Graduation presentation final

Graduation

presentation

DEVELOPING

ATTRACTIVE POWER

PLANT PORTFOLIOS

UNDER CO2-PRICE

UNCERTAINTY

1

In t roduct ion

Prob lem descr ip t ion , background and re levance

Research quest ion & approach

S imulat ion model

Scenar ios

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S imulat ion Resul ts : per fec t in format ion

Simulat ion resul ts : uncer ta in future

Conclus ions

OUTLINE

2

Vattenfall

Power generating company

Active in North-West Europe

Electricity and CO2-market

model

I n t roduct ion



S imulat ion model

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Conclus ions

INTRODUCTION

3

CO2-market as a measure to decrease greenhouse gas emissions.

Affects production costs of electricity.

How should the electricity market deal with CO2-costs

In t roduct ion

P rob lem descr ip t ion , back ground and re levance


S imulat ion model

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Conclus ions

PROBLEM DESCRIPTION

4

“Insight needs to be gained

in long-term CO2-prices and

how they may affect

investments from power

generating companies.”

In t roduct ion



S imulat ion model

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Conclus ions

PROBLEM STATEMENT

5

CO2-costs Coal

CO2-costs Gas

In t roduct ion



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BACKGROUND: COSTS OF

ELECTRICITY

6

Cost of Nuclear

Cost of Coal

Cost of Gas

Po

we

r p

rice

Electricity

price

Electricity

Demand

Capacity installed

New

electricity

price

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S imulat ion model

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Conclus ions

CO2-PRICES AND

INVESTMENTS

7

CO2-price

Power plant

investment

Changing power plant

portfolio

CO2-demand

Electricity

demand

Emission

cap

Fuel

prices

Other

mechanisms

affecting

investment

“How do uncertain CO2-

prices affect the

attractiveness of power plant

portfolios for power

generating companies in

West- and Middle Europe?”

In t roduct ion



S imulat ion model

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Conclus ions

RESEARCH QUESTION

8

1. Exploring of possibilities of the delivered simulation model

2. Developing a framework for identifying attractive portfolios

3. Experimenting

In t roduct ion



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RESEARCH APPROACH

9

Markowitz (1952): A

portfolio is attractive when

it is a good trade-off

between return and risk.

Translated into: Attractive

portfolios provide a high

potential return and low

regret.

In t roduct ion



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FRAMEWORK:

ATTRACTIVE PORTFOLIOS

10

In t roduct ion



S imula t ion mode l

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Conclus ions

SIMULATION MODEL:

11

In t roduct ion



S imula t ion mode l

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SIMULATION MODEL:

12

Out:

Long term:

Optimal capacity

expansion plan

Short term:

CO2-prices

Electricity prices

Cash flows of

power plants

In:

Existing

technology mix

Fixed penetration

of renewables

Electricity

demand

Fuel price

assumptions

Emission cap

development

Costs of potential

new builds

Constraints in

new builds

Several plausible futures created

Only differentiating on three factors, rest is fixed:

Electricity demand

Emission cap

Fuel prices

In t roduct ion



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Conclus ions

SCENARIOS

13

In t roduct ion



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SCENARIOS (2)

14

In t roduct ion



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Conclus ions

SIMULATION

15

1st set of runs:

Identification of optimal technology mixes for the 2014-2035 period

Perfect information assumed

2nd set of runs:

What happens when the future that occurs is different than expected by the market?

Higher gas prices

Nuclear wind and CCS

Tight Emission cap No

OCGT, more CCS, wind (and

nuclear)

Higher electricity demand

more total capacity &

relative more CCGT, wind,

CCS (and nuclear)

In t roduct ion



S imulat ion model

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Conclus ions

1ST SET OF RUNS:

PORTFOLIOS DEVELOPED

16

CO2-prices will probably grow higher than they currently are.

Perfect market knowledge:

CO2-prices could grow somewhere between 46 and 87 euro/ton.

Companies benefit from situations with high electricity demand and a tight emission cap.

However: There is no perfect market knowledge!!

In t roduct ion



S imulat ion model

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S imula t ion Resu l ts : per fec t in fo rmat ion


Conclus ions

CO2-PRICES AND POWER

PLANT PROFITABILITY

17

In t roduct ion



S imulat ion model

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Simula t ion resu l ts : uncer ta in fu ture

Conclus ions

2ND SET OF RUNS:

CO2-PRICES

18

Prepares for low electricity demand, a loose emission cap and low gas prices Gas technologies + little CCS

technology

Potential for high returns in situations of scarcity. This leads to higher prices

Least investment costs, no regret from overinvestment

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THE MOST ATTRACTIVE

PORTFOLIO:

19

Power generating companies

can best be reserved in their

investments.

