文献类型：期刊文献

中文题名：基于工业数据的催化裂化装置选择性催化还原脱硝机理模型

英文题名：MODELING THE DENITRIFICATION MECHANISM OF SELECTIVE CATALYTIC REDUCTION IN CATALYTIC CRACKING UNIT BASED ON INDUSTRIAL DATA

作者：戴宁锴[1];王杰[1];欧阳福生[1];王建平[2];焦云强[2];裴旭[2]

机构：[1]华东理工大学化工学院石油加工研究所,上海200237;[2]石化盈科信息技术有限责任公司

年份：2022

卷号：53

期号：8

起止页码：91

中文期刊名：石油炼制与化工

外文期刊名：Petroleum Processing and Petrochemicals

收录：CSTPCD;;Scopus;北大核心:【北大核心2020】；CSCD:【CSCD_E2021_2022】；

语种：中文

中文关键词：选择性催化还原;烟气脱硝;氮氧化物;机理模型;龙格库塔吉尔法;遗传优化算法

外文关键词：selective catalytic reduction;flue gas denitrification;nitrogen oxides;mechanism model;Runge-Kutta-Gill method;genetic algorithm method

摘要：通过研究选择性催化还原(SCR)技术机理,建立催化裂化(FCC)装置再生烟气SCR系统脱硝机理微分方程组模型。基于大量工业SCR系统数据,利用龙格库塔吉尔(RKG)方法对脱硝机理微分方程组进行求解,并结合遗传算法对模型参数进行寻优。结果表明,模型对FCC装置SCR系统出口氮氧化物(NO_(x))浓度预测的平均绝对误差为5.75%,模型预测值与装置实际值拟合的可决系数为0.906。这说明所建SCR脱硝机理模型具有较强的泛化能力和较高模拟精度,可用于优化FCC装置再生烟气SCR系统的操作条件,实现NO_(x)排放达标。
Based on the mechanism of selective catalytic reduction(SCR)technology,a set of denitrification mechanism modeling equations of regenerator flue gas SCR system in fluid catalytic cracking unit were established.According to a large amount data of SCR system,the mechanism model equations were solved by Runge-Kutta-Gill method,and the model parameters were optimized by combining genetic algorithm.The verification results show that the mean absolute percentage error of the model is 5.75%and the coefficient of determination is 0.906,which indicate that the established SCR denitrification mechanism model has strong generalization ability and high simulation accuracy.The model will be expected to play an important role in optimizing the operating conditions of the SCR systems for achievement standard of nitrogen oxides emission of the treated flue gas.