Airflow organization adjustment method and device, electronic device, and storage medium

Abstract

The application discloses an air flow organization adjustment method and device, electronic equipment and a storage medium, and relates to the field of financial technology or other related fields. The adjustment method comprises the following steps: constructing a building digital twin model based on building information of a target building, dividing the building digital twin model into N grid blocks, determining grid block data of each grid block based on preset data, simulating the air flow organization based on all the grid block data to obtain a simulation result, and controlling the preset air conditioning system to adjust the air flow organization based on the simulation result in the case that the simulation result indicates that there is local abnormal data. The application solves the technical problem that the air flow organization cannot be simulated and adjusted in real time in the related art.

Description

Technical Field

[0001] This invention relates to the field of financial technology, and more specifically, to a method and apparatus for adjusting airflow organization, an electronic device, and a storage medium thereof. Background Technology

[0002] Airflow organization plays a crucial role in the operation of air conditioning systems. Proper airflow organization can effectively meet environmental comfort requirements, reduce energy consumption, and lower investment costs. Currently, data centers are experiencing increasing power consumption and rack power requirements, along with increasingly stringent temperature and humidity control conditions. Improper airflow organization can lead to localized hotspots, affecting the safe and stable operation of servers, increasing energy consumption of the air conditioning system, raising data center operating costs, and hindering the green and environmentally friendly requirements of data centers.

[0003] In related technologies, airflow organization design is usually carried out in the planning and design stage, based on the design drawings and airflow organization simulation, or in the later modification stage, based on the situation at that time. However, in the actual construction or operation process, the building environment is changing. For example, there is a big difference between the designed building and the actual situation after completion. In the actual operation process, the outdoor environment changes in real time, and the internal environment of the building also changes in real time, which leads to real-time changes in airflow organization. Especially for data center computer rooms, the operating power of the servers in the computer room changes in real time, and the number of servers in the racks is also dynamically adjusted.

[0004] Therefore, there is an urgent need for a method that can simulate and adjust airflow organization in real time to provide reasonable airflow organization for buildings such as data centers.

[0005] There is currently no effective solution to the above problems. Summary of the Invention

[0006] This invention provides a method, apparatus, electronic device, and storage medium for adjusting airflow organization, thereby at least solving the technical problem in related technologies that cannot simulate and adjust airflow organization in real time.

[0007] According to one aspect of the present invention, a method for adjusting airflow organization is provided, comprising: constructing a building digital twin model based on building information of a target building, wherein the building digital twin model is used to acquire preset data in real time, the preset data including: environmental data and equipment data; dividing the building digital twin model into N grid blocks, wherein N is a positive integer; determining grid block data for each grid block based on the preset data; simulating airflow organization based on all the grid block data to obtain simulation results, wherein the airflow organization is provided by a preset air conditioning system pre-deployed within the target building; and, if the simulation results indicate the presence of local abnormal data, controlling the preset air conditioning system to adjust the airflow organization based on the simulation results.

[0008] Optionally, the step of constructing a digital twin model of a building based on the building information of the target building includes: determining the building volume information, the equipment location information, and the equipment volume information of each device within the target building based on the building information; constructing a three-dimensional model based on the building volume information, the equipment location information, and the equipment volume information; determining the equipment parameters of each device and acquiring the environmental parameters of the target building using preset sensors, wherein the preset sensors are pre-deployed on the target building; and uploading the equipment parameters and the environmental parameters to the three-dimensional model to obtain the digital twin model of the building.

[0009] Optionally, the step of dividing the building digital twin model into N grid blocks includes: determining the length, width, and height of the target building based on the building information; determining the number of length segments, width segments, and height segments based on the length, width, and height, respectively; and dividing the long side, wide side, and high side of the building digital twin model according to the number of length segments, width segments, and height segments, respectively, to obtain N grid blocks.

[0010] Optionally, the step of determining the grid block data of each grid block based on the preset data includes: locating the center point of the grid block; calculating the point data of the center point based on the preset data, wherein the point data includes: temperature value, humidity value, and wind speed value; and representing the point data as the grid block data of the grid block to which the center point belongs.

[0011] Optionally, the step of simulating the airflow organization based on all the grid block data to obtain simulation results includes: selecting all the temperature values ​​in all the grid block data at the same time point, and generating a temperature map for the time point based on all the temperature values; selecting all the humidity values ​​in all the grid block data at the same time point, and generating a humidity map for the time point based on all the humidity values; selecting all the wind speed values ​​in all the grid block data at the same time point, and generating a wind speed map for the time point based on all the wind speed values; and generating the simulation results based on the temperature map, humidity map, and wind speed map for each time point.

[0012] Optionally, after simulating the airflow organization based on all the grid block data and obtaining the simulation results, the method further includes: dividing the building digital twin model into M regions, where M is a positive integer; configuring the parameter threshold range for each region based on the functional requirements of each region; determining the region to which each grid block belongs; and determining the target grid block data as the local abnormal data when the target grid block data does not belong to the target parameter threshold range, wherein the target parameter threshold range is the parameter threshold range corresponding to the target region to which the target grid block indicated by the target grid block data belongs.

[0013] Optionally, the step of controlling the preset air conditioning system to adjust the airflow organization based on the simulation results includes: Step 1, determining a target air conditioner based on the air conditioner sorting results of the target grid block, wherein the target air conditioner is the air conditioner closest to the target grid block; Step 2, adjusting the air conditioning parameters of the target air conditioner until the simulation results indicate that there is no local abnormal data or the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold; Step 3, if the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold, selecting the next air conditioner based on the air conditioner sorting results and adjusting the air conditioning parameters of the next air conditioner, wherein the next air conditioner is the air conditioner closest to the target grid block in the preset air conditioning system other than the air conditioners whose air conditioning parameters have been adjusted, and the next air conditioner is represented as the new target air conditioner; repeating step 3 until the simulation results indicate that there is no local abnormal data or the air conditioning parameters of all air conditioners in the preset air conditioning system are adjusted to the maximum threshold.

[0014] Optionally, before determining the target air conditioner based on the air conditioner sorting result of the target grid block, the method further includes: determining the center point position of the center point of each grid block and the air conditioner center point position of the air conditioner center point of each air conditioner in the preset air conditioning system; calculating the distance between the center point and each air conditioner center point based on the center point position and the air conditioner center point position; sorting all distances to obtain the air conditioner sorting result of the grid block.

[0015] According to another aspect of the present invention, an airflow organization adjustment device is also provided, comprising: a construction unit for constructing a building digital twin model based on building information of a target building, wherein the building digital twin model is used to acquire preset data in real time, the preset data including: environmental data and equipment data; a segmentation unit for segmenting the building digital twin model into N grid blocks, wherein N is a positive integer; a determination unit for determining grid block data for each grid block based on the preset data; a simulation unit for simulating the airflow organization based on all the grid block data to obtain simulation results, wherein the airflow organization is provided by a preset air conditioning system pre-deployed in the target building; and an adjustment unit for controlling the preset air conditioning system to adjust the airflow organization based on the simulation results when the simulation results indicate the presence of local abnormal data.

[0016] Optionally, the construction unit includes: a first determining module, used to determine building volume information, equipment location information, and equipment volume information of each device within the target building based on the building information of the target building; a first construction module, used to construct a three-dimensional model based on the building volume information, the equipment location information, and the equipment volume information; a second determining module, used to determine the equipment parameters of each device and acquire environmental parameters of the target building using preset sensors, wherein the preset sensors are pre-deployed on the target building; and a first uploading module, used to upload the equipment parameters and the environmental parameters to the three-dimensional model to obtain the digital twin model of the building.

[0017] Optionally, the segmentation unit includes: a third determining module, used to determine the length, width, and height of the target building based on the building information; a fourth determining module, used to determine the number of length segments, the number of width segments, and the number of height segments based on the length, the width, and the height; and a first segmentation module, used to segment the long side, wide side, and high side of the building digital twin model according to the number of length segments, the number of width segments, and the number of height segments, to obtain N grid blocks.

[0018] Optionally, the determining unit includes: a first positioning module for locating the center point of the grid block; a first calculation module for calculating point data of the center point based on the preset data, wherein the point data includes: temperature value, humidity value, and wind speed value; and a first characterization module for characterizing the point data as the grid block data of the grid block to which the center point belongs.

[0019] Optionally, the simulation unit includes: a first selection module, configured to select all temperature values ​​in all grid block data at the same time point, and generate a temperature map for the time point based on all temperature values; a second selection module, configured to select all humidity values ​​in all grid block data at the same time point, and generate a humidity map for the time point based on all humidity values; a third selection module, configured to select all wind speed values ​​in all grid block data at the same time point, and generate a wind speed map for the time point based on all wind speed values; and a first generation module, configured to generate the simulation result based on the temperature map, humidity map, and wind speed map for each time point.

[0020] Optionally, the adjustment device further includes: a first division module, used to divide the building digital twin model into M regions after simulating the airflow organization based on all the grid block data and obtaining the simulation results, where M is a positive integer; a first configuration module, used to configure the parameter threshold range of each region based on the functional requirements of each region; a fifth determination module, used to determine the region to which each grid block belongs; and a sixth determination module, used to determine that the target grid block data is the local abnormal data when the target grid block data does not belong to the target parameter threshold range, wherein the target parameter threshold range is the parameter threshold range corresponding to the target region to which the target grid block indicated by the target grid block data belongs.

[0021] Optionally, the adjustment unit includes: a seventh determining module, used to execute step 1, determining a target air conditioner based on the air conditioner sorting result of the target grid block, wherein the target air conditioner is the air conditioner closest to the target grid block; a first adjusting module, used to execute step 2, adjusting the air conditioner parameters of the target air conditioner until the simulation result indicates that there is no local abnormal data or the air conditioner parameters of the target air conditioner are adjusted to the maximum threshold; a fourth selecting module, used to execute step 3, selecting the next air conditioner based on the air conditioner sorting result and adjusting the air conditioner parameters of the next air conditioner when the air conditioner parameters of the target air conditioner are adjusted to the maximum threshold, wherein the next air conditioner is the air conditioner closest to the target grid block in the preset air conditioner system excluding the air conditioners whose air conditioner parameters have been adjusted, and the next air conditioner is characterized as the new target air conditioner; and a first execution module, used to repeatedly execute step 3 until the simulation result indicates that there is no local abnormal data or the air conditioner parameters of all air conditioners in the preset air conditioner system are adjusted to the maximum threshold.

[0022] Optionally, before determining the target air conditioner based on the air conditioner sorting results of the target grid block, the system further includes: an eighth determining module, used to determine the center point position of the center point of each grid block and the air conditioner center point position of each air conditioner in the preset air conditioning system; a second calculation module, used to calculate the distance between the center point and each air conditioner center point based on the center point position and the air conditioner center point position; and a first sorting module, used to sort all distances to obtain the air conditioner sorting results of the grid block.

[0023] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform any of the above-described airflow organization adjustment methods.

[0024] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement any of the above-described methods for adjusting airflow organization.

