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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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

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10

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1000

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LCO

E $/

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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

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• 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

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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

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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

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Value of Offshore Wind Energy in High Damages, 3% Case

Damages Abatement

High Cost Low Cost High CostAdv Tech

Low CostAdv Tech

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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

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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

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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