offshore wind energy -...
TRANSCRIPT
Erin Baker, Director of IGERT: Offshore Wind Energy Engineering, Environmental Impacts, and Policy, University of MassachusettsPresented at WINDFARMS, Madrid, Spain, May 31, 2017
Offshore Wind EnergyWhere is it going, what can we do about it, and
why should we care?
2
Offshore Wind Energy: Where is it going?Forecasting technological change
3 Wiser et al, 2016
Experience curvesCost modeling
Expert Judgement
Expert ElicitationA structured method for eliciting subjective probabilities from experts.
Levelized Cost of Energy
5
Estimated change in LCOE over time across all three scenarios. Depicts the median of expert responses for expected LCOE reductions in the median (50th percentile) scenario as well as the low scenario (10th percentile) and high scenario (90th percentile) in percentage terms relative to 2014 baseline values. Floating offshore wind is compared against the 2014 baseline for fixed-bottom offshore. See Supplementary Discussion for full results.
Estimated Change in LCOE over time
Significant uncertainty around cost reductions for floating offshore
Note: Change is shown relative to baseline for fixed-bottom offshore as no 2014 baseline was established for floating offshore
$85/Mwh$70/Mwh
Where are cost reductions coming from?
8
Historical and forecast experience curves for onshore wind
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10
100
1000
10 100 1,000 10,000 100,000 1,000,000
LCO
E $/
MW
h
cumulative capacity (MW)
Historical US LCOE: Good to Excellent Sites (DOE 2015b)Historical Denmark LCOE (DEA 1999)Historical Coastal European LCOE (Lemming et al. 2009)Historical Global LCOE (BNEF 2015a)
LR 15.5
LR 10.5%
LR 18.6%LR 17.8%
Historical LCOE estimates come from four sources (Global: BNEF 2015a; US: DOE 2015b; Denmark: DEA 1999; European Coastal: Lemming et al.2009). Historical single-factor learning rates (LRs) are calculated based on cumulative global wind capacity. To estimate the implicit learning rate from the expert elicitation, we use median-scenario LCOE estimates and a range of projections for cumulative global wind capacity from IEA “New Policies” (IEA 2015), Bloomberg “Base Scenario” (BNEFb 2015), and GWEC “Moderate Scenario” (GWEC 2014).
Forecast experience curves for offshore wind
10
10
100
1000
10 100 1000 10000 100000 1000000 10000000
LCO
E $/
MW
h
Cumulative Capacity (MW)
Historical US LCOE: Good to Excellent Sites (DOE 2015b) Historical Denmark LCOE (DEA 1999)
Historical Coastal European LCOE (Lemming et al. 2009) Historical LCOE (Denmark, Germany, Global) (BNEF 2011)
Historical Global LCOE (BNEF 2015a) Expert Survey: Low Scenario Forecast
Expert Survey: Median Scenario Forecast Expert Survey: High Scenario Forecast
Expert survey offshore low Expert survey offshore mid
Expert survey offshore high Expert survey offshore low
Expert survey offshore mid Expert survey offshore high
Offshore Wind Experience curves, assu cumulative learning
Offshore Wind Experience curves, assuming a fresh start
Estimated change in LCOE for (a) onshore and (b) fixed-bottom offshore: expert survey results vs. other forecasts. Depicts the median of expert responses for expected LCOE reductions in the median (50th percentile) scenario as well as the low scenario (10th percentile) and high scenario (90th percentile) in percentage terms relative to 2014 baseline values. Other forecasts are included for comparison, originally compiled and presented in a U.S. Department of Energy report (DOE 2015).
Offshore Wind Energy: What can we do about it?
Estimated Change in LCOE over time
Offshore Wind Energy: What can we do about it?
Bending the curve through R&D
13
• Larger rotors, reduced specific power
• Rotor design advancements
• Taller towers• Reduced financing costs• Component
durability/reliability
• Larger turbine capacity• Foundation design• Economies of scale via
project size• Reduced financing costs• Component
durability/reliability
• Foundation design• Installation process• Foundation
manufacturing• Economies of scale via
project size• Installation and
transport equipment
Land-based Fixed-bottom Floating
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SUPPLYfor offshore wind energy is driven by siting and information collection.
Mass Production in Port
Float out installation
Installation and siting for economies of scale
Offshore Wind Energy DEMANDis driven by overall clean energy demand, and by offshore wind energy costs.
Efficiently sited wind fleets maximize benefits
Integration: maximize the value of wind energy within the energy system
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Renewable energy policy & grid integration
Small scale wind in Northern Ireland impacts the grid
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0
100
200
300
400
500
600
700
800
MW
Ameliorate consequences of small scale wind
Potential over-generation
Reduced incentives for large scale wind
Reverse power flow
Offshore Wind Energy: Why should we care?
