Deep peak shaving operating condition adaptability partitioning method and system for boiler component safety

Abstract

The application discloses a kind of deep peak shaving working condition adaptability partition methods and systems for boiler component safety, the present application includes respectively for each heating surface component of boiler, obtain the relationship curve diagram of temperature average of multiple temperature measuring points on heating surface component under different loads and find all inflection points;In all relationship curve diagrams, the load corresponding to the alarm temperature of the material of the corresponding heating surface component is found respectively when temperature average is greater than, and the relationship curve diagram corresponding to the maximum load is selected among all found loads;For the relationship curve diagram corresponding to the maximum load, all inflection points are labeled in order from high to low load, and according to the labeled inflection point as demarcation point, load is partitioned into continuously distributed stable peak shaving area, operating disturbance area, deep peak shaving area and non deep peak shaving area in order from high to low load.This application can realize reliable, convenient, fast deep peak shaving working condition partition evaluation for boiler component safety.

Description

Technical Field

[0001] This invention relates to the field of safe operation technology for power plant boilers under deep peak shaving conditions, specifically to an adaptive zoning method and system for deep peak shaving conditions oriented towards the safety of boiler components. Background Technology

[0002] At present, the new power system is developing rapidly and new energy power generation is connected to the grid on a large scale. However, new energy power generation has the characteristics of large fluctuations and prominent intermittency, which has a significant impact on the stability of the power grid. Its absorption requires sufficient adjustable power sources. Thermal power is one of the flexible resources that can achieve large-scale economical deep and rapid peak shaving. It is the ballast stone and regulator of the power grid stability. Therefore, the country is vigorously carrying out the flexible transformation of thermal power units to adapt to the deep peak shaving operation requirements under the new power system. In terms of the flexible operation of thermal power units, there are the following specific problems: (1) The boiler design peak shaving capacity is insufficient. How to determine the adjustable lower limit value based on the safety of boiler component materials; (2) The deep peak shaving adaptability of the boiler from the maximum output load to the minimum adjustable lower limit load range; (3) The determination of the most critical components affecting the material safety of boiler components under low load conditions. In China, there is a lot of research on boiler stable combustion, auxiliary equipment adaptability, control and frequency regulation support capabilities in deep peak shaving of coal-fired units. It is reported that the peak shaving lower limit of some coal-fired power units can reach 10% of the rated load. However, no research has been reported on the safety of boiler components materials in coal-fired power units under deep peak shaving conditions. Boiler components are frequently damaged under low load conditions, which seriously affects the safe operation of boilers. Summary of the Invention

[0003] The technical problem to be solved by this invention is to provide a method and system for adaptability zoning under deep peak shaving conditions for boiler component safety, addressing the aforementioned problems in the prior art. This invention proposes a method for assessing adaptability zoning under deep peak shaving conditions based on the material safety of boiler components in coal-fired power plants under deep peak shaving conditions. It utilizes the relationship between the temperature and load at measuring points of boiler components under different deep peak shaving conditions to implement a reliable, convenient, and rapid assessment, enabling timely detection of the adaptability of deep peak shaving under different loads.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0005] A deep peak-shaving adaptive zoning method for boiler component safety includes:

[0006] S101, for each heating surface component of the boiler, obtain the relationship curve of the average temperature of multiple temperature measuring points on the heating surface component under different loads, and find all the inflection points in the relationship curve.

[0007] S102, in all the relationship curves, find the loads corresponding to the material alarm temperature of the corresponding heated surface component that have an average temperature greater than the average temperature of the component, and select the relationship curve corresponding to the largest load among all the found loads.

[0008] S103, for the relationship curve corresponding to the largest load, mark all inflection points in order of load from high to low, and use the marked inflection points as dividing points to divide the load into continuously distributed stable peak-shaving area, operation disturbance area, deep peak-shaving area and non-deep peak-shaving area in order of load from high to low.

[0009] Optionally, dividing the load into continuously distributed stable peak-shaving zones, operational disturbance zones, deep peak-shaving zones, and non-deep peak-shaving zones according to the load from high to low includes: defining the area between the design maximum output load and the first inflection point as the stable peak-shaving zone; defining the area between the first inflection point and the second-to-last inflection point as the operational disturbance zone; defining the area between the second-to-last inflection point and the first-to-last inflection point as the deep peak-shaving zone; and defining the area after the first-to-last inflection point as the non-deep peak-shaving zone.

