Modelo inteligente para la ubicación de fallas en líneas de distribución con generación distribuida

Autores/as

Diego Armando Giral Ramírez
Universidad Distrital Francisco José de Caldas
https://orcid.org/0000-0001-9983-4555
César Augusto Hernández Suárez
Universidad Distrital Francisco José de Caldas
https://orcid.org/0000-0001-9409-8341
José David Cortés Torres
Universidad Industrial de Santander
https://orcid.org/0000-0001-9232-6785

Palabras clave:

Fallas de baja impedancia, Generación distribuida, Red de distribución, Inteligencia artificial, Algoritmos avanzados

Sinopsis

Para asumir los retos de los nuevos sistemas eléctricos, se requiere incorporar estrategias avanzadas. En los últimos años se han propuesto técnicas para localizar fallas en líneas de distribución, en las que la inteligencia artificial ha mostrado buenos resultados por su alto rendimiento y capacidad para dar una respuesta rápida. No existe una solución óptima para el problema de ubicación de fallas; debido a la generalidad de la inteligencia artificial, no es posible caracterizar un algoritmo como la mejor estrategia para este problema. Aunque se han logrado avances prometedores, todavía quedan muchas preguntas por responder. El enfoque constante consiste en identificar los avances en inteligencia artificial para lograr resultados cada vez efectivos.

Capítulos

  • Introducción
  • 1. Fundamentos teóricos
  • 2. Diseño del modelo inteligente
  • 3. Software de simulación
  • 4. Evaluación del modelo inteligente
  • Conclusiones
  • Trabajo futuro

Descargas

Los datos de descarga aún no están disponibles.

Biografía del autor/a

Diego Armando Giral Ramírez, Universidad Distrital Francisco José de Caldas

Docente de planta de la Universidad Distrital Francisco José de Caldas, adscrito a los programas de Tecnología en Electricidad de Media y Baja Tensión e Ingeniería Eléctrica, de la Facultad Tecnológica. Ingeniero eléctrico de la Universidad Distrital Francisco José de Caldas, magíster en Ingeniería Eléctrica de la Universidad de los Andes y doctor en Ingeniería de la Universidad Distrital Francisco José de Caldas. Ha publicado libros de investigación y artículos en el área de sistemas de potencia y telecomunicaciones.

César Augusto Hernández Suárez, Universidad Distrital Francisco José de Caldas

Docente de planta de la Universidad Distrital Francisco José de Caldas, adscrito a los programas de Tecnología en Electricidad de Media y Baja Tensión e Ingeniería Eléctrica, de la Facultad Tecnológica, y al Doctorado en Ingeniería, de la Facultad de Ingeniería. Ingeniero eléctrico con especialización en Interconexión de Redes y magíster en Ciencias de la Información y las Comunicaciones de la Universidad Distrital Francisco José de Caldas; doctor en Ingeniería de la Universidad Nacional de Colombia. Ha publicado libros de investigación y artículos en el área de telecomunicaciones.

José David Cortés Torres, Universidad Industrial de Santander

Ingeniero eléctrico de la Universidad Distrital Francisco José de Caldas; magíster en Ingeniería Eléctrica y estudiante del Doctorado en Ingeniería de la Universidad Industrial de Santander. Profesor de la Universidad Industrial de Santander, adscrito al programa de Ingeniería Eléctrica de la Escuela de Ingenierías Eléctrica, Electrónica y de Telecomunicaciones. Ha publicado artículos en el área de sistemas de potencia.

Referencias

Adefarati, T. y Bansal, R. C. (2016). Integration of renewable distributed generators into the distribution system: A review. IET Renewable Power Generation, 10(7), 873-884.

