The retail electricity market for households and

small businesses in Victoria

Analysis of offers and bills

July 2017

2

Executive Summary This Report examines the electricity retail market in Victoria from the perspective of the

offers that are made to households and small businesses. It also examines a sample of

686 household electricity bills for electricity purchased over the period from December

2016 to April 2017.

The main objective of this Report is to establish quantitative evidence of whether the

retail market is delivering outcomes that are in customers’ interests. The three main

strands of analysis in this Report are retail electricity prices, the retailers’ charge for

their service of retailing electricity, and the savings that customers might obtain by

switching to other retail offers.

Prices

The price of electricity to customers depends on many factors but most notably their

level of consumption, the pattern of their consumption (if they are on time-variant

tariffs), their location and the prices in their contracts with their retailer. The analysis of

retailers’ offers shows a wide range of prices even for the same customer profile. The

analysis of the sample of bills also shows a wide range between highest and lowest

although the median price amongst the popular retailers is similar.

The average price of electricity for the cohort of customers in the sample consuming

3.75% above and below 4,000 kWh per year, is 34.7 cents per kWh (after GST). This is

15% higher than the estimate of the representative electricity price for households in

Victoria, produced by the Australian Energy Markets Commission (AEMC)1. The

difference is likely to be partly explained by the AEMC’s assumption that customers are

always on their retailers’ cheapest offers.

1 A like-for-like comparison of average prices charged by the Big Three retailers finds that they

are 22% higher in the sample than the AEMC’s latest estimates – see page 57.

3

Retailers’ charges

The amount that retailers charge for their services is not separately itemised on

customers’ bills. Instead it has to be deduced by subtracting the known or estimated

charges for the other elements (the purchase of wholesale electricity, charge for

network and metering and environmental levies) that together with the retailers’

charge make up the bill that the customer is charged. The breakdown of the bill for the

representative customer in the sample is shown in Figure E1.

Figure E1: Disaggregation of average household electricity bill from sample

Looking at the estimate of the retailers’ charge across the sample, we find that for three-

quarters of customers, the retailers’ charge is more than the wholesale charge, and for

households in three of the five distribution areas, the retailers’ charge is higher than the

network charge for most customers.

The retailers’ charge in Victoria is remarkable by comparison with the estimated

retailer charge in other European countries, many of which have fully or partially

deregulated retail energy markets. Figure E2 below presents this comparison where the

retailers’ charge (on the Y-axis) is presented in cents per kWh.

$423%

$415%

$263%$88%

$55% $18%

$126%

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

Retailer's%%%%%%%%%%%%%%%%%charge

Network%%%%%%%%%%%charge

Wholesale%%%%%%%%%%%%%%charge

Metering%%%%%%%%%%%%%charge

Federal%environmental

Victoria%environmental

GST

Representativehousehold electricity%bill%from%sample%

4

Figure E2: Cross-country comparison of retailers’ charges for their retail service, to residential customers (cents per kWh)

While the range of the retailers’ charge in the sample bills varies considerably, the

retailers with the greatest number of bills in the sample (corresponding to their market

share in the population) tended to have the highest retailer charge as a proportion of

their customers’ bills, as shown in Figure E3 below:

!

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

Victoria

New

%South%W

ales

South%Au

stralia

Queensland

Great%Britain

Ireland

Germany

Holland

Slovakia

Luxumbourg

Belgium

Austria

Greece

Sweden

Slovenia

EU%Average

Poland

Finland

Italy

Norway

Spain

Denm

ark

France

Portugal

Hungary

Estonia

Lithuania

Retailers'%charge%%(A

ustralian%cents%p

er%kW

h)

5

Figure E3. Distribution of retailer charges as a percentage of total bill (after GST), by retailer

For most households in the sample, the retailers’ charge for its services is the biggest

single component of their electricity bill. About three out of four households in the

sample are paying more for electricity to be sold to them by their retailers than they are

paying for it to be produced by generators.

Comparing the retailers’ charge with the charge for network services, the analysis finds

that in three out of the five distribution regions in Victoria, most households are being

charged more for electricity to be sold to them than they are paying for it to be

transported over the transmission and distribution network.

The estimate of the retailers’ charge in the sample of bills is affected by assumptions of

the wholesale price. The conclusion that the retailers’ charge is more than the wholesale

charge is robust to far higher estimates of the wholesale price than the one used in this

report.

6

Saving by switching

A well established narrative in the discourse on retail energy markets in Australia is

that customers can save significantly by switching supplier. This report tested this by

analysing the savings that customers in the sample would receive if they switched to

the least expensive offer. The analysis found that customers in the sample could, on

average, reduce their bills by $294 per year, or around 21% by switching to the least

expensive offer. Segmentation of the savings into three clusters is shown in Figure E4.

Figure E4: Switching savings in three clusters

•   The “Low saving” cluster accounts for 204 out of the 686 bills. The median

saving for customers in this cluster is $84 per year.

•   The “Moderate saving” cluster has 280 bills and a median saving of $223 per

year.

•   The “High saving” cluster has 155 bills with median saving of $501 per year.

In addition to bills in these three clusters, there were 33 bills that were cheaper than any

offer in the market and there were 8 bills with savings of more than $1,000.

The analysis of switching savings also shows that customers served by the retailers

with the greatest number of customers in the sample will tend to save more than

customers of other less popular retailers.

This analysis assumes that customers are able to identify the least expensive offer for

themselves taking account of their consumption profile, whether or not they have

7

controlled load or solar, their location and their tariff type. It also assumes that

customers are able to access and evaluate all the relevant competing offers and that the

cheapest offers for them remain available for at least a year (or that customers switch to

comparably cheap offers if the chosen offer changes).

These are onerous assumptions and so the analysis tested the savings that customers

might obtain if they switched to the second, third, fourth and up to the tenth cheapest

offer. This found that the savings reduced considerably so that if the customer switched

to the fifth cheapest offer, the median saving in the sample would be less than half

what it would be if they switched to the cheapest offer. This suggests that the narrative

that customers can reduce their bill by switching should be tempered by the evidence

that the extent of savings depends greatly on customers’ ability to identify and switch

to the cheapest offer – and continue to switch again if the cheapest offer changes.

Finally the analysis of switching saving considered the extent to which customers

might reduce their bills by switching to the least expensive offer from their own

retailer. This also showed a wide range of savings for bills in the sample. However, the

median saving that customers might achieve by switching to the lowest offer from their

own retailer is considerably lower than the saving that they might achieve by switching

to the lowest offer in the market.

8

Table of Contents

1   Introduction   13  

Part A

2   Description  of  the  retail  market   15  

2.1   Customer  numbers   15  2.2   Retailers  and  retail  offers   16  2.3   Fixed  versus  variable  charges  in  retail  offers   22  2.4   Discounts   24  2.5   Incentives   27  2.6   Network  versus  retail  charges   27  2.7   The  comparison  challenge   30  

3   Bill  disaggregation  based  on  retail  offers   34  

3.1     Method   34  3.1.1 Estimating  the  bill   34  3.1.2 Estimating  the  wholesale  charge   37  3.1.3 Estimating  network  charge   40  3.1.4 Estimating  environmental  charges   40  3.1.5 Metering  charges   41  3.1.6 GST   41  

3.2   Results   41  

4   Inter-­‐‑state  and  international  comparison  of  prices  and  retailer  

charges  in  residential  offers   43  4.1   Prices   44  4.2   Retailer  charges   44  

Part B

5   Sample  data  description   46  

6   Retailers’  charges  in  the  sample  bills   58  

7   Switching  savings   71  

9

7.1   Savings  by  switching  to  the  least  expensive  offer  in  the  market   72  7.2   Cluster  analysis  of  saving   76  7.3   Impact  of  ability  to  identify  cheapest  offer   77  7.4   Savings  by  switching  to  the  least  expensive  offer  from  the  

existing  retailer   78  

Appendix  A:  Data  and  analytical  tools   82  

Appendix  B:  Load  profile  assumptions   83  

10

Table of Figures Figure 1. Box plot of annual charge ($)by retailer assuming 4 MWh per year ....... 19  Figure 2. Box plot of annual charge ($)by retailer in Powercor area assuming 4

MWh per year .................................................................................................. 19  Figure 3. Analysis of residential time of use tariffs (market offers) ......................... 20  Figure 4. Offer duration: number of days before 14 May 2017 when offers

were introduced to the market (all market offers, residential and

small business) ................................................................................................. 21  Figure 5. Scatter plot of fixed versus total charge in residential market offers

(assuming 4 MWh annum household) ......................................................... 23  Figure 6. Scatter plot of fixed and variable charges in residential market offers ... 23  Figure 7. Histogram showing frequency of annual charges (before-GST) with

and without conditional discounts (assuming a 4 MWh per year

household) ........................................................................................................ 26  Figure 8. Histogram showing frequency of annual charges (before-GST) with

and without conditional discounts (assuming a 10 MWh per year

small business) ................................................................................................. 26  Figure 9. Total retail charge minus total network charge ($ per year) 4 MWh

per annum household ..................................................................................... 28  Figure 10. Variable retail charge and variable network charge ($ per year) 4

MWh per annum household ......................................................................... 28  Figure 11. Fixed retail charge and fixed network charge ............................................. 29  Figure 12. Annual fixed retail and fixed network charge less metering charge ....... 29  Figure 13. Offer duration, all market offers, residential customers at 30 May

2017 .................................................................................................................... 38  Figure 14. Residential bill disaggregation based market offers, 4 MWh p.a. ........... 42  Figure 15. Small business bill disaggregation, 10 MWh p.a. ....................................... 42  Figure 16. Comparison of residential electricity prices (before and after tax)

(Australian cents per kWh) (May 2017 prices in Australia, 2015

prices in European countries) ........................................................................ 44  Figure 17. Inter-state comparison of retailer charges to residential customers ........ 45  Figure 18. Comparison of retailer charges to residential customers (cents per

kWh) .................................................................................................................. 45  Figure 19. Distribution by tariff type and network service provider ......................... 47  Figure 20. Distribution of tariff type by retailer ............................................................ 47  

11

Figure 21. Density distribution of daily consumption by cluster and in

aggregate .......................................................................................................... 48  Figure 22. Fixed charges versus total bill ($ per year) .................................................. 50  Figure 23. Annual fixed retail, fixed network and metering charges ........................ 50  Figure 24. Distribution of discounts by network service provider ............................ 51  Figure 25. Description of discounts ................................................................................. 52  Figure 26. Switching saving: impact of discount rate ................................................... 53  Figure 27. Description of retailers’ solar feed-in rates .................................................. 54  Figure 28. Distribution of the estimated annual bills ($ per customer per year)

in each distribution zone ................................................................................ 56  Figure 29. Retailers' charge ($ per year) versus wholesale price ($/MWh) .............. 60  Figure 30. Residential bill disaggregation based on average bill from sample (4

MWh) ................................................................................................................ 63  Figure 31. Histogram of the difference between network and retailers' charges ..... 64  Figure 32. Histogram of the difference between wholesale and retailers'

charges .............................................................................................................. 64  Figure 33. Histogram of retailers' charge by network service provider area ............ 65  Figure 34. Distribution of retailer charges as a percentage of total bill (before

GST), by retailer ............................................................................................... 67  Figure 35. Cross-country comparison of retailers' charge (cents per kWh) using

sample of bills .................................................................................................. 68  Figure 36. Ratio of retailers' charge to wholesale charge ............................................. 70  Figure 37. Distribution of annual saving by selecting the cheapest offer, by

network service provider area ....................................................................... 73  Figure 38. Distribution of saving (as a percentage of total bill) by selecting the

cheapest offer, by network service provider area ...................................... 73  Figure 39. Impact of controlled load on saving (as a percentage of the total bill)

by selecting the cheapest offer ....................................................................... 74  Figure 40. Impact of solar on saving (as a percentage of the total bill) by

selecting the cheapest offer ............................................................................ 75  Figure 41. Distribution of savings by cluster ................................................................. 76  Figure 42. Switching savings in three clusters ............................................................... 77  Figure 43. Distribution of saving ($ per customer per year) by switching to

cheapest market offer versus lowest existing retailer offer ...................... 79  Figure 44. Median saving ($ per customer per year) by switching to the lowest

market offer versus lowest offer from customers’ existing retailers ....... 80  

12

Figure 45. Relationship between switching saving and retailers’ market share

in actual bill sample ........................................................................................ 81   Table of Tables Table 1. Actual number of customers by tariff type - residential ................................... 16  Table 2. Actual number of customers by tariff type – small business ........................... 16  Table 3. Number of offers (market and standing) to residential and small

business by distribution area ................................................................................ 17  Table 4. Number of offers (market and standing) residential customers ...................... 18  Table 5. Variable charges in flat and block offers to residential customers

(market offers) ......................................................................................................... 20  Table 6. Variable charges in flat and block offers to small business customers

(market offers) ......................................................................................................... 20  Table 7. Summary statistics on daily charges in residential retail offers ....................... 22  Table 8. Summary statistics on daily charges in small business retail offers ................ 22  Table 9. Summary statistics on discounts in market offers to residential

customers ................................................................................................................. 24  Table 10. Summary statistics on discounts in market offers to small business

customers ................................................................................................................. 25  Table 11. Retailer market share in sample compared to population ................................ 49  Table 12. Summary information of discounts by type and incidence ............................. 52  Table 13. Summary statistics of estimated annual bills ($ per customer per

year) .......................................................................................................................... 55  Table 14. Summary statistics of estimated annual prices (cents per kWh) ..................... 57  Table 15. Analysis of average and median bills in the sample ......................................... 61  Table 16. Summary statistics on retailer charges for their services ($ per

customer per year) .................................................................................................. 66  Table 17. Summary statistics of estimated saving from switching to the lowest

market offers ($ per customer per year) .............................................................. 72  Table 18. Relationship between switching saving and selection of alternative

offers ......................................................................................................................... 78  

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1   Introduction

This Report provides quantitative information on the electricity retail market in

Victoria using data from publicly available offers and from a sample of customers’ bills.