This helps them avoiding

regret of making unnecessary

costs, but can also lead to

very high returns.

In t roduct ion



S imulat ion model

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ATTRACTIVE PORTFOLIOS

FOR POWER GENERATORS

20

In t roduct ion



S imulat ion model

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WRAP UP: WHY A CO2-

MARKET?

21

EU: CO2-market should

lead to lower

emissions.

CO2-market should

lead to cost-

ef fective

investments.

Market: CO2-prices are an

extra uncertainty to

deal with carefully.

We don’t invest

until we know what

wil l happen.

Potential Effects:

High electricity prices

High CO2-prices

Supply interruptions

“Introduction of a market

based mechanism might not

have been the best option to

decrease greenhouse gas

emissions.”

In t roduct ion



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22

PERSONAL OPINION

23

QUESTIONS?

24

EXTRA SLIDES

BACKGROUND: EU ETS

25

Emission

Certificate:

1 Ton of

CO2

In t roduct ion



S imulat ion model

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RELEVANCE: PRICE

VOLATILITY

26

RESEARCH APPROACH

Model

under-

standing

Investment

related

theories

Framework to

determine

attractive

portfolios

Attractive

portfolios

Simulation to

identify

attractive

portfolios

Design of

experiments

Uncertainties

surrounding

CO2-prices 27

𝑀𝑖𝑛: 𝑐𝑖 ,𝑡 ∗ 𝑔𝑖 ,𝑡 +𝑓𝑖 ,𝑡 ∗ 𝑔𝑖 ,𝑡 + 𝑉

𝑡

𝑜𝐿𝐿 ∗

𝑡𝑖

𝑈𝑆𝐸𝑡

Equilibrium model which can be asked to solve:

Optimal investments over a longer period of time.

Optimal allocation of CO2 emission allowances depending on

a specific emission-cap.

Optimal hour to hour dispatch of power generators.

MODEL EXPLANATION

28

Scenario 1 Scenario 2 Maximum

return:

Alternative 1 100 105 105

Alternative 2 102 104 104

Alternative 3 20 20.1 20.1

29

MEASUREMENT OF MAXIMUM RETURN

30

MEASUREMENT OF MAXIMUM REGRET

Scenario 1 Scenario 2 Maximum

regret

Alternative 1 2 0 2

Alternative 2 0 1 1

Alternative 3 82 84.9 84.9

PORTFOLIOS IDENTIFIED

31

P1: Tight cap,

high

demand,

low gas

prices

P2: Tight cap,

low

demand,

low gas

prices

P3: Middle cap,

high

demand,

low gas

prices

P4: Middle cap,

low

demand,

low gas

prices

P5: Low cap,

high

demand,

low gas

prices

P6: Low cap,

high

demand,

low gas

prices

7 GW 0 GW 1.2 GW 0 GW 0 GW 0 GW

3 GW 2.3 GW 3 GW 0 GW 0 GW 0 GW

55 GW 14 GW 50 GW 9 GW 41 GW 9.6 GW

0 GW 0 GW 7.5 GW 6.2 GW 19.7 GW 95 GW

0 GW 0 GW 0 GW 0 GW 0 GW 0 GW

//upload.wikimedia.org/wikipedia/commons/8/84/Dual-cycle.jpg

PORTFOLIOS IDENTIFIED

(2)

32

P7: Tight cap,

high

demand,

high gas

prices

P8: Tight cap,

low

demand,

high gas

prices

P9: Middle

cap, high

demand,

high gas

prices

P10: Middle

cap, low

demand,

high gas

prices

P11: Low cap,

high

demand,

high gas

prices

P12: Low cap,

high

demand,

high gas

prices

16.3 GW 4.8 GWW 10.1 GW 0 GW 4.3 GW 0 GW

5.3 GW 3 GWW 3 GW 2.3 GW 3 GW 0 GW

3.5 GW 11.3 GW 35 GW 9.9 GW 36.9 GW 7.7 GW

5.4 GW 0 GW 12.8 GW 3 GW 19.2 GW 7.7 GW

8 GW 0 GW 8 GW 0 GW 0 GW 0 GW

//upload.wikimedia.org/wikipedia/commons/8/84/Dual-cycle.jpg

ELECTRICITY PRICES:

33

In t roduct ion



S imulat ion model

Scenar ios

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Conclus ions

2ND SET OF RUNS:

RETURN AND REGRET

34

Re

turn

Regret

Uncertain market developments and policy making may have strong effects on the investment behavior of power generating companies.

In absence of clarity power generators can be expected to be reserved in their investments.

The extreme electricity prices this may cause has major effects on society.

ADDITIONAL

CONCLUDING REMARKS

35

Documents

Graduation presentation final