart meter rollout under Scenario 1 is justified by the low end estimate of the avoided meter costs and business efficiencies. In this case, the low end of these two benefit categories is 57% above the low cost estimate. If the high end cost estimate is taken then these two benefit categories are only 2% below the cost estimate. If the high business efficiency estimate is taken together with the avoided meter costs it is 36% above the high cost estimate â&#x20AC;˘ The demand response benefits (which include benefits from both network deferral and a reduction in greenhouse gas emissions, in addition to other market benefits) are estimated to be relatively low on a national basis. In Scenario 1 the demand response benefits range from between 6% and 11% as a proportion of total benefits. The benefits of network deferral account for the bulk of demand response benefits (for example, in Scenario 1 a nationwide network deferral benefit represents between 83% (lower demand response) and 51% (higher demand response) of the total demand response benefits. In comparison, greenhouse benefits represent 2% of total demand response benefits in the lower demand response case and 12% in the higher demand response case Inclusion of an interface with a HAN in the smart metering functionality increases the demand response benefit estimated for the three smart meter rollout scenarios compared with the estimates presented above, as well as increasing the rollout costs. The additional net benefit that may be realisable from the inclusion of the HAN ranges from $39m(in NPV terms over the twenty year period) to $392m. The net benefits including the HAN for a distributor-led rollout are illustrated in exhibit 8.

SMI refers to all the communication and data management support requirements of smart meters in addition to the meters themselves.

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Exhibit 8

NPV of benefits and costs ($m) â&#x20AC;&#x201C; national scenario 1 (including HAN)

Both costs and business efficiency benefits per NMI are greater for customers in rural and remote areas than for urban customers22. In relative terms the higher benefit per NMI in rural and remote areas exceeds the increase in costs per NMI for these customers, and so the net benefit per NMI of a smart meter rollout is greater for customers in rural and remote areas than it is for customers in urban areas. The analysis assumed power line carrier communications technology for rural and remote areas.

The national aggregated results mask differences in the underlying net benefits by jurisdiction, because both the costs and benefits vary according to the circumstances of each jurisdiction. Exhibit 9 summarises the results for scenario 1 for each jurisdiction, and indicates the upper and lower ranges for the net benefit estimated in each case.

The distinction between urban and rural is notionally a density of less than 100 customers per square kilometer. About 86% of customers are urban, and 14% rural/remote.

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Exhibit 9

Summary of Results by Jurisdiction â&#x20AC;&#x201C; Net Benefit (NPV, $m), Scenario 1 (Excluding HAN)

The results indicate that a distributor-led rollout of smart metering in Queensland, New South Wales, Victoria and Western Australia would deliver positive net benefits on the basis of the estimated avoided meter costs and business efficiencies alone. The inclusion of an interface with a home area network in these jurisdictions would likely further increase the net benefits (through further enhancing the demand response), particularly if direct load control was targeted to maximize both participation and the resultant network deferral benefits.

The results of the cost-benefit analysis for South Australia show that for a rollout of smart metering to have a net positive benefit, it is necessary to have costs at the low end of the range estimated. Customer business efficiency benefits are lower in South Australia than the national average, mainly due to much lower avoided costs for special reads (15% of the national average, driven by lower property churn, and much lower reading costs), lower avoided costs for routine meter reading, and less reduction assumed in the cost of calls to faults and emergencies lines.

The results suggest that a national mandatory smart metering rollout may not be justified in all jurisdictions, but then:41

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• The requirement to settle the wholesale market on the basis of net system load profiles, rather than actual usage information would remain • Retailers operating across jurisdictions may require different business processes for managing customer switching and services provided through smart metering, such as special reads. This is likely to increase the costs associated with managing a smart metering rollout 6.6 Non-smart meter direct load control may be a viable alternative in some jurisdictions A non-smart meter direct load control DLC scenario approach is a substitute for providing a direct load control capability via the inclusion of an interface with a home area network in the smart meter specification (functionality 16). The functionalities included in a DLC Scenario were:-

The results indicate that:• Nationally DLC can deliver net benefits of between $34m and $618m • In Queensland a non-smart meter DLC rollout is estimated to provide positive net benefits in both the upper and lower end of the ranges considered • In New South Wales a non-smart meter DLC rollout has a positive net benefit in the upper bound and a marginal net cost in the lower bound. However, this reflects the winter peaking assumption in New South Wales, which results in DLC not leading to any network deferral. Under the summer peaking sensitivity a non-smart meter DLC rollout is estimated to provide positive net benefits in both the upper and lower bounds • In Victoria, South Australia and Western Australia a non-smart meter DLC rollout is estimated to provide positive net benefits in the upper end of the ranges and to have either a zero or only minimal net benefit in the lower end of the range Based on cost estimates the incremental cost of providing direct load control capabilities via the smart metering rollout (i.e. functionality 16AB or 16C) is lower than a stand-alone DLC rollout as in scenario 3. This suggests that for those jurisdictions where smart metering is justified on other grounds, DLC capabilities should be implemented via the smart metering infrastructure. However, for jurisdictions

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where smart metering is not justified on the basis of business efficiency or avoided meter cost-benefits there may be benefits from implementing a nonsmart meter DLC program.

Over time business cost savings resulting from the introduction of smart metering would be expected to be passed through to customers in the form of lower tariffs, either through the regulatory price setting framework (for distribution businesses and for retail businesses in those jurisdictions where there is no retail competition) or through competition.

In general, our households with a relatively low proportion of total consumption during peak periods (for example households where occupants work during the day or households with average consumptions and matching the state load profile) are likely to be better off after the introduction of ToU tariffs, without necessarily needing to change current electricity usage behaviour. (Under flat tariffs these households are currently cross-subsidising households who use a greater proportion of electricity during peak periods). 6.7 Objectives Applying to the Rollout The Terms of Reference for the cost-benefit analysis set out a list of objectives against which the different scenarios for the rollout of smart meters must be assessed, namely:1. Reducing demand for peak power, with consequential infrastructure savings (e.g. network augmentation and generation) – a DLC rollout (Scenario 3) is expected to result in greater reductions in peak demand than a smart meter rollout, where smart meters do not also incorporate a DLC functionality (i.e. functionalities 15 or 16). 2. Driving efficiency and innovation in electricity business operations, including improving price signals for efficient investment and contracting – these are greatest for Scenario 1 (the distributor-led rollout) and are likely to be lower in Scenarios 2 and 4. 3. Promoting the long-term interest of electricity customers with regard to the price, quality, security and reliability of electricity – the greater is the expected level of business efficiencies that are achieved as a result of the smart meter rollout the lower will be the expected prices that customers will face in future. 4. Promoting competition in electricity retail markets – scenarios may differ in the ability of retailers to offer innovative products and to differentiate themselves from their competitors. 5. Enabling customers (including residential, business, low- and high-volume users) to make informed choices and better manage their energy use and greenhouse gas emissions – this objective would be facilitated where retailers introduced ToU tariffs and CPP and to provide customers with more information in relation to their energy usage via an interface with a HAN (functionality 16) via an IHD.

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6. Manage distributional price impacts for vulnerable customers – distributional price impacts are likely to arise where customers face time differentiated tariffs, as a result of a smart meter rollout, which should be accompanied by measures to address distributional price impacts on vulnerable customers. 7. Promoting energy efficiency and greenhouse benefits – reduction in greenhouse gas emissions would be the greatest under the smart metering scenarios compared to the DLC only scenario. As a result Scenarios 1, 2 and 4 are ranked above Scenario 3. 8. Providing a potential platform for other demand side response measures and avoiding discrimination against technologies, including alternative energy technologies – a smart metering rollout would provide a platform for DLC programs either where the meters include an interface to a HAN (i.e. functionality 16) or alternatively via the installation of DLC devices that interface with the smart meter communications infrastructure. Exhibit 10 presents NERA’s assessment of the relative ranking on a national basis of each of the rollout scenarios in relation to the objectives set out by the MCE. For each objective NERA ranked how well each of the scenarios meets that objective compared to the alternative scenarios. A ‘1’ indicates that that scenario meets the objective better than all other scenarios. A ‘2’ indicates that the scenario is ranked second, and so on. Where a scenario does not have an impact on meeting a particular objective this is indicated in the table by a dash (‘-‘). Exhibit 10

Assessment of rollout scenarios against MCE required objectives: relative ranking of scenarios (excluding functionalities 15 and 16

A distributor-led smart metering rollout best satisfies the MCE’s assessment objectives. 44

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IMPLEMENTING THE SMART METERING POLICY

Following a draft Regulatory Impact Statement prepared in April 2008, a final Regulatory Impact Statement “Cost-benefit Analysis of Options for a National Smart Meter Rollout” was presented to the MCE for Decision in June 200823. The analysis of functionalities and costs and benefits was based entirely on the consultants’ work, and so no general purpose is served by repeating it. But the paper did draw out the “split benefits problem” which “explains why the nature of Australia’s electricity sector means the market is unlikely to correct the problems discussed above [viz inefficient non-cost reflective electricity pricing] without government intervention”, see Annex 12.

The recommendation of the

officials was that MCE agree to:“1.

Include the interface to a Home Area Network as part of the national minimum functionality for smart meters.

Support a national rollout of smart meters to areas where benefits outweigh the costs enabled by a Market jurisdictions.

However given the variable benefit in different jurisdictions, support a staged rollout with further pilots or business-specific businesses cases progressed in most jurisdictions to confirm the net benefits and cost risks identified in the cost-benefit analysis.

Provide a mandate to distributors to undertake the rollout in National Electricity Market jurisdictions for the rollout period as deployment plans are set”.

On 13 June the MCE published “Smart Meter Decision Paper”24, commenting “As a critical part of the national framework, MCE agrees that distributors are the most appropriate party to manage any obligation for an accelerated rollout. To support this MCE agrees that residential and small customer metering and related data management services should remain the responsibility of distributors in National Electricity Market jurisdictions for at least the rollout period. This decision is consistent with the current approach in Victoria. To provide clarity on this policy position, and to allow the Australian Energy Market Commission to consider any related Rule changes efficiently, MCE will release a Statement of Policy Principles on this matter. MCE supports this distributor led rollout largely to manage the market failure risks specific to achieving an accelerated rollout, given the scale of change required, the complexity in market change and the need to maximise network operational benefits in the transition”.

http://www.mce.gov.au/assets/documents/mceinternet/Decison_RIS20080915090204.pdf.

http://www.mce.gov.au/assets/documents/mceinternet/Smart_Meter_Decision_Paper_MCE_13_June_200820080613153900.p df.

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Subsequently the MCE published proposals for amending the National Electricity Law25,26 “to provide:• That a Minister of a participating jurisdiction may make a determination in relation to a regulated DNO operating predominantly in that jurisdiction such that the regulated DNO must, in accordance with the Rules ensure that customers:*

specified in the determination (as defined by the minimum number of relevant customers, the class of relevant customers and the minimum number of supply points)

in the regions prescribed by the determination (e.g. all of their network)

must be provided with smart metering services:* *

which meet the standards specified in the Rules in accordance with a timetable prescribed by the determination

• That a Minister of a participating jurisdiction may specify in a determination that a regulated DNO operating predominantly in that jurisdiction must conduct such pilots and trials of remotely read interval meters of a nature and to timings, performance standards and service levels specified in the determination. It is anticipated the determination would specify:* * * * *

which businesses are involved the customer numbers and types of customers covered by the determination the type or functionality of remotely read meters or of associated processes and systems that would be trialled relevant timeframes for the pilots or trials pilots or trials process requirements

The central link to the Rules would be that 'smart metering services' would be defined as services provided to a customer by means of a remotely read interval meter which, at the time it was installed, met the specifications of a smart meter in the Rules”. The release of exposure draft of amendments to the National Electricity Law for smart meters reflects the fact that the matter is appropriate for Parliament to set the boundaries, rather than be a decision of the Australian Energy Market Commission. The legislative package should progress through the South Australian Parliament in May 2009 and will (with adoption) be applied to other states.

http://www.mce.gov.au/assets/documents/mceinternet/Exposure%20draft%20%20smart%20meter%20NEL%20amendments20081223153651.pdf. 26 http://www.mce.gov.au/assets/documents/mceinternet/Explanatory%20note%20%20smart%20meter%20NEL%20amendments20081224104911.pdf.

