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Contract No. DE-AC36-08GO28308

Installation, Operation, and 

Maintenance Strategies to 

Reduce the Cost of Offshore 

Wind Energy

B. Maples, G. Saur, and M. Hand

National Renewable Energy Laboratory

R. van de Pietermen and T. Obdam

Energy Research Centre of the Netherlands

Technical Report

NREL/TP-5000-57403

July 2013
NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC.

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

National Renewable Energy Laboratory

15013 Denver West Parkway

Golden, CO 80401

303-275-3000 • www.nrel.gov

Installation, Operation, and 

Maintenance Strategies to 

Reduce the Cost of Offshore 

Wind Energy 

B. Maples, G. Saur, and M. Hand

National Renewable Energy Laboratory

R. van de Pietermen and T. Obdam

Energy Research Centre of the Netherlands

Prepared under Task No. WE11.5056

Technical Report

NREL/TP-5000-57403

July 2013
NOTICE

This report was prepared as an account of work sponsored by an agency of the United States government. 

Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, 

express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of 

any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately 

owned rights. Reference herein to any specific commercial product, process, or service by trade name, 

trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, 

or favoring by the United States government or any agency thereof. The views and opinions of authors

expressed herein do not necessarily state or reflect those of the United States government or any agency thereof.

This report is available at no cost from the National Renewable Energy Laboratory (NREL) 

at www.nrel.gov/publications.

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Cover Photos: (left to right) photo by Pat Corkery, NREL 16416, photo from SunEdison, NREL 17423, photo by Pat Corkery, NREL 

16560, photo by Dennis Schroeder, NREL 17613, photo by Dean Armstrong, NREL 17436, photo by Pat Corkery, NREL 17721.

 Printed on paper containing at least 50% wastepaper, including 10% post consumer waste. 
iii

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Notice

This report is being disseminated by the Department of Energy. As such, the document was 

prepared in compliance with Section 515 of the Treasury and General Government 

Appropriations Act for Fiscal Year 2001 (Public Law 106-554) and information quality 

guidelines issued by the Department of Energy. Though this report does not constitute 

“influential” information, as that term is defined in DOE’s information quality guidelines or the 

Office of Management and Budget's Information Quality Bulletin for Peer Review (Bulletin), the 

study was reviewed both internally and externally prior to publication. For purposes of external 

peer review, the study benefited from the advice and comments of a panel of offshore wind 

industry experts. That panel included representatives from private corporations and national 

laboratories. 

Acknowledgments

The authors thank the U.S. Department of Energy (DOE) for supporting this work. For providing 

data and other input, and for reviewing sections of this report, the authors are grateful to: Fort 

Felker, Robin Newmark, Brian Smith, Walt Musial, Maureen Hand, Margaret Mann, David 

Kline, Karlynn Cory, Rebecca Meadows, Aaron Smith, KC Hallett, Tony Jimenez (National 

Renewable Energy Laboratory, NREL); Cash Fitzpatrick, Gary Norton, Brian Naughton, Logan 

Putnam (DOE); Luc Rademakers, Bernard Bulder (Energy Research Centre of the Netherlands); 

Jeffrey Fuchs (GE Energy); Jacob Andersen (Siemens Energy); Joel Whitman (Global Marine 

Energy); Natalia Nagree, Steven Kopits, Akos Losz (Douglas Westwood); Ashley Crowther 

(Romax Technologies); Michael Molek (GL Noble Denton); John Dunlop (American Wind 

Energy Association); George Hagerman (Virginia Tech); Doug Frangillo (Knud E. Hanson); 

Jaap Olthoff (wind consultant); and Anders Johnsson (Vattenfall). 
iv

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List of Acronyms and Abbreviations

AEP annual energy production 

BOP balance of plant (same as BOS)

BOS balance of station (same as BOP)

CAPEX capital expenditures 

CBM condition-based monitoring 

CF construction financing 

DEMOB demobilization 

DOE U.S. Department of Energy 

DP2 dynamically positioned 

ECN Energy Research Centre of the Netherlands 

FCR fixed charge rate 

FOA Funding Opportunity Announcement 

FTC fault type class

h hour 

Hs significant waveheight

ICC installed capital cost

IO&M installation, operation, and maintenance

kg kilogram 

km kilometer

kV kilovolt 

kW kilowatt 

kWh kilowatt-hour 

L liter

LCOE levelized cost of energy

m meter

MC maintenance category

MOB mobilization

m/s meter per second

MT metric tonne

MW megawatt

nmi nautical mile

NREL National Renewable Energy Laboratory 

OCC overnight capital cost 

O&M operation and maintenance 

OPEX operation expenditures 

RDS-PP reference designation system for power plants 

ROI return on investment

ROV remotely operated vehicle 

TCC turbine capital cost

USD U.S. Dollar

Vw wind velocity 

WeWi weather window 

WindPACT Wind Partnerships for Advanced Component Technology 

WT wind turbine 
v 

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Executive Summary

This report is intended to provide offshore wind industry stakeholders a basis for evaluating 

potential cost saving installation, operation, and maintenance (IO&M) strategies and 

technologies. The work was completed by the National Renewable Energy Laboratory (NREL) 

and its subcontractor, the Energy Research Centre of the Netherlands (ECN), in fulfillment of a 

U.S. Department of Energy (DOE) contract for subtopic 5.3: Optimized Installation, Operation, 

and Maintenance Strategies under topic 5: Optimized Infrastructure and Operations of Funding 

Opportunity Announcement (FOA) number DE-FOA-0000414, entitled “U.S. Offshore Wind: 

Removing Market Barriers.” For stakeholders carrying out project-specific evaluations of IO&M 

approaches presented herein, several related studies also conducted under this FOA will serve as 

valuable resources on specific aspects of offshore wind development infrastructure including 

ports, vessels, and supply chain parameters.

Some of the IO&M strategies in this report were analyzed without projecting the capital 

expenditures associated with an enabling technology or method. Thus, the results show the 

upside or added value to a strategy (e.g. increased energy production), and not the potential 

downside (e.g. added capital cost of new hardware). The results of the analysis can therefore be 

used by industry stakeholders to take the cost savings presented in this report and add their 

revised technologies costs to arrive at a net decrease or increase in cost of energy resulting from 

a proposed IO&M strategy. This allows many technologies that target the same improvement 

area to be evaluated subsequent to this study. To clarify this concept, an example is presented 

below. 

Company X is interested in bringing an innovative vessel capable of operating at 

higher wind and wave conditions to market. If a strategy using an innovative 

vessel capable of operating in higher wind and wave conditions (similar to 

Company X’s design) is shown to reduce costs by $100/kW with respect to the 

baseline, Company X can see that in order to be viable in the market, they must be 

able to deliver their innovative vessel at a rate no more than $100/kW greater than 

the vessel rate used in the baseline. If Company X can deliver their innovative 

vessel at $25/kW more than the baseline, they will have demonstrated that their 

new vessel technology is capable of saving $75/kW with respect to the baseline. 

Introduction

IO&M is expected to account for nearly one-third of offshore wind levelized cost of energy 

(LCOE) in the United States (U.S. Department of Energy, 2011). Consequently, there is a large 

potential for reducing LCOE through advanced IO&M strategies. NREL and ECN, along with a 

panel of subject matter experts who provided input, have used their offshore wind cost modeling 

capabilities to fulfill the project's two primary objectives: 

• Conduct analysis and modeling to identify the most practical means of reducing offshore 

wind LCOE through advanced IO&M techniques, integrated service providers, and preferred 

supporting infrastructure. 

• Identify preferred IO&M strategies in a case study of a hypothetical U.S. offshore wind 

project. 
vi 

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at www.nrel.gov/publications.

To accomplish the objectives related to installation costs, NREL has developed a new offshore 

wind turbine installation cost module which, coupled with the NREL offshore wind plant balance 

of station (BOS) model, is capable of analyzing many scenarios including the six (6) turbine 

assembly strategies and three (3) additional project installation strategies that this study analyzes. 

To accomplish the objectives related to O&M costs, ECN has established an O&M tool for the 

U.S. offshore market based on their industry-leading offshore wind operation and maintenance

(O&M) planning software, the ECN O&M Tool v.4 (Obdam, Braam, & Rademakers, 2011). This

tool has been used to identify the O&M cost implications of six (6) O&M strategies for this 

study. 

For the analysis, we used real-world wind and wave condition data, but parameters such as 

project size (500 MW), turbine size (5 MW), and location (46 km off the coast of Virginia) were 

chosen to represent a typical but hypothetical utility-scale offshore wind plant. This study does 

not attempt to represent an existing wind plant, or a wind plant currently under development. The 

same holds true for the realistic but hypothetical reference wind turbine used in this study. 

To demonstrate the impacts of the strategies investigated, the analysis has been divided into three 

(3) sections: baseline, advanced IO&M strategies, and preferred case study. 

• (Chapter 3) The baseline section establishes a reference project, IO&M strategy, and cost for 

use in further comparisons. 

• (Chapter 4) The advanced IO&M strategies section investigates individual IO&M strategies 

and demonstrates their impact on system LCOE. 

• (Chapter 5) Finally the preferred case study section applies the most impactful combination 

of those advanced IO&M strategies to the hypothetical offshore wind plant in order to 

present a preferred overall IO&M approach for that facility. 

Baseline 

The baseline installation strategy resulted in a total installation cost of $633 million dollars for 

the 500MW project. Vessel costs accounted for the majority of the total installation costs. The 

baseline O&M scenario yielded an availability of 84.5% and O&M costs of $0.0283/kWh. The 

majority of downtime is associated with corrective maintenance on the wind turbine and balance 

of plant structures. Table 1 illustrates that roughly 12% of the baseline LCOE is attributable to 

O&M and 20% to installation activities (installation vessels + ports and staging). 
vii 

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Table 1. Summary of Baseline LCOE

($/kW) ($/kWh)

Turbine Capital Cost 1800 0.0650

Development 118 0.0043

Port and Staging 26 0.0009

Support Structure 800 0.0289

Electrical Infrastructure 498 0.0180

Installation Vessels 1240 0.0448

Balance of Station 2682 0.0969

Insurance 90 0.0033

Decommissioning 471 0.0170

Contingency 448 0.0162

Soft Costs 1009 0.0364

Overnight Capital Cost (OCC) 5491 0.1983

Construction Financing 165 0.0060

Installed Capital Cost (ICC) 5656 0.2043

O&M ($/kW/yr) 784 0.0283

Net Annual Energy Production (AEP) (MWh/MW/yr) 3267

Fixed Charge Rate (FCR) 11.8%

Levelized Cost of Energy ($/kWh) 0.233

Advanced IO&M Strategies

At the onset of the project, a panel of subject matter experts (listed in Section 4) was gathered to 

brainstorm a list of potential advanced IO&M strategies. This set of strategies was down-selected

based on three criteria explained in Section 4, to those listed in Table 2 for further analysis.

Table 2. IO&M strategies investigated

Installation Strategies O&M Strategies

Land-based vs. offshore assembly Mother vessel accommodations

Direct delivery of components Helicopter access

Purpose-built installation vessel Fixed vessel contracts

Reduced electrical and foundation installation Improved crew transfer system

Spare part storage

Advanced condition-based monitoring (CBM)
viii

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Installation

A set of six (6) turbine assembly strategies, reflecting varying degrees of land-based vs. offshore 

assembly, and four (4) additional project installation strategies were analyzed in this study. The 

analyses of foundation and electrical strategies were conducted as sensitivity analyses wherein

the primary cost driver was varied higher and lower by a prescribed amount. The other 

installation analyses were designed to demonstrate the impact of a specific technology or 

approach. Figure 1 demonstrates the relative impact of each installation strategy with respect to 

the baseline installed BOS cost (BOS + insurance + contingency + construction financing), 

whether it be a sensitivity analysis (foundation and electrical) or an analysis of a particular 

technology or approach (purpose built vessel, component delivery, and turbine assembly). 

 

Figure 1. Impact of installation strategies investigated

The strategies varying the degree of assembly carried out on land, versus offshore, have the 

potential to make the biggest impact on BOS cost, either reducing it by almost $300/kW

compared to the baseline, or increasing BOS cost by approximately $650/kW. The strategy of 

arranging direct delivery of components to the project site (bypassing a staging port) increases 

the BOS cost compared to the baseline, as does the use of a purpose-built installation vessel, 

under this set of assumptions. Changes to the foundation installation duration would have the 

smallest impact on BOS costs compared to the baseline, and innovations affecting the electrical 

installation could have a slightly larger impact (either increasing or decreasing total BOS costs, 

depending on whether the innovation increased or decreased the electrical costs).

O&M

Table 3 summarizes the results of each of the O&M strategies investigated. As discussed further 

in Section 5 of the report, even though many of the strategies show promise for reducing LCOE, 

the benefits could overlap when implemented together (i.e., the improvements to LCOE may not 

be additive and the overall cost of implementing several strategies may exceed the benefit of 

reduced LCOE). 

Sensitivities New technology 

or approach

Baseline
ix

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Table 3. Quantitative summary of the O&M strategies investigated

O&M strategy 

summary 

Main strategy change 

compared to baseline

Availability

[%]

O&M Costs

[$/kWh] 

Total yearly 

effort

[M$]1

Result notes 

Baseline O&M 

scenario

– 84.5 0.0283 86.9 Investment and operational 

costs for onsite storage are 

not accounted for in the 

baseline.

Mother vessel 

accommodation

Reduced travel time from 

2.6 h to 0.5 h. Small parts in 

stock at mother vessel

91.2 0.0224 62.0 Analysis does not account for 

mother vessel investment and 

operations costs. [indication: 

$15M - $20M/year when 

rented from spot market, 

(BVG Associates, 2012)].

Helicopter access Reduced travel time from 

2.6 h to 1.0 h. Only for small 

repairs without spare parts.

87.1 0.0290 82.9 Includes estimated helicopter 

costs. Does not account for 

additional turbine investment 

costs for landing platform.

Vessel contracts Parameter study: Jack-up 

vessel contract 

Logistics time: 0 – 2200 h 

MOB/DEMOB costs: 

0 – 880 k$ 

83.0 – 85.0 0.0245 – 

0.0362 

82.3 – 99.4 Assuming clustering of large 

repairs, a fixed contract is 

only favorable in scenarios 

when costs per MOB/DEMOB 

can be lowered significantly. 

Improved crew 

transfer system

Parameter study: Access 

vessel limits

Wave height: 0.7 – 3.0 m 

Wind speed: 12 & 16 m/s

61.3 – 95.3 0.024 – 

0.044 

56.2 – 153.0 Wave height limit of 

workboats has large influence 

on availability and costs. Wind 

speed limit has very limited 

influence. Wave height limits 

greater than 1.7 m has 

minimal impact on costs. 

Spare part 

storage

Parameter study

Vary logistics time of part 

delivery for Maintenance 

Category (MC) 4 (MC4) 

repairs: 0 – 336 h

82.3 – 84.5 0.0283 – 

0.0290 

86.9 – 92.2 Longer logistics times lead to 

additional costs compared to 

baseline (i.e., small parts are 

stored onsite). 

Advanced CBM Parameter study

Assume Advanced 

Condition-Based Monitoring 

(CBM) for MC4 and MC6 

which are subsequently 

preventively replaced.

Detection rate: 0 – 100% 

84.5 – 86.9 0.0274– 

0.0283 

80.4 – 86.9 If a larger percentage of 

failures can be detected by

advanced CBM systems the 

availability increases and cost 

decreases. Analysis did not 

account for investment and 

operational costs for 

advanced CBM systems. 

Additional costs due to false 

alarms not considered.

 

1 Total O&M effort numbers presented in this report represent the sum of revenue losses and accrued O&M costs on a yearly basis. The $/kWh O&M 

costs, however, do not include the direct cost of revenue losses. Rather, the impact from loss of revenue on a $/kWh basis is accounted for via the 

change in energy production.
x 

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The two O&M strategies with the highest potential to improve availability and reduce revenue 

losses are: investment in an improved crew transfer system (e.g., application of a workboat with 

less restrictive weather limitations) and using a mother vessel to provide accommodation at the 

wind plant instead of daily transfer from the harbor. Both strategies focus on a reduction of the 

waiting time caused by bad weather conditions, which is the primary driver for the low wind 

plant availability in the baseline scenario. Individually, each of these strategies has the potential 

to reduce the total O&M effort from the baseline by more than $20 million. Other O&M 

strategies (helicopter access and advanced CBM) also yielded improvements, albeit much 

smaller than for the improved crew access system and mother vessel accommodation. On the 

other hand, ordering spare parts directly from the factory, rather than storing them onsite, causes 

longer downtimes and could decrease availability compared to the baseline. 

Preferred IO&M Case Study

For the preferred IO&M case study we:

• Analyzed combined installation strategies to establish a preferred installation strategy

• Analyzed combined O&M strategies to establish a preferred O&M strategy

• Assessed the tradeoffs between O&M costs, associated installation costs, and energy 

production impacts to establish a preferred IO&M strategy. 

Installation

As reported above, of the installation strategies that we investigated, only two showed potential 

cost reductions compared to the baseline: division of turbine assembly tasks between onshore 

and offshore; and changes to foundation and electrical installation approaches. Since we did not 

identify specific foundation or electrical installation technologies or process innovations, we did 

not include changes in these areas in our preferred installation strategy. 

Although the “bunny ears with 1-part tower assembly” method was potentially the lowest cost 

option, some turbine manufacturers may not allow the bunny ears method because transportation 

of the turbine in that unique configuration could lead to increased, or at least uncertain, loads on 

components. Consequently, the bunny ears style installation method was ruled out for the 

preferred case. The next lowest-cost assembly strategy was the “pre-assembled rotor with one 

part tower”, which we selected as the preferred installation strategy.

O&M

The majority of the O&M strategies aim to increase availability by reducing waiting time; 

therefore, the preferred O&M strategy analysis was completed in a multi-step approach where 

one strategy was applied (e.g., improved crew transfer) and then a second (or more) strategy(s)

(e.g., helicopter access) was added on top of the first. Table 4 summarizes the most impactful

combined O&M strategies investigated under this approach. 
xi 

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Table 4. Summary of O&M strategies studied with highest improvement opportunity 

O&M strategies Availability 

[%]

O&M Costs 

[$/kWh]

Total yearly 

effort [M$]2

Result notes:

Baseline O&M scenario 84.5 0.0283 86.9 This is the baseline O&M scenario

Step 1: Improved crew 

transfer

93.3 0.0248 62.1 

Significant effect compared to 

baseline: total O&M decreased 

by $24.8M. 

Step 1 + Variation A:

Mother vessel

95.2 0.0223 53.3 

Analysis does not account for 

increased cost of mother vessel 

[indication: $15M - $20M/year 

when rented from spot market, 

(BVG Associates, 2012)].

Step 1 + Variation B:

project-owned jack-up vessel 

93.8 0.0180 48.8 

Accounts for changes in operating 

expenses, but not capital cost of 

project-owned jack-up vessel.

Step 1 + Variation C:

Helicopter access 93.9 0.0260 63.3 

Increased operational costs. Does 

not account for additional turbine 

investment costs for landing 

platform.

Step 1 + Variation D:

Advanced CBM

93.7 0.0247 61.1 

Results shown are for 50% 

detection rate with 0% false alarms. 

Does not account for investment 

and operational costs for advanced 

CBM systems. 

IO&M

The preferred IO&M strategy for the case study would utilize a turbine installation procedure 

whereby the rotor would be pre-assembled in port before load-out for offshore installation. 

Additionally, the tower for the turbine would be completely assembled in port so that only a 

single offshore lift is necessary for its installation. The preferred IO&M strategy for the case 

study also included advancement in O&M where an improved U.S. work boat for crew transfer 

is used. This improved work boat reduced the waiting time caused by weather by increasing the 

allowable working sea state for average U.S. work boats from a significant wave height of 0.9 m 

to 1.5 m. Based on the wind and wave conditions at the hypothetical case study location, 

increasing the allowable sea state for work boats beyond 1.5 m would not provide significant 

impact on LCOE. 

Through the changes implemented in the preferred case study, a number of improvements were 

made to the LCOE. The changes to the turbine installation strategy had a mixed impact; ports 

and staging costs increased while installation vessel costs decreased. The nearly tripling in ports 

and staging costs is primarily a result of the increased storage area needed for the pre-assembled 

 

2 Total O&M effort numbers presented in this report represent the sum of revenue losses and accrued O&M costs on a yearly basis. The $/kWh O&M 

costs, however, do not include the direct cost of revenue losses. Rather, the impact from loss of revenue on a $/kWh basis is accounted for via the 

change in energy production.
xii 

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rotors. The improved assembly strategy, however, reduced the vessel costs by $185/kW (15%), 

which far outweighs the increase in port and staging costs. 

Overall O&M costs were lowered by $0.0035/kWh (12%), primarily because the increased sea 

state limits allowed for significantly reduced waiting periods. This reduction in waiting time has 

a substantial impact on the energy production, raising availability from 84.5% to 93.3%, an 

increase of nearly 12% or 381 MWh/MW per year. This increase in annual energy production 

(AEP) is the primary contributor to the overall reduction in LCOE seen in Table 5. 

Table 5. Improvements in LCOE through the preferred IO&M strategy

Baseline Preferred Impact

AEP (MWh/MW/yr) 3267 3648 +11.7% 

Availability (%) 84.5 93.3 +10.4%

O&M ($/kWh) 0.0283 0.0248 -12.4%

Ports & Staging ($/kW) 26 79 +304%

Installation Vessels ($/kW) 1240 1055 -15%

LCOE ($/kWh) 0.233 0.200 -14%

The IO&M improvements resulted in a sizable reduction in the overall LCOE for the case study. 

