An automatic energy-saving control method and device for a refrigeration system

Abstract

The application relates to the technical field of refrigeration control, and discloses an automatic energy-saving control method and device for a refrigeration system, which comprises the following steps: generating a target space model for a target space, judging whether the current distribution of refrigeration equipment can improve the cooling efficiency, simulating and generating a plurality of refrigeration schemes, determining an optimal cooling scheme according to user habits, and controlling the refrigeration equipment to operate with corresponding parameters, the automatic energy-saving control method and device for the refrigeration system can quickly reduce indoor temperature to a target temperature, minimize energy consumption on the premise of meeting the cooling demand, avoid direct blowing of cold air, consider user habits and body feeling, realize automatic and intelligent control of the refrigeration equipment through three-dimensional grid modeling, airflow and temperature field simulation, and equipment operation strategy optimization, avoid invalid refrigeration, and reduce energy consumption.

Description

Technical Field

[0001] This invention relates to the field of refrigeration control technology, specifically to an automated energy-saving control method and device for a refrigeration system. Background Technology

[0002] Refrigeration systems are widely used in air conditioning, refrigeration, freezing, and industrial cooling. Their main function is to reduce the temperature of a space by controlling the circulation of refrigerant. A typical refrigeration system includes a compressor, condenser, expansion valve (or throttle valve), evaporator, and various sensors and control devices. With the increasing energy crisis and environmental protection requirements, energy conservation has become an important development direction for refrigeration systems. In order to achieve intelligent, efficient, and energy-saving control goals, researchers have gradually introduced automated control, intelligent algorithms, and information technology to develop various advanced control methods. Therefore, automated energy-saving control methods and devices for refrigeration systems are of great significance in improving energy efficiency, reducing operating costs, and protecting the environment. By introducing advanced control theories, intelligent algorithms, and information technology, refrigeration control systems are developing towards intelligence, optimization, and greening, bringing broad application prospects to related industries.

[0003] Existing automated energy-saving control methods and devices for refrigeration systems cannot simulate and generate space based on indoor conditions, analyze airflow under the current spatial layout and distribution of refrigeration equipment, analyze the impact of the current spatial layout, object distribution, and refrigeration equipment distribution on the energy consumption and cooling time of the refrigeration equipment, and cannot simulate and generate several different refrigeration schemes and determine the optimal cooling scheme according to user habits, such as not being able to accept direct cold air. This can easily lead to energy waste, reduce user experience, and affect user health, thus its practicality has certain limitations. Summary of the Invention

[0004] This invention provides an automated energy-saving control method and apparatus for a refrigeration system, which helps to solve the problems mentioned in the background art.

[0005] This invention provides the following technical solution: an automated energy-saving control method for a refrigeration system, comprising:

[0006] Obtain the target space;

[0007] Generate a target space model from the target space;

[0008] Based on the target space model, determine whether the current distribution of refrigeration equipment can improve cooling efficiency;

[0009] If it is determined that the current distribution of refrigeration equipment can improve the cooling efficiency, then multi-equipment refrigeration simulation analysis and comprehensive refrigeration simulation analysis are performed on the indoor refrigeration equipment in sequence to generate multi-equipment refrigeration schemes and comprehensive refrigeration schemes respectively, and generate the first scheme set.

[0010] If it is determined that the current distribution of refrigeration equipment cannot improve the cooling efficiency, then the indoor refrigeration equipment is subjected to single-equipment refrigeration simulation analysis, multi-equipment refrigeration simulation analysis and comprehensive refrigeration simulation analysis in sequence, generating single-equipment refrigeration scheme, multi-equipment refrigeration scheme and comprehensive refrigeration scheme respectively, generating a second scheme set;

[0011] Obtain user usage habits;

[0012] Based on the first or second set of solutions, and combined with user habits, the best cooling solution is determined through comparative analysis of the solutions.

[0013] Based on the optimal cooling scheme, control the refrigeration equipment to operate with the corresponding parameters.

[0014] As an automated energy-saving control method for a refrigeration system according to the present invention, wherein: generating a target space model for a target space specifically involves: obtaining first layout information within the target space, denoted as... : ; among which, each first layout It can be represented as ; Obtain the second layout information within the target space, denoted as : ; among which, each second layout It can be represented as ; Obtain the third layout information within the target space, denoted as : ; among them, each third layout It can be represented as ; Obtain the fourth layout information within the target space, denoted as : ; among them, each fourth layout It can be represented as ; Obtain all refrigeration equipment within the target space, forming an equipment set, denoted as . : For each device Obtain its three-dimensional coordinate position: For each device To obtain its parameter information: ;in, The cooling capacity of the refrigeration equipment. The air volume supplied by the refrigeration equipment. The power of the refrigeration equipment, The air supply angle of the refrigeration equipment is as follows: ;in, This refers to the range of horizontal air supply angles. This refers to the range of vertical air supply angles; where... The fan speed settings for the refrigeration equipment are as follows: ;in, For the first Wind speed setting; for each device Get its current running status: ;in, To indicate whether the refrigeration equipment is on or off, mark it as... , The current set temperature of the refrigeration equipment. The current fan speed setting of the cooling equipment is marked as follows. ; Obtain the distribution information of all indoor items within the target space, forming an indoor item distribution set, denoted as: For each item Get its item attributes: Integrate the first, second, third, and fourth layout information within the target space to generate an initial spatial model, denoted as... : ; among them, each structure Each is represented as a three-dimensional geometric object, containing attributes such as its position, size, shape, and material; the initial spatial model The space is divided into uniform grids according to a given resolution, forming an initial gridded space. : ;in, To adjust a 3D spatial model according to resolution , , Functions that divide into grids , , These are the mesh dimensions in the x, y, and z directions, respectively; based on the device set and the initial meshing space. Forming a grid space for equipment : For device grid space Each device in Analyze its scope of influence. : ;in, This indicates that the air supply angle constraint is met. The air supply angle constraint means that only grids within the air supply angle range of the equipment are included in the influence range. For equipment Maximum effective radius of action; based on the distribution set of indoor items and equipment grid space. To form an indoor grid space : For indoor grid spaces Each item in Analyze its airflow properties : ;in, It is the original airflow velocity. It is an airflow resistance function;

[0015] According to indoor grid space and initial space model Update and generate the target space model.

[0016] As an automated energy-saving control method for a refrigeration system according to the present invention, the method for determining whether the current distribution of refrigeration equipment can improve cooling efficiency specifically involves calculating the average velocity of the initial airflow velocity field in the target space when no equipment is operating. For each device within the target space Within its air supply angle range Inside, several air supply directions are evenly selected. : ;in, The angle step size; for each direction The airflow velocity distribution of the device in this direction is determined using an airflow simulation function. ;in, It is a three-dimensional vector field representing the airflow velocity distribution of the device in this direction; calculate the average airflow velocity of the device in this direction: ;in, This represents the magnitude of the airflow velocity vector at that grid point. It represents the total number of grid cells; for each device within the target space. Calculate its maximum airflow lift rate: Define an efficiency determination function to determine whether the current distribution of refrigeration equipment can improve cooling efficiency: ;in, To increase the threshold, This indicates that there exists any device that satisfies the following in a certain direction. ;like If so, it is determined that the current distribution of refrigeration equipment can improve cooling efficiency; If the current distribution of refrigeration equipment fails to improve cooling efficiency, then it is determined that the current distribution of refrigeration equipment cannot improve cooling efficiency.

