Method for controlling flue gas desulfurization based on neural network prediction

Abstract

The invention relates to a method for controlling flue gas desulfurization based on neural network prediction. The method is characterized by comprising the following steps: S1, collecting sample datarelated to time variation in a wet flue gas desulfurization system, and determining neurons of an input layer and an output layer of a dynamic neural network according to the collected sample data; S2, modeling the wet flue gas desulfurization system by using the dynamic neural network in the S1 to establish a prediction model of the wet flue gas desulfurization system; and S3, calculating a sulfur dioxide concentration prediction value at a flue gas outlet of the wet flue gas desulfurization system by using the prediction model of the wet flue gas desulfurization system established in the S2, and controlling a slurry spray amount of the wet flue gas desulfurization system by using the sulfur dioxide concentration prediction value.

Description

Technical field [0001] The invention belongs to the technical field of flue gas desulfurization, and specifically relates to a method for predicting and controlling flue gas desulfurization based on neural network. Background technique [0002] The limestone-gypsum wet flue gas desulfurization technology uses limestone powder and water to make a slurry as an absorbent, pumped into the absorption tower and fully contacted and mixed with the flue gas. The sulfur dioxide in the flue gas and the calcium carbonate in the slurry and the air blown in from the lower part of the tower The oxidation reaction generates calcium sulfate. After calcium sulfate reaches a certain degree of saturation, it crystallizes to form dihydrate gypsum. [0003] The gypsum slurry discharged from the absorption tower is concentrated and dehydrated to make its water content less than 10%, and then sent to the gypsum storage bin by a conveyor for stacking. The flue gas after desulfurization is passed through a ...

AI Technical Summary

Problems solved by technology

When the load of the unit is in a steady state, a better control effect can be obtained, but under the condition of variable attack, the system presents nonlinearity and large hysteresis. At this time, it is difficult to better control the flow rate of the slurry in the spray tower

If the amount of slurry sprayed is too small, it will be difficult to ensure that the emission standard of flue gas can be met; if the amount of slurry sprayed is too much, it will cause waste of resources

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