A change in turbine installation strategy combined with an improved work boat decreased the 

LCOE for the preferred case study from a baseline of $0.233/kWh to $0.200/kWh. This 14% 

reduction in LCOE is primarily attributable to the increase in AEP and is a strong indicator that 

careful planning and analysis of IO&M strategies can significantly reduce LCOE. 
xiii

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Table of Contents

List of Figures ........................................................................................................................................... xv

List of Tables ............................................................................................................................................. xv

1 Introduction ........................................................................................................................................... 1

1.1 Disclaimer........................................................................................................................................ 1

1.2 Background...................................................................................................................................... 1

1.3 Scope of Work ................................................................................................................................. 2

1.4 LCOE............................................................................................................................................... 3

2 Wind Plant Characteristics.................................................................................................................. 5

2.1 Wind Plant Parameters..................................................................................................................... 5

2.2 Wind Turbine Parameters................................................................................................................ 5

3 Baseline IO&M Strategy....................................................................................................................... 7

3.1 Installation ....................................................................................................................................... 7

3.1.1 Assumptions for baseline installation strategy.................................................................. 7

3.1.2 Baseline Installation Costs................................................................................................ 8

3.2 Operation & Maintenance................................................................................................................ 9

3.2.1 Assumptions for baseline O&M strategy.......................................................................... 9

3.2.2 Baseline O&M Costs ...................................................................................................... 11

3.3 Baseline LCOE .............................................................................................................................. 13

4 Advanced IO&M Strategies................................................................................................................ 15

4.1 Installation ..................................................................................................................................... 15

4.1.1 Division of Land-based vs. Offshore Assembly ............................................................. 16

4.1.2 Direct Delivery of Turbine and Foundation.................................................................... 18

4.1.3 Purpose-Built Installation Vessel.................................................................................... 19

4.1.4 Electrical and Foundation ............................................................................................... 19

4.1.5 Summary ......................................................................................................................... 19

4.2 Operation & Maintenance.............................................................................................................. 20

4.2.1 Mother Vessel Accommodations.................................................................................... 20

4.2.2 Helicopter Access ........................................................................................................... 22

4.2.3 Vessel Contracts.............................................................................................................. 25

4.2.4 Improved Crew Transfer System .................................................................................... 26

4.2.5 Spare Part Storage........................................................................................................... 28

4.2.6 Advanced Condition-Based Monitoring ......................................................................... 29

4.2.7 Summary ......................................................................................................................... 30

5 Preferred IO&M Case Study............................................................................................................... 32

5.1 Preferred Installation Strategy ....................................................................................................... 32

5.2 Preferred O&M Strategy................................................................................................................ 34

5.3 Project-Owned Jack-Up Vessel ..................................................................................................... 38

5.4 Preferred IO&M Strategy .............................................................................................................. 40

6 Conclusions ........................................................................................................................................ 41

6.1 Disclaimer...................................................................................................................................... 42

6.2 Recommendations for Future Work............................................................................................... 42

References................................................................................................................................................. 43

Appendix A. Wind and Wave Data........................................................................................................... 45

Appendix B. NREL BOS Model Overview............................................................................................... 49

Overview .............................................................................................................................................. 49

Development ........................................................................................................................................ 49

Port and Staging ................................................................................................................................... 50

Support Structure.................................................................................................................................. 50

Electrical Infrastructure........................................................................................................................ 51

Array Cable.................................................................................................................................... 51
xiv 

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Export Cable .................................................................................................................................. 51

Offshore Substation ....................................................................................................................... 51

Installation Vessels............................................................................................................................... 52

Decommissioning................................................................................................................................. 52

Appendix C. Detailed O&M Assumptions............................................................................................... 54

General Wind Plant Data...................................................................................................................... 54

Wind Plant Breakdown and Failure Rates............................................................................................ 55

Wind Turbine................................................................................................................................. 55

Balance of Plant............................................................................................................................. 57

Maintenance Categories and Fault Type Classes................................................................................. 58

Wind Turbine................................................................................................................................. 58

Balance of Plant............................................................................................................................. 67

Repair Strategy: Transportation and Lifting Equipment ..................................................................... 69

Preventive Maintenance and Fixed Yearly Costs................................................................................. 73

Appendix D. Vessel Data.......................................................................................................................... 75

Workboat Access Vessel ...................................................................................................................... 76

Jack-Up Vessel..................................................................................................................................... 77

Cable Layer .......................................................................................................................................... 78

Diving Support Vessel.......................................................................................................................... 79

Turbine Crane....................................................................................................................................... 80

Appendix E. Maintenance Categories and Repair Strategies............................................................... 81

Wind Turbine ....................................................................................................................................... 81

Cat. 1: Remote Resets................................................................................................................... 81

Cat. 2: Inspection and Small Repair Inside the Turbine ............................................................... 82

Cat. 3: Inspection and Small Repair Outside the Turbine............................................................. 82

Cat. 4: Replacement of Small Parts (< 2000 kg)........................................................................... 83

Cat. 5: Preventive Replacement of Small Parts (< 2000 kg) ........................................................ 84

Cat. 6: Replacement of Large Parts with Large External Crane on Jack-Up Vessel .................... 84

Balance of Plant (BOP)........................................................................................................................ 86

Cat. 1: Small repair in transformer station.................................................................................... 86

Cat. 2: Large Repair in Transformer Station................................................................................. 87

Cat. 3: Small Repair to Foundation or Scour Protection............................................................... 87

Cat. 4: Cable Replacement............................................................................................................ 88

Appendix F. Preferred O&M Detail .......................................................................................................... 89
xv 

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List of Figures

Figure 1. Impact of installation strategies investigated ...............................................................................viii

Figure 2. Assumed wind plant location ......................................................................................................... 5

Figure 3. Power curve of the NREL offshore 5-MW reference wind turbine................................................. 6

Figure 4. Impact of assembly strategy on installation vessel costs ............................................................ 18

Figure 5. Summary of the impact of the installation strategies studied ...................................................... 20

Figure 6. LCOE as a function of logistic time and MOB/DEMOB costs of a jack-up vessel....................... 26

Figure 7. Model output as a function of the maximum allowed significant wave height of the 

workboats ............................................................................................................................................. 27

Figure 8. Significant wave height nonexceedance distribution for the mid-Atlantic and North Sea ........... 28

Figure 9. Example of the calculated relation between waiting time and mission time as determined 

using the WaitingTime module for the jack-up barge—yearly average for weather window no. 1 ...... 46

Figure 10. Waiting time as a function of mission time for the eight defined weather windows................... 47

Figure 11. Yearly average wind climate at 10-m height, as derived from the 10 years of hourly wind 

speed data............................................................................................................................................ 48

List of Tables

Table 1. Summary of Baseline LCOE..........................................................................................................vii

Table 2. IO&M strategies investigated.........................................................................................................vii

Table 3. Quantitative summary of the O&M strategies investigated.............................................................ix

Table 4. Summary of O&M strategies studied with highest improvement opportunity ................................. xi

Table 5. Improvements in LCOE through the preferred IO&M strategy ......................................................xii

Table 6. Turbine specifications for NREL offshore 5-MW baseline reference wind turbine ......................... 6

Table 7. Baseline BOS cost items ................................................................................................................ 8

Table 8. Costs and downtimes of the baseline caused by preventive and corrective maintenance .......... 12

Table 9. Summary of baseline LCOE ......................................................................................................... 13

Table 10. Time, wind, and wave limits for the six wind turbine installation strategies investigated............ 16

Table 11. Offshore lift operations for each installation strategy investigated ............................................. 17

Table 12. Model input for the helicopter...................................................................................................... 23

Table 13. Specifications for the helicopter.................................................................................................. 24

Table 14. Spare part logistic time for a scenario without onsite spare parts .............................................. 29

Table 15. Model output as a function of the percentage of corrective failures that can be preventively 

replaced because of information from condition monitoring systems for the drive train and 

generator .............................................................................................................................................. 30

Table 16. Quantitative summary of the O&M strategies investigated......................................................... 31

Table 17. Preferred BOS cost items ........................................................................................................... 33

Table 18. Summary of O&M strategies studied with highest improvement opportunity ............................. 36

Table 19. Summary of preferred LCOE ...................................................................................................... 40

Table 20. Advanced IO&M strategies ......................................................................................................... 41

Table 21. Improvements in LCOE through the preferred IO&M strategy ................................................... 42

Table 22. Weather windows for which the relation between waiting time and mission time is 

calculated.............................................................................................................................................. 45

Table 23. Weibull parameters per season at 10-m height, as derived from the hourly wind speed data... 48

Table 24. General data for the U.S. baseline wind plant ............................................................................ 54

Table 25. Cost and availability of technicians and length of working day................................................... 55

Table 26. Annual failure rates of components for the NREL offshore 5-MW baseline wind turbine........... 56

Table 27. Conversion of taxonomy used for data collection in Reliawind project to RDS-PP taxonomy ... 57

Table 28. Annual failure rates of components for the considered BOP items ............................................ 58

Table 29. Maintenance Categories and Fault Type Classes for wind turbine failures................................ 59

Table 30. Fault Type Classes for wind turbine failures............................................................................... 61

Table 31. Assignment of additional inspections for wind turbine failures ................................................... 63

Table 32. Wind turbine MCs and FTCs....................................................................................................... 65

Table 33. Maintenance Categories and Fault Type Classes for BOP failures ........................................... 67

Table 34. Fault Type Classes for BOP failures (1) ..................................................................................... 67
xvi 

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Table 35. Fault Type Classes for BOP failures (2) ..................................................................................... 68

Table 36. Assignment of MCs and FTCs for BOP components ................................................................. 68

Table 37. Definition of equipment for baseline O&M cost model................................................................ 69

Table 38. Definition of logistic times and costs for jack-up during winter and summer seasons................ 71

Table 39. Equipment applied per Maintenance Category for wind turbine (top) and BOP (bottom) .......... 72

Table 40. Input parameters preventive maintenance wind turbine and BOP structures ............................ 74

Table 41. Specifications of the workboat access vessel............................................................................. 76

Table 42. Specifications of the jack-up vessel with crane .......................................................................... 77

Table 43. Specifications of the cable-laying vessel .................................................................................... 78

Table 44. Specifications of the diving support vessel ................................................................................. 79

Table 45. Specifications of the nacelle crane ............................................................................................. 80

Table 46. Maintenance Categories for the turbine...................................................................................... 81

Table 47. Maintenance Categories for Balance of Plant ............................................................................ 86

Table 48. Summary of downtime and cost of potential preferred O&M strategies ..................................... 89
1 

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1 Introduction

This document summarizes the work completed by the National Renewable Energy Laboratory 

(NREL) and its subcontractor, the Energy Research Centre of the Netherlands (ECN), in 

fulfillment of a U.S. Department of Energy (DOE) contract for subtopic 5.3: Optimized 

Installation, Operation, and Maintenance Strategies under topic 5: Optimized Infrastructure and 

Operations of Funding Opportunity Announcement (FOA) number DE-FOA-0000414, entitled 

“U.S. Offshore Wind: Removing Market Barriers.” For those carrying out project-specific 

evaluations of cost-effective IO&M approaches presented herein, several related studies also 

conducted under this FOA will serve as valuable resources on specific aspects of offshore wind 

development infrastructure including ports, vessels, and supply chain parameters. 

1.1 Disclaimer

This study does not represent an existing wind plant, or a wind plant currently under 

development. The same holds true for the reference wind turbine used in this study. All data used 

in this study (among others: failure data, vessel capabilities and costs, repair strategies and wind 

turbine specifications) are relative and should not be taken as facts. Although the authors have 

attempted to use figures that are representative of contemporary large offshore wind plants, 

readers must always use their own data, applicable to their own situation. However, the data in 

this document can be used as a starting point with the relative changes associated with each 

strategy providing useful insight into overall trends. 

1.2 Background

The DOE National Offshore Wind Strategy guides the national effort to reduce the levelized cost 

of energy (LCOE) and deployment timelines for future offshore wind power projects (U.S. 

Department of Energy, 2011). 

Currently, installation, operation, and maintenance (IO&M) costs are expected to account for 

approximately 30% of the LCOE of offshore wind plants in the United States (U.S. Department 

of Energy, 2011). The National Renewable Energy Laboratory (NREL) along with its proposal 

partners, hereafter referred to as the Team, were granted an award by DOE under FOA DE-FOA0000414 to use the offshore wind cost model capabilities developed at NREL, along with the 

operating experience and O&M modeling capabilities of the rest of the Team, to meet the 

following main project objectives: 

• Conduct analysis and modeling to identify the most practical means of reducing LCOE and 

ensuring safety through advanced IO&M techniques, integrated service providers, and 

preferred supporting infrastructure 

• Identify preferred IO&M strategies in a case study of a hypothetical U.S. offshore wind 

project. 

This report is intended to provide industry stakeholders a basis for evaluating potential cost 

saving installation, operation, and maintenance (IO&M) strategies and technologies. Some of the 

IO&M strategies in this report were analyzed without projecting the capital expenditures 

associated with an enabling technology or method. Thus, the results show the upside or added 

value to a strategy (e.g. increased energy production), and not the potential downside (e.g. added 
2 

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at www.nrel.gov/publications.

capital cost of new hardware). The results of the analysis can therefore be used by industry 

stakeholders to take the cost savings presented in this report and add their revised technologies 

costs to arrive at a net decrease or increase in cost of energy resulting from a proposed IO&M 

strategy. This allows many technologies that target the same improvement area to be evaluated 

subsequent to this study. To clarify this concept, an example is presented below. 

Company X is interested in bringing an innovative vessel capable of operating at 

higher wind and wave conditions to market. If a strategy using an innovative 

vessel capable of operating in higher wind and wave conditions (similar to 

Company X’s design) is shown to reduce costs by $100/kW with respect to the 

baseline, Company X can see that in order to be viable in the market, they must be 

able to deliver their innovative vessel at a rate no more than $100/kW greater than 

the vessel used in the baseline. If Company X can deliver their innovative vessel 

at $25/kW more than the baseline, they will have demonstrated that their new 

vessel technology is capable of saving $75/kW with respect to the baseline. 

1.3 Scope of Work

The work in this study, titled “Analysis of Installation, Operation, and Maintenance Strategies to 

Reduce LCOE”, identifies the principal IO&M cost drivers while quantifying their impacts on 

the cost of energy. The work also identifies a preferred IO&M strategy for a hypothetical U.S. 

offshore wind project through a case study. Project objectives focus on understanding near-term 

U.S. offshore wind installation and long-term operation and maintenance (O&M) costs. 

As primary awardee for this project, NREL led all project management activities in addition to 

installation and LCOE analysis. Using data received through a separate contract with GL Garrad 

Hassan, a due diligence consultancy with direct experience in the area of offshore wind 

installations, NREL recently developed an offshore wind turbine installation cost model that is 

incorporated within the offshore balance of station (BOS) model. Using this new installation 

model, NREL conducted an analysis to identify primary installation cost drivers; the results 

quantify the potential impact on reducing the cost of energy for U.S. offshore wind projects. 

NREL contracted with the Energy Research Centre of the Netherlands (ECN) to use its 

commercially available O&M Tool (Obdam, Braam, & Rademakers, 2011) to model U.S. site 

conditions. The ECN O&M Tool v.4 was modified to represent U.S.-specific vessel capabilities, 

costs, and metocean data. ECN conducted an analysis to identify primary O&M cost drivers 

using the newly adapted O&M Tool; the results quantify the potential impact on reducing the 

cost of energy for U.S. offshore wind projects. 

The Team developed a hypothetical U.S. offshore wind plant case study to analyze the most 

practical means to reduce the cost of offshore wind energy while ensuring safety through 

advanced IO&M techniques. The case study used real-world wind and wave condition data, but 

parameters such as project size and distance from shore were chosen to represent a typical full

scale wind plant. A suite of alternative IO&M techniques was identified and applied to the 

baseline hypothetical offshore wind project to quantify the impact on system LCOE. The Team 

developed a preferred strategy for the hypothetical U.S. offshore wind project based on this 

sensitivity analysis and international experience.
3 

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1.4 LCOE

In the past, the Wind Partnerships for Advanced Component Technology (WindPACT) studies, 

conducted by DOE and led by NREL, used LCOE as a comparative metric. This method 

provided valuable insight to evaluate innovative concepts for reducing the cost of energy for 

land-based wind projects (Malcolm & Hansen, 2006) (Griffin, 2001) (Shafer, et al., 2001) 

(Smith, 2001). Accordingly, LCOE will be the primary metric used to compare various IO&M 

strategies in this study. The LCOE analysis approach is an all-inclusive, cradle-to-grave analysis 

of costs and energy production related to a power production facility. LCOE analysis permits the 

evaluation of the life-cycle costs of an offshore wind project, including capital investment costs 

(including installation), O&M costs, finance costs, and estimated energy production. 

For the purposes of this study, a number of assumptions had to be made with regard to the way 

LCOE is calculated (Short, Daniel, & Holt, 1995). We use the following equation and 

assumptions to calculate LCOE in this study: 

LCOE = �

ICC∗FCR

AEP � + O&M (1.4-1) 

Where:

ICC = OCC + (OCC ∗ CF) (1.4-2) 

 = Installed Capital Cost

OCC = TCC + BOS + Soft Costs (1.4-3) 

 = Overnight Capital Cost 

FCR = Fixed Charge Rate (Set to 11.8% for this study3)

O&M = Operation and Maintenance4

AEP = Annual Energy Production

TCC = Turbine Capital Cost �Set to $1800

kW for this study�

BOS = Balance of Station Costs

Soft Costs = Insurance + Contingency + Decommissioning (1.4-4) 

Insurance = (TCC + BOS) ∗ 0.02 (1.4-5) 

Contingency = (TCC + BOS) ∗ 0.1 (1.4-6) 

CF = Construction Financing (Set to 3% for this study5)

 

3 (Tegen, Hand, Maples, Lantz, Schwabe, & Smith, 2012)

4 O&M may be tax deductible to an extent. For the purposes of this study it is assumed that O&M has no tax deduction. If a tax deduction is applied to

O&M, the impact on LCOE of any innovations in O&M would be less substantial. Sources suggest a 60% tax deduction may be appropriate (Tegen, 

Hand, Maples, Lantz, Schwabe, & Smith, 2012)
4 

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at www.nrel.gov/publications.

Financial parameters needed for the LCOE analysis have been selected from NREL’s 2010 cost 

of energy review (Tegen, Hand, Maples, Lantz, Schwabe, & Smith, 2012) in an effort to 

represent expected U.S. offshore wind financial parameters as closely as possible. Because the 

turbine capital cost does not influence the relative results or conclusions of this analysis, a 

rounded value of $1,800/kW was used, based on values obtained from the 2010 Cost of Energy 

Review (Tegen, Hand, Maples, Lantz, Schwabe, & Smith, 2012). The BOS costs were estimated 

using NREL’s offshore BOS model, which is described in more detail in Appendix B. The O&M 

and AEP values for the LCOE analysis were calculated using the ECN offshore O&M Tool, 

which is described in more detail later in the report.

 

5 (Tegen, Hand, Maples, Lantz, Schwabe, & Smith, 2012)
5 

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2 Wind Plant Characteristics

2.1 Wind Plant Parameters

A hypothetical 500-MW wind plant consisting of 100 turbines of 5-MW rated capacity each, 

sitting atop monopile foundations, was established for all analyses in this study. The wind plant 

is assumed to be located in the Atlantic Ocean approximately 46 km (~25 nmi) off the coast of 

the U.S. state of Virginia, (see Figure 2.) The nearest port that is accessible for large vessels is 

The Port of Virginia at an approximate distance of 86 km (~46 nmi) from the wind plant (The 

Port of Virginia). The water depth at the location of the wind plant is approximately 30 m. The 

wind plant is assumed to be connected to the grid via an onshore substation, which is 

subsequently connected to a hypothetical offshore substation via two three-phase 220-kV subsea 

cables. Array cabling is arranged in a radial layout using three-phase 33-kV subsea cables. 

For all wind and wave parameters, 120 months of Wavewatch III hindcast data files covering the 

period from January 1, 2000 through December 31, 2009 for the WIS grid point 63198 were

used. The raw data is not freely available; however, more information on how the data were 

processed and used, as well as representative statistics can be seen in Appendix A. 

Figure 2. Assumed wind plant location

2.2 Wind Turbine Parameters

The 5-MW wind turbine used for reference in this study is the “NREL offshore 5-MW baseline 

wind turbine.” This theoretical turbine is representative of typical utility-scale, multi-megawatt 

turbine. The turbine is controlled via a variable-speed, collective-pitch control system connected 

through a high-speed drive train, using a multiple-stage gearbox design (Jonkman, Butterfield, 
6 

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Musial, & Scott, 2009). Main turbine specifications are given in Table 6, and a plot of the power 

curve is given in Figure 3. 

Table 6. Turbine specifications for NREL offshore 5-MW baseline reference wind turbine 

Parameter Value

Rotor diameter 126 m

Hub height 90 m

Rated power 5 MW

Power regulation Variable speed, collective pitch control system

Nacelle Crane Capacity 2000 kg

Figure 3. Power curve of the NREL offshore 5-MW reference wind turbine

The turbine is assumed to be equipped with an internal crane that is able to hoist small 

components like pitch motors and yaw drives (weight < 2000 kg). These components can be 

placed on a platform at the bottom of the tower during the replacement activities; hoisting can be 

done outside the tower using a crane located at the nacelle. For hoisting large components 

(generator, blades, nacelle, etc.) a large external crane is required, such as a crane on a jack-up 

vessel.
7 

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3 Baseline IO&M Strategy

3.1 Installation

For analyzing the baseline installation cost, NREL expanded the capability of its offshore BOS 

model. The model is capable of calculating budgetary level estimates for engineering, permitting, 

ports/staging, foundations, electrical infrastructure, vessels, and decommissioning. All 

noninstallation activities were calculated for the baseline using this model and were set constant 

for the analysis of the advanced installation strategies. A more detailed overview of the offshore 

BOS model and the data sources used therein can be seen in Appendix B. 

3.1.1 Assumptions for baseline installation strategy

To calculate the baseline installation costs we had to account for several aspects of the associated 

port and staging costs as well as vessel costs. 

We made the following port and staging, vessel, and installation assumptions: 

• All installation activities are staged out of the nearby harbor facility at The Port of Virginia, 

located 86 km from the wind plant. 

• The staging port is used to store 10 turbines at a time in preparation for installation. 

• Turbine components are delivered to the staging facility as soon as the original turbines leave 

for installation (i.e., 10 turbines remain at port at any given time during the installation 

period). 

• A dynamically positioned (DP2) heavy-lift cargo vessel is used to ferry the components from 

the foundation and turbine manufacturers to the staging port. 

• A set of offshore barges and seagoing tugs transports the foundations and components from 

the staging port to the wind plant. 

• A jack-up vessel is used to install the wind turbines. 

• The baseline turbine installation requires seven offshore lifts: 

1. First half of the tower

2. Second half of the tower 

3. Nacelle

4. Hub

5. Blade 1

6. Blade 2

7. Blade 3. 

• Decommissioning of the wind plant is carried out in reverse order of installation, and at a 

faster pace with lower day rates for vessels. More detail on the decommissioning 

assumptions can be seen in Appendix B.
8 

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• Foundations and offshore substation are lifted and set in place using a heavy-lift vessel. 

• Electrical cabling is installed with a cable-laying vessel with the assistance of a remotely 

operated vehicle (ROV). 

• A horizontal drilling rig, along with a dive support team, is used for the landfall operations of 

the export cable. 

• Supporting ocean-going tugs and crew vessels are used throughout the installation process. 

In practice, increased installation efficiency may be expected as an increasing number of 

offshore wind turbines are installed, leading to cost reductions. However, relevant installation 

cost reduction data were not available for this analysis, so we held all installation costs constant 

for the baseline installation strategy (e.g., the installation costs for the first few turbines of the 

100-turbine plant are equal to the costs of installing the last few turbines of the plant).

3.1.2 Baseline Installation Costs

The baseline installation strategy resulted in a total installation cost of $633 million dollars, 

which includes the costs of ports and staging and vessels. Vessel costs accounted for the majority 

of the total installation costs. 

Of the total vessel costs during installation, the largest cost is that of the cable-laying vessel, but 

is followed closely by the heavy-lift vessel, and the jack-up vessel. These results suggest that 

improvement in installation-related activities can provide a significant reduction in installation 

costs. Possible solutions to reducing these vessel costs could include reducing the time needed 

for the vessel activities by improving processes, or reduced vessel costs through vessel 

ownership. Similar savings could be achieved during the decommissioning phase if the strategies

were carried over. 

Additional savings may be realized by eliminating the use of a staging port. Though the staging 

port is not an overwhelming cost item, implementing just-in-time delivery of components to the 

wind plant from the manufacturing facility may prove valuable. A summary of the baseline BOS 

costs is presented in Table 7. 

Table 7. Baseline BOS cost items

Baseline BOS Cost Item ($/kW) ($/kWh)

Development 118 0.0043

Ports and Staging 26 0.0009

Support Structure 800 0.0289

Electrical Infrastructure 498 0.0180

Installation Vessels 1240 0.0448

Total 2682 0.0969
9 

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3.2 Operation & Maintenance 

The ECN O&M Tool Version 4 was developed to estimate the long-term annual average costs 

and downtime of an offshore wind farm (ECN Wind Industrial Support, 2012). The O&M tool is 

most appropriate when used in the planning phase of a wind farm. The Tool was used to estimate 

the costs of our baseline O&M strategy. 

The tool uses long-term average data as input (failure rates, wind and wave statistics, costs of 

vessels and spare parts, lead time of vessels and spare parts, etc.) and generates long-term 

average values as output (costs, downtime, and required resources). Evaluating a baseline 

scenario with the ECN O&M tool can reveal important O&M costs drivers, which can then be 

further analyzed via alternative scenarios to determine a preferred O&M strategy. 

The tool is straightforward because it is programmed in MS-Excel. Each change in the input 

parameters immediately results in a change of the output parameters. The tool includes 

automatically generated tables, pie charts, and bar charts to identify the drivers for costs and 

downtime and to assist in defining an improved strategy. The model requires an extensive list of 

input parameters and a detailed description of the proposed O&M strategy. These requirements

force the user to consider all aspects of O&M in detail. 

