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Prognostic Control to Enhance Offshore Wind Turbine Operations and Maintenance Strategies

Prognostic Control to Enhance Offshore Wind Turbine Operations and Maintenance Strategies. D. Todd Griffith 1 , Nate Yoder 2 , Brian Resor 1 , Jon White 1 , Josh Paquette 1 , Alistair Ogilvie 1 , Valerie Peters 1 1 Sandia National Laboratories 2 ATA Engineering

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Prognostic Control to Enhance Offshore Wind Turbine Operations and Maintenance Strategies

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  1. Prognostic Control to Enhance Offshore Wind Turbine Operations and Maintenance Strategies • D. Todd Griffith1, Nate Yoder2, Brian Resor1, Jon White1, Josh Paquette1, Alistair Ogilvie1, Valerie Peters1 • 1Sandia National Laboratories • 2ATA Engineering • European Wind Energy Association • (EWEA) 2012 Annual Event • April 16-19,2012; Copenhagen, Denmark

  2. Background • Operations and maintenance (O&M) costs for offshore wind plants are estimated to be 2-5x those for onshore plantsand represent 20-30% of the total levelized cost of energy [1] • Increased loading and environmental harshness • Difficulty of access [2] • Structural health monitoring of offshore turbines as part of a condition based maintenance paradigm could provide significant cost reductions • Reduce unscheduled maintenance • Improve supply chain management • Smart turbine load management • Operate and maintain turbines to maximize overall profit • [Sensing, CBM/SHM, Solid Mechanics, Controls] [3]

  3. Simulation Campaign: Broad View The most relevant damage and fault conditions for simulation and further study are being identified using other Sandia National Laboratories projects. Sandia/DOE Continuous Reliability Enhancement for Wind (CREW) Sandia/DOE Blade Reliability Collaborative (BRC) Simulation Campaign • [Sensing, CBM/SHM, • Solid Mechanics, Controls]

  4. Multi-scale Simulation of Damage • Damage Mitigating Control • (FAST) Healthy / Damaged Blade Model (ANSYS) High Fidelity Simulations (ANSYS) Equivalent Blade Model (SNL BPE) Full Turbine Simulations (FAST or ADAMS) • Global Operating Sensitivity • (FAST or ADAMS) • Local Sensitivity • (ANSYS) Offshore Turbine Model (NREL 5MW)

  5. Healthy/Damage Blade Model • Case Study #1: Blade models with variable length trailing edge disbondscreated [4]

  6. Sandia 5-MW NuMAD Blade Model • A NuMAD blade model of a 61.5 m blade was created using existing blade geometry from the DOWEC[5,6] study for the preliminary model development • First model was heavier than NREL 5-MW reference wind turbine[7] so UD carbon spar caps were added

  7. Multi-scale Simulation of Damage • Damage Mitigating Control • (FAST) Healthy / Damaged Blade Model (ANSYS) High Fidelity Simulations (ANSYS) Equivalent Blade Model (SNL BPE) Full Turbine Simulations • (FAST or ADAMS) • Global Operating Sensitivity • (FAST or ADAMS) • Local Sensitivity • (ANSYS) Offshore Turbine Model (NREL 5MW)

  8. Reduced Order Blade Models • High fidelity blade models reduced to equivalent beam elements for full turbine simulations 100s of DOF 10s to 100s of thousands of DOF BPE

  9. BPE Stiffness Changes due to Trailing Edge Disbonds • A decrease of over 1% seen in a blade section for the 0.75 m disbond • For the 6 m disbond two sections have decreases larger than 7.5%, max=13.3%

  10. Stiffness Changes due to Trailing Edge Disbonds • Even large TE disbonds caused very small decreases of less than 0.5% in both flap- and edge-wise bending stiffnesses

  11. Multi-scale Simulation of Damage • Damage Mitigating Control • (FAST) Healthy / Damaged Blade Model (ANSYS) High Fidelity Simulations (ANSYS) Equivalent Blade Model (SNL BPE) Full Turbine Simulations • (FAST or ADAMS) • Global Operating Sensitivity • (FAST or ADAMS) • Local Sensitivity • (ANSYS) Offshore Turbine Model (NREL 5MW)

  12. Full Turbine Simulations • Reduced order blade models integrated into 5-MW offshore turbine models in FAST and ADAMS Water 20 m [1] Ground

  13. Multi-scale Simulation of Damage • Damage Mitigating Control • (FAST) Healthy / Damaged Blade Model (ANSYS) High Fidelity Simulations (ANSYS) Equivalent Blade Model (SNL BPE) Full Turbine Simulations • (FAST or ADAMS) • Global Operating Sensitivity • (FAST or ADAMS) • Local Sensitivity • (ANSYS) Offshore Turbine Model (NREL 5MW)