[0010] Optionally, the various heating surface components of the boiler in step 101 include some or all of the following: water-cooled wall, wall-mounted superheater, low-temperature superheater, screen-type superheater, high-temperature superheater, low-temperature reheater, high-temperature reheater, and economizer.

[0011] Optionally, obtaining the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads in step 101 includes: for each given load under multiple given loads, selecting the average load value that is stable for a specified period of time under that given load, obtaining the temperature of multiple temperature measuring points on the heated surface component under that given load, and calculating the average value of the temperatures of multiple temperature measuring points as the average temperature under that given load; finally, generating a curve from the average temperature values ​​under different given loads to obtain the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads.

[0012] Optionally, in the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads, the horizontal axis represents the average load and the vertical axis represents the average temperature.

[0013] Optionally, finding all inflection points in the relationship curve graph in step 101 includes: for each measuring point in the relationship curve graph, calculating the difference between the average temperature of the measuring point and the previous measuring point, and the difference between the loads, and calculating the absolute value of the ratio between the difference between the average temperature and the difference between the loads. If the absolute value of the ratio is greater than or equal to a preset ratio, then the measuring point is determined to be an inflection point.

[0014] Optionally, after step S103, the output may include the heating surface component corresponding to the relationship curve of the maximum load as the key component that affects the material safety of the deep peak-shaving boiler component.

[0015] Furthermore, the present invention also provides a deep peak-shaving condition adaptive zoning system for boiler component safety, comprising:

[0016] The curve generation program unit is used to obtain the relationship curves of the average temperature of multiple temperature measuring points on each heating surface component of the boiler under different loads, and to find all the inflection points in the relationship curves.

[0017] The curve filtering program unit is used to find the loads corresponding to the material alarm temperature of the corresponding heated surface component when the average temperature is greater than the average temperature in all the relationship curves, and select the relationship curve corresponding to the largest load among all the found loads.

[0018] The operating condition zoning program unit is used to mark all inflection points on the relationship curve corresponding to the maximum load in descending order of load, and to divide the load into continuously distributed stable peak-shaving zone, operating disturbance zone, deep peak-shaving zone, and non-deep peak-shaving zone based on the marked inflection points as the dividing points.

[0019] Optionally, the operating condition zoning program unit divides the load into continuously distributed stable peak-shaving zones, operational disturbance zones, deep peak-shaving zones, and non-deep peak-shaving zones according to the load from high to low. This includes: the area between the design maximum output load and the first inflection point is designated as the stable peak-shaving zone; the area between the first inflection point and the second-to-last inflection point is designated as the operational disturbance zone; the area between the second-to-last inflection point and the first-to-last inflection point is designated as the deep peak-shaving zone; and the area after the first-to-last inflection point is designated as the non-deep peak-shaving zone.

[0020] Optionally, each of the heating surface components of the boiler includes some or all of the following: water-cooled wall, wall-mounted superheater, low-temperature superheater, screen-type superheater, high-temperature superheater, low-temperature reheater, high-temperature reheater, and economizer.

[0021] Optionally, the curve generation program unit obtains the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads by: for each given load under multiple given loads, selecting the average load value that is stable under the given load for a specified period of time, obtaining the temperature of multiple temperature measuring points on the heated surface component under the given load, and calculating the average value of the temperatures of multiple temperature measuring points as the average temperature under the given load; finally, generating curves from the average temperature values ​​under different given loads to obtain the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads.

[0022] Optionally, in the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads, the horizontal axis represents the average load and the vertical axis represents the average temperature.

[0023] Optionally, the curve generation program unit finds all inflection points in the relationship curve graph by: for each measuring point in the relationship curve graph, calculating the difference between the average temperature of the measuring point and the previous measuring point, and the difference between the loads, and calculating the absolute value of the ratio of the difference between the average temperature and the difference between the loads. If the absolute value of the ratio is greater than or equal to a preset ratio, then the measuring point is determined to be an inflection point.

[0024] Optionally, it also includes a key component identification program unit, which outputs the heating surface component corresponding to the relationship curve of the maximum load as the key component that affects the material safety of the deep peak-shaving boiler component.

