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A Framework for the Reliability Analysis of Wind Turbines against Windstorms and Non-Standard Inflow Definitions

A Framework for the Reliability Analysis of Wind Turbines against Windstorms and Non-Standard Inflow Definitions. Lance Manuel Dept. of Civil, Architectural, and Environmental Engineering University of Texas at Austin Paul S. Veers Wind Energy Technology Department

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A Framework for the Reliability Analysis of Wind Turbines against Windstorms and Non-Standard Inflow Definitions

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  1. A Framework for the Reliability Analysis of Wind Turbines against Windstorms and Non-Standard Inflow Definitions Lance Manuel Dept. of Civil, Architectural, and Environmental Engineering University of Texas at Austin Paul S. Veers Wind Energy Technology Department Sandia National Laboratories Paper No. AIAA-2009-1403 28th ASME Wind Energy SymposiumHeld in conjunction with the 47th AIAA Aerospace Sciences Meeting and Exhibition, Orlando, FL January 8, 2009

  2. Outline • Turbine design standards (specifications) • What is today’s practice regarding reliability? • Reliability in a Load and Resistance Factor Design (LRFD) format • Turbulence models for ultimate/fatigue limit states • Site assessment • What’s not covered? – Hazards, extreme events, windstorms • A framework for off-standard atmospheric conditions, windstorms, etc. • Event-tree approach (addressing “hazards”) • Example 1: low-level jets (more in AIAA-2009-1405 – Sim, Basu, Manuel) • Example 2: thunderstorm downbursts … work in progress • Concluding remarks

  3. Reliability based on standard design criteria Can non-standard flows be dealt with in a reliability framework? For any limit state: ultimate or fatigue? What parameters make up X? KeyThe vector, X, describes parameters needed for the “NORMAL TURBULENCE MODEL”(what about other non-neutral BL flows, windstorm hazards, etc.?) Goal: Establish reliability for specified limit states – ultimate, fatigue, etc. Long-term load distribution Joint PDF of environmental random variables Target probability of exceedance Short-term load distribution, conditional on environment

  4. Turbine design standard • Characteristic Loads • A suite of “Design Load Cases” (DLCs) • Includes aeroelastic model to apply atmospheric conditions to the dynamic structure • Characteristic Strength • Material properties • Damage rules • Statistical variation LRFDDesign Checking Equation MeanLoad CharacteristicLoad, L CharacteristicResistance, R MeanResistance aL ≤ fR Probability Distribution of Extreme Loads aL fR Distribution of Strength Design ConditionMargin

  5. Turbine design standard IEC Standards include a suite of Design Load Cases … yet these are not exhaustive

  6. Turbine design standard The Standard requires load extrapolation for extreme loads and load spectra for fatigue

  7. Turbine design standard The Normal Turbulence Model must be extrapolated to represent an extreme event in a 20-year service life.The atmospheric conditions are defined by the following: Normal Turbulence Model – Operating under Normal Conditions Prob. Sv(f) V Turbulence PSD f Wind Speed PDF Turbulence Intensity Coherence Parameters are defined for each wind speed class. Coh(r,f) f

  8. Turbine design standard ULTIMATE LIMIT STATELoad Extrapolation Long-term Extreme Load must result from many short operational simulations Sometimes, the largest loads come from moderate wind speeds

  9. Turbine design standard FATIGUE LIMIT STATELoad Spectra Long-term fatigue load spectra derived again from many short operational simulations

  10. Turbine design standard The IEC Standard does indeed address some site-specific conditions • The Standard requires site assessment (Section 11) to determine site complexity and wind conditions at the site. • demonstrate that conditions are no more severe than assumed for design • demonstrate structural integrity when conditions are more severe • The Standard addresses both normal and special conditions in targeted Annexes • Topographical complexity • Wind conditions (turbulence, inclination, shear, density) • Wakes of neighboring turbines • Earthquakes • Other conditions are not explicitly addressed at this time: • Thunderstorms Mostly covered by extreme wind • Hurricanes Sometimes covered by standard • Tornadoes Rarely covered by the standard conditions • Low-level jets Not yet addressed • Other … …

  11. A framework for off-standard atmospheric conditions Hazard

  12. A framework for off-standard atmospheric conditions Account for probability of failure due to all “hazards” (i.e., due to all off-standard extreme events) MachineResponse (Simulations) Site Assessment Each hazard, i, is characterized by its own parameters, Qi.Sweep over all possible values for these parameters, Qi. Requires aeroelastic response simulations for flows associated with the hazard/extreme event (e.g., LLJ, microburst, etc.) AN EVENT TREE-BASED HAZARD FRAMEWORK Hazard: Any non-standard atmospheric condition/event, including windstorms with their associated parameters

