| 학회 |
한국화학공학회 |
| 학술대회 |
2022년 봄 (04/20 ~ 04/23, 제주국제컨벤션센터) |
| 권호 |
28권 1호, p.374 |
| 발표분야 |
[주제 7] 수소 |
| 제목 |
Optimization of on-site SMR hydrogen production process based on mathematical model and machine learning model |
| 초록 |
Commercial on-site hydrogen production processes via steam methane reforming (SMR) are operated at ~70% lower than the maximum theoretical thermal efficiency of 89%. Thus, thermal efficiency is maximized in this study by improving the reactor configuration and optimizing operating conditions. First, the configuration of the reactor is investigated to increase the efficiency of the SMR process. Reactor modeling is conducted based on the mathematical model, and the performance of the single- and double-tube reactors is evaluated. As a result, conversion increases from 71.7% to 89.3%. Second, operating conditions optimization is conducted based on mathematical and machine learning models. Several constraints derived from the operational experience and previous studies are considered for optimization. Consequently, the thermal efficiency increased from 77.7% (pilot plant) to 81.3% (mathematical model) and 85.6% (machine learning model). |
| 저자 |
이재원1, 홍석영2, 조형태1, 문일2, 김정환1
|
| 소속 |
1한국생산기술(연), 2연세대 |
| 키워드 |
공정시스템(Process Systems Engineering) |
| E-Mail |
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| 원문파일 |
초록 보기 |
