Evaluation of the extreme and fatigue load measurements at alpha ventus

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RAVE Conference 2015, Bremerhaven

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Evaluation of the extreme and fatigue load measurements at alpha ventus

  1. 1. Gefördert auf Grund eines Beschlusses des Deutschen Bundestages Projektträger Koordination Evaluation of the extreme and fatigue load measurements at alpha ventus Ricardo Faerron, Sarah Lott, Kolja Müller, Prof. Dr. Po Wen Cheng Stuttgart Wind Energy (SWE), University of Stuttgart Rave International Conference 2015, Bremerhaven Evaluation of the extreme and fatigue load measurements at alpha ventus
  2. 2. Gefördert auf Grund eines Beschlusses des Deutschen Bundestages Projektträger Koordination Project Partners Work Packages B. Load-reducing control and load monitoring C. Design conditions for future wind turbines OWEA LOADS A. Load analysis and probabilistic load description
  3. 3. 3 Presentation Content Extrapolation 1. What are the procedures for extrapolation of ultimate loads from measurements? Fatigue in Wake 2. What is the deviation measured in the fatigue loads of two turbines in a wind park? IEC Simulations 3. What are the effects of the stochastic environmental conditions which are not considered in the design guidelines?
  4. 4. Part 1 Extrapolation 1. What are the procedures for extrapolation of ultimate loads from measurements? Fatigue in Wake 2. What is the deviation measured in the fatigue loads of two turbines in a wind park? IEC Simulations 3. What are the effects of the stochastic environmental conditions which are not considered in the design guidelines? 4
  5. 5. General Idea of Extreme Load Extrapolation No detailed information about the extrapolation procedure is given → room for interpretation Methods were developed for simulation data → unique opportunity to apply the methods to offshore measurement data Extract from IEC 61400-1 ed.3: Wind Turbine - Part 1: Design requirements time present future statistical methods 5
  6. 6. Load Extrapolation Procedure load data extreme load samples • global maximum method • block maximum method • peak over threshold method short-term and long-term distribution distribution function, e.g. • Gumbel • Weibull • GEV • Lognormal • Gamma … fitting method, e.g. • method of moments • maximum likelihood • least squares … extreme load estimation for a specific return period 6
  7. 7. Database for Extrapolation [Figure1:http://www.alpha-ventus.de Figure2:http://www.trianel-borkum.de/typo3temp/pics/ed103a7723.gif] Restrictions: • Status signal: Production, Power > 200kW • Freestream 3 years of measurement data 5MW wind turbine AD 5-116 7
  8. 8. Exemplary Short-Term Extrapolation The estimated extreme load essentially depends on the choice of the distribution function. 3.8 ∙ 10−7 8
  9. 9. Conclusion and Outlook Conclusion: • Load extrapolation with measurement data results in plausible extreme loads. • Lots of processing of the data is necessary. Outlook: • Further investigation of different extrapolation methods. • Comparison to simulation data. Which distribution function fits the evaluated measurement data best? Goodness of fit tests for all wind bins → Lognormal distribution 3.8 ∙ 10−7 9
  10. 10. Part 2 Extrapolation 1. What are the procedures for extrapolation of ultimate loads from measurements? Fatigue in Wake 2. What is the deviation measured in the fatigue loads of two turbines in a wind park? IEC Simulations 3. What are the effects of the stochastic environmental conditions which are not considered in the design guidelines? 10
  11. 11. Two cases can be analysed 11 Wake Wind Case A AV8 in wake of AV7 Case B AV7 in freestream Data sorting • 13 Months – Data from 01-Oct-2010 to 31-Oct-2011 • 10 min time series • Power production • No curtailment Edge and flap strain gauge sensors Adwen 5MW AD 5-116 [Figure1:Adaptationfromwikipedia.com/Lencer Figure2:http://www.trianel-borkum.de/typo3temp/pics/ed103a7723.gif]
