Publisher: Renewable Energy Volume 149, April 2020, Pages 664-681
Published on: 12/09/2019
DOI: https://doi.org/10.1016/j.renene.2019.12.048
Download the PaperAbstract:
An accurate analysis of wind speeds is vital to justify wind energy projects. Statistical distributions can be used to characterize wind speeds through considering uncertainty in wind resources. However, the selection of the most suitable probability density function (PDF) is still a challenging task. Therefore, this study aims at developing a framework to accurately evaluate the performance of different PDFs to fit wind speeds, as well as presenting a new metaheuristic optimization algorithm method, called Social Spider Optimization (SSO), for wind characterization purposes. Seven sites in Saudi Arabia are used as case studies. Results indicate that combined PDFs outperform single PDFs in representing the observed wind speeds frequencies at all considered sites. Weibull distribution appears to be the most prevalent single distribution while no combined PDF dominates the others. In addition, the proposed SSO method is found to be the most efficient method for estimating PDFs parameters in Saudi Arabia. Overall, this proposed framework can be used to evaluate different wind PDFs in other countries.
Keywords:
Wind speed, Probability density function, Combined density function, Metaheuristic optimization algorithm, Social spider optimization