addressing peak demand: the opportunities and risks for vulnerable households

7/15/2019 Addressing Peak Demand: The Opportunities and Risks for Vulnerable Households

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The opportunities and risks or

vulnerable households

DR GILL OWEN, Research Program Leader

Addressing Peak Demand


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ABOUT THE MONASH SUSTAINABILITY INSTITUTE

The Monash Sustainability Institute’s (MSI) mission is to solve the climate change and environmentalsustainability challenges acing our world. The problems are complex. To nd the answers, we have towork very dierently.

That’s why we bring together the best minds rom multiple elds o endeavour. We pull togetherscientists, lawyers, economists, psychologists, biologists, engineers, health proessionals, and more tonut out the ‘wicked’ problems. Together, the world-leading experts rom the Monash SustainabilityInstitute and Monash University, combine with the best industry and academic know-how rom aroundthe world to help create the world o the uture.

For more, visit: www.monash.edu/research/sustainability-institute.

DR GILL OWEN

Dr Gill Owen moved to Australia in August 2012. She has a joint part-time appointment between MSIand the Business and Economics Faculty. Gill has published extensively on energy eciency policy, thescope or electricity demand and response, and smart meters.

Until her departure rom the UK, Gill was also a non-executive Director o the England and Wales waterregulator - Owat; a member o Ogem’s (Great Britain Energy Regulator) Consumer Challenge Groupor the Distribution and Transmission Price Reviews; a member o the UK Government’s Smart MetersConsumer Advisory Group; Vice-Chair o the UK Government’s Fuel Poverty Advisory Group. She was aCommissioner o the UK’s Competition Commission or ten years until 2002 and was also previously anon-executive board member o Ogem.

ACKNOWLEDGEMENTS

I wish to thank a number o people or their help with this paper. Firstly, John Thwaites (MSI), Damian Sullivan(Brotherhood o St Lawrence), Tim Nelson, Cameron Reid , Lauren Solomon o AGL or their comments on drats and at theAdvisory Group meetings. Secondly, Paul Simshauser at AGL or very kindly providing sponsorship or the paper. Thirdly,

David Griggs and Julie Arcilla at MSI or general help and support. Finally, Vicki Kyriakakis or layout and design. Any errorsor omissions are solely mine.

MSI Report 13/3April 2013



Table o Contents

EXECUTIVE SUMMARY 1 INTRODUCTION 4 THE NATURE OF ELECTRICITY DEMAND (PEAK AND OVERALL) IN AUSTRALIA 5 OPTIONS FOR REDUCING PEAK AND OVERALL DEMAND 7

How customers could reduce demand 8Ways o incentivising demand response 9

ENERGY VULERNABILITY 10

Concessions available to help with electricity bills 10Households in nancial diculties 11

UNDERSTANDING THE WAY THAT HOUSEHOLDS USE ELECTRICITY 12

Electricity consumption by income level or concession card status 13

Electric heating 14Air conditioning 14Use o electricity or hot water 14Controlled load electricity 15Scope or demand response by level o consumption 15Conclusions on use o electricity by vulernable households 16

OPTIONS FOR REDUCING PEAK AND/OR OVERALL DEMAND 17

Eects and customer response to DSR 17Automation/ direct load control 18Impacts o DSR on vulnerable and low income consumers 18Without behaviour change 18

With behaviour change 19Large households 20Likely impacts o time o use pricing in Australia 20

FINDINGS 22

Understanding peaks and where demand reduction delivers value 22Impact o demand management on vulnerable households in Australia 22Are vulnerable households low users? 23

RECOMMENDATIONS 24

Beore demand response initiatives are developed at scale 24Actions to be taken or implementation o demand response 26Research agenda recommendations 28Conclusions 28



Executive Summary

Rising peak demand is considered to be one o the key drivers o Australia’s rising

electricity prices.

The peak demand problem

Recent data may suggest that peak demand may

not be growing so ast , but it would be premature

to conclude that peak demand is stabilising oralling.

There is growing consensus on the need to tackle

peak demand. This paper seeks to inorm the

debate by identiying potential impacts o

solutions to the peak demand problem on

vulnerable households and making some

recommendations. A more detailed programme o

work will be undertaken during 2013-14,

particularly on automation o demand response,

controlled load electricity and low users.

What can customers do about peak demand?

There are three main ways that customers could

change their electricity demand to save themselves

money and potentially reduce costs in the

electricity system:

f Customers can reduce some uses o electricity.

f Customers can shit electricity consumption to

an o-peak time period.

f Customers can sel-generate electricity (e.g.

solar PV).

Techniques or achieving demand response

include:

f Time o use taris - dierent prices applied to

xed periods during the day

f Critical peak taris- a high price on maybe just

a ew hours on a ew days a year.f Automation/ direct load control – using

technology to reduce consumption during

peak hours, such as turning down the

thermostat on air conditioning.

Automation delivers the greatest and most

sustained shits in demand (compared to price

incentives alone), particularly where consumers

have air conditioners or electric heating. A reviewo trials ound peak reductions o 31% with

automation (16% without) or critical peak price

taris and 16% (5% without) or ToU taris.

The timing o the peak and the dierential

between peak, shoulder and o-peak rates is

clearly crucial in terms o the impacts on

vulnerable households. Narrow peak periods (e.g.

4-7pm) or inrequent CPP peaks will have a

dierent impact than longer peak periods (e.g. 1-8

pm). The impacts on vulnerable households willalso vary depending upon what appliances they

have and at what times o day they use them.

Energy vulnerability

Rising energy costs aect all households and

businesses, but some are more vulnerable to the

impacts. Low incomes can make it dicult to pay

bills; and some have health vulnerabilities due to

age or disabilities. State based electricity

concessions are designed to assist low income

households to pay their energy bills. However,

these vary considerably rom state to state and

there is evidence to suggest that there is some

under-claiming amongst households who may

need them.

Large households and amilies with children tend

to ace more diculties paying electricity bills than

smaller and older households. However, some low

users may ration their usage to avoid the risk o bill

shocks. Vulnerabilty may thereore be visible (e.g.debt and diculty paying bills) or hidden (e.g.

households who over-economise – and potentially

risk their health).

1



Data rom NSW and Victoria suggest that mostvulnerable and low income households tend tobe low or medium users o electricity. Fewer lowincome consumers tend to be large users,although those who are may be particularlynancially stressed (e.g. large low incomehouseholds).

Key ndings

There is a dierence between peaks that ocurday in day out and peaks that occur or only aew occasions each year. I the main issue iscritical peaks (e.g. 4-5 pm on a ew very hot dayseach summer) then a year round time o use tari may be less useul than critical peak pricing/rebates and/or automation o response romappliances such as air-conditioners. Such anapproach may produce better outcomes or

vulnerable households than time o use tarisand to provide more certainty o response andthus ewer risks or retailers and networks.

1. We need to be clear about the peak demandproblems that need to be addressed – day inday out or a more limited number o criticalpeaks. This will enable us to better to tailorappropriate solutions, whether that is yearround time o use taris, critical peak pricingor direct load control.

2. Time o use pricing and other DSR methodsmay oer benets to many customers.However, time o use pricing and other DSRmethods may add complexity and risk intowhat is or many consumers an alreadycomplex electricity retail market. Manyvulnerable households are stuggling to paybills at present. Risks that might beacceptable or better o households may bemuch more problematic or low income

households. For some vulnerable householdsthere are also potential health risks – e,g, i new pricing encourages them to over-rationusage o heating and/or air conditioning.

3. Impacts on vulnerable households will varyaccording to actors including size o household, appliance ownership and usage,energy eciency and tari design. Any tari design creates winners and losers –vulnerable households will be in both groups

whatever the tari design.

Main recommendations

Governments

f Energy saving schemes need to address peak

and overall demand and need to be targeted to

vulnerable households. This could include

designating priority groups to benet rom

grants and low interest loans, plus tailoredadvice and inormation. It would be helpul to

have a national ramework that allows or some

fexibility to meet dierent circumstances in

dierent states.

f The concessions ramework should be reviewed

beore fexible pricing is introduced to ensure

the concessions will remain appropriately

targeted and to examine the scope or

harmonisation o concessions schemes between

states.

f There is a need to clariy take up rates or

concession cards and electricity rebates, along

with measures to improve take up.

f All Governments should adopt the opt-in

approach to time o use taris or all except the

largest household customers (about 12 MWh per

year).

Governments, energy retailers and welfareorganisations

f Boost take up o concessions and rebates

amongst vulnerable consumers.

f Increase understanding o peak and overall

usage o dierent appliances. Particular eorts

should be targeted to vulnerable households.

Energy retailers and welfare organisations

f Households receiving the o-peak concession in

Victoria will need advice beore switching to

time o use taris that might result in them

losing the o-peak concession.

Governments and energy retailers

f There is a need or research into low users, to

identiy i there are any problems such as

“sel-rationing” or under-claiming o concessions.

2



Energy retailers

f Agree not to market time o use taris to

vulnerable customers unless the customer has

had a smart meter or at least one year to

ensure they have sucient data to decide

whether they would benet. It would be good

practice not to market time o use taris to any

customer without this data.

f Make customers aware where they are paying

more on a time o use tari and hence should

consider whether they can shit usage to

o-peak times, reduce usage, or should opt

out o ToU.

f Provide customers with clear inormation on

demand response contracts , including any

“lock in” periods and early termination (exit)

ees.