Alwash, S. F., Ramachandaramurthy, V. K. y Mithulananthan, N. (2015). Fault-location scheme for power distribution system with distributed generation. IEEE Transactions on Power Delivery, 30(3), 1187-1195. https://doi.org/10.1109/TPWRD.2014.2372045 Aranha,C.,CamachoVillalón,C.L.,Campelo,F.,Dorigo,M.,Ruiz,R.,Sevaux,M.,Sörensen,K.yStützle,T.(2022).Metaphor-basedmetaheuristics,acallforaction:Theelephantintheroom.SwarmIntelligence,16(1),1-6.https://doi.org/10.1007/s11721-021-00202-9

Aslan, Y. y Yağan, Y. E. (2016, 30 de junio-2 de julio). ANN based fault location for medium voltage distribution lines with remote-end source [presentación en conferencia]. 2016 International Symposium on Fundamentals of Electrical Engineering (ISFEE), Bucarest, Rumania. https://doi.org/10.1109/ISFEE.2016.7803203

Bahmanyar, A., Jamali, S., Estebsari, A. y Bompard, E. (2017). A comparison framework for distribution system outage and fault location methods. Electric Power Systems Research, 145, 19-34. https://doi.org/10.1016/j.epsr.2016.12.018

Bao, W., Fang, Q., Wang, P., Yan, W. y Pan, P. (2021, 29-30 de mayo). A fault location method for active distribution network with DGs [presentación en conferencia]. International Conference on Smart Grid and Electrical Automation (ICSGEA), Kunming, China. https://doi.org/10.1109/ICSGEA53208.2021.00010

Bárcenas, D. y Rueda, J. (2021). Herramienta computacional para la localización de fallas en líneas de transmisión usando teoría de ondas viajeras [tesis de pregrado, Universidad del Norte]. DSpace UniNorte. http://hdl.handle.net/10584/11244 Barja-Martinez, S., Aragüés-Peñalba, M., Munné-Collado, Í., LloretGallego, P., Bullich-Massagué, E. y Villafafila-Robles, R. (2021). Artificial intelligence techniques for enabling Big Data services in distribution networks: A review. Renewable and Sustainable Energy Reviews, 150, artículo 111459. https://doi.org/https://doi.org/10.1016/j.rser.2021.111459 Beheshtaein,S.,Cuzner,R.,Savaghebi,M.,Golestan,S.yGuerrero,J.M.(2019).Faultlocationinmicrogrids:Acommunication-basedhigh-frequencyimpedanceapproach.IETGenerationTransmission&Distribution,13(8,SI),1229-1237.https://doi.org/10.1049/iet-gtd.2018.5166

Bkassiny, M., Li, Y. y Jayaweera, S. K. (2013). A survey on machinelearning techniques in cognitive radios. IEEE Communications Surveys & Tutorials, 15(3), 1136-1159. https://doi.org/10.1109/SURV.2012.100412.00017

Bozorg-Haddad, O. (ed.). (2018). Advanced optimization by nature-inspired algorithms (vol. 720). Springer. https://doi.org/10.1007/978-981-10-5221-7 Cadena,A.,Lozano,F.,Quijano,N.,Ramos,G.,Ríos,M.,Gordillo,G.,Torres,H.yLatorre,G.(2011).Redesinteligentesygeneracióndistribuida.UniversidaddelosAndes.Chang,K.-C.,Zhang,R.,Deng,H.,Chang,F.-H.,Wang,H.-C.yAmesimenu,G.D.K.(2022).ChaoticparticleswarmoptimizationalgorithmforfaultlocationofdistributionnetworkwithDGBT.EnA.E.Hassanien,V.Snášel,K.-C.Chang,A.DarwishyT.Gaber(eds.),InternationalConferenceonAdvancedIntelligentSystemsandInformatics(pp.256-266).SpringerInternationalPublishing.

Chaudhary, R., Sethi, S., Keshari, R. y Goel, S. (2012). A study of comparison of Network Simulator-3 and Network Simulator-2. International Journal of Computer Science and Information Technologies, 3(1), 3085-3092.

Chen, J., Chu, E., Li, Y., Yun, B., Dang, H. y Yang, Y. (2020). Faulty feeder identification and fault area localization in resonant grounding system based on wavelet packet and bayesian classifier. Journal of Modern Power Systems and Clean Energy, 8(4), 760-767. https://doi.org/10.35833/MPCE.2019.000051

Chen, X. y Jiao, Z. (2018, 17-19 de septiembre). Accurate fault location method of distribution network with limited number of PMUs [presentación en conferencia]. 2018 China International Conference on Electricity Distribution (CICED), Tianjin, China. https://doi.org/10.1109/CICED.2018.8592074

Chicco, G. y Mazza, A. (2019). 100 years of symmetrical components. Energies, 12(3), 450.

