Phase Identification of Low-voltage Distribution Network Based on Stepwise Regression Method

doi:10.35833/MPCE.2022.000655

Home > Archive>Volume 11, Issue 4, 2023 >1224-1234. DOI:10.35833/MPCE.2022.000655

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Phase Identification of Low-voltage Distribution Network Based on Stepwise Regression Method

DOI:

10.35833/MPCE.2022.000655

Author:

Yi Yingqi
Yi Yingqi
School of Electric Power, South China University of Technology, Guangdong Key Laboratory of Clean Energy Technology, Guangzhou 510641, China
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Liu Siliang
Liu Siliang
School of Electric Power, South China University of Technology, Guangdong Key Laboratory of Clean Energy Technology, Guangzhou 510641, China
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Zhang Yongjun
Zhang Yongjun
School of Electric Power, South China University of Technology, Guangdong Key Laboratory of Clean Energy Technology, Guangzhou 510641, China
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Xue Ying
Xue Ying
School of Electric Power, South China University of Technology, Guangdong Key Laboratory of Clean Energy Technology, Guangzhou 510641, China
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Deng Wenyang
Deng Wenyang
School of Electric Power, South China University of Technology, Guangdong Key Laboratory of Clean Energy Technology, Guangzhou 510641, China
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Li Qinghao
Li Qinghao
School of Electric Power, South China University of Technology, Guangdong Key Laboratory of Clean Energy Technology, Guangzhou 510641, China
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Affiliation:

School of Electric Power, South China University of Technology, Guangdong Key Laboratory of Clean Energy Technology, Guangzhou 510641, China

Fund Project:

This work was supported in part by the National Natural Science Foundation of China (No. 52177085) and Science and Technology Planning Project of Guangzhou (No. 202102021208).

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Abstract:

Accurate information for consumer phase connectivity in a low-voltage distribution network (LVDN) is critical for the management of line losses and the quality of customer service. The wide application of smart meters provides the data basis for the phase identification of LVDN. However, the measurement errors, poor communication, and data distortion have significant impacts on the accuracy of phase identification. In order to solve this problem, this paper proposes a phase identification method of LVDN based on stepwise regression (SR) method. First, a multiple linear regression model based on the principle of energy conservation is established for phase identification of LVDN. Second, the SR algorithm is used to identify the consumer phase connectivity. Third, by defining a significance correction factor, the results from the SR algorithm are updated to improve the accuracy of phase identification. Finally, an LVDN test system with 63 consumers is constructed based on the real load. The simulation results prove that the identification accuracy achieved by the proposed method is higher than other phase identification methods under the influence of various errors.

Key words:Phase identification ; low-voltage distribution network (LVDN) ; stepwise regression ; smart meter ; data-driven method

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Received:October 11,2022
Revised:January 01,2023
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Online: July 25,2023
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