In 2007, the tool received a validation statement from Germanischer Lloyd, which makes it the 

only software validated worldwide for analyzing offshore wind O&M. 

To model O&M costs, six wind turbine maintenance categories (MCs) and four BOS MCs were 

used, in which each MC is split up into one or more fault type classes (FTC). The material costs, 

crew size, repair time and logistic time are all based on experience from ECN with O&M 

modeling. The FTCs were developed largely based on Obdam & van der Zee (Obdam & van der 

Zee, 2011). The FTCs are developed based on an analysis of the contribution to overall 

downtime and engineering judgment to classify small, medium, and large repair actions. These 

analyses were performed in the past by ECN together with a turbine manufacturer. The costs for 

spare parts are quantified using a breakdown that shows the contribution of different component 

costs to the total investment costs of a modern geared wind turbine. More detail on MCs and 

FTCs can be seen in Appendix C. 

3.2.1 Assumptions for baseline O&M strategy

Generally, the costs for maintaining an offshore wind plant will be determined by both corrective 

and preventive maintenance. We used the ECN O&M tool to estimate the long-term yearly 

average O&M costs (including both corrective and preventive maintenance costs and conditionbased costs, when applicable) for the wind plant, as well as turbine availability during the same 

time period. To develop the baseline scenario and determine the values of the inputs for the ECN 

O&M Tool, we made several assumptions that are spelled out in the following list.

• Component replacements: 

o The failure rate of components is constant over time. 

o Large components are not kept in stock at the harbor. 
10 

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o Small parts (up to 2000 kg) are kept in stock at warehouse facilities located at the 

harbor. 

o Small parts are picked up from the vessel with a crane on the platform of the 

transition piece of the turbines; they are then lifted into the nacelle using the 

internal nacelle crane. 

• Vessel types and limitations:

o Workboats: 

̶ Used to transport small components (up to 2000 kg) from the harbor to the 

turbines. 

̶ Provide access to the offshore substation for small repairs. 

̶ Provide technicians access to the turbine for the replacement of larger 

components. 

̶ Wave height restrictions for the workboats for the baseline scenario were 

established with the current U.S. offshore oil and gas O&M vessel fleet in 

mind. Based on industry communications, these vessels operate in 

significant wave heights ranging from 0.5 m to 1.3 m (DouglasWestwood, 2012) (Frongillo, 2012). The average of this range, 0.9 m, is 

used for the baseline. Though typical offshore wind workboats in Europe 

have significant wave height restrictions around 1.5 m, those types of 

vessels are not currently operating in the United States and therefore were 

not considered for the baseline scenario. 

o Cable-laying vessel:

̶ Required to repair power cables inside the wind plant 

o Diving support ship (and crew of divers): 

̶ Used for preventive maintenance of cables and foundations 

o Jack-up vessel: 

̶ Required for the replacement of larger components (weights in excess of 

2000 kg) 

̶ Used to transport spare parts to the wind plant. 

• Personnel: 

o Personnel work only during daylight periods—14 hours (h) in summer, 12 h in 

spring and autumn, and 10 h in winter—except for repairs that require the use of a 

jack-up vessel, when two shifts of technicians will work 24 h per day. 

o Technicians are paid $125/h per person (Obdam & van der Zee, 2011). 

o Two teams of technicians working in 12-h shifts carry out replacements of large 

components. 
11 

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• Distance between harbor and wind plant: 

o Corrective and preventive maintenance will be performed from nearby harbor 

facilities located at The Port of Virginia, 86 km from the wind plant. 

o Average travel time to a turbine is 2.6 h, includes transfer of personnel to turbine. 

Detailed O&M assumptions, including failure frequencies, repair costs, repair logistics, and 

general wind plant data, are presented in Appendix C. 

3.2.2 Baseline O&M Costs

The baseline O&M scenario yields an availability of 84.5% and O&M costs of $0.0283/kWh, 

resulting in a total O&M effort (sum of O&M costs and revenue losses) of $86.9 million per 

year.

6

 The majority of downtime is associated with corrective maintenance on the wind turbine 

and balance of plant structures.

For small and medium size failures, the largest portion of downtime is caused by the workboat 

vessel waiting for bad weather to clear. For large failures, a primary contributor to overall 

downtime is the long logistic (mobilization) time for the jack-up vessel. These results suggest 

that, for the baseline O&M scenario, downtime can best be reduced by employing a vessel(s) that 

has less strict weather limits in terms of allowable wave height (e.g., another type of vessel or a 

helicopter) and/or reducing the required weather window (WeWi) length (e.g., using mother 

vessel accommodations to reduce travel times). Additional downtime reduction could be 

achieved with long-term contracts or in-house operations to enable quicker access to jack-up 

vessels. 

The majority of direct repair costs are related to corrective WT costs. For large replacements, the 

equipment costs dominate the total repair costs. Also, executing a long-term contract or in-house 

operations with a jack-up vessel may be beneficial if mobilization/demobilization costs could be 

lowered. 

The baseline O&M results indicate that most downtime and costs are related to failures in the 

control and protection system generator, followed by the blade adjustment, drive train, control 

and protection system turbine, and generator systems. The use of condition monitoring systems 

might be feasible to apply condition-based maintenance, thereby reducing corrective 

maintenance costs and downtime.

Table 8 shows the breakdown of downtime and costs for the baseline O&M scenario. A 

breakdown is given for each of the four seasons, which are added in the Total column. The 

results in the Year column differ from the Total column because the values in the Year column 

were calculated for average annual weather windows, rather than seasonal weather windows. In 

this analysis we account for seasonal differences in weather windows by using all results from 

the Total column. 

 

6 Total O&M effort numbers presented in this report represent the sum of revenue losses and accrued O&M costs on a yearly basis. The $/kWh O&M 

costs, however, do not include the direct cost of revenue losses. Rather, the impact from loss of revenue on a $/kWh basis is accounted for via the 

change in energy production. 
12 

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Table 8. Costs and downtimes of the baseline caused by preventive and corrective maintenance

Summary of downtime and costs Availability [%] 84.5%

Location U.S. baseline IO&M case study Costs [ $ct/kWh] 2.83

Type of WT NREL offshore 5-MW baseline Total effort [M $] 86.9

Wind farm 100 turbines

Winter Spring Summer Autumn Total Year

Downtime per year

Corrective WT Logistics hr 3,333 3,308 4,378 3,308 14,327 13,232

Waiting hr 39,794 18,404 5,404 25,667 89,269 73,926

Travel hr 385 385 385 385 1,540 1,540

Repair hr 3,460 2,819 1,934 2,819 11,031 11,275

TOTAL corrective WT hr 46,971 24,916 12,101 32,179 116,167 99,973

Corrective BOP Logistics hr 1,999 1,999 1,999 1,999 7,995 7,995

Waiting hr 2,166 1,715 561 2,964 7,406 6,838

Travel hr 33 33 33 33 130 130

Repair hr 594 503 253 503 1,853 2,011

TOTAL corrective BOP hr 4,792 4,249 2,845 5,498 17,384 16,974

Preventive TOTAL preventive hr 0 924 1,452 264 2,640 2,640

TOTAL hr 51,763 30,089 16,398 37,941 136,192 119,587

Availability % 76.4% 86.3% 92.5% 82.7% 84.5% 86.3%

Loss of production per year MWh 145,677 70,631 25,840 83,854 326,003 269,765

Energy production per year MWh 470,656 443,444 319,255 400,167 1,633,521 1,706,325

Revenue losses per year kUSD 18,210 8,829 3,230 10,482 40,750 33,721

Costs of repair per year

Material costs

Corrective WT TOTAL corrective WT kUSD 4,171 4,171 4,171 4,171 16,684 16,684

Corrective BOP TOTAL corrective BOP kUSD 15 15 15 15 58 58

Preventive TOTAL preventive kUSD 0 551 866 157 1,574 1,574

TOTAL kUSD 4,186 4,737 5,052 4,343 18,317 18,317

Labour costs

Corrective WT TOTAL corrective WT kUSD 1,164 1,102 997 1,102 4,366 4,410

Corrective BOP TOTAL corrective BOP kUSD 1 1 1 1 5 5

Preventive TOTAL preventive kUSD 0 778 1,103 222 2,103 2,224

TOTAL 1,166 1,882 2,100 1,326 6,474 6,639

Costs equipment

Corrective WT MOB/DEMOB kUSD 1,405 981 1,248 981 4,615 3,924

Waiting kUSD 1,871 1,305 787 1,416 5,379 5,209

Repair kUSD 2,192 1,959 2,326 1,955 8,432 7,826

TOTAL corrective WT kUSD 5,468 4,245 4,362 4,352 18,426 16,959

Corrective BOP MOB/DEMOB kUSD 150 150 150 150 598 598

Waiting kUSD 66 63 57 68 255 251

Repair kUSD 155 152 152 152 611 609

TOTAL corrective BOP kUSD 370 365 359 370 1,464 1,458

Preventive TOTAL preventive 0 565 761 161 1,487 1,610

TOTAL 5,838 5,174 5,482 4,882 21,376 20,027

Corrective WT kUSD 10,803 9,518 9,530 9,625 39,476 38,053

Corrective BOP kUSD 386 380 374 386 1,527 1,522

Preventive kUSD 0 1,894 2,730 541 5,164 5,408

Fixed yearly costs kUSD 0 0 0 0 0 0

Total costs of repair kUSD 11,189 11,793 12,634 10,552 46,168 44,983

Total cost per kWh USD cent/kWh 2.38 2.66 3.96 2.64 2.83 2.64

Total costs of repair per kW installed USD/kW 22 24 25 21 92 90

Total cost per kW investment 1.2% 1.3% 1.4% 1.2% 5.1% 5.0%

Total effort

Sum revenue losses & total costs of repair kUSD 29,399 20,622 15,864 21,033 86,918 78,704
13 

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3.3 Baseline LCOE

As mentioned in the introduction, the primary metric used for comparison in this study is 

levelized cost of energy. Annual energy production estimates were calculated using the ECN 

O&M Tool (Obdam, Braam, & Rademakers, 2011) on a seasonal basis using the same wind data 

set used for the waiting and downtime analysis, detailed in Appendix A. The wind data is 

presented at an elevation of 10 m and is extrapolated to a hub height wind speed using a standard 

shear exponent of 0.1. This extrapolation of wind speeds may lead to uncertainty in the absolute 

energy capture of the wind plant; however, because of the comparative nature of the analysis, 

this extrapolation does not affect the relative impacts of the different IO&M strategies on LCOE. 

Based on the baseline assumptions and analysis presented in sections 3.1 and 3.2, in conjunction 

with the LCOE equations from the introduction, we calculated the baseline LCOE (Table 9). 

Table 9. Summary of baseline LCOE 

($/kW) ($/kWh)

Turbine Capital Cost 1800 0.0650

Development 118 0.0043

Port and Staging 26 0.0009

Support Structure 800 0.0289

Electrical Infrastructure 498 0.0180

Installation Vessels 1240 0.0448

Balance of Station 2682 0.0969

Insurance 90 0.0033

Decommissioning 471 0.0170

Contingency 448 0.0162

Soft Costs 1009 0.0364

Overnight Capital Cost (OCC) 5491 0.1983

Construction Financing 165 0.0060

Installed Capital Cost (ICC) 5656 0.2043

O&M ($/kW/yr) 784 0.0283

Net Annual Energy Production (AEP) (MWh/MW/yr) 3267

Fixed Charge Rate (FCR) 11.8%

Levelized Cost of Energy ($/kWh) 0.233

Roughly 12% of the baseline LCOE is attributable to O&M and 20% to installation activities. 

With more than 30% of the LCOE attributable to IO&M activities, there is significant 

opportunity for cost reduction through IO&M improvement. 

The baseline LCOE is in line with estimates for future offshore wind plants in the general 

vicinity of the baseline project, with the primary exception of AEP (Tegen, Hand, Maples, Lantz, 

Schwabe, & Smith, 2012). The considerably low availability and AEP in the baseline case is 

attributable almost exclusively to the work boat wave restriction of 0.9 m (Douglas-Westwood, 
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2012), which is below values based on European experience used in other analyses (Tegen, 

Hand, Maples, Lantz, Schwabe, & Smith, 2012). Additional reasons for possible differences in 

baseline LCOE could stem from vessel cost assumptions, which can vary substantially. The 

reader should note that this baseline LCOE is substantially dependent on the specific baseline 

assumptions presented above. In the event that any of the assumptions are altered, depending on 

the sensitivity of the assumption to LCOE and how much it is varied, the baseline LCOE may be 

substantially different. In some cases, like those mentioned above, changes in a single 

assumption can alter the baseline LCOE by ±50%. 
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4 Advanced IO&M Strategies

At the onset of the project, a panel of subject matter experts was gathered to brainstorm about 

advanced IO&M strategies. A list of approximately 30 potential IO&M strategies was 

established and subsequently down-selected. The down-selected strategies were chosen based on 

three criteria:

1. Potential impact to LCOE (the larger the reduction the better), 

2. Ease of accurate representation in models (easier the better), and 

3. Assumed time to market of the strategy (shorter the better). 

The down-selected IO&M strategies included four installation strategies and six O&M strategies.

Representatives from the following organizations provided input to the brainstorming session: 

• Siemens 

• General Electric

• Vattenfall

• Global Marine Energy 

• Douglas-Westwood 

• GL Garrad Hassan

• Romax Technology 

• Knud E. Hansen USA 

• U.S. Department of Energy 

• American Wind Energy Association

• NREL

• ECN. 

It should be noted again that some of the analyses are presented in a way in which capital 

expenditures associated with an enabling technology or strategy were not included in the 

analysis. This analysis procedure allows the reader to understand the limitations on increased 

costs associated with implementing a particular strategy or technology, thus allowing many 

technologies that target the same improvement opportunity area to be evaluated for their relative 

value subsequent to this study. 

4.1 Installation 

The proposed strategies to reduce LCOE via changes to installation activities are:

• Division of land-based vs. offshore turbine assembly 

• Direct delivery of turbine and foundation components 

• Project-owned, purpose-built installation vessel

• Modified electrical and foundation installation approaches. 
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In the following subsections, we discuss our analysis of each of the strategies in more detail, 

including the effect on installation time and costs and a qualitative analysis of possible 

limitations. A summary of the quantitative results from each of these strategies is presented in 

Figure 5. 

4.1.1 Division of Land-based vs. Offshore Assembly

Wind turbines can be assembled in a variety of methods that combine assembly at port or at the 

wind plant. The adoption of a particular method will impact transportation, installation weather 

windows, and vessel requirements for the installation. There is inherent variability in the 

duration of any given installation activity; throughout this report, we present the average 

expected installation duration as well as a range (minimum and maximum duration). We used the 

average duration estimate in our analyses. The time, wind, and wave limits as shown in Table 10

were inputs for our analysis of the six wind turbine installation methods. The average installation 

duration is shortest for the fully pre-assembled strategy (8 h) and longest for the individual 

components strategy (34.5 h).The duration of installation is primarily a factor of the number of 

offshore lifts required for each installation method. Table 11 presents the total number of lifts 

and the sequence of the lifts for each of the installation strategies.

Table 10. Time, wind, and wave limits for the six wind turbine installation strategies investigated

Min.

duration 

[h]

Max.

duration 

[h]

Avg.

Duration 

[h]

Wind 

speed limit 

[m/s]

Hs*

limit 

[m]

Individual components 30 39 34.5 8 2

Bunny ears with 2-part tower 21 28 24.5 8 2

Bunny ears with 1-part tower 15 20 17.5 8 2

Pre-assembled rotor with 2-part tower 24 30 27 8 2

Pre-assembled rotor with 1-part tower 18 22 20 8 2

Fully pre-assembled 8 8 8 8 0.75

*High seas 
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Table 11. Offshore lift operations for each installation strategy investigated

WT Install Method

Total 

Lifts

Lower 

Tower

Upper 

Tower

Nacelle Hub

Blade 

1 

Blade 

2 

Blade 

3 

Individual components 7 1 2 3 4 5 6 7

Bunny ears with 2-part tower 4 1 2 3 4

Bunny ears with 1-part tower 3 1 2 3

Pre-assembled rotor with 2-

part tower

4 1 2 3 4 

Pre-assembled rotor with 1-

part tower

3 1 2 3 

Fully pre- assembled 1 1

Not all installation strategies will be appropriate for all projects. Among the many factors that 

will determine which installation methods can be used in a particular project, two important 

factors include the vessel specifications and possible restrictions on transportation methods. 

Within a class of vessels (e.g., heavy lift vessels or self-propelled jack-up vessels), the 

characteristics of each individual vessel (e.g., crane capacity, deck space, and weight limits) will 

determine which installation methods are possible and most suitable. Another influencing factor 

in determining what transportation option best matches the project goals is the possible 

restriction on transportation methods approved by the wind turbine manufacturer because of

stress placed on different components during transportation. 

In practice, the vessel selection process is heavily dependent on vessel availability and market 

conditions, as well as turbine and foundation designs. The model used in our analysis does not 

specifically address the impact of vessel selection on the installation strategy. Because of this 

generalization, the model does not account for the influence of factors such as the number of 

turbines that can fit on a given vessel per trip. Consequently, if one were to investigate these 

strategies for a specific project with prescribed vessel and component dimensions, the results 

may vary from those presented here. 

It should be noted that the fully pre-assembled turbine is installed using a sheerleg crane barge, a 

type of heavy lift vessel. All other methods use a jack-up vessel that is assumed to have suitable 

crane capacity. Average day rates for the jack-up and shear-leg crane vessels are $155,000 per 

day and $675,000 per day, respectively (Douglas-Westwood, 2012). 

Based on the analysis, the least-cost method available was the bunny ears strategy with 1-part 

tower, and the most expensive was the fully pre-assembled strategy. Except for the fully preassembled method, all other methods differed by a cost range of less than $300/kW, as seen in 

Figure 4. 
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The fully pre-assembled WT installation method has costs much higher than other methods for 

several reasons. Despite the single lift requiring the least offshore operations time, the method is 

affected significantly by weather limits. All other methods have a wind and wave limit of 8 m/s 

and 2 m, respectively, while the fully pre-assembled method has a wave height limit of 0.75 m. 

This has a large influence in the weather windows at the site and increases the overall average 

installation time to slightly less than that required for the individual components method, which 

had the lengthiest installation time. Additionally, the heavy lift sheerleg crane is substantially 

more expensive than the jack-up vessel used for the other installation strategies. The use of a 

more expensive vessel was more of a factor than the increased time caused by strict weather 

limits. Even if the sheerleg crane barge could be used with a wave limit of 2 m, the vessel cost 

still makes the fully pre-assembled method the most expensive option, despite the decrease in 

installation time because of the need for the least number of lifts.

The range of costs seen in Figure 4 is the result of the maximum and minimum anticipated 

installation durations shown in Table 10. The variation of WT installation duration could be a 

result of crew experience, improved installation techniques, design improvements, or ship 

modifications that affect the installation time. 

Figure 4. Impact of assembly strategy on installation vessel costs

4.1.2 Direct Delivery of Turbine and Foundation 

Turbines and foundations may be delivered from the manufacturers and fabricators to a staging 

port and then transported to the project site, or delivered directly to the project site (bypassing a 

staging port). Though not the primary driver of overall project costs, port and staging expenses 

can total in the tens of millions of dollars. The need for a staging port is driven by several factors 

that can vary between projects, including size of project, WT installation method, and distance to 

component manufacturers. 

We evaluated installation strategies that included a staging port as well as strategies that do not 

(i.e., direct delivery). We assumed there would always be a stock of components available for 

installation at the staging port and that delivery of components to the staging port would keep up 

with the installation rate. For the analysis of strategies that do not use a staging port, we assumed 

all components would be picked up for installation from the manufacturer’s port, located 150 km 

from the project site. 
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In this analysis, the use of a staging port is the least-cost option by $213/kW, although projectspecific conditions could cause the use of a staging port to be less cost-effective. For example, in 

the case of the bunny ears with 1-part tower strategy, the use of a staging port is not the least cost 

option if the project size is reduced from 500 MW to less than 100 MW. Other factors that can 

impact the economic effectiveness of a staging port are the distance of the component 

manufacturers to the proposed staging port, the need for separate delivery and installation 

vessels, speed of the vessels, and percentage of assembly at port versus at sea. 

4.1.3 Purpose-Built Installation Vessel

The scarcity of suitable turbine installation vessels in the U.S. market could lead to some early 

projects building a purpose-built vessel, which could then be used on an ongoing basis for O&M 

or leased to other projects. For this strategy we assume that a jack-up vessel, the major 

installation vessel for the wind turbines, is purpose-built for the project. This vessel accounts for 

just over 10% of the vessel costs. For the sensitivity analysis, we assume the operating expenses 

during installation activities for the project-owned jack-up vessel are estimated at $77,500 per 

day, 50% of the baseline dayrate based on estimates from (Kaiser & Snyder, 2010). 

Based on the reduced day rate of the project owned jack-up vessel, the analysis shows a potential 

savings of $41 million if the investment cost of the vessel is set to zero. With estimates of jackup vessel capital cost around $120 million, the savings from installation alone would not justify 

the capital cost of a purpose-built vessel. If the savings from the installation phase of the project 

were to be combined with the potential savings during the operational phase of the project, it 

may be financially viable. This combined analysis is presented in detail in section 5.3. 

Additional motivation for a developer building and operating its own installation vessel is the 

ability to customize the vessel specification to optimize its use. The impacts of customization are

heavily dependent on specific turbine specifications, and therefore beyond the scope of this more 

generalized analysis. If an analysis was completed for a specific turbine, location, and baseline 

vessel, the results may indicate that savings from the installation period of vessel use would be 

sufficient enough to justify costs for a purpose-built vessel. 

4.1.4 Electrical and Foundation 

To investigate the sensitivity of total BOS cost to changes in electrical and foundation 

installations approaches we conducted a parametric study. We varied the electrical installation 

costs ($/km) by ±25% to demonstrate the impact of potential future innovative technologies. 

Separately, we varied the foundation installation time by ±3 h per foundation, from a low of 20 h 

to a high of 26 h, to represent average bounds in current foundation technology installation times

(GL Garrad Hassan, 2012). 

The foundation parametric study shows an influence of ±$50/kW on overall BOS cost, but like 

the electrical impact of ±$80/kW, it is not as impactful as the other installation strategies

evaluated. 

4.1.5 Summary

Figure 5 summarizes the results of each of the installation strategies investigated with respect to 

the baseline installed BOS cost (BOS + insurance + contingency + construction financing). The 

different land-based versus offshore assembly strategies have the potential to incur the biggest 
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impact on BOS cost, reducing it by almost $300/kW compared to the baseline, or increasing it by 

approximately $650/kW. The strategy of arranging direct delivery of components to the project 

site (bypassing a staging port) increases the BOS cost compared to the baseline, as does the use 

of a purpose-built installation vessel. Changes to the foundation installation duration would have 

the smallest impact on BOS costs compared to the baseline, and innovations affecting the 

electrical installation could have a slightly larger impact (either increasing or decreasing total 

BOS costs, depending on whether the innovation increased or decreased the electrical costs).

Figure 5. Summary of the impact of the installation strategies studied 

4.2 Operation & Maintenance 

The proposed O&M strategies are:

• Mother vessel accommodation

• Helicopter access

• O&M vessel contracts

• Improved crew transfer system

• Spare part storage

• Advanced CBM. 

Our analysis investigated how each of the proposed strategies affects downtime and O&M costs 

relative to the baseline O&M strategy. In the following subsections we present our findings, 

including a qualitative analysis of possible limitations for each of the alternative O&M strategies

as well as a summary of the qualitative results (Table 16). 

