Intelligent model for electric power management: patterns

When talking about electric power, the first thing to think about is whether enough electrical energy is generated to use without paying attention to it, similar to thinking that water will never runs out, but when faced with extreme droughts, people think that water can be depleted and they must sa...

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Autores: amelec, viloria, Hernandez Palma, Hugo Gaspar, GAMBOA SUAREZ, RAMIRO, Niebles Núñez, William, Solórzano Movilla, José
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2020
País:Colombia
Institución:Corporación Universidad de la Costa
Repositorio:Repositorio REDICUC
Idioma:inglés
OAI Identifier:oai:repositorio.cuc.edu.co:11323/6188
Acceso en línea:https://hdl.handle.net/11323/6188
https://repositorio.cuc.edu.co/
Access Level:acceso abierto
Palabra clave:Electric power
Energy savings
Electrical energy
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dc.title.none.fl_str_mv Intelligent model for electric power management: patterns
title Intelligent model for electric power management: patterns
spellingShingle Intelligent model for electric power management: patterns
amelec, viloria
Electric power
Energy savings
Electrical energy
title_short Intelligent model for electric power management: patterns
title_full Intelligent model for electric power management: patterns
title_fullStr Intelligent model for electric power management: patterns
title_full_unstemmed Intelligent model for electric power management: patterns
title_sort Intelligent model for electric power management: patterns
dc.creator.none.fl_str_mv amelec, viloria
Hernandez Palma, Hugo Gaspar
GAMBOA SUAREZ, RAMIRO
Niebles Núñez, William
Solórzano Movilla, José
author amelec, viloria
author_facet amelec, viloria
Hernandez Palma, Hugo Gaspar
GAMBOA SUAREZ, RAMIRO
Niebles Núñez, William
Solórzano Movilla, José
author_role author
author2 Hernandez Palma, Hugo Gaspar
GAMBOA SUAREZ, RAMIRO
Niebles Núñez, William
Solórzano Movilla, José
author2_role author
author
author
author
dc.subject.none.fl_str_mv Electric power
Energy savings
Electrical energy
topic Electric power
Energy savings
Electrical energy
description When talking about electric power, the first thing to think about is whether enough electrical energy is generated to use without paying attention to it, similar to thinking that water will never runs out, but when faced with extreme droughts, people think that water can be depleted and they must save. In this sense, electrical energy must be saved and used completely and that is why the term energy efficiency is born. This new trend seeks to save electric power to avoid electricity supply shortages, as when countries face phenomena such as El Niño that generate droughts in some areas and rains in others. So, saving energy is a trend because it is important to be prepared for these phenomena, and guaranteeing a sustainable country. This document shows the importance of energy savings, as well as the need to design intelligent models that help to support the reduction of the problem of excessive consumption of electricity.
publishDate 2020
dc.date.none.fl_str_mv 2020-04-15T17:07:47Z
2020-04-15T17:07:47Z
2020
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dc.identifier.none.fl_str_mv 1742-6588
1742-6596
https://hdl.handle.net/11323/6188
doi:10.1088/1742-6596/1432/1/012032
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
https://repositorio.cuc.edu.co/
identifier_str_mv 1742-6588
1742-6596
doi:10.1088/1742-6596/1432/1/012032
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/6188
https://repositorio.cuc.edu.co/
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv [1] Caballero, V., Vernet, D., Zaballos, A., & Corral, G. (2018). Web of Energy: Hacia la integración inteligente para las redes de sensores en Smart Grids. XIII Jornadas de Ingeniería telemática (JITEL 2017). Libro de actas, 30-39.
[2] López, D., & Mideros, D. (2018). Diseño de un sistema inteligente y compacto de iluminación. Enfoque UTE, 9(1), 226-235.
[3] Velez, N. R. B. (2018). Gestión eficiente de redes eléctricas inteligentes en la mini-central fotovoltaica de la universidad técnica de Manabí (Doctoral dissertation).
[4] Garcia-Rendon, J. J., Gómez, A. G., Tobón, L. V., & Ceballos, H. V. (2018). Redes inteligentes y mecanismo de respuesta de la demanda: el caso del sector eléctrico colombiano Smart grids and demand response mechanism: the case of the Colombian electricity market? (No. 016975). UNIVERSIDAD EAFIT.
