Energy purchase costs - IPART · including any plant that would be required to meet any regulatory obligation. 1.3 This report This final report sets out Frontier Economics‟ advice

© Frontier Economics Pty. Ltd., Australia.

Energy purchase costs A FINAL REPORT PREPARED FOR IPART

March 2010

Final Report March 2010 | Frontier Economics i

Contents

Energy purchase costs

1 Introduction 1

1.1 Terms of Reference 1

1.2 Frontier Economics’ engagement 2

1.3 This report 2

2 Overview of modelling approach 5

2.1 Modelling for 2007 determination 5

2.2 Frontier Economics’ energy market models 6

2.3 Overview of modelling assumptions 8

3 Demand forecasts used in modelling 11

3.1 Accounting for load volatility 11

3.2 Standard Retailers’ regulated load shapes 14

3.3 System load forecasts 15

4 Long run marginal cost 18

4.1 Frontier’s approach to estimating LRMC 18

4.2 Responses to the Modelling methodology and assumptions report 19

4.3 Changes in input cost assumptions relative to 2007 determination 24

4.4 LRMC results 26

5 Market-based energy purchase costs 33

5.1 Spot and contract price forecasts 33

5.2 Market-based energy purchase costs 54

5.3 Volatility allowance 65

5.4 Comparison with LRMC results 69

5.5 Additional sensitivities 70

6 Impact of the CPRS 74

6.1 Approach to modelling the CPRS 74

6.2 Responses to the Modelling methodology and assumptions report 75

6.3 Responses to the draft report 77

6.4 CPRS results 79

7 Expanded RET, the GGAS and the ESS 83

ii Frontier Economics | March 2010 Final Report

Introduction

7.1 Expanded RET 83

7.2 The GGAS 92

7.3 The ESS 97

8 Ancillary services costs and market fees 101

8.1 Ancillary services costs 101

8.2 Market fees 104

9 Periodic review 106

9.1 Key uncertainties 106

9.2 Scope of the periodic review 109

9.3 Frequency of the periodic review 111

9.4 Materiality threshold for periodic reviews 112

10 Summary of advice 114

Appendix A – Modelling results 116

Appendix B – Modelling results using d-cyphaTrade contract

prices 121

Appendix C – Modelling results using example load shapes 124

Forward looking, hypothetical load shape example 124

Backward looking, NSLP load shape example 130

Final Report March 2010 | Frontier Economics iii

Tables & Figures


Figures

Figure 1: Frontier's energy modelling framework 7

Figure 2: Example daily load shapes for January 2009 and the monthly

average load shape 12

Figure 3: Diagrammatic comparison of the different ways of incorporating load

volatility into total cost 13

Figure 4: NSW annual energy forecasts from 2008 SOO and 2009 ESOO 16

Figure 5: NSW annual maximum demand forecasts from 2008 SOO and 2009

ESOO 17

Figure 6: Change in assumed capital cost – ACIL 2005 Report and ACIL

2009 Report (real 2009/10) 24

Figure 7: Change in assumed SRMC – ACIL 2005 Report and ACIL 2009

Report (real 2009/10) 25

Figure 8: LRMC for the Base and No CPRS cases (real 2009/10) 27

Figure 9: Investment outcomes - Base 31

Figure 10: Investment outcomes - No CPRS 31

Figure 11: Dispatch outcomes - Base 32

Figure 12: Dispatch outcomes - No CPRS 32

Figure 13: NSW annual average price forecast compared to d-cyphaTrade

forward prices (real 2009/10) 45

Figure 14: Distribution of forecast NSW annual average prices, Base case

(real 2009/10) 46

Figure 15: NSW supply demand balance including import capacity for

2010/11 (real 2009/10) 48


2011/12 (real 2009/10) 49


2012/13 (real 2009/10) 50

Figure 18: NEM dispatch outcomes - Base case 51

Figure 19: NEM dispatch outcomes - No CPRS case 52

Figure 20: Effect of carbon on an idealised supply curve 54

iv Frontier Economics | March 2010 Final Report

Introduction

Figure 21: Correlation between the Standard Retailers' regulated loads,

system load and system price (illustrative only) 56

Figure 22: Distribution of purchase cost – with and without contracts

(illustrative only) 57

Figure 23: Efficient frontiers – 2010/11 (real 2009/10) 62



Figure 26: Market-based energy purchase costs (real 2009/10) 65

Figure 27: Volatility allowance (real 2009/10) 69

Figure 28: Results using the LRMC and Market approaches (real 2009/10) 70

Figure 29: Average annual NSW price forecasts compared to the d-

cyphaTrade flat swap price 72

Figure 30: Energy purchase costs plus volatility premium for the Base, 2008

Demand and d-cyphaTrade cases 73

Figure 31: Carbon price pass-through under the LRMC approach 80

Figure 32: Carbon price pass-through under the market approach 81

Figure 33: Diagrammatic representation of bidding incentives with and without

a CPRS carbon price 82

Figure 34: NGAC spot prices, 2003 to 2009 (nominal) 95

Figure 35: Historic weekly ancillary services costs (nominal) 102

Figure 36: Forecast weekly ancillary services costs (real 2009/10) 103

Figure 37: Annual market fees (real 2009/10) 105

Figure 38: Total energy costs (excluding losses) (real 2009/10) 115

Figure 39: Results for d-cyphaTrade forward prices 123

Figure 40: Efficient frontiers for hypothetical case - 2010/11 126



Figure 43: Contract volumes for the hypothetical case - 2010/11 128



Figure 46: Energy purchase costs for the hypothetical case 130

Figure 47: Efficient frontiers for the historic 2008 NSLP case 131

Figure 48: Contract volumes for the historic 2008 NSLP case - CE 132

Figure 49: Contract volumes for the historic 2008 NSLP case - EA 133

Final Report March 2010 | Frontier Economics v

Tables & Figures

Figure 50: Contract volumes for the historic 2008 NSLP case - IE 133

Figure 51: Energy purchase costs for the historic 2008 NSLP case 134

Tables

Table 1: Input assumptions for new generation technologies 10

Table 2: Change in LRMC results relative to the draft report 28

Table 3: Renewable power percentages 84

Table 4: REC price (real 2009/10) 87

Table 5: Cost of complying with the expanded RET (real 2009/10) 92

Table 6: Implied floor price for NGACs (real 2009/10) 97

Table 7: ESS target 98

Table 8: Cost of complying with the ESS (real 2009/10) 100

Table 9: Ancillary services costs (real 2009/10) 104

Table 10: Market fees (real 2009/10) 105

Table 11: LRMC and market-based energy purchase cost results 116

Table 12: Breakdown of Market results 117

Table 13: Full results for the Base case 118

Table 14: Impact of changes to REC price 120

Table 15: d-cyphaTrade swap prices 122

Final Report March 2010 | Frontier Economics 1

Introduction

1 Introduction

The Independent Pricing and Regulatory Tribunal (IPART) was issued with a

terms of reference in June 2009 from the NSW Government requiring them to

determine regulated electricity retail tariffs and charges to apply to Standard

Retailers operating in NSW for the period between 1 July 2010 and 30 June 2013

(the determination).

Frontier Economics (Frontier) has been engaged by IPART to provide advice on

energy purchase costs for the determination.

1.1 Terms of Reference

The terms of references to IPART state:

This review should ensure the aims and approach of the 2007 determination

are preserved. IPART’s approach should result in prices that are based on the

efficient cost of supplying small retail customers, including customers who

revert from negotiated tariffs.

In regard to energy costs, the terms of reference state:

For energy purchases, IPART should determine a target Energy Purchase

Cost Allowance for 30 June 2013 and an Energy Purchase Cost Allowance for

each year of the Determination. The Energy Purchase Cost Allowance should

be set, using transparent and predictable methodology, at a level that would

allow a Standard Retailer Supplier to recover the efficient costs of managing

the risks associated with purchasing electricity from the NEM (including the

Carbon Pollution Reduction Scheme). Additionally, IPART should have regard

to the efficient costs of meeting any obligations that Standard Retail Suppliers

must comply with, including the costs of complying with greenhouse and

energy efficiency schemes (including present and future State and

Commonwealth schemes).

The Energy Purchase Cost Allowance for each year must not be lower than the

least cost mix of generating plant (based on those plants earning an economic

return on their market value), including any plant that would be required to

meet any regulatory obligation, (using generation technology that is available in

the NEM for the relevant year/period), to efficiently meet each Standard Retail

Supplier’s forecast regulated load.

The full Terms of Reference to IPART are available from IPART‟s web site.1

11 IPART Electricity Retail Price Terms of Reference. Available at:

http://www.ipart.nsw.gov.au/files/Terms%20of%20Reference%20-

%20Regulated%20electricity%20retail%20tariffs%20and%20charges%20for%20small%20customer

s%202010-2013%20-%2026%20June%202009%20-%20WEBSITE%20DOCUMENT.PDF

http://www.ipart.nsw.gov.au/files/Terms%20of%20Reference%20-%20Regulated%20electricity%20retail%20tariffs%20and%20charges%20for%20small%20customers%202010-2013%20-%2026%20June%202009%20-%20WEBSITE%20DOCUMENT.PDF



2 Frontier Economics | March 2010 Final Report

Introduction

1.2 Frontier Economics’ engagement

Frontier Economics has been engaged by IPART to provide advice on the

energy cost component of the determination. The focus of Frontier Economics‟

advice is the determination of forecast energy costs, including:

A total allowance for electricity purchase costs and associated volatility,

which, to the extent possible, should refer to publicly available market

information (such as d-cyphaTrade forward prices). This allowance should:

provide for the likely efficient impact of the Carbon Pollution reduction

Scheme (CPRS) on electricity prices

provide an efficient allowance that takes into account price and volume

for retailer compliance with expanded Commonwealth Mandatory

Renewable Energy Target (MRET) requirements and the licence

requirements relating to the NSW Greenhouse Gas Reduction Scheme

(GGAS) and the Energy Savings Scheme (ESS)

provide for fees (including charges for ancillary services) as imposed by

the Australian Energy Market Operator (AEMO) under the National

Electricity Rules

be based on the latest reasonable assumptions reflecting the operation

of the national electricity market

An estimate of the long run marginal cost (LRMC) of electricity generation,

including any plant that would be required to meet any regulatory obligation.

1.3 This report

This final report sets out Frontier Economics‟ advice to IPART on allowances

for energy costs to be incorporated into regulated retail tariffs and charges for

electricity for the current determination.

The modelling results set out in this final report are based on the modelling

methodology and assumptions set out in Frontier Economics‟ Modelling

methodology and assumptions report, provided to IPART in August 2009.2 For this

reason, for a detailed understanding of the modelling methodology and the

modelling assumptions underpinning the results set out in this final report, this

2 Frontier Economics, Modelling methodology and assumptions, A Report for IPART, August 2009.

Available at:

http://www.ipart.nsw.gov.au/files/Review%20of%20regulated%20electricity%20retail%20tariffs%

20and%20charges%202010%20to%202013%20-%20Frontier%20Economics%20%20-

%20electricity%20purchase%20cost%20allowance%20%20-

%20methodology%20and%20assumptions%20report%20-%2014%20August%202009.PDF

http://www.ipart.nsw.gov.au/files/Review%20of%20regulated%20electricity%20retail%20tariffs%20and%20charges%202010%20to%202013%20-%20Frontier%20Economics%20%20-%20electricity%20purchase%20cost%20allowance%20%20-%20methodology%20and%20assumptions%20report%20-%2014%20August%202009.PDF





Introduction

report should be read in conjunction with the Modelling methodology and assumptions

report.

The modelling results set out in this final report are, in large part, consistent with

those set out in Frontier Economics‟ Energy purchase costs draft report, provided to

IPART in December 2009.3 This final report is, essentially, an update of the draft

report. However ,there have been two changes to the modelling assumptions

since the release of Frontier Economics draft report:

slight amendments have been made to the discount cashflow model

developed by SFG Consulting to determine an annualised capital cost, and

the WACC assumption has been updated by IPART and this revised

assumption has been used as an input into Frontier Economics‟ modelling.

These changes result in changes to the results of Frontier Economics‟ LRMC

modelling, include both the modelling of the LRMC of supplying the Standard

Retailers‟ regulated load and the LRMC of meeting the expanded RET. The

change to the WACC also results in a slight change to the calculation of the

volatility allowance.

This final report is structured as follows:

Section 2 provides an overview of the two approaches used by Frontier to

estimate the energy purchase cost allowance, and the modelling

methodologies used under these two approaches

Section 3 provides an overview of the load shapes used in each the two

approaches to estimate an allowance for energy purchase costs

Section 4 sets out the results of Frontier‟s modelling of the LRMC of serving

the Standard Retailers‟ regulated load

Section 5 sets out the results of Frontier‟s modelling of the market-based

energy purchase cost of serving the Standard Retailers‟ regulated load

Section 6 sets out the results of Frontier‟s modelling of the impact of the

CPRS

Section 7 sets out Frontier‟s advice on the allowance for the costs of

complying with the expanded Renewable Energy Target (expanded RET), the

GGAS and the ESS

3 Frontier Economics. Energy purchase costs, Draft Report, December 2009. Available at:

http://www.ipart.nsw.gov.au/files/Consultant%20Report%20-%20Frontier%20Economics%20-

%20Energy%20Purchase%20Costs%20-%20December%202009%20-

%20WEBSITE%20DOCUMENT.PDF

http://www.ipart.nsw.gov.au/files/Consultant%20Report%20-%20Frontier%20Economics%20-%20Energy%20Purchase%20Costs%20-%20December%202009%20-%20WEBSITE%20DOCUMENT.PDF




Introduction

Section 8 sets out Frontier‟s advice on the allowance for ancillary services

costs and market fees

Section 9 provides a summary of Frontier‟s advice

In addition, this final report contains three Appendices:

Appendix A sets out Frontier Economics‟ modelling results

Appendix B sets out Frontier Economics‟ modelling results using d-

cyphaTrade contract prices, and

Appendix C sets out Frontier Economics modelling results using a

hypothetical retailer load shape and the NSLP.

With the release of Frontier Economics‟ Energy purchase costs draft report, Frontier

Economics also released two related files:

An addendum to Frontier Economics‟ Modelling methodology and assumptions

report, which sets out updates to the modelling assumptions since the release

of that report, and a spreadsheet setting out the same updated modelling

assumptions.

A spreadsheet setting out a sample set of results for a hypothetical retailer

load shape. The results include half-hourly load for the hypothetical retailer,

half-hourly system load, half-hourly spot prices, the contract position to meet

the half-hourly load for the hypothetical retailers (as modelled by Frontier

Economics), and the resulting market-based energy purchase cost. Given that

the Standard Retailers‟ regulated load is confidential, equivalent detail cannot

be released for each of the Standard Retailers‟. However, the same

methodology, has been applied to the hypothetical retailer load shape,

including the same methodology to ensure an appropriate relationship

between regulated load, system load and system prices.

With the release of this final report, Frontier Economics has released updates of

these two related files:

A spreadsheet setting out updates to the modelling assumptions since the

release of the draft report.

A spreadsheet setting out a sample set of results for a hypothetical retailer

load shape. For this final report, this sample set of results is set out both for

the hypothetical retailer load shape used for the draft report and for the Net

System Load Profile (NSLP).


Overview of modelling approach

2 Overview of modelling approach

As set out in Section 1.1, IPART‟s terms of reference for the determination

require IPART to consider two approaches to the energy purchase cost

allowance:

the LRMC of generating plant to serve the Standard Retailers‟ regulated load,

and

the market-based energy purchase to serve the Standard Retailers‟ regulated

load.

This section provides an overview of the modelling approach used by Frontier

Economics to estimate the LRMC to serve the Standard Retailers‟ regulated load

and the market-based energy purchase cost to serve the Standard Retailers‟

regulated load.

In undertaking the modelling for the purposes of this determination, Frontier

Economics has adopted its usual rigorous quality assurance standards. Frontier

Economics maintains a rigorous practice of mutual peer review to ensure

consistency, accuracy and best practice in our work. In order to safeguard our

strong reputation, we actively encourage collaboration and circulation of work-in-

progress materials among all levels within the firm prior to the preparation of any

reports and presentations. Frontier‟s standard practice for its modelling work is

to undertake a number of independent checks of input assumptions, calculations

and modelling results.

2.1 Modelling for 2007 determination

As discussed in Frontier Economics‟ Modelling methodology and assumptions report,

Frontier Economics adopts as its starting point substantially the same modelling

approach for the current determination as was used for the 2007 determination.

In part, this is a reflection of IPART‟s intention to draw on and expand on the

methodology that it used in the 2007 determination. IPART considers that

building on the methodology it used for the 2007 determination is consistent

with its terms of reference. It also considers that this is prudent, given that:

there is a reasonable degree of knowledge and acceptance among

stakeholders about the 2007 methodology

building on the current methodology will increase the regulatory certainty of

the 2010 review, and

developing and consulting on a completely new methodology would have

been extremely difficult given the timeframe for the review.



Frontier Economics also considers that the modelling approach that was used for

the 2007 determination remains appropriate for the current review. In particular,

Frontier Economics notes that Frontier Economics‟ energy modelling approach,

as adopted in the 2007 determination, was explicitly designed to examine the

impact of significant changes to the physical, regulatory or economic

characteristics of the electricity market. Frontier Economics‟ models contain a

representation of the physical, regulatory and economic characteristics of the

electricity market, so that they can be used to investigate the impact on costs and

on market outcomes of changes to these characteristics. For instance, some of

the factors that are expected to affect the electricity market during the term of

the current determination include changes to regulatory policies regarding

greenhouse gas emissions (including GGAS, MRET and the CPRS). As set out in

this report, assumptions about the operation of these policies over the period of

the current determination are incorporated into Frontier‟s modelling. Similarly, to

the extent that there have been changes in the ownership structure of the

industry, these have been accounted for in Frontier Economics‟ modelling.

In responding to IPART‟s Issues Paper, a number of stakeholders commented

that uncertainty over the design of regulatory policies such as the CPRS, MRET,

GGAS and the ESS make it difficult to determine the cost to retailers of these

policies over the course of the current determination. It is certainly the case that

changes to the design of these schemes, or decisions to defer or abandon these

schemes, have the potential to change the cost to retailers of these policies.

However, Frontier Economics considers that it is prudent to estimate the cost to

retailers of these schemes based on currently available information on their likely

operation. The impact of subsequent policy changes can be managed through

regulatory instruments such as the periodic review and cost pass-through

mechanism.

2.2 Frontier Economics’ energy market models

For the purposes of estimating energy costs, Frontier Economics adopts a three-

staged modelling approach, which makes use of three interrelated electricity

market models: WHIRLYGIG, SPARK and STRIKE. These models were used in

the 2007 determination. The key features of these models are as follows:

WHIRLYGIG optimises total generation cost in the electricity market,

calculating the least cost mix of existing plant and new plant options to meet

load. WHIRLYGIG provides an estimate of LRMC, including the cost of any

plant required to meet modelled regulatory obligations.

SPARK uses game theoretic techniques to identify optimal and sustainable

bidding behaviour by generators in the electricity market. SPARK determines

the optimal pattern of bidding by having regard to the reactions by generators

to discrete changes in bidding behaviour by other generators. The model



determines profit outcomes from all possible actions (and reactions to these

actions) and finds equilibrium bidding outcomes based on game theoretic

techniques. An equilibrium is a point at which no generator has any incentive

to deviate. The output of SPARK is a set of equilibrium dispatch and

associated spot price outcomes.

STRIKE uses portfolio theory to identify the optimal portfolio of available

electricity purchasing options (spot purchases, derivatives and physical

products) to meet a given load. STRIKE provides a range of efficient

purchasing outcomes for different levels of risk where risk relates to the

levels of variation of expected purchase costs.

The relationship between Frontier‟s three electricity market models is

summarised in Figure 1.

Figure 1: Frontier's energy modelling framework

* Plant output from WHIRLYGIG and SPARK differs due to different assumptions about bidding behaviour.

As discussed, there are essentially two aspects to Frontier Economics‟ analysis

for the current determination: an estimate of LRMC and an estimate of market-

based energy purchase costs.

● To estimate LRMC, Frontier uses WHIRLYGIG, which identifies the least

economic cost mix of existing plant and new plant options to meet load. The

results of the LRMC modelling are discussed in Section 4.

Plant build

Plant output*

LRMC

Demand

Network

Existing plant

New plant options

Regulations

Demand

Network

Existing plant

New plant options

Regulations

Plant build

Contract

levels

Plant build

Contract

levels

Industry structure

(ownership)

Strategic players

and bid options

Industry structure

(ownership)

Strategic players

and bid options

Pool prices

Plant output*

Price

distributions

Plant dispatch

Price

distributions

Plant dispatch

Customer load

Forward curve

Customer load

Forward curve

Efficient frontier’s

optimal portfolio



● To estimate energy purchase costs, Frontier Economics uses STRIKE, which

identifies the least cost portfolio of electricity purchasing options for each

level of risk. An important input into the estimation of energy purchase costs

(which is used in STRIKE) is a forecast of future spot prices. In order to

forecast spot prices, Frontier Economics uses SPARK, which applies game

theoretic techniques to forecast spot price outcomes. The results of

Frontier‟s market-based energy purchase cost modelling are discussed in

Section 5.

2.3 Overview of modelling assumptions

As with all modelling results, the results will depend on the input assumptions

used. A detailed description of the input assumptions used in the modelling

undertaken for this final report is provided in Frontier‟s Modelling methodology and

assumptions report, as updated by the spreadsheet accompanying the draft report

and this final report. Several general comments can be made about the choice of

these input assumptions:

To the extent possible, Frontier Economics has adopted input assumptions

that are publicly available. This increases the transparency of Frontier‟s

modelling results.

To the extent possible, Frontier Economics has adopted input assumptions

that are considered to be industry standard. Input assumptions from these

sources tend to be relatively widely accepted. Also, adopting input

assumptions from these sources is likely to better facilitate the comparison of

Frontier‟s modelling results with forecasts or modelling from other sources.

Frontier Economics has used the most recent input assumptions available at

the time the modelling is undertaken (within the constraint of using publicly

available and industry standard assumptions).

Reflecting these objectives, and as discussed in Frontier Economics‟ Modelling

methodology and assumptions report, to a large extent the following sources have

been relied upon:

AEMO, Electricity Statement of Opportunities for the National Electricity

Market, 2009. (AEMO 2009 ESOO)

ACIL Tasman, Fuel resource, new entry and generation costs in the NEM,

Final Report, Prepared for the Inter-regional Planning Committee, April

2009.4 (ACIL 2009 Report)

4 The data in this report is prepared for the Inter-regional Planning Committee to enable NEMMCo

to conduct market simulation studies as part of the National Transmission Statement.



Concept Economics, Review of Inputs to Cost Modelling of the NEM,

Report for the Queensland Competition Authority, May 2009. (Concept 2009

Report)

2.3.1 Amendments to modelling assumptions for the draft

report

At the time of release of the Modelling methodology and assumptions report, the

AEMO 2009 ESOO had not yet been published. The ESOO was released in

October, subsequent to when the modelling assumptions paper was published.

Prior to the draft report, updates were made to assumptions where appropriate

to reflect this more recent data. This includes updating input assumptions to

reflect the capacity of existing plant and the timing and size of committed plant

due to enter the NEM during the period of the determination. Frontier

Economics had already obtained the demand forecasts published in the ESOO

from the Network Transmission Operator‟s Annual Planning Reports, so that no

update of demand assumptions was required.

The other change to the modelling assumptions prior to the draft report related

to the amortisation of capital costs from the ACIL 2009 Report. The spreadsheet

accompanying the ACIL 2009 Report included an amortisation including a

treatment of tax and interest during construction. This amortisation used ACIL‟s

assumed WACC. As IPART wished to use a different WACC, Frontier

Economics needed to amortise costs to reflect IPART‟s WACC. This was

achieved with assistance from SFG Consulting.

With the release of Frontier Economics‟ Draft Report, IPART also released an

updated spreadsheet from Frontier Economics that reflects the new assumed

capacities from the 2009 ESOO, the revised fixed costs for new plant and

includes an example of how the amortisation is calculated.

2.3.2 Further amendments to modelling assumptions for the

final report

For this final report, there have been two further changes to the modelling

assumptions.

A slight change has been made to the model developed by SFG Consulting to

amortise fixed costs. This change is reflected in an updated example of how the

amortisation is calculated, which is set out in the spreadsheet released with this

final report.

IPART‟s WACC has also been updated since the draft report. This has resulted

in a change to the results of the amortisation of fixed costs. Table 14 of the

Modelling methodology and assumptions report has been reproduced as Table 1 below,



with the updated results for fixed costs. Further detail is set out in the

spreadsheet released with this final report.

