文献类型：期刊文献

英文题名：Life cycle assessment and multi-objective optimization for industrial utility systems

作者：Li, Hanxiu[1];Zhao, Liang[1]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2023

卷号：280

外文期刊名：ENERGY

收录：;EI(收录号：20232614313004);WOS:【SCI-EXPANDED(收录号:WOS:001028782400001)】；

基金：The work was supported National Natural Science Foundation of China (Basic Science Center Program: 61988101) , National Natural Science Fund for Distinguished Young Scholars (61925305) , National Natural Science Foundation of China (22178103) , Fundamental Research Funds for the Central Universities (222202317006) and Shanghai AI Lab.

语种：英文

外文关键词：Industrial utility system; Emission reduction; Life cycle assessment; Multi-objective optimization

摘要：Utility systems, which are energy and CO2 intensive, provide power and heat for the industrial process. Modeling, assessing, and optimization of utility systems can help promote sustainable development. This paper proposed a life cycle assessment-based multi-objective optimization framework to address this issue. First, measures for saving energy and reducing emissions were proposed to improve the utility system. The semiempirical models of the basic components in the improved utility system are developed using process mechanisms and historical data. Secondly, the theory of life cycle assessment (LCA) is employed to evaluate the environmental impacts comprehensively. The operating cost and environmental impact models of the system are then developed and solved by a weighted multi-objective optimization method. Finally, a case study from an industrial utility system is implemented to verify the effectiveness of the proposed method, and three scenarios with different emission reduction methods are compared. In the scenario with two emission reduction measures, it shows that the maximum reduction of environmental impacts could be 56.59%, while the operating cost increases by 36.17%. The Pareto frontiers of the three scenarios provide several choices to balance the operating cost and environmental impacts.