Main steam temperature prediction control method and device based on fusion model, equipment and medium

Abstract

The invention discloses a main steam temperature prediction control method, device, equipment and medium based on a fusion model, and the method comprises the steps: building a fusion prediction model based on a superheater dynamic heat transfer theory; updating the fusion prediction model based on historical operation data of the coal-fired unit; determining a predicted main steam temperature of the coal-fired unit based on the fusion prediction model, and constructing an optimization objective function according to the predicted main steam temperature; solving the optimization objective function according to a preset constraint condition to obtain an optimization objective; and determining the working mode of the coal-fired unit based on the function value of the optimization target, wherein the working mode comprises a stable mode, a variable load mode and a limit mode. The invention belongs to the field of coal-fired unit control. The intelligent degree of coal-fired unit control can be improved.

Description

Technical Field

[0001] The present invention relates to the field of coal-fired unit control, and in particular to a main steam temperature prediction and control method, device, equipment and medium based on a fusion model. Background Art

[0002] A coal-fired unit is a system that uses coal as fuel, releasing energy through combustion to heat water and generate steam, which in turn drives a steam turbine to generate electricity. It primarily consists of a boiler, steam turbine, generator, and various auxiliary systems. Coal-fired units are widely used in power generation worldwide due to their efficient and stable power generation capabilities, particularly in countries and regions with high energy demand.

[0003] However, with the increasing awareness of environmental protection and the development of technology, in order to reduce the impact on the environment, traditional coal-fired units need to gradually develop in a more intelligent and energy-saving direction. Therefore, there is an urgent need to provide a more intelligent and energy-saving operation control strategy. Summary of the Invention

[0004] The present invention solves the technical problems of insufficient intelligence and insufficient energy saving of control strategies in the prior art by providing a main steam temperature prediction control method, device, equipment and medium based on a fusion model, and achieves the technical effect of providing a more intelligent and energy-saving control strategy.

[0005] In a first aspect, the present invention provides a main steam temperature prediction and control method based on a fusion model, comprising:

[0006] Based on the superheater dynamic heat transfer theory, a fusion prediction model is constructed, which is used to predict the main steam temperature of coal-fired units;

[0007] Update the fusion prediction model based on the historical operating data of coal-fired units;

[0008] Based on the fusion prediction model, the predicted main steam temperature of the coal-fired unit is determined, and the optimization objective function is constructed based on the predicted main steam temperature;

[0009] Solve the optimization objective function with preset constraints to obtain the optimization target;

[0010] The operating mode of the coal-fired unit is determined based on the function value of the optimization target, where the operating modes include stable mode, variable load mode and limit mode.

[0011] Furthermore, based on the superheater dynamic heat transfer theory, a fusion prediction model is constructed, including:

[0012]

[0013] in, Main steam temperature T Z The rate of change of x over time, α is the heat transfer coefficient, T Z is the main steam temperature, T Y is the flue gas temperature, β is the steam heat absorption coefficient, is the rate of change of steam mass flow rate.

[0014] Furthermore, based on the historical operating data of coal-fired units, the fusion prediction model is updated, including:

[0015] Obtain historical operating data of coal-fired units, including fuel quantity, desuperheating water quantity, unit load, coal calorific value, and historical main steam temperature;

[0016] Input historical operating data into the fusion prediction model to obtain the predicted main steam temperature at each moment in the history;

[0017] Adjust the heat transfer coefficient and steam heat absorption coefficient based on the predicted main steam temperature at each historical moment and the historical main steam temperature at that moment;

[0018] When the preset conditions are met, the latest heat transfer coefficient and steam heat absorption coefficient are saved.

[0019] Furthermore, an optimization objective function is constructed based on the predicted main steam temperature, including:

[0020]

[0021] Among them, J is the function value of the optimization objective function, N P is the time domain length, T Z (x) is the predicted main steam temperature at time x, T Z (set) is the preset main steam temperature, Δu(x) is the change in the amount of desuperheating water, H Z (x) is the predicted main steam enthalpy at time x, H Z (opt) is the optimal main steam enthalpy.