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An analysis has identified limitations in the current regulatory framework which the Australian Energy Market Commission should consider in its review to achieve a certain predictable and accelerated rollout of smart meters, namely27:• The bundling of metering service charges with other distribution use of system charges makes it difficult to assess metering costs accurately • Lack of historical data makes it difficult to estimate future costs of new technology, which has implications for the incentive-based structure of the existing framework • Existing efficiency benefit sharing arrangements may discourage DNOs from passing through benefits to customers in a timely manner • There are differences in the classification of services between DNOs which may adversely impact on the consistency of a National Electricity Market wide framework The National Stakeholder Steering Committee (NSSC) has been established by the MCE to define a national framework for the rollout of smart metering infrastructure including technical, and operational requirements and changes to regulatory rules and procedures in the National Electricity Market, Western Australia and Northern Territory. The Committee has prepared a National Smart Metering Program (NSMP) work plan that specifies the tasks and deliverables required to specify the smart metering infrastructure functional specification and supporting regulatory framework, which the MCE approved on 12 December 2008. The Programme’s objective is to enable the stakeholders to achieve the outcomes and timetable agreed with the MCE in terms of:• Defining a regulatory framework for the National Electricity Market to underpin smart metering • Developing specifications and proposals for changes to the market and other jurisdictional rules and procedures and to establish and implement other elements of the framework • Coordinating and reporting on smart meter pilots as part of an overall plan for the potential deployment of SM services in the National Electricity Market, and considering arrangements for pilots and deployments in other jurisdictions • Providing quality advice to the MCE on technical, regulatory and economic matters including cost recovery for pilots and rollouts relating to smart metering • Providing a platform for sharing knowledge and experience between industry participants and other stakeholders nationally

Based on a presentation “National Rollout of Smart Meters in Australia, What has happened in the last year?”, David Prins, Etrog Consulting, 16 February 2009.

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To support the development of the national smart metering framework and to provide effective stakeholder engagement, the National Stakeholder Steering Committee for the National Smart Metering Programme is in the process of establishing four working groups:• • • •

Business Requirements Business Processes and Procedures Regulation Pilots and Trials * * *

As noted above, Victoria has mandated a rollout of smart meters and it is just about to begin. The government of South Australia remains skeptical of the benefits of smart metering in addressing what it regards as its key problem –the needle peak – and remains committed to developing a range of peak reducing initiatives including direct load control for residential customers. For customers “A smart meter sitting on a wall does nothing”. The NSW government considers that smart metering is probably the way to go, but notes that the cost-benefit analyses have a wide range of outcomes, and problems remain with communications in particular mesh technology. In 2012 officials will review the situation and the Minister will decide.

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Annex 1

Cross subsidies resulting from the net system load profile

In 2003 the Essential Services Commission of Victoria commissioned consultants Trowbridge Deloitte to assess the extent of cross subsidies resulting from using the simple net system load profile, and estimate the redistribution of prices that might occur with interval metering28. The consultant compared the load weighted costs of default tariffs for actual pool prices for 2001 and 2002 and also simulated pool prices for customer classes averaged across the five distribution businesses for:• all customers represented by the net system load profile • profiles for groups of customers derived from data held by the distribution businesses The analysis examined small/medium/large residential customers29 with different characteristics (e.g. with/without air conditioning, with/without controlled off-peak water heating, and 8 types of small commercial/industrial customers (bakery, dairy, farm, office, restaurant, small 5 day industry, small 7 day industry, and small industry with a high peak load)). The simulation allowed for various weather scenarios (hot/mild/cool summer, mid/warm winter) the two actual years. Deloitte Trowbridge argued that the simulated results were more representative of reality.

The consultant applied the current default tariffs and modelled customer groups’ consumption to determine a c/KWh annual bill by group, and separately calculated a c/KWh network cost component based on the current published network tariffs. The difference between these components is the “Retailer Tariff Residual”, which is available to a retailer to manage all its other costs associated with its business including:• • • •

Retailer operating costs Retail Margin NEMMCO charges Energy Costs, including costs associated with prudent hedging and ancillary service payments

The consultant then considered the potential individual components of the regulated default tariffs available to customers who did not switch based on the broad costs detailed in the Commission’s own analysis:28

Customer Energy Cost Cross Subsidies in the Victorian Electricity Market, Essential Services Commission, September 2003,http://www.esc.vic.gov.au/NR/rdonlyres/3195BB32-6D3D-47D4-9B37A54A8045D745/0/TrowbridgeR110903_CustomerCrossSubsidies.pdf. 29 The consultant constructed 28 residential customer profiles with the focus on electric hot water, off peak space heating and air conditioning appliances. Other appliances are treated as “standard”.

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• • • •

Network charges and costs as per each distributor’s 2003 tariff determination Retailer operating costs of Au$70 per customer per annum Retail margin of 4% Energy costs of Au$70/MWh

Under a net system load profile methodology for wholesale settlements, a retailer will face the same c/KWh energy costs for all its customers that are profiled. This equalisation of energy costs supports a standard energy allowance for all customers under the standing offers. The calculation resulted in an estimate of the retailer tariff margin (RTM) as follows:(RTM) Residential customers: general purpose tariff separately metered off peak tariff Non-residential customers: 5 day week industrial 7 day week restaurant dairy farm bakery

-5% to +15% -12% to +5% +2.5 to +10% +7.5% 0 to -15% -10 to 25%

• A positive RTM indicates that the customer group is more profitable than assumed and/or that within the envelope of the current price structure costs could increase while maintaining a reasonable retailer profit margin. This could include a higher cost for energy • A negative RTM indicates that the customer group is less profitable than assumed (potentially unprofitable) and/or that within the envelope of the current price structure costs could decrease to obtain a reasonable retailer profit margin. This could include lower costs for energy A positive outcome indicates that a customer group’s energy cost is likely to be lower under the current profiling arrangements than it would be if based on the customer group’s “true” cost of energy (i.e. the customer receives a cross subsidy). A negative outcome indicates the customer group’s cost is likely to be higher under the current profiling system than if based on the customer group’s “true” cost of energy (i.e. the customer pays a cross subsidy). In total, therefore these customers might have paid either Au$60 too little or Au$20 too much per customer in any particular year (based on a hypothetical typical domestic customer with a bill of Au$1,000, of which 40% is energy costs). For the largest (and smallest) users the volume cross subsidy is likely to be material. For example, if the average user has a bill of Au$1,000 a variable charge of Au$900 and an average unit of price of 15c/kWh, they would be using 6,000 kWh p.a. The typical Au$50 per customer EBIT margin would therefore account for 0.83c/kWh of the unit price. This means that the customer whose consumption is 50% greater than the average user is paying a 50

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margin of Au$75 p.a. (i.e. or 50% more than they ‘should’), while the customer whose consumption is 100% greater than the average user is paying a margin of Au$100 p.a. (i.e. double what they ‘should’). Conversely, smaller than average users are typically paying too little.

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Annex 2

Victoria Advanced Metering Infrastructure Technology Trials Report30

A stakeholder group was set up in Victoria to organize a series of trials of different communication technologies. The objective was to evaluate the ability of commercially available communications technologies to deliver the minimum state-wide functionality requirements of smart metering for customers across a range of geographic areas. In particular to assess the performance of communication systems and several key functionalities under realistic conditions, including:• • • • •

reliability of communications deliverability of the desired communications bandwidth speed and accuracy of routine meter reads response times (e.g. for single meter reads and connect/disconnect requests) performance on various distribution network configurations (for distribution line carrier (DLC) and power line carrier (PLC)) • the performance of various meter configurations under a range of conditions The technology trials aim to assist the distribution businesses in:• • • • • •

identifying technologies relevant to their network areas identifying potential vendors refining cost estimates gaining implementation experience identifying operational, safety and technical impacts and issues identifying installation issues at customer premises

Four technologies were assessed, namely:• power line carrier (PLC) communications send signals over powerlines between zone substations and meters; these signals can pass through distribution transformers. Outbound communications to meters is typically 10 to 30 bps whilst inbound communications from meters to zone substations is typically 20 to 600 bps depending on the number of meters communicating in parallel. PLC is often costeffective when customer density is low, and has often been preferred for communications in rural areas The conclusion was that there are PLC systems available suitable for further investigation for the Victorian rollout. There were concerns, however, regarding the potential “headroom” should future communications bandwidth requirements increase significantly. The PLC technology trials also identified a number of technical issues that require further investigation and resolution related to voltage “flicker” and “harmonics”. • Distribution line carrier (DLC) systems use the low voltage distribution network (“poles and wires”) downstream of the distribution transformers as the communications medium between meters and data 30

Department of Primary Industries, November 2007, http://www.dpi.vic.gov.au/dpi/dpinenergy.nsf/LinkView/8800A04258F64CB8CA2574E90013D9604CAC723B1D538D66CA 25740C000D2004/$file/AMI%20Technology%20Trials%20Report.pdf.

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concentrators generally located at the distribution transformers. This technology typically has relatively low end-point costs, but requires more concentrators than the other options. DLC typically achieves data communication rates between data concentrators and meters of between 100 bps and 5 kbps. The number of meters per data concentrator influences the overall latency of DLC:*

the DLC DLMS technology trials broadly concluded that although available communications bandwidth may potentially be adequate to meet the requirements of the Functionality Specification, there remain a number of concerns regarding headroom for any future growth in communications bandwidth requirements

the DLC LON technology trials concluded that there are systems with sufficient communications throughput to meet the requirements prescribed by the functionality specification. Much like the DLC DLMS trials, even under ideal conditions, there were bandwidth limitations. Further investigations should be undertaken by trialling participants to establish whether these constraints can be mitigated

â&#x20AC;˘ Mesh radio is a private radio network technology for communicating with meters that uses meters as repeaters in a mesh configuration. The meter collector receives and transmits signals to meters which, in turn, pass these signals on to other meters. The layout of the mesh is such that meters may be able to communicate with several meter collectors, so that if the path to one is not operational at a given time, then paths to other meter collectors can be used. Meter collectors can interact with about 1,000 meters in a mesh. Mesh radio achieves data communication rates of 5-20 kbps. The Mesh Radio technology trials generally concluded that the technology has sufficient inherent communications bandwidth to meet the requirements of the functionality specification â&#x20AC;˘ GPRS allows high-speed data services over existing GSM radio networks (which operates in the same way as a mobile phone). GPRS supports data transfer rates up to 40 kbps. Communications to and from the meters rely on existing public networks. With this system, there are no intermediate data concentrators or transceivers; communication is directly with each meter. The GPRS modem may be integrated into the meter at the customerâ&#x20AC;&#x2122;s premises. Whilst the GPRS trials scope did not fully align with the scope of other technology trials, it was found that the results supported the earlier view that GPRS has sufficient inherent bandwidth to meet the requirements prescribed by the functionality specification

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Annex 3

The effect of costing wholesale prices on interval consumption rather than profiles and customer responses to time-of-use and dynamic peak prices in NSW studies31

The use of interval data from smart metering changes the way in which the cost for electricity retailers serving mass market residential customers (viz wholesale energy purchase costs, network use of system charges) is calculated from using estimated profiles to the actual cost half hour by half hour. If retailers respond to the introduction of smart metering by implementing pricing changes that reflect customers’ particular consumption profiles, then some customers will win and others will lose compared to the traditional profiles. Potential retailer responses to any changes in cost to serve could include:• Increases in flat retail prices targeted toward higher cost customers to protect margins • Decreases in flat retail prices targeted toward lower cost customers, in order to retain customers and protect margins • Introduction of time of use prices (e.g. peak, shoulder and off-peak) in order better to match annual prices charged with individual customers’ profiles and thereby reduce hedging costs/protecting margins • Introduction of critical peak prices (called dynamic peak prices in the report) to apply during very high price periods, to reduce hedging costs/protect margins Customers could respond to increases in retail prices associated with smart metering in ways that could include the following:• Purchasing and activating pool pump timers so that pool pumps automatically do not operate during peak price periods • Activating clothes driers, washing machines, dishwashers and other items outside peak price periods • Where mains gas is available, switching to gas for space heating and cooking applications • Switching to solar energy or to gas for water heating • Minimising the use of electric heating and cooling devices during peak periods (for example by changing air-conditioner settings)

This annex is based on “Smart Meter Customer Impact: Initial Proposals”, A report to the Ministerial Council on Energy Standing Committee of Officials, Energy Market Consulting Associates, Consultation Draft, 27 February 2009, http://www.ret.gov.au/Documents/mce/_documents/Customer%20Impact%20Report%20v5%2001.pdf.

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There is a particular concern that some customers 1) with higher underlying costs, 2) who are low income32 could face price increases, which presents a public policy issue.

In order to assess the impact of the reallocation of costs, the consultants examined pilot studies reported by EnergyAustralia and Integral Energy in NSW, and also undertook its own analysis of their data. EnergyAustralia’s reported study In November 2008 EnergyAustralia had over 400,000 manually read interval meters installed; more than 150,000 of its retail customers were on time of use (ToU) tariffs. EnergyAustralia found that using half hourly costs the underlying costs of service were higher than with profile costing for 25% of its customers, and similar or lower for 75%.

