Intercooling tower shutter opening degree anti-freezing method, system, equipment and medium

Abstract

The invention discloses an indirect cooling tower shutter opening degree anti-freezing method, system and device and a medium. The method comprises the steps that shutter parameters of an indirect cooling tower are obtained; inputting the shutter parameters of the indirect cooling tower into a trained physical information neural network, and predicting to obtain temperature distribution information of a water return pipe of the indirect cooling tower and temperature distribution information in the indirect cooling tower; inputting the predicted temperature distribution information of the water return pipe of the indirect cooling tower and the predicted temperature distribution information in the indirect cooling tower into a trained DDPG model to obtain the optimal opening degree of a shutter in the shutter anti-freezing system; and the opening degree of the shutter in the shutter anti-freezing system is controlled according to the optimal opening degree of the shutter in the shutter anti-freezing system. The method, the system, the equipment and the medium can effectively achieve anti-freezing of the indirect cooling tower.

Description

Technical Field

[0001] The invention belongs to the technical field of antifreeze of louvers of inter-cooling towers, and relates to an antifreeze method, system, equipment and medium for the opening and closing degree of louvers of inter-cooling towers. Background Art

[0002] The northern region is rich in coal and short of water. Indirect air-cooling units (hereinafter referred to as units) have been widely used in thermal power units in northern my country due to their low dependence on water resources and good heat exchange performance. In the unit, the angle of the shutters can adjust the air flow in the system. By properly adjusting the opening and closing angle of the shutters, the speed and direction of the air flow can be controlled to avoid excessive concentration or stagnation of cold air and reduce the possibility of icing.

[0003] Since the north is prone to extreme weather such as severe cold and strong winds in winter, the unit is very likely to experience freezing and cracking of the heat dissipation tube bundle due to excessive heat dissipation. In serious cases, it will directly restrict the unit's power generation capacity, thereby affecting the safe operation of the unit and reducing the overall economic benefits.

[0004] As an important equipment in the industrial and construction fields, intercooler towers are particularly important for antifreeze in winter. However, the design and control strategies of traditional antifreeze systems are usually based on experience and rules, lacking a comprehensive understanding of complex systems. Even if measures such as fan inlet blocking are applied, the intercooler tower will still experience freezing of the heat dissipation tube bundle. The second is variable operating conditions. In actual operation, intercoolers are affected by changes in environmental conditions and changes in operating requirements. For example, changes in ambient temperature, humidity, and wind speed may cause changes in the performance of the shutter antifreeze system. In addition, the operating conditions of the intercooler tower may be constantly adjusted due to process requirements, seasonal changes, or other factors. Traditional static design and control strategies cannot adapt to this variability. Summary of the invention

[0005] The object of the present invention is to overcome the shortcomings of the above-mentioned prior art and to provide a method, system, device and medium for antifreezing the opening and closing degree of the shutters of an intercooling tower. The method, system, device and medium can effectively achieve antifreeze of the intercooling tower.

[0006] To achieve the above object, the present invention discloses a method for preventing freezing of the opening and closing degree of a louver of an intercooling tower, comprising:

[0007] Get the shutter parameters of the intercooler;

[0008] Inputting the shutter parameters of the intercooling tower into the trained physical information neural network to predict the return pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower;

[0009] Input the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model to obtain the optimal opening and closing degree of the blinds in the blinds antifreeze system;

[0010] The opening and closing degree of the shutters in the shutter antifreeze system is controlled according to the optimal opening and closing degree of the shutters in the shutter antifreeze system.

[0011] The further improvement of the antifreeze method of the opening and closing degree of the louver of the intercooling tower of the present invention is:

[0012] Furthermore, before inputting the shutter parameters of the intercooling tower into the trained physical information neural network, the method further includes:

[0013] Acquire a first historical data sample, the first historical data sample including the temperature distribution of the intercooling tower return pipe, the temperature distribution in the intercooling tower, and the opening and closing degree of the shutters, take the temperature distribution of the intercooling tower return pipe and the temperature distribution in the intercooling tower as the state space, take the opening and closing degree of the shutters as the action space, and use the first historical data sample to construct a first training set and a first test set;

[0014] A DDPG model is established, and the DDPG model is trained and tested using the first training set and the first test set to obtain a trained DDPG model.

