节点文献

基于高斯分布的风电场尾流效应计算模型

Wind Farm Wake Effect Calculation Model Based on Gaussian Distribution

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 张晓东张梦雨白鹤

【Author】 ZHANG Xiaodong;ZHANG Mengyu;BAI He;Key Laboratory of Condition Monitoring and Control for Power Plant Equipment,North China Electric Power University;Beijing JinFeng HuiNeng Technology Co.,Ltd.;

【机构】 华北电力大学电站设备状态监测与控制教育部重点实验室北京金风慧能技术有限公司

【摘要】 风电机组群的尾流效应一直是大型风电场设计与运行优化中不可忽略的问题。随着风电技术的迅速发展,人们对风电场尾流模型的研究越来越重视。目前风电场设计软件中采用的尾流模型难以满足大型风电场尾流效应计算的工程需要。因此在Jensen模型基础上引入服从高斯分布的速度亏损模型,得到了一种新的适用于远场尾流的分析模型,并以此为理论基础建立了多台风电机组的三维尾流效应模型,开发了相应的计算软件。采用新的尾流模型和改进Jensen模型以及修正后的改进Jensen模型分别对丹麦Horns Rev风电场和大丰风电场的部分风电机组进行尾流模拟,将模拟计算的数据和实际运行数据进行对比,结果表明新模型的模拟效果优于其他两种模型。

【Abstract】 The wake effect of wind turbines has always been a significant topic of large-sized wind farm design and optimization. With the rapid development of wind power technology,researchers pay more attention to the wake model of wind farms. As present common used wake models used in wind farm design software are hard to satisfy the project needs of wake effect calculation of large-sized wind farm,velocity deficit model following Gaussian distribution has been introduced based on Jensen type models,which is a new analysis model suitable for far-field analytical wake. With the above model as theoretical basis,researchers established 3D discrete wake effect model of more than one wind turbines and developed new calculation software. The new wake model and the improved Jensen model as well as the improved Jensen model after a second modification are used to conduct wake simulations for some wind turbines from Denmark Horns Rev offshore wind farm and Da Feng onshore wind farm. The results show that simulation effect of the new model is better than that of the used improved Jensen model and its amended one by comparing simulated calculation result with actual operating data.

【基金】 国家国际科技合作计划资助项目(2010DFA64600)
  • 【文献出处】 华北电力大学学报(自然科学版) ,Journal of North China Electric Power University(Natural Science Edition) , 编辑部邮箱 ,2017年05期
  • 【分类号】TM614
  • 【被引频次】14
  • 【下载频次】301
节点文献中: