Improvement in Wind Power Forecasting Based on Information Entropy-Related Concepts

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dc.contributor.author Ricardo Jorge Bessa en
dc.contributor.author Vladimiro Miranda en
dc.contributor.author João Gama en
dc.date.accessioned 2017-11-16T12:32:55Z
dc.date.available 2017-11-16T12:32:55Z
dc.date.issued 2008 en
dc.description.abstract This 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.identifier.uri http://repositorio.inesctec.pt/handle/123456789/1577
dc.language eng en
dc.relation 4882 en
dc.relation 208 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title Improvement in Wind Power Forecasting Based on Information Entropy-Related Concepts en
dc.type conferenceObject en
dc.type Publication en
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