Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo
ilustraciones, graficas
- Autores:
-
Morgado, Kevin
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/81490
- Palabra clave:
- 620 - Ingeniería y operaciones afines
Transformadores eléctricos
Electric transformers
Gestión de Activos
Transformadores de Potencia
Ciclo de Vida
Asset Management
Power Transformers
Life Cycle
Consumo de energía
Energy consumption
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| id |
UNACIONAL2_5bdfec564280e82a3469eca4c5f0f4bb |
|---|---|
| oai_identifier_str |
oai:repositorio.unal.edu.co:unal/81490 |
| network_acronym_str |
UNACIONAL2 |
| network_name_str |
Universidad Nacional de Colombia |
| repository_id_str |
|
| dc.title.spa.fl_str_mv |
Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo |
| dc.title.translated.eng.fl_str_mv |
Development of an asset management technique for distribution transformers based on a monitoring system |
| title |
Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo |
| spellingShingle |
Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo 620 - Ingeniería y operaciones afines Transformadores eléctricos Electric transformers Gestión de Activos Transformadores de Potencia Ciclo de Vida Asset Management Power Transformers Life Cycle Consumo de energía Energy consumption |
| title_short |
Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo |
| title_full |
Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo |
| title_fullStr |
Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo |
| title_full_unstemmed |
Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo |
| title_sort |
Desarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreo |
| dc.creator.fl_str_mv |
Morgado, Kevin |
| dc.contributor.advisor.none.fl_str_mv |
Rosero Garcia, Javier |
| dc.contributor.author.none.fl_str_mv |
Morgado, Kevin |
| dc.contributor.researchgroup.spa.fl_str_mv |
Electrical Machines & Drives, Em&D |
| dc.subject.ddc.spa.fl_str_mv |
620 - Ingeniería y operaciones afines |
| topic |
620 - Ingeniería y operaciones afines Transformadores eléctricos Electric transformers Gestión de Activos Transformadores de Potencia Ciclo de Vida Asset Management Power Transformers Life Cycle Consumo de energía Energy consumption |
| dc.subject.other.spa.fl_str_mv |
Transformadores eléctricos |
| dc.subject.other.eng.fl_str_mv |
Electric transformers |
| dc.subject.proposal.spa.fl_str_mv |
Gestión de Activos Transformadores de Potencia Ciclo de Vida |
| dc.subject.proposal.eng.fl_str_mv |
Asset Management Power Transformers Life Cycle |
| dc.subject.unesco.spa.fl_str_mv |
Consumo de energía |
| dc.subject.unesco.eng.fl_str_mv |
Energy consumption |
| description |
ilustraciones, graficas |
| publishDate |
2022 |
| dc.date.accessioned.none.fl_str_mv |
2022-06-02T16:29:53Z |
| dc.date.available.none.fl_str_mv |
2022-06-02T16:29:53Z |
| dc.date.issued.none.fl_str_mv |
2022 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
| status_str |
acceptedVersion |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/81490 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
| url |
https://repositorio.unal.edu.co/handle/unal/81490 https://repositorio.unal.edu.co/ |
| identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.relation.references.spa.fl_str_mv |
A. Doolgindachbaporn, G. Callender, P. Lewin, E. A. Simonson, and G. Wilson, “Data Driven Transformer Thermal Model for Condition Monitoring,” IEEE Transactions on Power Delivery, pp. 1–9, 2021. [Online]. Available: https://ieeexplore.ieee.org/document/9599483/ I. Soltanbayev, M. Bagheri, and T. Phung, “Real-time dry-type transformer aging evaluation,” Proceedings of the International Symposium on Electrical Insulating Materials, vol. 2, pp. 551–554, 2017. M. A. Mehmood, J. Li, F. Wang, Z. Huang, J. Ahmad, and M. Shoaib Bhutta, “Analyzing the health condition and chemical degradation in field aged transformer insulation oil using spectroscopic techniques,” 2018 International Conference on Diagnostics in Electrical Engineering, Diagnostika 2018, pp. 1–4, 2018. Z. Chunming, X. Wenxie, and D. Zhaohong, “Transformer Oil-Paper Insulation Aging Evaluation System Based on Different Aging Characteristics,” 2021 6th International Conference on Control, Robotics and Cybernetics (CRC), pp. 181–185, 2021. [Online]. Available: https://ieeexplore.ieee.org/document/9620125/ H. Gumilang, “Cost and Benefit Analysis on Treatment Method of Aged Power Transformer Insulating Oil,” 2021 3rd International Conference on High Voltage Engineering and Power Systems (ICHVEPS), pp. 203–206, 2021. [Online]. Available:https://ieeexplore.ieee.org/document/9600996/ Y. Wang, W. Wei, P. Xue, and B. Yan, “Analysis on comprehensive fault rate of oil-immersed power transformer based on FTA,” 2021 International Conference on Electronic Information Engineering and Computer Science (EIECS), pp. 972–975, 2021. [Online]. Available: https://ieeexplore.ieee.org/document/9588025/ J. Chen, Z. Yin, X. Cheng, and Y. Liu, “Big data analysis based identification method of low-voltage substation area,” Proceedings - 2021 2nd International Conference on Big Data and Informatization Education, ICBDIE 2021, pp. 169–172, 2021. Z. Y. Zheng, Z. Li, S. F. Yu, D. F. Ke, Z. J. Lao, J. Q. Lin, and J. J. Chen, “A new capacity inspection method for distribution transformer based on big data,” China International Conference on Electricity Distribution, CICED, pp. 38–41, 2018. G. P. Zheng, Z. Y. Hou, and X. N. Yin, “Research of the agent technology based on multi-thread