基于谱聚类的输电线覆冰过程微气象特征提取模型
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摘要
因输电线路覆冰造成的电网瘫痪是近年来常见的电网灾害之一,进而对电力系统安全运行的可控性以及电网灾害预警的可靠性提出了更高的要求。提出了基于谱聚类的输电线路覆冰过程特征提取模型,对覆冰过程进行了定性分析,该模型通过对影响覆冰过程的微气象因素进行特征提取(聚类),较为准确地对输电线覆冰严重程度进行了分离,并对微气象数据进行统计分析,将气象倾向率作为参考量,获得了严重覆冰、覆冰脱落等过程发生的气象条件,最后通过云南电网提供的相关数据验证了此模型的有效性,为电网部门输电线路覆冰灾害的预警提供气象参考条件。
Power grid paralysis caused by icing of transmission lines is one of the common power grid disasters in recent years,which puts forward higher requirements for the controllability of power system safe operation and the reliability of power grid disaster warning.A feature extraction model based on spectral clustering for icing process of transmission lines is proposed,and the icing process is qualitatively analyzed.By feature extraction(clustering)of the micro-meteorological factors that affect the icing process,the model can accurately separate the icing severity of transmission lines and integrate the micro-meteorological data.According to the analysis,the meteorological tendency rate is taken as the reference quantity,meteorological conditions such as severe icing,ice shedding and so on were obtained.The validity of the model is verified by the relevant data provided by Yunnan Power Grid,which provides meteorological reference conditions for the transmission line icing disaster warning of power grid departments.
Power grid paralysis caused by icing of transmission lines is one of the common power grid disasters in recent years,which puts forward higher requirements for the controllability of power system safe operation and the reliability of power grid disaster warning.A feature extraction model based on spectral clustering for icing process of transmission lines is proposed,and the icing process is qualitatively analyzed.By feature extraction(clustering)of the micro-meteorological factors that affect the icing process,the model can accurately separate the icing severity of transmission lines and integrate the micro-meteorological data.According to the analysis,the meteorological tendency rate is taken as the reference quantity,meteorological conditions such as severe icing,ice shedding and so on were obtained.The validity of the model is verified by the relevant data provided by Yunnan Power Grid,which provides meteorological reference conditions for the transmission line icing disaster warning of power grid departments.
引文
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[19]王允,刘普幸,曹立国,等.基于湿润指数的1960-2011年中国西南地区地表干湿变化特征[J].自然资源学报,2014,29(5):830-838.
[2]李庆峰,范峥,吴穹,等.全国输电线路覆冰情况调研及事故分析[J].电网技术,2008,32(9):33-36.
[3]韩军科,杨靖波,杨风利,等.超/特高压同塔多回输电线路脱冰跳跃动力响应分析[J].电网技术,2012,30(9):61-67.
[4]钟运平,程小华,戴栋,等.基于ZigBee技术输电线路在线监测系统的研究[J].电测与仪表,2013,50(5):105-109.
[5]张松海,施心陵,李鹏,等.基于动态拉力与倾角的输电线路覆冰过程辨识与建模[J].电力系统保护与控制,2016,44(9):57-61.
[6]刘春城,刘佼.输电线路导线覆冰机理及雨凇覆冰模型[J].高电压技术,2011,37(1):241-248.
[7]Makkonen L.Modeling power line icing in freezing precipitation[J].Atmospheric Research,1998,46(1/2):131-142.
[8]廖玉芳,段丽洁.湖南电线覆冰厚度估算模型研究[J].大气科学学报,2010,33(4):29-30.
[9]温华洋,田红,唐为安,等.安徽省电线积冰标准冰厚的气象估算模型[J].应用气象学报,2011,22(6):747-752.
[10]杨梅,苏沛,冯建辉.基于分形理论的输电线路覆冰厚度测量[J].测控技术,2018,37(9):111-116.
[11]黄新波,王玉鑫,朱永灿.基于遗传算法与模糊逻辑融合的线路覆冰预测[J].高电压技术,2016,42(4):1228-1235.
[12]戴栋,黄筱婷,代州,等.基于支持向量机的输电线路覆冰回归模型[J].高压电技术,2013,39(11):2822-2828.
[13]Niu D X,Liang Y,Wang H C,et al.Icing forecasting of transmission lines with a modified back propagation neural network-support vector machine-extreme learning machine with kernel(BPNN-SVM-KELM)based on the VarianceCovariance weight determination method[J].Energies,2017,10:1196-1217.
[14]张红斌,贺仁睦,刘应梅.基于KOHONEN神经网络的电力系统负荷动性聚类与综合[J].中国电机工程学报,2003,23(5):1-5.
[15]Seyoung P,Zhao H Y.Spectral clustering based on learning similarity matrix[J].Bioinformatics,2018,34(12):2069-2076.
[16]王焱,王卉蕾.改进的谱聚类算法在图像分割中的应用[J].测控技术,2018,37(4):11-15.
[17]杜凯颖,张为公,王东.基于改进模糊核聚类的室内定位方法研究[J].测控技术,2018,37(2):42-46.
[18]Hartigan J A,Wong M A.A K-means clustering algorithm[J].Applied Statistics,1979,28(1):100-108.
[19]王允,刘普幸,曹立国,等.基于湿润指数的1960-2011年中国西南地区地表干湿变化特征[J].自然资源学报,2014,29(5):830-838.