Abstract
FAST.Farm is a new midfidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on some of the principles of the Dynamic Wake Meandering model—including passive tracer modeling of wake meandering—but addresses many of the limitations of previous Dynamic Wake Meandering (DWM) implementations. Previous FAST.Farm verification studies show the similarities and differences between FAST.Farm and large-eddy simulations for rigid and flexible turbines. In this validation study, FAST.Farm turbine responses are compared to multiturbine measurements from a subset of a full-scale wind farm. FAST.Farm predictions of turbine generator power, rotor speed, and blade pitch for five-turbine simulations are compared to supervisory control and data acquisition results. Results reveal that FAST.Farm generator power mean and standard deviation results reasonably match measured data for upstream and downstream turbines, as well as the mean rotor speed and blade pitch above rated wind speeds. However, FAST.Farm generally underpredicts the mean rotor speed and overpredicts the mean blade pitch below rated operation. These errors are likely related to inaccuracies in the generic controller simulated. Despite controller differences, FAST.Farm predicts the same overall relative rotor power trends for all waked turbines at all wind speeds.
Highlights
In the context of wind farm design and optimization, it is crucial to be able to perform thousands of wind-farm-scale simulations expediently
FAST.Farm generally underpredicts the mean rotor speed and overpredicts the mean blade pitch below rated, which suggests that the generic turbine controller used in the OpenFAST model is not entirely representative of the controller implemented on the real GE 1.5-MW turbines
It was shown that FAST.Farm tends to predict lower relative generator power at below-rated wind speeds
Summary
In the context of wind farm design and optimization, it is crucial to be able to perform thousands of wind-farm-scale simulations expediently. FAST.Farm models the wind turbine dynamics and wake physics of wind farms for the purpose of accurately and efficiently predicting wind turbine power production and structural loading. Results were compared for laterally aligned three-turbine configurations with different inflow and control conditions using turbulent ambient wind data generated by a LES precursor and synthetic inflow [6, 9].
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