Optimization method for pulverized coal distribution system in coal-fired power plants

Abstract

The present invention discloses an optimization method for a pulverized coal distribution system of a coal-fired power plant, comprising: obtaining monitoring data of the pulverized coal distribution system through a sensor; constructing a simulation model based on the monitoring data, and optimizing the efficiency of the pulverized coal distribution system according to the value output by the simulation model: when the value output by the simulation model is close to 1, the efficiency of the pulverized coal distribution system is low, optimizing system parameters by using optimization indicators, and adaptively and dynamically adjusting the pulverized coal distribution ratio; when the value output by the simulation model is close to 0, the efficiency of the pulverized coal distribution system is medium, and the operating state of the pulverized coal distribution system is continuously monitored; when the value output by the simulation model is close to 1, the efficiency of the pulverized coal distribution system is high, and the operating state of the pulverized coal distribution system is continuously monitored. The present invention monitors the operating state of the system in real time according to the value output by the simulation model, adaptively optimizes parameters, adjusts the pulverized coal distribution ratio, improves environmental conditions, and improves the optimization performance and reliability of the system.

Description

Technical Field

[0001] The invention relates to the technical field of boiler combustion optimization, and in particular to an optimization method for a pulverized coal distribution system of a coal-fired power station. Background Art

[0002] At present, coal-fired power plants generally have the problem of uneven coal powder distribution in the primary air duct at the outlet of the pulverizer. This problem has a great impact on the combustion of the boiler. When the coal is unevenly distributed, the actual amount of coal powder entering each burner varies greatly, which easily leads to a mismatch in the air-powder ratio, causing the combustion organization to deteriorate, resulting in serious problems such as incomplete combustion and local overheating.

[0003] The pulverized coal distributor is one of the key equipment in the pulverizing system of the power station boiler. It can provide relatively uniform pulverized coal flow for the burners corresponding to the pulverizers on the same layer, thereby ensuring that the power of each burner is equal and the ignition conditions are similar, avoiding slagging in the furnace, pipe burst on the heating surface and even fire extinguishing in the furnace, improving the deviation of flue gas flow on both sides of the furnace outlet and the large deviation of reducing atmosphere caused by oxygen-deficient combustion in local areas of the furnace, and significantly reducing the emission of harmful gases such as NOX.

[0004] At present, power plants adjust the shrinkage holes on the primary air duct and measure the wind speed during the adjustment process to make the primary air unevenness coefficient less than ±10%. However, this method has poor on-site testing conditions and large measurement errors. Although many power plants have installed pulverized coal distributors, their structures are complex and occupy a large space, which brings many inconveniences to manufacturing, installation, operation and maintenance. Therefore, how to optimize the pulverized coal distribution system by adjusting parameters in real time and adapting to changes in the system's operating status, taking into account the complexity and variability of the system, and adopting an adaptive algorithm is a difficult problem that the present invention needs to solve. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: obtaining monitoring data of the pulverized coal distribution system through sensors;

[0008] A simulation model is constructed based on the monitoring data, and the efficiency of the pulverized coal distribution system is optimized according to the value output by the simulation model:

[0009] When the value output by the simulation model is close to -1, the efficiency of the pulverized coal distribution system is low, and the optimization index is used to optimize the system parameters and adaptively and dynamically adjust the pulverized coal distribution ratio;

[0010] When the value output by the simulation model is close to 0, the efficiency of the pulverized coal distribution system is medium, and the operating state of the pulverized coal distribution system is continuously monitored;

[0011] When the value output by the simulation model is close to 1, the efficiency of the pulverized coal distribution system is relatively high, and the operating status of the pulverized coal distribution system is continuously monitored.

[0012] As a preferred solution of the optimization method for the pulverized coal distribution system of a coal-fired power plant described in the present invention, the monitoring data includes at least the temperature, pressure, pulverized coal density, temperature and pressure of the combustion process, pulverized coal moisture content, and system ambient humidity of the pulverized coal distribution system.

