Boiler combustion optimization air distribution method based on online model prediction

A technology for boiler combustion and model prediction, applied in genetic models, predictions, genetic laws, etc., can solve the problems of inability to automatically adjust, unable to meet the long-term optimization of air distribution adjustment, and difficult to guarantee the accuracy of the model.

Inactive Publication Date: 2017-01-11
XIAN IBL TECH DEV
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Problems solved by technology

Algorithms for constructing models based on neural network technology and support vector machines have verified the accuracy of the model, while ignoring the timeliness of the model. Since the combustion process is not only nonlinear and strongly coupled, it also has time-varying characteristics, so , the effect of the model is obvious at the initial stage of construction, but as time goes by, the accuracy of the model is difficult to guarantee, so that it cannot meet the long-term optimization of air distribution adjustment
[0004] The boiler combustion optimization air dist

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  • Boiler combustion optimization air distribution method based on online model prediction
  • Boiler combustion optimization air distribution method based on online model prediction
  • Boiler combustion optimization air distribution method based on online model prediction

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Embodiment 1

[0107] Unit #1 of the first phase of a certain power plant is a 500MW coal-fired thermal power generation unit. Desulfurization and denitrification systems have been added to it, and low NOx systems have been replaced. X After the burner, the combustion situation of the boiler has changed a lot. In particular, the transformation of the air distribution of the burner enables the fuel to be burned step by step in the furnace and realizes the reduction of NO X the goal of. However, this layered air distribution method puts forward new requirements for unit combustion, control of secondary air baffles on each layer, total air volume and furnace oxygen control, etc., and is directly related to the safety, stability and economy of unit operation. sex. Therefore, the secondary air distribution optimization combustion system of the #1 and #2 unit boilers has been researched and transformed. In the original DCS——ABB Composer system, two new combustion optimization stations are added ...

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Abstract

Provided is a boiler combustion optimization air distribution method based on online model prediction. The method includes: constructing a boiler combustion optimization air distribution model by employing an improved BP neural network algorithm and model online update calculation; and performing optimization calculation on parameters such as the optimal oxygen amount, the primary air amount, each secondary air door and a burnout air door etc. with the combination of an adaptive genetic algorithm and dynamic optimization boundary so that a multi-target function constructed by the boiler efficiency and the pollutant discharge capacity reaches the optimal combustion range.

Description

technical field [0001] The invention relates to the field of coal-fired boiler combustion optimization, in particular to a boiler combustion optimization air distribution method based on online model prediction. Background technique [0002] At present, most of the air supply control in power plants adopts cascaded oxygen control and adjusts the air distribution method through manual experience. Without adjustment and misoperation, it will be difficult to meet the requirements of economical combustion and low emission in the long run. In serious cases, it will even cause safety accidents such as local high temperature, coking in the furnace, and bursting of water-cooled wall tubes. The deviation between the type of coal used and the type of coal designed is large, the boiler control process is more disturbing, and the boiler efficiency is reduced. Wind combustion appears to be particularly important. [0003] Boiler air supply and air distribution optimization methods need...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/12
CPCG06N3/126G06Q10/04G06Q50/06
Inventor 李金崔栋刚贺博郑晗旸
Owner XIAN IBL TECH DEV
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