Constrained Access Modelling - WA · outlooks for electricity demand in the WEM, including: Annual energy and seasonal peak demands Uptake of rooftop PV, behind-the-meter battery

Constrained Access Modelling

Methodology and Assumptions

Consultation Public Forum

13 March 2018

© 2018 Ernst & Young, Australia. All Rights Reserved. Liability limited by a scheme approved under Professional Standards Legislation.

Page 2 Copyright © 2018 Ernst & Young Australia. All Rights Reserved. Liability limited by a scheme approved under Professional Standards Legislation

Outline

► Purpose

► Modelling overview

► Assumptions

► Scenarios

► Generator assumptions

► General feedback


Purpose

► EY is conducting wholesale market modelling to forecast the impacts of fully

constrained-access under several scenarios

► Modelling outputs include the impact on:

► Wholesale market prices

► Generator dispatch

► Generator market revenues, including capacity market revenues

► Over the public consultation process we are seeking feedback and input from

industry stakeholders into the assumptions and methodology proposed

► We will publish a final report with anonymised generator names. Generators

can apply to find out which generator they are in the published outcomes


Overview of modelling approach

► Partially constrained access:

► Only GIA-connected and new entrant generators have fully constrained access

► Other existing generators retain their firm access rights

► Fully constrained access

► All generators have constrained access

Fully constrained access

Partially constrained

access

Scenario assumptions

Report

Presenting outcomes

comparing the partially and

fully constrained cases

2022-23 to 2031-32


Modelling network constraints

► In a constrained-access market, dispatch is conducted subject to constraint

equations representing network limitations

► For this modelling, two sets of constraint equations have been developed

by Western Power and the PUO:

► One for fully constrained access

► One for partially constrained access

► Pre-defined new entrant connection points are provided in the constraint

equations to enable EY to forecast changes in the capacity mix in each

scenario



► Multi-stage process

for each scenario

► Each market

simulation involves

time-sequential half-

hourly electricity

market dispatch

modelling

Market simulation


Market simulations

Capacity market price

forecast

Generator capacity mix forecasting

PUO

determines

generator

capacity

credits

Fully constrained case

Market simulation

Partially constrained case

Western

Power and

PUO provide

constraint

equations


Feedback on modelling approach

Are there any questions or concerns on the general modelling approach?


Market simulation overview

► Each scenario is defined by the input assumptions selected


Types of assumptions


Purpose of the scenarios

► There are many factors that could influence the evolution of the wholesale

electricity market (WEM) in WA, and these factors are uncertain

► To capture a range of possible outcomes EY will conduct modelling of several

scenarios

► The intention is to capture ‘bookends’ with respect to the potential impact of

fully constrained access


Proposed scenarios

► Each June, the Australian Energy Market Operator (AEMO) publishes three

outlooks for electricity demand in the WEM, including:

► Annual energy and seasonal peak demands

► Uptake of rooftop PV, behind-the-meter battery storage and electric vehicle

► The three scenarios proposed involve different electricity demand outlooks

► Electricity demand on is a major driver of changes in the mix of installed capacity in

electricity networks, and network congestion on a half-hour basis


Proposed scenarios – common macro assumptions

► No emissions policy

► An assumed list of new entrants being installed in the WEM as part of the

national Large-scale Renewable Energy Target (LRET)

► Coal and gas fuel price projections

► Generator parameters

► Outage rates, bidding patterns, capex and opex, WACC, loss factors, etc.


Possible alternative scenariosEmissions reduction policy

► An emissions reduction policy could be applied to the WEM

► A possible target is for the WEM to achieve its pro-rata share of the Paris

agreed target by 2020


Possible alternative scenariosA very low demand outlook

► Whilst the AEMO demand forecasts capture a range of demand outlooks, a

lower demand outlook is possible due to possible industrial load closures,

energy efficiency and grid defection

0

5,000

10,000

15,000

20,000

25,000

30,000

Ope

ratio

nal e

nerg

y (G

Wh

p.a.

sen

t-ou

t)

High Expected Low

► What might a very

low demand

scenario look like?


Feedback on the proposed scenarios

Do you agree that the demand outlook is a key driver to

explore for the impact of constrained access?

Should the PUO be exploring other assumptions in

defining the scenarios?


AssumptionsPeak demand

► EY models both the 10% probability of exceedence (POE) peak demand and

the 50% POE peak demand and presents weighted outcomes

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000A

nnua

l pea

k de

man

d (M

W)

10%

PO

E

High Expected Low


AssumptionsRooftop PV uptake

► EY models half-hourly rooftop PV based on historical satellite data at several

representative locations in the WEM

0

500

1,000

1,500

2,000

2,500

3,000C

apac

ity (

MW

)

High Expected Low


AssumptionsBehind-the-meter storage uptake

► AEMO assume that 25% of behind-the-meter storage capacity will contribute

to reducing peak demand

0

100

200

300

400

500

600

700C

apac

ity (

MW

)

High Expected Low


AssumptionsElectric vehicle uptake

0

200

400

600

800

1000

1200A

nnua

l ene

rgy

requ

ired

by E

Vs

(GW

h)