Energy retailers and distributors

f Automation o response should be explored as

a measure that may have potential or

vulnerable households.

Conclusion

Addressing peak demand – through time o use

pricing and other DSR methods -should bring the

potential to reduce costs to the benet o

consumers.

It will be important than we make vulnerable

households more resilient to a range o energyutures – including tackling peak demand.

3



Introduction

Electricity prices and bills to end consumers in Australia have risen substantially in recent

years.

Rising peak demand (and the investment

necessary to meet those peaks) is considered to be

one o the key drivers o Australia’s rising electricity

prices. There are a number o potential solutions tosmooth demand and thus mitigate the impact on

prices. However, solutions can have dierential

impacts on dierent types o consumer and hence

care is needed i they are to be air and equitable

or all Australians, particularly those who are

vulnerable due to low income, nancial stress, age,

disability or other reasons.

For example:

f Time o use taris may benet households who

can take advantage o o-peak rates but

disadvantage those who nd it dicult to

switch usage to o-peak periods. Evidence

rom a number o countries suggests that

eects vary amongst vulnerable households

depending upon a number o actors. 1

f Direct load control can be a way o reducing

peak demand that can be designed to have

negligible impact on comort (e.g. o airconditioning) or convenience (e.g. water

heating) and deliver nancial benets (sharing

the value o load reduction between customer

and supplier).However, capital investment may

be needed to introduce load control and some

consumers are wary o handing over control o

appliances in this way.

There is growing consensus on the need to tackle

peak demand2, although there is still considerable

debate about the most eective and equitable

ways to do so. This paper seeks to inorm thedebate by identiying potentail impacts o

solutions to the peak demand problem on

vulnerable households and making some

recommendations. A more detailed programme o

work, particularly on automation o demand

response, controlled load electricity and low users,

will be undertaken during 2013-14

1. For example see: Frontier Economics and Sustainability First. Demand side response in the domestic sector: a literature review o major

trials. DECC. August 2012

2. Reports rom the AEMC Power o Choice review (http://www.aemc.gov.au/Media/docs/Final-report-1b158644-c634-48b-bb3a-e3204beda30-0.pd); the Productivity Commission drat report on electricity network regulation (http://www.pc.gov.au/__data/assets/pd_le/0010/120043/electricity-drat-volume1.pd); the Senate Committee report on electricity prices (http://www.aph.gov.au/Parliamentary_Business/Committees/Senate_Committees?url=electricityprices_ctte/electricityprices/report/index.htm)

4



Nature o Electricity Demand in Australia

(Peak and Overall)

5

Customers’ electricity bills are made up o a number o dierent costs.

Networks (the poles and wires) account or around

51% o costs; electricity generation (power

stations) or around 20% ; carbon price or around

9%; with the remaining 20% being the retail and

environmental scheme costs (customer service,billing, renewables, energy eciency etc).3

Costs in the electricity system (and hence impacts

on customers’ electricity bills) are driven both by

overall demand (the total amount o electricity

consumed) and peak demand (the maximum

amount consumed at any one time). However,

peak demand is a particularly important driver o

costs. This is because building power stations and

networks to serve demand or only a small

number o hours o peak demand each year, means

that this inrastructure is eectively unused or

much o the time, yet the companies who have

built it will still need to recover the high xed costs.

The Australian Government estimates that 25 per

cent o retail electricity costs are derived rom peak

events that occur over a period o less than 40

hours per year. 4

The rapid growth o peak demand relative to

overall (or average) demand has been a majoractor inluencing costs in the Australian electricity

system.

Between 2005 and 2011, peak electricity demand

increased at a rate o approximately 1.8 per cent a

year, while total electricity demand grew at 0.5 per

cent a year.5

Maximum summer demand in each mainland

National Electricity Market (NEM) jurisdiction (New

South Wales, Queensland, South Australia,Victoria)

increased by between 20% and 38% between 2001

and 2012. During the same period, average

electricity demand increased by only 15%.6

Households represent around 25% o total

electricity demand but various studies have shown

that the residential contribution to peak demand

can be as high as 45 per cent on peak demand daysacross the system.7 The peak demand time is

typically between 4-8pm - the time o day when

busineses demand is still high and household

demand rises as people get home rom work and

school. One o the most signicant drivers o peak

demand is the use o air conditioning. Growth in

the installation and use o air conditioning by

households has been particularly rapid in recent

years. 73% o households in Australia had an air

conditioner in 2011 compared to 59% in 2005.

8

3. Department o Resources, Energy and Tourism. Fact sheet – Electricity prices. August 2012 . This is the national average split o costs –state averages do vary.

4. National Energy Saving Initiative, Issues Paper, prepared by the National Energy Savings Initiative Working Group, Department o ClimateChange and Energy Eciency and Department o Resources Energy and Tourism, December 2011, p.71.

5. AEMC. Power o Choice. Final Report,. November 2012 p. 8

6. AEMO. 2011-12 NEM Demand Review Inormation Paper.

7. AEMC. Power o Choice. Final Report,. November 2012.p.9 The AEMC notes that “These gures extracted rom various reports prepared orthe Essential Services Commission o South Australia (ESCOSA), Energex and Ergon Energy”.

8. ABS. Energy use and conservation survey 2011. October 2011. These gures extracted rom various reports prepared or the EssentialServices Commission o South Australia (ESCOSA), Energex and Ergon Energy including: Charles River Associates (CRA), Assessment o

Demand Management and Metering Strategy Options, Charles River Associates, prepared



6

I we look at what has been driving residential bill

increases in recent years, we can see that network

charges have been the biggest component, on

average responsible or 49% o the increase rom

2007-11 (generation cost increases accouted or

7% o the increase; retail costs and margin or 26%

and renewables costs or 18%).9 These

percentages do however vary rom state to state.

Overall electricity demand ell by 1% nationally

rom 2010 to 2012. While peak demand declined in

all jurisdictions in the summer o 2011/12, it should

be noted that the number o high temperature

days (over 35 degrees) was also signicantly lower.

For example, in Sydney and Melbourne, the

number o high temperature days in 2011/12 were

9 and 6 respectively - down rom peaks o 25 and

16 in the previous summers.10 Commenting on the

drop in peak demand rom 2010 to 2012, AEMCrecently noted that “It is too early to determine

whether this all represents a unique event or is

part o a trend.”11

Recent data rom AEMO suggest that peak

demand in the 2012/13 summer (signicantly

hotter than 2011/12) in New South Wales rose to

13.6 GW compared to 12 GW in 2011/12. However,

this was still below the 2010/11 peak demand o

14.5 GW, but similar to peak demand in 2006/07

and 2008/09. In Victoria peak demand in 2012/13has continued to all slightly – and was 9.1 GW

down rom the high point o 10.4 GW in 2008/09.12

These data may sugest that peak demand may not

be growing so ast as in the past or may even be

on a downward path, or a number o reasons

including a demand reduction response to rising

electricity bills, penetration o solar PV (which

replaces some network delivered electricity) and

also some economic restructuring. Recent

assessments published by the Australian EnergyMarket Operator (AEMO) suggest that peak

demand will slow but will continue to grow.13

It would threore be premature to conclude that

peak demand is stabilising or alling – we will need

to see the evidence over a number o years and it

will also be important to disaggregate the possible

reasons or changes in peak demand.

9. E. O’Young. Australia’s uture electricity price environment. April 2011. Cited in Oakley Greenwood. Policy options or maximisingdownward pressure on electricity prices. October 2012. p.17

10. AEMO. 2011-12 NEM Demand Review Inormation Paper.

11. AEMC. Possible uture retail electricity price movements: 1 July 2012 to 30 June 2015. AEMC, March 2013.

12. AEMO data based on analysis in : Sandiord, M. Our hot summer and peak demand – what really happened. Climate Spectator, 06 March2013.

13. Australian Energy Market Operator, National Electricity Forecasting report, June 2012, at page i.



Options or reducing peak and overall demand

There are several options or reducing peak and overall demand o electricity in Australia.

As the AEMC notes in its Power o Choice report:

“It is also important to note the dierence between

system peaks and network peaks. System peaks

occur when demand is highest across the state (aswholesale prices are set at a state level). However

networks need to deal with peak demand at the

circuit eeder and transormer level which can

dier rom the time o day rom system peaks and

also by location. The characteristics o peak

demand or a network business will dier by

location and season. Individual areas within the

network may be summer or winter peaking and

may have dierent proportions o residential

versus commercial and industrial loads, leading to

dierent peak demand proles.”14

This distinction between system and network

peaks and the locational and seasonal actors are

not only important or understanding what is

causing costs in the system but also or assessing

where action to reduce peak demand (or demand

growth) will deliver benets. For example, where a

part o the network (e.g. a substaion serving an

area o residential and business customers) is near

capacity and investment is needed, there will bethe potential to avoid or deer some o that

investment i peak demand can be reduced (or at

least not increased) by customers served by that

substation. However, to take another example,

where there is plenty o capacity at the susbtation

level, the benets o reducing peak demand may

be much lower.

