Low-carbon power generation using DME: A thermodynamic assessment of two DME-fueled sCO2 oxy-combustion power cycles

• DME is assessed as an alternative fuel for oxy-combustion sCO 2 power cycle. • A DME-fueled Liquefied Recycle Allam Cycle (LiRAC) is proposed. • LiRAC delivers liquid and dense phase purified CO 2 with competitive net efficiency. • DME- and NG-fueled Allam cycles are benchmarked under aligned conditions. • DME supports a pathway toward a closed carbon loop. Supercritical carbon dioxide (sCO 2 )-based oxy-combustion power cycles, such as the Allam cycle, enable high-efficiency power generation with integrated carbon capture without the need for additional amine-based scrubbing plant. While these cycles are mostly discussed in combination with fossil fuels, the use of a renewable chemical hydrogen carrier, dimethyl ether (DME), remains largely unexplored. Besides its good combustion characteristics, DME offers the potential to establish a circular carbon loop when recycling the captured CO 2 for DME-synthesis. This study evaluates DME as a fuel in the Allam cycle and benchmarks its thermodynamic performance against a natural gas-fired configuration under consistent system boundaries. The results show that the DME-fueled Allam cycle achieves a net efficiency of 50.4 % and an effective CO 2 capture rate exceeding 96 %, comparable to the natural gas-fired reference. These findings highlight DME as a promising fuel for sCO 2 oxy-combustion cycles Building on the integration of DME, a modified configuration, the Liquefied Recycle Allam Cycle (LiRAC), is proposed. The LiRAC integrates a vapor compression unit using DME as refrigerant to fully liquefy the CO 2 -rich working medium. This enables pump-based pressurization, reduces the energy demand associated with downstream CO 2 conditioning, and delivers most of the purified CO 2 in liquid form. The LiRAC achieves a net efficiency of 48.7 % while maintaining high CO 2 capture rates, demonstrating the feasibility of liquefied working-medium schemes and motivating further optimization and part-load assessment.