4.2.1 Mother Vessel Accommodations

Mother vessel accommodation has the benefit of significantly reducing the time to access the 

wind plant for minor repairs or inspection, with respect to operating out of port. Additionally, 
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because of the reduced travel times, the fair weather windows are smaller, thus allowing for 

more weather window opportunities that also reduce wind plant downtime. There are also 

disadvantages; both costs of vessels and worker wages are higher with the use of offshore 

accommodations. 

For the baseline scenario, we assume that maintenance is organized from the Port of Virginia at 

an approximate distance of 86 km from the wind plant. This results in a one-way travel time of 

2.6 h. In this subsection we discuss whether organizing the maintenance from an offshore base 

(e.g., a mother vessel) is beneficial for this location.

The mother vessel accommodations scenario differs from the baseline scenario in two ways. 

First, corrective and preventive maintenance will be performed from a mother vessel located

inside or close to the wind plant. From this mother vessel, workboats can be launched with an 

average travel time of 0.5 h, including the transfer of personnel to the turbine. Second, small 

parts (up to 2000 kg) will be kept in stock at the mother vessel instead of the harbor. 

Very little information is available on the costs for such a mother vessel in the United States. As 

a result, we chose not to include an estimated mother vessel cost to avoid false or misleading 

results. Instead, we consider only the benefits associated with this strategy. When more 

information on the investment and operational costs for a mother vessel become available the 

results of this analysis can be used to assess whether the use of a mother vessel would be an 

economically prudent solution. 

Organizing the maintenance from a mother vessel results in a significantly improved availability, 

compared to the baseline scenario, in which workboats are launched from shore. The total 

downtime for corrective maintenance is reduced by almost a factor of two; reduced downtime 

caused by waiting for good weather is the largest contributor to this reduction. This can be 

explained as follows: 

• Because of the shorter travel time each day, 4.2 h of additional working time on the turbines 

is available compared to the baseline; therefore repairs can be completed in fewer days. 

• Waiting time is a function of the length of the total mission. The shorter repair time 

combined with the shorter travel time results in a significantly reduced total mission time, 

which causes an even more significant reduction of the waiting time. 

The costs of repairs are also reduced, albeit by a smaller percent than for downtime. The main 

causes for the cost reduction are the lower costs for equipment during waiting and repair and 

reduced labor costs because everything with a day or hourly rate is utilized for less time. 

Again, it should be emphasized that this analysis did not account for costs of acquiring or 

operating the mother vessel. If more information about the costs of such vessels for the U.S. 

market becomes available, it can be assessed whether the calculated savings ($25 million per 

year compared to the baseline) are sufficient to justify the additional cost of:

• Investment in a mother vessel

• Operation of a mother vessel
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• More expensive offshore technicians because they must live and work offshore for a 

prolonged period of time. 

4.2.2 Helicopter Access

The advantage of using helicopters is that access to the wind plant is not limited by wave height, 

as is the case for workboats. Furthermore, travel times can be reduced. There are also 

disadvantages; no spare parts can be transported via helicopter, and both costs and safety risks 

are higher with the use of a helicopter. 

In this scenario helicopters instead of workboats are used for small repairs and inspections (for 

which no spare parts are required). For all repairs for which spare parts are required, workboats 

are used to transport those parts from the harbor to the wind plant (the same as in the baseline 

scenario). Workboats are used to transfer technicians for preventive maintenance on the wind 

turbines and corrective maintenance on the BOS in both the baseline and the helicopter access 

scenario. 

New model inputs were needed to perform this analysis. The helicopter's application for repair 

and its specifications are detailed in Table 12 and Table 13. 
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Table 12. Model input for the helicopter 

Nr of equipment Description

of equipment

Weather 

window

(normal 

day)

Hs Vw 0 0 Availability (nr. 

of equipment)

nr hr hr Freq.

min ML max min ML max 0: day

1: mission

1 Workboat 3 0.90 12.0 0.00 0.0 0 2.6 0

2 Jack-up barge (100 MT) 1 2.50 10.0 0.00 0.0 720 1

3 Cable layer 5 1.00 25.0 0.00 0.0 720 1

4 Diving support vessel 6 2.00 25.0 0.00 0.0 360 1

5 Turbine crane 7 0.90 10.0 0.00 0.0

6 Blade inspection 8 0.90 8.0 0.00 0.0

7 Helicopter 9 5.00 12.0 0.00 0.0 0 1.0 0

8 0.00 0.0 0.00 0.0

9 0.00 0.0 0.00 0.0

10 0.00 0.0 0.00 0.0

11 0.00 0.0 0.00 0.0

12 0.00 0.0 0.00 0.0

13 0.00 0.0 0.00 0.0

T logistic equip. T travel (+access)

one way

(For information only)

Nr of equipment Description

of equipment

USD/year USD/

mission

USD/

unit

unit Weighing

factor

USD/trip

min ML max min ML max 0: hr

1: day

Costs 

T_wait

1 Workboat 2,000 1 0.75 500

2 Jack-up barge (100 MT) 440,000 155,000 1 0.75 310,000

3 Cable layer 560,000 190,000 1 0.75 190,000

4 Diving support vessel 190,000 95,000 1 0.75 95,000

5 Turbine crane

6 Blade inspection

7 Helicopter 8,000

8

9

10

11

12

13

Variable cost equipment

(waiting and repair) 

[USD/unit]

Additional costs 

equipment during 

traveling

[USD/trip]

Cost equipment for 

MOB/DEMOB

[USD/mission]

Fixed costs per available 

equipment [USD/year]
24 

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Table 13. Specifications for the helicopter

Helicopter – 3 persons

Specification Value Remarks

Hs max at transfer Not relevant Modeled as 5.0 m

V max at transfer 12 m/s This limit refers to the maximum allowed wind speed 

for personnel working in the nacelle (Obdam & van 

der Zee, 2011). 

Travel time to turbine

(or speed)

1.0 h Estimate

Maximum crew size 3 Assumption, equal to 1 crew

Mobilization time 0 h Assumption, depends on contract

Maximum weight of load - Only technicians and consumables

Hourly rate $2,000/h Estimate

Modeled as fuel costs

Mob + demob costs 0 No MOB/DEMOB costs applicable

Fuel costs $8,000 per 

mission

Per mission: 1.0 (time) * 4 (trips) * 2 (rate) = $8k 

Hs = High seas V = wind velocity

Using a helicopter for small repairs and inspections will improve the wind plant availability by 

2.6%, bringing it up to 87.1%. The reduced downtime caused by waiting is the main reason for 

the improved availability. The downtime associated with travel is also reduced compared to the 

baseline scenario.

The total costs of repair are slightly higher than the baseline because the helicopter is more 

expensive than the workboat. Additional revenues (from higher wind plant availability) offset the 

higher cost of repair; we estimate annual savings of $4 million compared to the baseline 

scenario. It should be noted that the analysis did not account for the following (which would 

affect the total costs of the helicopter access scenario). 

• Helicopter ownership and logistics choices: 

o The helicopter could be owned by the operator of the wind plant (and located in 

the harbor), which would require an additional capital investment. 

o The wind plant operator could lease the helicopter (with the condition of 

immediate access when called upon) requiring an annual lease payment. 

• An additional investment is necessary to equip all turbines with facilities for helicopter 

access.
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4.2.3 Vessel Contracts

Vessel contracts aim to reduce downtime by establishing a paid agreement between the project 

operator and the vessel operator that guarantee vessel availability under short notice. Vessel 

contracts for large offshore crane vessels may be needed because of the long lead time associated 

with these high-demand, low-availability vessels. These agreements will come with a high price; 

however, in some cases the reduced down time can lead to substantial cost savings through 

increased wind plant availability. 

The costs for jack-up vessels have a substantial impact on the total O&M costs, especially when 

rented on the spot-market because of a long logistics time (lead time) and high mobilization and 

demobilization costs (MOB/DEMOB). 

To assess the validity of using a vessel contract, we quantify both the impact of logistics time 

and MOB/DEMOB costs of the jack-up vessel on the project’s LCOE (according to equation 

1.4-1). The output of this calculation can be used to assess how much money can be spent on a 

fixed contract, which results in a shorter logistics time and lower costs per mission.

The sensitivity of the LCOE to the MOB/DEMOB costs and logistics time is shown in Figure 6. 

As expected, the lower the MOB/DEMOB costs, the lower the LCOE. A lower logistics time, 

however, does not necessarily yield cost savings; the LCOE is actually higher when the logistics 

time is less than the baseline scenario (720 h in the baseline,). This difference can be explained 

by the fact that the model accounts for the clustering of large repair actions. The model assumes 

that all failures that occur during the logistics/mobilization period can be clustered, which leads 

to a reduction in total MOB/DEMOB costs, travel costs, and logistics downtime. For a shorter 

logistics time, on average, fewer repairs will be clustered. An average of two jack-up repairs 

were clustered in the baseline scenario (which assumes a logistics time of 720 h), whereas no

clustering occurred for shorter logistics times. Figure 6 indicates that this “turning point” lies 

between a logistics time of 360 and 720 h, based on the assumed failure frequencies used. 
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Figure 6. LCOE as a function of logistic time and MOB/DEMOB costs of a jack-up vessel

Negotiating a shorter logistics time will not necessarily yield cost savings, because doing so 

could reduce the number of repairs that can be clustered and therefore the full MOB/DEMOB

and travel costs will have to be paid for each replacement. According to this analysis, a fixed 

contract can only be favorable if the costs per event (MOB/DEMOB and possibly travel costs) 

can be lowered significantly. 

4.2.4 Improved Crew Transfer System

The workboats used for crew transfer in the baseline scenario were assumed to only allow access 

to the turbines in conditions with significant wave heights of up to 0.9 m (Douglas-Westwood, 

2012) (Frongillo, 2012). This limitation results in very low wind plant availability of 84.5%. In 

the following subsection, we discuss the effect of the weather limits of the crew transfer system 

on the downtime and O&M costs. 

Consistent with the analysis methodology used throughout this report, we did not address 

specific boat technology; instead, our analysis focused on the effect of the weather limits of the 

workboats. We varied the maximum allowed significant wave height for this equipment from 0.7 

m to 3.0 m and evaluated wind speed limits of 12 m/s and 16 m/s.

For the baseline scenario, the wave height limit for the turbine cranes and blade inspection were 

set equal to the wave height limit of the workboat. Similarly, the wave height limits for the 

turbine cranes and blade inspection for the improved crew transfer system scenarios were also set 

equal to the various workboat wave height limits. 
27 

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As shown in Figure 7, the maximum allowed wave height for the workboats has a significant 

influence on availability, costs, and the number of technicians needed. The availability for the 

baseline scenario (where Hs, max = 0.9 m was used) was low (84.5%), but drops to completely 

unacceptable levels if the wave height limit is reduced even further (0.7 m). As the wave height 

limit increases, availability increases asymptotically towards 95%, but increasing the wave 

height limit above 1.7 m yields negligible increases in availability. Figure 7 also shows that the 

wind speed limit for working in the nacelle has little or no influence on any of the parameters 

evaluated (availability, O&M costs, total effort, or number of technicians employed). 

Figure 7. Model output as a function of the maximum allowed significant wave height of the 

workboats
28 

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When interpreting these results it should be emphasized that only the weather limits of the 

workboats (and associated procedures) were changed. Naturally, different crew transfer systems 

will have different costs and, possibly, travel speeds, which will also impact the availability and 

O&M costs. If in the future more detailed information on alternative crew transfer systems for 

the U.S. market becomes available, the analyses discussed in this section could be used to 

identify the most optimal solution. However, from these results it can already be concluded that 

it is probably not reasonable to invest in crew transfer systems that can operate up to very high (> 

2.0 m) wave heights in the U.S. mid-Atlantic area. 

The results of this analysis are entirely dependent on wind and wave conditions of the midAtlantic. As seen in Figure 8, the significant wave height distribution between the mid-Atlantic 

and the North Sea are quite different. With a vessel wave restriction of 1.5 m in the mid-Atlantic, 

the wind plant would be accessible nearly 90% of the time, whereas in the North Sea, the wind 

plant would only be accessible roughly 60% of the time. To achieve more than 80% accessibility

in the North Sea, work boats would need to have wave restrictions well above 2 m, and limits 

closer to 3 m to reach availability levels close to 90%. This substantial difference in wave 

conditions demonstrates how the conclusions of this study could change substantially if different 

wind and wave conditions were used. 

Figure 8. Significant wave height nonexceedance distribution for the mid-Atlantic and North Sea

4.2.5 Spare Part Storage

The baseline scenario assumes that small spare parts are kept in stock in a storage facility in the 

harbor. This scenario requires no spare part logistics time for replacements categorized in 

Maintenance Category (MC) 4 (MC4) (small repairs using the turbine crane). The following 

paragraphs and table address how much extra downtime occurs (in addition to the travel time to 
29 

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the turbine) when small spare parts are not kept in stock onsite, but have to be delivered from the 

factory. 

We varied the logistic time for acquiring the spare parts necessary for MC4 replacements to 

investigate the effects of not keeping small spares in stock onsite. Because no clear information 

on realistic delivery times was available, we modeled three scenarios, assuming short, medium, 

and long delivery times, as outlined in Table 14. 

Table 14. Spare part logistic time for a scenario without onsite spare parts

Spare part logistic time (hours)

Fault Type 

Class (FTC) Baseline Short Medium Long

4 0 24 48 96

5 0 24 48 96

6 0 48 96 168

7 0 48 96 168

8 0 96 168 336

Logistics time is longer for more complex replacements that require more spare parts (e.g., repair 

scenarios categorized with a higher FTC). The longer the logistics time, the longer the turbine is 

not available. Failure to keep small parts in stock is expected to decrease availability. It should 

be emphasized that the baseline scenario did not account for investment in and operational costs 

of the onsite storage facilities. Therefore, if spare part delivery times are short enough, the lost 

revenues associated with decreased availability could be less than the investment and operational 

costs for the onsite storage facilities. More detailed information about the costs for the storage 

facility and delivery times of spare parts would be required for a more accurate benefit-cost 

analysis; our results simply emphasize that keeping small spare parts onsite has a positive effect 

on availability. 

It is worth noting that keeping spare parts for large failures (MC6) in stock will not improve 

availability, because the jack-up vessel, required for transporting these spare parts, has a logistics

time of 1 month. Keeping large spare parts onsite can only reduce logistics time when a jack-up 

vessel is available on short notice or owned by the project operator.

4.2.6 Advanced Condition-Based Monitoring

Advanced condition-based monitoring systems could provide more information on the condition 

of components, potentially reducing the number of unexpected failures that require corrective 

maintenance. If the advanced condition-based monitoring system is capable of identifying a 

possible failure before the component fails, the component can be repaired in a preventative 

maintenance manner, therefore the turbine can continue to operate for a greater period of time.
30 

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Unexpected failures in the drive train contribute significantly to total downtime and O&M costs. 

These systems are typically subject to the application of condition monitoring systems (for 

instance, vibration monitoring). To assess the possible benefits of having advanced conditionbased monitoring systems on these components, we assumed that a certain percentage of both the 

MC4 and MC6 corrective failures can be detected by the advanced condition-based monitoring 

systems. Although the failed (sub)components still need to be replaced, we assume the turbine 

can continue to operate until the required equipment, spare-parts, and technicians are available to 

correct the failure(s). This applies to failures in both MC4 and MC6.

As expected, wind plant availability increases with the percentage of failures that can be replaced 

in a preventive manner. When the condition monitoring systems can prevent 50% of the 

unexpected failures, availability increases by 1.2% as seen in Table 15. It is important to note 

that this analysis does not account for the investment and operational costs for the advanced 

condition-based monitoring systems. It is possible that the advanced condition-based monitoring 

systems could give false alarms, which may lead to unnecessary inspections, causing additional 

downtime. 

Table 15. Model output as a function of the percentage of corrective failures that can be 

preventively replaced because of information from condition monitoring systems for the drive 

train and generator

% of failures that are 

preventively replaced

Availability [%] O&M Costs [$/kWh] Total Effort [M$]

0% (baseline) 84.5 0.0283 86.9

25% 85.1 0.0280 85.3

50% 85.7 0.0278 83.6

75% 86.3 0.0276 82.0

100% 86.9 0.0274 80.4

4.2.7 Summary

Table 16 summarizes the results of each of the O&M strategies investigated. As discussed 

further in Section 5, even though many of the strategies show promise for reducing LCOE, the 

benefits could overlap when implemented together (i.e., the improvements to LCOE may not be 

additive). 
31 

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Table 16. Quantitative summary of the O&M strategies investigated

O&M strategy 

summary 

Main strategy change 

compared to baseline

Availability

[%]

O&M Costs

[$/kWh] 

Total yearly 

effort

[M$]7

Result notes 

Baseline O&M 

scenario 

– 84.5 0.0283 86.9 Investment and operational 

costs for onsite storage are 

not accounted for in the 

baseline.

Mother vessel 

accommodation 

Reduced travel time from 

2.6 h to 0.5 h. 

Small parts in stock at 

mother vessel

91.2 0.0224 62.0 Analysis does not account 

for mother vessel 

investment and operations 

costs.

Helicopter 

access

Reduced travel time from 

2.6 h to 1.0 h. Only for 

small repairs without 

spare parts. 

87.1 0.0290 82.9 Includes estimated 

helicopter costs. Does not 

account for additional 

turbine investment costs for 

landing platform.

Vessel 

contracts 

Parameter stud 

Jack-up barge contract

Logistics time: 

0 to 2200 h 

MOB/DEMOB costs vary: 

0 – 880 k$

83.0 – 85.0 0.0245 – 

0.0362 

82.3 – 99.4 Assuming clustering of 

large repairs, a fixed 

contract is only favorable in 

scenarios when costs per 

MOB/DEMOB can be 

lowered significantly. 

Improved crew 

transfer system 

Parameter study 

Access vessel limits

Wave height: 0.7 – 3.0 m 

Wind speed: 12 & 16 m/s 

61.3 – 95.3 0.024 – 

0.044 

56.2 – 153.0 Wave height limit of 

workboats has large 

influence on availability and 

costs. Wind speed limit has 

very limited influence. Wave 

height limits greater than 

1.7 m have minimal impact 

on costs. 

Spare part 

storage 

Parameter study 

Vary logistics time of part 

delivery for MC4 repairs: 

0 – 336 h 

82.3 – 84.5 0.0283 – 

0.0290 

86.9 – 92.2 Longer logistics times lead 

to additional costs 

compared to baseline (i.e., 

small parts are stored 

onsite). 

Advanced CBM Parameter study 

Assume Advanced 

Condition-Based 

Monitoring for MC4 and 

MC6, which are

subsequently preventively 

replaced. 

Detection rate: 0 – 100 % 

84.5 – 86.9 0.0274– 

0.0283 

80.4 – 86.9 If a larger percentage of 

failures can be detected by 

Advanced CBM systems 

the availability increases 

and costs decrease. 

Analysis did not account for 

investment and operational 

costs for Advanced CBM 

systems. Additional costs 

due to false alarms not 

considered.

 

7 Total O&M effort numbers presented in this report represent the sum of revenue losses and accrued O&M costs on a yearly basis. The $/kWh O&M 

costs, however, do not include the direct cost of revenue losses. Rather, the impact from loss of revenue on a $/kWh basis is accounted for via the 

change in energy production.
32 

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at www.nrel.gov/publications.

5 Preferred IO&M Case Study

This chapter outlines our approach to developing a preferred IO&M strategy for use in a case 

study. Specifically, we: 

• Analyzed combined installation strategies to establish a preferred installation strategy

• Analyzed combined O&M strategies to establish a preferred O&M strategy

• Assessed the tradeoffs between O&M costs and associated installation costs and energy 

production to establish a preferred IO&M strategy. 

5.1 Preferred Installation Strategy

Of the installation strategies that we investigated, only two showed installation cost reductions 

compared to the baseline: division of turbine assembly tasks between onshore and offshore, and 

changes to foundation and electrical installation approaches. 

We evaluated the impacts of changing the foundation and electrical installation approaches by 

conducting a sensitivity analysis (i.e., we evaluated how much installation costs would change 

for a given change in electrical installation cost or foundation installation time). We did not 

identify specific technologies or process innovations that would lead to these changes, however, 

so we did not include changes to foundation and electrical approaches in our preferred

installation strategy. 

As described in Section 4.1.1, we evaluated six different turbine assembly methods, 

distinguished by how much of the turbine is installed onshore versus offshore. Although the 

bunny ears with 1-part tower assembly method was the lowest cost option, some turbine 

manufacturers may not allow the bunny ears style installation method because transportation of 

the turbine in that unique configuration could lead to increased, or at least uncertain, loads on 

components. Consequently, the bunny ears style installation method was ruled out for the 

preferred case. The next lowest-cost assembly strategy was the pre-assembled rotor with one part 

tower, which we selected as the preferred installation strategy. 
33 

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Table 17 shows the total BOS costs for the case study that assumes the preferred installation 

strategy (pre-assembled rotor with one part tower turbine assembly) is used. Utilizing this turbine 

assembly method, the total preferred BOS cost ($2,550/kW) is 5% lower than the total baseline 

BOS cost ($2,682/kW). 

Table 17. Preferred BOS cost items

Preferred BOS Cost Item ($/kW) ($/kWh)

Development 118 0.0038

Ports and Staging 79 0.0026

Support Structure 800 0.0259

Electrical Infrastructure 498 0.0161

Installation Vessels 1055 0.0341

Total 2550 0.0825
34 

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5.2 Preferred O&M Strategy

Individually, a number of the O&M strategies we evaluated offer potential to improve both the 

wind plant availability and the O&M costs for the baseline scenario. We sought to identify which 

combination of these O&M strategies would lead to the greatest reduction in cost compared to 

the baseline. In this section, we describe how we combined the strategies and selected a preferred 

O&M strategy as input for comparison in a preferred IO&M strategy.

The two O&M strategies with the highest potential to improve availability and reduce revenue 

losses are: investment in an improved crew transfer system (e.g., application of a workboat with 

less restrictive weather limitations), and using a mother vessel to provide accommodation at the 

wind plant instead of daily transfer from the harbor. 

Both strategies focus on a reduction of the waiting time caused by bad weather conditions, which 

is the primary driver for the low wind plant availability in the baseline scenario. Individually, 

each of these strategies has the potential to reduce the total O&M effort from the baseline by 

more than $20 million. Other O&M strategies (helicopter access and advanced CBM) also

yielded improvements, albeit much smaller than for the improved crew access system and 

mother vessel accommodation. On the other hand, ordering spare parts directly from the factory, 

rather than storing them onsite, causes longer downtimes and could decrease availability 

compared to the baseline. 

These findings suggest that an improved crew access system in combination with a mother vessel 

accommodation would be the preferred O&M strategy. However, because each strategy 

addresses the waiting time caused by bad weather conditions, we cannot assume that the total 

improvement compared to the baseline equals the sum of the individual strategies. We evaluated

the cost savings associated with an improved crew access system (compared to the baseline) as 

well as the cost savings associated with four other scenarios (various combinations of an 

improved crew access system, plus one additional O&M improvement strategy). 

To identify a preferred O&M strategy, we first had to establish the capabilities of an improved 

crew transfer system and calculate the wind plant availability for different weather windows 

(combinations of significant wave height and wind speed). For the preferred O&M scenario, we 

assume that the workboats used can operate up to a significant wave height (Hs,max) of 1.5 m and 

maximum wind speed (Vmax) of 12 m/s. These limits are typically valid for workboats used for 

maintenance of offshore wind plants in Europe (Obdam & van der Zee, 2011) and are therefore 

considered realistic for use in the U.S. market, if the vessels were built in or relocated to the U.S. 

We also assume that the travel speed of the improved workboat is equal to the baseline workboat 

(one-way travel time is 2.6 h). However, because of the workboat's improved capabilities, it is 

also expected that the day rate for the improved workboat will be higher compared to the 

baseline. As a best estimate, we assume an increase in cost of 25%, which results in a day rate of 

$2,500. 
35 

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The additional four strategies we evaluated were composed of this specific improved crew 

transfer system scenario, which employs these specific work boat specifications (step 1), plus 

one of the O&M strategies below: 

• Variation A: Mother vessel

o Travel time of the workboats is reduced from 2.6 to 0.5 h because they are 

launched from the mother vessel. 

o An offshore premium of $175/h is taken into account for the technicians who, in 

this scenario, must live and work offshore for a prolonged period of time. 

