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風力エネルギーの運用・保守 (O&M) に関する調査レポート 2017年

The Wind Energy Operations & Maintenance Report 2017: Data and Independent Analysis to Help You Choose the Most Cost-effective O&M Strategy to Maximize ROI on Your Onshore Wind Power Assets

発行 New Energy Update 商品コード 234202
出版日 ページ情報 英文
納期: 即日から翌営業日
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本日の銀行送金レート: 1USD=114.65円で換算しております。
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風力エネルギーの運用・保守 (O&M) に関する調査レポート 2017年 The Wind Energy Operations & Maintenance Report 2017: Data and Independent Analysis to Help You Choose the Most Cost-effective O&M Strategy to Maximize ROI on Your Onshore Wind Power Assets
出版日: 2017年05月31日 ページ情報: 英文
概要

当レポートでは、風力発電施設の運用・保守の最適化戦略について調査し、風力エネルギー市場の現状、関連参入事業者、各種コスト、各コンポーネントの故障の状況・原因・影響、保守・保全戦略の種類と概要、タービンサイズ・発電容量による最適な保守戦略の選定に関する分析、様々なO&Mサービスと最適なO&Mサービス利用に関する検証などをまとめています。

エグゼクティブサマリー

調査手法

第1章 O&M市場の概要・規模・状況

  • 風力エネルギー市場の展望
    • 世界の設備発電容量
    • 世界市場の展望
  • 主要参入事業者
    • オペレーター
    • タービン製造業者
  • タービンサイズ
  • O&M市場
    • 風力発電所O&M市場の規模
    • 保証ステータス
    • O&M市場の動向

修復・リパワーリング市場

  • 修復
    • ブレード
    • 制御システムのアップグレード
    • パワーエレクトロニクス & 電子システム
    • 延命
  • リパワーリング

主要コンポーネントの故障・RCA (根本原因解析)

  • ブレード
  • ダイレクトドライブドライブトレイン
  • ギアボックスドライブトレイン
  • メインベアリング
  • ブレードベアリング

資産最適化

  • メンテナンス戦略
    • OEM
    • サードパーティー
    • 社内
    • ハイブリッド
    • リアクティブメンテナンス
    • 予防保全 (時間ベース)
    • 予知保全
    • 保守の改善
  • メンテナンススコアカードの測定方法
    • 故障状況
    • モデルパラメーター
  • メンテナンス戦略スコアカード
  • 制限・今後の活動

コンディションモニタリングシステム

結論

付録A

付録B

図表

このページに掲載されている内容は最新版と異なる場合があります。詳細はお問い合わせください。

目次

Real Data And Independent Analysis To Help You Maximize ROI on Your Wind Power Assets

Once a wind farm is operational, adopting a cost-effective operations and maintenance strategy is the main path for operators to maximize ROI on wind energy. The report will deliver concrete data and insight into several related areas of operations and maintenance for wind farms.

Key Questions Answered In This Report Include:

  • What are the failure rates of key components on different turbine types and capacities?
  • When is it more cost effective to carry out O&M in-house rather than working with OEMs or ISPs?
  • How are other companies reducing their O&M costs whilst delivering better wind farm performance?
  • Under which circumstances is it cost-effective to invest in condition monitoring systems, rather than carry out scheduled O&M?
  • What is the O&M market size?
  • What is the re-power market size?
  • What is the retrofit market size?
  • What are the end of warranty options for operators, when should they consider repowering or retrofitting?
  • How can I avoid catastrophic failure of gearboxes, generators or blades through best O&M practice?
  • What are the main causes of turbine failure and how can I prevent them?

Previous Buyers Of Our Reports Include:

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Key Deliverables Of The Report Include:

  • Access failure rates and repair time data for key components: Yaw System, control and protection system, generator system, turbine transmission system, rotor system, blade adjustment system and many more.
  • Identify the optimum maintenance strategy for gearboxes, generators and blades:
  • With WEU's proprietary scorecard you can select the optimum maintenance strategy for your assets.
  • Evaluate Retrofitting & Repowering: Explore Repowering, Retrofitting and End-of-Warranty options. Understand the latest condition monitoring capabilities and their impact on asset O&M strategies.
  • Benchmark your wind assets' reliability against your peer's: New insight into failure rates and repair times for key components across Danish, Variable Resistance, DFIM and Direct Drive turbines.

