Modelling of hydrogen blending into the UK natural gas network driven by a solid oxide fuel cell for electricity and district heating system

被引:8
|
作者
Samanta, Samiran [1 ]
Roy, Dibyendu [1 ]
Roy, Sumit [1 ]
Smallbone, Andrew [1 ]
Roskilly, Anthony Paul [1 ]
机构
[1] Univ Durham, Dept Engn, Durham DH1 3LE, England
关键词
Solid Oxide Fuel Cell (SOFC); District heating; Hydrogen economy; Artificial Neural Network; Cogeneration; PERFORMANCE-EMISSION CHARACTERISTICS; ENERGY; POWER; IMPACT; SOFC; IDENTIFICATION; COMBUSTION; MIXTURES;
D O I
10.1016/j.fuel.2023.129411
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A thorough investigation of the thermodynamics and economic performance of a cogeneration system based on solid oxide fuel cells that provides heat and power to homes has been carried out in this study. Additionally, different percentages of green hydrogen have been blended with natural gas to examine the techno-economic performance of the suggested cogeneration system. The energy and exergy efficiency of the system rises steadily as the hydrogen blending percentage rises from 0% to 20%, then slightly drops at 50% H2 blending, and then rises steadily again until 100% H2 supply. The system's minimal levelised cost of energy was calculated to be 4.64 & POUND;/kWh for 100% H2. Artificial Neural Network (ANN) model was also used to further train a sizable quantity of data that was received from the simulation model. Heat, power, and levelised cost of energy estimates using the ANN model were found to be extremely accurate, with coefficients of determination of 0.99918, 0.99999, and 0.99888, respectively.
引用
收藏
页数:11
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