[0025] In this disclosure, a digital twin model of the target building is constructed based on its building information. This digital twin model is then divided into N grid blocks. Based on preset data, the grid block data for each block is determined. Based on all grid block data, airflow organization is simulated to obtain simulation results. If the simulation results indicate the presence of local anomalies, the preset air conditioning system is controlled to adjust the airflow organization based on these results. In this disclosure, a digital twin model of the building is first constructed to acquire preset data in real time. Then, the digital twin model is divided into multiple grid blocks, and the grid block data for each block is calculated based on the preset data. Subsequently, airflow organization is simulated based on all grid block data to obtain simulation results. If the simulation results indicate the presence of local anomalies, the preset air conditioning system can be controlled in a timely manner to adjust the airflow organization, providing a reasonable airflow organization for the target building. This not only reduces the energy consumption of the air conditioning system but also ensures the stable operation of various devices within the target building, thereby solving the technical problem in related technologies where real-time simulation and adjustment of airflow organization is impossible. Attached Figure Description

[0026] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0027] Figure 1 This is a flowchart of an optional airflow organization adjustment method according to an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of an optional online real-time simulation and control process for airflow organization based on digital twins according to an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of an optional airflow organization adjustment device according to an embodiment of the present invention;

[0030] Figure 4 This is a hardware structure block diagram of an electronic device (or mobile device) for an airflow organization adjustment method according to an embodiment of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] It should be noted that the airflow organization adjustment method and apparatus in this disclosure can be used in the field of financial technology for adjusting airflow organization, and can also be used in any field other than financial technology for adjusting airflow organization. This disclosure does not limit the application field of the airflow organization adjustment method and apparatus.

[0034] It should be noted that all information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, and displayed data) disclosed herein are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use, and processing of such data must comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding access points are provided for users to choose to authorize or refuse. For example, this system has interfaces with relevant users or organizations. Before obtaining relevant information, a request to obtain the information must be sent to the aforementioned user or organization through the interface, and the relevant information will be obtained only after receiving consent from the aforementioned user or organization.

[0035] The following embodiments of the present invention can be applied to various systems / applications / devices that adjust airflow organization. The present invention proposes an online real-time simulation and control method for airflow organization based on digital twins. First, a digital twin model of the building is built. Then, a real-time online airflow organization simulation is constructed based on the digital twin model. The building's digital twin model can acquire indoor and outdoor environmental parameters in real time. Based on the real-time operating parameters, the airflow organization simulation status is obtained in real time, thereby promptly identifying problems such as local hotspots. Furthermore, based on the real-time online airflow organization simulation, the operating status of air conditioners in nearby areas can be controlled in conjunction with high-temperature areas and local hotspot areas. For example, the supply air temperature, fan speed, and supply louver angle can be adjusted to optimize the operation of the air conditioning system.

[0036] The present invention will now be described in detail with reference to various embodiments.

[0037] Example 1

[0038] According to an embodiment of the present invention, an embodiment of a method for adjusting airflow organization is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0039] Figure 1 This is a flowchart of an optional airflow organization adjustment method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0040] Step S101: Based on the building information of the target building, construct a digital twin model of the building. The digital twin model of the building is used to acquire preset data in real time. The preset data includes: environmental data and equipment data.

[0041] Step S102: Divide the building digital twin model into N grid blocks, where N is a positive integer.

[0042] Step S103: Based on preset data, determine the grid block data for each grid block.

[0043] Step S104: Based on all grid block data, simulate the airflow organization to obtain simulation results, wherein the airflow organization is provided by a pre-deployed pre-air conditioning system in the target building.

[0044] Step S105: If the simulation results indicate the presence of local abnormal data, the preset air conditioning system is controlled to adjust the airflow organization based on the simulation results.

[0045] Through the above steps, a digital twin model of the building can be constructed based on the building information of the target building. The digital twin model is divided into N grid blocks. Based on preset data, the grid block data of each grid block is determined. Based on all grid block data, the airflow organization is simulated to obtain simulation results. If the simulation results indicate the presence of local abnormal data, the preset air conditioning system can be controlled to adjust the airflow organization based on the simulation results. In this embodiment of the invention, a digital twin model of the building can be constructed first to acquire preset data in real time. Then, the digital twin model of the building can be divided into multiple grid blocks. The grid block data of each grid block is calculated and determined according to the preset data. Then, the airflow organization is simulated based on all grid block data to obtain simulation results. If the simulation results indicate the presence of local abnormal data, the preset air conditioning system can be controlled in a timely manner to adjust the airflow organization, providing a reasonable airflow organization for the target building. This not only reduces the energy consumption of the air conditioning system but also ensures the stable operation of various devices within the target building, thereby solving the technical problem in related technologies that cannot simulate and adjust airflow organization in real time.

[0046] The embodiments of the present invention will now be described in detail with reference to the steps described above.

[0047] Step S101: Based on the building information of the target building, construct a digital twin model of the building. The digital twin model of the building is used to acquire preset data in real time. The preset data includes: environmental data and equipment data.

[0048] Optionally, the steps of constructing a digital twin model of a building based on the building information of the target building include: determining the building volume information, the equipment location information and equipment volume information of each piece of equipment within the target building based on the building information of the target building; constructing a three-dimensional model based on the building volume information, equipment location information and equipment volume information; determining the equipment parameters of each piece of equipment and acquiring the environmental parameters of the target building using preset sensors, wherein the preset sensors are pre-deployed on the target building; and uploading the equipment parameters and environmental parameters to the three-dimensional model to obtain the digital twin model of the building.

