Assessing Potential Wind Energy Resources in Saudi Arabia with a Skew-t Distribution
Type
PreprintKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionStatistics Program
KAUST Grant Number
OSR-2015-CRG4-2640Date
2017-03-13Permanent link to this record
http://hdl.handle.net/10754/626467
Metadata
Show full item recordAbstract
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
arXivarXiv
arXiv:1703.04312Additional Links
http://arxiv.org/abs/1703.04312v1http://arxiv.org/pdf/1703.04312v1