Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.fuel.2010.12.043
Title: Investigating the trade-off between operating revenue and CO2 emissions from crude oil distillation using a blend of two crudes
Authors: Al-Mayyahi, M.A.
Hoadley, A.F.A.
Smith, N.E.
Rangaiah, G.P. 
Keywords: Heat integration
Multi-objective optimization
Petroleum refining
Process simulation
Issue Date: Dec-2011
Citation: Al-Mayyahi, M.A., Hoadley, A.F.A., Smith, N.E., Rangaiah, G.P. (2011-12). Investigating the trade-off between operating revenue and CO2 emissions from crude oil distillation using a blend of two crudes. Fuel 90 (12) : 3577-3585. ScholarBank@NUS Repository. https://doi.org/10.1016/j.fuel.2010.12.043
Abstract: Blending of different crude types is frequently used in petroleum refineries to improve their profitability and products yields. However, energy consumption and consequential CO2 emissions strongly depend on the types of crude being processed. The trade-off between CO2 emissions and economic objectives, such as net revenue, is investigated for cases of different crude blends using the multi-objective optimization approach. The first objective is the minimization of CO2 emissions whilst the second objective is maximizing the net revenue from the crude distillation unit (CDU). A rigorous model is used to estimate CO2 emissions from different sources within the CDU. This emissions model incorporates pinch analysis for heat integration, to optimize the distribution of utilities related to emissions. Blends of two crudes, 36 API and 27.7 API, are used as feedstock to a rigorous CDU model of the atmospheric crude tower, vacuum tower and heat exchanger network. Lighter crude blends recorded higher CO2 emissions and net revenue compared with the heavier blend due to the greater distilled fraction. However, CO2 emissions did not vary linearly with the fraction of each crude, as the heat exchanger network also influenced the degree of heat recovery and consequently the level of CO2 emissions. The multi-objective solutions show the influence of all 13 of the process variables on the objectives. © 2011 Elsevier Ltd. All rights reserved.
Source Title: Fuel
URI: http://scholarbank.nus.edu.sg/handle/10635/89282
ISSN: 00162361
DOI: 10.1016/j.fuel.2010.12.043
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

14
checked on Aug 16, 2018

WEB OF SCIENCETM
Citations

11
checked on Jul 24, 2018

Page view(s)

39
checked on Jun 8, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.