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 (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).