  13. Event Tree Framework – Example 1Hazard: Low-Level Jet Neutral Boundary Layer Convective Boundary Layer Stable Boundary Layer with Low Level Jet Graphic Credit: Bruce Bailey AWS Truewind Example: Low-Level Jet The Low-Level Jet occurs commonly at U.S. Great Plains sites as part of stable atmospheric BL flows LLJ - Kansas, USA Observed during CASES-99 [Poulos et al., BAMS, 2002] Presented by Jerome Fast, PNNL, 2008

  14. Event Tree Framework – Example 1Hazard: Low-Level Jet Example: LLJ data on jet height, maximum speeds, frequency 1359 soundings from a 2-year period Kansas-Oklahoma border Whiteman, C. D., et al., J. Appl. Meteor., 1997 328 ft = 100 m 46.0% of soundings showed max jet speed > 9.8 m/s 8.7% of soundings showed max jet speed > 19.5 m/s

  15. Event Tree Framework – Example 1Hazard: Low-Level Jet Event Reconstruction and Analysis Analysis of events down to the level of turbine loads is becoming possible by using mesoscale models and computational techniques such as Large Eddy Simulation (LES) in conjunction with aeroelastic codes (3rd paper in this session) NREL’s TurbSim also allows generation of LLJs in turbulence simulation LES for Turbulence Flow Field Source: S. Basu (TTU)

  16. Event Tree Framework – Example 1Hazard: Low-Level Jet Hazard = LLJ in our Event-Tree Framework Parameters characterizing LLJ = Q Q = {surface temperature cooling rate; geostrophic wind speed} Atmospheric flow simulation using LES or TurbSim for given Q. Aeroelastic response simulation using FAST TurbSim FAST Fatigue LES

  17. Event Tree Framework – Example 1Hazard: Low-Level Jet

  18. Event Tree Framework – Example 1Hazard: Low-Level Jet Turbulence Blade loads Fatigue load spectra neutral stable

  19. Event Tree Framework – Example 2Hazard: Thunderstorm Microburst Hazard = Thunderstorm microburst Thunderstorm downburst = Strong downdraft which includes an outflow of potentially damaging winds on or near the ground. Microburst = Downburst with diameter < 4 km and lasting < 5 min.

  20. Event Tree Framework – Example 2Hazard: Thunderstorm Microburst Hazard = Thunderstorm microburst Velocity field = U(x,y,z,t) = non-turbulent + turbulent component (analytical) (ARMA) Of interest: horizontal velocity (radial, storm front velocity) vertical velocity (downwards) References Oseguera, R. M. and Bowles, R. L., “A simple, analytical 3-dimensional downburst model based on boundary layer stagnation flow,” NASA-TM- 100632, NASA Langley Research Center, 18 pp., 1988. Vicroy, D. D., “A simple, analytical, axisymmetric microburst model for downdraft estimation,” NASA-TM-104053, NASA Langley Research Center, 13 pp., 1991. Vicroy, D. D., “Assessment of microburst models for downdraft estimation,” Journal of Aircraft, 29(6):1043–1048, 1992. Chay, M. T., Albermani, F., and Wilson, R., “Numerical and analytical simulation of downburst wind loads,” Engineering Structures, Vol. 28, pp. 240-254, 2006.

  21. Event Tree Framework – Example 2Hazard: Thunderstorm Microburst Hazard = Thunderstorm microburst Parameters characterizing microburst = Q Q = {radius of downdraft (R); storm duration (tm); max radial velocity (Ur,max ); elevation at which max radial velocity occurs (zm); radial distance at which max radial velocity occurs (rp = bR); translation velocity of storm front (Utrans)} Monte Carlo simulations

  22. Event Tree Framework – Example 2Hazard: Thunderstorm Microburst Radial velocity Horizontal velocity Resultant velocity Vertical velocity Typical microburst velocities at an assumed turbine hub located 1 km from center of microburst; 60 degrees offset from storm front direction; hub height = 90 meters (above ground level);for microburst lasting 3.5 min

  23. Event Tree Framework – Example 2Hazard: Thunderstorm Microburst horizontal vertical Annual rate of velocity exceedances (horizontal & vertical) based on Monte Carlo simulations for turbine site that experiences on average, 30 microbursts/yr

  24. Conclusions & Recommendations Widespread deployment of wind energy across large and diversified areas requires examination of a variety of unusual site-specific risks, including tornadoes, thunderstorms, low-level jets, and many others. • Hazards can be analyzed within an event-tree framework to assess the risk • Local (site-specific) events that are both frequent and outside the design conditions need to be characterized and analyzed for fatigue and extremes – winds near rated, extremes, etc. may be important • Atmospheric measurement campaigns are required to characterize locally important events (e.g., low-level jets) • Atmospheric modeling offers the potential to determine the criticality of unusual atmospheric events. Action Needed

  25. Acknowledgements Sandia National Laboratories Contract Nos. 681008 & 743358 Low-level jet example Prof. Sukanta Basu (Texas Tech University) Thunderstorm downburst example Mr. Hieu Huy Nguyen (PhD student, UT-Austin)

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