A physical approach of the wind power prediction based on the CFD pre-calculated flow fields is proposed in this paper. The flow fields are obtained based on a steady CFD model with the discrete inflow wind conditions...A physical approach of the wind power prediction based on the CFD pre-calculated flow fields is proposed in this paper. The flow fields are obtained based on a steady CFD model with the discrete inflow wind conditions as the boundary conditions, and a database is established containing the important parameters including the inflow wind conditions, the flow fields and the corresponding wind power for each wind turbine. The power is predicted via the database by taking the Numerical Weather Prediction （NWP） wind as the input data. In order to evaluate the approach, the short-term wind power prediction for an actual wind farm is conducted as an example during the period of the year 2010. Compared with the measured power, the predicted results enjoy a high accuracy with the annual Root Mean Square Error （RMSE） of 15.2% and the annual MAE of 10.80%. A good performance is shown in predicting the wind power＇s changing trend. This approach is independent of the historical data and can be widely used for all kinds of wind farms including the newly-built wind farms. At the same time, it does not take much computation time while it captures the local air flows more precisely by the CFD model. So it is especially practical for engineering projects.展开更多
针对旋埋刀辊在对长江中下游稻板田耕作时存在的高功耗问题,基于离散元方法构建稻板田旋耕功耗预测模型,以辅助旋埋刀辊功耗检测。连续3年对稻板田土壤含水率的进行监测,发现土壤含水率与其塑限接近,说明稻板田土壤塑性较差,结合土壤受...针对旋埋刀辊在对长江中下游稻板田耕作时存在的高功耗问题,基于离散元方法构建稻板田旋耕功耗预测模型,以辅助旋埋刀辊功耗检测。连续3年对稻板田土壤含水率的进行监测,发现土壤含水率与其塑限接近,说明稻板田土壤塑性较差,结合土壤受载后的形变及破坏特点,最终选定HertzMindlin with Bonding颗粒接触模型表征稻板田土壤的粘结和破坏情况。根据旋耕作业形式的特殊性和旋埋刀辊的结构特点,沿幅宽方向缩小旋埋刀辊的尺度,在旋耕测试平台的辅助下,完成标定参照试验。利用离散元软件建立旋耕作业模型,进行等步长爬坡试验,通过步阶次序建立接触参数与功耗指标之间的函数关系,代入标定参照试验功耗值,最终确定稻板田旋耕功耗预测模型的接触参数取值,完成模型的构建。为进一步验证该模型的适用性,在不同作业工况下对通用刀辊和旋埋刀辊进行误差对比试验,结果显示,预测误差范围为3.63%~9.48%,均值为6.65%,结合方差分析说明,稻板田旋耕功耗预测模型适用于不同旋耕刀辊及工况下的功耗预测。还原刀辊真实尺度的田间试验功耗预测误差范围为2.50%~12.81%,均值为7.28%,刀辊结构在缩放过程误差变化较小,说明模型能够准确反映旋埋刀辊在稻板田作业的功耗情况。展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No. 51206051)
文摘A physical approach of the wind power prediction based on the CFD pre-calculated flow fields is proposed in this paper. The flow fields are obtained based on a steady CFD model with the discrete inflow wind conditions as the boundary conditions, and a database is established containing the important parameters including the inflow wind conditions, the flow fields and the corresponding wind power for each wind turbine. The power is predicted via the database by taking the Numerical Weather Prediction （NWP） wind as the input data. In order to evaluate the approach, the short-term wind power prediction for an actual wind farm is conducted as an example during the period of the year 2010. Compared with the measured power, the predicted results enjoy a high accuracy with the annual Root Mean Square Error （RMSE） of 15.2% and the annual MAE of 10.80%. A good performance is shown in predicting the wind power＇s changing trend. This approach is independent of the historical data and can be widely used for all kinds of wind farms including the newly-built wind farms. At the same time, it does not take much computation time while it captures the local air flows more precisely by the CFD model. So it is especially practical for engineering projects.
文摘针对旋埋刀辊在对长江中下游稻板田耕作时存在的高功耗问题,基于离散元方法构建稻板田旋耕功耗预测模型,以辅助旋埋刀辊功耗检测。连续3年对稻板田土壤含水率的进行监测,发现土壤含水率与其塑限接近,说明稻板田土壤塑性较差,结合土壤受载后的形变及破坏特点,最终选定HertzMindlin with Bonding颗粒接触模型表征稻板田土壤的粘结和破坏情况。根据旋耕作业形式的特殊性和旋埋刀辊的结构特点,沿幅宽方向缩小旋埋刀辊的尺度,在旋耕测试平台的辅助下,完成标定参照试验。利用离散元软件建立旋耕作业模型,进行等步长爬坡试验,通过步阶次序建立接触参数与功耗指标之间的函数关系,代入标定参照试验功耗值,最终确定稻板田旋耕功耗预测模型的接触参数取值,完成模型的构建。为进一步验证该模型的适用性,在不同作业工况下对通用刀辊和旋埋刀辊进行误差对比试验,结果显示,预测误差范围为3.63%~9.48%,均值为6.65%,结合方差分析说明,稻板田旋耕功耗预测模型适用于不同旋耕刀辊及工况下的功耗预测。还原刀辊真实尺度的田间试验功耗预测误差范围为2.50%~12.81%,均值为7.28%,刀辊结构在缩放过程误差变化较小,说明模型能够准确反映旋埋刀辊在稻板田作业的功耗情况。