Chih, H.-C., Lin, W.-C., Huang, W.-T. y Yao, K.-C. (2022). Implementation of EDGE computing platform in feeder terminal unit for smart applications in distribution networks with distributed renewable energies. Sustainability, 14(20), artículo 13042. https://doi.org/10.3390/su142013042

Cikan, M. y Cikan, N. N. (2023). Optimum allocation of multiple type and number of DG units based on IEEE 123-bus unbalanced multi-phase power distribution system. International Journal of Electrical Power & Energy Systems, 144, artículo 108564. https://doi.org/https://doi.org/10.1016/j.ijepes.2022.108564

Dadary, S. y Afrakhte, H. (2017). Accuracy improvement of impedancebased fault locating method in distribution systems with DGs considering loss of laterals and load variations. International Transactions on Electrical Energy Systems, 27(11), artículo e2420. https://doi.org/10.1002/etep.2420

Dagenhart, J. (1999, 2-4 de mayo). The 40-ohm ground fault phenomenon [presentación en conferencia]. 1999 Rural Electric Power Conference (Cat. No. 99CH36302), Indianapolis, Estados Unidos. https://doi.org/10.1109/REPCON.1999.768690

Darab, C., Tarnovan, R., Turcu, A. y Martineac, C. (2019, 21-23 de mayo). Artificial intelligence techniques for fault location and detection in distributed generation power systems [presentación en conferencia]. 2019 8th International Conference on Modern Power Systems (MPS), Cluj-Napoca, Rumania. https://doi.org/10.1109/MPS.2019.8759662

Das, J. C. (2016). Understanding symmetrical components for power system modeling. John Wiley & Sons.

Das, S., Santoso, S. y Ananthan, S. N. (2021). Fault location on transmission and distribution lines: Principles and applications. John Wiley & Sons. De las Casas, M. B., Quintero, H. R., Sosa, I. O., Morales, D. S. y Mendoza, L. E. L. (2009). Influencia de la generación distribuida en los niveles de cortocircuito y en las protecciones eléctricas en subestaciones de 110/34, 5 kV. Ingeniería Energética, 30(1).

De Mársico, M. C., Scardamaglia, R. C. y Reboreda, J. C. (2020). Aves que parasitan nidos ajenos. Ciencia Hoy, 29(169), 49-55.

Dey, N. (2020). Applications of cuckoo search algorithm and its variants. Springer.

Farughian, A., Kumpulainen, L. y Kauhaniemi, K. (2018). Review of methodologies for earth fault indication and location in compensated and unearthed MV distribution networks. Electric Power Systems Research, 154, 373-380. https://doi.org/10.1016/j.epsr.2017.09.006

Fei, W. y Moses, P. (2019). Fault current tracing and identification via machine learning considering distributed energy resources in distribution networks. Energies, 12(22), artículo 4333. https://doi.org/10.3390/en12224333

Fortescue, C. L. (1918). Method of symmetrical co-ordinates applied to the solution of polyphase networks. Transactions of the American Institute of Electrical Engineers, 37(2), 1027-1140.

Gana, N., Ab Aziz, N. F., Ali, Z., Hashim, H. y Yunus, B. (2017). A comprehensive review of fault location methods for distribution power system. Indonesian Journal of Electrical Engineering and Computer Science, 6(1). https://doi.org/10.11591/ijeecs.v6.i1.pp185-192

Gao, S., Zhou, M., Wang, Y., Cheng, J., Yachi, H. y Wang, J. (2019). Dendritic neuron model with effective learning algorithms for classification, approximation, and prediction. IEEE Transactions on Neural Networks and Learning Systems, 30(2), 601-614. https://doi.org/10.1109/TNNLS.2018.2846646

Gaonkar, D. (ed.). (2010). Distributed generation. InTech. García-Martínez, C., Gutiérrez, P. D., Molina, D., Lozano, M. y Herrera, F. (2017). Since CEC 2005 competition on real-parameter optimisation: A decade of research, progress and comparative analysis’s weakness. Soft Computing, 21(19), 5573-5583. https://doi.org/10.1007/s00500-016-2471-9

Giral-Ramírez, D. (2022). Intelligent fault location algorithms for distributed generation distribution networks: A review. Przegląd Elektrotechniczny, 1(7), 139-146. https://doi.org/10.15199/48.2022.07.23 Goh,H.H.,Sim,S.Y.,Mohamed,M.A.H.,Rahman,A.K.A.,Ling,C.W.,Chua,Q.S.yGoh,K.C.(2017).Faultlocationtechniquesinelectricalpowersystem:Areview.IndonesianJournalofElectricalEngineeringandComputerScience,8(1),206-212.