[0013] As a preferred solution of the optimization method for the pulverized coal distribution system of a coal-fired power plant described in the present invention, the simulation model inputs the monitoring data into a virtual simulation platform and performs simulation and optimization in combination with the deep learning prediction results. The mathematical expression formula is as follows:

[0014]

[0015] Among them, T is the temperature of the coal powder distribution system, P is the pressure of the coal powder distribution system, ρ is the density of the coal powder, θ is the temperature of the combustion process, γ is the pressure of the combustion process, α is the moisture content of the coal powder, β is the humidity of the system environment, δ is the deep learning prediction result, and n is a constant. represents the integral of the exponential function over the pressure range from P to γ, represents the square root of moisture content, represents the harmonic series, Represents the normalization function of deep learning prediction results.

[0016] As a preferred solution of the optimization method for the pulverized coal distribution system of a coal-fired power plant described in the present invention, the value range of F(T, P, ρ, θ, γ, α, β, δ) is a real number set, which represents the simulation optimization result of the system;

[0017] and Represent the contribution of the system's physical parameters and deep learning prediction results to simulation optimization;

[0018] Represents the error correction term of the system, which is used to adjust the accuracy of the simulation results.

[0019] As a preferred solution of the optimization method for the pulverized coal distribution system of a coal-fired power plant described in the present invention, the optimization index at least includes pulverized coal utilization rate, energy consumption reduction rate, and environmental emission reduction rate.

[0020] Beneficial effects of the present invention: The present invention takes into account the complexity and diversity of the coal powder distribution system, combines multiple parameters of the system, and constructs a simulation optimization model on a virtual simulation platform with exponential functions, integral functions, harmonic series, and normalized functions of deep learning prediction results. The system operating status is monitored in real time according to the value output by the simulation model, so as to adaptively optimize parameters, adjust the coal powder distribution ratio, improve environmental conditions, and improve the optimization performance and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0022] Figure 1 It is a schematic flow chart of the optimization method for the pulverized coal distribution system of a coal-fired power plant shown in the present invention. DETAILED DESCRIPTION

[0023] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0024] Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without making any creative work should fall within the scope of protection of the present invention.

[0025] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0026] Example 1

[0027] According to an embodiment of the present invention, Figure 1 The flowchart shown is a method for optimizing a pulverized coal distribution system for a coal-fired power plant, which specifically includes the following steps:

[0028] S1: Acquire monitoring data of the pulverized coal distribution system through sensors;

[0029] S2: Build a simulation model based on the monitoring data, and optimize the efficiency of the pulverized coal distribution system according to the values ​​output by the simulation model:

[0030] a: When the value output by the simulation model is close to -1, the efficiency of the pulverized coal distribution system is low. The optimization index is used to optimize the system parameters and dynamically adjust the pulverized coal distribution ratio;

[0031] b: When the value output by the simulation model is close to 0, the efficiency of the pulverized coal distribution system is medium, and the operating status of the pulverized coal distribution system is continuously monitored;

[0032] c: When the value output by the simulation model is close to 1, the efficiency of the pulverized coal distribution system is high, and the operating status of the pulverized coal distribution system is continuously monitored.

[0033] Preferably, the embodiment of the present invention takes into account the complexity and diversity of the coal powder distribution system, combines multiple parameters of the system, constructs a simulation optimization model on a virtual simulation platform with exponential functions, integral functions, harmonic series and normalized functions of deep learning prediction results, and monitors the system operation status in real time according to the values ​​output by the simulation model, so as to adaptively optimize parameters, adjust the coal powder distribution ratio, improve environmental conditions, and improve the optimization performance and reliability of the system.

[0034] It should be noted that the collected monitoring data needs to be preprocessed to form numerical parameters that meet the input of the virtual simulation platform. The steps of preprocessing the monitoring data in this embodiment include:

[0035] (1) Eliminate duplicate, useless, and irrelevant parameters in the monitoring data;

[0036] (2) Using coding strategies to convert the filtered information parameters into unified dummy variables;

[0037] (3) Standardize the dummy variables by subtracting their mean and dividing them by the standard deviation, so that the different configuration values ​​of the parameters are replaced by mathematical values ​​to form numerical parameters.

[0038] As an example, the monitoring data includes at least the temperature, pressure, and density of the pulverized coal distribution system, the temperature and pressure of the combustion process, the moisture content of the pulverized coal, and the system environment humidity.