The Report covers the retail market applicable to residential and small business

customers.

This Report has two main parts:

•   The first part (in Sections 2, 3 and 4) analyses the offers that retailers make to

new customers, in order to estimate bills, prices and retailers’ charges for their

services and compare these nationally and internationally.

•   The second part (in Sections 5, 6, and 7) analyses a sample of 686 residential

electricity customer bills. The analysis of these bills provides information based

on what customers are actually paying and answers other questions, such as

how much retailers are charging for their services and how much customers

could save by switching to the cheapest retailers.

To delineate these two separate strands of analysis, Sections 2, 3 and 4 form Part A, and

Sections 5 to 7 form Part B. The Appendices describes the tools used to undertake the

analysis.

The graphical representations used in this report are common in data science and

statistics but are not always widely used in energy economics and policy studies in

Australia. A summary of the graphical depictions used in this Report are as follows:

 

•   Histogram: this depicts the distribution of the data by displaying the number of

data items with values corresponding to the count of those data items (on the x-

axis) corresponding to the value depicted on the Y-axis.

•   Box plots: this depicts the range of the chosen data item by drawing the box that

shows the values between the 25th and 75th percentile. The median of the range

is shown as a bar in the box and “whiskers” in the box show the range of the

data 1.5 times the difference in the 25th and 75th percentile.

14

•   Dot plots: this shows the median value of the range as the dot and the bars

either side of dot as the limits of the range of the data.

•   Scatter plot: this plots the relationship between two variables. Where

applicable, we have included lines of best fit of the data based on linear

regressions. Where applicable we also show the “R-squared” error which

measures how well the line of best fit, fits the data (an R-squared error of 1 is a

perfect fit).

15

2   Description of the retail market

This section describes the Victorian retail electricity market. It describes, in order,

customer numbers, retailers and retail offers, fixed versus variable charges in retail

offers, discounts, and retail versus network charges.

2.1   Customer numbers

There are around 2.4 million residential electricity accounts and 340,000 small business

electricity accounts. A wide variety of tariff structures are used and these can be

summarised under five headings:

•   Block tariffs: These are tariffs which charge different amounts for blocks of

consumption metered daily, monthly or three monthly. There may be between 2

and 4 blocks. Some retailers have seasonal block charges but this is rare. A daily

charge is also levied.

•   Flat tariffs: This tariff has a single rate for consumption and a daily charge.

•   Time of Use: This is a tariff that has different charges in two periods. For

residential customers the peak period is from 7am to 11pm Monday to Friday.

For business customers peak is from 8am to 10pm seven days a week. Some

retailers use different time definitions but this is rare. Some retailers charge for

the peak period in varying blocks, but this is rare. A daily charge is also levied.

•   Flexible tariffs: This is a tariff with charges in peak, shoulder and off-peak

periods. Some retailers charge for the peak period in varying blocks, but this is

rare. Flexible tariffs can have seasonally varying charges but this is rate. A daily

charge is also levied.

Some customers also have dedicated circuits for the purpose, mainly, of water heating.

The dedicated charge is a single cents per kWh rate. In addition to these tariffs, tariffs

that charge for household peak demand have been introduced but there are almost no

customers on these tariffs. Table 2show the number of residential and small business

customers classified by tariff type. The main observation in relation to residential

customer is that around 2 million of the 2.3 million accounts are flat or block tariffs and

of this 2 million around 15% also have dedicated circuit tariffs.

16

Table 1. Actual number of customers by tariff type - residential

Dedicated

circuit

Block or flat

without dedicated

circuit

Block or flat with

dedicated circuit

Two-part time-of-

use Flexible TOTAL Ausnet 99,322 391,368 99,322 62,873 - 652,885 Jemena - 275,000 - 16,927 1,100 293,028 United 13,300 490,566 13,300 24,702 - 541,868

Powercor 175,123 351,312 175,123 161,899 76 863,534 Citipower 27,052 207,504 27,052 41,342 23 302,973

TOTAL 314,797 1,715,751 314,797 307,744 1,199 2,339,490

The main observation in relation to small business customers is that a little more than

half have time-varying offers. For both residential and small business customers,

flexible (three part time of use) tariffs have a small number of customers.

Table 2. Actual number of customers by tariff type – small business

 Single  rate  

Time-­‐of-­‐use   Flexible   TOTAL  

Ausnet   27,113   81,200   3,226   111,539  Jemena   15,361   11,237   -­‐   26,599  United   37,017   18,236   -­‐   55,253  

Powercor   40,081   48,835   -­‐   88,916  Citipower   25,007   28,772   -­‐   53,779  TOTAL   144,578   188,280   3,226   336,085  

2.2   Retailers and retail offers

Twenty-four retailers offer to sell grid-supplied electricity to households and/or small

business electricity consumers in Victoria. Almost all of these retailers make “market”

offers and “standing” offers. Retailers have discretion in setting the prices in these

offers, but are restricted from changing their standing offers more than twice per year.

Retailers are required to post the terms of their offers in electricity price fact sheets on

their websites. In total on 11 May 2017 there were 2,841 offers to residential and small

business customers in the five regions of Victoria on the Victorian Government’s

Switchon price comparison website as summarised in Table 3 below.

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Table 3. Number of offers (market and standing) to residential and small business by

distribution area

Retailer / network service

provider ausnet citipower jemena powercor united energy

agl 23 18 24 30 26 alinta 5 6 6 5 6

bluenrg 9 9 9 7 9 click 33 32 33 21 33

commander 25 19 20 25 24 covau 14 15 14 8 14

diamond 9 11 10 9 9 dodo 11 11 12 15 14

ea 18 18 18 18 18 erm 9 9 10 8 7

firstenergy 12 12 12 12 11 globird 14 27 16 14 13

lumo 37 37 37 37 37 momentum 37 37 30 39 41

next 12 14 13 12 11 origin 40 40 40 40 40 pacific 12 18 14 23 12

peopleenergy 6 6 6 7 6 powerdirect 6 9 7 7 7 powershop 11 12 11 8 11

qenergy 27 36 19 13 20 redenergy 7 10 10 14 10

simply 44 41 40 46 47 sumo 21 21 21 21 21

TOTAL 442 468 432 439 447

The choice of offers available to customers is often limited by their type of tariff, with

many retailers not offering to change customers to a different type structure. Table 4

shows the number of market and standing offers by retailer, classified by tariff type to

residential customers

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Table 4. Number of offers (market and standing) residential customers

Retailer   Block  and  flat  

Time  of  use   Flexible    

agl   49   41   0  alinta   18   10   0  bluenrg   9   4   0  click   65   30   3  commander   25   53   0  covau   18   8   8  diamond   15   9   8  dodo   23   14   10  ea   40   20   15  firstenergy   19   10   0  globird   31   16   13  lumo   70   35   20  momentum   39   35   19  next   10   5   0  origin   80   40   80  pacific   23   24   0  peopleenergy   10   6   0  powerdirect   21   10   0  powershop   20   9   9  qenergy   21   28   6  redenergy   20   11   5  simply   64   58   10  sumo   30   15   12  sumo   45   45   12  TOTAL   765   536   230  

To show the range of the offers made by each retailer and in comparison to other

retailers, Figure 1 shows box plot of the annual charge in market offers that each

retailer make to residential customers. The calculation in this chart assumes all

conditional discounts are received. Part of the range show in these box plots is

explained by differences in the various network service providers, reflecting different

network service provider chargers. To adjust for this, Figure 2 shows box plots for

offers in just one network service provider area (Powercor). Relative to Figure 1 it

shows a narrower, but still wide range of offers from most retailers and also amongst

retailers.

19

Figure 1. Box plot of annual charge ($)by retailer assuming 4 MWh per year

Figure 2. Box plot of annual charge ($)by retailer in Powercor area assuming 4 MWh per year

Table 5 presents summary statistics on the variable charges in flat and block tariffs for

residential customers. It shows that block tariffs typically have higher rates than the

variable rate in flat offers and also that the median rate in block offers barely varies

between blocks. Table 6 for small business customers shows that median and average

flat rates are about 10% higher than for residential customers, while block rates are

about the same.

20

Table 5. Variable charges in flat and block offers to residential customers (market offers)

Block tariffs

Flat rate

(cents per kWh)

Block 1 (cents per

kWh)

Block 2 (cents per

kWh)

Balance rate (cents per kWh)

Highest 35.4 41.7 33.7 38.5 Lowest 14.1 10.9 22.7 11.2 Median 25.8 27.7 28.6 28.5 Average 25.2 27.1 28.8 26.9

Table 6. Variable charges in flat and block offers to small business customers (market offers)

Block tariffs

Flat rate

(cents per kWh)

Block 1 (cents per

kWh)

Block 2 (cents per

kWh)

Balance rate (cents per kWh)

Highest 48.8 40.9 37.7 45.3 Lowest 15.3 12.6 22.7 12.4 Median 27.5 26.6 27.8 26.6 Average 27.6 26.8 29.0 27.0

Figure 3 analyses the residential time of use offers. It shows that the off-peak rate

ranges between a low of just under 10 cents per kWh to a high of more than 27 cents

per kWh. It is also notable that the difference between the peak and off-peak rates

varies over a very wide range.

Figure 3. Analysis of residential time of use tariffs (market offers)

0

5

10

15

20

25

30

0 5 10 15 20 25 30

Off-peakrate(centsperkWh)

Peakminusoff-peakrate(centsperkWh)

21

In addition to the generally available retail offers that are posted on retailers’ website,

some retailers make bespoke offers that are not generally available and so the terms of

these offers are not included on their websites. An example of such bespoke offer is

Origin Energy’s “Predictable Power” plan which offers fixed monthly charges for 12

months.

Retailers update their market offers frequently. Many of them change their market

offers around a few dates such as the start of the year but again several other times a

year. Figure 4 shows that around 25% the 1,476 market offers to households and small

businesses on 14 May 2017, were introduced around the start of the year, with the

remaining 75 % introduced mostly more recently. It should be noted that Figure 4 is

obtained by analysing market offers based on their offer dates. We are aware of at least

one instance where rates have been changed but the date of the revised offer stayed the

same as the original offer. The data shown in Figure 4 might therefore be considered to

be a conservative estimate of the spread of offer duration.

Figure 4. Offer duration: number of days before 14 May 2017 when offers were introduced to

the market (all market offers, residential and small business)

0

100

200

300

400

500

600

20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500

Numbero

foffers

Noofdaysbefore14May2017

22

2.3   Fixed versus variable charges in retail offers

Fixed charges (the daily charge) in residential electricity offers in Victoria are typically

higher than elsewhere in Australia and higher than we have observed in any other

electricity market. Summary statistics of the fixed charge on residential retail offers2 in

Victoria is shown in

Table 7 below.

Table 7. Summary statistics on daily charges in residential retail offers

Daily charge

(cents per day)

Highest 260

Lowest 72

Median 114

Average 114

Table 9 for small business customers shows that median and average daily rates, by

comparison with Table 7 are about 20% higher than for residential customers.

Table 8. Summary statistics on daily charges in small business retail offers

Daily charge

(cents per day) Highest 365 Lowest 53 Median 138 Average 146

The proportion of the customers’ bill that is accounted for by fixed charges will depend

on many factors, but particularly their annual consumption and the discounts in their

offers. The lower the consumption the greater the proportion of the bill that is

explained by fixed charges. In addition, as described later in more detail, the

predominant discount in retail offers is to discount usage charges rather than the total

bill. This enlarges fixed charges relative to consumption charges. Figure 5 shows the

range of fixed charges (on the y-axis) and total charge assuming that all conditional

discounts in offers that have them, are met.

2 Excluding the handful of “Climate Saver” offers in the Powercor area.

23

Figure 5. Scatter plot of fixed versus total charge in residential market offers (assuming 4

MWh annum household)

Figure 6 narrows the focus to examine the scatter plot of the variable charge in flat

offers (on the Y-axis) relative to the fixed charge on those same offers. It shows,

interestingly that that there is no consistent relationship between fixed and variable

offers: the flat (variable) rate varies over much the same range irrespective of the level

of the fixed charge.

Figure 6. Scatter plot of fixed and variable charges in residential market offers

$100

$200

$300

$400

$500

$600

$700

$500 $700 $900 $1,100 $1,300 $1,500 $1,700 $1,900

Fixedcharge

Totalcharge

0

5

10

15

20

25

30

35

40

65 85 105 125 145 165

Flatrate(centsperkWh)

Dailycharge(centsperday)

24

2.4   Discounts

Table 9 presents summary statistics on discounts in market offers to residential

customers. It shows that of the 1,270 residential market offers in May 2017 there were

247 that did not have any discount. 738 offers had a discount on usage charges, of

which almost all were conditional discounts. Similarly of the 285 offers that had

discounts on the total bill, all of these were conditional (based on the way that the

retailers depict their offers in Switchon)3.

