Multi-objective optimization of a fire-tube heat recovery steam generator system

In the present paper, a fire-tube heat recovery steam generator (HRSG) system (including evaporator, superheater and economizer) have been considered and multi-objective optimization using genetic algorithm is applied in order to obtain optimum design parameters which yield the maximum Second law efficiency and the least capital cost. Geometric variables including number of tubes in a row, tube length and diameter, transverse pitch of each section and pinch point difference as the thermodynamic variable are considered as optimization parameters. The study was performed via MATLAB to develop model equations and implementing optimization.