摘要
[目的]风力机组的尾流效应是风电场能量损失的重要因素,研究机组尾流有利于优化机组排布,提升风电场的经济性。[方法]分别对8种常见尾流模型的尾流风速衰减、湍流强度预测情况进行对比研究。为确保评估的合理性,基于风场测量数据及风洞实验数据进行定量分析,对比数据范围限定于风机下游距离3倍到10倍风轮直径。[结果]分析结果表明:对于尾流风速预估,二维模型较一维模型与实际尾流风速分布结构更契合,其中Jensen-Guass有着更好的尾流宽度预测,而2D-k-Jensen尾流中心风速预测精度更高且多工况适应性更强,最大平均偏差及偏差标准差分别为8.7%、5.5%,均适用于机组尾流风速预估。一维模型中的Jensen模型尾流中心风速预估能力虽最好,部分工况平均偏差低于10%,但Park模型在尾流风速水平分布预测上表现更佳,案例2中预测性能与二维模型相当,各工况平均偏差均低于10%,较前者更适合尾流速度预测。对于湍流强度的预测,Ishihara模型在湍流结构的预测展现出明显优势,平均偏差均低于10%,但尾流中心处湍流强度预测结果较差,不利于下游机组位置处湍流强度的预测,其余模型中Frandsen、Jensen-Guass在低环境湍流强度工况的预测相对较好,但高环境湍流强度下两者存在相反趋势,Frandsen模型预测精度更高,适合机组湍流强度预估,而Jensen-Guass的预估结果远大于实验值,预测结果较不稳定。高上游风速下各模型尾流风速预估精度均有较大的提升,环境湍流强度的提高对模型尾流风速和湍流强度预估精度有一定的促进作用,Jensen-Guass模型除外。[结论]Jensen-Guass和2D-k-Jensen模型尾流风速预测值与实测数据吻合较好,Frandsen模型湍流强度预测性能更佳,可作为海上风场机位排布优化及尾流控制分析的参考尾流模型。
[Introduction]The wake effect of wind turbines is an important cause of energy loss in wind farms.The wake study of wind turbines is beneficial to optimization of the turbine arrangement and improvement of the economic efficiency of wind farms.[Method]This paper presented a comparative study of the wake wind speed decay and turbulence intensity prediction of eight common wake models,respectively.To ensure the rationality of the evaluation,the quantitative analysis was carried out based on wind farm measurements and wind tunnel experimental data,and the range of comparison data was limited to 3 to 10 times the diameter downstream the turbine.[Result]The analysis results show that,for the prediction of wake wind speeds,the two-dimensional model fits the actual wake wind speed distribution structure better than the one-dimensional model,in which Jensen-Guass has better wake width prediction ability,while the 2D-k-Jensen wake center wind speed prediction has higher accuracy and adaptability to multiple conditions,with the maximum mean deviation and standard deviation of 8.7%and 5.5%,respectively,which are both applicable to the prediction of turbine wake wind speed.Jensen model has the best prediction ability of wake center wind speed in one-dimensional model,and the mean deviation of some conditions is less than 10%.While Park model is better in predicting the horizontal distribution of wake wind speed.In Case 2,the prediction performance is comparable to that of two-dimensional model,and the mean deviation of each condition is less than 10%,so it is more suitable for wake speed prediction than the former.For the prediction of turbulence intensity,the Ishihara model shows a clear advantage in the prediction of turbulent structure,with mean deviations below 10%,but the prediction of turbulence intensity at the center of the wake is poor,which is not conducive to the prediction of the turbulence intensity at locations downstream the turbine.Among the remaining models,Frandsen and Jensen-Guass models are relatively good at prediction of low ambient turbulence intensities.However,there is an opposite trend between the two for high ambient turbulence intensities:the Frandsen model has higher prediction accuracy and is suitable for turbine turbulence intensity prediction,whereas the prediction result of Jensen-Guass is much larger than the experimental value,and is unstable.The prediction accuracy of wake wind speed for all models is greatly improved at high upstream wind speeds,and the increase in ambient turbulence intensity contributes to the prediction accuracy of the wake wind speed and turbulence intensity for all models,except for the Jensen-Guass model.[Conclusion]The predicted values of wake wind speed for the Jensen-Guass model and the 2D-k-Jensen model coincides better with the measured data,while the prediction performance of the Frandsen model turbulence intensity is better,so they can be used as the reference wake models for the optimization of wind turbine placement and wake control analysis for offshore wind farms.
作者
李胜
葛文澎
吴嘉诚
曲春明
孙睿
LI Sheng;GE Wenpeng;WU Jiacheng;QU Chunming;SUN Rui(MingYang Smart Energy Group Corporation,Zhongshan 528437,Guangdong,China)
出处
《南方能源建设》
2024年第1期42-53,共12页
Southern Energy Construction
基金
国家重点研发计划重点专项“风力发电复杂风资源特性研究及其应用与验证”(2018YFB1501100)。
关键词
风力机组
尾流模型
风速衰减
湍流强度
实测数据
对比研究
wind turbines
wake models
wind speed attenuation
turbulence intensity
measured data
comparison and research
作者简介
第一作者/通信作者:李胜,1997-,男,四川眉山人,工程师,中国海洋大学建筑与土木工程硕士,主要从事海上风电技术研究工作,e-mail:lisheng03@mywind.com.cn;葛文澎,1990-,男,计算流体力学工程师,硕士,从事风资源评估研究工作,e-mail:gewenpeng@mywind.com.cn;吴嘉诚,1991-,男,技术支持工程师,硕士,从事海上风电市场及前期设计研究工作,e-mail:wujiacheng@mywind.com.cn;曲春明,1995-,男,工程师,硕士,主要从事风电机组流体仿真相关工作,e-mail:quchunming@mywind.com.cn;孙睿,1995-,男,工程师,硕士,主要研究领域为风电机组设计,e-mail:wysunrui01@163.com。
