Multinodal Load Forecasting Using an ART-ARTMAP-Fuzzy Neural Network and PSO Strategy

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorIFMT-
Autor(es): dc.contributorUniversidade Federal de Mato Grosso do Sul (UFMS)-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorAntunes, Juliana Fonseca-
Autor(es): dc.creatorSouza Araujo, Nelcileno Virgilio de-
Autor(es): dc.creatorMinussi, Carlos Roberto [UNESP]-
Autor(es): dc.creatorIEEE-
Data de aceite: dc.date.accessioned2022-02-22T00:08:27Z-
Data de disponibilização: dc.date.available2022-02-22T00:08:27Z-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2013-01-01-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/196091-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/196091-
Descrição: dc.descriptionThis work presents a system based on Artificial Neural Networks and PSO (Particle Swarm Optimization) strategy, to multinodal load forecasting, i.e., forecasting in several points of the electrical network (substations, feeders, etc.). Short-term load forecasting is an important task to planning and operation of electric power systems. It is necessary precise and reliable techniques to execute the predictions. Therefore, the load forecasting uses the Adaptive Resonance Theory. To improve the precision, the PSO technique is used to choose the best parameters for the Artificial Neural Networks training. Results show that the use of this technique with a little set of training data improves the parameters of the neural network, calculated by the MAPE (mean absolute perceptual error) of the global and multinodal load forecasted.-
Descrição: dc.descriptionIFMT, Inst Educ Ciencia & Tecnol Mato Grosso, Dept Informat, Cuiaba, Brazil-
Descrição: dc.descriptionUniv Fed Mato Grosso, UFMT, Inst Comp, Cuiaba, Brazil-
Descrição: dc.descriptionUNESP Univ Estadual Paulista, Dept Engn Eletr, Ilha Solteira, Brazil-
Descrição: dc.descriptionUNESP Univ Estadual Paulista, Dept Engn Eletr, Ilha Solteira, Brazil-
Formato: dc.format6-
Idioma: dc.languageen-
Publicador: dc.publisherIeee-
Relação: dc.relation2013 Ieee Grenoble Powertech (powertech)-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectMultinodal Load Forecasting-
Palavras-chave: dc.subjectParticle Swarm Optimization-
Palavras-chave: dc.subjectAdaptive Resonance Theory-
Palavras-chave: dc.subjectArtificial Neural Network-
Título: dc.titleMultinodal Load Forecasting Using an ART-ARTMAP-Fuzzy Neural Network and PSO Strategy-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.