Community detection in national-scale high voltage transmission networks using genetic algorithms
The large-scale interconnection of electricity networks has been one of the most important investments made by electric companies, and this trend is expected to continue in the future. One of the research topics in this field is the application of graph-based analysis to identify the characteristics...
| Principais autores: | , , , |
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| Formato: | info:eu-repo/semantics/article |
| Idioma: | English |
| Publicado em: |
2024
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| Assuntos: | |
| Acesso em linha: | http://hdl.handle.net/10835/15073 |
| _version_ | 1789406382259175424 |
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| author | Guerrero López, Manuel Alejandro Baños Navarro, Raúl Gil Montoya, Francisco Alcayde García, Alfredo |
| author_facet | Guerrero López, Manuel Alejandro Baños Navarro, Raúl Gil Montoya, Francisco Alcayde García, Alfredo |
| author_sort | Guerrero López, Manuel Alejandro |
| collection | DSpace |
| description | The large-scale interconnection of electricity networks has been one of the most important investments made by electric companies, and this trend is expected to continue in the future. One of the research topics in this field is the application of graph-based analysis to identify the characteristics of power grids. In particular, the application of community detection techniques allows for the identification of network elements that share valuable properties by partitioning a network into some loosely coupled sub-networks (communities) of similar scale, such that nodes within a community are densely linked, while connections between different communities are more sparse. This paper proposes the use of competitive genetic algorithms to rapidly detect any number of community structures in complex grid networks. Results obtained in several national- scale high voltage transmission networks, including Italy, Germany, France, the Iberian peninsula (Spain and Portugal), Texas (US), and the IEEE 118 bus test case that represents a portion of the American Electric Power System (in the Midwestern US), show the good performance of genetic algorithms to detect communities in power grids. In addition to the topological analysis of the networks representing power grids, it is discussed the implications of these results from the viewpoint of the engineering task, and how they could be used to analyse the vulnerability risk of power grids to avoid large-scale cascading failures. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-15073 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2024 |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-150732024-01-10T12:39:36Z Community detection in national-scale high voltage transmission networks using genetic algorithms Guerrero López, Manuel Alejandro Baños Navarro, Raúl Gil Montoya, Francisco Alcayde García, Alfredo high voltage transmission networks Electric power system power grid complex networks community detection genetic algorithms The large-scale interconnection of electricity networks has been one of the most important investments made by electric companies, and this trend is expected to continue in the future. One of the research topics in this field is the application of graph-based analysis to identify the characteristics of power grids. In particular, the application of community detection techniques allows for the identification of network elements that share valuable properties by partitioning a network into some loosely coupled sub-networks (communities) of similar scale, such that nodes within a community are densely linked, while connections between different communities are more sparse. This paper proposes the use of competitive genetic algorithms to rapidly detect any number of community structures in complex grid networks. Results obtained in several national- scale high voltage transmission networks, including Italy, Germany, France, the Iberian peninsula (Spain and Portugal), Texas (US), and the IEEE 118 bus test case that represents a portion of the American Electric Power System (in the Midwestern US), show the good performance of genetic algorithms to detect communities in power grids. In addition to the topological analysis of the networks representing power grids, it is discussed the implications of these results from the viewpoint of the engineering task, and how they could be used to analyse the vulnerability risk of power grids to avoid large-scale cascading failures. 2024-01-10T12:39:36Z 2024-01-10T12:39:36Z 2018-07-01 info:eu-repo/semantics/article http://hdl.handle.net/10835/15073 en Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
| spellingShingle | high voltage transmission networks Electric power system power grid complex networks community detection genetic algorithms Guerrero López, Manuel Alejandro Baños Navarro, Raúl Gil Montoya, Francisco Alcayde García, Alfredo Community detection in national-scale high voltage transmission networks using genetic algorithms |
| title | Community detection in national-scale high voltage transmission networks using genetic algorithms |
| title_full | Community detection in national-scale high voltage transmission networks using genetic algorithms |
| title_fullStr | Community detection in national-scale high voltage transmission networks using genetic algorithms |
| title_full_unstemmed | Community detection in national-scale high voltage transmission networks using genetic algorithms |
| title_short | Community detection in national-scale high voltage transmission networks using genetic algorithms |
| title_sort | community detection in national-scale high voltage transmission networks using genetic algorithms |
| topic | high voltage transmission networks Electric power system power grid complex networks community detection genetic algorithms |
| url | http://hdl.handle.net/10835/15073 |
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