The Report Will Enable You To:

  • Maximize energy yield
  • Identify the failure types that have the biggest impact on your bottom line
  • Quantify the costs and benefits of adopting predictive O&M compared to scheduled and reactive approaches
  • Identify components most at risk of failure and estimate repair times
  • Benchmark against global leaders in Operations and Maintenance
  • Find out whether it is more cost-effective to leave O&M to a turbine manufacturer, outsource it to an independent service provider or bringing O&M in-house
  • Identify the O&M strategy most suitable to each market
  • Weigh up the costs and benefits of CMS
  • Evaluate the costs and benefits of re-powering vs retrofitting

WHO SHOULD BUY THIS REPORT

Owners and operators of wind power assets will benefit form actionable analysis on the costs and benefits of each O&M approach. The unique failure rate data provides insight into the performance of different turbine types.

The following functions will benefit

  • Asset managers: get a deeper understanding of the costs and performance implications of each O&M approach so you can maximize return on investment on your wind power assets.
  • O&M directors: optimise your wind farm performance and benchmark against your peers, by drawing on exclusive quantitative analysis.
  • Business Development Managers O&M: measure the O&M, repower and retrofit market size, evaluate opportunities in key markets globally and compare your technologies performance with your peers

Table of Contents

List of Figures

List of Tables

Executive Summary

Methodology

1. O&M MARKET OVERVIEW, SIZING AND STATUS

  • 1.1. Wind Energy Market Outlook
    • 1.1.1. Global Installed Capacity
      • 1.1.1.1. Global Wind Barometer
      • 1.1.1.2. Asia-Pacific
        • China
        • India
      • 1.1.1.3. Regional Markets - North America
        • The US
        • Canada
        • Mexico
      • 1.1.1.4. Regional Markets - Europe .
        • Germany
        • France
        • The UK
        • Turkey
        • Italy
      • 1.1.1.5. Regional Markets - Latin America
        • Brazil
        • Argentina
        • Chile
    • 1.1.2. Worldwide Future Prospects
  • 1.2. Major Market Players
    • 1.2.1. Operators
    • 1.2.2. Turbine Manufacturers
  • 1.3. Turbine Size
  • 1.4. O&M Market
    • 1.4.1. Wind Farm O&M Market Size
    • 1.4.2. Warranty Status
    • 1.4.3. O&M Market Trends

2. RETROFIT AND REPOWERING MARKET

  • 2.1. Retrofitting
    • 2.1.1. Blades
      • 2.1.1.1. Power Curve Upgrade
      • 2.1.1.2. Blade Protection
      • 2.1.1.3. Noise Mitigation
    • 2.1.2. Control System Updates
      • 2.1.2.1. Advanced Controls
      • 2.1.2.2. SCADA
      • 2.1.2.3. LiDAR
    • 2.1.3. Power Electronics & Electrical Systems
      • 2.1.3.1. Grid Connection Upgrades .
    • 2.1.4. Life Extension
  • 2.2. Repowering
    • 2.2.1. Global Repowering Market .
    • 2.2.2. European Repowering Market .
      • 2.2.2.1. Germany
      • 2.2.2.2. Denmark
      • 2.2.2.3. Spain
      • 2.2.2.4. United Kingdom
      • 2.2.2.5. Netherlands
    • 2.2.3. US Repowering Market
      • 2.2.3.1. California

3. FAILURE FREQUENCIES AND DOWNTIMES

  • 3.1. Definitions and methodology
    • 3.1.1. Turbine Technology
      • 3.1.1.1. Type A - Danish Concept
      • 3.1.1.2. Type B - Variable Resistance
      • 3.1.1.3. Type C - Doubly Fed Induction Motor (DFIM) .
      • 3.1.1.4. Type D-EE/PM - Direct Drive
    • 3.1.2. Turbine Size
    • 3.1.3. Turbine Age
  • 3.2. Results
    • 3.2.1. All Turbine Groups
    • 3.2.2. Type A - Danish Concept
    • 3.2.3. Type B - Variable Resistance
    • 3.2.4. Type C - DFIM
    • 3.2.5. Type D - Direct Drive
  • 3.3. The Variance

4. CONDITION MONITORING SYSTEM

  • 4.1. CMS Market
    • 4.1.1. OEM Options
    • 4.1.2. Retrofit Options
  • 4.2. CMS Market Options
    • 4.2.1. Vibration Measurement
    • 4.2.2. Oil Pressure, Temperature & Particle Count
  • 4.3. CMS Potential - Big Data

