Identification of Low-voltage User Meter Box Combined with Known Phase and Address Information

Junteng LUO; Jianmin ZHANG; Yaojun CHEN; Li YAO; Lübin MA; Huanlei YU

doi:10.7500/AEPS20201005001

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Identification of Low-voltage User Meter Box Combined with Known Phase and Address Information

Application Research | 更新时间：2025-06-16

- Identification of Low-voltage User Meter Box Combined with Known Phase and Address Information
- Automation of Electric Power Systems Vol. 45, Issue 9, Pages: 115-121(2021)
- 作者机构：
  
  1.杭州电子科技大学自动化学院，浙江省杭州市 310018
  2.浙江华云信息科技有限公司，浙江省杭州市 310012
  3.国网浙江省电力有限公司营销服务中心，浙江省杭州市 311121
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China;State Grid Corporation of China;National Invention Patent of China
- DOI：10.7500/AEPS20201005001
  CLC：
- Received：05 October 2020，
  
  Revised：2020-12-04，
  
  Published Online：23 February 2021，
  
  Published：10 May 2021
- 稿件说明：
移动端阅览
罗钧腾,章坚民,陈耀军等.融合已知相别和地址信息的低压用户计量表箱识别[J].电力系统自动化,2021,45(9):115-121.

LUO Junteng,ZHANG Jianmin,CHEN Yaojun,et al.Identification of Low-voltage User Meter Box Combined with Known Phase and Address Information[J].Automation of Electric Power Systems,2021,45(9):115-121.
罗钧腾,章坚民,陈耀军等.融合已知相别和地址信息的低压用户计量表箱识别[J].电力系统自动化,2021,45(9):115-121. DOI： 10.7500/AEPS20201005001.

LUO Junteng,ZHANG Jianmin,CHEN Yaojun,et al.Identification of Low-voltage User Meter Box Combined with Known Phase and Address Information[J].Automation of Electric Power Systems,2021,45(9):115-121. DOI： 10.7500/AEPS20201005001.

摘要

用户电能表与表箱的关系不清楚可能导致严重后果，用户电能表的所属计量表箱识别是低压配电网计量拓扑识别问题之一。由于同一计量箱的用户入线共用同一条配电箱母线，若已知总等效单相计量箱数量

，则原问题可转换为基于用户电压时序波形的

类分类问题。在分析这种方法在实际工程应用中缺点的基础上，提出了一种融合已知相别和地址信息的低压配电计量表箱识别方法。首先，采用聚类方法将分相后的电压时序波形辨识到配电分线箱层面。然后，利用经过挖掘和补全的地址文本信息构建基于相邻关系的约束，并采用约束的

-medoids聚类算法将用户区划分为表箱层面。最后，通过2个具典型特征的低压配电网案例验证了所提方法的有效性。

Abstract

Unclear mapping relationship between the user meters and the meter boxes

which may lead to serious consequences. Therefore

the identification of the meter box of the user meters is one of the metering topology identification problems of low-voltage distribution network. Since the entry lines of user meters in the same meter box share the same distribution box bus

if the total number

of the equivalent single-phase meter is known

the original problem can be converted into an

-classification problem based on the voltage sequential waveforms. Based on the analysis of the shortcomings of such method in practical engineering applications

an identification method of the low-voltage power distribution meter box combining the known phase and address information is proposed. First

the clustering method is used to identify the phase-separated voltage sequential waveforms to the distribution box level. Then

the mined and complemented address text information is applied to construct constraints based on neighborhood relations

and the constrained

-medoids clustering algorithm is used to divide users into the meter box level. Finally

two low-voltage distribution network cases with typical characteristics are used to verify the effectiveness of the proposed method.

关键词

Keywords

references

罗钧腾，章坚民，姚力，等 . 基于电压和功率数据的低压用户相别识别优化建模与应用［J/OL］. 电力系统自动化［ 2020-10-05 ］. http：//doi.org/10.7500/AEPS20200107007 http://doi.org/10.7500/AEPS20200107007 .

LUO Junteng ， ZHANG Jianmin ， YAO Li ， et al . Low-voltage customer phase optimal identification modeling and application using voltage and active power data ［J/OL］. Automation of Electric Power Systems ［ 2020-10-05 ］. http：//doi.org/10.7500/AEPS20200107007 http://doi.org/10.7500/AEPS20200107007 .

唐捷，蔡永智，周来，等 . 基于数据驱动的低压配电网线户关系识别方法［J］. 电力系统自动化， 2020 ， 44 （ 11 ）： 127 - 137 .

TANG Jie ， CAI Yongzhi ， ZHOU Lai ， et al . Data-driven based identification method of feeder-consumer connectivity in low-voltage distribution network ［J］. Automation of Electric Power Systems ， 2020 ， 44 （ 11 ）： 127 - 137 .

NI F ， LIU J Q ， WEI F ， et al . Phase identification in distribution systems by data mining methods ［C］// 2017 IEEE Conference on Energy Internet and Energy System Integration （EI2 ）， November 26 - 28 ， 2017 ， Beijing ， China .

OLIVIER F ， SUTERA A ， GEURTS P ， et al . Phase identification of smart meters by clustering voltage measurements ［C］// 2018 Power Systems Computation Conference （PSCC）， June 11 - 15 ， 2018 ， Dublin ， Ireland .

耿俊成，张小斐，万迪明，等 . 基于电压曲线聚类分析的低压用户相序自动识别［J］. 电力大数据， 2019 ， 22 （ 12 ）： 1 - 8 .

GENG Juncheng ， ZHANG Xiaofei ， WAN Diming ， et al . Automatic phase identification of low-voltage users based on voltage curves cluster analysis ［J］. Power System and Big Data ， 2019 ， 22 （ 12 ）： 1 - 8 .

