Graph Analysis to Fully Automate Fault Location Identification in Power Distribution Systems
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866915569505140736 |
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| author | Kahnamouei, Ali Shakeri Lotfifard, Saeed |
| author_facet | Kahnamouei, Ali Shakeri Lotfifard, Saeed |
| contents | This paper proposes graph analysis methods to fully automate the fault location identification task in power distribution systems. The proposed methods take basic unordered data from power distribution systems as input, including branch parameters, load values, and the location of measuring devices. The proposed data preparation and analysis methods automatically identify the system's topology and extract essential information, such as faulted paths, structures, loading of laterals and sublaterals, and estimate the fault location accordingly. The proposed graph analysis methods do not require complex node and branch numbering processes or renumbering following changes in the system topology. The proposed methods eliminate the need for human intervention at any step of the fault location identification process. They are scalable and applicable to systems of any size. The performance of the proposed algorithm is demonstrated using the IEEE 34-bus distribution test system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_19059 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Graph Analysis to Fully Automate Fault Location Identification in Power Distribution Systems Kahnamouei, Ali Shakeri Lotfifard, Saeed Systems and Control This paper proposes graph analysis methods to fully automate the fault location identification task in power distribution systems. The proposed methods take basic unordered data from power distribution systems as input, including branch parameters, load values, and the location of measuring devices. The proposed data preparation and analysis methods automatically identify the system's topology and extract essential information, such as faulted paths, structures, loading of laterals and sublaterals, and estimate the fault location accordingly. The proposed graph analysis methods do not require complex node and branch numbering processes or renumbering following changes in the system topology. The proposed methods eliminate the need for human intervention at any step of the fault location identification process. They are scalable and applicable to systems of any size. The performance of the proposed algorithm is demonstrated using the IEEE 34-bus distribution test system. |
| title | Graph Analysis to Fully Automate Fault Location Identification in Power Distribution Systems |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2510.19059 |