[5] Abdul Masud, M., Zhexue Huang, J., Wei, C., Wang, J., Khan, I., Zhong, M.: Inice: A New Approach for Identifying the Number of Clusters and Initial Cluster Centres. Inf. Sci. (2018). https://doi.org/10.1016/j.ins.2018.07.034
[6] Martins, L.; Carvalho, R.; Victorino, C.; Holanda, M.: Early Prediction of College Attrition Using Data Mining. 16th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 1075-1078 (2017)
[7] Gómez, V. A., Hernández, C., & Rivas, E. (2018). Visión General, Características y Funcionalidades de la Red Eléctrica Inteligente (Smart Grid). Información tecnológica, 29(2), 89102.
[8] Inga, E., Inga, J., Correa, E., & Hincapié, R. (2018). Reconstrucción del patrón de consumo eléctrico a partir de Big Data mediante técnica de MapReduce. Enfoque Ute, 9(1), 177-187.
[9] Makhabel, B.: Learning Data Mining with R. Packt Publishing 1st Ed, pp. 143 (2015)
[10] Witten, I.; Frank, E.; Hall, M.; Pal, C.: Data Mining Practical Machine Learning Tools and Techniques. Elsevier 4th Ed, pp. 167-169 (2016).
[11] Bishop, C. (1995). Extremely well-written, up-to-date. Requires a good mathematical background, but rewards careful reading, putting neural networks firmly into a statistical context. Neural Networks for Pattern Recognition
[12] Figueroa, J. F., Ochoa, M. A. R., Rodriguez, M. S., & Palma, M. G. V. (2018). Diseño de un medidor de energía eléctrica bidireccional y monitoreado mediante aplicación móvil/Design of a two-way electric power meter monitoring with a mobile application. RECI Revista Iberoamericana de las Ciencias Computacionales e Informática, 7(14), 1-30.
[13] Sanchez L., Vásquez C., Viloria A., Cmeza-estrada (2018) Conglomerates of Latin American Countries and Public Policies for the Sustainable Development of the Electric Power Generation Sector. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham.
[14] Perez, R., Inga, E., Aguila, A., Vásquez, C., Lima, L., Viloria, A., & Henry, M. A. (2018, June). Fault diagnosis on electrical distribution systems based on fuzzy logic. In International Conference on Sensing and Imaging (pp. 174-185). Springer, Cham.
[15] Perez, Ramón, Carmen Vásquez, and Amelec Viloria. "An intelligent strategy for faults location in distribution networks with distributed generation." Journal of Intelligent & Fuzzy Systems Preprint (2019): 1-11.
[16] Bucci, N., Luna, M., Viloria, A., García, J. H., Parody, A., Varela, N., & López, L. A. B. (2018, June). Factor analysis of the psychosocial risk assessment instrument. In International Conference on Data Mining and Big Data (pp. 149-158). Springer, Cham.
[17] Chakraborty, S., Das, S.: Simultaneous variable weighting and determining the number of clusters—A weighted Gaussian algorithm means. Stat. Probab. Lett. 137, 148–156 (2018). https://doi.org/10.1016/j.spl.2018.01.015.
[18] Escobar, Adriana Marcela Vega, et al. "Home energy management model: preliminary proposal/Modelo de gestion de energia electrica domiciliaria: propuesta preliminar." Redes de Ingenieria, vol. 6, no. 1, 2015, p. 95+. Gale OneFile: Informe Académico, Accessed 12 Oct. 2019.
[19] Sandoval-Ruiz, C. (2017). Modelo Neuro-Adaptativo en VHDL, basado en circuitos NLFSR, para Control de un Sistema Inteligente de Tecnología Sostenible. Universidad, Ciencia Y Tecnología, 21(85), 140-149.
[20] Sánchez Fleitas, N., Comas Rodríguez, R., Lorenzo, G., & Matilde, M. (2019). Sistema Inteligente de Información Geográfica para las empresas eléctricas cubanas. Ingeniare. Revista chilena de ingeniería, 27(2), 197-209.
