Abstract
A simple gas turbine cycle namely as the Kraftwerk Union AG unit including a Siemens gas turbine model V93.1 with 60 MW nominal power and 26.0% thermal efficiency utilized in the Fars power plant located is considered for the efficiency enhancement. A typical tubular vertical recuperative heat exchanger is designed in order to integrate into the cycle as an air pre-heater for thermal efficiency improvement. Thermal and geometric specifications of the recuperative heat exchanger are obtained in a multi-objective optimization process. The exergetic efficiency of the gas cycle is maximized while the payback time for the capital investment of the recuperator is minimized. Combination of these objectives and decision variables with suitable engineering and physical constraints makes a set of the MINLP optimization problem. Optimization programming is performed using the NSGA-II algorithm and Pareto optimal frontiers are obtained in three cases including the minimum, average and maximum ambient air temperatures. In each case, the final optimal solution has been selected using three decision-making approaches including the fuzzy Bellman-Zadeh, LINMAP and TOPSIS methods. It has been shown that the TOPSIS and LINMAP decision-makers when applied on the Pareto frontier which is obtained at average ambient air temperature yields best results in comparison to other cases.
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