Consumer phase identification in low-voltage distribution network considering vacant users-Reference-Cited by-同舟云学术

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Consumer phase identification in low-voltage distribution network considering vacant users

Published:2020-10 Issue: Volume:121 Page:106079
ISSN:0142-0615
Container-title:International Journal of Electrical Power & Energy Systems
language:en
Short-container-title:International Journal of Electrical Power & Energy Systems

Author:

Zhou Lai,Zhang Yongjun,Liu Siliang,Li Kun,Li Canbing,Yi Yingqi,Tang Jie

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference24 articles.

1. A voltage regulator for power quality improvement in low-voltage distribution grids;Hock;IEEE Trans Power Electron,2018

2. Programmable protective device for LV distribution system protection;Naik;Protection Control Modern Power Syst,2018

3. A two-level coordinated voltage control scheme of electric vehicle chargers in low-voltage distribution networks;Wang;Electr Power Syst Res,2019

4. Optimal sizing of PV and BESS for a smart household considering different price mechanisms;Zhou;IEEE Access,2018

5. Energy hub modeling to minimize residential energy costs considering solar energy and BESS;Ha;J Mod Power Syst Clean Energy,2017

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven consumer-phase identification in low-voltage distribution networks considering prosumers;Frontiers in Energy;2024-05-10

2. Topology Identification of Active Low-Voltage Distribution Network Based on Regression Analysis and Knowledge Reasoning;Energies;2024-04-07

3. Line–Household Relationship Identification Method for a Low-Voltage Distribution Network Based on Voltage Clustering and Electricity Consumption Characteristics;Processes;2024-01-28

4. Consumer-feeder relationship identification method for low-voltage distribution station area considering feature fusion of voltage variation and spatial distribution;Energy Reports;2023-09

5. A model for identifying the feeder-transformer relationship in distribution grids using a data-driven machine-learning algorithm;Frontiers in Energy Research;2023-07-28

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