Thermal power plant boiler combustion adjustment optimization method and system

Abstract

The invention discloses a thermal power plant boiler combustion adjusting and optimizing method and system, and relates to the technical field of thermal power plants. By arranging the boiler pipeline three-dimensional digital twinborn visualization module, the thermal power plant data analysis supporting platform, the heating surface wall temperature monitoring module and the heating surface heat absorption monitoring module, the combustion optimization effect is evaluated, and thermal power plant boiler combustion data and corresponding analysis results are managed, visualized and stored; energy management can be realized through internet cloud management and control, the intelligent level of combustion management of the boiler of the thermal power plant is improved, the combustion efficiency can be effectively improved, pollution emission can be reduced, the service life of equipment can be prolonged, and the automation level can be improved by optimizing operation parameters, reducing abrasion and corrosion of the boiler, prolonging the service life of the equipment and reducing the maintenance cost; and technical support is provided for green sustainable development of a thermal power plant.

Description

Technical Field

[0001] The invention relates to the technical field of thermal power plants, and in particular to a method and system for adjusting and optimizing combustion of boilers in thermal power plants. Background Art

[0002] A thermal power plant is a factory that uses coal, oil, and natural gas as fuel to produce electricity. Its basic production process is: the fuel burns in the boiler to heat water to make steam, converting the chemical energy of the fuel into thermal energy. The steam pressure drives the turbine to rotate, converting the thermal energy into mechanical energy, and then the turbine drives the generator to rotate, converting the mechanical energy into electrical energy. A modern thermal power plant is a large and complex factory that produces electricity and thermal energy. The existing boiler combustion adjustment method is generally based on the thermal power plant control system, which adjusts the boiler combustion based on historical experience data, expert database data, and theoretical knowledge.

[0003] Chinese patent announcement number CN 105276611 B discloses a method and system for adjusting and optimizing the combustion of a thermal power plant boiler, which maintains a stable boiler load, adjusts the oxygen content at the outlet of the economizer in the boiler, determines the optimal operating oxygen content of the boiler, maintains the boiler at the optimal operating oxygen content, performs a test on the boiler to change the SOFA air damper opening, obtains the optimal oxygen content and SOFA air damper opening combination of the boiler under the current load, modifies the control function of the boiler according to the optimal oxygen content and SOFA air damper opening combination under the current load, performs a hot adjustment test on the boiler to make the boiler in the optimal operating condition under the current load, adjusts the boiler load, repeats the above operations, and obtains the optimal operating condition of the boiler under different loads. In the whole process, based on the actual combustion of the combustion boiler, the optimal operating oxygen content, the optimal oxygen content and SOFA air damper opening combination and the hot adjustment are used to achieve accurate adjustment and optimization of the combustion of the thermal power plant boiler and reduce nitrogen oxide emissions.

[0004] The above scheme still has the following problems when it is used: no real-time monitoring of various equipment in the thermal power plant, including actual heating surface wall temperature monitoring and heating surface heat absorption monitoring, resulting in incomplete comparison of each group of data, resulting in omissions in the actual collected data, which affects the subsequent adjustment and optimization of the boiler combustion scheme. At the same time, there is a problem of difficulty in managing each link, and the overall intelligent management level is low, which affects normal use. Therefore, the present invention needs to design a thermal power plant boiler combustion adjustment and optimization method and system to solve the above-mentioned problems. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for optimizing boiler combustion adjustment in a thermal power plant in order to solve the above-mentioned problems, thereby solving the problems mentioned in the background technology.

[0006] In order to solve the above problems, the present invention provides a technical solution:

[0007] A method for optimizing combustion adjustment of a thermal power plant boiler comprises the following specific steps:

[0008] S1. Collect and organize boiler design drawings and ledger information, and combine with the four-tube inspection data of the unit maintenance to display the boiler economizer, water wall, superheater, reheater and connecting pipes, inlet and outlet headers, drum structure and boiler pipe welds, metal material basic physical structure information and the specific conditions of previous maintenance processes in a three-dimensional visualization;

[0009] S2. Use stable operating condition detection and cluster analysis algorithms to mine the historical operating data of the unit, and establish a database of benchmark values ​​of water-coal ratio, wall temperature measurement points, thermal deviation, boiler expansion and operating parameters under stable conditions in each load condition range under different coal qualities, operating oxygen content, air distribution methods, and ambient temperature conditions;

[0010] S3. Analyze the heat absorption and heat absorption ratio of each heating surface, determine the heat matching characteristics to achieve reasonable boiler design, meet the design parameter operation requirements under various loads, and have good temperature regulation characteristics, determine the ash pollution of the heating surface and the combustion temperature field, and provide data support for the wear and explosion prevention of the four boiler tubes through single wall temperature over-temperature statistics and cumulative over-temperature statistics;

[0011] S4. The wall temperature measurement points are grouped according to the heating surface and displayed graphically. Intuitive icons are used instead of abstract numerical displays. Various sensors are arranged in the boiler. Sensor data are collected and recorded regularly. Based on the collected data, a mathematical model of the boiler combustion process is established. The optimal fuel-air ratio is calculated by combining genetic algorithms and deep learning optimization algorithms. The combustion optimization effect is evaluated by analyzing the boiler's thermal efficiency, fuel consumption and emission data.

