Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43804
Title: A new probabilistic method to estimate the long-term wind speed characteristics at a potential wind energy conversion site
Authors: Carta, José A. 
Velázquez, Sergio 
UNESCO Clasification: 3322 Tecnología energética
1208 Probabilidad
Keywords: Conditional distributions
Measure–correlate–predict method
Wind speed
Stratified cross-validation
Root relative squared error
Issue Date: 2011
Publisher: 0360-5442
Journal: Energy 
Abstract: This paper proposes the use of a new Measure–Correlate–Predict (MCP) method to estimate the long-term wind speed characteristics at a potential wind energy conversion site. The proposed method uses the probability density function of the wind speed at a candidate site conditioned to the wind speed at a reference site. Contingency-type bivariate distributions with specified marginal distributions are used for this purpose. The proposed model was applied in this paper to wind speeds recorded at six weather stations located in the Canary Islands (Spain). The conclusion reached is that the method presented in this paper, in the majority of cases, provides better results than those obtained with other MCP methods used for purposes of comparison. The metrics employed in the analysis were the coefficient of determination (R2) and the root relative squared error (RRSE). The characteristics that were analysed were the capacity of the model to estimate the long-term wind speed probability distribution function, the long-term wind power density probability distribution function and the long-term wind turbine power output probability distribution function at the candidate site.
URI: http://hdl.handle.net/10553/43804
ISSN: 0360-5442
DOI: 10.1016/j.energy.2011.02.008
Source: Energy [ISSN 0360-5442],v. 36 (5), p. 2671-2685
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