[0022] Furthermore, preset constraints include:

[0023] Desuperheating water temperature constraint: T w，l ≤T w，s ≤T w，k , where T w，l With T w，k is the preset desuperheating water temperature, T w，s It is the real-time value of the desuperheating water temperature;

[0024] Predicted main steam temperature constraint: T Z (set)-5≤T Z (x)≤T Z(set)+5, where T Z (x) is the predicted main steam temperature at time x, T Z (set) is the preset main steam temperature;

[0025] Steam flow restriction: 100≤F s ≤200, where F s is the real-time steam flow;

[0026] Flue gas temperature constraint: 150≤T Y ≤250, where T Y is the flue gas temperature.

[0027] Furthermore, the operating mode of the coal-fired unit is determined based on the optimization target, including:

[0028] When the function value of the optimization objective is within the preset unit operation range, the coal-fired unit is controlled to operate in a stable mode; or,

[0029] When the function value of the optimization objective is greater than the maximum value of the preset unit operation range, the coal-fired unit is controlled to operate in the limit mode; or,

[0030] When the value of the optimization target is less than the minimum value of the preset unit operating range, the coal-fired unit is controlled to operate in a variable load mode.

[0031] Furthermore, the preset unit operating range includes:

[0032] 50≤G s ≤500, where G s It is the preset unit operating range.

[0033] In a second aspect, the present invention provides a main steam temperature prediction and control device based on a fusion model, comprising:

[0034] A model building module is used to build a fusion prediction model based on the superheater dynamic heat transfer theory, where the fusion prediction model is used to predict the main steam temperature of the coal-fired unit;

[0035] An update module is used to update the fusion prediction model based on the historical operating data of the coal-fired units;

[0036] A function construction module is used to determine the predicted main steam temperature of the coal-fired unit based on the fusion prediction model and to construct an optimization objective function based on the predicted main steam temperature;

[0037] The optimization solution module is used to solve the optimization objective function with preset constraints to obtain the optimization target;

[0038] The mode operation module is used to determine the working mode of the coal-fired unit based on the optimization target, where the working modes include stable mode, variable load mode and limit mode.

[0039] In a third aspect, the present invention provides an electronic device, comprising:

[0040] processor;

[0041] a memory for storing processor-executable instructions;

[0042] The processor is configured to execute to implement the main steam temperature prediction and control method based on the fusion model as provided in the first aspect.

[0043] In a fourth aspect, the present invention provides a non-temporary computer-readable storage medium. When the instructions in the non-temporary computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the main steam temperature prediction and control method based on the fusion model provided in the first aspect.

[0044] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0045] The main steam temperature prediction and control method provided by the present invention integrates the superheater dynamic heat transfer theory and historical operation data, constructs and continuously updates a prediction model with a physical basis, and improves the prediction accuracy of the main steam temperature change trend.

[0046] The present invention establishes an optimization objective function, comprehensively considers temperature deviation, control action amplitude and steam energy quality, and judges the operating status of the unit based on its function value, automatically switches to stable mode, variable load mode or limit mode, and realizes adaptive control under different working conditions. It not only improves the intelligence level and responsiveness of the control system, but also optimizes energy efficiency while ensuring safety, effectively copes with complex and changeable operating environments, and improves the stability and economy of coal-fired unit operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 A schematic flow chart of the main steam temperature prediction and control method based on the fusion model provided by the present invention;

[0049] Figure 2This is a structural schematic diagram of the main steam temperature prediction and control device based on the fusion model provided by the present invention. DETAILED DESCRIPTION

[0050] The embodiment of the present invention solves the technical problems of insufficient intelligence and insufficient energy saving of the control strategy in the prior art by providing a main steam temperature prediction and control method based on a fusion model.

