Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/107180
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dc.contributor.authorWinter Althaus, Gabrielen_US
dc.contributor.authorGonzález Landín, Begoñaen_US
dc.contributor.authorPulido Alonso, Antonioen_US
dc.contributor.authorGalván González, Blas Joséen_US
dc.contributor.authorMaarouf, Mustaphaen_US
dc.date.accessioned2021-05-11T08:48:08Z-
dc.date.available2021-05-11T08:48:08Z-
dc.date.issued2015en_US
dc.identifier.issn2254-2833en_US
dc.identifier.urihttp://hdl.handle.net/10553/107180-
dc.description.abstractThe economic development is the most influential factor on the power consumption of each country and each region, in long term estimation. In years of economic and financial crisis like the current one, a great variability of Gross Domestic Product (GDP) and Consumer Price Index (CPI) is observed. Particularly, CPI is sensitive to changes in the price of energy and the establishment of monetary policy. Therefore, the improvement of including CPI, in addition to GDP and population, as an explanatory variable to forecast the electricity consumption is investigated. For electricity companies it is important to have efficient prediction techniques to reduce uncertainty in the energy demand and obtain an optimal and realistic scheduling of the production of electricity. In pursuit of more objective conclusions, estimates are made using prediction methods of different nature, such as Multiple Linear Regression and Multiple Logarithmic Regression, which are classical statistical techniques, Support Vector Machine, which is a statistical learning technique, a Genetic Algorithm, which is an evolutionary computation techniques and an Artificial Neural Network, which is a machine learning technique. As a case study, the prediction of electricity demand in the Canary Islands is considered. It is of great interest for being an insulated electric system. The best prediction results are obtained with techniques which posses a greater capability to emulate nonlinear dependencies of the electricity demand in relation to population, GDP and CPI.en_US
dc.languagespaen_US
dc.relation.ispartofDYNAen_US
dc.sourceDYNA [ISSN 2254-2833], v. 4en_US
dc.subject3306 Ingeniería y tecnología eléctricasen_US
dc.subject330609 Transmisión y distribuciónen_US
dc.subject5310 Economía internacionalen_US
dc.subject.otherElectricity Demanden_US
dc.subject.otherLong-Term Predictionen_US
dc.subject.otherMultiple Linear Regressionen_US
dc.subject.otherMultiple Logarithmic Regressionen_US
dc.subject.otherSupport Vector Machineen_US
dc.subject.otherGenetic Algorithmsen_US
dc.subject.otherArtificial Neural Networksen_US
dc.subject.otherInsular Electric Systemen_US
dc.titlePredicciones de la demanda de la energía eléctrica con datos de la actual crisis económica y financiera. Aplicación a la región Canariaen_US
dc.title.alternativePredictions of electricity demand, including data of the present economic and financial crisis. Application to the canary islandsen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typearticleen_US
dc.identifier.doi10.6036/ES7782en_US
dc.identifier.issue3-
dc.relation.volume4en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.utils.revisionen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INGen_US
dc.description.sjr0,238
dc.description.sjrqQ2
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.author.deptGIR SIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Matemáticas-
crisitem.author.deptGIR SIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Matemáticas-
crisitem.author.deptGIR SIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Ingeniería Eléctrica-
crisitem.author.deptGIR SIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.orcid0000-0003-0890-7267-
crisitem.author.orcid0000-0002-7915-0655-
crisitem.author.orcid0000-0002-3406-5086-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameWinter Althaus, Gabriel-
crisitem.author.fullNameGonzález Landín, Begoña-
crisitem.author.fullNamePulido Alonso, Antonio-
crisitem.author.fullNameGalvan Gonzalez,Blas Jose-
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