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The performance of wind turbines is not only dependent on the wind turbine design itself, but is also dependent on the accurate assessment of wind resources at the installation site. In this paper, the numerical site calibration (NSC) method using three-dimensional Reynolds-averaged Navier–Stokes (RANS) simulation was proposed to accurately forecast the wind flow characteristics of wind turbine sites with complex terrains, namely Methil in Scotland, and Haenam in South Korea. From NSC at the Methil and Haenam sites, it was shown that the complicated and vortical flow fields around hills and valleys were captured using the three-dimensional RANS CFD simulation in Ansys CFX software based on a high-resolution scheme with a renormalization group (RNG)-based k-ε turbulence model. It was also shown that topographically induced wind profile and turbulence intensity over a local-scale complex terrain are remarkably dominated by flow separation after passing hills. It was concluded that the proposed NSC method using three-dimensional RANS simulation with a high-resolution scheme was an economically useful method for evaluating wind flow characteristics numerically to assess wind turbine sites with complex terrains and designing the wind farm layout.

Downwind turbines have favorable characteristics such as effective energy capture in up-flow wind conditions over complex terrains. They also have reduced risk of severe accidents in the event of disruptions to electrical networks during strong storms due to the free-yaw effect of downwind turbines. These favorable characteristics have been confirmed by wind-towing tank experiments and computational fluid dynamics (CFD) simulations. However, these advantages have not been fully demonstrated in field experiments on actual wind farms. In this study—although the final objective was to demonstrate the potential advantages of downwind turbines through field experiments—field measurements were performed using a vertical-profiling light detection and ranging (LiDAR) system on a wind farm with downwind turbines installed in complex terrains. To deduce the horizontal wind speed, vertical-profiling LiDARs assume that the flow of air is uniform in space and time. However, in complex terrains and/or in wind farms where terrain and/or wind turbines cause flow distortion or disturbances in time and space, this assumption is not valid, resulting in erroneous wind speed estimates. The magnitude of this error was evaluated by comparing LiDAR measurements with those obtained using a cup anemometer mounted on a meteorological mast and detailed analysis of line-of-sight wind speeds. A factor that expresses the nonuniformity of wind speed in the horizontal measurement plane of vertical-profiling LiDAR is proposed to estimate the errors in wind speed. The possibility of measuring and evaluating various wind characteristics such as flow inclination angles, turbulence intensities, wind shear and wind veer, which are important for wind turbine design and for wind farm operation is demonstrated. However, additional evidence of actual field measurements on wind farms in areas with complex terrains is required in order to obtain more universal and objective evaluations.