Abstract
Many bottom-mounted offshore wind farms are currently planned for the coastal areas of Japan, in which wind speeds of 6.0–10.0 m/s are extremely common. The impact of such wind speeds is very relevant for the realization of bottom-mounted offshore wind farms. In evaluating the feasibility of these wind farms, therefore, strict evaluation at wind speeds of 6.0–10.0 m/s is important. In the present study, the airflow characteristics of 2 MW-class downwind wind turbine wake flows were first investigated using a vertically profiling remote sensing wind measurement device (lidar). The wind turbines used in this study are installed at the point where the sea is just in front of the wind turbines. A ground-based continuous-wave (CW) conically scanning wind lidar system (“ZephIR ZX300”) was used. Focusing on the wind turbine near-wakes, the detailed behaviors were considered. We found that the influence of the wind turbine wake, that is, the wake loss (wind velocity deficit), is extremely large in the wind speed range of 6.0–10.0 m/s, and that the wake loss was almost constant at such wind speeds (6.0–10.0 m/s). It was additionally shown that these results correspond to the distribution of the thrust coefficient of the wind turbine. We proposed a computational fluid dynamics (CFD) porous disk (PD) wake model as an intermediate method between engineering wake models and CFD wake models. Based on the above observations, the wind speed range for reproducing the behavior of the wind turbine wakes with the CFD PD wake model we developed was set to 6.0–10.0 m/s. Targeting the vertical wind speed distribution in the near-wake region acquired in the “ZephIR ZX300”, we tuned the parameters of the CFD PD wake model (CRC = 2.5). We found that in practice, when evaluating the mean wind velocity deficit due to wind turbine wakes, applying the CFD PD wake model in the wind turbine swept area was very effective. That is, the CFD PD wake model can reproduce the mean average wind speed distribution in the wind turbine swept area.
Highlights
In a large-scale offshore wind farm, two major problems have been highlighted regarding the wind turbines located on the downstream side due to the wind turbine wakes located on the upstream side: (i) a decrease in the amount of power generated by the wind turbine located on the downstream side and (ii) the occurrence of failures inside the wind turbine nacelle and wind turbine blades
The purple symbol is the observation result obtained by the Doppler lidar at a wind speed of 8 m/s, which was the target of the numerical simulations using the computational fluid dynamics (CFD) porous disk (PD) wake model
The validity of the CFD PD wake model was verified by the wake of a 2 MW-class downwind turbine
Summary
Most common engineering wake model/analytical wake havior wind turbine wakesThe [4,5,6,7,8,9]. The most common engineering wake model/analytimodel for wind farms is the so-called. Park cal wake model for wind farms is the so-called Park wake model by Jensen [8] and Katic wake model implements a simple formula for the size of the wake deficit and its expansion [9]. The Park and its expansion with aparameter single adjustable parameter wake model is still widely used for evaluating business feasibility in the wind industry. Engineering wake models aretoextremely difficult the mutual interference wind turbine wakes. CW conically scanning wind lidar system is just in front of the wind turbines.
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