González, D. (2014). Sobretensiones debidas a cortocircuitos fase-tierra en redes de media tensión para distintos regímenes de neutro. Universidad de Sevilla.

Hashemi, A., Dowlatshahi, M. B. y Nezamabadi-Pour, H. (2021). Gravitational search algorithm: Theory, literature review, and applications. Handbook of AI-Based Metaheuristics, 119-150.

He, X., Qian, Q., Wang, Y., Wang, Y. y Shi, S. (2018, 20-22 de octubre). Adaptive traveling waves based protection of distribution lines [presentación en conferencia]. 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2), Pekín, China. https://doi.org/10.1109/EI2.2018.8582627

Hernández, C., Giral, D. y Marquez, H. (2017). Evolutive algorithm for spectral handoff prediction in cognitive wireless networks. Contemporary Engineering Sciences, 10(14), 673-689. https://doi.org/10.12988/ces.2017.7766

Hernández-Sampieri, R., Fernández-Collado, C. y Baptista, P. (2006). Metodología de la investigación. McGraw-Hill.

Huang, X., Xie, Z. y Huang, X. (2020). Fault location of distribution network base on improved cuckoo search algorithm. IEEE Access, 8, 2272-2283. https://doi.org/10.1109/ACCESS.2019.2962276

Hui, Y., Yan, X., Bin, Q. y Qi, W. (2019, 10-13 de mayo). Fault location method for DC distribution network based on particle swarm optimization [presentación en conferencia]. 2019 IEEE 2nd International Conference on Electronics Technology (ICET), Chengdú, China. https://doi.org/10.1109/ELTECH.2019.8839476 Ibrahim,K.S.M.H.,Huang,Y.F.,Ahmed,A.N.,Koo,C.H.yElShafie,A.(2021).Areviewofthehybridartificialintelligenceandoptimizationmodellingofhydrologicalstreamflowforecasting.AlexandriaEngineeringJournal,61(1),279-303.

Ibrahim, M. S., Dong, W. y Yang, Q. (2020). Machine learning driven smart electric power systems: Current trends and new perspectives. Applied Energy, 272, artículo 115237. https://doi.org/https://doi.org/10.1016/j.apenergy.2020.115237

IEEE. (2009). IEEE application guide for IEEE Std 1547(TM), IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems. En IEEE Std 1547.2-2008 (pp. 1-217). https://doi.org/10.1109/IEEESTD.2008.4816078

IEEE. (2015). Guide for determining fault location on AC transmission and distribution lines. En C37.114-2014 (pp. 1-76). https://doi.org/https://doi.org/10.1109/IEEESTD.2015.7024095

IEEE. (2018). IEEE Standard for Interconnection and Interoperability of Distributed Energy Resources with Associated Electric Power Systems Interfaces. En IEEE Std 1547-2018 (revision of IEEE Std 15472003) (pp. 1-138). https://doi.org/10.1109/IEEESTD.2018.8332112

IEEE. (2019). IEEE recommended practice for conducting short-circuit studies and analysis of industrial and commercial power systems. En IEEE Std 3002.3-2018 (pp. 1-184). https://doi.org/10.1109/IEEESTD.2019.8672198

IEEE. (2022). IEEE PES Test Feeder. https://cmte.ieee.org/pes-testfeeders/ resources/

International Electrotechnical Commission. (2016). IEC 60909-0:2016. Short-circuit currents in three-phase a.c. systems. https://webstore.iec.ch/ publication/24100

Jenkins, N., Ekanayake, J. y Strbac, G. (2014). Distributed generation. IET.