[0025] Furthermore, the present invention also provides a deep peak-shaving adaptive zoning system for boiler component safety, comprising an interconnected microprocessor and a memory, wherein the microprocessor is programmed or configured to execute the deep peak-shaving adaptive zoning method for boiler component safety.

[0026] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program for being programmed or configured by a microprocessor to execute the deep peak-shaving adaptive zoning method for boiler component safety.

[0027] Compared with the prior art, the present invention has the following main advantages:

[0028] 1. This invention addresses the material safety of boiler components in coal-fired power units under deep peak shaving conditions. It proposes a method for assessing the adaptability of boiler components under deep peak shaving conditions by zoning. In all relationship curves, the method identifies the loads whose average temperature exceeds the material alarm temperature of the corresponding heating surface component. From all identified loads, the method selects the relationship curve corresponding to the highest load. All inflection points are then marked in descending order of load. These inflection points serve as dividing points, and the loads are zoned in descending order of load into continuously distributed stable peak shaving zones, operational disturbance zones, zones suitable for deep peak shaving, and zones unsuitable for deep peak shaving. This fully utilizes the relationship between the measured temperature and load of boiler components under different deep peak shaving conditions, enabling reliable, convenient, and rapid assessment of the adaptability of deep peak shaving conditions, thus allowing for timely detection of the adaptability of deep peak shaving under different loads.

[0029] 2. This invention is based on actual unit operating data and follows the changes in unit operating conditions to obtain the actual situation of load unit operating condition adaptability zoning, which is of guiding significance for the actual peak-shaving operation of units. The method of this invention does not require complex calculation and experimental processes, is simple and easy to implement, is not affected by differences in unit type or performance, has universal applicability, and can realize real-time monitoring and evaluation of boiler equipment operating status, real-time diagnosis of boiler peak-shaving safety performance, and improve the unit's boiler peak-shaving support capability. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the basic process of the method in an embodiment of the present invention.

[0031] Figure 2 This is a graph showing the relationship between the maximum load in this embodiment of the invention. Detailed Implementation

[0032] The following section will take a 600MW supercritical unit boiler at a power plant in Hunan Province as an example to further illustrate the invention in detail.

[0033] like Figure 1 As shown, the deep peak-shaving adaptive zoning method for boiler component safety in this embodiment includes:

[0034] S101, for each heating surface component of the boiler, obtain the relationship curve of the average temperature of multiple temperature measuring points on the heating surface component under different loads, and find all the inflection points in the relationship curve.

[0035] S102, in all the relationship curves, find the loads corresponding to the material alarm temperature of the corresponding heated surface component that have an average temperature greater than the average temperature of the component, and select the relationship curve corresponding to the largest load among all the found loads.

[0036] S103, for the relationship curve corresponding to the maximum load, all inflection points are marked in descending order of load. Based on these marked inflection points, the load is divided into four continuously distributed zones in descending order of load: a stable peak-shaving zone, an operational disturbance zone, a zone capable of deep peak-shaving, and a zone not capable of deep peak-shaving. It should be noted that the stable peak-shaving zone, operational disturbance zone, zone capable of deep peak-shaving, and zone not capable of deep peak-shaving are zones defined for existing deep peak-shaving conditions. Due to the limitations of this embodiment's zoned mechanism for existing deep peak-shaving conditions, the specific definitions of the stable peak-shaving zone, operational disturbance zone, zone capable of deep peak-shaving, and zone not capable of deep peak-shaving are not detailed here.

[0037] In this embodiment, each heating surface component of the boiler in step 101 includes some or all of the following: water-cooled wall, wall-mounted superheater, low-temperature superheater, screen-type superheater, high-temperature superheater, low-temperature reheater, high-temperature reheater, and economizer.

[0038] In this embodiment, step 101, obtaining the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads, includes: for each given load under multiple given loads, selecting the average load value that is stable for a specified period of time under that given load, obtaining the temperature of multiple temperature measuring points on the heated surface component under that given load, and calculating the average value of the temperatures of multiple temperature measuring points as the average temperature under that given load; finally, generating curves from the average temperature values ​​under different given loads to obtain the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads.

