多目标优化配煤掺烧方式下的烟气成分分析

Analysis of Flue Gas Composition under Multi-objective Optimized Coal Blending Mode

锅炉排烟成分的具体分析对燃烧状态监测和燃烧优化控制具有重要意义,但高温、复杂的环境给烟气成分直接测量带来困难。因此建立了基于配煤掺烧的电站锅炉烟气成分分析模型,通过配煤掺烧实验,以满足不同负荷、机组经济性等多个目标。在分析不同配煤掺烧方式后,确定了适合超超临界锅炉的配煤掺烧方案。通过软测量技术完成入炉煤质收到基水份和灰份的在线测量,进而得到配煤煤质各参数。鉴于燃煤各元素与烟气成分两者的相关性,从入炉煤元素中提取排烟成分信息,最终实现对烟气成分的间接测量。仿真实验结果表明,软测量下的煤质成分计算值与电厂实际检测值误差较小,该模型能够为烟气成分的监测提供一种快速分析工具,为电厂锅炉燃烧优化和节能减排提供依据。

The specific analysis of the boiler exhaust gas composition is of great significance for combustion state monitor and combustion optimization control,but the high temperature and complex environment bring difficulties to the direct measurement of the flue gas composition.Therefore,we established a model of flue gas composition analysis of power plant boiler based on coal blending,and conducted coal blending experiments to achieve multiple goals such as different loads and unit economy.After analyzing different coal blending methods,a coal blending combustion scheme suitable for ultra-supercritical boilers was determined.The on-line measurement of the basic moisture and ash content of the coal entering the furnace was completed through the soft-sensing technology,and the various parameters of the coal blending quality were obtained.Based on the correlation between the various elements of coal and the composition of the flue gas,the information of the exhaust smoke composition was extracted from the elements of the coal entering the furnace,and finally the indirect measurement of the composition of the flue gas was realized.The simulation experiment results show that the calculated value of coal composition under soft measurement has a small error with the actual detection value of the power plant.This model can provide a rapid analysis tool for the monitoring of flue gas composition,and provide a basis for the optimization of power plant boiler combustion and energy saving and emission reduction.