[0051] The technical solution of the present invention is to solve the above technical problems, and the overall idea is as follows:

[0052] The main steam temperature predictive control method based on the fusion model includes:

[0053] Based on the dynamic heat transfer theory of superheater, a fusion prediction model is constructed, where the fusion prediction model is used to predict the main steam temperature of the coal-fired unit; based on the historical operating data of the coal-fired unit, the fusion prediction model is updated; based on the fusion prediction model, the predicted main steam temperature of the coal-fired unit is determined, and an optimization objective function is constructed according to the predicted main steam temperature; the optimization objective function is solved with preset constraints to obtain the optimization target; based on the function value of the optimization target, the operating mode of the coal-fired unit is determined, where the operating modes include stable mode, variable load mode and limit mode.

[0054] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0055] First, the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the associated objects.

[0056] The present invention provides Figure 1 The main steam temperature prediction and control method based on the fusion model shown includes steps S11-S15:

[0057] Step S11: constructing a fusion prediction model based on the superheater dynamic heat transfer theory, wherein the fusion prediction model is used to predict the main steam temperature of the coal-fired unit.

[0058] Specifically include:

[0059]

[0060] in, Main steam temperature T Z The rate of change of x over time, α is the heat transfer coefficient, T Z is the main steam temperature, TY is the flue gas temperature, β is the steam heat absorption coefficient, is the rate of change of steam mass flow rate.

[0061] The superheater dynamic heat transfer theory is a theory that studies the dynamic change law of the heat transfer process between steam and flue gas inside the superheater in a coal-fired unit.

[0062] The superheater is a key component in a boiler system, heating saturated steam to superheated steam to improve turbine efficiency and prevent damage to blades caused by wet steam. The heat transfer process in a superheater is inherently unsteady, involving several heat transfer modes: convection from the flue gas to the tube wall, conduction through the tube wall, and convection between the steam within the tube and the tube wall.

[0063] The fusion prediction model combines two key factors: the heat transfer process (driven by the difference between flue gas temperature and steam temperature) and the steam flow characteristics (driven by the change in steam mass flow rate).

[0064] The fusion prediction model is a dynamic model that can predict the changing trend of the main steam temperature based on the real-time changes in flue gas temperature and steam flow, thereby providing a more accurate control basis for the coal-fired unit.

[0065] In actual power plant control systems, excessively high main steam temperatures can damage equipment, while excessively low temperatures can affect efficiency. Using a fusion prediction model, feedforward or predictive control can be implemented: predicting changes in main steam temperature in advance allows for proactive adjustments to water spray cooling or other control measures to maintain temperature stability, improving system response speed and safety.

[0066] Step S12: updating the fusion prediction model based on the historical operation data of the coal-fired unit.

[0067] Specifically, it includes: obtaining the historical operating data of the coal-fired unit, where the historical operating data includes fuel quantity, desuperheating water quantity, unit load, coal calorific value and historical main steam temperature; inputting the historical operating data into the fusion prediction model to obtain the predicted main steam temperature at each moment in history; adjusting the heat transfer coefficient and steam heat absorption coefficient according to the predicted main steam temperature at each moment in history and the historical main steam temperature at that moment; and saving the latest heat transfer coefficient and steam heat absorption coefficient when the preset conditions are met.

[0068] Obtain historical operating data from the power plant's monitoring system over a period of time. This data includes, but is not limited to, fuel quantity, desuperheating water quantity, unit load, coal calorific value, and main steam temperature.

[0069] The historical data is fed into the established fusion prediction model as input variables. Based on the dynamic heat transfer mechanism of the superheater, the fusion prediction model can predict the main steam temperature at each moment based on input conditions such as the current flue gas temperature and steam flow rate change rate.

[0070] By comparing the difference between the predicted main steam temperature output by the fusion prediction model and the actual recorded historical main steam temperature, the degree of matching between the heat transfer coefficient and steam heat absorption coefficient and the actual system characteristics can be evaluated.

