Modeling of the denitration process of the SNCR system of coal-fired power plants based on Bi-LSTM

During the operation of thermal power units, a large amount of NO x pollutants is generated due to combustion. In order to reduce NO x emissions, the implementation and optimization of denitrification technology has become a key issue in the current environmental protection. In the selective non-catalytic reduction (SNCR) denitration control system, due to the delay in the chemical reaction time of sampling, it is impossible to accurately predict the NO x concentration and to quickly adjust the amount of ammonia injection. In this work builds a SNCR denitrification model based on Bi-LSTM to predict the main steam flow rate and the flow rate of urea solution in the furnace area at the current moment using upstream boiler operation parameters. Comparing with SVR, DNN, CNN, LSTM network, the proposed method performs the best in simulation. The MSEs of main steam flow and furnace zone urea solution urea flow are as low as 0.000151 and 0.001232, respectively, and the R 2 s are as high as 0.998905 and 0.998905, respectively.