Table 9. Summary statistics on discounts in market offers to residential customers

Number of offers

Median Average Highest Lowest

Discount on Total (conditional and unconditional)

285 10% 17% 34% 1%

Of which unconditional 0 0 0 0 0

Of which conditional 285 10% 17% 34% 1% Discount on Usage (conditional and unconditional)

738 22% 22% 40% 0%

Of which unconditional 75 18% 16% 22% 0%

Of which conditional 663 26% 22% 40% 0% No discount 247

TOTAL 1270

Table 10 provides summary statistics on discounts in market offers to small business

customers. It shows generally similar outcomes to those for residential customers

although discounts are much less prevalent in business offers although those do offer

discounts typically offer discounts that are more commonly unconditional, at least

relative to what they offer to residential customers.

3Specifically, Powershop includes an unconditional discount in its Standard Saver offers’ fact

sheets but it factors this in to its price and only shows a conditional discount in its depiction of

these offers in Switchon.

25

Table 10. Summary statistics on discounts in market offers to small business customers

  Number  of  offers  

Median   Average   Highest   Lowest  

Discount    on  Total  (conditional  and  unconditional)  

132   0%   0%   0%   0%  

Of  which  unconditional   0   0   0   0   0  

Of  which  conditional   132   0%   0%   0%   0%  Discount  on  Usage  (conditional  and  unconditional)  

397   10%   22%   42%   0%  

Of  which  unconditional   162   28%   26%   42%   0%  

Of  which  conditional   235   20%   19%   40%   3%  

No  discount   219          

TOTAL   748          

Discounts are clearly a significant part of most Victorian retail electricity offers.

However, notwithstanding this, it is notable that the least expensive offers are not

actually those with the highest discounts. For example, ranking the 10 cheapest offers

for a 4 MWh per year residential customer on a flat or multiflat tariff in Citipower’s

area. The two least expensive offers had no discount, the fourth least expensive had just

a 1% discount. The remaining six however had an average discount of 36%. The same

pattern is seen in other distribution areas for both residential and small business

customers.

The conditions in conditional discounts relate most frequently to on-time bill payment

and the acceptance of direct debt, or on-line only accounts or payment in advance. A

wide diversity of approaches are applied by retailers in the specification of their

discounts. A combination of discounts are sometimes offered. Some of the most recent

offers link discount rates on consumption to the solar feed-in rate this is offered (a

lower discount on consumption implies a higher feed-in rate and vice versa).

Discounts are sometimes fixed for the duration of what is often referred to as the

“benefit period” at the end of which they may be varied or withdrawn. Benefit periods

are typically one year, but in some offers extend to two years.

As might be expected, with such large conditional discounts, the annual bill in many

residential offers will be significantly affected by whether the conditions in the discount

are satisfied. This is shown in Figure 7 which shows the annual charges on the offers

26

with conditional discounts. It shows that if the conditions are not met, annual charges

are typically in the range from $1,300 to $1,500 per year. If the conditions are met, the

annual charge is most frequently in the range from $1,100 to $1,200 per year

Figure 7. Histogram showing frequency of annual charges (before-GST) with and without

conditional discounts (assuming a 4 MWh per year household)

Figure 8 replicates the analysis in Figure 7 for small business customers. Unsurprisingly

the same trend for small business customers can be seen as for residential customers.

Figure 8. Histogram showing frequency of annual charges (before-GST) with and without

conditional discounts (assuming a 10 MWh per year small business)

0

50

100

150

200

250

300

350

400

450

Freqency

alldiscountsreceived onlyunconditionaldiscounts

0

50

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400

Frequency

alldiscountsreceived onlyunconditionaldiscounts

27

2.5   Incentives

In addition to discounts, some retailers offer various incentives mainly to entice new

customers. These incentives tend to be fleeting and only some retailers include relevant

details in their fact sheets. Examples of incentives in the market at the time of writing

this report include:

•   A $50 reduction in your first bill if you call the retailer and they don’t attend to

your call in two minutes.

•   Free electricity for the 12th month after joining the retailer;

•   A $50 reduction in the first bill if the customer joins the retailer directly rather

than via a switching site.

•   An allocation of airmiles if the customer joins the retailer and stays with them

for a defined period of time.

•   One cinema ticket per month for each month that the customer stays with the

retailer, for the first 10 months.

These fleeting incentives are not priced in the assessment of retail prices or margins in

this Report.

2.6   Network versus retail charges

As discussed in the next section, the charge for retailing electricity (the “retailers’

charge”) and the charge for network services are typically the two largest components

of the residential electricity bill. A question frequently asked is how network and retail

charges relate to each other. This subsection explores the data on this. Three figures are

presented showing in order total retail versus total network, and then the variable retail

versus variable network and finally the fixed retail versus fixed network charges. The

dataset used here is the average of the median offers (assuming all discounts are

achieved) for AGL, Origin Energy and Energy Australia which together supply around

70% of all Victorian households. Figure 9 shows that for the average of the median

offers, these retailers adjust their retail offers to reflect the network charges so that the

difference between the total retail charge and total network charge is approximately the

same across all five distribution areas.

28

Figure 9. Total retail charge minus total network charge ($ per year) 4 MWh per annum

household

Figure 10 shows, in addition that retailers set their variable charges so that their net

income after subtracting variable network charges is approximately constant, and about

half the level of the total variable retail charge.

Figure 10. Variable retail charge and variable network charge ($ per year) 4 MWh per annum

household

Figure 11 shows that the difference between the income retailers obtain from fixed

charges on their median offers is approximately constant across distribution region.

However comparing the relative size of the orange and grey bars in Figure 10 and 11, it

is clear that retailers set their fixed charges in such a way that their mark up on the

network service providers’ fixed charges is far higher than their mark up on the

network service providers’ variable charges.

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

Ausnet Citipower Jemena Powercor United

Retailm

inusne

twork

Retail Network Difference

$0

$100

$200

$300

$400

$500

$600

$700

$800

$900

$1,000

Ausnet Citipower Jemena Powercor United

Retailminusnetwork(variablecharge)

Retail Network Difference

29

Figure 11. Fixed retail charge and fixed network charge

The difference in Figure 11 might be explained as reflecting the dominant pricing policy

that is chosen. It might also be argued to reflect, in part, retailers’ approach to the

recovery of consumption-invariant smart meter charges from network service

providers (this charge is described in the next section). Figure 12 shows the difference

between the fixed retail charge and the fixed network charge after deducting the

metering charge for a single phase single element meter (the predominant residential

meter). In this case the gap between this difference and the retail charge is much bigger

than shown in Figure 11.

Figure 12. Annual fixed retail and fixed network charge less metering charge

It is necessary to caution against drawing a conclusion from this is that the meter

charges explain why fixed retailer charges are higher in Victoria than in other states. In

any market there is no “correct” way to recover the charges that retailers incur, in the

structure of the charges that they set in their offers to their customers. Retailers might

$0

$50

$100

$150

$200

$250

$300

$350

$400

$450

$500

Ausnet Citipower Jemena Powercor United

Retailminusne

twork(fixedc

harge)

Retail Network Difference

$0#

$50#

$100#

$150#

$200#

$250#

$300#

$350#

$400#

$450#

$500#

Ausnet Citipower Jemena Powercor United

Fixed#charge

Retail Network Metering# Retail#E network#E metering

30

suggest that they set their retail fixed charges to recover the cents per day metering

charges that they incur. But the evidence does not support this claim: the cents per day

fixed charges have not declined as the metering charges have declined. To the contrary

in almost all cases they have increased. For example in 2017, the weighted average

metering charge to households declined by $25.40 compared to the previous year. Yet

the median fixed charge in all retail offers to households in the market on 31 December

2016 was $401.30 per year, but for all the offers in the market on 12 May 2017 it had

risen to $412.45. Only a small part of this difference is explained by slightly higher fixed

changes in the network charges of distributors.

It should also be recognised that some retailers offer very different tariffs from their

peers although in Victoria these offers are not generally available. For example both

Sumo and Origin Energy offers that might be described as “all you can eat” – a fixed

payment for a period irrespective of consumption in that period. In New South Wales,

Pooled Energy and Mojo both offer tariffs that have annual or monthly subscription

charges in lieu of charges that would otherwise be variable with consumption.

2.7   The comparison challenge

Accurate comparison of competing offers is, even in ostensibly simple cases, in fact

incredibly difficult. For customers to evaluate the market they need historic

information on their consumption volumes and, if on time-variant offers, the

proportion of their consumption at different times of the day. They then need to

consider how this might change in assessing their future requirements. If they have

solar they need to be able to reliably estimate their likely annual exports to the grid.

Then they need to search the market for competing offers and evaluate them. The

evaluation needs to consider:

•   The rates – variable and fixed. This is non-trivial in almost all cases. Block rate

tariffs – common in some distribution areas - need to take account of the volume

of consumption and whether the blocks are defined daily, monthly or quarterly.

•   Discounts – conditional, unconditional on total bill or usage.

•   The value of up-front incentives and progressive rewards.

•   If applicable, the volume and price of Green Power (only some retailers offer it

and they offer varying proportions and different combinations of fixed or

consumption-variant charges.

31

•   Solar feed-in rates (which often depend on whether customers have access to

premium rates) and depend on system size in some cases, system volume in

others and in some cases vary over time (higher initial rates that decline after a

period)

•   The impact of exit fees, which in some cases change depending on the duration

of the customers’ tenure with the retailer.

•   Whether offers are fixed or not: some offer truly fixed prices for a period. Others

offer fixed discounts for a period.

•   Whether offers in the market are actually available to them. Some retailers post

apparently attractive offers but in fact on further inquiry it becomes clear that

they are only available to customers with certain Network Meter Identifiers in

the relevant distribution areas. Some retailers offer tariffs without fixed

charges, but again on closer inspection they are not available to new entrants

(and the retailers don’t say this in their fact sheets). Some retailers will accept

new customers that wish to change their tariff type (time of use versus flat or

block). Others, and this seems to be the default, will not.

Victoria has a range of complex offers. This reflects many factors not least a legacy from

many decades ago when electricity was sold by both the state electricity commission

and numerous local government authorities and the various organisations adopted

different pricing practises. While many residential customers are currently on relatively

straight-forward two part (fixed and variable) rates, many much more complex

variants exist.

For example some retailers make offers that have seasonally differentiated peak,

shoulder and off-peak charges and the the peak charges vary depending on the level of

consumption in the peak period. In Powercor’s area, some customers are offered

“climate saver” seasonal charges for air-conditioners connected to separate circuits.

Many retailers include rates for this offer – as a form of seasonal controlled load – but

on closer inspection customers scanning the market will find that they are not (in some

cases) available to new customers.

A further complication is that retailers have started to offer customers charges that

include rates for peak demand. Retailers measure this in different ways and customers

are likely to find it difficult to predict their peak demands over the measured period.

32

Analysis of historic half-hourly consumption data require sophisticated analytical skill,

and may nonetheless be a poor predictor of future demand charges. 4

Accurate comparison of competing offers requires that the analysis takes account of the

many ways that offers differ from one another (tariff type, existence of controlled load,

discount type (conditional or unconditional and if conditional, type of condition),

discount incidence (total bill or energy bill), upfront bill payment, Green Power rates,

solar feed-in rates, duration of benefit periods, exit fees, other fees and charges. Even

apparently innocuous differences can have a significant impact on bills and, quite

understandably, none of the retailers clearly spell out all the relevant terms of their

offers in bill-boards, websites, TV or radio advertisements.

Finding all the relevant information to ensure a proper assessment is not easy. Retailers

are obliged to post the terms of their offers on their websites in “energy price fact

sheets” but in most cases these can be difficult to locate and in some cases require user

interaction (e.g. post code, whether or not the user has controlled load, or solar,

whether the customer wants gas and electricity or just electricity offers and so on) to

order to view or download the relevant sheet. This impedes pair-wise comparison. The

fact sheets are often incomplete – for example many don’t mention solar feed-in rates or

Green Power rates and often also incentives - requiring users to search for the

additional information on retailers’ websites. Some parts of this problem also exist in

respect of the data provided by some retailers to the Victorian Government’s price

comparison website. This impedes accurate comparison of offers.

In addition, unlike in other states in the NEM, retailers in Victoria are not required to

follow a standard format in their energy price fact sheets. Having worked with these

4 Understandably, the Victorian Government’s price comparison website excludes these

demand charges in its calculation of the bill for those offers that include such charges.

However this does render an inaccurate estimate of the charges on those offers, which

customers would only find out about on further interaction with the retailers offering

those tariffs.

33

fact sheets extensively, obvious and not so obvious errors are apparent. In some cases

careful review and correction is needed.

It might be suggested that many customers might not be concerned to find the absolute

best offer in the market, but instead settle on a better offer. This may be the case but

obscure and difficult details can affect bills significantly.

