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

Operations Expenditures: 

Trends And Continuing Ch

Eric Lantz

AWEA Wind Power Conferenc

Chicago, Illinois

May 7, 2013

NREL/PR‐6A20‐58606
DISCLAIMER AGREEMENT

These information (“Data”) are provided by the National Renewable Energy Laboratory (“NREL”), which is ope

Sustainable Energy LLC (“Alliance”) for the U.S. Department of Energy (the “DOE”).

It is recognized that disclosure of these Data is provided under the following conditions and warnings: (1) the

for reference purposes only; (2) these Data consist of forecasts, estimates or assumptions made on a best‐effo

present expectations; and (3) these Data were prepared with existing information and are subject to change w

The names DOE/NREL/ALLIANCE shall not be used in any representation, advertising, publicity or other mann

promote any entity that adopts or uses these Data. DOE/NREL/ALLIANCE shall not provide any support, consuof any kind with regard to the use of these Data or any updates, revisions or new versions of these Data.

YOU AGREE TO INDEMNIFY DOE/NREL/ALLIANCE, AND ITS AFFILIATES, OFFICERS, AGENTS, AND EMPLOYEES A

DEMAND, INCLUDING REASONABLE ATTORNEYS' FEES, RELATED TO YOUR USE, RELIANCE, OR ADOPTION OF T

PURPOSE WHATSOEVER. THESE DATA ARE PROVIDED BY DOE/NREL/ALLIANCE "AS IS" AND ANY EXPRESS OR 

INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PAR

EXPRESSLY DISCLAIMED. IN NO EVENT SHALL DOE/NREL/ALLIANCE BE LIABLE FOR ANY SPECIAL, INDIRECT OR 

OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF 

MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT O

THE USE OR PERFORMANCE OF THESE DATA.

Disclaimer
Acknowledgements

Thanks to the U.S. Department of Energy, Office o

Efficiency and Renewable Energy, Wind and Wate

Technologies Office for funding this work.

Funding provided under contract no. DE

‐AC36

‐08G

the National Renewable Energy Laboratory.

Thanks also to our partners at GL Garrad Hassan a

KEMA.
Presentation Outline• Background• Historical Data

o Operations Expenditureso System Availabilityo Major Component Replacement Rates

• Other Market Insights• Challenges
Background
NREL’s Interest In Operations Expenditures (

Multi‐Faceted

• Minimizing OpEx could increase plant profit

helping to support a lower cost of energy.

• Understanding opportunities for reductions 

requires a baseline level of knowledge of:

o OpExo System or Plant Availabilityo Major component replacement rates

• Publicly available empirical data on the varia

above are limited in scope and resolution.

An empirically derived baseline of OpEx and componen

experience‐based insights into recent trends are useful fo

making and industry benchmarking.
Data Housed By Project Partners GL Garrad Hassan a

Were Analyzed Independently, with a Focus on Thre

• Historical OpEx

• Historical “plant” or “system” availability

o Not to be confused with manufacturer, contractua

availability

• Major component failure rates and typical rep

o Blades, gearboxes, generatorso Sensitivities in failure rates as a result of serial fail

explored

• The combined GL Garrad Hassan and DNV KEMA s

represents about 10 GW of operating wind plants

• Data shown today represent analysis completed b

respective partners for NREL
Expert Opinions Were Also Collected• How have condition monitoring and more advanced 

designs affected historical OpEx?

• What have been the primary causes of missed OpEx 

• What is the relationship between downtime and Op

• How do trends vary regionally?

• What are the current strategies to service plants and 

these changed over time?

• Have technology perceptions affected financing term

Opinions were gathered from within the partner or

well as from semi‐structured discussions with ow
Historical Operations Expend

System Availability, And Repl
Critical Caveats• Datasets studied are not comprehensive a

quality varies by project and across time.