5. ASSET OPTIMISATION

  • 5.1. Operation Strategies
    • 5.1.1. OEMs and EOW full-service contracts
    • 5.1.2. Independent service providers (third parties)
    • 5.1.3. In-house O&M
    • 5.1.4. Tapered (Hybrid)
  • 5.2. Maintenance Strategies
    • 5.2.1. Reactive Maintenance (Corrective)
    • 5.2.2. Preventive (Time-Based) Maintenance .
    • 5.2.3. Predictive Maintenance .
      • 5.2.3.1. Performance monitoring (non-intrusive condition monitoring)
      • 5.2.3.2. Condition-based maintenance
      • 5.2.3.3. Reliability-based maintenance (risk-based)
    • 5.2.4. Improvement Maintenance
  • 5.3. Maintenance Scorecard Methodology .
    • 5.3.1. Failure Scenarios
    • 5.3.2. Model Parameters
      • 5.3.2.1. Unscheduled Cost Factors .
      • 5.3.2.2. Supply Chain factors .
      • 5.3.2.3. CMS Factors
      • 5.3.2.4. Additional Factors
  • 5.4. Maintenance Strategy Scorecard .
    • 5.4.1. The Effect of Turbine Capacity and Farm Size
      • 5.4.1.1. Reference Failure Scenario .
      • 5.4.1.2. High Gearbox Failure Scenario
      • 5.4.1.3. High Blade Failure Scenario
      • 5.4.1.4. High Generator Failure Scenario .
    • 5.4.2. The Effect of Capacity Factor (CF) and Cost of Electricity (CoE) . .
      • 5.4.2.1. Reference Failure Scenario .
      • 5.4.2.2. High Gearbox Failure Scenario
      • 5.4.2.3. High Blade Failure Scenario
      • 5.4.2.4. High Generator Failure Scenario .
    • 5.4.3. The Effect of Farm Age
      • 5.4.3.1. Reference Failure Scenario .
      • 5.4.3.2. High Gearbox Failure Scenario
      • 5.4.3.3. High Blade Failure Scenario
      • 5.4.3.4. High Generator Failure Scenario .
  • 5.5. Limitations and Future Work

CONCLUDING REMARKS

APPENDIX A - FAILURE RATE AND MTTR CALCULATION METHODOLOGY

APPENDIX B - SCORECARD OUTPUT

APPENDIX C - THE EFFECT OF TURBINE AND FARM SIZE

  • C.1. Remote Location, No Spare in Stock
  • C.2. Proximate Location, Spares in Stock