Table 1: Input assumptions for new generation technologies

Technology

Fixed

cost

($/kW)

Fixed O&M

costs

($/MW/year)

Annualised

fixed costs

($/MW/h)

Marginal

Cost

(SO) ($/MWh)

Emissions

(SO)

(tCO2/MWh)

Heat Rate

(SO)

(GJ/MWh)

CCGT 1,275 31,000 $8.59 40.95 0.47 7.20

OCGT 918 13,000 $13.09 85.63 0.76 11.61

SC Black Coal 2,213 48,000 $24.93 12.77 0.88 9.00

USC Black Coal 2,368 48,000 $26.38 11.97 0.82 8.37

IGCC Black Coal 3,481 50,000 $42.56 15.34 0.86 8.78

SC Brown Coal 2,434 55,000 $27.88 7.65 1.05 11.25

Sources: ACIL 2009 Report, Concept 2009 Report

Notes: Fixed costs are the amortised capital, tax and interest during construction costs.

All costs are in real 2009/10 dollars.

Marginal costs in this table are for plant in Central NSW region, except SC Brown Coal which is for VIC plant.

Emissions include fugitive emissions.

Emissions in this table are for plant in NSW region, except SC Brown Coal which is for VIC plant.


Demand forecasts used in modelling

3 Demand forecasts used in modelling

As discussed in the Modelling methodology and assumptions report the modelling

framework uses forecasts of the demand for both system load and for the

regulated load of each of the NSW Standard Retailers.

Ultimately, a key objective in the modelling is to capture the volatility of load

over time. This is particularly important is respect of forecasts of the Standard

Retailers‟ regulated load, because the load volatility that retailers face is an

important determinant of the costs and risks they face in supplying their

customers.

This section provides an overview of the load forecasts used in the modelling,

including:

accounting for load volatility

the assumptions regarding the forecast regulated load of each Standard

Retailer, and

the assumptions regarding the forecast system demand.

3.1 Accounting for load volatility

In setting the regulated price it is important that Standard Retailers are

compensated for the cost associated with the volatility of the load that they are

likely to face. Load volatility reflects the extent to which load differs from

expected levels on a half hourly basis.

In practice, actual load in the future will always be greater than or less than

forecast. Figure 2 shows the average and actual daily regulated load shapes for

January 2009 provided by the NSW Ministerial Corporation responsible for

administering the Electricity Tariff Equalisation Fund (ETEF). The shapes are

based on NSW regulated load as a whole and are not specific to any individual

retailer. It is clear from Figure 2 that the average load shape over the month is

flatter and less volatile than many of the individual day‟s shapes. For example, the

load shape with the highest peak load (approximately 1,400 MW) has roughly the

same minimum level as the average shape but its peak value is 40% greater. As

such, the load is said to be „peakier‟ and is more volatile. Deviations above the

expected level are usually associated with higher prices, due to the positive

correlation between load and pool prices. As a result, retailers are more

concerned about these upside deviations than by the downside risk that load is

less than expected (ignoring the costs of over-contracting).



Figure 2: Example daily load shapes for January 2009 and the monthly average load

shape

Ultimately, retailers need to ensure that they recover the cost of buying energy

from the pool (plus any contracting costs) for a given expected load shape.

Necessarily, this cost includes the cost of managing the risks associated with

volatility of load. There are a number of ways that this can be accomplished. For

example:

load volatility can be implicitly included in a range of forecast load shapes

such that that total cost to serve incorporates load volatility directly (for the

purposes of this report this will referred to as the Implicit method); or

cost to serve can be worked out for some average profile (with reduced load

volatility) and the cost of load volatility can be added on as a premium

(referred to in this report as the Separate method).

The Implicit method involves using an assumed load shape, or set of load shapes,

that are representative of the level of volatility that is expected in the future.

These load shapes would presumably be consistent with observed historic load in

terms of volatility levels. For example, an expected case would have volatility

consistent with average historic volatility levels and other sensitivity load shapes

could be constructed that had higher and/or lower levels of volatility in line with

the spread of historic volatility outcomes. Any cost calculated in this way reflects

the cost of energy including the cost of load volatility.



In the Separate method, load volatility is incorporated as a premium to some

average forecast load shape. This average shape would be flatter and less volatile

than actual historic outcomes (or likely future outcomes) due to the averaging

process in direct analogy to the shapes shown in Figure 2. The bundled cost in

this case is comprised of the (lower) base cost associated with the cost of serving

the average load shape plus some premium to cover the load volatility, which is

calculated separately. Typically, the „load volatility premium‟ under this Separate

method is related to the cost of managing the incremental variations in the load.

One example would be the cost of purchasing additional cap contracts (which

cap the price of electricity at a specified level). The „load volatility premium‟ can

be thought of as a load forecasting correction premium that is necessitated by

using a flat, average profile.

Frontier Economics‟ view is that the two methods, if performed correctly, should

deliver similar total costs. This is shown diagrammatically in Figure 3.

Figure 3: Diagrammatic comparison of the different ways of incorporating load

volatility into total cost

The Implicit method results in a total energy purchase cost and does not

distinguish between base cost and „load volatility premium‟. Frontier Economics

considers that modelling the load volatility using the Implicit approach is



preferable because while these two methods could be aligned in principle, in

practice the Separate method unnecessarily introduces modelling complexities

and inconsistencies which are likely to result in an estimate of energy purchase

costs that are not reflective of efficient costs.

For example, it is extremely important to ensure that there is an effective

correlation between load and price volatility for the purposes of calculating

LRMC and market based costs, otherwise the estimated energy purchase costs

will be inefficient. For example, if a two-staged (Separate) approach was used to

calculate LRMC this would require building a generation system for an average

load and then, ex-post, grafting some extra plant onto the system to meet load

volatility. This two-staged approach risks losing the scope and scale economies

that exist in a system of generating plants that can economically meet base,

intermediate and peak load requirements. A similar problem exists in the market

based energy purchase cost concept. An approach that relies on first hedging for

average load and then, separately, for a volatility component, risks losing the

portfolio benefits of a suite of contracts that can effectively hedge volatile load.

Capturing the efficiencies of these plant and hedging portfolio benefits is a key

aspect of Frontier Economics‟ approach for measuring an efficient energy

purchase cost.

Using load shapes that are consistent with historic levels of volatility is consistent

with this preferred modelling approach. Frontier Economics used the forecasts

of regulated load submitted by the Standard Retailers. These forecast load are

consistent with observed levels of volatility and encapsulated a spread in volatility

outcomes for the Standard Retailers‟ regulated load shapes. This allowed Frontier

Economics to properly incorporate load volatility into the analysis as well as

allowing for the correlation between load and price to be included correctly.

3.2 Standard Retailers’ regulated load shapes

Frontier Economics has used data provided by the Standard Retailers on

regulated load. Forecast half hourly regulated load was submitted by each

Standard Retailer for each financial year of the determination. For a given retailer

and financial year, three forecasts were provided. These forecasts represented an

expected, low and high volatility case. Volatility was measured using the annual

load factor.5

Frontier Economics examined the load forecasts provided by each Standard

Retailer in detail and compared the load forecasts with historical ETEF data

(taking account of any embedded generation). Based on this analysis, Frontier

5 Load factor is average load divided by peak load and is a simple measure of the peakiness/volatility

of the load shape.



Economics is satisfied that the load forecasts provided by each Standard Retailer

reflect historic trends in average demand, peak demand and load factor.

In addition, Frontier Economics worked with the Standard Retailers to ensure:

● each of the three forecasts reflected the expected annual energy as forecast by

each retailer. As such, for a given retailer and year, all three of the half hourly

load traces have the same annual energy, but different levels of volatility

throughout the year, and

● all of the retailer forecasts were properly correlated to both system demand

and prices. This was important for the market modelling as it enables the

modelling of price outcomes for the system and then correctly mapped these

prices back to each of the Standard Retailers‟ regulated load shapes.

As a result of accounting for load volatility through a range of forecast load

shapes that reflect actual historic and likely future volatility, Frontier Economics

does not need to separately include a „load volatility premium‟ in the

determination. Rather, this cost is already included in the costs associated with

and across the Standard Retailers‟ regulated load shapes.

3.3 System load forecasts

As discussed in the Modelling methodology and assumptions report, both

WHIRLYGIG (when used to model the system) and SPARK require

assumptions on system load. Three main input assumptions are required for each

of the NEM regions:

half hourly profile shapes

forecast of annual energy, and

forecast of summer and winter peak demand.

The profile shapes are properly correlated to the regulated load shapes submitted

by the Standard Retailers. Forecast assumptions for energy and peak demand

were taken from the AEMO 2009 ESOO for each NEM region.

Frontier Economics chose to use the High energy, 50% POE case from the

AEMO 2009 ESOO. While the AEMO 2009 ESOO was released in August

2009, the demand forecasts in the document were finalised by the Transmission

Network Service Providers and their consultants much earlier, in March 2009. At

this point, pessimism regarding the impact of the global financial crisis on the

economy, and on demand for electricity, was at its height. As a result, Frontier

Economics considers that the medium forecast from the AEMO 2009 ESOO is

likely to reflect an unrealistically low forecast of demand over the period of the

determination. For these reasons the high energy forecasts from the AEMO 2009

ESOO are considered to be more reflective of likely demand over the period of

the determination.



Figure 4 compares the NSW annual energy forecasts from the NEMMCO 2008

SOO6 and the AEMO 2009 ESOO. Figure 5 compares the forecasts of

maximum demand from the same reports. In terms of energy, the NEMMCO

2008 SOO medium forecast is at least 3,000 GWh higher than both the AEMO

2009 ESOO medium and high forecasts. A similar relationship is also apparent in

the maximum demand forecasts, where the NEMMCO 2008 SOO forecast is at

least 150 MW higher than the AEMO 2009 ESOO forecast.

Figure 4: NSW annual energy forecasts from 2008 SOO and 2009 ESOO

Note: Forecasts are Scheduled, Semi-Scheduled and Significant Non-Scheduled Demand on a Sent Out

basis.

6 NEMMCO, Statement of Opportunities for the National Electricity Market, 2008 (NEMMCO 2008 SOO).



Figure 5: NSW annual maximum demand forecasts from 2008 SOO and 2009 ESOO

Note: Forecasts are Scheduled, Semi-Scheduled and Significant Non-Scheduled Demand on a Generator

Terminal basis.


Long run marginal cost

4 Long run marginal cost

The LRMC of generating plant is typically determined on the basis of the least

economic cost mix of plant to meet the required load to a particular security

standard. The LRMC of generating plant should also have regard to other

statutory obligations, including obligations to meet greenhouse targets.

This section sets out the results of the LRMC modelling of generating plant to

serve the regulated load of the Standard Retailers, including:

an overview of the approach to estimating LRMC that is considered to be

consistent with the terms of reference

a discussion of responses to the Modelling methodology and assumptions report,

and further work that has undertaken since the release of that report in

regard to capital costs of generating plant, and

the results of the LRMC modelling of the generation system.

4.1 Frontier’s approach to estimating LRMC

As discussed in the Modelling methodology and assumptions report, there are two broad

approaches to estimating the LRMC:

Stand-alone LRMC – this approach assumes that there is currently no plant

available to serve the required load. This approach effectively builds, and

prices, a whole new least-cost generation system to meet the required load.

This approach has the effect of re-pricing all existing capacity at efficient

levels.

Incremental LRMC – this approach assumes that the existing mix of

generation plant in the system is in place and that the required load can be

served using both existing generation plant and new generation plant. Under

this approach, new generation plant is only built if it is required as part of a

least-cost generation system to meet the required load. This approach prices

load on the basis of the least cost way of adding to the existing stock of plant.

Before considering which model to use, it is useful to consider how capital and

variable costs are treated when estimating LRMC. Frontier Economics treats the

capital costs of existing and committed generation plant as sunk, and therefore

irrelevant to economic decisions. In deciding whether to run existing plant, only

variable costs are taken into account. In contrast, capital costs of new plant are

relevant to economic decisions, since these costs are not sunk. In deciding

whether to run new plant, therefore, both capital costs and variable costs are

taken into account. An implication of this is that, under an incremental LRMC,

the capital cost of generation plant will not be reflected in the estimate of LRMC

unless investment in new generation plant is part of a least-cost outcome.



This is important for estimating LRMC over the period to 2012/13. Since

investment that is likely to occur over the period to 2012/13 is already

committed, an estimate of incremental LRMC will not account for the capital

costs of new plant as these are, by definition, sunk. This is not consistent with

the terms of reference, which require that the LRMC be “based on …

[generation plant] earning an economic return on their market value”. Stand-

alone LRMC produces an LRMC that accounts for capital costs, an appropriate

economic return, as well as variable costs.

Calculating an incremental LRMC is also problematic in cases where the

objective is to estimate the LRMC of meeting a subset of the system load, such as

a regulated load. The reason is that investments in the existing mix of generation

plant (i.e. base load, shoulder and peak) have been undertaken to meet system

load; these investments cannot be appropriately incorporated into modelling of a

much smaller load, such as a regulated load.

For these reasons, Frontier Economics estimates the LRMC of serving the

Standard Retailers‟ regulated load using the stand-alone LRMC approach. Under

this approach, the load used to estimate LRMC is the Standard Retailers‟

regulated load, and the LRMC is the cost of adding an increment of capacity to a

hypothetical new least-cost generation system to meet this regulated load.7

Importantly, however, and as set out in Figure 1 and discussed in more detail in

the Modelling methodology and assumptions report, least cost modelling has also been

undertaken to provide inputs for subsequent stages of Frontier Economics‟

modelling approach. This is discussed in more detail in Section 5.1 and Section 7.

4.2 Responses to the Modelling methodology and

assumptions report

In response to the Modelling methodology and assumptions report, a number of

stakeholders commented on specific input assumptions proposed to be used in

modelling of LRMC. This section provides an overview of, and response to,

these submissions.

4.2.1 Discount rate

In regard to the assumed discount rate,8 Origin Energy commented that the real

pre-tax discount rate set out in Table 8 of the Modelling methodology and assumptions

7 In effect, the LRMC is calculated by adding to the regulated load an increment that is the same

shape as the regulated load. This ensures that the LRMC reflects the mix of plant that is efficient,

given the shape of the regulated load.

8 Discussed in Section 3.3.2 of Frontier‟s Modelling methodology and assumptions report.



report (7.3 per cent) is inconsistent with the real pre-tax discount rate set out in

Section 3.3.2 of the same report and in IPART‟s report (8.2 per cent).

This inconsistency is a result of Table 8 in Frontier‟s Modelling methodology and

assumptions report not being updated to reflect the advice from IPART on the

appropriate discount rate for electricity generation assets. For clarity, a real pre-

tax discount rate of 8.0% has been used in the LRMC modelling, as instructed by

IPART. This has changed relative to the draft report (where 8.2% was used) in

line with the updated WACC provided by IPART.

4.2.2 Capital cost assumptions

AGL raised two sets of comments regarding the capital cost assumptions set out

in the Modelling methodology and assumptions report.

Treatment of taxation and interest during construction

In regard to the calculation of fixed costs for new generation plant,9 AGL

commented on and requested further information on the treatment of interest

during construction and taxation.

Since releasing the Modelling methodology and assumptions report, Frontier Economics

has received further information on the calculation of generators‟ fixed costs as

reported in the ACIL 2009 Report. Following this, and in order that the fixed

costs used in the modelling are consistent with the WACC assumptions adopted

by IPART, SFG Consulting has constructed a discounted cashflow model that

consistently incorporates the WACC assumptions, tax and interest during

construction. This discounted cashflow model was used to calculate the

amortised fixed costs assumed in the modelling.

Renewable generation plant

In regard to renewable generation plant,10 AGL commented that it has concerns

with the use of capital cost inputs from the Concept 2009 Report. In particular,

AGL commented that it considers that the Concept 2009 Report understates the

capital costs of wind generation, which have increased due to economic

conditions and global demand for renewable technologies.

Frontier Economics notes that the Concept Economics report is a useful source

of costs for renewable technologies in the NEM for a number of reasons:

It is a recent study, undertaken for the purposes of a recent regulatory

determination of electricity tariffs





For thermal generation, the cost estimates in the ACIL 2009 Report and the

Concept 2009 Report are very similar, and

In regard to the cost estimate for renewable generation plant, Frontier

Economics notes that the cost estimate from the Concept 2009 Report is

within the range of a number of other publicly available cost estimates

4.2.3 Fuel cost assumptions

Origin Energy raised a number of questions about the fuel price forecasts set out

in the ACIL 2009 Report and used in the modelling:11

Origin Energy submits that other advisers show the links between domestic

markets and international markets, which lifts domestic fuel prices, and

Origin Energy submits that fuel costs should reflect assumptions regarding

the expanded RET and CPRS that are consistent with Frontier Economic‟

modelling.

Given the current plans for the development of a sizeable coal resource to supply

NSW baseload generators (Cobbora) dedicated to the supply of existing and new

coal fired generators in NSW at prices that reflect extraction costs, not the

opportunity cost of the coal, Frontier Economics expects that Origin Energy‟s

concerns about the internationalisation of fuel prices is largely related to gas

prices, not coal prices.

In regard to gas prices, Frontier Economics notes that the ACIL 2009 Report

explicitly states that the announcement of proposals to process coal seam

methane for export as LNG from Gladstone is one of the factors that have

driven the updated forecasts for gas prices in the ACIL 2009 Report, compared

to earlier ACIL reports. The modelling of gas prices in the ACIL 2009 Report

assumes the development of two LNG facilities at Gladstone, and the forecast

gas prices converge “to what could be considered a new long term equilibrium

level with the inclusion of significant LNG export facilities”.12

In regard to assumptions regarding the expanded RET and CPRS, Frontier

Economics notes that the ACIL 2009 Report explicitly states that the

commencement of the CPRS and the expanded RET are factors that have driven

ACIL‟s updated forecasts for gas prices.13

Accordingly, we have used the fuel price forecasts set out in the ACIL 2009

Report in our modelling.


12 ACIL 2009 Report, page 68.

13 ACIL 2009 Report, page 63.



4.2.4 Hydrology assumptions

In regard to assumptions about hydrology,14 some stakeholders questioned

whether the availability of water to thermal generation plant is likely to reflect

normal hydrology conditions. EnergyAustralia noted that there is a growing

consensus that Australia is entering an El Nino pattern, and that this is likely to

lead to drier conditions with an impact on hydro storages. Origin Energy

commented that Snowy Hydro may not be in a position to generate to the rate

assumed by Frontier Economics.

Frontier Economics notes that the Bureau of Meteorology (BOM) have

identified an El Nino event over the Pacific Basin, and that the BOM state that

El Nino events are usually associated with below average rainfall. The BOM‟s

most recent rainfall outlook for the December quarter states that:15

The chances of exceeding median rainfall in November to January are

between 25 per cent and 40 per cent over southeast Queensland, and eastern

NSW. This means that for every ten years with ocean patterns like the

current, about six or seven years are expected to be drier than average over

these regions, while about three or four years are wetter

The chances of exceeding median rainfall in November to January are

between 40 per cent and 60 per cent in Victoria, South Australia, western

NSW and most of Queensland. This means that above average falls are about

as equally likely as below average falls in these regions

This suggests that for much of the NEM, above average rainfalls are about as

likely as below average rainfalls over the coming summer.

Of course rainfalls over the longer-term, including the period of the

determination, are impossible to predict. This is the reason that Frontier

Economics proposes to model average rainfall conditions. In this regard,

Frontier Economics notes that average energy production by Snowy Hydro over

the period 2002/03 to 2008/09 has been 4360 GWh, only slightly below the

4,500 GWh limit adopted in the modelling.16 Energy production by Snowy Hydro

in 2007/08 and 2008/09 has been below these average levels, but Frontier


15 Bureau of Meteorology, National Seasonal Rainfall Outlook: Probabilities for November 2009 to January

2010, 23 October 2009. Available at::

http://www.bom.gov.au/climate/ahead/rain_ahead.shtml

16 Snowy Hydro‟s actual energy production includes gas-fired generation. However, since Snowy

Hydro only operates peaking gas-fired generators, these do not generate substantial energy.

http://www.bom.gov.au/climate/ahead/rain_ahead.shtml



Economics notes that Snowy Hydro‟s water storages are currently above those at

same time in 2006, 2007 and 2008.17

4.2.5 Plant availability

In regard to assumptions about the availability of Colongra, a peaking open cycle

gas turbine plant located on the Central Coast of NSW, Origin Energy

commented that it understands that Colongra has limited gas availability, so its

availability to run at an operating cost of $90/MWh is limited. Frontier

Economics notes that since Colongra is a peaking plant, with a high marginal

cost even when running on gas, it will only require limited gas. Colongra is

forecast in SPARK to run at capacity factors at or less than 1 per cent. Frontier

Economics considers that this level of operation is unlikely to be prevented by

gas restrictions.

In regard to assumptions about the availability of new generation plant,18 Origin

Energy commented that the assumption that the USC and IGCC generation

technologies will be available from 2013/14 is unrealistic. Frontier Economics

notes that proposals to develop both USC and IGCC plant in the NEM are

public, and that some of these proposals are for plant to be available by 2013/14.

Nevertheless, it may be that IGCC, in particular, is not available at commercial

scale until later than 2013/14. Ultimately, however, since this is beyond the

period of the current determination, it will make no difference to modelling

results used for the purpose of this determination.

In any event, neither USC nor IGCC coal plant are part of the optimal plant mix

determined by Frontier‟s modelling, so the availability of such plant from

2013/14 is a moot point.

4.2.6 Outage rate for peaking plant

In regard to assumptions about outage rates for peaking plant,19 Origin Energy

commented that the assumption of a forced outage rate for gas peaking plant of

zero is not appropriate.

Frontier Economics notes that the assumption that the forced outage rate for

peaking plant is zero is simply an assumption that peaking plant will be made

available when it is required. The operators of peaking assets are highly

incentivised to ensure that this is the case as such plant typically only run for less

than 3 per cent of the year. This assumption has therefore been retained.

17 Snowy Hydro lake levels available at:

http://www.snowyhydro.com.au/lakeLevels.asp?pageID=360&parentID=6


19 Discussed in Section 3.3. of Frontier‟s Modelling methodology and assumptions report.

http://www.snowyhydro.com.au/lakeLevels.asp?pageID=360&parentID=6



4.3 Changes in input cost assumptions relative to

2007 determination

The 2007 determination used ACIL Tasman‟s 2005 report on generator costs as

a source for input cost assumptions (this being the most up to date source at the

time). The current determination uses the ACIL 2009 Report. In the time

between the 2007 determination and the current determination there have been

significant increases in both the capital costs and, particularly in the case of gas,

the fuel costs of new entrant plant. Other costs have also increased.

Figure 6 and Figure 7 show the assumed capital cost and SRMC costs from the

ACIL 2005 Report (used in the previous determination) and the ACIL 2009

Report (used in the current determination). Costs are presented in real 2009/10

dollars.

Figure 6: Change in assumed capital cost – ACIL 2005 Report and ACIL 2009 Report

(real 2009/10)



Figure 7: Change in assumed SRMC – ACIL 2005 Report and ACIL 2009 Report

(real 2009/10)

The greatest increase in assumed costs between the 2007 determination and the

current determination occurs for capital costs. This increase reflects increases in

commodity prices, and particularly increases in the prices for generating turbines,

from 2005 to 2009. Increases in assumed labour costs of construction are also a

factor. Cost increases are on the order of 30-40 per cent, depending on

technology.

Estimates of SRMC costs have also increase from 2005 to 2009. The cost of both

coal and gas has increased, as have variable operating and maintenance costs.

This has resulted in an SRMC increase of approximately 20-25 per cent for coal

and CCGT plant. For OCGT plant not only has the assumed cost of gas

increased in line with CCGT plant but the cost has increased more. This is

because the delivered cost of gas is inversely related to the capacity factor of the

plant that requires the gas. CCGT plant operate at higher capacity factors and pay

less for gas as a result, OCGT plant operate far less frequently and pay a higher

gas price.

The effect of the increase in assumed input costs results in higher estimates of

LRMC than were calculated as part of the previous determination. This is

discussed below.



4.4 LRMC results

Results for the stand alone LRMC approach are set out in this section.

As discussed above, the results presented in the following Section reflect changes

in the input assumptions for:

an update of WACC, which is used to amortise the costs of all generation

options included in the modelling, and

a change in the discounted cashflow model that is used to amortise the fixed

costs of thermal options.

WACC was updated from 8.2% to 8.0% resulting in a lower cost for each of the

generation options included in the modelling. The change in the cashflow model

resulted in slightly higher fixed costs for the thermal generation options.

Combining these changes produced a net effect of reducing the input fixed cost

assumptions in the modelling.

4.4.1 Results

Results are presented for two cases – Base and No CPRS. Key assumptions for

each case are as follows:

Base

o ACIL 2009 Report cost with Frontier/SFG amortisation of fixed

costs (WACC updated and amortisation revised since the draft

report)

o Regulated forecast load for the expected volatility case

o CPRS5 modelled as a carbon price as set out in Frontier‟s Modelling

methodology and assumptions report

No CPRS

o As per Base but with an assumed carbon price of zero

The cost of carbon is modelled as a carbon price which is included in the SRMC

of each generation technology, at the emissions rate of the technology. Results

are presented in Figure 8.



Figure 8: LRMC for the Base and No CPRS cases (real 2009/10)

LRMC for the three businesses starts in the $60-$70/MWh range for 2010/11.

This is significantly higher than the $45-$55/MWh range from the final year of

the last determination.20 The increase is the result of the increase in input costs,

as discussed in Section 4.3.

