Risk managing cost-effective decarbonisation of the power ... · The Modelling • A new approach...

Risk managing cost-effective decarbonisation of the power sector

in Germany

FINAL RESULTS

April 2013

This project is funded by the European Climate Foundation

1E3G ‐ Third Generation Environmentalism

• Objectives and the methodology

• Baseline analysis results

• Sensitivity analysis results

• New baselines based on Increased Ambition

• Annex – Assumptions and modelling

Contents

E3G ‐ Third Generation Environmentalism

2

Objectives of the analysis


3

The Modelling

• A new approach is needed to move the debate from least cost decarbonisation to cost‐effective risk managed delivery of policy objectives. This model puts greater emphasis on uncertainty and risks than traditional equilibrium models which tend to focus only on finding a least‐cost solution to a given set of constraints

• The Investment Decision Model developed by Redpoint is an agent‐basedinvestment model. It realistically captures investor behaviour by assuming no perfect foresight: Investors are considered to take decisions based on their expectations of returns according to their knowledge of the future at a given time, assuming a five‐year market foresight.

• Focuses on the resilience and robustness of the decarbonisation pathways against unforeseen changes in key market drivers, electricity demand, natural gas prices, RES and CCS deployment.

• A similar analysis was carried out for Great Britain and Poland to represent different Member States’ circumstances and reflect European‐wide issues


4

Overview of the baseline scenarios


5

Two baseline policy scenarios reflect competing approaches to delivering power sector decarbonisation in line with the power sector carbon target of 95 MtCo2 pa in 2030 based on

the Leitstudie 2011A scenario.

Carbon Prices in the baseline scenariosTechnology Support Scenario

– RES‐E subsidy continues post 2020

– Carbon price trajectory of the EC’s Energy Roadmap 2050

Carbon Price Scenario

– Carbon price is the single driver of decarbonisation

– RES‐E subsidy stops in 2015 – no further development of supply chains

Technology Support and Carbon Price baseline scenarios were stress tested against a range of uncertainties

N.B. Further details of the underlying assumptions can be found in Annex


6

Germany high level conclusions (1/2)

• German policy must simultaneously deliver decarbonisation, security, and affordability objectives. Our analysis shows that policies designed to manage future risks and uncertainties are able to meet this requirement.

• There remains significant on‐going potential for coal to gas switching and steady deployment of renewables which increase resilience against failures to deliver electricity efficiency and CCS capacity.

• The carbon price is an effective driver in increasing or reducing power sector carbon emissions. However, the analysis assumed that lignite and hard‐coal plants can continue to operate at low‐load factors and this might not be technically feasible without significant investment. Technical constraints of this nature will make the impact of carbon price on emissions less predictable and introduce discontinuities.


7

Germany high level conclusions (2/2)

• If the carbon price was the single driver of decarbonisation, i.e. renewable subsidies stopped in 2015, the market would deliver gas as the least cost option with the exception that CCS could be fitted at some point in the future. However, failures to deploy CCS would mean that very high carbon prices would be required to quickly attract significant level of renewable energy.

• German decarbonisation policy places high significance on improved energy efficiency, especially in buildings. As a consequence, if Germany fails to deliver electrical efficiency, an early phase‐out of lignite and hard‐coal plants and replacement with gas will be required to compensate for increased power sector emissions. At the same time, the ability for the power sector to compensate for efficiency failures in other sectors will require more extensive deployment of low‐carbon technologies.

• Low energy demand scenarios provide higher system resilience against the risk of high power sector costs and failures to deploy CCS capacity. Thus managing energy demand is central to deal with uncertainties and secure the delivery of decarbonisation targets.


