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Boiler soot blowing optimization method for complementing pollution factors based on time sequence prediction algorithm

A prediction algorithm and time series technology, applied in design optimization/simulation, calculation, computer-aided design, etc., can solve problems such as false soot blowing, and achieve good results, significant technical and economic benefits, and simple and reasonable methods.

Pending Publication Date: 2021-12-07
ZHEJIANG ZHENENG TECHN RES INST
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the disadvantages of the above methods are: under unsteady conditions, such as large fluctuations in boiler load or a short period of time after the heating surface has just completed soot blowing, due to the change of heat storage on the heating surface, it is difficult for the pollution factor to accurately reflect the real-time Due to the actual contamination of the heating surface, the pollution factor fluctuates greatly under unsteady working conditions. If the actual calculated pollution factor of unsteady working conditions is used to judge whether soot blowing is required, it will cause a large number of false soot blowing Case

Method used

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  • Boiler soot blowing optimization method for complementing pollution factors based on time sequence prediction algorithm
  • Boiler soot blowing optimization method for complementing pollution factors based on time sequence prediction algorithm
  • Boiler soot blowing optimization method for complementing pollution factors based on time sequence prediction algorithm

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Embodiment 1

[0064] Embodiment 1 of the present application provides a coal-fired boiler soot blowing optimization method based on time series prediction algorithm to complement pollution factors:

[0065] Step 1. Calculation of the pollution factor of the heating surface;

[0066] Step 2. According to the upper limit and lower limit of pollution factors, boiler load and quality of working fluid measurement point data, etc., data cleaning is performed to eliminate abnormal data;

[0067] Step 3. Steady-state working condition time period capture;

[0068] Step 3.1. Capture the time period not affected by sootblowing: use the sootblower action current measurement point, the sootblower start command measurement point, the sootblower exit command measurement point, judge the sootblowing time period, and capture the sootblower Time period; introduce the stable time t after soot blowing, determine the soot blowing time period and the unsteady time period affected by soot blowing, then the rema...

Embodiment 2

[0090] On the basis of Embodiment 1, Embodiment 2 of the present application provides the application of the soot blowing optimization method of a coal-fired boiler based on the time series prediction algorithm of Embodiment 1 to complement the pollution factor in the soot blowing optimization process of a 1000MW coal-fired boiler:

[0091] 1. Model training

[0092] The process of model training is as follows figure 1 shown.

[0093] Step 1. Calculation of the pollution factor of the heating surface;

[0094] The boiler is equipped with online measuring points for the flue gas temperature at the inlet section of the low-temperature superheater and low-temperature reheater and the inlet and outlet of all heating surfaces of the downstream flue, and measuring points for the temperature of working fluid at the inlet and outlet of all heating surfaces. Mass-side parameters and existing flue gas-side parameters, taking into account the effects of radiation heat transfer and conv...

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Abstract

The invention relates to a boiler soot blowing optimization method for complementing pollution factors based on a time sequence prediction algorithm. The method comprises the following steps: calculating the pollution factors of a heating surface; removing abnormal data; carrying out grabbing in a steady-state working condition time period; and complementing the pollution factors in the unsteady state time period by using a time sequence prediction algorithm. The invention has the advantages that the steady-state working condition is grabbed, the pollution factors in the time period of the steady-state working condition are calculated, the pollution factors under the non-steady-state working condition are complemented according to the time sequence prediction algorithm, and therefore soot blowing is guided. The problems that the actual contamination condition of the heating surface is difficult to accurately reflect in real time and the contamination factor is easy to greatly fluctuate due to the fact that the heat storage amount of the heating surface is changed under the unsteady state working condition can be avoided, and therefore, a large amount of mistaken soot blowing operation is avoided. The method is simple and reasonable, has a good effect in practical application, does not need to add extra equipment and measuring points, and is remarkable in technical benefit and economic benefit.

Description

technical field [0001] The invention belongs to the technical field of coal-fired power plants, and in particular relates to a coal-fired boiler soot blowing optimization method based on a time series prediction algorithm to complement pollution factors. Background technique [0002] During the combustion of pulverized coal in coal-fired power plant boilers, non-combustible ash and other mineral components will be deposited on the heating surface, mainly including slagging in high-temperature areas such as water walls and ash accumulation on the heating surface of the tail flue. The thermal resistance of the dust deposited on the heating surface is much higher than that of the metal pipe wall. If it is not removed in time, it will lead to a series of problems such as the decrease of the heat transfer performance of the heating surface, the increase of the exhaust gas temperature, the increase of the flue resistance, the high temperature corrosion and the increased wear of the...

Claims

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Application Information

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IPC IPC(8): G06F30/27G06F119/08G06F119/12
CPCG06F30/27G06F2119/08G06F2119/12
Inventor 项群扬朱松强陈勤根解剑波范海东孙科达孙永平张震伟
Owner ZHEJIANG ZHENENG TECHN RES INST