Actions needed to reduce peak wholeseale

electricity costs may be dierent rom those or

networks. For example, as more wind power comes

onto the grid, there may be value in demand

response to balance peaks and troughs in windgeneration. In these cases using storage (e.g.

electric storage heating or hot water or electric

vehicles) might be a good option – with these

stores taking in electricity at times o peak wind

output and reducing their intake o electrity at

times o low wind output (again automation o

response could make this easier or customers).

Similarly, customers could be incentivised to use

their solar PV output at times o high electricity

prices (e.g. by running their washing machines,dishwashers, clothes dryeres) at those times.

Peak demand can also be either a year round or

inrequent problem and thereore the types o

solution may also need to vary. Demand side

response initiatives can thereore be aimed at:

f delivering a consistent day-in day-out

reduction at peak time – or example each

weekday or a whole winter or summer season.

This is most useul when systems arecharacterised by regular peaks o similar sizes;

or

f delivering a reduction during critical peaks. This

requires an occasional response rom

consumers, such as during exceptionally hot or

cold periods. Exceptional events may in uture

also be driven by changes in wind generation

output. 15

14. AEMC. Power o Choice. Final Report,. November 2012, p.9

15. Denitions taken rom p.10-11 o DSR in the domestic sector - a literature review o major trials by Frontier Economics and SustainabilityFirst or DECC, August 2012 (http://www.decc.gov.uk/assets/decc/11/meeting-energy-demand/uture-elec-network/5756-demand-side-response-in-the-domestic-sector-a-lit.pd)

7



How customers could reduce demand

There are three main ways16 that customers could

change their electricity demand to save

themselves money and potentially reduce costs in

the electricity system:

f Customers can reduce some uses o electricity.

For example, raising (air conditioning) or

lowering (heating/water heating) thermostat

settings, reducing the run time o air

conditioners, dimming or reducing lighting,

using ecient appliances.

f Customers can shit electricity consumption to

an o-peak time period. For example,

customers could pre-cool their property at

o-peak (lower cost) times. Customers could

also run certain appliances (notably washing

machines, dishwashers, clothes dryers, electricwater heaters) at o-peak periods when prices

are lower.

f Customers can sel-generate electricity - e.g.

solar PV. Customers can run appliances using

their own electricity at peak times (thus

reducing their use o network-delivered

electricity).

The methods to acilitate customer demand

response include:

f Dierent types o taris. (see page 9)

f Contracts, (mostly or business consumers), to

curtail load (at pre-agreed times or in response

to changing conditions on the electricity

network); and

f Automated devices including ‘smart’ controls,

thermostats and appliances which respond to

changes in the electricity network or a price

signal.17

f Ecient appliances, lighting and insulation

measures to reduce electricity demand.

f Inormation and eedback (or example, via

in-home displays, web portals, inormation on

bills) so that customers can identiy ways in

which they can reduce or shit their demand.

The nature o electricity demand, the drivers o

costs and the scope to do something about those

costs is thereore a somewhat complex issue. We

need to bear these complexities in mind as we

look or solutions. There are various dierent ways

to incentivise and enable consumers to reduce

peak demand. Some o these may be better or

some consumers than others. . A number o

retailers in some states are already oering time o

use taris, in some cases passing on time varying

charges rom the networks. Victoria intends to

move to more widepsread adoption o time o use

pricing rom July 2013 and the AEMC Power o

Choice report suggested time o use pricing should

be adopted in the uture or network charges.

It is important, thereore, that we assess how best

to deliver the optimal solution o reduced peak

demand and customer benets and incoprrate thisinto the development o this market. It will be

particuarly important to establish which methods

will work best or vulnerable consumers.

16. Based on Goldman et al. National Action Plan or Energy Eciency. Coordination o Energy Eciency and Demand Response, 2010.

17 Ogem. op cit p. 10

8



9

WAYS OF INCENTIVISING DEMAND RESPONSE

TIME OF USE TARIFFS

There are typically three (o-peak, peak andshoulder) dierent prices applied to xedperiods during the day. Typical times in NSWare :

f peak - 1pm-8pm weekdays;

f shoulder – 7am-1pm & 8pm-10pm onweekdays; 7 am-10pm on weekends;

f o-peak – 10pm-7am every day

CRITICAL PEAK TARIFFS

Target periods o exceptionally high demand- eg. use o air conditioning at peak times onvery hot days. CP Price taris charge a highprice at the “critical peak”. CP Rebate tarisgive consumers a rebate or reducing useduring the critical peaks. As the dates o critical peaks are not known in advance,consumers are notied the day beore byphone, text or email and/or real-timereminders on the day. Most CPP and CPR tari trials have been accompanied by a ToU tari.A ew CPP and CPR taris have been trialledalongside rising block taris (where per unitprices increase with total consumption). Forconsumers on this type o tari, critical peaksare the only times when they ace a pricesignal to shit demand.

REAL-TIME PRICING

Prices would change in line with wholesalecosts - or example, based on day-aheadhourly wholesale electricity prices. Real timepricing has not been used extensively and hasbeen mainly or business customers ratherthan households.

AUTOMATION/ DIRECT LOAD CONTROL ANDSTORAGE

Direct load control involves the use o technology to reduce consumption rom agiven appliance during peak hours, such as airconditioning (e.g. by turning down thetherostat or cycling it o or short periods).Automation can deliver day-in day-out orcritical peak reductions in demand. One o the characteristics o electricity is that it

cannot easily be stored as electricity. However,it can be stored in batteries, or as heat. DSRstorage options are where consumers (usuallyvia automated control) allow electricity to betaken in and stored on their premises duringo-peak times and used later. This might be inthe orm o hot water (electric water heaterand storage tank) or electric storage (slab)heaters; or electric vehicles.

ON-SITE/ DISTRIBUTED GENERATION

Consumers generate their own electricity orheat rather than use network distributedelectricity. For example, by using electricityrom their solar PV system during the daytimeto run air conditioner, washing machine etc ;or using solar thermal to heat water.



Energy vulnerability

Rising energy costs aect all households and businesses, but some are more

vulnerable than others to the impacts.

Households may ace :

f Financial vulnerability – low incomes can makeit dicult to pay bills and make huseholdsparticularly likely to experience problems dueto price shocks.

f Health vulnerability – households withoccupants who may be at risk o healthimpacts i heating and/or cooling is inadequateor have high needs or hot water, due to age(very elderly and very young) or varioushealth reasons

In addition, some households may be vulnerabledue to low levels o education or literacy or may

not have English as their rst language. They maynd it more dicult to identiy and access ways o reducing their energy costs.

Concessions available to help with electricity bills

State based electricity concessions are designed toassist low income households to pay their energybills. While energy concessions dier in dierent jurisdictions Victoria provides a useul example.

In 2007 approximately 38% (800,000) o Victorianhouseholds received the main year roundelectricity concession.18 The concession is set at17.5%19 o the total bill, with no specic cap (theaverage rate in 2013 is around $30020). Households

with controlled load electricity (or o-peak waterheating and slab heating) are also entitled to theO Peak Concession which provides a 13%reduction on the o-peak tari rates on all

quarterly electricity bills and can be received inaddition to the Annual Electricity Concession. Thetotal cash value o the concessions to householdswith controlled load thereore tends to be higher.

Households eligible or concessions include thosewith a Commonwealth Health Care Card, aPensioner Concession Card, or DVA Gold Card.Most o these households are on low incomes.However a proportion o households with aCommonwealth Health Care card are retirees with

higher income. The above gures or Victoria suggest thatsubstantial numbers o households qualiy or aconcession on electricity bills. Similar guresemerge or New South Wales. The NSWGovernment provides an energy rebate or eligiblehouseholds o $161 per year paid throughelectricity bills. IPART ound that between 30-44%o all households, in the regions that theysurveyed, hold a concession card.21

However, IPART did also nd that most peoplewith concession cards are on very low incomes.

10

18. Roy Morgan Research or Department o Human Services, Victorian Utility Consumption Household Survey 2007, Final Report, April2008, p v.

19. In July2012 a threshold or the electricity concession was introduced to oset the Federal Government’s carbon tax compensation. TheVictorian concession is not applied to the rst $171.60 o a household’s annual electricity bill. This is so that households are not

compensated by two levels o government or the same expense.

20. Johnston, M. The relative value o energy concessions. St Vincent de Paul, January 2013. p.11

21. IPART. Residential energy and water use in Sydney, the Blue Mountains and Illawarra. Results rom the 2010 household survey. December2010.



11

In Sydney at least 61% o households with aconcession card were in the lowest income groupand a urther 19% were in the lower-middleincome group.22 More than 70% o householdsthat held a concession card in the Hunter, Gosordand Wyong areas were in the lowest incomegroup

IPART also ound that most low-incomehouseholds held a concession card (78% in Sydneyin 2010 and 86% in the Hunter, Gosord andWyong areas in 2008) and most o thesehouseholds were aware that they could claimrebates, and did claim them. Nevertheless, morethan 20% o households that held a concessioncard in Sydney did not claim rebates. Thesenon-claiming low-income households may beeven more vulnerable to utility price increasesthan those that do hold a concession card.

