Wind Power Forecasting With Entropy-Based Criteria Algorithms

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2008

Autores

Ricardo Bessa (Autor) FEUP; Vladimiro Miranda (Autor) FEUP; João Gama (Autor) Outra

Ata de Conferência Internacional

Título: 2008 10TH INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS

Páginas: 106-112

10th International Conference on Probabilistic Methods Applied to Power Systems

Rincon, PR, MAY 25-29, 2008

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 5 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: P-004-54H

Abstract (EN): 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. Renyi's Entropy is combined with a Parzen Windows estimation of the error pdf to form the basis of three criteria (MEE, MCC and MEEF) under which neural networks are trained. The results are favourably compared with the traditional minimum square error (MSE) criterion. Real case examples for two distinct wind parks are presented.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7