基于层次分析法的停电试验与不停电检测技术等效性分析模型
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摘要
为了评价停电试验与不停电检测技术的等效性,提出了一种基于层次分析法的停电试验与不停电检测技术等效性分析模型。首先根据两种技术的状态量获取过程确定了准确度、有效性与故障检出能力组成的准则层,以及数据数值准确度等七个指标构成的指标层。采用层次分析法计算各指标权重系数,建立了双层次的等效性评价指标体系。根据各指标层中各指标性质,确定各个指标层指标的量化方法及归一化计算方法。针对不停电检测和停电试验的数据数量不相等、时序不匹配的特点,提出了数据三次样条插值拟合后再取值的数据预处理方法,最终建立等效性分析模型。实例分析表明该模型可以减少人为干预,综合状态量数据获取的主要阶段来评价不停电检测对停电试验的等效性。
In order to evaluate the equivalence of power outage test and power outage detection technology,a model of power off-line test and on-line detection technology equivalence analysis based on AHP( analytic hierarchy process) is proposed. Firstly,the standard layer composed of accuracy,validity and fault detection ability and the index layer composed of seven indexes such as data numerical accuracy are determined according to the state quantity acquisition process of the two technologies. The weight coefficient of each index is calculated by AHP,and a two-level equivalence evaluation index system is established. According to the properties of each indicator in each indicator layer,the quantitative method and the normalized calculation method of each indicator layer are determined. Aiming at the characteristics of unequal number of data and mismatch of time series of power outage test and power outage test,a data preprocessing method with three spline interpolation fitting is proposed,and an equivalence analysis model is finally established. The example shows that this model can reduce the human intervention,and the equivalence of on-line detection to power failure test can be evaluated by synthesizing the main stage of state variable data acquisition.
In order to evaluate the equivalence of power outage test and power outage detection technology,a model of power off-line test and on-line detection technology equivalence analysis based on AHP( analytic hierarchy process) is proposed. Firstly,the standard layer composed of accuracy,validity and fault detection ability and the index layer composed of seven indexes such as data numerical accuracy are determined according to the state quantity acquisition process of the two technologies. The weight coefficient of each index is calculated by AHP,and a two-level equivalence evaluation index system is established. According to the properties of each indicator in each indicator layer,the quantitative method and the normalized calculation method of each indicator layer are determined. Aiming at the characteristics of unequal number of data and mismatch of time series of power outage test and power outage test,a data preprocessing method with three spline interpolation fitting is proposed,and an equivalence analysis model is finally established. The example shows that this model can reduce the human intervention,and the equivalence of on-line detection to power failure test can be evaluated by synthesizing the main stage of state variable data acquisition.
引文
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[16]张霖,杨超,李诗勇,等. 500 k V变压器多维状态监测与故障诊断[J].电力大数据,2018,21(02):67-73.ZHANG Lin,YANG Chao,LI ShiYong,et al. Multi-dimensionalstate monitoring and fault diagnosis of 500 k V Transformer[J].Power System and Big Data,2018,21(02):67-73.
[17]艾博,牛会,田晓云.容性设备绝缘带电检测技术在变电站的应用分析[J].内蒙古电力技术,2016,34(06):61-64.AI Bo,NIU Hui,TIAN Xiaoyun. Application analysis of capacitiveequipment insulation online detection technology in substation[J]. Inner Mongolia Electric Power,2016,34(06):61-64.
[18]杨玉新,王建芳,纪巍,等.应用多种带电检测技术联合诊断设备缺陷效果分析[J].内蒙古电力技术,2016,34(03):63-67.YANG Yuxin,WANG Jianfang,JI Wei,et al. Analysis of jointdiagnosing effect by using a variety of charged detectiontechniques[J]. Inner Mongolia Electric Power,2016,34(03):63-67.
[19]钟伟,朱泽厅.配电网架空线路带电检测技术应用探讨[J].浙江电力,2016,35(04):18-21.ZHONG Wei,ZHU Zheting. Discussion on application of livedetection technology in overhead lines of distribution networks[J]. Zhejiang Electric Power,2016,35(04):18-21.
[2]王少华,叶自强,梅冰笑.输变电设备在线监测及带电检测技术在电网中的应用现状[J].高压电器,2011,47(04):84-90.WANG Shaohua,YE Ziqiang,MEI Bingxiao. Application status ofonline monitoring and live detection technologies of transmissionand distribution equipment in electric network[J]. High VoltageApparatus,2011,47(04):84-90.
[3]张晶晶,许修乐,丁明,等.基于模糊层次分析法的变压器状态评估[J].电力系统保护与控制,2017,45(03):75-81.ZHANG Jingjing,XU Xiule,DING Ming,et al. A conditionassessment method of power transformers based on fuzzy analytichierarchy process[J]. Power System Protection and Control,2017,45(03):75-81.