[0017] As an automated energy-saving control method for a refrigeration system according to the present invention, the single-device refrigeration simulation analysis specifically involves: obtaining a set of devices. For each device Set the parameter combination for simulation operation: In parameter combinations, From All wind speed settings selected in the program. From the angle range The selected typical wind directions are as follows: In parameter combinations, The outlet air temperature selected from the set of temperatures is specifically as follows: In parameter combinations, The wind force is estimated based on wind speed and air volume, specifically: ;in, air density, For the air supply volume of the equipment; for each combination of equipment operating parameters Set up an airflow simulation function to simulate and calculate the airflow velocity field generated in the indoor space: In the airflow simulation function, Indicates on the path, This is the wind speed setting. The unit direction vector is specifically: In the airflow simulation function, The distance from the grid point to the device is specifically: In the airflow simulation function, The distance decay function is as follows: In the airflow simulation function, The angle deviation factor is as follows: In the airflow simulation function, The obstacle blocking factor is as follows: For each set of equipment operating parameter combinations Set up a temperature simulation function to simulate and calculate the temperature field it generates in the indoor space: In the temperature simulation function, This indicates that the area is within the equipment's influence range. For the heat convection term, specifically: In the temperature simulation function, For heat conduction, specifically: ;in, The thermal diffusivity; in the temperature simulation function, The term is for thermal radiation, specifically: Based on spatial layout and object distribution, identify areas that are far from equipment or obstructed, forming a set of difficult areas: ; in each region Several data collection points are set up in the middle. For each region For each collection point, acquire the collection point data: ;in, The location of the collection point is marked as , The temperature at the sampling point, For user accessibility of the collection point, For collection points and equipment The distance between them is as follows: Among all user-reachable data collection points, select the point furthest from the device and designate it as the user's farthest point, denoted as: Collect the temperature at the farthest point from the user, define it as the farthest temperature from the user, and denot it as: Among all data collection points, select the point farthest from the device and designate it as the physical farthest point, denoted as: Collect the temperature at the physical farthest point, define it as the physical farthest temperature, and denot it as: Define a point analysis function to determine the analysis and data collection points: Simulate equipment operation, record and analyze data collection points. Temperature from initial temperature Reduced to target temperature The required time is defined as the simulation duration: Simulate equipment operation and calculate and analyze data collection points. Temperature from initial temperature Reduced to target temperature The energy consumption corresponding to that time is defined as the simulated energy consumption: Obtain all simulation schemes and form a single simulation set: Obtain user preference data: ;like Therefore, the single-equipment cooling scheme is determined as follows: ;like Therefore, the single-equipment cooling scheme is determined as follows: .

[0018] As an automated energy-saving control method for a refrigeration system according to the present invention, the multi-device refrigeration simulation analysis specifically involves: obtaining a set of devices. Generate all possible device combinations: For each combination Set different operating modes to generate a set of all possible operating modes: For each device Set parameters according to its operating mode; for each combination and operating mode For each device Based on its operating status, the airflow velocity field generated by a single device in an indoor space is simulated and calculated using an airflow simulation function: ;in, For wind direction, For wind speed; for each combination and operating mode The airflow fields of all devices are weighted and superimposed to calculate the overall airflow velocity field generated in the indoor space: ;in, For device weights, specifically , The obstacle blocking factor is specifically... Get combinations The number of devices in cooling mode is defined as the cooling quantity; if the cooling quantity is ≥1, a temperature field simulation is performed to simulate the overall temperature field generated in the indoor space: ;in, The temperature update function has the following formula: In the temperature update function, For the heat convection term, specifically: In the temperature update function, For heat conduction, specifically: ;in, Here is the thermal diffusivity; in the temperature update function, The term is for thermal radiation, specifically: ;in, For emission rate, The Stefan-Boltzmann constant is... The surface temperature of the object; based on the spatial layout and distribution of objects, identify areas far from the equipment and those that are obstructed, forming a set of difficult areas: ; in each region Several data collection points are set up in the middle. For each region At each sampling point, the temperature change process is recorded and denoted as... For each combination and operating mode The simulation device operates, recording the temperature at all sampling points from the initial temperature. Reduced to target temperature The required time is defined as the simulation duration: For each combination and operating mode The simulation device operates, recording the temperature at all sampling points from the initial temperature. Reduced to target temperature The energy consumption corresponding to that time is defined as the simulated energy consumption: Obtain all simulation schemes to form a multi-simulation set: Obtain user preference data: ;like Therefore, the multi-device cooling solution is determined as follows: ;like Therefore, the multi-device cooling solution is determined as follows: .

[0019] As an automated energy-saving control method for a refrigeration system according to the present invention, the comprehensive refrigeration simulation analysis specifically involves: obtaining the temperature of the air output by the refrigeration equipment in the air supply mode, and defining it as the air supply temperature. The temperature of the air output by the refrigeration equipment in refrigeration mode is obtained and defined as the refrigeration temperature. Define an analysis selection function to determine the simulation analysis to be performed under the current indoor and outdoor temperatures: ;like Then, perform multi-device cooling simulation analysis, and extract the corresponding multi-device cooling scheme as the comprehensive cooling scheme, considering only combinations without air supply modes; if Then, perform a single-device cooling simulation analysis to extract the corresponding single-device cooling solution: Perform multi-device cooling simulation analysis, and extract the corresponding multi-device cooling scheme considering only combinations without air supply modes: Set up a scheme selection function to select the scheme with the lowest energy consumption as the overall cooling scheme: As an automated energy-saving control method for a refrigeration system according to the present invention, the scheme comparison analysis specifically involves: obtaining a first scheme set or a second scheme set, and defining it as the target analysis set. For each solution within the target analysis set Extract its solution information: ;in, To simulate duration, To simulate energy consumption, For wind direction; to obtain user usage habits: ;like Then the human body location is obtained and denoted as Define a wind direction analysis function to determine the plan. Will it cause cold air to blow directly on the body? ;in, Wind direction Vector from device to human body included angle For the set included angle threshold, The specific formula is: ;like Then determine the scheme This can cause cold air to blow directly on the body; if Then determine the scheme It will not cause cold air to blow directly on the human body; regarding the solution Perform a matching analysis; extract the solution with the highest matching degree as the optimal cooling solution.

