Techno-economic optimization of a biomass gasification energy system with Supercritical CO2 cycle for hydrogen fuel and electricity production

•Development of a new system for simultaneous production of power and hydrogen fuel.•Adding an ejector to the absorption chiller cycle to improve its cooling capacity.•Using Supercritical CO2 power generation cycle for efficiency enhancement.•Influence of different biomass fuels on the system performance.•The highest energy efficiency was for the system with municipal solid waste (41.21%). Biomass is considered a carbon–neutral fuel and can play a significant role in obtaining sustainable energy generation. This study aims to raise the exergy efficiency and reduce costs in a novel energy system that is employed to generate power, heating, cooling, fresh water, and hydrogen fuel. Based on this, municipal solid waste (MSW), wood, and paper are considered as biomass fuels of the examined system and the system performance is evaluated from a thermodynamic and thermo-economic point of view through a parametric study. In the considered system, the generated gas in the gasifier supplies the energy required to run an externally fired gas turbine module. The waste heat of the gas turbine cycle is used to run a supercritical CO2 (S-CO2) power generation cycle coupled with a heat exchanger to supply hot water and run an organic Rankine cycle (ORC) power generation cycle, as well as an absorption chiller cycle equipped with an ejector to produce cooling. In addition, the waste heat of the ORC is employed to produce fresh water through a humidification-dehumidification (HDH) desalination unit, a part of which is used to supply a proton exchange membrane electrolyzer (PEME) and the remaining is for other purposes. By considering the exergy efficiency and the levelized cost of energy (LCOE) as objective functions, a multi-objective optimization based on the genetic algorithm has been applied. An artificial neural network (ANN) plays an intermediating role in the optimization process to reduce the calculation time and raise the optimization speed. The relationship between the objective function and decision variables was analyzed using the ANN to determine the optimal point in this energy system. The results show that under optimal operating conditions, the exergy efficiency of the system with the biomass fuels of MSW, wood, and paper is equal to 41.21 %, 40.25 %, and 39.33 %, respectively. The LCOE values ​​under the same conditions are 30.77 $/MWh, 32.06 $/MWh, and 33.6 $/MWh, respectively. Furthermore, at the optimum point, the amount of fresh water and hydrogen produc