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Classification of customers based on temporal load profile patterns

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Classification of customers based on temporal load profile patterns

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dc.contributor.author Benítez Sánchez, Ignacio Javier es_ES
dc.contributor.author Quijano Lopez, Alfredo es_ES
dc.contributor.author Delgado Espinos, Ignacio es_ES
dc.contributor.author Diez Ruano, José Luís es_ES
dc.date.accessioned 2018-07-01T04:21:50Z
dc.date.available 2018-07-01T04:21:50Z
dc.date.issued 2017 es_ES
dc.identifier.uri http://hdl.handle.net/10251/104883
dc.description.abstract [EN] The deployment of Advanced Metering Infrastructure (AMI) is providing to utilities large amounts of energy consumption data from their customers, in form of daily load profiles with energy consumed per hour or a smaller period. These data can yield valuable results when analyzed, in order to extract useful knowledge about the typical patterns of consumption of energy from the customers. The proper mechanisms and tools have to be developed and implemented for this objective. Big Data and Big Data Analytics systems will contribute to analyze this information and help to extract knowledge from the data, summarized in form of patterns or other mining knowledge, that will aid experts in decision support. In the present work a classification of customers based on their temporal load profiles is proposed. This classification procedure could be implemented in the current Big Data Analytics software systems, providing an added value to their statistical analysis options. Previous works in the literature present algorithms that allow to classify load profiles from customers by processing batch datasets and obtaining static patterns of load profiles. The proposed technique allows to analyze patterns not only in shape but also in their evolution or trend of energy consumption at each hour of the day through time. Specific quantitative indicators that characterize the patterns (and the consumers associated to them) are described and tested for this purpose. es_ES
dc.language Inglés es_ES
dc.publisher CIGRE Conseil international des grands réseaux électriques es_ES
dc.relation.ispartof Cigre Science & engineering es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Load profiles es_ES
dc.subject Dynamic clustering es_ES
dc.subject Pattern recognition es_ES
dc.subject Classification es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title Classification of customers based on temporal load profile patterns es_ES
dc.type Artículo es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Tecnología Eléctrica - Institut de Tecnologia Elèctrica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Benítez Sánchez, IJ.; Quijano Lopez, A.; Delgado Espinos, I.; Diez Ruano, JL. (2017). Classification of customers based on temporal load profile patterns. Cigre Science & engineering. (7):143-148. http://hdl.handle.net/10251/104883 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://www.cigre.org/Menu-links/Publications es_ES
dc.description.upvformatpinicio 143 es_ES
dc.description.upvformatpfin 148 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.issue 7 es_ES
dc.identifier.eissn 2426-1335 es_ES
dc.relation.pasarela 326745 es_ES


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