• Variation B: Jack-up barge owned by project 

o The mobilization and travel costs for the jack-up vessel are set to zero, because it 

is no longer rented from the spot market. 

o Only an estimation for the OPEX, related to the jack-up being applied for O&M 

purposes, is made because a more detailed modeling of a project-owned jack-up 

vessel is needed, which is performed in Section 5.3. 

o No logistic time is considered for the jack-up barge. 

• Variation C: Helicopter access

o Crew transfer for small repairs and inspections is done by helicopter. 

o Helicopter access is not limited by wave height.

o Additional capital expenses (e.g., helicopter access at each turbine) are not 

considered. 

• Variation D: Advanced condition-based monitoring 

o Employing advanced CBM, we assume 50% of medium and large corrective 

repairs on the drivetrain system can be avoided with preventive maintenance. 

o For these repairs, the turbine is only shut down during the actual replacement. 

Using a two-step approach, we evaluated the preferred O&M strategy. First, only the improved 

workboats are included as the initial preferred O&M strategy. Next, the other strategies are 

added as variations to the initial preferred O&M strategy to evaluate their potential for further 

cost reduction. A summary of the results is presented in Table 18, and a detailed summary of 

downtime and O&M costs for the assessment of O&M strategies is given in Appendix F. 
36 

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Table 18. Summary of O&M strategies studied with highest improvement opportunity

O&M strategies Availability 

[%]

O&M Costs 

[$/kWh]

Total yearly 

effort [M$]8

Result notes:

Baseline O&M 

scenario 84.5 0.0283 86.9

This is the baseline O&M 

scenario

Step 1: Improved 

crew transfer 93.3 0.0248 62.1

Significant effect 

compared to baseline: 

total O&M decreased by

$24.8M. 

Step 1 + Variation A:

Mother vessel

95.2 0.0223 53.3

Analysis does not account 

for increased cost of 

mother vessel [indication: 

$15M - $20 M/year when 

rented from spot market, 

(BVG Associates, 2012)] 

Step 1 + Variation B:

project-owned jackup vessel

93.8 0.0180 48.8

Accounts for changes in 

operating expenses, but 

not capital cost of projectowned jack-up vessel. 

Step 1 + Variation C:

Helicopter access

93.9 0.0260 63.3

Increased operational 

costs. Does not account for

additional turbine 

investment costs for 

landing platform.

Step 1 + Variation D:

Advanced CBM

93.7 0.0247 61.1

Results shown are for 50% 

detection rate with 0% 

false alarms. Does not 

account for investment 

and operational costs for 

CBM systems. 

Using only the improved access system (workboats capable of operating up to 1.5 m significant 

wave height) results in savings of approximately $24.8 million annually compared to the 

baseline, which is a result of the greatly reduced waiting time caused by bad weather conditions.

It should be noted that these significant savings are realized because the baseline work boat was 

chosen to reflect the currently available work boats in the United States, which are optimized for 

 

8 Total O&M effort numbers presented in this report represent the sum of revenue losses and accrued O&M costs on a yearly basis. The $/kWh O&M 

costs, however, do not include the direct cost of revenue losses. Rather, the impact from loss of revenue on a $/kWh basis is accounted for via the 

change in energy production.
37 

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National Renewable Energy Laboratory (NREL) 

at www.nrel.gov/publications.

the offshore oil and gas industry, not the offshore wind industry. If the offshore wind industry 

were to grow significantly in the United States, it would be reasonable to assume that even firstof-a-kind wind plants would use work boats similar to those in Europe (with a 1.5-m significant 

wave height). However, because they are not currently available in the United States, this type of 

workboat was not considered for the baseline. 

The results for Variation A (improved crew access system plus use of a mother vessel) indicate 

that additional savings of around $9 million can be expected when the maintenance is organized 

from a mother vessel, because this strategy further reduces travel times. When a mother vessel is 

rented from the spot market, estimates of annual costs fall between $15 million and $20 million

(BVG Associates, 2012), which indicates that for the selected wind plant location the use of a 

mother vessel will be prohibitively expensive. For wind plants located further offshore, the use 

of a mother vessel will likely be part of the preferred O&M strategy. It was beyond the scope of 

this analysis to identify the cross over point at which the distance from shore is great enough that 

the costs of a mother vessel are offset by the savings from reduced travel time between the wind 

plant and harbor. To accurately evaluate at which distance from shore this turning point lies, 

time series data with wave height and wind speed for a number of locations with different 

distances from shore would be needed because these parameters can vary significantly from one 

location to the next. 

The results of Variation B (improved crew access system plus a project-owned jack-up vessel) 

indicate potential cost savings of approximately $13.3 million compared to Step 1 (jack-up 

vessel is rented from the spot market). These findings assume that no variable costs other than 

OPEX are incurred for the jack-up vessel and that the jack-up vessel is always available

(logistics time is equal to 0 h). If the project-owned jack-up vessel is also suitable for the wind 

plant installation and decommissioning phases, larger cost savings are possible. However, this 

method also requires a more detailed assessment of the investment costs for such a vessel. 

Operational costs must be considered when the vessel is also applied for the installation and 

decommissioning phases, as well as when the vessel is in standby or idling. To better assess

whether the use of a project-owned jack-up vessel is a cost-effective solution, we conducted a 

separate, more detailed assessment presented in Section 5.3. 

The results for Variation C (improved crew access system plus helicopter access) show that 

having helicopter access for small repairs and inspections will slightly improve wind plant 

availability, but will also lead to higher costs. The reduced revenue losses do not offset the 

higher costs of repair with the helicopter; the total O&M costs will increase by approximately 

$1.1 million. The main reason for this is that accessing the turbine via helicopter is not feasible

for repairs that require the delivery of spare parts. It is worth noting that operating helicopters 

will also require the addition of landing platforms for the technicians on the turbines; these are 

additional costs that we did not account for in our analysis. For wind plants located further 

offshore, the use of a helicopter may have a positive effect on the total O&M effort. As with the 

analysis of the mother vessel, to accurately evaluate at which distance from shore this cross over 

point occurs, it is necessary to have time series data with wave height and wind speed for a 

number of locations with different distances from shore. These data are needed because the wind 

and wave conditions affect decisions about which vessel (or helicopter) to employ for a given 

repair and affect the timing of those repairs. 
38 

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The analysis for Variation D (improved crew access system plus the installation of advanced 

condition based monitoring systems at the drive train and generator systems), shows that if more 

than 50% of the medium and large replacements on both systems can be detected, at least $1

million annually could be saved compared to the Step 1 scenario (improved crew access system 

only). This cost savings estimate does not account for the costs associated with additional 

inspections caused by false alarms or the investment costs for the actual monitoring systems. It is 

worth noting that we do not know whether a target of 50% failure prediction can be achieved by 

these systems; 50% was used as a best estimate given our current understanding of CBM 

systems. Taking these caveats into account, we chose not to include advanced condition-based 

monitoring in the preferred IO&M strategy. 

Our analysis indicates that including the improved workboats, possibly coupled with a jack-up 

vessel owned by the project (Variation B), is the preferred O&M strategy. The possible 

advantages of a project-owned jack-up vessel are discussed in more detail in Section 5.3. 

5.3 Project-Owned Jack-Up Vessel 

The use of a project-owned jack-up vessel for the operational, installation, and decommissioning 

phases could offer an opportunity for substantial cost savings. We assessed the potential IO&M 

cost savings over the assumed 20-year lifetime of the baseline wind plant. The cost savings for 

installation, decommissioning, and operational phases include the OPEX for the jack-up vessel, 

and total approximately $307 million. The savings can be broken down as follows: 

• Installation and decommissioning phase (NREL BOS model): $ 40,856,000 

• Operational phase (ECN O&M Tool v4.4): $ 266,164,000 

To provide net savings to an offshore wind project, the approximate $307 million in savings will 

have to offset the costs of a project-owned jack-up vessel, which are composed of both: 

• CAPEX: Principal and interest on debt to cover initial capital outlay

• OPEX: Vessel operating expenses, consisting of personnel, fuel costs, insurance, and 

administrative costs when the vessel is idling (i.e., when the vessel is standby and not applied 

for IO&M purposes). 

Our estimate of the jack-up vessel CAPEX for the assumed 20 years of lifetime9 included the 

following assumptions, based on information supplied in (RWE Innogy) and (Kaiser & Snyder, 

2010): 

• The vessel investment costs are $120 million and are financed through a cash payment of 

20% and a loan of 80% over 10 years with a 5.5% yearly fixed interest rate (assuming 

monthly principal payments). 

• The vessel is operated in-house by the project owner, thus the ROI is set at 0%.

 

9 After 20 years, the vessel is assumed to be fully depreciated. 
39 

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at www.nrel.gov/publications.

The total CAPEX estimate for the 20 year project lifetime is calculated as follows: 

(5.3-1) 

The OPEX for IO&M are accounted for in the $307 million cost savings for IO&M. However, in 

practice, when a vessel is owned by the project, the project owner would incur additional OPEX

when the vessel is not being used for IO&M, i.e., when the vessel is idling. We estimated the

OPEX for idling by assuming a day rate of $38,750 when the vessel is waiting for a suitable 

weather window to perform repairs.

10 We assume the vessel is idling for all days in the 20-year 

project lifetime that it is not being used for O&M (1101.4 days) or for installation and 

decommissioning (819.5 days; 454 days for installation, plus 365.5 days for decommissioning). 

The total number of days during the 20-year project lifetime is 7305 days (including 5 leap 

days). Total OPEX for idling is: 

( )

( ) k634,208$k75.38$5.8194.11017305

20 & / rateday

=⋅−−=

= − − ⋅ ⇒

idling

idling days yr MOdays days Install Decomm

OPEX

OPEX NN N (5.3-2) 

The total costs associated with a project-owned jack-up vessel during the 20 years of wind plant 

lifetime are estimated to be approximately $355 million—the sum of the CAPEX and OPEX as 

estimated in equations (5.3-1) and (5.3-2). This cost estimate is $48 million higher than the 

estimated cost savings of $307 million. Given the assumptions that we applied to our analysis of 

this particular 500-MW wind plant, the total lifetime costs outweigh the benefits of investing in a 

project-owned jack-up vessel. During the O&M phase of the wind plant, the jack-up vessel is 

only utilized for O&M activities approximately 15% of the time; we assume it would remain idle 

the remaining 85% of the time. 

There are significant costs associated with the project-owned jack-up vessel when the vessel is 

idling, because its deployment for IO&M purposes is moderate with an average utilization of 

26.3% during the project’s lifetime of 20 years. A portion of the jack-up’s idling OPEX may be 

recovered if it could be used (and paid for) by other projects (i.e., by renting the vessel to other 

projects/wind plants). However, even though utilization of the vessel at additional locations 

would decrease idling time, it could introduce logistics time (the time for the vessel to complete 

its other job and travel back to the owner’s wind plant again). The preferred O&M strategy, 

however, assumed logistics time would be zero (because the jack-up vessel would always be 

available); therefore, the actual cost savings would be less than the estimates presented in the 

previous section. Additionally, the idling OPEX still have to be paid for the days when it is not 

possible to rent the vessel to other projects or wind plants. A more in-depth analysis of this 

tradeoff for the jack-up vessel is beyond the scope of this report. Opportunities may exist for 

 

10 For the estimation on the day rate in (Obdam & van der Zee, 2011), it is assumed that only 75% of the commercial day rate is charged when the vessel 

is waiting for a suitable weather window to perform repairs. This 25% reduction of the day rate, or $38.75k is assumed to be fully attributed to a 

reduction in OPEX (e.g., by reduced fuel and personnel costs) and is translated to a 50% reduction of the OPEX for the jack-up when waiting/idling.

( )

k620,146$

12

055.0

120

k000,120$8.0 k000,120$ 121

20

120

1

20

=

⇒











 ⋅



 



 ⋅ = + ∑ ⋅−

=

=

y

i

i

y month

CAPEX

CAPEX i month

month
40 

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wind plant operators and/or third parties to operate and rent their own jack-up vessels if the 

vessel can be applied to more or larger offshore wind projects. 

5.4 Preferred IO&M Strategy

Based on the findings presented in Sections 5.1 to 5.3, the preferred IO&M strategy for the case 

study involves the method of installing the turbines in a pre-assembled rotor with one part tower, 

and investing in improved work boats (for crew access to the turbines) that can operate in higher 

sea states. 

We calculated annual energy production estimates using the ECN O&M Tool (Obdam, Braam, 

& Rademakers, 2011) on a seasonal basis using the same wind data set used for the waiting and 

downtime analysis, detailed in Appendix A. The LCOE for the case study using the preferred 

IO&M strategy is $0.20/kWh, as shown in Table 19. 

Table 19. Summary of preferred LCOE

($/kW) ($/kWh)

Turbine Capital Cost 1800 0.0582

Development 118 0.0038

Port and Staging 79 0.0026

Support Structure 800 0.0259

Electrical Infrastructure 498 0.0161

Installation Vessels 1055 0.0341

Balance of Station 2550 0.0825

Insurance 87 0.0028

Decommissioning 380 0.0123

Contingency 435 0.0141

Soft Costs 902 0.0292

Overnight Capital Cost (OCC) 5252 0.1699

Construction Financing 158 0.0051

Installed Capital Cost (ICC) 5409 0.1750

O&M ($/kW/yr) 767 0.0248

Net Annual Energy Production (AEP) (MWh/MW/yr) 3648

Fixed Charge Rate (FCR) 11.8%

Levelized Cost of Energy ($/kWh) 0.200
41 

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6 Conclusions

Installation, operation, and maintenance are expected to account for nearly one-third of offshore 

wind LCOE in the United States. Consequently, there is a large potential for reducing LCOE 

through advanced IO&M strategies. After investigating several IO&M strategies (listed in Table 

20) we found that a combination of one of the installation strategies and one of the O&M 

strategies would prove to have the greatest impact on LCOE. 

Table 20. Advanced IO&M strategies 

Installation Strategies O&M Strategies

Land-based vs. offshore assembly Mother vessel accommodations

Direct delivery of components Helicopter access

Purpose-built installation vessel Vessel contracts

Reduced electrical and foundation installation Improved crew transfer system

Spare part storage

Advanced CBM

The preferred IO&M strategy for the case study included: 

1. A specialized turbine assembly procedure; instead of assembling the turbine offshore 

as individual components, the rotor would be pre-assembled in port before load-out for 

installation. Additionally, the tower would be assembled in port so that only a single 

offshore lift would be necessary. 

2. Improved workboat for crew transfer; use of this improved work boat (an 

advancement in the O&M phase of the project) would reduce waiting time caused by

weather, by increasing the allowable working sea state from a significant wave height of 

0.9 m to 1.5 m. 

The preferred turbine installation strategy had an effect on two primary LCOE categories: ports 

and staging, and vessels. Compared to the baseline, the ports and staging costs increase in the 

preferred installation strategy because of the increased storage area needed for the pre-assembled 

rotors (their packing density is significantly less than that of individual components). The ports 

and staging costs also increase because of the additional work conducted at the port (the rotors 

and towers are assembled at the staging port). However, because the preferred installation 

strategy requires less offshore assembly, the overall vessel costs are lower than in the baseline 

scenario. Vessel costs are reduced by $185/kW (15% less than the baseline vessel costs), which

more than offsets the increase in port and staging costs. 

The preferred O&M strategy lowered overall O&M costs by $0.0035/kWh (12%), primarily 

because the increased sea state limits of the improved workboats, allowed for significantly 

reduced waiting periods caused by wind and wave conditions. This reduction in waiting time has 

a substantial impact on availability, and therefore energy production, raising AEP by almost 400 
42 

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MWh/MW per year—an increase of more than 10% compared to the baseline. This increase in 

AEP is the primary contributor to the overall reduction in LCOE seen in Table 21. 

Table 21. Improvements in LCOE through the preferred IO&M strategy

Baseline Preferred Impact

AEP (MWh/MW/yr) 3267 3648 +11.7% 

Availability 84.5 93.3 +10.4%

O&M ($/kWh) 0.0283 0.0248 -12.4%

Ports & Staging ($/kW) 26 79 +304%

Installation Vessels ($/kW) 1240 1055 -15%

LCOE ($/kWh) 0.233 0.200 -14%

The IO&M improvements applied to the case study reduced LCOE by 14% compared to the 

baseline; specifically, our LCOE estimate declined from $0.233/kWh (in the baseline) to 

$0.200/kWh (in the case study with a preferred IO&M approach). This 14% reduction in LCOE 

is primarily attributable to the increase in AEP and is a strong indicator that careful planning and 

analysis of IO&M strategies can significantly reduce LCOE.

6.1 Disclaimer

All data and results presented in this study (among others: failure data, vessel capabilities and 

costs, repair strategies, and wind turbine specifications) are indicative of averages and should not 

be taken as absolutes. Although the authors have attempted to use figures that are representative 

of contemporary large offshore wind plants, readers must always use their own data, applicable 

to their own situation. However, the data in this document can be used as a starting point with the 

relative changes associated with each strategy providing useful insight into overall trends. 

As discussed earlier in the report, a number of assumptions were made that heavily influence the 

results of the analysis. In the event that any of the assumptions are altered, depending on the 

importance of the assumption and how much it is varied, the conclusions of this study may be 

substantially different. In some cases, changes in a single assumption can alter the LCOE by 

±50%. Section 4.2.4 demonstrates an example of this using wave heights and indicates how 

simple changes in assumptions can lead to significant differences in conclusions. 

6.2 Recommendations for Future Work

The authors of this study have attempted to use data that are representative of large offshore 

wind turbines and plants that are expected to be built off the shores of the United States in the 

near future. Continued work focusing on how the underlying assumptions and unknown capital 

costs impact the conclusions is important. By expanding the work to look at the impact of the 

underlying assumptions, the results can be more useful to the offshore wind industry because of 

the more universal nature of the results. Additional efforts to look at unique installation methods 

for electrical and foundations would likely prove valuable, based on the initial results seen in this 

study. Furthermore, estimating the “break even” points for various technologies may be valuable. 
43 

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References

ECN Wind Industrial Support. (2012). Retrieved January 24, 2013, from 

http://www.ewis.nl/fileadmin/ecn/units/wind/docs/EWIS/SP-310_OM_Tool_Brochure.pdf

BVG Associates. (2012). Offshore Wind Cost Reduction Pathways; Technology Work Stream. 

Douglas-Westwood. (2012, July). DOE-NREL vessel types - Maples July19, 2012.xls.

Frongillo, D. L. (2012, July 19). General Manager / Naval Architect / Marine Engineer. (S. Kopits, 

Interviewer) 

GL Garrad Hassan. (2012). Expected Offshore Wind Farm balance of Station Costs in the United States.

Unpublished.

Griffin, D. (2001). WindPACT Trubine Design Scaling Studies Technical Area 1 --Composite Blades for 80 - 

to 120Meter Rotor, 21 March 2000 - 15 March 2001. 

Jonkman, J., Butterfield, S., Musial, W., & Scott, G. (2009). Definition of a 5-MW Reference Wind Turbine 

for Offshore System Development. 

Kaiser, M., & Snyder, B. (2010). Offshore Wind Energy Installation and Decommissioning Cost Estimation 

in the U.S. Outer COntinental Shelf. Baton Rouge, Louisiana: Energy Research Group, LLC.

Krohn, S., Morthorst, P., & Awerbuch, S. (2009). Economics of Wind Energy. European Wind Energy 

Association . Brussels.

Malcolm, D., & Hansen, A. (2006). WindPACT Turbine Rotor Design Study: June 2000-June 2002 

(Revised). 

Obdam, T. S., Braam, H., & Rademakers, L. (2011). User Guide and Model Description of ECN O&M Tool 

Version 4. 

Obdam, T., & van der Zee, T. (2011). ECN O&M Tool Case Study for a Far Offshore Wind Farm. 

RWE Innogy. (n.d.). Precision Work on the High Seas. Retrieved October 29, 2012, from 

http://www.rwe.com/web/cms/en/453962/rwe-innogy/technologies/offshorelogistics/installation-vessel/ 

Shafer, D., Strawmyer, K., Conley, R., Guidinger, J., Wilkie, D., Zellman, T., et al. (2001). WindPACT 

Turbine Design Scaling Studies: Technical Area 4 -- Balance-of-Station Cost; 21 March 2000 - 15 

March 2001. 

Short, W., Daniel, P., & Holt, T. (1995). A Manual for the Economic Evaluation of Energy Efficiency and 

Renewable Energy Technologies. NREL.
44 

This report is available at no cost from the 

National Renewable Energy Laboratory (NREL) 

at www.nrel.gov/publications.

Smith, K. (2001). WindPACT Turbine Design Scaling Studies Technical Area 2: Turbine, Rotor and Blade 

Logistics; 27 March 2000 - 31 December 2000. 

Tegen, S., Hand, M., Maples, B., Lantz, E., Schwabe, P., & Smith, A. (2012). 2010 Cost of Wind Energy 

Review. 

The Port of Virginia. (n.d.). Retrieved May 10, 2012, from http://www/portofvirginia.com/

U.S. Department of Energy. (2011). A National Offshore WInd Strategy: Creating an Offshore Wind 

Energy Industry in the United States. 

Uraz, E. (2011). Offshore Wind Turbine Transportation & Installation Analyses "Planning Optimal Marine 

Operations for Offshore Wind Projects". Gotland University, Wind Energy, Visby, Sweeden.

Van Oord ACZ. (2001). Cable Installation Study for DOWEC. 

VGB PowerTech. (2007). Guideline Reference Designation System for Power Plants, RDS-PP; Application 

Explanations for Wind Power Plants. 

Wilkinson, M. (2010). Methodology and Results of the Reliawind Reliability Field Study. 

Wilkinson, M., & Hendriks, B. (2011). Report on Wind Turbine Reliability Profiles. 
45 

This report is available at no cost from the 

National Renewable Energy Laboratory (NREL) 

at www.nrel.gov/publications.

Appendix A. Wind and Wave Data

For the analysis of waiting time caused by bad weather conditions for the wind plant, a series of 

meteorological data were used. For this analysis, 120 months of Wavewatch III hindcast data 

files covering the period from 01-Jan-2000 through 31-Dec-2009 for the WIS grid point 63198 

were used. 

The files included a timestamp, wind speed (at 10 m), wind direction, significant wave height 

and wave period. For the analysis described in this report, only the timestamp, wind speed and 

significant wave height were used. The files came with a 1-hourly sample rate. However, MSExcel 2003 and earlier can only handle 65536 rows, which made it impossible to include all data. 

Therefore, the 1-hourly data were transformed to 3-hourly data to ensure the full 10-year period 

could be included in the analysis. The conversion was done by simply taking the average over 

every 3 h in the original dataset.

Subsequently, the WaitingTime module of the ECN O&M Tool was applied to determine the 

average waiting time (because of bad weather) as a function of the mission time. This is done for 

the weather windows listed in Table 22. As shown in the table for certain weather restrictions, in 

fact, two weather windows were defined: one for a normal working day (Lwd = 0 = 12 h) and 

one for a long working day (Lwd = 1 = 24 h).

Table 22. Weather windows for which the relation between waiting time and mission time is 

calculated

The results of the calculation are presented as 2nd and 3rd order polynomials. An example of 

such a relation is shown in Figure 9. 

weather day

window Hs Vw Lwd

1 2.5 10 0 0 0

1 2.5 10 0

2 2.5 10 1

3 0.9 12 0

4 0.9 12 1

5 1 25 0

6 2 25 0

7 0.9 10 0

8 0.9 8 0

weather restrictions
46 

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Figure 9. Example of the calculated relation between waiting time and mission time as determined 

using the WaitingTime module for the jack-up barge—yearly average for weather window no. 1

Besides the results over a period of 10 years, the four yearly seasons are also considered 

separately, and are defined as follows: 

• Winter: December, January, February

• Spring: March, April, May

• Summer: June, July, August

• Autumn: September, October, November. 