[0071] Utilize parameter identification or optimization algorithms, such as least square method, gradient descent method or Kalman filter, to reversely adjust the heat transfer coefficient and steam heat absorption coefficient in the model according to the prediction error.

[0072] The preset conditions may be the number of training times or the error rate, etc., which are not limited here.

[0073] Step S13: determining the predicted main steam temperature of the coal-fired unit based on the fusion prediction model, and constructing an optimization objective function according to the predicted main steam temperature.

[0074] Specifically include:

[0075]

[0076] Among them, J is the function value of the optimization objective function, N P is the time domain length, T Z (x) is the predicted main steam temperature at time x, T Z (set) is the preset main steam temperature, Δu(x) is the change in the amount of desuperheating water, H Z (x) is the predicted main steam enthalpy at time x, H Z (opt) is the optimal main steam enthalpy.

[0077] During coal-fired unit operation, main steam temperature not only affects unit efficiency but also equipment safety. Optimization objective functions, serving as core optimization metrics within the Model Predictive Control (MPC) framework, are widely used in control systems. These optimization objectives are used to improve main steam temperature control accuracy, reduce control system energy consumption and equipment losses, and achieve energy efficiency optimization and intelligent management of unit operations.

[0078] Step S14: Solve the optimization objective function with preset constraints to obtain the optimization objective.

[0079] Preset constraints, including:

[0080] Desuperheating water temperature constraint: T w，l ≤T w，s ≤T w，k , where Tw，l With T w，k is the preset desuperheating water temperature, T w，s It is the real-time value of the desuperheating water temperature;

[0081] Predicted main steam temperature constraint: T Z (set)-5≤T Z (x)≤T Z (set)+5, where T Z (x) is the predicted main steam temperature at time x, T Z (set) is the preset main steam temperature;

[0082] Steam flow restriction: 100≤F s ≤200, where F s is the real-time steam flow;

[0083] Flue gas temperature constraint: 150≤T Y ≤250, where T Y is the flue gas temperature.

[0084] Based on the preset constraints, the input conditions of the fusion prediction model are constrained, and then the optimization objective function is solved (when the predicted main steam temperature constraint is not met, it means that the unit operation has failed and needs to be shut down immediately). The predicted main steam enthalpy value can be determined based on the predicted main steam temperature.

[0085] Step S15: determining the operating mode of the coal-fired unit based on the function value of the optimization target, wherein the operating mode includes a stable mode, a variable load mode, and a limit mode.

[0086] Specifically, it includes: when the function value of the optimization target is within the preset unit operating range, controlling the coal-fired unit to operate in a stable mode; or, when the function value of the optimization target is greater than the maximum value of the preset unit operating range, controlling the coal-fired unit to operate in an extreme mode; or, when the value of the optimization target is less than the minimum value of the preset unit operating range, controlling the coal-fired unit to operate in a variable load mode.

[0087] When the optimization objective function value is within the preset operating range, the main steam temperature, enthalpy and other parameters are all within the ideal range. The control system only needs to maintain the current state without frequent adjustments.

[0088] If the optimization objective function value exceeds the maximum value within the preset operating range, the current operating state deviates significantly from the ideal state. Issues such as excessive main steam temperature, excessive control action, or degraded energy quality may exist, indicating that the system is approaching safety or performance limits. Strong intervention measures can be taken to prioritize safety, such as rapidly increasing the amount of desuperheating water or limiting the rate of load increase, to prevent the system from entering the danger zone.

[0089] When the optimization objective function value is less than the minimum value of the preset operating range, it means that it is in a large dynamic change process, such as a sharp drop in load, a reduction in fuel input, etc., which leads to large fluctuations in the main steam temperature or insufficient control action. The control strategy can be adaptively adjusted to enhance the response speed and ensure that good steam parameters can be maintained during the load change process to avoid sudden temperature increases or decreases.

