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All Journal International Journal of Electrical and Computer Engineering
Elbarkouky, Reda A.
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Computer Science & IT Electrical & Electronics Engineering

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Commercial wind turbines modeling using single and composite cumulative probability density functions Omar, Othman A. M.; Ahmed, Hamdy M.; Elbarkouky, Reda A.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp47-56

Abstract

As wind turbines more widely used with newer manufactured types and larger electrical power scales, a brief mathematical modelling for these wind turbines operating power curves is needed for optimal site matching selections. In this paper, 24 commercial wind turbines with different ratings and different manufactures are modelled using single cumulative probability density functions modelling equations. A new mean of a composite cumulative probability density function is used for better modelling accuracy. Invasive weed optimization algorithm is used to estimate different models designing parameters. The best cumulative density function model for each wind turbine is reached through comparing the RMSE of each model. Results showed that Weibull-Gamma composite is the best modelling technique for 37.5% of the reached results.
Co-Authors Ahmed, Hamdy M. Omar, Othman A. M.