APPENDIX D

  • C.1. The Effect of CF and CoE
  • C.2. The effect of Farm Age

ABBREVIATIONS

BIBLIOGRAPHY

List of Figures

  • Figure 1: Global evolution towards market based mechanisms
  • Figure 2: Worldwide wind energy capacity .
  • Figure 3: Steady decrease of levelised cost of wind energy
  • Figure 4: Increasing corporate purchase trend .
  • Figure 5: Global annual cumulative wind installed capacity
  • Figure 6: Global wind capacity distribution .
  • Figure 7: Worldwide cumulative installed capacity breakdown
  • Figure 8: Top 10 new installed capacity in 2016
  • Figure 9: Chinese wind sector installed capacity and generated electricity
  • Figure 10: Evolution of the Indian Wind Capacity (2010-2016) .
  • Figure 11: US Installed Wind Power Capacity, All States
  • Figure 12: US Installed Wind Power Capacity, Top States .
  • Figure 13: Age Structure of Turbine Fleet in the US by 1Q 2017
  • Figure 14: Canada`s installed capacity, end of 2016
  • Figure 15: USD-MXN exchange rate trend
  • Figure 16: Cumulative Installed Power in the European Union by Source
  • Figure 17: German Onshore Wind Capacity including Repowering and Dismantling
  • Figure 18: Onshore Wind Pipeline by January 2017 (Turbines larger than 0.5MW)
  • Figure 19: Geographic Placement of the Grid Expansion Area .
  • Figure 20: German wholesale prices in 2016 .
  • Figure 21: IEA New Policies Scenario -2020 and 2030 capacity forecasts by region . .
  • Figure 22: Top 15 operators around the world by MW installed capacity
  • Figure 23: Global Newly Installed Capacity by Turbine Manufacturer - 2016
  • Figure 24: Market share of Top 10 turbine manufacturers
  • Figure 25: Evolution of wind turbine capacity and size in Germany
  • Figure 26: Evolution of average nameplate capacity, rotor diameter, and hub height in the US .
  • Figure 27: Wind Turbine Characteristics in 2030 for Onshore Wind Projects
  • Figure 28: Onshore wind O&M market size forecast
  • Figure 29: Global growth of out-of-warranty O&M market
  • Figure 30: China's estimated cumulative off-warranty onshore wind capacity .
  • Figure 31: WEU 2015 Survey - the typical length of the O%M service contracts . .
  • Figure 32: MAKE 2016 Survey - Average length of service packages offered by major western OEMs .
  • Figure 33: Past, present and future O&M strategy for large European utilities . .
  • Figure 34: Estimated share of the direct drive and geared turbines
  • Figure 35: Age of Global Wind Capacity Installed Worldwide
  • Figure 36: Older Generation of Wind Turbines
  • Figure 37: Newer Generation of Wind Turbines .
  • Figure 38: Performance Landscape of Modern Onshore Wind Turbines .
  • Figure 39: Global Production Potential of a 3-5% AEP Increase on Aging Turbines, at 22.9% Capacity Factor .
  • Figure 40: EU-27/28 Production Potential of 3-5% AEP Increase on Aging Turbines, at 28% Capacity Factor . .
  • Figure 41: U.S. Production Potential of 3-5% AEP Increase on Aging Turbines, at 29% Capacity Factor
  • Figure 42: Moder Wind Turbines vs Rotor Diameter .
  • Figure 43: Vortex Generator AEP Gain
  • Figure 44: Bladena's Retrofit Blade Technologies .
  • Figure 45: Adjusted reference power curve obtained by filtering icing condition data
  • Figure 46: WIPS heating elements
  • Figure 47: Power curve with and without WIPS
  • Figure 48: Relationship between AEP, Rotor Diameter and Sound Power Level .
  • Figure 49: Power Curve Analysis
  • Figure 50: Power curve comparison of 14 turbines of a European wind farm
  • Figure 51: Gamesa's Aging Fleet Solution
  • Figure 52: Siemens' Wind Service Portfolio .
  • Figure 53: Hypothetical wind shear profile for an agricultural land
  • Figure 54: Reduction of Blade ad hub lifetime fatigue loads with individual blade control . .
  • Figure 55: Reduction of extreme loads
  • Figure 56: German, US and Danish National Installed Wind Energy Capacity in 2000 .
  • Figure 57: Cumulative Global Repowering Market Potential (GW) .
  • Figure 58: Cumulative EU-27/28 Repowering Market Potential (GW) .
  • Figure 59: Germany's aging wind turbine installed capacity landscape
  • Figure 60: Germany's Onshore Wind Turbine Age Structure .
  • Figure 61: Denmark's aging wind turbine installed capacity landscape
  • Figure 62: Spain's aging wind turbine installed capacity landscape
  • Figure 63: UK's aging wind turbine installed capacity
  • Figure 64: Renewable Investment expected to fall 95% by 2020
