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Decision Support Model for Optimal Design of Wind Technologies Based Techno–Economic Approach

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submitted on 2023-08-24, 11:40 and posted on 2023-09-20, 09:30 authored by Fatima-Azahraa Bourhim, Samir Berrhazi, Ahmed Ouammi, Rachid Benchrifa

This paper aims to propose a practical decision support model for the optimal design of future wind turbines based on available wind potential on the site of interest. A developed decision support model based a comprehensive wind turbine modeling and a constrained techno-economic optimization framework is presented. Optimization was subject to the Net Present Value ( NPV ) maximization of the net incomes from wind energy generation, under the constraints on wind turbine nominal power restriction and the maximum ratio permitted between the rotor diameter and tower hub height. Optimizations of rotor diameter and tower height sizing have direct impacts on energy and cost production, those parameters have been considered as the design variables. The optimal design selection considers: the nominal power, rotor diameter, and tower hub height, which led to the maximum NPV in a specific site. Furthermore, an analysis of the Levelized Cost of Energy production ( LCOE ) has been performed. The developed decision support model has been tested and applied to a case study to validate its application and performance. The developed model was verified and significant results were achieved using three different wind sites: Dakhla, Casablanca, and Tanger. Results showed that the optimal design of the wind turbine technologies is given by the limit conditions cited, conducting to the maximum NPV with low LCOE and more exploitation of available wind potential in Dakhla and Tanger; however Casablanca was found as no profitable site for wind projects presenting negative NPV.

Other Information

Published in: IEEE Access
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1109/access.2021.3123561

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

IEEE

Publication Year

  • 2021

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Qatar University
  • College of Arts and Sciences - QU
  • Center for Sustainable Development - CAS