submitted on 2025-07-29, 07:47 and posted on 2025-07-29, 07:48authored byLaveet Kumar, Ahmad K. Sleiti, Ibrahim Hassan, S. Rezaei-Gomari, Mohammad Azizur Rahman
<p dir="ltr">This paper presents a comprehensive thermo-economic analysis of a novel Power-to-X (P2X) polygeneration system designed for the production of hydrogen, ammonia, and methanol with near-zero CO<sub>2</sub> emissions. The system integrates an air separation unit (ASU), a direct oxy-combustor (DOC) powered by natural gas, combined with a supercritical carbon dioxide (sCO<sub>2</sub>) power cycle, water electrolyzer (WE), a Haber-Bosch process (HBP), and a methanol production unit (MPU). The system is investigated in four configurations: ASU + DOC-sCO<sub>2</sub> (S1), ASU + DOC-sCO<sub>2</sub> + WE (S2), ASU + DOC-sCO<sub>2</sub> + WE + HBP (S3), and ASU + DOC-sCO<sub>2</sub> + WE + HBP + MPU (S4), each contributing to improve energy efficiency and reduced emissions. Simulation results show that the overall system efficiency reaches 56 %, improving from 45 % to 56 % across different configurations. The system's levelized cost of hydrogen (LCOH) decreases significantly from $1.70/kg to $0.80/kg, and the levelized cost of electricity (LCOE) decreases from 4.30 ¢/kWh to 3.30 ¢/kWh. CO<sub>2</sub> emissions are reduced from 200 gCO<sub>2</sub>/MWe to 145 gCO<sub>2</sub>/MWe, with the CO<sub>2</sub> reduction rate improving from 89 % to 94 %. These results demonstrate the economic viability and environmental sustainability of the proposed P2X system paving the way for industrial decarbonization and large-scale deployment in future energy infrastructures.</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Hydrogen Energy<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijhydene.2025.150201" target="_blank">https://dx.doi.org/10.1016/j.ijhydene.2025.150201</a></p>
Funding
Open Access funding provided by the Qatar National Library.
Qatar National Research Fund (NPRP14S-0321-210080), Machine Learning Approach for Single Phase and Multiphase Flow Leak Detection and Monitoring in Onshore/Offshore Pipelines and Subsurface Sequestration Sites.