Thermodynamic modeling and multi-objective evolutionary-based optimization of a new multigeneration energy system

• Comprehensive thermodynamic modeling of a multi-generation system is reported.
• New multi-generation systems are proposed for more environmentally benign applications.
• Multi-objective optimization technique is applied based on a code developed in the Matlab software.
• A sensitivity analysis to determine the effect of design parameters on objective functions is conducted.

A comprehensive thermodynamic modeling and multi-objective optimization is reported of a multigeneration energy system, based on a micro gas turbine, a dual pressure heat recovery steam generator, an absorption chiller, an ejector refrigeration cycle, a domestic water heater and a proton exchange membrane electrolyzer, that produces multiple commodities: power, heating, cooling, hot water and hydrogen. Energy and exergy analyses and an environmental impact assessment are included. A multi-objective optimization method based on a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) is applied to determine the best design parameters for the system. The two objective functions utilized in the optimization study are the total cost rate of the system, which is the cost associated with fuel, component purchasing and environmental impact, and the system exergy efficiency. The total cost rate of the system is minimized while the cycle exergy efficiency is maximized using an evolutionary algorithm. To provide insight, the Pareto frontier is shown for a multi-objective optimization. In addition, a closed form equation for the relationship between exergy efficiency and total cost rate is derived. A sensitivity analysis is performed to assess the effects of several design parameters on the system total exergy destruction rate, CO2 emission and exergy efficiency.