一种基于电力大数据的反窃电预测方法
A prediction method of anti-electricity stealing based on big data of electric power
-
摘要: 针对传统的反窃电预测方法准确度低的问题，提出了一种基于电力大数据的反窃电预测方法.该方法根据异常规则构造窃电数据样本，引入线损率增长率这一约束条件，使用4种机器学习分类算法分别在电压、电流和功率因数数据集上构建预测模型，将其输出的数据异常用户与线损异常用户相结合，输出疑似窃电用户清单.实验结果表明，该方法预测准确度令人满意，在疑似窃电用户识别方面是高效可行的.Abstract: Aiming at the problem of low accuracy of traditional prediction methods of anti-electricity stealing, a prediction method of anti-electricity stealing based on big data of electric power was proposed. This method firstly constructed samples of electricity stealing data according to abnormal rules, and introduced the growth rate of line loss rate constraint conditions.Then it used four machine learning classification algorithms to build a prediction model on the voltage, current and power factor data sets respectively, combined the users with abnormal data output and users with abnormal line loss to output a list of users suspected of stealing electricity.Experimental results showed that the prediction accuracy of the method was satisfactory,and it was efficient and feasible in identifying users suspected of stealing electricity.
-
-
[1]
PAN W,YANG Q,AGGARWAL C,et al.Big data[J].IEEE Intelligent Systems,2007,32(2):7.
-
[2]
王红平,唐永锋.大数据思维在高校学生信息化管理中的支撑作用[J].科技创新导报,2018,15(13):231.
-
[3]
JOSHI P,RAO P.Global pulses scenario:Status and outlook[J].Annals of the New York Academy of Sciences,2017,1392(1):6.
-
[4]
SEVERIN A J.Dealing with data:Training new scientists[J].Science,2011,331(6024):1516.
-
[5]
BIRNEY E.The making of ENCODE:Lessons for big-data projects[J].Nature,2012,489(7414):49.
-
[6]
孙宏斌,郭庆来,潘昭光.能源互联网:理念、架构与前沿展望[J].电力系统自动化,2015,39(19):1.
-
[7]
FANG X,MISRA S,XUE G,et al.Smart grid——The new and improved power grid:A survey[J].IEEE Communications Surveys & Tutorials,2012,14(4):944.
-
[8]
CHEN L J,XU X H,WANG C M.Research on anti-electricity stealing method base on state estimation[C]//Proceedings of Power Engineering and Automation Conference(PEAM).Piscataway:IEEE,2011.
-
[9]
李海.用电监察面临的问题及反窃电措施[J].企业改革与管理,2014(4):119.
-
[10]
周瑾.窃电与防窃电[J].电力与电工,2004,24(3):73.
-
[11]
沈海泓.远方电能计量运行监测系统研究[D].保定:华北电力大学(河北),2004.
-
[12]
李小佳.对反窃电技术研究及"零距离"复录系统的实现[D].广州:华南理工大学,2011.
-
[13]
李大勇,王瑜,黎灿兵,等.基于无线射频技术的防窃电开箱记录仪设计[J].电测与仪表,2008,45(10):51.
-
[14]
孙凤杰,刘争芳,张永灿.基于GPRS无线传输的防窃电系统[J].电力系统通信,2007,28(171):53.
-
[15]
余昌华,谢剑英.Winsocket技术在电力远程监控系统中的应用[J].计算机工程,2000,26(10):81.
-
[16]
窦健,陈秀群,张海龙,等.一种具有约束条件的用电异常检测模型:201711154836.7[P].2018-05-22.
-
[17]
吴迪,王学伟,窦健,等.基于大数据的防窃电模型与方法[J].北京化工大学学报(自然科学版),2018,45(6):79.
-
[18]
庄池杰,张斌,胡军,等.基于无监督学习的电力用户异常用电模式检测[J].中国电机工程学报,2016,36(2):379.
-
[19]
程超,张汉敬,景志敏,等.基于离群点算法和用电信息采集系统的反窃电研究[J].电力系统保护与控制,2015,43(17):69.
-
[20]
王新霞,王珂,焦东翔,等.基于正态分布离群点算法的反窃电研究[J].电气应用,2017,36(7):60.
-
[21]
窦健,刘宣,卢继哲,等.基于用电信息采集大数据的防窃电方法研究[J].电测与仪表,2018,55(21):43.
-
[22]
任玮蒙,许庆,谢智奕,等.基于电量、电压和电流异常分析的异常用电判断方法:201410706073.2[P].2015-03-11.
-
[1]
-
点击查看大图
计量
- PDF下载量: 26
- 文章访问数: 1689
- 引证文献数: 0
下载:
