Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of one week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a ca...

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Detalhes bibliográficos
Autor principal: Catalao, J. P. S. (author)
Outros Autores: Pousinho, H. M. I. (author), Mendes, V. M. F. (author)
Formato: article
Idioma:por
Publicado em: 2017
Assuntos:
Texto completo:http://hdl.handle.net/10174/21178
País:Portugal
Oai:oai:dspace.uevora.pt:10174/21178
Descrição
Resumo:In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of one week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. © 2011 Elsevier Ltd. All rights reserved.