[0015] Furthermore, before inputting the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model, the method further includes:

[0016] Acquire a second historical data sample, wherein the second historical data sample includes shutter parameters of an intercooling tower and corresponding temperature distribution of a return water pipe of the intercooling tower and temperature distribution information in the intercooling tower, and construct a second training set and a second test set based on the second historical data sample;

[0017] Constructing the physical information neural network;

[0018] The physical information neural network is trained and tested based on the second training set and the second test set to obtain a trained physical information neural network.

[0019] Furthermore, the physical information neural network performs physical modeling based on the heat conduction equation, and the heat conduction equation is:

[0020]

[0021] Where ρ is the density of the material, c p is the specific heat capacity of the material, T is the temperature, t is the time, k is the thermal conductivity, and Q is the heat source term.

[0022] The invention discloses an antifreeze system for the opening and closing degree of a louver of an intercooling tower, comprising:

[0023] The first acquisition module is used to obtain the shutter parameters of the intercooler;

[0024] A prediction module, used for inputting the shutter parameters of the intercooling tower into the trained physical information neural network, and predicting the return pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower;

[0025] A calculation module, used for inputting the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model to obtain the optimal opening and closing degree of the shutters in the shutter antifreeze system;

[0026] A control module is used to control the opening and closing degree of the shutters in the shutter antifreeze system according to the optimal opening and closing degree of the shutters in the shutter antifreeze system.

[0027] The further improvement of the intercooling tower shutter opening and closing degree antifreeze system of the present invention is:

[0028] Furthermore, it also includes:

[0029] A second acquisition module is used to acquire a first historical data sample, wherein the first historical data sample includes a temperature distribution of a return pipe of an intercooling tower, a temperature distribution in the intercooling tower, and an opening degree of a louver, and the temperature distribution of the return pipe of the intercooling tower and the temperature distribution in the intercooling tower are used as a state space, and the opening degree of the louver is used as an action space, and the first historical data sample is used to construct a first training set and a first test set;

[0030] The first training module is used to establish a DDPG model, train and test the DDPG model through the first training set and the first test set to obtain a trained DDPG model.

[0031] Furthermore, it also includes:

[0032] A third acquisition module is used to acquire a second historical data sample, wherein the second historical data sample includes the shutter parameters of the intercooling tower and the corresponding temperature distribution of the return pipe of the intercooling tower and the temperature distribution information in the intercooling tower, and construct a second training set and a second test set based on the second historical data sample;

[0033] A construction module, used to construct the physical information neural network;

[0034] The second training module is used to train and test the physical information neural network based on a second training set and a second test set to obtain a trained physical information neural network.

[0035] Furthermore, the physical information neural network performs physical modeling based on the heat conduction equation, and the heat conduction equation is:

[0036]

[0037] Where ρ is the density of the material, c p is the specific heat capacity of the material, T is the temperature, t is the time, k is the thermal conductivity, and Q is the heat source term.

[0038] The present invention discloses a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the intercooling tower shutter opening degree anti-freezing method are implemented.

[0039] The present invention discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the intercooling tower shutter opening and closing degree anti-freezing method are implemented.

[0040] The present invention has the following beneficial effects:

[0041] The intercooling tower shutter opening and closing degree antifreeze method, system, equipment and medium described in the present invention predict the optimal opening and closing degree of the shutters in the shutter antifreeze system based on the physical information neural network and the DDPG model during specific operation, and control the shutter antifreeze system accordingly. The intercooling tower system is protected from freezing by the shutter antifreeze system to achieve the best antifreeze effect, reduce the possibility of icing, ensure the normal operation of the intercooling tower in cold weather, and avoid icing affecting its function. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0043] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0046] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0047] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. 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 the present invention generally indicates that the associated objects are in an "or" relationship.

[0048] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0049] The word "if" as used herein 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.

