مشخصات پژوهش

خانه /Thermo-economic optimization ...
عنوان
Thermo-economic optimization of a hydrogen storage structure using liquid natural gas regasification and molten carbonate fuel cell
نوع پژوهش مقاله چاپ‌شده
کلیدواژه‌ها
Hydrogen storage Hydrogen liquefaction Liquefied natural gas regasification Molten carbonate fuel cells Power cycles Thermo-economic analysis
چکیده
Liquid natural gas (LNG) regasification and fuel cells can be employed to supply the required precooling and electrical power for hydrogen liquefaction, respectively. Such an approach helps reduce the process complexity and the number of equipment, total costs, and carbon footprints, and enhance the controllability of the process. This paper proposes an integrated structure for hydrogen liquefaction and storage by employing the LNG regasification process for precooling and four multi-component refrigerant cycles for liquefaction. Molten car- bonate fuel cells, gas turbines power cycles, the two-stage organic Rankine cycle, and the carbon dioxide power cycle are used for supplying the electrical power. A liquid hydrogen production capacity of 1766 kmol/h and 1576.7 MW electrical power generation are attained in this integrated process. The coefficient of performance, specific energy consumption, and specific power consumption of the integrated structure are calculated to be 0.175, 4.772 kWh/kgLH2, and 3.872 kWh/kgLH2, respectively. The exergy efficiency of 83.03% and the exergy destruction of 47.87 MW are obtained based on the exergy analysis. The maximum shares of exergy destruction are attributed to the heat exchangers, gas turbines, and fuel cells with the magnitudes of 45.43%, 24.75%, and 10.93%, respectively. The prime cost of product and rate of return are calculated to be 0.0840 US$/kWh and 24.02%, respectively. According to the sensitivity analysis, it is found that increasing the molar fraction of he- lium in the multi-component refrigerant cycle from 81.31% to 93.61% leads to a reduction in the net power production (151.2 MW) and total exergy efficiency (81.39%) of the proposed process. Using the multi-objective genetic algorithm method, the total exergy efficiency and the rate of return are optimized to be 86.32% and 29.66%, respectively.
پژوهشگران بهرام قربانی (نفر اول)، سهراب زنده بودی (نفر دوم)، علیرضا خاتمی جویباری (نفر سوم)