• Data are skewed toward recent builds bec

when the capacity has come on line; howe

projects only offer 1‐3 years of operating d

• Operating data beyond 5 years are sparse 

not be fully representative of industry exp

Results may be sensitive to the da

considered
Data from DNV KEMA for Projects Commissioned Thr

Suggest OpEx Initially of $40‐$50/kW and Increasing 

• Increases are primarily attributed to unscheduled maintenance and increa

audit compliance, system operator fees, other fees, royalty payments)

• Preliminary analysis of additional data and including more recent projects 

sensitive to servicing agreement terms as well as regional competition

Data Source: DNV KEMANote: Sample does not contain data for projects commissioned after 2009

$0

$10$20$30$40$50$60$70

1 2 3 4 5 6 7 8 9 

2179 MW 2230 MW 1915 MW 1455 MW 1065 MW 773 MW 606 MW 568 MW 568 M

Average OpEx (2011 $/kW)

Soft CostsTurbine O&MBOP

Plant Operating Year:

Sample:
GL Garrad Hassan’s Sample Shows Turbine 

Expenditures Increasing for More Recent Pr

Potential OpEx reductions resulting from enhanced turbine reliability m

deployment of more complex equipment or operations across

a broader ar

sample size, servicing agreement details, and market forces also affe

Data Source: GL Garrad Hassan

$0$5

$10$15$20$25$30

1 2 3 4 5 6 7 8 

2230 MW

991 MW

2761 MW1239 MW

3324 MW 2988 MW 2181 MW 1689 MW 1978 MW 2085 MW 

Capacity Weighted Average Turbine O&M (2011 $/kW) Commissioned Thru 

Commissioned After 

Operating Year:

Comissioned

Thru 2008:

Commissioned

After 2008:
When Adjusting for Curtailment, System Av

Appears Stable At About 95% Through At L

When factoring in curtailment, sample‐wide system availability is about 

minimization of plant downtime may at some point require considerati

policy and planning.

Source: GL Garrad Hassan
Annually, 1% ‐ 3% of Turbines Require Blade 

with Spikes In Years 1 and 5

0%1%2%3%4%5%6%7%8%9%

10%

1 2 3 4 5 6 7 8 9 

1539 1640 1417 1119 935 674 525 500 50

Share of Turbines Requiring Blade Replacements

Operating Year:

Total Turbines:

• Blade replacements in years 1 and 2 are typically the result of manufac

damage that occurs during transport and construction.

• On average, about 2% of turbines per year (through 10 years of operat

replacements; lightning strikes are the most commonly noted cause of 

Data Source: DNV KEMA
More Turbines Require Gearbox and Gener

Replacements, Particularly in Years 4‐6

• Average gearbox failure rate over 10 years of operations is estimated at 5%

• The average generator failure rate is somewhat lower and over 10 years o

estimated at 3.5%.

• Serial failures were observed to have a noteworthy effect on gearbox and 

potentially skewing the results.

Data Source: DNV KEMA

0%1%2%3%4%5%6%7%8%9%

10%

1 2 3 4 5 6 7 8 

1539 1640 1417 1119 935 674 525 500 

Share of Turbines Requiring Component

Replacements

Gearb

Operating Year:

Total Turbines:
Other Market Insights
Unscheduled Maintenance Remains a SigniSource of Uncertainty for the Industry

• Failure rates and unscheduled maintenance ar

principal drivers of uncertainty around OpEx e

o Gearbox replacements can approach $500k includ

generator and blade replacements are typically les

non‐trivial.

• There is no clear link between downtime and O

expenditures.

o This may be a function of data limitations rather th

of an actual correlation.

• The value of condition monitoring is not yet fu

understood.

o Condition monitoring is generally seen as useful ev

perspectives on costs savings remain varied.

o Some operators cite logistics, parts availability, and 

maintenance as more critical.
Competition and Risk Management Are Exp

Continue to Influence OpEx and Servicing S

• Regional competition and clustering are corre

OpEx (i.e., more competition and a higher conof plants results in lower OpEx).

o Market share can also play a role.

• Proper management of risk has a direct impac

financing terms.

o New products and more competition among prov

owners to choose the service and terms that mat

appetite.

• Servicing and OpEx management strategies ha

in the last decade; continued evolution entails

o More sophisticated electronic reporting and bette

documentation

o Consideration of regional climate, turbulence, and 

models
Challenges

• The absence of standardized reporting 

the industry makes comparisons across

operations‐related datasets very difficu

• Limited data for older projects make co

for plants operating in the 7‐10 year timmore tentative.

o The time required to gather years of operat

continue to make it difficult to understand 

technological developments affect OpEx.

• Operations servicing remains dynamic a

create continued data and reporting ch

the future.
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

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

Photo from Green Mountain Power Corporation, NREL 05593