18 research outputs found
Optimale controle van energie-extractie in LES van windturbineparken
No full textIn large wind farms, the vertical interaction of the farm with the atmospheric boundary layer plays an important role, i.e. the total energy extraction is governed by the vertical transport of kinetic energy from higher regions in the boundary layer towards the turbine level. The current dissertation investigates the use of optimal control techniques in large-eddy simulations of wind farm boundary-layer interaction with the aim of increasing the total energy extraction in wind farms. The individual wind turbines are considered as flow actuators and their energy extraction is dynamically regulated in time so as to optimally influence the flow field and the vertical turbulent energy transport. The dissertation focuses on the development of a framework for a gradient-and adjoint-based scheme for wind-farm power optimization. To this end, a receding-horizon optimal control approach is employed in combination with the non-linear Polak-Ribière conjugate gradient method and the Brent line search algorithm. The gradient of the cost functional required by the conjugate-gradient method is determined using a continuous adjoint-based approach. The adjoint equations for the standard Navier-Stokes equations are extended to include the adjoints for the subgrid-scale model and wall-stress model, and the adjoint of the wind-turbine model.
In the first optimization studies, the optimal control of an infinite wind farm is investigated. The first control case focuses on the direct maximization of the energy extraction. It is found that the energy extraction increases by 16% compared to the uncontrolled reference. This is directly related to an increase in the vertical fluxes of energy towards the wind turbines, and vertical shear stresses increase considerably. A further analysis, decomposing the total stresses into dispersive and Reynolds stresses, shows that the dispersive stresses increase drastically, and that the Reynolds stresses decrease on average, but increase in the wake region, leading to better wake recovery. It is further observed that turbulent dissipation levels in the boundary layer increase, and overall, the outer layer of the boundary layer enters into a transient decelerating regime, while the inner layer and the turbine region attain a new statistically steady equilibrium within approximately one wind-farm through-flow time. Two additional optimal control cases study the penalization of turbulent dissipation. For the current wind-farm geometry, it is found that the ratio between the wind-farm energy extraction and turbulent boundary-layer dissipation remains roughly around 70%, but can be slightly increased by a few percent by penalizing the dissipation in the optimization objective. For a pressure-driven boundary layer in equilibrium, it is estimated that such a shift can lead to an increase in wind-farm energy extraction of 6%.
The second optimization study investigates the application of the optimal control to a finite-sized wind farm. A fringe region is employed to impose non-periodicity to the domain and the adjoint for the fringe forcing term is added to the original adjoint LES equations. It is found that the energy extraction increases by 7.3% compared to the uncontrolled case. The value is significantly lower when compared to the optimization of the infinite wind farm. One possible reason for this could be that the turbines in the front row - which contribute 16.5% of the whole farm power in the current case - are already operating close to the optimal condition, and hence, their performance cannot be improved much further by coordinated control. However, even the 7.3% gain achieved in this dissertation can be beneficial, especially for large wind farms.status: Publishe
〈原著論文〉A method for the design of a scaled wind turbine for wind tunnel experiments
No full textThe current work introduces a blade element momentum theory-based tool called BEMTurbine for designing and evaluating the performance of wind turbines. BEMTurbine is a python-based open source tool that can be used to optimize blade parameters (chord length and twist angle) for the aerodynamic performance. This tool is then used to design a model wind turbine with a rotor diameter 0.25 m and the optimum tip speed ratio of 5. Rotor of this turbine is manufactured using a 3D printer. The BEM analysis shows that the maximum power coefficient of the model turbine is 0.47, and is attained at the design tip speed ratio of 5.Ⅲ.論文集application/pdfdepartmental bulletin pape
沿岸近傍の洋上風力発電の流体解析用の高精度数値流体シミュレーションツールの開発
No full text研究種目：奨励研究助成金; 課題番号：SR17Research Paperapplication/pdfresearch repor
〈原著論文〉Measurement of flow fields in the wake of upwind and downwind wind turbines in wind tunnel experiments
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Can LiDARs Replace Meteorological Masts in Wind Energy?
No full textThis paper discusses whether profiling LiDARs can replace meteorological tower-based wind speed measurement for wind energy applications without severely compromising accuracy. To this end, the accuracy of LiDAR is evaluated in a moderately complex terrain by comparing long-term wind data measured by a profiling LiDAR against those obtained from tower-mounted cup and sonic anemometers. The LiDAR-measured wind speeds show good agreement with those measured using the sonic anemometer, with the slope of regression line being 1.0 and R 2 > 0.99 . Furthermore, the turbulence intensity obtained from the LiDAR has better agreement with that from the sonic anemometer compared to the cup anemometer which showed the lowest turbulence intensities among the three devices. A comparison of the turbulence intensity obtained from the 90th percentile of the standard deviation distribution shows that the LiDAR-measured turbulence intensities are mostly larger (by 2% or less) than those measured by the sonic anemometer. The gust factors obtained from both devices roughly converged to 1.9, showing that LiDAR is able to measure peak wind speed with acceptable accuracy. The accuracy of the wind speed and power distributions measured using the profiling LiDAR are then evaluated by comparing them against the corresponding distributions obtained from the sonic anemometer. Furthermore, the annual capacity factor—for the NREL 5-MW wind turbine—from the LiDAR-measured wind speed is 2% higher than that obtained from the sonic anemometer-measured wind speed. Numerical simulations are performed using OpenFAST in order to compute fatigue loads for the wind speed and turbulence distributions for the LiDAR and the sonic anemometer measurements. It is found that the 20 years lifetime Damage Equivalent Loads (DELs) computed for the LiDAR wind speed were higher than those for the sonic anemometer wind speeds, by 2%–6% for the blade root bending moments and by 11%–13% for the tower base bending moments. This study shows that even with some shortcomings, profiling LiDARs can measure wind speeds and turbulence intensities with acceptable accuracy. Therefore, they can be used to analyze wind resource and wind power potential of prospective sites, and to evaluate whether those sites are suitable for wind energy development
Measurement and Prediction of Wind Fields at an Offshore Site by Scanning Doppler LiDAR and WRF
No full textLiDAR-based wind speed measurements have seen a significant increase in interest in wind energy. However, reconstruction of wind speed vector from a LiDAR-measured radial wind speed is still a challenge. Furthermore, for extensive application of LiDAR technology, it can be used as a means to validate simulation and analytical models. To that end, this study employed scanning Doppler LiDAR for assessment of wind fields at an offshore site and compared Weather Research and Forecasting (WRF)-based mesoscale simulations and several wake models with the measurements. Firstly, the effect of carrier-to-noise-ratio (CNR) and data availability on the quality of scanning LiDAR measurements was evaluated. Analysis of vertical profiles show that the average wind speed is higher for wind blowing from the sea than that blowing from the land. Furthermore, profiles obtained from the WRF simulation also show a similar tendency in the LiDAR measurements in general, though it overestimates the wind speeds at higher altitudes. A method for reconstruction of wind fields from plan-position indicator (PPI) and range height indicator (RHI) scans of LiDAR-measured line of sight velocities was then proposed and first used to investigate the effect of coastal terrain. An internal boundary layer with strong shear could be observed to develop from the coastline. Finally, the flow field around wind turbine was measured using PPI scan and used to validate wake models
