Uncertainty quantification in wind farm flow models

Research output: Book/ReportPh.D. thesisResearch

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This thesis formulates a framework to perform uncertainty quantification
within wind energy. This framework has been applied to some of the most common models used to estimate the annual energy production in the planning stages of a wind energy project. Efficient methods to propagate input uncertainties through a model chain are presented and applied to several wind energy related problems such as: annual energy production estimation, wind turbine power curve estimation, wake model calibration and validation, and
estimation of lifetime equivalent fatigue loads on a wind turbine. Statistical methods to describe the joint distribution of multiple variables are applied to the description of the wind resources at a given location. A new method to predict the performance of an aeroelastic wind turbine model, and its corresponding uncertainty, is presented. This approach helps understand the uncertainty in
the lifetime performance of a wind turbine under realistic inflow conditions. Operational measurements of several large offshore wind farms are used to perform model calibration and validation of several stationary wake models. These results provide a guideline to identify the regions in which a model fails to make accurate predictions, and therefore help guide research and development to focus on areas with the biggest uncertainty to lower costs of energy
Original languageEnglish
PublisherDTU Wind Energy
Number of pages207
Publication statusPublished - 2017

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