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RWE Innogy 6/1/2014PAGE 1 O&M Modelling for Large Scale Offshore Wind Farms by Use of Markov Processes 6th of February 2013, EWEA 2013 Remote Wind Farms:

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Presentation on theme: "RWE Innogy 6/1/2014PAGE 1 O&M Modelling for Large Scale Offshore Wind Farms by Use of Markov Processes 6th of February 2013, EWEA 2013 Remote Wind Farms:"— Presentation transcript:

1 RWE Innogy 6/1/2014PAGE 1 O&M Modelling for Large Scale Offshore Wind Farms by Use of Markov Processes 6th of February 2013, EWEA 2013 Remote Wind Farms: Strategies and Concepts Burcu Özdirik

2 PAGE 2 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Background Far-shore Wind Farm Projects and Challenges Various Design Parameters Number and type of WTG Distance between WTGs Wear and tear on the WTG components Various Locations of Sites Distance to shore Weather conditions Capacity factor Operational Particulars Logistic strategies Working regulations Scheduled maintenance concepts Comparability with regards to the economic efficiency of O&M is required.

3 PAGE 3 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik System Characteristics Modelling Framework Offshore Operations Markov Modell assembly - loop monthly - loop annual - loop Technical AvailabilityDemand of Resources results Modelling Approach System Accessibility System Reliability

4 PAGE 4 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Scope of Work Influencing factors of Offshore O&M Economic Efficiency of Operations Technical Availability of OWF Downtime [h] Respective Period (e.g. 1 a = 8760 [h] Downtime due to Unscheduled Maintenance [h] Downtime due to Scheduled Maintenance [h] Unplanned Outages / Failures Repair Mission Costs Access- time Travel- time Logistics Weather Port Dist. Logistics Repair- time Mobil.- time Component Type of WTG Lead- time Logistics Personnel Logistics Spare Parts Type of FC Weather waiting- time Port Dist. Weather on site Logistics Repair-time

5 PAGE 5 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Characteristics of MC WTG FC I FC II FC III FC IV Markov Modell MC repair - time spare parts number of technicians means of transportation H s or v w limitation PAX access-time lead time equipment Speed [kmh] mobilisation time fuel consumption availability lead time Modelling Approach Elements of System and their characteristics Reliability Parameters System-Reliability Assemblies Technical System (OWF) Sub-system MC BoP FC I FC II FC III FC IV Assemblies System-Reliability Sub-system FC – Failure Class MC – Maintenance Class

6 PAGE 6 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Modelling Approach Assembly-specific Markov-Chain FC IFC II FC IIIFC IV Curtailed Load Operation Probability of subsequent damages Residence period is determined by the property of ergodicity Monthly assembly-specific transition matrices Initial probability (probability to fail) Probability of Repair Monthly accessibility indicator Duration of mission Access- and Mobilisation time Travelling time Repair time Further delays

7 PAGE 7 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Results Technical Availability 97% - Thornton Bank (2009) and alpha ventus 97% (2011) [3, 4, 5] Failure data of IWES [1] Weather data of FINO 1 [2] Wave height limitations 1.5 m Wind speed limitation 18 m/s Service of 180 man-hours per WTG starting in June General Assumptions 50 x 5 MW WTGs (rotor diameter of 128 m) 40 km distance to an operational port Area of site is 40 km² with 8D distance between WTGs 25 service technicians Offshore Wind Farm 200 x 5 MW WTGs (rotor diameter of 128 m) 100 km distance to an operational port Area of site is 280 km² with 10D distance between WTGs 100 service technicians Large Scale Far Shore Wind Farm 95% 97%

8 PAGE 8 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Annual Downtime [h/a] Results Average Annual Downtime per WTG 70 h 25 h 60 h

9 PAGE 9 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Conclusions Modelling results reflect the current experiences regarding operational offshore wind farms Flexible assembly-specific modelling over the calendar year enables a mid- and long-term comparability of planned offshore wind farms Markov chains around assembly specific operations enable the modelling of the interacting influence factors and their impact on the technical availability and the demand of resources The model further enables evaluations with regards to -Logistic strategies & Simultaneous use of vessels -Impact of limiting resources -Maintenance strategies The model is expandable in order to provide cost-benefit analysis

10 PAGE 10 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Thank you for your attention. Burcu Özdirik Doctoral Candidate Operations and Maintenance Offshore Wind, RWE Innogy Institute of Environmental Technology and Energy Economics Technical University of Hamburg- Harburg

11 PAGE 11 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik References [1]S. Faulstich, M. Durstewitz, B. Hahn, K. Knorr and K. Rohring, Windenergie Report Deutschland 2008, Institut für Solare Energieversorgunstechnik (ISET), Kassel, [2]FINO 1, [Online available: 2012, accessed on [3]D. Koenemann, Erwartungen übertroffen – Ein Rückblick auf das erste Betriebsjahr 2011, BWK – Das Energie Fachmagazin, Bd. 64, pp , 2012 [4]alpha ventus – Pressemitteilung 2012, [Online available: accessed on [5]Repower Systems – Pressemitteilung 2010, [Online available: accessed on

12 PAGE 12 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Results Parameter Variation for Far-shore WF Assumptions Speed of vessels Distance to port Reliability Maintainability Serviceability Distance within WF Lead- times

13 PAGE 13 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Accessibility Indicators FINO 1 Weather Data (7 years)

14 PAGE 14 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Accessibility Indicators for Hs 1.5m FINO 1 Weather Data (7 years)

15 PAGE 15 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Results Demand of Vessels for the Far-shore Wind Farm

16 PAGE 16 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Results Demand of CTVs for the Far-shore Wind Farm Additional CTVs for scheduled Maintenance

17 PAGE 17 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Split of WTG into Assemblies Rotor-system (blade, bearing, hub) Pitch-system Yaw-system Generator Gearbox Sensors Drive Train incl. Bearings Electrical Control

18 PAGE 18 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Results Split of Downtime for the Far-shore Wind Farm Far-shore WF Far-shore WF (with helicopter)

19 PAGE 19 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Results Split of Downtime for the Far-shore Wind Farm Far-shore WF (CTV 1.5m) Far-shore WF (CTV 2m)

20 PAGE 20 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Results Split of Downtime for the Offshore Wind Farm Offshore WF Offshore WF (with helicopter)

21 PAGE 21 RWE InnogyIUE – TUHH EWEA 2013 February 2013Burcu Özdirik Transition Probabilities


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