[0012] As a preferred technical solution, the mathematical model in step S4 needs to take fuel characteristics, air flow, and combustion temperature into consideration when establishing the mathematical model.

[0013] As a preferred technical solution, the sensor in step S4 includes a temperature sensor, a pressure sensor, an oxygen sensor, and a flue gas composition analyzer.

[0014] As a preferred technical solution, the operating parameters in step S2 include operating oxygen content, wall temperature measurement points, and real-time value of thermal deviation.

[0015] As a preferred technical solution, the boiler four-tube inspection data in step S1 includes tube number, material, tube diameter, wall thickness, design, wall temperature measurement point location, operating parameters, installation location and inspection and maintenance data.

[0016] A boiler combustion adjustment and optimization system for a thermal power plant, the boiler combustion adjustment and optimization system comprising a boiler pipeline three-dimensional digital twin visualization module, a thermal power plant data analysis support platform, a heating surface wall temperature monitoring module and a heating surface heat absorption monitoring module, the boiler pipeline three-dimensional digital twin visualization module and the thermal power plant data analysis support platform are bidirectionally communicatively connected, the output end of the heating surface wall temperature monitoring module is communicatively connected to the input end of the heating surface heat absorption monitoring module, and the output end of the heating surface heat absorption monitoring module is communicatively connected to the input end of the thermal power plant data analysis support platform.

[0017] As a preferred technical solution, the three-dimensional digital twin visualization module of the boiler pipeline includes an equipment structure management unit, a four-tube wall temperature control unit, a support and hanger equipment unit, a castable management unit and a boiler expansion monitoring unit. The output ends of the equipment structure management unit, the four-tube wall temperature control unit, the support and hanger equipment unit and the castable management unit are respectively communicatively connected to the input end of the boiler expansion monitoring unit, and the boiler expansion monitoring unit is bidirectionally communicatively connected to the thermal power plant data analysis support platform;

[0018] The equipment structure management unit is used to collect and organize boiler design drawings and ledger information, realize archiving and quick query of basic parameter data of the four tubes of the boiler, and combine the four-tube inspection data of the unit maintenance to display the structure of the boiler economizer, water-cooled wall, superheater, reheater and connecting pipes, inlet and outlet headers, steam drum and boiler pipe welds, basic physical structure information of metal materials and specific conditions of previous maintenance processes in three-dimensional visualization;

[0019] The four-tube wall temperature control unit is used to mark the existing wall temperature measurement point positions on the three-dimensional visualization model of the boiler, so as to facilitate the rapid positioning of the spatial positions of abnormal and over-temperature measurement points;

[0020] The support and hanger equipment unit is used to record the name, type, model, installation load, elevation, design value, cold state value and hot state value information of the support and hanger, and analyze the stress state of the pipeline through the support and hanger information. The cold and hot state values ​​of the support and hanger can be recorded and compared online on-site before and after each start and stop of the unit, and the cause of data abnormality can be analyzed and resolved in time;

[0021] The castable management unit is used to mark castable parameters, construction and overhaul maintenance data and other previous overhaul contents on the three-dimensional visualization model of the boiler, so as to facilitate data analysis for overhaul and accurately guide the overhaul and maintenance work;

[0022] The boiler expansion monitoring unit is used to increase the boiler online expansion indication index, and uses the thermal power plant data analysis support platform to combine the boiler operating load, operating parameters and theoretical design values, historical load values, and actual expansion values ​​to perform data analysis, automatically find out abnormal values ​​and issue an alarm.

[0023] As a preferred technical solution, the thermal power plant data analysis support platform includes a reference value database, a thermal power plant data analysis terminal, and a key operating parameter comparison unit. The reference value database and the thermal power plant data analysis terminal are bidirectionally connected, and the key operating parameter comparison unit is integrated inside the thermal power plant data analysis terminal.

[0024] The reference value database is used to mine the historical data of unit operation by using stable operating condition detection and cluster analysis algorithm, by establishing a reference value database of water-coal ratio, wall temperature measurement points, thermal deviation, boiler expansion and operating parameters under stable conditions in each load condition range under different coal quality, operating oxygen content, air distribution mode and ambient temperature conditions;

[0025] The thermal power plant data analysis terminal is used to check the heating surface pipes, castables, supports and hangers, expansion indicators and other equipment and record data. Through data analysis and comparison, combined with the unit operation hours and equipment life assessment, preventive maintenance of the unit is achieved, and forward-looking maintenance analysis is achieved based on data analysis;

[0026] The key operating parameter comparison unit is used to compare each key operating parameter with its partition operating condition benchmark value, and adopts the time-shift sliding window method to identify abnormal state points. When the key operating parameters continue to deviate from the normal operating boundary, an early warning is issued to remind the operating personnel to make timely adjustments to the air distribution method, coal distribution method, etc. before the wall temperature reaches the alarm value, so as to prevent the wall temperature from over-temperature alarm.

