基于多过程模型融合的流化床配风解耦燃烧参数预测与优化  

Prediction and optimization of decoupled combustion parameters in fluidized bed air distribution based on multi-process model integration method

作　　者：狄子琛 常成功 杨凤玲 吴海滨 程芳琴 DI Zichen;CHANG Chenggong;YANG Fengling;WU Haibin;CHENG Fangqin(Institute of Resources and Environment Engineering,Shanxi University,Taiyuan 030006,China;School of Environment,Tsinghua University,Beijing 100084,China)

机构地区：[1]山西大学资源与环境工程研究所,山西太原030006 [2]清华大学环境学院,北京100084

出　　处：《洁净煤技术》2023年第8期95-101,共7页Clean Coal Technology

基　　金：山西省科技战略研究专项资助项目(202204031401048);山西省基础研究计划资助项目(202103021223027);山西省留学人员科技活动择优资助项目(20220003)。

摘　　要：循环流化床广泛应用于矸石、污泥等低品位燃料转化,近年来随着其用途和需求变化,进行了广泛的适应性改造,准确模拟和预测流化床炉内燃烧状况可为此提供基础支撑。针对当前流化床模型复杂,难以兼顾多参数精准预测问题,构建了基于热力学和动力学的流化床模型,计算了燃料变化对需氧量的影响以及空隙率和温度随床层高度的变化。通过构建热力学模型,预测了碳含量为74.05%、17.71%、24.27%、34.01%的4种煤矸石,理论需氧量分别为15.17、4.00、4.47、6.20 kg/h。计算结果关联了燃料类型与理论需氧量,可辅助风机功率、风量等参数设计;通过串联10个RCSTR动力学模块嵌入动力学模型,实现不同床层的空隙率、温度、气体分布等关键参数计算,单点参数误差低于15%。多过程模型融合方法的建立可实现不同类型静态指标分类预测,为燃料变换时调控流化床进风量、一二次风风口位置等参数提供理论依据和设计参考。Circulating fluidized bed(CFB)has been widely used for the conversion of low-grade fuels such as gangue and sludge.In recent years,with the changes in the applications and requirements,extensive adaptive modifications have been made to the CFB.Accurate simulation and prediction of the combustion performance inside the fluidized bed can provide fundamental support for these modifications.A fluidized bed model based on thermodynamics and kinetics was constructed to address the complexity of current fluidized bed models and the difficulty of accurately predicting multiple parameters.The influence of fuel variation on the oxygen demand,as well as the variation of void fraction and temperature with bed height were calculated.By constructing the thermodynamic model,the theoretical oxygen demands for four types of coal gangue with carbon contents of 74.05%,17.71%,24.27%and 34.01%were predicted,with theoretical oxygen demand of 15.17,4.00,4.47 and 6.20 kg/h,respectively.The calculated results were related to fuel type and theoretical oxygen demand,which can assist in the design of parameters such as fan power and air volume.Furthermore,by embedding 10 RCSTR dynamic modules in series into the kinetic model,the key parameters,including void fraction,temperature,and gas distribution,for different bed layers were calculated,with the single-point parameter error of less than 15%.The classification and prediction of different types of static indicators can be achieved by the establishment of a multi process model fusion method,providing theoretical basis and design references for regulating parameters such as fluidized bed air flow rate and primary-secondary air inlet positions during fuel transformation.

关 键 词：Aspen Plus 循环流化床 参数预测 热力学 动力学 

分 类 号：TK22[动力工程及工程热物理—动力机械及工程]