[0049] In this embodiment of the invention, a digital twin model of the building can be constructed based on the actual condition of the building (i.e., the actual building information). This digital twin model is used to acquire preset data in real time, including environmental data (such as temperature and humidity inside and outside the building) and equipment data (such as the power of each piece of equipment within the building). Specifically, based on the building information of the target building, the building volume information (e.g., length, width, and height), the equipment location information of each piece of equipment within the target building (e.g., the location of each piece of equipment within the building), and the equipment volume information (e.g., the length, width, and height of each piece of equipment) can be determined. Then, based on the building volume information, equipment location information, and equipment volume information, a three-dimensional model is constructed (i.e., a 3D model of the building is established based on its actual condition). For example, a 3D model of the building can be created using 3D software. Subsequently, based on the parameters required for subsequent airflow organization simulation, parameters of the building's indoor and outdoor environment (e.g., outdoor temperature and humidity, indoor temperature and humidity) and equipment parameters of various devices within the building (e.g., equipment power, lighting power, air conditioning operating parameters) can be obtained through sensors (i.e., determining the equipment parameters of each device and using preset sensors (sensors pre-deployed on the target building) to acquire the environmental parameters of the target building). The obtained indoor and outdoor environmental parameters and equipment parameters are then uploaded to the building's 3D model, ensuring a one-to-one correspondence between the 3D model and its parameters and the actual building and its parameters, thus forming a digital twin model of the building (i.e., uploading the equipment parameters and environmental parameters to the 3D model to obtain the building's digital twin model).

[0050] Step S102: Divide the building digital twin model into N grid blocks, where N is a positive integer.

[0051] Optionally, the step of dividing the building digital twin model into N grid blocks includes: determining the length, width, and height of the target building based on building information; determining the number of length segments, width segments, and height segments based on the length, width, and height; and dividing the long side, wide side, and high side of the building digital twin model according to the number of length segments, width segments, and height segments to obtain N grid blocks.

[0052] In this embodiment of the invention, the building digital twin model can be divided into small blocks (i.e., the building digital twin model is divided into N (N is a positive integer) grid blocks) based on the finite volume method. Specifically, the length, width and height of the target building can be determined according to the building information. Then, the number of length segments, width segments and height segments to be divided can be determined according to the length, width and height segments respectively. Then, the long side, wide side and high side of the building digital twin model can be divided according to the number of length segments, width segments and height segments to obtain multiple grid blocks.

[0053] In this embodiment of the invention, the more grid blocks there are and the smaller the grid block volume is, the more accurate the data calculated subsequently.

[0054] Step S103: Based on preset data, determine the grid block data for each grid block.

[0055] Optionally, the step of determining the grid block data of each grid block based on preset data includes: locating the center point of the grid block; calculating the point data of the center point based on the preset data, wherein the point data includes: temperature value, humidity value, and wind speed value; and representing the point data as the grid block data of the grid block to which the center point belongs.

[0056] In this embodiment of the invention, the grid block data of each grid block can be determined based on preset data acquired in real time from the building digital twin model. Specifically, the center point of each grid block can be located first. Then, based on the conservation of momentum, mass, and energy of each grid block, the point data (such as temperature, humidity, and velocity) of the center point of each grid block can be calculated in real time according to the preset data acquired from the building digital twin model. This yields the data of the entire model (i.e., the point data of the center point is calculated based on the preset data, including temperature, humidity, and wind speed values). The point data is then represented as the grid block data of the grid block to which the center point belongs (i.e., the data of the center point of each grid block is used as the data of the entire grid block).

[0057] Step S104: Based on all grid block data, simulate the airflow organization to obtain simulation results, wherein the airflow organization is provided by a pre-deployed pre-air conditioning system in the target building.

[0058] Optionally, the step of simulating airflow organization based on all grid block data to obtain simulation results includes: selecting all temperature values ​​in all grid block data at the same time point, and generating a temperature map for that time point based on all temperature values; selecting all humidity values ​​in all grid block data at the same time point, and generating a humidity map for that time point based on all humidity values; selecting all wind speed values ​​in all grid block data at the same time point, and generating a wind speed map for that time point based on all wind speed values; and generating simulation results based on the temperature map, humidity map, and wind speed map for each time point.

[0059] In this embodiment of the invention, the data of the center point of each grid block is used to form the data change situation or actual change situation of the entire model (such as the temperature change situation of the model). The more grid blocks there are and the smaller the grid block volume is, the more detailed and accurate the model data change situation is.

[0060] In this embodiment of the invention, the online real-time simulation of airflow organization (provided by a pre-deployed air conditioning system in the target building) based on all grid block data is achieved by calculating the data of each grid block in real time according to the indoor and outdoor environmental parameters and equipment parameters of the building obtained in real time by the model, so that the model data can obtain simulation results in real time according to environmental changes.

[0061] In this embodiment of the invention, all temperature values ​​in all grid block data at the same time point can be selected, and a temperature map for that time point can be generated based on all temperature values. Alternatively, all humidity values ​​in all grid block data at the same time point can be selected, and a humidity map for that time point can be generated based on all humidity values. Furthermore, all wind speed values ​​in all grid block data at the same time point can be selected, and a wind speed map for that time point can be generated based on all wind speed values. Then, simulation results can be generated based on the temperature map, humidity map, and wind speed map for each time point (i.e., the simulation results include a cloud map composed of the temperature, humidity, and wind speed values ​​of each grid block at each time point, which is used to display the changes in parameters within the building in real time).

[0062] Optionally, after simulating the airflow organization based on all grid block data and obtaining the simulation results, the method further includes: dividing the building digital twin model into M regions, where M is a positive integer; configuring the parameter threshold range for each region based on the functional requirements of each region; determining the region to which each grid block belongs; and determining the target grid block data as local anomalous data when the target grid block data does not belong to the target parameter threshold range, wherein the target parameter threshold range is the parameter threshold range corresponding to the target region to which the target grid block belongs, as indicated by the target grid block data.