34

3   Bill disaggregation based on retail offers

This section breaks the residential and small business offers down into their component

parts to derive the retailers’ charge for their service of selling electricity. This charge is

some times referred to as the “gross margin”. The first subsection describes the

calculation and the second presents the results.

3.1   Method

The retailers’ charge for its services is not separately disclosed on customer’s bills.

Instead it has to be calculated by estimating the electricity bill and then deducting the

cost of the other components that make up the bill including the wholesale, network,

environmental and metering charges. Some of these charges (environmental, network

and metering charges) are known or can be accurately estimated. Others, specifically

the wholesale charge, might plausibly lie in a reasonably wide range.

3.1.1   Estimating the bill

The calculations here are for a representative household. The first task is to define the

volume of electricity that that household purchases, and then the price that the

household pays for that volume of electricity.

Dealing first with volume, we have assumed 4,000 kWh per year. This is rounded down

from the 4,026 kWh per year estimate that the Australian Energy Markets Commission

used for its Price Trends report5, based on the consumption estimate for a two person

household that is also supplied with gas. This consumption is similar (slightly higher)

than the median household consumption on Ausnet Service’s network. The Ausnet

data – the only publicly available primary dataset that we know of - provides the

distribution of household customer numbers by consumption band and provides

confidence that the 4,000 kWh per year estimate is a reasonable estimate to use for a

representative household.

5 See for example “Retail electricity price trends report, 2016” available from the AEMC’s

website.

35

For small business customers, some will consume less than households and others very

much more. For the representative small business customer 10,000 kWh per year is

assumed.

Moving to the price, a weighted median is estimated. The weights are based on the

latest data on retailers’ customer numbers on Standing and Market Offers (these

customer number data from the Essential Services Commission) and also on the

number of residential customers in each of Victoria’s five distribution regions (from the

network service providers’ Regulatory Information Notices). The weighting also

includes assumptions on the proportion of customers receiving conditional discounts

and those not, as described below.

The challenge in developing a plausible estimate of the bill paid by a representative

customer in Victoria is to account for the number of customers on Standing Offers

(whose prices are easily known) and then to arrive at a plausible weighting of the

estimated bills by making reasonable assumptions on the proportion of the customers

that are on market offers that paying the fully discounted prices and the proportion

that receive guaranteed unconditional discounts, if any at all.

The estimate of the price on Standing Offers uses the median offer of each retailer. The

estimate the price in Market Offers uses a weighted average of the median price

assuming that half of all customers on Market Offers receive all conditional and

unconditional discounts, and that the other half are on offers that receive only

unconditional discounts6.

This approach merits further explanation. As discussed in the sub-section on discounts,

most retailers in Victoria offer customers conditional introductory discounts for defined

periods, which are often called “benefit periods”. These benefit periods are typically a

year, sometimes two, counted from the time that they have taken up the offer. The

6 This approach is equivalent to assume that in the market half of customers receive discounts

equivalent to the offers made to new customers and the other half have either lost their

discounts as their introductory discounts have lapsed or they or have failed to meet the

conditions of the conditional discounts by paying their bills on time.

36

discounts that customers receive at the end of the “benefit period” vary from none to

some. Those that continue to offer discounts typically replace them with lower

discounts than they had made in their introductory offers.

The rationale for the 50/50 weighting adopted here is as follows:

•   Data from the Australian Energy Market Operator shows that the typical annual

residential switching rate (after excluding new homes in Victoria) is around 15-

20% per year.

•   Assuming this switching rate applies consistently to all consumers, the typical

rate at which customers switch suppliers is every 4 to 6.7 years (the inverse of

the annual switching rate).

•   This is well beyond the duration of the benefit period of all discounts. Many,

probably most, customers will therefore be receiving none or at most some

reduced discount (if they were always receiving the full introductory discounts

why would retailers make them conditional and restrict them to defined

“benefit periods”).

•   On the other hand, some retailers may not withdraw all discounts at the end of

the benefit period and some customers may obtain cheaper offers from their

existing retailers without switching.

Balancing these counter-vailing factors, the 50/50 assumption of the proportion of

customers that are on fully discounted Market Offers versus Market Offers without

conditional discounts is adopted.

It should be noted that in its Residential Price Trends Report, the AEMC assumes that

all customers on Market Offers are on their retailer’s cheapest Market Offers. This is

likely to underestimate customers’ bills and their average prices as quantified later in

this section and verified in the analysis of the bill sample in Section 7.7

7 The representative customers’ bill applying the AEMC’s approach for offers valid on 14 May 2017 results in an annual bill for a 4 MWh per annum representative customer on a flat or block tariff of $1,100 before GST per year. This compares to the calculation using our approach which estimates the bill to be $1,326 before GST - 21% higher than the AEMC’s estimate for market offers in Victoria in the year to June 2017.

37

3.1.2   Estimating the wholesale charge

The Department commissioned Jacobs to provide monthly estimates of the wholesale

prices applicable to residential customers in each of the four regions of the NEM. The

issue is to decide how to use these monthly prices in estimating wholesale prices for the

representative customer. There are many plausible ways that this could be done.

One approach would be simply to use Jacobs’ May wholesale price estimate. However

the retail offers that are analysed in this report will remain valid for some future period

before they will be changed. And, many of the offers currently available were

introduced to the market some time previously.

A reasonable estimate of wholesale charges at any point in time should therefore take

account of when the retail offers were introduced to the market and how long they are

likely to remain in the market in future. This allows for a balanced estimate of the

wholesale price for the duration of that retailer offer, to be established.

Two pieces of information are needed to make a plausible estimate of wholesale prices

using Jacobs’ base monthly price data:

•   firstly, how long the offers have been in the retail market when the market is

assessed; and

•   second, how long offers currently in the market can reasonably be expected to

remain in the market for.

On the first issue, this report analysed the retail market in May 2017. To estimate how

long offers have been in the retail market, we analysed the tenure of the market offers

to residential customers that were listed on Switchon, the Government’s price

comparison website, at the end of 30 May 2017. Figure 13 below shows the offer

duration (on the Y-axis) i.e. how long ago (from 30 May 2017) the offers were

introduced to the market, for each of the 1017 market offers available on 30 May 2017

(on the x-axis).

38

Figure 13. Offer duration, all market offers, residential customers at 30 May 2017

As at 30 May 2017 the median offer had been introduced to the market 135 days earlier

(4.5 months). Three quarters of all offers had been introduced to the market just under 5

months ago. From this information we chose an offer duration of 5 months, in other

words that for the purpose of analysing wholesale prices we assume that the market

offer for the representative customer was first made available to the market five months

back from the end of 30 May.

Turning now to the second issue (how long offers can reasonably be expected to remain

valid for) the duration of offers in the market was assessed by examining all market

offers available to residential customers in December 2016. This date was chosen in

recognition of the traditional re-pricing that occurs in Victoria around the start of the

year. The analysis at the end of December showed a median duration of just over 10

months and a 75th percentile duration of just over 11 months. In other words, of the

offers in the market at the end of December 2016, 75 percent had been introduced to the

market at most 11 months previously.

0"

50"

100"

150"

200"

250"

300"

350"

400"

450"

500"

1" 41"

81"

121"

161"

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241"

281"

321"

361"

401"

441"

481"

521"

561"

601"

641"

681"

721"

761"

801"

841"

881"

921"

961"

1001"

How$long$ago$th

e$off

er$was$introd

uced

$(days)$$

Market$offer$$

39

Figure 13 shows that offers are increasingly being updated more frequently than the

traditional annual re-pricing8. We presume this reflects retailers’ response to wholesale

price changes i.e. they are changing (raising) their retail offers more frequently than

they otherwise would have, in recognition of the recent increases in wholesale prices.

Erring on the side of caution, we nevertheless assume that market offers will typically

endure for 10 months before they are revised. This is a conservative estimate: it may

well be that the effective duration is somewhat shorter. Certainly it is reasonable to

expect offer duration to be shorter in future than it has been in the past.

Bringing the two strands of the analysis together (i.e. when offers for the representative

customer were introduced to the market and how long these offers will endure in the

market for) means that the appropriate estimate of wholesale prices in May 2017 is

established by taking the average of Jacobs’ monthly wholesale price estimates for 10

months starting from 1 January 2017 (5 months back from 30 May 2017). This gives a

wholesale price in Victoria of $66/MWh. The prices in New South Wales, Queensland

and South Australia, established using the same approach are $77/MWh, $88/MWh

and $146/MWh respectively.

It is important to be clear that this analysis does not suggest that wholesale prices will

not be appreciably higher in future than they are today. Rather, the analysis reflects the

assumption – based on the observed offer duration data – that retailers will reprice

their offers to reflect future changes in wholesale prices. If the study in this Report was

repeated in, say, October 2017, it would result in a higher wholesale price estimate but

also a higher retail price estimate. The same principle would apply if the study was

done at some earlier date, say December 2016, at which point it will have shown lower

wholesale and retail prices.

Finally an important result in this study – the retailers’ charge for its services - is

somewhat sensitive to wholesale price assumptions, but this charge is far more

sensitive to estimates of the customers’ bills. For example, if the Victoria wholesale

8 This is also implicit in the December 2016 data in which the median is 10 months and even 75

percent of all offers were in the market for less than a year. In other words, even in 2016 many

retailers were re-pricing offers that they might have first established in January.

40

price was assumed to 10% higher than the estimate used here (i.e. $72.6/MWh rather

than $66/MWh) the retailers’ charge for its services would reduce from $489 per

customer per year to $462 per customer. By contrast if retail bills were assumed to be

10% lower than the $1,326 per year calculated in this report, the retailers’ charge for its

services would reduce from $489 to just $356 per year

3.1.3   Estimating network charge

The network charge in each distribution region is based on the relevant 2017 rates

specified in the published tariff sheets of each distribution network service provider,

for two-part (flat rates) and block tariffs for residential customers.

For small business customers the weighted average of the network charges on time of

use and flat rate is calculated with the weighting set the proportion on time of use

versus flat tariffs.

The weighted average Victorian network charge weights the network charge for each

distributor based on the number of customers that that retailer serves compared to the

total number of household customers. These network tariff calculations are performed

in MarkIntell (Insight).

3.1.4   Estimating environmental charges

The Environmental charge is the sum of separate components for the Federal Small

Scale Certificate Scheme and the Federal Large Scale Renewable Energy Target Scheme,

the Victorian Premium Feed-in Tariff, and the Victorian Energy Efficiency Target.

Federal Small Scale Scheme

This the product of the Small Scale Technology Percentage (as published by the Clean

Energy Regulator) and the Small Scale Technology Certificate price which is assumed

to be $40 per certificate.

Federal Large Scale Renewable Energy Target This is the product of the Renewable Power Percentage (RPP) and the price of Large

Scale Generation Certificates (LGCs). The price of LGCs is assumed to be $70 per

certificate representing a $10 per certificate discount to the spot retail price at the time

of writing. We suggest this discount reflects the likely average wholesale price for

41

LGC’s paid by retailers. The federal environmental charge calculations are performed

in MarkIntell.

Victoria Energy Efficiency Target

This is estimated based on the Victoria Government’s 2017 Victorian Energy Efficiency

Certificate (VEEC) liability priced at $16 per certificate based the average of the

previous 12 months’ prices, published by Green Energy Trading, and assuming the cost

is spread evenly over the 37 TWh distributed by Victoria’s distributors each year.

Premium feed-in tariffs

This is based on 2016 data of aggregate eligible feed-in volume of 120 GWh priced at

$600 per MWh and spread evenly over the 37 TWh distributed by Victoria’s

distributors each year.

3.1.5   Metering charges

This is the based on the prices in distributors’ tariff sheets for single element meters.

weighted by the number of customers in each distribution area.

3.1.6   GST

This is calculated at the statutory rate on the sum of all the pre-GST elements of the bill.

3.2   Results

Figure 14 shows the breakdown of the residential electricity bill in Victoria based on the

assumptions described in the previous sub-section. Figure 17 shows the breakdown for

small business customers on the same assumptions.

42

Figure 14. Residential bill disaggregation based market offers, 4 MWh p.a.

Figure 15. Small business bill disaggregation, 10 MWh p.a.

!$489!!

!$409!!

!$266!!!$89!!

!$55!! !$18!!

!$133!!

$0!

$200!

$400!

$600!

$800!

$1,000!

$1,200!

$1,400!

$1,600!

Retailer's!!!!!!!!!!!!!!!!!charge!

Network!!!!!!!!!!!charge!

Wholesale!!!!!!!!!!!!!!charge!

Metering!!!!!!!!!!!!!charge!

Federal!environmental!

Victoria!environmental!

GST!

RepresentaIve!annual!household!electricity!bill!!

!$647!!

!$1,098!!

!$660!!!$89!! !$137!! !$45!!

!$268!!

$0!

$500!

$1,000!

$1,500!

$2,000!

$2,500!

$3,000!

$3,500!

Retailer's!!!!!!!!!!!!!!!!!charge!

Network!!!!!!!!!!!charge!

Wholesale!!!!!!!!!!!!!!charge!

Metering!!!!!!!!!!!!!charge!

Federal!environmental!

Victoria!environmental!

GST!

RepresentaJve!annual!small!business!electricity!bill!!