in transformer substation communication,” Proceedings of the 2006 International Conference on Machine Learning and Cybernetics, vol. 2006, pp. 56–60, 2006. S. Tellez, D. Alvarez, W. Montano, C. Vargas, R. Cespedes, E. Parra, and J. Rosero, “National Laboratory of Smart Grids (LAB+i) at the National University of Colombia- Bogotá Campus,” in 2014 IEEE PES Transmission and Distribution Conference and Exposition, PES T and D-LA 2014 - Conference Proceedings, vol. 2014-Octob. Institute of Electrical and Electronics Engineers Inc., 2014, pp. 1–6. W. M. Salamanca, D. L. Álvarez, J. A. García, J. S. Marín, and E. Gómez-Luna, “State Estimator Assessment Platform in Distribution Systems with Advanced Metering Infrastructure and Distributed Generation using Real Time Simulations,” in 2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1–6. A. F. Cerón, I. F. Orduña, G. Aponte, and A. A. Romero, “Panorama de la gestión de activos para transformadores de potencia,” Informacion Tecnologica, vol. 26, no. 3, pp. 99–110, 2015. International Organization for Standardization, “ISO 55000: Asset Management-Overview, Principles and Terminology,” 2014. J. Woodhouse, “Briefing: Standards in asset management: PAS 55 to ISO 55000,” Infrastructure Asset Management, vol. 1, no. 3, pp. 57–59, 2014. A. Attwater, J. Q. Wang, A. Parlikad, and P. Russell, “Measuring the performance of asset management systems,” IET Conference Publications, vol. 1, no. CP642, 2014. D. Zhou, C. Li, and Z. Wang, “Power transformer lifetime modeling,” in Proceedings of IEEE 2012 Prognostics and System Health Management Conference, PHM-2012, 2012, pp. 1–7. A. Azmi, J. Jasni, N. Azis, and M. Z. Kadir, “Evolution of transformer health index in the form of mathematical equation,” Renewable and Sustainable Energy Reviews, vol. 76, pp. 687–700, 2017. G. R. Steeves, “Transformer lifecycle: Power transformer asset management,” Transformers Magazine, vol. 3, no. 2, pp. 52–56, 2016. [Online]. Available: https://hrcak.srce.hr/167406 C. Liu, G. Huang, K. Zhang, F. Wen, M. A. Salam, and S. P. Ang, “Asset management in power systems,” in IET Seminar Digest. Institution of Engineering and Technology, 2015, pp. 1–5. J. L. Deng, “Introduction to Grey system theory,” Journal of Grey System, vol. 1, no. 1, pp. 1–24, 1989. T. Suwnansri, “Asset management of power transformer: Optimization of operation and maintenance costs,” in 2014 International Electrical Engineering Congress, iEECON 2014. Institute of Electrical and Electronics Engineers Inc., 2014. A. Babizki, M. Foata, K. Lindl, D. Beerboom, E. Pawlowski, M. Zdrallek, R. Funk, and J. Linossier, “Practical approach for fleet management of transformers considering different stakeholders’ perspectives,” 4th International Colloquium ”Transformer Research and Asset Management”, 2017. R. D. Medina, A. A. Romero, E. E. Mombello, and G. Ratta, “Assessing degradation of power transformer solid insulation considering thermal stress and moisture variation,” Electric Power Systems Research, vol. 151, pp. 1–11, 2017. I. Karatzas and S. E. Shreve, “Brownian Motion,” in Brownian Motion and Stochastic Calculus. Springer, 1998, pp. 47–127. A. A. Romero-Quete, H. D. Gómez, J. D. Molina, and G. Moreno, “Método práctico para la evaluación de riesgo en parques de transformadores de potencia,” DYNA (Colombia), vol. 84, no. 200, pp. 11–18, 2017. A. A. Romero, E. E. Mombello, and G. Ratta, “An overview on power transformer management: Individual Assets and Fleets,” in 2012 Sixth IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T D-LA), 2012, pp. 1–7. P. Boss, J. Patelli, and J. Aubin, “Guide on economics of transformer management,” pp. 1–67, 2004. W. H. Bartley, P. E. Hartford, and S. Boiler, “Life Cycle Management of Utility Transformer Assets Breakthrough Asset Management for the Restructured Power Industry Life Cycle Management of Utility Transformer Assets,” Hartford Steam Boiler Inspection & Insurance Co, Tech. Rep., 2002. E. Duarte, D. Falla, J. Gavin, M. Lawrence, T. McGrail, D. Miller, P. Prout, and B. Rogan, “A practical approach to condition and risk based power transformer asset replacement,” in Conference Record of IEEE International Symposium on Electrical Insulation, 2010, pp. 1–4. A. J. Trappey, C. V. Trappey, C. Y. Wu, and C. W. Lin, “A patent quality analysis for innovative technology and product development,” Advanced Engineering Informatics, vol. 26, no. 1, pp. 26–34, 2012. A. J. C. Trappey, C. V. Trappey, L. Ma, and J. C. M. Chang, “Intelligent engineering asset management system for power transformer maintenance decision supports under various operating conditions,” Computers & Industrial Engineering, vol. 2015, no. 84, pp. 3–11, 2015. [Online]. Available: http://dx.doi.org/10.1016/j.cie.2014.12.033 P. Sarajcev, D. Jakus, and J. Vasilj, “Optimal scheduling of power transformers preventive maintenance with Bayesian statistical learning and influence diagrams,” Journal of Cleaner Production, vol. 258, pp. 1–13, 2020. Y. Zhao, J. Wen, F. Xiao, X. Yang, and S. Wang, “Diagnostic Bayesian networks for diagnosing air handling units faults – part I: Faults in dampers, fans, filters and sensors,” Applied Thermal Engineering, vol. 111, pp. 1272–1286, 2017. