Exergy analysis and multi-objective optimisation for energy system: a case study of a separation process in ethylene manufacturing

In chemical industry, most processes face the challenge of high energy consumption. The approach presented in this study can reduce the energy footprint and increase efficiency. The energy system of a separation process in ethylene manufacturing is used to demonstrate the effectiveness of the approach. The chilling train system of the separation process in a typical ethylene plant consumes most cooling and provides appropriate feed for distillation columns. The steady state simulation of system was presented and the simulation results were proved accurate. The conventional exergy analysis identifies that Dephlegmator No.1 (a heat exchange and mass transfer device) has the highest exergy destruction (1401.28 kW). Based on advanced exergy analysis, Dephlegmator No.1 has the highest rate of avoidable exergy destruction (89.04 %). Finally, a multi-objective optimisation aiming to maximise system exergy efficiency and to minimise operational cost was performed and the Pareto frontier was obtained. The multi-objective optimized exergy efficiency is 79.53 % (improved by 0.61 %) and the operational cost is 0.02031 yuan/kg (saved by 11.19 %). This study will guide future research to reduce energy consumption in process manufacturing. (C) 2020 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

Automated summary

Most processes in the chemical industry face challenges of high energy consumption, but the method proposed in this study can reduce energy consumption and improve efficiency. Using the energy system of a separation process in ethylene manufacturing as an example, the study demonstrates the effectiveness of the approach through advanced exergy analysis and multi-objective optimization, achieving increased system exergy efficiency and reduced operational costs. This research provides guidance for future studies on reducing energy consumption in process manufacturing.