Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/28337
Title: A novel approach for utilizing waste heat resources in the steel industry
Authors: Wang, R
Zhang, W
Yang, S
Zhang, Z
Fan, S
Lai, CS
Keywords: low-temperature waste heat;waste heat recovery;nest optimization model;pressure loss;steel industry
Issue Date: 13-Nov-2023
Publisher: Frontiers Media
Citation: Wang, R. et al. (2023) 'A novel approach for utilizing waste heat resources in the steel industry', Frontiers in Energy Research, 11, 1257344, 1 - 18. doi: 10.3389/fenrg.2023.1257344.
Abstract: The efficient utilization of waste heat resources plays a pivotal role in enhancing energy efficiency and curbing carbon emissions. To address this, effective planning for waste heat recovery (WHR) utilization becomes imperative, guiding consumers in device installation and capacity allocation. This paper introduces a novel approach to WHR utilization planning, tailored specifically for steel factories, with the goal of achieving optimal WHR solutions. The approach automates device selection, capacity allocation, and operational strategies while considering their impact on the regular manufacturing processes of the factories to maximize overall benefits. Unlike existing methods, this approach introduces discrete capacity selection modeling, considering the constraints of the limited product range during device selection. A numerical study illustrates the effectiveness of the proposed model in delivering optimal WHR device selection, capacity allocation, and operational strategies under various economic conditions. These enhancements contribute to the increased practicality and realism of the proposed method in comparison to existing approaches.
Description: Data availability statement: The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
URI: https://bura.brunel.ac.uk/handle/2438/28337
DOI: https://doi.org/10.3389/fenrg.2023.1257344
Other Identifiers: ORCiD: Chun Sing Lai https://orcid.org/0000-0002-4169-4438
1257344
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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