Multi-objective Optimisation Using Fuzzy and Weighted Sum Approach for Natural Gas Dehydration with Consideration of Regional Climate

Abstract

The majority of the existing simulation-based research works on natural gas dehydration via absorption using tri-ethylene glycol (TEG) have focused on solving single or bi-objective problems where most of the objectives are in conflict with one another. It was not until 2017 that multi-objective problems with conflicting nature have started gaining significant interest in this field, especially those involving 3 or more objectives. In this work, a multi-objective optimisation (MOO) framework was developed involving two different techniques, i.e. the fuzzy optimisation and the weighted sum approach, for handling different conflicting objectives in a natural gas dehydration process. The developed framework is straightforward, which can be applied by anyone effortlessly and can be easily extended to data from other literatures. Two different case studies, which involved bi- and tri-objectives, are given here to illustrate the efficacy of the developed framework for improving the sustainability and performance of the natural gas dehydration process. Relative to previous works without optimisation, the optimum results obtained here provide a compromised solution between different objectives. Using fuzzy optimisation in case 1, for example, increases the net profit by 0.2% and reduces the VOC emissions by 33% (i.e. better sustainability). Although the water dew point increases by 15%, it is still within the specification range and hydrate formation will not occur.