Title: Exergy analysis and optimisation of a wind turbine using genetic and searching algorithms

Authors: E. Asgari; M.A. Ehyaei

Addresses: Department of Mechanical Engineering, Dezful Branch, Islamic Azad University, Dezful 98, Iran ' Department of Mechanical Engineering, Pardis Branch Islamic Azad University, Tehran, Iran

Abstract: The present paper deals with a developed and improved approach for exergy analysis and optimisation of Bergey Excel-S wind turbine by searching as well as genetic algorithm. This paper investigated mathematical modelling of wind turbine which finally related to objective function. Results showed that genetic algorithm is a more efficient optimisation method than searching method. By using genetic algorithm, output power, first and second law efficiencies increased by 61%, 56.5%, and 62.2% respectively, if we used optimum values of cut-in, rated, and furling speeds (u_c = 1.27, u_r = 12.19, u_r = 15.73). However by using searching algorithm, output power, first and second law efficiencies increased 8.4%, 8.5%, and 8.4%, respectively, if we used optimum values of cut-in, rated, and furling speeds (u_c = 2.99, u_r = 13.31, u_r = 15.05).

Keywords: wind turbines; wind power; wind energy; entropy; genetic algorithms; exergy analysis; optimisation; mathematical modelling; exergy efficiency; second law; search algorithms.

DOI: 10.1504/IJEX.2015.068228

International Journal of Exergy, 2015 Vol.16 No.3, pp.293 - 314

Received: 20 Feb 2013
Accepted: 01 Apr 2014
Published online: 25 Mar 2015 *

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