Development and application of secondary air optimization control system based on artificial neural network model

Abstract

The invention discloses a secondary air optimization control method based on an artificial neural network model. The secondary air optimization control method is implemented by the following steps that 1) measuring points of mass flow rate and flow velocity of pulverized coal are additionally arranged on a primary air pulverized coal pipeline, and pulverized coal distribution between the pipes and the flow state of the pulverized coal in the pipes are adjusted; 2) boiler operation data is read, the boiler efficiency is calculated online, a neural network boiler model is established, and the neural network boiler model is trained by using the operation data; and 3) the self-learning function and the high-speed optimization solution searching capability of the neuron network boiler model are utilized, the influence of the opening degree of a secondary air door and the change of the secondary air volume on the boiler efficiency and the nitrogen oxide emission concentration is predicted, finally, the optimal secondary air door and air volume instruction is output, and secondary air optimization control is realized. The fuzzy control principle of the artificial neuron network model and the characteristic of a multivariable high-speed optimization solution searching are utilized, the internal function relation of parameters such as the opening degree of the secondary air door and the boiler efficiency is analyzed, and automatic optimization control over the secondary air door and the air volume is achieved.

Description

technical field [0001] The invention belongs to the field of boiler combustion control, and in particular relates to a secondary air optimization control method based on an artificial neural network model. Background technique [0002] Boiler combustion efficiency mainly depends on the combustion state of pulverized coal in the furnace, and the ratio of secondary air can greatly affect the combustion state of pulverized coal in the furnace. At present, the control of the opening of the secondary air door mainly relies on the automatic control of the original DCS system Signal or operating personnel manually operate the adjustment. [0003] The secondary air door opening command given by the original DCS is generally based on the calculated value of the coal feeder feed rate feedback signal, that is, when the output coefficient of the coal mill is large, the opening of the secondary air door of the corresponding layer is appropriately increased, otherwise, it is decreased , ...

AI Technical Summary

Problems solved by technology

[0003] The secondary air door opening command given by the original DCS is generally based on the calculated value of the coal feeder feed rate feedback signal, that is, when the output coefficient of the coal mill is large, the opening of the secondary air door of the corresponding layer is appropriately increased, otherwise, it is decreased , this command algorithm is relatively simple, ignoring important factors such as the distribution of pulverized coal in the pipeline, the change of the flow state of pulverized coal in the pipe, and the overall air distribution structure of the boiler. , which greatly affects the combustion efficiency of pulverized coal in the furnace

[0004] There are also problems in adjusting the secondary damper manually by the operator. Firstly, due to the limitation of the operator's own energy, real-time adjustment and fine adjustment of the secondary damper cannot be achieved; secondly, the secondary damper instructions given by the operator can only rely on the relevant boilers. The operating regulations or the combustion adjustment experiment report given by the thermal engineering institute cannot meet the actual needs of the boiler in different states and under various working conditions.

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