Application of Differential Evolution for Wind Turbine Micrositing

  • Shafiq -ur-Rehman Massan Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Karachi
  • Asim Imdad Wagan Mohammad Ali Jinnah University, Karachi
  • Muhammad Mujtaba Shaikh Department of Basic Sciences and Related Studies, Mehran University of Engineering and Technology, Jamshoro.
  • Muhammad Saleh Shah Government Saifee Zahabi Edhi College of Education, Karachi.
DOI: https://doi.org/10.22581/muet1982.1702.13

Abstract

WTM (Wind Turbine Micrositing) has been an important topic of discussion in recent times. A number of Evolutionary Algorithms have been applied to the WTM problem. The DEA (Differential Evolution Algorithm) is used for a bi-constrained optimization for getting maximum power production at the least cost from a 2x2 km space. It is shown that the DEA performs comparably to the GA (Genetic Algorithms) for wind farm optimization. The optimal configuration obtained enlists the number of turbines, the cost of power generated as well as the power produced. Moreover, this study is augmented by comparison with past approaches by using the GA for the same purpose.

Published
Apr 1, 2017
How to Cite
MASSAN, Shafiq -ur-Rehman et al. Application of Differential Evolution for Wind Turbine Micrositing. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 36, n. 2, p. 353-366, apr. 2017. ISSN 2413-7219. Available at: <https://publications.muet.edu.pk/index.php/muetrj/article/view/316>. Date accessed: 15 nov. 2024. doi: http://dx.doi.org/10.22581/muet1982.1702.13.
Citation Formats
Issue
Vol 36 No 2 (2017): April Issue
Section
Articles
This is an open Access Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License