Energy, exergy, economic, and environmental (4E) analysis and ANN-GA optimization of an advanced hybrid cycle producing hydrogen, freshwater, and green methane from recycled CO2

Amidst escalating global energy demands and intensifying environmental crises, transitioning from conventional linear energy models to integrated hybrid systems has become a critical imperative for achieving long-term global sustainability. This study proposes a novel, integrated hybrid multi-generation energy system comprising a Brayton cycle, a Rankine cycle, a Dual-Fluid ORC, a PEM electrolyzer, a MED unit, a methanation reactor, and Thermoelectric Generators (TEGs) to generate electricity while producing freshwater, synthetic methane, and hydrogen. A key innovation of this configuration is its internal carbon capture and utilization loop, in which waste CO 2 captured from the gas turbine exhaust (capturing 137.8 tons of CO 2 annually) reacts with green hydrogen from the PEM electrolyzer to synthesize methane, which is then recycled back into the combustion chamber to reduce fossil fuel dependency. The system is rigorously evaluated using energy, exergy, techno-economic, and environmental analyses. Baseline scenario results show 60.28 % energy efficiency, 56.82 % exergy efficiency, $183.63/h total cost rate, 0.5653 exergoenvironmental impact index, and 47.70 kg/s freshwater production. To improve thermodynamic and economic performance, an ANN–GA hybrid multi–objective optimization framework is employed. Optimization via the LINMAP decision-making approach yields an enhanced energy efficiency of 61.80 % and a 10.1 % increase in freshwater production rate to 52.53 kg/s, with a total cost rate of $188.05/h. Furthermore, employing the Weighted Sum method, the energy efficiency and freshwater production rate are further elevated to 62.86 % and 53.87 kg/s (a 12.9 % improvement over the baseline), respectively. These findings demonstrate that the proposed integrated system offers a robust and sustainable pathway for decarbonization and multi-resource generation.