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Pattern aggregation of wind energy conversion technologies using clustering analysis

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Detalhes bibliográficos
Resumo:The main objective of this research is the identification of homogeneous groups within a set of wind farms of a major wind energy promoter in Portugal, based on two multivariate analyses: Hierarchical Cluster Analysis and K-means Clustering, using two independent variables, capacity factor and net production, both per year. K-means Clustering output provides the same results as the Hierarchical Cluster Analysis. Outputs allowed the identification of three homogenous groups of wind farms: (1) medium installed capacity and asynchronous generator based technologies, (2) high installed capacity and direct driven synchronous generator based technology and (3) low installed capacity with no differentiation on the technology concept, but including the wind farms with the higher capacity factors.
Autores principais:Fernandes, Paula Odete
Outros Autores:Ferreira, Ângela P.
Assunto:Hierarchical Cluster Analysis K-means Clustering Wind farms Wind turbine generators
Ano:2014
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:The main objective of this research is the identification of homogeneous groups within a set of wind farms of a major wind energy promoter in Portugal, based on two multivariate analyses: Hierarchical Cluster Analysis and K-means Clustering, using two independent variables, capacity factor and net production, both per year. K-means Clustering output provides the same results as the Hierarchical Cluster Analysis. Outputs allowed the identification of three homogenous groups of wind farms: (1) medium installed capacity and asynchronous generator based technologies, (2) high installed capacity and direct driven synchronous generator based technology and (3) low installed capacity with no differentiation on the technology concept, but including the wind farms with the higher capacity factors.