Multiobjective optimization of a hydrogen production system with low CO 2 emissions

Wei Wu; Yan Chi Liou; Ya Yan Zhou

doi:10.1021/ie202789j

Multiobjective optimization of a hydrogen production system with low CO ₂ emissions

Wei Wu, Yan Chi Liou, Ya Yan Zhou

Department of Chemical Engineering

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

Since the steam methane reforming usually increases the temperature of stream and concentration of CO ₂, this work introduces a CO ₂ reformer that can produce syngas by consuming CH ₄ and CO ₂. In the proposed configuration, a CO ₂ reformer is directly added between the steam methane reforming (SMR) process and a high-temperature shift (HTS) converter. To pursue the process optimization with respect to maximizing hydrogen production and minimizing carbon dioxide emission, a nondominated sorting genetic algorithm-II (NSGA-II) is employed to solve a constrained multiobjective optimization (MOO) problem. Finally, the proposed system configuration with heat recovery manner is validated by an Aspen HYSYS simulator.

Original language	English
Pages (from-to)	2644-2651
Number of pages	8
Journal	Industrial and Engineering Chemistry Research
Volume	51
Issue number	6
DOIs	https://doi.org/10.1021/ie202789j
Publication status	Published - 2012 Feb 15

All Science Journal Classification (ASJC) codes

Chemistry(all)
Chemical Engineering(all)
Industrial and Manufacturing Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1021/ie202789j

Cite this

@article{9262344b7f494756a4e8bf09176891a9,

title = "Multiobjective optimization of a hydrogen production system with low CO 2 emissions",

abstract = "Since the steam methane reforming usually increases the temperature of stream and concentration of CO 2, this work introduces a CO 2 reformer that can produce syngas by consuming CH 4 and CO 2. In the proposed configuration, a CO 2 reformer is directly added between the steam methane reforming (SMR) process and a high-temperature shift (HTS) converter. To pursue the process optimization with respect to maximizing hydrogen production and minimizing carbon dioxide emission, a nondominated sorting genetic algorithm-II (NSGA-II) is employed to solve a constrained multiobjective optimization (MOO) problem. Finally, the proposed system configuration with heat recovery manner is validated by an Aspen HYSYS simulator.",

author = "Wei Wu and Liou, {Yan Chi} and Zhou, {Ya Yan}",

year = "2012",

month = feb,

day = "15",

doi = "10.1021/ie202789j",

language = "English",

volume = "51",

pages = "2644--2651",

journal = "Industrial and Engineering Chemistry Research",

issn = "0888-5885",

number = "6",

}

TY - JOUR

T1 - Multiobjective optimization of a hydrogen production system with low CO 2 emissions

AU - Wu, Wei

AU - Liou, Yan Chi

AU - Zhou, Ya Yan

PY - 2012/2/15

Y1 - 2012/2/15

N2 - Since the steam methane reforming usually increases the temperature of stream and concentration of CO 2, this work introduces a CO 2 reformer that can produce syngas by consuming CH 4 and CO 2. In the proposed configuration, a CO 2 reformer is directly added between the steam methane reforming (SMR) process and a high-temperature shift (HTS) converter. To pursue the process optimization with respect to maximizing hydrogen production and minimizing carbon dioxide emission, a nondominated sorting genetic algorithm-II (NSGA-II) is employed to solve a constrained multiobjective optimization (MOO) problem. Finally, the proposed system configuration with heat recovery manner is validated by an Aspen HYSYS simulator.

AB - Since the steam methane reforming usually increases the temperature of stream and concentration of CO 2, this work introduces a CO 2 reformer that can produce syngas by consuming CH 4 and CO 2. In the proposed configuration, a CO 2 reformer is directly added between the steam methane reforming (SMR) process and a high-temperature shift (HTS) converter. To pursue the process optimization with respect to maximizing hydrogen production and minimizing carbon dioxide emission, a nondominated sorting genetic algorithm-II (NSGA-II) is employed to solve a constrained multiobjective optimization (MOO) problem. Finally, the proposed system configuration with heat recovery manner is validated by an Aspen HYSYS simulator.

UR - http://www.scopus.com/inward/record.url?scp=84863131228&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84863131228&partnerID=8YFLogxK

U2 - 10.1021/ie202789j

DO - 10.1021/ie202789j

M3 - Article

AN - SCOPUS:84863131228

VL - 51

SP - 2644

EP - 2651

JO - Industrial and Engineering Chemistry Research

JF - Industrial and Engineering Chemistry Research

SN - 0888-5885

IS - 6

ER -