43

4   Inter-state and international comparison of prices

and retailer charges in residential offers

This section extends the analysis of Victorian prices and retailer charges in residential

offers by comparing them to those in other contestable markets in Australia and then

comparing the Australian markets to those in Europe based on the analysis in the

Agency for the Cooperation of Energy Regulators’ (ACER)/ Council of European

Energy Regulators (CEER) 2016 report9.

ACER’s analysis assumes a 3.5 MWh per year customer. As explained earlier, we

assumed a 4 MWh per year customer in our Victoria analysis. Considering the effect of

high fixed charges in Australia this differences means that the comparison will

understate Australian average prices (and retailer charges) relative to those in Europe.

For example, on 11 May 2017, the median pre-tax price in market offers for a 4 MWh

per year customer (assuming all discounts are met) is 28.2 cents per kWh. But for a 3.5

MWh customer the median price rises to 30.4 cents per kWh. On this basis, this

international comparison should be considered favourable to Australia i.e. that it

understates Australian prices and retailer charges, relative to the international

comparators.

The comparison with Europe has used current market exchange rates (0.67 Euros per

Australian dollar). This is about comparable to purchasing power parity exchange rates

for western European countries. For some of the eastern and southern European

countries PPP rates of exchange are lower so the comparison of prices and retailer

charges with theirs, is more favourable to Australia. This is explore further in Part B.

The comparison distinguishes the pre-tax and taxation components. In several

European countries with high electricity prices – for example Germany, Denmark,. Italy

and Portugal - high prices are explained by taxes not by the prices charged by the

electricity industry itself.

9 Agency for the Cooperation of Energy Regulators and Council of European Energy Regulators, November 2016. “Market Monitoring Report 2015 - ELECTRICITY AND GAS RETAIL MARKETS”. p.43

44

4.1   Prices

Figure 16 compares residential electricity prices before and after taxes in the contestable

retail markets in Australia with the residential electricity prices in retail markets in

Europe based on the methodology described in the previous section. It should be noted

that the prices charged by the dominant retailers in New South Wales, South Australia

and Queensland will increase from July and this will further extend the gap between

the pre-tax prices in these states and those in Europe.

Figure 16. Comparison of residential electricity prices (before and after tax) (Australian cents

per kWh) (May 2017 prices in Australia, 2015 prices in European countries)

4.2   Retailer charges

Figure 17 compares the retailers’ charge to residential customers for the representative

customers in Victoria compared to the other deregulated retail markets in Australia.

However as noted above prices in these other states are shortly to rise and this will

affect the comparison (as will future price changes in Victoria of course).

!"!!!!

!10!!

!20!!

!30!!

!40!!

!50!!

!60!!

Victoria!

New!South!Wales!

South!Australia!

Queensland!

Great!Britain!

Ireland!

Germany!

Holland!

Slovakia!

Luxumbourg!

Belgium!

Austria!

Greece!

Sweden!

Slovenia!

EU!Average!

Poland!

Finland!Italy!

Norway!Spain!

Denmark!

France!

Portugal!

Hungary!

Estonia!

Lithuania!

Retail!price!(Australian!cents!p

er!kWh)!

Retail!prices!pre"tax! Taxes!!

45

Figure 17. Inter-state comparison of retailer charges to residential customers

Figure 18 extends the analysis by comparing retailer charges to residential customers in

the retail markets in Australia to the outcomes in retail markets (mostly) in various

European countries. Clearly retailers’ charges for their services in Australia, but

particularly Victoria are far higher than those estimated by ACER for the various

European countries.

Figure 18. Comparison of retailer charges to residential customers (cents per kWh)

!$#!!!!

!$50!!

!$100!!

!$150!!

!$200!!

!$250!!

!$300!!

!$350!!

!$400!!

!$450!!

!$500!!

NSW! SA! QLD! VIC!

Retailer(cha

rges(($

(per(customer(per(year)(

!

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

Victoria

New

%South%W

ales

South%Au

stralia

Queensland

Great%Britain

Ireland

Germany

Holland

Slovakia

Luxumbourg

Belgium

Austria

Greece

Sweden

Slovenia

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Poland

Finland

Italy

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ark

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ustralian%cents%p

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46

Part B: Analysis of a sample of household electricity bills

5   Sample data description

This section describes the sample of household electricity bills that are analysed. It

begins with a description of the data source and then of relevant aspects of the data. It

ends with information on the estimated annual electricity bills based on the bill data.

Newgate collected customer bill information including copies of customers’ bills.

Newgate captured the data in a database and undertook preliminary quality control.

The Department undertook further quality control. We tested various data entries in

the course of this analysis. The final dataset covered 686 unique residential electricity

bills. The data from this that is used in this analysis includes:

•   Retailer and network service provider identity for each bill

•   All relevant variable and fixed rates;

•   Solar feed-in rates (after excluding the statutory entitlements, where applicable);

•   All relevant discounts;

•   All relevant consumption amounts.

Figure 19 summarises the sample bills by distribution region and tariff type. All tariffs

have daily charges (cents per day) and in addition:

•   Flat tariffs have single consumption rates that apply at all times;

•   Flexible tariffs have peak, shoulder and off-peak rates and may also have block

structures for peak rates;

•   Multiflat tariffs are block tariffs typically with at least two block rates;

•   Multi-tou tariffs contain a combination of block rates and time of use structures;

•   Tou5 is a time of use tariff with oo-peak rates form 11pm to 7am on weekdays and peak rates at other times.

47

Figure 19. Distribution by tariff type and network service provider

Figure 20 summarises the sample bill data by tariff type and retailer. The share of

retailers in this sample per retailer accords approximately with the known market share

of the population, with the possible exception of Simply Energy which is over-

represented in the sample relative to the population. Flat tariffs dominate for all

retailers except Momentum whose dominant tariff type is multiflat.

Figure 20. Distribution of tariff type by retailer

48

Consumption

The density distribution of consumption is an important feature of the sample. Figure

21 shows the density distribution of consumption of bills in the sample (the Y axis

shows the percentage of the sample set corresponding to the consumption value on the

X-axis). The top distribution in the figure shows the distribution of all bills in the

sample. The lower distributions breaks the sample into three consumption clusters

(low, medium and high) and shows the distribution of each on the same axis.10

The distributions in this figure, but particularly the density distribution of the

aggregate dataset shows the skew distribution of consumption in the sample. This

skew is also seen in consumption data in the population.11 This is an important

characteristic of the data that needs to be taken into account. The skew means that the

median (the middle value) is less than the mean (the average of all values). This is an

important because the selection of the “typical” customer is often based on the median.

Since the median is less than the mean, the “typical” customer consumes less than the

average and, assuming unchanged prices, the typical customer’s bill will be less than

the average bill. As shown later, the gap between median and average is quite large.

Figure 21. Density distribution of daily consumption by cluster and in aggregate

10 The clusters were determined in a R. package that defines clusters that have the minimum intra-cluster variance and maximum inter-cluster variance. 11 Ausnet Services, referenced earlier, has published a distribution of the consumption of small customers on its network and it shows the same skew distribution.

49

Retailer market share in sample versus population

The retailer market share in the sample compared to their known shares in the

population at the end of 2016 is shown in Table 11 below. The table shows a reasonably

close correspondence in the sample compared to the population (based on the customer

numbers published by the Essential Services Commission in December 2016), although

the larger retailers tend to be slightly under-represented in the sample and conversely

the smaller retailers mostly slightly over-represented.

Table 11. Retailer market share in sample compared to population

.

Fixed charge versus total charge

Figure 22 below charts the annual fixed charge versus the total annual bills for all bills

in the sample. It shows a wide range (from just under $200 per year to just under $600

per year) and that fixed charges are a significant part of the bill even for high

consumption customers (for whom fixed charges are relatively the smallest part of the

bill).

Market'share'*'sample

Market'share'*'

populationagl 19.1% 20.8%origin 17.3% 18.2%ea 14.6% 19.6%simply 12.5% 9.2%redenergy+lumo 12.5% 17.4%momentum 6.7% 2.7%powershop 5.0% 2.2%dodo 2.6% 2.3%alinta 2.3% 3.2%click 2.2% 1.4%globird 1.7% 0.2%powerdirect 1.5% 1.6%pacifichydro 0.7% 0.0%sumo 0.6% 0.4%opg 0.3% 0.3%peopleenergy 0.1% 0.4%next 0.1% 0.0%

50

Figure 22. Fixed charges versus total bill ($ per year)

Figure 23, analyses the difference between the fixed charges in the retail bill (after all

relevant discounts) and compares it to the fixed network charge and metering charge

and the difference between the fixed retail and sum of fixed network and metering. The

pattern and quantum in this chart is consistent with the pattern and quantum of this

analysis based on offers in the market (see Figure 11), rather actual bills.

Figure 23. Annual fixed retail, fixed network and metering charges

!$#!!!!

!$50!!

!$100!!

!$150!!

!$200!!

!$250!!

!$300!!

!$350!!

!$400!!

!$450!!

ausnet! ci2power! jemena! powercor! united!energy!

Fixed&charge&($

&per&year)&

Retail! Network! Metering! Retail#network#metering!

51

Discounts

Figure 24 shows histograms that describe the distribution of discounts by network

service provider area. For the purpose of these histograms, discounts on usage were

restated as a percentage discount on the total bill to ensure that discounts on usage and

discounts on the total bill can be placed on a common footing. The charts show that in

all distribution regions, discounts are common.

Figure 24. Distribution of discounts by network service provider

Figure 25 distinguishes the discounts on total bills from discounts applied to usage

usage charges. In both cases, the discount rates cover a wide range.

52

Figure 25. Description of discounts

To understand other important aspects of discounts, Table 12 provides summary

information distinguishing between discounts on usage and total bills and discounts

that are conditional or unconditional. The most widely used discount (on about half of

all bills in the sample) are conditional discounts on usage, followed by conditional

discounts on the total bill and then unconditional discounts on usage. A few bills had

discounts on both usage and the total bill that were conditional/unconditional and/or

unconditional and conditional. Around 1/7th of all bills had no discount at all.

Table 12. Summary information of discounts by type and incidence

This picture is broadly consistent with the frequency and incidence of discounts in

offers, as discussed in Part A.

Discount)on Discount)typeNumber)of)

bills Min.1st)

Quartile. Median Mean3rd)

Quartile. Max.energy unconditional 113 2% 3% 8% 14% 28% 42%energy conditional 314 1% 26% 28% 27% 35% 55%total)bill conditional 171 2% 10% 19% 18% 24% 40%total)bill unconditional 52 3% 10% 28% 22% 30% 33%energy)&)energy conditional)and)unconditional 57 6% 28% 30% 29% 34% 63%total)bill)&)energy unconditional)and)conditional) 9 6% 12% 30% 24% 34% 38%total)bill)and)total)bill) unconditional)and)conditional) 1 16% 16% 16% 16% 16% 16%No)discount No)discount 101 0 0 0 0 0 0

53

While information on the discounts themselves is useful showing the effect they have

on bills is of course where they can really be measured. The measure here is how

competitive rates are after all discounts have been deducted. This competitiveness can

be measured by establishing how much customers would save if they switched from

their offer to the least expensive offer in the market. This is shown in Figure 26 which

distinguishes those bills with discounts in four categories (none, 0-10%, 10%-30% and >

30 %). This group of charts shows that savings vary considerably across the clusters

and within the clusters, as measured by the low R-squared scores of the lines of best fit

of the data in each cluster. The charts show that some of the bills that have no discount

are hard to beat in the market. Only for those bills with more than a 30% discount is

there a relatively consistent upper limit (at around $300) of the savings that customers

on those bills might expect from switching to the least expensive offer in the market.

Figure 26. Switching saving: impact of discount rate

54

Solar feed-in rates

Only the retailer component of feed-in tariffs is included in this analysis. The statutory

(“Premium Feed-in-Tariff”) component (if applicable) will reduce the bill to the

relevant customer but does not affect the analysis of retailers’ charges for their services.

Figure 27 describes retailers’ solar feed-in rates (stated in $/kWh) of those in bills in the

sample with solar feed-in tariffs.

Figure 27. Description of retailers’ solar feed-in rates

Estimated annual bills

An important part of this study is the calculation of the estimated annual bill based on

the bills in this study. The bills, typically for 30 or 90 day billing periods are annualised

assuming that the consumption, and if applicable the consumption pattern, is

representative of the annual consumption and pattern of that customer. In practice this

might not always be the case but there is unlikely to be any significant asymmetric

55

error in this annualisation assumption12. Even if this were not the case, any asymmetric

error is likely to be small. By testing different annualisation assumptions13 we found

that even reasonably large asymmetric annualisation errors do not affect the main

observations in this Report.

Concession payments are not included in this analysis. There are 125 bills in the sample

that receive some form of concession payment. This does not affect the calculation of

the retailers’ charges for their services, but will affect the analysis of the bill and price

for customers entitled to the concession.

Estimates of annual charges and customer prices include GST (in recognition of the fact

that GST is rarely deductible to households). Table 13 (ordered by number of bills in the

sample) presents summary statistics of the estimated annual charges for each retailer in

the sample.

