a new approach to optimization of cogeneration systems using genetic algorithm

application of cogeneration systems based gas turbine for heat and power production is increasing. because of finite natural energy resources and increasing energy demand the cost effective design of energy systems is essential. cgam problem as a cogeneration system is considered here for analyzing. two new approaches are considered, first in thermodynamic model of gas turbine and cogeneration system considering blade cooling of gas turbine and second using genetic algorithm for optimization. the problem has been optimized from thermodynamic and thermoeconomic view point. results show that turbine inlet temperature (tit) in thermodynamic optimum condition is higher than thermoeconomic one, while blade cooling technology must be better for optimum thermodynamic condition. heat recovery of recuperator is lower in thermoeconomic case; also, stack temperature is higher relative to thermodynamic case. the sensitivity of the optimal solution to the decision variables is studied. it has been shown that while for both thermodynamic and thermoeconomic optimum condition, pressure ratio, blade cooling technology factor and pinch-point temperature difference (only for thermoeconomic case) has the lowest effect, turbomachinery efficiencies (epically compressor polytropic efficiency) have the major effect on performance of cycle. finally; a new product known as mercury 50 gas turbine is studied for a cogeneration system and it has been optimized thermoeconomicly. results show good agreement with manufacturer data.