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A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings

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A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings

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dc.contributor.author Hernandez, Luis es_ES
dc.contributor.author Baladron, Carlos es_ES
dc.contributor.author Aguiar, Javier M. es_ES
dc.contributor.author Carro, Belen es_ES
dc.contributor.author Sanchez-Esguevillas, Antonio J. es_ES
dc.contributor.author Lloret Mauri, Jaime es_ES
dc.contributor.author Massana, Joaquim es_ES
dc.date.accessioned 2016-05-27T14:38:03Z
dc.date.available 2016-05-27T14:38:03Z
dc.date.issued 2014
dc.identifier.issn 1553-877X
dc.identifier.uri http://hdl.handle.net/10251/64858
dc.description.abstract Recently there has been a significant proliferation in the use of forecasting techniques, mainly due to the increased availability and power of computation systems and, in particular, to the usage of personal computers. This is also true for power network systems, where energy demand forecasting has been an important field in order to allow generation planning and adaptation. Apart from the quantitative progression, there has also been a change in the type of models proposed and used. In the '70s, the usage of non-linear techniques was generally not popular among scientists and engineers. However, in the last two decades they have become very important techniques in solving complex problems which would be very difficult to tackle otherwise. With the recent emergence of smart grids, new environments have appeared capable of integrating demand, generation, and storage. These employ intelligent and adaptive elements that require more advanced techniques for accurate and precise demand and generation forecasting in order to work optimally. This review discusses the most relevant studies on electric demand prediction over the last 40 years, and presents the different models used as well as the future trends. Additionally, it analyzes the latest studies on demand forecasting in the future environments that emerge from the usage of smart grids. es_ES
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers (IEEE) es_ES
dc.relation.ispartof Communications Surveys and Tutorials, IEEE Communications Society es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Electric demand forecasting es_ES
dc.subject Short-term load forecasting es_ES
dc.subject Smart grid es_ES
dc.subject Microgrid es_ES
dc.subject Smart building es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/SURV.2014.032014.00094
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres es_ES
dc.description.bibliographicCitation Hernandez, L.; Baladron, C.; Aguiar, JM.; Carro, B.; Sanchez-Esguevillas, AJ.; Lloret Mauri, J.; Massana, J. (2014). A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings. Communications Surveys and Tutorials, IEEE Communications Society. 16(3):1460-1495. doi:10.1109/SURV.2014.032014.00094 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://dx.doi.org/10.1109/SURV.2014.032014.00094 es_ES
dc.description.upvformatpinicio 1460 es_ES
dc.description.upvformatpfin 1495 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 16 es_ES
dc.description.issue 3 es_ES
dc.relation.senia 288057 es_ES


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