Table 13. Summary statistics of estimated annual bills ($ per customer per year)

12 Net system load profile data does not suggest that consumption in the period December to

April during which most consumption in this sample occurred is meaningfully different from

average annual consumption. 13 Assuming the consumption in the annual bill was 10% above or below average for the bill.

retailer count Min. 1st$Qu. Median Mean 3rd$Qu. Max.agl 131 531$""""""""""! 935$""""""""""! 1,331$"""""""! 1,518$"""""""! 1,743$"""""""! 6,801$"""""""!origin 119 211$""""""""""! 906$""""""""""! 1,267$"""""""! 1,397$"""""""! 1,666$"""""""! 4,523$"""""""!ea 100 368$""""""""""! 929$""""""""""! 1,269$"""""""! 1,414$"""""""! 1,709$"""""""! 5,470$"""""""!simply 86 427$""""""""""! 791$""""""""""! 1,049$"""""""! 1,220$"""""""! 1,443$"""""""! 4,433$"""""""!redenergy 51 320$""""""""""! 723$""""""""""! 950$""""""""""! 1,185$"""""""! 1,518$"""""""! 3,118$"""""""!momentum 46 488$""""""""""! 816$""""""""""! 1,115$"""""""! 1,244$"""""""! 1,542$"""""""! 2,788$"""""""!lumo 35 396$""""""""""! 812$""""""""""! 1,208$"""""""! 1,392$"""""""! 1,640$"""""""! 3,539$"""""""!powershop 34 480$""""""""""! 824$""""""""""! 955$""""""""""! 1,167$"""""""! 1,418$"""""""! 2,975$"""""""!dodo 18 434$""""""""""! 785$""""""""""! 1,049$"""""""! 1,167$"""""""! 1,365$"""""""! 2,703$"""""""!alinta 16 519$""""""""""! 999$""""""""""! 1,228$"""""""! 1,436$"""""""! 1,743$"""""""! 3,182$"""""""!click 15 574$""""""""""! 991$""""""""""! 1,214$"""""""! 1,361$"""""""! 1,601$"""""""! 3,045$"""""""!globird 12 3!$###############! 396$""""""""""! 756$""""""""""! 700$""""""""""! 943$""""""""""! 1,354$"""""""!powerdirect 10 1,133$"""""""! 1,409$"""""""! 1,645$"""""""! 1,785$"""""""! 2,167$"""""""! 2,911$"""""""!pacifichydro 5 481$""""""""""! 589$""""""""""! 742$""""""""""! 1,023$"""""""! 787$""""""""""! 2,518$"""""""!sumo 4 1,058$"""""""! 1,094$"""""""! 1,302$"""""""! 1,549$"""""""! 1,756$"""""""! 2,534$"""""""!opg 2 988$""""""""""! 1,090$"""""""! 1,191$"""""""! 1,191$"""""""! 1,293$"""""""! 1,395$"""""""!peopleenergy 1 1,986$"""""""! 1,986$"""""""! 1,986$"""""""! 1,986$"""""""! 1,986$"""""""! 1,986$"""""""!next 1 581$""""""""""! 581$""""""""""! 581$""""""""""! 581$""""""""""! 581$""""""""""! 581$""""""""""!

56

Figure 28 shows the distribution of the annual bill by distribution region. A few

observations stand out:

•   Customers bills vary over a wide range;

•   In all cases the distribution is skewed (the median is less than the mean in all

but one case);

•   The median (and mean) vary by distribution zone in a way that is consistent

with the analysis of offers in the Part A Report (charges are higher in those

distribution areas – Ausnet and Powercor – where network charges are higher).

Figure 28. Distribution of the estimated annual bills ($ per customer per year) in each

distribution zone

The summary statistics presented in Table 14 takes the estimated annual bills and

divides them by the estimated annual consumption to yield the estimated annual prices

(cents per kWh). As expected, average prices vary widely, but again the differences

between the median and average prices reflect the skew in the distribution of

consumption in the sample.

57

Table 14. Summary statistics of estimated annual prices (cents per kWh)

It merits observation here that the average price for the Big Three retailers here – 34

cents per kWh before GST is 22% higher than the Australian Energy Markets

Commission calculates in its latest report on the competitiveness of the retail electricity

industry.14

14 Australian Energy Markets Commission, July 2017. “2017 AEMC Retail Energy Competition

Review”. Page 112.

retailerNumber+of+

bills Min. 1st+Qu. Median Mean 3rd+Qu. Max.agl 131 17 27 32 37 40 180origin 119 14 28 33 37 39 103ea 100 19 29 34 36 40 77simply 86 16 24 28 31 36 65redenergy 51 16 28 35 36 40 82momentum 46 13 24 29 30 34 62lumo 35 13 26 34 34 40 61powershop 34 23 28 32 33 35 58dodo 18 21 29 35 37 40 83alinta 16 25 31 35 48 45 212click 15 25 27 31 33 38 49globird 12 0 28 30 33 40 58powerdirect 10 21 23 29 27 30 32pacifichydro 5 18 24 27 29 34 42sumo 4 29 30 31 31 31 32opg 2 29 32 34 34 37 40peopleenergy 1 30 30 30 30 30 30next 1 35 35 35 35 35 35

58

6   Retailers’ charges in the sample bills

This section breaks down (disaggregates) the bills in the sample into their component

parts, distinguishing between the wholesale charge (the charge for electricity

production), the network charge (the charge for transporting electricity over the

transmission and distribution networks), the regulated charge for smart meters, the

charge for federal and Victorian Government environmental programs, and finally the

retailers’ charges for their service of retailing electricity. The focus here is particularly

on understanding the retailers’ charge and how it compares to the other parts that

make up the customers’ bill. The section focusses on developing point estimates of the

retailers’ charges to representative households, comparing retailers’ charges relative to

network and wholesale charges across the sample, and finally showing how the retailer

charges compares within and between retailers.

All 686 bills including 75 with controlled load rates and 102 with solar feed-in and three

with both are included in the analysis. For the bills with solar feed-in we assume that

the opportunity cost to retailers of purchasing fed-in electricity is the wholesale price of

electricity. So retailers that pay feed-in rates lower than the assumed wholesale price

will improve their margins from those customers (by the difference between the

wholesale price and the feed-in rate they pay). Conversely retailers that pay a price for

fed-in electricity that is higher than the assumed wholesale price will lose margin on

those customers based on the difference between the wholesale price and feed-in rates

they pay.

The wholesale and environmental prices and charges are established as described in

Part A. The application of the wholesale price methodology described in Part A results

in a wholesale charge of $61.6/MWh for electricity billed in this December 2016 to

April 2017 period.15

15 Wholesale electricity prices have increased significantly in Victoria over the last year, though the measure of this depends on which contracts are examined or how spot prices are analysed. The approach in this Report to setting a wholesale price in the analysis of customer bills, as described in Part A, adopts the typical assumption that retailers hedge their prices in advance of their retail sales. This means that wholesale price estimates lag the current day prices in contract markets (which hedge future

59

Wholesale price assumptions sometimes attract an undue amount of attention

considering that in the analysis of retailer charges it is not the most important factor.

Specifically, if we assume a 4 MWh per year household, a $1 change in the assumed

wholesale price results in a $4 change in the estimate of the retailers’ charge for its

services. So changing the assumed wholesale price from say $50 per MWh to $70 per

MWh (a 40% increase) will change the estimate of the retailers’ charge by $80 per

customer per year. This is less than a 16% increase in the estimated retailer’s charge.

This is represented graphically in Figure 29 below:

prices). Wholesale prices contracts for the period December 2017 to April 2018 are very much higher – perhaps even twice as high – as they have been for the same period a year earlier (i.e. the time that the bills in this study fall due). Clearly the calculation of retailers’ charges for the period from December 2017 to April 2018 should properly take account of the reasonably estimated wholesale prices at this time, and also the retail prices that will apply that time. From this it should be clear that the relevant issue in wholesale price estimates for retailer charge calculations is to ensure that the relevant retail prices are measured at the same time to which those wholesale prices apply. We do not yet know what prices retailers intend to charge for sales in the period from December 2017 to April 2018. At the time of writing this report, retailers in Victoria as elsewhere in Australia have been increasing their prices by large amounts. If retail prices do not rise later this year, this will mean that retailers’ charge later this year will become meaningfully lower than estimated in this report. A study of retailers’ charges in future should use the information that will become available on retail prices in future, along with the much higher estimates of wholesale prices applicable to that time, in the calculation of retailer charges at that time. Wholesale price assumptions are relevant also in the analysis of the relative competitive position of the retailers. The retailers with the largest number of customers in Victoria typically also own most of the electricity production in Victoria, though the proportion of own production does vary amongst the largest retailers. For the smaller retailers, almost none of whom produce any of the electricity that they sell, higher wholesale prices translate into small retailer charges without any offsetting gain from higher wholesale margins. This is an important difference and should be considered in the analysis of Victoria’s retail markets, but it is beyond the scope of this study.

60

Figure 29. Retailers' charge ($ per year) versus wholesale price ($/MWh)

Consequently, the observation (discussed later) that retailers’ charge for their services

are generally greater than the wholesale charge is robust to the estimate of the

wholesale prices that is used in this Report.

The calculation of environmental and metering charges in this analysis are set out in

the Part A analysis.16 The network charge is established for each bill based on the

network tariff that matches precisely or if not most closely, the structure of the retail

tariff and where applicable includes controlled load rates. This is automated in the

analytical tool – SwitchGov – and all bills and their constituent elements are priced in

SwitchGov, which is described in the Appendix.

Two important features merit discussion in understanding disaggregated bills:

•   Firstly, as shown earlier, the distribution of consumption is leftward skewed i.e.

there are more bills in the sample whose annual consumption is less than the

average consumption, than there are whose consumption is more than the

average (the mean is higher than the median).

•   Secondly, also as discussed earlier, fixed charges form a significant part of the

bill for all but the very largest customers. The effect of the high fixed charges

16 These are $109, $85, $85, $85 and $60 per year in Ausnet, Citipower, Jemena, Powercor and

United Energy.

$200$

$250$

$300$

$350$

$400$

$450$

$500$

$40$ $43$ $45$ $48$ $50$ $53$ $55$ $58$ $60$ $63$ $65$ $68$ $70$ $73$ $75$ $78$

Retailers'*charge*($*/*custom

er*/*ye

ar)*

Wholesale*price* ($/MWh)

61

means that customers that purchase small amounts of electricity pay higher

prices – per kWh – than those that purchase large amounts of electricity, even if

their total annual bill is lower. Consequently the retailers’ charge for its services

forms a larger part of the bill for smaller customers, even if in absolute terms the

retailers’ charge is smaller than it is for large customers.

Retailer charge estimates for representative customers

Disaggregation of annual bills using the average annual bill and median annual bill is

presented in Table 15 below. In this table, the second and third columns show the

disaggregation on average and for the median bill. The third and fourth columns

present this information in cents per kWh, by dividing each element of the bill by the

Annual grid purchases. The fifth and sixth columns present the elements of the bill as a

percentage of the total bill (before GST).

Table 15. Analysis of average and median bills in the sample

Several observations stand out:

1.   As expected, the volume of electricity purchased from the grid for the median

customer is less than it is on average (this reflects the skewed consumption

distribution).

2.   Also as expected, the median retailers’ charge does not decrease in proportion

to the consumption (this reflects the effect of the large fixed charges in typical

retail bills). Specifically, the retailers’ charge for the average and median is

much the same, while the median customer buys much less electricity than the

Average Median Average Median Average MedianRetail'(before'GST) 1,247$""""" ! 1,094$""" ! 29.0!!!! ! 37.9!!!! !Network((before(GST) 436$"""""""" ! 394$"""""" ! 10.1!!!! ! 13.7!!!! ! 34.9% 36.0%Wholesale((before(GST) 265$"""""""" ! 178$"""""" ! 6.2!!!!!! ! 6.2!!!!!! ! 21.2% 16.2%

Federal'environmental'(before'GST) 55$"""""""""" ! 35$"""""""" ! 1.3!!!!!! ! 1.2!!!!!! ! 4.4% 3.2%Victoria(environmental((before(GST) 16$"""""""""" ! 11$"""""""" ! 0.4!!!!!! ! 0.4!!!!!! ! 1.3% 1.0%Metering((before(GST) 87$"""""""""" ! 109$"""""" ! 2.0!!!!!! ! 3.8!!!!!! ! 6.9% 10.0%Retailers'*charge*(before*GST) 389$"""""""" ! 368$"""""" ! 9.1!!!!!! ! 12.8!!!! ! 31.2% 33.6%GST 125$"""""""" ! 109$"""""" ! 2.9!!!!!! ! 3.8!!!!!! !Annual&grid&purchases&&(kWh) 4,295!!!!!!! ! 2,884!!!!! ! 4,295!! ! 2,884!! !

Annual&bill&($&per&year) Percentage)of)bill)before&GST

Annual&bill&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&(cents'per'kWh)

62

average. This means that lower consumption customers pay much more per

kWh for the retailers’ services, than higher consumption customers. This also

translates into significantly higher prices per kWh purchased for the median

customer compared to the average.

3.   For both the average and median bill, the retailers’ charge and network charge

are approximately comparable as a percentage of the total bill.

The median bill shown in Table 15 has a consumption of 2,884 kWh, this is far below

the median consumption in the sample of 3,558 kWh per year and results in an estimate

of annual prices that are far above average prices. The retailer charge estimate for this

median customer is very different to the retailer charge for the customer either side of

the median.

