optimization of single and multi objective hlr dry cooling tower of the combined cycle power plant using genetic algorithm

in this paper the effect of site conditions, which are altitude, temperature and relative humidity and also heat dissipation capacity are investigated on the optimized design of natural draft dry cooling towers with specific kind of heat exchangers, known as forgo t60 type. a genetic algorithm program has been developed for optimized design of these cooling towers. objective function includes both cost and performance of the tower. the optimized dimensions of the tower, the number of heat exchangers and mass flow rate of water and air are the results of this optimization program. the results show it is possible to find the variation of the optimized value of each design variable versus the variations of the site conditions and heat dissipation capacity. also finding an optimum for all design parameters for any site condition is possible; however it is very dependent on how exact the cost analysis is.