[0027] As a preferred technical solution, the heating surface wall temperature monitoring module includes a grouping chart unit, a cumulative data monitoring and statistical unit and a trend prevention unit, the output end of the grouping chart unit is communicatively connected to the input end of the cumulative data monitoring and statistical unit, the trend prevention unit is integrated inside the cumulative data monitoring and statistical unit, and the output end of the cumulative data monitoring and statistical unit is communicatively connected to the input end of the heating surface heat absorption monitoring module;

[0028] The grouping charting unit is used to analyze the heat absorption and heat absorption ratio of each heating surface, determine whether the heat matching characteristics can achieve a reasonable boiler design, meet the design parameter operation requirements under various loads, and have good air temperature regulation characteristics, determine the ash pollution of the heating surface and the combustion temperature field, calculate and display the total heat absorption and ratio of the economizer, water-cooled wall, low-pass, screen-pass, high-pass and primary steam-water, calculate the total heat absorption and ratio of low-repass, screen-repass and secondary steam-water, and display and query the time change trend curve and ratio ring diagram of each heat absorption ratio online based on the thermal power plant data analysis support platform;

[0029] The cumulative data monitoring and statistical unit is used for single wall temperature over-temperature statistics, by statistical over-temperature measuring points, over-temperature parts, start time, end time, duration, maximum temperature time point, maximum temperature, average temperature, according to the severity and duration of the progressive degree of rating, providing over-temperature time period historical curves, etc.;

[0030] The cumulative data monitoring and statistical unit is also used for cumulative over-temperature statistics, and statistics the over-temperature measuring points, over-temperature parts, cumulative over-temperature time, maximum temperature, average over-temperature humidity, the top few temperatures, and automatic severity rating on a daily / weekly / monthly / year basis, to provide data support for the wear and explosion prevention work of the four-tube boiler;

[0031] The trend prevention unit is used to prevent large-area bed coking and prevent boiler bed coking accidents by using the bed wall temperature distribution characteristics and change trends.

[0032] As a preferred technical solution, the heating surface heat absorption monitoring module includes a combustion monitoring and optimization unit, a combustion efficiency evaluation module and a heating surface heat absorption monitoring unit, the output end of the heating surface heat absorption monitoring unit is communicatively connected to the input end of the combustion monitoring and optimization unit, and the output end of the combustion monitoring and optimization unit is communicatively connected to the input end of the combustion efficiency evaluation module; the combustion monitoring and optimization unit is used to arrange a variety of sensors in the boiler for real-time monitoring of the combustion state, and regularly collect and record sensor data;

[0033] The combustion efficiency evaluation module is used to establish a mathematical model of the boiler combustion process based on the collected data, and calculate the optimal fuel-air ratio by combining genetic algorithm and deep learning optimization algorithm to achieve dynamic adjustment. By analyzing the thermal efficiency, fuel consumption and emission data of the boiler, the combustion optimization effect is evaluated, and the optimization effect report is regularly generated to facilitate comprehensive analysis and decision-making by operators;

[0034] The heating surface heat absorption monitoring unit is used to group the wall temperature measurement points according to the heating surface area, and display them all in a graphical form, replacing abstract numerical display with intuitive graphical display, providing data screening and graphical comparative analysis across years and multiple working conditions, and capable of intuitive graphical real-time display and historical query, historical review of the current real-time wall temperature of the heating surface, rate of change, historical trends of related state parameters, and spatial distribution status, thereby minimizing the amplitude of combustion heat deviation and reducing the occurrence of wall temperature overtemperature.

[0035] The beneficial effects of the present invention are as follows: the present invention constructs a complete boiler combustion adjustment and optimization system by setting up a three-dimensional digital twin visualization module for boiler pipelines, a thermal power plant data analysis support platform, a heating surface wall temperature monitoring module and a heating surface heat absorption monitoring module. In actual use, the boiler design drawings and ledger information are collected and sorted, and the four-tube detection data of the unit maintenance are combined to judge the ash pollution situation of the heating surface and the combustion temperature field situation. At the same time, through the single wall temperature over-temperature statistics and cumulative over-temperature statistics, data support is provided for the wear and explosion prevention work of the boiler four tubes. The wall temperature measuring points are grouped according to the heating surface area, and all are displayed in a graphical manner, with intuitive icon display instead of abstract numerical display. A variety of sensors are arranged in the boiler, and sensor data is collected and recorded regularly. Based on the collected data, a mathematical model of the boiler combustion process is established, and the optimal fuel-to-air ratio is calculated by combining genetic algorithm and deep learning optimization algorithm. By analyzing the thermal efficiency, fuel consumption and emission data of the boiler, the combustion optimization effect is evaluated. The boiler combustion data of the thermal power plant and the corresponding analysis results are managed, visualized and stored, which is helpful to realize energy management through Internet cloud management and control, and improve the intelligence level of boiler combustion management in thermal power plants. By optimizing operating parameters, the wear and corrosion of the boiler can be reduced, the service life of the equipment can be extended, and the maintenance cost can be reduced. It can effectively improve the combustion efficiency, reduce pollution emissions, extend the life of the equipment and improve the automation level, providing technical support for the green and sustainable development of thermal power plants. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] For ease of explanation, the present invention is described in detail with reference to the following specific implementations and the accompanying drawings.

