Energy saving technologies and mass-thermal network optimization for decarbonized iron and steel industry: A review

Wang, R. Q.; Jiang, L.; Wang, Y. D.; Roskilly, A. P.

Abstract

The iron and steel industry relies significantly on primary energy, and is one of the largest energy consumers in the manufacturing sector. Simultaneously, numerous waste heat is lost and discharged directly into the environment in the process of steel production. Thus considering conservation of energy, energy-efficient improvement should be a holistic target for iron and steel industry. The research gap is that almost all the review studies focus on the primary energy saving measures in iron and steel industry whereas few work summarize the secondary energy saving technologies together with former methods. The objective of this paper is to develop the concept of mass-thermal network optimization in iron and steel industry, which unrolls a comprehensive map to consider current energy conservation technologies and low grade heat recovery technologies from an overall situation. By presenting an overarching energy consumption in the iron and steel industry, energy saving potentials are presented to identify suitable technologies by using mass-thermal network optimization. Case studies and demonstration projects around the world are also summarized. The general guideline is figured out for the energy optimization in iron and steel industry while the improved mathematical models are regarded as the future challenge.

Citation

Wang, R. Q., Jiang, L., Wang, Y. D., & Roskilly, A. P. (2020). Energy saving technologies and mass-thermal network optimization for decarbonized iron and steel industry: A review. Journal of Cleaner Production, 274, Article 122997. https://doi.org/10.1016/j.jclepro.2020.122997

• Journal Article Type: Article
• Acceptance Date: Jun 22, 2020
• Online Publication Date: Jul 17, 2020
• Publication Date: 2020-11
• Deposit Date: Aug 4, 2020
• Publicly Available Date: Aug 4, 2020
• Journal: Journal of Cleaner Production
• Print ISSN: 0959-6526
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 274
• Article Number: 122997
• DOI: https://doi.org/10.1016/j.jclepro.2020.122997
• Public URL: https://durham-repository.worktribe.com/output/1295185