Extrapolation of Extreme Response for Wind Turbines based on Field Measurements Authors: Henrik Stensgaard Toft, Aalborg University, Denmark John Dalsgaard Sørensen, Aalborg University / Risø-DTU, Denmark

Contents Introduction Load Extrapolation based on Extreme Response in Storms Numerical Example Conclusion Future Work

Introduction The extreme load can occur in two situations: Standstill position – The wind turbine is parked and behave like a “normal” civil engineering structure (wind speed > 25m/s). Operational condition – The wind turbine is producing power and behave like a machine (wind speed 3-25m/s).

Introduction The extreme load during operation is dependent on: The mean wind speed. The turbulence intensity. The type and settings of the control system. Flap Bending Moment Pitch controlled wind turbine Tower Mudline Moment Pitch controlled wind turbine

Introduction IEC : Extreme load determined from 10min. simulations of the response during operation over the range of significant wind speeds. The method is based on the following assumptions: Local extremes in the response are independent. Individual 10min. time series are independent. In the present paper are these assumptions investigated.

Introduction In the present paper is a new method for estimation of the extreme load presented. By comparing the extreme load determine by this method and the method in IEC can the assumptions about independence be studied. The new method uses a long measured time series which rarely is available – Therefore is the new method only used for validation of the existing method.

Load Extrapolation based on Extreme Response in Storms The new method for estimating the extreme load is based on: Existing methods for estimating e.g. the extreme wave height. Assumption about independent storms.

Load Extrapolation based on Extreme Response in Storms A storm wind speed U storm should be defined so extreme loads occur for mean wind speeds above U storm.

Load Extrapolation based on Extreme Response in Storms U storm is defined from the nominal wind speed U nom (typically m/s) and the standard deviation for the turbulence  1. Independence of storms: Storms are combined if the mean wind speed between them not are below a percentile of U storm. Storms are separated a minimum number of hours.

Load Extrapolation based on Extreme Response in Storms 1.The measured time series is divided into independent storms. 2.For each storm is the extreme response extracted. 3.To the largest extreme responses is a distribution function fitted. 4.The characteristic load is calculated for the probability:

Numerical Example Stall controlled onshore wind turbine. Dataset for response measured over 62 days in winter and spring. (52 days of complete measurements) Dataset for mean wind speed measured over 4 years. Site: Less severe than class III in IEC Turbulence intensity I ref = 0.12.

Numerical Example Nominal wind speed U nom Storm wind speed U storm Storms per year  Length of storm T s 14m/s9.5m/s2028.0h 15m/s10.2m/s1657.4h 16m/s11.0m/s1356.7h Investigation of storm definition. Storms are combined if the mean wind speed between them not are below 80% of U storm. Storms are separated at least 2 hours. Higher nominal wind speed leads to less and shorter storms.

Numerical Example Load extrapolation according to IEC Extremes extracted by the Peak Over Threshold method. Characteristic loads calculated with/without statistical uncertainty (Hessian matrix). Normalized characteristic loads. ThresholdCharacteristic load without stat. unc.with stat. unc

Numerical Example DistributionCharacteristic load without stat. unc.with stat. unc. Weibull Gumbel Load extrapolation based on extreme response in storms. 25 largest extremes from independent storms are used. Measured time series are short – 52 days of complete measurements Choice of distribution function has a significant influence on the results.

Conclusion New method for calculation of the extreme response is proposed. Definition of a storm is proposed. Higher characteristic load using the new method which could indicate that the 10min. time series or local extremes are dependent. Based on a stall controlled wind turbine and a short measured time series.

Future Work Refinement of the storm definition based on: Longer measured time series. More severe sites. Estimation of the “correct” long-term distribution for the extreme response: Weibull Gumbel Etc. Comparison of the new method and IEC for a long measured time series.

Extrapolation of Extreme Response for Wind Turbines based on Field Measurements Authors: Henrik Stensgaard Toft, Aalborg University, Denmark John Dalsgaard Sørensen, Aalborg University / Risø-DTU, Denmark