Combined heat and power generation unit SCR inlet smoke temperature online calculation method based on BP neural network

A technology of BP neural network and combined heat and power unit, which is applied in the direction of neural learning method, biological neural network model, calculation, etc., to achieve the effect of realizing scientific dispatching of power grid, ensuring the stability of electric energy, and realizing real-time scientific calculation

Active Publication Date: 2018-10-12
ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY +1
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However, in the current public technology, there is a lack of a method that can scientifically rea

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  • Combined heat and power generation unit SCR inlet smoke temperature online calculation method based on BP neural network
  • Combined heat and power generation unit SCR inlet smoke temperature online calculation method based on BP neural network

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[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, In other words, other drawings can also be obtained from these drawings on the premise of not paying creative work.

[0027] combine figure 1 , figure 2 , an online calculation method of smoke temperature at SCR inlet of cogeneration unit based on BP neural network, including the following steps:

[0028] (1) Design and conduct multi-coal and multi-working condition boiler thermal tests, obtain test data of coal quality, load, heating and extraction steam volume, and SCR inlet smoke temperature under different test conditions, and use test data to train BP neural network , to establish the initial calculation model of SCR inlet smoke temperature;

[0029] (2) Publish the ...

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Abstract

The invention discloses a combined heat and power generation unit SCR inlet smoke temperature online calculation method based on a BP neural network. The method comprises the following steps of carrying out designing, carrying out multi-coal and multi-working-condition boiler thermal tests, obtaining test data of coal quality, load, heat supply steam extraction capacity and SCR inlet smoke temperature under different test working conditions, training the BP neural network through utilization of test data, and establishing an SCR inlet smoke temperature initial calculation model; issuing the smoke temperature initial calculation model in a form of an online website through utilization of a network programming technology, thereby realizing online determination of the SCR inlet smoke temperature under different operation conditions; and after the SCR inlet smoke temperature deviates, carrying out real-time online correction on the smoke temperature initial calculation model through combination of practical operation data of a thermal power generation unit. According to the method, related staff can calculate and predict the SCR inlet smoke temperature of a combined heat and power generation unit under different coal quality and different load rates in real time, the peak-load regulation limit of the set can be accurately determined, and when the boiler heat exchange condition is changed, the self-correction of a model can be realized.

Description

technical field [0001] The invention relates to an online calculation method for smoke temperature at the SCR inlet of a cogeneration unit based on BP neural network. Background technique [0002] With the rapid development of social economy and the continuous increase of new energy installed capacity, the peak-to-valley difference of power load in my country's power system continues to increase, which intensifies the pressure on power grid peak regulation. In order to improve the peak-shaving capacity of the power grid and promote the consumption of new energy, combined heat and power units began to participate in the peak-shaving power grid. Tests have shown that when thermal power units actually participate in peak regulation, there is no scientific basis for the magnitude of peak regulation. In the process of load reduction, the efficiency of denitrification equipment is often low or even out of operation due to the low smoke temperature at the inlet of SCR equipment, re...

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Application Information

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IPC IPC(8): G06F17/50G06N3/08
CPCG06N3/084G06F30/20
Inventor 郭俊山韩悦车永强祝令凯郑威郭盈
Owner ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY
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