[0063] In this embodiment of the invention, for a building digital twin model, parameter ranges (i.e., parameter threshold ranges) can be set according to relevant areas. For example, the temperature in the cold aisle of a data center server room cannot exceed 27°C, and the relative humidity cannot exceed 65%. Specifically, the building digital twin model can be divided into M (positive integer) areas (i.e., the model can be divided into multiple areas according to different functions). Based on the functional requirements of each area, the parameter threshold range for each area is configured (e.g., if a certain area needs to house multiple servers, the temperature of that area cannot be too high). Then, the area to which each grid block belongs is determined. If the target grid block data does not belong to the target parameter threshold range (i.e., the target grid block data is not within the parameter threshold range corresponding to the target area to which the indicated target grid block belongs), then the target grid block data can be determined to be locally abnormal data, and the air conditioning near the target area needs to be adjusted to bring the target grid block data within the target parameter threshold range.

[0064] Step S105: If the simulation results indicate the presence of local abnormal data, the preset air conditioning system is controlled to adjust the airflow organization based on the simulation results.

[0065] Optionally, the steps for controlling the airflow organization of the preset air conditioning system based on simulation results include: Step 1, determining the target air conditioner based on the air conditioner sorting results of the target grid block, wherein the target air conditioner is the air conditioner closest to the target grid block; Step 2, adjusting the air conditioning parameters of the target air conditioner until the simulation results indicate that there is no local abnormal data or the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold; Step 3, when the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold, selecting the next air conditioner based on the air conditioner sorting results and adjusting the air conditioning parameters of the next air conditioner, wherein the next air conditioner is the air conditioner closest to the target grid block in the preset air conditioning system other than the air conditioners whose air conditioning parameters have been adjusted, and the next air conditioner is represented as the new target air conditioner; Step 3 is repeated until the simulation results indicate that there is no local abnormal data or the air conditioning parameters of all air conditioners in the preset air conditioning system are adjusted to the maximum threshold.

[0066] In this embodiment of the invention, if the simulation results show the existence of local hotspots (i.e., when the simulation results indicate the presence of local abnormal data), the airflow organization of the preset air conditioning system can be adjusted according to the simulation results. Specifically, the target air conditioner (the air conditioner closest to the target grid block) can be determined first based on the air conditioner sorting results of the target grid block (i.e., the results sorted in advance based on the distance between the air conditioners and the target grid block). Then, the air conditioning parameters of the target air conditioner (e.g., supply air temperature, fan speed, supply louver angle, etc.) are adjusted until the simulation results indicate that there is no local abnormal data (i.e., the local hotspot problem has been resolved) or the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold (e.g., the temperature has been adjusted to the lowest level, the fan speed has been adjusted to the maximum level, etc.). If the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold, but the local hotspot problem has not been resolved, the next air conditioner (i.e., the air conditioner closest to the target grid block in the preset air conditioning system other than the air conditioner whose air conditioning parameters have been adjusted) can be selected according to the air conditioner sorting results, and the air conditioning parameters of the next air conditioner can be adjusted. The next air conditioner is then designated as the new target air conditioner. If the air conditioning parameters of the new target air conditioner are adjusted to the maximum threshold, but the local hot spot problem is still not resolved, continue to adjust the parameters of the next nearest air conditioner until the simulation results indicate that there is no local abnormal data or the air conditioning parameters of all air conditioners in the preset air conditioning system are adjusted to the maximum threshold.

[0067] For example, based on the building's digital twin model and the simulation results, when the local temperature exceeds the set temperature, for a data center server room, the nearest air conditioner is selected based on the location of the data center air conditioner and the location of the local temperature zone. Its air supply volume is increased or its air supply temperature is decreased to lower the local temperature. If the nearest air conditioner has reached its maximum capacity (i.e., it cannot lower the temperature or increase the air supply volume), then the second nearest air conditioner is adjusted, and so on.

[0068] Optionally, before determining the target air conditioner based on the air conditioner sorting results of the target grid block, the method further includes: determining the center point position of the center point of each grid block and the air conditioner center point position of each air conditioner in the preset air conditioning system; calculating the distance between the center point and each air conditioner center point based on the center point position and the air conditioner center point position; sorting all distances to obtain the air conditioner sorting results of the grid block.

[0069] In this embodiment of the invention, the distance between each air conditioner and each grid block can be determined first to obtain the air conditioner sorting result of each grid block. Specifically, the center point position of the center point of each grid block and the air conditioner center point position of each air conditioner in the preset air conditioning system can be determined first. Then, based on the center point position and the air conditioner center point position, the distance between the center point and each air conditioner center point is calculated. After sorting all distances, the air conditioner sorting result of the grid block is obtained.

[0070] The following describes in detail another optional implementation method.

[0071] This invention proposes an online real-time simulation method and system control method for airflow organization based on digital twins. Based on digital twins and computational fluid dynamics, a digital twin model of a building is constructed. This model can receive real-time indoor and outdoor environmental parameters, such as outdoor temperature and humidity, indoor temperature and humidity, equipment power, lighting power, and air conditioning operating parameters. These environmental and equipment parameters are displayed on the digital twin model in real time. A real-time online airflow organization simulation is built upon this model. Based on the real-time operating parameters of the environment and equipment, the airflow organization simulation of the digital twin model is dynamically obtained in real time, generating airflow temperature cloud maps, humidity cloud maps, wind speed cloud maps, and wind speed streamline diagrams, thereby identifying local hotspots and other issues. Based on the real-time online airflow organization simulation of the digital twin model, the operating status of air conditioning in nearby areas is controlled in conjunction with the model's airflow temperature and local hotspot areas. This includes adjusting parameters such as supply air temperature, fan speed, and supply louver angle, thereby optimizing the air conditioning system operation.

