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A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles

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A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles

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dc.contributor.author Serrano-Guerrero, Xavier es_ES
dc.contributor.author Escrivá-Escrivá, Guillermo es_ES
dc.contributor.author Luna-Romero, Santiago es_ES
dc.contributor.author Clairand, Jean-Michel es_ES
dc.date.accessioned 2021-06-04T03:33:11Z
dc.date.available 2021-06-04T03:33:11Z
dc.date.issued 2020-03 es_ES
dc.identifier.uri http://hdl.handle.net/10251/167332
dc.description.abstract [EN] Electricity consumption patterns reveal energy demand behaviors and enable strategY implementation to increase efficiency using monitoring systems. However, incorrect patterns can be obtained when the time-series components of electricity demand are not considered. Hence, this research proposes a new method for handling time-series components that significantly improves the ability to obtain patterns and detect anomalies in electrical consumption profiles. Patterns are found using the proposed method and two widespread methods for handling the time-series components, in order to compare the results. Through this study, the conditions that electricity demand data must meet for making the time-series analysis useful are established. Finally, one year of real electricity consumption is analyzed for two different cases to evaluate the effect of time-series treatment in the detection of anomalies. The proposed method differentiates between periods of high or low energy demand, identifying contextual anomalies. The results indicate that it is possible to reduce time and effort involved in data analysis, and improve the reliability of monitoring systems, without adding complex procedures. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Energies es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Electricity consumption profiles es_ES
dc.subject Electricity consumption patterns es_ES
dc.subject Building management systems es_ES
dc.subject Outlier detection es_ES
dc.subject Time-series treatment es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/en13051046 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPS//6602277-01/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica es_ES
dc.description.bibliographicCitation Serrano-Guerrero, X.; Escrivá-Escrivá, G.; Luna-Romero, S.; Clairand, J. (2020). A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles. Energies. 13(5):1-23. https://doi.org/10.3390/en13051046 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/en13051046 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 23 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 13 es_ES
dc.description.issue 5 es_ES
dc.identifier.eissn 1996-1073 es_ES
dc.relation.pasarela S\404533 es_ES
dc.contributor.funder Universidad Politécnica Salesiana, Ecuador es_ES
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dc.subject.ods 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos es_ES


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