文献类型：期刊文献

英文题名：A multi-criteria decision support model for adopting energy efficiency technologies in the iron and steel industry

作者：Ren, Hongtao[1];Zhou, Wenji[2];Makowski, Marek[3,4];Zhang, Shaohui[3,5];Yu, Yadong[1];Ma, Tieju[1,3]

机构：[1]East China Univ Sci & Technol, Sch Business, Meilong Rd 130, Shanghai 200237, Peoples R China;[2]Renmin Univ China, Sch Appl Econ, Beijing 100872, Peoples R China;[3]Int Inst Appl Syst Anal, Schlosspl 1, A-2361 Laxenburg, Austria;[4]Polish Acad Sci, Syst Res Inst, Newelska 6, PL-01447 Warsaw, Poland;[5]Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing 100083, Peoples R China

年份：2023

卷号：325

期号：2

起止页码：1111

外文期刊名：ANNALS OF OPERATIONS RESEARCH

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000751729700001)】；

基金：This research was funded by the National Natural Science Foundation of China (71961137012, 71571069, 71704055, 71874055, 71904007), the National Science Centre of Poland (2018/30/Q/HS4/00764), and the Major Innovation and Planning Interdisciplinary Platform for the "Double-First Class" Initiative, Renmin University of China.

语种：英文

外文关键词：Multi-criteria decision analysis; Energy efficiency; Technology adoption; Iron and steel production; Air pollution

摘要：Promoting energy efficiency in iron and steel production provides opportunities for mitigating environmental impacts from this energy-intensive industry. Energy efficiency technologies differ in investment costs, fuel-saving potentials, and environmental performance. Hence the decision-making of the adoption strategy needs to prioritize technological combinations concerning these multi-dimensional objectives. To address this problem, this study proposes a hybrid multi-criteria decision-support model for adopting energy efficiency technologies in the iron and steel industry. The modeling framework integrates a linear programming model that determines the optimal technology adoption rates based on the techno-economic, energy, and environmental performance details and an interactive multi-criteria model analysis tool for diverse modeling environments. A real case study was performed in which a total number of 56 energy efficiency technologies were investigated against various criteria concerning economics, energy, and environmental performances. The results examine the tradeoffs and synergies were examined with regard to seven criteria. A balanced solution shows that a total investment of 13.4 billion USD could save 2.51 Exajoule fuel consumption, cut 67.4 million tons (Mton) CO2 emissions, and reduce air pollution of 1.5 Mton SO2, 1.41 Mton NOx, and 0.86 Mton PM, respectively. The case study demonstrates the effectiveness and applicability of the proposed multi-criteria decision-making support framework.