Risk-based optimization for representative natural gas liquid (NGL) recovery processes by considering uncertainty from the plant inlet
The need to reduce energy requirement and improve operational flexibility of the NGL recovery process is a challenging problem. Different design options have been developed over the past four decades. This paper presents optimization of six selected process schemes subject to various upstream feed c...
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| Main Authors: | , , , , , |
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| Format: | Article |
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Elsevier B.V.
2015
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949655596&doi=10.1016%2fj.jngse.2015.01.028&partnerID=40&md5=20f3109172a76edfbf57dfe10a946470 http://eprints.utp.edu.my/31662/ |
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| Summary: | The need to reduce energy requirement and improve operational flexibility of the NGL recovery process is a challenging problem. Different design options have been developed over the past four decades. This paper presents optimization of six selected process schemes subject to various upstream feed conditions. The process schemes were chosen for their numerous advantages such as future forefront, wide application and commercial availability. HYSYS process models were constructed for each process schemes under common sets of criteria. The information was then transferred to GAMS for optimization. One year real feed plant data was used to examine the performance of the process schemes. The results from single chance constrained optimization showed that the enhanced NGL recovery process (IPSI-1) provides a very competitive profit value with only a 6 risk of violating constraint compared to gas sub-cooled process (GSP) scheme (28). On the other hand, profit value obtained from the joint chance constrained optimization for GSP was higher than IPSI-1 with a competitive risk of violating constraint 33 and 26, respectively. Flexible decision to produce more sales gas or NGL product could be made before the plant operation by looking the profit value and its corresponding risk of violation of a constraint. © 2015 Elsevier B.V. |
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