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S1359431116301193 S. Ceferin, G. Janc, Z. Toros, T. Kastelic, and B. Praˇsnikar, “Power transformer monitoring systems for better asset management,” in CIRED - Open Access Proceedings Journal, vol. 1. Institution of Engineering and Technology, 2017, pp. 395–399. X. Zhang and E. Gockenbach, “Asset-management of transformers based on condition monitoring and standard diagnosis,” IEEE Electrical Insulation Magazine, vol. 24, no. 4, pp. 26–40, 2008. A. E. Abu-Elanien and M. M. Salama, “Asset management techniques for transformers,” Electric Power Systems Research, vol. 80, no. 4, pp. 456–464, 2010. A. Alqudsi and A. El-Hag, “Application of machine learning in transformer health index prediction,” Energies, vol. 12, no. 14, pp. 1–13, 2019. P. Bohatyrewicz, J. P lowucha, and J. Subocz, “Condition assessment of power transformers based on health index value,” Applied Sciences (Switzerland), vol. 9, no. 22, pp. 1–11, 2019. W. Zuo, H. Yuan, Y. Shang, Y. Liu, and T. Chen, “Calculation of a Health Index of Oil-Paper Transformers Insulation with Binary Logistic Regression,” Mathematical Problems in Engineering, vol. 2016, pp. 1–9, 2016. [Online]. Available: https://doi.org/10.1155/2016/6069784 A. F. Cerón, D. F. Echeverry, G. Aponte, and A. A. Romero, “´Indice de salud para transformadores de potencia inmersos en aceite mineral con voltajes entre 69kV y 230kV usando lógica difusa,” Informacion Tecnologica, vol. 26, no. 2, pp. 107–116, 2015. F. Scatiggio and M. Pompili, “Health index: The TERNA’s practical approach for transformers fleet management,” in 2013 IEEE Electrical Insulation Conference, EIC 2013, 2013, pp. 178–182. A. N. Jahromi, R. Piercy, S. Cress, J. R. Service, and W. Fan, “An approach to power transformer asset management using health index,” IEEE Electrical Insulation Magazine, vol. 25, no. 2, pp. 20–34, 2009. A. J. Patil, A. Singh, and R. K. Jarial, “A Novel Fuzzy Based Technique for Transformer Health Index Computation,” in 2019 6th IEEE International Conference on Advances in Computing, Communication and Control, ICAC3 2019. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1–6. G. C. Jaiswal, M. S. Ballal, and D. R. Tutakne, “Health index based condition monitoring of distribution transformer,” in IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016, vol. 2016-Janua. Institute of Electrical and Electronics Engineers Inc., 2017, pp. 1–5. N. L. Keijsers, “Neural Networks,” Encyclopedia of Movement Disorders, pp. 257–259, 2010. [Online]. Available: https://www.sciencedirect.com/topics/neuroscience/neuralnetworks K. L. Du and M. N. Swamy, Fundamentals of Machine Learning. Springer-Verlag London Ltd, 2014, vol. 1. S. Kittan, S. Kornhuber, P. Kastel, G. Nitsche, G. Valtin, and M. Weise, “Review and Implementation of Transformer Health Index Methods in line with the Development of a Condition Assessment Tool,” in 2018 International Conference on Diagnostics in Electrical Engineering, Diagnostika 2018. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 1–4. A. Y. Alqudsi and A. H. Elhag, “A cost effective artificial intelligence based transformer insulation health index,” in 2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems, CATCON 2017 - Proceedings, vol. 2018-Janua. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 108–111. R. A. Ghunem, A. H. El-Hag, K. Assaleh, and F. Al Dhaheri, “Estimating transformer oil parameters using artificial neural networks,” in 2009 International Conference on Electric Power and Energy Conversion Systems, (EPECS), 2009, pp. 1–4. S. Sinha and S. Tiwari, “An Improvement in Performance and Computational Cost of ANN Based Wind Speed Prediction System,” in Proceedings of the 4th International Conference on Communication and Electronics Systems, ICCES 2019. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 542–546. V. Richard, R. Loison, R. Gillard, H. Legay, and M. Romier, “Loss analysis of a reflectarray cell using ANNs with accurate magnitude prediction,” in 2017 11th European Conference on Antennas and Propagation, EUCAP 2017. Institute of Electrical and Electronics Engineers Inc., 2017, pp. 2396–2399. S. Pervaiz, I. Deiab, S. Zafar, and S. Shams, “Prediction of energy consumption and surface roughness in reaming operation of Al-6061 using ANN based models,” in 2012 International Conference on Robotics and Artificial Intelligence, ICRAI 2012, 2012, pp. 169–173. X. Su, C. Pan, X. Yang, and J. Zou, “Application of Elman Neural Network in Top Oil Temperature Prediction of Transformer,” in ICHVE 2018 - 2018 IEEE International Conference on High Voltage Engineering and Application. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1–4. G. Athanasopoulos and R. Hyndman, Forecasting: principles and practice, 3rd ed. Melbourne: OTexts, 2021. [Online]. Available: OTexts.com/fpp3 S. I. Vagropoulos, G. I. Chouliaras, E. G. Kardakos, C. K. Simoglou, and A. G. Bakirtzis, “Comparison of SARIMAX, SARIMA, modified SARIMA and ANN-based models for short-term PV generation forecasting,” 2016 IEEE International Energy Conference, ENERGYCON 2016, pp. 1–6, 2016. N. K. Chikkakrishna, C. Hardik, K. Deepika, and N. Sparsha, “Short-term traffic prediction using sarima and FbPROPHET,” 2019 IEEE 16th India Council International Conference, INDICON 2019 - Symposium Proceedings, pp. 1–4, 2019. F. Wu, C. Cattani, W. Song, and E. Zio, “Fractional ARIMA with an improved cuckoo search optimization for the efficient Short-term power load forecasting,” Alexandria Engineering Journal, vol. 59, no. 5, pp. 3111–3118, 2020. C. E. D´Negri and E. L. D. Vito, “Introducción al razonamiento aproximado: lógica difusa,” Revista Americana de Medicina Respiratoria, vol. 6, no. 3, pp. 126–136, 2006. [Online]. Available: https://www.redalyc.org/articulo.oa?id=382138367007 A. KHALIL, N. MBAREK, and O. TOGNI, “Fuzzy