8






Contents


9

Where technology are supported low carbon capacity is deployed continuously, while in the Carbon Price Scenario decarbonisation is driven by gas in 2020s


10

Carbon Price Scenario baselineCumulative new build (GW)

Technology Support Scenario baselineCumulative new build (GW)

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

20

40

60

80

100

120

Cum

ulat

ive

New

Bui

ld -

GW

SolarOffshore WindOnshore WindBiomassGTOilHydro / PSGas CCSCoal CCSLignite CCSGasCoalLigniteNuclear

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

20

40

60

80

100

120

Cum

ulat

ive

New

Bui

ld -

GW


In the Carbon Price Scenario, there is no renewables build beyond 2015. New build consists of unabated gas plant and lignite CCS coming online from 2025

Unabated gas capacity remains a significant part of the capacitymix in the Carbon Price Scenario


11

Carbon Price Scenario baselineGeneration capacity (GW)

Technology Support Scenario baselineGeneration capacity (GW)

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

50

100

150

200

250

Cap

acit

y -G

W


2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

50

100

150

200

250

Cap

acit

y -G

W


While coal, lignite and nuclear capacity is replaced by solar and offshore wind, gas capacity does not change and CCS capacity is not required

Unabated gas capacity increases while hard‐coal is squeezed out of the market due to the higher carbon price

Unabated hard-coal and lignite is replaced with offshore wind and gas

Carbon Price Scenario baselineGeneration Mix (TWh)

Technology Support Scenario baselineGeneration Mix (TWh)

12

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SolarOffshore WindOnshore WindBiomassGTOilHydro / PSGas CCSCoal CCSLignite CCSGasCoalLigniteNuclearDemand

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SolarOffshore WindOnshore WindBiomassGTOilHydro / PSGas CCSCoal CCSLignite CCSGasCoalLigniteNuclearDemand


Despite significant reductions, lignite and, to a certain extent, unabated hard‐coal remain in the mix up to 2030 and CCS capacity is not required

Unabated gas increases its share of the generation mix significantly, as a result of the higher carbon price and CCS capacity is required

Carbon emissions reduction follow a fairly linear path in both scenarios


13

Carbon Price Scenario baselineEmissions by fuel (mn tonnes CO2)

Technology Support Scenario baselineEmissions by fuel (mn tonnes CO2)

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

50

100

150

200

250

300

mn

tonn

es C

O2

SolarOffshore WindOnshore WindBiomassGTOilHydro / PSGas CCSCoal CCSLignite CCSGasCoalLigniteNuclearTarget Line

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

50

100

150

200

250

300

mn

tonn

es C

O2

SolarOffshore WindOnshore WindBiomassGTOilHydro / PSGas CCSCoal CCSLignite CCSGasCoalLigniteNuclearTarget Line

Cumulative emissions are slightly higher in the Carbon Price Scenario as most low‐carbon capacity is only commissioned in the 2020s.

Power sector costs are higher in Technology Support Scenario-baseline


14

Carbon Price Scenario baselineBreakdown of power sector costs, € bn 2012-30

cumulative

Technology Support Scenario baselineBreakdown of power sector costs, € bn 2012-30

cumulative

Wholesale costs are lower where technologies were supported compared to where carbon price was the only driver for investment


15

Carbon Price Scenario Wholesale costs, € bn 2012-30

Technology Support ScenarioWholesale costs, € bn 2012-30






Contents


16


17

Carbon Price ScenarioRequired carbon price (€/tCO2)

Ranges of carbon prices

(52 to 150 €/tCO2)

Coal to gas switching option allows carbon price to be an effective instrument, but failure to deploy CCS and high demand almost double required carbon price

High demand and failure to deploy CCS (due to cost or policy/technology failure)

requires much higher carbon prices to achieve policy

objectives


18


Required carbon price in Carbon Price Scenario to meet power sector decarbonisation target

High demand and failure to deploy CCS (due to cost or policy/technology failure)

requires much higher carbon prices to achieve policy

objectives


19

Technology Support ScenarioAnnual CO2 Emissions (mn tonnes CO2)

Carbon Price ScenarioAnnual CO2 Emissions (mn tonnes CO2)

Renewables deployment produces steady abatement with more predictable delivery

Renewables deployment produces steady abatement with more predictable delivery


20

Technology Support ScenarioCarbon intensity (g/kWh)

Carbon Price ScenarioCarbon intensity (g/kWh)


21

Total power sector costs - Impact of sensitivities (1/2)

Carbon Price ScenarioPower sector costs, € bn 2012-30, cumulative

Technology Support ScenarioPower sector costs, € bn 2012-30, cumulative

Costs are more resilient to uncertainty especially to higher electricity demand and higher gas price volatility