[21] Camarena, N., & Angel, M. (2019). Modelo de gestión de la energía, para disminuir los costos productivos del horno N 3, en la Empresa UNACEM SAA.
[22] Ruiz, M., & Inga, E. (2019). Asignación óptima de recursos de comunicaciones para sistemas de gestión de energía. Enfoque UTE, 10(1), 141-152.
[23] Reina Espinosa, C. (2019). Adaptación de modelos de ciudades sostenibles e inteligentes para Santiago de Cali (Doctoral dissertation, Universidad Santiago de Cali).
[24] Rendón, J. J. G., Gómez, A. G., Tobón, L. V., & Ceballos, H. V. (2019). Redes inteligentes y mecanismo de respuesta de la demanda. Revista de Economía del Caribe, (23), 33.
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spelling Intelligent model for electric power management: patternsamelec, viloriaHernandez Palma, Hugo GasparGAMBOA SUAREZ, RAMIRONiebles Núñez, WilliamSolórzano Movilla, JoséElectric powerEnergy savingsElectrical energyWhen talking about electric power, the first thing to think about is whether enough electrical energy is generated to use without paying attention to it, similar to thinking that water will never runs out, but when faced with extreme droughts, people think that water can be depleted and they must save. In this sense, electrical energy must be saved and used completely and that is why the term energy efficiency is born. This new trend seeks to save electric power to avoid electricity supply shortages, as when countries face phenomena such as El Niño that generate droughts in some areas and rains in others. So, saving energy is a trend because it is important to be prepared for these phenomena, and guaranteeing a sustainable country. This document shows the importance of energy savings, as well as the need to design intelligent models that help to support the reduction of the problem of excessive consumption of electricity.amelec, viloria-will be generated-orcid-0000-0003-2673-6350-600Hernandez Palma, Hugo Gaspar-will be generated-orcid-0000-0002-3873-0530-600GAMBOA SUAREZ, RAMIRO-will be generated-orcid-0000-0002-5727-6409-600Niebles Núñez, WilliamSolórzano Movilla, JoséJournal of Physics: Conference Series2020-04-15T17:07:47Z2020-04-15T17:07:47Z2020Artículo de revistahttp://purl.org/coar/resource_type/c_6501Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/version/c_ab4af688f83e57aaapplication/pdfapplication/pdf1742-65881742-6596https://hdl.handle.net/11323/6188doi:10.1088/1742-6596/1432/1/012032Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/eng[1] Caballero, V., Vernet, D., Zaballos, A., & Corral, G. (2018). Web of Energy: Hacia la integración inteligente para las redes de sensores en Smart Grids. XIII Jornadas de Ingeniería telemática (JITEL 2017). Libro de actas, 30-39.[2] López, D., & Mideros, D. (2018). Diseño de un sistema inteligente y compacto de iluminación. Enfoque UTE, 9(1), 226-235.[3] Velez, N. R. B. (2018). Gestión eficiente de redes eléctricas inteligentes en la mini-central fotovoltaica de la universidad técnica de Manabí (Doctoral dissertation).[4] Garcia-Rendon, J. J., Gómez, A. G., Tobón, L. V., & Ceballos, H. V. (2018). Redes inteligentes y mecanismo de respuesta de la demanda: el caso del sector eléctrico colombiano Smart grids and demand response mechanism: the case of the Colombian electricity market? (No. 016975). UNIVERSIDAD EAFIT.[5] Abdul Masud, M., Zhexue Huang, J., Wei, C., Wang, J., Khan, I., Zhong, M.: Inice: A New Approach for Identifying the Number of Clusters and Initial Cluster Centres. Inf. Sci. (2018). https://doi.org/10.1016/j.ins.2018.07.034[6] Martins, L.; Carvalho, R.; Victorino, C.; Holanda, M.: Early Prediction of College Attrition Using Data Mining. 16th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 1075-1078 (2017)[7] Gómez, V. A., Hernández, C., & Rivas, E. (2018). Visión General, Características y Funcionalidades de la Red Eléctrica Inteligente (Smart Grid). Información tecnológica, 29(2), 89102.