Influence of non-Gaussian wind characteristics on wind turbine extreme response

Kuangmin Gong, Xinzhong Chen

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


The wind turbulence inflows specified in current wind turbine design standards and turbine response simulation tools are usually modeled as stationary random Gaussian processes. Field measurement data, however, suggest that wind turbulence in complex terrain exhibits non-Gaussian characteristics. This study presents a comprehensive investigation on extreme response of operational and parked wind turbines to non-Gaussian wind field. The non-Gaussian wind fields with specified non-Gaussian statistics and power spectral characteristics are generated using translation process theory and spectral representation method. The wind turbine response time histories at each wind speed bin are simulated. The turbine response statistical moments influenced by the non-Gaussian wind inflow are examined. The extreme response distributions conditional on wind speeds are determined from the simulation data using global maxima method and random process model method. The overall extreme response distribution is then calculated by further integrating the distribution of mean wind speed, which is used to quantify the extreme responses with various mean recurrence intervals (MRIs). The results showed that the non-Gaussian characteristics of wind inflows can result in noticeably larger extremes of blade root edgewise and tower base fore-aft bending moments of operational turbine, and blade root flapwise bending moment of parked turbine. The responses with larger MRIs are more sensitive to the non-Gaussian characteristics of wind inflows. The responses of parked turbine are less sensitive to non-Gaussian, especially, the tower base side-to-side bending moment is almost not affected by non-Gaussian. New insights on the determination of extreme response distribution from random process method are also presented focusing on a better modeling of the response distribution tail.

Original languageEnglish
Pages (from-to)727-744
Number of pages18
JournalEngineering Structures
StatePublished - Feb 2014


  • Extreme value distribution
  • Global maxima method
  • Non-Gaussian wind turbulence
  • Random process model method
  • Translation process theory
  • Wind turbines


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