[0020] As an automated energy-saving control method for a refrigeration system according to the present invention, wherein: for the scheme To perform matching analysis, specifically: define a solution evaluation function to determine whether it is necessary to calculate the matching degree of the solutions. ;like In this case, there is no need to calculate the matching degree of the solution; the matching degree of the solution can be directly determined. ;like Then calculate the maximum cooling time among all schemes in the target analysis set: ; Calculate the maximum energy consumption among all schemes in the target analysis set: For each option in the target analysis set Calculate the normalized cooling time score: For each option in the target analysis set Calculate the normalized energy consumption score: ; Obtaining user preferences ;like Then the weight set is set as ;like Then the weight set is set as For each option in the target analysis set Calculate the degree of match between it and user habits: .

[0021] The present invention also discloses an apparatus for implementing an automated energy-saving control method for a refrigeration system, comprising:

[0022] Data acquisition module: used to collect spatial layout information, distribution location and parameter information of refrigeration equipment, and distribution information of indoor items within the target space;

[0023] Model generation module: used to generate a target space model of the target space based on the collected spatial layout information, distribution location and equipment parameter information of the refrigeration equipment, and distribution information of indoor items within the target space;

[0024] Simulation analysis module: used to perform various cooling simulation analyses on the target space, generate different cooling schemes, and analyze and determine the most suitable optimal cooling scheme;

[0025] Data analysis module: used to compare and analyze different generated cooling solutions to determine the most suitable and optimal cooling solution;

[0026] Equipment control module: Used to control the refrigeration equipment in the target space to operate with corresponding parameters according to the optimal cooling scheme, so that the target space is cooled to the required temperature.

[0027] The present invention has the following beneficial effects:

[0028] 1. The automated energy-saving control method and device for the refrigeration system generates an indoor space model by acquiring the indoor spatial layout, including the layout of walls, windows, etc., the distribution of all indoor refrigeration equipment, and the distribution of all indoor items. This provides an accurate spatial structural basis, clarifies the influence range of equipment and the distribution of obstacles, and improves the accuracy of the simulation.

[0029] 2. The automated energy-saving control method and device for this refrigeration system, when the indoor temperature needs to be lowered by refrigeration equipment, determines whether the distribution of all indoor refrigeration equipment can improve cooling efficiency. If it cannot improve cooling efficiency, single-equipment refrigeration simulation analysis, multi-equipment refrigeration simulation analysis, and comprehensive refrigeration simulation analysis based on indoor and outdoor environmental data are performed on the indoor refrigeration equipment. Based on user habits, the most suitable refrigeration scheme is selected as the optimal cooling scheme. According to the optimal cooling scheme, the operation of the refrigeration equipment is controlled to achieve closed-loop control, dynamically adapt to environmental changes, avoid ineffective equipment combinations, and improve simulation efficiency. Single-equipment simulation analysis can still find the optimal operating strategy when the equipment distribution is poor. Multi-equipment simulation analysis fully leverages the synergistic effect. Comprehensive simulation analysis, combined with environmental temperature difference, further improves energy-saving effect. At the same time, user preferences, user habits, and physical sensations are considered to enhance personalized experience and satisfaction.

[0030] 3. The automated energy-saving control method and device for this refrigeration system, when the indoor temperature needs to be lowered by refrigeration equipment, if the refrigeration efficiency can be improved, multi-device refrigeration simulation analysis is performed on the indoor refrigeration equipment, and comprehensive refrigeration simulation analysis is performed on the indoor refrigeration equipment based on indoor and outdoor environmental data. According to user habits, the most suitable refrigeration scheme is selected as the optimal cooling scheme. Based on the optimal cooling scheme, the operation of the refrigeration equipment is controlled to achieve closed-loop control, dynamically adapt to environmental changes, avoid ineffective equipment combinations, and improve simulation efficiency. When the equipment is well distributed, the multi-device simulation analysis fully leverages the synergistic effect. The comprehensive simulation analysis, combined with the ambient temperature difference, further improves the energy-saving effect. At the same time, user preferences are considered to avoid direct cold air blowing, improve user habits, enhance physical comfort, and improve personalized experience and satisfaction. Under the premise of meeting the cooling needs, energy consumption is minimized, direct cold air blowing is avoided, and user habits and physical comfort are considered. Through three-dimensional mesh modeling, airflow and temperature field simulation, and equipment operation strategy optimization, automated and intelligent control of the refrigeration equipment is achieved. Attached Figure Description

[0031] Figure 1 This is a flowchart of the automated energy-saving control method for the refrigeration system of the present invention;

[0032] Figure 2 This is a block diagram of the apparatus for implementing the automated energy-saving control method of the refrigeration system according to the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Example 1: An automated energy-saving control method for a refrigeration system, see reference. Figure 1 ,include:

[0035] Obtain the target space;

[0036] Generate a target space model from the target space;

[0037] Based on the target space model, determine whether the current distribution of refrigeration equipment can improve cooling efficiency;

[0038] If it is determined that the current distribution of refrigeration equipment can improve the cooling efficiency, then multi-equipment refrigeration simulation analysis and comprehensive refrigeration simulation analysis are performed on the indoor refrigeration equipment in sequence to generate multi-equipment refrigeration schemes and comprehensive refrigeration schemes respectively, and generate the first scheme set.

[0039] If it is determined that the current distribution of refrigeration equipment cannot improve the cooling efficiency, then the indoor refrigeration equipment is subjected to single-equipment refrigeration simulation analysis, multi-equipment refrigeration simulation analysis and comprehensive refrigeration simulation analysis in sequence, generating single-equipment refrigeration scheme, multi-equipment refrigeration scheme and comprehensive refrigeration scheme respectively, generating a second scheme set;

[0040] Obtain user usage habits;

[0041] Based on the first or second set of solutions, and combined with user habits, the best cooling solution is determined through comparative analysis of the solutions.

[0042] Based on the optimal cooling scheme, control the refrigeration equipment to operate with the corresponding parameters.

[0043] Specifically, generating a target space model for the target space involves:

[0044] Obtain the first layout information within the target space, where the first layout information is the wall layout information, denoted as... : ;

[0045] Among them, each first layout It can be represented as: ;

[0046] in, The location of the wall is indicated by using three-dimensional coordinates to represent the start and end points of the wall, for example... , The dimensions of the wall are expressed in terms of length, width, and height, for example... , The wall material is represented by a string, for example... ;

[0047] Obtain the second layout information within the target space, where the second layout information is the window layout information, denoted as... : ;

[0048] Among them, each second layout It can be represented as: ;

[0049] in, The window position is indicated by using three-dimensional coordinates to represent the center position of the window, for example... , Window dimensions are indicated by their width and height, for example... , The window type is represented by a string, for example... , Indicates the direction a window faces, specifically expressed in angles, for example... (0° north, clockwise direction);

[0050] Obtain the third layout information within the target space, wherein the third layout information is the door layout information, denoted as... : ;

[0051] Each third layout It can be represented as: ;

[0052] in, The position of the door is indicated, specifically by using three-dimensional coordinates to represent the center position of the door, for example... , The dimensions of the door are indicated, specifically by its width and height, for example... , The gate type is represented by a string, for example... ;

[0053] Obtain the fourth layout information within the target space. This fourth layout information is fixed structural layout information, such as columns and beams, denoted as... : ;

[0054] Each fourth layout It can be represented as: ;

[0055] in, To indicate the position of a fixed structure, specifically, to represent the center position of the fixed structure using three-dimensional coordinates, for example... , This indicates fixed structural dimensions, specifically expressed as length, width, and height, for example... ;

[0056] Acquire all refrigeration devices within the target space, forming a device set, denoted as . :

[0057] ;

[0058] For each device By using indoor positioning technologies such as UWB, Bluetooth beacons, RFID, or equipment installation drawings, the three-dimensional coordinates of the equipment indoors can be accurately obtained.