[0072] Figure 2 This is a schematic diagram of an optional online real-time simulation and control process for airflow organization based on digital twins according to an embodiment of the present invention, such as... Figure 2As shown, the specific process is as follows:

[0073] (1) Build a digital twin model of the building. The digital twin model receives indoor and outdoor environmental parameters and equipment operation parameters in real time. The digital twin model is adjusted and displayed in real time according to the corresponding environment and equipment operation parameters.

[0074] (2) Based on computational fluid dynamics, a real-time online digital twin model is constructed to simulate airflow organization. The airflow organization simulation of the digital twin model is obtained dynamically in real time according to the environmental and equipment operating parameters obtained in real time.

[0075] (3) Based on the real-time online airflow organization simulation of the digital twin model, the operating status of the air conditioner in the corresponding area with high airflow temperature and local hot spot area is controlled in a coordinated manner to optimize the airflow organization and the rational operation of the air conditioning system.

[0076] In this embodiment of the invention, the online real-time simulation and control process for airflow organization based on digital twins specifically involves three aspects: digital twin model building, online real-time airflow organization simulation, and linkage control.

[0077] Building a digital twin model:

[0078] (1) Based on the actual condition of the building, establish a three-dimensional model of the building, such as by using 3D software to establish a 3D model of the building.

[0079] (2) Based on the parameters required for subsequent airflow organization simulation, obtain the parameters of the building's indoor and outdoor environment and equipment parameters through sensors, such as outdoor temperature and humidity, indoor temperature and humidity, equipment power, lighting power, air conditioning operating parameters, etc.

[0080] (3) Upload the obtained indoor and outdoor environmental parameters and equipment parameters to the three-dimensional model of the building, so that the three-dimensional digital model and parameters of the building correspond one-to-one with the actual building and parameters, thereby forming a digital twin model of the building.

[0081] Online real-time airflow organization simulation:

[0082] (1) Based on the finite volume method, the model is divided into small blocks by mesh generation. The data at the center point of each small block (such as temperature, humidity, velocity, etc.) is used as the data for the entire small block. The more meshes there are, the smaller the volume of the small blocks, and the more accurate the calculated data.

[0083] (2) The data of all grid blocks in the entire model form the data changes or actual changes of the entire model (such as the temperature changes of the model). The more grids there are and the smaller the size of the small blocks, the more detailed and accurate the changes in the model data are.

[0084] (3) Based on the measurement data obtained from the model, and based on the conservation of momentum, mass and energy of each grid block, the data of each grid block is calculated in real time, thereby obtaining the data of the entire model.

[0085] (4) Online real-time simulation is to calculate the data of each grid block in real time based on the indoor and outdoor environmental parameters and equipment parameters of the building obtained in real time, so that the model data can obtain simulation results in real time according to environmental changes.

[0086] Linkage control:

[0087] (1) In the building digital twin model, set the range of parameters according to the relevant area, such as the temperature of the cold aisle of the data center computer room should not exceed 27°C and the relative humidity should not exceed 65%.

[0088] (2) Based on the building digital twin model and the obtained simulation results, when the local temperature exceeds the set temperature, select the nearest air conditioner according to the location of the data center air conditioner and the location of the local temperature area, increase its air supply volume or reduce its air supply temperature to reduce the local temperature. If the nearest air conditioner has reached its maximum capacity, adjust the second nearest air conditioner, and so on.

[0089] In this embodiment of the invention, by building a digital twin model of the building, a real-time online airflow organization simulation can be constructed based on the digital twin model. The digital twin model of the building can acquire indoor and outdoor environmental parameters in real time, and obtain the airflow organization simulation status in real time based on the real-time operating parameters, thereby promptly identifying problems such as local hot spots. In addition, based on the real-time online airflow organization simulation, the operating status of air conditioners in nearby areas can be controlled in conjunction with the temperature of high-temperature areas and local hot spots, such as supply air temperature, fan speed, and air supply louver angle, to optimize the operation of the air conditioning system.

[0090] The following is a detailed description with reference to another embodiment.

[0091] Example 2

[0092] The airflow organization adjustment device provided in this embodiment includes multiple implementation units, each of which corresponds to a specific implementation step in Embodiment 1 above.

[0093] Figure 3 This is a schematic diagram of an optional airflow organization adjustment device according to an embodiment of the present invention, such as... Figure 3 As shown, the adjustment device may include: a construction unit 30, a segmentation unit 31, a determination unit 32, a simulation unit 33, and an adjustment unit 34, wherein...

[0094] The building unit 30 is used to build a digital twin model of the building based on the building information of the target building. The digital twin model of the building is used to acquire preset data in real time. The preset data includes: environmental data and equipment data.

[0095] Segmentation unit 31 is used to divide the building digital twin model into N grid blocks, where N is a positive integer;

[0096] The determining unit 32 is used to determine the grid block data of each grid block based on preset data;

[0097] Simulation unit 33 is used to simulate airflow organization based on all grid block data and obtain simulation results, wherein the airflow organization is provided by a pre-deployed pre-air conditioning system in the target building;

[0098] The adjustment unit 34 is used to control the preset air conditioning system to adjust the airflow organization based on the simulation results when the simulation results indicate the presence of local abnormal data.

