Method for estimating content of sulfur oxide at inlet of desulfurization system based on as-fired coal quality measurement

Abstract

The invention discloses a method for estimating the content of sulfur oxide at an inlet of a desulfurization system based on as-fired coal quality measurement. The method comprises the following steps: 1, recording historical data of key parameters; 2, constructing a sulfur content steady-state conservation equation; 3, determining the sulfur-containing oxidation weight gain coefficient of the coal; 4, establishing a desulfurization system inlet sulfur oxide dynamic transfer function; 5, performing parameter identification to obtain dynamic parameters; 6, obtaining the prediction of the sulfur oxide content at the inlet of the desulfurization system; The sulfur content of the coal is obtained through a coal quality online detection device, and a desulfurization system inlet sulfur oxide content calculation model is established through the sulfur content before entering the furnace and the desulfurization system inlet sulfur content conservation theorem, so that the desulfurization system inlet sulfur oxide content change condition is obtained; Therefore, subsequent accurate limestone slurry demand quantity calculation and slurry pump control are guided.

Description

technical field [0001] The invention belongs to the technical field of prediction of thermal power generation units, and relates to a method for estimating the content of sulfur oxides at the inlet of a desulfurization system based on the measurement of the quality of incoming coal. Background technique [0002] With the rapid development of the country's economy, people's demand for electricity continues to increase, and the number of coal-fired power generation units used as the main power supply is also increasing. At the same time, the pollutants emitted by coal-fired power generation units also increase accordingly. In the face of increasingly severe environmental protection problems and the implementation of the national policy on ultra-low emission of pollutants from coal-fired power plants, it is imperative to control and reduce pollutant emissions from coal-fired power plants. SO2 is one of the main pollutants emitted by coal-fired power plants. How to ensure ultra-...

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Problems solved by technology

[0003] At present, the theoretical research on the prediction of sulfur oxide content at the inlet of the desulfurization system mostly uses neural network algorithms or random forest prediction algorithms. The excess air coefficient, the original flue gas temperature at the FGD inlet, the original flue gas pressure at the FGD inlet, and the measured value of the total flue gas flow are input and predicted to obtain the predicted value of SO2 concentration at the inlet of the desulfurization system. When the prediction time is short, there is better accuracy. Prolonged time will lead to poor accuracy, and incomplete sampling will lead to poor prediction results; on the other hand, there is no prediction from the mechanism method, and the trend of change cannot be predicted more accurately, and it cannot directly participate in actual operation control, which will affect the desulfurization efficiency

[0004] On the other hand, due to factors such as the diversity of coal types in my country and the cost of coal combustion, coal blending and coal quality instability have become one of the problems faced by coal-fired units in thermal power plants

First of all, most of the coal quality analysis in power plants currently uses offline laboratory analysis, which has to go through the steps of sampling, shrinking, sample preparation, and testing.

Secondly, the coal quality online detection device can also detect the coal quality quickly and in real time, and at the same time can make an accurate weighted average judgment on the overall quality of the batch of coal, which is of great significance to thermal power plants, but the current coal quality online detection It is mostly used to display coal quality information to operators, but how to use coal quality analysis data to guide post-combustion, desulfurization, and denitrification control has not yet been studied by scholars

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