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Wang and Mendel’s Fuzzy Rule Learning Method for Energy Consumption Forecasting considering the Influence of Environmental Temperature

2016Journal article Restricted access
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dc.contributor.authorJozi, Aria
dc.contributor.authorPinto, Tiago
dc.contributor.authorPraça, Isabel
dc.contributor.authorSilva, Francisco
dc.contributor.authorTeixeira, Brigida
dc.contributor.authorVale, Zita
dc.date.accessioned2017-07-13T10:33:04Z
dc.date.embargo2117
dc.date.issued2016
dc.description.abstractReliable consumption forecasts are crucial in several aspects of power and energy systems, e.g. to take advantage of the full potential of flexibility from consumers and to support the management from operators. With this need, several methodologies for electricity forecasting have emerged. However, the study of correlated external variables, such as temperature or luminosity, is still far from adequate. This paper presents the application of the Wang and Mendel’s Fuzzy Rule Learning Method (WM) to forecast electricity consumption. The proposed approach includes two distinct strategies, the first one uses only the electricity consumption as the input of the method, and the second strategy considers a combination of the electricity consumption and the environmental temperature as the input, in order to extract value from the correlation between the two variables. A case study that considers the forecast of the energy consumption of a real office building is also presented. Results show that the WM method using the combination of energy consumption data and environmental temperature is able to provide more reliable forecasts for the energy consumption than several other methods experimented before, namely based on artificial neural networks and support vector machines. Additionally, the WM approach that considers the combination of input values achieves better results than the strategy that considers only the consumption history, hence concluding that WM is appropriate to incorporate different information sources.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/GIIS.2016.7814944pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/10029
dc.language.isoengpt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relation.ispartofseriesGIIS;2016
dc.relation.publisherversionhttp://ieeexplore.ieee.org/document/7814944/pt_PT
dc.subjectElectricity Consumptionpt_PT
dc.subjectEnvironmental Temperaturept_PT
dc.subjectForecastingpt_PT
dc.subjectWang and Mendel’s Fuzzy Rulept_PT
dc.subjectFuzzy Rule Based Systemspt_PT
dc.titleWang and Mendel’s Fuzzy Rule Learning Method for Energy Consumption Forecasting considering the Influence of Environmental Temperaturept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleGLOBAL INFORMATION INFRASTRUCTURE AND NETWORKING SYMPOSIUMpt_PT
person.familyNamePinto
person.familyNamePraça
person.familyNameSilva
person.familyNameVale
person.givenNameTiago
person.givenNameIsabel
person.givenNameFrancisco
person.givenNameZita
person.identifierR-000-T7J
person.identifier299522
person.identifier1422904
person.identifier632184
person.identifier.ciencia-id2414-9B03-C4BB
person.identifier.ciencia-idC710-4218-1BFF
person.identifier.ciencia-idB81C-4758-2D59
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8248-080X
person.identifier.orcid0000-0002-2519-9859
person.identifier.orcid0000-0001-8570-4362
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridT-2245-2018
person.identifier.ridK-8430-2014
person.identifier.ridI-5708-2015
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35219107600
person.identifier.scopus-author-id22734900800
person.identifier.scopus-author-id56870827300
person.identifier.scopus-author-id7004115775
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication8d58ddc0-1023-47c0-a005-129d412ce98d
relation.isAuthorOfPublicationee4ecacd-c6c6-41e8-bca1-21a60ff05f50
relation.isAuthorOfPublicationd050c135-4d9d-4fb2-97d1-cac97be3f6b9
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