Hybrid Evolutionary-Adaptive Approach to Predict Electricity Prices and Wind Power in the Short-Term

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2014

Autores

Osorio, GJO (Autor) Outra; Matias, JCO (Autor) Outra; Catalao, JPS (Autor) Outra

Ata de Conferência Internacional

Título: Proceedings - 2014 Power Systems Computation Conference, PSCC 2014

2014 Power Systems Computation Conference, PSCC 2014

18 August 2014 through 22 August 2014

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00A-8N5

DOI: 10.1109/pscc.2014.7038453

Abstract (EN): Nowadays, with the new paradigm shift in the energy sector and the advent of the smart grid, or even with the mandatory imposition for a gradual reduction of greenhouse gas emissions, the renewable producers, namely the wind power producers are faced with the competitiveness and deregulated structure that characterizes the liberalized electricity market. In a liberalized electricity market, the most important signal for all market players corresponds to the electricity prices. In this sense, accurate approaches for short-term electricity prices prediction are needed, and also for short-term wind power prediction due to the increasing share of wind generation. Hence, this paper presents a new hybrid evolutionary-adaptive approach for wind power and electricity market prices prediction, in the short-term, based on mutual information, wavelet transform, evolutionary particle swarm optimization and adaptive neuro-fuzzy inference system, tested on real case studies, proving its superiority in a comprehensive comparison with other approaches previously published in the scientific literature.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7