[0039] In this embodiment, the raw data acquired under various given loads includes different power generation loads and the corresponding temperatures of the measuring points on the heating surface components and the main steam flow rate. The raw data acquisition includes historical operating data of a 600MW supercritical unit boiler at a power plant in Hunan Province from January 17, 2022 to June 19, 2022. The maximum output of this unit is 666MW. Key parameters such as generator active power, main steam flow rate, and the temperature of the measuring points at the outlet side of the heating surface tubes were selected. The data sampling frequency was one record per minute to acquire the raw sample data.

[0040] After acquiring the raw data, the average load value stable for a specified period under the given load is selected. This involves removing load data where the load change rate exceeds a preset value of 0.5% BMCR / min and the continuous load change exceeds a preset value of 2 MW / min, based on the normal range of the raw data under different stable operating loads of the unit. Then, the load value within a certain period under the given load of the unit is selected, and the average load value (MW) is calculated and recorded. Simultaneously, for each given load under various given loads, the average load value stable for a specified period under that given load is selected, and the temperature (°C) of multiple temperature measuring points on the heated surface components under that given load is obtained. The average temperature of these multiple measuring points is then calculated as the average temperature value under that given load.

[0041] For each given load under multiple given loads, this embodiment first processes the rated load, and then successively decreases the load change as the next given load, and so on, until the average load under all given loads and the average temperature under the given load are obtained. For example, this embodiment includes: (1) Selecting data that is stable at the rated load of 600MW for a certain period of time, and calculating the average load value as 601.2MW using a known method; (2) Selecting the corresponding 600MW load and the temperature (outlet pipe wall temperature) data of the sixth measuring point of the front wall of the rear shaft at the same corresponding time in step 3, and calculating and recording the average temperature value as 418.1℃ using a known method; (3) Gradually selecting a stable load value of 550MW for a certain period of time by decreasing the load value of integers as described in step 3, and calculating and recording the average load value as 550.3MW using a known method; (4) Selecting the corresponding 550MW load and the temperature (outlet pipe wall temperature) data of the sixth measuring point of the front wall of the rear shaft at the same time in step 5, and calculating and recording the average temperature value as 413.4℃ using a known method; (5) Repeating step (3) in sequence. Step (4): Select data from the stable operation of loads of 505MW, 450MW, 420MW, 410MW, 400MW, 355MW, 300MW, 200MW, and 180MW for a certain period of time, and calculate the average load values ​​using known methods as 504.9MW, 454.1MW, 419.4MW, 409.9MW, 400.5MW, 355.1MW, 300.6MW, 200.4MW, and 180.8MW, respectively. Calculate the average temperature (outlet pipe wall temperature) at the 6th measuring point of the front wall of the rear shaft under the corresponding load and time using known methods as 398.5℃, 388.3℃, 399.6℃, 398.9℃, 387.1℃, 390.4℃, 387.3℃, 361.3℃, and 381.1℃, respectively. Based on this, known methods can be used to establish a relationship curve between the average load value and the average temperature value of the component measuring points. As an optional implementation, in this embodiment, the relationship curve of the average temperature values ​​of multiple temperature measuring points on the heated surface component under different loads is plotted with the horizontal axis representing the average load value and the vertical axis representing the average temperature value. The above steps are repeated sequentially to establish relationship curves for all heated surface components, including water-cooled walls, wall-mounted superheaters, low-temperature superheaters, screen-type superheaters, high-temperature superheaters, low-temperature reheaters, high-temperature reheaters, economizers, etc.

[0042] In this embodiment, step 101, finding all inflection points in the relationship curve graph, includes: for each measuring point in the relationship curve graph, calculating the difference between the average temperature of that measuring point and the previous measuring point, and the difference between the loads, and calculating the absolute value of the ratio of the difference between the average temperature and the difference between the loads. If the absolute value of the ratio is greater than or equal to a preset ratio, then the measuring point is determined to be an inflection point. Undoubtedly, the preset ratio can be set according to actual needs; for example, in this embodiment, the preset ratio is 10%. That is, when the absolute value of the ratio of the difference between the average temperature and the difference between the average load is greater than or equal to 10%, it is considered an inflection point. Furthermore, all inflection points can be marked immediately in order of load from high to low; alternatively, they can be marked later when needed to avoid unnecessary marking operations.