EnergyAustralia undertook a strategic pricing study to test customer responsiveness to time-related price signals in order to identify the potential network (avoided network capital expenditure) and retail (reduced wholesale energy purchase cost) benefits.

Participants in the study were divided into five

groups, namely those who:• • • • •

Were only provided with enhanced billing information Were put on a seasonal ToU tariff Were put on critical peak price (CPP) tariff with a low peak Were put on CPP tariff with a high peak without an in-house display Were put on CPP tariff with a high peak with an in-house display

There was a significant reduction in energy consumption by residential customer of between 5% and 7% on CPP days, which represented conservation rather than the time-shifting of consumption energy reduction levels were similar for winter and summer seasons. The response from businesses was much lower and less reliable.

There are a range of government measures and programs in place in each jurisdiction to assist those who have difficulty in paying their energy bills. The three relevant NSW government programs are:• Pensioner rebates • Life support rebates • Energy accounts payments assistance

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Integral Energy’s reported study The Integral Energy trial was conducted for the two-year period from 1 August 2006 from 31 July 2008.30 Over 900 residential customers had interval meters installed and were placed in one of three treatment groups, namely those who:• Were put on a seasonal ToU tariff • Were put on a CPP tariff • Were put on a CPP tariff and provide with an in home display which allowed customers to monitor their own energy usage A further control group of 360 customers remained on regulated tariffs set by the regulator IPART. All customers that participated in the trial were given $100 on joining the trial, and $200 on completion.

Integral Energy’s preliminary results compared the energy usage of those on a CPP tariff and those on a CPP tariff with an in home display (IHD) and showed that in the last 18 months of the trial:• The CPP customers exhibited a reduction in energy use in peak periods of 37% and a total energy reduction of 2.4% • The CPP IHD customers exhibited a reduction in energy use in peak periods of 41% and a total energy reduction of 3.6% Exhibits A2 and A2 show the effects of the various trial tariffs compared with the control groups for a hot summer day and a cold winter day. Exhibit A1

Integral Energy graph with preliminary results for pricing trial: average load profiles for control and treatment groups, for 11 January 2007

Note DPP = CPP.

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Exhibit A2

Integral Energy graph with preliminary results for pricing trial: average load profiles for control and treatment groups, for 15 June 2007

Note DPP = CPP. The preliminary results showed that on average the CPP IHD customers saved $300 over the two-year trial period, as compared to the control group. Of this, $200 was ascribed to being due to change in behaviour, while the remaining $100 was due to the more cost reflective nature of the tariff. The consultant’s analysis of EnergyAustralia’s data For EnergyAustralia, after data cleansing it had a total of 1.154 customers comprising:• • • •

241 on seasoned ToU 297 on CPP 289 on CPP with IHD 327 in the control group

Exhibit A3 shows in graphical form the underlying wholesale energy cost/unit calculated for each customer using 1) the profile33 based price, and 2) the actual cost of energy based on half-hourly market prices and interval meter data – the consultant uses the acronym COGS for “cost of goods sold”. The exhibit shows each of the observations in the sample, ranked in order of increasing interval-based cost of service.

The profile is the net system load profile and given the acronym NLSP.

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Exhibit A3

EnergyAustralia interval-metered sample for 2006/07: comparison of profile based and interval based wholesale energy cost per-unit

Exhibit A4 shows the data in tabular form. Exhibit A4

EnergyAustralia interval-metered sample for 2006/07 data: proportion of sample customers with wholesale energy cost more (less) than specified range from profiled-based COGS

For 34% of customers retailers would incur a wholesale energy cost that is 10% or more higher than the current profiled-based cost for that customer.

There was no statistically significant correlation between consumption and unit cost, but the usageweighted average cost from the EnergyAustralia sample was nevertheless 2% lower than the arithmetic mean of costs per customer, suggesting that larger customers did on average have slightly lower costs.

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Exhibit A5 combines in graphical form the wholesale energy plus network costs (which typically comprise around one-third of retail charges to customers) of the cost of service to show their aggregate impact, while exhibit A6 shows the data in tabular form. Exhibit A5

EnergyAustralia interval-metered sample for 2006/07: Sum of wholesale energy and network annual COGS by customer, interval/ToU and non-interval/non-ToU based COGS

Exhibit A6

EnergyAustralia interval-metered sample for 2006/07 data: proportion of sample customers with COGS (wholesale energy plus network costs) more (less) than specified range from non interval-based COGS

It appears that the load shape for customers with pensioner rebates is slightly more skewed towards peak use than for other customers on the different programs, but the effect is relatively modest. For example, for the top 15% of this group of customers the average annual amount by which their underlying cost exceeds the current profiled cost is $34 per customer.

Using the 2006/07 sample of customers with interval data (but who were not on ToU tariffs), the consultant analysed the potential cost impact if they were to be charged using EnergyAustraliaâ&#x20AC;&#x2122;s current ToU tariffs.

The standard tariff structure was an inclining block tariff (IBT), with a fixed charge of 59

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33c/day, and usage charges of 10.8377c/kWh for the first 1,750 kWh used in a billing quarter (91 days) and 14.7598c/kWh for electricity used in excess of that threshold. The ToU tariff was 22.5c/kWh in peak times, 8.1896c/kWh in shoulder periods, and 4.8623c/kWh in off-peak periods.

As is shown in exhibit A7, with EnergyAustraliaâ&#x20AC;&#x2122;s ToU tariff 13% of the customers have a cost that is more that 10% above the average, and 10% would have a cost more than 10% below the average. Costs would be more than 20% higher for only 1% of customers, and similarly, more than 20% lower for another 1%. Exhibit A7

EnergyAustralia sample for 2006/07: proportion of customers with ToU-based customer cost more (less)than specified range from average non-ToU based retail cost

The cost of service for customers with interval meters was lower for approximately 50% of customers and higher for the other 50%; for 30% of customers it would be more than 10% higher than the current profiled-based cost and for 16% it would be more than 20% higher. Conversely, for 25% of customers the underlying cost of service would have been more than 10% less than the current profiled-based cost. The cost of service is naturally greater for those customers with a greater proportion of their consumption in higher-cost periods.

Analysis of the set of hardship customers (viz those on federal, state and EnergyAustralia assistance schemes) found a much smaller variance in the cost of service with interval metering. A lower proportion of such customers was found to have an increase in cost of service (39% to 49% across the different samples) and the range of variance was markedly less; only 5% of EAssist customers, 10% of the state EAPA scheme customers and 15% of customers on pensioner support had an underlying cost of service that was more than 10% above the average profiled-based cost. 60

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The consultant’s analysis of Integral Energy’s data The Integral Energy pricing trial offered customers two pricing options: CPP with and without associated provision of an in-home display (IHD), and seasonal ToU (SToU). The average annual and per-unit costs cost for the control group and for each of the three treatment groups is shown exhibit A8. Exhibit A8

Integral Energy Trial, 2007/08 data: average and per-unit costs per customer

Note DPP = CPP Exhibit A9 shows the differences in annual customer costs for the three treatment groups, compared with the annual costs for the control group customers on the standard (inclining block) tariff. This shows annual costs which are on average $92 less for customers in the CPP treatment group, $139 less for those in the treatment group involving a CPP tariff together with provision of an in-home display, and no significant difference for customers with SToU pricing:• It does not appear that seasonal ToU tariffs lead to a reduction in per-unit retail costs to customers, suggesting that there was little if any price-responsive load shifting • Customers on CPP tariffs (with and without IHDs) appear to have a lower per-unit customer cost ($5 6/MWh respectively, or around 4%), which is a direct result of load reduction in the higher-cost CPP periods. The usage of the CPP group is around 50 kWh less in aggregate than the control group over the fourteen CPP periods that were called in the study period, which represents reductions of around 40% at these peak times, and results in savings of between $75 and $86 per customer p.a. • CPP tariff customers also used less energy than the control group. Consequently their annual bills were on average $92 (for CPP) and $139 (for CPP with an IHD) less than for the control group

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Exhibit A9

Integral Energy Trial, 2007/08 data: Annual per-customer average use and average cost in CPP peak periods

Note DPP = CPP. General customer impacts Customers facing higher per unit retail costs are characterised by:• Heavier than average use of air-conditioning for cooling during weekdays • Larger numbers at home during weekdays • Higher probability of being retired or otherwise reliant on pensions for the majority of income (which is related to the previous point) • A higher than average reliance on electricity for heating during winter and no access to mains gas • Living in non-metropolitan areas, as this is associated with lower income • Living in sub-regions with higher than average total heating and cooling requirements

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Annex 4

Meter functionalities considered in NERAâ&#x20AC;&#x2122;s Phase 1 Overview Report on smart metering for the Ministerial Council on Energy34

The functionalities that NERA assumed to be core for all smart meters are shown in exhibit A10, and those that were not recommended for inclusion in a minimum national functionality are shown in exhibit A11. Exhibit A10

Functionalities recommended for inclusion in a minimum national functionality

Most of these functionalities are recommended on the basis that the quantitative benefits outweigh the costs, even given uncertainty in the estimates and costs and benefits.

http://www.mce.gov.au/assets/documents/mceinternet/SmartMetering%20BAPhase2Stream1_overviewNERA2008030517595 7.pdf.

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Exhibit A11

Functionalities not recommended for inclusion in a minimum national functionality

There were a few functionalities where there is remaining uncertainty, as outlined in exhibit A12. Exhibit A12

Functionalities requiring further analysis

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Annex 5

Functionality - enabling direct load control via the smart meter infrastructure and facilitation of a connection with an IHD

Two of the functionalities that NERA concluded in Phase 1 which required further analysis due to the uncertainty as to their costs and benefits were functionalities 15, which provides an interface with other load control devices, and 16 which has the potential to provide DLC benefits similar to scenario 3, but within a smart metering infrastructure. As they both provide DLC capability they can be considered as alternatives to each other and only one should be included in the minimum national functionality. Functionality 16 also has the added feature of allowing for the connection of an IHD, which has the potential to enhance a customer’s demand response through the real time provision of information on a household’s electricity consumption. This capability is provided via an interconnection with a HAN. Adding functionality 15 The additional net benefit that may be realised from adding functionality 15 to the minimum national functionality is set out in the following tables. Exhibit A13

NPV of costs and benefits ($m) - functionality 15, national basis

The key features in relation to functionality 15 are:• Costs required at the meter • The interface does require a device to be installed on air-conditioners and pool pumps, in order to allow them to be remotely cycled by the smart metering system. This device must operate on the basis of whatever SMI communications technology and protocols are in place for a particular premises • This device is assumed to be installed only in new and replacement airconditioners and pool pumps for those household that choose to take-up a DLC tariff from 2009 • The costs of the device for air-conditioners is between $40 and $80 plus a further $40 to $80 for installation • 7.5% uptake rate for DLC is assumed under this functionality.

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Adding functionality 16: Interface to home area network using open standard Functionality 16 involves the inclusion in a smart meter of an in-home communications device (eg, Zigbee) to allow it to interface with in-home devices (including IHDs). This would allow consumers to establish a HAN that would communicate between any in-home device and display (including computers or air-conditioners) and their electricity meters. Functionality 16 may impact on the net benefits flowing from a smart meter by providing a DLC capability, and by allowing for customers to be provided with an IHD which may further enhance their demand response.

The results of our incremental analysis of the additional net benefit that may be realised from adding either functionality 16AB which does not have an in-home display, or 16C which incorporates an inhome display, to the minimum national functionality is set as follows. As noted at the beginning of this section we have considered separately the incremental net benefits associated with utilising the DLC capabilities of functionality 16 only and the incremental net benefit with utilising both the DLC capability and also providing an IHD. Exhibit A14

NPV of costs and benefits ($m) - functionality 16, national basis

The key assumptions underpinning the incremental analysis for functionality 16AB for the provision of a DLC capability only are as follows:-

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• There is a cost at the meter of incorporating the interface with a HAN estimated at between $10 and $12 per meter, but the inclusion of an interface with a HAN at the meter avoids the need to also include an optical port in the meter which saves between $1 and $1.5 per meter. The net additional cost at the meter of incorporating functionality 16 is assumed to lie in the range of $8.5 to $11 per meter • An open system in-home communications device (eg, Zigbee) would be incorporated in new and replacement air-conditioners and pool pumps in order to enable them to be remotely cycled within the HAN. The costs of this device are between $20 and $50 each plus an installation cost of between $40 and $80 • Since the DLC device is an open-system the difficulty of ensuring compatability with proprietary systems in different areas is avoided, so the higher take-up rate of 15% for DLC may be more realistic for this functionality than for functionality 15 • The back-end systems costs and on-going operational costs estimated for functionality 16 without an IHD are the same as those estimated for functionality 15 The estimated demand impact associated with the DLC capability only from functionality 16AB is the same as for functionality 15 for the lower bound, but higher than functionality 15 for the upper bound. The cost of achieving this demand impact is however higher for functionality 16AB than for 15. Although the installed device costs are lower for functionality 16AB, there is an additional cost at the meter for all customers that is not incurred under functionality 15.