Environmental benefits of offshore wind energy
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Offshore wind can reduce emissions, reduce the cost of abatement, or both
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Defining value of offshore wind
Total cost without offshore wind
Total cost with offshore wind
Total CostCost of damagesCost of reducing emissions
Defining value of offshore wind
𝐶𝐶 𝜇𝜇∗,𝑅𝑅∗,𝜙𝜙,𝜓𝜓 + 𝐷𝐷 𝜇𝜇∗,𝜙𝜙,𝜓𝜓 − 𝐶𝐶 𝜇𝜇𝑤𝑤 ,𝑅𝑅𝑤𝑤,𝜙𝜙,𝜓𝜓 − 𝐷𝐷 𝜇𝜇𝑤𝑤,𝜙𝜙,𝜓𝜓
Cost of abatement Cost of damages
Without offshore wind With offshore wind
Defining value of offshore wind
𝐶𝐶 𝜇𝜇∗,𝑅𝑅∗,𝜙𝜙,𝜓𝜓 + 𝐷𝐷 𝜇𝜇∗,𝜙𝜙,𝜓𝜓 − 𝐶𝐶 𝜇𝜇𝑤𝑤 ,𝑅𝑅𝑤𝑤,𝜙𝜙,𝜓𝜓 − 𝐷𝐷 𝜇𝜇𝑤𝑤,𝜙𝜙,𝜓𝜓
Cost of abatement Cost of damages
Without offshore wind With offshore wind
Level of abatement
Capacity by
technology
Policy
Parameters
Calculating cost of abatement and damages
𝐷𝐷 Δ𝑇𝑇 = 𝑎𝑎(Δ𝑇𝑇)𝑏𝑏
Nordhaus and Sztorc 2013; Kolstad et al. 2014; Hope 2011
02468
1012141618
0 1 2 3 4
Dam
ages
(% G
WP)
ΔT (°C)
b = 1.5 b = 2 b = 3
GCAM Integrated Assessment Model
Cost assumptions
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Cost Assumptions in perspective with expert judgment
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11% of experts say 10% chance or better
4% of experts say 10% chance or better
Median high
Median low
Supply curves
Developed with data from Schwartz et al. 2010; Beiter et al. 2016; Mone et al. 2013; Green et al. 2007; Myhr et al. 2014; Bjerkseter and Agotnes 2013
Supply curves
Developed with data from Schwartz et al. 2010; Beiter et al. 2016; Mone et al. 2013; Green et al. 2007; Myhr et al. 2014; Bjerkseter and Agotnes 2013
Calculating cost of abatement and damages
𝐷𝐷 Δ𝑇𝑇 = 𝑎𝑎(Δ𝑇𝑇)𝑏𝑏
Nordhaus and Sztorc 2013; Kolstad et al. 2014; Hope 2011
02468
1012141618
0 1 2 3 4
Dam
ages
(% G
WP)
ΔT (°C)
b = 1.5 b = 2 b = 3
GCAM Integrated Assessment Model
High Cost Low Cost High CostAdv Tech
Low CostAdv Tech
-20000
2000400060008000
1000012000140001600018000
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
Valu
e (B
illio
n201
5$)
Scenario
Value of Offshore Wind Energy in Mid Damages, 3% Case
Damages Abatement
Value of permitting offshore wind
Cost of
High Cost Low Cost High CostAdv Tech
Low CostAdv Tech
-20000
2000400060008000
1000012000140001600018000
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
Valu
e (B
illio
n201
5$)
Scenario
Value of Offshore Wind Energy in High Damages, 3% Case
Damages Abatement
High Cost Low Cost High CostAdv Tech
Low CostAdv Tech
-20000
2000400060008000
1000012000140001600018000
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
BA
U $
10 T
ax $
100
Tax
Valu
e (B
illio
n201
5$)
Scenario
Value of Offshore Wind Energy in Mid Damages, 3% Case
Damages Abatement
Value of offshore wind
Value of offshore wind in BAULo
w C
ost A
dv T
ech
Hig
h C
ost A
dv T
ech
Low
Cos
t
Hig
h C
ost 0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1.50% 3% 5%
Val
ue (B
illio
n201
5$)
Discount Rate (%)
Value of Offshore Wind Energy in BAU Case
Low Cost Adv Tech High Cost
Mid Damages, Low Cost Adv Tech Mid Damages, High Cost
Value with Low Cost, Advanced Technology and High Damages
Value of technological change
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1.50% 3% 5%
Val
ue (B
illio
n201
5$)
Discount Rate (%)
Value of Offshore Wind Energy in BAU Case
Low Cost Adv Tech High Cost Mid Damages, Low Cost Adv Tech Mid Damages, High Cost
Value of Technological Change in High Damages Case $45 trillion
….in Mid Damages Case ($4 trillion at 3%)
…in Low Damages Case ($470 billion at 5%)
Offshore Wind Energy
Reference and Acknowledgements Reference: Wiser, Ryan, Karen Jenni, Joachim Seel, Erin Baker, Maureen Hand, Eric
Lantz, and Aaron Smith. "Expert elicitation survey on future wind energy costs." Nature Energy 1 (2016): 16135.
IEAWind Implementing Agreement for Cooperation in the Research, Development, and Deployment ofWind Energy Systems (IEAWind).
US Department of Energy (DOE) under Contract Nos DE-AC02-05CH11231 (LBNL) and DE-AC36-09GO28308 (NREL),
IEAWind collaborators: V. Berkhout, A. Duffy, B. Cleary, R. Lacal-Arántegui, L. Husabø, J. Lemming, S. Lüers, A. Mast,W. Musial, B. Prinsen, K. Skytte, G. Smart, B. Smith, I. Bakken Sperstad, P. Veers, A. Vitina and D.Weir.
This work is partially supported by the NSF-sponsored IGERT: Offshore Wind Energy Engineering, Environmental Science, and Policy (Grant Number 1068864).
Thanks to the Joint Global Change Research Institute for support and access to their GCAM-USA model.
Offshore Wind Energy