  • Figure 65: Netherland's aging wind turbine installed capacity landscape
  • Figure 66: US' aging wind turbine installed capacity landscape .
  • Figure 67: Cumulative U.S. Repowering Market Potential (GW) .
  • Figure 68: Relationship between MTTF, MTTR and MTBF .
  • Figure 69: Evolution of the wind turbine drivetrain market share in different regions
  • Figure 70: Failure Rate for All Turbines
  • Figure 71: MTTR for all turbines
  • Figure 72: Failure Rate of <1MW Danish Concept Turbines
  • Figure 73: MTTR of <1MW Danish Concept Turbines
  • Figure 74: Failure Rate of <1MW Variable Resistance Turbines
  • Figure 75: Failure Rate of ≥1MW Variable Resistance Turbines
  • Figure 76: MTTR of <1MW Variable Resistance Turbines
  • Figure 77: MTTR of ≥1MW Variable Resistance Turbines
  • Figure 78: Failure Rate of <1MW DFIM Turbines
  • Figure 79: Failure Rate of ≥1MW DFIM Turbines
  • Figure 80: MTTR of <1MW DFIM Turbines
  • Figure 81: MTTR of ≥1MW DFIM Turbines
  • Figure 82: Failure Rate of <1MW Direct Drive Turbines .
  • Figure 83: MTTR of<1MW Direct Drive Turbines
  • Figure 84: Failure Rate variance for turbine groups <1MW
  • Figure 85: Failure Rate variance for turbine groups ≥1MW
  • Figure 86: MTTR variance for turbine groups <1MW
  • Figure 87: MTTR variance for turbine groups ≥1MW
  • Figure 88: O&M Strategy
  • Figure 89: Corrective, CBM and Scheduled O&M Strategies .
  • Figure 90: Siemens' SIPLUS CMS System features 16 IEPE Sensors
  • Figure 91: CMS Data Collection to Interpretation Cycle
  • Figure 92: Ring Gear Fault Detection
  • Figure 93: Hydraulic Unit and Gearbox HS Bearing Failure Detection
  • Figure 94: Consolidating wind market
  • Figure 95: Risk feeling depending on the operator type
  • Figure 96: Which O&M service strategy do you believe is the best fit in the post-warranty period?
  • Figure 97: Progressive transition from being an owner to a third party service provider . .
  • Figure 98: Liftra Self-Hoisting Crane changing gearbox on Siemens 2.3MW
  • Figure 99: Wind farm performance and its main risks .
  • Figure 100: Concept of spare part pooling
  • Figure 101: Pooling effect for a typical gearbox.
  • Figure 102: Emerging hybrid relationships
  • Figure 103: Currently used maintenance strategies .
  • Figure 104: Which O&M response approach do you tend to adopt in relation to a fleet of ageing wind turbines?
  • Figure 105: Decision flow chart for the justification of reactive maintenance.
  • Figure 106: How would you best describe your approach towards O&M activities over the whole lifecycle of your assets? .
  • Figure 107: Bearing life scatter
  • Figure 108: Condition monitoring symptom and fault analysis and response process
  • Figure 109: In general do you tend to deploy condition monitoring systems (CMS) on your assets? .
  • Figure 110: What kind of CMS do you typically deploy?
  • Figure 111: The strategic equation for reliability based maintenance .
  • Figure 112: Considerations for the Maintenance Scenarios
  • Figure 113: Maintenance strategy scorecard workflow .
  • Figure 114: P-F curve
  • Figure 115: Probability versus component condition indicator .
  • Figure 116: Reference Scenario - The effect of Turbine Capacity and Farm Size on the strategy . .
  • Figure 117: High Gearbox Failure Scenario - The effect of Turbine Capacity and Farm Size on the strategy . .
  • Figure 118: High Blade Failure Scenario - The effect of Turbine Capacity and Farm Size on the strategy . .
  • Figure 119: High Generator Failure Scenario - The effect of Turbine Capacity and Farm Size on the strategy .
  • Figure 120: Reference Failure Scenario - The effect of Capacity Factor and Electricity Tariff on the strategy
  • Figure 121: High Gearbox Failure Scenario - The effect of Capacity Factor and Electricity Tariff on the strategy . .
  • Figure 122: High Blade Failure Scenario - The effect of Capacity Factor and Electricity Tariff on the strategy . .
  • Figure 123: High Generator Failure Scenario - The effect of Capacity Factor and Electricity Tariff on the strategy
  • Figure 124: Reference Failure Scenario cost ratings with respect to farm age and income factor .
  • Figure 125: High Gearbox Failure Scenario cost ratings with respect to farm age and income factor
  • Figure 126: High Blade Failure Scenario cost ratings with respect to farm age and income factor
  • Figure 127: High Generator Failure Scenario cost ratings with respect to farm age and income factor .

