Wind farms model aggregation using probabilistic clustering

• Autor(es): Fernandes, Paula O. ; Ferreira, Ângela P.
• Data: 2013
• Identificador Persistente: http://hdl.handle.net/10198/10862
• Origem: Biblioteca Digital do IPB
• Assunto(s): Wind farms; Wind turbine generators; Cluster analysis; Discriminant analysis
• Tipo de Documento: Artigo
• Idioma: Inglês

Descrição

The main objective of this research is the identification of homogeneous groups within wind farms of a major operator playing in the energy sector in Portugal, based on two multivariate analyses: Hierarchical Cluster Analysis and Discriminant Analysis, by using two independent variables: annual liquid hours and net production. From the produced outputs there were identified three homogenous groups of wind farms: (1) medium Installed Capacity and Induction Generator based Technology, (2) high Installed Capacity and Synchronous Generator based Technology and (3) medium Installed Capacity and Synchronous Generator based Technology, which includes the wind farms with the higher annual liquid hours. It has been found that the results obtained by cluster analysis are well classified, with a total percentage of correct classification of 97,1%, which can be considered excellent.