In 2010/11, as is the case for all years, the LRMC determined for the businesses

is highest for Integral Energy and lowest for Country Energy. This is reflective of

the load shapes of the businesses. Integral Energy‟s regulated load is relatively

peaky due to it containing the majority of western Sydney‟s temperature-sensitive

load. Conversely, Country Energy‟s regulated load is more geographically diverse

leading to an overall flatter load. EnergyAustralia‟s regulated load lies in the

middle of these two businesses.

Over the three years of the determination, the LRMC results for the No CPRS

case remain relatively constant. This is consistent with the assumed input costs

being relatively constant in real terms. The exception to this is gas costs, which

are forecast in the ACIL 2009 Report to rise over the determination period.

These rises have little effect on the total calculated LRMC as gas generators do

not operate very much in the absence of an emission trading scheme.

20 Price ranges are quoted in real 2009/10 dollars.



For the Base case, which assumes a carbon price in line with the Commonwealth

Government‟s forecasts associated with the CPRS 5 target, LRMC rises over the

period of the determination. These rises are due to the imposed cost of carbon in

2011/12 and 2012/13. The effect of carbon, and the levels of pass-through that

are an output of the modelling, are discussed in more detail, along with the

market carbon results, in Section 6.

4.4.2 Differences relative to the draft report

Updating the analysis for the updated WACC and cost amortisation calculation

has resulted in consistently lower LRMC outcomes. Results have reduced by

approximately 1 per cent relative to the results presented in the draft report, this

is shown in Table 2. In 2010/11, when there is no price on carbon and the

investment mix is dominated by coal, both the Base and No CPRS cases fall by

approximately 1.3 per cent in line with the decrease in input costs. This decrease

is constant across all three years for the No CPRS case, consistent with the mix

of plant remaining constant over time in that case. For the Base case, where the

introduction of a carbon price changes the plant mix towards CCGT over time,

the cost difference is not as large. The reason for this is the different build

profiles for different types of plant; the cost amortisation model accounts for

these different build profiles in determining the fixed costs of different

generation technologies.

Table 2: Change in LRMC results relative to the draft report

Financial year Business Base No CPRS

2010/11 CE -1.2% -1.2%

EA -1.3% -1.3%

IE -1.4% -1.4%

2011/12 CE -1.1% -1.2%

EA -1.2% -1.3%

IE -1.3% -1.4%

2012/13 CE -0.8% -1.2%

EA -0.9% -1.3%

IE -1.0% -1.4%



4.4.3 Investment and dispatch outcomes

The following charts (Figure 9 to Figure 12) present the investment and dispatch

outcomes associated with the LRMC modelling, for each Standard Retailer and

for each financial year. Figure 9 and Figure 10 present the investment results for

the Base and No CPRS cases respectively. Similarly, Figure 11 and Figure 12

present the dispatch results for the Base and No CPRS cases respectively. The

charts show the results as a percentage of total investment/dispatch. This enables

easy comparison between the three Standard Retailers, which have different peak

load and energy.

In considering the investment and dispatch outcomes associated with the LRMC

modelling, it is important to note that under the stand-alone LRMC approach,

the system that is built to serve the Standard Retailers‟ regulated load is optimised

each year. This is important because in cases where the regulated load is falling

over time, if the system is not optimised each year the resulting LRMC would

reflect excess capacity in the later years of the determination, and may not include

a capital cost component. Because the system is optimised each year, changes in

patterns of investment and dispatch from year to year – particularly in response

to the introduction of the CPRS – are more pronounced than would be expected

in the actual system where investments require long lead times and, once

committed, plant will remain in the system until it is retired. These investment

constraints are reflected in Frontier Economics‟ modelling under the market-

based approach.

The optimal pattern of investment and dispatch involves a mixture of coal fired,

CCGT and OCGT plant in every case presented.

For the Base case investment (Figure 9), the mix across the Standard Retailers in

2010/11 is roughly 40-50% coal, 10-15% CCGT and the residual capacity is

OCGT. The percentage of OCGT plant is higher for EnergyAustralia and higher

still for Integral Energy when compared to Country Energy. This reflects the

relative peakiness of the Standard Retailers load (Integral Energy is the peakiest).

For 2011/12 and 2012/13, as the assumed carbon price increases, we observe a

substitution away from coal fired plant towards CCGT. This reflects the way in

which the carbon price changes the economics of the investment decision around

coal fired and gas fired baseload plant.

For the No CPRS case investment (Figure 10), the percentage mix of technology

in 2010/11 is the same as for the Base case. This is consistent with the fact that

there is no carbon price in 2010/11 in the Base case. For the No CPRS case, the

percentage mix of technology remains essentially the same for 2011/12 and

2012/12, since there is no carbon price to drive changes in patterns of

investment.

The dispatch results are consistent with the investment outcomes. In the Base

case, CCGT comprises an increasing percentage of dispatch over time. In



comparison, in the No CPRS case, the percentage output levels between the

three technologies remain constant.



Figure 9: Investment outcomes - Base

Figure 10: Investment outcomes - No CPRS



Figure 11: Dispatch outcomes - Base

Figure 12: Dispatch outcomes - No CPRS


Market-based energy purchase costs

5 Market-based energy purchase costs

Electricity retailers buy energy in a wholesale market characterised by volatile

spot prices, but sell energy to customers at prices that tend to be fixed

(particularly for small retail customers). In order to manage the price risk

associated with buying at variable prices and selling at fixed prices, retailers enter

into a range of hedging contracts to provide greater certainty about their

wholesale energy costs. If retailers are not hedged adequately, their margins can

be quickly eroded by a short period of high spot prices. Similarly, if retailers are

over hedged this adds to their costs, unnecessarily reducing their margins.

Market-based energy purchase costs are the costs that retailers face in buying

energy from the wholesale market, including the hedging contracts that retailers

enter into to manage their risk. The estimation of market-based energy purchase

costs can be separated into two broad steps:

forecasting spot and contract prices, and

based on these forecast prices, and the regulated load that the Standard

Retailers supplied, determining an efficient hedging strategy and the cost and

risk associated with that hedging strategy.

This section sets out Frontier Economics‟ approach to estimating market-based

energy purchase costs, and the results of the analysis, including:

the approach to, and results of, the modelling of spot prices

the approach to, and results of, the modelling of the market-based energy

purchase cost, and

the approach to, and results of, the modelling of the volatility allowance.

Note that the volatility allowance included in Frontier Economics‟ framework is

not intended to compensate the Standard Retailers for load (or price volatility) as

this is already incorporate via the assumed load shapes as discussed in Section

3.1. The volatility allowance is intended to compensate the Standard Retailers for

the residual risk on the optimal portfolio of hedging contracts determined in

STRIKE. This residual risk represents the component of portfolio risk that

cannot be eliminated using blocky instruments like quarterly swaps and caps.

This is discussed is greater detail below.

5.1 Spot and contract price forecasts

5.1.1 Frontier’s approach to price forecasts

As discussed in the Modelling methodology and assumptions report, spot prices can be

forecast under a market-based approach using a model of the electricity market.



Models are used to gain an understanding of the strategic incentives that market

participants face within the physical and economic characteristics of the market,

and the implications of these strategic incentives for bidding behaviour and

market outcomes.

More than a decade of experience in electricity markets has shown that bidding

behaviour can change substantially over time in response to regulatory changes,

new investments, new owners, and changing contracting forms and levels. The

result is that historical patterns of bidding behaviour are of limited use for

predicting future patterns of bidding behaviour and future market outcomes.

This is particularly important within the context of the current determination,

with the introduction of the CPRS, the expanded MRET and the NSW

Government‟s Energy Reform Strategy all having the potential to alter bidding

behaviour and market outcomes.

In this context, electricity market models are useful tools for understanding the

impacts of various inter-related developments on outcomes in the market. To

usefully predict future patterns of bidding behaviour and future market

outcomes, models of electricity markets need to reflect the interactions between

the physical and economic characteristics of the electricity market and the

strategic incentives that market participants face.

As discussed in the Modelling methodology and assumptions report, Frontier

Economics uses SPARK to forecast spot electricity prices. Like all electricity

market models, SPARK reflects the dispatch operations and price-setting process

that occurs in the NEM. Unlike other models, however, generator bidding

behaviour is a modelling output from SPARK, rather than an input assumption.

That is, SPARK calculates a set of optimal (i.e. sustainable) generator bids for

every market condition. As the market conditions change, so does the optimal set

of bids. SPARK finds the optimal set using advanced game theoretic techniques.

The revised market price cap of $12,500/MWh, which comes into effect on 1

July 2010, was included in the SPARK modelling.

SPARK, and WHIRLYGIG, use a representative set of demand points to

approximate actual half hourly load, in this case 30 points per year. This is done

to minimise the large number of computations that are required by the game

theoretic framework that the model employs.21

When constructing the representative demand points used in SPARK, Frontier

retains a mapping from the assumed half hourly profile for each NEM region,

which is correlated with the regulated load forecasts submitted by the Standard

21 For each year modelled in SPARK, approximately 5.5 million different supply curves for the market

are modelled. If the same set of possible supply curves was modelled against all 17,520 half hourly

demand level per year then SPARK would need to run approximately 3.26 billion supply curves in

total – this would not be computationally feasible.



Retailers to the representative demand points. Once the SPARK modelling has

produced prices for NSW, these results are used, along with the mapping, to

determine the peak and offpeak prices by quarter. Finally, a half hourly pool price

profile that is correlated to the assumed system demand profile is scaled to match

the quarterly peak and offpeak prices forecast by SPARK. The end result is a half

hourly pool price forecast which:

reflects the forecasted changes to quarterly, peak and offpeak prices as

modelled using SPARK

is properly correlated to forecast half hourly load for both:

o the NSW system, and

o the regulated load forecasts submitted by the Standard Retailers

These pairs of half hourly prices and loads can then be used in STRIKE to

determine optimal contracting positions.

5.1.2 Responses to the Modelling methodology and

assumptions report

In response to the Modelling methodology and assumptions report, a number of

stakeholders commented on the modelling methodology and assumptions used

in Frontier‟s modelling of spot prices. This section provides an overview of, and

response to, these submissions.

Country Energy comments

Country Energy proposed significant changes to the approach to estimating the

energy purchase cost allowance, including making greater use of actual costs

faced by the Standard Retailers. For the portion of expected regulated load that is

known and hedged, Country Energy commented that the energy purchase cost

allowance should be based on the Standard Retailers‟ actual forward costs, rather

than forecasts of these costs. For the portion of expected regulated load that is

not known and hedged, Country Energy commented that the energy purchase

cost allowance should reflect observable, but non-public, data for actual forward

hedge costs over the price period and “expressions of interest from generators”.

Ultimately, Frontier Economics considers that the question of whether to base

the energy purchase cost allowance on the Standard Retailers‟ actual forward

costs is one for IPART. However, Frontier Economics considers that there are a

number of practical and policy implications of the approach proposed by

Country Energy that are worth considering.

First, there are some significant incentive issues:

● Basing the energy purchase cost allowance on retailers‟ actual forward costs is

likely to weaken the incentives of retailers to hedge efficiently. If retailers are



able to pass through their actual costs to regulated customers, then the

incentives that retailers have to contract efficiently so as to minimise cost and

risk is reduced. This will have implications for customers: if regulated tariffs

are based on actual forward costs that are not efficient, then customers will

ultimately face higher regulated tariffs. Country Energy recognises the

implications of their proposed approach on retailers‟ incentives, and propose

that retailers‟ actual forward costs be subject to an efficiency test. The issue

then becomes how to robustly conduct an efficiency test. Given that retailers

will develop their hedging books to serve their entire business – both

regulated and non-regulated – it is not clear that even information on the

retailers‟ actual hedging books would assist IPART without a difficult if not

insoluble contract allocation process. Frontier considers that any efficiency

test will ultimately result in IPART being required to independently form a

view on what constitutes an appropriate hedging strategy, and the cost of that

hedging strategy. This is in fact the approach that IPART takes by seeking to

model the energy costs faced by retailers over the period of the current

determination.

● Relying on generators to provide information to IPART on prices they

“intend” to supply Standard Retailers for the regulated load is also

problematic. If generators know that IPART‟s decision on what to allow

retailers to pass through to customers is based on the prices they put

forward, they will have the incentive to inflate these prices above efficient

levels as the generators have a strong interest in seeing higher prices. As with

relying on retailer information on forward contracts, this would need to be

addressed by independently assessing these proposed energy costs, which is

what IPART is in effect doing through the current modelling process.

Second, relying on the Standard Retailers‟ actual forward costs to determine the

energy purchase cost allowance will create significant practical difficulties. As

discussed, since Standard Retailers hedge to cover their entire book (both

regulated load and market load) using Standard Retailers‟ actual hedge books as a

basis for determining the energy purchase cost allowance would require decisions

about the appropriate allocation of Standard Retailers‟ contracts to different

loads. This is not a simple matter. Relying on Standard Retailers‟ actual costs also

results in a less transparent process, with little prospect of the Standard Retailers

agreeing to the public release of information on their contract position or costs.

Half-hourly spot prices

In regard to the conversion of forecast spot prices into half-hourly spot prices,

some stakeholders raised concerns about the extent to which Frontier

Economics‟ spot price modelling reflects spot prices that occur during the



periods of highest demand.22 In particular, stakeholders were concerned that the

representative demand points adopted in Frontier Economics‟ spot price

modelling will not adequately capture outcomes during high demand trading

intervals.

Frontier Economics recognises that there is an important relationship between

demand and prices and that it is necessary to capture the impact on average

energy prices of infrequent, but highly priced, half hours of peak demand.

Indeed, Frontier Economics has developed its modelling approach to reflect the

impact that the correlation between half-hourly spot prices and half hourly load

has on retailers. While modelling each half-hourly trading interval in SPARK is

too computationally demanding to be practical, Frontier Economics models a

representative demand curve, reflecting a sample of demand points that are

chosen to provide greater focus on the high demand end of the load duration

curve.

Ultimately, to ensure that spot price volatility is adequately captured, the spot

prices for the representative demand points, as modelled in SPARK, are mapped

to a set of half-hourly spot prices in such a way that the volatility in the set of

half-hourly spot prices is reflective of the actual volatility observed historically in

the NEM.

Frontier Economics considers that this combination of focussing on the high

demand end of the load duration curve, and adjusting to reflect historical levels

of volatility, is sufficient to ensure its modelling adequately captures the expected

spot prices that occur during the periods of highest demand.

Contract premium

In regard to the contract premium used to forecast contract prices,23 some

stakeholders commented that the 5 per cent contract premium adopted by

Frontier Economics in forecasting contract prices is insufficient.24

Frontier Economics notes that available market information does not allow a

robust calculation of an implied contract premium. The difficulty is that the

contract premium is the difference between expected spot prices and expected

contract prices. While historic spot prices are publicly available, and there are

publicly available sources of expected contract prices, expected spot prices are

not directly observable. Frontier Economics has adopted a 5 per cent contract

premium based on its experience advising a range of generators and retailers in

the NEM over a number of years.

22 See, for example, EnergyAustralia, Jackgreen, Origin Energy.

23 Discussed in Section 5.3.1 of Frontier‟s Modelling methodology and assumptions report

24 See, for example, EnergyAustralia, Origin Energy.



Frontier Economics uses three sets of forward prices to calculate efficient

hedging strategies using STRIKE:

● forecasts from Frontier‟s modelling;

● forecasts from the Standard Retailers; and

● d-cyphaTrade prices.

The 5 per cent contract premium is used:

● to calculate contract prices based on Frontier‟s modelled spot prices, and

● to calculate implied spot prices based on d-cyphaTrade contract prices.

However, in using the Standard Retailer‟s spot and contract price forecasts, the

contract premium implied by these forecasts is used (rather than applying a 5 per

cent contract premium to the Standard Retailer‟s spot price forecasts).

Use of d-cyphaTrade contract prices

A number of stakeholders have supported the use of publicly available forward

prices rather than modelled price forecasts. For instance, d-cyphaTrade

commented that the prices of actual trades of electricity hedge contracts are a

more accurate and commercially relevant prediction of future prices than

hypothetical cost modelling, and that hedging contracts are traded on d-

cyphaTrade out to 4 years ahead. d-cyphaTrade also commented that the prices

of these hedging contracts are inclusive of any relevant CPRS costs.

As discussed above, different forward prices have been used in STRIKE to

calculate efficient hedging strategies: forecasts from Frontier Economics‟

modelling and d-cyphaTrade prices. These different forecasts can be helpful to

IPART in forming their views as to an appropriate energy purchase cost estimate.

In saying this there are two issues with relying on d-cyphaTrade prices.

● While contracts are currently available for trade on d-cyphaTrade for each of

the years of the current determination, the traded volumes for the later years

of the determination, particularly 2012/13, are very low. Frontier Economics

considers that, with such low volumes traded, the Tribunal should not place a

heavy weight on the d-cyphaTrade prices further out

● While d-cyphaTrade prices are carbon-inclusive, as long as there is

uncertainty about the design of the CPRS or the implementation of the

CPRS, d-cyphaTrade prices will in fact reflect various assumptions about

both the probability of the CPRS being implemented, and the price impact of

the CPRS. For this reason the d-cyphaTrade prices for later years is unlikely

to fully reflect the costs of the CPRS. At this stage, this makes it difficult to

use d-cyphaTrade prices as either an indication of a carbon-inclusive price or

a carbon-exclusive price.



Use of rolling average contract prices

A number of stakeholders commented that the energy purchase cost allowance

should assess costs on the basis of a rolling average of contract prices, using

transparent market data.25 Stakeholders raised a number of concerns with an

approach in which contract prices are marked-to-market, rather than based on a

rolling average of contract prices, including the following:

Some stakeholders commented that an approach in which contract prices are

based on a rolling average of contract prices is consistent with approaches

adopted by the QCA and the ICRC.26

In considering the appropriate approach to estimating the energy purchase

cost allowance, Frontier Economics has been guided by IPART‟s terms of

reference. In particular, Frontier Economics notes that the terms of reference

focus on the promotion of competition. Frontier Economics considers that

an approach in which contract prices are based on a rolling average of

contract prices is inconsistent with the promotion of competition. In

particular, if contract prices are increasing over time, using a rolling average

of contract prices will result in regulated tariffs being based on contract prices

that are below prevailing contract prices. In this circumstance, new entrants

will not be able to compete with the regulated tariff.


marked-to-market fails to recognise that it is standard practice for prudent

retailers to hedge over time.27

Frontier Economics recognises that retailers purchase hedge contracts over

time, and Frontier Economics‟ methodology is not inconsistent with such an

approach.28 By using a mark-to-market framework, Frontier Economics‟

modelling reflects the fact that the value of a contract to a retailer at a point

in time is not determined by its cost when purchased, but by its market value

given the market conditions at that time. Marking to market therefore

provides a better measure of the true value of the electricity required to

supply Standard Retailers‟ regulated load than a rolling average of contract

prices.29

25 See, for example, AGL, EnergyAustralia, Integral Energy, Jackgreen, Origin Energy and TRUenergy.

26 See, for example, EnergyAustralia and TRUenergy.

27 See, for example, AGL, EnergyAustralia, Origin Energy.

28 This is explicitly stated in the Modelling methodology and assumptions report.

29 To expect that the economic decisions of retailers would reflect the actual cost they incurred in

constructing their hedging book is akin to suggesting that the economic decisions of generators

would reflect the actual cost they incurred in acquiring carbon permits. In the latter case, this implies

that generators that receive a free allocation of carbon permits will not reflect the market value of




marked-to-market is inappropriate because it is unrealistic to think that

retailers are able to sell their hedge contracts (since they have an obligation to

supply) or that retailers are able to sell out of their entire hedge book without

affecting the price of electricity on that day.30

The logic that economic decisions should be based on the market value of

goods and services (as determined by marking-to-market those goods and

services) does not depend on the actual sale of goods and services. In

markets in which incremental customers are contestable, competitive

retailers‟ decisions about supplying an incremental customer will be

determined by the market value of the inputs required to supply that

incremental customer.


marked-to-market is inconsistent with the terms of reference, which require

consideration of the efficient costs of a Standard Retailer. Since Standard

Retailers have an obligation to supply it is suggested that an approach in

which contract prices are marked-to-market does not make sense.31

Certainly, Standard Retailers have an obligation to supply small retail

customers. However, the Standard Retailers‟ obligation to supply does not

change the point outlined above that the efficient cost of doing so is

determined by market conditions, and not the costs (whether averaged over

time or not) incurred by retailers in purchasing contracts.


marked-to-market can result in tariffs that do not reflect actual costs, or that

adopting a rolling hedge strategy will smooth year on year profitability.32

It is certainly the case that marking-to-market contract prices can result in

regulated tariffs that do not reflect actual costs. However, Frontier

Economics‟ view is that the regulatory framework allows for efficient, not

actual, costs to be recovered. To the extent retailers outperform the allowed

efficient costs, they can improve their profitability, and vice versa. These

incentives are fundamental to the regulatory regime, and are supported by

our modelling approach.

EnergyAustralia commented that if a prudent retailer carries out-of-the

money hedge contracts in its portfolio, it cannot expect to recover these costs

carbon permits in their bids, so that a free allocation of carbon permits will result in a lower spot

price.

30 See, for example, AGL and Origin Energy.

31 See, for example, AGL and Origin Energy.

32 See, for example, EnergyAustralia, Origin Energy and TRUenergy.



from the market. Yet, if it is industry practice for prudent retailers to hedge

over time, hedging across the industry should be generally consistent and

consequently passed through to consumers at the levels at which they

contracted.

Frontier Economics considers that, even if all incumbent retailers have

purchased inputs at prices higher than prevailing levels, this does not imply

that prices in competitive markets would reflect these higher prices. New

entry, and the threat of new entry, will constrain prices to efficient levels in

competitive markets and it is these efficient prices that are relevant when

determining energy costs.

5.1.3 Responses to the draft report

In response to the Energy purchase costs draft report, a number of stakeholders

commented on the modelling methodology and assumptions used in Frontier‟s

modelling of spot prices. This section provides an overview of, and response to,

these submissions.

Price forecasts for 2010/11

A number of retailers commented that the market-based energy purchase cost for

2010/11 resulting from Frontier Economics‟ SPARK modelling is too low. These

comments are addressed in further detail in Section 5.5, which investigates the

sensitivity of the modelling results for 2010/11 to demand forecasts.

Use of rolling average contract prices

A number of stakeholders made submissions expressing a preference for rolling

average contract prices to be used as the basis for the determination. Frontier

Economics has not changed its position on this issue since the comments made

in the draft report and repeated in Section 5.1.2.

Use of modelled spot prices

AGL commented that the market-based energy purchase cost allowance is too

low, in part due to the assumption that Frontier Economics‟ modelled prices are

to be preferred to observable market prices.

Frontier Economics considers that there are reasons that both modelled prices

and observed market prices are useful.

Modelled prices are useful for at least three reasons. First, where observed

market prices are not based on liquid trade (as is currently the case for d-

cyphaTrade contracts in the last two years of the determination period) it is

difficult to rely on market prices and modelled prices offer an alternative source

of information. Second, where there is uncertainty as to a change in the physical,

commercial or policy environment affecting power markets, market prices will



reflect this uncertainty. It appears that this is currently the case for d-cyphaTrade

prices for 2011/12 and beyond, which appear to reflect uncertainty over the

CPRS. Modelled prices assist in these circumstances because modelled prices can

provide information unaffected by this uncertainty: for instance, modelling can

provide an indication of the operation of energy markets with and without the

CPRS. This can also assist in assessing the impact of a change in regulation

during the period of a determination. Third, modelled prices provide an

opportunity to understand the impacts on energy markets of changes to the

physical, commercial or policy environment. This can be important to the

process of setting regulatory prices.

Observed market prices are also useful for a number of reasons. First, using

observed market prices provides greater transparency to the regulatory process,

because the prices do not depend on input assumptions or modelling

frameworks. Second, observed market prices reflect the expectations of a wide

range of market participants, each taking into account the information available

to them.

For these reasons, Frontier Economics considers that, for the current

determination, there is value in considering both modelled prices and observed

market prices. Indeed, Frontier Economics has calculated the market-based

energy purchase cost allowance using both modelled prices and observed market

prices and included these results in both the draft report and this final report.

Contract premium

AGL commented that the 5 per cent contract premium (compared to spot

prices) adopted by Frontier Economics misconstrues the nature of the contract

market, because the premium inherent in contract prices is a premium above the

expected spot outcome.

Frontier Economics‟ spot price modelling is specifically intended to provide a

view on the expected spot outcome. The 5 per cent contract premium that is

adopted by Frontier Economics is a premium to this expected spot outcome. As

a result, the contract premium is forward looking, as AGL suggest it should be.

Country Energy’s comments

Country Energy again suggested that IPART should have regard to retailers‟

actual purchase costs. In contrast to their submission on the Modelling methodology

and assumptions report, in their submission to the draft report Country Energy

proposed that retailers‟ actual purchase costs could be used as a basis for

benchmarking the energy purchase cost allowance.

Frontier Economics considers that using retailers‟ actual purchase costs to

benchmark the energy purchase cost allowance does not avoid the practical

difficulties associated with determining an efficient energy purchase cost



allowance based on information on a retailers‟ contract book (the principal of

these difficulties is allocating contracts that the retailers have entered to cover

their total load to the regulated proportion of that load).

