Electric power systems load forecasting: A survey

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorLotufo, D. P.-
Autor(es): dc.creatorMinussi, C. R.-
Data de aceite: dc.date.accessioned2025-08-21T18:14:18Z-
Data de disponibilização: dc.date.available2025-08-21T18:14:18Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued1999-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/PTC.1999.826467-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/228326-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/228326-
Descrição: dc.descriptionThis work reviews the latest works on load forecasting, classifying them according to presented methods and models, as statistical, intelligent systems, neural networks and fuzzy logic. As there are many different models and methods, we have studied the principal ones since those considered as classical statistical until those modern like neural networks and fuzzy logic. We emphasize the importance of load forecasting in modern operation centers, and conclude that nowadays the most used forecasting methods are the neural networks and fuzzy logic, but the statistical ones continue being used although in less quantity.-
Descrição: dc.descriptionDEE/FEIS/UNESP Ilha-
Descrição: dc.descriptionDEE/FEIS/UNESP Ilha-
Formato: dc.format36-
Idioma: dc.languageen-
Relação: dc.relationInternational Conference on Electric Power Engineering, PowerTech Budapest 1999-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectFuzzy logic-
Palavras-chave: dc.subjectIntelligent systems-
Palavras-chave: dc.subjectLoad forecasting-
Palavras-chave: dc.subjectLoad models-
Palavras-chave: dc.subjectNeural networks-
Palavras-chave: dc.subjectPrediction methods-
Título: dc.titleElectric power systems load forecasting: A survey-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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