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Retrofit and optimisation for a vacuum gas oil hydrotreating system based on exergy load distribution analysis

Authors: Lixia Kang; Yongzhong Liu; Xiaoqiang Liang;

Retrofit and optimisation for a vacuum gas oil hydrotreating system based on exergy load distribution analysis

Abstract

The energy-intensive hydrotreating processes, which operate at high pressure and high temperature, are widely adopted in refineries to improve the quality of oil products. In this paper, the energy and emission performance of a vacuum gas oil hydrotreating unit is investigated by the exergy load distribution analysis incorporated with process simulations. The quantitative relationship among the exergy loads, exergy efficiencies of the subsystems and the exergy efficiency of the entire system is obtained. Two operational optimisation strategies and one retrofit scheme for the entire system are proposed by adjusting the exergy loads and exergy efficiencies of the subsystems. Results show that the exergy efficiency of the entire system increases by 1.23% through the proposed operational optimisation strategies, and the CO2 emission of the entire system can be reduced by 56.45% through the proposed retrofit scheme.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average