Transcript Dougal Burnett

Potential climate change impacts on the
economics of offshore renewable energy
portfolios
Dougal Burnett
Professor Gareth Harrison
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Today’s Agenda

Climate Change Sensitivity of 
- Resource


Offshore Wind
Wave and Others

- Levelised Costs (and risk)

- Optimal Electricity Generation Mixes


Using Mean Variance Portfolio Theory (MVPT)
ARIES Project - Marine Related Activities
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Research Question

What is the potential impact of climate change on renewable
energy resource and future optimal electricity generation
portfolio mixes in the UK?

WHY?
• All studies (to date) using ‘Mean Variance Portfolio Theory’ (MVPT)
studies assume resource output based on the characteristics of the
current climate.
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Research Flowchart
Current and future climate
scenario parameters
Conversion to technology
and placement
Cost modelling for both
current and future climate
scenarios
Optimal portfolio mix
analysis for current and
future climate scenarios
Comparison of optimal
portfolio mix for current
climate with optimal
mixes for future climate
scenarios
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Research Flowchart
Offshore Wind: An overview of the process for generation of the
‘Offshore Wind Resource Model’
Current and future climate
scenario parameters
Conversion to technology
and placement
Cost modelling for both
current and future climate
scenarios
Optimal portfolio mix
analysis for current and
future climate scenarios
Comparison of optimal
portfolio mix for current
climate with optimal
mixes for future climate
scenarios
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Offshore Wind Resource Model
Showing Winter and
Summer months for
wind and capacity
factor
Mean Wind Speed at 80m height
Current Climate (1961-1990)
Data Source HadRM3
Capacity Factor
Current climate (1961-1990)
based on VESTAS V90 3MW
Wind Turbine
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Potential Wind Farm Deployment
54 Wind Farm Locations Included:
(Operational, In Construction, Consented, In
Planning)
Installed Capacity = 47.8 GW
Overall Annual Capacity Factor = 39.2%
Overall Annual Energy Output = 164.2 TWh
Assumptions: 95% technical availability, 10% array wake loss, 2% electrical cable
loss
Installed Capacity
(GW)
Overall Baseline Capacity Factors and Energy Output – Including Losses
ANN
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
Capacity Factor (%)
39.2
47.1
46.8
44.5
39.6
34.3
29.1
26.1
29.7
37.6
43.7
46.0
46.8
Energy Output (TWh)
164.24
16.75
15.05
15.83
13.65
12.17
10.00
9.25
10.56
12.93
15.56
15.82
16.67
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Wind Climate Change Impact
Probabilistic Projected Wind Speed Change (%)
Normal Distribution
1
0.9
Format:
Value = 50% (10%, 90%)
0.2
Probability Density
1.1
10% probability of being less than 7.5
50% probability of being less than 10
90% probability of being less than 12.5
0.8
Value = 10 (7.5, 12.5)
0.7
0.15
0.6
0.5
0.1
0.4
Cumulative Probability
0.25
0.3
0.05
0.2
0.1
10%
0
2
3.6
5.2
6.8
50%
8.4
10
90%
11.6
13.2
0
14.8
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork
16.4
18th
18
and 19th April) 2012
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Impact on Offshore Wind Output
2050s and 2080s
UK Potential Offshore Wind Farm Output - Baseline and 2050s - including losses
Medium Emissions with 50%, 10% & 90% Probabilities
Energy Output (GWh)
18000
16000
14000
12000
Baseline
2050s 10
2050s 50
2050s 90
10000
8000
6000
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
UK Potential Offshore Wind Farm Output - Baseline and 2080s - Including Losses
Medium Emissions with 50%, 10% & 90% Probabilities
Energy Output (GWh)
18000
16000
14000
12000
Baseline
2080s 10
2080s 50
2080s 90
10000
8000
6000
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
DEC
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Impact on Offshore Wind Output
2050s and 2080s
•54 Wind Farm Locations Included:
•2050s – Annual Reduction of 3.4 TWh for 50%
probability level (-2.1%)
•2080s – Annual Reduction of 5.5 TWh for 50%
probability level (-3.4%)
Offshore Wind - Future Climate Energy Output
Scenario
Generated (GWh)
Change (GWh)
Baseline
164,245
2050s 10% Probability
151,774
-12,471
-7.59%
2050s 50% Probability
160,835
-3,410
-2.08%
2050s 90% Probability
168,822
4,577
2.79%
2080s 10% Probability
148,498
-15,747
-9.59%
2080s 50% Probability
158,687
-5,558
-3.38%
2080s 90% Probability
167,803
3,558
2.17%
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
Change (%)
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Other UK Resource Assessments
Wave Energy
Shetland
Onshore Wind
Solar PV
Pierson-Moskowitz
Spectrum
Orkney
Cornwall
Western Isles
Hydro Power
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Research Flowchart
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Levelised Costs 2010 & 2020
Levelised cost for offshore wind in 2020 &
Projected climate change variability
Own Calculations. Based on input parameters from (Burnett 2012; Mott MacDonald 2010; Allan et al. 2010, 2011;
IEA 2010; Ernst & Young 2011)
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Example of risk adjusted costs
An example showing risk due to fuel price variability
captured directly within the levelised cost
(a CAPM type approach)
(empirically derived using the historic price risk for coal and natural gas )
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Research Flowchart
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Mean Variance Portfolio
Theory - Background

