工业燃煤锅炉燃烧优化关键技术探析

Analysis on the technology of combustion optimization for industrial coal-fired boiler

优化工业锅炉燃烧技术可提高锅炉燃烧性能及降低环境污染程度。结合工业燃煤锅炉优化燃烧的实际情况,探析了基于参数调整的试验研究、燃烧理论建模研究、燃烧设备设计与改造研究、检测技术的燃烧优化研究、人工智能的燃烧优化研究该5种燃烧优化技术的优化改进。由相关分析可知:试验调整优化锅炉燃烧技术的方法一般适用于新建锅炉的调试阶段或更换燃料等情况;开展工业锅炉冷热态模拟可验证设计的合理性,多用于离线分析或仿真研究,尚不能应用于燃烧过程的在线实时建模和优化;对锅炉燃烧设备设计和优化改造的应用较为广泛,但其受到煤种及制粉系统的限制,该类优化并不全面;基于检测技术的燃烧优化技术目前仅能作为燃烧优化的辅助手段;人工智能技术用于工业煤粉锅炉的燃烧优化,可解决锅炉燃烧煤质的自动辨别问题、锅炉运行特性的非线性动态建模问题及基于多目标优化的锅炉运行优化控制问题。

Optimization of industrial coal-fired boiler combustion technology could improve the combustion performance of boiler and reduce the environmental pollution degree.Combining with the practical circumstance of optimization combustion of industrial coal-fired boiler,the five kinds of combustion technology optimizations(experimental research based on parameter adjusting,combustion theory modeling research,combustion equipment design and reformation research,combustion optimization research of testing technology and combustion optimization research on artificial intelligence)were discussed.From relative analysis we can see that:adjustment and optimization of boiler combustion normally should be used in commissioning phase of new boiler,or during the period of fuel change;the cold and hot state simulation could verify the rationality of design,it was always used in offline analysis or simulation study,it still could not be used in online real-time modeling and optimization in the combustion process;the applications of boiler design and optimization were relatively wide,but because of the restrictions of coal type and powder preparation system,this kind of optimization was not comprehensive;the combustion optimization based on the testing technology could only be the auxiliary means for combustion optimization;if the artificial intelligence technology could be used in the combustion optimization of industrial pulverized coal boiler,the problem of automatic identification,nonlinear dynamic modeling problem of boiler operating characteristics,and the boiler operation optimization control problem based on multi-objective optimization could be resolved.