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Superstructure optimization models for regional coal industry development considering water resources constraints—A case study of Ordos, China.

Authors :
Cheng, Chao
Gao, Dan
Zhang, Heng
Xu, Zipeng
Huang, Jiguang
Source :
Computers & Chemical Engineering. Oct2023, Vol. 178, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

• A modeling method that combines superstructure modeling and a mixed integer programming is proposed. • 4 major coal application industries and 14 coal technology categories are considered. • Three scenarios are set to analyze coal industry development under the constraints. • Increases in available water resources impact the coal chemical industry most significantly. • Significant reductions in CO 2 emissions require reductions in IDCL and CTO production. Optimizing the industrial structure is an important way to address resource constraints, achieve sustainable development. In this study, a planning method that combines the superstructure modeling concept and the mathematical method of mixed integer programming is proposed to investigate the optimized results of the coal industry under given constrained water resources, with 4 major coal application industries and 14 coal technology categories are considered. The results indicate that an increase in available water resources is associated with an increased local utilization rate of coal. Under the Water Rights Replacement Scenario, the local utilization rate of coal reaches 24.9%. Changes in available water resources significantly impact the coal chemical industry. In addition, significant reduction by 25% in carbon dioxide emissions requires 70 percent reduction in IDCL and CTO production. The policy implications for the development of the coal industry are also provided in the end. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00981354
Volume :
178
Database :
Academic Search Index
Journal :
Computers & Chemical Engineering
Publication Type :
Academic Journal
Accession number :
171953934
Full Text :
https://doi.org/10.1016/j.compchemeng.2023.108384