Mean Variance Portfolio Theory (MVPT)
• Introduced by Markowitz (1952) as a tool to create efficient financial
investment portfolios

MVPT and Electricity Generation Portfolios
• Widely used in recent years to explore optimal efficient electricity generation portfolios that include
renewable energy
• First explored by Bar-Katz and Levy (1978)
• Pioneered by Shimon Awerbuch (2003, 2005, 2006, 2007…)
• (Doherty et al. 2006; Delaquil et al. 2005; Grubb et al. 2006; Jansen et al. 2004; Roques et al.
2006a; White 2007). Bazilian and Roques (2008)

Used to explore Marine Technologies in the Scotland electricity generation mix. Allan et
al. (2011)
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Mean Variance Portfolio
Theory - Background
Capitalises on the diversity between historical cost characteristics of the two
technologies (In the example the correlation of historical cost components of each
technology = -0.6)
“An efficient portfolio is where the cost is lowest for a given level of risk; or
where risk is lowest for a given cost”
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Cost – Risk Graph
2020 Projected Technology Cost – Risk Characteristics
Projected levelised costs from Burnett (2012)
Historical Risk data from Awerbuch et al. (2007) and Allan et al. (2011)
UK 2009 mix from DUKES (2011)
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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MVPT – Physical Constraints
MVPT Analysis – Physical Constraints
(External physical constraints are required to be placed on technologies when MVPT is applied to electricity generation technologies)
MVPT technology constraints for three future
scenarios
Technology
2009 UK mix (%)
Approx
Upper Constraint
2020 (%)
Upper Constraint
2050 (%)
Upper Constraint
2050 20% (%)
Gas
44.5
39
5
5
Gas & CCS
0
1
30
20
Coal
28.1
34
5
5
Coal & CCS
0
1
30
20
Nuclear
18.6
20
50
20
Onshore Wind
2.03
12.0
15
20
Offshore Wind
1.47
10
15
20
0
10
15
20
Hydro
1.41
5.0
5.0
20
Biomass
2.86
10
10
20
Wave
0
2.5
10
20
Tidal Current
0
2.5
5
20
Solar PV
0.005
2.5
10
20
Far Offshore Wind
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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MVPT Analysis on Cost-Risk
Graph
Derived MVPT efficient frontiers for the three different future constraint scenarios
(At each point on each efficient frontier is an optimal generation mix)
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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A closer look at three points on
the 2050s efficient frontier
Technology
2050 Upper
Constraints
Point A
Point B
Point C
TWh
Point A (Medium Cost & Risk) = Overall a
more diverse mix
Point B (High Cost, Low Risk) = large
renewables share and limited nuclear etc.
Point C (Low Cost, High Risk) = large
nuclear share and limited renewables
(No Offshore Wind, No Wave)
Gas
25
0
25
0
Gas & CCS
150
17.5
6.6
27.8
Coal
25
0
25
0
Coal & CCS
150
11.5
13.6
0
Nuclear
250
121.3
25.5
250
Onshore Wind
75
75
75
75
Offshore Wind
75
74.7
70.7
0
Far Offshore Wind
75
0
75
0
Hydro
25
25
8.5
25
Biomass
50
50
50
50
Wave
50
50
50
0
Tidal Current
25
25
25
25
Solar PV
50
50
50
47.2
Cost (£/MWh)
-
86
100.5
73.1
Risk (%)
-
6.0
4.3
10.4
CO2 (MT)
-
1.8
34.5
1.1
CO2 Reduction from
1990 (%)
-
99.1
83.1
99.4
Example assumes 2050 total UK electricity
generation
500 2012
TWh
th April)
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork
18th and 19=
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The cost-risk mix along the
2050s efficient frontier
Low Cost = large nuclear
share and limited
renewables
Electricity Generation
(TWh)
500
450
90
400
80
350
70
300
60
250
50
200
40
150
30
100
20
50
10
0
73.5
75.5
77.5
Electricity Generation
(TWh)
500
Low Risk = Large share
of Offshore Wind &
Wave
CO2 (MtCO2)
100
0
79.5
81.5
83.5
85.5
87.5
89.5
Cost (£/MWh)
91.5
93.5
95.5
97.5
Solar PV
Tidal
Wave
Far Offshore Wind
Offshore Wind
Onshore Wind
hydro
Nuclear
Biomass
Gas with CCS
Gas
Coal with CCS
Coal
CO2
99.5
CO2 (MtCO2)
100
450
90
400
80
350
70
300
60
250
50
200
40
150
30
100
20
50
10
0
Solar PV
Tidal
Wave
Far Offshore Wind
Offshore Wind
Onshore Wind
Hydro
Nuclear
Biomass
Gas with CCS
Gas
Coal with CCS
Coal
CO2
0
4.3
4.7
5.1
5.5
5.9
6.3
6.7
7.1
7.5
7.9
8.3
8.7
9.1
9.5
9.9
10.3
Risk (%) - standard deviation
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Cost – Risk Graph
2050s climate variability
2020 Projected Technology Cost – Risk Characteristics
showing 2050s climate variability
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Cost – Risk Graph
2080s climate variability
2020 Projected Technology Cost – Risk Characteristics
showing 2080s climate variability
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Efficient Frontier Variability
Due To Climate Change
MVPT Efficient Frontier – Variability due to climate change
Showing the variability of MVPT efficient frontiers for different future
climate scenarios (includes variability of on- and offshore wind, solar PV,
wave and hydro).
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Variability in Technology Mix
at Point A
Changes in mix required to maintain
the baseline climate portfolio cost
and minimal risk
for the different climate projection
scenarios
Affected technologies: Nuclear, Gas
& Coal with CCS
Offshore Wind, Wave
Technology
Baseline
2050
50%
2050
10%
2050
90%
2080
50%
2080
10%
2080
90%
Gas
0
0
0
0
0
0
0
Gas & CCS
17.5
22.6
33.3
25.6
25.7
36.5
26.1
Coal
0
0
0
0
0
0
0
Coal & CCS
11.5
17.6
29.2
23.5
21.2
32.7
24.1
Nuclear
121.3
121.8
140.7
90.6
124
142.8
90.5
Onshore Wind
75
75
75
75
75
75
75
Offshore Wind
74.7
75
71.9
75
75
63
75
Far Offshore
Wind
0
0
0
11.2
0
0
10.1
Hydro
25
25
25
24.1
25
25
24.2
Biomass
50
50
50
50
50
50
50
Wave
50
38
0
50
29
0
50
Tidal Current
25
25
25
25
25
25
25
Solar PV
50
50
50
50
50
50
50
Cost (£/MWh)
86.0
86.0
86.0
86.0
86.0
86.0
86.0
Risk (%)
6
6.1
6.9
5.3
6.2
7
5.3
CO2 (MT)
1.8
2.5
4
3.2
3
4.5
3.3
CO2 Reduction
from 1990 (%)
99.1
98.8
98.0
98.4
98.5
97.8
98.4
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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ARIES
(Adaptation and Resilience in Energy Systems)