连子宽，姚力，刘晟源，等 . 基于 t -SNE降维和BIRCH聚类的单相用户相位及表箱辨识［J］. 电力系统自动化， 2020 ， 44 （ 8 ）： 176 - 184

LIAN Zikuan ， YAO Li ， LIU Shengyuan ， et al . Phase and meter box identification method for single-phase users based on t -SNE dimension reduction and BIRCH clustering ［J］. Automation of Electric Power Systems ， 2020 ， 44 （ 8 ）： 176 - 184 .

MA Y ， FAN X ， TANG R ， et al . Phase identification of smart meters by spectral clustering ［C］// 2018 2nd IEEE Conference on Energy Internet and Energy System Integration （EI2 ）， October 20 - 22 ， 2018 ， Beijing ， China .

BLAKELY L ， RENO M J ， FENG W . Spectral clustering for customer phase identification using AMI voltage time series ［C］// 2019 IEEE Power and Energy Conference at Illinois （PECI）， February 2 - 3 ， 2019 ， Illinois ， USA .

LIU S ， CUI X ， LIN Z ， et al . Practical method for mitigating three-phase unbalance based on data-driven user phase Identification ［J］. IEEE Transactions on Power Systems ， 2020 ， 35 （ 2 ）： 1653 - 1656 .

杨志淳，沈煜，杨帆，等 . 基于数据关联分析的低压配电网拓扑识别方法［J］. 电测与仪表， 2020 ， 57 （ 18 ）： 5 - 11 .

YANG Zhichun ， SHEN Yu ， YANG Fan ， et al . Topology identification method of low voltage distribution network based on data association analysis ［J］. Electrical Measurement and Instrumentation ， 2020 ， 57 （ 18 ）： 5 - 11 .

SHORT T A . Advanced metering for phase identification， transformer identification， and secondary modeling ［J］. IEEE Transactions on Smart Grid ， 2012 ， 4 （ 2 ）： 651 - 658 .

YE C ， JINMING C ， HAO J ， et al . Two-stage topology identification method for distribution network via clustering correction ［C］// 2019 IEEE Innovative Smart Grid Technologies-Asia ， May 21 - 24 ， 2019 ， Sichuan ， China .

薛禹胜，赖业宁 . 大能源思维与大数据思维的融合：（一）大数据与电力大数据［J］. 电力系统自动化， 2016 ， 40 （ 1 ）： 1 - 8 .

XUE Yusheng ， LAI Yening . Integration of macro energy thinking and big data thinking： Part one big data and power big data ［J］. Automation of Electric Power Systems ， 2016 ， 40 （ 1 ）： 1 - 8 .

王慧芳，曹靖，罗麟 . 电力文本数据挖掘现状及挑战［J］. 浙江电力， 2019 ， 38 （ 3 ）： 1 - 7 .

WANG Huifang ， CAO Jing ， LUO Lin . Current status and challenges of power text data mining ［J］. Zhejiang Electric Power ， 2019 ， 38 （ 3 ）： 1 - 7 .

曹靖，陈陆燊，邱剑，等 . 基于语义框架的电网缺陷文本挖掘技术及其应用［J］. 电网技术， 2017 ， 41 （ 2 ）： 637 - 643 .

CAO Jing ， CHEN Lushen ， QIU Jian ， et al . Semantic framework-based defect text mining technique and application in power grid ［J］. Power System Technology ， 2017 ， 41 （ 2 ）： 637 - 643 .

刘梓权，王慧芳 . 基于知识图谱技术的电力设备缺陷记录检索方法［J］. 电力系统自动化， 2018 ， 42 （ 14 ）： 158 - 164 .

LIU Ziquan ， WANG Huifang . Retrieval method for defect records of power equipment based on knowledge graph technology ［J］. Automation of Electric Power Systems ， 2018 ， 42 （ 14 ）： 158 - 164 .

低压配电设计规范： GB 50054—2011 ［S］. 北京：中国计划出版社， 2012 .

Low voltage power distribution design code ： GB 50054—2011 ［S］. Beijing ： China Planning Press ， 2012 .

低压计量箱技术规范： Q/GDW 11008—2013 ［S］. 北京：中国电力出版社， 2014 .

Technical specification for low voltage metering ： Q/GDW 11008—2013 ［S］. Beijing ： China Electric Power Press ， 2014 .

国家电网有限公司380/220 V配电网工程典型设计［S］. 北京：中国电力出版社， 2018 .

State Grid Corporation of China 380/220 V distribution network project typical design ［S］. Beijing ： China Electric Power Press ， 2018 .

ROUSSEEUW P J . Silhouettes： a graphical aid to the interpretation and validation of cluster analysis ［J］. Journal of Computational and Applied Mathematics ， 1987 ， 20 ： 53 - 65 .

WAGSTAFF K ， CARDIE C ， ROGERS S ， et al . Constrained k -means clustering with background knowledge ［C］// Proceedings of the Eighteenth International Conference on Machine Learning ， June 28-July 1 ， 2001 ， Williamstown ， USA .

BILENKO M ， BASU S ， MOONEY R J . Integrating constraints and metric learning in semi-supervised clustering ［C］// Proceedings of the Twenty-first International Conference on Machine Learning ， July 4 - 8 ， 2004 ， Banff ， Canada .

MAATEN L ， HINTON G . Visualizing data using t -SNE ［J/OL］. Journal of Machine Learning Research ［ 2020-10-05 ］. https：//www.ixueshu.com/document/dbf0659b0f293d63318947a18e7f9386.html https://www.ixueshu.com/document/dbf0659b0f293d63318947a18e7f9386.html .

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