[0059] ;

[0060] For each device To obtain its parameter information, the equipment parameter information is usually provided by the equipment manufacturer and stored in the equipment database or on the equipment nameplate. It can be obtained by reading the equipment database or scanning the equipment nameplate. ;in, This refers to the cooling capacity of the refrigeration equipment, i.e., the rated cooling capacity of the equipment. This refers to the air supply volume of the refrigeration equipment, i.e., the rated air supply volume of the equipment. This refers to the power of the refrigeration equipment, i.e., the rated power of the equipment. The air supply angle of the refrigeration equipment is as follows: ;in, This refers to the range of horizontal air supply angles. The range of vertical air supply angles;

[0061] in, The fan speed settings for the refrigeration equipment are as follows: ;in, For the first Wind speed setting;

[0062] For each device This allows for the acquisition of the device's current operating status. The device's operating status information is obtained in real time through its own control system or sensors, such as through the smart control panel of an air conditioner or a smart home system. ;in, To indicate whether the refrigeration equipment is on or off, mark it as... , The current set temperature of the refrigeration equipment. The current fan speed setting of the cooling equipment is marked as follows. ;

[0063] Obtain the distribution information of all indoor items within the target space, forming an indoor item distribution set, denoted as: ;

[0064] For each item Get its item attributes: ;in, Let the three-dimensional coordinates of the object within the room be denoted as . , The dimensions of the item are denoted as . ,in, Indicates the length of an item, Indicates the width of the item. Indicates the height of an item. The geometric shape type of the item is denoted as... , The surface material type of the item is denoted as , The current surface temperature of the item is denoted as . ;

[0065] Integrate the first, second, third, and fourth layout information within the target space to generate an initial spatial model, denoted as . : ; among them, each structure Elements such as walls, windows, doors, and fixed structures are represented as three-dimensional geometric objects, containing attributes such as their position, size, shape, and material. Each structure, such as walls, windows, doors, and fixed structures, is converted into a geometric object in three-dimensional space, such as a cube, plane, or polyhedron. Using 3D modeling techniques, such as boundary representation B-Rep, constructing solid geometry CSG, or triangular meshes, an overall spatial model is constructed. All structures are combined in a unified coordinate system to form a complete initial interior space model. ;

[0066] Initial spatial model The space is divided into uniform grids according to a given resolution, forming an initial gridded space. And represented as a set of three-dimensional meshes: ;in, To adjust a 3D spatial model according to resolution , , Functions that divide into grids , , These are the grid dimensions in the x, y, and z directions, respectively, which represent the resolution, or the size of each grid cell. ;

[0067] Based on the device set and the initial mesh space Forming a grid space for equipment This involves mapping the location and parameters of the refrigeration equipment to the corresponding mesh in the indoor space model: ; where, function The definition is as follows: That is, for each device According to its location Based on the size and dimensions, determine the grid range it occupies, and update the attributes of these grid cells with device information, such as device ID, type, air supply angle, and fan speed. If multiple devices occupy the same grid, they can be processed according to priority or a merging strategy, such as overlaying or merging. Here, represents the device. The grid space occupied;

[0068] For device grid space Each device in Analyze its scope of influence. :

[0069] ;

[0070] in, For equipment The maximum effective radius of action can be estimated based on factors such as air volume and air velocity. This indicates that the air supply angle constraint is met. The air supply angle constraint means that only grid cells within the equipment's air supply angle range, including both horizontal and vertical directions, are included in the influence range. Centered on the equipment location, all grid cells within its air supply angle range are calculated. It is determined whether each grid cell is within the equipment's effective radius and whether it is within the air supply angle's coverage area. Grid cells within the equipment's effective radius and within the air supply angle's coverage area are added to the influence range set. That is, based on the air supply angle and distance of the equipment, calculate the influence range of each device on the surrounding grid;

[0071] Based on the distribution set of indoor items and the grid space of equipment To form an indoor grid space That is, mapping the location and attributes of items to the corresponding grid in the interior space model: ; where, function The definition is as follows: That is, for each item According to its location and size Calculate the grid area occupied by the item, update the attributes of these grid cells with item information, such as item ID, shape, material, surface temperature, etc. If the item overlaps with equipment or other items, it can be handled according to priority or merging strategy, such as marking it as "mixed occupation" or "impassable". Here, represents the item. The grid space occupied;

[0072] For indoor grid spaces Each item in Analyze its airflow properties This represents the airflow velocity vector or drag coefficient of each grid cell: ;in, The original airflow velocity is set to 0. It is an airflow obstruction function used to adjust the airflow speed or direction of the grid based on the shape, size, material, and other properties of the object. In other words, it calculates the degree of obstruction to the airflow based on the shape and size of the object and updates the airflow properties of the grid.

[0073] According to indoor grid space and initial space model Update and generate the target space model.

[0074] Using the above method, an indoor spatial layout is generated by acquiring information such as the layout of walls and windows, the distribution of all indoor cooling equipment, and the distribution of all indoor items. When the indoor space needs to be cooled by cooling equipment, the distribution of all indoor cooling equipment is used to determine whether it can improve cooling efficiency. If it cannot improve cooling efficiency, single-equipment cooling simulation analysis, multi-equipment cooling simulation analysis, and comprehensive cooling simulation analysis based on indoor and outdoor environmental data are performed on the indoor cooling equipment. Based on user habits, the most suitable cooling scheme is selected as the optimal cooling scheme. If it can improve cooling efficiency, multi-equipment cooling simulation analysis and comprehensive cooling simulation analysis based on indoor and outdoor environmental data are performed on the indoor cooling equipment. Based on user habits, the most suitable cooling scheme is selected as the optimal cooling scheme. According to the optimal cooling scheme, the operation of the cooling equipment is controlled to quickly reduce the indoor temperature to the target temperature. Under the premise of meeting the cooling requirements, energy consumption is minimized, direct cold air is avoided, and user habits and comfort are considered. Through 3D mesh modeling, airflow and temperature field simulation, and equipment operation strategy optimization, automated and intelligent control of the cooling equipment is achieved.

