TY - JOUR
T1 - Simulation-based modeling and optimization for refinery hydrogen network integration with light hydrocarbon recovery
AU - Yang, Minbo
AU - Zeng, Siying
AU - Feng, Xiao
AU - Zhao, Liang
N1 - Publisher Copyright:
© 2021 Hydrogen Energy Publications LLC
PY - 2022/1/22
Y1 - 2022/1/22
N2 - Purge gases from hydrocrackers and hydrotreaters and refinery off-gases are important hydrogen sources. Some of these hydrogen sources are also rich in light hydrocarbons that are valuable energy resources and chemical materials. In this work, a systematic method is proposed to integrate hydrogen networks considering light hydrocarbon recovery. This work first develops a hydrogen network superstructure with light hydrocarbon recovery. Aspen HYSYS is employed for rigorous process and thermodynamic modeling of the light hydrocarbon recovery process, and a simulation-optimization model is then developed. To solve the simulation-optimization model efficiently, the genetic algorithm is used as the global solver to determine the feed to light hydrocarbon recovery unit, and the linprog and fmincon solvers are combined to determine the optimal hydrogen network design. The application and effectiveness of the proposed method is validated through a case study. The results show that fresh hydrogen consumption decreases by 13% and the total annualized cost reduces to 72% because of light hydrocarbon recovery. This method could provide useful guides for the management of hydrogen and light hydrocarbons in refineries.
AB - Purge gases from hydrocrackers and hydrotreaters and refinery off-gases are important hydrogen sources. Some of these hydrogen sources are also rich in light hydrocarbons that are valuable energy resources and chemical materials. In this work, a systematic method is proposed to integrate hydrogen networks considering light hydrocarbon recovery. This work first develops a hydrogen network superstructure with light hydrocarbon recovery. Aspen HYSYS is employed for rigorous process and thermodynamic modeling of the light hydrocarbon recovery process, and a simulation-optimization model is then developed. To solve the simulation-optimization model efficiently, the genetic algorithm is used as the global solver to determine the feed to light hydrocarbon recovery unit, and the linprog and fmincon solvers are combined to determine the optimal hydrogen network design. The application and effectiveness of the proposed method is validated through a case study. The results show that fresh hydrogen consumption decreases by 13% and the total annualized cost reduces to 72% because of light hydrocarbon recovery. This method could provide useful guides for the management of hydrogen and light hydrocarbons in refineries.
KW - Genetic algorithm
KW - Hydrogen network integration
KW - Light hydrocarbon recovery
KW - Simulation-optimization method
KW - Total annualized cost
UR - https://www.scopus.com/pages/publications/85120856109
U2 - 10.1016/j.ijhydene.2021.11.069
DO - 10.1016/j.ijhydene.2021.11.069
M3 - 文章
AN - SCOPUS:85120856109
SN - 0360-3199
VL - 47
SP - 4662
EP - 4673
JO - International Journal of Hydrogen Energy
JF - International Journal of Hydrogen Energy
IS - 7
ER -
