SCR denitration system prediction model optimization method based on machine learning

Abstract

The invention provides an SCR denitration system prediction model optimization method based on machine learning. The SCR denitration system prediction model optimization method comprises the followingsteps: S1, collecting the NOx concentration of a boiler outlet in an SCR denitration system and real-time sample data of related indexes influencing the NOx concentration; s2, carrying out dimensionreduction processing by utilizing principal component analysis; s3, establishing a support vector machine model; s4, introducing an exponential decay model to iteratively update the step size value ofthe longicorn beard algorithm, and optimizing vector machine parameters; s5, performing simulation of a support vector machine; and S6, repeating the step S1S5. The invention provides an SCR denitration system prediction model optimization method based on machine learning, which solves the problem that accurate control of ammonia injection quantity is difficult to realize in the existing thermalpower plant; and the invention comprises performing dimension reduction processing on sample data based on a PCA method, iteratively updating a step size value by introducing an exponential decay model, and optimizing by improving a BAS algorithm to obtain optimal support vector machine model parameters, and establishing an optimized support vector machine regression (SVM) model.

Description

technical field

[0001] The invention is a machine learning-based SCR denitrification system prediction model optimization method, which relates to the fields of geotechnical engineering and tunnel engineering, and specifically relates to the fields of real-time monitoring and forecasting of foundation pit excavation deformation and stability analysis. Background technique

[0002] More than half of my country's nitrogen oxide (NOx) emissions come from coal combustion, and one of the key industries for NOx pollution control is the thermal power industry. Selective Catalytic Reduction technology (Selective Catalytic Reduction, SCR) is under the condition of a catalyst, select the flue downstream of the boiler with a flue temperature of 300 ~ 4000 ℃, inject the reducing agent into the NOx reaction in the flue gas, and reduce the NOx , reduced to pollution-free N2 and H20. The SCR denitrification system has become an important equipment for large thermal power units to achieve ...

Examples

Embodiment Construction

[0082] A machine learning-based SCR denitrification system prediction model optimization method of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0083] Such as figure 1 As shown, the pulverized coal is burned in the boiler to form flue gas, which contains NO X , SO 2 Pollutants, such as pollutants, enter the SCR denitrification reactor after being cooled by the heat exchanger. The reactor inlet is equipped with an ammonia injection grid (the ammonia injection grid refers to the ammonia injection pipe and grid), and then the ammonia from the liquid ammonia evaporator After the gas is mixed with the dilution air, the NO in the flue gas X A selective reduction reaction occurs under the action of a catalyst to generate water and ammonia. At present, it is difficult for most coal-fired power plants to accurately control the amount of ammonia injection. Insufficient ammonia injection will ...

technical field

[0001] The invention is a machine learning-based SCR denitrification system prediction model optimization method, which relates to the fields of geotechnical engineering and tunnel engineering, and specifically relates to the fields of real-time monitoring and forecasting of foundation pit excavation deformation and stability analysis. Background technique

[0002] More than half of my country's nitrogen oxide (NOx) emissions come from coal combustion, and one of the key industries for NOx pollution control is the thermal power industry. Selective Catalytic Reduction technology (Selective Catalytic Reduction, SCR) is under the condition of a catalyst, select the flue downstream of the boiler with a flue temperature of 300 ~ 4000 ℃, inject the reducing agent into the NOx reaction in the flue gas, and reduce the NOx , reduced to pollution-free N2 and H20. The SCR denitrification system has become an important equipment for large thermal power units to achieve ...

Examples

Embodiment Construction

[0082] A machine learning-based SCR denitrification system prediction model optimization method of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0083] Such as figure 1 As shown, the pulverized coal is burned in the boiler to form flue gas, which contains NO X , SO 2 Pollutants, such as pollutants, enter the SCR denitrification reactor after being cooled by the heat exchanger. The reactor inlet is equipped with an ammonia injection grid (the ammonia injection grid refers to the ammonia injection pipe and grid), and then the ammonia from the liquid ammonia evaporator After the gas is mixed with the dilution air, the NO in the flue gas X A selective reduction reaction occurs under the action of a catalyst to generate water and ammonia. At present, it is difficult for most coal-fired power plants to accurately control the amount of ammonia injection. Insufficient ammonia injection will ...

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