Functionality 16C involves the HAN capability interacting with a smart thermostat rather than an open system in-home communications device (e.g. Zigbee). This again allows both a DLC capability and the provision of IHDs. The key features of 16C for the provision of a DLC capability are:• The additional net cost per meter is the same as for functionality 16AB and is between $8.50 and $11 per meter • The back-end systems costs and on-going operational costs for functionality 16 without an IHD are the same as those estimated for functionality 15 • The cost of a smart thermostat is estimated to be in the range of $50 to $100 • there are no additional installation costs associated with smart thermostats. Overall the installed device costs for 16C are below those assumed for 15 and 16AB • Smart thermostats are capable of interacting with both new airconditioners and existing airconditioners. Since there would be no additional costs associated with extending the DLC capability to existing air-conditioners for 16C both new and replacement and existing air-conditioners could participate in the DLC program. This increases the potential amount of MW that could be placed 67

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under DLC and therefore the potential demand impact compared with functionality 16AB and functionality 15 • The costs of the smart thermostats are only incurred for those customers who sign up to a DLC program As a result of the above assumptions, the potential demand response available from a DLC capability underpinned by smart thermostats (ie, functionality 16C) is greater than for functionalities 16AB and 15, since it can be applied to both new and existing air-conditioners. The device costs are also estimated to be lower for functionality 16C. Additional Impact From Provision of an IHD Functionality 16AB and functionality 16C would facilitate the provision by retailers of an IHD which has the potential to enhance customer demand responses. There is, however, a great deal of uncertainty regarding the extent of this additional demand impact; in particular it is difficult to isolate the incremental impact of IHDs on demand. The Consumer Impact report prepared by NERA for workstream 435 contains a comprehensive summary of information available from a range of studies and trials, both in Australia and overseas. This summary indicates that the evidence of the impact of IHD on customer demand is very mixed:• Preliminary findings from the trials conducted by EnergyAustralia and Integral in Australia had indicated no statistically significant difference in behaviour in relation to CPP days from customers with an IHD and customers without. We understand that more recent results from the trials being conducted by Integral have found a significant difference in behaviour, with customers in the trial reducing their peak demand in CPP periods by around 5% greater than customers without an IHD • The trials conducted by Country Energy indicated that on-going education was important notwithstanding the fact that customers had in-home displays • In the United Kingdom Sarah Darby published a report in 2006 that reviewed the results of a number of studies relating to the effectiveness of feedback on energy consumption. One of the key findings of this review was that studies examining direct feedback through either a meter or a display monitor had observed savings of between 5 to 15%. However, the report cautioned against the difficulties in comparing studies given the considerable differences in sample size (only 3 in one case), the duration of the study, and additional interventions in some cases such as insulation or the provision of financial incentives to save

http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Metering%20CBA%20Phase%202%20Stream%204%20%20consumers%20-%20NERA%202008022920080304153026.pdf.

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â&#x20AC;˘ A trial undertaken by Hydro One in Ontario between July 2004 and September 2005 involving 435 participants who were provided with IHDs that measured and displayed their electrical consumption in both kWh and in monetary terms in real time. A control group was established and the participants in this trial were not provided with any additional educational material on electricity conservation. Participants were also not subject to time varying tariffs or CPP. According to Hydro One, participants in the trial were able to achieve aggregate reductions in consumption of 6.5%. For customers without electric heating the reduction was 5.1%. Since tariffs were unchanged in this trial the conservation effect represents a shift in the participantsâ&#x20AC;&#x2122; demand curves The cost of IHDs was estimated at $100 per device and the back-end costs associated with providing messaging services would be higher. They would only be provided to customers that take-up ToU tariffs, CPP or DLC. This leads to an assumption that between 45 and 60% of customers would have an IHD. Exhibit A15 presents the results of the incremental analysis for functionality 16 including an IHD. Exhibit A15

Assumptions for functionality 16 including an IHD

The lower bound, a zero demand response is assumed, so the inclusion of an IHD results in an increased cost, with no increase in benefits. The upper bound assumes an additional 7% conservation impact resulting from the provision of IHDs to those customers on ToU tariffs, CPP and DLC. A comparison of the key assumptions between functionalities 15 and 16 is shown in exhibit A16 together with a summary of the assumptions for scenario 3. Exhibit A16

Assumptions for functionalities 15, 16 and scenario 3

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NERA recommended that an interface to a home area network (functionality 16) is included as part of the national minimum functionality.

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Annex 6

Standards and interoperability

Exhibit A17 shows the various communications links and interfaces in a generic smart metering system. For some smart metering communications technologies there are no data concentrators are required – for example with point to point GPRS the wide area network (WAN) extends from the MDA back-end systems through to the meter. When data concentrators are used the WAN is from the data concentrator to the MDA back-end systems and the local area network (LAN) connects between the data concentrator and the meter. Exhibit A17 shows a schematic of this system. Exhibit A17

Smart metering system communications chain

At either end of the smart metering system communications chain the communications links (and interfaces) are standardised:• The interface to MSATS/B2B systems is an open standard – aseXML • Assuming that functionality number 16 is adopted, the home area network that connects the meter to in home devices could be an open standard, such as Zigbee For many smart metering systems the WAN (no. 2 in exhibit 20) is partially standardised as TCP/IP and is typically used for the lower layers of the protocol. However in many smart metering systems the application layer for the WAN is proprietary.

There are two main open international communications protocol standards that are applicable to smart metering. These are ANSI c12.22 in North America and DLMS-COSEM in Europe. NERA was advised that these protocols may not be entirely suitable for direct application to a smart meter rollout in Australia due to not supporting all the functionalities that may be adopted:-. • ANSI c12.22 defines a meter-to-communications interface (interface 4 in the above figure) and an application layer protocol. It requires that meters use ANSI c12.19 data tables and it provides an application layer to read or write data to those tables. ANSI c12.22 is not a standard yet but ANSI has 71

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advised Impaq Consulting that it is likely to be released in the next few months. This standard does not attempt to standardise all layers of a protocol used for the LAN or WAN. Hence it does not provide a means for interchangeability of smart metering hardware. It does however allow for the commands and instructions to be interpreted by complying smart metering systems in the same way â&#x20AC;˘ DLMS-COSEM, or Device Language Messaging Specification (DLMS) â&#x20AC;&#x201C; Companion Standard for Electricity Metering (COSEM), is specified in the IEC 62056 & 61334 series of standards. DLMSCOSEM specifies an application layer and interface requirements The consultant concluded that it would not be appropriate to simply adopt an existing open standard because it would limit the number of metering manufacturers with access to the Australian market, thereby reducing competition in meter provision.

Further consideration should be given to the

development within the Australian market of interoperability of meters with communications systems

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Annex 7

Costs, benefits, and net benefits

Assessment of costs The following six categories of transitional costs were estimated for each of the three smart meter rollout scenarios:1. 2. 3. 4. 5. 6.

Meters and their installation Communications Meter data and communications management Market operator systems to manage changes to market settlement information and new meteringrelated B2B transactions Retailer systems to support the retailer activities expected to be undertaken as a result of the rollout of smart meters in each scenario Distribution systems to support the distributor activities expected to be undertaken as a result of the rollout of smart meters in each scenario

In addition, an allowance has been made for programme management costs relating to the rollout of the smart metering infrastructure.

In addition to the initial transition costs, there will also be ongoing operating costs associated with smart meters and their associated infrastructure, including communications operating costs, namely:• Ongoing annual operational costs, based on a rate of 15% of the IT related transitional cost, and the operating costs associated of communications based on an estimate of an annual maintenance cost and backhaul data charges • A modem refresh for scenarios 2 and 4 and IT system refresh in 2020 of 40% of the original cost • The cost estimate for the cost of meters comprises between 48-62% of the total cost and is the largest cost • The meter installation cost is the second largest cost item for a smart meter rollout, accounting for between 18 - 23% of the overall transitional costs • The third most important cost category is distributor costs, which account for between 6 - 8% of overall transitional costs • The fourth most important cost category is the provision of communications with significant ongoing operational costs for communications where point to point services such as Global Packet Radio service (GPRS), or Public Switched Telephone Network (PSTN) (dial-up) or satellite are required. These are assumed to be required to a greater extent under scenarios 2 and 4. The range of communications costs reflects different assumptions about the technology adopted

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• For the first three years there may be increases in customer communications costs (an increase of $2 per customer p.a., call centre costs (an increase of $1.80 per customer p.a.) and other costs (an increase of $2 per customer p.a.) such as those associated with billing, dealing with customer complaints and general management time devoted to the rollout In aggregate, the increase in retail costs in scenario 1 is estimated to be between $89m and $101m in NPV terms, which is 2-3% of the total cost for rollout under scenario 1 in NPV terms.

In addition to a difference in the allocation of costs between scenarios, see exhibit A18, there is also a difference in the level of costs estimated for each scenario as a result of:• Differences in the infrastructure required (including communications infrastructure) • Differences in economies of scale and scope • Differences in the likely extent of competition in the provision of metering and data services (and the extent to which this competition is more effective than regulation in revealing efficient cost levels) Exhibit A18

Allocation of costs between scenarios

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Differences in communications infrastructure between scenarios A key difference between scenarios is the communications infrastructure that is needed to support the smart metering systems in each scenario:• For the distributor-led rollout (scenario 1), in urban areas it is assumed the communications infrastructure would be mesh-radio for a coverage of 97% with GPRS infilling the remaining 3%. In rural and remote areas the communications technology is assumed to be power line carrier • For the retailer-led rollout (scenario 2) and for the centralized alternative, the base case assumed was a mesh radio solution with GPRS for in-fill (20%) for urban customers, with GPRS for rural non-remote and PSTN (dial-up) access for remote customers. There is, however, uncertainty as to whether a mesh radio solution would be suitable under a retailer-led rollout, as it implies either a degree of cooperation between retailers or the involvement of a third-party communications provider able to obtain contractual certainty from the retailers sufficient to underwrite rolling out such a system Different scenarios also imply differences in the non-communications infrastructure required due to differences in the roles of the various parties under each of the scenarios, and therefore differences in the requirements for interfaces between the parties. For example, under the distributor-led scenario (scenario 1), distributors are responsible for managing communications with the meters. As a result, distributorinitiated transactions (such as providing quality of supply information collected by the meter) can be communicated directly to distribution operations, rather than needing to go through the ‘transactions manager’ business-to-business (B2B) hub. In contrast, under the retailer-led scenarios (scenario 2 and scenario 4) there would be a need for additional communications interfaces to provide this information to the distributors.

A key difference among scenarios is the number of meter data management (MDM) systems and meter data warehouses that are needed:• In scenario 1 there is one MDM system per distributor (in their role as meter data aggregator (MDA)) at a cost of around $9m to $12m each, and one meter data warehouse per retailer at a cost of between $4 and $6m each • In scenario 2, there is broadly one MDM system for each retailer (due to their responsibility for the provision of MDA services) and a meter data warehouse for each distributor. Given that there is assumed to be a smaller number of retailers acting as MDAs than there are distributors, this therefore results in a reduction in the overall costs of these two systems taken together • Under scenario 4, the costs are estimated to be lower again, as only two MDM systems are required (one for the National Electricity Market operator and one for the WA IMO), with a meter data warehouse for each distributor. Although the costs of the MDM systems are assumed to be higher in 75

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this scenario ($22m to $29m), overall the costs of the MDM and data warehouses taken together are lower There is a difference in the unit costs for meters estimated for each of the scenarios due to:â&#x20AC;˘ Differences in the assumed communications technology between scenarios, which affects the cost of meters compatible with that communications technology â&#x20AC;˘ Differences in the implications of communications churn and customer churn under the different scenarios, which affects the likely approach to integration of the communications modem within the meter for each of the scenarios Under scenario 1 it is assumed that the smart meter has integrated communications. This means that in the event that communications systems change the entire meter would need to be replaced. But it is unlikely that DNOs would choose to churn the communications system over the period of the assessment.

