Bed temperature is one of the important operating parameters of circulating fluidized bed(CFB)boiler.In view of the problems of strong bed temperature coupling,many disturbing factors and complicated control,there is an urgent need to establish a mathematical model of bed temperature to realize the bed temperature control,to ensure the safe and smooth operation of CFB boiler.To this end,chaotic mapping,tangent flight(TF)and Cauchy variational strategies are firstly introduced to improve the northern goshawk optimization(NGO)algorithm,and the TF-NGO algorithm is tested with a system model of the actual operating conditions.The test results show that the TF-NGO algorithm has faster convergence speed and higher optimization accuracy.Secondly,the field operation data of 350 MW supercritical CFB boiler in a Shanxi power plant are collected and preprocessed.Finally,the TF-NGO algorithm is used to identify the parameters of the proposed model,and the model is validated with the actual operating condition data.The identification and validation results show that the bed temperature model identified by the TF-NGO algorithm fits well with the actual output and can effectively reflect the dynamic characteristics of the bed temperature,which proves the validity of the proposed model.This study lays foundation for the subsequent research on the optimal control of bed temperature in 350 MW supercritical CFB boilers.
维普
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