摘要
燃料性质复杂多变是当前循环流化床机组运行过程中普遍面临的问题,现场应用过程中发现:利用锅炉风量-氧量热量信号计算得到的燃料发热量信号动态特性好,但存在较多干扰并且静态误差大;传统BTU(煤热值)校正计算得到的燃料发热量信号静态误差小,但滞后很大。利用卡尔曼滤波器对两种方法得到的燃料发热量信号进行融合,即将风量-氧量热量信号计算得到的燃料发热量参数作为状态,将BTU校正计算得的燃料发热量参数作为估计对象经过滤波计算,能够获得即快又准的燃料发热量信号。通过仿真和对一300 MW循环流化床机组运行数据进行分析,相对于动态法变负荷工况动态误差减小15%以上,相对静态法反映速度提升10 min以上,用于BTU校正时补偿量提高20%以上,验证了方法的有效性。
The complex and changeable fuel properties are common to the current circulating fluidized bed unit during operation.In the process of field application,it is found that:despite more interference and large static error,the fuel calorific value calculated by boiler air volume-oxygen quantity heat signal is good,while it presents small static error and large lag when calculated by traditional BTU(coal calorific value)correction.This paper uses the Kalman filter to fuse the fuel calorific value obtained by the two methods and obtains the fuel calorific signal quickly and accurately.The effectiveness of the method is verified by the simulation and analysis of the operation data of a 300 MW circulating fluidized bed unit.
作者
李泽铭
田亮
LI Zeming;TIAN Liang(School of Control and Computer Engineering,North China Electric Power University,Baoding 071003,China)
出处
《华北电力大学学报（自然科学版）》
CAS
北大核心
2021年第2期89-95,113,共8页
Journal of North China Electric Power University：Natural Science Edition
基金
国家重点研发计划项目(2017YFB0902100)。