Jiang, B., Dong, X., Shi, S. y Wang, B. (2015, 26-30 de julio). Fault line identification of single line to ground fault for non-effectively grounded distribution networks with double-circuit lines [presentación en conferencia]. IEEE Power and Energy Society General Meeting, Denver, Estados Unidos. https://doi.org/10.1109/PESGM.2015.7286346

Jin, Q. y Ju, R. (2012, 27-30 de julio). Fault location for distribution network based on genetic algorithm and stage treatment [presentación en conferencia]. 2012 Spring Congress on Engineering and Technology, Denver, Estados Unidos. https://doi.org/10.1109/PESGM.2015.7286346

Kaur, A., Kaur, A. y Sharma, S. (2018, 22-23 de febrero). Cognitive decision engine design for CR based IoTs using differential evolution and bat algorithm [presentación en conferencia]. 2018 5th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India. https://doi.org/10.1109/SPIN.2018.8474273 Khaleghi,A.,OukatiSadegh,M.,Ghazizadeh-Ahsaee,M.yMehdipourRabori,A.(2018).Transientfaultarealocationandfaultclassificationfordistributionsystemsbasedonwavelettransformandadaptiveneuro-fuzzyinferencesystem(ANFIS).AdvancesinElectricalandElectronicEngineering,16(2),155-166.https://doi.org/10.15598/aeee.v16i2.2563

Kumar, R. y Saxena, D. (2020). A literature review on methodologies of fault location in the distribution system with distributed generation. Energy Technology, 8(3), artículo 1901093. https://doi.org/https://doi.org/10.1002/ente.201901093

Lala, H., Karmakar, S. y Ganguly, S. (2019). Detection and localization of faults in smart hybrid distributed generation systems: A Stockwell transform and artificial neural network-based approach. International Transactions on Electrical Energy Systems, 29(2), artículo e2725. https://doi.org/10.1002/etep.2725

Li, J., Liu, Y., Li, C., Zeng, D., Li, H. y Wang, G. (2022). An FTU-based method for locating single-phase high-impedance faults using transient zero-sequence admittance in resonant grounding systems. IEEE Transactions on Power Delivery, 37(2), 913-922. https://doi.org/10.1109/TPWRD.2021.3074217

Li, W., Su, J., Wang, X., Li, J. y Ai, Q. (2020). Fault location of distribution networks based on multi-source information. Global Energy Interconnection, 3(1), 76-84. https://doi.org/https://doi.org/10.1016/j.gloei.2020.03.005

Li, Y., Shen, H. y Wang, M. (2016, 6-10 de noviembre). Optimization spectrum decision parameters in CR using autonomously search algorithm [presentación en conferencia]. International Conference on Signal Processing (ICSP), Chengdú, China. https://doi.org/10.1109/ICSP.2016.7878007

Lin, W.-C., Huang, W.-T., Yao, K.-C., Chen, H.-T. y Ma, C.-C. (2021). Fault location and restoration of microgrids via particle swarm optimization. Applied Sciences, 11(15), artículo 7036. https://doi.org/10.3390/app11157036

Long, C., Zhang, H., Shi, Y., Guo, R. y Dong, L. (2022). An optimal meter placement method based on virtual flow. Proceedings of the Asia Conference on Electrical, Power and Computer Engineering, 63, 1-5. https://doi.org/10.1145/3529299.3533394

Madani, V., Das, R. y Meliopoulos, A. P. (2017, 21-23 de diciembre). Active distribution network and microgrid integration strategy [presentación en conferencia]. 2017 7th International Conference on Power Systems (ICPS), Pune, India. https://doi.org/10.1109/ICPES.2017.8387348 Maruf,H.M.M.,Müller,F.,Hassan,M.S.yChowdhury,B.(2018,2528dejunio).Locatingfaultsindistributionsystemsinthepresenceofdistributedgenerationusingmachinelearningtechniques[presentaciónenconferencia].20189thIEEEInternationalSymposiumonPowerElectronicsforDistributedGenerationSystems(PEDG),Charlotte,EstadosUnidos.https://doi.org/10.1109/PEDG.2018.8447728

Mejdi, L., Kardous, F. y Grayaa, K. (2022). Impact analysis and optimization of EV charging loads on the LV grid: A case study of workplace parking in Tunisia. Energies, 15(19), artículo 7127. https:// doi.org/10.3390/en15197127

Mer, D. K. y Patel, R. R. (2016, 3-5 de marzo). The concept of distributed generation & the effects of its placement in distribution network [presentación en conferencia]. 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, India. https://doi.org/10.1109/ICEEOT.2016.7755458

Mora Flórez, J. J. y Pérez Londoño, S. M. (2016). Localización de fallas de baja impedancia en sistemas de distribución de energía eléctrica, a partir del fundamental de tensión y corriente. Universidad Tecnológica de Pereira.