Costs increase significantly if electricity demand is higher than expected. Costs increase even further when unexpected higher electricity demand is combined with failure of CCS deployment

Total power sector costs are more predictable where technologies are supported (2/2)


22

Cost range+11% to -5%

Overall power sector costs can go up by 11% in the case that electricity demand is higher than expected

Overall powers sector costs can go up by 18% when electricity demand is higher than expected and CCS fails to be deployed


Technology Support ScenarioPower sector costs, € bn 2012-30, cumulative

Carbon Price ScenarioPower sector costs, € bn 2012-30, cumulative

Wholesale costs are more resilient to uncertainties and show lower cost risks where technologies are supported


23


Carbon Price ScenarioWholesale costs, € bn 2012-30, cumulative

Technology Support ScenarioWholesale costs, € bn 2012-30, cumulative

Overall wholesale costs can go up by 20% e.g. when electricity demand is higher than expected

Overall wholesale costs go up by 48% e.g. when electricity demand is higher than expected and CCS fails to be deployed

Large gas demand uncertainties, in particular in Carbon Price Scenario, raise questions as to the level of new investment required in gas infrastructure (1/2)


24

Technology Support ScenarioPower sector gas consumption (bcm)

Carbon Price ScenarioPower sector gas consumption (bcm)

Future value of new gas investments remains uncertain


25

Technology Support ScenarioPower sector gas consumption (bcm)

Carbon Price ScenarioPower sector gas consumption (bcm)

Power sector gas consumption – Impact of sensitivities (2/2)


26

Technology Support ScenarioNew gas capacity (GW)

Carbon Price ScenarioNew gas capacity (GW)

Range ofnew gas build

New gas capacity - Impact of sensitivities (1/2)

Similar to results regarding gas consumption in the power sector, new built gas capacity shows large variation under different scenarios and sensitivities


27

New gas capacity - Impact of sensitivities (2/2)

Technology Support ScenarioNew gas capacity (GW)

Carbon Price ScenarioNew gas capacity (GW)

Generation in Carbon Price Scenario –Impact of sensitivities (1/2)

28

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

Shifting Momentum

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SM - High Demand

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SM - Low Demand

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SM - High Gas

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SM - High Demand - Low CCS

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SM - Low Demand - Low CCS

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SM - Low Gas

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SM - High Demand EFF

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

SM - Low CCS


Carbon Price baseline

Generation in Carbon Price Scenario –Impact of sensitivities (2/2)

29

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

SM - HighCCS

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

SM - Expensive CCS

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

SM - Lignite Load Factor

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

SM - Increased Ambition

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

SM - High OffW ind

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

SM - Low OffW ind


Generation in Technology Support Scenario -Impact of sensitivities (1/2)

30

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

Policy Momentum

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

PM - High OffW Ind

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

PM - Low OffW ind

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

PM - High Gas

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

PM - High Demand

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

PM - Low Demand

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

PM - Low Gas

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

PM - High Demand EFF

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-TW

h

PM - Low CCS


Technology Support baseline

31

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

PM - High CCS

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

PM - Lignite Load Factor

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

PM - Increased Ambition

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

PM - High OffW ind

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

PM - Low OffW ind

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

700

Gen

erat

ion

-T

Wh

Policy Momentum


Generation in Technology Support Scenario -Impact of sensitivities (2/2)






Contents


32

Increased Ambition –Carbon intensity of 100 g/kWh and 50g/kWh


33

700//

Driving Increased Ambition through only carbon price would require unsustainably high carbon prices


Delivery of doubling ambition to 100 g/kWh would require higher deployment of RES and CCS gas


34

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

Gen

erat

ion

-T

Wh

Technology Support– Increased Ambition (100 g) Generation mix (TWh)

Carbon Price– Increased Ambition (100 g)Generation mix (TWh)

SolarOffshore windOnshore WindBiomassOilGTHydro / PSGas CCSCoal CCSLignite CCSGasCoalLigniteNuclear


• Coal and lignite phased out and replaced by a significant increase in unabated and CCS‐gas instead of CCS‐lignite