[0075] Example 2 is an improvement on Example 1. The automated energy-saving control method for this refrigeration system determines whether the current distribution of refrigeration equipment can improve cooling efficiency. Specifically:

[0076] Calculate the average velocity of the initial airflow velocity field in the target space without any equipment operating: ;in, This is the original airflow velocity at that grid point, set to 0;

[0077] For each device within the target space Within its air supply angle range Inside, several air supply directions are evenly selected. For example, take an angle every 10°: ;in, The angle step size is 10°.

[0078] For each direction The airflow velocity distribution of the device in this direction is determined using an airflow simulation function. ;in, It is a three-dimensional vector field representing the airflow velocity distribution of the device in that direction;

[0079] Calculate the average airflow velocity of the device in this direction: ;in, This represents the magnitude of the airflow velocity vector at that grid point, i.e., the wind speed. It is the total number of grid cells;

[0080] For each device within the target space Calculate its maximum airflow lift rate: ;

[0081] Define an efficiency determination function to determine whether the current distribution of refrigeration equipment can improve cooling efficiency:

[0082] ;in, To increase the threshold, for example, by 0.2 (20%), this is used to determine whether the distribution of refrigeration equipment can improve cooling efficiency. This indicates that there exists any device that satisfies the following in a certain direction. ;

[0083] like If so, it is determined that the current distribution of refrigeration equipment can improve cooling efficiency;

[0084] like If the current distribution of refrigeration equipment fails to improve cooling efficiency, then it is determined that the current distribution of refrigeration equipment cannot improve cooling efficiency.

[0085] This embodiment also provides single-device refrigeration simulation analysis, specifically: obtaining a set of devices. ;

[0086] For each device Set the parameter combination for simulation operation: ;

[0087] In parameter combinations, From All wind speed settings selected in the program. From the angle range Several typical wind directions were selected, one for every 15°, specifically: ;

[0088] In parameter combinations, The outlet air temperature selected from the set of temperatures is specifically as follows: ;in, , , The selected set temperature, such as 16, 18, and 20 respectively;

[0089] In parameter combinations, The wind force is estimated based on wind speed and air volume, specifically: ;in, air density, Air volume for the equipment;

[0090] For each set of equipment operating parameter combinations Set up an airflow simulation function to simulate and calculate the airflow velocity field generated in the indoor space:

[0091] ;

[0092] In the airflow simulation function, Indicates on the path, This is the wind speed setting. The unit direction vector is specifically: ;

[0093] In the airflow simulation function, The distance from the grid point to the device is specifically: ;

[0094] In the airflow simulation function, This is a distance attenuation function used to describe the phenomenon that wind speed gradually decreases with increasing distance. Specifically: ;

[0095] In the airflow simulation function, This is the angle deviation factor, used to describe the phenomenon that wind speed decreases as the supply air angle deviates from the main direction. Specifically: ;

[0096] In the airflow simulation function, The obstacle blocking factor quantifies the degree to which obstacles weaken or block airflow and temperature, making the simulation results closer to the real indoor environment. 0 represents complete obstruction. Specifically: ;

[0097] For each set of equipment operating parameter combinations Set up a temperature simulation function to simulate and calculate the temperature field it generates in the indoor space:

[0098] ;

[0099] In the temperature simulation function, This indicates that the area is within the equipment's influence range. For the heat convection term, specifically: ;in, This is the three-dimensional wind speed vector for this grid point. This is the temperature gradient vector at this grid point. For time step;

[0100] In the temperature simulation function, For heat conduction, specifically: ;in, This is the thermal diffusivity, such as 0.01;

[0101] In the temperature simulation function, The term is for thermal radiation, specifically: Among them, for Emissivity, with a value between 0 and 1. The Stefan-Boltzmann constant is... This refers to the surface temperature of objects, such as furniture and appliances. Current grid temperature

[0102] Based on the spatial layout and object distribution, identify areas that are far from equipment or obstructed, such as corners or behind furniture, to form a set of difficult areas: ;

[0103] In each region Several data collection points are set up in the middle. For each region For each collection point, acquire the collection point data: ;in, The location of the collection point is marked as , The temperature at the sampling point, To determine user accessibility of the data collection point, based on the user's historical data, it is necessary to determine whether the user will pass through or stay at the data collection point. If the user will pass through or stay at the data collection point, then... =True, if the user will not pass through or stay at the collection point. , For collection points and equipment The distance between them is as follows: ;

[0104] Among all user-accessible data collection points, select the point furthest from the device and designate it as the user's furthest point, denoted as: Collect the temperature at the farthest point from the user, define it as the farthest temperature from the user, and denot it as: ;

[0105] Among all data collection points, select the point farthest from the device and designate it as the physical farthest point, denoted as: Collect the temperature at the physical farthest point, define it as the physical farthest temperature, and denot it as: ;

[0106] Define a point analysis function to determine the analysis and data collection points: ;

[0107] That is, the physical farthest point is used first, but if the user will never reach that point, the farthest point that the user can reach is used as a second choice, where represents the physical farthest point that the user will not pass through or stay at.

[0108] Simulate equipment operation, record and analyze data collection points Temperature from initial temperature Reduced to target temperature The required time is defined as the simulation duration: ;in, A function to record the duration of the simulation;

[0109] Simulate equipment operation and calculate and analyze data collection points. Temperature from initial temperature Reduced to target temperature The energy consumption corresponding to that time is defined as the simulated energy consumption: Obtain all simulation schemes and form a single simulation set: ;

[0110] Obtaining user preference data: ;

[0111] like If the user prefers rapid cooling, then the single-device cooling solution is determined as follows:

[0112] ;

[0113] like If the user preference is energy saving, then the single-device cooling solution is determined as follows:

[0114] .

[0115] This embodiment also provides multi-device refrigeration simulation analysis, specifically: obtaining a set of devices. ;

[0116] Generate all possible device combinations, such as A={A1,A2,A3}, then ECO={{A1,A2},{A1,A3},{A2,A3},{A1,A2,A3}}: ;

[0117] For each combination Different operating modes are set, generating a set of all possible operating modes. Each device can select a cooling mode and a fan supply mode. The cooling mode outputs cold air, i.e., setting the temperature, fan speed, and air direction. The fan supply mode outputs normal air, i.e., only setting the fan speed and air direction. ; among them, each It is a function mapping: For example, for CO={A1,A2}, possible operating modes include: (A1 cooling, A2 supplying air), (A1 supplying air, A2 cooling), (A1 cooling, A2 cooling), (A1 supplying air, A2 supplying air).

[0118] For each device Set the parameters according to its operating mode: if the equipment is in cooling mode, then the airflow direction is... Wind speed is The outlet air temperature is If the equipment is in air supply mode, the airflow direction is... Wind speed is The outlet air temperature is the ambient temperature, meaning it does not cool.

