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Multi-objective optimization of an integrated gasification combined cycle for hydrogen and electricity production
Computers & Chemical Engineering ( IF 4.3 ) Pub Date : 2018-06-15 , DOI: 10.1016/j.compchemeng.2018.06.004
Maan Al-Zareer , Ibrahim Dincer , Marc A. Rosen

In this paper, an integrated coal gasification combined cycle system for the production of hydrogen and electricity is optimized in terms of energy and exergy efficiencies, and the amount and cost of the produced hydrogen and electricity. The integrated system is optimized by focusing on the conversion process of coal to syngas. A novel optimization process is developed which integrates an artificial neural network with a genetic algorithm. The gasification system is modeled and simulated with Aspen Plus for large ranges of operating conditions, where the artificial neural network method is used to represent the simulation results mathematically. The mathematical model is then optimized using a genetic algorithm method. The optimization demonstrates that the lower is the grade of coal of the three considered coals, the less expensive is the hydrogen and electricity that can be produced by the considered integrated gasification combined cycle (IGCC) system.



中文翻译:

氢气和电力生产的整体气化联合循环的多目标优化

在本文中,从能源和火用效率以及所产生的氢和电的量和成本方面优化了用于生产氢和电的集成煤气化联合循环系统。通过关注煤到合成气的转化过程来优化集成系统。开发了一种新颖的优化过程,该过程将人工神经网络与遗传算法集成在一起。使用Aspen Plus对气化系统进行建模和仿真,以适应较大范围的运行条件,其中使用人工神经网络方法来数学表示仿真结果。然后使用遗传算法方法对数学模型进行优化。优化表明,三种考虑的煤中煤的等级较低,

更新日期:2018-06-15
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