To obtain more insight into the results of the waiting time calculations, some additional analyses 

were performed. Initially, a comparison was made between the yearly average calculated relation 

between waiting time and mission time for different weather windows (see Figure 10). 

First, it can be seen that for the two “sets” of weather limits (1-2 and 3-4, see also Table 22) the 

weather window (WeWi) applicable for the normal working day (WeWi 1 and 3) yields longer 

waiting times compared to the weather window applicable for the long working day (WeWi 2 

and 4). This is expected, because the calculations take into account that a suitable weather 

window can only start during the working day. Also, see section 5.3.2 in (Obdam, Braam, & 

Rademakers, 2011). 

Second, it can be observed that for WeWi 8 the longest waiting times will occur. It is noticed that 

the difference is very small between the waiting times of WeWis 3 and 7, although there is a 2-

m/s lower wind speed limit for weather window 7. WeWi 8 has a similar wave height limit, as 

set by the capabilities of the workboat, yet has an even lower wind speed limit set at 8 m/s. This 

clearly results in longer waiting times, as seen in Table 22. 
47 

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Figure 10. Waiting time as a function of mission time for the eight defined weather windows

In addition to the estimation of average waiting time (caused by bad weather conditions) the 

meteorological data were also used to derive the wind climate in the wind plant. The wind 

climate information is necessary to estimate the wind plant capacity factor, which again is used 

to make estimations of the lost revenues associated with downtime (Obdam, Braam, & 

Rademakers, 2011). By applying MATLAB commercial software, the wind climate is 

characterized by a Weibull-fit, including scale parameter A and shape parameter k. Whereas for 

the waiting time analyses the 3-hourly data were used, for deriving the Weibull parameters the 1-

hourly wind speed data were used. (For wind resource assessment, usually 10-minute or 1-hourly 

data are used.) The yearly average wind speed distribution, including the associated Weibull 

approximation, is shown in Figure 11. 
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Figure 11. Yearly average wind climate at 10-m height, as derived from the 10 years of hourly wind 

speed data

Similar to the yearly average wind speed distribution, Weibull-fits are made for the spring, 

summer, autumn, and winter seasons. The results for the Weibull approximations are given in 

Table 23 below. 

Table 23. Weibull parameters per season at 10-m height, as derived from the hourly wind speed 

data 

Weibull parameters at 10 m

Season shape scale

Winter 2.46 9.49

Spring 2.34 8.24

Summer 2.49 6.52

Autumn 2.11 8.01

Year 2.22 8.07
49 

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Appendix B. NREL BOS Model Overview

Overview

To model capital expenditures associated with installation activities and other BOS cost items, 

NREL used and further developed its offshore BOS model. The model was built on data 

provided by GL Garrad Hassan in a report that investigated the major contributions to offshore 

wind-project BOS costs in the United States (GL Garrad Hassan, 2012). The data covered the 

key cost drivers and trends, and provided typical values, expected ranges, and assumptions made 

based on today’s technology and best practices. Because of the immature nature of the U.S. 

offshore wind market and high level of uncertainty in specific cost elements, budgetary level 

costs were provided at a moderate level of detail. In compiling the information contained in the 

report, GL Garrad Hassan drew from its active participation in offshore wind projects in Europe, 

along with its experience in the onshore wind industry in the United States. 

Through the work completed in this study, a few components of the BOS model have been 

updated. The primary sections of the model that have been updated are the Installation Vessel 

and Decommissioning sections. The data necessary for these updates come from both the GL 

Garrad Hassan report and a number of other data sources (BVG Associates, 2012), (DouglasWestwood, 2012), (GL Garrad Hassan, 2012), (Kaiser & Snyder, 2010), and (Uraz, 2011). 

Development

Development costs in the BOS model encompass the work completed by a wind project 

developer up to the works completion date. For each of the categories considered in development 

costs, a high, low, and typical value is available for use. Ranges between the high and low values 

for some of the cost items can range by factors of nearly 100. Because of the high uncertainty of 

the U.S. market, for this study, the typical value was used. In its current operational state, the 

model simply adds up all of the development cost components and does not have any 

dependency on project parameters. A list of primary cost categories included in development 

costs are presented below. 

• Project management

• Front end engineering design (FEED) and Pre-FEED studies

• Detailed engineering design of the support structure 

• State and outer continental shelf (OCS) leasing process

• Site assessment plan

• Construction operation plan

• National Environmental Policy Act (NEPA) environmental impact study (EIS) for met tower 

and project 

• Physical and biological resource studies for the met tower and project
50 

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• Socioeconomic, land use, navigation, and transportation studies for the meteorological tower 

and project 

• Federal Aviation Administration (FAA) studies 

• Coastal Zone Management Act (CZMA) consistency

• Rivers and Harbors Act, Clean Water Act, Endangered Species Act, Marine Mammal 

Protection Act, Migratory Bird Treaty Act, and National Historic Preservation Act 

compliance 

• Additional state and local permitting. 

Port and Staging

Port and staging costs in the offshore BOS model are based entirely on the data provided by GL 

Garrad Hassan (GL Garrad Hassan, 2012). As with other sections of the model, there are high, 

low and average costs provided for each of the port and staging cost components. Below are the 

primary cost components that the port and staging module includes.

• Wind turbine and support structure storage area

• Port entrance and exit fees

• Quayside docking fees 

• Wharfage costs

• Port cranes including self-propelled modular transport units (SPMTs), crawler and tower 

cranes. 

To calculate the entrance, exit, docking, and wharfage costs, the port and staging module 

analyzes how many trips are taken by each of the installation vessels, based on the installation 

strategy utilized. For the storage area costs, the module looks at total storage area and the time 

for storage. To calculate the storage area, the module makes assumptions about blade, nacelle, 

and tower dimensions based on turbine rating. Then, based on the installation strategy, it 

calculates the total storage area required, including clearance allocations. The crane costs are set 

constant, assuming that the necessary cranes are on site and paid for throughout the entire 

project, regardless of usage. 

Support Structure

The BOS model calculates the support structure as three primary pieces for the monopile 

structure: primary steel, secondary steel, and transition piece. For the primary steel, a mass is 

calculated based on a simple scaling relationship that is dependent on turbine rating and water 

depth. From the calculated mass of the primary steel, an average cost per tonne (average between 

high and low estimate) is applied to generate a cost for the primary steel. Calculations for the 

secondary steel are carried out in the same manner with specific scaling relationships and costs. 

Transition piece mass relies on a scaling relationship based solely on the turbine rating, then the 

model applies that mass to a cost per tonne. Size dimensions, such as length, width, etc. are not 

used in the support structure module; however, they are used in the port and staging module and 

therefore are calculated there. 
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Electrical Infrastructure

Electrical infrastructure costs are binned in three primary cost buckets in the offshore BOS 

model: array cable, export cable, and offshore substation. 

Array Cable

The array cable cost module is currently capable of calculating array cable costs and 

requirements for only a radial cable layout and two cable sizes. Based on the turbine rating and 

the cable electrical capacity, the number of turbines that can fit on one string is determined. The 

number of turbines on one string, number of turbines, and array spacing all factor into the 

calculated length of array cable needed. With an average array cable cost per meter (average 

between high and low estimate) and ancillary costs per turbine and substation interface, a total 

array cable cost is determined. The installation of the cables is calculated on a $/km basis; 

however, this calculation is performed in the installation vessels module. 

Export Cable

Export cable costs are calculated in the same manner as the array cable, with the exception that 

additional landfall expenses must be taken into account. Simple, single-cost estimates for the 

following landfall expenses are made by the model. 

• Horizontal directional drilling

• Multi-purpose marine vessel rental

• Dive team

• Winch rental and operation 

• Transition joint civil and electrical work. 

Offshore Substation

Primary costs for the offshore substation components are based on estimates for a 500-MW wind 

plant and are not scaled to or from another plant size. The offshore substation is expected to be 

built at a dockside construction yard and transported and installed by a heavy-lift vessel. This 

installation cost is accounted for in the installation vessels module. The cost of the offshore 

substation is calculated by applying costs for the primary substation components, listed below, 

and totaling them.

• Main power transformers

• High voltage switchgear 

• Medium voltage switchgear

• Back-up generator 

• Ancillary systems

• Workshop, fire protection, accommodations, etc. 
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Installation Vessels

A complete spread of installation vessels is modeled in the offshore BOS model. For the six 

installation strategies investigated in this study, the vessel spread may change slightly, based on 

the lifting requirements of each strategy. Because it is beyond the capabilities of the model to 

understand when the exact periods of weather downtime occur, the model assumes that all 

installation vessels in the spread are contracted for the entire length of the construction period. 

Weather downtime is, however, calculated to demonstrate its relative impact on offshore 

installation operations by establishing a nonexceedance distribution based on wind and wave 

restrictions for each vessel and operation. An example of this distribution is presented in section 

4.2.4. Based on the nonexceedance distribution and the restriction of the vessel or operation, an 

average waiting time is assigned and added to the overall installation time. Vessels considered 

for the installation (and decommissioning) are listed below. 

• Heavy lift vessel (2000 tonne and 5000 tonne) 

• DP2 heavy lift cargo vessel 

• Jack up vessel

• Offshore barge 

• Seagoing tug (100 tonne) 

• Anchor handling tug (120-, 150-, and 200-tonne class)

• Dredging vessel 

• Rock dumping vessel (for scour protection) 

• Crew transfer vessel (12 person) 

• Grout spread vessel

• Sheerleg crane barge

• Work class ROV

• Survey boat 

• Cable-laying vessel

• Wind plant security vessel. 

Decommissioning

Decommissioning activities are modeled in the offshore BOS model in the same manner as the 

installation but in reverse order and with a few key differences. Based on information presented 

in (BVG Associates, 2012) and (Kaiser & Snyder, 2010) the following assumptions are assumed 

to be the only differences between installation and decommissioning. 

• Select activities have a reduced time associated with them because of the decommissioning 

process having fewer restrictions that are necessary in installation to protect the components 

from getting damaged. 
53 

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• Cable removal utilizes an offshore barge and 100-tonne seagoing tug instead of a cable 

installation vessel. Cable removal time is also reduced 10%.

• Vessel costs are reduced to the minimum vessel day rate because decommissioning has a 

much more flexible schedule. 

• Ultra-high power water jet cutting equipment is required for the removal of the monopile. 

• No scour protection removal is needed. 
54 

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Appendix C. Detailed O&M Assumptions

General Wind Plant Data

The general wind plant data used for the modeling are listed in Table 24 below. Note that the 

kWh price in the Wind Farm Data table is the assumed power purchase agreement (PPA) price, 

which is used in the “lost revenue” calculations. The PPA price of $0.125/kWh was chosen 

because it was representative of the region's current end consumer price. In reality, PPAs for first 

of a kind offshore wind plants will most likely be higher than the one chosen in this study. 

Table 24. General data for the U.S. baseline wind plant

All general information is based on discussions between ECN, NREL, and the Expert Panel. The 

capacity factors were calculated with the ECN O&M Tool, where the Weibull coefficients 

describing the wind climate were derived with from the same time series that were used to assess 

the waiting time caused by bad weather conditions. 

All year long a crew of 70 technicians is employed, which consists of two crews of 35 

technicians, which are exchanged every two weeks. At all times 35 technicians are required for 

carrying out maintenance in the wind plant. For the baseline analysis, it is assumed that these 

technicians are paid based on hourly tariffs for work only. It is assumed that the technicians cost 

$125 per man-hour. Personnel are considered to work only during daylight periods, except for 

repairs that require the use of a jack-up vessel, when two shifts of technicians will work 24 h per 

day. The cost of technicians and length of working day used in the model are listed in Table 25. 

Wind Farm Data WT Characteristics

Name of wind farm Type Windturbine

Miscellaneous General data

kWh price 0.125 USD P_rated 5000 kW

Number of turbines 100 - Investment costs 1800 USD/kW

Lifetime 20 years

Capacity factors Weighing factors fail. freq.

Season Season

Weigh. 

Factor

Winter 56% Winter 0.25

Spring 47% Spring 0.25

Summer 32% Summer 0.25

Autumn 44% Autumn 0.25

Year 45%

U.S. baseline IO&M case study NREL offshore 5-MW baseline
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Table 25. Cost and availability of technicians and length of working day

Wind Plant Breakdown and Failure Rates

A breakdown of the wind turbines was made to assign failure frequencies to the individual 

components. In addition, the failure rates of certain balance of plant items were considered. Both 

aspects are discussed in the following subsections.

Wind Turbine

The annual failure rates set for the main systems of the NREL offshore 5-MW baseline wind 

turbine are given in Table 26. The wind turbine breakdown in main systems is based on the 

descriptions published for the NREL offshore 5-MW baseline turbine and assumptions made by 

NREL and ECN (among others, the assumption that the turbine is equipped with an internal 

crane). The classification for the wind turbine systems of the NREL 5-MW baseline turbine is 

based on the Reference Designation System for Power Plants (RDS-PP) taxonomy which is 

based on basic and sector-specific IEC and ISO standards. The classification is made using the 

guideline for application of RDS-PP, which is published by VGB PowerTech (VGB PowerTech, 

2007). 

Cost and availability technicians 

Variable costs

Hourly rate technician 125 USD/hr

Fixed costs

Yearly salary costs technician USD

Season Winter Spring Summer Autumn Year

Nr. of employed technicians 92 92 66 72 70

Total salary cost [USD] 0 0 0 0 0

Length of working day

Season

nr. shifts start end nr. shifts start end

Winter 1 7 17 hr 2 0 24 hr

Spring 1 7 19 hr 2 0 24 hr

Summer 1 6 20 hr 2 0 24 hr

Autumn 1 7 19 hr 2 0 24 hr

Year 1 7 19 hr 2 0 24 hr

Normal Long
56 

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Table 26. Annual failure rates of components for the NREL offshore 5-MW baseline wind turbine

The failure frequencies (failures per year) for each of the wind turbine’s components are derived 

from the results of the Reliawind project, in which the contribution of components to the overall 

failure rate is given in percentages. The Reliawind project ran from 2008 to March 2011, and we 

used the published information on reliability in Deliverable 1.3, which is believed to be the latest 

information available on the reliability of wind turbines (Wilkinson & Hendriks, 2011) 

(Wilkinson M. , 2010). According to the publications, failure data were collected by an analysis 

of, among others, 10-minute SCADA data, automated fault-logs, and O&M reports. The data 

collected met the following conditions: 

• Site of at least 15 wind turbines 

• Turbines have been running for at least 2 years since commissioning 

• Variable speed, pitch regulated wind turbines (represent modern turbines) 

• Rated at > 850 kW. 

Based on ECN’s experience in O&M modeling, the average annual failure rate for a wind turbine 

lies between 3 and 6 over a lifetime of 20 years. Therefore, a failure frequency of 4.5 is used for 

this case study. This is similar to an ECN case study performed for a far offshore wind plant in 

the North Sea, see (Obdam & van der Zee, 2011). The Reliawind reliability figures are used to 

calculate a breakdown of failure rates for systems that represent the NREL 5-MW wind turbine. 

In this process, the Reliawind taxonomy used for data collection is converted to the RDS-PP 

based taxonomy, for which the details are given in Table 27. 

Wind Turbine Component 

Value Min ML Max

MDA- Rotor system 0.1307 0.2025 0.4050 0.8100

MDC - Blade adjustment 0.9778 0.0563 0.1125 0.2250

MDK - Drive train 0.2888

MDL - Yaw gearbox 0.5076

MDX - Hydraulic system 0.0536

MDY - Control and protection system turbine 0.8616

MKA - Generator 0.3246

MKY - Control and protection system generator 0.6001

MSA - Generator lead / transmission cables 0.4651

MST - Transformer 0.0795

MUD - Machinery enclosure 0.0138

UMD - Turbine structure / tower 0.1512

XA - Heating, ventilation, air conditioning 0.0140

XM - Crane system 0.0144

XN - Elevator system 0.0055

AB - Lightning protection / grounding 0.0118

MD - Remote Resets 5.0000

Total 9.5000 2.2500 4.5000 9.0000

Annual Failure Frequency

main components
57 

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In addition to failures that require a visit to the turbines, the effects of remote resets were also 

modeled by defining the general wind turbine system code “MD- Remote Resets.” For the 

baseline scenario it is assumed that on average each turbine needs to be remotely reset 5 times 

per year. Thus, the total modeled failure frequency equals 9.5 failures per year.

Table 27. Conversion of taxonomy used for data collection in Reliawind project to RDS-PP 

taxonomy 

Balance of Plant

Failures in the wind plant offshore substation, foundation and scour protection, and cables 

(between wind turbines and offshore substation) were also taken into account. However, because

very little information was available for these figures, ECN made some best estimates (Obdam & 

van der Zee, 2011). The resulting numbers are shown in Table 28. The wind plant is assumed to 

be connected to the grid via an onshore substation, which is subsequently connected to a single 

offshore substation. 

System (RDS-PP taxonomy) Reliawind sub system or assembly 

(reliawind WT taxonomy)

Reliawind failures

MDA - Rotor system Blades + Hub + hub cover 0.1307

MDC - Blade adjustment Pitch system + slip rings + blade 

bearings 0.9778

MDK - Drive train Drive train module 0.2888

MDL - Yaw gearbox Yaw system 0.5076

MDX - Hydraulic system Hydraulic system 0.0536

MDY - Control and protection system turbine Control & comm system + nacelle 

sensors + CMS + auxiliary + wind farm 0.8616

MKA - Generator Generator assembly 0.3246

MKY - Control and protection system generator Power cabinet + protection cabinet + 

frequency converter 0.6001

MSA - Generator lead / transmission cables LV & MV switchgear + power feeder 

cables 0.4651

MST - Transformer Transformer 0.0795

MUD - Machinery enclosure Nacelle cover + bedplate + lighting 

points + beacon 0.0138

UMD - Turbine structure / tower Structural module 0.1512

XA - Heating, ventilation, air conditioning Cooling system 0.0140

XM - Crane system Service crane 0.0144

XN - Elevator system Lift 0.0055

AB - Lightning protection / grounding Lightning protection + grounding 0.0118

Total failures 4.5000
58 

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Table 28. Annual failure rates of components for the considered BOP items

Maintenance Categories and Fault Type Classes

In the following subsections it is discussed in detail how the different Maintenance Categories 

and fault Type Classes for both wind turbine and balance of plant failures were modeled in the 

ECN O&M Tool. More information on the maintenance categories is presented in Appendix E. 

Wind Turbine

For this analysis, 6 Maintenance Categories (MC) were identified. Each MC is split up into one 

or more Fault Type Classes (FTC). The modeled MCs and FTCs are shown in Table 29. 

BOP Component 

Value

Transformer 0.5000

Foundation / Scour protect 3.0000

Cables within wind farm 0.0500

Annual Failure Frequency

main components

Add Remove
59 

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Table 29. Maintenance Categories and Fault Type Classes for wind turbine failures

Maintenance categories

Description Nr Nr.

Remote reset (only downtime, no visit) 1 no crew, Repair = 2 hr, no costs 1

Inspection and small repair inside 2 small crew, Repair = 4 hr, consumables 2

Inspection and small repair outside 3 small crew, Repair = 8 hr, consumables 3

Replacement small parts (< 2 MT) internal crane 4 small crew, Repair = 8 hr, low costs 4

4 small crew, Repair = 16 hr, low costs 5

4 large crew, Repair = 16 hr, medium costs 6

4 large crew, Repair = 24 hr, medium costs 7

4 large crew, Repair = 24 hr, high costs 8

Preventive replacement small parts (< 2 MT) internal crane 5 small crew, Repair = 8 hr, low costs 9

5 large crew, Repair = 16 hr, medium costs 10

Replacement large parts (< 100 MT) large external crane 6 large crew, Repair = 24 hr, medium/high costs 11

6 large crew, Repair = 24 hr, high costs 12

6 large crew, Repair = 40 hr, medium/high costs 13

6 large crew, Repair = 40 hr, very high costs 14

Fault type class classification

Description

Add Remov
60 

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The material costs, crew size, repair time and logistic time shown in Table 30 are all based on 

experience from ECN with O&M modeling. The FTCs were developed largely based on our 

existing Demo K13 baseline model for the North Sea, which is supplied with the commercial 

O&M Tool software (Obdam & van der Zee, 2011). For the Demo K13 model, the FTCs are 

developed based on an analysis of the contribution to overall downtime and engineering 

judgment to classify small, medium, and large repair actions. These analyses were performed in 

the past by ECN together with a turbine manufacturer. The costs for spare parts are quantified 

using a breakdown that shows the contribution of different component costs to the total 

investment costs of a modern geared wind turbine. Details for this cost breakdown are given in 

(Krohn, Morthorst, & Awerbuch, 2009). 

It is assumed that small parts (up to 2000 kg) are kept in stock at warehouse facilities at the 

harbor, and therefore the logistic time for spare parts for MC1 to MC4 was set to zero. MC5 

represents preventive replacement of small components; the turbine is assumed to be shut down 

only when maintenance is being performed. Therefore, the FTCs for MC5 are flagged to be the 

condition-based maintenance (CBM) type. 
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Table 30. Fault Type Classes for wind turbine failures

Type

0 = corr

1 = cbm

Nr.

mean value

mean value [USD] mean 

value

mean 

value

mean 

value

no crew, Repair = 2 hr, no costs 1 0 0.00% 0 0 2 0

small crew, Repair = 4 hr, consumables 2 0 0.010% 900 3 4 0

small crew, Repair = 8 hr, consumables 3 0 0.010% 900 3 8 0

small crew, Repair = 8 hr, low costs 4 0 0.100% 9,000 3 8 0

small crew, Repair = 16 hr, low costs 5 0 0.100% 9,000 3 16 0

large crew, Repair = 16 hr, medium costs 6 0 1.000% 90,000 4 16 0

large crew, Repair = 24 hr, medium costs 7 0 1.000% 90,000 4 24 0

large crew, Repair = 24 hr, high costs 8 0 5.000% 450,000 4 24 0

small crew, Repair = 8 hr, low costs 9 1 0.100% 9,000 3 8 0

large crew, Repair = 16 hr, medium costs 10 1 1.000% 90,000 4 16 0

large crew, Repair = 24 hr, medium/high costs 11 0 2.000% 180,000 6 24 168

large crew, Repair = 24 hr, high costs 12 0 3.000% 270,000 6 24 336

large crew, Repair = 40 hr, medium/high costs 13 0 2.000% 180,000 6 40 336

large crew, Repair = 40 hr, very high costs 14 0 10.000% 900,000 6 40 336

Logistic Time 

Spare Parts [hrs]

Fault type class classification

Description

Crew Size

(Labour Costs)

Repair Time

[hrs]

Material Costs

[% of Investm.] Add Remove

Type

0 = corr

1 = cbm

Length 

working day

0 = normal

1 = long

Repair 

splittable

0 = no

1 = yes

Nr.

mean value mean 

value mean value mean value

no crew, Repair = 2 hr, no costs 1 0 0 1 1

small crew, Repair = 4 hr, consumables 2 0 6 0 1

small crew, Repair = 8 hr, consumables 3 0 6 0 1

small crew, Repair = 8 hr, low costs 4 0 12 0 0

small crew, Repair = 16 hr, low costs 5 0 12 0 0

large crew, Repair = 16 hr, medium costs 6 0 12 0 0

large crew, Repair = 24 hr, medium costs 7 0 12 0 0

large crew, Repair = 24 hr, high costs 8 0 12 0 0

small crew, Repair = 8 hr, low costs 9 1 12 0 0

large crew, Repair = 16 hr, medium costs 10 1 12 0 0

large crew, Repair = 24 hr, medium/high costs 11 0 24 1 0

large crew, Repair = 24 hr, high costs 12 0 24 1 0

large crew, Repair = 40 hr, medium/high costs 13 0 24 1 0

large crew, Repair = 40 hr, very high costs 14 0 24 1 0

Fault type class classification

Description

Time to Organise 

[hrs] Add Remove
62 

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It is also taken into account that before a replacement is carried out, first one or more inspections 

are performed. For the baseline scenario, it is assumed that before small (MC4) and large (MC6) 

replacements, on average respectively 1 and 2 inspections are carried out. These inspections can 

be characterized as small repairs (MC2). The assignment of additional inspections is illustrated 

in Table 31 for two components. 
63 

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Table 31. Assignment of additional inspections for wind turbine failures

Wind Turbine Component Maintenance 

Category

Probability of 

occurrence Maint. 

