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作 者:汪颖[1] 王欢 王昕[2] Wang Ying;Wang Huan;Wang Xin(School of Electrical Engineering and Information,Sichuan University,Chengdu 610065,China;CEIEC Shenzhen Electric Technology Inc,Shenzhen 518000,Guangdong,China)
机构地区:[1]四川大学电气信息学院,成都610065 [2]深圳市中电电力技术股份有限公司,广东深圳518000
出 处:《电测与仪表》2020年第15期1-7,共7页Electrical Measurement & Instrumentation
基 金:国家自然科学基金资助项目(51807126)。
摘 要:为准确识别电网中各类暂降源,提出了一种基于改进灰色关联分析的电压暂降源识别方法。分析了其产生机理,并利用暂降分段法,分析电网中各类暂降源的波形特点;针对传统灰色关联分析模型的不足,利用熵权法进行改进;提取电压暂降波形的时域特征,形成六类暂降源对应的标准参考序列和待识别暂降源对应的比较序列,利用改进的灰色关联分析模型计算参考序列和比较序列的关联度,实现暂降源的准确识别。通过PSCAD/EMTDC仿真和实测数据对所提方法进行验证,并与其他方法对比,证明了所提方法能在样本较少的情况下准确识别各类暂降源,且能确定短路引起暂降的故障类型,具有较大的工程应用前景。In order to accurately identify all kinds of sag sources in power grid,a method based on improved grey correlation analysis is presented for identification of voltage sags source. Firstly,the generation mechanism of different voltage sags is analyzed,and the waveform characteristics of various sag sources in power grid are analyzed by using the sag segmentation method. Secondly,considering the shortcomings of the traditional grey correlation analysis model,the entropy weight method is used to improve it. Then,the time domain characteristics of voltage sag waveform is extracted to form the standard reference sequence of six types of sag sources and the comparison sequence corresponding to the sag sources to be identified. The improved grey correlation analysis model is used to calculate the correlation degree between the reference sequence and comparison sequence to achieve accurate identification of sag sources. Finally,the proposed method is validated by PSCAD/EMTDC simulation data and measured data. And compared with other existing methods,the proposed method can not only accurately identify all kinds of sag source with fewer samples,but can also determine the specific fault types while sags are caused by short circuit faults. It has great engineering application prospects.
关 键 词:电压暂降 暂降分段法 灰色关联分析 熵权法 特征提取 暂降源识别
分 类 号:TM933[电气工程—电力电子与电力传动]
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