The average bill is a better choice for characterisation of representative customer, but is

susceptible to the criticism that with a skewed consumption distribution it can not be

accepted as an estimate of the bill for a customer whose annual consumption is typical

of the population.

To characterise a representative customer, we have selected those bills whose

consumption is in the range from 3,850 kWh per year to 4,150 kWh per year (3.75%

either side of 4,000 kWh per year). In the sample there are 36 bills with annual

consumption in this range and the average of their consumption is 4,007 kWh per year,

close to the Victorian Government’s assumption of 4,026 kWh as the annual

consumption of the typical residential customer. A waterfall chart of the disaggregated

bill based on the average bill for customers in this range is shown in Figure 30.

The average bill in this sample is $1,389 (after GST), giving an average price of 34.7

cents per kWh. The average retailers’ charge for these customers is $423 per year, with a

standard deviation of $167. This level of variability is an inevitable consequence of the

high level of dispersion of the prices paid by customers in this consumption range and

indeed in the whole sample. In properly understanding the retailers’ charge it is

important to focus not just on the representative customer but also on the outcomes for

all customers as shown in more detail in Figure 31, 32, 33 and Table 16.

63

Figure 30. Residential bill disaggregation based on average bill from sample (4 MWh)

Retailers’ charge relative to network and wholesale charges across the sample

Recognising the challenge of defining a central estimate for the sample, it is valuable to

understand the outcomes for all bills in the sample. Figure 31 shows the difference

between the retailers’ charge and the network charge for all bills in the sample. It shows

that retailer charges are mostly higher than network charges except for customers in

Ausnet Services’ and possibly also Powercor’s area of supply.

$423%

$415%

$263%$88%

$55% $18%

$126%

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

Retailer's%%%%%%%%%%%%%%%%%charge

Network%%%%%%%%%%%charge

Wholesale%%%%%%%%%%%%%%charge

Metering%%%%%%%%%%%%%charge

Federal%environmental

Victoria%environmental

GST

Representativehousehold electricity%bill%from%sample%

64

Figure 31. Histogram of the difference between network and retailers' charges

Figure 32 compares the retailers’ charges and wholesale (production) charges across the

sample by showing the difference between the retailers’ charge and wholesale charge

for all bills in the sample. This shows that for around three quarters of all customers in

the sample, the retailers’ charge for their services in selling electricity is more than the

charge for producing that electricity.

Figure 32. Histogram of the difference between wholesale and retailers' charges

65

Retailers’ charge analysed by distribution area

Figure 33 below presents histograms of the retailers’ charge by distribution region. It

shows, as expected, a skew in the distribution of the retailers’ charge, originating in the

skew in the consumption distribution. In these charts, for the purpose of presentational

clarity, the scale has been limited to $1000 but there are several bills with annual

retailers’ charge of $2,000 per year or more. Closer inspection of the charts also shows

reasonable differences in the distribution of the retailers’ charges in each distribution

area.

Figure 33. Histogram of retailers' charge by network service provider area

Retailers’ charges analysed by retailer

It also useful to know how the retailers’ charges for their services compare amongst the

different retailers in the sample. Table 16 presents summary statistics on retailer

charges (expressed as dollars per customer per year) calculated according to this

methodology and ranked in the table in order of the number of bills supplied by each

retailer in the sample.

66

Table 16. Summary statistics on retailer charges for their services ($ per customer per year)

In this table, the three largest retailers are shown to have median retailer charges in the

range from $342 to $380 per year. The average retailers’ charge is around 10% higher

than the median reflecting the skew in the distribution of consumption.

The table also shows that for several retailers the minimum retailer charge is negative.

As discussed in further detail later, 19 out of the 686 bills have prices that are lower

than any of the commonly available offers in the market at the time of those bills.

Figure 34 displays the retailer charge calculated as a percentage of the total bill, for each

retailer

retailerNumber+of+

bills Min. 1st+Qu. Median Mean 3rd+Qu. Max.agl 131############# 228&$########### 322$########### 376$########### 468$########### 479$########### 2,361$########origin 119############## 146&$########### 277$########### 380$########### 447$########### 552$########### 1,401$########ea 100############## 49&$############## 242$########### 342$########### 389$########### 505$########### 2,060$########simply 86################ 11$############## 148$########### 223$########### 233$########### 262$########### 882$###########redenergy 51################ 211&$########### 232$########### 321$########### 324$########### 435$########### 744$###########momentum 46################ 243&$########### 225$########### 259$########### 257$########### 290$########### 544$###########lumo 35################ 132&$########### 248$########### 332$########### 383$########### 473$########### 1,565$########powershop 34################ 122$########### 240$########### 298$########### 378$########### 433$########### 1,075$########dodo 18################ 138&$########### 201$########### 280$########### 241$########### 329$########### 385$###########alinta 16################ 250$########### 348$########### 392$########### 477$########### 527$########### 902$###########click 15################ 191$########### 263$########### 430$########### 404$########### 500$########### 727$###########globird 12################ 339&$########### 110$########### 167$########### 118$########### 206$########### 318$###########powerdirect 10################ 146$########### 243$########### 323$########### 392$########### 389$########### 949$###########pacifichydro 5################## 9$################ 35$############## 44$############## 61$############## 105$########### 112$###########sumo 4################## 170$########### 236$########### 348$########### 344$########### 455$########### 509$###########opg 2################## 268$########### 289$########### 310$########### 310$########### 330$########### 351$###########peopleenergy 1################## 351$########### 351$########### 351$########### 351$########### 351$########### 351$###########next 1################## 114$########### 114$########### 114$########### 114$########### 114$########### 114$###########

67

Figure 34. Distribution of retailer charges as a percentage of total bill (before GST), by

retailer

This figure shows that the retailers with the greatest number of customers also tend to

have the highest retailer charge. In other words, in the sample the retailers with the

largest market share are also those that charge more for their services than the retailers

with the smallest market share. The gap between the established, popular retailers and

the newer entrants is large. This is also evident in the savings that customers might

obtain if they switched to the least expensive retailers. This is explored in further detail

in the next Section.

Cross-country comparison of retailers’ charge

The comparison of the retailers’ charge (as in Part A – see Figure 18) in Victoria and

other parts of Australia with the retailers’ charge in various European countries17, using

17 The European data is taken from Figure 21 of the ACER/CEER Report which provides an annual average from 2008 to 2015. The retailer charges in 2015 were higher in some countries most notably in Britain, compared to the 2008 to 2015 average, but the Report attributed this to the depreciation of the Pound after the Brexit vote and so this increase reflects primarily a currency effect. Using the 2015 measure, the retailers’ charge in Britain is a little below that for New South Wales. The retailers’ charge was also appreciably higher in 2015 than the average for 2008 to 2015 in Germany, Ireland, Belgium, Austria, Greece and France. The higher 2015 numbers narrow the gap to Victoria, but in all cases a significant gap still remains.

68

the retailers’ charge based on the 4 MWh cohort average in Australia, is shown in

Figure 35 below.

Figure 35. Cross-country comparison of retailers' charge (cents per kWh) using sample of

bills

As described in Part A, the retailers’ charge for the European countries is taken from

the Agency for the Cooperation of Energy Regulators (ACER) and Council of European

Energy Regulators (CEER) Report18. That Report uses the same approach in this Report,

of subtracting production and distribution costs from the estimate of the representative

bill19. The bills for the European countries assume consumption of 3,500 kWh per year,

whereas the Victorian prices assume 4,000 kWh20. Considering the effect of fixed

charges, particularly in Victoria, the retailers’ charge in Victoria per kWh would be

about one cent per kWh (about 10%) higher than shown in the Figure 31 had we

assumed a consumption level of 3,500 kWh rather than 4,000 kWh per year. Similar

18 Agency for the Cooperation of Energy Regulators (ACER) and Council of European Energy Regulators (CEER), November 2016. “ACER Market Monitoring Report 2015 - ELECTRICITY AND GAS RETAIL MARKETS”. 19 Their Report refers to what we call the “retailers’ charge” as the “mark-up” or “gross profitability” 20 To be precise, for NSW, QLD and SA we use 4,800 kWh per year using exactly the same analysis for these states as in Part A since actual bill data is not available for these states.

!

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%Victoria

New

%South%W

ales

South%Au

stralia

Queensland

Great%Britain

Ireland

Germany

Holland

Slovakia

Luxumbourg

Belgium

Austria

Greece

Sweden

Slovenia

EU%Average

Poland

Finland

Italy

Norway

Spain

Denm

ark

France

Portugal

Hungary

Estonia

Lithuania

Retailers'%charge%%(A

ustralian%cents%p

er%kW

h)

69

increases would apply in the other Australian states had we also used a consumption

level of 3,500 kWh for them.

It should also be noted that the estimates for New South Wales, Queensland and South

Australia are for May 2017, before significant price rises in each of these states from late

June 2017 onwards.

ACER/CEER, like us, needed to estimate the wholesale element of the bill in order to

pull apart the wholesale from retailers’ charges. Their report explains that their

methodology for estimating wholesale charges “is based on the assumption that suppliers

are rational and apply a ‘close-to-optimal’ procurement strategy”21 . As such, the retailers’

charge estimates that they derived are higher than they would be had they made no

such assumption22. By contrast, our estimate of wholesale price makes no such “close-to-

optimal” assumption in estimating wholesale prices. As such the gap between

Australian and European country retailers’ charge estimates are likely to be further

understated for this reason.

It might be argued that the use of a market exchange rate in converting between the

Euro and the Australian dollar undermines the validity of this comparison since it fails

to take account of the relative purchasing power parity between Australia and the

various European countries.23 This argument has limited value – the relative

purchasing power based on the OECD’s PPP data shows that AUD/EURO market

exchange rates are only overvalued a little (around 20% in some cases but often less) in

comparison between Australia and the wealthy European countries. While the AUD

has greater purchasing power in the cohort of less wealthy European countries, the gap

is still not nearly large enough to close the gap in their retailers’ charges relative to

21 Ibid, p. 42. 22 Because the wholesale charge estimate is lower than it otherwise would be. 23 For example, in its response to a private submission by the author of this Report, the Independent Pricing and Regulatory Tribunal rejected an international comparison of retailers’ charges along the same lines as shown in Figure 34 for these reasons – see IPaRT 2016, “Review of the performance and competitiveness of the retail electricity market in NSW”. Sydney. Page 20. From  1  July  2015  to  30  June  2016

70

Victoria. It should be noted also be noted that ACER/CEER does not use PPP

adjustments in their own cross-country comparisons.

Another way to compare retailers’ charges in Victoria with those in the European

countries is to take the ratio of the retailers’ charge to the wholesale charge in each

country, using the Euro prices for the European countries and Australian dollar prices

for Australia. This takes away any need to convert from one currency to another. The

result of this is shown in Figure 36 below. Consistent with the results in Figure 34, the

retailers’ charge relative to the wholesale charge in Victoria for the representative

customer is far higher than in the European countries (more than double the next

highest, Germany).

Figure 36. Ratio of retailers' charge to wholesale charge

!

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

Ratio%of%Retail%/%Wholesale%charges

71

7   Switching savings

It has long been suggested that customers can get a better deal by shopping around.

This analysis tests this by quantifying how much customers in the sample could reduce

their bills if they switched to the least expensive offers; or to the least expensive offer

from their existing retailer. It also explores what savings would be if the customer

switched to the second, third, fourth and up to the tenth cheapest offer.

In this analysis, the dataset of commonly available offers against which the bills were

compared was established by scraping the websites of all commonly available offers

from all of the relevant retailers. These data are available in MarkIntell (Offer) which is

described in Appendix A. The comparison for each offer is based on the offers that

were available in the same month as the date of each bill.

The comparison of the customers’ bill with what it otherwise would be on all

commonly available offers from all licensed retailers, entails pricing all of the

competing offers for the same parameters (annual consumption, consumption pattern if

applicable, existence of solar feed-in, existence of controlled load) specific to that

customer. Although in principle, customers can choose to change from one tariff

structure to another, in practice few retailers allow this and so the comparator offers in

each bill are restricted to offers with the same tariff structure.

The analysis involves first pricing (working out the charges) in each of the bills based

on all the relevant details of each bill. Then secondly, for each bill, working out what

the charge would be for that specific customer, on all other commonly available offers

in the market at the time that the bill was due. These competing offers are then ranked

to find the cheapest alternative market offer for each bill.

The rest of this section discusses in order the results of the analysis for switching to the

least expensive offer in the market and then switching to the least expensive offer from

the customers’ existing retailer.

72

7.1   Savings by switching to the least expensive offer in the

market

Table 17 presents summary statistics of the estimated annual saving that customers in

the sample would obtain if they switched to the least expensive offer.

Table 17. Summary statistics of estimated saving from switching to the lowest market offers ($ per customer per year)

The table shows, as expected, that the average saving across the sample is higher than

the median saving. The three largest retailers offer a small number of their existing

customers (5 in total) better deals than they could get from the commonly available

offers in the market. But as discussed later in more detail, there is a strong correlation

between the median saving from switching away from the current retailer and the

number of bills of that retailer in the sample. In other words, those customers of the

retailers with the largest market share also tends to have the greatest likelihood of find

the largest savings by switching retailer. Figure 37 shows the distribution of the annual

saving, ordered by network service provider area within which the customer is located.

