Efficiency enhancement of a commercial natural gas liquid recovery plant: A MINLP optimization analysis

This paper aims at modeling and optimizing a Middle East-based commercial natural gas liquid (NGL) recovery and fractionation plant, using a predictive process simulator. NGL units are known to be highly energy-intensive as steam-based heating and refrigeration-based cryogenic cooling are critical r...

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Published in:Separation science and technology Vol. 55; no. 5; pp. 955 - 966
Main Authors: Murali, Ashwin, Berrouk, Abdallah S., Dara, Satyadileep, AlWahedi, Yasser F., Adegunju, Sulaimon, Abdulla, Haitham Salmeen, Das, Anjan Kumar, Yousif, Nafisa, Hosani, Mariam Al
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 23.03.2020
Taylor & Francis Ltd
Subjects:
Algorithms
Approximation
Computer simulation
Cryogenic cooling
distillation
Economics
Feeds
Fractionation
Gas temperature
gPROMS
Heating
Liquefied natural gas
Liquefied petroleum gas
Mixed integer
Model accuracy
Naphtha
Natural gas
Natural gas liquids
Natural gas prices
NGL recovery process
Nonlinear programming
Optimization
Profitability
Ratios
Recovery
Refrigeration
Revenue
simulation
Simulators
Steady state models
Steam consumption
ISSN:0149-6395, 1520-5754
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Summary:This paper aims at modeling and optimizing a Middle East-based commercial natural gas liquid (NGL) recovery and fractionation plant, using a predictive process simulator. NGL units are known to be highly energy-intensive as steam-based heating and refrigeration-based cryogenic cooling are critical requirements for their operation. Indeed, these units govern the degree of profitability of gas plants especially during low natural gas price scenarios. As a result, this study explores the ways of improving the performance of NGL units through a deterministic optimization analysis. A steady state model of the plant is built using gPROMS process builder followed by validation using plant data to ensure the model accuracy. A mixed integer nonlinear programming optimization problem is formulated with the objective of maximizing the net revenue of the plants by means of manipulating various decision variables such as feed gas temperature, column operating pressure, feed stage location, reflux and boil up ratios subject to specific process constraints. Optimization problem is solved using outer approximation equality relaxation augmented penalty algorithm. It is determined that the process optimization yields an additional revenue of 4.1 MM USD annually due to ~22% increase in Liquefied Petroleum Gas (LPG) production, ~6% increase in Naphtha production, and ~16% reduction in steam consumption in the reboiler of the columns.
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ISSN:0149-6395
1520-5754
DOI:10.1080/01496395.2019.1574825