[0050] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0051] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0052] Embodiment 1

[0053] refer to Figure 1 The method for preventing freezing of the shutter opening and closing degree of the intercooling tower of the present invention comprises the following steps:

[0054] 1) Obtain the shutter parameters of the indirect cooling tower;

[0055] 2) inputting the shutter parameters of the intercooling tower into the trained physical information neural network to predict the return pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower;

[0056] 3) The predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower are input into the trained DDPG model to obtain the optimal opening and closing degree of the blinds in the blinds antifreeze system.

[0057] 4) Controlling the opening and closing degree of the blinds in the blinds antifreeze system according to the optimal opening and closing degree of the blinds in the blinds antifreeze system.

[0058] In this embodiment, the training process of the DDPG model is:

[0059] 31) obtaining a first historical data sample, wherein the first historical data sample includes a temperature distribution of a return pipe of an intercooling tower, a temperature distribution in a tower, and a shutter opening degree, taking the temperature distribution of the return pipe of the intercooling tower and the temperature distribution in the tower as a state space, taking the shutter opening degree as an action space, and using the first historical data sample to construct a first training set and a first test set;

[0060] 32) Establishing a DDPG model, training and testing the DDPG model using the first training set and the first test set to obtain a trained DDPG model.

[0061] It should be noted that the DDPG model is an Actor-Critic structure, in which the Actor network is responsible for learning the antifreeze optimization strategy and outputting the action of the blinds parameters; the Critic network is responsible for learning the value function and evaluating the value of the current state and action.

[0062] In this embodiment, the training process of the physical information neural network is:

[0063] 21) obtaining a second historical data sample, wherein the second historical data sample includes shutter parameters of an intercooling tower and corresponding temperature distribution of a return pipe of the intercooling tower and temperature distribution information in the intercooling tower, and constructing a second training set and a second test set based on the second historical data sample;

[0064] 22) constructing the physical information neural network, wherein the physical information neural network performs physical modeling based on the heat conduction equation, wherein the heat conduction equation is:

[0065]

[0066] Where ρ is the density of the material, c p is the specific heat capacity of the material, T is the temperature, t is the time, k is the thermal conductivity, and Q is the heat source term.

[0067] 23) Training the physical information neural network based on the training set and the test set to obtain a trained physical information neural network.

[0068] It should be noted that the present invention makes a judgment based on the predicted return pipe temperature distribution and the temperature distribution in the tower. When the return pipe temperature environment is at a low temperature, it is necessary to reduce the opening and closing degree of the shutters of the shutter antifreeze system to reduce the heat loss in the tower to provide a sufficient antifreeze effect. When the return pipe temperature environment is at a high temperature, it is necessary to increase the opening and closing degree of the shutters to prevent the return pipe temperature from being too high, resulting in a decrease in the efficiency of the system; for areas where the return pipe temperature is unevenly distributed, the opening and closing degree of the shutters in each sector is adjusted to achieve the best temperature regulation effect. When the temperature in the tower is at a low temperature, the opening and closing degree of the shutters of the shutter antifreeze system is adjusted to reduce the heat loss in the tower to provide a sufficient antifreeze effect. When the temperature in the tower is at a high temperature, it is necessary to increase the opening and closing degree of the shutters to prevent the temperature in the tower from overheating and increasing energy consumption.

[0069] The present invention is based on the physical information neural network and the DDPG model to predict the optimal opening and closing degree of the blinds in the blinds antifreeze system, and control the blinds antifreeze system to perform antifreeze protection on the intercooling tower system through the blinds antifreeze system. According to the real-time monitoring data and the changes in operating conditions, the parameters and control strategies of the blinds antifreeze system are automatically adjusted to achieve the best antifreeze effect, reduce the possibility of icing, ensure that the intercooling tower operates normally in cold weather, and avoid icing affecting its function. At the same time, it can not only reduce maintenance costs and operating costs, but also reduce energy consumption, thereby reducing energy expenses and enhancing the competitiveness of enterprises. Reducing energy consumption will also be beneficial to reducing environmental pollution and reducing carbon emissions, and have a positive impact on the sustainable development of the environment. Antifreeze protection measures are not only for protecting equipment, but also for achieving energy conservation and emission reduction and promoting the goal of sustainable development.

