A new data-driven method based on Niching Genetic Algorithms for phase and substation identification-Reference-Cited by-同舟云学术

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A new data-driven method based on Niching Genetic Algorithms for phase and substation identification

Published:2021-10 Issue: Volume:199 Page:107434
ISSN:0378-7796
Container-title:Electric Power Systems Research
language:en
Short-container-title:Electric Power Systems Research

Author:

Jimenez Victor Adrian^ORCID,Will Adrian^ORCID

Funder

Universidad Tecnológica Nacional

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference29 articles.

1. AEA 92559-1: towards an Argentinean smart grid vision;Tripaldi,2015

2. Phase identification in distribution networks with micro-synchrophasors;Wen,2015

3. Phase identification of smart meters by clustering voltage measurements;Olivier,2018

4. Identifying topology of low voltage distribution networks based on smart meter data;Pappu;IEEE Trans. Smart Grid,2018

5. Dynamic phase balancing in the smart distribution networks;Soltani;Int. J. Electr. Power Energy Syst.,2017

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1. A review on topology identification methods and applications in distribution networks;Electric Power Systems Research;2024-09

2. Overview on topology identification technologies for a low-voltage distribution network;Archives of Electrical Engineering;2024-01-02

3. Topology Identification of Low-voltage Distribution Network Based on Mining Hidden Nodes;2023 Panda Forum on Power and Energy (PandaFPE);2023-04

4. Transformer-customer relationship identification for low-voltage distribution networks based on joint optimization of voltage silhouette coefficient and power loss coefficient;Electric Power Systems Research;2023-03

5. Topology identification method for residential areas in low-voltage distribution networks based on unsupervised learning and graph theory;Electric Power Systems Research;2023-02

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