It shows a similar distribution in all areas.

retailerNumber+of+bills Min. 1st+Qu. Median Mean 3rd+Qu. Max.

agl 131 395%$''''''''''' 207$''''''''''' 295$''''''''''' 380$''''''''''' 412$''''''''''' 2,553$''''''''origin 119 205%$''''''''''' 184$''''''''''' 296$''''''''''' 372$''''''''''' 494$''''''''''' 1,332$''''''''ea 100 72%$'''''''''''''' 166$''''''''''' 272$''''''''''' 333$''''''''''' 427$''''''''''' 2,131$''''''''simply 86 115%$''''''''''' 33$'''''''''''''' 97$'''''''''''''' 124$''''''''''' 174$''''''''''' 1,052$''''''''redenergy 51 52$'''''''''''''' 155$''''''''''' 231$''''''''''' 278$''''''''''' 370$''''''''''' 689$'''''''''''momentum 46 12$'''''''''''''' 87$'''''''''''''' 123$''''''''''' 140$''''''''''' 191$''''''''''' 395$'''''''''''lumo 35 11$'''''''''''''' 117$''''''''''' 252$''''''''''' 287$''''''''''' 362$''''''''''' 1,213$''''''''powershop 34 5$'''''''''''''''' 126$''''''''''' 162$''''''''''' 209$''''''''''' 241$''''''''''' 1,118$''''''''dodo 18 67$'''''''''''''' 114$''''''''''' 152$''''''''''' 193$''''''''''' 221$''''''''''' 486$'''''''''''alinta 16 186$''''''''''' 233$''''''''''' 288$''''''''''' 377$''''''''''' 396$''''''''''' 842$'''''''''''click 15 19$'''''''''''''' 128$''''''''''' 266$''''''''''' 265$''''''''''' 349$''''''''''' 643$'''''''''''globird 12 %$'''''''''''' 27$'''''''''''''' 65$'''''''''''''' 71$'''''''''''''' 90$'''''''''''''' 215$'''''''''''powerdirect 10 9$'''''''''''''''' 130$''''''''''' 161$''''''''''' 266$''''''''''' 243$''''''''''' 830$'''''''''''pacifichydro 5 29%$'''''''''''''' %$'''''''''''' 22$'''''''''''''' 26$'''''''''''''' 45$'''''''''''''' 93$''''''''''''''sumo 4 49$'''''''''''''' 117$''''''''''' 196$''''''''''' 231$''''''''''' 310$''''''''''' 483$'''''''''''opg 2 204$''''''''''' 208$''''''''''' 212$''''''''''' 212$''''''''''' 216$''''''''''' 220$'''''''''''next 1 23$'''''''''''''' 23$'''''''''''''' 23$'''''''''''''' 23$'''''''''''''' 23$'''''''''''''' 23$''''''''''''''peopleenergy 1 259$''''''''''' 259$''''''''''' 259$''''''''''' 259$''''''''''' 259$''''''''''' 259$'''''''''''

73

Figure 37. Distribution of annual saving by selecting the cheapest offer, by network service provider area

Figure 38 shows the distribution of the switching saving as a percentage of the

respective customers’ bill.

Figure 38. Distribution of saving (as a percentage of total bill) by selecting the cheapest offer, by network service provider area

74

Figure 39 shows the impact of controlled load tariffs on switching savings. It shows that

the existence of a controlled load does not have a large impact on the savings available

to those customers, relative to others without controlled load, if they switched to the

least expensive offers available to them.

Figure 39. Impact of controlled load on saving (as a percentage of the total bill) by selecting

the cheapest offer

Figure 40 repeats the analysis in Figure 39 but focusses on whether customers have

solar rather than controlled load. It shows that that the median and range of savings (as

a percentage of bills) is similar for households that have solar PV and those that don’t

have solar PV.

75

Figure 40. Impact of solar on saving (as a percentage of the total bill) by selecting the cheapest

offer

Figure 41 shows the savings expressed as an annual dollar amount and as a percentage

of the total bill for the three consumption clusters described earlier in the section

describing the data. This shows the wide range of savings (in dollars) in each cluster

but also that the median saving rate in each cluster is similar at around 21%. This is

alternatively stated as an average saving of $294 per customer.

76

Figure 41. Distribution of savings by cluster

7.2   Cluster analysis of saving

We identified three clusters to categorise the saving that customers would achieve by

switching retailer. This is shown in Figure 42. The y-axis shows the savings that

customers would obtain if they switched to the cheapest offer in the market. In the

figure, the bills are collected into three clusters:

•   The “Low saving” cluster accounts for 204 out of the 686 bills. The median

saving for customers in this cluster is $84 per year.

•   The “Moderate saving” cluster has 280 bills and a median saving of $223 per

year.

•   The “High saving” cluster has 155 bills with median saving of $501 per year.

In addition to these three clusters as shown, there were 33 bills that had no saving or

were cheaper than any offer in the market and there were 8 bills with savings of more

than $1,000 per year.

77

Figure 42. Switching savings in three clusters

7.3   Impact of customers’ ability to identify the cheapest offer

The savings calculations here are worked out for each customer after having found the

cheapest offer for that customer based on the profile of their consumption, their

existing prices and whether they have controlled load and/or solar. All offers in the

market were scanned to find the right offer for that customer at the date of their bill.

This is a sophisticated and data intensive analysis that will be beyond all but the very

best informed customers. Furthermore the tools needed for this sort of comparison are

not publicly available. A question that therefore needs to be answered is how much

customers might save if they were not able to find the cheapest offer available to them,

but instead the second, third, fourth and up to tenth cheapest offer. This analysis was

undertaken and the results are shown in Table 18 below (inclusive of the GST). The

table shows, in rows, the savings available if the first to tenth cheapest offer for each

customer was selected. The second column shows the number of bills with a switching

saving greater than zero. The third column shows the total annual saving if all

customers in the sample switched to the cheapest offer. The statistical summary that

follows in the remaining columns then describes the information on the savings in the

sample.

The table shows that there is a big gap between the saving that customers would obtain

if they selected the cheapest offer, than the second cheapest. For example, the median

78

annual saving drops from $218 to $106 and the total saving for all bills in the sample

drops from $190,009 per year to $60,0025 per year. The gap between the second and

third, third and fourth and so on is smaller than between the first and second, but if

customers were only able to identify the fifth cheapest offer applicable to them, the

median saving would have more than halved from $218 to $108 per year. The

conclusion from this is that while the retail market offers many of the customers in the

sample the ability to reduce their bill by switching, in practice the savings they obtain

depends strongly on their ability to find the cheapest offer applicable to them. In this

regard it is interesting, for example, that an offer that frequently appeared as the least

expensive offer is not identified in any of the commercial switching sites in Victoria.

Table 18. Relationship between switching saving and selection of alternative offers (inclusive

of GST)

7.4   Savings by switching to the least expensive offer from the existing retailer

Figure 43 compares how much customers would save if they switched to the least

expensive offer in the market or the cheapest offer from their own retailer. The median

of the saving is typically the largest for the three largest retailers. For the largest

retailers, the range of savings that their customers might achieve by switching to their

best offers is wide. But the median of the range is not large. By contrast, for these same

retailers, the range and the median of the saving if their customers switched to lowest

offers in the market, is large.

Switching)to:

Number)of)bills)with)saving

Sum)of)saving)

across)all)bills Min. 1st)Qu. Median Mean 3rd)Qu. Max.

Lowest)offer 647 $190,009 $1 $128 $218 $294 $369 $2,393Second)lowest)offer 586 $133,316 $0 $87 $156 $228 $277 $2,190Third)lowest)offer 509 $103,925 $0 $63 $125 $205 $251 $2,030Fourth)lowest)offer 476 $94,950 $0 $54 $114 $199 $248 $2,002Fifth)lowest)offer 442 $85,857 $0 $50 $108 $195 $251 $1,981Sixth)lowest)offer 419 $79,519 $0 $45 $103 $190 $244 $1,916Seventh)lowest)offer 401 $74,546 $0 $44 $100 $186 $237 $1,862Eigth)lowest)offer 379 $68,792 $0 $36 $96 $182 $228 $1,841Nineth)lowest)offer 348 $64,236 $0 $35 $99 $185 $241 $1,785Tenth)lowest)offer 319 $60,025 $0 $35 $106 $188 $260 $1,772

79

Figure 43. Distribution of saving ($ per customer per year) by switching to cheapest market

offer versus lowest existing retailer offer

The dot plot in Figure 44 shows the median annual saving for the least expensive offer

in the market compared to the least expensive offer from the customers’ existing

retailers. This illustrates clearly the large gap between the two, particularly for the

largest retailers.

80

Figure 44. Median saving ($ per customer per year) by switching to the lowest market offer

versus lowest offer from customers’ existing retailers

Analysis of the savings that customers might obtain by switching to the lowest offer

from their existing retailer rather than the lowest commonly available offer in the

market, suggests that most customers, particularly those supplied by the largest

retailers24, would pay considerably less by switching to the lowest offer in the market

rather than the lowest commonly available offer from their retailer. This is shown in

Figure 45.

24 Alinta and to a lesser extent Click are exceptions but should be treated with caution considering the limited number of their bills in the sample.

81

Figure 45. Relationship between switching saving and retailers’ market share in actual bill

sample

Finally, it may be the case that retailers would be prepared to offer customers lower

prices than in their commonly available offers in order to retain those customers if they

threatened to switch25. However the data from the sample of bills does not provide

evidence that this is common.

25 For the larger retailers that obtain economies of scale in retailing and economies of scope through vertical integration, it is very likely that the marginal cost to supply is far below their commonly available prices. In this case, a profit-maximising retailer can be expected to discount its commonly available prices more heavily in order to retain the customer.

82

Appendix A: Data and analytical tools

The data used in Part A is contained in MarkIntell (Offer) and the analysis of this data

was mostly undertaken in MarkIntell (Insight) with post-processing in Excel in some

areas. MarkIntell (Offer) and MarkIntell (Insight) are subscription web-deployed data

and analytical tools:

•   MarkIntell (Offer) (MIOffer) is a database with all relevant price information,

solar feed-in information, GreenPower rates, exit fees and incentives for all

publicly available standing and market offers to residential and small business

electricity users in Victoria, New South Wales, South East Queensland and

South Australia since June 2016 (since April 2016 in Victoria). Until April 2017

all data was sourced by scraping and mining the energy price fact sheets in all

licensed retailers’ websites. Since 1 May 2017, MIOffer contains all offers

scraped and mined from the two official price comparison websites (which

contains offers supplied to them by all licensed retailers). MIOffer is updated

daily. MIOffer is updated twice each day.

•   MarkIntell (Insight) (MIInsight) uses the data stored in from MIOffer and also

includes all relevant network tariffs and matches of these to each retail offer to

analyse electricity bills and break them down into their component parts using

assumptions on load profiles, consumption levels, wholesale energy and federal

environmental certificate prices, customer location and tariff types. Results can

be sliced by customer type, distributor, retailer, tariff type, offer type and

combinations thereof and displayed using Google Graphics visualisation

techniques or exported to CSV for post-processing.

•   MarkIntell (Switch) (MISwitch) is electricity and gas price comparison software

that captures data from customers’ bills and then uses data from MIOffer and

analysis from MIInsight to find the offers that achieve the lowest bills for that

customer. It ranks the offers and savings on all available offers based on the

consumption profile and existing prices in that customer’s bill. It allows

annualisation adjustments of all relevant consumption or solar production

parameters to account for seasonal effects. MISwitch covers the contestable

83

retail electricity and gas markets in Victoria, New South Wales, Queensland and

South Australia.

The analysis in Part B was undertaken using SwitchGov, which is an adaption of

MISwitch.

Appendix B: Load profile assumptions

Value DescriptionControlled)load)/)dedicated)circuit)/)Annual)consumption)(kWh) 0NSW)Controlled)load)1)/)dedicated)circuit)/)Annual)consumption)(kWh) 0NSW)Controlled)load))2/)dedicated)circuit)/)Annual)consumption)(kWh) 0Solar)export)to)the)grid)/)Annual)consumption)(kWh) 0Minimum)daily)demand)charge 0Proportion)of)year)classified)as)summer)in)demand)charge)tariff 0Peak)demand)(kW/kVA)))summer 0Peak)demand)(kW/kVA))non/summer 0Annual)consumption)proportion,)peak)non/summer 0.1Flexible)Summer)Peak 0.11Flexible)Non/Summer)Peak 0.13Flexible)Summer)Off/Peak 0.13Flexible)Non/Summer)Off/Peak 0.15Annual)consumption)proportion,)peak)summer 0.2Flexible)Summer)Shoulder 0.23Flexible)Non/Summer)Shoulder 0.25Annual)consumption)proportion,)off/peak)non/summer 0.25Time)of)use)7day,proportion)annual)consumption,)off/peak 0.26Annual)consumption)proportion,)off/peak)summer 0.45Time)of)use)5day,proportion)annual)consumption,)off/peak 0.47Summer)proportion)in)seasonal)flat)rate 0.5Non/summer)proportion)in)seasonal)flat)rate 0.5Time)of)use)5day,)proportion)annual)consumption,)peak 0.53Time)of)use)7day,)proportion)annual)consumption,)peak 0.74Proportion)of)annual)gas)demand)in)Off/peak)months 0.8