5.1.4 Effect of revised assumptions on market based results

As discussed previously, the updated WACC and cost amortisation calculation

has altered the fixed costs associated with new generating technologies. This has

necessitated an update of Frontier Economics LRMC modelling, both for the

Standard Retailers‟ regulated load and for the LRMC of meeting the expanded

RET (discussed in Section 7). This is required as the results for these approaches

depend explicitly on the input fixed costs. However, this is not the case for the

market based results.

The market based approach involves first forecasting the pattern of new

investment using WHIRLYGIG and then dispatching the market using SPARK

to determining pricing outcomes for the NEM in the presence of strategic

bidding. The results of the first stage depend of the input fixed costs insofar as

they determine the pattern of new investment. In SPARK the investment path is

based on the WHIRLYGIG outcomes and different patterns of investment can

result in different modelling outcomes.

Frontier Economics has forecast the likely investment path for the NEM using

WHIRLYGIG based on the updated input assumptions. Over the period of the

determination there is no change in the pattern of investment in the NEM

relative to the modelling for the draft report. As a result, no change is required to

the investment path used in SPARK and the market based price estimates have

not changed as a result of the updated input costs.

The only change to the market based results is to the volatility allowance, because

the WACC is an input into the calculation of the volatility allowance. Except for

the volatility allowance, the results presented here for the market based approach

are therefore unchanged relative to the draft report.

5.1.5 Price forecast results

This section presents the results of SPARK modelling.

The price forecast results for the NSW region from SPARK are presented in

Figure 13. Consistent with the LRMC results presented in this report, price

forecast results are presented for two cases – Base and No CPRS. Key

assumptions for each case are as follows.

Base

o ACIL 2009 report cost with Frontier Economics/SFG amortisation

of fixed costs

o AEMO 2009 ESOO High energy, 50% POE demand assumptions



o CPRS5 modelled as a carbon price as per the Modelling methodology and

assumptions report

No CPRS

o As per Base, but with an assumed carbon price of zero

D-cyphaTrade forward prices for flat annual swaps as of the 9th of October 2009

are also included in Figure 13 for the purpose of comparison. The d-cyphaTrade

prices provide an indication of the market view on future contract prices (and by

association pool prices). For 2010/11, liquidity of d-cyphaTrade traded contracts

is higher than in the later years of the determination. This is partly due to the

natural reduction in contract liquidity over time, but is exacerbated by uncertainty

in the market around the CPRS. As a result, the d-cyphaTrade price becomes

increasingly unreliable in the later years.

As seen in Figure 13, the NSW annual average price modelled by Frontier

Economics in 2010/11 is roughly $33/MWh. This is relatively low when

compared to historic price levels and the corresponding d-cyphaTrade price. This

is a result of the system demand forecast for 2010/11 from the AEMO 2009

ESOO. As discussed, this reflects a low demand forecast, including as a result of

assumptions about the impact of global financial crisis. The fact that the d-

cyphaTrade price is higher than the price modelled by Frontier Economics

suggests that the market‟s view on demand and price levels is higher than the

values embodied in the AEMO 2009 ESOO forecast.

As seen in Figure 13, the NSW annual average price modelled by Frontier

Economics for the Base and No CPRS cases diverge in 2011/12 with the

introduction of the CPRS. Prices rise in both cases (including the No CPRS case)

due to the tightening of the supply demand balance. In the Base case an

additional increase occurs over and above the No CPRS case due solely to the

impact of the assumed carbon price. In 2012/13 prices in the No CPRS case rise

slightly due to the growth in demand whereas the Base case prices increase

significantly due to the additional carbon effect.

Levels of carbon pass-through for the market cases (and LRMC) are discussed in

more detail in Section 6.



Figure 13: NSW annual average price forecast compared to d-cyphaTrade forward

prices (real 2009/10)

The prices presented in Figure 13 are average annual prices. SPARK produces

equilibrium prices for multiple levels of demand across the year. It is also

possible to construct a distribution of the average annual prices by randomly

sampling from the set of equilibrium prices for a given modelling year. These

distributions reflect random sampling across the set of equilibrium bids, and

resultant prices, as determined by SPARK. The distributions do not reflect

changes in other input assumptions. Other input assumptions, such as forecast

energy, forecast peak demand, the system load shape, generator fuel costs and the

assumed carbon price, are all held constant when the distributions are generated.

These distributions are shown in Figure 14 for the Base case. The distributions

appear normal, however no assumption of normality has been made.33

The expected levels of the distributions (the horizontal axis intersection of the

distribution peak) correspond to the average annual prices presented in Figure

13. The widths of the distributions give an indication of the volatility associated

with the expected annual average price. In 2010/11 the distribution is relatively

33 The distributions are of average annual price, not half hourly prices. Even though the distribution of

half hourly prices is right-skewed the distribution of the average annual price is normal. This is

consistent with the Central Limit Theorem.



tight reflecting relatively low incidence of high prices arising from the loose

supply demand balance. In 2011/12 the distribution widens in line with higher

levels of volatility.

In 2012/13 the distribution tightens again. This is due to the increased carbon

price in spite of the higher average level of prices. This result arises from the

effect that a known carbon price has on the volatility of pool prices, as discussed

below.

Figure 14: Distribution of forecast NSW annual average prices, Base case (real

2009/10)

As discussed, the forecast market prices modelled using SPARK result in

relatively low price forecasts for 2010/11. This is a direct consequence of the

assumed demand for this year. Prices then rise significantly over the remaining

years due to two main factors – the tightening supply demand balance and the

additional costs imposed by carbon. Both of these effects can be seen in the

supply demand curves for NSW output from SPARK.



The supply demand curves for NSW are shown for the three years of the current

determination in Figure 15 to Figure 17. Each figure shows the assumed

maximum, average and minimum demand levels for NSW. Also depicted are the

maximum and minimum strategy supply curves for NSW, as input into SPARK.

The maximum strategy supply curve corresponds to all strategic generators

offering the maximum amount of capacity into the market that is available under

their assumed menu of bidding strategies;34 this capacity is offered at SRMC.

Similarly, the minimum strategy supply curve corresponds to strategic generators

bidding the minimum amount of capacity into the market that is available under

their assumed menu of bidding strategies. For illustrative purposes, the full NSW

import capacity of the Victoria-NSW, QNI and DirectLink interconnectors has

been included (at a cost of $5/MWh to reflect interregional losses). The

availability of this capacity depends on dispatch outcomes in other NEM regions

and transmission constraints.

Initially, in 2010/11, there is significant spare capacity. This is characterised by

the fact that even if all strategic generators in NSW offer a minimum amount of

capacity into the market, the NSW price will not rise above $100/MWh as long

as the interconnectors are fully available. For substantial proportion of the year

the NSW market price will be around the $25/MWh level.

In 2011/12 two major changes occur. Firstly, a carbon price of approximately

$10/tCO2e is imposed on the market. This has the effect of raising the supply

curve in line with the marginal emissions intensity of individual generators.

Secondly, demand grows in terms of peak, average and minimum demand. Both

these effects are illustrated in Figure 16. In this year it is now possible for the

NSW price to rise significantly above $100/MWh due to strategic withdrawal of

capacity by the NSW generators. This can occur even if the interconnectors are

fully available.

In 2012/13 these trends continue. The supply curve rises further in line with the

assumed carbon price of approximately $26/tCO2e (based on modelling carbon

price estimates from Commonwealth Treasury). Also, the supply demand balance

tightens even further, increasingly the likelihood of high prices, due to demand

growth.

34 The Modelling methodology and assumptions report details the menu of bidding strategies for all strategic

generators.



Figure 15: NSW supply demand balance including import capacity for 2010/11 (real

2009/10)




2009/10)




2009/10)

The impact of carbon on generator output

Previous results demonstrated that part of the cause of the increase in pool prices

over the period of the determination is due to the introduction of the CPRS and

the associated price on carbon. Fundamentally, putting a price on carbon

increasing pool prices as it increases the bid prices that generators offer electricity

into the pool, this also changes how the stock of generation plant is dispatch over

time.

Figure 18 and Figure 19 show the mix of NEM wide dispatch for the Base and

No CPRS cases respectively. Dispatch is broken down into five categories: green

(mostly Snowy Hydro and Hydro Tasmania), Black Coal, Brown Coal, Gas

(CCGT and Cogeneration plant) and Liquid (peaking plant). In the Base case it is

clear that the carbon price in 2011/12 and 2012/13 results in a greater



proportion of demand being met by, lower emission, gas fired generation. This is

at the expense of brown and black coal generation. In the No CPRS case, the

proportion of gas increases slightly due to tightening supply demand but not

nearly as much as in the Base case.

In the Base case the proportion of gas output rises from approximately 8% in

2010/11 to approximately 12% in 2012/13. The equivalent outcome in the

LRMC case (Figure 11) was an increase from approximately 15% to 30%. In the

market based approach, where investment does not respond to the carbon price

over the period of the determination, only the dispatch of existing plant changes

in response to carbon. In the LRMC approach, where the optimal system is built

'fresh' every year, a larger proportion of gas fired plant is built and dispatched as

part of the optimal mix resulting in the observed changes in dispatch.

Figure 18: NEM dispatch outcomes - Base case



Figure 19: NEM dispatch outcomes - No CPRS case

The effect of carbon pricing on pool price volatility

The imposition of a carbon price on a wholesale electricity market will clearly

impact both the level and volatility of pool prices. In the case of the price level it

is unambiguous that the effect will be an increase. This is because the carbon

price either increases the marginal cost of electricity generators (in the case of

thermal plant) or leaves the cost unchanged (in the case of renewable plant).

Given that thermal plant will be marginal for at least some proportion of time,

and given that these thermal plant bid to recover the increase in their costs

associated with carbon emissions, prices will rise as the results of a carbon price.

When it comes to price volatility, the direction of the effect is ambiguous. The

impact of the carbon price on electricity price volatility can be broken up into

two categories:

the impact of an uncertain carbon price on the supply curve of the market,

and

the impact of a certain carbon price on the supply curve of the market and

how this then influences pool prices

The first effect arises from the fact that carbon permits will be traded. As such,

the cost of carbon will be a time varying and volatile parameter within the SRMC

of any given thermal plant. This will result in the supply curve for the market for

a given year being „fuzzy‟: as a proportion of the SRMC of each generator, the



carbon cost will be uncertain. To the extent that the carbon price is volatile this

may lead to an increase in the volatility of pool prices.

For example, if a given plant is the marginal plant in NSW for 10 per cent of the

year then, in a world without a cost of carbon, prices would be relatively constant

when this plant is marginal. In contrast, with a volatile carbon price across the

year, the prices for the 10 per cent of the time that that plant is marginal would

presumably vary in line with variations in the carbon price. This can act to

increase pool price volatility. This effect could be greater if the variations in the

carbon price lead to a re-ordering of the merit order of supply.

This first effect is impossible to capture with any degree of accuracy at this stage.

The reason is that there is no way that the volatility of carbon prices, and the

correlation between carbon prices and electricity demand, can be robustly

estimated at this stage. For this reason, Frontier Economics has investigated this

effect through the modelling of a range of carbon price sensitivities around the

results.

The second impact of carbon pricing on pool price volatility is the effect that a

given carbon price has on the supply curve of the market and therefore the

volatility of pool prices. There is an argument to be made that for some merit

orders and some carbon prices, this effect can act to reduce the volatility of pool

prices. This arises because of the way in which carbon changes the differentials in

marginal cost between different generating technologies.

For example, Figure 20 shows an idealised supply curve. The curve includes three

generating technologies – Coal, CCGT and OCGT – and breaks the marginal

cost of these technologies into a fuel plus variable operation and maintenance

components and a carbon cost component. For a given carbon price, in this case

$26/tCO2e, the marginal cost differential between coal and CCGT reduces.

This implies that, in a world with carbon being priced, when the pool price

transitions from a marginal coal price to a marginal CCGT price due to a change

in demand the change in the resultant pool price is less than would be the case if

there was no carbon price. That is, the pool price moves less with carbon. As a

result, volatility (but certainly not price level) is reduced by the presence of a

carbon price.

Whilst it is true that the opposite effect is observed between the marginal cost

differential between CCGT and OCGT, the overall effect on annual volatility

comes down to how often prices transition between Coal and CCGT and CCGT

and OCGT.

This reduction in spot price volatility from a carbon price can be seen in the

forecast of pool prices produced by Frontier Economics as evidenced by the

tighter distribution for 2012/13 in Figure 14. Importantly, this outcome depends

on the merit order and the carbon price. Given both of these are likely to change

as the CPRS takes effect from 2012/13 onwards, it is unclear at this stage



whether other forces will cause spot price volatility to increase rather than

decline. For example, the strategic bidding incentives created by the cap and

trade system could significantly increase price volatility as the carbon price rises.

Figure 20: Effect of carbon on an idealised supply curve

5.2 Market-based energy purchase costs

5.2.1 Frontier’s approach to estimating market-based energy

purchase costs

Electricity retailers buy energy in a wholesale market characterised by volatile

spot prices, but sell energy to customers at prices that tend to be fixed

(particularly for small retail customers on regulated tariffs). In this environment,

retailers‟ margins can be quickly eroded by a short period of high spot prices, if

retailers are not adequately hedged. In order to manage the price risk associated

with buying at variable prices and selling at fixed prices, retailers enter into a

range of hedging contracts. In order to calculate the market-based energy

purchase costs, it is important to take into account the contracts that retailers

purchase to hedge their price risk, and the cost of these contracts.



As discussed in the Modelling methodology and assumptions report, Frontier

Economics uses STRIKE to determine the efficient mix of hedging products that

retailers would enter into over the period of the determination, and the energy

costs and risks associated with each of these efficient mixes.

Ultimately, retailers hedge to reduce the volatility of the energy purchase cost of

their customers. This volatility arises from:

load volatility;

price volatility; and

the correlation of load and price.

Load volatility, as discussed in Section 3.1, is accounted for in Frontier

Economics‟ modelling by using, for each Standard Retailer, three forecast load

shapes, which represent a realistic range of load volatility outcomes.

Appropriately accounting for price volatility – and the correlation between load

and price – requires that, for each forecast load shape for each Standard Retailer,

the regulated load is properly correlated to the NSW system load. Given that

NSW market prices reflect NSW system load, ensuring an appropriate correlation

between the forecast load shape for each Standard Retailer and the NSW system

load also ensures an appropriate correlation between the forecast load shape for

each Standard Retailer and NSW market prices.

This concept is illustrated in Figure 21, using hypothetical time series data for the

regulated loads of each of the Standard Retailers, the NSW system load and the

NSW market price. The circled area shows how the peaks in each of the

regulated loads are co-incidental to (correlated with) the peak in NSW system

load. The NSW system load then drives the NSW market price. Frontier

Economics has ensured that each regulated load shape provided by the Standard

Retailers has been appropriately correlated to the NSW system load shape and,

through the SPARK price forecasts, to NSW market prices.



Figure 21: Correlation between the Standard Retailers' regulated loads, system load

and system price (illustrative only)

For a given Standard Retailer and for each regulated load forecast shape there is

an associated system load shape and resultant system price shape that is

appropriately correlated to the regulated load. For a given Standard Retailer, the

outcomes across the three price-load shape pairs, and the correlation between

them, account for all the variation in the energy purchase cost that the Standard

Retailers face for the regulated load in NSW.

Using these inputs STRIKE sees a distribution of likely pool purchase cost for a

given year. An example is shown diagrammatically in Figure 22 (which is not

based on any actual data). If the entire load is priced at the pool price (no

contracts are entered into) then the distribution of purchase costs will be very

wide representing a high level of volatility associated with the expected purchase

cost. Adding contracts to the portfolio:

increases expected purchase cost (to the extent that contracts sell at a

premium), and

changes the volatility (risk) associated with the expected purchase cost

In Figure 22 we see these effects in the series with contracts. The expected

purchase cost is higher and its distribution is narrower. The trade off between



reduced cost and reduced risk is exactly what STRIKE quantifies when it

constructs the efficient frontier of contracting options.

Figure 22: Distribution of purchase cost – with and without contracts (illustrative only)

Each point on the efficient frontiers calculated by STRIKE represents an optimal

bundle of contracts for a given risk profile. At the high risk end of the efficient

frontier, very little weight is placed on risk in the portfolio and STRIKE tries to

find the set of contracts that minimise the expected purchase cost regardless of

how risky this is (indicated by how wide the distribution of purchase costs gets).

In the extreme this may involve the entire load being purchased at spot prices.

Conversely, at the conservative end of the efficient frontier, a high weight is put

on risk. In this case, STRIKE seeks to minimise risk with little regard to cost,

which is equivalent to finding a set of contracts that minimises the spread in the

distribution of expected purchase costs notwithstanding that this will increase

expected purchase costs. It is the cost associated with this conservative position

that is was used in the 2007 determination.

Likelihood of price cap events

The inputs used to construct a likely distribution of purchase costs in STRIKE

will not necessarily include the possibility of a price cap event for every discrete



contracting period. That is, it may be the case that forecast prices for a given

quarter and peak/offpeak period do not reach (or approach) the market price

cap. This is particularly the case for offpeak periods. Whilst this outcome reflects

the reality that price cap events are unlikely to occur during offpeak times,

retailers need to contract in recognition of the fact that high price outcomes are a

possibility at all times. In order to replicate this in STRIKE, additional data is

input into the model. Specifically, eight additional 'half hours' are included for

each retailer, each year - one for each quarter, peak and offpeak. For these half

hours the NSW price is assumed to be $12,500/MWh (the market price cap) and

the regulated load for each retailer is assumed to be the maximum load for that

quarter, peak/offpeak as submitted by the Standard Retailers. These additional

half hours are given a relatively lower weighting than the actual data that is input

into STRIKE. This results in the cost impact of this additional data being

minimised however the resultant optimal contracting position at the conservative

end of the efficient frontier reflects the possibility of high priced events occurring

for every period over which discrete contracting decisions are made.

Blocky contracting options and residual risk

Even at the conservative end of the efficient frontier, there is still some residual

risk in the portfolio. This arises because the contracts available in STRIKE –

quarterly, peak and offpeak swaps and caps – do not allow a riskless portfolio to

be constructed: difference payments on swaps and caps can never perfectly

mirror the pool costs of a time varying load shape priced at a time varying price.

This residual error is compensated for via a volatility allowance which is

discussed in Section 5.3.35

Frontier considers that the fixed menu of contracts in STRIKE – quarterly, peak

and offpeak swaps and caps – is a broad enough collection of products for the

purposes of this analysis. These products trade in the market and forward prices

for them are available publically. By entering into combinations of these products

across quarters, longer term products can be created by proxy. Similarly, flat

products can be created by combining contracts across peak and offpeak periods.

Frontier did not include more sculpted or otherwise exotic contracts in the menu

of options as such products are usually very specific to the overall load shape

being hedged or the strategic optionality that the seller and buyer are willing to

agree on. These reasons preclude the creation of an objective set of exotic

contracts that would be available to, and systematically priced for, each of the

Standard Retailers. Because STRIKE calculates optimal hedging strategies, the

inclusion of exotic contracts in the analysis would, if anything, result in a lower

cost and/or lower risk hedging strategies.

35 Note this differs from the „load volatility premium‟ discussed in Section 3.1 as a means (which

Frontier does not use) of accounting for the cost of load volatility.



5.2.2 Responses to the Modelling methodology and

assumptions report

A number of stakeholders commented on the modelling methodology and

assumptions related to contracting documented in the Modelling methodology and

assumptions report. This section provides an overview of, and response to, these

submissions.

Hedging position

Some stakeholders commented that they consider the hedging positions that

occur on the efficient frontier determined by STRIKE cannot be achieved in

practice. In particular, some stakeholders consider that the variation in the

contract position from quarter to quarter cannot be achieved in practice.36

Frontier notes that the variation from quarter to quarter in the hedging positions

associated with the efficient frontier do not imply that the Standard Retailers will

be required to buy and/or sell a large quantity of hedge contracts at the

beginning of each quarter, as some commentators suggested. Rather, Frontier

expects that Standard Retailers would purchase contracts over time leading up to

each quarter, and do so to reflect different expectations of spot prices and load.

The real issue in a hedging position that varies from quarter to quarter is whether

contracts are available on a quarterly basis. If the majority of contracts in the

market are available only on a flat annual basis (or even on a flat basis over a

longer period), and quarterly contracts are only available in small quantities, then

it may be difficult to construct a hedging position with significant variation from

quarter to quarter even by purchasing contracts over time.

However, Frontier Economics considers that the available evidence does not

support the view that there are insufficient contracts available on a quarterly basis

to allow retailers to construct a hedging position that varies significantly from

quarter to quarter. Furthermore, given that variations in contract position for the

Standard Retailers‟ regulated load from quarter to quarter are not substantial, and

particularly when these hedges will form part of a much larger portfolio of

hedges (recognising that Standard Retailers‟ regulated load accounts for around

20 per cent of total energy demand in NSW) the variation of hedge quantity will

be very small. Therefore Frontier Economics considers that this variation in

hedge quantities can be accommodated by retailers in practice.

Liquidity of contract markets

EnergyAustralia commented that there are issues associated with the liquidity of

contract markets. EnergyAustralia commented that generators generally only

36 See, for example, EnergyAustralia and Origin Energy.



contract 75 per cent of their nominal capacity, in order to avoid exposure to

unfunded difference payments in the event that they have an outage.

EnergyAustralia commented that this leaves the market short of contracts

ultimately meaning that contract volumes to cover the Standard Retailers‟

regulated load cannot be sourced without moving the market price.

Frontier Economics notes that the NSW market has more generation capacity

than is required to meet forecast load, and that AEMO‟s ESOO does not

forecast a requirement for additional generation capacity in NSW until 2015/16.

This suggests that, while NSW is approaching supply-demand balance, there

remains more than sufficient generation capacity to meet forecast load.

However, as EnergyAustralia note, contract liquidity is driven both by total

generation capacity, and generators‟ preparedness to sign contracts backing that

generation capacity. It is important that assumptions about generators‟

preparedness to sign contracts (which will have an impact on spot price forecasts

and contract price forecasts) are consistent with assumptions about the ability of

retailers to hedge their load with contracts.

Frontier Economics‟ assumptions around generator contract levels in the NEM

are consistent with EnergyAustralia's comment of generators only being willing

to hedge 75% of capacity. They are also consistent with the fact that generators

carry a time varying volume of contracts. Typically generators reduce their

contracted volume at offpeak times - when dispatch is less certain - and around

planned maintenance events.

Frontier Economics has forecast pool prices under the assumption that all

generators in the NEM are hedged according to a proportion of efficient output.

Efficient output is calculated by using SPARK to determine the dispatch of the

system under the assumption that all capacity is bid into the market at SRMC.

Setting the assumed contract levels as a proportion of efficient output acts as a

proxy for the observed time variance of generator contract levels. The

proportions chosen were 60% of efficient output as swap cover and 20% as $300

cap cover for an aggregate level of 80%. While the aggregate level of cover is

slightly above EnergyAustralia's 75%, the contract volume is sculpted and

comprises one quarter caps which have a different effect on generator bidding

incentives compared to swaps.

5.2.3 Market-based energy purchase cost results

This section presents the results of the STRIKE modelling. Results are presented

as follows:

efficient frontiers for 2010/11 through 2012/13 for each business, and

market-based energy purchase costs for 2010/11 through 2012/13 for each

business



In response to a data request from IPART, the Standard Retailers have provided

views on NSW spot prices and contract prices over the period from 2010/11 to

2012/13. However, the spot prices and contract prices were not provided on a

common basis across the retailers and, in some cases, a complete set of spot

prices and contracts was not available. For these reasons, the price forecasts

provided by the Standard Retailers do not provide a useful comparator for the

forward prices modelled by Frontier Economics and available from d-

cyphaTrade. As a result, market-based energy purchase costs have not been

calculated using the Standard Retailers‟ forecasts of pool and contract prices (but

have been calculated using d-cyphaTrade prices, as set out in Appendix B).

Efficient frontiers

For the financial years 2010/11, 2011/12 and 2012/13 and for each business, the

efficient frontier of contracting options has been calculated. This frontier is a

representation of the expected purchase cost and the associated risk (as measured

by standard deviation) of a set of contracts that minimise risk whilst maximising

return (minimising purchase cost). Each point on the efficient frontier is

associated with a specific quantity of contracts.

For the purposes of Frontier Economics‟ modelling, the available contracts are to

buy and sell quarterly, peak and offpeak, swaps and caps. These contracts have

been priced at a 5 per cent contract premium to the forecast spot prices. That is,

if the Q4 peak average price was forecast to be $100/MWh, then swaps would be

available to buy at $105/MWh and available to sell at $95.24/MWh. Similarly,

cap premiums were set such that any transaction involved a 5 per cent premium.