[0119] For each combination and operating mode For each device Based on its operating status, such as cooling or ventilation, the airflow velocity field generated by a single device in an indoor space is simulated and calculated using an airflow simulation function. ;in, For wind direction, Wind speed;

[0120] For each combination and operating mode The airflow fields of all devices are weighted and superimposed to calculate the overall airflow velocity field generated in the indoor space: ;in, This represents the device weight, with a default value of 1. It is used to determine the proportion of the device's influence on airflow in the space. , The obstacle blocking factor quantifies the degree to which obstacles weaken or block airflow and temperature, making the simulation results closer to the real indoor environment. 0 represents complete obstruction. ;

[0121] Get Combinations The number of devices in cooling mode is defined as the cooling quantity.

[0122] If the cooling capacity is ≥1, then a temperature field simulation is performed to simulate the overall temperature field generated in the indoor space: ;in, Here is the temperature update function, used to update the temperature and jointly drive the evolution of the indoor temperature field. Its specific formula is: ;

[0123] In the temperature update function, The term "heat convection" describes the physical process by which "wind carries away heat," specifically: ;in, This is the three-dimensional wind speed vector for this grid point. This is the temperature gradient vector at this grid point. For time step;

[0124] In the temperature update function, The term for heat conduction describes the physical process of heat diffusing to lower temperatures, specifically: ;in, This is the thermal diffusivity, such as 0.01;

[0125] In the temperature update function, The term "thermal radiation" describes the physical process of "heat radiated by a high-temperature object," specifically: ;in, Emissivity, with a value between 0 and 1. The Stefan-Boltzmann constant is... This refers to the surface temperature of objects, such as furniture and appliances. The current grid temperature;

[0126] Based on the spatial layout and object distribution, identify areas that are far from equipment or obstructed, such as corners or behind furniture, to form a set of difficult areas: ;

[0127] In each region Several data collection points are set up in the middle. ;

[0128] For each region At each sampling point, the temperature change process is recorded and denoted as... , where t = 0, 1, ..., N;

[0129] For each combination and operating mode The simulation device operates, recording the temperature at all sampling points from the initial temperature. Reduced to target temperature The required time is defined as the simulation duration:

[0130] ;

[0131] For each combination and operating mode The simulation device operates, recording the temperature at all sampling points from the initial temperature. Reduced to target temperature The energy consumption corresponding to the time is defined as the simulated energy consumption, which is the power of all devices multiplied by the running time:

[0132] ;

[0133] Obtain all simulation schemes to form a multi-simulation set: ;

[0134] Obtaining user preference data: ;

[0135] like If the user prefers rapid cooling, then the multi-device cooling solution is determined as follows:

[0136] ;

[0137] in, This indicates the simulation duration with the smallest extracted value. This means extracting the simulated energy consumption with the smallest value from the data corresponding to several simulation durations with the smallest values;

[0138] like If the user preference is energy saving, then the multi-device cooling solution is determined as follows:

[0139] .

[0140] in, This represents the simulated energy consumption with the lowest extracted value. This means extracting the simulation duration with the smallest value from the data corresponding to several simulation energy consumption values ​​with the smallest values;

[0141] This embodiment also provides a comprehensive refrigeration simulation analysis, specifically:

[0142] The temperature of the air output by the refrigeration equipment in air supply mode is defined as the supply air temperature.

[0143] ;

[0144] That is, in the air supply mode, the refrigeration equipment does not cool, but only supplies air, and its temperature is equal to the outdoor temperature;

[0145] The temperature of the air output by the refrigeration equipment in refrigeration mode is defined as the refrigeration temperature.

[0146] ;

[0147] That is, when the refrigeration equipment is in refrigeration mode, it outputs cold air at a temperature set by the user or a default value, such as 16℃, 18℃, 20℃, etc.

[0148] Define an analysis selection function to determine the simulation analysis to be performed under the current indoor and outdoor temperatures:

[0149] ;

[0150] like Then, perform multi-device cooling simulation analysis, and extract the corresponding multi-device cooling scheme as a comprehensive cooling scheme under the condition of only considering the combination without air supply mode;

[0151] like Then, perform a single-device cooling simulation analysis to extract the corresponding single-device cooling solution:

[0152] ;

[0153] in, This is a function used to extract the corresponding single-device cooling scheme through single-device cooling simulation analysis;

[0154] Perform multi-device cooling simulation analysis, and extract the corresponding multi-device cooling scheme considering only combinations without air supply modes:

[0155] ;

[0156] Set up a scheme selection function to select the scheme with the lowest energy consumption as the overall cooling scheme:

[0157] .

[0158] Example 3 is an improvement on Example 2. In this example, a comparative analysis of the solutions is conducted, specifically as follows:

[0159] Obtain either the first set of solutions or the second set of solutions, and define them as the target analysis set. ;

[0160] For each scheme within the target analysis set Extract its solution information:

[0161] ;

[0162] in, To simulate duration, To simulate energy consumption, The wind direction refers to the direction of air supply. The set of solution information also includes other parameters, such as equipment combination and operating mode.

[0163] Obtain user usage habits, including whether users accept direct cold airflow and user preferences:

[0164] ;

[0165] in, This indicates whether the user accepts direct cold airflow. If the user does not accept direct cold airflow, then... Conversely, , Indicates user preferences, marked as ,in, To cool down quickly, To save energy;

[0166] like Then the human body location is obtained and denoted as ;

[0167] Define a wind direction analysis function to determine the plan. Will it cause cold air to blow directly on the body?

[0168] ;

[0169] in, Wind direction Vector from device to human body included angle The set angle threshold, such as 30°, is used to judge the scheme. Will it cause cold air to blow directly on the body? The specific formula is:

[0170] ;

[0171] like Then determine the scheme This can cause cold air to blow directly onto the body;

[0172] like Then determine the scheme It will not cause cold air to blow directly on the body;

[0173] Regarding the plan Perform matching analysis;

[0174] The solution with the highest matching degree is selected as the best cooling solution.

[0175] Among them, the scheme Perform matching analysis, specifically:

[0176] Define a solution evaluation function to determine whether it is necessary to calculate the solution's matching degree:

[0177] ;

[0178] like If the user does not accept direct cold air blowing and the solution would result in direct air blowing, then there is no need to calculate the solution's matching degree; the solution's matching degree can be directly determined. ;

[0179] like Then calculate the maximum cooling time among all schemes in the target analysis set: ; Calculate the maximum energy consumption among all schemes in the target analysis set: For each option in the target analysis set Calculate the normalized cooling time score: For each option in the target analysis set Calculate the normalized energy consumption score: Normalization is used to map indicators of different dimensions to the [0,1] interval, allowing them to be compared and weighted on the same scale; obtaining user preferences. ;like If the user preference is for rapid cooling, then the weight set is set as follows: ;like If the user preference is energy saving, then the weight set is set as follows: For each option in the target analysis set Calculate the degree of match between it and user habits: .