[0037] Figure 1 It is a method flow chart of a method and system for optimizing combustion adjustment of a thermal power plant boiler according to the present invention;

[0038] Figure 2 It is a system overall structure topology diagram of a method and system for adjusting and optimizing combustion of a thermal power plant boiler according to the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0040] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0041] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0042] It should be understood that although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0043] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0044] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0045] It should be particularly noted that any symbols and / or numbers in the specification that are not marked in the accompanying drawings are not drawing marks.

[0046] The optional embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0047] like Figure 1 and Figure 2 As shown, this specific implementation adopts the following technical solutions:

[0048] A method for optimizing combustion adjustment of a thermal power plant boiler comprises the following specific steps:

[0049] S1. Collect and organize boiler design drawings and ledger information, and combine them with the four-tube inspection data of the unit overhaul. The boiler four-tube inspection data includes tube number, material, tube diameter, wall thickness, design, wall temperature measurement point location, operating parameters and installation location and overhaul and maintenance data. The three-dimensional visualization displays the structure of the boiler economizer, water-cooled wall, superheater, reheater and connecting pipes, inlet and outlet headers, steam drum and boiler pipe welds, basic physical structure information of metal materials and specific conditions of previous overhaul processes;

[0050] S2. Use stable operating condition detection and cluster analysis algorithms to mine the historical operating data of the unit. By establishing a database of benchmark values ​​of water-coal ratio, wall temperature measurement points, thermal deviation, boiler expansion and operating parameters under stable conditions in each load condition range under different coal qualities, operating oxygen content, air distribution methods and ambient temperature conditions, the operating parameters include operating oxygen content, wall temperature measurement points and real-time values ​​of thermal deviation;

[0051] S3. Analyze the heat absorption and heat absorption ratio of each heating surface, determine the heat matching characteristics to achieve reasonable boiler design, meet the design parameter operation requirements under various loads, and have good temperature regulation characteristics, determine the ash pollution of the heating surface and the combustion temperature field, and provide data support for the wear and explosion prevention of the four boiler tubes through single wall temperature over-temperature statistics and cumulative over-temperature statistics;

[0052] S4. The wall temperature measurement points are grouped according to the heating surface and displayed graphically. Intuitive icons are used instead of abstract numerical displays. Various sensors are arranged in the boiler, including temperature sensors, pressure sensors, oxygen sensors, and flue gas composition analyzers. Sensor data are collected and recorded regularly. Based on the collected data, a mathematical model of the boiler combustion process is established. When establishing the mathematical model, fuel characteristics, air flow, and combustion temperature factors need to be considered. The optimal fuel-to-air ratio is calculated by combining genetic algorithms and deep learning optimization algorithms. The combustion optimization effect is evaluated by analyzing the thermal efficiency, fuel consumption, and emission data of the boiler.

[0053] A boiler combustion adjustment and optimization system for a thermal power plant, the boiler combustion adjustment and optimization system comprising a boiler pipeline three-dimensional digital twin visualization module, a thermal power plant data analysis support platform, a heating surface wall temperature monitoring module and a heating surface heat absorption monitoring module, the boiler pipeline three-dimensional digital twin visualization module and the thermal power plant data analysis support platform are bidirectionally communicatively connected, the output end of the heating surface wall temperature monitoring module is communicatively connected to the input end of the heating surface heat absorption monitoring module, and the output end of the heating surface heat absorption monitoring module is communicatively connected to the input end of the thermal power plant data analysis support platform.

[0054] In this solution, the three-dimensional digital twin visualization module of the boiler pipeline includes an equipment structure management unit, a four-tube wall temperature control unit, a support and hanger equipment unit, a castable management unit and a boiler expansion monitoring unit. The output ends of the equipment structure management unit, the four-tube wall temperature control unit, the support and hanger equipment unit and the castable management unit are respectively connected to the input end of the boiler expansion monitoring unit for communication, and the boiler expansion monitoring unit is connected to the thermal power plant data analysis support platform for bidirectional communication;

[0055] The equipment structure management unit is used to collect and organize boiler design drawings and ledger information, realize archiving and quick query of basic parameter data of the four tubes of the boiler, and combine the four-tube inspection data of the unit maintenance to display the structure of the boiler economizer, water-cooled wall, superheater, reheater and connecting pipes, inlet and outlet headers, steam drum and boiler pipe welds, basic physical structure information of metal materials and specific conditions of previous maintenance processes in three-dimensional visualization;

[0056] The four-tube wall temperature control unit is used to mark the existing wall temperature measurement point positions on the three-dimensional visualization model of the boiler, so as to facilitate the rapid positioning of the spatial positions of abnormal and over-temperature measurement points;

[0057] The support and hanger equipment unit is used to record the name, type, model, installation load, elevation, design value, cold state value and hot state value information of the support and hanger, and analyze the stress state of the pipeline through the support and hanger information. The cold and hot state values ​​of the support and hanger can be recorded and compared online on-site before and after each start and stop of the unit, and the cause of data abnormality can be analyzed and resolved in time;

[0058] The castable management unit is used to mark castable parameters, construction and overhaul maintenance data and other previous overhaul contents on the three-dimensional visualization model of the boiler, so as to facilitate data analysis for overhaul and accurately guide the overhaul and maintenance work;

[0059] The boiler expansion monitoring unit is used to increase the boiler online expansion indication index, and uses the thermal power plant data analysis support platform to combine the boiler operating load, operating parameters and theoretical design values, historical load values, and actual expansion values ​​to perform data analysis, automatically find out abnormal values ​​and issue an alarm.

