GHG emission reduction via multiple fuel options in carbon-constrained industrial clusters
Author | Bechara, Christelle |
Author | Alnouri, Sabla Y. |
Available date | 2024-03-30T11:05:22Z |
Publication Date | 2023-01-01 |
Publication Name | Computer Aided Chemical Engineering |
Identifier | http://dx.doi.org/10.1016/B978-0-443-15274-0.50002-0 |
Citation | Bechara, C., & Alnouri, S. Y. (2023). GHG emission reduction via multiple fuel options in carbon-constrained industrial clusters. In Computer Aided Chemical Engineering (Vol. 52, pp. 7-12). Elsevier. |
ISSN | 15707946 |
Abstract | This paper primarily investigates the effect of incorporating multiple fuel options onto carbon constrained industrial clusters. The purpose of doing so was to maximize the profit through the optimal allocation of multiple types of fuel. The cluster consists of a number of different production plants and a power plant for the processing of value-added products as well as the generation of electricity. The power plant is connected to the electric grid and constitutes the main source of electricity for the cluster. It also has the ability to produce more power and export it to the grid. The integration of additional plants that could generate new products, convert, or store carbon dioxide through CCUS technologies, and produce cleaner power through the use of renewable and/or multiple and blended fuels is assessed. It was found that the incorporation of multiple types of fuel within a single cluster resulted in the lowest post-capture emissions with 9469 t CO2/d generating a high-end profit of $907.16 million/y, when compared to cases which relied on a single fuel option only. |
Language | en |
Publisher | Elsevier B.V. |
Subject | Biomass Energy Fuel GHG Emissions Industrial Clusters |
Type | Book chapter |
Pagination | 7-12 |
Volume Number | 52 |
Check access options
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
This item appears in the following Collection(s)
-
GPC Research [494 items ]