[0043] After establishing the load-temperature relationship curve for each heated surface component, the load-temperature relationship curves for each component are different, resulting in varying impacts. In step 102 of this embodiment, when selecting the relationship curve corresponding to the maximum load, the comparison object is the average temperature. Since 2) different components may have temperatures exceeding the alarm temperature, the load corresponding to each component exceeding the alarm temperature will definitely be different because the operating conditions, materials, flow rates, etc., of each component are different. The load corresponding to the first time it reaches the over-temperature will definitely not be the same. The maximum load among all the loads corresponding to the over-temperature is set as the highest load. The component with the highest load corresponding to the over-temperature is definitely unique, so the most severe temperature-load curve of that component is basically unique, and the trend of the temperature-load curves of all measuring points on that component is also consistent. Therefore, in step 102 of this embodiment, when identifying the loads corresponding to the material alarm temperatures of the corresponding heated surface components with average temperatures greater than those in all the relationship curves, and selecting the relationship curve corresponding to the largest load among all the identified loads, the boiler of this unit exceeds the wall temperature alarm point at the outlet pipe wall temperature measuring point 6 of the rear shaft front casing wall. When the maximum load exceeds the design material 15CrMoG wall temperature alarm point of 490℃, the maximum load is 200.5MW, and the temperature at measuring point 6 is 515.3℃. Therefore, this relationship curve can be used as the relationship curve corresponding to the largest load found. Figure 2 As shown, the relationship curve represents the highest load corresponding to overheating in this boiler component, and thus this relationship curve is selected as the evaluation curve for the deep peak shaving zone of this boiler.

[0044] It should be noted that in step 103, when dividing the load into continuously distributed stable peak-shaving zones, operational disturbance zones, deeply shaving zones, and non-deeply shaving zones according to the load order from high to low, the required inflection points can be selected as the dividing points as needed. For example, as a preferred embodiment, in step 103 of this embodiment, dividing the load into continuously distributed stable peak-shaving zones, operational disturbance zones, deeply shaving zones, and non-deeply shaving zones according to the load order from high to low includes: the area between the design maximum output load and the first inflection point is designated as the stable peak-shaving zone; the area between the first inflection point and the second-to-last inflection point is designated as the operational disturbance zone; the area between the second-to-last inflection point and the first-to-last inflection point is designated as the deeply shaving zone; and the area after the first-to-last inflection point is designated as the non-deeply shaving zone. In step S103 of this embodiment, for the relationship curve corresponding to the maximum load, all inflection points are marked in order from high to low load, and the first inflection point is designated as inflection point 1, the second inflection point as inflection point 2, and so on, resulting in the following... Figure 2 As shown, the load is the average load, the temperature is the average temperature, and the numbers in the graph are the inflection point numbers. See [link to graph]. Figure 2 It can be seen that inflection point 1 is 450MW, inflection point 2 is 410MW, inflection point 3 is 400MW, and inflection point 4 is 200MW. Therefore, after dividing the load into continuously distributed stable peak-shaving zone, operational disturbance zone, deep peak-shaving zone, and non-deep peak-shaving zone according to the load from high to low, the results are as follows: 1) Stable peak-shaving zone: maximum output load from 666 to 450MW; 2) Operational disturbance zone: 450MW-400MW area; 3) Deep peak-shaving zone: 400MW-200MW area; 4) Non-deep peak-shaving zone: area after 200MW.

[0045] Based on the selection mechanism of the heating surface component corresponding to the relationship curve corresponding to the maximum load, it can be seen that the heating surface component corresponding to the relationship curve corresponding to the maximum load is the key component affecting the material safety of the deep peak-shaving boiler components. Therefore, after step S103 in this embodiment, the heating surface component corresponding to the relationship curve corresponding to the maximum load is further output as the identified key component affecting the material safety of the deep peak-shaving boiler components.

