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    Assessing Potential Wind Energy Resources in Saudi Arabia with a Skew-t Distribution

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    1703.04312v1.pdf
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    Description:
    Preprint
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    Type
    Preprint
    Authors
    Tagle, Felipe
    Castruccio, Stefano
    Crippa, Paola
    Genton, Marc G. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Statistics Program
    KAUST Grant Number
    OSR-2015-CRG4-2640
    Date
    2017-03-13
    Permanent link to this record
    http://hdl.handle.net/10754/626467
    
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    Abstract
    Facing increasing domestic energy consumption from population growth and industrialization, Saudi Arabia is aiming to reduce its reliance on fossil fuels and to broaden its energy mix by expanding investment in renewable energy sources, including wind energy. A preliminary task in the development of wind energy infrastructure is the assessment of wind energy potential, a key aspect of which is the characterization of its spatio-temporal behavior. In this study we examine the impact of internal climate variability on seasonal wind power density fluctuations using 30 simulations from the Large Ensemble Project (LENS) developed at the National Center for Atmospheric Research. Furthermore, a spatio-temporal model for daily wind speed is proposed with neighbor-based cross-temporal dependence, and a multivariate skew-t distribution to capture the spatial patterns of higher order moments. The model can be used to generate synthetic time series over the entire spatial domain that adequately reproduces the internal variability of the LENS dataset.
    Publisher
    arXiv
    arXiv
    arXiv:1703.04312
    Additional Links
    http://arxiv.org/abs/1703.04312v1
    http://arxiv.org/pdf/1703.04312v1
    Collections
    Preprints; Preprints; Statistics Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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