Logic based model for self-optimizing energy consumption in IoT environment,” in 2021 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2021, pp. 1–7. [Online]. Available: https://ieeexplore.ieee.org/document/9417265/ M. K. Paramathma, D. Devaraj, V. A. I. Selvi, and M. Karuppasamypandian, “Development of Fuzzy Logic Based Approach for Consumer Side Management in Smart Home,” in 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2021, pp. 1056–1061. [Online]. Available: https://ieeexplore.ieee.org/document/9404550/ F. Krykhtine, L. E. N. Safortes, C. A. Nunes Cosenza, M. Villarino, J. Caldeira, M. Aredes, and P. De Oliveira Reis Filho, “Fuzzy Logic for Evaluating Electrician Maintenance Teams at Transmission Lines Work Environment,” in Proceedings of the 3rd International Conference Ergo-2018: Human Factors in Complex Technical Systems and Environments, Ergo 2018. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 234–240. M. S. Uddin, Y. A. Sekercioglu, and N. Mani, “Fuzzy logic systems: A classification based on capabilities in handling uncertainty,” in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2007, pp. 807–811. S. Tellez, J. Chinchilla, O. Duarte, and J. Rosero, “Demand side management through LAB+i platform: Case study,” in 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016. Institute of Electrical and Electronics Engineers Inc., 2017, pp. 1–6. D. Alvarez, J. Reyes, W. Montano, and E. Parra, “Sistema de Gestión de Energía en Tiempo Real del Campus de la Universidad Nacional de Colombia, Sede Bogotá,” Mundo Eléctrico, vol. 101, pp. 48 – 57, 2015. [Online]. Available: http://www.mundoelectrico.com/index.php/component/k2/item/159-edicion-101-automatizacion W. M. Salamanca and J. A. García, “Computing platform for power flow models in real time: Case study - Real-time monitoring on a photovoltaic generation system and its integration into the load flow of Universidad Nacional de Colombia power grid model,” in 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016. Institute of Electrical and Electronics Engineers Inc., 2017, pp. 1–8. R. Cespedes, “Applications of a reference model to smarter electrical energy systems,” in 2013 IEEE Grenoble Conference PowerTech, POWERTECH 2013, 2013, pp. 1–5. J. A. Restrepo, S. E. Sierra, and J. A. Rosero, “Load curve characterization based on real time measurements: Case of study in Colombia,” in Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 1–5. W. M. Salamanca and J. R. García, “Metering Management Center for Colombia and short-term strategies to implement programs related to smart metering,” in 2019 FISEIEEE/ CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1–7. J. Schneider, A. J. Gaul, C. Neumann, J. Hografer, W.Wellbow, M. Schwan, and A. Schnettler, “Asset management techniques,” International Journal of Electrical Power and Energy Systems, vol. 28, no. 9 SPEC. ISS., pp. 643–654, 2006. M. Dachyar and M. I. Perkasa, “Asset management improvement design in state university,” in 2018 International Conference on Information Management and Processing, ICIMP 2018, vol. 2018-Janua. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 21–25. J. Van Der Aelst, “A field proven vision on Asset Management in an industrial environment,” in IET Conference Publications, 2011, pp. 1–5. J. R. Garcia, A. A. Zambrano P, and O. Duarte, “Implementation of an Energy Demand Forecasting Model under a Smart Grids Environment,” in Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 1–5. D. Duckett, C. Arpino, and S. McNelly, “IEEE Guide for Loading Mineral-Oil-Immersed Transformers and Step-Voltage Regulators,” IEEE Std C57.91-2011 (Revision of IEEE Std C57.91-1995), pp. 1–123, 2012. Icontec, “GTC 50:1997. Electrotecnia. Transformadores de distribución sumergidos en liquido refrigerante con 65°C de calentamiento en los devanados. Guía de cargabilidad.” pp. 1–32, 1997. J. A. Rodrigo, “Predicción (forecasting) de la demanda eléctrica con Python,” 2021. [Online]. Available: https://www.cienciadedatos.net/documentos/py29-forecastingdemanda-energia-electrica-python.html S. Taylor and B. Letham, “Prophet: forecasting at scale - Facebook Research,” 2017. [Online]. Available: https://research.fb.com/blog/2017/02/prophet-forecastingat-scale/ I. The MathWorks, “Time Series Forecasting Using Deep Learning - MATLAB & Simulink - MathWorks América Latina,” 2021. [Online]. Available: https://la.mathworks.com/help/deeplearning/ug/time-series-forecasting-usingdeep-learning.html J. Perktold, S. Seabold, and J. Taylor, “statsmodels - Statistical models, hypothesis tests, and data exploration,” 2021. [Online]. Available: https://www.statsmodels.org/stable/index.html |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
| dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
| dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.format.extent.spa.fl_str_mv |
xiii, 101 páginas |
| dc.format.mimetype.spa.fl_str_mv |
application/pdf |
| dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.publisher.program.spa.fl_str_mv |
Bogotá - Ingeniería - Maestría en Ingeniería - Automatización Industrial |
| dc.publisher.department.spa.fl_str_mv |
Departamento de Ingeniería Eléctrica y Electrónica |
| dc.publisher.faculty.spa.fl_str_mv |
Facultad de Ingeniería |
| dc.publisher.place.spa.fl_str_mv |
Bogotá, Colombia |
| dc.publisher.branch.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Bogotá |
| institution |
Universidad Nacional de Colombia |
| bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/81490/3/Tesis_maestria_Title.pdf https://repositorio.unal.edu.co/bitstream/unal/81490/4/license.txt https://repositorio.unal.edu.co/bitstream/unal/81490/5/Tesis_maestria_Title.pdf.jpg |
| bitstream.checksum.fl_str_mv |
4ee8d733f7d10c35664496eb705e9eaa 8153f7789df02f0a4c9e079953658ab2 da15320a759d5e7e04bc0f01b8255e52 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| repository.mail.fl_str_mv |
repositorio_nal@unal.edu.co |
| _version_ |
1806886485327085568 |
| spelling |
Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Rosero Garcia, Javier275208baaebbfda7d303f6baf775f000600Morgado, Kevinb7e7767a68fe1413634c5ab4632f9faa600Electrical Machines & Drives, Em&D2022-06-02T16:29:53Z2022-06-02T16:29:53Z2022https://repositorio.unal.edu.co/handle/unal/81490Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, graficasEn este documento se desarrolló un sistema de diagnóstico del estado actual de una flota de cuatro transformadores de potencia del Campus Universitario de la Universidad Nacional de Colombia sede Bogotá, teniendo en cuenta el registro en tiempo real de tensión, corriente y de edad de estos dispositivos almacenado en el Laboratorio Nacional de Redes Inteligentes (LAB+i). Para este fin, se implementó un sistema de gestión de activos compuesto de un módulo de predicción basado en métodos estadísticos y de un módulo de lógico difusa, con el objetivo de la clasificación de los transformadores considerando las condiciones de consumo de energía y comparando el desempeño con métodos actuales de gestión. Se identificó que este sistema se puede utilizar tanto para el seguimiento del estado de la flota en tiempo real como para su proyección en el futuro, si bien se presentaron retos asociados a asegurar una operación continua en el tiempo. (Texto tomado de la fuente)This paper presents the development of a diagnostic system for the current status of a fleet of four power transformers of the University Campus of the Universidad Nacional de Colombia in Bogotá, considering the real-time recording of voltage, current, and device age through the National Laboratory of Smart Grids (LAB+i). For this purpose, an asset management system was implemented, consisting of a prediction module based on statistical methods and a fuzzy logic module for the classification of transformers according to their conditions of energy consumption. It was identified that this management system could be used to monitor the status of the fleet in real-time and with future values, although there were challenges associated with its continuous operation over time.MaestríaMagíster en Ingeniería - Automatización IndustrialGestión de Activos en Sistemas de Potenciaxiii, 101 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Automatización IndustrialDepartamento de Ingeniería Eléctrica y ElectrónicaFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá620 - Ingeniería y operaciones afinesTransformadores eléctricosElectric transformersGestión de ActivosTransformadores de PotenciaCiclo de VidaAsset ManagementPower TransformersLife CycleConsumo de energíaEnergy consumptionDesarrollo de una técnica de gestión de activos para transformadores de distribución basada en sistema de monitoreoDevelopment of an asset management technique for distribution transformers based on a monitoring systemTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMA. Doolgindachbaporn, G. Callender, P. Lewin, E. A. Simonson, and G. Wilson, “Data Driven Transformer Thermal Model for Condition Monitoring,” IEEE Transactions on Power Delivery, pp. 1–9, 2021. [Online]. Available: https://ieeexplore.ieee.org/document/9599483/I. Soltanbayev, M. Bagheri, and T. Phung, “Real-time dry-type transformer aging evaluation,” Proceedings of the International Symposium on Electrical Insulating Materials, vol. 2, pp. 551–554, 2017.M. A. Mehmood, J. Li, F. Wang, Z. Huang, J. Ahmad, and M. Shoaib Bhutta, “Analyzing the health condition and chemical degradation in field aged transformer insulation oil using spectroscopic techniques,” 2018 International Conference on Diagnostics in Electrical Engineering, Diagnostika 2018, pp. 1–4, 2018.Z. Chunming, X. Wenxie, and D. Zhaohong, “Transformer Oil-Paper Insulation Aging Evaluation System Based on Different Aging Characteristics,” 2021 6th International Conference on Control, Robotics and Cybernetics (CRC), pp. 181–185, 2021. [Online]. Available: https://ieeexplore.ieee.org/document/9620125/H. Gumilang, “Cost and Benefit Analysis on Treatment Method of Aged Power Transformer Insulating Oil,” 2021 3rd International Conference on High Voltage Engineering and Power Systems (ICHVEPS), pp. 203–206, 2021. [Online]. Available:https://ieeexplore.ieee.org/document/9600996/Y. Wang, W. Wei, P. Xue, and B. Yan, “Analysis on comprehensive fault rate of oil-immersed power transformer based on FTA,” 2021 International Conference on Electronic Information Engineering and Computer Science (EIECS), pp. 972–975, 2021. [Online]. Available: https://ieeexplore.ieee.org/document/9588025/J. Chen, Z. Yin, X. Cheng, and Y. Liu, “Big data analysis based identification method of low-voltage substation area,” Proceedings - 2021 2nd International Conference on Big Data and Informatization Education, ICBDIE 2021, pp. 169–172, 2021.Z. Y. Zheng, Z. Li, S. F. Yu, D. F. Ke, Z. J. Lao, J. Q. Lin, and J. J. Chen, “A new capacity inspection method for distribution transformer based on big data,” China International Conference on Electricity Distribution, CICED, pp. 38–41, 2018.G. P. Zheng, Z. Y. Hou, and X. N. Yin, “Research of the agent