Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia
The exigencies as soon as to competitiveness and productivity have influenced in the energetic consumption and the demand of electrical energy in Colombia, reason why at the present time it is of much interest and utility to have access to tools or valid models to reach greater knowledge in which re...
- Autores:
-
Garcia-Guiliany, Jesús
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad del Atlántico
- Repositorio:
- Repositorio Uniatlantico
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniatlantico.edu.co:20.500.12834/779
- Acceso en línea:
- https://hdl.handle.net/20.500.12834/779
- Palabra clave:
- Energy Consumption, Electric Demand, Multiple Linear Regression Model
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc/4.0/
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Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia |
| title |
Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia |
| spellingShingle |
Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia Energy Consumption, Electric Demand, Multiple Linear Regression Model |
| title_short |
Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia |
| title_full |
Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia |
| title_fullStr |
Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia |
| title_full_unstemmed |
Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia |
| title_sort |
Multiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombia |
| dc.creator.fl_str_mv |
Garcia-Guiliany, Jesús |
| dc.contributor.author.none.fl_str_mv |
Garcia-Guiliany, Jesús |
| dc.contributor.other.none.fl_str_mv |
De-la-hoz-Franco, Emiro Rodríguez-Toscano, Andrés-David De-la-Hoz-Hernández, Juan-David Hernandez-Palma, Hugo G |
| dc.subject.keywords.spa.fl_str_mv |
Energy Consumption, Electric Demand, Multiple Linear Regression Model |
| topic |
Energy Consumption, Electric Demand, Multiple Linear Regression Model |
| description |
The exigencies as soon as to competitiveness and productivity have influenced in the energetic consumption and the demand of electrical energy in Colombia, reason why at the present time it is of much interest and utility to have access to tools or valid models to reach greater knowledge in which related to the possible future projections. Next, the results of a quantitative study are presented that through the analysis of data collected between 2007 and 2017 that made possible the construction of a multiple linear regression model to estimate the demand of electric energy. These types of instruments currently originate as alternatives to promote management strategies in the energy field in the country. The final results allow to visualize an estimated figure for the next periods which will serve to contrast with the official results and to generate from this information possible lines of intervention in different organisms. |
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2019 |
| dc.date.issued.none.fl_str_mv |
2019-10-10 |
| dc.date.submitted.none.fl_str_mv |
2019-03-09 |
| dc.date.accessioned.none.fl_str_mv |
2022-11-15T19:14:48Z |
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2022-11-15T19:14:48Z |
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Artículo |
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https://hdl.handle.net/20.500.12834/779 |
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10.32479/ijeep.7813 |
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Universidad del Atlántico |
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Repositorio Universidad del Atlántico |
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https://hdl.handle.net/20.500.12834/779 |
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10.32479/ijeep.7813 Universidad del Atlántico Repositorio Universidad del Atlántico |
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eng |
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eng |
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International Journal of Energy Economics and Policy |
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Universidad del Atlántico |
