In this paper, a methodology is developed to analyze how ambient and wake turbulence affects the power generation of a single wind turbine within an array of turbines. Using monitoring data from a wind power plant, we selected two sets of wind and power data for turbines on the edge of the wind plant that resemble (i) an out-of-wake scenario (i.e., when the turbine directly faces incoming winds) and (ii) an in-wake scenario (i.e., when the turbine is under the wake of other turbines). For each set of data, two surrogate models were then developed to represent the turbine power generation (i) as a function of the wind speed; and (ii) as a function of the wind speed and turbulence intensity. Support vector regression was adopted for the development of the surrogate models. Three types of uncertainties in the turbine power generation were also investigated: (i) the uncertainty in power generation with respect to the published/reported power curve, (ii) the uncertainty in power generation with respect to the estimated power response that accounts for only mean wind speed; and (iii) the uncertainty in power generation with respect to the estimated power response that accounts for both mean wind speed and
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