Households in nancial diculties

Income is only one o theactors that aect thelikelihood o a household experiencing nancialdiculties paying utility bills. In particular, IPARTound that such households were also more likelyto:

f have three or more occupants (and thereore to

consume more) f renting or have a mortgage (and thereore

higher accommodation costs)

f use large amounts o electricity (more than 8

MWh per year)

Simshauser and Nelson ound that amongst AGL

customers, those classied as Hardship Customers

(those with diculties in paying bills who may or

may not also be classed as vulnerable customers)

are mainly within the 30-49 age bracket and tendto be larger (3 or more persons) households – i.e.

amilies with children.23

22. The actual proportions might be slightly higher because 13% o households that held a concession card reused to provide incomeinormation.

23. Simshauser, P and Nelson, T. The energy market death spiral – rethinking customer hardship. AGL Applied Economic and PolicyResearch. Working Paper No 31. June 2012.

24. Roy Morgan Research or Department o Human Services, Victorian Utility Consumption Household Survey 2007, Final Report, April2008, p.111

25. Simshauser, P and Nelson, T. The energy market death spiral – rethinking customer hardship. AGL Applied Economic and Policy Research.Working Paper No 31. June 2012.

ABS data show that o households receivding

various orms o government pensions and

allowances, more than 40% o unemplyed and

low income amily households report not being

able to pay utility bills on time, as do 25% o

households containing disabled people. However,

only 5% o aged pensioner households report such

problems. This might be taken as indication that

older households who receive concessions are

nancially better o than other concession

recipients. This may well be true or some o these

older households. However, some o these older

households may avoid payment diculties due to

other strategies – or example by rationing their

usage to avoid the risk o bill shocks Vulnerabilty

may thereore be visible (e.g. via debt and diculty

paying bills) or hidden (e.g. households who

over-economise – and potentially risk their health

– due to worries about large bills).

One piece o evidence that may suggest this is an

issue comes rom the 2007 utility consumption

survey in Victoria. This ound that aged concession

households used their main heater slightly less

requently (44.3 times per month) than other

concession households (46.2 times per month)

during May to November.24 The gap in knowledge,

about those who may be managing their energy

bills by “going without”, is noted by Simshauser and

Nelson.25 This issue o “sel rationing” would merit

urther research to establish whether it is a

signicant problem anongst some vulnerable

householders.



Understanding the way households use

electricity There is a need to understand how people use electricity in order to assess their peak-

time usage levels and their potential to shit usage to o-peak periods.

This includes an understanding o their ownershipand usage o major electricity consumingappliances, insulation levels in their property andother actors.

The Independent Pricing and Regulatory Tribunal

o NSW (IPART) analysed electricity and gas

consumption data in NSW as well as data about the

household, the dwelling and uses o energy.26

O the households surveyed in Sydney in 2010:

f 27% were small electricity users (up to 4 MWhper annum)

f 60% were medium electricity users (with 21%consuming 4 to 6 MWh, 18% consuming 6 to 8MWh and 21% consuming 8 to 12 MWh perannum)

f 13% were large electricity users (consumingmore than 12 MWh per annum)

12


Large electricity users in Sydney had moreoccupants (3.8 compared to 1.7), and were morelikely to consist o couples with children (70%compared to 16% o small users) rather than single

people or couples without children and morelikely to have higher incomes. Small electricityusers were more likely to live in fats, to have lowerincomes, to be retirees or pensioners (42%compared to 16% o large users).

Not surprisingly, households that use mains gasgenerally use less electricity, because some o their major uses (e.g. heating, hot water) are o gasrather than electricity. 63% o households withoutgas are large users o electricity compared to 49%

o households with gas. However households withgas may be large users o household energy intotal, when their gas and electricity consumptionare taken into account.

Similar data are not available or Victoria but it islikely that households who are large and all userso electricity would have similar ownership anduses o electricity using appliances.

SMALL AND LARGE ELECTRICITY USERS IN NSW

Small electricity users:

f 45% have an electric hot water system(main source)

f 47% use only electricity or cooking

f

47% mainly use electricity or heating

Large electricity users:

f 70% have an electric hot water system(main source)

f 64% use only electricity or cooking

f

65% mainly use electricity or heating



13

Higher electricity consumption is associatedwith having large electricity usingappliances, and with more requent use o

these appliances. Large electricity usingappliances are mainly : hot water heaters,clothes dryers, dishwashers, washingmachines, microwave ovens, secondrerigerators, air conditioners and swimmingpools (pumps use energy).

There is considerable variation betweenhouseholds in the requency o their use o major electricity using appliances (clothesdryers, washing machines and dishwashers).

Not surprisingly, the more requentlyhouseholds use their appliances the highertheir electricity consumption. Clearly, usagealso varies depending upon the eciency o the appliance.

MAJOR ELECTRICITY USING APPLIANCES: COST OF USE

IPART ound that, on average :

f using a clothes dryer 3 times per week-

870 kWh per annum (3 x 290 kWh) At $0.22 per kWh this would cost $191.

f Using a dishwasher 6 times per week -1,850 kWh per annum (6 x 309 kW) At$0.22 per kWh this could cost $407)

f Every hour o use o an air conditioneradds on average about 2.5 kWh toelectricity consumption. So, using an airconditioner or 5 days per week, 6 hoursper day or 6 months o the year uses

2,000 kWh (cost around $440 at $0.22 perkWh).

Electricity consumption by income level orconcession card status

IPART ound that on average, high incomehouseholds (above $130,000 per annum) use moreelectricity and gas than low income households(below $33,800 per annum). Low-incomehouseholds were less likely to own clothes dryers,dishwashers and swimming pools. However, therewere signicant numbers o both large and smallusers within each income category.

• Smallelectricityusers(lessthan4MWhperannum) - 39% are low-income households; 6%are high-income households

• Largeelectricityusers(morethan12MWhperannum) - 6% are low-income households; 31% arehigh-income households

The table on the right shows the distribution o low income households in NSW at the variouslevels o consumption. It shows that low incomehouseholds are concentrated at the below 8 MWhlevel (81% o low income households).

TABLE 1: Distribution o low income households in

NSW survey areas within consumption bands

(IPART)27

Household Income

(beore tax) < $33,800

Percentage

<4 MWH 34%

4-6 MWh 27%

6-8 MWh 20%

8-12 MWh 15%

12 MWH+ 3%

As the table above shows, 18% o low incomehouseholds use more than 8 MWh per year andthereore could be classed as high users, with 3%being very high users (over 12 MWh).




14

Research in Victoria (2007)28 showed thatconcession card holders tend to use less electricitythan households on average.

TABLE 2: Average Electricity Consumption inVictoria, 200729

Household Type Average Consumption

Aged concession cardholders

4000 KWh

Other concession cardholders

4600 KWh

All concession cardhouseholds

4300 KWh

Non-concession cardholders

5300 KWh

Electric heating

In 2007 85% o households in Victoria had gas

heating o some kind. 34% o households had

some orm o electric heating but or many o

these this would be a orm o secondary heating

alonsgdie their gas heating (e.g,. a portable electric

heater). Gas ducted heating was more common

amongst non concession households (51%) than

amongs concession households (31%). Concessionhouseholds were more likely to have a gas built in

heater (55%) than non concession households

(35%). This may suggest that concession

households could be more reliant on electricity or

supplementary heating than non concession

households, as the latter are more likely to have

whole house gas heating, whereas concession

households have gas heating only in one room.

This would require more investigation to reach a

conclusion.

28. Roy Morgan Research or Department o Human Services, Victorian Utility Consumption Household Survey 2007, Final Report, April2008, p 75

29. Ibid.

30. Deloitte. Advanced metering inrastructure : consumer impacts study. Final report Volume 1 October 2011. Report or Department o Primary Industry and Resources Victoria.

31.IPART 2011 (Appendix C, section C.4.4).

32. Roy Morgan research or Department o Human Services, Victorian Utility Consumption Household Survey 2007, Final Report, April 2008,p. 117

33. IPART report on Sydney 2010 – (page 35 and Ch 4).

More recent research by Deloitte ound that in

Victoria 15% o all households surveyed used

electricity or heating and or most vulnerable

groups the percentage using electric heating is

similar to this or lower.30 Use o electricity is higher

in regional Victoria (22%) where there is generally

less access to natural gas.

Air conditioning

About 59% o households surveyed in NSW by

IPART had an air conditioner. Low-income

households were somewhat less likely to have air

conditioners than those with higher incomes.

Nevertheless, more than hal o low-income

households had an air conditioner. However,

IPART’s view is that high-income households on

average may have more powerul air conditionersthan low-income households. In addition, IPART

ound some evidence that high-income

households use their air conditioners more

requently than low-income households.31

72% o households in Victoria had some orm o air

conditioning in 2007 and, on average, concession

households were as likely to have air conditioning

as non-concession households. However, there is a

marked dierence between aged concession

households where 74% have an air conditioner,compared to other concession households (61%).32

Use o electricity or hot water

The proportion o respondents in Sydney who had

an electric hot water system in 2010 was 56% and

78% o those with any orm o electric hot water

had an o-peak system.33

In Victoria, in 2007, concession card holders weremore likely to use electricity or hot water (21%)than non-concession households (18%).



