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This paper presents a ground-breaking design for a multigeneration system capable of simultaneously producing electricity, hydrogen, and cooling loads. This research advances sustainable energy systems by introducing an innovative design that optimally utilizes waste heat and integrates biomass gasification with advanced thermodynamic cycles. It also provides a model for future studies on carbon emission reduction and improved efficiency. The proposed system effectively harnesses waste heat from the Brayton cycle to drive the supercritical carbon dioxide cycle, steam Rankine cycle, absorption refrigeration, and proton exchange membrane electrolyzer. This approach improves overall efficiency and offers a promising solution for integrated energy generation. Additionally, employing the sCO 2 cycle provides high thermal efficiency, cost-effectiveness, and lower environmental impacts compared to traditional power generation methods. Extensive evaluations, including techno-economic and environmental analyses, confirm the system's practicality and potential for future commercial application. Additionally, a parametric investigation of five essential design parameters provides important insights into the system's performance and flexibility. Analysing the proposed system determined that the gasifier-Bryton unit has the highest irreversibility and cost rate among other subsystems. A novel approach combining artificial neural networks (ANN) with a non-dominated sorting genetic algorithm II (NSGA-II) has been developed to optimize the system, substantially reducing computational time and costs associated with system performance analysis. According to the three-objective optimization, the system in the optimal operating mode provides 45. 89 kg/h of hydrogen with an exergy efficiency of 33. 15 % and a total cost rate of 159. 5 /h. After the optimization process, significant achievements have been observed, including a 5. 02 % improvement in exergy efficiency, an increase of 7. 29 kg/h of hydrogen production, and a decrease of 0. 1 ton/MW in the CO 2 emission index.
Zihao et al. (Sat,) studied this question.