Phase Identification of Smart Meters by Spectral Clustering

被引：0

作者：

Ma, Yi ^{[1
]}

Duan, Pan ^{[2
]}

Du, Jinyang ^{[3
,4
]}

Fan, Xingyuan ^{[4
,5
]}

Tang, Run ^{[4
,5
]}

Sun, Ying ^{[4
,6
]}

Duan, Qichang ^{[1
]}

机构：

[1] Chongqing Univ, Sch Automat, Chongqing, Peoples R China

[2] Chongqing Univ Posts & Telecommun, Sch Automat, Chongqing, Peoples R China

[3] Harbin Univ Sci & Technol, Harbin, Heilongjiang, Peoples R China

[4] Guangzhou Power Supply Bur Co Ltd, Guangzhou, Guangdong, Peoples R China

[5] Wuhan Univ, Wuhan, Hubei, Peoples R China

[6] Harbin Inst Technol, Harbin, Heilongjiang, Peoples R China

来源：

2018 2ND IEEE CONFERENCE ON ENERGY INTERNET AND ENERGY SYSTEM INTEGRATION (EI2) | 2018年

基金：

中国国家自然科学基金;

关键词：

clustering; spectral clustering; phase identification; smart meter; distributed power grid;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Phase identification is important for the safe operation of distributed power grid, and a data-driven phase identification approach has been proposed in this paper, in which the OpenDSS (Open distribution system simulator) is used to perform power flow analysis on a real distribution feeder-European Low Voltage Test Feeder. The spectral clustering is used to identify phases of users/smart meters. Verification by European Low Voltage Test Feeder in different settings. The phase identification accuracy of proposed method is over 95% when the voltage sampling period is no more than 1 hour in the case of complete data set. Results indicate that the proposed method performs better than the constrained k-means method when the sampling period exceeds 15 minutes.

引用

页数：5

共 13 条

[1]

[Anonymous], AM CONTR C

[2]

[Anonymous], IEEE POW EN SOC GEN

[3]

[Anonymous], APPL POW EL C EXP AP

[4]

[Anonymous], DISTR TEST FEED

[5]