Intelligent fault detection system for microgrids

The dynamic features of microgrid operation, such as on-grid/off-grid operation mode, the intermittency of distributed generators, and its dynamic topology due to its ability to reconfigure itself, cause misfiring of conventional protection schemes. To solve this issue, adaptive protection schemes t...

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Autores:: Cepeda, Cristian
Orozco-Henao, Cesar
Percybrooks, Winston
Pulgarín-Rivera, Juan Diego
Montoya, Oscar Danilo
Gil-González, Walter
Vélez, Juan Carlos

Tipo de recurso:

Fecha de publicación:: 2020

Institución:: Universidad Tecnológica de Bolívar

Repositorio:: Repositorio Institucional UTB

Idioma:: eng

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dc.title.spa.fl_str_mv	Intelligent fault detection system for microgrids
title	Intelligent fault detection system for microgrids
spellingShingle	Intelligent fault detection system for microgrids Fault detector Microgrid Machine learning-based techniques
title_short	Intelligent fault detection system for microgrids
title_full	Intelligent fault detection system for microgrids
title_fullStr	Intelligent fault detection system for microgrids
title_full_unstemmed	Intelligent fault detection system for microgrids
title_sort	Intelligent fault detection system for microgrids
dc.creator.fl_str_mv	Cepeda, Cristian Orozco-Henao, Cesar Percybrooks, Winston Pulgarín-Rivera, Juan Diego Montoya, Oscar Danilo Gil-González, Walter Vélez, Juan Carlos
dc.contributor.author.none.fl_str_mv	Cepeda, Cristian Orozco-Henao, Cesar Percybrooks, Winston Pulgarín-Rivera, Juan Diego Montoya, Oscar Danilo Gil-González, Walter Vélez, Juan Carlos
dc.subject.keywords.spa.fl_str_mv	Fault detector Microgrid Machine learning-based techniques
topic	Fault detector Microgrid Machine learning-based techniques
description	The dynamic features of microgrid operation, such as on-grid/off-grid operation mode, the intermittency of distributed generators, and its dynamic topology due to its ability to reconfigure itself, cause misfiring of conventional protection schemes. To solve this issue, adaptive protection schemes that use robust communication systems have been proposed for the protection of microgrids. However, the cost of this solution is significantly high. This paper presented an intelligent fault detection (FD) system for microgrids on the basis of local measurements and machine learning (ML) techniques. This proposed FD system provided a smart level to intelligent electronic devices (IED) installed on the microgrid through the integration of ML models. This allowed each IED to autonomously determine if a fault occurred on the microgrid, eliminating the requirement of robust communication infrastructure between IEDs for microgrid protection. Additionally, the proposed system presented a methodology composed of four stages, which allowed its implementation in any microgrid. In addition, each stage provided important recommendations for the proper use of ML techniques on the protection problem. The proposed FD system was validated on the modified IEEE 13-nodes test feeder. This took into consideration typical features of microgrids such as the load imbalance, reconfiguration, and off-grid/on-grid operation modes. The results demonstrated the flexibility and simplicity of the FD system in determining the best accuracy performance among several ML models. The ease of design’s implementation, formulation of parameters, and promising test results indicated the potential for real-life applications.
publishDate	2020
dc.date.accessioned.none.fl_str_mv	2020-09-10T21:20:58Z
dc.date.available.none.fl_str_mv	2020-09-10T21:20:58Z
dc.date.issued.none.fl_str_mv	2020-03-06
dc.date.submitted.none.fl_str_mv	2020-09-03
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dc.identifier.citation.spa.fl_str_mv	Cepeda, C .; Orozco-Henao, C .; Percybrooks, W .; Pulgarín-Rivera, JD; Montoya, OD; Gil-González, W .; Vélez, JC Sistema inteligente de detección de fallas para microrredes. Energías 2020 , 13 , 1223.