• CCS‐gas becomes part of the mix• Lignite and coal are significantly

pushed out• Higher deployment of

renewables

Matching UK ambition would require near phase out of coal/lignite, deployment of CCS and offshore wind

35

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 -

100

200

300

400

500

600

Gen

erat

ion

-TW

h

Technology Support– Increased Ambition (50 g) Generation mix (TWh)

Carbon Price– Increased Ambition (50 g)Generation mix (TWh)

• Very high deployment of renewables would be needed to meet the target

• Need both CCS‐gas and lignite

• Very high deployment of renewables would be needed to meet the target

• Higher ambition and very high carbon prices push out most fossil‐fuel based generation

• CCS‐gas instead of CCS‐lignite becomes economical



Increasing ambition costs more, but additional power sector costs are less significant where RES was supported


36

Technology Support Scenario baselinesPower sector costs, € bn 2012-30 annual

Carbon Price Scenario baselinesPower sector costs, € bn 2012-30 annual

Overall, additional cost of higher ambition is €121 to 391bn between 2012‐30

Overall, additional cost of higher ambition is €20 to 49bn between 2012‐30 and is cheaper than the CPS

Wholesale costs soar under Carbon Price when ambitions are increased


37

Technology Support Scenario baselinesWholesale costs, € bn 2012-30 annual

Carbon Price Scenario baselinesWholesale costs, € bn 2012-30 annual

Increasing ambition would increase gas consumption in general


38

Carbon Price Scenario baselinesPower sector gas consumption (bcm)

Technology Support Scenario baselinesPower sector gas consumption (bcm)

• Gas consumption increases more than 50% to deliver 100 g/kWh policy objective

• On the contrary, delivering 50 g/kWh would require less gas consumption as significant renewables replace lower emission fossil fuel gas

Gas consumption increases about 33‐50% to deliver increased ambition






Contents


39

Redpoint Investment Decision Model (IDM)

• The Redpoint IDM constructs detailed market outlooks in the GB power market covering the period of 2012‐2030.

• The IDM is based on an agent simulation engine that aims to mimic players’ decision‐making with regards to their investment decisions in new plant as well as their decisions to retire existing plants.

• The model contains a list of potential new‐build projects according to their size, cost and earliest possible year of operation. Total investment in a particular technology is limited by the technology’s maximum annual and cumulative build constraints. If the constraint is binding, the projects with the highest expected returns are built.

• Technology costs (capex and opex) can be varied over time and if required set endogenously within the model dependent on levels of deployment, which may affect rates of learning and position on the supply curves.

• For each year, the levelised cost of energy (LCOE) of potential new‐build projects are compared against their expected revenues (given assumed load factors, future price expectations, capacity payments and support levels) and where costs are less than expected revenues, projects are moved first to a planning stage, and subsequently, if still economic, to a committed development phase.

• Additionally, retirement decisions for existing plants are also made on the basis of near term profitability expectations.

• A 5‐year forward‐looking view for investing in a new plant is assumed and a 1‐year forward‐looking view for plant retirement decisions.

• Where applicable, the model can include full representation of Contracts for Difference (CfDs) and a universal capacity mechanism.

40E3G ‐ Third Generation Environmentalism

Investment modelling – Non perfect foresight

• The model has a 5 year forward view of commodity prices and demand supply (1)

• Rolling through each year, the model estimates power prices and dispatch for the forward view horizon. The resulting expected gross margin is compared to the expected levelised costs (2).

• On that basis the model decides whether a project should enter the planning stage (3) and then rolls forward to the next year (4). During planning the project can still be cancelled. Once the planning period is over the model will decide whether to move to the construction phase at which point the project is committed.


41

Generator decisions: new build and retirement

• Generator build decisions: For new plants the levelised non‐fuel cost includes capital costs and annual fixed costs. The gross margin is calculated as the expected margin from power revenues, capacity payments and financial support less fuel and carbon costs and non‐fuel variable costs. There are two trigger points which a project must pass to progress to construction. If a project is “in the money” it enters planning. If it continues to be in the money at the end of the planning period, the project is committed to the construction phase, and will become operational after a defined number of years.