High Expected Low


AssumptionsElectric vehicle daily charge profile

► EY uses an in-house assumption on time-of-day charging from EVs

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0:30

1:30

2:30

3:30

4:30

5:30

6:30

7:30

8:30

9:30

10:3

0

11:3

0

12:3

0

13:3

0

14:3

0

15:3

0

16:3

0

17:3

0

18:3

0

19:3

0

20:3

0

21:3

0

22:3

0

23:3

0

Sca

led

char

ge p

rofil

e

Weekday Weekend


AssumptionsGas price projections

► The latest gas price forecast for the WEM is the AEMO GSOO, Dec 2017

► Gas prices impact

wholesale market prices

and the cost of gas

generation

► The gas price delta from

2016-17 to each future

year impacts on bids

► It is proposed to use the

GSOO Base gas price

trajectory for each

scenario

0

2

4

6

8

10

12

14

Gas

pric

es (

$/G

J)

High Base Low


AssumptionsNew entrant generator capital costs

► Source is from the AEMO NTNDP 2016, except EY has adjusted wind and

solar PV capex down to be more in line with recent public information

► Capital costs

trajectories will

influence the

market-driven

new entrant

capacity in each

scenario, which

will influence

congestion

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Cap

ital c

osts

(fo

r ye

ar o

f com

plet

ion)

(R

eal J

une

2016

$/k

W n

amep

late

)

Black Coal CCGT OCGT Solar PV - Fixed Solar PV - SAT Wind


AssumptionsOther macro assumptions

Assumptions Proposed value Impact on outcomes

Weighted-average cost of

capital (WACC)7.5% pre-tax real

Direct impact on annual repayments on

capex for new entrant generators.

Economic lifetimeThermal: 30 years

Renewables: 25 yearsAs above.

Available capacity factor for

renewable generation

Existing units:

as per historical generation

New entrants:

Wind (north country): 44%

Wind (rest of WEM): 39%

Solar PV: as modelled

Impact on dispatch patterns and new

entrant commercial viability


AssumptionsRetiring generators by 2022

Project Capacity (MW) Region Reason

KWINANA_GT1 20.8 OCGT

Announced by Synergy

MUJA_G1 (Muja A) 55 Black Coal

MUJA_G2 (Muja A) 55 Black Coal

MUJA_G3 (Muja B) 55 Black Coal

MUJA_G4 (Muja B) 55 Black Coal

MUNGARRA_GT1 37.2 OCGT



WEST_KALGOORLIE_GT2 38.2 Distillate

WEST_KALGOORLIE_GT3 24 Distillate


AssumptionsNew entrant development by 2022

Project Capacity (MW) Region Type

Byford Solar 30 Kwinana Single axis tracking PV

Greenough River 2 30 North Country Single axis tracking PV

Emu Downs Solar Farm 20 North Country Single axis tracking PV

Northam Solar Project 9.9 East Country Single axis tracking PV

Badgingarra 130 North Country Wind turbine

Warradarge Stage 1 180 North Country Wind turbine

Cunderdin Solar Farm 100 East Country Single axis tracking PV

Should the PUO consider other generators to be commissioned by 2022?

► New entrants selected either have offtake agreements in place or are in

Synergy’s renewable project development plan


AssumptionsGenerator outage rates

Generator type

Full forced

outage rate

(%)

Mean time to

repair - full

(hours)

Partial forced

outage rate

(%)

Partial

derating

(%)

Mean time

to repair -

partial

(hours)

Maintenance

outage rate

(weeks per

year)

Black coal 1.72% 55.03 9.88% 26.17% 26.62 3

CCGT /

cogeneration3.02% 14.05 7.84% 29.88% 71.64 2

OCGT (natural

gas fuel)3.02% 33.55 7.84% 31.89% 10.75 1

OCGT (liquid fuel) 1.06% 33.55 5.22% 31.89% 10.75 1

Wind and solar Outages captured in the modelled capacity factor / generation profiles

Are these publically sourced outage rates reasonable?


AssumptionsOther generator parameters

Generator typeFOM ($/MW sent-

out)

VOM ($/MWh

sent-out)

Heat rate

(%, commissioned in 2022-23)

Black coal 42,073 3 41.8%

CCGT / cogeneration 10,000 7 53.6%

OCGT (natural gas fuel) 4,000 10 36.6%

OCGT (liquid fuel) 4,000 10 36.6%

Wind 45,000 0 N/A

Solar PV – fixed 25,000 0 N/A

Solar PV - tracking 30,000 0 N/A

Are these publically sourced parameters reasonable?


AssumptionsFeedback

Should the modelling consider alternative new entrant generation sources?

Generators are invited to submit appropriate assumption data for specific

generators to improve modelling accuracy.

These data needs to be able to be published.


Capacity market price modelling

► To estimate the reserve capacity price, EY will apply the formula in the latest

WEM market rules:

► Despite the PUO’s proposed mandated capacity auction in the 2024-25

capacity year, this will not be modelled explicitly, considering the absence of

specified auction design settings

RCP = MINBRCP × ′Intercept′

1 − ′Surplus′ + 0.03 × ′Slope′, BRCP × 1.1


Market modelling chart


Approach to half-hourly modelling

► To model future half-hourly demand,

wind and solar generation, EY bases

each modelled future year on

historical years

► EY proposes to use two historical

years for this modelling: 2015-16 and

2016-17.

► EY will test the robustness of the

outcomes on individual historical

years



► The methodology involves a

feedback loop where the PUO

will forecast the assigned

capacity credits while EY will

use these credits to forecast

the capacity mix

Should the modelling

consider an alternative

approach?

Market simulation


Market simulations

Capacity market price

forecast

Generator capacity mix forecasting

PUO

determines

generator

capacity

credits

Fully constrained case

Market simulation

Partially constrained case

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Documents

Constrained Access Modelling - WA · outlooks for electricity demand in the WEM, including: Annual energy and seasonal peak demands Uptake of rooftop PV, behind-the-meter battery