NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by 

Understanding Wind Power Cos

Value of a Comprehensive Appr

2nd NREL Wind Energy Systems Engineering 

Broomfield, ColoradoEric LantzJanuary 2930, 2013

NREL/PR-5000-58104
Analysis Disclaimer

This work has been funded by the U.S. Department of Energy, O

Efficiency and Renewable Energy, Wind and Water Power Progra

No. DE‐AC36‐08GO28308 with the National Renewable Energy L
Presentation Overview• Background• Historical data and limitations

• The value of levelized cost of energy 

how it is calculated

• Conclusions
Background
For Much of the History of the Wind Indust

Measures of Progress Pointed in the Same 

• Less‐than‐perfect industry metrics cam

used inside and outside of the industr

• But, with more emphasis on optimizat

incremental advancement today, prior 

may fail to tell the full story

• Levelized cost of energy (LCOE) offers 

capture the array of critical variables itransparent and consistent way that p

greater industry insights
Historical Data and Limitation
Capital Cost is a Very Common Metric for Ch

Industry Progress

• These data are relatively accessible and clearly illustrate trends in har

installation costs

• Throughout the 1980s and 1990s, capital cost declined substantially

•Over the last 5‐7 years, the story has become more complex—input p

at the same time, technology underwent a shift to greater productivit

larger rotors and taller towers

0

500

1,0001,5002,0002,5003,0003,5004,0004,5005,000

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Installed Project Cost (2011 $/kW) Individual Project Cost (584 projects totaling 42,614 M

 Capacity-Weighted Average Project Cost

Source: Wiser and Bolinger 2012
Along With Capital Cost Data, Turbine Price D

an Indicator of Installation Costs

• Turbine price data offer

a real‐time perspective on hardware costs, w

65% to 75% of installed costs

•However, the lag time between execution of turbine supply agreeme

commercial operation date complicates one’s ability to reliably use tindicator of project costs

• Turbine price data may not fully reflect technological innovations th

increased productivity at

a given turbine price

0

200400600800

1,0001,2001,4001,6001,8002,0002,200

Jan-97

Jan-98

Jan-99

Jan-00

Jan-01

Jan-02

Jan-03

Jan-04

Jan-05

Jan-06

Jan-07

Jan-08

Jan-09

J10

Announcement Date

Orders <5 MWOrders from 5 - 100 MWOrders >100 MW

Turbine Transaction Price (2011$/kW) 

Source: Wiser and Bolinger 2012
In Some Instances, Analysts Will Use Capac

to Supplement Capital Cost or Turbine Price 

• These data are also relatively accessible and give a sense of industry p

•U.S. fleet‐wide data suggest that improvements on the order of 20% t

to 35% NCF) have occurred since the early 2000s

•At the same time, the data appear contradictory. For example:

o In Spain, capacity factors have been declining since 2000

o U.S. gains appear most dramatic from 1999 to 2002, with only margina

occurring since the mid‐2000s

0%5%

10%15%20%25%30%35%

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 20

5 12 41 84 97 119 143 168 210 254 35

544 1,000 1,531 3,271 3,811 5,211 5,880 8,712 10,695 15,670 24,3

Capacity Factor Based on Estimated Generation (if no curtailment in s

 Based on Actual Generation (with curtailment) 4-Year Moving Average (based on estimated generati

Year:

Projects:

MW:

Source: Wiser and Bolinger 2012
Analysis of Power Market Transactions Prov

Additional Layer of Insights

•Actual market‐based payments for wind‐generated electricity can so

good proxy for wind power costs

• Such data may not reflect all revenue streams (e.g., the production t

tax incentives) and shed little insight on what factors determine mar

wind resource, capital costs, turbine performance, and financing par

payments even result in profitability

0

10203040506070

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 20

11 12 22 33 47 64 80 97 120 150 18

588 600 741 1,444 2,294 3,103 4,056 4,987 7,980 10,535 13,

 Cumulative Capacity-Weighted Average Wind Power Price (with 25% and 75% quartiles)

