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首页> 外文期刊>International journal of green energy >OPTIMIZATION WITH GENETIC ALGORITHMS OF A GAS TURBINE CYCLE WITH H_2-SEPARATING MEMBRANE REACTOR FOR CO_2 CAPTURE
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OPTIMIZATION WITH GENETIC ALGORITHMS OF A GAS TURBINE CYCLE WITH H_2-SEPARATING MEMBRANE REACTOR FOR CO_2 CAPTURE

机译：H_2分离膜反应器用于CO_2捕集的燃气轮机循环遗传算法的优化

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摘要

A gas turbine power process with CO_2 capture through precombustion decarbonization, which employs a H_2-separating membrane reactor is presented. Optimization with the process thermal efficiency as objective Junction is made through the use of genetic algorithms. The use of genetic algorithms enabled a division of the optimization parameters into two groups; one group where the values are at their optimum at the limit of the investigated parameter range, and one group where there actually is an optimum within the investigated range. It was found that the process has a severe efficiency penalty caused by the use of heat from hydrogen combustion for the reforming process. The process is a zero CO_2 emission power process and also NO_x emissions should be low, due to the inherent mixing of hydrogen with steam.
机译：提出了一种通过预燃烧脱碳捕集CO_2的燃气轮机发电工艺，该工艺采用了H_2分离膜反应器。通过使用遗传算法，以过程热效率为目标进行优化。遗传算法的使用将优化参数分为两组。一组值在研究的参数范围的极限处处于最佳状态，而一组实际上在研究的参数范围内处于最佳状态。已发现该方法具有严重的效率损失，这是由于将氢气燃烧产生的热量用于重整过程所致。该过程是零CO_2排放功率过程，并且由于氢与蒸汽的固有混合，NO_x排放也应低。

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