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- Publisher
- SAGE
- Copyright
- © The Author(s) 2017
- ISSN
- 0309-524X
- eISSN
- 2048-402X
- DOI
- 10.1177/0309524X17721999
- Publisher site
- See Article on Publisher Site
Abstract
The effectiveness of autonomous wind plants depends basically on the characterization, sizing, and environmental design and analysis of its renewable energy conversion system. This article presents an assessment on wind potential characterization to be used to compute the size of a wind farm turbine. Different methods are adopted to estimate parameters of the Weibull distribution. The modified maximum likelihood method is selected as the most accurate with reference to comparison between many approaches output results and measurements provided by the National Institute of Meteorology. Also, an artificial neural network–based algorithm is developed to optimize the MMLM parameters. The monthly wind potential distribution is consequently computed for Sfax, Tunisia. Obtained results are used to optimize the size calculation of wind turbine blades and battery capacity for a standalone wind farm. The proposed approach profitability is evaluated upon the lost produced energy.
Journal
Wind Engineering – SAGE
Published: Dec 1, 2017