[4]王俏文,丁坚勇,陶文伟,等.基于层次分析模型的二次设备状态检修方法[J].南方电网技术,2013,7(04):97-102.WANG Qiaowen; DING Jianyong; TAO Wenwei,et al. A condition-based maintenance method of secondary electrical equipmentsbased on hierarchy model[J]. Southern Power System Technology,2013,7(04):97-102.
[5]李存斌,李小鹏,高坡.基于变权模糊物元模型的变压器状态实时评估[J].广东电力,2015,28(11):66-73.LI Cunbin,LI Xiaopeng,GAO Po. Real-time evaluation ontransformer state based on variable weight fuzzy matter-elementmodel[J]. Guangdong Electric Power,2015,28(11):66-73.
[6]朱金海. 220 k V变压器油色谱在线监测数据的准确性分析[D].厦门:厦门理工学院,2016.
[7]徐湘忆,陈璐,熊鸣翔,等.变压器油中溶解气体在线监测装置准确性分析[J].电力与能源,2016(03):295-300.Xu Xiangyi,Chenlu,Xiongmingxiang,et al. Accuracy of onlinemonitoring devices for dissolved gas in transformer oil[J]. Power&Energy,2016(03):295-300.
[8]郑一鸣,何文林,王文浩,等.基于多源信息的电力变压器全量状态评价模型[J].智能电网,2016,4(09):894-900.ZHENG Yiming,HE Wenlin,WANG Wenhao,et al. Powertransformer comprehensive condition evaluation model based onmulti-source information[J]. Smart Grid,2016,4(09):894-900.
[9]张友强,寇凌峰,盛万兴,等.配电变压器运行状态评估的大数据分析方法[J].电网技术,2016,40(03):768-773.ZHANG Youqiang,KOU Lingfeng,SHENG Wanxing,et al. Bigdata analytical method for operating state assessment of distributiontransformer[J]. Power System Technology,2016,40(03):768-773.
[10]赵文清,朱永利,姜波,等.基于贝叶斯网络的电力变压器状态评估[J].高电压技术,2008,34(05):1032-1039.ZHAO Wenqing,ZHU Yongli,JIANG Bo,et al,Conditionassessment for power transformers by bayes networks[J]. HighVoltage Engineering,2008,34(05):1032-1039.
[11] Huang Y C. Condition assessment of power transformers usinggenetic-based neural networks[J]. IEEE Science,Measurement and Technology,2003,150(1):19-24.
[12] TANG W H,SPURGEON K,WU Q H,et al. An evidential reasoningapproach to transformer condition assessments[J]. Power DeliveryIEEE Transactions on,2004,19(4):1696-1703.
[13]赵嘉玉,韩肖清,梁琛,等.隶属函数与欧氏距离相结合的配电网优化重构[J].电网技术,2017,41(11):3624-3631.ZHAO Xiyu,HAN Xiaoqing,LIANG Shen,et al. Optimaldistribution network reconstruction combining fuzzy membershipwith euclidean distance[J]. Power System Technology,2017,41(11):3624-3631.
[14]陈大力,沈岩涛,谢槟竹,等.基于余弦相似度模型的最佳教练遴选算法[J].东北大学学报(自然科学版),2014,35(12):1697-1700.CHEN Dali,SHEN Yantao,XIE Binzhu,et al. A measure modelof similarity for finding the best coach[J]. Journal of NortheasternUniversity(Natural Science),2014,35(12):1697-1700.
[15]刘建学,李守军.基于余弦相似度的因子分析在食品成分检测中的应用[J].食品科学,2005,26(06):109-112.LIU Jianxue, LI Shoujun. Dynamical clustering by cosinesimilarity algorithm[J]. Food Science,2005,26(06):109-112.
[16]张霖,杨超,李诗勇,等. 500 k V变压器多维状态监测与故障诊断[J].电力大数据,2018,21(02):67-73.ZHANG Lin,YANG Chao,LI ShiYong,et al. Multi-dimensionalstate monitoring and fault diagnosis of 500 k V Transformer[J].Power System and Big Data,2018,21(02):67-73.
[17]艾博,牛会,田晓云.容性设备绝缘带电检测技术在变电站的应用分析[J].内蒙古电力技术,2016,34(06):61-64.AI Bo,NIU Hui,TIAN Xiaoyun. Application analysis of capacitiveequipment insulation online detection technology in substation[J]. Inner Mongolia Electric Power,2016,34(06):61-64.
[18]杨玉新,王建芳,纪巍,等.应用多种带电检测技术联合诊断设备缺陷效果分析[J].内蒙古电力技术,2016,34(03):63-67.YANG Yuxin,WANG Jianfang,JI Wei,et al. Analysis of jointdiagnosing effect by using a variety of charged detectiontechniques[J]. Inner Mongolia Electric Power,2016,34(03):63-67.
[19]钟伟,朱泽厅.配电网架空线路带电检测技术应用探讨[J].浙江电力,2016,35(04):18-21.ZHONG Wei,ZHU Zheting. Discussion on application of livedetection technology in overhead lines of distribution networks[J]. Zhejiang Electric Power,2016,35(04):18-21.