Under scenarios 2 and 4 retailers have the role of meter provider. In this scenario meters would be installed with separate communications, rather than being integrated, which provides maximum interoperability between meters and communication modems, such that where a customer changed retailer they would be able to also change either the meter, the modem, both or neither. This, in turn, provides retailers with flexibility to offer meter upgrades to customers as part of their competitive strategy, or to retain the existing meter (having reached a commercial agreement with the previous retailer to utilize the meter) but change the communications modem in order to utilise the new retailerâ&#x20AC;&#x2122;s communications network. The retailers may not have an incentive to install meters with separate communication modems, as providing such interoperability has implications for the extent of retail competition. As a result this may be an aspect of the rollout that would need to be mandated, if this rollout scenario were adopted.

In addition, under scenarios 2 and 4 a refresh of the modems is likely during the period of the cost-benefit assessment as retailers are likely to want to take advantage of developments in communications systems over the twenty year assessment period. Having a separate modem reduces the costs of this refresh as the meter itself does not need to be replaced. The cost of a meter with a separate modem under scenarios 2 and 4 is estimated to be around $20 to $45 higher than the cost of a meter with an integrated modem under Scenario 1.

The responses from meter vendors have indicated that costs per meter are unlikely to fall considerably for volumes above 250,000 units. The retailers supplying most Australian consumers are comfortably of this 76

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size. As a result there are no material differences in costs among the three smart metering scenarios for a particular technology.

A key distinction between the distributor-led and retailer-led scenarios is the assumption about the extent of competition in the provision of meters and metering data management services. Under the distributorled scenario the meters are owned by DNOs and purchased through competitive tendering processes. For the retailer-led scenario the retailer chooses whether to purchase and own meters, or contract with meter providers to provide metering services, which is likely to include data management services that may be provided competitively. Assessment of benefits The key business efficiency benefits to distributors are:• • • • •

The avoided costs of routine manual meter reading The avoided cost of special reads (e.g. when customers move into or out of a premise)36 The avoided costs of manual disconnections and reconnections Reductions in calls to faults and emergency lines Avoided cost of customer complaints about voltage quality of supply

Together these five benefits account for 67 to 74% of the total annual distribution business efficiencies identified on a national basis.

In addition, the ability of a distributor to obtain a particular benefit may also be affected by jurisdictional regulatory or legislative requirements. For example, in South Australia and Queensland a representative of the DNO must be present when a property is reconnected.

In New South Wales and Queensland the ability of smart meters to facilitate load management through a dedicated control circuit would be a benefit because the existing ripple-control systems present in those jurisdictions would not require replacement. There is a benefit from reduced post-storm restoration costs ranging from 2-6%.

The estimates provided for the avoided cost of special reads relates to activity-based costing information provided by DNOs, or to DNOs’ published charges. These cost estimates do not reflect the marginal cost of the service but are calculated on the basis of the total systems requirements to provide special reads (e.g. they incorporate the costs of the back-end systems and personnel that are also required). Marginal costs for a special read may be in the region of $4 per read.

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In relation to service quality improvements, the benefit from reductions in unserved energy as a result of quicker detection of outages and quicker service restoration times is a further 3 - 9% annual benefit in addition to the total national annual business efficiency benefits calculated. The potential business efficiency benefit to retailers resulting from the smart metering rollout are:• • • •

A reduction in call-centre costs after 3 years as a result of fewer high bill enquires A reduction in bad-debt and working capital requirements A reduction in hedging costs, due to interval data leading to improved forecasting Other cost reductions, including costs for data validation and settlement and management time

In total the reduction in retailer business costs arising from the introduction of smart meters of between $3.7 and $7.4 per customer, of which between $1.8 and $3.6 is an overall economic benefit (as distinct from a transfer). This implies total cost savings of $98m to $196m in NPV terms for retailers which is between 4 to 6% of the total estimated business efficiencies.

The business efficiency benefits are expected to be largely the same across all scenarios. The key exception is the benefits for DNOs associated with the reduction in calls to faults and emergencies, the reduced cost for post-storm restoration and the avoided cost of customer complaints about loss of supply that turn out not to be loss of supply it was assumed that only 50% of the benefit estimated from scenario 1 arising from meter loss of supply detection functionality would arise in scenarios 2 and 4. Avoided metering replacement costs represent between 39 - 44% of the overall benefits estimated. Demand response benefits Smart meters have the potential to influence customer demand via two mechanisms:• Through the introduction of time-varying tariffs; and/or • Through the direct control of certain appliances in key periods Such reductions in customer demand lead to the following potential benefits:• • • •

Deferral of the need for peak network augmentation Reduction in retailers’ hedging costs as a result of reductions in peak wholesale prices Deferral of peak generating capacity and reductions in the level of unserved energy Generation operating costs and carbon emissions, as the result of changes in the pattern of electricity market dispatch

The first three of these benefits depends on the impact of a smart meter rollout or of a nonsmart meter DLC rollout on the level of peak demand, either at times at which the network is constrained or at times 78

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of peak wholesale prices.

The fourth category of benefits depends on the impact of a rollout on the

timing of demand (i.e. whether demand is shifted from peak to off-peak periods, simply reduced in peak periods, or reduced in both peak and off-peak periods), which in turn impacts the pattern of electricity market dispatch.

In estimating the impact of a smart meter or DLC rollout on demand it is necessary to make assumptions on the following: • The tariffs that will be offered by retailers following the rollout of smart meters or a DLC alternative • The expected take-up rates for those tariffs • The change in customers’ demand profile in response to the tariffs offered Network deferral is a significant driver of the overall demand-side benefits. The potential extent of network deferral was based on valuing each kVA of demand reduction (at between $130 to $165 per kVA, depending on the jurisdiction) and discounting it by 25% to reflect the uncertainty surrounding the extent of network deferral that may actually be expected to accrue. Taken together, these assumptions imply that 67% of the total implied kVA reduction translates into a deferral of network augmentation. While every kVa of demand reduced by DLC can be considered firm because it can be dispatched by the DNO, demand response from ToU tariffs and CPP, by contrast, is not firm. CRA has used a three-year delay of the demand response schedule was used to combine and simplify the impact of these considerations in assessing the network benefit of demand response from DLC and ToU tariffs and CPP. There is no difference in the demand-related benefits across scenarios. Assessment of net benefits for particular circumstances The national assessment of net benefits is shown in exhibit A19. The results of the cost-benefit analysis for the different jurisdictions varied depending (among other things) on their climate and their network conditions.

Thus Victoria’s DNOs have strong networks, but South Australia has suffered from

significant summer maximum demand network constraints that have, in recent years, led to forced outages in isolated areas. South Australia has particularly peaky summer load driven in part by a growth in the use of air-conditioners with a penetration of about 85% and increasing. The results of the costbenefit analysis for South Australia show that for a rollout of smart metering under the distributor-led scenario (Scenario 1) to have a net positive benefit, it is necessary to have costs at the low end of the range. A DLC rollout may be more effective in reducing peak demand (as a result of the avoidance of customer fatigue on consecutive peak days), and so Scenario 3 may be more appropriate. 79

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Exhibit A19

Summary of Results by Jurisdiction â&#x20AC;&#x201C; per meter point (NPV, $)

Exhibit A20 presents the stakeholder breakdown on an aggregate basis across Australia. It is apparent that no rollout scenario is always net positive to all stakeholders and that there are winners and losers amongst stakeholders depending on the scenario and the actual level of costs and benefits achieved.

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Exhibit A20

Stakeholder breakdown â&#x20AC;&#x201C; national (NPV, $m)

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Differences in costs between urban, rural and remote areas Exhibits A21 presents the breakdown of the national cost-benefit analysis for urban and rural/remote areas for the three smart meter rollout scenarios. Exhibit A21

Urban and rural/remote breakdown - national total NPV ($m)

On a per meter point basis, meter costs are higher in rural and remote areas compared to urban areas. The national weighted average costs for meters with integrated communications is between $136 and $190 for meters compatible with the mesh radio network assumed for urban areas, but rises to $168 to $184 for meters compatible with PLC, which is assumed for customers in rural and remote areas under Scenario 1. 82

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Under Scenarios 2 and 4, the difference is even more pronounced because the meters used would have separate communications. The national weighted average cost for this type of meter is between $164 and $234 for meters compatible with mesh radio (i.e. the majority of urban meters) and $209 to $320 for meters compatible with GPRS (i.e. the majority of rural/remote customers).

There are differences in the communications technology assumed for customers in urban, rural and remote areas, under each of the smart meter rollout scenarios. These differences are summarized exhibit A22. Exhibit A22

Communications technologies assumed

The avoided costs of routine meter reading are $6.45 per meter point for urban areas, $11.64 per meter point for rural areas and $26.99 per meter point for remote areas. The avoided costs for routine reads are higher per customer for rural and remote areas. The value of avoided costs for special reads on a per meter point basis, $7.01 for urban areas, $12.51 for rural areas and $32.24 for remote areas. The avoided costs for special reads are higher per customer for rural and remote areas.

The avoided costs for connections and disconnections on a per meter point basis are $2.31 for urban areas, $4.03 for rural areas and $10.25 for remote areas.

The avoided costs for connections and

disconnections are higher per customer for rural and remote areas.

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The value of avoided costs from reductions in calls to faults and emergency lines per meter point are $1.79 for urban areas, $3.26 for rural areas and $8.83 for remote areas. The avoided costs for a reduction in calls are higher per customer for rural and remote areas.

The avoided costs of investigating customer complaints about voltage-related quality of supply per annum are on a per meter point basis $1.72 for urban areas, $3.09 for rural areas and $8.28 for remote areas. The avoided costs are higher per customer for rural and remote areas.

Overall, total business efficiency benefits on a per meter point basis are estimated to be greater for rural and remote customers compared to urban customers, $495 per meter point for rural/remote customers versus $222 per NMI for urban customers in the low benefits case and $646 per meter point for rural/remote customers versus $293 per meter point for urban customers in the high benefits case.

The net benefit per meter point is greater for customers in rural and remote areas than it is for customers in urban areas, and ranges in NPV terms from $300 to $821 in Scenario 1 for customers in rural and remote areas compared to -$59 to $251 per meter point for customers in urban areas.

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Annex 8

Network benefits and operational costs37

Exhibit A23 below shows the value of the quantified network benefits of scenario 1 at a national level, by major category. Exhibit A23

Value of the quantified network benefits of Scenario 1 by major category

The avoided cost in exhibit is the annual value of avoided new and replacement metering that would be required in the first year of the assessment period, in the absence of a smart meter rollout. This includes both the meter costs and installation costs. The value shown here assumes that all new and replacement metering would have been accumulation meters.

The largest benefits are those from avoided meter costs, meter reading and demand response. This is consistent with the business cases for smart metering in many overseas jurisdictions. Exhibit A24 below provides an overview of the lower and upper bounds of benefits by jurisdiction.

Cost-benefit Analysis of Smart Metering and Direct Load Control, Stream 2: Network Benefits and Recurrent Costs, Phase 2 â&#x20AC;&#x201C; Consultation Report, CRA International, 27 February 2008. http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Metering%20CBA%20Phase%202%20Stream%202%20%20Networks%20-%20CRAI%202008020320080304152554.pdf.

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Exhibit A24

Overview of the lower and upper bounds of benefits by jurisdiction

The proportion of total benefits in each jurisdiction is broadly in line with the proportion of numbers of electricity customers. The exception to this is Western Australia, where the higher proportion of benefits is attributed to the fact that in WA in the absence of a smart meter rollout, substantial meter replacements will be required in the near term, and this major meter replacement programme is avoided if smart meters are rolled out instead.

The assessed value of benefits in urban, rural and remote areas is shown in exhibit A25 below. The proportion of customers that are in the remote category is much less than that for the rural category, and yet the assessed value of benefits is comparable. This is because, on a per customer basis, the avoided costs of manual services to remote customers are much larger than for rural customers. For example, meter reading, connections and disconnections all involve much longer travel time for remote customers, resulting in higher per customer avoided costs when these activities are automated with smart metering.

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Exhibit A25

Assessed value of benefits in urban, rural and remote areas

Exhibit A26

Assessed value of benefits per customer by jurisdiction

The following is a brief analysis of the variations between the three jurisdictions on which this report focuses:â&#x20AC;˘ New South Wales: most categories of benefits per customer are in line with the national averages in most areas. The avoided cost of manual connections and disconnections is somewhat less than the national average, since most DNOs in NSW do not perform a disconnection on customer move-out â&#x20AC;˘ Victoria: per customer benefits are lower than the national average, due mainly to lower avoided costs of new and replacement metering (driven by a lower proportion of off-peak customers), less reduction in cost of calls to faults and emergencies lines, and lower demand response benefits

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â&#x20AC;˘ South Australia: per customer benefits are lower than the national average, mainly due to much lower costs for special reads (15% of the national average driven by lower property churn, and much lower reading costs), lower costs for routine meter reading, lower avoided costs of new and replacement metering (driven by a lower customer growth rate), and less reduction in costs of calls to faults and emergencies lines

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Annex 9

Key points from the KPMG report on “Retailer Impacts”38

Summary and conclusions “Available evidence suggests that it would be optimistic to assume that, just because smart meters will enable retailers to introduce more cost reflective tariffs reflecting each customer’s load profile, this will happen broadly across small customers in the foreseeable future. The technology lowers the barriers to retailers introducing such tariffs, but the benefits for many customers might be too small to make it worthwhile for retailers to market those products aggressively. They may also meet customer resistance to the tariff changes that might logically be made.

