Integrated biomass–geothermal system for decarbonized ammonia production enhanced by a supercritical CO2 cycle: a data-driven approach
Fuel, cilt.428, 2027 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 428
- Basım Tarihi: 2027
- Doi Numarası: 10.1016/j.fuel.2026.140022
- Dergi Adı: Fuel
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chemical Abstracts Core, Chimica, Compendex, INSPEC, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Ammonia production, Biomass gasification, Decarbonization pathways, Particle swarm optimization (PSO), Supercritical CO2 brayton cycle, Techno-economic assessment
- İstanbul Gelişim Üniversitesi Adresli: Evet
Özet
Ammonia’s emergence as a carbon-free energy carrier calls for pathways that decarbonize both its synthesis and the electricity that powers it. This work proposes a hybrid biomass–geothermal platform for electricity and ammonia production. The configuration couples a gas turbine fueled by biomass-derived syngas with a supercritical CO2 Brayton cycle, a dual-flash geothermal configuration, and an ammonia synthesis loop. A comprehensive exergy accounting is performed alongside an environmental and techno-economic evaluation. Exergy destruction is dominated by the gas turbine and gasification train (70.6%, 4148.95 kW), followed by the geothermal subsystem (1188.14 kW) and the supercritical CO2 cycle (297.5 kW). A multidimensional parametric analysis is conducted to evaluate the sensitivity of system performance indicators to key decision variables. The split ratio of the supercritical CO2 cycle exhibits a non-monotonic influence on system behavior: both efficiency and net power generation increase until a split ratio of 0.74, beyond which thermodynamic mismatches reduce system performance. Under favorable geothermal temperature and pressure conditions, normalized CO2 emissions decrease to 28.47 kg/GJ. Conversely, increasing the gas turbine inlet temperature raises the levelized cost of electricity by up to 41%, while simultaneously reducing efficiency and increasing emissions. To efficiently explore the design space, artificial neural network surrogate models are integrated with a multi-objective particle swarm optimization algorithm. The optimal solution yields an exergy efficiency of 54.68%, an ammonia production rate of 592.9 kg/day, and a levelized cost of electricity of 6.47 cents/kWh. Scenario analysis indicates that the project net present value ranges from $2.29 million under conservative price assumptions to $6.53 million under favorable market conditions.