List of Tables

  • Table 1: Worldwide cumulative installed capacity breakdown (Onshore and Offshore)
  • Table 2: Top Five Capacity Additions during 2016, MW
  • Table 3: Summary of Winning Wind Projects in 2016 Round One Auctions .
  • Table 4: Summary of Winning Wind Projects in 2016 Round Two Auctions .
  • Table 5: German Wind Tenders 2017-2019
  • Table 6: PPE Scenarios for Onshore Wind Energy in France
  • Table 7: Latest deals in the onshore wind ISP market .
  • Table 8: Top Retrofit Product & Services
  • Table 9: Retrofit Product and Suppliers
  • Table 10 Summary of Ice Protection Supplier
  • Table 11: Knorr-Bremse PowerTech Power Supply and Grid Compensation .
  • Table 12: Environmental Impact of Wind Turbine Life Extension
  • Table 13: Gamesa's Retrofit Services .
  • Table 14: Full vs Partial Repowering Options
  • Table 15: Full vs Partial Repowering Pros & Cons .
  • Table 16: 2016 Net and Gross Additions in Germany
  • Table 17: Component categories and sub-components of wind turbines
  • Table 18: Characteristics of key turbine technologies
  • Table 19: Data fills for turbine nameplate capacity and technology
  • Table 20: Data fills for year of operation and technology .
  • Table 21: Number of Sensors as per GNVHL-SE-0439
  • Table 22: Main O&M contract models in Europe
  • Table 23: Advantages and disadvantages of OEM service contracts
  • Table 24: Advantages and disadvantages of ISP service contracts .
  • Table 25: Advantages and disadvantages of in-house maintenance
  • Table 26: Advantages and disadvantages of hybrid strategies
  • Table 27: JUWI's knowledge gain through hybrid maintenance strategies
  • Table 28: Pros and cons of different maintenance strategies .
  • Table 29: 20 Year failure rate inputs for all scenarios
  • Table 30: Periodic maintenance cost and frequency
  • Table 31: Component cost assumptions
  • Table 32: Component downtime per failure assumptions
  • Table 33: Average labor cost per failure assumptions
  • Table 34: Major component crane assumptions .
  • Table 35: Average crane cost per failure assumptions
  • Table 36: Lead time assumptions
  • Table 37: Transportation time assumptions
  • Table 38: CMS costs
  • Table 39: Total failure cost for all gearbox failures for a given population
  • Table 40: Gearbox CMS parameters for major failure modes*
  • Table 41: Compound gearbox CMS parameters
  • Table 42: Major component CMS parameter assumptions .
  • Table 43: Additional failure cost due to secondary damage
  • Table 44: Cost reduction for CMS
  • Table 45: Farm parameters
  • Table 46: Periodic maintenance costs .
  • Table 47: Component risk factors and failure scenario
  • Table 48: Supply chain factors
  • Table 49: Condition monitoring system (CMS) factors
  • Table 50: Major component lifetime O&M costs
  • Table 51: Scorecard output based on the lifetime cost comparison*
  • Table 52: Normalized scorecard result
  • Table 53: Case 1 - 3MW turbines, 630MW wind farm
  • Table 54: Case 1 - 2MW turbines, 420MW wind farm
  • Table 55: Case 1 - 1MW turbines, 210MW wind farm
  • Table 56: Case 2 - 3MW turbines, 315MW wind farm
  • Table 57: Case 2 - 2MW turbines, 210MW wind farm
  • Table 58: Case 2 - 1MW turbines, 105MW wind farm
  • Table 59: Case 3 - 3MW turbines, 210MW wind farm
  • Table 60: Case 3 - 2MW turbines, 140MW wind farm
  • Table 61: Case 3 - 1MW turbines, 70MW wind farm
  • Table 62: Case 4 - 3MW turbines, 105MW wind farm
  • Table 63: Case 4 - 2MW turbines, 70MW wind farm
  • Table 64: Case 4 - 1MW turbines, 35MW wind farm
  • Table 65: Case 5 - 3MW turbines, 630MW wind farm
  • Table 66: Case 5 - 2MW turbines, 420MW wind farm
  • Table 67: Case 5 - 1MW turbines, 210MW wind farm
  • Table 68: Case 6 - 3MW turbines, 315MW wind farm
  • Table 69: Case 6 - 2MW turbines, 210MW wind farm
  • Table 70: Case 6 - 1MW turbines, 105MW wind farm
  • Table 71: Case 7 - 3MW turbines, 210MW wind farm
  • Table 72: Case 7 - 2MW turbines, 140MW wind farm
  • Table 73: Case 7 - 1MW turbines, 70MW wind farm
  • Table 74: Case 8 - 3MW turbines, 105MW wind farm
  • Table 75: Case 8 - 2MW turbines, 70MW wind farm
  • Table 76: Case 8 - 1MW turbines, 35MW wind farm
  • Table 77: Reference Failure Scenario - the effect of Farm Age
  • Table 78: High Gearbox Failure Scenario - the effect of Farm Age
  • Table 79: High Blade Failure Scenario - the effect of Farm Age
  • Table 80: High Generator Failure Scenario - the effect of Farm Age .
  • Table 81: Reference Failure Scenario - the effect of Farm Age
  • Table 82: High Gearbox Failure Scenario - the effect of Farm Age
  • Table 83: High Blade Failure Scenario - the effect of Farm Age
  • Table 84: High Generator Failure Scenario - the effect of Farm Age .
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