[0060] In this solution, the thermal power plant data analysis support platform includes a reference value database, a thermal power plant data analysis terminal, and a key operating parameter comparison unit. The reference value database and the thermal power plant data analysis terminal are bidirectionally connected, and the key operating parameter comparison unit is integrated inside the thermal power plant data analysis terminal.

[0061] The reference value database is used to mine the historical data of unit operation by using stable operating condition detection and cluster analysis algorithm, by establishing a reference value database of water-coal ratio, wall temperature measurement points, thermal deviation, boiler expansion and operating parameters under stable conditions in each load condition range under different coal quality, operating oxygen content, air distribution mode and ambient temperature conditions;

[0062] The thermal power plant data analysis terminal is used to check the heating surface pipes, castables, supports and hangers, expansion indicators and other equipment and record data. Through data analysis and comparison, combined with the unit operation hours and equipment life assessment, preventive maintenance of the unit is achieved, and forward-looking maintenance analysis is achieved based on data analysis;

[0063] The key operating parameter comparison unit is used to compare each key operating parameter with its partition operating condition benchmark value, and adopts the time-shift sliding window method to identify abnormal state points. When the key operating parameters continue to deviate from the normal operating boundary, an early warning is issued to remind the operating personnel to make timely adjustments to the air distribution method, coal distribution method, etc. before the wall temperature reaches the alarm value, so as to prevent the wall temperature from over-temperature alarm.

[0064] In this solution, the heating surface wall temperature monitoring module includes a grouping chart unit, a cumulative data monitoring and statistical unit and a trend prevention unit. The output end of the grouping chart unit is communicatively connected to the input end of the cumulative data monitoring and statistical unit. The trend prevention unit is integrated inside the cumulative data monitoring and statistical unit. The output end of the cumulative data monitoring and statistical unit is communicatively connected to the input end of the heating surface heat absorption monitoring module.

[0065] The grouping charting unit is used to analyze the heat absorption and heat absorption ratio of each heating surface, determine whether the heat matching characteristics can achieve a reasonable boiler design, meet the design parameter operation requirements under various loads, and have good steam temperature regulation characteristics, determine the ash pollution of the heating surface and the combustion temperature field, calculate and display the total heat absorption and ratio of the economizer, water-cooled wall, low-pass, screen-pass, high-pass and primary steam-water, calculate the total heat absorption and ratio of low-repass, screen-repass and secondary steam-water, and display and query the time change trend curve and ratio ring diagram of each heat absorption ratio online based on the thermal power plant data analysis support platform;

[0066] The cumulative data monitoring and statistical unit is used for single wall temperature over-temperature statistics, by statistical over-temperature measuring points, over-temperature parts, start time, end time, duration, maximum temperature time point, maximum temperature, average temperature, according to the severity and duration of the progressive degree of rating, providing over-temperature time period historical curves, etc.;

[0067] The cumulative data monitoring and statistical unit is also used for cumulative over-temperature statistics, and statistics the over-temperature measuring points, over-temperature parts, cumulative over-temperature time, maximum temperature, average over-temperature humidity, the top few temperatures, and automatic severity rating on a daily / weekly / monthly / year basis, to provide data support for the wear and explosion prevention work of the four-tube boiler;

[0068] The trend prevention unit is used to prevent large-area bed coking and prevent boiler bed coking accidents by using the bed wall temperature distribution characteristics and change trends.

[0069] In this solution, the heating surface heat absorption monitoring module includes a combustion monitoring and optimization unit, a combustion efficiency evaluation module and a heating surface heat absorption monitoring unit. The output end of the heating surface heat absorption monitoring unit is communicatively connected to the input end of the combustion monitoring and optimization unit, and the output end of the combustion monitoring and optimization unit is communicatively connected to the input end of the combustion efficiency evaluation module; the combustion monitoring and optimization unit is used to arrange a variety of sensors in the boiler to monitor the combustion state in real time, and regularly collect and record sensor data;

[0070] The combustion efficiency evaluation module is used to establish a mathematical model of the boiler combustion process based on the collected data, and calculate the optimal fuel-air ratio by combining genetic algorithm and deep learning optimization algorithm to achieve dynamic adjustment. By analyzing the thermal efficiency, fuel consumption and emission data of the boiler, the combustion optimization effect is evaluated, and the optimization effect report is regularly generated to facilitate comprehensive analysis and decision-making by operators;

[0071] The heating surface heat absorption monitoring unit is used to group the wall temperature measurement points according to the heating surface area, and display them all in a graphical form, replacing abstract numerical display with intuitive graphical display, providing data screening and graphical comparative analysis across years and multiple working conditions, and capable of intuitive graphical real-time display and historical query, historical review of the current real-time wall temperature of the heating surface, rate of change, historical trends of related state parameters, and spatial distribution status, thereby minimizing the amplitude of combustion heat deviation and reducing the occurrence of wall temperature overtemperature.