Moreno, S. R., Pierezan, J., Coelho, L. dos S. y Mariani, V. C. (2021). Multi-objective lightning search algorithm applied to wind farm layout optimization. Energy, 216, artículo 119214. https://doi.org/ https://doi.org/10.1016/j.energy.2020.119214

Na, W., Yan-jun, J. y Jian-tao, Y. (2008, 9-12 de noviembre). Fault location of distribution network based on plant growth simulation algorithm [presentación en conferencia]. 2008 International Conference on High Voltage Engineering and Application, Chongqing, China. https://doi.org/10.1109/ICHVE.2008.4774003

Naghizadeh, R., Afrakhte, H. y Ziapour, M. (2018, 8-10 de mayo). Smart distribution network reconfiguration based on optimal planning of distributed generation resources using teaching learning based algorithm to reduce generation costs, losses and improve reliability [presentación en conferencia]. Iranian Conference On Electrical Engineering (ICEE), Mashhad, Irán. https://doi.org/10.1109/ICEE.2018.8472451

Nuthalapati, B. y Sinha, U. K. (2019). Fault detection and location of broken power line not touching the ground. International Journal of Emerging Electric Power Systems, 20(3), 2-11. https://doi.org/10.1515/ijeeps-2018-0321

Primadianto, A. y Lu, C.-N. (2017). A review on distribution system state estimation. IEEE Transactions on Power Systems, 32(5), 3875-3883. https://doi.org/10.1109/TPWRS.2016.2632156

Priya, G. S. y Geethanjali, M. (2018, 9-10 de marzo). Design and development of distance protection scheme for wind power distributed generation [presentación en conferencia]. 2018 National Power Engineering Conference (NPEC), Madurai, India. https://doi.org/10.1109/NPEC.2018.8476720

Rashedi, E., Nezamabadi-pour, H. y Saryazdi, S. (2010). BGSA: Binary gravitational search algorithm. Natural Computing, 9(3), 727-745. https://doi.org/10.1007/s11047-009-9175-3 Schneider,K.P.,Mather,B.A.,Pal,B.C.,Ten,C.-W.,Shirek,G.J.,Zhu,H.,Fuller,J.C.,Pereira,J.L.R.,Ochoa,L.F.,DeAraujo,L.R.,Dugan,R.C.,Matthias,S.,Paudyal,S.,McDermott,T.E.yKersting,W.(2018).AnalyticconsiderationsanddesignbasisfortheIEEEdistributiontestfeeders.IEEETransactionsonPowerSystems,33(3),3181-3188.https://doi.org/10.1109/TPWRS.2017.2760011

Shareef, H., Ibrahim, A. A. y Mutlag, A. H. (2015). Lightning search algorithm. Applied Soft Computing, 36, 315-333. https://doi.org/ https://doi.org/10.1016/j.asoc.2015.07.028

Sharifzadeh, A., Ameli, M. T. y Azad, S. (2021). Power system challenges and issues. En M. Nazari-Heris, S. Asadi, B. Mohammadi-Ivatloo, M. Abdar, H. Jebelli y M. Sadat-Mohammadi (eds.), Application of machine learning and deep learning methods to power system problems (pp. 1-17). Springer.

Sharma, R., Mahela, O. P. y Agarwal, S. (2018, 24-25 de febrero). Detection of power system faults in distribution system using Stockwell transform [presentación en conferencia]. 2018 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), Bhopal, India. https://doi.org/10.1109/SCEECS.2018.8546879 Shi,Y.,Sagduyu,Y.E.,Erpek,T.,Davaslioglu,K.,Lu,Z.yLi,J.H.(2018,20-24demayo).Adversarialdeeplearningforcognitiveradiosecurity:Jammingattackanddefensestrategies[presentaciónenconferencia].2018IEEEInternationalConferenceonCommunicationsWorkshops(ICCWorkshops),Kansas,EstadosUnidos.https://doi.org/10.1109/ICCW.2018.8403655 Sifat,A.I.,McFadden,F.S.,Ahmed,A.,Rayudu,R.yHunzel,A.(2017,4-7dediciembre).Feasibilityofmagneticsignature-baseddetectionoflowandhighimpedancefaultsinlow-voltagedistributionnetworks[presentaciónenconferencia].2017IEEEInnovativeSmartGridTechnologies-Asia(ISGT-Asia),Auckland,NuevaZelanda.https://doi.org/10.1109/ISGT-Asia.2017.8378472

