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

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 (uc = 1.27, ur = 12.19, ur = 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 (uc = 2.99, ur = 13.31, ur = 15.05).