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Autores
Orientador(es)
Resumo(s)
A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. 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. Finally, conclusions are duly drawn.
Descrição
Palavras-chave
Electricity market Fuzzy logic Neural networks Price forecasting Swarm optimization Wavelet transform Neuro-evolutionary algorithm Arima models Market Network System Decomposition Information Environment Transform
Contexto Educativo
Citação
CATALÃO, J. P. S.; POUSINHO, H. M. I.; MENDES, V. M. F. - Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting. IEEE Transactions on Power Systems. ISSN 0885-8950. Vol. 26, n.º 1 (2011) p.137-144.
Editora
IEEE-INST Electrical Electronics Engineers INC