基於跡流模型之風機功率預測

A Wake Model for Wind Turbine Power Prediction

李可掬(Ke-Chu Lee)

指導教授 ： 趙修武

國立臺灣大學/工學院/工程科學及海洋工程學研究所/碩士(2018年)

https://doi.org/10.6342/NTU201803554

摘要

本文建立基於物體力項及紊流源項之風機制動盤跡流模型，以目標風機之幾何及運轉參數描述制動盤作用於流體之物體力項，並以紊流源項描述因葉片旋轉運動產生的紊流生成現象。本研究使用FORTRAN語法開發風機制動盤跡流模擬程式WIFA3D，利用SIMPLE演算法分離壓力與速度耦合關係，平行求解三維穩態連續方程式、動量方程式以及修正k-ε紊流模型。跡流模型常數c_k1及c_k2在風洞實驗案例中建議採用1.5及0.95；在離岸風場案例中建議採用及3.0及0.70，說明跡流模型常數對風機幾何及紊流尺度具有變異性。本文以風洞測量值驗證本研究的制動盤跡流模型，發現該模型能有效描述跡流軸向速度、剪應力及紊流強度分佈。本研究的風場模擬結果能合理預測風機發電量，發現風場中下游風機輸出功率漸趨穩定。此現象為紊流生成及紊流消散達成動態平衡的結果，前者造成跡流擴散並增強跡流與外圍氣流混合，後者為避免跡流產生持續擴散的現象。

關鍵字

制動盤模型 ； 紊流源 ； 功率預測 ； WIFA3D

並列摘要

This thesis describes a wake model which incorporates an actuator disk with a body force and turbulence source approach. The force source simulates the flow deceleration effect based on the wake flow of the wind turbine, whereas the turbulence source models the turbulence generation resulting from the rotational motion of the turbine rotor. The investigated three-dimensional flow field is described by the steady continuity and momentum equations together with a modified k-ε turbulence model, which are solved by an in-house, parallelized, RANS-based Fortran code, WIFA3D, which employs a SIMPLE algorithm to decouple pressure and velocity. The proposed turbulence model also includes the turbulence dissipation arising in the atmospheric condition. The model constants are calibrated with a wind tunnel experiment and a power measurement from Horns Rev offshore wind farm. The constant pair of the proposed model is c_k1=1.5 and c_k2=0.95 for small scale flow, as well as c_k1=3.0 and c_k2=0.70 for large scale flow, emphasizing the importance of a proper choice of model constants for different geometrical features and turbulence scales. The simulation result of the wind tunnel flow is validated against the spatial distribution of the streamwise velocity, the shear stress and the turbulence intensity, in addition to the output power. In the case of wind farm simulation, an almost stable output power is predicted for downstream wind turbines in a cascading arrangement, which gives a favorable agreement with the field measurement. The reason for this effect is a dynamic equilibrium between the turbulence strength, which enhances the wake expansion as well as the mixing process, and the turbulence dissipation, which prevents the wake from a complete velocity recovery.

並列關鍵字

Actuator Disk Model ； Turbulence Source ； Power Prediction ； WIFA3D

參考文獻

[1] Vidal-Amaro, J. J., Østergaard, P. A., & Sheinbaum-Pardo, C. (2015). Analysis of Large-scale Integration of Renewable Energy Sources in the Mexican Electricity System. Energy and Sustainability Vi. 449-461.

[2] Thor, S. E., & Weis-Taylor, P. (2002). Long-term Research and Development Needs for Wind Energy for the Time Frame 2000–2020. Wind Energy: An International Journal for Progress and Applications in Wind Power Conversion Technology, 5(1), 73-75.

[3] Banos, R., Manzano-Agugliaro, F., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J. (2011). Optimization Methods Applied to Renewable and Sustainable Energy: A Review. Renewable and Sustainable Energy Reviews, 15(4), 1753-1766.

[4] Barthelmie, R. J., & Pryor, S. C. (2014). Potential Contribution of Wind Energy to Climate Change Mitigation. Nature Climate Change 4, no. 8: 684.

[5] Manwell, J. F., Gowan, J. G., & Rogers, A. L. (2002). Wind Energy Explained.