[0099] The aforementioned adjustment device can construct a digital twin model of the building based on the building information of the target building using the construction unit 30. The building digital twin model is then divided into N grid blocks using the segmentation unit 31. The grid block data of each grid block is determined by the determination unit 32 based on preset data. The airflow organization is simulated by the simulation unit 33 based on all grid block data to obtain simulation results. Finally, the adjustment unit 34 controls the preset air conditioning system to adjust the airflow organization based on the simulation results if the simulation results indicate the presence of local abnormal data. In this embodiment of the invention, a building digital twin model can be constructed first to acquire preset data in real time. Then, the building digital twin model is divided into multiple grid blocks, and the grid block data of each grid block is calculated and determined based on the preset data. Afterward, the airflow organization is simulated based on all grid block data to obtain simulation results. If the simulation results indicate the presence of local abnormal data, the preset air conditioning system can be controlled in a timely manner to adjust the airflow organization, providing a reasonable airflow organization for the target building. This not only reduces the energy consumption of the air conditioning system but also ensures the stable operation of various devices within the target building, thereby solving the technical problem in related technologies where real-time simulation and adjustment of airflow organization is impossible.

[0100] Optionally, the construction unit includes: a first determining module, used to determine the building volume information, the equipment location information and equipment volume information of each piece of equipment in the target building based on the building information of the target building; a first construction module, used to construct a three-dimensional model based on the building volume information, equipment location information and equipment volume information; a second determining module, used to determine the equipment parameters of each piece of equipment and to acquire the environmental parameters of the target building using preset sensors, wherein the preset sensors are pre-deployed on the target building; and a first uploading module, used to upload the equipment parameters and environmental parameters to the three-dimensional model to obtain a digital twin model of the building.

[0101] Optionally, the segmentation unit includes: a third determining module, used to determine the length, width and height of the target building based on building information; a fourth determining module, used to determine the number of length segments, width segments and height segments based on the length, width and height respectively; and a first segmentation module, used to segment the long side, wide side and high side of the building digital twin model according to the number of length segments, width segments and height segments respectively, to obtain N grid blocks.

[0102] Optionally, the determining unit includes: a first positioning module for locating the center point of a grid block; a first calculation module for calculating point data of the center point based on preset data, wherein the point data includes: temperature value, humidity value, and wind speed value; and a first characterization module for characterizing the point data as grid block data of the grid block to which the center point belongs.

[0103] Optionally, the simulation unit includes: a first selection module, used to select all temperature values ​​in all grid block data at the same time point, and generate a temperature map for the time point based on all temperature values; a second selection module, used to select all humidity values ​​in all grid block data at the same time point, and generate a humidity map for the time point based on all humidity values; a third selection module, used to select all wind speed values ​​in all grid block data at the same time point, and generate a wind speed map for the time point based on all wind speed values; and a first generation module, used to generate simulation results based on the temperature map, humidity map, and wind speed map for each time point.

[0104] Optionally, the adjustment device further includes: a first division module, used to divide the building digital twin model into M regions after simulating the airflow organization based on all grid block data and obtaining the simulation results, where M is a positive integer; a first configuration module, used to configure the parameter threshold range of each region based on the functional requirements of each region; a fifth determination module, used to determine the region to which each grid block belongs; and a sixth determination module, used to determine that the target grid block data is local abnormal data when the target grid block data does not belong to the target parameter threshold range, wherein the target parameter threshold range is the parameter threshold range corresponding to the target region to which the target grid block belongs, as indicated by the target grid block data.

[0105] Optionally, the adjustment unit includes: a seventh determining module, used to execute step 1, determining the target air conditioner based on the air conditioner sorting result of the target grid block, wherein the target air conditioner is the air conditioner closest to the target grid block; a first adjusting module, used to execute step 2, adjusting the air conditioner parameters of the target air conditioner until the simulation result indicates that there is no local abnormal data or the air conditioner parameters of the target air conditioner are adjusted to the maximum threshold; a fourth selecting module, used to execute step 3, selecting the next air conditioner based on the air conditioner sorting result and adjusting the air conditioner parameters of the next air conditioner when the air conditioner parameters of the target air conditioner are adjusted to the maximum threshold, wherein the next air conditioner is the air conditioner closest to the target grid block in the preset air conditioner system excluding the air conditioners whose air conditioner parameters have been adjusted, and the next air conditioner is characterized as the new target air conditioner; and a first execution module, used to repeatedly execute step 3 until the simulation result indicates that there is no local abnormal data or the air conditioner parameters of all air conditioners in the preset air conditioner system are adjusted to the maximum threshold.

[0106] Optionally, before determining the target air conditioner based on the air conditioner sorting results of the target grid block, the system further includes: an eighth determining module, used to determine the center point position of the center point of each grid block and the air conditioner center point position of each air conditioner in the preset air conditioning system; a second calculation module, used to calculate the distance between the center point and each air conditioner center point based on the center point position and the air conditioner center point position; and a first sorting module, used to sort all distances to obtain the air conditioner sorting results of the grid block.

[0107] The aforementioned adjustment device may also include a processor and a memory. The aforementioned construction unit 30, segmentation unit 31, determination unit 32, simulation unit 33, adjustment unit 34, etc., are all stored in the memory as program units, and the processor executes the aforementioned program units stored in the memory to realize the corresponding functions.

[0108] The aforementioned processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and by adjusting kernel parameters, the airflow organization of the preset air conditioning system can be adjusted based on simulation results, provided that local anomalies are indicated by the simulation results.

[0109] The aforementioned memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0110] This application also provides a computer program product that, when executed on a data processing device, is suitable for executing an initialization program with the following method steps: constructing a digital twin model of the building based on the building information of the target building; dividing the digital twin model of the building into N grid blocks; determining the grid block data of each grid block based on preset data; simulating the airflow organization based on all grid block data; obtaining simulation results; and, if the simulation results indicate the existence of local abnormal data, controlling a preset air conditioning system to adjust the airflow organization based on the simulation results.

[0111] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the above-described airflow organization adjustment method.