The more likely outcome is that retailers offer more cost reflective tariffs to a significant minority of market, perhaps up to half of it, and also offer Direct Load Control “DLC” tariffs to a subset of these customers. It seems likely that the tariffs retailers offer will be different to what may be ‘ideal’ from the perspective of sending the most cost reflective prices signals possible to customers. This would be consistent with the need to produce offers to which customers are most receptive (i.e. are saleable in most competitive retail markets)”. The customer’s perspective of the electricity purchaser decision From the customer’s perspective the electricity retail purchase decision involves a transaction which is:• Of relatively low transaction value with an annual average for residential customers of 6600kWh costing Au$970. Energy accounts for 2.7% of household expenditure, so if the average customer were in a position to achieve a 10% reduction in their energy bills by switching retailer, this would reduce their household expenditure by 0.25%. Not surprisingly customers devote comparatively little attention to the electricity purchase decision (i.e. who to buy from and on what terms). Policymakers have known for many years that energy costs have traditionally had a low priority in these decisions. For example, in 1991 the International Energy Agency stated “most historical records of individual decisions on energy efficiency point to high implied discount rates – at least 35% - and in some cases, as much as 200%”39 • Of relatively low emotional value. Electricity is what marketing professionals often describe as a “low involvement” product, which the retailers interviewed confirmed

Cost-benefit Analysis of Smart Metering and Direct Load Control Smart Metering – Workstream 3: Retailer Impacts – Phase 2 Consultation Report, MCE, March 2008. http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Metering%20CBA%20Phase%202%20Stream%203%20%20retail%20-%20KPMG%202008030320080304152737.pdf. 39

International Energy Agency, “Energy and Environment Series: Energy Efficiency and Environment”, OECD, Paris 1991, p83.

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A report by the UK Department of Trade and Industry presented market research on switching suppliers, for a number of products with similarities to energy40, and stated in relation to energy that:“Consumer interest in these markets is low, and switching has been primarily triggered by proactive sales visits/approaches from energy companies and by the familiarity of some suppliers…”. The report also expressed some surprise regarding the levels of switching in energy, given the limited economic benefits, stating:“Despite the relatively high levels of switching in-home energy, only nominal savings are expected as a result of switching in these markets”. The study found customers (for energy and mobile phones in particular) had difficulty comparing offers and interpreting information provided to them. For example, only 9% of energy customers (the lowest of the products in the survey) said that finding the best package for them was “very easy” and the qualitative research indicated that these findings were probably overstated. In the qualitative research “people struggled to interpret information on mobile phones as well as energy in a way that was personally relevant to them.”

These conclusions appear to be consistent with those drawn from behavioural

economics, which demonstrates that customers often rely on “intuition and rules of thumb to make decisions, often without perfect knowledge.” The retailer’s perspective on electricity retailing Retail operating costs (including margin) account for about 12% of the final price of electricity. The typical domestic electricity bill is about $1,000 per annum, on which the retailer makes about $50 per customer (before interest and tax), which leaves around $70 per customer for a retailer’s operating

The Department of Trade and Industry, ‘Switching Supplier’, a research study commissioned by the Consumer Affairs Directorate, November 2000.

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costs41. Small variations around the mean of costs can change that profitability considerably. For example, one retailer stated that “If a customer calls you more than a couple of times a year, you have probably just lost your margin on that customer”. Another retailer explained that for this reason “retailers really do not want their customers to care” about the product. Given the way the market currently works, the ‘ideal’ customer typically is one that:• • • •

Pays on time, ideally by direct debit Does not communicate frequently with the retailer Is disinclined to switch Is a relatively large user for electricity and gas because retailers typically recover the margin mostly in the unit price, which also partly explains why dual fuel customers are more attractive. Furthermore customer acquisition costs are largely independent of volume and of one or two fuels – so more volume and dual fuel is economically advantageous from the perspective of customer acquisition

The thin retailer margins constrains the degree to which they are in a position to offer differential tariffs. Energy retailing is therefore a service which, for the mass market, involves a low degree of customization and customer contact. Retailers tend to operate mass marketing campaigns and make their competitive offers very similar to existing offers to overcome customer inertia (e.g. similar tariffs, but with a discount). Australian retailers typically sell electricity door-to-door or over the phone via specialist

Estimated annual retailer operating cost-to-serve in Victoria (Au$):

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contractors and so offers must be saleable in these environments. The key constraints on retailers introducing any new tariffs include:• The cost of introducing and marketing a new product and the minimum numbers of potential customers required to make it commercially feasible • The minimum savings or other perceived benefits required to make it saleable to customers • The ability to identify, target and market to the relevant customers cost effectively A rollout of smart meters will enable retailers to introduce more cost reflective tariffs, but they will have to find ways to address these constraints. As one retailer summarized:“the key question a retailer will ask itself is: are more cost reflective tariffs going to increase the $50 margin I can make on the typical customer?” There was wide opposition amongst energy retailers to a mandatory rollout of smart meters because of a view that it “will not generate significant benefits in terms of demand side response (although some retailers saw that they might provide other benefits for customers). Retailers generally do not believe that customers will value or demand (in material numbers) the more cost reflective tariffs that smart meters allow. They also believe the associated demand reductions will be modest”.

“The typical view is that it is likely to be very difficult to sell retail products by focusing on tariffs as the customer does not understand them and is not interested in investing the time necessary to understand them. This is simply because their bills are not significant enough for them to care. One retailer stated our salespeople “never talk about tariffs when trying to win a customer” – all they do is offer the same basic offer, but with some alternative benefit. The retailer also stated that if you talk about tariffs “you are dead” in terms of making sales. Only one retailer indicated that it was likely to be proactive in using the new technology to introduce new tariffs. All others suggested that they would follow the market. Given that the vast majority of customers are reactive this is likely to mean that retailers will not be inclined to introduce more cost reflective tariffs across their customer base. Retailers therefore believe that it is likely to be an expensive way of targeting customers who might respond to more cost reflective tariffs.

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A report by the Essential Services Commission of South Australia found there was “no evidence that small customers would accept more complicated structures with the introduction of smart metering”42. They have also found low take up rates in certain jurisdictions where smart meters are voluntary. Unwinding the cross subsidies There are three types of more cost reflective tariffs that various parties have indicated smart meters might facilitate and which might lead to more demand side response:• Time of Use (ToU) tariffs. Smart meters will reveal the load profile cross subsidy inherent in current tariffs reliant on accumulation meters, which might allow non-incumbent retailers to ‘cherry-pick’ those customers who are currently paying too much on flat tariffs based on the net system load profile • Critical Peak Price (CPP) tariffs which send a more focused price signal about the costs of consuming at peak times • Direct Load Control (DLC) tariffs which typically provide a discount off an existing tariff offer Unwinding the load profile cross subsidy (see Annex 1) by offering more cost reflective tariffs has significant implications that would appear to be at odds with the conventional retail business model and customer preferences (i.e. simple retail product offers). And it creates losers who are likely to resist moving to ToU tariffs.

For the largest (and smallest) users the volume cross subsidy is likely to be material. For example, if the average user has a bill of Au$1,000, a variable charge of Au$900, and an average unit of price of 15c/kWh, they would be using 6,000 kWh per year. The typical Au$50 per customer EBIT margin would therefore account for 0.83c/kWh of the unit price. This means that the customer whose consumption is 50% greater than the average user is paying a margin of $75 per annum (I.e. or 50% more than they ‘should’), while the customer whose consumption is 100% greater than the average user is paying a margin of Au$100 per annum (ie. double what they ‘should’). Conversely, small than average users are typically paying too little. There is a particular issue with subsidies to households with airconditioning:• The Victorian Essential Services Commission has estimated that the cross subsidies between those domestic customers that do not have air conditioning and those that do, could be as much as $200 per customer per annum

Energetics, Electricity Pricing Structures for Customers with Interval Meters, Public Report for the Essential Services Commission of South Australia, March 2003.

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• Work by EnergyAustralia for its network area suggests that the average non-air conditioning customer is paying $70 too much, while the average air conditioning customer who is paying $86 too little43. Other work by EnergyAustralia suggests that for some load shapes it:“would expect energy costs (at least for retailers, if not customers) could double from their current level. This reflects the fact that, historically, in NSW, up to 50% of the energy costs is driven by price spikes. This differing exposure to price spikes is the key reason for variations in energy purchase costs between the three net system load profiles”. • Charles River Associates in work for Integral Energy on the impact of air conditioning on its network concludes that the cross subsidy might be in the range of $80-110m p.a., which equates to between $110-151 per customer p.a.44 The consequences of the cross subsidies are that:•

“If, for example, there are a relatively large number of customers currently paying a relatively small amount of money to a few large winners, then it might take longer for the cross subsidy to be unwound, or it might only be unwound for a relatively small group of customers. This is because non-incumbent retailers may be less able to offer significant enough savings to these newly profitable customers for it to place significant pressure on the incumbent retailer to rebalance its tariffs. The incumbent is likely to reprice the customers who are the major beneficiaries of the subsidy, but other retailers are unlikely to compete for these customers in the shorter term because their prices will have to increase first

• If, however, there are a small number of customers paying a relatively large amount of money to a relatively large group of small winners, then there is likely to be greater pressure for the cross subsidy to be unwound. This is because the non-incumbent retailer is more able to offer significant enough savings to these newly profitable customers to get them to switch, and thus place more pressure on the incumbent to respond accordingly. In the first instance, removing the cross subsidy will lead to lower bills for these customers which may influence their incentive to respond to the price signals, but presumably only in the short term” “It is optimistic to assume that just because smart meters will enable retailers to introduce more cost reflective tariffs, this will happen broadly across the customer base in the foreseeable future because the benefits for many customers may be too small to make it worthwhile for retailers to pursue45. They may also meet customer resistance to the necessary tariff changes. The more likely outcome is that retailers offer more cost reflective tariffs to a small but significant segment of the market, including CPP to a 43

EnergyAustralia, Increasing Block Network Tariff: Follow-up presentation to IPART’s Pricing Issues Consultation Group, 18 June 2003. This would appear to relate to energy costs only. 44 Charles River Associates, Impact on Air Conditioning on Integral Energy’s Network, May 2003. This would appear to relate to network costs only. 45 Just because smart meters reveal the load profile cross subsidy, does not necessarily mean that retailers will voluntarily offer ToU tariffs to win these customers because from the retailers’ perspective there may be more cost effective ways of unwinding the cross subsidy e.g. offering essentially flat rate tariffs, but with larger up-front discounts to the more attractive customers. But in this case, it is less obvious that this would provide much more cost reflective price signals, because the discount might not be in a form that links it to the customer’s profile in a way that is meaningful to the customer.

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subset of these customers. It also seems likely that the tariffs retailers offer will be different to what may be ideal from the perspective of sending the most cost reflective price signals possible to customers. This would be consistent with the need to produce offers to which customers are most receptive”. The prospects for take-up of more cost reflective tariffs A number of variables, both from a retailer’s and customer’s perspective, are likely to influence the take up of these tariffs generally and by jurisdiction. For customers the key variables are likely to include:• The initial impact, if any, on the customer’s bill. From KPMG’s view it would be reasonable to assume that:*

for bill savings of greater than (say) 10% a majority of customers will be prepared to move and thus create a competitive threat to the incumbent retailers

for bill savings of between (say) 5-10% a significant majority of customers will be prepared to move

for bill savings of between (say) 0-50% a minority of customers will be prepared to move

• The customer’s willingness to take more price risk • The customer’s willingness to switch for savings or prospective savings dependent on behavioural change • The complexity of the offers and how easy it is for the customer to respond • How the information about usage is communicated to customers • Environmental concerns The key issue for retailers is whether offering more cost reflective tariffs is going to assist in enhancing or maintaining margins. If they are not, then they are not likely voluntarily to offer (i.e. actively sell) more cost reflective tariffs. For retailers the key variables that may influence their margins are likely to include:• The extent of the load cross subsidy and its distribution • Customers’ willingness to switch for savings or prospective savings dependent on behavioural change • The costs of introducing more cost reflective tariffs • The benefits of introducing more cost reflective tariffs in terms of customer retention/winning new customers, and managing exposure to wholesale price risk 95

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KPMG think it is reasonable to expect that:• Some non-incumbent retailers will target those customers who will save significant amounts (i.e. above 10%) of money under more cost reflective offers and actively sell these tariffs to them • Incumbent retailers to watch market developments closely and be prepared to start offering more cost reflective tariffs to these customers relatively quickly if it became apparent that they risked losing a significant number of their (newly) more attractive customers It would not be unreasonable to assume that up to about 30% of customers would end up on ToU tariffs, which is at the high end of the range of the retailers’ views and therefore may be somewhat optimistic.

