Optimization model of converter gas calorific value based on cabinet location prediction
Converter gas is an important energy medium produced during converter smelting,and improving the calo-rific value of converter gas is of great significance for user use and balanced scheduling.At present,most studies focus on increasing the amount of recovered gas,but there are no reports on improving the quality of gas recovery through regulation.In order to improve the quality of converter gas recovery within the limit of cabinet recycling,and increase the efficiency of converter gas waste heat and energy recovery.This article establishes an optimization model for the calorific value of converter gas by combining the prediction and control of the starting and ending recov-ery time of the cabinet.By analyzing the characteristics of gas generation and gas consumption,a carbon balance was established based on the blowing plan to develop a prediction model for the average gas flow rate.Compared with actual production data,the accuracy of the model reached 96%.The Sarima model was used to train and develop a gas consumption prediction model based on historical data,with an accuracy of 97%.Based on the initial cabinet position at the beginning of the blowing process,a gas cabinet position prediction model was established to predict the changes in cabinet positions during the blowing cycle,with an accuracy of 95%.Fit the CO concentration charac-teristic curve based on historical data,with a variance of over 0.95.Using nonlinear programming optimization algo-rithms,with the goal of recovering the calorific value of gas as the optimization objective,and the container capacity and CO concentration at the beginning and end of the recovery as constraints,a control model for the start and end of the recovery time of converter gas was developed.The optimization scheme was solved through programming,which improved the calorific value of converter gas during the blowing cycle.Taking the control results of a single steel furnace as an example,the calorific value of the recovered gas before and after the control was increased from 6 278.3 kJ/m3 to 6 654.6 kJ/m3,reducing the emission of high calorific value gas.By comparing with a large amount of on-site data,the average heat value of recovered gas has increased by 5%.This modeling process pro-vides an effective optimization method for improving the heat value of converter gas.
calorific value of converter gascabinet predictionnonlinear programmingCO concentrationoptimi-zation model
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