15

Around 2% o households in Victoria had solar hotwater systems in 2007. 34 The majority (70%) o households with an electrical hot water systemhad an o peak system, while one in ve had astandard system (19%). Compared with previoussurveys (2001 and 1996), there was a slightincrease in the incidence o having a standardsystem (19% compared with 15% in 2001). Aged

concession households were the most likelysub-group to have o peak hot water systems –83%, compared with 69% o non-concessionhouseholds and just over hal (53%) o other

concession households.35

Controlled load electricity

Controlled Load electricity is remotely controlled

by the network provider, and is usually switched

on only at night. Most Controlled Load electricity

is used or hot water, including both electric

storage systems and electricity boosted solar hot

water systems. But it can also be used or other

purposes such as swimming pool pumps and

certain types o heating (“slab heating”). In return

or enabling the control o the relevant appliance

usage to o peak times (typically 11pm to 7 am) ,

customers are charged a separate lower tari or

this controlled load. The controlled load tari is

usually ar cheaper than the standard tari – orexample 10-12c/kwh, as opposed to 22c/kwh

(2012 average rates). Customers with controlled

load will continue to pay a rate similar to the

standard rate or all other electricity uses.

Controlled load customers have a dual element

meter that can record the two dierent tari rates.

The contolled load rate is not usually available or

other uses o electricity at night.36 This is dierent

rom the UK where households on the equivalent

tari (Economy 7) usually also benet rom lowerpriced night rate electricity or other appliances

used at night time – so this can be very useul as a

means o reducing the cost o using appliances

such as washing machines, dishwashers and

34. Roy Morgan research or Department o Human Services, Victorian Utility Consumption Household Survey 2007, Final Report, April2008, p 78

35. Roy Morgan research or Department o Human Services, Victorian Utility Consumption Household Survey 2007, Final Report, April2008, p 103

36. Although a number o retailers are now starting to oer taris that do allow or o-peak rates or other appliances.

37. NSW Oce o Environment and Heritage website, Choosing a hot water system, at http://www.environment.nsw.gov.au/energy/hwschoose.htm

38. IPART 2011. op cit.

clothes dryers that can be used overnight (many o

these appliances have built in timers).

Controlled Load (or o-peak) hot water systems

generally use more electricity than standard

electric ones because they need to have larger

storage tanks as the water is heated only at night.37

However, having a Controlled Load electricity

supply can mean lower bills or hot water despitehigher consumption because o the low unit rate

or the night time electricity. For households

without gas, IPART ound that having a Controlled

Load supply on average increases electricity

consumption by about 510 kWh per annum but

reduces bills by about $270 per annum compared

to otherwise similar households without a

Controlled Load supply.38

The issue o controlled load supply will be explored

in more detail in a uture paper.

Scope or demand response by level o

consumption

Based on levels o demand in NSW, the box on the

next page provides an example o how scope or

demand response may dier amongst households

who are low, medium and large users o electricity.

This is purely indicative at this stage and will be the

subject o urther work.



16

Low users o electricity (below 4MWh perannum) have limited scope or load shitingand many o these households may already

likely to be pretty rugal. But they could beoered measures (e.g. ecient appliances,lighting) to help reduce overall demand andbills. Some o these households may haveenough o-peak use to benet rom ToU(would depend upon the tari design)

Larger users (above 8 MWh per annum ) willbe the most stressed by electricity costs andcould have load that could be shited such as

: a lot o large appliances; requent use o such appliances; air con and requent usageo it; using electricity or heating and/or hotwater.

POTENTIAL SCOPE FOR DEMAND RESPONSE BY SIZE OF CUSTOMER

Medium users (above 4Mwh but below 8MWh) with at least two o the ollowingcharacteristics might also have scope to load

shit : a lot o large appliances; requent useo such appliances; air con and requentusage; using electricity or heating and/or hotwater.

Conclusions on use o electricity by vulnerable

households

What do the availbale data or NSW and Victoriatell us?

It seems that most vulnerable and low incomehouseholds would tend to be low or low/mediumusers o electricity. Very ew low incomeconsumers would tend to be in the large userscatgeory, although it is possible that those whoare may be particularly nancially stressed (e.g.large low income households in larger properties).

Clearly more work will need to be done to obtain a

uller up-to-date picture o electricity usage byvulnerable and non-vulnerable households.Although Deloitte has done some modelling toproduce load proles or dierert types o customers this does not tell us what appliancesare used at what times o day and what uses mightbe capable o being shited. However, even basedon these data we can see that there are signicantnumbers o huseholds in Victoria and NSW withlarge electricity loads (heating, hot water, airconiditoning) who could be impacted negativelyor positively by fexible pricing and other demandresponse measures such as load control.



Options or reducing peak and/or overall demand

- likely impacts on vulnerable households There are various options available to reduce peak and/ or overall demand o

electricity.

Eects and customer response to demand sideresponse (DSR)

There have been many trials in Australia and other

countries o ways to secure demand response via

time o use incentives and automation. A major

review o worldwide trials o household demand

side response was publishedby the UK Department

o Energy and Climate Change in July 2012.39

Key ndings included:

f Consumers do shit electricity demand inresponse to higher prices during peak periodseven i accompanied by only basic inormation.However the size o the shit varies

signicantly. Basic inormation may includeridge magnets, inormation sheets, and basicbill inserts. The size o the shit achieved intrials: day-in day-out DSR: 0% to 22%; criticalpeak DSR: 5% to 38%.

f Automation delivers the greatest and mostsustained shits in demand, particularly whereconsumers have air conditioners or electricheating. Most automation trials aimed toreduce demand at critical peaks, rather than on

a day-in day-out basis. f Ater automation, a combination o price

incentives and enhanced inormation generally

delivers the greatest response. Enhanced

inormation includes billing which breaks

consumption down into dierent tari periods,

and real-time interactive inormation (such as

in-home displays (IHDs)).

39. Demand Side Response in the domestic sector- a literature review o major trials, Final Report Undertaken by Frontier Economics andSustainability First, DECC, August 2012

f Consumer eedback on taris and interventions

aimed at encouraging DSR is generally positive.

Although it should be noted that most trials

have been voluntary with consumers choosing

whether to opt-in.

f Savings made by some consumers are “passive”

(i.e. without behaviour change) i they were

already consuming less than average at peak

times. For other consumers savings were

achieved by reducing consumption and/or

shiting to cheaper periods.

There are some areas where DSR evidence remains

inconclusive:

f The response o vulnerable and low-incomeconsumers to DSR initiatives.

f The impact o non-economic signals (e.g.

inormation) alone. In some trials the messages

were conusing or consumers – e.g. the

dierence between reducing electricity use in

general as opposed to at peak times o day.

f Whether DSR persists over time i it is not

automated or directly controlled, because

many trials have been relatively short (one yearor less).

Thus, whilst much has been learnt rom trials, there

are clearly many areas where understanding

consumer responses and impacts o demand

response is still being developed.

17



Automation/ direct load control

Peak demand reductions are generally much moresignicant with automation than without – areview o a large number o trials ound peak reduction o 31% with automation (16% without)or CPP taris, 20% (12% without) or CPR taris,and 16% (5% without) or ToU taris.40 Faruqui and

Palmer also show that percentage reductions inpeak demand (ToU, CPP and CPR taris) aregreater with enabling technology, than without.41

The LIPA Edge Direct Control Programme (LongIsland Power Authority in the USA) appliedautomation or air conditioning units, duringcritical peaks, without a peak price signal.42

Consumers had the ability to override without anancial penalty, but overriding rates seem tohave been low – around 21%.

Results rom the OG&E Trial in the United Statesshowed the provision o an in home display (IHD)or web portal access along with a CPP tari produced smaller percentage reductions romlow-income consumers than or higher incomeconsumers. In contrast when the CPP tari wascombined with a smart thermostat, whichprovides an automated response to tari rates,peak demand reductions were higher orlow-income than high-income consumers.43 This

may be because low income households were lesslikely to override the settings than those on higherincomes. Other actors which may be correlatedwith income, such as the age o participants, mayalso have driven this result, but this may alsoindicate the potential value o the approach orvulnerable groups.

Impacts o DSR on vulnerable and low incomeconsumers

Some key points to note when assessing impactson vulnerable and low income consumers:

f Dierent denitions o vulnerable and lowincome are used. Sometimes the ocus is juston low income households; in other cases

other vulnerability actors (e.g. age, disability)are considered. In some cases, consumers havesel-dened themselves as vulnerable; inothers proxies such as eligibility or meanstested benets have been used.

f Not all trials have sought to dierentiatebetween types o consumer – hence thelimited nature o the evidence base.

f There is also a need to distinguish between

impacts assuming no behaviour change (i.e. i the household makes no changes to theirconsumption or whatever reason) and theimpacts o any behaviour change (response).

Without behaviour change:

A number o studies have ound that manylow-income consumers already consume a higherproportion o electricity at o- peak times,

compared to the average consumer. These fatterloads (electricity use spread evenly across the day)mean that, beore any behaviour change,low-income consumers may see a reduction inbills in a move rom a fat rate tari to a ToU or aCPP tari.44 Faruqui and Palmer simulated theimpact on electricity bills o CPP taris and oundthat 65% o low-income consumers wereimmediately better o on the CPP rate than theywould be on a fat tari, beore any behaviourchange.45 See also the Northern Ireland Powershit

trial example in on page 19.