[0070] Embodiment 2

[0071] The intercooling tower shutter opening and closing degree antifreeze system of the present invention comprises:

[0072] The first acquisition module is used to obtain the shutter parameters of the intercooler;

[0073] A prediction module, used for inputting the shutter parameters of the intercooling tower into the trained physical information neural network, and predicting the return pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower;

[0074] A calculation module, used for inputting the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model to obtain the optimal opening and closing degree of the shutters in the shutter antifreeze system;

[0075] A control module is used to control the opening and closing degree of the shutters in the shutter antifreeze system according to the optimal opening and closing degree of the shutters in the shutter antifreeze system.

[0076] In this embodiment, it also includes:

[0077] A second acquisition module is used to acquire a first historical data sample, wherein the first historical data sample includes a temperature distribution of a return pipe of an intercooling tower, a temperature distribution in the intercooling tower, and an opening degree of a louver, and the temperature distribution of the return pipe of the intercooling tower and the temperature distribution in the intercooling tower are used as a state space, and the opening degree of the louver is used as an action space, and the first historical data sample is used to construct a first training set and a first test set;

[0078] The first training module is used to establish a DDPG model, train and test the DDPG model through the first training set and the first test set to obtain a trained DDPG model.

[0079] In this embodiment, it also includes:

[0080] A third acquisition module is used to acquire a second historical data sample, wherein the second historical data sample includes the shutter parameters of the intercooling tower and the corresponding temperature distribution of the return pipe of the intercooling tower and the temperature distribution information in the intercooling tower, and construct a second training set and a second test set based on the second historical data sample;

[0081] A construction module, used to construct the physical information neural network;

[0082] The second training module is used to train and test the physical information neural network based on a second training set and a second test set to obtain a trained physical information neural network.

[0083] In this embodiment, the physical information neural network performs physical modeling based on the heat conduction equation, and the heat conduction equation is:

[0084]

[0085] Where ρ is the density of the material, c p is the specific heat capacity of the material, T is the temperature, t is the time, k is the thermal conductivity, and Q is the heat source term.

[0086] The division of modules in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present application may be integrated into a processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0087] Embodiment 3

[0088] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the intercooling tower shutter opening degree antifreeze method are implemented, for example, comprising: obtaining the shutter parameters of the intercooling tower; inputting the shutter parameters of the intercooling tower into a trained physical information neural network to predict the return pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower; inputting the predicted return pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into a trained DDPG model to obtain the optimal opening degree of the shutter in the shutter antifreeze system; and controlling the opening degree of the shutter in the shutter antifreeze system according to the optimal opening degree of the shutter in the shutter antifreeze system. The memory may include a memory, such as a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk memory, etc. The processor, network interface, and memory are interconnected through an internal bus, and the internal bus may be an industrial standard architecture bus, a peripheral component interconnection standard bus, an extended industrial standard architecture bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program may include a program code, and the program code includes computer operation instructions. The memory may include a memory and a non-volatile memory, and provide instructions and data to the processor.

[0089] Embodiment 4

[0090] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of implementing the intercooling tower shutter opening and closing antifreeze method, for example, include: obtaining the shutter parameters of the intercooling tower; inputting the shutter parameters of the intercooling tower into the trained physical information neural network, predicting the return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower; inputting the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model, and obtaining the optimal opening and closing degree of the shutter in the shutter antifreeze system; controlling the opening and closing degree of the shutter in the shutter antifreeze system according to the optimal opening and closing degree of the shutter in the shutter antifreeze system. Specifically, the computer-readable storage medium includes, but is not limited to, for example, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0091] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0092] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, 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 generate 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 flowchart and / or block diagram. 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.

[0093] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate 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 A function specified in one or more boxes.

[0094] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0095] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and disclosure of the invention. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0096] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

[0097] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any simple modification, change and equivalent structural change made to the above embodiment based on the technical essence of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for preventing freezing of the shutter opening and closing degree of an indirect cooling tower, characterized in that: include: Get the shutter parameters of the intercooler; Inputting the shutter parameters of the intercooling tower into the trained physical information neural network to predict the return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower; Input the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model to obtain the optimal opening and closing degree of the blinds in the blinds antifreeze system; The opening and closing degree of the shutters in the shutter antifreeze system is controlled according to the optimal opening and closing degree of the shutters in the shutter antifreeze system.

