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An intelligent strategy for faults location in distribution networks with distributed generation
| dc.contributor.author | Perez, Ramon | spa |
| dc.contributor.author | Vasquez, Carmen | spa |
| dc.contributor.author | Viloria Silva, Amelec Jesus | spa |
| dc.date.accessioned | 2019-06-10T14:16:59Z | |
| dc.date.available | 2019-06-10T14:16:59Z | |
| dc.date.issued | 2019 | |
| dc.identifier.issn | 1064-1246 | spa |
| dc.identifier.uri | http://hdl.handle.net/11323/4841 | spa |
| dc.description.abstract | The exact location of faults in the electrical distribution systems is a problem that affects not only the users, but also the companies providing the electric service. With greater time invested in this period, the losses due to unbilled energy and inconvenience to users increases, thus decreasing the quality of service. One of the causes of the growth in time is the misunderstanding that might exist in the localization systems that act under the presence of distributed generation sources in the distribution networks. In this sense, the present research develops an intelligent diagnosis of faults in distribution systems with distributed generation. Three stages are defined: Identification of the type of fault, the location of the zone, and the exact point of fault. A mixed method based on artificial intelligence and mathematical algorithms is applied. Eleven different types of faults that can occur in a distribution system are considered with six different values of fault resistances ranging from 5 to 30 . The errors found are less than 2% in the location of the fault point with robustness to variations in the load and the penetration of distributed generation. | spa |
| dc.language.iso | eng | |
| dc.publisher | Journal of Intelligent and Fuzzy Systems | spa |
| dc.relation.ispartof | 10.3233/JIFS-18807 | spa |
| dc.rights | info:eu-repo/semantics/restrictedAccess | spa |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | spa |
| dc.subject | Fault identification | spa |
| dc.subject | fault location | spa |
| dc.subject | electric distribution systems | spa |
| dc.subject | distributed generation | spa |
| dc.subject | accuracy | spa |
| dc.title | An intelligent strategy for faults location in distribution networks with distributed generation | spa |
| dc.type | Pre-Publicación | spa |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
| dc.identifier.instname | Corporación Universidad de la Costa | spa |
| dc.identifier.reponame | REDICUC - Repositorio CUC | spa |
| dc.identifier.repourl | https://repositorio.cuc.edu.co/ | spa |
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Barrera and G. Carrillo, Fault location in power distribution systems using a learning algorithm for multivariable data analysis, IEEE Transactions on Power Delivery 22(3) (2007), 1715–1721. [26] R. Salim, K. de Oliveira, A. Filomena, M. Resener and A. Bretas, Hybrid fault diagnosis scheme implementation for power distribution systems automation, IEEE Transactions on Power Delivery 23(4) (2008), 1846–1856. [27] F. Trindade and W. Freitas, Low voltage zones to support fault location in distribution systems with smart meters, IEEE Transactions on Smart Grid pp(99) (2016), 1–10. [28] R. Perez, E. Inga, A. Aguila, C. V ´ asquez, L. Lima, A. Vilo- ´ria and M. Henry, Fault diagnosis on electrical distribution systems based on fuzzy logic, Advances in Swarm Intelligence ICSI 2018 Lecture Notes in Computer Science 10942 (2018), 174–185. | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_816b | spa |
| dc.type.content | Text | spa |
| dc.type.driver | info:eu-repo/semantics/preprint | spa |
| dc.type.redcol | http://purl.org/redcol/resource_type/ARTOTR | spa |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | spa |
| dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | spa |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | spa |
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