Exergoeconomic analysis and optimization of an Integrated Solar Combined Cycle System (ISCCS) using genetic algorithm

In this study, thermoeconomic concept is applied using genetic algorithm for optimization of an Integrated Solar Combined Cycle System (ISCCS) that produces 400 MW of electricity. Attempt is made to minimize objective function including investment cost of equipments and cost of exergy destruction. Optimization process carried out by using exergoeconomic principles and genetic algorithm. The developed code first validated with a thermal system and good comparison is observed. Then the analysis is made for the ISCCS, and it shows that objective function for the optimum operation reduced by about 11%. Also cost of electricity produced by steam turbine and gas turbine in the optimum design of the ISCCS are about 7.1% and 1.17% lower with respect to the base case. These objectives are achieved with 13.3% increase in capital investment. Finally, sensitivity analysis is carried out to study the effect of changes in the unit cost of electricity for the system important parameters such as interest rate, plant lifetime, fuel cost, solar operation period and system construction period.