Figure 23 to Figure 25 below show the efficient frontiers for each year, for each

business, for the Base case. The vertical axes of these figures represent the

expected annual average energy costs for the efficient (lowest cost) mix of energy

purchasing options at a given level of risk (in $/MWh). The horizontal axes of

these figures represent risk as the standard deviation for each level of efficient

costs (in $/MWh). These cost efficiency frontiers slope downwards to the right,

indicating that the least risky position is also associated with the highest energy

cost. This result is intuitively obvious – that is, more price insurance costs more

money.

On each frontier an elbow point has been defined. The elbow point denotes the

point on the frontier where the rate of change in the slope of the frontier is

maximised (i.e. second order derivative of the frontier). This elbow point

indicates the position on the frontier where costs are lowest for a given increase

in risk. The less risky position (i.e. most conservative) is indicated by the most

left point of the efficient frontier.

Each frontier has been truncated at the point the standard deviation exceeds

$10/MWh to permit a closer view of the detail around the area of interest. The



figures have been presented on a common set of axes to aid comparison. All

figures are real 2009/10 dollars.

In 2010/11 the energy purchase costs are in the order of $40/MWh to

$45/MWh. This is consistent with a pool price in the order of $33/MWh, a 5 per

cent contract premium and the effect of the load shape of each business on

purchasing cost. The same ranking between the businesses as seen in the LRMC

results – Integral Energy most expensive, followed EnergyAustralia and then

Country Energy as the cheapest – is maintained. This reflects the relative load

shape of the three businesses, as discussed in Section 3.

Costs rise over the period of the determination in line with forecast increases in

pool prices. Risk also increases (frontiers shift to the right) in 2011/12 for all

three businesses in line with the volatility of pool prices. In 2012/13 risk remains

fairly constant for Country Energy and Integral Energy. For these two

businesses, the reduction in pool price volatility is offset almost exactly by a

worsening regulated load shape over time. For EnergyAustralia, the regulated

load shape improves over the period of the current determination. As such, the

risk for EnergyAustralia in 2012/13 reduces due to the combined effect of

reduced load volatility and reduced price volatility.

Figure 23: Efficient frontiers – 2010/11 (real 2009/10)







The market-based energy purchase cost associated with the most conservative

position on the frontier was used for the purposes of the 2007 determination.

Even at the conservative point there is still some residual risk associated with the

portfolio, which arises from the imperfection of swaps and caps that vary by

quarter, peak and offpeak, as instruments to offset variations in the cost of

forecast load priced at the pool price, which varies on the half hour. In order to

compensate retailers for the carrying cost of capital needed to cover against this

residual risk, a volatility allowance is included. This is discussed in Section 5.3.


Market-based energy purchase costs associated with the conservative point on

the efficient frontier are presented for two cases – Base and No CPRS. As set out

above, pertinent assumptions for each case are as follows.

Base

o ACIL 2009 report cost with Frontier Economics/SFG amortisation

of fixed costs

o AEMO 2009 ESOO High energy, 50% POE demand assumptions

o CPRS5 modelled as a carbon price as per Frontier‟s Modelling

methodology and assumptions report

No CPRS

o As per Base, but with an assumed carbon price of zero

For a given case, year and business, STRIKE has been used to optimise over

three load-price shapes that capture the volatility of prices and load, and the

correlation between the two. That is, STRIKE has found an optimal contracting

position taking into account the possibility of three alternate versions of the

future.

The market-based energy purchase costs presented are comprised solely of the

pool purchase cost of the Standard Retailers‟ regulated load and the premiums

and difference payments made on the optimal set of contracts as determined by

STRIKE. These are summarised in Figure 26. The numbers presented

correspond to the conservative point on the efficient frontier for each business.

The market-based energy purchase costs are on the order of $40/MWh to

$48/MWh for 2010/11, reflecting low pool price forecasts for that year. Without

carbon, the costs rise to roughly $60/MWh for the final two years. With carbon,

the cost increases rise in 2011/12 with the introduction of the capped CPRS and

rise further in 2012/13 when the $10 cap is removed. In the final year the

purchase cost is around $100/MWh.



There is roughly a $35/MWh difference between the Base and No CPRS

purchase costs in 2012/13 due to higher pool prices. NSW pool prices are almost

$30/MWh higher in the Base case relative to the No CPRS case. This increase is

amplified when the energy purchase cost is calculated due to the assumed 5%

premium in contract prices and when each Standard Retailer‟s load shape is

accounted for (relatively more energy is purchased at relatively higher price

times). The impact of carbon costs is discussed in more detail in Section 6.

Figure 26: Market-based energy purchase costs (real 2009/10)

5.3 Volatility allowance

5.3.1 Frontier’s approach to the volatility allowance

As discussed, the efficient frontiers still leave an element of risk in the portfolio.

Consistent with the approach from the 2007 determination, Frontier considers

that it is appropriate to compensate the retailers for this residual risk through a

volatility allowance. This volatility allowance is distinct from any form of load or

price volatility premium (as discussed in Section 3.1), which has already been

accounted for in the assumed load-price shapes input into STRIKE.



The efficient purchasing frontiers presented above relate to the efficient prices

that Frontier expects each retailer to have to pay over the period of the current

determination. More specifically, for any given energy purchase strategy

represented on the efficient frontiers, we would expect that roughly 50 per cent

of the time the actual market-based energy purchase cost would be above the

market-based energy purchase cost implied by that strategy, and 50 per cent of

the time the actual market-based energy purchase cost would be below the

market-based energy purchase cost implied by that strategy.

At times when the actual market-based energy purchase cost is above the

expected market-based energy purchase cost, retailers will be earning a net

margin below the allowed margin (all other things being equal). At times when

the actual market-based energy purchase cost is below the expected market-based

energy purchase cost, retailers will be earning a net margin above the allowed

margin (all other things being equal). Ideally, retailers would use margin windfalls

to offset shortfalls. However, there is a risk that shortfalls may occur prior to

earning any windfalls. One way of managing this risk is to hold working capital to

fund these cashflow shortfalls. To ensure that retailers are able to fund any

additional working capital requirements, Frontier Economics has estimated the

maximum amount of working capital that each retailer is expected to require in

each year over the determination period to manage the risk of cashflow

shortfalls.

This working capital requirement is based on the standard deviation associated

with the conservative point of each retailer‟s frontier. More specifically, Frontier

Economics has estimated the difference between the expected market-based

energy purchase cost and the expected purchase cost plus 3.5 standard deviations

from the expected value.37 We then estimate the cost of holding sufficient

working capital, applying an updated WACC of 8.0%, to fund a shortfall of this

magnitude.

37 The amount of working capital allowed for each year was calculated as 3.5 times the standard

deviation in energy costs. If energy costs were normally distributed, energy costs would only ever

exceed 3.5 standard deviations above the expected cost about 1 in every 3000 years, or 99.97%

confidence level. However, the energy cost distributions are slightly skewed, with a marginally higher

probability of high cost outcomes compared to a normal distribution. Allowing for this, a

conservative estimate of the confidence level associated with a 3.5 standard deviation working

capital allowance would be 1 in every 200 years, or 99.5%. The working capital cost was therefore

calculated as 3.5 times the standard deviation (at the conservative point of the frontier) times the

annual cost of capital (WACC). For example, if the standard deviation was $3/MWh, the amount of

working capital allowed each year would be 3.5 x $3/MWh = $10.50/MWh. Assuming a WACC of

10%, the annual cost of holding the working capital would be $10.50 x 10% = $1.05/MWh.





commented on Frontier‟s calculation of the volatility allowance. This section

provides an overview of, and response to, these submissions.

Volatility allowance and spot prices

Origin Energy commented that Frontier Economics‟ calculation of the volatility

allowance assumes that the actual market price will equally vary above and below

the forecast market price.

Frontier Economics does not assume that the actual market price will equally

vary above and below the forecast market price. The half-hourly prices provided

as part of the example calculations and results released with Frontier Economics‟

draft report and final report provide information on the distribution of prices in

Frontier Economics‟ modelling.

Volatility allowance and contract prices

Origin Energy commented that Frontier Economics‟ calculation of the volatility

allowance has been set at 5 per cent of the spot price forecast.

The volatility premium is based on the cost of holding capital to manage the risk

that retailers continue to face at the conservative point on the efficient frontier. It

is calculated using the standard deviation of expected returns at the conservative

point on the efficient frontier and a cost of capital. The 5 per cent premium to

the spot forecast is used to determine contract prices. Whilst these contract

prices affect the cost of the most conservative point on the efficient frontier, they

do not affect the volatility of expected returns, and hence, do not directly affect

the volatility premium.

Volatility allowance and risk management

AGL commented that it is concerned that the value of the volatility allowance is

inadequate to compensate retailers for the cost of managing risks in the energy

market.

The volatility allowance is not intended as the only compensation to retailers for

the cost of managing risks in the energy market. As set out in Frontier

Economics‟ Modelling methodology and assumptions report and Frontier Economics‟

Energy purchase costs draft report, Frontier Economics uses STRIKE to determine

the efficient portfolios of hedging contracts that retailers can adopt to manage

the risks associated with the wholesale market, such as load and price volatility.

The energy purchase cost calculated using STRIKE includes the cost of hedging

products used to manage retailers‟ energy purchase risk. The example calculation

released by Frontier Economics provides information on the cost of these



hedging products. There are also other mechanisms by which retailers‟ risks are

managed, including the annual review process.

Changes to volatility allowance relative to the previous

determination

AGL commented that they would like clarification of the improved data that led

to a reduction in the volatility allowance relative to the previous determination.

As discussed, the volatility allowance is related to the degree of risk that retailers‟

remain exposed to even if they are hedged as defined by the conservative point

on the efficient frontier (where the risk is determined by the standard deviation

of expected returns at the conservative point). Because retailers‟ risks depend to a

large extent on the correlation between load and prices, the volatility allowance

also depends to a large extent on the correlation between the standard retailers‟

regulated load forecasts and forecast system load and prices. The data submitted

by the standard retailers‟ for this determination included more precise

information on the correlation between the standard retailers‟ regulated load

forecasts and forecast system load and prices, which resulted in a more precise

treatment of risk in Frontier Economics‟ modelling.

5.3.3 Volatility allowance results

The volatility premiums calculated using the framework described above are set

out in Figure 27. These premiums are for the Base case and correspond to the

conservative point on the efficient frontier. The relativities between the years and

businesses are consistent with the risk associated with these conservative points

on the efficient frontiers. Volatility premiums have reduced by 2.4% relative to

the draft report due to the change of WACC from 8.2% to 8.0%.



Figure 27: Volatility allowance (real 2009/10)

5.4 Comparison with LRMC results

Figure 28 sets out the market-based energy purchased cost, including the

volatility premium, for the Base and No CPRS cases, and the corresponding

LRMC results. Figure 28 also sets out the determination prices for 2009/10 for

the purposes of comparison.

Initially the LRMC results are greater for both the Base and No CPRS case

(which are identical in 2010/11). This is consistent with the loose supply-demand

assumptions in the market case, coupled with the increased input cost

assumptions in the LRMC case. In 2011/12 the gap between LRMC and market-

based energy purchased cost is reduced, reflecting the tightening supply-demand

balance in the market case. However, LRMC is still higher.

In 2012/13 the market-based energy purchase cost is higher than LRMC in the

Base case. This reflects the higher level of carbon pass-through that is achieved

under the market approach. In the LRMC approach, the stand alone system that

is built to meet the Standard Retailers‟ regulated load can adapt to the presence of

a carbon price. As such, in 2012/13 in the LRMC approach, the stand alone

system includes a relatively higher proportion of gas fired CCGT plant (which

has a lower emissions factor and therefore lower carbon cost). This results in a

lower level of carbon pass-through than in the market case (where no investment



changes occur due to carbon within the determination period). This is discussed

further in Section 6. For the No CPRS cases the LRMC and market outcomes are

broadly consistent, however LRMC is slightly higher.

Figure 28: Results using the LRMC and Market approaches (real 2009/10)

5.5 Additional sensitivities

In response to the draft report, a number of retailers commented that the

market-based energy purchase cost for 2010/11 resulting from SPARK is too

low, and lower than observed market prices for 2010/11.38 Retailers generally

agreed that the AEMO 2009 SOO demand forecasts are likely too low, and that

these demand forecasts are part of the explanation for the level of the market-

based energy purchase cost for 2010/11 from SPARK.

38 See, for example, EnergyAustralia and Integral Energy. In addition, AGL commented that Frontier

Economics‟ modelled spot prices for 2010/11 are lower than historic spot prices for most years

from 2000/01 to 2008/09. However, Frontier Economics considers that comparing forecast prices

with historic spot prices is largely irrelevant, particularly where there are significant changes

affecting, or expected to affect, the market.



As discussed in Frontier Economics‟ Energy purchase costs draft report and at the

public forum, Frontier Economics considers that the reason that market-based

energy purchase cost for 2010/11 resulting from SPARK are low is that the

demand forecasts from the AEMO 2009 ESOO, which are an important input

into Frontier Economics‟ modelling, are likely to be unrealistically low.

Recognising the unusual circumstances resulting from the fact that the demand

forecasting for the AEMO 2009 ESOO was undertaken during the depths of the

global financial crisis, Frontier Economics adopted the high energy forecast from

the AEMO 2009 ESOO. In light of the improved economic outlook in Australia,

Frontier Economics considered that the high energy forecast from the AEMO

2009 ESOO were more likely appropriate than the medium energy forecast.

Whether the high energy forecast is a reasonable reflection of outcomes under

the improved economic outlook in Australia is ultimately a question that cannot

be answered within the timeframe for IPART‟s determination. As set out in

Figure 4, for 2010/11, even the high energy forecast from the AEMO 2009

ESOO is lower than the medium energy forecast from the previous years‟ SOO.

In any case, even in the current unusual circumstances, Frontier considers that in

the interests of transparency it is appropriate to use demand forecasts from the

AEMO ESOO. Of course there is the possibility that the demand forecasts from

the AEMO ESOO will be subject to further uncertainty over the course of the

current determination. This can be addressed through the periodic review

process. Also, this is one reason that, in addition to advising IPART on market-

based energy purchase costs resulting from Frontier Economics‟ SPARK

modelling, Frontier Economics also advises IPART on market-based energy

purchase costs using d-cyphaTrade contract prices.

Figure 29 compares Frontier Economics‟ spot price forecasts from the Base case

(which uses the high energy forecast from the AEMO 2009 ESOO) with spot

price forecasts using the medium energy forecast from the NEMMCO 2008

SOO and d-cyphaTrade forward prices.39 Figure 29 clearly shows that increasing

the level of demand assumed in SPARK results in higher market price forecasts.

In 2010/11, the forecast prices from the 2008 Demand case are close to the d-

cyphaTrade forward curve. Note that the assumed forward curve used in

STRIKE includes a 5% premium over forecast spot prices, which means that the

2008 Demand case forward curve is actually slightly higher than the d-

cyphaTrade forward prices. In 2011/12 and 2012/13, the forecast prices in the

2008 Demand remain higher than for the Base case, by around $4/MWh (and

higher than the d-cyphaTrade forward curve in these years, which appears not to

be fully pricing in the introduction of the CPRS).

39 See Appendix B – Modelling results using d-cyphaTrade contract prices



Figure 29: Average annual NSW price forecasts compared to the d-cyphaTrade flat

swap price

Figure 30 shows the energy purchase cost plus volatility allowance for the Base,

2008 Demand, d-cyphaTrade and LRMC Base cases.

In 2010/11, when the forward curve used in both the d-cyphaTrade and 2008

Demand cases are around $41/MWh on a flat annual basis, the calculated energy

purchase costs for these two scenarios are also very similar for each retailer. The

Base LRMC result is still significantly higher than any of the other cases

considered. Even if the demand forecasts from the NEMMCO 2008 SOO are

used (which were prepared a year prior to the global financial crisis) then the

LRMC approach would still be used in the determination for the 2010/11 year.

In 2011/12 the three modelling approaches return similar values, all of which are

higher than the d-cyphaTrade case.

In 2012/13, both of the market cases are higher than LRMC, which is higher

than the d-cyphaTrade case. This reflects the impact of carbon pricing on energy

purchase costs and is discussed in more detail in the Section 6.



Figure 30: Energy purchase costs plus volatility premium for the Base, 2008 Demand

and d-cyphaTrade cases


Impact of the CPRS

6 Impact of the CPRS

As discussed in Section 4 and Section 5 of this report, assumptions about the

introduction of the CPRS are incorporated in both Frontier Economics‟

modelling of LRMC and the modelling of the market-based energy purchase

cost. This section provides further detail on how the CPRS is incorporated in the

modelling, and sets out the impact of the CPRS on the modelling results.

6.1 Approach to modelling the CPRS

Frontier Economics‟ modelling framework uses the same approach to model the

impact of the CPRS for both LRMC modelling and market-based modelling.

As discussed in the Modelling methodology and assumptions report, given that the

CPRS covers sectors beyond electricity and allows for international trade of

permits, it is assumed that the Australian electricity sector will be a price taker in

the global carbon market, which seems inarguable given the tiny size of

Australia‟s demand for permits relative to the rest of the world.

Since modelling the global carbon market is beyond Frontier Economics‟ scope

of work for this review, the Commonwealth Treasury‟s carbon price assumptions

used in their CPRS modelling have been employed in this analysis.40

As discussed in the Modelling methodology and assumptions report, the carbon prices

incorporated in Frontier‟s modelling have been adjusted to reflect the changes by

the Commonwealth Government of the CPRS since the release of the White

Paper. Two important changes incorporated in the modelling are:

the start date of the scheme has been delayed to 1 July 2011 (FY2011/12),

and

the price of carbon has been fixed at $10/tCO2-e (nominal) in the first year

of the scheme

The Commonwealth Treasury have recently revised their forecasts of carbon

prices to reflect the appreciating exchange rate. The previous modelling

undertaken by the Commonwealth was based on a longer term view of exchange

rates. The recent revision was undertaken for the purposes of the Mid Year

Economic and Fiscal Outlook (MYEFO). This adopts a much nearer term view

of the economy and may not be appropriate for forecasting carbon prices for 3½

years time. Frontier Economics is currently reviewing Commonwealth Treasury‟s

40 Commonwealth Treasury‟s carbon price assumptions are converted from calendar year to financial

year by taking a simple average of calendar year prices. Commonwealth Treasury‟s carbon price

assumptions are then converted into 2009/10 dollars, consistent with the rest of Frontier

Economics‟ modelling assumptions.


Impact of the CPRS

most recent forecasts of carbon prices to determine their appropriateness for this

review. These results were released on 2nd November 2009 which was after

assumptions for the modelling presented in this report were finalised.

The revised carbon price forecast released on 2nd November 2009 takes

Australia‟s strengthening exchange rate into account and forecasts that the

carbon price will decrease slightly in 2012/13 relative to the assumption used in

this modelling. If this analysis had assumed a lower input carbon price then, all

other things being equal, this would result in lower pool prices and lower energy

purchase costs.

These carbon price assumptions are inputs into Frontier‟s modelling in essentially

the same way. In both WHIRLYGIG and SPARK, each generator‟s variable costs

are assumed to increase with the CPRS by the product of the assumed carbon

price and the generators emissions intensity.

6.2 Responses to the Modelling methodology and

assumptions report

In response to Frontier‟s Modelling methodology and assumptions report, a number of

stakeholders have commented on Frontier Economics‟ proposed modelling of

the CPRS. This section responds to these submissions.

6.2.1 Carbon-inclusive or carbon-exclusive

A number of stakeholders have commented on whether prices should be

modelled on a carbon-inclusive of carbon-exclusive basis. EnergyAustralia

commented that wholesale prices should be modelled exclusive of carbon, as the

current uncertainty surrounding the CPRS is likely to result in a mis-matched cost

allowance. Other stakeholders commented that wholesale prices should be

modelled inclusive of carbon as this is how the market will operate.41

While an approach under which a carbon exclusive price is modelled and a

carbon price is passed through may have intuitive appeal, the difficulty with the

approach is that the extent to which the carbon price is passed through to spot

prices will be determined by outcomes in the market, and cannot be determined

independently of outcomes in the market. As discussed in the Modelling methodology

and assumptions report, Frontier Economics considers that a carbon inclusive price

is more appropriate because the spot market, and most likely contract markets,

will move to carbon inclusive pricing.

41 See, for example, d-cyphaTrade and Origin Energy.


Impact of the CPRS

6.2.2 Carbon price pass-through

Some stakeholders have raised questions about the assumptions about carbon

price pass-through used in Frontier Economics‟ modelling.

As discussed in the Modelling methodology and assumptions report, in the modelling

the pass-through of carbon costs into spot prices is not a modelling input, but is

a modelling output. That is, spot prices are not increased according to the carbon

price adjusted for an assumed carbon pass-through. Rather, the modelling

includes input assumptions that define the extent to which the costs of each

generator increase as a result of a carbon price (which is determined by the

carbon price and each generators‟ emissions intensity). This increase in costs is

incorporated in both the LRMC modelling and spot price modelling.

In order to determine the pass-through of carbon costs into spot prices that is

implied by the modelling, it is necessary to model a scenario with a carbon price

and a scenario without a carbon price. From the difference between these

scenarios it is possible to determine the implied pass-through rate. In this sense,

Frontier Economics‟ modelling reflects how the market will operate: the pass-

through rate is a result of the way that generators bid in response to the carbon

costs that they each face, and can only be determined by comparison between a

market with a carbon price and the same market without a carbon price.

The carbon pass-through rate resulting from the modelling is set out in Section

6.3.

6.2.3 Assumptions about CPRS

In response to the Modelling methodology and assumptions report, some stakeholders

questioned the source of assumptions about the CPRS and the expanded RET

for the purposes of the annual reviews:

Origin Energy requested information on whether carbon assumptions will be

updated in periodic reviews, and from where this information will be sourced

Frontier‟s views on the scope and timing of periodic reviews are set out in

Section 9. Frontier considers that it would be appropriate to revisit

assumptions about future carbon prices as part of the periodic review

process. However, Frontier Economics considers that there is little point in

speculating at this stage as to what source of information on carbon prices

would provide the most appropriate source of input assumptions. As noted

above, the Commonwealth Treasury has recently updated its view of future

carbon prices based on the recent appreciation of the Australian dollar.

Frontier Economics is currently reviewing this analysis to determine the

appropriateness of MYEFO based forecasts for the longer term modelling

presented in this report. IPART‟s Draft Report will continue further detail on


Impact of the CPRS

the treatment of the uncertainty related to the carbon price through the

periodic review process.

AGL raised concerns that Concept Economics will not be updating its report

on the costs of renewable generation, as the business has gone into

administration.

Frontier does not consider that this is reason to use some other source of

information for input assumptions on renewable generation. For the purpose

of the periodic reviews, Frontier Economics considers that it would be

appropriate at the time of the periodic review for IPART and their

consultants to use the best information available at the time. This would be

the case for input assumptions for renewable technologies as well as all other

input assumptions.

6.3 Responses to the draft report


commented on Frontier Economics‟ proposed modelling of the CPRS. This

section provides an overview of, and response to, these submissions.

6.3.1 Relationship between CPRS and expanded RET

EnergyAustralia again suggested that IPART should adopt a carbon-exclusive

approach to estimating the energy purchase cost allowance. EnergyAustralia‟s

argument is that the assumption that the CPRS will be implemented has an

impact on the allowance for the costs of complying with the expanded RET and

the GGAS, and this impact occurs in each year of the determination.

EnergyAustralia is correct that the assumption that the CPRS will be in place in

2011/12 and 2012/13 has an impact on REC price forecasts for 2010/11.

EnergyAustralia‟s argument is essentially that they cannot now buy RECs for

2010/11 at a price that is based on the certain introduction of the CPRS. The

reason is that wind farm proponents would not be willing to commit to an

investment now, because to do so they would be taking on the risk that the

CPRS is abandoned or delayed, or the forecast carbon price falls.

However, EnergyAustralia‟s recommendation to model carbon-exclusive prices

does not resolve this difficulty. Modelling a carbon-exclusive price would result

in a REC price forecast for 2010/11 that is based on the certain absence of the

CRPS, which is not realistic. in addition, a REC price forecast based on the

certain absence of the CPRS would be inconsistent with the assumptions used in

the rest of the analysis, particularly regarding black price forecasts.


Impact of the CPRS

6.3.2 Treatment of carbon in stand-alone LRMC modelling

AGL commented that the LRMC modelling of the regulated load undertaken by

Frontier Economics is unlikely to capture the full costs of carbon incurred by

retailers.

AGL‟s comment seems to be directed at the emissions-intensity of the

hypothetical system built and operated to meet the regulated load.

Frontier Economics has modelled the LRMC of the regulated load on a stand-

alone basis, for reasons discussed in Frontier Economics‟ Modelling methodology and

assumptions report. With the introduction of a carbon price, the result of this

approach is for the hypothetical system to shift to less emissions-intensive

generation technologies. Because the stand-alone approach results in a new mix

of plant each year, the shift to less emissions-intensive generation technologies

happens far more quickly than occurs in practice. This is apparent from the

emissions intensities resulting from the various modelling approaches undertaken

by Frontier Economics, as set out in Frontier Economics‟ draft report and this

final report.

