Statistical Analysis of Radial Velocity and Spectrum Width for Wind Turbines Radar Echo

Yu Shi, Xiaoliang Wang, Weikun He
{"title":"Statistical Analysis of Radial Velocity and Spectrum Width for Wind Turbines Radar Echo","authors":"Yu Shi, Xiaoliang Wang, Weikun He","doi":"10.1109/ICCC56324.2022.10066021","DOIUrl":null,"url":null,"abstract":"The number of wind farms has increased rapidly in the past few years. Some studies have shown that wind farms interfere with weather radar and air traffic control surveillance radar. The radar echo signal of fast-rotating wind turbine blades has a wide Doppler spectrum, and the general radar clutter processing methods cannot remove wind turbine clutters with such characteristics, which interferes with the target detection performance of nearby radar equipment seriously. The study of statistical characteristics of the echo signal of wind turbines could provide basis for detection, recognition, elimination of wind turbine clutters. This paper provides statistical models of radial velocity and spectrum width for wind turbines based on Level II data of the WSR-88D weather radar. The orientation of blades' rotation plane has impact on statistical analysis result. In order to solve this problem, we employ the wind direction information to estimate the orientation of blades' rotation plane and we analysis the statistical characteristics in some particular orientation. The real data are utilized to obtain the empirical probability density function and then different probability density functions are used to fit the empirical probability density function. The K-S test and root mean square error are employed to compare the performance of different statistical models. Through the statistical analysis of four different types of wind turbine, the preferable statistical model for radial velocity and spectrum width are obtained.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCC56324.2022.10066021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The number of wind farms has increased rapidly in the past few years. Some studies have shown that wind farms interfere with weather radar and air traffic control surveillance radar. The radar echo signal of fast-rotating wind turbine blades has a wide Doppler spectrum, and the general radar clutter processing methods cannot remove wind turbine clutters with such characteristics, which interferes with the target detection performance of nearby radar equipment seriously. The study of statistical characteristics of the echo signal of wind turbines could provide basis for detection, recognition, elimination of wind turbine clutters. This paper provides statistical models of radial velocity and spectrum width for wind turbines based on Level II data of the WSR-88D weather radar. The orientation of blades' rotation plane has impact on statistical analysis result. In order to solve this problem, we employ the wind direction information to estimate the orientation of blades' rotation plane and we analysis the statistical characteristics in some particular orientation. The real data are utilized to obtain the empirical probability density function and then different probability density functions are used to fit the empirical probability density function. The K-S test and root mean square error are employed to compare the performance of different statistical models. Through the statistical analysis of four different types of wind turbine, the preferable statistical model for radial velocity and spectrum width are obtained.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
风力机雷达回波径向速度和频谱宽度的统计分析
在过去几年中,风力发电场的数量迅速增加。一些研究表明,风力发电场会干扰气象雷达和空中交通管制监视雷达。快速旋转风电叶片的雷达回波信号具有较宽的多普勒频谱,一般的雷达杂波处理方法无法去除具有这一特性的风电杂波,严重干扰了附近雷达设备的目标探测性能。研究风电机组回波信号的统计特性,可以为风电机组杂波的检测、识别和消除提供依据。本文基于WSR-88D气象雷达二级数据,建立了风力机径向速度和谱宽的统计模型。叶片旋转平面的方向对统计分析结果有影响。为了解决这一问题,我们利用风向信息来估计叶片旋转平面的方向,并分析了在特定方向上的统计特性。利用实际数据得到经验概率密度函数,然后用不同的概率密度函数拟合经验概率密度函数。采用K-S检验和均方根误差比较不同统计模型的性能。通过对四种不同类型风力机的统计分析,得到了较好的径向速度和谱宽统计模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Backward Edge Pointer Protection Technology Based on Dynamic Instrumentation Experimental Design of Router Debugging based Neighbor Cache States Change of IPv6 Nodes Sharing Big Data Storage for Air Traffic Management Study of Non-Orthogonal Multiple Access Technology for Satellite Communications A Joint Design of Polar Codes and Physical-layer Network Coding in Visible Light Communication System
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1