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Intelligent Optimized Wind Turbine Cost Analysis for Different Wind Sites in Jordan

Author

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  • Ayman Al-Quraan

    (Electrical Power Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid 21163, Jordan)

  • Bashar Al-Mhairat

    (Electrical Power Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid 21163, Jordan)

Abstract

Choosing the right wind site and estimating the extracted energy of the wind turbines are essential to successfully establishing a wind farm in a specific wind site. In this paper, a method for estimating the extracted energy of the wind farms using several mathematical models is proposed. The estimating method, which was based on five wind turbines, Q 1 , Q 2 , Q 3 , Q 4 , and Q 5 and three wind distribution models, gamma, Weibull, and Rayleigh, was used to suggest suitable specifications of a wind turbine for a specific wind site and maximize the extracted energy of the proposed wind farm. An optimization problem, developed for this purpose, was solved using the whale optimization algorithm (WOA). The suggested method was tested using several potential wind sites in Jordan. The proposed wind farms at these sites achieved the maximum extracted energy, maximum capacity factor ( CF ), and minimum levelized cost of energy ( LCoE ) based on the solution of the developed optimization problem. The developed model with Q 3 and the Rayleigh distribution function was validated with real measurement data from several wind farms in Jordan. Error analysis showed that the difference between the measured and estimated energy was less than 20%. The study validated the provided model, which can now be utilized routinely for the assessment of wind energy potential at a specific wind site.

Suggested Citation

  • Ayman Al-Quraan & Bashar Al-Mhairat, 2022. "Intelligent Optimized Wind Turbine Cost Analysis for Different Wind Sites in Jordan," Sustainability, MDPI, vol. 14(5), pages 1-24, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:3075-:d:765395
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    4. Ayman Al-Quraan & Bashar Al-Mhairat & Ahmad M. A. Malkawi & Ashraf Radaideh & Hussein M. K. Al-Masri, 2023. "Optimal Prediction of Wind Energy Resources Based on WOA—A Case Study in Jordan," Sustainability, MDPI, vol. 15(5), pages 1-23, February.
    5. Rubel C. Das & Yu-Lin Shen, 2023. "Analysis of Wind Farms under Different Yaw Angles and Wind Speeds," Energies, MDPI, vol. 16(13), pages 1-19, June.
    6. Mahfuzur Rahman & Solaiman Chowdhury & Mohammad Shorfuzzaman & Mohammad Kamal Hossain & Mohammad Hammoudeh, 2023. "Peer-to-Peer Power Energy Trading in Blockchain Using Efficient Machine Learning Model," Sustainability, MDPI, vol. 15(18), pages 1-15, September.

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