基于降低飞灰含碳量的火电厂锅炉燃烧过程运行优化研究  

Research on Operation Optimization of Combustion Process of Thermal Power Plant Boiler Based on Reducing Carbon Content of Fly Ash

作　　者：陈浩 CHEN Hao(SPIC&GCL Binhai Electric Power Generation Co.,Ltd.,Yancheng 224500,China)

机构地区：[1]国家电投集团协鑫滨海发电有限公司,江苏盐城224500

出　　处：《化工管理》2024年第36期120-123,共4页Chemical Management

摘　　要：文章研究探讨了火电锅炉燃烧过程中关键工况参数对飞灰含碳量的影响,并基于主成分分析法(PCA)和BP神经网络模型进行了优化预测。通过MATLAB平台系统训练,确定了煤粉细度、一次风速和二次风挡开度等主要影响因素。此外,创新性地应用狼群算法对锅炉燃烧参数进行了多维度优化,显著提高了燃烧效率,降低了飞灰含碳量,为火电行业的节能减排和绿色发展提供了科学依据和技术支持。The influence of key operating parameters on the carbon content of fly ash during combustion of thermal power boiler was studied,and the optimal prediction was carried out based on principal component analysis(PCA)and BP neural network model.Through MATLAB platform system training,the main influencing factors such as fineness of pulverized coal,primary wind speed and secondary wind baffle are determined.In addition,the study innovatively applied wolf pack algorithm to optimize boiler combustion parameters in multiple dimensions,which significantly improved combustion efficiency and reduced carbon content of fly ash,providing scientific basis and technical support for energy conservation,emission reduction and green development of thermal power industry.

关 键 词：飞灰碳含量 火电锅炉 燃烧过程 运行优化 

分 类 号：TQ160.5[化学工程—高温制品工业]