Self-adaptive modeling method for boiler closed-loop combustion optimization
A combustion optimization and modeling method technology, applied in the direction of adaptive control, general control system, instrument, etc., can solve the problems of inability to use the combustion optimization system to run online and slow calculation speed, so as to ensure the self-adaptive ability and reduce the update cost The time required and the effect of reducing the number of iterative solutions
Active Publication Date: 2020-07-28
南京英璞瑞自动化科技有限公司
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[0004] However, the existing update algorithm based on support vector regression machine (such as accurate online support vector regression machine AOSVR) needs multi-step iterations, and the calculation speed is too slow to be used for online operation of combustion optimization system
Therefore, for the support vector regression model, there is still a lack of an update algorithm that is both fast and accurate.
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[0047] The present invention will be further explained below in conjunction with the accompanying drawings and specific embodiments.
[0048] Such as figure 1 As shown, the present invention provides an adaptive modeling method for boiler closed-loop combustion optimization, comprising the following steps:
[0049] Step 1: Build the boiler combustion system model offline:
[0050] The plant-level monitoring information system is used to collect historical operating data for a long period of time, and the data segments under each typical working condition are selected as the initial model training samples. Data is divided into three categories: control variables and state variables as inputs, and manipulated variables as outputs. Controlled variables include coal feed bias, secondary damper opening, burnout damper opening, oxygen setting after economizer, etc.; state variables include unit load, total coal, etc.; controlled variables include boiler efficiency, reheating, etc....
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The invention discloses a self-adaptive modeling method for boiler closed-loop combustion optimization, which comprises the following steps of: establishing a boiler combustion system model offline: acquiring real-time operation data during online operation, and calculating model prediction output of a controlled variable; performing self-adaptive updating of the online operation model; optimizingand calculating the control quantity; and performing optimization calculation of the next moment. According to the method, based on the simplified KKT condition, the number of times of iterative solution is greatly reduced, so that the time required for updating can be effectively shortened while the updating precision is ensured, and the method can be used for realizing online closed-loop combustion optimization control.
Description
technical field [0001] The invention belongs to the technical field of thermal automatic control, and in particular relates to an adaptive modeling method for boiler closed-loop combustion optimization. Background technique [0002] In recent years, with the gradual improvement of environmental protection requirements, power plants need to reduce pollutant emissions as much as possible while ensuring combustion efficiency and safety. Therefore, the optimization of boiler combustion process has increasingly become a research hotspot. At present, the combustion optimization mainly adopts the data-based modeling method, that is, the nonlinear model of the boiler combustion is established first, and then the performance indicators related to the boiler efficiency and nitrogen oxide (NOx) emission are constructed, and the operating parameters are optimized using the optimization algorithm. Optimize calculations. Therefore, establishing an accurate and efficient nonlinear model ...
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CPCG05B13/042
Inventor 李益国
Owner 南京英璞瑞自动化科技有限公司