[0039] In an optional embodiment, the sensors used to collect monitoring data include at least a temperature sensor, a humidity sensor, and a pressure sensor.

[0040] Furthermore, the simulation model in this embodiment inputs monitoring data into the virtual simulation platform and performs simulation and optimization in combination with the deep learning prediction results. Its mathematical expression formula is as follows:

[0041]

[0042] Among them, T is the temperature of the coal powder distribution system, P is the pressure of the coal powder distribution system, ρ is the density of the coal powder, θ is the temperature of the combustion process, γ is the pressure of the combustion process, α is the moisture content of the coal powder, β is the humidity of the system environment, δ is the deep learning prediction result, and n is a constant. represents the integral of the exponential function over the pressure range from P to γ, represents the square root of moisture content, represents the harmonic series, Represents the normalization function of deep learning prediction results.

[0043] As an example, the value range of F(T, P, ρ, θ, β, α, γ, δ) is a real number set, which represents the simulation optimization result of the system.

[0044] As an example, and Represents the contribution of the system’s physical parameters and deep learning prediction results to simulation optimization.

[0045] As an example, Represents the error correction term of the system, which is used to adjust the accuracy of the simulation results.

[0046] It should also be noted that in this embodiment, when the value output by the simulation model is close to -1, the efficiency of the pulverized coal distribution system is low. The system parameters can be optimized by optimizing the indicators, the pulverized coal distribution ratio can be adaptively and dynamically adjusted, the combustion process parameters can be optimized, or the environmental conditions can be improved.

[0047] In an optional embodiment, the optimization index includes at least coal powder utilization rate, energy consumption reduction rate, and environmental emission reduction rate.

[0048] In an optional embodiment, the optimization of system parameters may be achieved by iteratively optimizing the parameters of the simulation model through a virtual simulation platform, which will not be described in detail in this embodiment.

[0049] The aforementioned adaptive dynamic adjustment of the pulverized coal distribution ratio, optimization of combustion process parameters or improvement of environmental conditions can be customized according to the on-site operating conditions, and the embodiments of the present invention do not make a sole limitation thereto.

[0050] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for optimizing a pulverized coal distribution system in a coal-fired power plant, characterized in that: include: Acquire monitoring data of the pulverized coal distribution system through sensors; A simulation model is constructed based on the monitoring data, and the efficiency of the pulverized coal distribution system is optimized according to the value output by the simulation model: The simulation model is simulated and optimized by inputting the monitoring data into the virtual simulation platform and combining the deep learning prediction results. The mathematical expression formula is as follows: Among them, T is the temperature of the coal powder distribution system, P is the pressure of the coal powder distribution system, ρ is the density of the coal powder, θ is the temperature of the combustion process, γ is the pressure of the combustion process, α is the moisture content of the coal powder, β is the humidity of the system environment, δ is the deep learning prediction result, and n is a constant. represents the integral of the exponential function over the pressure range from P to γ, represents the square root of moisture content, represents the harmonic series, A normalization function representing the deep learning prediction results; The value range of F(T, P, ρ, θ, γ, α, β, δ) is a real number set, which represents the simulation optimization result of the system; and Represent the contribution of the system's physical parameters and deep learning prediction results to simulation optimization; Represents the error correction term of the system, which is used to adjust the accuracy of the simulation results; When the value output by the simulation model is close to -1, the efficiency of the pulverized coal distribution system is low, and the optimization index is used to optimize the system parameters and adaptively and dynamically adjust the pulverized coal distribution ratio; When the value output by the simulation model is close to 0, the efficiency of the pulverized coal distribution system is medium, and the operating state of the pulverized coal distribution system is continuously monitored; When the value output by the simulation model is close to 1, the efficiency of the pulverized coal distribution system is relatively high, and the operating state of the pulverized coal distribution system is continuously monitored; The optimization index at least includes coal powder utilization rate, energy consumption reduction rate, and environmental emission reduction rate.

2. The optimization method for the pulverized coal distribution system of a coal-fired power plant according to claim 1, characterized in that: The monitoring data at least includes the temperature, pressure, coal powder density of the coal powder distribution system, the temperature and pressure of the combustion process, the water content of the coal powder, and the system environment humidity.

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