Reverse Identification of the Relationship of Feeder-Transformer Connectivity in Distribution Grid Applying Smart Meter Measurement Data

doi:10.12204/j.issn.1000-7229.2020.11.010

Abstract

Abstract:

According to the energy conservation theory, from the perspective of satisfying the power constraints and minimizing the fluctuation of the line loss rates of the medium-voltage lines, this paper converts the intelligent identification of the connection relationship in distribution networks into a combination optimization problem between medium-voltage lines and distribution transformers. Accordingly, an intelligent recognition model is proposed. In order to speed up the solution speed and improve the recognition accuracy, the dimension reduction optimization is performed by merging the distribution transformers with high correlation of voltage fluctuations. After that, the branch-and-bound algorithm is used to solve the problem, and the intelligent identification is realized. Finally, applying the measurement data obtained by the electricity information acquisition system, the proposed scheme is implemented with MATLAB and CPLEX for example analysis. The analysis results verify the feasibility and effectiveness of the identification scheme.

Key words: distribution network, topology recognition, feeder-transformer connectivity, combinatorial optimization, branch-and-bound algorithm, data mining

CLC Number:

TM711

XIE Chao, LI Chenxi, ZHANG Dairun, ZENG Haodong. Reverse Identification of the Relationship of Feeder-Transformer Connectivity in Distribution Grid Applying Smart Meter Measurement Data[J]. ELECTRIC POWER CONSTRUCTION, 2020, 41(11): 94-100.

Figures/Tables 11

Fig.1 π- shaped equivalent model of a power line

Fig.2 Voltage vector diagram

Fig.3 Flow chart of branch and bound algorithm

Table 1 Parameters of medium-voltage distribution line

Table 2 Parameters of distribution transformer

Fig.4 Relationships of feeder-transformer connectivity recorded in the GIS

Fig.5 Area division results

Fig.6 Equivalent voltage chart of outlets of distribution transformers in area A2

Table 3 Differences in relationships of feeder-transformer connectivity between recognition result and GIS records

