In this study, an inventive multi-generation energy system utilizing solar and biomass energy as a complementary fuel are proposed and analyzed, by means of a thermodynamic and thermoeconomic investigation and multi-objective optimization. For supplying electricity, heating and cooling power, a Rankine cycle including a turbine, a heater and a double effect absorption chiller, for liquefaction of natural gas, a Linde-Hampson cycle, for desalination of sea water, a multi-effect desalination system, for solar energy exploitation, a parabolic Trough solar collector and for combustion of biomass, a burner is utilized. Results outline that, the studied system has potential to generate 16.11 kW electricity, 28.94 kW heating power, 23.41 kW cooling power, 8.8 kg/h fresh water and 0.02 m³/h liquefied natural gas with the energy and exergy efficiencies of 46.8%, 11.2%, and product cost rate of 15.16 $/h. A comprehensive modeling is accomplished by applying mass, energy, exergy and thermoeconomic balances to all component of the multi-generation energy system. The investigation becomes more comprehensive with a sensitivity analysis in order to survey the dependency of the thermodynamic and thermoeconomic performance upon the decision variables such as stack gasses temperature, temperature difference of evaporator1, evaporator2 temperature and Turbine inlet temperature. Finally, optimized performance of the system is determined using Genetic Algorithm and deriving Pareto front considering the exergy efficiency and product cost rate as objective functions. The optimized multi-generation energy system could yield the exergy efficiency of 9.9% and the product cost rate of 13.32 $/h.

在这项研究中，通过热力学和热经济学研究以及多目标优化，提出并分析了利用太阳能和生物质能作为补充燃料的创造性多代能源系统。为了提供电力，加热和冷却动力，包括涡轮机，加热器和双效吸收式冷却器的兰金循环，用于天然气的液化的林肯循环，用于海水淡化的林德-汉普森循环，多效淡化系统，为了利用太阳能，使用了抛物槽式太阳能集热器，为了燃烧生物质，使用了燃烧器。结果表明，所研究的系统具有产生16.11 kW电力，28.94 kW热功率，23.41 kW制冷功率，8.8 kg / h淡水和0.02 m ^3的潜力。/ h液化天然气，能源和火用效率分别为46.8％，11.2％和产品成本率为15.16 $ / h。通过将质量，能量，火用和热经济平衡应用于多代能源系统的所有组成部分，可以完成全面的建模。为了进行热力学和热经济性能对决策变量（如烟囱气体温度，蒸发器1，蒸发器1的温差，蒸发器2的温度和涡轮进口温度）的依赖关系的调查，此研究变得更加全面。最后，使用遗传算法并以火用效率和产品成本比率为目标函数，推导帕累托锋，确定系统的最佳性能。