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Hybrid Evolutionary Neuro-fuzzy Computational Tool to Forecast Wind Power and Electricity Prices

Title
Hybrid Evolutionary Neuro-fuzzy Computational Tool to Forecast Wind Power and Electricity Prices
Type
Article in International Conference Proceedings Book
Year
2012
Authors
Osorio, GJ
(Author)
Other
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Pousinho, HMI
(Author)
Other
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Matias, JCO
(Author)
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Conference proceedings International
Pages: 321-328
3rd IFIP/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems
Costa de Caparica, PORTUGAL, FEB 27-29, 2012
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Other information
Authenticus ID: P-002-FGM
Abstract (EN): 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.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 8
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