CPP tariffs are likely to be more effective in sending a more precise signal to encourage demand response which could lead to larger savings for more targeted customer responses, but:• The majority of the benefits will flow to customers willing to alter their behaviour, but wanting to retain the flexibility to decide if and when they do it • The benefits for retailers are likely to be primarily about retaining existing customers and winning new customers who are in this part of the market (i.e. price sensitive and willing to change behaviour • Overall these offers are unlikely to be particularly margin enhancing for the retailers except to the extent it results greater market share • Retailers are unlikely to derive significantly greater value from CPP tariffs because any demand reductions are likely to take time to realize and are not particularly firm The key variables on the customers’ side that are likely to influence the up-take of CPP tariffs are:• The potential impact in their bills • The customers’ willingness to accept price risk • The complexity of the offers and how easy it is for the customer to respond The key variables on the retailers’ side that are likely to influence the up-take of CPP tariffs are:• The number of customers willing to take price risk and accept more complex offers, but wanting to maintain control of their consumption decisions • The attractiveness of these customers • The costs of introducing more cost reflective tariffs Based on discussions with retailers and the market evidence, it might be reasonable to assume that the take-up of CPP tariffs is not likely to be more than 10% for the following reasons:-

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• There is limited evidence to suggest that the majority of customers are willing to bear significant electricity price risk • Even if they were prepared to accept price risk, with the intention of saving money by altering their behaviour, the additional savings are likely to be relatively modest for the typical customer (perhaps about $50 p.a.) Retailers are more likely than customers to ‘drive’ the take-up of DLC tariffs, using this approach as a marketing tool to provide upfront savings to win some customers, as this is similar to how the market currently works. Based on discussions with retailers and the market evidence, it would be reasonable to assume that the take-up of DLC tariffs is not more than 10%. Effect on the level of competition Based on the information currently available, KPMG’s view is that smart meters are likely to increase the degree of competition in the market, but only modestly. The reason for this view are that:• In the first instance, smart meters only change the types of customers that are most attractive to retailers (e.g. from large users to large flatter profile users) • Smart meters may, however, also increase the degree to which the relevant customers are attractive to retailers. This is because it may reveal a cross subsidy that is larger and for a greater proportion of customers (i.e. it can provide the basis for providing larger discounts to some customers that are likely to encourage more switching) But the willingness of customers to switch more broadly may limit the extent of this effect if they are obliged to take more price risk. Where switching levels are already relatively high, the incremental benefits might also be too modest to encourage significantly more switching.

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Annex 10

Customers impacts of smart metering46

Focus groups’ findings The customer focus groups canvassed participants’ views as to their willingness to adopt alternative tariff structures (including DLC), see Annex 11. A consistent finding across all of the focus groups was that participants were much more willing to consider a DLC tariff option compared to other alternatives. Participants viewed DLC options as providing them with a way to ‘do the right thing’ and reduce electricity consumption without needing to think about it and in that respect it not impacting their lifestyle. The fact that they would also reduce their electricity costs and receive a payment for adopting DLC was viewed as a bonus.

In contrast to their willingness to consider DLC, the vast majority of participants did not see much benefit to them in adopting CPP. Views included that the need to change behaviour to avoid CPP prices would impact on people’s way of life and that only the ‘naive’ or ‘greeny’ would do so. Participants commented that they could leave the house (eg, go to a shopping centre) in order to avoid CPP events, but that they would have no incentive to adopt this form of tariff in the first place. The 5 % discount offered on tariffs at off-peak times was considered to be too low to outweigh the disadvantages and the potential risks of a high electricity bill. • High income earners commented that they may choose to run certain appliances at off-peak times (washing machines, dishwashers) and that they may become more conscious of general electricity usage • In contrast, lower income earners saw ToU tariffs as an opportunity to try to further reduce their bills Australian and foreign trials and studies of critical peak pricing • Country Energy in NSW found that it achieved a 25% reduction in demand on CPP days and an 8% reduction in overall energy consumption. Preliminary results in the trials conducted by EnergyAustralia and Integral in NSW found a conservation effect in summer CPP periods of between 7 and 15%. Preliminary results indicate that the reduction in peak demand outlined above is statistically significant, but both trials have reported that the conservation of energy dominated the deferral effect • In Victoria the potential reduction in residential peak demand resulting from CPP has been estimated at between 8 and 18 % (CRA, 2002 based on an end-use model) and 20 % (ESC, 2002, based on an 46

Cost-benefit Analysis of Smart Metering and Direct Load Control Work Stream 4: Consumer Impacts Phase 2 Consultation Report, NERA, Report for the Ministerial Council on Energy Smart Meter Working Group, 29 February 2008.

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own use elasticity of -0.1). In South Australia work by CRA in 2004 found the potential for a 10 % reduction in peak demand using a smart meter with CPP • The Statewide Pricing Pilot (SPP) in California is one of the most comprehensive international trials of ToU pricing, CPP and enabling technology that has been undertaken recently. The Pilot found a 13% reduction in peak demand and a 2.4% reduction in overall consumption on summer critical peak days, while for winter critical peak days the reductions were 3.9% in peak demand and 0.6% in overall consumption. The Pilot found that reductions in peak demand were achieved largely as the result of demand shifting to non-critical peak periods, with only low levels of conservation achieved overall • The Ontario Smart Price Pilot found reductions of 17.5 % in peak demand for the CPP group and 25.4 % for the critical peak rebate group. On non-CPP days there was an 8.5 % reduction for the CPP group and 11.9 % for the critical peak rebate group. Overall consumption was reduced by 7.4 % for the CPP group. Results for the CPP rebate group were not statistically significant • Ofgem in the UK has estimated a 2.5% reduction in peak demand associated with CPP and a 1% reduction in overall consumption Australian and foreign studies of ToU tariffs • Integral Energy in NSW found no statistically significant difference in the response of participants paying seasonal ToU tariffs relative to the control group • Energex in Queensland found no change in peak demand as a result of the introduction of ToU tariffs only, but found a 12 % reduction in peak demand and a 13 % reduction in overall consumption for residential customers on ToU tariffs who were provided with timers for their appliances that enabled them to be turned off between 4.30pm to 8.30pm. They found a 34 % reduction in peak demand for customers on ToU tariffs with DLC. As in California (see below), Energex found no response from customers that were only provided with information on energy efficiency • CRA and Impaq Consulting in 2005 calculated a 10 % reduction in peak demand in Victoria using elasticities drawn from the Californian Pilot and assuming a 100 % take-up of ToU tariffs • In Tasmania, the Office of the Tasmanian Energy Regulator estimated a 10 % reduction in peak demand using smart meters with ToU tariffs. This estimate was based on customer responsiveness factors that were developed using the observed response of customers in Tasmania to Aurora Energy’s pay as you go ToU tariffs • Trials of demand management conducted by ETSA Utilities in South Australia found a 17 % reduction in peak demand from direct load control of airconditioners of residential customers • The Californian Pilot found a 4.7 % reduction in peak demand in summer for non-critical peak days and a 0.17 % overall increase in consumption, whilst for non critical peak days in winter they found a 1.4 % decrease in peak demand and a 0.02 % reduction in overall consumption. The Californian Pilot included an information group that faced a standard flat tariff but were provided with information on how they could reduce load during peak periods, and were also informed of CPP periods and

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requested to avoid energy. The result from this group suggested that a demand response in the absence of a price signal was not sustainable. • The Ontario Smart Price Pilot found that the reduction in peak demand was not statistically significant, but that overall consumption was reduced by 6 % • Puget Sound Energy in the US found between a 5 and 6 % reduction in peak demand from ToU tariffs and a 5 % reduction in overall consumption • In Northern Ireland a 10 % reduction in peak demand has been found from ToU tariffs with a 3.5 % reduction in overall consumption Estimates of elasticity The residential and commercial elasticity estimates based on the California Pilot study for each jurisdiction are set out in exhibit A27 - short run and long run elasticities are assumed to be the same. Exhibit A27

Elasticity assumptions

NERA’s analysis incorporated an adjustment to the elasticities for each jurisdiction where there are two or more consecutive CPP days, which results in a higher reduction in average energy consumption on the consecutive days (10% in summer and 5% in winter). This adjustment reflects an assumption that the daily-read capability of smart meters can be used to provide feedback to customers on ‘how they went’ on 100

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a CPP day, which may result in an enhanced response on a consecutive CPP day. This is an upper estimate of potential additional demand response on consecutive CPP days (the lower estimate being zero). A number of studies have indicated that commercial customers are less responsive than residential customers to ToU tariffs and CPP. NERA therefore assumed that the elasticity of substitution for commercial customers is zero. In the short run, commercial customers have also been found to be less responsive to daily electricity prices and NERA assumed that the price elasticity measure would be half of that attainable by residential customers on a non-peak day and that the same estimates would apply across each jurisdiction. The changes are shown for 2016, the first financial year in which the rollout of smart meters is complete across all jurisdictions in the modelling. Exhibit A28

Residential â&#x20AC;&#x201C; overall change in maximum demand and consumption (2016)

Exhibit A29 below sets out the peak demand reductions for small commercial customers on ToU tariffs. Exhibit A29

Commercial - estimates of the response to ToU for those customers on ToU tariffs (2016)

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Exhibit A30 presents the estimates of the overall change in small commercial consumption, given an uptake rate assumption for ToU tariffs of 40 %. Since the elasticity of substitution has been assumed to be zero for small commercial customers and the price elasticity does not vary with the time of day, their response to ToU tariffs is uniform across the day and thus the results are presented as a change in daily consumption. Exhibit A30

Small commercial customers â&#x20AC;&#x201C; overall change in maximum demand and consumption (2016)

Finally, exhibit A31 shows the estimated impact of the introduction of ToU and CPP tariffs to the total jurisdictional maximum demand and energy consumption. Exhibit A31

All customers - overall change in maximum demand and consumption (2016)

The overall impact on jurisdictional load is much smaller than is the case for customers facing ToU or CPP tariffs. This is unsurprising, since the consumption of these customers accounts for only a fraction of the demand in each jurisdiction. Assuming a higher demand and conservation response gives the following impact.

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Exhibit A32

Demand impact of high demand response case residential – overall change in maximum demand and consumption (2016)

Exhibit A33

Demand impact of high demand response case all customers – overall change in maximum demand and consumption (2016)

The demand side response with DLC is based on assuming retrofitting a DLC control device to the existing stock of air conditioners and incorporating one. The assumptions are as follows:Comparative energy consumption Cycling strategy Take up rate Proportion of trial participants that may not be at home during the trial Number of days and terms of direct load control Event

Selection criteria for direct load control event days

1.9 kW 50% 10% (20% high case) 10% Up to 15 days with direct load control event extending for a maximum of six hours 8 events in NSW, 15 in NT, 14 in Qld, 15 in SA, 0 in Tas, 15 in Vic and 15 in WA. Above 30° Celsius and the maximum demand levels reached on those days were in the top 5 percentile of the jurisdiction’s 2006/07 load duration curve; or the wholesale prices reached on those days were in the top 5 percentile of prices paid in the jurisdiction over 2006/07

The results for a 20% take up rate are shown in exhibit A34. 103

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Exhibit A34

Estimated half hourly demand reduction attainable during DLC events with a 20 % take up rate (MW)

A similar procedure was used for pool pumps. Increase in demand response associated with in-home displays Preliminary findings from the trials conducted by EnergyAustralia and Integral indicated no statistically significant difference in behaviour in relation to CPP days from customers with an IHD and customers without. More recent results from the trials being conducted by Integral, however, have found a significant difference in behaviour, with customers in the trial reducing their peak demand in CPP periods by a greater amount than customers without an IHD, by around 5%, see Annex 3.

Trials conducted by Country Energy, in which customers were given a smart meter, indicated that ongoing education was important notwithstanding the fact that customers had in-home displays. This may suggest that any general demand response associated with the provision of an in-home display may not be maintained in the longer run, in the absence of continuing customer education.