[0072] Example

[0073] When the boiler combustion adjustment optimization system is connected to the thermal power plant management:

[0074] S1. The staff of the thermal power plant checks the required equipment one by one. When they are all able to operate normally, they start the boiler combustion adjustment and optimization system. The equipment structure management unit collects and organizes the boiler design drawings and ledger information to archive and quickly query the basic parameter data of the four tubes of the boiler. The four-tube inspection data of the boiler includes the tube number, material, tube diameter, wall thickness, design, wall temperature measurement point location, operating parameters and installation location and maintenance data. Combined with the four-tube inspection data of the unit maintenance, the three-dimensional visualization displays the structure of the boiler economizer, water-cooled wall, superheater, reheater and connecting pipes, inlet and outlet headers, steam drum and boiler pipe welds, basic physical structure information of metal materials and the specific conditions of previous maintenance processes. The four-tube wall temperature control unit marks the existing wall temperature measurement point locations in the three-dimensional visualization model of the boiler for easy and quick positioning. The spatial location of abnormal and over-temperature measurement points; the support and hanger equipment unit is used to record the name, type, model, installation load, elevation, design value, cold state value and hot state value information of the support and hanger, and analyze the stress state of the pipeline through the support and hanger information. The cold and hot state values ​​of the support and hanger can be recorded and compared on-site before and after each start and stop of the unit, and the cause of data abnormality can be analyzed and resolved in time. The castable management unit marks the castable parameters, construction and maintenance data and other previous maintenance contents on the three-dimensional visualization model of the boiler to facilitate data analysis for maintenance and accurately guide maintenance work. The boiler expansion monitoring unit adds an online expansion indicator for the boiler, and uses the thermal power plant data analysis support platform to combine the boiler operating load, operating parameters and theoretical design values, historical load values, and actual expansion values ​​for data analysis, automatically find abnormal values ​​and alarm;

[0075] S2. The benchmark database uses stable operating condition detection and cluster analysis algorithms to mine the historical data of the unit operation. By establishing a database of the water-coal ratio, wall temperature measurement points, thermal deviation, boiler expansion and operating parameters of the unit under stable conditions in each load condition range under different coal qualities, operating oxygen content, air distribution methods, and ambient temperature conditions, the thermal power plant data analysis terminal checks the heating surface pipes, castables, supports and hangers, expansion indicators and other equipment and records the data. Through data analysis and comparison, combined with the unit's operating hours and equipment life assessment, the unit's preventive maintenance is achieved, and forward-looking maintenance analysis is achieved based on data analysis. The key operating parameter comparison unit is used to compare each key operating parameter with its partition operating condition benchmark value. The operating parameters include operating oxygen content, wall temperature measurement points, and real-time thermal deviation values. The time-shift sliding window method is used to identify abnormal state points. When the key operating parameters continue to deviate from the normal operating boundary, an early warning is issued to remind the operating personnel to make timely adjustments to the air distribution method, coal distribution method, etc. before the wall temperature reaches the alarm value to prevent the wall temperature from over-temperature alarm;

[0076] S3. Analyze the heat absorption and heat absorption ratio of each heating surface through grouped graphical units, determine whether the heat matching characteristics can achieve reasonable boiler design, meet the design parameter operation requirements under various loads, and have good air temperature regulation characteristics, determine the ash pollution of the heating surface and the combustion temperature field, calculate and display the total heat absorption and ratio of economizer, water-cooled wall, low pass, screen pass, high pass and primary steam-water, calculate the total heat absorption and ratio of low reheat, screen reheat and secondary steam-water, based on the thermal power plant data analysis support platform online display, historical query of each heat absorption ratio time change trend curve, ratio ring diagram, cumulative data monitoring statistical unit is used for single wall temperature overtemperature statistics, through statistical overtemperature Temperature measurement points, over-temperature parts, start time, end time, duration, maximum temperature time point, maximum temperature, average temperature, and rating by severity and duration progression, providing over-temperature time period historical curves, etc. The cumulative data monitoring and statistical unit is also used for cumulative over-temperature statistics, and automatically rates over-temperature measurement points, over-temperature parts, cumulative over-temperature time, maximum temperature, average over-temperature humidity, the top few temperatures, and severity by day / week / month / year, providing data support for the wear and explosion prevention of the four tubes of the boiler. The trend prevention unit is used to prevent large-area bed coking, and prevents coking accidents in the boiler bed through the bed wall temperature distribution characteristics and change trends;