2. The method for preventing freezing of shutter opening and closing degree of intercooling tower according to claim 1, characterized in that: Before inputting the shutter parameters of the intercooling tower into the trained physical information neural network, the method further includes: Acquire a first historical data sample, the first historical data sample including the temperature distribution of the intercooling tower return pipe, the temperature distribution in the intercooling tower, and the opening and closing degree of the shutters, take the temperature distribution of the intercooling tower return pipe and the temperature distribution in the intercooling tower as the state space, take the opening and closing degree of the shutters as the action space, and use the first historical data sample to construct a first training set and a first test set; A DDPG model is established, and the DDPG model is trained and tested using the first training set and the first test set to obtain a trained DDPG model.

3. The method for preventing freezing of shutter opening and closing degree of intercooling tower according to claim 1, characterized in that: Before inputting the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model, the method further includes: Acquire a second historical data sample, wherein the second historical data sample includes shutter parameters of an intercooling tower and corresponding temperature distribution of a return water pipe of the intercooling tower and temperature distribution information in the intercooling tower, and construct a second training set and a second test set based on the second historical data sample; Constructing the physical information neural network; The physical information neural network is trained and tested based on the second training set and the second test set to obtain a trained physical information neural network.

4. The method for preventing freezing of shutter opening degree of intercooling tower according to claim 2, characterized in that: The physical information neural network performs physical modeling based on the heat conduction equation, which is: Where ρ is the density of the material, c p is the specific heat capacity of the material, T is the temperature, t is the time, k is the thermal conductivity, and Q is the heat source term.

5. An antifreeze system for the opening and closing degree of the shutters of an indirect cooling tower, characterized in that: include: The first acquisition module is used to obtain the shutter parameters of the intercooler; A prediction module, used for inputting the shutter parameters of the intercooling tower into the trained physical information neural network, and predicting the return pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower; A calculation module, used for inputting the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model to obtain the optimal opening and closing degree of the shutters in the shutter antifreeze system; A control module is used to control the opening and closing degree of the shutters in the shutter antifreeze system according to the optimal opening and closing degree of the shutters in the shutter antifreeze system.

6. The intercooling tower shutter opening and closing degree antifreeze system according to claim 5, characterized in that: Before inputting the shutter parameters of the intercooling tower into the trained physical information neural network, the method further includes: A second acquisition module is used to acquire a first historical data sample, wherein the first historical data sample includes a temperature distribution of a return pipe of an intercooling tower, a temperature distribution in the intercooling tower, and an opening degree of a louver, and the temperature distribution of the return pipe of the intercooling tower and the temperature distribution in the intercooling tower are used as a state space, and the opening degree of the louver is used as an action space, and the first historical data sample is used to construct a first training set and a first test set; The first training module is used to establish a DDPG model, train and test the DDPG model through the first training set and the first test set to obtain a trained DDPG model.

7. The intercooling tower shutter opening and closing degree antifreeze system according to claim 5, characterized in that: Before inputting the predicted return water pipe temperature distribution of the intercooling tower and the temperature distribution information in the intercooling tower into the trained DDPG model, the method further includes: A third acquisition module is used to acquire a second historical data sample, wherein the second historical data sample includes the shutter parameters of the intercooling tower and the corresponding temperature distribution of the return pipe of the intercooling tower and the temperature distribution information in the intercooling tower, and construct a second training set and a second test set based on the second historical data sample; A construction module, used to construct the physical information neural network; The second training module is used to train and test the physical information neural network based on a second training set and a second test set to obtain a trained physical information neural network.

8. The intercooling tower shutter opening and closing degree antifreeze system according to claim 7, characterized in that: The physical information neural network performs physical modeling based on the heat conduction equation, which is: Where ρ is the density of the material, c p is the specific heat capacity of the material, T is the temperature, t is the time, k is the thermal conductivity, and Q is the heat source term.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the intercooling tower shutter opening degree anti-freezing method as described in any one of claims 1-4 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the intercooling tower shutter opening degree anti-freezing method as described in any one of claims 1-4 are implemented.

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