Yu Ting Wu

Assessment of wind characteristics and wind turbine characteristics in Taiwan

Wind characteristics and wind turbine characteristics in Taiwan have been thoughtfully analyzed based on a long-term measured data source (1961–1999) of hourly mean wind speed at 25 meteorological stations across Taiwan. A two-stage procedure for estimating wind resource is proposed. The yearly wind speed distribution and wind power density for the entire Taiwan is firstly evaluated to provide annually spatial mean information of wind energy potential. A mathematical formulation using a two-parameter Weibull wind speed distribution is further established to estimate the wind energy generated by an ideal turbine and the monthly actual wind energy generated by a wind turbine operated at cubic relation of power between cut-in and rated wind speed and constant power between rated and cut-out wind speed. Three types of wind turbine characteristics (the availability factor, the capacity factor and the wind turbine efficiency) are emphasized. The monthly wind characteristics and monthly wind turbine characteristics for four meteorological stations with high winds are investigated and compared with each other as well. The results show the general availability of wind energy potential across Taiwan.

Simulation of Turbulent Flow Inside and Above Wind Farms: Model Validation and Layout Effects

A recently-developed large-eddy simulation framework is validated and used to investigate turbulent flow within and above wind farms under neutral conditions. Two different layouts are considered, consisting of thirty wind turbines occupying the same total area and arranged in aligned and staggered configurations, respectively. The subgrid-scale (SGS) turbulent stress is parametrized using a tuning-free Lagrangian scale-dependent dynamic SGS model. The turbine-induced forces are modelled using two types of actuator-disk models: (a) the ‘standard’ actuator-disk model (ADM-NR), which calculates only the thrust force based on one-dimensional momentum theory and distributes it uniformly over the rotor area; and (b) the actuator-disk model with rotation (ADM-R), which uses blade-element momentum theory to calculate the lift and drag forces (that produce both thrust and rotation), and distributes them over the rotor disk based on the local blade and flow characteristics. Validation is performed by comparing simulation results with turbulence measurements collected with hot-wire anemometry inside and above an aligned model wind farm placed in a boundary-layer wind tunnel. In general, the ADM-R model yields improved predictions compared with the ADM-NR in the wakes of all the wind turbines, where including turbine-induced flow rotation and accounting for the non-uniformity of the turbine-induced forces in the ADM-R appear to be important. Another advantage of the ADM-R model is that, unlike the ADM-NR, it does not require a priori specification of the thrust coefficient (which varies within a wind farm). Finally, comparison of simulations of flow through both aligned and staggered wind farms shows important effects of farm layout on the flow structure and wind-turbine performance. For the limited-size wind farms considered in this study, the lateral interaction between cumulated wakes is stronger in the staggered case, which results in a farm wake that is more homogeneous in the spanwise direction, thus resembling more an internal boundary layer. Inside the staggered farm, the relatively longer separation between consecutive downwind turbines allows the wakes to recover more, exposing the turbines to higher local wind speeds (leading to higher turbine efficiency) and lower turbulence intensity levels (leading to lower fatigue loads), compared with the aligned farm. Above the wind farms, the area-averaged velocity profile is found to be logarithmic, with an effective wind-farm aerodynamic roughness that is larger for the staggered case.

Field Measurements of Wind Turbine Wakes with Lidars

AbstractField measurements of the wake flow produced from a 2-MW Enercon E-70 wind turbine were performed using three scanning Doppler wind lidars. A GPS-based technique was used to determine the position of the wind turbine and the wind lidar locations, as well as the direction of the laser beams. The lidars used in this study are characterized by a high spatial resolution of 18 m, which allows the detailed characterization of the wind turbine wake. Two-dimensional measurements of wind speed were carried out by scanning a single lidar over the vertical symmetry plane of the wake. The mean axial velocity field was then retrieved by averaging 2D scans performed consecutively. To investigate wake turbulence, single lidar measurements were performed by staring the laser beam at fixed directions and using the maximum sampling frequency. From these tests, peaks in the velocity variance are detected within the wake in correspondence of the turbine top tip height; this enhanced turbulence could represent a sourc...

Quantitative prediction of traffic pollutant transmission into buildings.

Abstract An integrated air quality model that combines a CFD model and multi-room pollutant transport model has been developed to study the effect of traffic pollution on indoor air quality of a multi-room building located in close proximity to busy roads. The CFD model conducts the large eddy simulation of the three-dimensional turbulent flows and pollutant transport processes in outdoor, whereas the multi-room pollutant transport model performs zonal airflow and pollutant transport in indoor. The integrated model is verified with available field measurement of traffic-induced CO concentrations. Twelve scenarios of numerical experiments for various configurations of window openness are carried out to study the effects of the air change rate and the outdoor pollutant dispersion on indoor air quality. It is concluded that the windward side opening is a significant factor contributing to indoor air quality. Using air inlets on the sideward and leeward envelopes simultaneously can effectively lower the daily mean and peak indoor levels of traffic pollutants and maintain a desirable air change rate.

Transport Mechanisms of Coarse, Fine, and Very Fine Particulate Matter in Urban Street Canopies with Different Building Layouts

A particulate matter (PM) transport model is developed to investigate coarse PM (PM10), fine PM (PM2.5), and very fine PM (PM1) transport mechanisms in urban street canopies under low-wind conditions. Two common building layouts (i.e., the open and staggered street canopies) are considered. Large eddy simulations with the subgrid-scale stress model and the wall function are used to simulate urban streetcanopy flows. The Lagrangian particle tracking approach, considering the effects of the drag force, gravitational force, Brownian motion, and Saffman lift force on particles is adopted to study PM transport behaviors in urban street canopies. The box counting method is used to calculate the canopy-averaged PM10/PM2.5/PM1 mass concentrations and transport mechanisms at each tracking time. The simulated results show that the removal efficiencies of PM10 ,P M2.5, and PM1 in the open street canopies are all better than those in the staggered street canopies. As a result, the open street canopies having higher PM removal ability lead to a swifter shift of the particle size distributions towards smaller size and less deviation than the staggered street canopies. The major particle removal mechanism for the open street canopies is particle escape, whereas wall deposition plays the most important role for the staggered street canopies. In comparison with the effectiveness of PM10/PM2.5/PM1 removal for both building layouts, PM10 particles are easier to overcome the root mean square vertical turbulent velocity and need less time to deposit. Fine particles would follow airflow paths and need longer time to deposit. As a result, PM2.5 and PM1 are more difficult to be removed than PM10.