4.7 Article

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

期刊

APPLIED THERMAL ENGINEERING
卷 211, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.applthermaleng.2022.118438

关键词

Exergy; Gas turbine; Solid Oxide Fuel Cell; Exergoenvironmental; Exergoeconomic; Advanced analysis

资金

  1. INTERREG MAC 2014-2020 programme
  2. ERDF funds, within the E5DES [MAC2/1.1a/309]

向作者/读者索取更多资源

This research proposes a novel combination of a solid oxide fuel cell and gas turbine system, coupled with an organic Rankine cycle and a multi-effect thermal desalination system. Through multi-objective optimization algorithms, the energy and exergy efficiencies of the system are improved, while reducing energy cost and environmental impact.
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. 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.

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