[0090] The preset unit operating range can be determined based on the actual situation of each unit. For example, the preset unit operating range of an 800w unit includes:

[0091] 50≤G s ≤500, where G s It is the preset unit operating range.

[0092] In summary, the main steam temperature prediction and control method based on the fusion model provided by the present invention includes: constructing a fusion prediction model based on the superheater dynamic heat transfer theory, wherein the fusion prediction model is used to predict the main steam temperature of the coal-fired unit; updating the fusion prediction model based on the historical operation data of the coal-fired unit; determining the predicted main steam temperature of the coal-fired unit based on the fusion prediction model, and constructing an optimization objective function based on the predicted main steam temperature; solving the optimization objective function with preset constraints to obtain the optimization target; determining the working mode of the coal-fired unit based on the function value of the optimization target, wherein the working mode includes a stable mode, a variable load mode, and a limit mode. The main steam temperature prediction and control method provided by the present invention integrates the superheater dynamic heat transfer theory and historical operation data, constructs and continuously updates a prediction model with a physical basis, and improves the prediction accuracy of the main steam temperature change trend. The present invention establishes an optimization objective function, comprehensively considers temperature deviation, control action amplitude and steam energy quality, and judges the operating status of the unit based on its function value, automatically switches to stable mode, variable load mode or limit mode, and realizes adaptive control under different working conditions. It not only improves the intelligence level and responsiveness of the control system, but also optimizes energy efficiency while ensuring safety, effectively copes with complex and changeable operating environments, and improves the stability and economy of coal-fired unit operation.

[0093] Based on the same inventive concept, the present invention provides Figure 2 The main steam temperature prediction control device based on the fusion model shown includes:

[0094] A model building module 21 is used to build a fusion prediction model based on the superheater dynamic heat transfer theory, wherein the fusion prediction model is used to predict the main steam temperature of the coal-fired unit;

[0095] An updating module 22 is used to update the fusion prediction model based on historical operating data of the coal-fired unit;

[0096] A function construction module 23 is used to determine the predicted main steam temperature of the coal-fired unit based on the fusion prediction model, and to construct an optimization objective function according to the predicted main steam temperature;

[0097] The optimization solution module 24 is used to solve the optimization objective function with preset constraints to obtain the optimization target;

[0098] The mode operation module 25 is used to determine the working mode of the coal-fired unit based on the optimization target, wherein the working mode includes a stable mode, a variable load mode and a limit mode.

[0099] Based on the same inventive concept, the present invention also provides an electronic device, comprising:

[0100] processor;

[0101] a memory for storing processor-executable instructions;

[0102] The processor is configured to execute to implement the main steam temperature prediction and control method based on the fusion model as provided above.

[0103] Based on the same inventive concept, the present invention also provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor of an electronic device, the electronic device is able to implement the main steam temperature prediction and control method based on the fusion model as provided above.

[0104] Since the electronic device described in this embodiment is an electronic device used to implement the information processing method in the embodiment of the present invention, based on the information processing method described in the embodiment of the present invention, those skilled in the art will be able to understand the specific implementation of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present invention will not be described in detail here. As long as the electronic device used by those skilled in the art to implement the information processing method in the embodiment of the present invention falls within the scope of protection of the present invention.

[0105] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0106] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts 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, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0107] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0109] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0110] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. The main steam temperature prediction and control method based on the fusion model is characterized by: include: Based on the superheater dynamic heat transfer theory, a fusion prediction model is constructed, wherein the fusion prediction model is used to predict the main steam temperature of the coal-fired unit; Updating the fusion prediction model based on historical operating data of the coal-fired unit; Determining a predicted main steam temperature of the coal-fired unit based on the fusion prediction model, and constructing an optimization objective function according to the predicted main steam temperature; Solving the optimization objective function with preset constraints to obtain the optimization objective; The operating mode of the coal-fired unit is determined based on the function value of the optimization target, wherein the operating mode includes a stable mode, a variable load mode and a limit mode.