Sonoda, D., De Souza, A. C. Z. y Da Silveira, P. M. (2018). Fault identification based on artificial immunological systems. Electric Power Systems Research, 156, 24-34. https://doi.org/https://doi.org/10.1016/j.epsr.2017.11.012

Sörensen, K. (2015). Metaheuristics—the metaphor exposed. International Transactions in Operational Research, 22(1), 3-18.

Srinivasa Rao, T. C., Tulasi Ram, S. S. y Subrahmanyam, J. B. V. (2019). Fault signal recognition in power distribution system using deep belief network. Journal of Intelligent Systems, 29(1), 459-474. https://doi.org/10.1515/jisys-2017-0499

Steinberg, J. (2003). Cebras: nacidas para migrar. National Geographic, 12(9), 30-43.

Strezoski, L., Stefani, I. y Brbaklic, B. (2019, 1-4 de julio). Active management of distribution systems with high penetration of distributed energy resources [presentación en conferencia]. IEEE EUROCON 2019. 18th International Conference on Smart Technologies, Novi Sad, Serbia. https://doi.org/10.1109/EUROCON.2019.8861748

Sun, H., Yi, H., Zhuo, F., Du, X. y Yang, G. (2020). Precise fault location in distribution networks based on optimal monitor allocation. IEEE Transactions on Power Delivery, 35(4), 1788-1799. https://doi.org/10.1109/TPWRD.2019.2954460

Sun, Z., Wang, Q. y Wei, Z. (2021). Fault location of distribution network with distributed generations using electrical synaptic transmissionbased spiking neural P systems. International Journal of Parallel, Emergent and Distributed Systems, 36(1), 11-27. https://doi.org/10.1080/17445760.2019.1682145

Tao, F., Zhang, L. y Laili, Y. (2016). Configurable intelligent optimization algorithm. Springer.

Tao, W., Yang, G. y Zhang, J. (2016, 22-26 de mayo). Fault section locating for distribution network with DG based on improved ant colony algorithm [presentación en conferencia]. 2016 IEEE 8th International Power Electronics and Motion Control Conference (IPEMC-ECCE Asia), Hefei, China. https://doi.org/10.1109/IPEMC.2016.7512600

Tashakkori, A., Wolfs, P. J., Islam, S. y Abu-Siada, A. (2020). Fault location on radial distribution networks via distributed synchronized traveling wave detectors. IEEE Transactions on Power Delivery, 35(3), 1553-1562. https://doi.org/10.1109/TPWRD.2019.2948174

Tleis, N. (2019). Power systems modelling and fault analysis: Theory and Practice. Academic Press.

Torres, H. (2002). El rayo: mitos, leyendas, ciencia y tecnología. Universidad Nacional de Colombia.

Trojovská, E., Dehghani, M. y Trojovský, P. (2022). Zebra optimization algorithm: A new bio-inspired optimization algorithm for solving optimization algorithm. IEEE Access, 10, 49 445-49 473. https://doi.org/10.1109/ACCESS.2022.3172789 Trujillo,C.L.,Santamaría,F.,Hernández,J.A.,Jaramillo,A.A.,Gaona,E.E.,Rivas,E.,Flórez,O.D.,Rodriguez,D.J.,Alarcón,J.A.yRojas,H.E.(2015).Microrredeseléctricas.EditorialUD.UnidaddePlaneaciónMineroEnergética,UniversidadNacionaldeColombiayUniversidaddelValle.(2018).ObservatorioColombianodeEnergía:aproximaciónalascondicionesparasuconformación.

Vasuki, A. (2020). Nature-inspired optimization algorithms. CRC Press.