[0046] In summary, the deep peak-shaving adaptive zoning method for boiler component safety in this embodiment is based on actual unit operating data and follows the changes in unit operating conditions to obtain the actual load situation of the unit in the zoning, which is of guiding significance for the actual peak-shaving operation of the unit. Using this deep peak-shaving adaptive zoning method for boiler component safety in this embodiment requires no complex calculation or experimental process, is simple and easy to implement, is not affected by differences in unit type or performance, has universal applicability, and can realize real-time monitoring, evaluation, and diagnosis of boiler peak-shaving safety performance, thereby improving the unit's boiler peak-shaving support capability. This deep peak-shaving adaptive zoning method for boiler component safety in this embodiment can perform zoning evaluation of deep peak-shaving conditions for in-service boilers without complex calculation or experimental processes, and is simple, safe, and reliable.

[0047] Furthermore, this embodiment also provides a deep peak-shaving condition adaptive zoning system for boiler component safety, including:

[0048] The curve generation program unit is used to obtain the relationship curves of the average temperature of multiple temperature measuring points on each heating surface component of the boiler under different loads, and to find all the inflection points in the relationship curves.

[0049] The curve filtering program unit is used to find the loads corresponding to the material alarm temperature of the corresponding heated surface component when the average temperature is greater than the average temperature in all the relationship curves, and select the relationship curve corresponding to the largest load among all the found loads.

[0050] The operating condition zoning program unit is used to mark all inflection points on the relationship curve corresponding to the maximum load in descending order of load, and to divide the load into continuously distributed stable peak-shaving zone, operating disturbance zone, deep peak-shaving zone, and non-deep peak-shaving zone based on the marked inflection points as the dividing points.

[0051] In this embodiment, the operating condition zoning program unit divides the load into continuously distributed stable peak-shaving zones, operational disturbance zones, deep peak-shaving zones, and non-deep peak-shaving zones according to the load from high to low. The division includes: the area between the design maximum output load and the first inflection point as the stable peak-shaving zone; the area between the first inflection point and the second-to-last inflection point as the operational disturbance zone; the area between the second-to-last inflection point and the first-to-last inflection point as the deep peak-shaving zone; and the area after the first-to-last inflection point as the non-deep peak-shaving zone.

[0052] In this embodiment, each heating surface component of the boiler includes some or all of the following: water-cooled wall, wall-mounted superheater, low-temperature superheater, screen-type superheater, high-temperature superheater, low-temperature reheater, high-temperature reheater, and economizer.

[0053] In this embodiment, the curve generation program unit obtains the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads by: for each given load under multiple given loads, selecting the average load value that is stable for a specified period of time under the given load, obtaining the temperature of multiple temperature measuring points on the heated surface component under the given load, and calculating the average value of the temperatures of multiple temperature measuring points as the average temperature under the given load; finally, generating curves from the average temperature values ​​under different given loads to obtain the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads.

[0054] In this embodiment, the graph showing the relationship between the average temperature of multiple temperature measuring points on the heated surface component under different loads has the horizontal axis representing the average load and the vertical axis representing the average temperature.

[0055] In this embodiment, the curve generation program unit finds all inflection points in the relationship curve graph by: for each measuring point in the relationship curve graph, calculating the difference between the average temperature of the measuring point and the previous measuring point, and the difference between the loads, and calculating the absolute value of the ratio between the difference between the average temperature and the difference between the loads. If the absolute value of the ratio is greater than or equal to a preset ratio, the measuring point is determined to be an inflection point.

[0056] In this embodiment, a key component identification program unit is also included, which is used to output the heating surface component corresponding to the relationship curve of the maximum load as the key component that affects the material safety of the deep peak-shaving boiler component.

[0057] Furthermore, this embodiment also provides a deep peak-shaving adaptive zoning system for boiler component safety, including a microprocessor and a memory interconnected, wherein the microprocessor is programmed or configured to execute the deep peak-shaving adaptive zoning method for boiler component safety.

[0058] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program that is programmed or configured by a microprocessor to execute the deep peak-shaving adaptive zoning method for boiler component safety.

