Optimization of a dual mixed refrigerant process using a nonsmooth approach
Matias Vikse,
Harry A.J. Watson,
Donghoi Kim,
Paul I. Barton and
Truls Gundersen
Energy, 2020, vol. 196, issue C
Abstract:
This article uses a nonsmooth flowsheeting methodology to create simulation and optimization models for dual mixed refrigerant processes. New improved operating conditions are obtained using the primal-dual interior-point optimizer IPOPT, with sensitivity information calculated using new developments in nonsmooth analysis to obtain generalized derivative information using a nonsmooth generalization of the vector forward mode of automatic differentiation. Several optimization studies are performed with constraints on both the minimum temperature difference (ΔTmin) and total heat exchanger conductance (UAmax) used to represent the trade-offs between energy consumption and the required heat transfer area. In addition, comparison is made with the conventional process simulator Aspen HYSYS using particle swarm optimization. Results show that the nonsmooth model was able to reduce the required compression power by 14.4% compared to the initial feasible design for the dual mixed refrigerant process, and by 20.4–21.6% for the dual mixed refrigerant process with NGL extraction. Furthermore, the solutions obtained from the nonsmooth model were 1.9–8.1% better than the design obtained by particle swarm optimization. Multistart optimization also shows that IPOPT converges to the best known solution when starting from an initial feasible design.
Keywords: Process optimization; Nonsmooth models; DMR processes; LNG (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544220301067
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:196:y:2020:i:c:s0360544220301067
DOI: 10.1016/j.energy.2020.116999
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().