Energies, Vol. 18, Pages 6107: Methods of Increasing the Efficiency and Yield of a Methanol Production Plant in Waste-to-Fuel Technology with an Economic Analysis
Energies doi: 10.3390/en18236107
Authors:
Janusz Kotowicz
Mateusz Brzęczek
Łukasz Böhm
The article describes oxygen gasification installation for waste biomass in waste-to-fuel technology, in which the final product is liquid methanol (the reference case). A comprehensive techno-economic model integrates oxygen-based gasification of wet sludge with three waste-heat recovery technologies—expander, Stirling engine, and organic Rankine cycle—and directs the recovered electrical power to a PEM electrolyzer for additional hydrogen production. The model captures full material flows, thermodynamic efficiencies, CO2 balances, and an economic analysis over a 20-year horizon. A comparison of the use of an expander, Stirling engines, and ORC modules to power the electrolytic hydrogen generation installation was proposed. The produced hydrogen is an additional substrate for the methanol reactor, which will consequently increase the methanol yield from the entire installation and reduce the specific CO2 emissions. Oxygen from the electrolysis process can be used in the gasifier, which will reduce the energy consumption of the Air Separation Unit, and thus increase the efficiency of the entire gasification system. In addition to the technical evaluation, an economic analysis was carried out to assess the profitability of the proposed concepts, showing that process integration can significantly improve both energy performance and economic feasibility of methanol production in waste-to-fuel systems. Results show that proposed modifications have the potential to increase overall efficiency from 75.498% (reference scenario) to even 82.545% (best scenario), while specific emissions of carbon dioxide drop from 1.746 kg CO2/kg CH3OH (reference scenario) to 1.468 kg CO2/kg CH3OH (best scenario), with an increase in methanol yield of about 9.4% (from 0.255 kg CH3OH/kg Bio in reference scenario to 0.279 in best scenario).