18

40. Vaasa ett, 2011, The Potential o Smart Meter Enabled Programs to Increase Energy and Systems Eciency: A Mass Pilot Comparison;Short name: Empower Demand. Available at http://www.esmig.eu/press/lestor/empower-demand-report.pd.

41. Faruqui and Palmer, 2012, The Discovery o Price Responsiveness- A Survey o Experiments involving Dynamic Pricing o Electricity.Unpublished paper submitted to the EDI Quarterly. (cited in Frontier Economics/Sustainability First paper or DECC.)

42. Frontier/SF paper

43. Demand Side Response in the domestic sector- a literature review o major trials

Final Report Undertaken by Frontier Economics and Sustainability First, DECC, August 2012

44. Faruqui, A & Palmer, J. “The Impact o Dynamic Pricing on Low Income Customers,” IEE Whitepaper prepared by The Brattle Group, Inc.,June 2010

45. Faruqui, A & Palmer, J. “The Impact o Dynamic Pricing on Low Income Customers,” IEE Whitepaper prepared by The Brattle Group, Inc.,June 2010



The timing o the peak and the dierential

between peak, shoulder and o-peak rates is

clearly crucial. Some such variations are bound to

occur as peak periods are not the same in all areas

and there can also be dierences between peaks

on the networks and the generation side. Narrow

peak periods (e.g. 4-7pm) or inrequent CPP peaks

will have a dierent impact than longer peak

periods (e.g. 1-8 pm). For example, there is

currently considerable variation in rates and time

periods or controlled load taris and the time o

use taris already available in Australia.

With behaviour change:

Low-income consumers do respond to incentives

to shit load, but their responses tend to be smaller

than the responses or average consumers.46 There

are a number o possible reasons which include:

f Lower overall electricity use may limit the

extent to which they can reduce demand at any

time o day (including peaks). Low income

households in Australia (as in the UK), tend to

have lower electricity use than the average

(although some larger low income households

have high electricity usage)

f Flatter load shapes. Vulnerable consumers maybe at home during the daytime (e.g.unemployed, retired or disabled) and thushave usage more spread out rather than“peaky”.

f Other consumer characteristics. In the PG&E Trial in the US, the dierence between

low-income and average consumers wasaccounted or by dierences in appliancesused by these groups (notably airconditioners). Available evidence suggests thatbetter o households in Australia may tend tomake more use o air conditioners and havemore powerul air conditioning units and somay have more scope to reduce usage.

f Smaller economic incentives. I low-incomeconsumers receive a discount on the price they

pay or electricity, the impact o the peak pricedierential may be limited. This was ound toaect CARE consumers in the CaliorniaState-Wide Pricing Pilot and the PG&E Trial. Inthe Ireland Electricity Smart Metering Trials, orhouseholds receiving the Free ElectricityAllowance (elderly, carers, and disabled), peak electricity use ell less than the averageconsumer on ToU taris. In Australia it wouldbe useul to examine the impact o billconcessions in this context.

19

The Keypad Powershit trial was undertaken

with 200 Keypad (prepayment meter)

customers rom October 2003 to September

2004. 100 customers (“Price Message Group”

PMG) were given the Keypad time o day

(ToU) tari( 4 time bands, 3 rates). The ToU

rates were 5.76p/kwh low; 8.64p/kwh

medium; 15.36p/kwh high (9.146p / kWh was

the comparable fat rate price or Keypad

customers).

They were compared to a control group o

100 keypad customers who had a fat-rate

tari, but or whom the ToU bands were used

to enable comparison. The average annual

PMG spend was £371.98 compared to

£393.54 by the control group on the standardkeypad tari.

NORTHERN IRELAND TIME OF USE TARIFF TRIALS

But i the control group had had the

time-o-day price bands applied to their

usage pattern, they would have paid £377.60.

This suggests that that much o the saving or

the PMG may have been passive (i.e.

refecting lower use at peak periods by

keypad customers) rather than an active

response to the price signal. This may be

because they are at home during the day

(which was mostly o-peak) and thus using

appliances more at lower cost times.

46. The Institute or Electric Eciency (IEE) Whitepaper “The Impact o Dynamic Pricing on Low Income Customers” (2010)



Large households

Most trials have ound that smaller households (1-2

people) are more responsive (and thus more likely

to benet) rom time o use pricing than larger

households. The reasons or this are unclear – it

may be that it is less easy to control response with

more people in the household or that it is less easy

to be fexible about time o use. In an Ontario trialhouseholds with small children said they ound it

dicult to shit the times they did laundry.47

The one major exception was the Ireland smartmeter trials where households with childrenresponded most – this was attributed to theeects o educational initiatives in schools inIreland, which may result in children drivingbehaviour change in their household.48

The potential impact on households with 3 or

more occupants is an important consideration in

the Australian context. Larger households tend to

use more elecrtricity and thus may have particular

problems aording their electricity bills. IPART

ound that larger households are more likely to

have payment diculties than smaller households.

This is also the nding o research conducted by

Simshauser and Nelson based on AGL customers

in hardship.49

Likely impacts o time o use pricing in Australia The most detailed work in Australia on time o use

pricing and low income households was

undertaken by Deloitte or the Department o

Primary Industries (DPI) in Victoria in 2011 and

2012.50 Deloitte modelled a number o time o use

taris to test their impacts on dierent types o

customer. They produced two reports51 that assess

the potential impacts on domestic and small

business consumers o time o use pricing in

Victoria, with a ocus on vulnerable customers.

Deloitte’s key ndings included:

f The eects o Flexible Pricing on vulnerable

customers are likely to be highly variable both

among and within dierent groups. Eects are

dependent on the structure and level o taris,

existing tari levels, whether customers

currently have a controlled load o peak tari,

and how much customers alter theirconsumption in response to price changes.

f There were a broadly similar number o winners

and losers under all the modeled ToU taris -

although who wins and who loses diers

according to the tari design.

f Without elasticity (i.e. no change in usage)

- 52-57% o all residential consumers are better

o under the modeled taris. Deloitte also

modeled the impacts o taris on dierentgroups o vulnerable consumers.52 For elderly

consumers the range is 52-62% better o. For

needs assistance households the range is

47-48% better o. For most other groups at

least 50% o households are better o.

f Although the average customers in a

vulnerable group were only slightly better or

worse o, there was signicant variation. Some

customers may thereore experience large

annual bill changes.

f Under the Stage 2 modeled taris, with zero

elasticity, (no change in usage) average bill

impacts or all residential consumers ranged

rom +1% to –2.5%. With non-zero elasticity (a

change in usage), the average bill impacts

ranged rom –1% to –4.5%.

47. Hydro One Networks Inc. Time-o-Use Pricing Pilot Project Results. EB-2007-0086. May 2008.

48. Commission or Energy Regulation. Electricity Smart Metering Customer Behaviour Trials Findings Report CER/11/080a. May 2011.

49. Simshauser, P and Nelson, T. The energy market death spiral – rethinking customer hardship. AGL Applied Economic and Policy Research. Working Paper

No 31. June 2012.

50. Deloitte. Advanced metering inrastructure : consumer impacts study. Final report Volume 1 October 2011. Report or Department o Primary Industry

and Resources Victoria. & Deloitte. Advanced metering inrastructure : consumer impacts study. Stage 2. Final report. July 2012. Report or Department o

Primary Industry and Resources Victoria.

51. In Stage 1 Deloitte collected data rom electricity distributors and retailers. They combined these data with demographic actors to model the impacts on

dierent types o vulnerable households o a number o dierent taris. The Stage 1 data varied in both denition and quality, so questions arose as to the

applicability o identied time-o-use patterns. Stage 2 aimed to address these issues by using more data and market research. Stage 2 also included aquantitative telephone survey o 3,003 consumers to determine their sensitivity to price change and compare each vulnerable group with households not in

any vulnerable group. Six ocus group sessions were also held with vulnerable consumers, gathering their views on smart meters, Flexible Pricing and energy

aordability.

52. Modeling was a multi- stage process. Firstly they obtained load proles or all consumers in an area. Secondly, they obtained data on prevalence o types

o vulnerable consumers (e.g. low income, disabled) in that area. For areas with a high prevalence o a type o vulnerable consumer (e.g. disabled) the load

proles or those areas were then averaged and the result assumed to be the load prole or that type o vulnerable consumer.20



f Under the taris modeled in stage 2, 25% o all

households would ace bills at least 13% higher

than at present. 5% o all households would

ace bills at least 60% higher than at present.

f For dual element meter customers, shiting to

Flexible Pricing will mean that their hot water

(and/or slab heating) use is charged at the new

o peak rate, and so the impact will dependcrucially on whether this new rate is higher or

lower than their current controlled load o

peak rates.

Deloitte survey and ocus group ndings

f In the survey, all vulnerable groups, exceptHealth Care Card holders, expressed muchhigher sensitivity to bill increases thannon-vulnerable households. The highest levelso sensitivity were amongst Regional andSingle Parent households. All participants saidit would be dicult to shit their heating andcooling rom peak times. They were slightlymore likely to reduce consumption rather thanshit it, but said any change would be dicult.

