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针对循环流化床锅炉残碳量无法直接测量的问题,提出了利用容易测量的风量和煤量信息,间接测量残碳量的方法。首先通过机理分析,建立残碳量动态机理模型,能够实时反映炉膛内的燃烧状况,然后基于广义卡尔曼滤波(EKF)理论建立了信息融合算法,通过给煤量、总风量等信息准确估算出炉膛内的残碳量。最后通过对某电厂300MW机组进行实验论证,根据残碳量计算的热量、床温、氧量和实际值对比验证,负荷在95%～65%的范围内变化时,误差不超过2%,证明循环流化床锅炉中残碳量可以通过广义卡尔曼滤波信息融合方法准确预测。
Aiming at the problem that the residual carbon in circulating fluidized bed boiler can not be directly measured, a method of indirectly measuring the amount of residual carbon using the information of air volume and coal quantity which is easy to measure is proposed. Firstly, through the mechanism analysis, a dynamic mechanism model of residual carbon was established to reflect the combustion condition in the furnace in real time. Then an information fusion algorithm was established based on the generalized Kalman filter (EKF) theory. The information of coal consumption and total air flow were accurately estimated Residual carbon content in the furnace. Finally, a 300MW unit in a power plant is experimentally demonstrated. The comparison of the calculated heat, bed temperature, oxygen amount and actual value of residual carbon verifies that the error does not exceed 2% when the load varies from 95% to 65% The residual carbon in circulating fluidized bed boiler can be accurately predicted by the generalized Kalman filter information fusion method.