  14. FAST Sensitivity results • Skewness of pitching moment on damaged blade demonstrated highest sensitivity to presence and size of disbond

  15. Full Offshore Turbine Simulations using ADAMS • 1,007 total response measurements both on- and off-rotor were investigated • Pitching moments once again showed large changes in moments

  16. Multi-scale Simulation of Damage • Damage Mitigating Control • (FAST) Healthy / Damaged Blade Model (ANSYS) High Fidelity Simulations (ANSYS) Equivalent Blade Model (SNL BPE) Full Turbine Simulations • (FAST or ADAMS) • Global Operating Sensitivity • (FAST or ADAMS) • Local Sensitivity • (ANSYS) Offshore Turbine Model (NREL 5MW)

  17. ANSYS Strain Field Investigation • Disbond results in localized difference in strain localized around the edges of the disbond

  18. Multi-scale Simulation of Damage • Damage Mitigating Control • (FAST) Healthy / Damaged Blade Model (ANSYS) High Fidelity Simulations (ANSYS) Equivalent Blade Model (SNL BPE) Full Turbine Simulations • (FAST or ADAMS) • Global Operating Sensitivity • (FAST or ADAMS) • Local Sensitivity • (ANSYS) Offshore Turbine Model (NREL 5MW)

  19. Smart Turbine Load Management (1) • Turbine load management • Fatigue damage implications are considered first • Others: residual strength, deflection, etc. Damage Equivalent Load Fatigue Damage

  20. Smart Turbine Load Management (2) • Prognostic Control: damage mitigating controls strategy to • Increase life • Increase energy capture • Improved maintenance planning

  21. 19 Summary • A multi-scale methodology was developed to investigate the sensitivity of operational response measurements; Case Study #1: Trailing Edge Disbond • Addresses sensor selection and damage characterization through sensitivity analysis at both fine and coarse scales of the model • Prognostic control strategies were considered to manage turbine loads in the presence of damage for improved offshore turbine O&M strategies • The simulation campaign is currently being exercised for additional forms of damage in blade, tower and foundation as well as operating fault conditions (e.g. rotor imbalance) • Cost benefit analysis and alternate prognostic controls are being explored References W. Musial, R. Thresher, B. Ram. Large-Scale Offshore Wind Energy for the United States: Assessment of Opportunities and Barriers. CO, Golden: National Renewable Energy Laboratory, 2010. http://www.eurocopter.co.uk http://www.oceanpowermagazine.net http://www.netcomposites.com Kooijman, H.J.T., Lindenburg, C., Winkelaar, D., and van derHooft, E.L., “DOWEC 6 MW Pre-Design: Aero-elastic modeling of the DOWEC 6 MW pre-design in PHATAS,” ECN-CX--01-135, DOWEC 10046_009, Petten, the Netherlands: Energy Research Center of the Netherlands, September 2003. Lindenburg, C., “Aeroelastic Modeling of the LMH64-5 Blade,” DOWEC-02-KL-083/0, DOWEC 10083_001, Petten, the Netherlands: Energy Research Center of the Netherlands, December 2002. Jonkman, J.; Butterfield, S.; Musial, W.; and Scott, G., "Definition of a 5-MW Reference Wind Turbine for Offshore System Development," NREL/TP-500-38060, Golden, CO: National Renewable Energy Laboratory, February 2009.

  22. Extra Slides

  23. Multi-scale Simulation of Damage • Damage Mitigating Control • (FAST) Healthy / Damaged Blade Model (ANSYS) High Fidelity Simulations (ANSYS) Equivalent Blade Model (SNL BPE) Full Turbine Simulations • (FAST or ADAMS) • Global Operating Sensitivity • (FAST or ADAMS) • Local Sensitivity • (ANSYS) Offshore Turbine Model (NREL 5MW)

  24. 6 Equivalent Beam Properties with BPE • A Matlab based interface between NuMAD and BPE was created so that equivalent beam properties could be extracted from NuMAD models • The developed model has effective blade structural properties that closely approximate those used in the NREL 5-MW reference wind turbine blades[7]

  25. 7 Damaged Beam Properties with BPE • BPE was modified to allow for the automated insertion of variable length disbonds at a user specified location • Using BPE variety one healthy and a series of damaged blade models were created • 36 damaged blades with trailing edge disbonds extending between 0.125 and 6 m outboard from max chord were created • BPE modified slightly to improve performance over localized stiffness discontinuities

  26. 13 Full Offshore Turbine Simulations using ADAMS • Average responses also show significant changes • Changes localized to damaged region • Other responses and sensitivity measures currently being investigated

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