Wind Power Price (2011 $/MWh)

Year:

Projects:

MW:

Sample includes projects built from 1998-2011

Source: Wiser and Bolinger 2012
No Single Metric Tells the Complet

• Capital cost (and turbine price) data fail to explain e

industry cost drivers (input prices or exchange rates

improvements in performance

• Capacity factor data are subject to year‐on‐year win

variability and don’t show megawatt‐hours (MWh) p

invested or potential changes in the quality of the w

where a project is located

o Capacity factor is also limited, at least in part, by the p

energy losses at the top end of the power curve that re

cut‐out speeds

• Market transaction data do not necessarily reflect a 

accounting of industry costs and say very little abou

including the wind regimes where projects are sited
The LCOE Solution
LCOE Applies a Relatively Comprehensive App

Resolve Most of These Issues

• At its most basic level:

• At a slightly more detailed level, LCOE is comprised of fo

o Installed Capital Cost (ICC)o Net Annual Energy Production (AEPnet)o Annual Operations Expenses (AOE)

– Operation and maintenance + insurance, land lease payments, oth

o Fixed Charge Rate

– Cost of financing– Assumed plant life

• The relationship among these variables is summarized a

 

AEPnet

FCRICC AOE LCOE   

Energy Lifetime Product

costs Lifetime PV LCOE 

LCOE helps provide a greater understanding of the im

in a given variable and is a better reflection of change

costs than any other independent metr
The LCOE Approach Also Offers Insights into 

Sensitivity of Costs to Changes in Project Pa

Capital cost and capacity factor are two of the most 

but others are also important

Source: Tegen et al. 2012
LCOE Offers an Enhanced Ability to Analyze World Tradeoffs

Recent technological innovations demonstrate that higher ca

merited at lower wind speed sites when the performance g

using a larger rotor or taller tower offset the incremental co

increased material use and more difficult logis

Source: Wiser et al. 2012

200

200

Cur

T

Current, 2012‐13:

Low Wind‐speed

(80mTower)

$0

$20$40$60$80

$100$120$140$160

5.5 6.0 6.5 7.0 7.5 8.0 

Levelized Cost of Energy ($/MWh)

No Incentives

50mWind‐speed (m/s)

(air density = 1.225 kg/m3)

Class 2 Class 3 Class 4 Class 5 C

Current, 2012‐13:

Low Wind‐speed

(100m Tower)
Linking LCOE to Representative Technology Resource Data Allows for Further Industry I

200

Standard 

0

500,000

1,000,0001,500,0002,000,0002,500,0003,000,000

$30 $40 $50 $60 $70 $80 

Available Land Area (km

2

)

Levelized Cost of Energy ($/MWh)

201

LoweTech 

w/: PTC/MACRSw/o: PTC/MACRS $57 $67 $77 $89 $99 $110 

Percentage Increase Since 200

< $35/MWh w/ PTC & MACRS: < $55/MWh w/ PTC & MACRS: < $75/MWh w/ PTC & MACRS: 

Source: Wiser et al. 2012

The more nuanced perspective offered by detailed LCOE anal

ability to apply specific technology cost and performance dat

how new regional markets might be opened by technologica
Conclusions
Conclusions• In an era that emphasizes turbine and plan

optimization, industry metrics such as cap

may be less indicative of future technologi

• LCOE offers more nuanced market insights 

increased transparency relative to any ind

metric

o It also requires more data and a detailed unde

industry trends

• In the absence of a widespread shift to LCO

be increasingly difficult to communicate th

achievements of the industry as well as th

possibilities
Eric Lantz

Research Analyst

Strategic Energy Analysis Center

National Renewable Energy Laboratory

http://www.nrel.gov/analysis/

http://www.windpoweringamerica.gov/

Phone: (303) 384‐7418

email: Eric.Lantz@nrel.gov

Thank You

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by t

NREL 05593