[8] Inga, E., Inga, J., Correa, E., & Hincapié, R. (2018). Reconstrucción del patrón de consumo eléctrico a partir de Big Data mediante técnica de MapReduce. Enfoque Ute, 9(1), 177-187.[9] Makhabel, B.: Learning Data Mining with R. Packt Publishing 1st Ed, pp. 143 (2015)[10] Witten, I.; Frank, E.; Hall, M.; Pal, C.: Data Mining Practical Machine Learning Tools and Techniques. Elsevier 4th Ed, pp. 167-169 (2016).[11] Bishop, C. (1995). Extremely well-written, up-to-date. Requires a good mathematical background, but rewards careful reading, putting neural networks firmly into a statistical context. Neural Networks for Pattern Recognition[12] Figueroa, J. F., Ochoa, M. A. R., Rodriguez, M. S., & Palma, M. G. V. (2018). Diseño de un medidor de energía eléctrica bidireccional y monitoreado mediante aplicación móvil/Design of a two-way electric power meter monitoring with a mobile application. RECI Revista Iberoamericana de las Ciencias Computacionales e Informática, 7(14), 1-30.[13] Sanchez L., Vásquez C., Viloria A., Cmeza-estrada (2018) Conglomerates of Latin American Countries and Public Policies for the Sustainable Development of the Electric Power Generation Sector. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham.[14] Perez, R., Inga, E., Aguila, A., Vásquez, C., Lima, L., Viloria, A., & Henry, M. A. (2018, June). Fault diagnosis on electrical distribution systems based on fuzzy logic. In International Conference on Sensing and Imaging (pp. 174-185). Springer, Cham.[15] Perez, Ramón, Carmen Vásquez, and Amelec Viloria. "An intelligent strategy for faults location in distribution networks with distributed generation." Journal of Intelligent & Fuzzy Systems Preprint (2019): 1-11.[16] Bucci, N., Luna, M., Viloria, A., García, J. H., Parody, A., Varela, N., & López, L. A. B. (2018, June). Factor analysis of the psychosocial risk assessment instrument. In International Conference on Data Mining and Big Data (pp. 149-158). Springer, Cham.[17] Chakraborty, S., Das, S.: Simultaneous variable weighting and determining the number of clusters—A weighted Gaussian algorithm means. Stat. Probab. Lett. 137, 148–156 (2018). https://doi.org/10.1016/j.spl.2018.01.015.[18] Escobar, Adriana Marcela Vega, et al. "Home energy management model: preliminary proposal/Modelo de gestion de energia electrica domiciliaria: propuesta preliminar." Redes de Ingenieria, vol. 6, no. 1, 2015, p. 95+. Gale OneFile: Informe Académico, Accessed 12 Oct. 2019.[19] Sandoval-Ruiz, C. (2017). Modelo Neuro-Adaptativo en VHDL, basado en circuitos NLFSR, para Control de un Sistema Inteligente de Tecnología Sostenible. Universidad, Ciencia Y Tecnología, 21(85), 140-149.[20] Sánchez Fleitas, N., Comas Rodríguez, R., Lorenzo, G., & Matilde, M. (2019). Sistema Inteligente de Información Geográfica para las empresas eléctricas cubanas. Ingeniare. Revista chilena de ingeniería, 27(2), 197-209.[21] Camarena, N., & Angel, M. (2019). Modelo de gestión de la energía, para disminuir los costos productivos del horno N 3, en la Empresa UNACEM SAA.[22] Ruiz, M., & Inga, E. (2019). Asignación óptima de recursos de comunicaciones para sistemas de gestión de energía. Enfoque UTE, 10(1), 141-152.[23] Reina Espinosa, C. (2019). Adaptación de modelos de ciudades sostenibles e inteligentes para Santiago de Cali (Doctoral dissertation, Universidad Santiago de Cali).[24] Rendón, J. J. G., Gómez, A. G., Tobón, L. V., & Ceballos, H. V. (2019). Redes inteligentes y mecanismo de respuesta de la demanda. Revista de Economía del Caribe, (23), 33.CC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2reponame:Repositorio REDICUCinstname:Corporación Universidad de la Costainstacron:Corporación Universidad de la Costa2024-09-17T19:24:10Z
score 15,81155

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