%0 Conference Proceedings
%T Hybrid Evolutionary Neuro-fuzzy Computational Tool to Forecast Wind Power and Electricity Prices
%+ University of Beira Interior [Portugal] (UBI)
%+ Center for Innovation in Electrical and Energy Engineering [Lisboa] (CIEEE)
%+ Faculdade de Engenharia da Universidade do Porto (FEUP)
%A Osório, G., J.
%A Pousinho, H., I.
%A Matias, J., O.
%A Monteiro, C.
%A Catalão, J., S.
%Z Part 12: Renewable Energy
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 3rd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS)
%C Costa de Caparica, Portugal
%Y Luis M. Camarinha-Matos
%Y Ehsan Shahamatnia
%Y Gonçalo Nunes
%I Springer
%3 Technological Innovation for Value Creation
%V AICT-372
%P 321-328
%8 2012-02-27
%D 2012
%R 10.1007/978-3-642-28255-3_35
%K Forecasting
%K computational tool
%K Wind power
%K Electricity prices
%Z Computer Science [cs]Conference papers
%X The intermittence of the renewable sources due to its unpredictability increases the instability of the actual grid and energy supply. Besides, in a deregulated and competitive framework, producers and consumers require short-term forecasting tools to derive their bidding strategies to the electricity market. This paper proposes a novel hybrid computational tool, based on a combination of evolutionary particle swarm optimization with an adaptive-network-based fuzzy inference system, for wind power forecasting and electricity prices forecasting in the short-term. The results from two real-world case studies are presented, in order to illustrate the proficiency of the proposed computational tool.
%G English
%Z TC 5
%Z WG 5.5
%2 https://inria.hal.science/hal-01365601/document
%2 https://inria.hal.science/hal-01365601/file/978-3-642-28255-3_35_Chapter.pdf
%L hal-01365601
%U https://inria.hal.science/hal-01365601
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-WG5-5
%~ IFIP-DOCEIS
%~ IFIP-AICT-372