Fig.7 Revision of feeder-transformer connectivity

Fig.8 Changes of daily input power and line loss rate of L1 and L2

References 20

[1]	ÜBERMASSER S, LEBER T, STIFTER M , et al. Maximizing local renewable energy consumption by shifting flexible electrical loads in time and space[J]. e & i Elektrotechnik und Informationstechnik, 2014,131(8):372-377.
[2]	马钊, 周孝信, 尚宇炜 , 等. 未来配电系统形态及发展趋势[J]. 中国电机工程学报, 2015,35(6):1289-1298.
	MA Zhao, ZHOU Xiaoxin, SHANG Yuwei , et al. Form and development trend of future distribution system[J]. Proceedings of the CSEE, 2015,35(6):1289-1298.
[3]	ZHOU K L, YANG S L, SHAO Z . Energy Internet: The business perspective[J]. Applied Energy, 2016,178:212-222.
[4]	吴克河, 王继业, 李为 , 等. 面向能源互联网的新一代电力系统运行模式研究[J]. 中国电机工程学报, 2019,39(4):966-978.
	WU Kehe, WANG Jiye, LI Wei , et al. Research on the operation mode of new generation electric power system for the future energy Internet[J]. Proceedings of the CSEE, 2019,39(4):966-978.
[5]	栾文鹏, 余贻鑫, 王兵 . AMI数据分析方法[J]. 中国电机工程学报, 2015,35(1):29-36.
	LUAN Wenpeng, YU Yixin, WANG Bing . AMI data analytics[J]. Proceedings of the CSEE, 2015,35(1):29-36.
[6]	徐丙垠, 李天友, 薛永端 . 配电网继电保护与自动化[M]. 北京: 中国电力出版社, 2017.
[7]	张亚健, 杨挺, 孟广雨 . 泛在电力物联网在智能配电系统应用综述及展望[J]. 电力建设, 2019,40(6):1-12.
	ZHANG Yajian, YANG Ting, MENG Guangyu . Review and prospect of ubiquitous power Internet of Things in smart distribution system[J]. Electric Power Construction, 2019,40(6):1-12.
[8]	葛磊蛟, 汪宇倩, 戚嘉兴 , 等. 面向城市能源互联网的电力物联网内涵、架构和关键技术[J]. 电力建设, 2019,40(9):91-98.
	GE Leijiao, WANG Yuqian, QI Jiaxing , et al. The content, frameworks and key technologies of power Internet of Things for urban energy Internet[J]. Electric Power Construction, 2019,40(9):91-98.
[9]	KIPPING A, TRØMBORG E . Modeling and disaggregating hourly electricity consumption in Norwegian dwellings based on smart meter data[J]. Energy and Buildings, 2016,118:350-369.
[10]	刘道伟, 张东霞, 孙华东 , 等. 时空大数据环境下的大电网稳定态势量化评估与自适应防控体系构建[J]. 中国电机工程学报, 2015,35(2):268-276.
	LIU Daowei, ZHANG Dongxia, SUN Huadong , et al. Construction of stability situation quantitative assessment and adaptive control system for large-scale power grid in the spatio-temporal big data environment[J]. Proceedings of the CSEE, 2015,35(2):268-276.
[11]	王贺飞, 李洪涛, 余昆 , 等. 基于DSCADA和μPMU数据融合的配电网运行拓扑辨识[J]. 电力建设, 2019,40(6):123-131.
	WANG Hefei, LI Hongtao, YU Kun , et al. Identification of distribution network operation topology based on DSCADA and μPMU telemetry data fusion[J]. Electric Power Construction, 2019,40(6):123-131.
[12]	刘道伟, 章锐, 李柏青 , 等. 基于状态量测的电网拓扑结构反向识别方法研究[J]. 中国电机工程学报, 2019,39(24):7107-7117.
	LIU Daowei, ZHANG Rui, LI Baiqing , et al. Research on reverse recognition method of power system topological structure based on state measurement[J]. Proceedings of the CSEE, 2019,39(24):7107-7117.
[13]	LUAN W, PENG J, MARAS M, et al. Distribution network topology error correction using smart meter data analytics [C]// 2013 IEEE Power & Energy Society General Meeting. Vancouver, BC, Canada: IEEE, 2013.
[14]	LUAN W, PENG J, MARAS M , et al. Smart meter data analytics for distribution network connectivity verification[J]. IEEE Transactions on Smart Grid, 2015,6(4):1964-1971.
[15]	耿俊成, 吴博, 万迪明 , 等. 基于离群点检测的低压配电网拓扑结构校验[J]. 电力信息与通信技术, 2017,15(5):61-65.
	GENG Juncheng, WU Bo, WAN Diming , et al. Low-voltage transformer area topology verification based on outlier detection[J]. Electric Power Information and Communication Technology, 2017,15(5):61-65.
[16]	耿俊成, 张小斐, 郭志民 , 等. 基于离散Fréchet距离和剪辑近邻法的低压配电网拓扑结构校验方法[J]. 电测与仪表, 2017,54(5):50-55.
	GENG Juncheng, ZHANG Xiaofei, GUO Zhimin , et al. Topology verification of low-voltage transformer areas based on discrete Fréchet distance and editing nearest-neighbors method[J]. Electrical Measurement & Instrumentation, 2017,54(5):50-55.
[17]	蒋涛, 汤新华, 李娟 . 基于停电图纹识别线变关系的实现[J]. 大众用电, 2018,32(10):26-27.
[18]	刘剑, 邰能灵, 范春菊 , 等. 基于暂态电流Pearson相关性的两电平VSC-HVDC直流线路故障判别[J]. 电工技术学报, 2017,32(3):74-85.
	LIU Jian, TAI Nengling, FAN Chunju , et al. A fault identification method for two-level VSC-HVDC DC line based on Pearson correlation of transient current[J]. Transactions of China Electrotechnical Society, 2017,32(3):74-85.
[19]	唐泽洋, 周鲲鹏, 曹侃 , 等. 基于配电网运行数据的线变关系校验方法[J]. 高电压技术, 2018,44(4):1059-1068.
	TANG Zeyang, ZHOU Kunpeng, CAO Kan , et al. Substation area topology verification method based on distribution network operation data[J]. High Voltage Engineering, 2018,44(4):1059-1068.
[20]	邢杰, 唐泽洋, 刘焱 , 等. 基于电网运行数据的配网线变关系校验影响因素分析[J]. 电力大数据, 2019,22(2):13-19.
	XING Jie, TANG Zeyang, LIU Yan , et al. Analysis of influencing factors for checking the relationship of feeder-transformer connectivity distribution gird based on operation data of power gird[J]. Power Systems and Big Data, 2019,22(2):13-19.