technology based on multi-thread in transformer substation communication,” Proceedings of the 2006 International Conference on Machine Learning and Cybernetics, vol. 2006, pp. 56–60, 2006.S. Tellez, D. Alvarez, W. Montano, C. Vargas, R. Cespedes, E. Parra, and J. Rosero, “National Laboratory of Smart Grids (LAB+i) at the National University of Colombia- Bogotá Campus,” in 2014 IEEE PES Transmission and Distribution Conference and Exposition, PES T and D-LA 2014 - Conference Proceedings, vol. 2014-Octob. Institute of Electrical and Electronics Engineers Inc., 2014, pp. 1–6.W. M. Salamanca, D. L. Álvarez, J. A. García, J. S. Marín, and E. Gómez-Luna, “State Estimator Assessment Platform in Distribution Systems with Advanced Metering Infrastructure and Distributed Generation using Real Time Simulations,” in 2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1–6.A. F. Cerón, I. F. Orduña, G. Aponte, and A. A. Romero, “Panorama de la gestión de activos para transformadores de potencia,” Informacion Tecnologica, vol. 26, no. 3, pp. 99–110, 2015.International Organization for Standardization, “ISO 55000: Asset Management-Overview, Principles and Terminology,” 2014.J. Woodhouse, “Briefing: Standards in asset management: PAS 55 to ISO 55000,” Infrastructure Asset Management, vol. 1, no. 3, pp. 57–59, 2014.A. Attwater, J. Q. Wang, A. Parlikad, and P. Russell, “Measuring the performance of asset management systems,” IET Conference Publications, vol. 1, no. CP642, 2014.D. Zhou, C. Li, and Z. Wang, “Power transformer lifetime modeling,” in Proceedings of IEEE 2012 Prognostics and System Health Management Conference, PHM-2012, 2012, pp. 1–7.A. Azmi, J. Jasni, N. Azis, and M. Z. Kadir, “Evolution of transformer health index in the form of mathematical equation,” Renewable and Sustainable Energy Reviews, vol. 76, pp. 687–700, 2017.G. R. Steeves, “Transformer lifecycle: Power transformer asset management,” Transformers Magazine, vol. 3, no. 2, pp. 52–56, 2016. [Online]. Available: https://hrcak.srce.hr/167406C. Liu, G. Huang, K. Zhang, F. Wen, M. A. Salam, and S. P. Ang, “Asset management in power systems,” in IET Seminar Digest. Institution of Engineering and Technology, 2015, pp. 1–5.J. L. Deng, “Introduction to Grey system theory,” Journal of Grey System, vol. 1, no. 1, pp. 1–24, 1989.T. Suwnansri, “Asset management of power transformer: Optimization of operation and maintenance costs,” in 2014 International Electrical Engineering Congress, iEECON 2014. Institute of Electrical and Electronics Engineers Inc., 2014.A. Babizki, M. Foata, K. Lindl, D. Beerboom, E. Pawlowski, M. Zdrallek, R. Funk, and J. Linossier, “Practical approach for fleet management of transformers considering different stakeholders’ perspectives,” 4th International Colloquium ”Transformer Research and Asset Management”, 2017.R. D. Medina, A. A. Romero, E. E. Mombello, and G. Ratta, “Assessing degradation of power transformer solid insulation considering thermal stress and moisture variation,” Electric Power Systems Research, vol. 151, pp. 1–11, 2017.I. Karatzas and S. E. Shreve, “Brownian Motion,” in Brownian Motion and Stochastic Calculus. Springer, 1998, pp. 47–127.A. A. Romero-Quete, H. D. Gómez, J. D. Molina, and G. Moreno, “Método práctico para la evaluación de riesgo en parques de transformadores de potencia,” DYNA (Colombia), vol. 84, no. 200, pp. 11–18, 2017.A. A. Romero, E. E. Mombello, and G. Ratta, “An overview on power transformer management: Individual Assets and Fleets,” in 2012 Sixth IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T D-LA), 2012, pp. 1–7.P. Boss, J. Patelli, and J. Aubin, “Guide on economics of transformer management,” pp. 1–67, 2004.W. H. Bartley, P. E. Hartford, and S. Boiler, “Life Cycle Management of Utility Transformer Assets Breakthrough Asset Management for the Restructured Power Industry Life Cycle Management of Utility Transformer Assets,” Hartford Steam Boiler Inspection & Insurance Co, Tech. Rep., 2002.E. Duarte, D. Falla, J. Gavin, M. Lawrence, T. McGrail, D. Miller, P. Prout, and B. Rogan, “A practical approach to condition and risk based power transformer asset replacement,” in Conference Record of IEEE International Symposium on Electrical Insulation, 2010, pp. 1–4.A. J. Trappey, C. V. Trappey, C. Y. Wu, and C. W. Lin, “A patent quality analysis for innovative technology and product development,” Advanced Engineering Informatics, vol. 26, no. 1, pp. 26–34, 2012.A. J. C. Trappey, C. V. Trappey, L. Ma, and J. C. M. Chang, “Intelligent engineering asset management system for power transformer maintenance decision supports under various operating conditions,” Computers & Industrial Engineering, vol. 2015, no. 84, pp. 3–11, 2015. [Online]. Available: http://dx.doi.org/10.1016/j.cie.2014.12.033P. Sarajcev, D. Jakus, and J. Vasilj, “Optimal scheduling of power transformers preventive maintenance with Bayesian statistical learning and influence diagrams,” Journal of Cleaner Production, vol. 258, pp. 1–13, 2020.Y. Zhao, J. Wen, F. Xiao, X. Yang, and S. Wang, “Diagnostic Bayesian networks for diagnosing air handling units faults – part I: Faults in dampers, fans, filters and sensors,” Applied Thermal Engineering, vol. 111, pp. 1272–1286, 2017. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S1359431116301193S. Ceferin, G. Janc, Z. Toros, T. Kastelic, and B. Praˇsnikar, “Power transformer monitoring systems for better asset management,” in CIRED - Open Access Proceedings Journal, vol. 1. Institution of Engineering and Technology, 2017, pp. 395–399.X. Zhang and E. Gockenbach, “Asset-management of transformers based on condition monitoring and standard diagnosis,” IEEE Electrical Insulation Magazine, vol. 24, no. 4, pp. 26–40, 2008.A. E. Abu-Elanien and M. M. Salama, “Asset management techniques for transformers,” Electric Power Systems Research, vol. 80, no. 4, pp. 456–464, 2010.A. Alqudsi and A. El-Hag, “Application of machine learning in transformer health index prediction,” Energies, vol. 12, no. 14, pp. 1–13, 2019.P. Bohatyrewicz, J. P lowucha, and J. Subocz, “Condition assessment of power transformers based on health index value,” Applied Sciences (Switzerland), vol. 9, no. 22, pp. 1–11, 2019.W. Zuo, H. Yuan, Y. Shang, Y. Liu, and T. Chen, “Calculation of a Health Index of Oil-Paper Transformers Insulation with Binary Logistic Regression,” Mathematical Problems in Engineering, vol. 2016, pp. 1–9, 2016. [Online]. Available: https://doi.org/10.1155/2016/6069784A. F. Cerón, D. F. Echeverry, G. Aponte, and A. A. Romero, “´Indice de salud para transformadores de potencia inmersos en aceite mineral con voltajes entre 69kV y 230kV usando lógica difusa,” Informacion Tecnologica, vol. 26, no. 2, pp. 107–116, 2015.F. Scatiggio and M. Pompili, “Health index: The TERNA’s practical approach for transformers fleet management,” in 2013 IEEE Electrical Insulation Conference, EIC 2013, 2013, pp. 178–182.A. N. Jahromi, R. Piercy, S. Cress, J. R. Service, and W. Fan, “An approach to power transformer asset management using health index,” IEEE Electrical Insulation Magazine, vol. 25, no. 2, pp. 20–34, 2009.A. J. Patil, A. Singh, and R. K. Jarial, “A Novel Fuzzy Based Technique for Transformer Health Index Computation,” in 2019 6th IEEE International Conference on Advances in Computing, Communication and Control, ICAC3 2019. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1–6.G. C. Jaiswal, M. S. Ballal, and D. R. Tutakne, “Health index based condition monitoring of distribution transformer,” in IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016, vol. 2016-Janua. Institute of Electrical and Electronics Engineers Inc., 2017, pp. 1–5.N. L. Keijsers, “Neural Networks,” Encyclopedia of Movement Disorders, pp. 257–259, 2010. [Online]. Available: https://www.sciencedirect.com/topics/neuroscience/neuralnetworksK. L. Du and M. N. Swamy, Fundamentals of Machine Learning. Springer-Verlag London Ltd, 2014, vol. 1.S. Kittan, S. Kornhuber, P. Kastel, G. Nitsche, G. Valtin, and M. Weise, “Review and Implementation of Transformer Health Index Methods in line with the Development of a Condition Assessment Tool,” in 2018 International Conference on Diagnostics in Electrical Engineering, Diagnostika 2018. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 1–4.A. Y. Alqudsi and A. H. Elhag, “A cost effective artificial intelligence based transformer insulation health index,” in 2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems, CATCON 2017 - Proceedings, vol. 2018-Janua. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 108–111.R. A. Ghunem, A. H. El-Hag, K. Assaleh, and F. Al Dhaheri, “Estimating transformer oil parameters using artificial neural networks,” in 2009 International Conference on Electric Power and Energy Conversion Systems, (EPECS), 2009, pp. 1–4.S. Sinha and S. Tiwari, “An Improvement in Performance and Computational Cost of ANN Based Wind Speed Prediction System,” in Proceedings of the 4th International Conference on Communication and Electronics Systems, ICCES 2019. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 542–546.V. Richard, R. Loison, R. Gillard, H. Legay, and M. Romier, “Loss analysis of a reflectarray cell using ANNs with accurate magnitude prediction,” in 2017 11th European Conference on Antennas and Propagation, EUCAP 2017. Institute of Electrical and Electronics Engineers Inc., 2017, pp. 2396–2399.S. Pervaiz, I. Deiab, S. Zafar, and S. Shams, “Prediction of energy consumption and surface roughness in reaming operation of Al-6061 using ANN based models,” in 2012 International Conference on Robotics and Artificial Intelligence, ICRAI 2012, 2012, pp. 169–173.X. Su, C. Pan, X. Yang, and J. Zou, “Application of Elman Neural Network in Top Oil Temperature Prediction of Transformer,” in ICHVE 2018 - 2018 IEEE International Conference on High Voltage Engineering and Application. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1–4.G. Athanasopoulos and R. Hyndman, Forecasting: principles and practice, 3rd ed. Melbourne: OTexts, 2021. [Online]. Available: OTexts.com/fpp3S. I. Vagropoulos, G. I. Chouliaras, E. G. Kardakos, C. K. Simoglou, and A. G. Bakirtzis, “Comparison of SARIMAX, SARIMA, modified SARIMA and ANN-based models for short-term PV generation forecasting,” 2016 IEEE International Energy Conference, ENERGYCON 2016, pp. 1–6, 2016.N. K. Chikkakrishna, C. Hardik, K. Deepika, and N. Sparsha, “Short-term traffic prediction using sarima and FbPROPHET,” 2019 IEEE 16th India Council International Conference, INDICON 2019 - Symposium Proceedings, pp. 1–4, 2019.F. Wu, C. Cattani, W. Song, and E. Zio, “Fractional ARIMA with an improved cuckoo search optimization for the efficient Short-term power load forecasting,” Alexandria Engineering Journal, vol. 59, no. 5, pp. 3111–3118, 2020.C. E. D´Negri and E. L. D. Vito, “Introducción al razonamiento aproximado: lógica difusa,” Revista Americana de Medicina Respiratoria, vol. 6, no. 3, pp. 126–136, 2006. [Online]. Available: https://www.redalyc.org/articulo.oa?id=382138367007A. KHALIL, N. MBAREK, and O. TOGNI, “Fuzzy Logic based model