Furthermore, because the stand-alone approach involves building a new system

for just the regulated load, the emissions intensity even in the absence of a cost

of carbon is lower than for the NEM as a whole. This reflects the fact that a

power system built with today's more efficient technology would produce lower

average emissions that the NEM which is comprised mostly of older, less

efficient plant. Ultimately this reflects the fact that the hypothetical system that is

built in the stand-alone approach differs from the actual system of the NEM in

numerous ways.

The stand-alone approach is an attempt to estimate the efficient costs associated

with meeting an increment of regulated load. Including the costs of carbon in

determining this marginal cost seems entirely consistent with this objective. The

suggested alternative, of determining the carbon component of LRMC at the

NEM emissions intensity, is not consistent with the concept of the efficient new

entrant costs required to meet the marginal regulated customer. For these reasons

Frontier Economics has continued to include variable carbon costs in the

optimisation process when LRMC is determined.

6.3.3 Carbon price assumptions for the annual review

In response to Frontier Economics‟ draft report, AGL again questioned the

source of the carbon price assumption that will be adopted for the purposes of

the annual review.

As discussed in Frontier Economics‟ draft report, Frontier Economics considers

that it would be appropriate to revisit the assumptions about future carbon prices


Impact of the CPRS

as part of the periodic review process, but that there is little point in speculating

at this stage what source of information would provide the most appropriate

source of input assumptions.

6.4 CPRS results

The carbon pass-through under the market-based approach and cost-based

approach is determined slightly differently.

For the cost-based approach, carbon pass-through can be determined as an

output of Frontier Economics‟ modelling by comparing the difference between

the LRMC determined for the Base and No CPRS cases. This determination of

carbon pass-through also includes the effect of each retailer‟s load shape, and is

not directly comparable to the expected level of market carbon pass-through.

For the market-based approach, carbon pass-through can be determined by

comparing the pool price outcomes between the Base and No CPRS cases. This

level of pass-through represents the extent to which wholesale electricity prices

($/MWh) increase for a given carbon price ($/tCO2e).

Figure 31 shows the level of carbon pass-through for the cost-based approach.

The assumed carbon price is represented by columns (measured against the right

axis). The level of carbon pass-through is represented by the line series

(measured against the left axis). As discussed, the LRMC pass-through reflects

the load shape of each retailer as well as the pure effect of carbon. As such a

different pass-through rate is shown for each business. The level of pass-through

reduces in 2012/13 relative to 2011/12. This is because the plant mix of the

stand alone generation system built to meet the load includes more CCGT plant

in 2012/13.


Impact of the CPRS

Figure 31: Carbon price pass-through under the LRMC approach

Figure 32 shows the pure carbon pass-through of carbon prices into electricity

prices under the market-based approach. There are two key features to note.

Firstly, carbon pass-through in the market-based approach is much higher than in

the LRMC case. This reflects the fact that in reality (which is better reflected in

market based approach) investment cannot respond to the carbon price within

the period of the current determination; only the dispatch of existing plant can

change to meet the target within this short timeframe. Given that the existing

stock of plant has a higher average emissions factor than any hypothetical new

system of plant, the level of carbon pass-through is higher in the market-based

approach.

Secondly, the levels of carbon pass-through are high – at or above 100 per cent.

This will be the case for the period where the CPRS is active but prior to new

investment coming into the NEM in response to the CPRS (and the associated

higher prices). This is the same period covered by the determination. High levels

of carbon pass-through at the beginning of a cap and trade scheme are an

indication that the scheme is working and that new, low emission investment will

occur in the future, eventually lowering the average emissions of the NEM and

the carbon pass-through.


Impact of the CPRS

Figure 32: Carbon price pass-through under the market approach

The level of carbon pass-through also increases from 2011/12 to 2012/13. Two

factors drive the level of carbon pass-through in the market case as follows:

The level of the carbon price changes the shape of the supply curve such that

the different marginal plant set different pool prices. With a merit order such

as is seen in the NEM, as the carbon price rises, the marginal plant should

become increasingly efficient (cleaner) over time such that the average

emissions of the system reduce.

The change to the supply curve of the market changes the strategic incentives

of market participants. As the relative price differential between Coal and

CCGT reduces it becomes less profitable for strategic generators to withdraw

capacity to bring on CCGT generation. Conversely, the price differential

between Coal and OCGT remains high. It is likely that, particularly in the

early stages of a cap and trade scheme, coal generators will be incentivised to

engage in even more aggressive withdrawal strategies in order to bring

OCGT plant into the market to set higher prices. This incentive does not

exist in the absence of a cap and trade scheme because it is more profitable to

behave less aggressively and only withdraw enough capacity to bring CCGT

plants on. This is concept is illustrated in Figure 33.


Impact of the CPRS

In 2012/13, the strategic response to the change in the supply curve of the

market caused by the introduction of a $26/tCO2e carbon price overwhelms the

propensity for CCGT plant to set prices more frequently. As such, the level of

pass-through in 2012/13 is higher than in 2011/12 even though the carbon price

has more than doubled.

Figure 33: Diagrammatic representation of bidding incentives with and without a

CPRS carbon price


Expanded RET, the GGAS and the ESS

7 Expanded RET, the GGAS and the ESS

In addition to estimating the energy purchase cost allowance for the period of the

determination, Frontier‟s scope of work also includes estimating a range of other

energy-related costs that Standard Retailers will face over the period of the

determination.

This section considers the costs that Standard Retailers will face as a result of the

following related schemes:

the expanded RET

the GGAS, and

the EES

7.1 Expanded RET

The expanded RET scheme has been established to encourage additional

generation of electricity from renewable energy sources to achieve a 20 per cent

share of renewable energy in Australia‟s electricity supply in 2020.

The expanded RET places a legal liability on wholesale purchasers of electricity

to proportionately contribute towards the generation of additional renewable

electricity. Liable parties support additional renewable generation through the

purchase of Renewable Energy Certificates (RECs) that are created through

generation from renewable energy power stations, solar water heaters and small

generation units.

7.1.1 Frontier’s approach to estimating costs of complying

with the expanded RET

In order to calculate the cost to a standard retailer of complying with the

expanded RET, it is necessary to determine the renewable power percentage for a

standard retailer (or the number of RECs that a standard retailer needs to

surrender) and the cost of obtaining RECs to meet the renewable power

percentage.

Renewable power percentage

The renewable power percentage establishes the rate of liability under the

expanded RET and is the mechanism that liable parties use to determine how

many RECs need to be surrendered to discharge their liability each year.

The renewable power percentages is set to achieve the renewable energy targets

specified in the legislation, which will ultimately achieve the renewable energy

target for 2020 of 45,000 GWh. The Office of the Renewable Energy Regulator



(ORER) is responsible for setting the renewable power percentage for each year,

and does so on an ex-ante basis. For 2010, the renewable power percentage was

not set. In this case the Renewable Electricity Act42 states that the renewable

power percentage should be calculated as the renewable power percentage for the

previous year divided by the required GWh's of renewable energy for the

previous year multiplied by the required GWh's of renewable energy for the

current year. This process increases the renewable power percentage in line with

increases in the renewable energy target. This process does not decrease the

renewable power percentage to account for any growth in demand; as a result the

process is conservative in that it overestimates the renewable power percentage.

Frontier Economics has used the published renewable power percentage for

calendar year 200943, the forecast increases in the target44 and the process

outlined above to estimate the renewable power percentage for each calendar

year. These values have then been average to arrive at the financial year

renewable power percentages set out in Table 3.

Table 3: Renewable power percentages

Year Renewable power percentage

(% of liable acquisitions)

2010/11 6.1 %

2011/12 7.2 %

2012/13 8.1 %

Source: Renewable Energy (Electricity) Regulations 2001, Frontier calculations.

Cost of obtaining RECs

The cost to a retailer of obtaining RECs can be determined either based on the

costs of meeting the expanded RET or the price at which RECs are traded.

Frontier Economics estimates the cost of RECs on the basis of the LRMC of

meeting the expanded RET. The LRMC of meeting the expanded RET is

calculated as an output from Frontier Economics‟ least-economic cost modelling

42 Renewable Energy (Electricity) Act 200 compiled Feb. 2010, pp 40-47.

43 Available at

www.comlaw.gov.au/comlaw/Legislation/LegislativeInstrumentCompilation1.nsf/0/2F4D5782236

7DA5ECA25768E0078C081?OpenDocument.

44 Available at www.orer.gov.au/publications/pubs/ret-thebasics-0909.pdf.



of the power system, using WHIRLYGIG. The LRMC of meeting the expanded

RET is effectively the marginal cost of an incremental increase in the expanded

RET. WHIRLYGIG accounts for the expanded RET by incorporating the target

for each year as a constraint in the model. The constraint can be met by eligible

generators as specified under the scheme.

There are important interactions between the wholesale electricity market, the

expanded RET and the CPRS. One way to think about the expanded RET is as a

„subsidy‟ to cover the additional cost of renewable generation over thermal

generation. Thought of in this way, the REC price represents the „subsidy‟

(measured in $/MWh) required for renewable generation to be competitive with

thermal generation to the extent that the RET targets are met each year. An

implication of this is that changes to the cost of thermal generation will have an

impact on the REC price. If the cost of thermal generation increases, the

„subsidy‟ required for renewable generation to be competitive with thermal

generation will decrease. One reason that the cost of thermal generation would

increase is the introduction of the CPRS, which will impose a carbon cost on

thermal generation. It is therefore expected that the cost of RECs will fall as the

price of carbon, as reflected in the electricity market, increases. Even an expected

future increase in the costs of thermal generation can have an impact on the REC

price because the expanded RET scheme permits banking and (to an extent)

borrowing of RECs.

Of course the target under the expanded RET is also an important driver of REC

prices. As the target increases it is expected that the marginal supplier of RECs

will be increasingly costly, resulting in a higher REC price for a higher target.

These factors are reflected in Frontier Economics‟ modelling of the expanded

RET. As discussed in the Modelling methodology and assumptions report, Frontier

Economics models the expanded RET under a cost-based approach using

WHIRLYGIG. This provides the LRMC of meeting the expanded RET. Given

that the expanded RET target relates to generation across Australia, and is

designed to provide incentives to alter the existing mix of generation output, the

expanded RET is modelled using the incremental approach and the system load

shape.45

7.1.2 Re-modelling the LRMC of meeting the expanded RET

For this final report, Frontier Economics‟ has re-modelled the LRMC of meeting

the expanded RET. This is due to the change in the input assumptions used for

Frontier Economics‟ least-cost modelling of the power system.

As discussed previously, there have been two changes to input assumptions:

45 Frontier‟s modelling accounts for the fact that the expanded RET can be met by generation outside

the NEM.



the WACC has been updated by IPART, and

the amortisation of the thermal capital costs has been revised by SFG

Consulting.

While these changes have resulted in small relative changes to the estimate of the

stand-alone LRMC for each standard retailers‟ regulated load, it is not necessarily

the case that the relative changes to the LRMC of meeting the expanded RET

would be of a similar magnitude. The reason is that the cost of meeting the

expanded RET is effectively the subsidy required for renewable plant in order to

make it competitive with thermal plant. Changes to the cost of thermal plant can

therefore have a significant impact on the cost of meeting the expanded RET.

In fact, the LRMC of meeting the expanded RET can be quite sensitive to input

cost assumptions for a number of reasons:

the LRMC of meeting the expanded RET is calculated relative to the total

system costs over the modelling period (in this case over 10 years) and

represent a very small change on a large base cost.

The renewable supply options included in the model are relatively

discrete. Only four different technology types have been included for

each region.

Banking and borrowing under the expanded RET, coupled with the

dynamics of the wholesale market, can result in changes to the LRMC of

meeting the expanded RET that are proportionally large, but reflect only

small changes in the overall pattern of investment and dispatch.

In this instance, given the fact that the investment needed to meet the expanded

RET was close to a point where meeting the target would require more expensive

technologies, a small change in input assumptions has resulted in a relatively large

change in the forecast LRMC of meeting the scheme. This is reflected in the re-

modelled results for the estimate of the LRMC of meeting the expanded RET.

These are presented in Table 4, and compared with the estimates from the draft

report. The permit cost forecast is around $30/REC, an increase of around

$13/REC on the draft report.

In order to understand how these changes to the estimate of the LRMC of

meeting the expanded RET relate to outcomes in the broader energy market, it is

useful to compare the estimate of the total energy purchase cost from this final

report with those from the draft report. This demonstrates that the impact of the

increase in the REC component on total energy costs is less than 1 per cent. This

comparison is set out in Appendix A, which summarises the results of Frontier

Economics‟ advice to IPART.



Table 4: REC price (real 2009/10)

Year Draft Report

REC price

($/certificate)

Final Report

REC price

($/certificate)

Change

(%)

2010/11 $ 16.39 $ 29.68 81%

2011/12 $ 17.04 $ 30.86 81%

2012/13 $ 17.73 $ 32.10 81%

Source: Frontier Economics

Following this re-modelling of the LRMC of meeting the expanded RET,

Frontier Economics‟ estimate of the cost of RECs remains below the current

market price of RECs. Observed market prices for RECs remain above $30 per

certificate.46 Frontier Economics considers that this is ultimately because the

REC price is inversely related to pool prices. Frontier Economics considers that

higher observed market prices for RECs are due to two factors resulting in lower

expectations about pool prices relative to the assumptions used in Frontier

Economics‟ analysis:

Uncertainty about the design and implementation of the CPRS, and the effect

that this will have on market prices. As discussed in Section 5.1.5, this

uncertainty is reflected in market prices, with d-cyphaTrade prices for

2012/13 seeming to reflect a degree of uncertainty about the implementation

of the CPRS. Accordingly, expectations about REC prices falling due to the

implementation of the CPRS do not appear to be fully priced into the REC

market. This uncertainty is not reflected in Frontier Economics‟ modelling,

with the CPRS incorporated in the modelling for both 2011/12 and 2012/13.

Uncertainty about the extent to which higher costs of thermal generation will

be reflected in market prices. As discussed in Section 5.1.5, Frontier

Economics considers that spot market prices are currently below LRMC as a

result of uncertainty about levels of demand following the demand forecasts

set out in the latest AEMO 2009 ESOO and the impact on demand of the

recent warm winter. This uncertainty is not reflected in Frontier Economics‟

modelling because REC prices are forecast on the basis of LRMC, and

LRMC is driven principally by generation costs.

46 See, for example: Intelligent Energy Systems, 2009 REC Market Review, A report for the Clean

Energy Council, October 2009.




In response to Frontier Economics‟ Energy purchase costs draft report, a number of

stakeholders commented on Frontier‟s calculation of the cost of complying with

the expanded RET. This section provides an overview of, and response to, these

submissions.

Frontier Economics’ estimate of the LRMC of meeting the

expanded RET

A number of retailers commented that observed market prices for RECs are in

excess of the LRMC estimate.47 Recognising the relationship between the

expanded RET and the CPRS, and the uncertainty surrounding the CPRS, a

number of retailers suggested basing the expanded RET allowance on observed

market prices of around $35 per REC.48

Frontier Economics notes that the estimated LRMC of meeting the expanded

RET has increased since the draft report, but remains below observed market

prices for RECs.

Frontier Economics considers that basing the allowance for the expanded RET

on the market price of RECs would represent a significant change in approach

from that proposed in Frontier Economics‟ Modelling methodology and assumptions

report (which was largely accepted at the time by retailers). Frontier Economics

also considers that there are good reasons to adopt a cost-based approach to

modelling REC prices, including:

to ensure consistency of treatment of the CPRS across energy price forecasts

and estimates of the LRMC of meeting the expanded RET and GGAS,

because a cost-based approach is consistent with the way that many retailers

acquire RECs, through investments in, or long-term PPAs with, renewable

generators, and

because a cost-based approach is consistent with the Terms of Reference.

Transparency of modelling

EnergyAustralia suggested that there is a lack of transparency around the LRMC

of renewable generation in Frontier Economics‟ modelling. EnergyAustralia

requested that Frontier Economics release a supplementary report detailing its

calculation of the LRMC of renewable generation. EnergyAustralia state that, in

the absence of a stated LRMC they assume Frontier Economics have used a

47 See, for example, AGL, Country Energy, EnergyAustralia, Integral Energy, Origin Energy and

TRUenergy.

48 See, for example, Country Energy, Integral Energy and Origin Energy.



LRMC of $88/MWh for wind generation (as set out in a 2008 Frontier

Economics report for the AEMC).

The LRMC of renewable generation can be calculated using the input

assumptions (primarily capital cost, operating cost, operating characteristics,

technical life and discount rate) that are set out, for each type of renewable

generation, in Frontier Economics‟ Modelling methodology and assumptions report.

Capital cost assumptions

A number of retailers commented that they consider a key reason for Frontier

Economics estimates of the LRMC of RECs being below the current market

price of RECs is that the capital cost assumptions for renewable generation

adopted by Frontier Economics are too low.

The capital cost assumptions for renewable plant that were adopted by Frontier

Economics came from a Concept Economics report for the QCA. The Concept

Economics report was used as an additional source to the ACIL 2009 Report

because the Concept Economics report had a broader range of technologies

(particularly renewable technologies) than the ACIL 2009 Report. Frontier

Economics examined the capital cost assumptions from the Concept Economics

report, and found them to be comparable to a range of other sources, including:

for wind, the ACIL 2009 Report for AEMO, and

ABARE data on capital costs for proposed renewable projects.

A representative from ACIL Tasman suggested to Frontier Economics that he

considers the capital cost assumption for wind from the Concept Economics

report now to be at the low end of the range. However, ACIL Tasman have not

yet released an update of their cost forecasts and, at this stage, they continue to

use the capital cost assumptions from their ACIL 2009 Report in their current

modelling work for the QCA (which includes a capital cost assumption for wind

generation that is only slightly higher than that in Concept Economics).49

Given the broad support for the use of publicly available information, and the

fact that the publicly available information continues to suggest that the capital

cost estimates in Concept Economics‟ report are reasonable, Frontier Economics

has continued to adopt these capital cost estimates for this final report. As

discussed in Section 9, Frontier Economics considers that it would be

appropriate to revisit these, and other relevant assumptions, for the purposes of

the periodic reviews.

49 ACIL Tasman, The calculation of energy costs in the BRCI for 2010-11, Draft Report, 14 December 2009.

ACIL Tasman‟s report notes that the capital cost forecasts from the ACIL 2009 Report were

checked to ensure the underlying assumptions were still relevant before the capital costs were used

in this work for the QCA.



Other modelling assumptions

Some retailers commented that Frontier Economics‟ input assumptions for wind

generation do not appear to take account of the dispatch profile of wind

generators.50 Frontier Economics does include a dispatch profile for wind

generators in its LRMC modelling. Frontier has assumed that wind generators

produce according to a flat profile equivalent to the maximum capacity factor

that is assumed for each station. For example, wind in NSW was assumed to

have a maximum capacity factor of 30% across the year and, additionally, was

assumed to run to a 30% availability profile. This means that for every 100 MW

installed only 30 MW can be dispatched. Frontier uses a flat profile, as opposed

to a time varying profile that reflects wind speed across the day and seasons,

because the timing of wind output is not a major driver of results in cost

optimisation models. In Frontier Economics‟ experience, the factors that are

important to LRMC modelling are:

the contribution that wind generation makes to reserve at times of peak

demand (which Frontier Economics assumes is between 0% and 8%,

depending on the region), and

the total output of wind generation, which is constrained by the maximum

capacity factor of wind (which Frontier Economics assumes is between 30%

and 40%).

Frontier Economics considers that in a cost-based model, the inclusion of a

highly detailed profile of wind is not central to the modelling results. The reason

is that in a cost-based model all generators are dispatched according to their

SRMC. Since wind has a very low SRMC, it will tend to operate up to its

maximum capacity factor. Including a different profile for wind generation (in

addition to an assumed maximum capacity factor) will simply change the periods

during which wind generation operates, without having a significant impact on

total costs. In a market-based model, however, the dispatch profile of wind is

important because it will have an impact on bidding incentives and outcomes and

the magnitude of pool revenue that is received by wind plant.

Country Energy commented that LRMC modelling of the REC price does not

account for supply and demand for RECs, which strongly affect the REC price.

LRMC modelling of the REC price does account for supply and demand for

RECs. Demand for RECs is a function of the expanded RET target, which is

included as a constraint that must be met by generation output in the

optimisation modelling, as discussed in Frontier Economics‟ Modelling methodology

and assumptions report. Supply for RECs is accounted for through the operation of

renewable generation in the modelling, taking account of the existing stock of

50 See. for example, EnergyAustralia and Origin Energy.



RECs at the commencement of the modelling period and the generation of

RECs from non-generation sources over the modelling period.

EnergyAustralia commented that it is unclear how Frontier Economics‟

modelling of the LRMC of meeting the expanded RET accounts for factors

affecting the demand and supply of RECs, such as RECs created from sources

other than generation, RECs that have been currently banked and the demand

and supply for RECs from regions outside the NEM. Frontier Economics

accounts for these factors by adjusting the expanded RET constraint in the

model to account for these factors. For instance, an estimate of the existing

supply of RECs is included in the modelling so that these RECs can be used to

meet the target. An estimate of RECs created from non-generation sources is

included in the modelling so that the these RECs can be used to meet the target.

And the fact that the expanded RET target is a national target is accounted for in

the modelling by pro-rating the RET target included in the NEM modelling on

the basis of the NEM‟s share of the total Australian electricity market.

Importantly, Frontier Economics‟ modelling of the LRMC of meeting the

expanded RET does not account for the announcement on 26 February 2010 of

proposed changes to the expanded RET.51 At this stage, the Commonwealth

Government has not finalised or released enough information to be able to

accurately account for the proposed changes to the scheme. As such, Frontier

Economics has not included the proposed changes.

Relationship between REC prices and spot prices

Some retailers commented that during 2009 wholesale energy prices and REC

prices both fell, contrary to Frontier Economics‟ argument that the REC price is

inversely related to wholesale energy prices.52

Frontier Economics has consistently argued that the interaction between the

wholesale energy market and the REC market mean that, all other things being

equal, an inverse relationship between energy prices and REC prices will be

observed. However, this does not imply that energy prices and REC prices will

always move in opposite directions. The reason is that there are any number of

other factors that can affect both energy prices and REC prices, and these factors

can mask the inverse relationship between energy prices and REC prices.

51 http://www.climatechange.gov.au/en/minister/wong/2010/media-

releases/February/mr20100226.aspx

52 See, for example, Country Energy and EnergyAustralia.

http://www.climatechange.gov.au/en/minister/wong/2010/media-releases/February/mr20100226.aspx

http://www.climatechange.gov.au/en/minister/wong/2010/media-releases/February/mr20100226.aspx



Comparison with other forecasts of REC prices

EnergyAustralia commented that Frontier Economics‟ estimate of the LRMC of

RECs is below estimates of the price of RECs from a range of other sources and

below regulatory allowances for the price of RECs in other jurisdictions.

Frontier Economics notes that re-modelling the LRMC of meeting the expanded

RET to reflect updated input assumptions has resulted in a higher estimate of the

LRMC of the expanded RET, and one that is more in line with some of the other

sources and regulatory allowances referred to by EnergyAustralia. However,

there remain differences between Frontier Economics‟ estimates and those from

some other sources. This is to be expected. Frontier Economics‟ forecast of the

REC price is dependent on both the approach to estimating the REC price and

the input assumptions used. The other regulatory allowances and other sources

cited by EnergyAustralia use other approaches (in some cases a market-based

approach) and other input assumptions, including other input assumptions in

regard to the carbon price.

7.1.4 Cost of complying with expanded RET

Based on the renewable power percentages set out in Table 3 and the REC price

forecasts set out in Table 4, the cost of complying with the RET is set out in

Table 5.

Table 5: Cost of complying with the expanded RET (real 2009/10)

Year Cost of complying with expanded REC

($/MWh)

2010/11 $ 1.78

2011/12 $ 2.16

2012/13 $ 2.55


7.2 The GGAS

The Greenhouse Gas Abatement Scheme (GGAS) is designed to reduce the

greenhouse gas emissions associated with the production and use of electricity.

Under the GGAS, electricity retailers, and certain other parties, are required to

meet emissions benchmarks based on the size of their share of the electricity

market. The GGAS establishes annual emissions benchmarks for these scheme



participants, which participants are required to meet by obtaining and

surrendering NSW Greenhouse Gas Abatement Certificates (NGACs). If

participants fail to meet their targets through the surrender of NGACs, a penalty

is imposed.

7.2.1 Approach to estimating costs of complying with the

GGAS

In order to calculate the cost to a standard retailer of complying with the GGAS,

it is necessary to determine the emissions target for a standard retailer (or the

number of NGACs a standard retailer needs to surrender) and the cost of

obtaining NGACs to meet the emissions target.

Emissions target

The emissions target for individual participants under the GGAS is based on the

level of the participant‟s electricity sales as a proportion of the total electricity

sales for NSW. For example, if a standard retailer is responsible for 10 per cent

of the total electricity sales in NSW, the standard retailer is responsible for

meeting 10 per cent of the required reduction in emissions.

Cost of obtaining NGACs

The cost to a retailer of obtaining NGACs can be determined either based on the

costs of meeting the GGAS target or the price at which NGACs are traded.