21

f All participants o the ocus group sessionssaid that more inormation was needed onhousehold energy use, with many expressingrustration in understanding the connectionbetween their own appliance use and theirelectricity bills. Some participants expressed adistrust o energy companies and a belie thatgovernment should provide more inormation,

particularly to help them deal with the newpricing structures.

f Once the various concepts, reasons and issueswere explained ocus group participantsseemed to view Flexible Pricing as ‘air’ but insome cases ‘dicult’. In general, Critical Peak Incentives or Rebates were viewed moreavourably than Critical Peak Pricing, whileDirect Load Control o air conditioning wasviewed as problematic and unpopular. In

Home Displays were considered useul, witharound hal the participants indicating theywould be willing to pay a one o ee o $50-$100 to receive such a device



22

Findings

It is important to understand the nature o peak and overall demand to be able to design

appropriate solutions that will deliver value to customers and the electricity system.

Firstly, we do not know how ar it will continue to

increase and hence it will be very improtant to

review changes in trends and to try to

disaggregate the reasons or changes (e.g. energy

eciency measuers, own generation such as PV,behavioural change, economic restrucuring).

Secondly, we do not know how much value there

will be to the energy networks or retailers in

securing demand response – how will the costs

and risks compared to supply side solutions such

as more generation or network reinoocement ?

Thirdly, we do not know how willin g customers en

masse will be to provide demand response and

demand reduction. Fourthly, we do not know what

unintended consequensces ight result roma more

active demand side – e..g loss o revenue or some

market actors, dierential impacts on customers

who take up time o use taris and those who do

not.

Understanding peaks and where reductions in

demand will deliver value

There is clearly a considerable dierence between

peaks that are ocurring day in day out and peaksthat occur or only a ew occasions each year. I the

main issue in a particular electricity market or state

is critical peaks in summer (e.g. 4-5 pm on a ew

very hot days each summer) – something that may

apply particularly to network peaks - then a year

round time o use tari may not be very useul.53 A

better soution in this case might be critical peak

pricing or rebates or those times only – and

maybe some automation o response rom key

appliances such as air-conditioners.

53. I we are seeking to balance intermittent generation such as wind, or example, then demand response may be required year round.Even in these cases, however, automated demand response – e.g. using some orm o storage –and/or dynamic pricing may be a moreeective approach than year round time o use taris.

Such an approach may be particularlyt benecial

or vulnerable households based on some research

ndings as cited earlier. Direct load control may

also be better rom the perspective o retailers and

networks as it is more likley to provide certainty o response and thus to create ewer risks.

KEY FINDING: We need to be clear about what

types o demand response are most appropriate to

the problems that need to be addressed – day in

day out or a more limited number o critical peaks

and to tailor solutions appropriate to the problems

identiied – whether that be year round time o use

taris, critical peak pricing or direct load control.

Impact o demand management on vulnerable

households in Australia

Time o use pricing and other DSR methods may

oer beneits that would be valuable to many

customers. Price signals are important and do have

an impact - or better o households the incentive

o a gain or loss may be useul to motivate

behaviour change. But or vulnerable consumers

the position is more complex. Time o use pricing

and other DSR methods will add complexity andrisk into what is or many consumers an already

complex electricity retail market, with many taris

to choose rom. Many low income and vulnerable

households are stuggling to pay bills at present.

Risks that might be acceptable or better o

households are likely to be much more

problematic or low income households.



For some low income and vulnerable householdsthere are also potential health as well as nancialrisks – e,g, i new pricing encourages them tocurtail usage o heating and/or air conditioning totemperature levels that may be injurious to health.

The types o vulnerable household who are o most concern are those on low incomes who also

have other vulnerability actors – young children,very elderly, disabilities, nancial stress.Households with limited nancial literacy, orunderstanding o their energy usage may also beparticularly vulnerable, as they may be at risk o entering contracts that are inappropriate or theircircumstances and/or may not be able to makethe changes needed to benet.

A key issue then is how to identiy and target suchhouseholds or any assistance. This is where

proxies – such as bill payment diculties and/orconcession card status can oten be important.

We cannot predict the impact o time o use andother demand management measures onvulnerable households in Australia withoutknowing their circumstances. Impacts are likely tovary between vulnerable households dependentupon key actors including:

f whether they use electricity or heating (andwhether on peak or o-peak)

f whether they use electricity to heat water (andwhether on peak or o-peak)

f possession and extent o usage o airconditioning

f possession and usage o major electricityusing appliances such as clothes dryers anddishwashers

f number o people in the household

f whether they tend to be in the property in thedaytime or out most days

f size o the property

f insulation levels

f any particularly high needs or electricity (e.g.health related)

Average impact assessments are thereore notvery useul as the basis o policy decisions abouthow to implement DSR in respect o vulnerablehouseholds. There is such signicant variationbetween and within vulnerable groups that policyneeds to be more tailored to ensure that thosewho can benet rom DSR do so and that thosewould not benet are protected rom adverse

eects.

KEY FINDING: We cannot rely on tari designalone to avoid any negative impacts as any tari design creates winners and losers – vulnerablehouseholds will be in both groups whatever thetari design.

Are vulnerable households low users?

The data rom NSW suggest that low incomehouseholkds tend to be lower electricity usersthan better o households. Few low incomehouseholds in NSW use more than 8 MWh peryear and most use less than 6 MWh per year.However, there are some high users amongst lowincome households and many o them may beparticularly nancially stressed. In Victoria,households with vulnerable elderly, single income,low income and health care cards each spendsignicantly less on electrcity than the average

residential household.54

However, we need to see whether this distributionis also the case in other states and also howdemand splits between peak and o-peak uses.

23

54. Deloitte, 2011 report p.xx



Recommendations

ACTIONS TO BE TAKEN BEFORE DEMANDRESPONSE INITIATIVES ARE DEVELOPED AT SCALE

Energy eciency measures

There needs to be a concerted eort to use energyeciency measures to reduce overall and peak demand amongst all households, but with aspecial ocus on targeting such measures tovulnerable households. Such meausres should inparticular taregt those appliances that tend to beused at peak, such as air conditioning, on-peak (not slab) electric heating and on-peak electric hotwater, lighting and making homes perorm betterthermally through insulation. These measures willhelp to make vulnerable households more resilientto the development o demand side management,help to reduce their electricity bills, improvecomort and deliver environmental benets. Itwould be helpul to have a national ramework,with incentives to reduce peak as well as overall

demand, that allows or some fexibility to meetdierent circumstances in dierent states.

Recommendation to Governments:

To ensure that vulnerable households can beneitrom energy eiciency will require eective peak and overall energy savings schemes targeted tovulnerable households. This could includedesignating priority groups to beneit romassistance such as grants and low interest loans,plus appropriately tailored advice and inormation.

The ollowing recommendations are divided into two sections:

1. Actions that need to be undertaken soon and beore peak demand reduction

measures, such as fexible pricing and load control are developed at scale.

2. Actions that need to be taken in the lead-up to and during the implementation o

peak demand reduction measures.

Concessions ramework

Deloitte ound that, on average, there are notlikely to be signicant increases to vulnerablecustomers’ bills caused by Flexible Pricing and thatno changes were needed to electricityconcessions in Victoria, “provided the ToU tarisare oered on a voluntary or ‘opt in’ basis, andthat consistent inormation is provided tovulnerable customers on how Flexible Pricing

would aect them.”55 However, a comprehensivereview o electricity concessions was beyond thescope o the Deloitte study. A recent report by StVincent de Paul has highlighted that householodscurrently with a controlled load o-peak tari could lose out i they moved to one o the newtime o use taris because the Victorian o-peak electricity concession does not apply to thesetaris.56 Furthermore, the Victorian concessionramework has some notable dierences romother states. The AEMC recommended thatGovernments review their concessionsrameworks to see whether they will remainsuitable in the light o fexible pricing. (Power o Choice nal report).


The concessions ramework should be reviewedbeore lexible pricing is introduced to ensure theconcessions will remain appropriately targetedand to examine the scope or harmonisation o

concessions schemes between states.

24

55. Deloitte 2012 op, cit. p.11

56. Johnston, M. The relative value o energy concessions. St Vincent de Paul, January 2013. p.10



Recommendation to energy retailers and

welfare organisations:

Households receiving the o-peak concession inVictoria will need careul advice beore switchingto time o use taris that might result in themlosing the o-peak concession.

Under claiming o electricity rebates

The IPART study ound that between 14-22% o low income households in their survey areas didnot hold a concession card. They also ound thatmore than 20% o households that held aconcession card in Sydney did not claim rebates.IPART also ound that low-income households thatdo not hold a concession card tend to use moreenergy and water (mainly because they have more

occupants); and are more likely to be rentingprivately or paying o their homes, and thus maybe particularly inancially stressed. Thus it seemspossible that more than 30% o households whomight be able to claim an electricity rebate in NSWdo not do so.

In Victoria, a considerable discrepancy betweenthose who believe they are receiving a concessionand those who actually receive one was ound in amajor survey undertaken or the DHS. In 2007, 78%

o households who claimed to receive anelectricity concession actually received one. Itwould thereore seem that there may be manypeople missing out on the help with their bills thatis available under the concessions scheme.57

Recommendations to Governments:

There is a need or action irstly to clariy take uprates or concession cards and the electricityrebates that can be claimed. Secondly, to identiyhouseholds not holding concession cards or not

claiming rebates to improve take up amongst thisgroup.