According to the results of a UK study involving energy consumption displays attached to stoves, customers who were provided with the display were able to achieve average reductions in energy usage of 15.2 % while those who were provided with the information packages were able to achieve average reductions in energy usage of 3%47. The authors of this study further found that while the information pack group were more aware of energy-savings behaviours they did not appear to actually adopt those behaviours. The authors concluded that this demonstrated that the display increased motivation to modify energy usage relative to what otherwise would have been achieved with information only. However, this study only covered 41 customers.

G. Wood, M. Newborough, Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design, 17 November 2002.

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A report prepared for the Californian Information Display Pilot Technology Assessment also contained a review of in-home display studies extending back from 198648. This review found that customers were able to achieve savings of 4 to 11 %. The in-home display studies referred to in this report included: • A study of in-home displays undertaken in Canada and California in 1986 that resulted in conservation of 4 to 5 % in Canada but no change in consumption in California • The UK study cited above pertaining to stoves • A Northern Ireland trial involving prepayment meters with a display that resulted in reductions of 11 % when participants were provided with instructions and 4 % when no instructions were provided It is worth noting in this context that:• The results presented for the Northern Ireland trial differ from those cited in the Ofgem “Domestic Metering Innovation” report which stated that a recent ToU trial involving 186 participants resulted in peak reductions of 10 % and conservation levels of 3.5 % and an earlier trial involving 100 participants achieved average reductions in consumption of 3 %49 • In the UK in 2006 Sarah Darby published a report that reviewed the results of a number of studies relating to the effectiveness of feedback on energy consumption50 Change in demand and consumption from functionalities 15 and 16 Exhibits A35 and A36 show the incremental reduction in peak demand and the overall energy conservation associated with functionalities 15 and 16, compared to the base demand response case. The reductions relate to overall changes in consumption, rather than only for those customers on CPP and ToU tariffs. Exhibit A35 assumes 7.5% DLC uptake and no additional conservation effect, while Exhibit A36 is a high demand case assuming 15 DLC uptake and 7% additional impact.

Primen, Final Report – California Information Display Pilot Technology Assessment, December 2004, pp. 5-6.

Ofgem, Domestic Metering Innovation, 1 February 2006.

Hydro One Brampton Networks Inc., Conservation and Demand Management Plan, Annual Report to December 31 2005, p.7-8.

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Exhibit A35

All customers – incremental change in consumption assuming 7.5% DLC uptake and no additional conservation impact

Exhibit A36

All customers – incremental change in consumption assuming 15% DLC uptake and 7% additional conservation impact

Case studies assessing the bill impacts on different types of households on different tariffs The case studies examined were as follows:• • • • • •

Small family, low income Retired couple, low income Large household, high income Single unemployed occupant Large family, median income Single unemployed mother

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For each of the case studies NERA examined the effect on the household bill for a ToU tariff; a ToU in combination with a CPP tariff; and a ToU tariff in combination with participation in a DLC programme. The first case is summarised as follows.

A single mother lives with her two children in south eastern Queensland in a small three bedroom home that has mains gas, which is used for cooking and hot water heating; there is an air conditioner as well as a washing machine and dryer. The average annual consumption is 7980 kWh.

Exhibit A37 shows the change in the bill associated with each of the tariff products that have been developed for Queensland. The current bill is $1,188 with 40 % of total electricity consumed during the peak periods of 7am to 9pm on working days. Assuming no change in consumption profile, the shift to ToU tariffs would lead to a reduction in her annual bill of $27 for the year, around 2.3 %. The combination of a CPP tariff with a daily ToU component is estimated to result in a slightly greater effect, reflecting the discount for off-peak electricity, see exhibit 8.25. Exhibit A37

Estimated bill with no change in demand

The CPP results in a larger bill saving compared to the ToU tariff as more electricity is shifted from the critical periods into the relatively less expensive off peak periods. Peak demand reduces by over 4 % as a result of the change in tariffs; for ToU alone the peak reduction is 3.6 %. The results are shown in exhibit A38. Exhibit A38

Estimated bill with demand response

Participation in DLC has no additional impact on consumption compared to the ToU tariffs alone â&#x20AC;&#x201C; reflecting that the air conditioner is not used during many DLC events because the woman is mostly at 107

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work during the day. The larger reduction in annual bill (10.5%) reflects the annual payment of $75 received for participation in the programme.

The estimated change in peak and off-peak electricity demand under each of the tariff product offerings is shown in exhibit A39; the highest decrease in total demand comes from a CPP and ToU tariff product, of approximately 0.5% above the ToU change. Exhibit A39

Estimated change in electricity demand

Estimates of the own price elasticity of demand One of the most recent studies in Australia of the long run price elasticity of demand was undertaken by the National Industry of Economic and Industry Research using time series data extending from 1980 to 1995. Separate estimates were developed for each jurisdiction in the National Electricity Market and for residential, commercial and industrial customers. The jurisdictional estimates are set out in exhibit A40. Exhibit A40

Long run own price elasticity estimates

The long run price elasticity estimates for alternative customer classes were:â&#x20AC;˘ -0.25 for residential customers â&#x20AC;˘ -0.35 for commercial customers â&#x20AC;˘ -0.38 for industrial customers A number of studies of the short and long run own price elasticity of demand have also been published internationally over the last ten years. The table below provides a summary of these studies which is based on the results of the reviews undertaken by the Productivity Commission in 2001 and IPART in 2003. 108

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Exhibit A41

Summary of recent international studies

Summary of results from trials and jurisdictional reviews Table A42 and Table A43 provide a summary of the estimated elasticity measures and assumed reductions in peak demand and consumption flowing from each of the jurisdictional reviews, practical trials and elasticity studies outlined in the preceding sections. The range of short run elasticity measures is wide for both residential and commercial customers, specifically:â&#x20AC;˘ For small to medium sized businesses the short run elasticity measures range from -0.004 to -0.24 with a large number of observations centred around -0.02 to -0.04 â&#x20AC;˘ For residential customers the short run elasticity measures range from -0.011 to -0.79 although differences can be observed between the ranges established for trials undertaken in relation to CPP, ToU tariffs, direct load control and enabling technologies and academic studies

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Exhibit A42

Summary of results for small to medium sized businesses

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Exhibit A43

Summary of residential customer results

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Annex 11

Results from focus group studies

Objectives of the study Marketing consultant Red Jelly was commissioned by NERA to run a series of focus groups51:• To briefly understand the customer context in terms of appliance usage and electricity consumption which will directly impact on and explain responses to smart meter functions • To gauge current involvement and levels of awareness and perceptions of electricity costs, issues related to electricity supply that impact on reactions to smart meter price offers • To explore customer reactions to the overall concept of smart meters • To explore customer reactions to a range of different individual smart meter price offers, in order to identify those offers with the greatest perceived benefits and appeal and potential to impact and change customer consumption behaviour, namely:* * * * * *

triggers and barriers to appeal potential customer acceptance perceived benefits for them as a customer, and drivers of these perceptions anticipated behaviour change as a result of the offer; what would people do differently information needs, types of questions specific offers raise for customer relevance of offer to consumer situation and needs

The key findings • There is a marked difference between the individual sense of responsibility to conserve energy and day to day behaviour related to saving electricity – at a day to day level the primary motivation for most consumers to save electricity is to save money on the bill rather than actually saving or conserving energy • Higher income earners acknowledge they could be doing more to save electricity. They were generally well read and media savvy on current issues; they openly admit they do not want to go without comforts or alter their lifestyle habits • Lower income earners were very much living ‘hand to mouth’ and often truly struggling financially. They are typically in survival mode and the electricity bill is a real burden. As a result they are generally already using an absolute minimum of electricity out of financial necessity, and often feel there is not much more they could do to save electricity. Energy saving light bulbs and switching appliances off at the power point when not in use were among the most common and popularly mentioned measures for saving electricity; both these measures were mentioned to have made noticeable savings for customers on electricity bills 51

Phase 2: Qualitative Assessment of Consumer Responses to the National Electricity Smart Meter Rollout Program, Full Qualitative Research Report (FINAL), Prepared by: Red Jelly for NERA, 25 January 2008. http://www.mce.gov.au/assets/documents/mceinternet/Smart%20Metering%20CBA%20Phase%202%20Stream%204a%20%20consumer%20focus%20groups%20-%20NERA%202008022220080304153216.pdf.

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• For those with air conditioning or a pool pump, direct load control (DLC) is the most appealing offer with the ability to save money, to save energy, and feel good, essentially without having to think or do anything. This offer was perceived as very much a ‘win win’ situation for all, including the environment and almost a ‘no brainer’ for some in the sense that why would not everyone take this up • The appeal of the ToU offer was almost entirely among customers who are not at home during peak period. It ensures minimal impact on household habits along with the opportunity to make savings during off peak times on a much lower tariff than the current standard tariff:*

some low and middle income earners perceived benefit from taking up a ToU offer, even if home during the day, but would be more reluctant about shifting certain household chores to outside peak times and generally not reducing the amount of electricity used

for those for whom ToU was relevant, and an offer they would consider on its own, then the combination of the ToU and DLC was ideal in terms of optimising cost savings as well as saving in energy usage due to the more efficient running of equipment on DLC

both the ToU with Critical Peak Pricing offer and the prepayment offer were the least appealing options overall, especially given the complete lack of perceived direct benefits or incentives for customers and based on the qualitative research sample, would have extremely low take-up

• The current regulated tariff in comparison to the other price options was perceived as simple, straightforward and easy among some high income earners, pensioners and those generally who resist change or who find choice overwhelming or time consuming. The rationale was that if you stay on the current tariff then there is no need to have to think about anything, and the old adage ‘if it ain’t broke don’t fix it’ was a common mantra for these customers

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Annex 12

Split benefits problem52

The benefits of smart meters in a market system are split between retailers, DNOs and customers, which makes it difficult for individual businesses to capture enough of the benefits to justify investment in smart meters while the customer benefit may not enter into their assessments. The benefits to a DNO are further complicated by the regulatory arrangement. Under a traditional framework any costs may be included in the regulatory asset base, while the benefits will accrue to the customers. As NERA concludes (Overview section 18.3.1):In practice…as the distribution businesses are subject to price regulation and regulators will seek to pass-through to consumers the benefits of the efficiency gains achieved by the distribution businesses in the form of lower network charges going forward...As a result it would still remain necessary to mandate a rollout of smart meters, as no one stakeholder group has a positive business case to undertake such a rollout as a commercial exercise. The split benefits problem is a major reason why the Victorian Government has committed to a mandated rollout of smart meters, and why MCE focused on the costs and benefits of national rollout and the DLC alternative.

Exhibit A44 provides a statistical breakdown of the costs and benefits of a smart meter and DLC rollout by stakeholder. Considering only first order impacts, the consultant’s calculations of a distributor-led smart meter rollout the total benefits available to the distribution sector outweigh the costs of a rollout, suggesting distribution businesses could make a business case without government intervention. However the second order effects, where prices adjust over the longer term and regulatory regimes remove efficiencies to pass and change in net benefits and costs through to customers, changes the picture:• Under a distributor-led roll out (Scenario 1) the first order net benefits were calculated by the consultants to be in the range negative $226m to positive $2.6bn, which initially suggests that some distributors may have an independent business case. The benefits are largely efficiencies to network businesses, which are estimated at $2.46bn to $2.94bn. Distributors may maintain the benefits over the first regulatory period but not beyond, when the AER would be expected to return most of this benefit to customers through lower network tariffs. This assumption would lead to distributors retaining around $1bn of the operational efficiencies but a further $1.5bn to $2bn would be returned to customers through lower network tariffs. This would leave the net benefits for distributors closer to negative $2.2bn to positive $1.1bn, leaving distributors with a significant risk of making a loss and unlikely to invest – even though customers would benefit

From 2.6 of Ministerial Council on Energy (MCE) Smart Meters Phase Two (Cost-benefit Analysis) Regulatory Impact Statement (June 2008).

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â&#x20AC;˘ Under a retail led rollout (Scenario 2) the consultants do not find a positive business case for retailers even only considering first-order effects with a net cost range to retailers of $2.8 - $5.3bn which could be further reduced by retail competition. In this case distributors are estimated to capture net benefits of up to $4.4bn. As with the distributor-led case, distributors could lose some of these benefits (perhaps around $1- $1.5bn using the logic in the previous example) passed on by the regulator in the form of lower network prices. Some of this benefit may be captured by retailers, as retailers are unlikely to compete away value under cost. However, the retailers case would still be significantly negative and would be very unlikely to rollout smart meters of their own accord without some incremental service business case. In addition a mandate may not resolve the problem and allow retailers to pay back their investment under retail competition, unless costs were evenly distributed. This may be difficult given diverse retailer demographics. This could lead to a need for further retail regulation to cover metering Exhibit A44

Costs and Benefits by Stakeholder ($m) - National, Total NPV

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