Multi-Objective Optimization of Molten Carbonate Fuel Cell and Absorption Refrigerator Hybrid System

The multi-objective optimization of the hybrid system consisting of molten carbonate fuel cell and absorption refrigerator is carried out based on the nondominated sorting genetic algorithm II (NSGA-II). The operating current density, temperature, pressure of the molten carbonate fuel cell and the irreversibility parameter of the absorption refrigerator are selected as the decision variables, and the equivalent power, efficiency and ecological performance of the hybrid system are treated as the comprehensive optimization objective functions. The Pareto optimal solution set under the constraint conditions of decision variables is get. Two kinds of effective decision-making tools are used: TOPSIS and LINMAP. They are used to obtain relative optimum solution as well as the optimized operation condition. At last, the results of the multi-objective optimization are compared with those of the single objective optimization. Copyright (C) 2018 Elsevier Ltd. All rights reserved.