Cat

Number of 

additional 

inspections

FTC

Value

MDA- Rotor system 0.1307 2 52.5% 0.134 0.069 2

MDC - Blade adjustment 0.9778 2 65% 0.831 0.636 2

4 10% 0.098 0.098 1 6

5 20% 0.196 0.196 9

6 5% 0.049 0.049 2 11

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MDK - Drive train 0.2888 2 45% 0.318 0.130 2

MDL - Yaw gearbox 0.5076 2 45% 0.330 0.228 2

5 45% 0.228 0.228 10

6 10% 0.051 0.051 2 13

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

Annual Failure 

Frequency

main components

 Annual Failure Frequency

maintenance categories

Add Remove
64 

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For the components MDC – Blade adjustment, MDL – Yaw gearbox, and XN – Elevator system, 

it was assumed that part of the maintenance can be carried out in a preventive manner(e.g., for 

the replacement of certain small components such as pitch motors/batteries, yaw drives, and 

elevator components). The turbine only has to be shut down during the actual replacement, and 

therefore no time-to-organize, logistics, weather, and travel downtime have to be considered. 

These preventive replacements are categorized as MC5. The full assignment of all Maintenance 

Categories and Fault Type Classes to the different wind turbine components is listed in Table 32. 
65 This report is available at no cost from the 

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Table 32. Wind turbine MCs and FTCs

Wind Turbine Component Maintenance 

Category

Probability of 

occurrence Maint. 

Cat

Number of 

additional 

inspections

FTC

Value

MDA- Rotor system 0.1307 2 52.5% 0.134 0.069 2

3 5.0% 0.007 0.007 3

4 15.0% 0.020 0.020 1 4

4 20.0% 0.026 0.026 1 6

6 5.0% 0.007 0.007 2 13

6 2.5% 0.003 0.003 2 14

0.000 0.000

0.000 0.000

MDC - Blade adjustment 0.9778 2 65% 0.831 0.636 2

4 10% 0.098 0.098 1 6

5 20% 0.196 0.196 9

6 5% 0.049 0.049 2 11

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MDK - Drive train 0.2888 2 45% 0.318 0.130 2

4 45% 0.130 0.130 1 6

6 10% 0.029 0.029 2 14

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MDL - Yaw gearbox 0.5076 2 45% 0.330 0.228 2

5 45% 0.228 0.228 10

6 10% 0.051 0.051 2 13

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MDX - Hydraulic system 0.0536 2 60% 0.054 0.032 2

4 40% 0.021 0.021 1 4

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MDY - Control and protection system turbine 0.8616 2 55% 0.862 0.474 2

4 45% 0.388 0.388 1 4

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MKA - Generator 0.3246 2 45% 0.357 0.146 2

4 45% 0.146 0.146 1 6

6 10% 0.032 0.032 2 12

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MKY - Control and protection system generator 0.6001 2 45% 0.600 0.270 2

4 45% 0.270 0.270 1 5

4 10% 0.060 0.060 1 8

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MSA - Generator lead / transmission cables 0.4651 2 55% 0.465 0.256 2

4 45% 0.209 0.209 1 4

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

Annual Failure 

Frequency

main components

 Annual Failure Frequency

maintenance categories

Add Remove
66 This report is available at no cost from the 

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MST - Transformer 0.0795 2 45% 0.079 0.036 2

4 45% 0.036 0.036 1 5

4 10% 0.008 0.008 1 8

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MUD - Machinery enclosure 0.0138 2 40% 0.014 0.006 2

4 60% 0.008 0.008 1 4

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

UMD - Turbine structure / tower 0.1512 2 55% 0.159 0.083 2

4 30% 0.045 0.045 1 4

4 10% 0.015 0.015 1 7

6 5% 0.008 0.008 2 14

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

XA - Heating, ventilation, air conditioning 0.0140 2 50% 0.014 0.007 2

4 50% 0.007 0.007 1 4

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

XM - Crane system 0.0144 2 50% 0.014 0.007 2

4 50% 0.007 0.007 1 4

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

XN - Elevator system 0.0055 5 100% 0.005 0.005 9

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

AB - Lightning protection / grounding 0.0118 2 100% 0.012 0.012 2

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

MD - Remote Resets 5.0000 1 100% 5.000 5.000 1

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

Total 9.5000 2.2500 1 . 5.0000 5.0000

2 . 4.2424 2.3909

Additional inspections 3 . 0.0065 0.0065

Inspection MC 2 4 . 1.4948 1.4948

5 . 0.4294 0.4294

6 . 0.1783 0.1783

7 0.0000 0.0000

8 . 0.0000 0.0000

. 11.3514 9.5000
67 

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Balance of Plant

For BOP failures, four maintenance categories are identified. Again, each MC is split up in one 

or more Fault Type Classes. The modeled MCs and FTCs for BOP failures are shown in Table 

33, Table 34, and Table 35. 

Table 33. Maintenance Categories and Fault Type Classes for BOP failures

The material costs, repair times, crew sizes and logistic times for the different BOP repairs and 

replacements shown in Table 33 are ECN’s best estimates and are taken from (Obdam & van der 

Zee, 2011). As can be seen, no crew size is defined for both the small foundation/scour 

protection repair and cable replacement. For these maintenance activities, labor costs for divers 

and specialist technicians are assumed to be included in the costs for the vessels.

Table 34. Fault Type Classes for BOP failures (1)

Similar to wind turbine failures, a time-to-organize is also modeled for BOP failures. For the 

small repairs, a period of 6 h is considered, whereas for the large transformer repairs, a period of 

12 h is considered, and for cable replacements one period of 24 h is taken into account. 

Furthermore, for all BOP failures it is assumed that the repair activities can only be carried out 

during daylight conditions (normal working day). Additionally, it is assumed that all BOP repairs 

and replacements can be carried out over multiple nonadjacent days (splittable).

For the wind plant, it is assumed that all turbines are connected to an onshore substation via a 

single offshore transformer station. Therefore, a transformer station failure is assumed to affect 

100% of the wind turbines in the wind plant. Furthermore, it is assumed that during a small 

repair on the foundation or scour protection no turbines have to be shut down. Finally, the 

Maintenance categories

Description Nr Nr.

Small transformer repair 1 1

Large transformer repair 2 2

Small foundation / scour protection repair 3 3

Cable replacement 4 4

small crew, Repair = 8 hr, low costs

medium crew, Repair = 48 hr, high costs

diving crew, Repair = 8 hr, low costs

no crew, Repair = 32 hr, high costs

Fault type class classification

Description

Add Remov

Nr. mean value mean 

value

mean 

value

mean 

value

1 6,000 3 8 0

2 300,000 4 48 1440

3 6,000 0 8 48

4 450,000 0 32 240

small crew, Repair = 8 hr, low costs

medium crew, Repair = 48 hr, high costs

diving crew, Repair = 8 hr, low costs

no crew, Repair = 32 hr, high costs

Fault type class classification Material Costs

[USD]

Crew Size

[-]

Repair Time

[hrs]

Logistic Time 

Spare Parts [hrs]

Description

Add Remove
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assumption is made that in case of a cable failure, on average 13% (approximately 1/8) of the 

wind plant has to be shut down. 

Table 35. Fault Type Classes for BOP failures (2)

The full assignment of MCs and FTCs for BOP components is shown in Table 36. 

Table 36. Assignment of MCs and FTCs for BOP components 

Length 

working day

0 = normal

1 = long

Repair 

splittable

0 = no

1 = yes

Percentage 

wind farm 

shut down

[%]

Nr. mean 

value mean value mean value

1 6 0 1 100%

2 12 0 1 100%

3 6 0 1 0%

4 24 0 1 13%

small crew, Repair = 8 hr, low costs

medium crew, Repair = 48 hr, high costs

diving crew, Repair = 8 hr, low costs

no crew, Repair = 32 hr, high costs

Fault type class classification

Description

Time to Organise

[hrs] Add Remove

BOP Component Mainte-nance 

Category

Probability of 

occurrence Maint. 

Cat

FTC

Value

Transformer 0.5000 1 90% 0.450 0.450 1

2 10% 0.050 0.050 2

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

Foundation / Scour protection 3.0000 3 100% 3.000 3.000 3

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

Cables within wind farm 0.0500 4 100% 0.050 0.050 4

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

0.000 0.000

Total 3.5500 2.2500 1 . 0.4500 0.4500

2 . 0.0500 0.0500

3 . 3.0000 3.0000

4 . 0.0500 0.0500

5 . 0.0000 0.0000

6 . 0.0000 0.0000

7 0.0000 0.0000

8 . 0.0000 0.0000

. 3.5500 3.5500

Annual Failure 

Frequency

main components

 Annual Failure Frequency

maintenance categories

Add Remove
69 

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Repair Strategy: Transportation and Lifting Equipment

A baseline O&M scenario is worked out in which the following devices for transportation and 

hoisting are foreseen:

• Workboat access vessel (transferring technicians and transporting small components)

• Jack-up vessel (transporting and hoisting large components) 

• Cable-laying vessel (replacing cables)

• Diving support vessel (for underwater inspections and repairs) 

• Turbine cranes capable of hoisting small components to and from the workboats. (internal 

crane at the nacelle and davit crane on the turbine platform). 

The relevant model input data for these vessels are given in Appendix D. The figures used are 

partly based on previous experience from ECN, combined with available data sheets from the 

manufacturers of this equipment, and some engineering judgment. Using the information from 

chapter 4, the equipment, including costs and weather limits, are modeled in the O&M Tool as 

depicted in Table 37. 

Table 37. Definition of equipment for baseline O&M cost model

The following main assumptions are made in modeling of the defined equipment: 

• No travel times are modeled for the jack-up barge, cable-laying vessel, and diving support 

vessel. Naturally these vessels need some time to travel to the wind plant, but more relaxed 

weather restrictions apply as these types of large vessels are in transit. If a travel time would 

be modeled, the waiting time for this equipment would be overestimated. 

EQUIPMENT

U.S. baseline IO&M case study

Nr of equipment Description

of equipment

Weather 

window

(normal 

day)

Hs Vw 0 0 Weather 

window

(long day)

Hs Vw 0 0

1 Workboat 3 0.90 12.0 0.00 0.0 4 0.90 12.0 0.00 0.0

2 Jack-up barge (100 MT) 1 2.50 10.0 0.00 0.0 2 2.50 10.0 0.00 0.0

3 Cable layer 5 1.00 25.0 0.00 0.0 0.00 0.0 0.00 0.0

4 Diving support vessel 6 2.00 25.0 0.00 0.0 0.00 0.0 0.00 0.0

5 Turbine crane 7 0.90 10.0 0.00 0.0 0.00 0.0 0.00 0.0

6 Blade inspection 8 0.90 8.0 0.00 0.0 0.00 0.0 0.00 0.0

(For information only) (For information only)

Nr of 

equipment

Description

of equipment

Availability (nr. 

of 

equipment

nr hr hr Freq. USD/year USD/

mission

USD/

unit

unit Weighing

factor

USD/trip

0: day

1: mission

0: hr

1: day

Costs 

T_wait

1 Workboat 0 2.6 0 2,000 1 0.75 500

2 Jack-up barge (100 MT) 720 1 440,000 155,000 1 0.75 310,000

3 Cable layer 720 1 560,000 190,000 1 0.75 190,000

4 Diving support vessel 360 1 190,000 95,000 1 0.75 95,000

5 Turbine crane

6 Blade inspection

Variable cost equipment

(waiting and repair) 

[USD/unit]

Additional costs 

equipment during 

traveling

[USD/trip]

T logistic 

equip.

T travel (+access)

one way

Cost equipment for 

MOB/DEMOB

[USD/mission]

Fixed costs per 

available 

equipment 

[USD/year]

Season: Year
70 

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• For the turbine crane and blade inspection equipment, no logistic time, travel time, and costs 

are specified. However, only the appropriate weather window is selected to account for the 

possible waiting time associated with using the equipment. For both the turbine crane and 

blade inspection equipment, a maximum significant wave height of 0.9 m is modeled, 

because of the fact that during operations with this equipment it should be possible to transfer 

technicians to the workboat at all times.

• For the workboat and jack-up barge, a weather window for both a “normal” and a “long” 

working day is selected. For the baseline scenario, the workboat is applied in both normal 

and long working days. The jack-up is only applied during long working days, but in a 

sensitivity study the application of the jack-up barge during normal working days may also 

be investigated. 

• All vessels are assumed to be leased when required for maintenance. For the jack-up barge, 

cable-laying vessel, and diving support vessel, a mobilization time is modeled to reflect 

limited availability on the market for such large vessels. The workboats are assumed to be 

readily available upon request. 

• The fuel cost for the workboat is given as the costs per trip. A round trip will take 

approximately 5 h (2 one-way trips of 2.6 h), with an assumed fuel cost of $100/h this leads 

to a modeled fuel cost of $500 per trip.

For the jack-up barge, different logistic times and costs are modeled for winter and summer (see

Appendix D). The variations per season are listed in Table 38. The logistics time and costs for 

spring and autumn are assumed equal to values used to model the yearly average. Table 39

shows which equipment will be deployed for each defined FTC for both the wind turbines and 

BOP. The numbers in the block Repair Strategy of this table correspond with the numbers in 

Table 37 where the devices are specified in detail.
71 

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Table 38. Definition of logistic times and costs for jack-up during winter and summer seasons

Description

of equipment

Availability

nr hr USD/ 

season

USD/

mission

USD/

unit

unit Weighing

factor

USD/trip

min min min 0: hr

1: day

Costs 

T_wait

Jack-up barge (100 MT) 0 480 0 315,000 125,000 1 0.75 250,000

T logistic 

equip.

Cost equipment for 

MOB/DEMOB

[USD/mission]

Variable cost equipment

(waiting and repair) 

[USD/unit]

Additional costs 

equipment during 

traveling

[USD/trip]

Fixed costs per 

available equipment 

[USD/season]

Season: Winter

Description

of equipment

Availability

nr hr USD/ 

season

USD/

mission

USD/

unit

unit Weighing

factor

USD/trip

max max max 0: hr

1: day

Costs 

T_wait

Jack-up barge (100 MT) 0 960 0 560,000 190,000 1 0.75 380,000

T logistic 

equip.

Season: Summer

Variable cost equipment

(waiting and repair) 

[USD/unit]

Additional costs 

equipment during 

traveling

[USD/trip]

Fixed costs per 

available equipment 

[USD/season]

Cost equipment for 

MOB/DEMOB

[USD/mission]
72 

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Table 39. Equipment applied per Maintenance Category for wind turbine (top) and BOP (bottom)

Distribution of Fault Type Classes and Cost Breakdown for Wind Turbine

Maintenance categories Effective 

length 

working day 

[hrs]

Description Nr Nr. Access 

equipment

2nd device 3rd device 4th device Access 

equipment

2nd device 3rd device 4th device

Remote reset (only downtime, no visit) 1 no crew, Repair = 2 hr, no costs 1 24

Inspection and small repair inside 2 small crew, Repair = 4 hr, consumables 2 1 6.8

Inspection and small repair outside 3 small crew, Repair = 8 hr, consumables 3 1 5 6 2 6.8

Replacement small parts (< 2 MT) internal crane 4 small crew, Repair = 8 hr, low costs 4 1 5 2 6.8

4 small crew, Repair = 16 hr, low costs 5 1 5 4 6.8

4 large crew, Repair = 16 hr, medium costs 6 1 5 4 6.8

4 large crew, Repair = 24 hr, medium costs 7 1 5 6 6.8

4 large crew, Repair = 24 hr, high costs 8 1 5 6 6.8

Preventive replacement small parts (< 2 MT) internal crane 5 small crew, Repair = 8 hr, low costs 9 1 5 2 6.8

5 large crew, Repair = 16 hr, medium costs 10 1 5 4 6.8

Replacement large parts (< 100 MT) large external crane 6 large crew, Repair = 24 hr, medium/high costs 11 1 2 12 13.6

6 large crew, Repair = 24 hr, high costs 12 1 2 12 13.6

6 large crew, Repair = 40 hr, medium/high costs 13 1 2 20 13.6

6 large crew, Repair = 40 hr, very high costs 14 1 2 20 13.6

Season: Year

Fault type class classification

Description

Time [hrs] equipment is used during repair

If 0 equal to repair time

Repair strategy

Usage of devices Add Remove

Distribution of Fault Type Classes and Cost Breakdown for Balance of Plant

Maintenance categories Effective 

length 

working day 

[hrs]

Description Nr Nr. Access 

equipment

2nd device 3rd device 4th device Access 

equipment

2nd device 3rd device 4th device

Small transformer repair 1 1 1 6.8

Large transformer repair 2 2 1 6.8

Small foundation / scour protection repair 3 3 4 12

Cable replacement 4 4 3 12

small crew, Repair = 8 hr, low costs

medium crew, Repair = 48 hr, high costs

diving crew, Repair = 8 hr, low costs

no crew, Repair = 32 hr, high costs

Fault type class classification

Description

Season: Year

Repair strategy

Usage of devices

Time [hrs] equipment is used during repair

If 0 equal to repair time Add Remove
73 

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Preventive Maintenance and Fixed Yearly Costs

For the baseline scenario it is assumed that all turbines in the wind plant will be maintained once 

per year (so 19 times during the 20-year lifetime of the wind plant), with 3 technicians during 24 

h. In addition to this, every five years (3 times during the 20-year lifetime of the wind plant) a 

larger preventive maintenance campaign is carried out. This campaign requires a crew of 6 

technicians during 48 h. It is also assumed that in the years a large preventive campaign is 

carried out that no regular preventive maintenance is performed. Therefore, during the 20-year 

lifetime the following was assumed: 

• 16 times regular preventive maintenance 

• 3 times large preventive maintenance. 

It is assumed that for both maintenance campaigns the workboats can be used and that work can 

only be performed during daylight hours (normal working day). Furthermore, the required 

material costs are a best estimate, based on ECN’s experience in O&M modeling. 

It is also assumed that all balance of plant preventive maintenance is carried out from a diving 

support vessel (i.e., regular underwater inspections). Because this vessel can stay within the wind 

plant for the duration of the maintenance, travel time does not need to be modeled. The crew 

costs are included in the rate for the diving support vessel. It is estimated that 160 h of BOP 

preventive maintenance is carried out every year throughout the 20 years of assumed lifetime of 

the wind plant. The input sheet for preventive maintenance is depicted in Table 40. 

In this study, only costs directly related to corrective and preventive maintenance have been 

taken into account. Other costs, for instance, costs for a 24-h control room or insurance costs, are 

outside the scope of this study. 
74 

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Table 40. Input parameters preventive maintenance wind turbine and BOP structures

Preventive maintenance per wind turbine or BOP item

Description

Type of preventive maintenance (0 = WT; 1 = BOP) 0 - 0 -

Percentage wind farm shut down (only for BOP) [%] 100% 100%

Number of occurances during lifetime of 20 years 16 - 3 -

Duration of maintenance 24 hrs 48 hrs

Crew size 3 - 6 -

Mat. Costs 12,500 USD 37,500 USD

Type of equipment 1 Workboat 1 Workboat

Travel time to or from the wind farm (one-way) [hr] 2.1 hrs 2.1 hrs

Length working day (0 = normal; 1 = long) 0 - 0 -

Distribution over seasons winter spring summer autumn winter spring summer autumn

0% 35% 55% 10% 0% 35% 55% 10%

Regular WT preventive maintenance Large WT preventive maintenance

Preventive maintenance per wind turbine or BOP item

Description

Type of preventive maintenance (0 = WT; 1 = BOP) 1 -

Percentage wind farm shut down (only for BOP) [%] 0%

Number of occurances during lifetime of 20 years 19 -

Duration of maintenance 160 hrs

Crew size 0 -

Mat. Costs 12,500 USD

Type of equipment 4 Diving support vessel

Travel time to or from the wind farm (one-way) [hr] 0 hrs

Length working day (0 = normal; 1 = long) 0 -

Distribution over seasons winter spring summer autumn

0% 35% 55% 10%

Regular BOP preventive maintenance
75 

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Appendix D. Vessel Data

For the baseline configuration, it has been decided that the following methods and equipment are 

the most likely option for the transfer of equipment and personnel and for hoisting components: 

• Workboat access vessel (for transferring technicians and transporting small components) 

• Jack-up vessel (for transporting and hoisting large components)

• Cable-laying vessel (for replacing cables)

• Diving support vessel (for underwater inspections and repairs) 

• Turbine cranes capable of hoisting small components to and from the workboats 

(specifically, internal crane at the nacelle and davit crane on the turbine platform). 
76 

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Workboat Access Vessel

For the transfer of personnel and small spare parts, a workboat vessel type is used. The 

workboats considered in this study are relatively fast and can transport up to 12 persons. The 

specifications used for the cost modeling are given in Table 41. 

Table 41. Specifications of the workboat access vessel

Workboat - 12 persons

Specification Value Remarks

Hs max at transfer 0.9 m Average wave height limits taken from (DouglasWestwood, 2012)

V max at transfer 12 m/s This limit refers to the maximum allowed wind speed 

for personnel working in the nacelle (Obdam & van 

der Zee, 2011)

Travel time to turbine

(or speed)

2.6 h Engineering judgment (Obdam & van der Zee, 2011) 

Travel time to wind plant 2.3 h (86km/20 kts) +

 Time for access to turbine 0.3 h (estimate) + 

The total travel time is estimated at 2.6 h (avg).

Maximum crew size 12 Assumption

Mobilization time 0 h Assumption, depends on market conditions

Availability - The workboats are chartered when required.

Maximum weight of load 2000 kg Assumption Deck crane with 2 ton safe work load

Day rate 2k Dollar/day

(75% waiting)

Estimate

Based on ECN’s discussions with vessel operators

Mob + demob costs 0 No MOB/DEMOB costs applicable

Fuel costs Approx. 100 

Dollars/h 

Engineering judgment

Based on average consumption at cruise speed and 

while idling of 100 L/h (Diesel price $4.00/gallon)
77 

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Jack-Up Vessel

The transportation and hoisting of large components, such as that during installation, will be 

done with a jack-up vessel, because of its ability to lift itself out of the water. A stable platform 

is created, from which a large crane can be operated. The specifications used for the cost 

modeling are given in Table 42. 

Table 42. Specifications of the jack-up vessel with crane

Jack-up vessel

Specification Value Remarks

Hs max 2.5 m (Douglas-Westwood, 2012)

V max 10 m/s Relevant for hoisting (Obdam & 

van der Zee, 2011).

Travel time (one way) - The travel time is at least one 

day. However, during this period 

weather conditions are not 

relevant and therefore no travel 

time needs to be modeled.

Mobilization time 720 h (year, spring, autumn)

480 h (winter) 

960 h (summer)

Estimate, depends on market 

conditions

Based on values in (Obdam & van 

der Zee, 2011)

Availability Limited Chartered when required.

Maximum height of crane 100 m

Maximum weight of load > 100 MT

Day rate 155k Dollar (year, spring,

autumn) 

125k Dollar (winter)

190k Dollar (summer)

(75% during waiting in harbor)

Estimate

Based on values in (Obdam & van 

der Zee, 2011). 