[0059] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0060] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A deep peak-shaving operating condition adaptive zoning method for boiler component safety, characterized in that, include: S101, for each heating surface component of the boiler, obtain the relationship curve of the average temperature of multiple temperature measuring points on the heating surface component under different loads, and find all inflection points in the relationship curve; finding all inflection points in the relationship curve includes: for each measuring point in the relationship curve, calculate the difference between the average temperature of the measuring point and the previous measuring point, and the difference between the loads, and calculate the absolute value of the ratio of the difference between the average temperature and the difference between the loads. If the absolute value of the ratio is greater than or equal to a preset ratio, the measuring point is determined to be an inflection point; S102, in all the relationship curves, find the loads corresponding to the material alarm temperature of the corresponding heated surface component that have an average temperature greater than the average temperature of the component, and select the relationship curve corresponding to the largest load among all the found loads. S103, for the relationship curve corresponding to the largest load, mark all inflection points in order of load from high to low, and use the marked inflection points as dividing points to divide the load into continuously distributed stable peak-shaving area, operation disturbance area, deep peak-shaving area and non-deep peak-shaving area in order of load from high to low.

2. The deep peak-shaving adaptive zoning method for boiler component safety according to claim 1, characterized in that, In step S103, the load is divided into continuously distributed stable peak-shaving areas, operational disturbance areas, deeply shaving areas, and non-deeply shaving areas according to the load from high to low. This includes: the area between the design maximum output load and the first inflection point is designated as the stable peak-shaving area; the area between the first inflection point and the second-to-last inflection point is designated as the operational disturbance area; the area between the second-to-last inflection point and the first-to-last inflection point is designated as the deeply shaving area; and the area after the first-to-last inflection point is designated as the non-deeply shaving area.

3. The deep peak-shaving adaptive zoning method for boiler component safety according to claim 1, characterized in that, In step S101, the various heating surface components of the boiler include some or all of the following: water-cooled wall, wall-mounted superheater, low-temperature superheater, screen-type superheater, high-temperature superheater, low-temperature reheater, high-temperature reheater, and economizer.

4. The deep peak-shaving adaptive zoning method for boiler component safety according to claim 1, characterized in that, Step S101, obtaining the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads, includes: for each given load under multiple given loads, selecting the average load value that is stable for a specified period of time under that given load, obtaining the temperature of multiple temperature measuring points on the heated surface component under that given load, and calculating the average value of the temperatures of multiple temperature measuring points as the average temperature under that given load; finally, generating curves from the average temperature values ​​under different given loads to obtain the relationship curve of the average temperature of multiple temperature measuring points on the heated surface component under different loads.

5. The deep peak-shaving adaptive zoning method for boiler component safety according to claim 4, characterized in that, In the curve diagram showing the relationship between the average temperature of multiple temperature measuring points on the heated surface component under different loads, the horizontal axis represents the average load, and the vertical axis represents the average temperature.

6. The deep peak-shaving adaptive zoning method for boiler component safety according to claim 1, characterized in that, Step S103 is followed by outputting the heating surface component corresponding to the relationship curve of the maximum load as the key component that affects the material safety of the peak-shaving boiler component.

7. A deep peak-shaving adaptive zoning system for implementing the deep peak-shaving adaptive zoning method for boiler component safety as described in any one of claims 1 to 6, characterized in that, include: The curve generation program unit is used to obtain the relationship curves of the average temperature of multiple temperature measuring points on each heating surface component of the boiler under different loads, and to find all inflection points in the relationship curves. Finding all inflection points in the relationship curves includes: for each measuring point in the relationship curves, calculating the difference between the average temperature of the measuring point and the previous measuring point, and the difference between the loads, and calculating the absolute value of the ratio of the difference between the average temperature and the difference between the loads. If the absolute value of the ratio is greater than or equal to a preset ratio, the measuring point is determined to be an inflection point. The curve filtering program unit is used to find the loads corresponding to the material alarm temperature of the corresponding heated surface component when the average temperature is greater than the average temperature in all the relationship curves, and select the relationship curve corresponding to the largest load among all the found loads. The operating condition zoning program unit is used to mark all inflection points on the relationship curve corresponding to the maximum load in descending order of load, and to divide the load into continuously distributed stable peak-shaving zone, operating disturbance zone, deep peak-shaving zone, and non-deep peak-shaving zone based on the marked inflection points as the dividing points.

8. A deep peak-shaving adaptive zoning system for boiler component safety, comprising interconnected microprocessors and memory, characterized in that, The microprocessor is programmed or configured to execute the deep peak-shaving adaptive zoning method for boiler component safety as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, The computer program is used to be programmed or configured by a microprocessor to execute the deep peak-shaving adaptive zoning method for boiler component safety as described in any one of claims 1 to 6.

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