This study presents a comprehensive technical, environmental, and economic analysis of a thermal power plant utilizing solid oxide fuel cells (SOFC) to meet urban demands for electrical power, fresh water, and hydrogen. The integrated system includes SOFC with anode and cathode recycling, multi-effect desalination, a power generation cycle with a heat recovery unit using a thermoelectric generator, and a hydrogen compression unit. A detailed parametric analysis was conducted to identify optimal conditions for key outputs such as total cost rate and exergy efficiency, employing genetic algorithms and artificial neural networks. According to the economic evaluation, the SOFC stack accounts for 65.11 % of total costs at 139.8 $/h, with the inverter contributing 11.9 %. The environmental analysis shows that the proposed system emits the least CO per energy unit compared to SOFC/GT and SOFC/GT/RC systems. The parametric study indicates that increasing the pressure ratio enhances the output power of the SOFC and the production of the gas turbine. However, this also leads to higher compressor consumption, thereby reducing net power. Furthermore, increasing the current density results in greater production of electricity, hydrogen, and freshwater, while also raising the exhaust gas temperature, which aids in the desalination process. The optimization results show an exergy efficiency of 61.38 % and a total cost rate of 132.9 $/h, with artificial neural networks reducing optimization time from 124 h to 14 min.

中文翻译：

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将基于热电的热回收和制氢装置与 SOFC 驱动的多联产结构相结合；深入的经济机器学习驱动分析


本研究对利用固体氧化物燃料电池 (SOFC) 满足城市对电力、淡水和氢气需求的火力发电厂进行了全面的技术、环境和经济分析。该集成系统包括具有阳极和阴极回收功能的SOFC、多效海水淡化、带有使用热电发电机的热回收单元的发电循环以及氢气压缩单元。采用遗传算法和人工神经网络进行了详细的参数分析，以确定总成本率和火用效率等关键输出的最佳条件。根据经济评估，SOFC电堆占总成本的65.11%，为139.8美元/h，其中逆变器占11.9%。环境分析表明，与 SOFC/GT 和 SOFC/GT/RC 系统相比，所提议的系统每能源单位排放的二氧化碳最少。参数研究表明，增加压力比可以提高SOFC的输出功率和燃气轮机的产量。然而，这也导致压缩机消耗更高，从而降低净功率。此外，增加电流密度可以产生更多的电力、氢气和淡水，同时还提高废气温度，这有助于海水淡化过程。优化结果显示，火用效率为 61.38%，总成本率为 132.9 $/h，人工神经网络将优化时间从 124 小时缩短至 14 分钟。