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Revisión sistemática de literatura sobre modelos de pronósticos de consumo de energía eléctrica

Systematic review of literature on electrical energy consumption forecast models;
Revisão sistemática de literatura sobre modelos de previsão de consumo de energia elétrica

dc.contributor.authorMazzeo, Agustín José
dc.contributor.authorSepúlveda Cano, Lina María
dc.contributor.authorVilla Montoya, Luisa Fernanda
dc.contributor.authorGallego Burgos, Ricardo Alonso
dc.date.accessioned2021-10-05T18:14:46Z
dc.date.available2021-10-05T18:14:46Z
dc.date.created2019-07-11
dc.identifier.issn1692-3324
dc.identifier.urihttp://hdl.handle.net/11407/6530
dc.description"El creciente consumo de energía eléctrica, los cambios climáticos y el desarrollo de nuevas tecnologías exigen mejoras para la gestión eficiente de la energía. El adecuado pronóstico del consumo de energía es relevante para el desarrollo sostenible de cualquier país. En este artículo se propone una revisión sistemática de literatura seleccionada a partir de cadenas de búsqueda formada por las palabras forecasting, energyy consumptionaplicadas en las bases de datos científicas. Se comparan principalmente los modelos/técnicas utilizadas, las variables consideradas y las métricas de error usadas con el fin de obtener conocimiento de cada una de las propuestas, relevar sus características y así poder evidenciar el vacío en la literatura que podría determinar la semilla para un nuevo trabajo de investigación. Como conclusiones se observan el uso continuo de redes neuronales artificiales para el pronóstico de consumo, la importancia determinar las variables de entrada y la medición del error para evaluar la precisión de los modelos. Finalmente, como nueva línea de investigación se propone desarrollar un modelo para el pronóstico de corto plazo de CEE para un país latinoamericano en vías de desarrollo, a partir de la comparación y evaluación de diferentes técnicas/modelos, variables y herramientas ya existentes.
dc.descriptionThe growing consumption of electrical energy, climate change and the development of new technologies demand improvements for efficient energy management. An adequate forecast of the energy consumption is relevant for the sustainable development of any country. This article proposes a systematic review of selected literature based on search chains formed by the terms forecasting, energy and consumptionapplied to the scientific databases. In the article are compared mostly the models/ techniques used, the considered variables and the error metrics used for obtaining knowledge on each one of the proposals, relieve its features and thus highlight the void in the literature that might be determinant for new research work. As conclusions are made evident the continuous use of neural networks for forecasting theenergy consumption, the importance of determining the input variables and the error measuring for evaluating the precision of the models. Finally, the development of a model for the CEE short term forecast of a Latin-American developing country based on the comparison and evaluation of different techniques/models, variables and already existing tools is proposed as a new line of research.
dc.descriptionO crescente consumo de energia elétrica, as mudanças climáticas e o desenvolvimento de novas tecnologias exigem melhoras para a gestão eficiente da energia. A adequada previsão do consumo de energia é relevante para desenvolver sustentável de qualquer país. Neste artigo, é proposta uma revisão sistemática de literatura selecionada a partir de redes de busca formada pelas palavras ""forecasting"", ""energy"" e ""consumption"" aplicadas nas bases de dados científicas. São comparados, principalmente, os modelos ou técnicas utilizados, as variáveis consideradas e as medidas de erro usadas a fim de obter conhecimento de cada uma das propostas, destacar suas características e, assim, poder evidenciar a lacuna na literatura quepoderia determinar a semente para um novo trabalho de pesquisa. Como conclusões, são observados o uso contínuo de redes neurais artificiais para prognosticar o consumo, a importância de determinar variáveis de entrada e a medição do erro para avaliar a exatidão dos modelos. Finalmente, como nova linha de pesquisa,propõe-se desenvolver um modelo para prever, em curto prazo, de CEE para um país latino-americano em via de desenvolvimento, a partir da comparação e da avaliação de diferentes técnicas e modelos, variáveis e ferramentas já existentes."
dc.formatPDF
dc.format.extentp. 107-142
dc.format.mediumElectrónico
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.publisherUniversidad de Medellín
dc.relation.ispartofseriesRevista Ingenierías Universidad de Medellín; Vol. 19 Núm. 36 (2020)
dc.relation.haspartRevista Ingenierías Universidad de Medellín; Vol. 19 Núm. 36 enero-junio 2020
dc.relation.urihttps://revistas.udem.edu.co/index.php/ingenierias/article/view/2573
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0
dc.sourceRevista Ingenierías Universidad de Medellín; Vol. 19 Núm. 36 (2020): enero-junio; 107-142
dc.subjectPrevisión
dc.subjectConsumo de energía
dc.subjectCorto Plazo
dc.subjectLargo plazo
dc.subjectRedes neuronales
dc.subjectForecast
dc.subjectEnergy consumption
dc.subjectShort term
dc.subjectLong term
dc.subjectNeural networks
dc.subjectPrevisão
dc.subjectConsumo de energia
dc.subjectCurto prazo
dc.subjectLongo prazo
dc.subjectRedes neurais
dc.titleRevisión sistemática de literatura sobre modelos de pronósticos de consumo de energía eléctrica
dc.titleSystematic review of literature on electrical energy consumption forecast models
dc.titleRevisão sistemática de literatura sobre modelos de previsão de consumo de energia elétrica
dc.typeArticle
dc.identifier.doihttps://doi.org/10.22395/rium.v19n36a6
dc.relation.citationvolume19
dc.relation.citationissue36
dc.relation.citationstartpage107
dc.relation.citationendpage142
dc.audienceComunidad Universidad de Medellín
dc.publisher.facultyFacultad de Ingenierías
dc.coverageLat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degreesLong: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees
dc.publisher.placeMedellín
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dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
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