文献类型：期刊文献

中文题名：大型炼化一体化过程全流程低碳运行分析与决策优化综述

英文题名：A Review of Low-carbon Operation Analysis and Decision Optimization in Large-scale Integrated Refinery-petrochemical Production Processes

作者：彭鑫[1];沈菲菲[1];张庭伟[1];堵威[1];钟伟民[1];钱锋[1]

机构：[1]华东理工大学能源化工过程智能制造教育部重点实验室,上海200237

年份：2024

卷号：38

期号：4

起止页码：571

中文期刊名：中国科学基金

外文期刊名：Bulletin of National Natural Science Foundation of China

收录：CSTPCD;;北大核心:【北大核心2023】；CSCD:【CSCD2023_2024】；CSSCI:【CSSCI_E2023_2024】；

基金：国家自然科学基金项目(61988101,61925305,62173145,62303186);中央高校基本科研业务费专项资金(222202417006);上海人工智能实验室资助。

语种：中文

中文关键词：炼化一体化过程;碳足迹建模;低碳运行;决策优化;分布式协同优化

外文关键词：integrated refinery-petrochemical process;carbon footprint modeling;low-carbon operation;decision optimization;distributed collaborative optimization

摘要：石化工业是国民经济支柱产业,也是高能耗高排放行业。面向双碳背景下传统石化行业低碳化、智能化转型需求,针对碳排与工艺耦合机理复杂的炼化一体化全流程碳足迹表征精度低问题、耦合互联多装置生产流程碳排异常环节难追溯问题以及实际工业环境下全流程优化方案不收敛问题,本文以大型炼化一体化全流程为研究对象,描述了利用过程机理、工业大数据和人工智能技术,研究炼化一体化全流程碳足迹建模理论、全流程碳排异常环节溯源理论以及全流程装置分布式协同决策优化理论,实现炼化一体化全流程低碳优化。在为流程工业碳足迹建模、溯源和优化提供方法的同时,也为实际炼化一体化企业高效、低碳、智能生产提供指导建议。
The large-scale petrochemical industry is a pillar industry of the national economy,characterized by high energy consumption and carbon emissions.In response to the demand for low-carbon and intelligent transformation in the traditional petrochemical industry under the context of dual carbon goals,this study describes the utilization of process mechanisms industrial big data,and artificial intelligence technology.It investigates theoretical frameworks for modeling the carbon footprint of the entire integrated petrochemical process,tracing irregular carbon emissions throughout the process,and achieving distributed collaborative optimization of process units.Meanwhile,this study also offers recommendations for efficient,low-carbon,and intelligent production in real-world integrated petrochemical enterprises.