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Garcia-Guiliany, Jesúsb64c8b5f-a507-493c-9d0c-6c6fe3df8ac8De-la-hoz-Franco, EmiroRodríguez-Toscano, Andrés-DavidDe-la-Hoz-Hernández, Juan-DavidHernandez-Palma, Hugo G2022-11-15T19:14:48Z2022-11-15T19:14:48Z2019-10-102019-03-09https://hdl.handle.net/20.500.12834/77910.32479/ijeep.7813Universidad del AtlánticoRepositorio Universidad del AtlánticoThe exigencies as soon as to competitiveness and productivity have influenced in the energetic consumption and the demand of electrical energy in Colombia, reason why at the present time it is of much interest and utility to have access to tools or valid models to reach greater knowledge in which related to the possible future projections. Next, the results of a quantitative study are presented that through the analysis of data collected between 2007 and 2017 that made possible the construction of a multiple linear regression model to estimate the demand of electric energy. These types of instruments currently originate as alternatives to promote management strategies in the energy field in the country. The final results allow to visualize an estimated figure for the next periods which will serve to contrast with the official results and to generate from this information possible lines of intervention in different organisms.application/pdfenghttp://creativecommons.org/licenses/by-nc/4.0/Attribution-NonCommercial 4.0 Internationalinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2International Journal of Energy Economics and PolicyMultiple Linear Regression Model Applied to the Projection of Electricity Demand in ColombiaPúblico generalEnergy Consumption, Electric Demand, Multiple Linear Regression Modelinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1BarranquillaSede NorteAndrews-Speed, P., Liao, X., Dannreuther, R. (2014), The Strategic Implications of China’s Energy Needs. London: Routledge.Ardila, L.M.C., Cardona, C.J.F. (2017), Structure and current state of the wholesale electricity markets. IEEE Latin America Transactions, 15(4), 669-674.Banco Mundial. (2017), Sección Indicadores. Available from: https://www.datos.bancomundial.org/indicador.Fabra, N., Reguant, M. (2014), Pass-through of emissions costs in electricity markets. American Economic Review, 104(9), 2872-2899.Government Publications Office. editor. (GPO). (2016), International Energy Outlook 2016: With Projections to 2040. Government Printing Office.Holmberg, K., Erdemir, A. (2017), Influence of tribology on global energy consumption, costs and emissions. Friction, 5(3), 263-284.Informe de Operación del Sistema Interconectado Nacional (SIN). (2017), Demanda de Energía Nacional. Available from: http://www.informesanuales.xm.com.co/2017/SitePages/operacion/4-1-Demanda-de-energia-nacional.aspx.Kaytez, F., Taplamacioglu, M.C., Cam, E., Hardalac, F. (2015), Forecasting electricity consumption: A comparison of regression analysis, neural networks and least squares support vector machines. International Journal of Electrical Power and Energy Systems, 67, 431-438.Montgomery, D., Peck, E.A., Vining, G. (2012), Introduction to Linear Regression Analysis. Vol. 821. New Jersey: John Wiley and Sons.Nejat, P., Jomehzadeh, F., Taheri, M.M., Gohari, M., Majid, M.Z.A. (2015), A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2emitting countries). Renewable and Sustainable Energy Reviews, 43, 843-862.Ñustes, W., Riviera, S. (2017), Colombia: territorio de inversión en fuentes no convencionales de energía renovable para la generación eléctrica. Revista Ingeniería, Investigación y Desarrollo, 17, 37-48.Palma, H.H. (2017), Direccionamiento estratégico para la dinamización del sector salud en el departamento del Atlántico. BIOCIENCIAS, 12(1), 79-84.Pukšec, T., Mathiesen, B.V., Novosel, T., Duić, N. (2014), Assessing the impact of energy saving measures on the future energy demand and related GHG (greenhouse gas) emission reduction of Croatia. Energy, 76, 198-209.ánchez-Villegas, A. (2014), In: Martínez-González, M.A., Faulín, F.J., editors. Bioestadística Amigable. Barcelona: Elsevier.Stephanidis, C. editor. (2018), HCI International 2018 Posters’ Extended Abstracts: 20th International Conference. Vol. 852. HCI International 2018, Las Vegas, NV, USA, Proceedings. Springer.Unidad de Planeación Minera y Energética (UPME). (2015), Plan Energetico Nacional Colombia: Ideario Energético 2050. Available from: http://www1.upme.gov.co/Documents/PEN_IdearioEnergetico2050.pdf.http://purl.org/coar/resource_type/c_6501ORIGINAL7813-21483-1-PB.pdf7813-21483-1-PB.pdfMultiple Linear Regression Model Applied to the Projection of Electricity Demand in Colombiaapplication/pdf383142https://repositorio.uniatlantico.edu.co/bitstream/20.500.12834/779/1/7813-21483-1-PB.pdf5b36a47370607bf074d6e9ec3dc5fe92MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8914https://repositorio.uniatlantico.edu.co/bitstream/20.500.12834/779/2/license_rdf24013099e9e6abb1575dc6ce0855efd5MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81306https://repositorio.uniatlantico.edu.co/bitstream/20.500.12834/779/3/license.txt67e239713705720ef0b79c50b2ececcaMD5320.500.12834/779oai:repositorio.uniatlantico.edu.co:20.500.12834/7792022-11-15 14:14:49.004DSpace de la Universidad de Atlánticosysadmin@mail.uniatlantico.edu.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 |