dc.description.abstract |
Wind energy is a clean and renewable resource. Taiwan gives impetus to it nowadays. Wind energy is seldom discussed about the relationship between wind field and the power generation performance from the perspective of meteorology. According to the standard of assessing the power generation performance from IEC(2005), Lidar is often used to measure the wind condition. Because of the limitation of the site observation, the model is applied in this study to understand the interaction between the wind turbines and the atmosphere boundary layer.
This study focuses on the eight wind turbines at Taoyuan Datan. The wind speed is measured by Doppler Lidar. There are four fronts passing through from 2015/12/15 to 2015/12/30. The postfrontal cold northeasterlies lead to the maximum wind speed happened. The type of target wind turbine is Vestas V80 with height of 78 meters and rotor diameter of 80 meters. Field measurements are performed using Doppler wind Lidar which lies 160 meters to the northwest of the target wind turbine to verify the model results. On the other hand, Large-Eddy Simulation(LES), MYNN planet boundary layer and Wind Farm Parameterization (WFP), which are based on the WRF model, are applied to discuss the interaction between the wake flow generated from wind turbines and the atmosphere boundary layer. Model design with six nesting domain are used for the multiscale atmospheric simulations. In addition, the initial and boundary conditions of the fifth and the sixth nested domain are made by one-way nested down, and WFP inserted eight wind turbines only is used in domain six.
The idea of the WFP is about energy transition. The kinetic energy loss caused by the turbine drag force is converted into electric power and turbulence kinetic energy (TKE). The difference between WF (with WFP) and Ctrl (without WFP) are apparent behind the wind turbines that the wind speed decreases around 2m/s while TKE increase among the wake flow. The TKE budget of the wake flow is based on the three parts: vertical transport, shear production and dissipation rate. Comparing to Ctrl, the boundary layer height of WF is slightly higher due to the hybrid method in MYNN that consider both the virtual potential temperature and TKE. The simulated wind speed in different parameterizations have high correlation with the observation, but LES has a higher positive bias. Wind speed distribution in WF is closer to the observation, especially for wind speed over 10m/s. The power curve of the WF form WFP is similar to the manufacturer, but far from the observation in high wind speed region because of the attenuated performance and yaw misalignment. | en_US |