[0180] Example 4: This example also discloses an apparatus for implementing an automated energy-saving control method for a refrigeration system, see reference. Figure 2 ,include:

[0181] Data acquisition module: used to collect spatial layout information within the target space, including wall layout information, window layout information, door layout information, fixed structure layout information, distribution location and equipment parameter information of refrigeration equipment, and distribution information of indoor items;

[0182] Model generation module: used to generate a target space model of the target space based on the collected spatial layout information, distribution location and equipment parameter information of the refrigeration equipment, and distribution information of indoor items within the target space;

[0183] Simulation analysis module: used to perform various cooling simulation analyses on the target space, generate different cooling schemes, and analyze and determine the most suitable optimal cooling scheme;

[0184] Data analysis module: used to compare and analyze different generated cooling solutions to determine the most suitable and optimal cooling solution;

[0185] Equipment control module: Used to control the refrigeration equipment in the target space to operate with corresponding parameters according to the optimal cooling scheme, so that the target space is cooled to the required temperature.

Claims

1. An automated energy-saving control method for a refrigeration system, characterized in that: include: Obtain the target space; Generate a target space model from the target space; Based on the target space model, determine whether the current distribution of refrigeration equipment can improve cooling efficiency; If it is determined that the current distribution of refrigeration equipment can improve the cooling efficiency, then multi-equipment refrigeration simulation analysis and comprehensive refrigeration simulation analysis are performed on the indoor refrigeration equipment in sequence to generate multi-equipment refrigeration schemes and comprehensive refrigeration schemes respectively, and generate the first scheme set. If it is determined that the current distribution of refrigeration equipment cannot improve the cooling efficiency, then the indoor refrigeration equipment is subjected to single-equipment refrigeration simulation analysis, multi-equipment refrigeration simulation analysis and comprehensive refrigeration simulation analysis in sequence, generating single-equipment refrigeration scheme, multi-equipment refrigeration scheme and comprehensive refrigeration scheme respectively, generating a second scheme set; Obtain user usage habits; Based on the first or second set of solutions, and combined with user habits, the best cooling solution is determined through comparative analysis of the solutions. Based on the optimal cooling scheme, control the refrigeration equipment to operate with the corresponding parameters.

2. The automated energy-saving control method for a refrigeration system according to claim 1, characterized in that: Generate a target space model from the target space, specifically as follows: Obtain the first layout information within the target space, denoted as : ； Among them, each first layout It can be represented as: ； Obtain the second layout information within the target space, denoted as : ； Among them, each second layout It can be represented as: ； Obtain the third layout information within the target space, denoted as : ； Each third layout It can be represented as: ； Obtain the fourth layout information within the target space, denoted as : ； Each fourth layout It can be represented as: ； All refrigeration devices within the target space are acquired and grouped into a device set, denoted as . : ； For each device Obtain its three-dimensional coordinate position: ； For each device To obtain its parameter information: ； in, The cooling capacity of the refrigeration equipment. The air volume supplied by the refrigeration equipment. The power of the refrigeration equipment, The air supply angle of the refrigeration equipment is as follows: ； in, This refers to the range of horizontal air supply angles. The range of vertical air supply angles; in, The fan speed settings for the refrigeration equipment are as follows: ； in, For the first Wind speed setting; For each device Get its current running status: ； in, To indicate whether the refrigeration equipment is on or off, mark it as... , The current set temperature of the refrigeration equipment. The current fan speed setting of the cooling equipment is marked as follows. ; Obtain the distribution information of all indoor items within the target space, forming an indoor item distribution set, denoted as: ； For each item Get its item attributes: ； Integrate the first, second, third, and fourth layout information within the target space to generate an initial spatial model, denoted as . : ； Each structure Each is represented as a three-dimensional geometric object, including its position, size, shape, and material properties; Initial spatial model The space is divided into uniform grids according to a given resolution, forming an initial gridded space. : ； in, To adjust a 3D spatial model according to resolution , , Functions that divide into grids , , These are the grid dimensions in the x, y, and z directions, respectively; Based on the device set and the initial mesh space Forming a grid space for equipment : ； For device grid space Each device in Analyze its scope of influence. : ； in, This indicates that the air supply angle constraint is met. The air supply angle constraint means that only grids within the air supply angle range of the equipment are included in the influence range. For equipment Maximum effective radius of action; Based on the distribution set of indoor items and the grid space of equipment To form an indoor grid space : ； For indoor grid spaces Each item in Analyze its airflow properties : ； in, It is the original airflow velocity. It is an airflow resistance function; According to indoor grid space and initial space model Update and generate the target space model.

3. The automated energy-saving control method for a refrigeration system according to claim 1, characterized in that: To determine whether the current distribution of refrigeration equipment can improve cooling efficiency, the following steps are taken: Calculate the average velocity of the initial airflow velocity field in the target space without any equipment operating: ； For each device within the target space Within its air supply angle range Inside, several air supply directions are evenly selected. : ； in, The angle step size; For each direction The airflow velocity distribution of the device in this direction is determined using an airflow simulation function. ； in, It is a three-dimensional vector field representing the airflow velocity distribution of the device in that direction; Calculate the average airflow velocity of the device in this direction: ； in, The magnitude of the airflow velocity vector at each grid point. It is the total number of grid cells; For each device within the target space Calculate its maximum airflow lift rate: ； Define an efficiency determination function to determine whether the current distribution of refrigeration equipment can improve cooling efficiency: ； in, To increase the threshold, This indicates that there exists any device that satisfies the following in a certain direction. ; like If so, it is determined that the current distribution of refrigeration equipment can improve cooling efficiency; like If the current distribution of refrigeration equipment fails to improve cooling efficiency, then it is determined that the current distribution of refrigeration equipment cannot improve cooling efficiency.