ARIES is part of The Adaptation and Resilience in a Changing Climate (ARCC) Coordination Network (ACN) of
EPSRC funded projects
A Collaborative project with Heriot Watt University
AIM - To deliver a comprehensive risk framework to assess and manage UK energy system (electricity and gas)
resilience to climate change:
ARIES will establish a scientifically sound framework for assessing future impacts and adaptation at a UK and regional level. Using a
bottom-up approach, it will capture the potential for changes in future energy supply and demand and the consequent impact on
electricity and gas system resilience. It will identify climate risks for individual supply and demand factors and, through integrated
modelling, allow examination of system-level risks and cumulative effects.


ARIES is a very broad project covering all aspects of adaptation and resilience in energy systems as society
progresses towards a low carbon energy system and future climate variability.
The ARIES offshore wind, marine and electricity generation related research will build upon and further develop
much of what has been presented in the previous slides in this presentation:




Higher resolution spatial and time-series resource models including frequency of extreme events
Improved and more complete climate scenario projection data
Regionalised resource assessments….
…..
For more info: http://www.ukcip-arcc.org.uk
Or contact Professor Gareth Harrison [email protected] or Dougal Burnett [email protected]
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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ARIES
Some of the other University of Edinburgh offshore wind and
marine resource research activities to feed into ARIES and
improve resource modelling
Wavewatch III model
ECMWF reanalysis data
(Atul Agarwal)
Edinburgh University - UK
mesoscale UK Wind Resource
Model
(Sam Hawkins)
UK Tidal Current Resource
Scenario Assessment
(Dr. Abhinaya Sankaran Iyer)
Economics of Ocean Energy and Marine Energy – HMRC, UCC (Cork 18th and 19th April) 2012
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Thank you for your attention.
Any Questions?
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