2. The main steam temperature prediction and control method based on the fusion model according to claim 1 is characterized in that: Based on the superheater dynamic heat transfer theory, a fusion prediction model is constructed, including: in, Main steam temperature T Z The rate of change of x over time, α is the heat transfer coefficient, T Z is the main steam temperature, T Y is the flue gas temperature, β is the steam heat absorption coefficient, is the rate of change of steam mass flow rate.

3. The main steam temperature prediction and control method based on the fusion model according to claim 2, characterized in that: Based on the historical operating data of the coal-fired units, the fusion prediction model is updated, including: Acquiring historical operating data of the coal-fired unit, wherein the historical operating data includes fuel quantity, desuperheating water quantity, unit load, coal calorific value, and historical main steam temperature; Inputting historical operation data into the fusion prediction model to obtain the predicted main steam temperature at each moment in the history; Adjust the heat transfer coefficient and steam heat absorption coefficient based on the predicted main steam temperature at each historical moment and the historical main steam temperature at that moment; When the preset conditions are met, the latest heat transfer coefficient and steam heat absorption coefficient are saved.

4. The main steam temperature prediction and control method based on the fusion model according to claim 2 is characterized in that: The optimization objective function is constructed based on the predicted main steam temperature, including: Among them, J is the function value of the optimization objective function, N P is the time domain length, T Z (x) is the predicted main steam temperature at time x, T Z (set) is the preset main steam temperature, Δu(x) is the change in the amount of desuperheating water, H Z (x) is the predicted main steam enthalpy at time x, H Z (opt) is the optimal main steam enthalpy.

5. The main steam temperature prediction and control method based on the fusion model according to claim 1 is characterized in that: Preset constraints, including: Desuperheating water temperature constraint: T w，l ≤T w，s ≤T w，k , where T w，l With T w，k is the preset desuperheating water temperature, T w，s It is the real-time value of the desuperheating water temperature; Predicted main steam temperature constraint: T Z (set)-5≤T Z (x)≤T Z (set)+5, where T Z (x) is the predicted main steam temperature at time x, T Z (set) is the preset main steam temperature; Steam flow restriction: 100≤F s ≤200, where F S is the real-time steam flow; Flue gas temperature constraint: 150≤T Y ≤250, where T Y is the flue gas temperature.

6. The main steam temperature prediction and control method based on the fusion model according to claim 1, characterized in that: Determining the operating mode of the coal-fired unit based on the optimization target includes: When the function value of the optimization objective is within a preset unit operation range, controlling the coal-fired unit to operate in a stable mode; or, When the function value of the optimization objective is greater than the maximum value of the preset unit operation range, controlling the coal-fired unit to operate in a limit mode; or, When the value of the optimization target is less than the minimum value of the preset unit operation range, the coal-fired unit is controlled to operate in a variable load mode.

7. The main steam temperature prediction and control method based on the fusion model according to claim 6 is characterized in that: Preset unit operating range, including: 50≤G s ≤500, where G s It is the preset unit operating range.

8. The main steam temperature prediction and control device based on the fusion model is characterized by: include: A model building module, configured to build a fusion prediction model based on superheater dynamic heat transfer theory, wherein the fusion prediction model is used to predict the main steam temperature of the coal-fired unit; An updating module, configured to update the fusion prediction model based on historical operating data of the coal-fired unit; a function construction module, configured to determine the predicted main steam temperature of the coal-fired unit based on the fusion prediction model, and to construct an optimization objective function according to the predicted main steam temperature; An optimization solution module, used to solve the optimization objective function based on preset constraints to obtain an optimization target; A mode operation module is used to determine the working mode of the coal-fired unit based on the optimization target, wherein the working mode includes a stable mode, a variable load mode and a limit mode.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute to implement the main steam temperature prediction and control method based on the fusion model according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that When the instructions in the non-transitory computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to implement the main steam temperature prediction and control method based on the fusion model as described in any one of claims 1 to 7.

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