  12. 12. 0.65 0.7 0.75 0.8 0.85 0.9 0.95 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 4 6 8 10 12 14 16 18 0 0.2 0.4 0.6 0.8 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Fino1 WdSpd @ 90m 4 6 8 10 12 14 16 18 Case A: AV8 in Wake Damage equivalent loads (DEL) on the blades 12 DEL Edgewise DEL Flapwise Turbine AV7 in Freestream Normalized DEL TurbineAV8inWake NormalizedDEL
  13. 13. Comparing the damage on the blades based on linear damage accumulation and the Palmgren-Miner Rule 13
  14. 14. 0 5 10 15 20 25 0 10 20 30 40 PercentageOf TotalDamage (Reference:AV7) Turbine 7 Turbine 8 0 5 10 15 20 25 0 0.1 0.2 0.3 0.4 0.5 Percentage/ #Measurements Turbine 7 Turbine 8 0 5 10 15 20 25 0 200 400 600 800 Numberof measurements Fino 1 Wind Speed @90m (m/s) Case B: Freestream vs Wake Comparing Damage of Flap Measurements Turbine AV7 in freestream Turbine AV8 in wake Rated wind speed = 12.4m/s 14
  15. 15. 0 5 10 15 20 25 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 NormalizedDEL Fino 1 wind speed @ 90m (m/s) 0 5 10 15 20 25 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 NormalizedDEL Fino 1 wind speed @ 90m (m/s) 15 Freestream Wake Case B: Freestream vs Wake Outliers for flap sensors Larger scattering Conclusion: • A better understanding of outliers is needed to properly characterize damage and fatigue of measurement data
  16. 16. Part 3 Extrapolation 1. What are the procedures for extrapolation of ultimate loads from measurements? Fatigue in Wake 2. What is the deviation measured in the fatigue loads of two turbines in a wind park? IEC Simulations 3. What are the effects of the stochastic environmental conditions which are not considered in the design guidelines? 16
  17. 17. Validation of IEC 61400-3: DLC 1.2 (fatigue + production) 𝑀 𝑇𝐵,𝐹𝐴 [Figure1:http://www.alpha-ventus.de, Figure2,3:KoljaMueller,SWE] 1. What is the scatter range of IEC simulations? 2. Can load scatter be captured with simulation model? 𝑣 𝑟𝑎𝑡𝑒𝑑 = 13 𝑚/𝑠 filtered measurements: Apr 2011-Jan 2012 17
  18. 18. Scatter range of loads from IEC simulations scatter included in IEC assumptions low in comparison to measurements damage scatter around rated wind critical Repeat 10,000 times Weibull dist. Damage Over lifetime (20 yrs) 100 simulations Per wind bin Take DEL of 6 simulations per bin 18 SWE Computer Model
  19. 19. 19 Capture load scatter through consideration of scatter of environmental conditions Consider scatter of • Wind speed • Turbulence intensity • Wind shear • Wave height • Wave period Based on 5 year Fino1 data [Figure:KoljaMueller,MarioReiber,SWE] Conclusion:  Stochastics of measured loads can be simulated when considering scatter of environmental conditions  Turbulence intensity major contributor to scatter of DEL (MyTB) Design of Experiment : 3 step, Full Factorial = 4374 simulations Box Behnken = 738 simulations 19
  20. 20. Summary • Extrapolation of measurements show how the extrapolated load depends heavily on the distribution function used • Characteristic behaviour of fatigue on blades has been shown. While a better understanding of outliers is necessary to understand measurement of loads. • Scattering of load measurements can be captured through consideration the stochastic environmental condition in the simulations 20
  21. 21. Thank you for your attention Gefördert auf Grund eines Beschlusses des Deutschen Bundestages Projektträger Koordination faerron@ifb.uni-stuttgart.de
  22. 22. Supplemental slides 22 http://www.ecn.nl/docs/library/report/19 95/c95074.pdf The damage caused by a load spectrum of n cycles with ranges Sr,i Sr = is the range of a load cycle -1/m = is the slope of the S-N line on log-log scale
  23. 23. Case B: Freestream vs Wake Comparative Damage Edge Sensors 23 AV7 in freestream AV8 in wake Rated wind speed = 12.4m/s 2 4 6 8 10 12 14 16 18 0 5 10 15 20 25 PercentageOfTotalDamage (Reference:AV7) Turbine 7 edge Turbine 8 edge 2 4 6 8 10 12 14 16 18 0 0.01 0.02 0.03 Percentage/ #Measurements Turbine 7 edge Turbine 8 edge 2 4 6 8 10 12 14 16 18 0 200 400 600 800 Numberofmeasurements Fino1 Wind Speed 90m (m/s)

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