[0077] S4. The combustion monitoring and optimization unit arranges a variety of sensors in the boiler, including temperature sensors, pressure sensors, oxygen sensors, and flue gas composition analyzers, to monitor the combustion status in real time, collect and record sensor data regularly, and the combustion efficiency evaluation module establishes a mathematical model of the boiler combustion process based on the collected data. When establishing the mathematical model, it is necessary to consider fuel characteristics, air flow, and combustion temperature factors. The genetic algorithm and deep learning optimization algorithm are combined to calculate the optimal fuel-air ratio and realize dynamic adjustment. By analyzing the thermal efficiency, fuel consumption and emission data of the boiler, the combustion optimization effect is evaluated, and optimization effect reports are generated regularly to facilitate operators to conduct comprehensive analysis and decision-making. The heating surface heat absorption monitoring unit groups the wall temperature measurement points according to the heating surface, and displays them all in a graphical manner, using intuitive icon display instead of abstract numerical display, providing data screening and graphical comparative analysis across years and multiple working conditions, and can intuitively display and query the history in a graphical manner, and historically review the real-time wall temperature, change rate, historical trend of related state parameters, and spatial distribution status of the current heating surface, thereby minimizing the combustion heat deviation amplitude and reducing the occurrence of wall temperature overheating.

[0078] Those of ordinary skill in the art will appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0079] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices, equipment and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0080] In the several embodiments provided in the present application, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or units can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or equipment, which can be electrical, mechanical or other forms.

[0081] The modules for three-dimensional digital twin visualization of boiler pipelines, thermal power plant data analysis support platform, heating surface wall temperature monitoring, and heating surface heat absorption monitoring may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0082] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0083] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program instructions, such as a USB flash drive, a mobile hard disk, a read-only storage server, a random access storage server, a magnetic disk or an optical disk.

[0084] In addition, it should be noted that the combination of the various technical features in this case is not limited to the combination described in the claims of this case or the combination described in the specific embodiments. All technical features described in this case can be freely combined or combined in any way unless there is a contradiction between them.

[0085] It should be noted that the above examples are only specific embodiments of the present invention, and the present invention is obviously not limited to the above examples, and there are many similar variations. All variations directly derived or associated from the contents disclosed by the technicians in this field should fall within the protection scope of the present invention.

[0086] The above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing boiler combustion adjustment in a thermal power plant, characterized in that: The specific steps include: S1. Collect and organize boiler design drawings and ledger information, and combine with the four-tube inspection data of the unit maintenance to display the boiler economizer, water wall, superheater, reheater and connecting pipes, inlet and outlet headers, drum structure and boiler pipe welds, metal material basic physical structure information and the specific conditions of previous maintenance processes in a three-dimensional visualization; S2. Use stable operating condition detection and cluster analysis algorithms to mine the historical operating data of the unit, and establish a database of benchmark values ​​of water-coal ratio, wall temperature measurement points, thermal deviation, boiler expansion and operating parameters under stable conditions in each load condition range under different coal qualities, operating oxygen content, air distribution methods, and ambient temperature conditions; S3. Analyze the heat absorption and heat absorption ratio of each heating surface, determine the heat matching characteristics to achieve reasonable boiler design, meet the design parameter operation requirements under various loads, and have good temperature regulation characteristics, determine the ash pollution of the heating surface and the combustion temperature field, and provide data support for the wear and explosion prevention of the four boiler tubes through single wall temperature over-temperature statistics and cumulative over-temperature statistics; S4. The wall temperature measurement points are grouped according to the heating surface and displayed graphically. Intuitive icons are used instead of abstract numerical displays. Various sensors are arranged in the boiler. Sensor data are collected and recorded regularly. Based on the collected data, a mathematical model of the boiler combustion process is established. The optimal fuel-air ratio is calculated by combining genetic algorithms and deep learning optimization algorithms. The combustion optimization effect is evaluated by analyzing the boiler's thermal efficiency, fuel consumption and emission data.

2. The method for optimizing combustion adjustment of a thermal power plant boiler according to claim 1, characterized in that: When establishing the mathematical model in step S4, factors such as fuel characteristics, air flow, and combustion temperature need to be considered.

3. The method for optimizing combustion adjustment of a thermal power plant boiler according to claim 1, characterized in that: The sensors in step S4 include a temperature sensor, a pressure sensor, an oxygen sensor, and a flue gas composition analyzer.

4. The method for optimizing combustion adjustment of a thermal power plant boiler according to claim 1, characterized in that: The operating parameters in step S2 include operating oxygen content, wall temperature measurement points, and real-time value of thermal deviation.

5. The method for optimizing combustion adjustment of a thermal power plant boiler according to claim 1, characterized in that: The boiler four-tube inspection data in step S1 includes tube number, material, tube diameter, wall thickness, design, wall temperature measurement point location, operating parameters, installation location and inspection and maintenance data.

6. A thermal power plant boiler combustion adjustment and optimization system, used to implement a thermal power plant boiler combustion adjustment and optimization method as claimed in any one of claims 1 to 5, characterized in that: The boiler combustion adjustment and optimization system includes a boiler pipeline three-dimensional digital twin visualization module, a thermal power plant data analysis support platform, a heating surface wall temperature monitoring module and a heating surface heat absorption monitoring module. The boiler pipeline three-dimensional digital twin visualization module and the thermal power plant data analysis support platform are bidirectionally communicatively connected, the output end of the heating surface wall temperature monitoring module is communicatively connected to the input end of the heating surface heat absorption monitoring module, and the output end of the heating surface heat absorption monitoring module is communicatively connected to the input end of the thermal power plant data analysis support platform.

