The Power Curve Working Group's assessment of wind turbine power performance prediction methods

摘要: Abstract. Wind turbine power production deviates from the reference power curve in real-world atmospheric conditions. Correctly predicting turbine performance requires models to be validated for a wide range of wind turbines using inflow different locations. The Share-3 exercise is most recent intelligence-sharing exercise of Power Curve Working Group, which aims advance modeling performance. goal of is search methods that reduce error and uncertainty prediction when shear and turbulence digress from design Herein, we analyze data 55 power performance tests nine contributing organizations with statistical tests to quantify skills prediction-correction methods. We assess the accuracy precision four proposed trial against baseline method, uses conventional definition wind speed air density at hub height. reduce power-production errors compared baseline method high wind speeds, contribute heavily production; however, the trial fail significantly uncertainty most meteorological For meteorological conditions wind turbine produces less than its reference suggests, using deviation matrices leads more accurate prediction. We also determine half submissions, set has a large influence on effectiveness method. Overall, this work affirms value data-sharing efforts advancing modeling and establishes groundwork future collaborations.