Wind turbine wake evaluation using a vertical profiling Lidar and new CFD porous disk model

Abstract

Wind turbine wakes reduce the power generation and life of the downstream wind turbines. Accurately predicting the impact of wind turbine wakes is very important for evaluating the feasibility of large wind farms. We have recently proposed a computational fluid dynamics (CFD) porous disk (PD) wake model as an intermediate method between engineering wake models and CFD wake models in order to predict accurately the time-averaged wind speed deficits in the wind turbine wakes. In this study, to further evaluate the validity of the CFD PD wake model, we additionally measured the wind turbine wakes of 2 MW‐class downwind turbines installed on the coastal area using a vertical profiling lidar (ZephIR ZX300), and considered them including the data in the previous report to clarify its airflow characteristics in detail. Based on the measurement results by the lidar, we reproduced the wind turbine wake using the CFD PD wake model. The simulated vertical distribution of wind speed by the CFD PD wake model corresponded with the measurement result of the lidar.