The integration of renewable energies can improve the thermodynamic performance and increase the popularity and commercialization of the energy production system. Moreover, the exploitation of renewables in the form of cascade energy systems with multigeneration goals has been able to overcome many restrictions and penalties. Meantime, fuel cells are efficient, carbon-free, and promising energy conversion technologies can act as a storage system and improve the sustainability of the energy system. In this article, a new two-source multigeneration system (TS/MGS) based on a biomass fuel and a geothermal source is introduced and evaluated. The upstream process of the considered system is based on a municipal solid waste (MSW)-gasification process-fueled solid oxide fuel cell (SOFC) stack. Besides, the downstream process is comprised of a geothermal source based on a triple-flash cycle, an ejection-based refrigeration process, a water electrolysis cycle, and a domestic water heater unit. The offered TS/MGS is capable of generating electricity, cooling load, heating load, and hydrogen fuel. Converting MSW to energy, in addition to producing efficient energy, can help waste management in urban communities. The operation of the offered TS/MGS was comprehensively investigated from thermodynamic, cost and environmental standpoints. Moreover, the optimal behavior of the TS/MGS is compared under two different decision-making approaches (based on a tri-objective optimization algorithm). Under the considered design parameters, the considered TS/MGS can provide about 3.92 MW of electric power, 2.19 MW of cooling load, ∼ 1.55 MW of heating load, and 0.1 g/s of hydrogen fuel to the consumer (at a thermal efficiency of 33.5% and an exergy efficiency of 61%). The values of total unit cost of products and levelized total carbon dioxide emissions were 0.0211 $/kWh and 0.21 kg/kWh. Under the TOPSIS decision-making approach, relatively more optimal exergoeconomic and environmental outcomes can be achieved compared to the LINMAP decision-making approach. However, the thermodynamic behavior under the LINMAP decision-making approach is more optimal than the TOPSIS decision-making approach.
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