• Generator retirement decisions: The logic for closure decisions of existing generators is analogous to that for new investments. The key difference, however, is that the capital already invested is ignored as this is considered to be a sunk cost. As a result, total annual fixed costs are compared against the expected gross margin and, when these are higher for a pre‐defined number of years, the plant retires.

42

Expected gross margin

Forward looking stack +

prices

Anticipated low carbon support

Capital and fixed O&M

costs

Expected transmission

charges

Expected levelised non-

fuel costs

Planning Under Construction OperationalCommit

Compare

Trigger 1 Trigger 2

Anticipated capacity

payments

Expected gross margin

Forward looking stack +

prices

Fixed O&M costs

Expected transmission

charges

Expected fixed costs

Plan closure Close

Compare

Trigger 1 Trigger 2

Anticipated capacity

payments


The model allowed policy intervention to correct deviation from the policy objective


43

• High demand + low CCS ‐> Increased carbon price to €150/t and push out all lignite and hard‐coal generation• Low CCS; Expensive CCS; High demand; High electricity demand (low efficiency) ‐> Increased carbon price between 90€/t and €100/t• Low demand + low CCS ‐> Increased carbon price only to €75/t

Over delivery

Carbon Price scenario

• Low demand; Low gas price; High CCS ‐> Increased carbon price only to €65/t or maintained baseline carbon price

Technology Support scenario

Over delivery

• High demand; Low offshore wind ‐> Increased offshore wind (between 30 and 35 GW by 2030)

• High electricity demand (low efficiency) ‐> Subsidy for lignite‐CCS

• Low demand; Low gas price; High offshore wind ‐> Reduced offshore wind deployment rate

Capital cost assumptions


44

Nuclear CCGT Gas CCS Coal & Lignite CCS

Onshore Wind Biomass Solar PV

2011 3582 703 1335 2837 912 2005 33162015 3451 692 1273 2700 912 1943 28242020 3287 678 1196 2528 911 1866 22092025 3236 653 1058 2219 903 1850 17912030 3184 629 920 1910 895 1833 1372

Offshore Wind (Low)

Offshore Wind (Base)

Offshore Wind (High)

2011 2142 2535 29642015 1933 2288 26752020 1672 1979 23142025 1602 1896 22172030 1532 1813 2120

Capital costs (£/kW, real 2011)

• All capital costs except offshore wind are based on the Energy Roadmap 2050

• Offshore wind capital costs (Base/High/Low) are based on the study by ARUP for DECC

• The costs evolve over time reflecting learning curves and economies of scale. In particular solar and CCS are not yet mature technologies and can therefore follow steep learning curves.

Long run marginal cost of electricity assumptions in baseline scenarios

45

Nuc

lear

CC

GT

CC

GT

CC

SC

oal C

CS

Lign

iteLi

gnite

CC

SO

nsho

re W

ind

Offs

hore

Win

d

Nuc

lear

CC

GT

CC

GT

CC

SC

oal C

CS

Lign

iteLi

gnite

CC

SO

nsho

re W

ind

Offs

hore

Win

d

Nuc

lear

CC

GT

CC

GT

CC

SC

oal C

CS

Lign

iteLi

gnite

CC

SO

nsho

re W

ind

Offs

hore

Win

d

2012 2020 2030

0

20

40

60

80

100

120

140

160

180

200

LRM

C (€

/MW

h -r

eal 2

011)

CarbonFuelVOMFixedCapital

The chart on the right shows the development LRMC of various technologies, split into their various components.


Other cost assumptions

46

Technology Hurdle Rate Variable Operating & Maintenance (€/MWh)

Fixed costs (% of capital costs)

Gas 8.2% 1.40 3.0%

Coal 9.0% 2.50 3.0%

Lignite 9.0% 3.50 3.0%

Gas CCS 12.0% 3.50 3.0%

Coal CCS 12.0% 5.50 3.0%

Lignite CCS 12.0% 5.50 3.0%

Nuclear 11.5% 5.00 2.0%

Onshore W ind 9.0% 0.40 4.0%

Offshore W ind 11.0% 0.40 5.5%


Baseline commodity prices

• The Base commodity prices are based on the 450 scenario from the IEA World Energy Outlook 2011.