dc.identifier.uri.none.fl_str_mv	https://hdl.handle.net/20.500.12585/9371
dc.identifier.url.none.fl_str_mv	https://www.mdpi.com/1996-1073/13/5/1223
dc.identifier.doi.none.fl_str_mv	10.3390/en13051223
dc.identifier.eissn.none.fl_str_mv	1996-1073
dc.identifier.instname.spa.fl_str_mv	Universidad Tecnológica de Bolívar
dc.identifier.reponame.spa.fl_str_mv	Repositorio Universidad Tecnológica de Bolívar
identifier_str_mv	Cepeda, C .; Orozco-Henao, C .; Percybrooks, W .; Pulgarín-Rivera, JD; Montoya, OD; Gil-González, W .; Vélez, JC Sistema inteligente de detección de fallas para microrredes. Energías 2020 , 13 , 1223. 10.3390/en13051223 1996-1073 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar
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dc.format.extent.none.fl_str_mv	21 páginas
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dc.publisher.place.spa.fl_str_mv	Cartagena de Indias
dc.publisher.discipline.spa.fl_str_mv	Ingeniería Electrónica
institution	Universidad Tecnológica de Bolívar
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spelling	Cepeda, Cristian0281547a-1c7a-4ab0-a0e2-60d485d2467dOrozco-Henao, Cesarb7606b9b-c12f-48d3-a4a0-23903e7dcfe6Percybrooks, Winstond5a4d0c2-3a12-4627-8e36-20768cd9795ePulgarín-Rivera, Juan Diegoa5c925f9-72b1-4693-940e-9328606393aaMontoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Gil-González, Walterce1f5078-74c6-4b5c-b56a-784f85e52a08Vélez, Juan Carlosa2c62bdd-ff1f-4ce9-b5d4-686660c1bc632020-09-10T21:20:58Z2020-09-10T21:20:58Z2020-03-062020-09-03Cepeda, C .; Orozco-Henao, C .; Percybrooks, W .; Pulgarín-Rivera, JD; Montoya, OD; Gil-González, W .; Vélez, JC Sistema inteligente de detección de fallas para microrredes. Energías 2020 , 13 , 1223.https://hdl.handle.net/20.500.12585/9371https://www.mdpi.com/1996-1073/13/5/122310.3390/en130512231996-1073Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe dynamic features of microgrid operation, such as on-grid/off-grid operation mode, the intermittency of distributed generators, and its dynamic topology due to its ability to reconfigure itself, cause misfiring of conventional protection schemes. To solve this issue, adaptive protection schemes that use robust communication systems have been proposed for the protection of microgrids. However, the cost of this solution is significantly high. This paper presented an intelligent fault detection (FD) system for microgrids on the basis of local measurements and machine learning (ML) techniques. This proposed FD system provided a smart level to intelligent electronic devices (IED) installed on the microgrid through the integration of ML models. This allowed each IED to autonomously determine if a fault occurred on the microgrid, eliminating the requirement of robust communication infrastructure between IEDs for microgrid protection. Additionally, the proposed system presented a methodology composed of four stages, which allowed its implementation in any microgrid. In addition, each stage provided important recommendations for the proper use of ML techniques on the protection problem. The proposed FD system was validated on the modified IEEE 13-nodes test feeder. This took into consideration typical features of microgrids such as the load imbalance, reconfiguration, and off-grid/on-grid operation modes. The results demonstrated the flexibility and simplicity of the FD system in determining the best accuracy performance among several ML models. The ease of design’s implementation, formulation of parameters, and promising test results indicated the potential for real-life applications.21 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Intelligent fault detection system for microgridsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Fault detectorMicrogridMachine learning-based techniquesCartagena de IndiasIngeniería ElectrónicaInvestigadoresAkorede, M.F.; Hizam, H.; Pouresmaeil, E. Distributed energy resources and benefits to the environment. Renew. Sustain. Energy Rev. 2010, 14, 724–734Chowdhury, S.; Chowdhury, P. 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