Recommendation to Governments, energycompanies and welfare organisations:

Further work needs to be done to boost take up o concession cards and rebates amongst vulnerableconsumers who are not claiming them.

25

Low users

For very low consuming households some

research would be useul into why they are such

low users. I it is one or two people in a very small

lat, or a household using gas or heat, hot water

and cooking or a household with a solar PV, then

low consumption may be reaosnable. But there

may be some low consuming households who donot have gas or solar PV, or are not in a very small

property who are under consuming with potentail

health risks. Note that Hardship programmes tend

to ocus on people having diicult paying bills so

they may miss those who are under consuming to

avoid getting into bill diiculty. In the UK this is

well recognised as a problem particually amongst

elderly people who tend to be more averse to

getting into debt than younger people.

Recommendation to Governments and energycompanies:

There is a need or some research into low users.

This would help to indentiy whether this group

aces any particular problems such as “sel

rationing” or whether they are in act adopting

sensible energy management strategies that might

be useul or other hoseholds. The extent to which

they are claining concessio0n couild also be

assesssed.

Inormation, advice and data

All consumers should make decisions about

demand response options (load control and

lexible pricing) based on an understanding o

their electricity use and clear inormation on the

options avaiolable.

This is even more impirtant or vulnerable

households. Smart meters, in home dispalys andweb portals should enable consumer to have more

data on their current usage proile. A key issue is

how to ensure that households get acces to

devides such as in home displays – schemes such

as VEET are helping the diusion o these devices,

but there may be need or a more systematic

approach.

57. Roy Morgan research or Department o Human Services, Victorian Utility Consumption Household Survey 2007, Final Report, April2008



26

In Great Britain, all households will get an in home

display ree o charge with their smart meter – the

displays being installed at the same time as the

meter as part o the roll-out.

For some households comparison sites (which

need to be accredited to ensure they meet certain

standards) will be suicient – the household could

input their data rom their smart meter and work out whether a time o use taru would be a good

option or them. Some low income and vulnerable

households will be as able to make their own

choices, provdied they have suicient inormation,

as are other households . For others however,

there will be a need or a qualiied advisor to

provide an energy audit, and advice on the options

based on their circumstances. In some cases this

advice will be best perormed in the home.

Recommendation to Governments, energycompanies and welfare organisations:

There is the need or a concerted eort to increaseenergy awareness and understanding o peak andoverall demand usage o dierent appliancesamongst households. This will includeinormation and advice, in home displays etc.Particular eorts to be targeted to vulnerablehouseholds.

ACTIONS TO BE TAKEN FOR IMPLEMENTATION OFDEMAND RESPONSE

Marketing o Time o Use taris

When ToU taris are markted to customers then itis likely some who will not beneit will end upsigning up, given the experiences to date in retailenergy markets o poor customer choices wherecustomers switch to a worse deal. IPART’s 2010review o the retail market in NSW ound thatoutcomes or customers who had entered thecompetitive market were not uniormly positive.For example, some customers were unknowinglypaying rates higher than the regulated rates.58 In2008-09 almost all customers surveyed by Ogemsaid they switched to save money but as many asone third may not have achieved a price reduction. This was higher or consumers who switched as aresult o a direct sales approach.59

Recommendation to energy retailers:

Retailers should agree not to market time o use

taris to a deined group o low income and

vulnerable customers unless the customer has had

a smart meter or at least one year to establish

their load proile - one years’s data - that will help

them make the decision as to whether they would

beneit. It would actually be good practice not tomarket time o use to any customer without this

data.

Opt-in to Time o Use taris

In Victoria customers will have to opt-in to time o

use taris. The AEMC, in their Power o Choice

review, proposed dierent approaches or network

charges or household customers (which retailers

are then likely to pass on to households),according to whether they are or low, medium

and high users. The deault or low users will be no

time o use tari unless they opt in, the deault or

medium ussers is a time o use taru unless they

opt out, and high users will have to have a time o

use tari. The AEMC did not speciy the levels at

which these consumption bands should be set as

they consider this should be determined stater by

state in the light o state charactertistcs. However,

they did say that the threshold or consumers(Band 1) who would have madatroay time o use

pricing should be substantially above the average

consumption, so that it captures those consumers

with multiple heavy load appliances such as

electric vehicles, or large air-conditioning systems.


Adopt the opt-in approach to time o use taris or

all except the largest household customers (about

12 MWh per year) at least in the early years o such

taris.

58. Review o regulated prices and charges or electricity 2013-16. Electricity issues paper. IPART, November 2012.

59. Ogem. Op cit.



Recommendation to retailers, networks,

regulators and Governments:

Need to ensure eective co-ordination o policy

and practice on the use o time varying charging to

ensure that an opt-in policy works eectively.

Opt-out o Time o Use taris

The Victorian Government proposal to allocustomers to o opt out o time o use taris aterone year i the tari is not beneicial could behelpul – but customers may need advice oninterpreting the bill and making this decision. It ishowever, important to note the potential orcustomer inertia which may mean that manycustomers who should opt-out do not. For this tobe an eective protection thereore, cusomers

may need prompting to check whether theyshould stay on the time o use tari.


Make customers aware where they are payingmore on a time o use tari and hence should nowconsider whether they can do more to shit usageto o-peak times, to reduce their usage (e.g.through energy saving measures) or should beopting out o ‘time o use’.

It is also worth noting that the ability to opt-in andout o time o use taris could potentailly raise

risks and hence costs or retailers, i they have

purchased electricity on an assumption o time o

use response and/or are paying network charges

on this basis. It is thereore possible that retailers

would seek to mitigate these risks by including exit

ees or early termination o time o use contracts.


Provide customers with clear inormation on timeo use contracts , including whether they include“lock in” periods and early termination ees.

Automation/ direct load control

Automation oers the potential to deliver DSR (at

least or major loads such as air conditioning, hot

water and heating), with minimal price risk and

inconvenience to the customer and this may be

particularly beneicial or vulnerable customers.

27

However, there is evidence o some consumer

reluctance to accept automation. Direct Load

Control o air conditioning was viewed as

problematic and unpopular by particpants in the

ocus groups o vulnerable households conducted

by Deloitte in Victoria.60 In some trials it has been

ound to be more diicult to recruit households to

take part in direct load control than time o use

pricing options. Yet there are also considerable

numbers o households who do already have

experience o controlled load hot water and

heating in Australia and other countries.

The results o some trials also suggest that initial

doubt about participation can be mitigated by

providing consumers with the options to override

any automated response – even i many consumers

in act do not use the override unction. Thus it

may well be that automation could be a moreacceptable measure or many households,

provided that it is discussed with them ully

(including the scope to override), the beneits (bill

savings) are understood and they are able to

choose whether to accept it or not. Automation

may oer the potential to deliver DSR (at least or

major loads such as air conditioning, hot water

and heating), with minimal price risk and

inconvenience to the customer and this may be

particularly beneicial or low income and

vulnerable customers.

Automation may also require capital investment,

which some vulnerable households may not be

able to aord. It would thereore also be necessary

to consider whether and how these costs could be

unded.

Recommendation to energy retailers and

distributors:

Automation o response should be explored as a

measure that may have considerable potential or


60. Deloitte 2012 op cit.



Research agenda recommendations

We need much better data on household

electricity use amongst dierent types o

household to identiy where demand response

initiatives can deliver beneits to the electricity

system and consumers. Our uture research

programme will contribute to this. In particular we

intend to conduct research into low users,controlled load electricity and the potential uture

role o automation.

There is also need to make better use o the

indings o research and trials conducted to date

by Governments, energy companies and others.

There is an important data curation and sharing

task to be undertaken to obtain maximum beneit

rom this investment.

Conclusions

Peak demand presents a challenge or the

electricity system and addressing it should bring

the potential to reduce costs to the beneit o

consumers. However, it is important that we tackle

it sensibly and in ways that do not disadvantage


There is clearly a considerable dierence between

peaks that ocur day in day out and peaks that

occur or only a ew occasions each year. We

thereore need to be clear about the peak demand

problems that need to be addressed to enable us

to better to tailor appropriate solutions, whether

that be year round time o use taris, critical peak

pricing or direct load control.

Time o use pricing and other DSR methods may

oer beneits to many customers. Price signals areimportant and do have an impact - or better o

households the incentive o a gain or loss may be

useul to motivate behaviour change. However,

time o use pricing and other DSR methods could

add complexity and risk into what is or many

consumers an already complex electricity retail

market. Many vulnerable households are

struggling to pay bills at present.

Risks that might be acceptable or better o

households are likely to be much moreproblematic or low income households. It will

thereore be important than we take eective

action to help make vulnerable households more

resilient to a range o energy utures – including

tackling peak demand.

28



FURTHER INFORMATION

Monash Sustainability Institute

Building 74, Clayton Campus

Monash University, Victoria, 3800, Australia

T: +61 3 9905 9323

E: [email protected]

W: www.monash.edu/research/sustainability-institute

addressing peak demand: the opportunities and risks for vulnerable households

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