Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/1577
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dc.contributor.authorRicardo Jorge Bessaen
dc.contributor.authorVladimiro Mirandaen
dc.contributor.authorJoão Gamaen
dc.date.accessioned2017-11-16T12:32:55Z-
dc.date.available2017-11-16T12:32:55Z-
dc.date.issued2008en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/1577-
dc.description.abstractThis paper reports new results in adopting entropy concepts to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. It also addresses the differences relevant to power system operation between off-line and on-line training of neural networks. Real case examples are presented.en
dc.languageengen
dc.relation4882en
dc.relation208en
dc.rightsinfo:eu-repo/semantics/embargoedAccessen
dc.titleImprovement in Wind Power Forecasting Based on Information Entropy-Related Conceptsen
dc.typeconferenceObjecten
dc.typePublicationen
Appears in Collections:CPES - Articles in International Conferences

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