Publication detail
A new strategy for mixed refrigerant composition optimisation in the propane precooled mixed refrigerant natural gas liquefaction process
Zhang, Shouxin Zou, Zimo Klemes, Jiri Jaromir Varbanov, Petar Sabev Shahzad, Khurram Ali, Arshid Mahmood Wang, Bo-Hong
English title
A new strategy for mixed refrigerant composition optimisation in the propane precooled mixed refrigerant natural gas liquefaction process
Type
journal article in Web of Science
Language
en
Original abstract
The natural gas liquefaction process occupies a considerable part of the energy consumption in the LNG industry chain, and efficient optimisation methods should be developed to improve the economic and environmental performances of this process. In this work, a new optimisation strategy based on the particle swarm optimisation (PSO) algorithm and bisection method was developed to optimise the propane precooled refrigerant process (C3MR). In the proposed optimisation strategy, the molar fractions of the mixed refrigerant (MR) components were directly adopted as variables in the PSO algorithm, and the MR flow rate was independently adjusted by the bisection method to satisfy the minimum temperature approach constraints. The results show that the optimal operating conditions reduced the energy requirement of the C3MR process by 4% and decreased the consumption of MR by 31.9%, compared to traditional using the flow rates of MR components as variables. The correlations among the properties of key streams were calculated based on the intermediate results of the proposed method and visualised with the heat map. The results show that the energy requirement of the C3MR process decreased with the increase of the low boiling temperature components and increased with the high boiling temperature components of MR.
English abstract
The natural gas liquefaction process occupies a considerable part of the energy consumption in the LNG industry chain, and efficient optimisation methods should be developed to improve the economic and environmental performances of this process. In this work, a new optimisation strategy based on the particle swarm optimisation (PSO) algorithm and bisection method was developed to optimise the propane precooled refrigerant process (C3MR). In the proposed optimisation strategy, the molar fractions of the mixed refrigerant (MR) components were directly adopted as variables in the PSO algorithm, and the MR flow rate was independently adjusted by the bisection method to satisfy the minimum temperature approach constraints. The results show that the optimal operating conditions reduced the energy requirement of the C3MR process by 4% and decreased the consumption of MR by 31.9%, compared to traditional using the flow rates of MR components as variables. The correlations among the properties of key streams were calculated based on the intermediate results of the proposed method and visualised with the heat map. The results show that the energy requirement of the C3MR process decreased with the increase of the low boiling temperature components and increased with the high boiling temperature components of MR.
Keywords in English
Energy efficiency; Mixed refrigerant composition; Natural gas liquefaction; Optimisation; Propane precooled mixed refrigerant
Released
01.07.2023
Publisher
PERGAMON-ELSEVIER SCIENCE LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
Location
PERGAMON-ELSEVIER SCIENCE LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
ISSN
0360-5442
Volume
274
Number
1
Pages count
14
BIBTEX
@article{BUT187462,
author="Jiří {Klemeš} and Petar Sabev {Varbanov} and Bohong {Wang},
title="A new strategy for mixed refrigerant composition optimisation in the propane precooled mixed refrigerant natural gas liquefaction process",
year="2023",
volume="274",
number="1",
month="July",
publisher="PERGAMON-ELSEVIER SCIENCE LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND",
address="PERGAMON-ELSEVIER SCIENCE LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
",
issn="0360-5442"
}