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
Key words
carbon content of fly ash/thermal power boiler/combustion process/operation optimization
维普
万方数据