Frontier Economics estimates the cost of NGACs on the basis of the LRMC of

meeting the GGAS target. The LRMC of meeting the GGAS target is calculated

as an output from WHIRLYGIG. The LRMC of meeting the GGAS target is

effectively the marginal cost of an incremental increase in the GGAS target.

WHIRLYGIG accounts for the GGAS by incorporating the GGAS target for

each year as a constraint in the model. The constraint can be met by eligible

generators as specified under the scheme.

In incorporating the GGAS target into WHIRLYGIG, it is important to take

account of NGACs that have been created but not surrendered. NGACs that

have been created but not surrendered can be used to meet the GGAS target in

future years. Since the commencement of the GGAS, more NGACs have been

created than surrendered in each year. This was particularly evident during 2007

and 2008, when a large number of certificates where created but not surrendered

under both the generation rule and the demand-side abatement rule.53 As a result,

as of the end of 2008, over 24 million NGACs have been created but not

53 IPART, Compliance and Operation of the NSW Greenhouse Gas Reduction Scheme during 2008, Report to

Minister, July 2009.



surrendered.54 The availability of these NGACs to meet the emissions target has

been incorporated into WHIRLYGIG.

In incorporating the GGAS target into WHIRLYGIG, it is also important to take

account of the termination of the GGAS to account for the introduction of the

CPRS. The legislation that extended the GGAS in 2006 did so until 2021 or until

the establishment of a national emissions trading scheme. Therefore, when the

CPRS is assumed to come into operation in July 2011, the GGAS is assumed to

cease operating. The expiration of GGAS in July 2011 has been incorporated

into WHIRLYGIG.

The LRMC of meeting the GGAS target for 2010/11, as calculated as an output

from WHIRLYGIG, is zero. This implies that an incremental increase in the

GGAS target can be met without incurring any additional costs in 2010/11. The

reason for this is a combination of the number of NGACs that have been created

but not surrendered, and the termination of the GGAS in July 2011. Largely as a

result of these two factors, the GGAS target can be met without requiring any

increase in economic cost.

It would appear that these same factors have been affecting the NGAC price

during 2008 and 2009. IPART‟s report on the GGAS notes that NGAC prices

have fallen to around $3 to $4, as seen in Figure 34.55 IPART‟s report noted that

factors affecting the NGAC price include the announcement of the CPRS,

uncertainty about the way the GGAS might transition to the CPRS, a perceived

surplus of NGACs in later years, and the publication of forecasts of future

supply and demand for NGACs.56


Minister, July 2009, page 69.


Minister, July 2009, pages 74-76.


Minister, July 2009, pages 74-75.



Figure 34: NGAC spot prices, 2003 to 2009 (nominal)

Source: IPART, Compliance and Operation of the NSW Greenhouse Gas Reduction Scheme during 2008,

Report to Minister, July 2009. Data sourced from Next Generation Energy Solutions: www.nges.com.au


In response to Frontier Economics‟ Energy purchase costs draft report, a number of

stakeholders commented on Frontier‟s treatment of the cost of complying with

the GGAS. This section provides an overview of, and response to, these

submissions.

Frontier Economics’ estimate of the LRMC of meeting the GGAS

A number of retailers commented that observed market prices for NGACs are in

excess of the LRMC estimate (which is zero).57 Recognising the relationship

between GGAS and the CPRS, and the uncertainty surrounding the CPRS, a

number of retailers suggested basing the GGAS allowance on observed market

prices of around $5 per NGAC.58

Basing the allowance for the GGAS on the market price of NGACs would

represent a significant change in approach from that proposed in Frontier

Economics‟ Modelling methodology and assumptions report (which was largely

accepted by retailers). Also, Frontier Economics considers that there are good

reasons to adopt a cost-based approach to modelling NGAC prices, including to

57 See, for example, County Energy, EnergyAustralia, Integral Energy, Origin Energy, TRUenergy.

58 See, for example, County Energy, EnergyAustralia, Integral Energy.

http://www.nges.com.au/



ensure consistency of the treatment of the CPRS across energy price forecasts

and the LRMC of meeting the expanded RET and the GGAS.

Other modelling assumptions

Country Energy and EnergyAustralia noted that there have been recent changes

to the GGAS rules which have an effect on demand and/or supply of NGACs.

Frontier Economics‟ treatment of the GGAS in its LRMC accounts for the

current design of the GGAS. In any case, Frontier Economics‟ analysis indicates

that there is likely to be a substantial surplus of NGACs in July 2011 when the

CPRS is scheduled to be introduced, and that changes to the design of the

GGAS are therefore unlikely to change the fact that the LRMC of meeting the

GGAS is zero.

Federal Government compensation

A number of retailers suggested that the Federal Government commitment to

pay compensation to holders of NGACs when the CPRS is introduced creates a

floor price for NGACs, which should be taken into account when determining

the price of NGACs.59

In practice, the Federal Government commitment to pay compensation to

holders of NGACs will create a floor to the NGAC price up to the end of the

scheme. The floor will be the expected amount of compensation per NGAC, and

will therefore depend on the number of NGACs remaining at the

commencement of the CPRS in July 2011. While it is difficult to forecast the

number of NGACs remaining in July 2011, because it will depend, in part, on

decisions by accredited certificate providers that will be influenced by the offer of

compensation, it is clear reasonable assumptions about the number of NGACs

remaining in July 2011 provide a floor price for NGACs that is consistent with

the current market price for NGACs. Table 6 sets out the implied floor price for

NGACs for a range of forecasts of the NGACs remaining on 1 July 2011. This

assumes that the $80 million in compensation from the Federal Government

would be paid in 2011/12, and discounted by parties holding NGACs at a rate

equivalent to the Treasury bond rate.

59 See, for example, Country Energy, EnergyAustralia.



Table 6: Implied floor price for NGACs (real 2009/10)

NGACs remaining on 1 July 2011 Implied floor price of NGACs

($/NGAC)

15,000,000 $ 4.93

20,000,000 $ 3.70

25,000,000 $ 2.96

30,000,000 $ 2.47


In summary, while the commercial cost of NGACs in the market may be greater

than zero due to the proposed Commonwealth Government compensation, the

efficient cost of meeting the target remains zero. This is driven by the large

surplus of NGACs currently in existence or due to be produce before 1st July

2011, and the termination of the GGAS scheme on the commencement of the

CPRS.

7.2.3 Cost of complying with the GGAS

Based on the LRMC of the GGAS being zero for 2010/11, Standard Retailers

will not face an additional cost of complying with the GGAS in 2010/11. For

2011/12 and 2012/13, it is assumed that the GGAS ceases to operate with the

commencement of the CPRS.

7.3 The ESS

The Energy Saving Scheme (ESS) is designed to increase opportunities to

improve energy efficiency by rewarding companies who undertake eligible

projects that either reduce electricity consumption or improve the efficiency of

energy use.

Under the ESS, electricity retailers, and certain other parties, are required to meet

individual energy savings targets based on the size of their share of the electricity

market. The ESS establishes annual energy savings targets for these scheme

participants, which participants are required to meet by obtaining and

surrendering Energy Savings Certificates (ESCs). If participants fail to meet their

targets through the surrender of ESCs, a penalty is imposed.



7.3.1 Approach to estimating costs of complying with the ESS

In order to calculate the cost to a standard retailer of complying with the ESS, it

is necessary to determine the energy savings target for a standard retailer (or the

number of ESCs that a standard retailer needs to surrender) and the cost of

obtaining ESCs to meet the energy savings target.

Energy savings target

The ESS target is defined as a proportion of total annual NSW electricity sales to

be saved through the take-up of energy efficiency projects.

The ESS target is allocated each year to electricity retailers in proportion to their

liable electricity sales. Liable electricity sales are defined as total annual NSW

electricity sales less sales to exempt emission-intensive trade-exposed activities.

Taking this into account, the ESS target defined as a proportion of total annual

NSW electricity sales and as a proportion of total annual liable sales is set out in

Table 7.

Table 7: ESS target

Calendar year Effective scheme target

(% of annual

NSW electricity sales)

Retailer compliance obligation

(% of annual

liable electricity sales)

2009 (from 1 July) 0.4 % 0.5 %

2010 1.2 % 1.5 %

2011 2.0 % 2.5 %

2012 2.8 % 3.5 %

2013 3.6 % 4.5 %

2014 – 2020 4.0 % 5.0 %

Source: ESS web site. Available at: http://www.ess.nsw.gov.au/about/scheme_structure.asp

Cost of obtaining ESCs

The cost of obtaining ESCs is the price at which ESCs are traded. This is

determined by the supply of and demand for ESCs.

The difficulty with forecasting the price at which ESCs are traded is that there is

significant uncertainty about the supply side of the market. A large number of

energy efficiency projects are cost-saving in themselves. In the absence of any

http://www.ess.nsw.gov.au/about/scheme_structure.asp



barriers to the take-up of cost-saving energy efficiency projects, these projects

should be adopted without a scheme such as the ESS: energy users should not

require the additional incentive provided by selling ESCs to encourage the

adoption of these projects. The fact that cost-saving energy efficiency projects

are not necessarily adopted indicates that there is some barrier to their take-up.

The ESS is designed to overcome these barriers.60

Because the ESS is designed to overcome the barriers to the take-up of energy

efficiency projects, rather than to subsidise the costs of energy efficiency projects,

estimating the price at which ESCs will trade is very difficult. The price of ESCs

will likely be driven by the cost of overcoming the barriers to the take-up of

energy efficiency projects, which is far more difficult to estimate than would be

the cost to subsidise energy efficiency projects. The absence of a historic ESCs

prices makes the task more difficult still.

For these reasons, Frontier Economics has adopted the penalty price of the ESS

as a proxy for the price of ESCs. The penalty price will act as a cap on the price

of ESCs. The penalty price of the scheme is $24.50/MWh,61 which is equivalent

to an after-tax price of $35.00/MWh.

7.3.2 Cost of complying with the ESS

Based on the energy savings targets set out in Table 7 and the ESS penalty price

of $35.00/MWh, the cost of complying with the ESS is set out in Table 8.

60 The ESS web site states that the ESS was designed to overcome barriers to the take-up of energy

efficiency projects, including:

● the time and cost of getting reliable information about making energy savings;

● absence of specialist companies which are able to provide reliable information and make

energy saving easy and affordable; and

● split incentive between landlords and tenants where building owners bear the cost of

energy efficiency improvements such as air conditioning or lighting, but are not motivated

to do so because tenants will receive the benefits in lower electricity bills.

61 The penalty price is in 2009/10 dollars and will escalate with CPI.



Table 8: Cost of complying with the ESS (real 2009/10)

Year Cost of complying with ESS

($/MWh)

2010/11 $ 0.70

2011/12 $ 1.05

2012/13 $ 1.40



Ancillary services costs and market fees

8 Ancillary services costs and market fees

In addition to estimating the energy purchase cost allowance for the period of the

determination, Frontier Economics‟ scope of work also includes estimating a

range of other energy-related costs that Standard Retailers will face over the

period of the determination.

This section considers the costs that Standard Retailers will face as a result of the

following:

ancillary services costs; and

market fees.

8.1 Ancillary services costs

Ancillary services are those services used by AEMO to manage the power system

safely, securely and reliably. Ancillary services can be grouped under the

following categories:

Frequency Control Ancillary Services (FCAS) are used to maintain the

frequency of the electrical system

Network Control Ancillary Services (NCAS) are used to control the voltage

of the electrical network and control the power flow on the electricity

network, and

System Restart Ancillary Services (SRAS) are used when there has been a

whole or partial system blackout and the electrical system needs to be

restarted

AEMO operates a number of separate markets for the delivery of FCAS and

purchases NCAS and SRAS under agreements with service providers. AEMO

publishes historic data on ancillary services costs on its web site.

8.1.1 Approach to estimating ancillary services costs

To estimate the future cost of ancillary services, Frontier Economics has

conducted statistical analysis of the past levels and movements of ancillary

services costs. The objective has been to determine whether statistical models of

past levels and movements of ancillary services costs provide sufficient

explanatory power to predict future ancillary services costs.

This approach to estimating the future cost of ancillary services is consistent with

the approach adopted by Frontier Economics for the 2007 determination. For

that determination, it was found that statistical model of movements in ancillary

services costs had sufficient explanatory power to predict future ancillary services

costs.



8.1.2 Results of ancillary services costs

A time series of weekly ancillary services costs for market customers in the NEM

is set out in Figure 35. The data in Figure 35 incorporates the costs of FCAS,

NCAS and SRAS.

Figure 35: Historic weekly ancillary services costs (nominal)

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50

15

/06

/20

03

15

/09

/20

03

15

/12

/20

03

15

/03

/20

04

15

/06

/20

04

15

/09

/20

04

15

/12

/20

04

15

/03

/20

05

15

/06

/20

05

15

/09

/20

05

15

/12

/20

05

15

/03

/20

06

15

/06

/20

06

15

/09

/20

06

15

/12

/20

06

15

/03

/20

07

15

/06

/20

07

15

/09

/20

07

15

/12

/20

07

15

/03

/20

08

15

/06

/20

08

15

/09

/20

08

15

/12

/20

08

15

/03

/20

09

15

/06

/20

09

15

/09

/20

09

NEM

an

cill

ary

serv

ice

co

sts

($

/MW

h)

Source: AEMO

Consistent with the 2007 determination, Frontier has forecast ancillary services

costs using a simple time-series regression. The model regresses the log of weekly

NEM ancillary service costs (in real 2009/10 dollars) on a constant, a time trend

and two structural breaks. The model has the following parametric form:

In the 2007 determination, Frontier noted that the historical NEM ancillary

services data appeared to exhibit a structural break at week 28 of 2005 (week

starting 3 July 2005). For the 2010 determination, in addition to this structural

break, Frontier has included a second structural break at week 39 of 2008 (week

starting 21 September 2009).

The model ultimately chosen to forecast NEM ancillary services costs was the

most statistically robust of a range of models that were considered, each using

slightly different specifications and parameters. Both of the structural breaks

included in the chosen model are statistically significant at a confidence level of



0.1 per cent, while the model‟s over-all explanatory power (as measured by its R2)

is 0.425.

Outlined in Figure 37 below is a chart of historic weekly ancillary services costs

(in real 2009/10 dollars), the fitted values of the chosen forecasting model and

forecast weekly ancillary services costs up to the end of financial year 2012/13.

Figure 36: Forecast weekly ancillary services costs (real 2009/10)

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50

15

/06

/20

03

15

/12

/20

03

15

/06

/20

04

15

/12

/20

04

15

/06

/20

05

15

/12

/20

05

15

/06

/20

06

15

/12

/20

06

15

/06

/20

07

15

/12

/20

07

15

/06

/20

08

15

/12

/20

08

15

/06

/20

09

15

/12

/20

09

15

/06

/20

10

15

/12

/20

10

15

/06

/20

11

15

/12

/20

11

15

/06

/20

12

15

/12

/20

12

15

/06

/20

13

NEM

an

cial

lry

serv

ice

s co

sts

($2

009

/10

, $/M

Wh

)

AS costs ($2009/10) AS costs - fitted ($2009/10) AS costs - forecast ($2009/10)

Source: AEMO, Frontier Economics

Forecast weekly ancillary services costs were converted to forecast annual

ancillary services costs by taking an arithmetic average across forecast financial

years. The approach adopted by Frontier Economics to forecasting ancillary

services costs results in an allowance for ancillary services costs over the period

of the current determination as set out in Table 9.



Table 9: Ancillary services costs (real 2009/10)

Year Ancillary services costs

($/MWh)

2010/11 $ 0.43

2011/12 $ 0.43

2012/13 $ 0.43


8.2 Market fees

Market fees are charged to participants in the NEM in order to recover the cost

of operating the market.

The market fees charged to participants are based on the budgeted revenue

requirements of AEMO (previously NEMMCo). The revenue requirements are

based on the operational expenditures of AEMO (previously NEMMCo) and are

divided into the following categories:

general fees, and

FRC fees

8.2.1 Approach to estimating market fees

Market fees are set out on AEMO‟s website. Generally, operational expenditure

is relatively stable, with the result that market fees are also relatively stable.

Market fees for 2007/08 through 2009/10 are available on AEMO‟s website. To

forecast market fees for 2010/11 through 2012/13, Frontier Economics has

applied a simple liner trend to the sum of general fees and FRC fees. Historic and

forecast market fees are set out in Figure 37.



Figure 37: Annual market fees (real 2009/10)

$0.00

$0.05

$0.10

$0.15

$0.20

$0.25

$0.30

$0.35

$0.40

2007/8 2008/9 2009/10 2010/11 2011/12 2012/13

NEM

fee

s ($

/MW

h, $

20

09/1

0)

General ($2009/10) FRC $(2009/10) Total ($2009/10)

Source: AEMO and Frontier analysis.

Note: Total fees are the sum of general fees and FRC fees.

8.2.2 Results of market fees

The linear trend approach to forecasting market fees results in an allowance for

market fees over the period of the current determination as set out in Table 10.

Table 10: Market fees (real 2009/10)

Year Market fees

($/MWh)

2010/11 $ 0.37

2011/12 $ 0.37

2012/13 $ 0.37



Periodic review

9 Periodic review

As part of the 2007 determination, IPART conducted an annual review of the

market-based energy purchase cost. Under the annual review, regulated tariffs

were reset if an annual review found that there was a change in the forecast cost

of supplying electricity in greater than the materiality threshold of 10 per cent.

The intention of the annual review was to address the risks associated with a step

change in the market-based energy purchase cost during the period of the

determination.

The terms of reference for the 2010 to 2013 determination require IPART to

allow for a periodic review of the energy purchase cost allowance, including the

cost of complying with greenhouse and energy efficiency schemes. As part of

Frontier Economics‟ scope of work, IPART has asked for Frontier Economics

views on the periodic review process. As part of the public consultation process

for the current determination, IPART has invited submissions on the scope, the

frequency and the materiality threshold for the periodic reviews.

A clear benefit of periodic reviews is that they provide an opportunity to reset

regulated tariffs in circumstances in which outcomes in the market diverge from

those that are forecast as part of the determination of regulated tariffs. Periodic

reviews therefore promote the outcome of cost-reflective regulated tariffs, and

the efficiencies associated with that outcome. However, periodic reviews come at

a cost, including the reduction in regulatory certainty for businesses and

customers and the costs of undertaking the periodic reviews and implementing

any required changes. Decisions about the design of the periodic review can

usefully be informed by consideration of factors that are important to the

determination of the energy purchase cost allowance. In this sense, Frontier

Economics‟ advice on the energy purchase cost allowance can provide useful

context for decisions about the design of the periodic review. Given this, this

section considers the design of the periodic review, including:

key uncertainties for the current determination of the energy purchase cost

allowance

implications for the scope of the periodic review

implications for the frequency of the periodic review, and

implications for the materiality threshold for the periodic review

9.1 Key uncertainties

In addition to the general uncertainty associated with input assumptions used for

modelling the energy purchase cost allowance (as discussed in Section 9.2),

estimating the energy purchase cost allowance for the current review is subject to


Periodic review

two more particular uncertainties: the NSW Government‟s Energy Reform

Strategy and the introduction of the CPRS.

9.1.1 Energy Reform strategy

In November 2008 the NSW Government announced the Energy Reform

Strategy. The Energy Reform Strategy is intended to implement systematic

reforms to the energy sector in NSW. Key elements of the Energy Reform

Strategy include:

continued Government ownership and operation of existing power stations

and all electricity networks in NSW

contracting the electricity trading rights of Government-owned power

stations to the private sector, commonly referred to as the „Gentrader‟ model

selling key power station development sites in NSW, and

selling the retail arms of Country Energy, EnergyAustralia and Integral

Energy

The announced timing for the Energy Reform Strategy is for bidder data rooms

to be open from February 2010, with the transaction culminating in the receipt

and evaluation of bids by the Government later in the year. Because the Energy

Reform Strategy will not be implemented until after the conclusion of the current

determination, it is worth thinking about the extent to which the Energy Reform

Strategy, and particularly the Gentrader model, would be likely to have an impact

on the energy purchase cost allowance over the period of the determination.

The implementation of the Gentrader model, by transferring control of trading

rights from the existing Government-owned generators to the private sector, may

have an impact on outcomes in the wholesale electricity market. There are three

aspects of the Gentrader model that could potentially have an impact on Frontier

Economics‟ forecast of energy purchase costs:

Payments from Gentraders to generators. The NSW Government‟s

strategy paper62 makes it clear that the Gentraders will be responsible for the

principal variable costs faced by generators – fuel costs and carbon costs.

Since the Gentraders will be exposed to the variable costs associated with

their dispatch decisions, there is no reason to expect that Gentraders‟

dispatch decisions will vary from those they would make as owner of the

plant and therefore no reason to expect that the payments under the

Gentrader contract will imply a revision to modelling assumptions.

62 New South Wales Energy Reform Strategy, Delivering the Strategy: approach to transactions and market

structure, September 2009, Section 3.4 and 3.5.


Periodic review

The allocation of risk. The NSW Government‟s strategy paper63 makes it

clear that one of the objectives of the Energy Reform Strategy is to transfer

market risk to private sector Gentraders. Since the Gentraders will be

exposed to market risk associated with their dispatch decisions (as well as the

associated variable costs), there is no reason to expect that Gentraders‟

dispatch decisions will vary from those they would make as owner of the

plant and therefore no reason to expect that the allocation of risk under the

Gentrader contract will imply a revision to modelling assumptions.

Market structure. The identity of successful bidders for Gentrader contracts

will likely have some impact on bidding behaviour in the market. It is

impossible to know the identity of successful bidders until the sale process

has been complete, and therefore impossible to model the post-transaction

market structure with any degree of certainty. However, given that a key

objective of the Energy Reform Strategy is to ensure competitive market

outcomes,64 and given that the ACCC is unlikely to clear any transaction that

would be expected to have a significant impact on prices, a reasonable

approach is to assume the existing industry structure for the purposes of the

Draft Determination and Final Determination for each year of the regulatory

period, but to revisit market structure as part of the periodic reviews for

2011/12 and 2012/13.

9.1.2 CPRS

Significant work has been undertaken over the last several years to progress the

introduction of an emissions trading scheme in Australia. In particular, the

Commonwealth Government has released a Green Paper65 and a White Paper66

on the design of an emissions trading scheme, and has subsequently developed

the CPRS legislative package. The CPRS legislative package was introduced to

the House of Representatives in May 2009 and passed by the House of

Representatives in June 2009. However, in August 2009 the Senate voted against

the CPRS Bills. The CPRS Bills have since been re-introduced, with a second

Senate vote currently expected in late November 2009, but this could be delayed.

Because of the ongoing negotiation on the CPRS, there is uncertainty about both

the design of the CPRS and the timing of the introduction of the CPRS.


structure, September 2009, Section 3.5.


structure, September 2009, Section 1.1.

65 Australian Government, Carbon Pollution Reduction Scheme Green Paper, July 2008.

66 Australian Government, Carbon Pollution Reduction Scheme: Australia’s Low Pollution Future, December

2008.


Periodic review

Assuming the design of the CPRS remains fundamentally as proposed, the key

uncertainty that will impact on the current determination relates to the date of

the introduction of the CPRS and the carbon price that is likely over the period

of the current determination.67 The uncertainty associated with the carbon price

is discussed in more detail in Section 9.2.

9.2 Scope of the periodic review

9.2.1 Submissions from stakeholders

In responding to IPART‟s Draft Methodology Paper, stakeholders offered different

views on the scope of the periodic reviews. Generally, stakeholders were

supportive of a broader review than undertaken as part of the current

determination.

9.2.2 Frontier Economics’ view

Frontier Economics considers that, in thinking about the scope of the periodic

reviews, it is useful to think about the framework within which energy costs

should be considered. The terms of reference for the current determination

require calculation of both LRMC and the market-based energy purchase cost.

There are a number of input assumptions that are common to modelling of the

LRMC and the market-based energy purchase cost. For this reason, in order to

have a consistent approach to modelling the LRMC and the market-based energy

purchase cost, both should be incorporated into the periodic review. Given that

the volatility allowance is one of the outputs from the modelling undertaken to

determine the market-based energy purchase cost, and will vary depending on

outcomes of that modelling, Frontier Economics considers that it would be

appropriate to incorporate the volatility allowance in the periodic review.68

In order that the periodic review provides a reasonable view of LRMC and

market-based energy purchase cost at the time of the periodic review, Frontier

Economics considers that the modelling should incorporate updated input

assumptions where they are readily available, subject to the objective of using

publicly-available and industry-standard input assumptions in the interests of

transparency. The Modelling methodology and assumptions report provided an

overview of the input assumptions that are most material to Frontier Economics‟

estimate of the energy purchase cost allowance. For each of these input

assumptions, it is worth considering the extent to which more up-to-date and

67 Depending on the extent to which the carbon price in Australia is determined in a global market, the

target under the CPRS may be an important determinant of the carbon price.

68 IPART‟s terms of reference requires that the periodic review also consider the costs of complying

with greenhouse and energy efficiency schemes.