MOB + DEMOB costs 440k Dollar (year, spring,

autumn) 

315k Dollar (winter) 

560k Dollar (summer) 

Estimate

Based on values in (Obdam & van 

der Zee, 2011). 

Cost during travel 310k Dollar (year, spring,

autumn) 

250k Dollar (winter) 

380k Dollar (summer)

Assumption: two days of travel 

are required  travel costs equal 

two times the day rate
78 

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Cable Layer

For the (re)placement of cables within the wind plant, a cable-layer vessel is used. The vessel has 

the necessary equipment to dig up and remove the failed cable, lay the new cable, and bury it. 

The cable layer is equipped with a Remotely Operated Vehicle (ROV).The vessel stays inside 

the wind plant throughout the repair action. The vessel has all necessary equipment and 

technicians on board to lay a new cable in the wind plant. The specifications used for the cost 

modeling are given in Table 43. 

Table 43. Specifications of the cable-laying vessel

Cable laying vessel

Specification Value Remarks

Hs max during cable laying 1.0 m Source: Van Oord DOWEC study (Van Oord 

ACZ, 2001)

V max during cable laying Not relevant Modeled as 25 m/s

Travel time to turbine 3.5 h Engineering judgment

Based on a transit speed of 14 kts (DouglasWestwood, 2012)However, during this periods 

weather conditions are not relevant and 

therefore no travel time needs to be modeled.

Mobilization time 720 h Estimate, depends on market conditions

Availability Limited Chartered when required.

Maximum weight of load 1000 tons

Day rate 190k Dollar 

(75% during 

waiting in harbor)

Estimate

Based on values given (Obdam & van der Zee, 

2011)

MOB + DEMOB costs 560k Dollar Estimate

Based on values given (Obdam & van der Zee, 

2011)

Cost during travel 190k Dollar Based on the assumption that in total one day 

of travel is needed  travel costs equal the 

day rate
79 

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Diving Support Vessel

For inspection and repair under water, for instance of foundations and scour protection, a diving 

support vessel is required. It is assumed that a crew of divers is included in the day rate. It is 

assumed that the diving support vessel is equipped with a Remotely Operated Vehicle (ROV). 

During longer operations, the diving crew can stay on the vessel, which remains inside the wind 

plant. The specifications used for the cost modeling are given in Table 44. 

Table 44. Specifications of the diving support vessel

Diving support vessel

Specification Value Remarks

Hs max during operation 2.0 m

V max during operation Not relevant Modeled as 25 m/s

Travel time to turbine 3 h Based on a transit speed of 16 knots. 

However, during this periods weather 

conditions are not relevant and therefore 

no travel time needs to be modeled.

Mobilization time 360 h Estimate, depends on market conditions

Availability Limited Chartered when required.

Maximum weight of load Not relevant

Day rate 95k Dollar (75% during 

waiting in harbor)

Estimate

Based on values given (Obdam & van der 

Zee, 2011)

MOB + DEMOB costs 190k Dollar Estimate

Based on values given (Obdam & van der 

Zee, 2011)

Cost during travel 95k Dollar Based on the assumption that in total one 

day of travel is needed  travel costs 

equal the day rate

Fixed annual costs - Not applicable
80 

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Turbine Crane

To hoist small components up to 2000 kg up to the nacelle for repairs and small replacements, 

the davit and nacelle cranes available on the wind turbine are used. The davit crane on the 

platform is used to hoist small components from a vessel to and from the platform, after which 

the nacelle crane is used to lift those all the way up to the nacelle. The nacelle crane can lift 

small components from the platform of the wind turbine up to the nacelle at moderate wind 

speeds. The specifications used for the cost modeling are given in Table 45. 

Table 45. Specifications of the nacelle crane

Specifications of the nacelle crane

Specification Value Remarks

Hs max at transfer Hoisting 0.9 m Assumed equal to the workboat’s access 

limits

V max at transfer Hoisting 10 m/s Estimate

Availability One crane available for 

each wind turbine. 

100 Cranes in total

Maximum weight of load 2000 kg Estimate

Costs - Not applicable

The crane will receive preventive 

maintenance at regular intervals.
81 

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Appendix E. Maintenance Categories and Repair 

Strategies 

Six different Maintenance Categories for the wind turbines are identified for the baseline and 

advanced strategies. In addition, four Maintenance Categories regarding BOP are defined. All 10 

MCs are discussed in the following subsection. 

Wind Turbine

In Table 46, the six identified Maintenance Categories for the wind turbine are listed. 

Table 46. Maintenance Categories for the turbine

Cat. 1: Remote resets, no access, only downtime

Cat. 2: Inspection and small repair inside, only personnel and tools, repair time 2 to 6 h (e.g., replacement 

of generator fuses)

Cat. 3: Inspection and small repair outside, only personnel and tools, repair time 6 to 10 h (e.g., cleaning 

of blades)

Cat. 4: Replacement of small parts (≤ 2000 kg), internal crane, hoisting outside, repair time typically 8 to 

24 h (e.g., replacement of pitch motor)

Cat. 5: Preventive replacement of small parts (≤ 2000 kg), internal crane, hoisting outside, repair time 

typically 8 to 24 h (e.g., replacement of pitch batteries)

Cat. 6: Replacement of large parts (≥ 2000 kg), external crane on jack-up vessel needed, (e.g., 

replacement blade, pitch bearing, etc.), repair time typically 24 to 40 h

Below, for each MC, the typical maintenance actions are worked out in more detail. As stated 

already in the introduction, all data should be considered best estimates.

Cat. 1: Remote Resets

The wind turbines can shut down because of certain warnings or errors.

The typical actions for a remote reset look like this: 

1. The turbine is shut down because of a warning. 

2. The 24-h monitoring team investigates the cause of the error (~2 h). 

3. If the warning is found to be not serious, the turbine is restarted.

The reset can be carried out in 2 h. Transportation of personnel and access to the turbine is not 

necessary, because all actions are carried out remotely.
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Cat. 2: Inspection and Small Repair Inside the Turbine

Three technicians have to be transported to the turbine to carry out the inspection or repair. No 

additional equipment needs to be transported; only tools that fit into a toolbox. 

A typical inspection or repair looks like this: 

1. The workboat is launched from the harbor and travels to the faulted wind turbine (~2.3 h). 

2. Three (3) technicians are transferred from the workboat to the turbine (~0.3 h).

3. Technicians carry out inspection or repair, the workboat remains within the wind plant 

(2 to 6 h). 

4. Personnel return to the workboat and travel back to the harbor (~2.6 h). 

The repair can be carried out in 2 to 6 h. Transportation of personnel and access to the turbine 

can be done in conditions up to Vw = 12 m/s and Hs = 0.9 m. On average, a period of 6 h is 

required to organize the inspection or repair. 

For these inspections or repairs a normal working day (only during daylight) is applicable. 

Furthermore, these repairs do not have to be carried out in one continuous period with good 

weather, but can be split over multiple nonadjacent days. 

Cat. 3: Inspection and Small Repair Outside the Turbine

This category includes, for instance, cleaning of the blades or inspection of the tower, or 

repairing the gel coat of the blades. At least two technicians need to be transported to the turbine 

to carry out an inspection or repair at the outside of the turbine. Transportation of the necessary 

equipment for lowering personnel from the hub along the blade(s) can be done with the 

workboat. 

A typical inspection looks like this: . 

1. The workboat, with hoisting equipment, is launched from the harbor and travels to the faulted 

wind turbine (~2.3 h). 

2. Three (3) technicians with gear for working outside are transferred from the workboat 

(~ 0.3 h). 

3. The equipment will be put on the platform and hoisted with the turbine crane into the nacelle 

or hub, and the equipment for lowering technicians will be installed (1 h). 

4. The technician is hoisted from the hub along blade 1, and blade 1 is inspected.

5. The technician is hoisted into hub. 

6. The rotor is rotated through 120 degrees and steps 3 and 4 are repeated. 

7. Step 5 is repeated.

8. Personnel return to the workboat and travel back to the harbor (~2.6 h). 

The installation of the hoisting equipment and subsequent inspection of all three blades will take 

approximately 6 to 10 h. Transportation of personnel and access to the turbine can be done in 

conditions up to Vw = 12 m/s and Hs = 0.9 m. Inspection and repair outside the nacelle can be 
83 

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done in conditions up to Vw = 8 m/s (derived from communication with technicians). On average, 

a period of 6 h is required to organize the inspection or repair. 

For these inspections or repairs a normal working day (only during daylight) is applicable. 

Furthermore, these repairs do not have to be carried out in one continuous period with good 

weather, but can be split over multiple nonadjacent days. 

Cat. 4: Replacement of Small Parts (< 2000 kg)

Smaller spare parts like a pitch motor, or parts of a hydraulic system, need to be transported to 

the turbine, put on the platform, and subsequently hoisted into the nacelle with the help of the 

internal crane. All smaller spare parts weigh less than 2000 kg. 

A typical maintenance action looks like the following: 

Inspection

1. The workboat is launched from the harbor and travels to the faulted wind turbine (~2.3 h). 

2. Three (3) technicians are transferred from the workboat to the turbine (~ 0.3 h).

3. Technicians carry out inspection, the workboat remains within the wind plant (~ 2 to 6 h). 

4. Personnel return to the workboat and travel back to the harbor (~2.6 h). 

Replacement

1. A workboat, with 3 to 4 technicians and the spare part, is launched from the harbor and 

travels to the failed turbine (~2.3 h).

2. The technicians are transferred from the workboat (~ 0.3 h). 

3. In case the failed component needs to be replaced, the spare component is hoisted to the 

platform with the small crane on the lower turbine platform (~1 h). 

4. The failed component is dismantled and lowered outside the tower to the turbine platform 

(2 to 8 h). 

5. The spare component is hoisted from the platform into the nacelle using the internal crane 

(~2 h). 

6. The spare component is mounted (2 to 12 h). 

7. The failed component is hoisted to the workboat using the small crane on the platform. (~ 1 

h) 

8. Personnel return to the workboat and travel back to the harbor (~2.6 h). 

For the inspection, the criteria for MC2 are valid. For the baseline, it is assumed that on average 

1 inspection is performed before the actual replacement is carried out.
84 

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The total duration of the repair action will be about 8 to 24 h. Transportation of personnel and 

access to the turbine can be done in conditions up to Vw = 12 m/s and Hs = 0.9 m. Putting spare 

parts from the workboat on the platform using a Davit crane can be done in conditions up to Vw = 

12 m/s and Hs = 0.9 m, hoisting of equipment from the platform to the nacelle with the turbine 

crane is possible in conditions up to Vw = 10 m/s. Spare parts for this category are kept in stock 

at the harbor. On average, a period of 12 h is required to organize the repair action. 

For these inspections or repairs, a normal working day (only during daylight) is applicable. 

Furthermore, these repairs do have to be carried out in one continuous period with good weather 

and cannot be split over multiple nonadjacent days. 

Cat. 5: Preventive Replacement of Small Parts (< 2000 kg)

For the baseline scenario, it is assumed that some of the smaller components (e.g., pitch batteries 

or yaw drives) can be replaced preventively, based on observed degradation (in fact, conditionbased maintenance). The advantages of this planned replacement are that the turbine is only shut 

down during the actual repair and no logistic, organizational, weather, and travel downtimes 

have to be considered. 

The repair procedure for the preventive replacement of small parts is identical to the corrective 

replacement (MC4), and will therefore not be elaborated here.

Cat. 6: Replacement of Large Parts with Large External Crane on Jack-Up Vessel

To hoist large components, such as the transformer or blades, a large crane on a jack-up vessel is 

needed. A typical maintenance action may look like the following: 

Inspection

1. The workboat is launched from the harbor and travels to the faulted wind turbine (~2.3 h). 

2. Three (3) technicians are transferred from the workboat to the turbine (~ 0.3 h). 

3. Technicians carry out the inspection, while the workboat remains within the wind plant (~ 

2 to 6 h). 

4. Personnel return to the workboat and travel back to the harbor (~2.6 h). 

Replacement

1. The workboat is launched from the harbor and travels to the faulted wind turbine (~2.3 h). 

Note that this has to be done every working day until the repair is finished! 

2. Technicians are transferred to the turbine with the workboat (~0.3 h). Note that this has to be 

done every working day until the repair is finished! 

3. The failed component is dismounted (4 to 8 h). 

4. The spare part is transported from the harbor to the wind plant by the jack-up vessel (8 h 

from harbor).

5. The jack-up vessel is positioned (1 h). 
85 

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6. The failed component is removed and let down to the jack-up vessel and the new component 

is hoisted (6 to 10 h). 

7. The spare part is mounted crudely (2 h). 

8. Mounting the new part is finished, and the turbine is taken into operation (12 to 20 h, 

depending on the component). 

9. Personnel return to the workboat and travel back to the harbor (~2.6 h). 

For the inspection, the criteria for MC2 are valid. For the baseline, it is assumed that on average 

2 inspections are performed before the actual replacement is carried out. 

The replacement of the failed component will take about 24 to 40 h. Transportation of personnel 

and access to the turbine can be done in conditions up to Vw = 12 m/s and Hs = 0.9 m. During the 

hoisting activities, the weather conditions should be good, i.e., a wind speed less than 10 m/s 

(hoisting and working in the open nacelle). During positioning of the jack-up ship, the significant 

wave height should be less than 2.5 m. Large spare parts are not kept in stock at the harbor and 

have to be ordered. The average logistic time for the spare parts is 1 to 2 weeks (168 to 336 h). 

On average, a period of 24 h is required to organize the repair action. 

For these inspections or repairs, a long working day (24-h, around the clock) is applicable. 

Furthermore, these repairs do have to be carried out in one continuous period with good weather 

and cannot be split over multiple nonadjacent days. 
86 

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Balance of Plant (BOP)

In addition to the maintenance categories for the wind turbines, four MCs were defined to 

consider failure of the foundation, transformer station, and cables. In Table 47, the four identified 

Maintenance Categories for the wind turbine are listed. 

Table 47. Maintenance Categories for Balance of Plant

Cat. 1: Remote resets, no access, only downtime

Cat. 2: Inspection and small repair inside, only personnel and tools, repair time 2 to 6 h (e.g., replacement 

of generator fuses)

Cat. 3: Inspection and small repair outside, only personnel and tools, repair time 6 to 10 h (e.g., cleaning 

of blades)

Cat. 4: Replacement of small parts (≤ 2000 kg), internal crane, hoisting outside, repair time typically 8 to 

24 h (e.g., replacement of pitch motor)

Cat. 5: Preventive replacement of small parts (≤ 2000 kg), internal crane, hoisting outside, repair time 

typically 8 to 24 h (e.g., replacement of pitch batteries)

Cat. 6: Replacement of large parts (≥ 2000 kg), external crane on jack-up vessel needed, (e.g., 

replacement blade, pitch bearing, etc.); repair time typically 24 to 40 h

Below, for each MC, the typical maintenance actions are worked out in more detail. As stated 

already in the introduction, all data should be considered best estimates.

Cat. 1: Small repair in transformer station

Three technicians have to be transported to the transformer station to carry out the repair. No 

additional equipment needs to be transported—only tools that fit into a toolbox. 

A typical inspection or repair looks like this: 

1. The workboat is launched from the harbor and travels to the transformer station where the 

fault occurred (~2.3 h). 

2. Three (3) technicians are transferred from the workboat to the transformer station (~0.3 h). 

3. Technicians carry out the repair and the workboat remains in the vicinity of the transformer 

station (4 to 12 h). 

4. Personnel return to the workboat and travel back to the harbor (~2.6 h). 

The repair can be carried out in 4 to 12 h. Transportation of personnel and access to the 

transformer station can be done in conditions up to Vw = 12 m/s and Hs = 0.9 m. On average a 

period of 6 h is required to organize the repair action.
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For these inspections or repairs, a normal working day (only during daylight) is applicable. 

Furthermore, these repairs do not have to be carried out in one continuous period with good 

weather, but can be split over multiple nonadjacent days. 

Cat. 2: Large Repair in Transformer Station

Four technicians have to be transported to the transformer station to carry out the repair. Small 

components required for the repair are brought to the transformer platform by the workboats. 

A typical inspection or repair looks like this: 

1. The workboat is launched from the harbor and travels to the transformer station where the 

fault occurred (~2.3 h). 

2. The technicians are transferred from the workboat to the transformer station (~0.3 h). 

3. The components are hoisted onto the transformer platform using a crane on the platform (2 to 

4 h). 

4. Technicians carry out the repair (30 to 52 h). 

5. Replaced components are hoisted onto the workboat (2 to 4 h).

6. Personnel return to the workboat and travel back to the harbor (~2.6 h). 

The repair can be carried out in 36 to 60 h. Transportation of personnel and access to the 

transformer station can be done in conditions up to Vw = 12 m/s and Hs = 0.9 m. Hoisting spare 

parts from the workboat on the transformer platform using the platform crane can be done in 

conditions up to Vw = 12 m/s and Hs = 0.9 m. Spare parts for the transformer station are not kept 

in stock at the harbor and have to be ordered. The logistic time for the spare parts, including 

delivery at the harbor, is about 2 months. On average, a period of 12 h is required to organize 

the repair action.

Cat. 3: Small Repair to Foundation or Scour Protection

For repairs that are carried out under water, a diving support vessel with a crew of divers is 

required. 

A typical underwater repair to foundation or scour protection looks like this: 

1. The diving support vessel is launched from the harbor and travels to the location where the 

fault occurred (3 h). 

2. The vessel is positioned near the fault and the diving crew enters the water (~0.5 h).

3. The divers carry out the repair (4 to 12 h). 

4. The divers return to the diving support vessel and the vessel travels back to the harbor (~3.5 

h). 
88 

This report is available at no cost from the 

National Renewable Energy Laboratory (NREL) 

at www.nrel.gov/publications.

The repair can be carried out in 4 to 12 h. Diving operations can be done in conditions up to Hs = 

2.0 m, where wind speed is not relevant. The logistic time of spare parts required for underwater 

repairs is about 2 days. On average, a period of 6 h is required to organize the repair action. 

Cat. 4: Cable Replacement

If the integrity of one of the cables connecting the wind turbines to the transformer station or the 

transformer station to the onshore station is damaged, it will have to be replaced. This requires a 

specialized cable-laying vessel.

A typical cable repair action looks like this: 

1. The cable-laying vessel picks up the spare parts from the harbor and travels to the location of 

the faulted cable (3.5 h). 

2. Technicians use an ROV to detach the faulted cable (6 to 10 h). 

3. The cable-laying vessel is positioned above the broken cable (4 h). 

4. The cable-laying vessel hoists the broken cable from the sea surface (2 to 6 h). 

5. The cable-laying vessel lays the new cable (6 to 10 h). 

6. Technicians use an ROV to attach the new cable to the structures (6 to 10 h). 

7. The affected transformer/wind turbines are commissioned and the cable-laying vessel travels 

back to the harbor (3.5 h). 

The repair can be carried out in 24 to 40 h. Cable-laying operations can be done in conditions up 

to Hs = 1.0 m, where wind speed is not relevant. The logistic time of spare parts required for 

cable replacements is about 1 to 2 weeks. On average a period of 24 h is required to organize the 

repair action.
89 

This report is available at no cost from the 

National Renewable Energy Laboratory (NREL) 

at www.nrel.gov/publications.

Appendix F. Preferred O&M Detail

Table 48. Summary of downtime and cost of potential preferred O&M strategies

Summary of downtime and costs Availability [%]

Location U.S. baseline IO&M case study Costs [ $ct/kWh]

Type of WT NREL offshore 5-MW baseline Total effort [M $]

Wind farm 100 turbines Baseline Step 1 Step 1 + Variation A Step 1 + Variation B Step 1 + Variation C Step 1 + Variation D1

Annotation

Access vessel Hs = 

1.5m

Mother vessel with 0 

costs

Jack-up Tlog = 0h 

with OPEX

Helicopter access CBM 50% Detection 

rate

Total Total Total Total Total Total

Downtime per year

Corrective WT Logistics hr 14,327 14,327 14,327 9,942 14,327 12,445

Waiting hr 89,269 17,162 7,832 17,162 13,192 15,568

Travel hr 1,540 1,540 296 1,540 861 1,496

Repair hr 11,031 11,031 7,155 11,031 11,031 11,031

TOTAL corrective WT hr 116,167 44,060 29,610 39,675 39,411 40,540

Corrective BOP Logistics hr 7,995 7,995 7,995 7,995 7,995 7,995

Waiting hr 7,406 1,680 936 1,680 1,680 1,680

Travel hr 130 130 25 130 130 130

Repair hr 1,853 1,853 902 1,853 1,853 1,853

TOTAL corrective BOP hr 17,384 11,658 9,858 11,658 11,658 11,658

Preventive TOTAL preventive hr 2,640 2,640 2,640 2,640 2,640 2,640

TOTAL hr 136,192 58,358 42,108 53,973 53,709 54,838

Availability % 84.5% 93.3% 95.2% 93.8% 93.9% 93.7%

Loss of production per year MWh 326,003 135,733 94,501 126,617 124,717 127,388

Energy production per year MWh 1,633,521 1,823,791 1,865,022 1,832,907 1,834,807 1,832,136

Revenue losses per year kUSD 40,750 16,967 11,813 15,827 15,590 15,924

Costs of repair per year

Material costs

Corrective WT TOTAL corrective WT kUSD 16,684 16,684 16,684 16,684 16,684 16,684

Corrective BOP TOTAL corrective BOP kUSD 58 58 58 58 58 58

Preventive TOTAL preventive kUSD 1,574 1,574 1,574 1,574 1,574 1,574

TOTAL kUSD 18,317 18,317 18,317 18,317 18,317 18,317

Labour costs

Corrective WT TOTAL corrective WT kUSD 4,366 4,366 3,457 4,366 3,857 4,366

Corrective BOP TOTAL corrective BOP kUSD 5 5 4 5 5 5

Preventive TOTAL preventive kUSD 2,103 2,103 1,911 2,103 2,103 2,103

TOTAL 6,474 6,474 5,372 6,474 5,965 6,474

Costs equipment

Corrective WT MOB/DEMOB kUSD 4,615 4,615 4,615 0 4,615 4,615

Waiting kUSD 5,379 3,967 2,968 1,925 3,853 3,967

Repair kUSD 8,432 8,757 7,229 3,245 11,796 8,757

TOTAL corrective WT kUSD 18,426 17,339 14,812 5,170 20,264 17,339

Corrective BOP MOB/DEMOB kUSD 598 598 598 598 598 598

Waiting kUSD 255 254 253 254 254 254

Repair kUSD 611 612 611 612 612 612

TOTAL corrective BOP kUSD 1,464 1,463 1,463 1,463 1,464 1,463

Preventive TOTAL preventive 1,487 1,585 1,565 1,585 1,653 1,585

TOTAL 21,376 20,387 17,839 8,218 23,381 20,387

Corrective WT kUSD 39,476 38,389 34,953 26,220 40,805 38,389

Corrective BOP kUSD 1,527 1,527 1,525 1,527 1,527 1,527

Preventive kUSD 5,164 5,262 5,050 5,262 5,330 5,262

Fixed yearly costs kUSD 0 0 0 0 0 0

Total costs of repair kUSD 46,168 45,178 41,528 33,009 47,663 45,178

Total cost per kWh USD cent/kWh 2.83 2.48 2.23 1.80 2.60 2.47

Total costs of repair per kW installed USD/kW 92 90 83 66 95 90

Total cost per kW investment 5.1% 5.0% 4.6% 3.7% 5.3% 5.0%

Total effort

Sum revenue losses & total costs of repair kUSD 86,918 62,145 53,341 48,836 63,252 61,102

Summary of cost savings Potential cost reduction vs 

baseline (step 1 only) and vs 

step 1 (Variations)

kUSD/year 24,773 8,804 13,308 -1,108 1,043

Reduction over lifetime = 20 

years

kUSD

495,465 176,079 266,164 -22,154 20,861