Dynamic modeling method of boiler combustion system based on online support vector machine

A technology for support vector machines and boiler combustion, which is applied in special data processing applications, instruments, electrical digital data processing, etc., and can solve problems such as poor adaptability, poor control effect, and reduced modeling accuracy.

Inactive Publication Date: 2018-02-02
ZHEJIANG ZHENENG TAIZHOU NO 2 POWER GENERATION CO LTD +1
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  • Abstract
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  • Application Information

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Problems solved by technology

When the load, coal quality, and equipment characteristics of the boiler combustion system change, its control characteristics will also change. The online update strategy based on support vector replacement has poor adaptability to characteristic changes, which may lead to a decrease in modeling accuracy, resulting in poor control effects

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  • Dynamic modeling method of boiler combustion system based on online support vector machine
  • Dynamic modeling method of boiler combustion system based on online support vector machine
  • Dynamic modeling method of boiler combustion system based on online support vector machine

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Embodiment Construction

[0055] Below in conjunction with accompanying drawing and specific embodiment, further illustrate the present invention, it should be understood that embodiment is only for illustrating the present invention and is not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention All modifications of the valence form fall within the scope defined by the appended claims of the present application.

[0056] Based on the thermal test and operating data of a 600MW unit, a dynamic model of its boiler combustion system was established. The sampling time is 20 seconds, press figure 1 The input and output structure organization sample data of the dynamic modeling shown in the figure, among which 500 groups are selected as training samples, and 12,000 groups are selected as test samples. In order to improve the performance of the model, the load of the training samples mus...

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Abstract

The invention discloses a dynamic modeling method of a boiler combustion system based on an online support vector machine. The method comprises the following steps: firstly, taking the NOx emission and a boiler efficiency value as model output, and then taking the main influence factors of the furnace total coal-supply quantity, the total air, the auxiliary air, the flue gas oxygen content and soon which influence the boiler emission and efficiency as model input; secondly, in the dynamic modeling process, considering the order of input and output variables in order to reflect the dynamic change characteristics of an object; and finally, establishing a dynamic model of the boiler combustion system through an improved online adaptive least square support vector machine algorithm (FVS-ALS). Compared with a traditional steady-state model, the model of the invention has higher prediction accuracy and has an on-line correction function, and can adapt to the change of control characteristics of the combustion system caused by changes in load, coal quality and equipment characteristics, and is of great value to the timely and accurate monitoring of the running state of the boiler combustion system and the operation optimization accordingly.

Description

technical field [0001] The invention relates to a dynamic modeling method of a boiler combustion system based on an online support vector machine, belonging to the field of thermal automatic control. Background technique [0002] At present, boiler combustion optimization mainly adopts the combination of data-based nonlinear modeling and intelligent optimization algorithm. Firstly, the boiler combustion characteristic model is established, and then the operating parameters are optimized with the best boiler efficiency and emission as performance indicators. However, these methods are essentially based on the steady-state model, and cannot optimize the control of the combustion system during the dynamic load change process. When the model changes, it lacks the function of online correction of the model parameters, and it is difficult to eliminate the model parameters. The influence of errors on the optimization results will cause many difficulties in practical application. T...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F30/17G06F30/20
Inventor 周慎学沈奇夏克晁王焕明潘天尧李益国
Owner ZHEJIANG ZHENENG TAIZHOU NO 2 POWER GENERATION CO LTD
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