7. The thermal power plant boiler combustion adjustment and optimization system according to claim 6 is characterized in that: The three-dimensional digital twin visualization module of the boiler pipeline includes an equipment structure management unit, a four-tube wall temperature control unit, a support and hanger equipment unit, a castable management unit and a boiler expansion monitoring unit. The output ends of the equipment structure management unit, the four-tube wall temperature control unit, the support and hanger equipment unit and the castable management unit are respectively connected to the input end of the boiler expansion monitoring unit for communication, and the boiler expansion monitoring unit is connected to the thermal power plant data analysis support platform for bidirectional communication; The equipment structure management unit is used to collect and organize boiler design drawings and ledger information; The four-tube wall temperature control unit is used to mark the existing wall temperature measurement point positions on the three-dimensional visualization model of the boiler, so as to facilitate the rapid positioning of the spatial positions of abnormal and over-temperature measurement points; The support and hanger equipment unit is used to record the support and hanger name, type, model, installation load, elevation, design value, cold state value and hot state value information, and analyze the stress state of the pipeline through the support and hanger information; The castable management unit is used to mark castable parameters, construction and maintenance data and other previous maintenance contents on the three-dimensional visualization model of the boiler; The boiler expansion monitoring unit is used to increase the boiler online expansion indication index, and uses the thermal power plant data analysis support platform to combine the boiler operating load, operating parameters and theoretical design values, historical load values, and actual expansion values ​​to perform data analysis, automatically find out abnormal values ​​and issue an alarm.

8. The thermal power plant boiler combustion adjustment and optimization system according to claim 6, characterized in that: The thermal power plant data analysis support platform includes a reference value database, a thermal power plant data analysis terminal, and a key operating parameter comparison unit. The reference value database and the thermal power plant data analysis terminal are bidirectionally connected, and the key operating parameter comparison unit is integrated inside the thermal power plant data analysis terminal. The reference value database is used to mine the historical data of unit operation by using stable operating condition detection and cluster analysis algorithm, by establishing a reference value database of water-coal ratio, wall temperature measurement points, thermal deviation, boiler expansion and operating parameters under stable conditions in each load condition range under different coal quality, operating oxygen content, air distribution mode and ambient temperature conditions; The thermal power plant data analysis terminal is used to inspect and record data on equipment such as heating surface pipes, castables, supports and hangers, and expansion indicators; The key operating parameter comparison unit is used to compare each key operating parameter with its partition operating condition reference value, and adopts a time-shift sliding window method to identify abnormal state points.

9. The thermal power plant boiler combustion adjustment and optimization system according to claim 6, characterized in that: The heating surface wall temperature monitoring module includes a grouping chart unit, a cumulative data monitoring and statistical unit and a trend prevention unit, the output end of the grouping chart unit is communicatively connected to the input end of the cumulative data monitoring and statistical unit, the trend prevention unit is integrated inside the cumulative data monitoring and statistical unit, and the output end of the cumulative data monitoring and statistical unit is communicatively connected to the input end of the heating surface heat absorption monitoring module; The grouping charting unit is used to analyze the heat absorption and heat absorption ratio of each heating surface, determine the heat matching characteristics to achieve a reasonable boiler design, meet the design parameter operation requirements under various loads, good air temperature regulation characteristics, and determine the ash pollution of the heating surface and the combustion temperature field; The cumulative data monitoring and statistical unit is used for single wall temperature over-temperature statistics, and is graded according to severity and duration by counting over-temperature measuring points, over-temperature locations, start time, end time, duration, maximum temperature time point, maximum temperature, and average temperature; The cumulative data monitoring and statistical unit is also used for accumulating over-temperature statistics, and statistically analyzing over-temperature measuring points, over-temperature parts, cumulative over-temperature time, maximum temperature, average over-temperature humidity, the top few temperatures, and automatic rating of severity by day / week / month / year; The trend prevention unit is used to prevent large-area bed coking.

10. The thermal power plant boiler combustion adjustment and optimization system according to claim 6, characterized in that: The heating surface heat absorption monitoring module includes a combustion monitoring and optimization unit, a combustion efficiency evaluation module and a heating surface heat absorption monitoring unit, the output end of the heating surface heat absorption monitoring unit is communicatively connected to the input end of the combustion monitoring and optimization unit, and the output end of the combustion monitoring and optimization unit is communicatively connected to the input end of the combustion efficiency evaluation module; The combustion monitoring and optimization unit is used to arrange various sensors in the boiler, collect sensor data regularly and record them; The combustion efficiency evaluation module is used to establish a mathematical model of the boiler combustion process based on the collected data, calculate the optimal fuel-air ratio by combining the genetic algorithm and the deep learning optimization algorithm, and evaluate the combustion optimization effect by analyzing the thermal efficiency, fuel consumption and emission data of the boiler; The heating surface heat absorption monitoring unit is used to group the wall temperature measurement points into regions according to the heating surface, and display them all in a graphical manner, using intuitive graphical displays instead of abstract numerical displays, and providing data screening and graphical comparative analysis across years and multiple working conditions.

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