for self-optimizing energy consumption in IoT environment,” in 2021 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2021, pp. 1–7. [Online]. Available: https://ieeexplore.ieee.org/document/9417265/M. K. Paramathma, D. Devaraj, V. A. I. Selvi, and M. Karuppasamypandian, “Development of Fuzzy Logic Based Approach for Consumer Side Management in Smart Home,” in 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2021, pp. 1056–1061. [Online]. Available: https://ieeexplore.ieee.org/document/9404550/F. Krykhtine, L. E. N. Safortes, C. A. Nunes Cosenza, M. Villarino, J. Caldeira, M. Aredes, and P. De Oliveira Reis Filho, “Fuzzy Logic for Evaluating Electrician Maintenance Teams at Transmission Lines Work Environment,” in Proceedings of the 3rd International Conference Ergo-2018: Human Factors in Complex Technical Systems and Environments, Ergo 2018. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 234–240.M. S. Uddin, Y. A. Sekercioglu, and N. Mani, “Fuzzy logic systems: A classification based on capabilities in handling uncertainty,” in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2007, pp. 807–811.S. Tellez, J. Chinchilla, O. Duarte, and J. Rosero, “Demand side management through LAB+i platform: Case study,” in 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016. Institute of Electrical and Electronics Engineers Inc., 2017, pp. 1–6.D. Alvarez, J. Reyes, W. Montano, and E. Parra, “Sistema de Gestión de Energía en Tiempo Real del Campus de la Universidad Nacional de Colombia, Sede Bogotá,” Mundo Eléctrico, vol. 101, pp. 48 – 57, 2015. [Online]. Available: http://www.mundoelectrico.com/index.php/component/k2/item/159-edicion-101-automatizacionW. M. Salamanca and J. A. García, “Computing platform for power flow models in real time: Case study - Real-time monitoring on a photovoltaic generation system and its integration into the load flow of Universidad Nacional de Colombia power grid model,” in 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016. Institute of Electrical and Electronics Engineers Inc., 2017, pp. 1–8.R. Cespedes, “Applications of a reference model to smarter electrical energy systems,” in 2013 IEEE Grenoble Conference PowerTech, POWERTECH 2013, 2013, pp. 1–5.J. A. Restrepo, S. E. Sierra, and J. A. Rosero, “Load curve characterization based on real time measurements: Case of study in Colombia,” in Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 1–5.W. M. Salamanca and J. R. García, “Metering Management Center for Colombia and short-term strategies to implement programs related to smart metering,” in 2019 FISEIEEE/ CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019. Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1–7.J. Schneider, A. J. Gaul, C. Neumann, J. Hografer, W.Wellbow, M. Schwan, and A. Schnettler, “Asset management techniques,” International Journal of Electrical Power and Energy Systems, vol. 28, no. 9 SPEC. ISS., pp. 643–654, 2006.M. Dachyar and M. I. Perkasa, “Asset management improvement design in state university,” in 2018 International Conference on Information Management and Processing, ICIMP 2018, vol. 2018-Janua. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 21–25.J. Van Der Aelst, “A field proven vision on Asset Management in an industrial environment,” in IET Conference Publications, 2011, pp. 1–5.J. R. Garcia, A. A. Zambrano P, and O. Duarte, “Implementation of an Energy Demand Forecasting Model under a Smart Grids Environment,” in Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018. Institute of Electrical and Electronics Engineers Inc., 2018, pp. 1–5.D. Duckett, C. Arpino, and S. McNelly, “IEEE Guide for Loading Mineral-Oil-Immersed Transformers and Step-Voltage Regulators,” IEEE Std C57.91-2011 (Revision of IEEE Std C57.91-1995), pp. 1–123, 2012.Icontec, “GTC 50:1997. Electrotecnia. Transformadores de distribución sumergidos en liquido refrigerante con 65°C de calentamiento en los devanados. Guía de cargabilidad.” pp. 1–32, 1997.J. A. Rodrigo, “Predicción (forecasting) de la demanda eléctrica con Python,” 2021. [Online]. Available: https://www.cienciadedatos.net/documentos/py29-forecastingdemanda-energia-electrica-python.htmlS. Taylor and B. Letham, “Prophet: forecasting at scale - Facebook Research,” 2017. [Online]. Available: https://research.fb.com/blog/2017/02/prophet-forecastingat-scale/I. The MathWorks, “Time Series Forecasting Using Deep Learning - MATLAB & Simulink - MathWorks América Latina,” 2021. [Online]. Available: https://la.mathworks.com/help/deeplearning/ug/time-series-forecasting-usingdeep-learning.htmlJ. Perktold, S. Seabold, and J. Taylor, “statsmodels - Statistical models, hypothesis tests, and data exploration,” 2021. [Online]. Available: https://www.statsmodels.org/stable/index.htmlEstudiantesInvestigadoresMaestrosORIGINALTesis_maestria_Title.pdfTesis_maestria_Title.pdfTesis de Maestría en Automatización Industrialapplication/pdf4382877https://repositorio.unal.edu.co/bitstream/unal/81490/3/Tesis_maestria_Title.pdf4ee8d733f7d10c35664496eb705e9eaaMD53LICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/81490/4/license.txt8153f7789df02f0a4c9e079953658ab2MD54THUMBNAILTesis_maestria_Title.pdf.jpgTesis_maestria_Title.pdf.jpgGenerated Thumbnailimage/jpeg4625https://repositorio.unal.edu.co/bitstream/unal/81490/5/Tesis_maestria_Title.pdf.jpgda15320a759d5e7e04bc0f01b8255e52MD55unal/81490oai:repositorio.unal.edu.co:unal/814902023-08-04 23:04:40.806Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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 |