@inproceedings{7d26b82e696e4364ba76ffdcc3d89b01,
title = "A Genetic Algorithm Based Feeder-User Connection Mapping Method with Limited Meter Data in Distribution Networks",
abstract = "The dynamic topology of urban distribution power systems poses a significant challenge in accurately mapping energy supply districts, critical for illustrating feeder-household connections and ensuring efficient energy matching. Traditional approaches rely heavily on comprehensive smart meter data or the installation of new monitoring equipment, both of which are costly. This research proposes a novel genetic algorithm-based mapping technique that requires only energy consumption data. This approach leverages historical consumption patterns to produce feeder-user connection maps with high precision. A case study confirms the effectiveness of the algorithm in feeder-user connection mapping, and shows its potential for utility management optimization.",
keywords = "connection mapping, distribution power system, energy supply district, genetic algorithmd",
author = "Yiwei Hu and Furong Li",
year = "2024",
month = may,
day = "31",
doi = "10.1109/PHM61473.2024.00072",
language = "English",
series = "Proceedings - 2024 Prognostics and System Health Management Conference, PHM 2024",
publisher = "IEEE",
pages = "376--379",
editor = "Ziqiang Pu and Versna Spasic-Jokic and Platon Sovilj and Yifan Wu",
booktitle = "Proceedings - 2024 Prognostics and System Health Management Conference, PHM 2024",
address = "USA United States",
note = "2024 Prognostics and System Health Management Conference, PHM 2024 ; Conference date: 28-05-2024 Through 31-05-2024",
}