Periodic review

relevant information is likely to become available over the period of the current

determination:

Standard Retailers’ regulated load. For the purposes of estimating the

energy purchase cost allowance (both LRMC and market-based energy

purchase costs) the key input is the shape of the Standard Retailers‟ regulated

load. In the short-term, this load shape is driven to a large extent by weather

conditions: hotter summers and colder winters are likely to result in a peakier

load shape and, therefore, a higher energy purchase cost allowance. While an

additional year of data for the Standard Retailers‟ regulated load shape can

provide useful additional information on which to forecast the regulated load

shape for future years, historical data suggests that trends over time in the

regulated load shape are not particularly strong. Given this, and given that

updating forecasts of Standard Retailers‟ regulated load is a substantial

exercise, Frontier Economics considers that there are good reasons for

retaining the original regulated load forecasts for the purposes of modelling

for the periodic reviews.

System load. Forecasts of system load are important in forecasting spot

prices, and therefore contract prices. Forecasts of system load can move

significantly from year to year, which can have an impact on modelling

results. System load forecasts are updated annually, based on updated

information on economic and market conditions. Given this, and given that

publicly-available and industry-standard forecasts of system load tend to be

updated on a regular basis, Frontier Economics considers that it would be

appropriate to use updated forecasts of system load, where available, for the

purposes of modelling for the periodic reviews.

Generators’ capital costs. Estimates of generators‟ capital costs are

important for estimating LRMC. Estimates of generators‟ capital costs can

move significantly over the period of a determination, which can have an

impact on modelling results. Given this, and given that publicly-available and

industry-standard estimates of generators‟ capital costs tend to be updated on

a regular basis, Frontier Economics considers that it would be appropriate to

use updated estimates of generators‟ capital costs, where available, for the

purposes of modelling for the periodic reviews.

Generators’ fuel costs. Estimates of generators‟ fuel costs are important for

estimating LRMC and forecasting spot prices. Estimates of generators‟ fuel

costs can move significantly over the period of a determination, which can

have an impact on modelling results. Given this, and given that publicly-

available and industry-standard estimates of generators‟ fuel costs tend to be

updated on a regular basis, Frontier Economics considers that it would be

appropriate to use updated estimates of generators‟ fuel costs, where

available, for the purposes of modelling for the periodic reviews.


Periodic review

Carbon prices. Estimates of carbon prices for 2012/13 are important for

estimating LRMC and forecasting spot prices. Forecasts of carbon price for

2012/13 are likely to move significantly over the next few years. This will

reflect both increased clarity on the design and implementation of the CPRS,

and an improved understanding of the carbon price likely to result from the

introduction of the CPRS. While the extent to which publicly-available and

industry-standard forecasts of carbon prices will become available over the

next few years remains uncertain, it is very likely both that updated carbon

price forecasts will become available and derivative markets for carbon will

emerge. Given this, Frontier Economics considers that it would be

appropriate to use updated estimates of carbon prices, where available, for

the purposes of modelling for the periodic reviews.

Generation control, generators’ bidding strategies and generators’

contract levels. While bidding control over generation assets is generally

public information, generators‟ bidding strategies and generators‟ contract

levels cannot be publicly observed. Frontier Economics develops these

assumptions on the basis of its experience in the electricity industry.

However, assumptions about contract levels, in particular, can be informed

by cost modelling. For these reason, to the extent that other input

assumptions are updated for the purposes of modelling for the periodic

reviews, Frontier Economics considers that it would also be appropriate to

update input assumptions on generation contract and to revisit assumptions

on generators‟ bidding strategies and generators‟ contract levels.

9.3 Frequency of the periodic review

9.3.1 Submissions from stakeholders

In responding to IPART‟s Draft Methodology Paper, stakeholders were generally

supportive of undertaking periodic reviews more frequently than on an annual

basis after the introduction of CPRS.

9.3.2 Frontier Economics’ view

Frontier Economics considers that, in thinking about the timing of periodic

reviews, it is important to think about the opportunities that retailers have to

hedge their wholesale energy costs.

Retailers have generally commented that they enter into hedging contracts to

manage their exposure to spot prices over a number of years leading up to the

start of a contract year. Ultimately, retailers tend to hedge a substantial

proportion of their load, which is consistent with outcomes towards the

„conservative‟ end of the efficient frontier.


Periodic review

Retailers are able to hedge their exposure to spot prices because there is a liquid

wholesale market for hedging contacts (while markets for exchange-traded

contracts, such as d-cyphaTrade contracts, are not necessarily liquid beyond a

year or two, hedging contracts can also be traded directly between parties). By

determining the energy purchase cost allowance on the basis of an efficient

hedging strategy, the determination provides for the cost that retailers face in

hedging their risk, but also provides incentives for efficient contracting by

retailers.

This intertemporal contracting behaviour by retailers is important for generators

to help them manage their risks. Generators face considerable fixed costs but

earn highly volatile spot revenues. Contracting for longer periods is crucial to

help them finance these fixed costs. If retailers have incentives to contract for

shorter periods to manage the stranding risk of longer term contracts, generators

will face greater revenue uncertainty. This will increase risks for generators which,

in presence of a distinctly more uncertain environment due to the CPRS, will

create material financing problems for generators.

Therefore, in deciding how frequently to review energy purchase costs it is

important to consider the effect this has on retailers‟ incentives to hedge their

costs into the future, which in turn affects the ability of generators to manage

their risks in the market. This has become a more critical matter with the looming

introduction of the CPRS, which will significantly and adversely affect the

position of many generators. It is important that frequent periodic reviews do not

exacerbate the generators risk profile by increasing the difficulties they face in

securing their preferred contracting profile over time.

This is not to suggest that Frontier Economics does not support periodic

reviews, rather it suggests that the scope of them be clearly defined and that they

are not too frequent.

9.4 Materiality threshold for periodic reviews

There are efficiency benefits to ensuring that regulated electricity tariffs are

reflective of the costs of supplying electricity. These benefits are best achieved by

resetting regulated electricity tariffs whenever a periodic review finds that the

forecast costs of supplying electricity have changed. In other words, these

benefits are best achieved if there is no materiality threshold for periodic reviews.

On the other hand, a materiality threshold will ensure that retailers still have an

incentive to manage costs. IPART needs to weight the importance of the

incentives to manage costs against the retailers ability to influence costs and the

extent to which prices need to be cost reflective.

In addition there are costs associated with to resetting regulated electricity tariffs

that need to be considered:


Periodic review

There are costs to consumers and the regulated businesses due to a loss of

regulatory certainty. In particular, evidence suggests that consumers prefer

contracts at fixed prices. Providing for frequent periodic reviews, and having

no materiality threshold, exposes consumers to more frequent price changes,

and

There are costs to the regulated businesses of giving effect to a change in the

regulated tariff. While regulated tariffs will need to be changed at the

beginning of each financial year to give effect to changes in network tariffs,

giving effect to changes in the regulated tariffs at other times (for instance, on

six-monthly intervals) will create costs for the retailers

Considering these costs there are likely to be some benefits to having some

materiality threshold that must be met before a change in forecast costs give rise

to a change in regulated tariffs under a periodic review.


Summary of advice

10 Summary of advice

Frontier Economics has calculated the cost to an efficient standard retailer of

supplying the Standard Retailers‟ regulated load using two approaches:

a stand alone, cost-based approach to estimate the LRMC of supplying the

Standard Retailers‟ regulated load; and,

a market-based approach to estimate the market-based energy purchase cost,

including a volatility allowance.

Frontier has also estimated a number of other costs, including:

GGAS costs

MRET costs

ESS costs

Ancillary services costs, and

Market fees

Combining these other costs with each of the LRMC and the market-based

energy purchase cost enables the determination of the total energy cost

(excluding losses). Consistent with the terms of reference, the energy purchase

cost allowance will be based on the market-based energy purchase cost, with the

LRMC providing a floor to the energy purchase cost allowance. Given this,

Figure 38 provides a comparison of each of the LRMC and the market-based

energy purchase cost, combined with the other costs set out above, both for the

Base case. Black markers have been included at the level of the maximum value

for each year, for each retailer, in line with the terms of reference. These black

markers denote the value of the total energy cost (excluding losses). For the first

two years of the determination the LRMC results in higher estimates for the Base

case, and therefore sets the total energy cost for those years. In the final year of

the determination the market-based energy purchase cost associated with the

conservative point is higher, and therefore sets the total energy cost for that year.


Summary of advice

Figure 38: Total energy costs (excluding losses) (real 2009/10)


Appendix A – Modelling results


This appendix presents the numerical results presented in the figures in the body

of the report.

LRMC and market-based energy purchase costs

Table 11 presents both the LRMC and market-based energy purchase costs for

the Base and No CPRS cases. These results reflects:

for LRMC, the total fixed and variable costs, including carbon, of the

optimal mix and dispatch of plant as determined by WHIRLYGIG; and,

for market-based energy purchase costs, the total pool and contract

purchase cost associated with hedging the regulated load plus the volatility

allowance.

Table 11: LRMC and market-based energy purchase cost results

FinYear Business LRMC Market-based energy

purchase costs

Base No CPRS Base No CPRS

2011 CE $61.71 $61.71 $42.27 $42.22

EA $66.30 $66.30 $44.21 $44.13

IE $68.43 $68.43 $45.91 $45.82

2012 CE $69.14 $61.58 $68.06 $57.10

EA $73.00 $65.38 $71.56 $60.35

IE $75.81 $68.29 $74.13 $62.52

2013 CE $81.69 $61.50 $95.24 $59.83

EA $84.90 $64.66 $97.85 $61.99

IE $88.21 $68.25 $103.76 $65.61


Breakdown of market-based energy purchase costs



Table 12 presents a breakdown of the market-based energy purchase cost results

into the pool and contract purchase costs and the volatility allowance for the

Base, No CPRS and CPRS 15 cases.

Table 12: Breakdown of Market results

FinYear Business Pool and contract costs Volatility premium Total

Base No

CPRS

CPRS 15 Base No

CPRS

CPRS

15

Base No

CPRS

CPRS 15

2011 CE $41.82 $41.80 $41.82 $0.45 $0.42 $0.45 $42.27 $42.22 $42.27

EA $43.83 $43.82 $43.83 $0.37 $0.32 $0.37 $44.21 $44.13 $44.21

IE $45.52 $45.50 $45.52 $0.38 $0.32 $0.38 $45.91 $45.82 $45.91

2012 CE $67.33 $56.43 $67.33 $0.73 $0.67 $0.73 $68.06 $57.10 $68.06

EA $70.79 $59.68 $70.79 $0.78 $0.67 $0.78 $71.56 $60.35 $71.56

IE $73.25 $61.78 $73.25 $0.88 $0.74 $0.88 $74.13 $62.52 $74.13

2013 CE $94.56 $59.40 $103.98 $0.68 $0.43 $0.73 $95.24 $59.83 $104.70

EA $97.26 $61.62 $106.72 $0.59 $0.37 $0.63 $97.85 $61.99 $107.35

IE $102.95 $65.16 $112.94 $0.81 $0.46 $0.88 $103.76 $65.61 $113.82




Full results

Table 13 shows the full results for both the LRMC and market-based energy

purchase costs for the Base case only. Results are presented for energy69, volatility

premium, GGAS, REC, ESS, ancillary fees and NEM fess.

Table 13: Full results for the Base case

Framework FinYear Business Energy Volatility GGAS REC ESS Ancillary NEM

Fees

Total

LRMC 2011 CE $61.71 $0.00 $0.00 $1.78 $0.70 $0.43 $0.37 $64.99

EA $66.30 $0.00 $0.00 $1.78 $0.70 $0.43 $0.37 $69.57

IE $68.43 $0.00 $0.00 $1.78 $0.70 $0.43 $0.37 $71.71

2012 CE $69.14 $0.00 $0.00 $2.16 $1.05 $0.43 $0.37 $73.15

EA $73.00 $0.00 $0.00 $2.16 $1.05 $0.43 $0.37 $77.02

IE $75.81 $0.00 $0.00 $2.16 $1.05 $0.43 $0.37 $79.82

2013 CE $81.69 $0.00 $0.00 $2.55 $1.40 $0.43 $0.37 $86.44

EA $84.90 $0.00 $0.00 $2.55 $1.40 $0.43 $0.37 $89.64

IE $88.21 $0.00 $0.00 $2.55 $1.40 $0.43 $0.37 $92.96

Market 2011 CE $41.82 $0.45 $0.00 $1.78 $0.70 $0.43 $0.37 $45.54

EA $43.83 $0.37 $0.00 $1.78 $0.70 $0.43 $0.37 $47.48

IE $45.52 $0.38 $0.00 $1.78 $0.70 $0.43 $0.37 $49.18

2012 CE $67.33 $0.73 $0.00 $2.16 $1.05 $0.43 $0.37 $72.07

EA $70.79 $0.78 $0.00 $2.16 $1.05 $0.43 $0.37 $75.57

IE $73.25 $0.88 $0.00 $2.16 $1.05 $0.43 $0.37 $78.15

2013 CE $94.56 $0.68 $0.00 $2.55 $1.40 $0.43 $0.37 $99.99

EA $97.26 $0.59 $0.00 $2.55 $1.40 $0.43 $0.37 $102.60

IE $102.95 $0.81 $0.00 $2.55 $1.40 $0.43 $0.37 $108.50


69 Fixed and variable costs for the LRMC approach, pool and contract purchase costs for market.



Changes to REC price

In order to understand how these changes to the estimate of the LRMC of

meeting the expanded RET relate to outcomes in the broader energy market,

Table 14 compares the estimate of the total energy purchase cost from this final

report with those from the draft report. This demonstrates that the impact of the

increase in the REC component on total energy costs is small:

In the first two years of the determination, when the LRMC approach is

higher than the market approach, the effect of the increase in the REC

cost is offset by the reduction in the black component (due to updating

WACC and the cost amortisation). This is not unexpected, given the

relationship between the estimate of the black component of LRMC and

the estimate of the LRMC of meeting the expanded RET. In this case the

greatest change is an increase of 0.28 per cent for Country Energy.

In the final year, when the market approach is higher overall, the effect of

the increase in the REC cost is not offset by any changes to black costs

(which do not change in the market approach). In this case the greatest

change is an increase of 1.09 per cent for Country Energy.



Table 14: Impact of changes to REC price

Framework FY Business Final Draft % change

LRMC 2011 CE $64.99 $64.92 0.10%

EA $69.57 $69.68 -0.15%

IE $71.71 $71.87 -0.23%

2012 CE $73.15 $72.95 0.28%

EA $77.02 $76.97 0.06%

IE $79.82 $79.83 -0.02%

2013 CE $86.44 $85.90 0.63%

EA $89.64 $89.23 0.46%

IE $92.96 $92.62 0.36%

Market 2011 CE $45.54 $44.76 1.75%

EA $47.48 $46.70 1.68%

IE $49.18 $48.40 1.62%

2012 CE $72.07 $71.12 1.34%

EA $75.57 $74.63 1.27%

IE $78.15 $77.20 1.23%

2013 CE $99.99 $98.79 1.21%

EA $102.60 $101.40 1.18%

IE $108.50 $107.31 1.11%



Appendix B – Modelling results using d-cyphaTrade

contract prices

Appendix B – Modelling results using d-

cyphaTrade contract prices

In addition to using spot and contract prices forecast using SPARK to determine

the market-based energy purchase cost, Frontier Economics has also used d-

cyphaTrade prices to determine the market-based energy purchase cost.

Frontier Economics have used d-cyphaTrade forward prices for quarterly, peak

and offpeak swaps taken from the d-cyphaTrade website on 9 October 2009.

Caps contracts were not used because forward prices did not exist for the entire

period of the determination (no trades in 2012/13) and because prices presented

large arbitrage opportunities when compared to swap prices.

Modelling using the d-cyphaTrade prices was performed using the approach set

out in Section 5.2.1. The only difference was that rather than scaling the price

profile shapes to the forecast SPARK pool prices, the price profile shapes were

scaled to the d-cyphaTrade prices such that the d-cyphaTrade price were at a 5%

premium. This ensured a premium that was consistent with the analysis

performed using the SPARK forecast prices.

The d-cyphaTrade forward prices as of 9 October 2009 are presented in Table

15. The market-based energy purchase costs are presented in Figure 39, with the

LRMC and market-based energy purchase costs using the Frontier Economic

pool price forecast included for comparison. In both cases the market-based

energy purchase costs include the volatility allowance.



contract prices

Table 15: d-cyphaTrade swap prices

CalYear Quarter Peak Offpeak

2010 3 $53.15 $25.69

4 $54.50 $24.34

2011 1 $84.15 $25.15

2 $54.00 $25.60

3 $59.75 $30.02

4 $58.00 $32.95

2012 1 $78.25 $68.47

2 $48.25 $54.88

3 $49.00 $49.36

4 $43.00 $55.50

2013 1 $78.25 $92.30

2 $48.25 $60.79

Source: d-cyphaTrade, 9/10/2009 (http://d-cyphatrade.com.au/)

The d-cyphaTrade forward prices are higher than the Frontier Economics

forecasts in 2010/11, lower in 2011/12 and then lower again in 2012/13. In

2012/13 it appears that the full cost of the CPRS is not being priced into the

forward curve. The market-based energy purchase cost calculated using the d-

cyphaTrade prices show the same relativities when compared to the market-

based energy purchase costs using the Frontier Economics spot and contract

prices.

http://d-cyphatrade.com.au/



contract prices

Figure 39: Results for d-cyphaTrade forward prices



Appendix C – Modelling results using example load

shapes

Appendix C – Modelling results using

example load shapes

Frontier Economics has performed two sample calculations of the market-based

energy purchase cost for the purpose of illustrating the methodology for

stakeholders.

The first sample calculation, which was also included in the draft report, is a

forward looking estimation of the energy cost of hedging a hypothetical load

shape. This example allows stakeholders to observe how Frontier Economics'

forecast prices are correlated with system demand and the regulated load shape.

The shape used in this example is weighted average of the load forecasts

submitted by the Standard Retailers for the expected volatility case.

The second example is a backward looking estimation of the energy purchase

cost for the Net System Load Profile for each of the Standard Retailers using

historic NSLP and NSW price data for calendar year 2008. This example allows

stakeholders to see Frontier Economics' framework applied to publically

available data.

Spreadsheets containing all data and the energy costs calculations for both

examples have been released in conjunction with this report.

Forward looking, hypothetical load shape

example

This sample calculation utilises a hypothetical regulated load shape. The

hypothetical regulated load shape is constructed as a weighted average regulated

load shape, where the average is taken across the regulated loads of the three

Standard Retailers for the expected volatility case. The reason that a weighted

average load shape has been used is to protect the confidential nature of each

individual Standard Retailers‟ regulated load. The weightings used to construct

the average load shape will not be made public.

Using a weighted average of the regulated load shapes ensures that the example

shape remains properly correlated to the system load shape and resultant pool

prices, as discussed in Section 5.2.1. The purpose of this example is to allow

stakeholders to observe how prices and loads are correlated.

In determining the peak demand for the hypothetical load shape Frontier

Economics has assumed a co-incident peak across the three Standard Retailers.

That is, Frontier Economics has aligned the peak half hour for each retailer and


then taken a weighted average.70 This assumption is conservative to the extent

that it is equivalent to assuming that all three Standard Retailers peak for the

same half hour. For the results presented in Section 5.2 and for the NSLP

example presented below no such assumption needs to be made as energy costs

are determined for each Standard Retailer individually rather than for some

combination of all three.

Results are presented here for the efficient frontier, contract volumes and

market-based energy purchase cost. Accompanying this report is a spreadsheet

containing the half-hourly weighted average regulated load shape, half-hourly

system load, half-hourly NSW price and contract volumes, so that participants

can analyse the results of Frontier Economics‟ modelling in more detail.

In the results presented below there are three differences between what is

presented for the hypothetical load relative to the analysis performed on the

Standard Retailers‟ regulated load shapes:

The load shape used is a weighted average across the three Standard

Retailers‟ for the expected volatility case that was submitted.

Only a single load/price pair, the expected volatility case, has been

optimised in STRIKE. For the Standard Retailers, three load/price pairs

were optimised simultaneously for each retailer71.

Peak load is taken to be co-incident across the three Standard Retailers in

constructing the hypothetical load shape.

Efficient frontiers

The efficient frontiers for the hypothetical case are presented for each year in

Figure 40 to Figure 42. The efficient frontiers for the Standard Retailers have

been included for the purpose of comparison. The efficient frontier for the

hypothetical case is consistently less risky at the conservative (left most) end. This

reflects the fact that the model is only optimising over a single load/price pair in

this case. In terms of cost, the hypothetical case has a cost within the range of the

costs for the Standard Retailers, consistent with the hypothetical case using a

weighted average of the loads used in the other cases.

70 As opposed to taken a weighted average on the half hour and then determining the peak so that the

diversity of peak demand across the three Standard Retailers is accounted for.

71 As discussed in Section 5.2.



shapes

Figure 40: Efficient frontiers for hypothetical case - 2010/11




Contract volumes

Figure 43 to Figure 45 present by year the optimal contract volumes for the

hypothetical case at the most conservative point on the efficient frontier.

Volumes are broken down into swap and cap components by quarter and

peak/offpeak. The average and peak load for the hypothetical case are included

for each segment to aid analysis.

Generally, the optimal position involves being hedged between average and peak

load with swaps. In peak times, additional cap cover is included to bring the

volume roughly to peak levels. In some cases, notably Q4 in 2011/12 and

2012/13, the offpeak contract volume is higher than the peak contract volume.

This is consistent with historic outcomes and reflects quarters where peak

electricity demand occurs on a weekend, which is categorised as offpeak.



shapes

Figure 43: Contract volumes for the hypothetical case - 2010/11





Figure 46 shows the market-based energy purchase costs for the hypothetical

case, compared to the market-based energy purchase costs for each of the

Standard Retailers. Again, consistent with the hypothetical case using a weighted

average of the load from the other cases, the market-based energy purchase costs

lie in between the results from the other cases.



shapes

Figure 46: Energy purchase costs for the hypothetical case

Backward looking, NSLP load shape example

This sample calculation utilises the historic NSLP load shape and historic NSW

prices for calendar year 2008.

Using the historic NSLP and NSW price data allows stakeholders to examine the

results of Frontier Economics' approach when applied to publically available

data. Both load and price data were downloaded from AEMO.72 Frontier has

confirmed that the load in the NSLP file is on a kWh basis. Frontier have

converted this to MW and only considered the load for the three Standard

Retailers. No other manipulation of the load data has been undertaken.

Results are presented here for the efficient frontier, contract volumes and

market-based energy purchase cost. Accompanying this report is a spreadsheet

containing the half-hourly NSLP load shape, half-hourly NSW price and contract

volumes, so that participants can analyse the results of Frontier Economics‟

modelling in more detail.

In the results presented below the only differences between what is presented for

this example relative to the analysis performed on the Standard Retailers‟

regulated load shapes is that only a single load/price pair, the actual historic data,

72 NSLP data for 2008 can be found at http://www.aemo.com.au/electricityops/nslp_datafiles/700-

0602.zip and NSW price data at for 2008 can be found at

http://www.aemo.com.au/data/aggPD_2006to2010.html#2008.


has been optimised in STRIKE. For the Standard Retailers, three load/price pairs

were optimised simultaneously for each retailer.73

Efficient frontiers

The efficient frontiers for the historic NSLP case are presented for 2008 for each

Standard Retailer in Figure 40. Time weighted average pool prices for NSW

where around $40/MWh in nominal terms for 2008. Calculated energy purchase

costs were at a premium to the average pool prices, at the conservative point this

cost is around $50/MWh. 2008 was not especially volatile in NSW and the risk

on the portfolio is fairly low.

Figure 47: Efficient frontiers for the historic 2008 NSLP case

Contract volumes

Figure 43 to Figure 50 present the optimal contract volumes for the historic

NSLP case at the most conservative point on the efficient frontier for each

Standard Retailer. Volumes are broken down into swap and cap components by

quarter and peak/offpeak. The average and peak load for the hypothetical case

are included for each segment to aid analysis.

Generally, the optimal position involves being hedged between average and peak

load with swaps. In peak times, additional cap cover is included to bring the

73 As discussed in Section 5.2.



shapes

volume roughly to peak levels. In some cases, Q4 for CE and EA, the offpeak

contract volume is comparable to the peak contract volume. This is consistent

with historic outcomes and reflects quarters where peak electricity demand

occurs on a weekend, which is categorised as offpeak.

Figure 48: Contract volumes for the historic 2008 NSLP case - CE


Figure 49: Contract volumes for the historic 2008 NSLP case - EA

Figure 50: Contract volumes for the historic 2008 NSLP case - IE



shapes


Figure 46 shows the market-based energy purchase costs for the historic NSLP

case.

Figure 51: Energy purchase costs for the historic 2008 NSLP case


FRONTIER ECONOMICS NETWORK

BRISBANE | MELBOURNE | SYDNEY | BRUSSELS | COLOGNE | LONDON | MADRID

Frontier Economics Pty Ltd 395 Collins Street Melbourne Victoria 3000

Tel: +61 (0)3 9620 4488 Fax: +61 (0)3 9620 4499 www.frontier-economics.com

ACN: 087 553 124 ABN: 13 087 553 124

http://www.frontier-economics.com/

Documents

Energy purchase costs - IPART · including any plant that would be required to meet any regulatory obligation. 1.3 This report This final report sets out Frontier Economics‟ advice