Vaziri, M., Vadhva, S., Oneal, T. y Johnson, M. (2011, 3-5 de agosto). Distributed generation issues, and standards [presentación en conferencia]. 2011 IEEE International Conference on Information Reuse & Integration, Las Vegas, Estados Unidos. https://doi.org/10.1109/IRI.2011.6009588 Veerasamy,V.,AbdulWahab,N.I.,Ramachandran,R.,Thirumeni,M.,Subramanian,C.,Othman,M.L.yHizam,H.(2019).Highimpedancefaultdetectioninmedium-voltagedistributionnetworkusingcomputationalintelligence-basedclassifiers.NeuralComputingandApplications,31(12),9127-9143.https://doi.org/10.1007/s00521-019-04445-w

Wang, X., Yu, X., Xue, Y., Zhu, Y. y Fu, J. (2018). Application of improved quantum genetic algorithm in fault location of distribution network. En B. Xu (ed.), Proceedings of 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC 2018) (pp. 2524-2529). IEEE.

Wang, X.-F., Song, Y. e Irving, M. (2010). Modern power systems analysis. Springer Science & Business Media.

Wolpert, D. H. y Macready, W. G. (1997). No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1), 6782. https://doi.org/10.1109/4235.585893

Xiong, G., Yuan, X., Mohamed, A. W., Chen, J. y Zhang, J. (2022). Improved binary gaining-sharing knowledge-based algorithm with mutation for fault section location in distribution networks. Journal of Computational Design and Engineering, 9(2), 393-405. https://doi.org/10.1093/jcde/qwac007

Yang, H., Guo, Y. y Liu, X. (2020). Fault section location of active distribution network based on wolf pack and differential evolution algorithms. International Journal of Performability Engineering, 16(1), 143-151.

Yang, X.-S. y Deb, S. (2010). Engineering optimisation by cuckoo search. International Journal of Mathematical Modelling and Numerical Optimisation, 1(4), 330-343.

Yellagoud, S. K. y Talluri, P. R. (2018, 27-28 de octubre). Assessment of fault location methods for electric power distribution networks [presentación en conferencia]. 2018 4th International Conference for Convergence in Technology (I2CT), Mangalore, India. https://doi.org/10.1109/I2CT42659.2018.9058148Yem Souhe,F.G.,Boum,A.T.,Ele,P.,Mbey,C.F.yFobaKakeu,V.J.(2022).Anovelsmartmethodforstateestimationinasmartgridusingsmartmeterdata.AppliedComputationalIntelligenceandSoftComputing,2022(1),1-14.https://doi.org/10.1155/2022/7978263

Yu, D. C. y Khan, S. H. (1994). An adaptive high and low impedance fault detection method. IEEE Transactions on Power Delivery, 9(4), 1812-1821.

Zhang, B., Liu, H., Song, J. y Zhang, J. (2019, 3-5 de enero). Simulation on grounding fault location of distribution network based on regional parameters [presentación en conferencia]. International Symposium on High Assurance Systems Engineering (HASE), Hangzhou, China.

Zhang, T., Yu, H., Zeng, P., Sun, L., Song, C. y Liu, J. (2020). Single phase fault diagnosis and location in active distribution network using synchronized voltage measurement. International Journal of Electrical Power & Energy Systems, 117. https://doi.org/10.1016/j.ijepes.2019.105572 Zhao,D.,Chen,Y.,Wang,Y.,Zhao,Y.,Fu,Z.,Du,J.,Wang,L.,Cheng,R.,Zhen,Y.,Zhang,H.,Zhou,Y.yRen,Q.(2022).ElectromagneticthermalanalysisofFTUunderthehigh-powerelectromagneticenvironment.Electronics,11(16),artículo2528.https://doi.org/10.3390/electronics11162528

Zhao, M. y Zhang, Y.-F. (2020). Fault section location for distribution network containing DG based on IBQPSO. Journal of Computational Methods in Sciences and Engineering, 20(3), 937-949.

Descargas

Publicado

April 7, 2025

Licencia

Creative Commons License

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.

Detalles sobre el formato de publicación disponible: Formato físico

Formato físico

ISBN-13 (15)

978-958-787-750-2

Dimensiones físicas

Detalles sobre el formato de publicación disponible: PDF

PDF

ISBN-13 (15)

978-958-787-751-9
Loading...