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http://hdl.handle.net/10553/116672
Título: | Optimal design and analysis of a combined freshwater-power generation system based on integrated solid oxide fuel cell-gas turbine-organic Rankine cycle-multi effect distillation system | Autores/as: | Manesh, Mohammad Hasan Khoshgoftar Ghorbani, Shabnam Blanco Marigorta, Ana María |
Clasificación UNESCO: | 330801 Control de la contaminación atmosférica 330806 Regeneración del agua 331330 Turbinas |
Palabras clave: | Exergoenvironmental Analysis Environmental-Analyses Economic-Analysis Desalination Exergy, et al. |
Fecha de publicación: | 2022 | Publicación seriada: | Applied Thermal Engineering | Resumen: | Gas turbine output has a very good capability for heat recovery and increases production capacity by heat recovery steam generator and heat recovery vapor generator. Also, gas turbines have good potential for coupling with a solid oxide fuel cell to increase power generation. The present research proposes and evaluates a novel combination of a solid oxide fuel cell and gas turbine system with an organic Rankine cycle and a multi-effect thermal desalination system.& nbsp;Conventional and advanced exergetic, exergoenvironmental and exergoeconomic analyses are performed to better understand the proposed system in view of performance, economic, and environmental impacts. To find the optimal design values, minimize the total exergetic environmental impacts and total exergetic cost rate, and maximize exergetic efficiency, as objective functions, multi-target optimization using the multi-target water cycle algorithm and the multi-target genetic algorithm is used. The analyses are conducted using MATLAB software. Results determine the optimal hybrid system could produce 5000 m(3)/day of freshwater, with five effects on the MED-TVC. The energy and exergy efficiencies of the suggested hybrid system reached 47.85% and 41.94%, respectively, an increase of 11.6% and 3.6% compared to the coupled gas turbine system and solid oxide fuel cell. Furthermore, by applying the Multi-objective Genetic Algorithm and Multi-objective Water Cycle Algorithm optimization, the overall efficiency of cogeneration is increased by 28% and 27.5%. The total exergetic cost is reduced by 23.12% and 22.46%, and the total exergetic environmental impact is reduced by 20.15% and 19.65%, respectively. | URI: | http://hdl.handle.net/10553/116672 | ISSN: | 1359-4311 | DOI: | 10.1016/j.applthermaleng.2022.118438 | Fuente: | Applied Thermal Engineering[ISSN 1359-4311],v. 211, (Julio 2022) |
Colección: | Artículos |
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