{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T16:00:29Z","timestamp":1776355229355,"version":"3.51.2"},"reference-count":28,"publisher":"World Scientific Pub Co Pte Ltd","issue":"06","funder":[{"name":"Research and Development Special Project ofState Grid Sichuan Provincial Electric Power Company","award":["521916230001"],"award-info":[{"award-number":["521916230001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:p> With the rapid development of the\u00a0smart grid, the fast and accurate fault location of low-voltage distribution networks has become the key to ensuring the stability and reliability of the\u00a0power supply. This paper aims to explore and construct a fault location model of low-voltage distribution network based on an\u00a0attention diagram neural network. First, this paper analyzes the current situation and challenges of fault location in low-voltage distribution network, and points out that traditional methods have limitations when processing large-scale and high-dimensional power system data. Subsequently, a\u00a0graph neural network (GNN) is introduced for processing graph-structured network data, and combined with attention mechanisms. Thus, an innovative attention-graph neural network model (named as A-GNN) is proposed for the purpose. The model can make full use of the topology structure and node feature information in the power grid, and dynamically adjust the information aggregation weight between different nodes through the attention mechanism. This is expected to achieve efficient and accurate fault location. In the experimental part, we trained and tested the A-GNN model based on the real low-voltage distribution network dataset, and compared it with several prediction models. The experimental results show that the A-GNN model has higher accuracy and recall rate in fault location tasks, especially in complex fault scenarios. <\/jats:p>","DOI":"10.1142\/s0218126625501427","type":"journal-article","created":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T14:34:16Z","timestamp":1730990056000},"source":"Crossref","is-referenced-by-count":3,"title":["An Attentional Graph Neural Network-Based Fault Point Positioning Model for Low-Voltage Distribution Networks"],"prefix":"10.1142","volume":"34","author":[{"given":"Yuan","family":"Meng","sequence":"first","affiliation":[{"name":"State of Grid Sichuan Electric Power Company, Guang\u2019an Power Supply Company, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keqi","family":"Yao","sequence":"additional","affiliation":[{"name":"State of Grid Sichuan Electric Power Company, Guang\u2019an Power Supply Company, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1217-5078","authenticated-orcid":false,"given":"Jun","family":"He","sequence":"additional","affiliation":[{"name":"State of Grid Sichuan Electric Power Company, Guang\u2019an Power Supply Company, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shun","family":"Li","sequence":"additional","affiliation":[{"name":"State of Grid Sichuan Electric Power Company, Guang\u2019an Power Supply Company, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Gu","sequence":"additional","affiliation":[{"name":"State of Grid Sichuan Electric Power Company, Guang\u2019an Power Supply Company, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2025,1,24]]},"reference":[{"key":"S0218126625501427BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.124277"},{"key":"S0218126625501427BIB002","doi-asserted-by":"publisher","DOI":"10.1145\/3627915.3628081"},{"key":"S0218126625501427BIB003","doi-asserted-by":"publisher","DOI":"10.35833\/MPCE.2022.000204"},{"key":"S0218126625501427BIB004","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2024.110176"},{"key":"S0218126625501427BIB005","doi-asserted-by":"publisher","DOI":"10.1142\/S0129156424400433"},{"key":"S0218126625501427BIB006","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3345795"},{"key":"S0218126625501427BIB007","doi-asserted-by":"publisher","DOI":"10.3389\/fnbot.2024.1396979"},{"key":"S0218126625501427BIB008","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2023.109158"},{"key":"S0218126625501427BIB009","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2024.3365157"},{"key":"S0218126625501427BIB010","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2023.120932"},{"key":"S0218126625501427BIB011","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRD.2022.3190938"},{"key":"S0218126625501427BIB012","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2023.109265"},{"key":"S0218126625501427BIB013","doi-asserted-by":"publisher","DOI":"10.3390\/en15186762"},{"key":"S0218126625501427BIB014","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2021.3130311"},{"key":"S0218126625501427BIB015","doi-asserted-by":"publisher","DOI":"10.1049\/gtd2.12590"},{"key":"S0218126625501427BIB017","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2024.114282"},{"key":"S0218126625501427BIB018","doi-asserted-by":"publisher","DOI":"10.3390\/en17092060"},{"key":"S0218126625501427BIB019","doi-asserted-by":"publisher","DOI":"10.35833\/MPCE.2024.000177"},{"key":"S0218126625501427BIB020","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2022.108853"},{"key":"S0218126625501427BIB021","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2023.113898"},{"key":"S0218126625501427BIB022","doi-asserted-by":"publisher","DOI":"10.3390\/app132312690"},{"key":"S0218126625501427BIB023","doi-asserted-by":"publisher","DOI":"10.3390\/en15010104"},{"key":"S0218126625501427BIB024","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3316600"},{"key":"S0218126625501427BIB025","doi-asserted-by":"publisher","DOI":"10.1080\/23311916.2021.1975900"},{"key":"S0218126625501427BIB026","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3227641"},{"key":"S0218126625501427BIB027","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2022.108085"},{"key":"S0218126625501427BIB028","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3429341"},{"key":"S0218126625501427BIB029","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2024.110518"}],"container-title":["Journal of Circuits, Systems and Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218126625501427","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T04:11:30Z","timestamp":1744690290000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S0218126625501427"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,24]]},"references-count":28,"journal-issue":{"issue":"06","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["10.1142\/S0218126625501427"],"URL":"https:\/\/doi.org\/10.1142\/s0218126625501427","relation":{},"ISSN":["0218-1266","1793-6454"],"issn-type":[{"value":"0218-1266","type":"print"},{"value":"1793-6454","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,24]]},"article-number":"2550142"}}