• Where applicable, the lignite fuel price is assumed to be 1.7 €/GJ (real 2011) throughout the modelling horizon.

47

2011 2013 2015 2017 2019 2021 2023 2025 2027 20290

10

20

30

40

50

60

70

80

90

100

110

120

130

curr

/uni

t -r

eal 2

011

ARA Coal ($/t) Brent Oil ($/bbl) Gas ($/mmbtu) EUA Carbon (€/t)


Gas price shocks were introduced overnight with no foresight for beginning or ending of the event

• Baseline gas price is based on the 450 scenario from the IEA World Energy Outlook 2011.

• High and low gas price shocks are 75% higher or lower than the baseline price.

• Gas price shocks introduced overnight in early 2020s and lasts for 4‐5 years

0

20

40

60

80

100

120

2011 2013 2015 2017 2019 2021 2023 2025 2027 2029

Base

Low Shock

High Shock

Gasprice ‐p/therm (real


46

Electricity demand: baseline and sensitivity assumptions


49

HIGH DEMAND

BASELINE DEMAND

LOW DEMAND

• Overall electricity demand is 490 TWh. This is based on the Leitstudie 2011A scenario (incl. ca 25 TWh demand for electric vehicles and 10 TWh for hydrogen production). The Leitstudie scenario is consistent with the government’s long term target of a 25% reduction in electricity demand by 2050 compared to 2008.

• Overall electricity demand is 575 TWh. This was due to a combination of failing to deliver demand reductions in the domestic, SME and industrial sectors (only half of the demand assumed in the Leitstudie 2011A is realised). In addition there is higher demand from electric vehicles compared to baseline (ca. 56 TWh in 2030). The additional EV demand is consistent with the Leitstudie 2011C scenario which specifically looks at higher long term electrification of the transport sector in Germany.

• Overall electricity demand is 441 TWh. This is also based on the Leitstudie 2011A demand but with no demand from electric vehicles or for hydrogen production.

Investment decisions were taken with the expectation of base electricity demand but then were subject to higher or lower electricity demand

• Investment decisions were made with the expectation of a base demand. The model illustrates how uncertain demand development works.

• Every five years, investors readjust their expectations in line with a base demand (red) trajectory (green and purple dotted lines); however, the demand remains higher or lower than their expectations (yellow and blue lines). For example:

– In the High Demand case, the expectation in 2015 follows the green dashed line, although outturn demand follows the yellow line.

– In 2019 expectations still follow the downward path (smaller green dashed line).

– In 2020 expectations are reset but again follow the downward gradient as illustrated by the green dashed lines.

• This 5 year cycle continues throughout the modelling horizon.

Germany - Annual electricity demand trajectories


48

2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030400

450

500

550

600

650

700

Ann

ual E

lect

rici

ty D

eman

d -T

Wh

LowBaseHighBase-LowBase-High

• High deployment: 50% higher than the baseline deployment (ca. 30 GW by 2030)

• Baseline: No CCS built under Technology Support scenario baseline; Max. 15 GW of combined CCS capacity across all fuels (gas, hard‐coal, lignite) in Carbon Price scenario baseline

• Low deployment: CCS technology fails a year into construction of the first commercial plant and there is no subsequent CCS deployment.

Technology deployment assumptions and maximum levels

51

CCS

Onshore wind• High deployment: maximum potential of 50 GW by 2030

• Baseline: Capacity is currently ca. 30GW. Maximum potential of 45 GW by 2030

• Low deployment: maximum potential of 40 GW by 2030

• High deployment: maximum potential of 35GW by 2030

• Baseline: as per government target trajectory of 10GW by 2020 and 25GW by 2030.

• Low deployment: no further offshore wind build beyond the 10 GW in 2020

• Consistent with current government policy we assume that existing nuclear plants are phased out as planned an there is no new nuclear build

Offshore wind

Nuclear


Risk managing cost-effective decarbonisation of the power ... · The Modelling • A new approach...

Documents

Transcript of Risk managing cost-effective decarbonisation of the power ... · The Modelling • A new approach...