4. The automated energy-saving control method for a refrigeration system according to claim 1, characterized in that: Single-device refrigeration simulation analysis, specifically: Get device set ; For each device Set the parameter combination for simulation operation: ； In parameter combinations, From All wind speed settings selected in the program. From the angle range The selected typical wind directions are as follows: ； In parameter combinations, The outlet air temperature selected from the set of temperatures is specifically as follows: ； In parameter combinations, The wind force is estimated based on wind speed and air volume, specifically: ； in, air density, Air volume for the equipment; For each set of equipment operating parameter combinations Set up an airflow simulation function to simulate and calculate the airflow velocity field generated in the indoor space: ； In the airflow simulation function, Indicates on the path, This is the wind speed setting. The unit direction vector is specifically: ； In the airflow simulation function, The distance from the grid point to the device is specifically: ； In the airflow simulation function, The distance decay function is as follows: ； In the airflow simulation function, The angle deviation factor is as follows: ； In the airflow simulation function, The obstacle blocking factor is as follows: ； For each set of equipment operating parameter combinations Set up a temperature simulation function to simulate and calculate the temperature field it generates in the indoor space: ； In the temperature simulation function, This indicates that the area is within the equipment's influence range. For the heat convection term, specifically: ； In the temperature simulation function, For heat conduction, specifically: ； in, The thermal diffusivity; In the temperature simulation function, The term is for thermal radiation, specifically: ； Based on spatial layout and object distribution, identify areas that are far from equipment and obstructed, forming a set of difficult areas: ； In each region Several data collection points are set up in the middle. ; For each region For each collection point, acquire the collection point data: ； in, The location of the collection point is marked as , The temperature at the sampling point, For user accessibility of the collection point, For collection points and equipment The distance between them is as follows: ； Among all user-accessible data collection points, select the point furthest from the device and designate it as the user's furthest point, denoted as: ； The temperature at the farthest point from the user is collected and defined as the user's farthest temperature, denoted as: ； Among all data collection points, select the point farthest from the device and designate it as the physical farthest point, denoted as: ； The temperature at the physical farthest point is collected and defined as the physical farthest temperature, denoted as: ； Define a point analysis function to determine the analysis and data collection points: ； Simulate equipment operation, record and analyze data collection points Temperature from initial temperature Reduced to target temperature The required time is defined as the simulation duration: ； Simulate equipment operation and calculate and analyze data collection points. Temperature from initial temperature Reduced to target temperature The energy consumption corresponding to that time is defined as the simulated energy consumption: ； Obtain all simulation schemes and form a single simulation set: ； Obtaining user preference data: ； like Therefore, the single-equipment cooling scheme is determined as follows: ； like Therefore, the single-equipment cooling scheme is determined as follows: 。 5. The automated energy-saving control method for a refrigeration system according to claim 1, characterized in that: Multi-device refrigeration simulation analysis, specifically: Get device set ; Generate all possible device combinations: ； For each combination Set different operating modes to generate a set of all possible operating modes: ； For each device Set parameters according to its operating mode; For each combination and operating mode For each device Based on its operating status, the airflow velocity field generated by a single device in an indoor space is simulated and calculated using an airflow simulation function: ； in, For wind direction, Wind speed; For each combination and operating mode The airflow fields of all devices are weighted and superimposed to calculate the overall airflow velocity field generated in the indoor space: ； in, For device weights, specifically , The obstacle blocking factor is specifically... ; Get Combinations The number of devices in cooling mode is defined as the cooling quantity. If the cooling capacity is ≥1, then a temperature field simulation is performed to simulate the overall temperature field generated in the indoor space: ； in, The temperature update function has the following formula: ； In the temperature update function, For the heat convection term, specifically: ； In the temperature update function, For heat conduction, specifically: ； in, The thermal diffusivity; In the temperature update function, The term is for thermal radiation, specifically: ； in, For emission rate, The Stefan-Boltzmann constant is... The surface temperature of the object; Based on spatial layout and object distribution, identify areas that are far from equipment and obstructed, forming a set of difficult areas: ； In each region Several data collection points are set up in the middle. ; For each region At each sampling point, the temperature change process is recorded and denoted as... ; For each combination and operating mode The simulation device operates, recording the temperature at all sampling points from the initial temperature. Reduced to target temperature The required time is defined as the simulation duration: ； For each combination and operating mode The simulation device operates, recording the temperature at all sampling points from the initial temperature. Reduced to target temperature The energy consumption corresponding to that time is defined as the simulated energy consumption: ； Obtain all simulation schemes to form a multi-simulation set: ； Obtaining user preference data: ； like Therefore, the multi-device cooling solution is determined as follows: ； like Therefore, the multi-device cooling solution is determined as follows: 。 6. The automated energy-saving control method for a refrigeration system according to claim 1, characterized in that: Comprehensive refrigeration simulation analysis, specifically: The temperature of the air output by the refrigeration equipment in air supply mode is defined as the supply air temperature. ； The temperature of the air output by the refrigeration equipment in refrigeration mode is defined as the refrigeration temperature. ； Define an analysis selection function to determine the simulation analysis to be performed under the current indoor and outdoor temperatures: ； like Then, perform multi-device cooling simulation analysis, and extract the corresponding multi-device cooling scheme as a comprehensive cooling scheme under the condition of only considering the combination without air supply mode; like Then, perform a single-device cooling simulation analysis to extract the corresponding single-device cooling solution: ； Perform multi-device cooling simulation analysis, and extract the corresponding multi-device cooling scheme considering only combinations without air supply modes: ； Set up a scheme selection function to select the scheme with the lowest energy consumption as the overall cooling scheme: 。 7. The automated energy-saving control method for a refrigeration system according to claim 1, characterized in that: The comparative analysis of the options is as follows: Obtain either the first set of solutions or the second set of solutions, and define them as the target analysis set. ; For each scheme within the target analysis set Extract its solution information: ； in, To simulate duration, To simulate energy consumption, Wind direction; Obtaining user usage habits: ； like Then the human body location is obtained and denoted as ; Define a wind direction analysis function to determine the plan. Will it cause cold air to blow directly on the body? ； in, Wind direction Vector from device to human body included angle For the set included angle threshold, The specific formula is: ； like Then determine the scheme This can cause cold air to blow directly onto the body; like Then determine the scheme It will not cause cold air to blow directly on the body; Regarding the plan Perform matching analysis; The solution with the highest matching degree is selected as the best cooling solution.

8. The automated energy-saving control method for a refrigeration system according to claim 1, characterized in that: Regarding the plan Perform matching analysis, specifically: Define a solution evaluation function to determine whether it is necessary to calculate the solution's matching degree: ； like In this case, there is no need to calculate the matching degree of the solution; the matching degree of the solution can be directly determined. ; like Then calculate the maximum cooling time among all schemes in the target analysis set: ； Calculate the maximum energy consumption among all options in the target analysis set: ； For each option in the target analysis set Calculate the normalized cooling time score: ； For each option in the target analysis set Calculate the normalized energy consumption score: ； Get user preferences ; like Then the weight set is set as ; like Then the weight set is set as ; For each option in the target analysis set Calculate the degree of match between it and user habits: 。 9. An apparatus for implementing the automated energy-saving control method of the refrigeration system according to claim 1, characterized in that: include: Data acquisition module: used to collect spatial layout information, distribution location and parameter information of refrigeration equipment, and distribution information of indoor items within the target space; Model generation module: used to generate a target space model of the target space based on the collected spatial layout information, distribution location and equipment parameter information of the refrigeration equipment, and distribution information of indoor items within the target space; Simulation analysis module: used to perform various cooling simulation analyses on the target space, generate different cooling schemes, and analyze and determine the most suitable optimal cooling scheme; Data analysis module: used to compare and analyze different generated cooling solutions to determine the most suitable and optimal cooling solution; Equipment control module: Used to control the refrigeration equipment in the target space to operate with corresponding parameters according to the optimal cooling scheme, so that the target space is cooled to the required temperature.

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