Dynamic multi-objective optimization applied to a solar-geothermal multi-generation system for hydrogen production, desalination, and energy storage

The design of optimal energy systems is vital to achieving global environmental and economic targets. In the solar-geothermal multi-generation systems, most previous investigations have relied on static multi-objective optimization approach (SMOA), which may leave considerable room for improvement under certain conditions. this numerical study, condition at operate a system – can simultaneously produce hydrogen, fresh water, electricity, heat, along with storing − determined via dynamic (DMOA). Optimization performed using combination NSGA-II TOPSIS, results are benchmarked against those SMOA. decision variables include solar area, geothermal water extraction mass flow, hydrogen storage pressure. objective functions production exergy efficiencies payback period. It found that when compared SMOA, DMOA significantly improve all functions. annual increases by 14.4, 16.1, 13.5, 14.3%, respectively, while average increase 5.2 3.0%, respectively. use also reduces period from 5.56 4.43 years, 4.4% reduction in This shows such as efficiencies, viability, safety system. • Dynamic outperforms examined Annual freshwater rise 13.5 14.3%. electricity heat generation 14.4 16.1%. Payback drops years. 3.0%.