Anomaly detection and clustering‐based identification method for consumer–transformer relationship and associated phase in low‐voltage distribution systems

Anomaly detection and clustering‐based identification method for consumer–transformer relationship and associated phase in low‐voltage distribution systems

Abstract The identification accuracy of low‐voltage distribution consumer–transformer relationship and phase are crucial to three‐phase unbalanced regulation and error correction in consumer–transformer relationships. However, owing to the rapid increase in the number of consumers and the upgrade of...

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Bibliographic Details
Main Authors: Zhenyue Chu, Xueyuan Cui, Xingli Zhai, Shengyuan Liu, Weiqiang Qiu, Muhammad Waseem, Tarique Aziz, Qin Wang, Zhenzhi Lin
Format: Article
Language:English
Published: Wiley 2022-12-01
Series:Energy Conversion and Economics
Subjects:
clustering by fast search and find of density peaks
consumer–transformer relationship
fast dynamic time warping distance
local outlier factor
low‐voltage distribution systems
phase identification
Online Access:https://doi.org/10.1049/enc2.12073

Internet

https://doi.org/10.1049/enc2.12073

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