[0112] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the above-described airflow organization adjustment method.

[0113] Figure 4 This is a hardware structure block diagram of an electronic device (or mobile device) for an airflow organization adjustment method according to an embodiment of the present invention. Figure 4 As shown, an electronic device may include one or more ( Figure 4 The processor 402 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and the memory 404 for storing data may also be included. In addition, it may include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a keyboard, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 4 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device described above. For example, the electronic device may also include components that are more... Figure 4 The more or fewer components shown, or having the same Figure 4 The different configurations shown.

[0114] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0115] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0116] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0117] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0118] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0119] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0120] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for adjusting airflow organization, characterized in that, include: Based on the building information of the target building, a digital twin model of the building is constructed. The digital twin model of the building is used to acquire preset data in real time. The preset data includes: environmental data and equipment data. The building digital twin model is divided into N grid blocks, where N is a positive integer; Based on the preset data, the grid block data for each grid block is determined; wherein, the grid block data is the point data of the center point of the grid block, and the point data includes: temperature value, humidity value, and wind speed value; Based on all the grid block data, the airflow organization is simulated to obtain simulation results, wherein the airflow organization is provided by a pre-deployed pre-air conditioning system in the target building; If the simulation results indicate the presence of local abnormal data, the preset air conditioning system is controlled to adjust the airflow organization based on the simulation results. After simulating the airflow organization based on all the grid block data and obtaining the simulation results, the method further includes: dividing the building digital twin model into M regions, where M is a positive integer; configuring the parameter threshold range for each region based on the functional requirements of each region; determining the region to which each grid block belongs; and determining the target grid block data as the local abnormal data when the target grid block data does not belong to the target parameter threshold range, wherein the target parameter threshold range is the parameter threshold range corresponding to the target region to which the target grid block indicated by the target grid block data belongs. The method of controlling the preset air conditioning system to adjust the airflow organization based on the simulation results includes: Step 1, determining the target air conditioner based on the air conditioner sorting results of the target grid block, wherein the target air conditioner is the air conditioner closest to the target grid block, and the air conditioner sorting results are obtained by sorting the distances between the center point position of the center point of each grid block and the center point position of the air conditioner center point of each air conditioner in the preset air conditioning system; Step 2, adjusting the air conditioning parameters of the target air conditioner until the simulation results indicate that there is no local abnormal data or the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold; Step 3, when the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold, selecting the next air conditioner based on the air conditioner sorting results and adjusting the air conditioning parameters of the next air conditioner, wherein the next air conditioner is the air conditioner closest to the target grid block in the preset air conditioning system other than the air conditioner whose air conditioning parameters have been adjusted, and the next air conditioner is represented as the new target air conditioner; repeating step 3 until the simulation results indicate that there is no local abnormal data or the air conditioning parameters of all air conditioners in the preset air conditioning system are adjusted to the maximum threshold.

2. The adjustment method according to claim 1, characterized in that, The steps for constructing a digital twin model of a building based on its architectural information include: Based on the building information of the target building, determine the building volume information, the equipment location information and equipment volume information of each piece of equipment within the target building; A three-dimensional model is constructed based on the building volume information, the equipment location information, and the equipment volume information. The equipment parameters of each device are determined, and the environmental parameters of the target building are acquired using preset sensors, wherein the preset sensors are pre-deployed on the target building; The equipment parameters and environmental parameters are uploaded to the 3D model to obtain the building digital twin model.

3. The adjustment method according to claim 1, characterized in that, The step of dividing the building digital twin model into N grid blocks includes: Based on the building information, determine the length, width, and height of the target building; Based on the length, the width, and the height, determine the number of length segments, the number of width segments, and the number of height segments, respectively; Based on the length segmentation number, the width segmentation number, and the height segmentation number, the long side, wide side, and high side of the building digital twin model are respectively segmented to obtain N grid blocks.

4. The adjustment method according to claim 1, characterized in that, The step of determining the grid block data for each grid block based on the preset data includes: Locate the center point of the grid block; Based on the preset data, calculate the point data of the center point; The point data is represented as the grid block data of the grid block to which the center point belongs.

5. The adjustment method according to claim 4, characterized in that, The steps for simulating the airflow organization based on all the grid block data and obtaining simulation results include: Select all the temperature values ​​in all the grid block data at the same time point, and generate a temperature map for the time point based on all the temperature values; Select all humidity values ​​from all grid block data at the same time point, and generate a humidity map for that time point based on all humidity values; Select all the wind speed values ​​in all the grid block data at the same time point, and generate a wind speed map for the time point based on all the wind speed values; The simulation results are generated based on the temperature map, humidity map, and wind speed map at each of the stated time points.

6. The adjustment method according to claim 1, characterized in that, Before determining the target air conditioner based on the air conditioner sorting results of the target grid block, the process also includes: Determine the center point position of the center point of each of the grid blocks and the center point position of the air conditioner center point of each air conditioner in the preset air conditioning system; Based on the location of the center point and the location of the air conditioner center point, calculate the distance between the center point and each of the air conditioner center points; Sort all distances to obtain the air conditioner sorting result for the grid blocks.

7. An airflow organization adjustment device, characterized in that, include: A construction unit is used to construct a digital twin model of a building based on the building information of the target building. The digital twin model of the building is used to acquire preset data in real time. The preset data includes: environmental data and equipment data. A segmentation unit is used to divide the building digital twin model into N grid blocks, where N is a positive integer; The determining unit is used to determine the grid block data of each grid block based on the preset data; wherein the grid block data is the point data of the center point of the grid block, and the point data includes: temperature value, humidity value, and wind speed value; The simulation unit is used to simulate the airflow organization based on all the grid block data and obtain simulation results, wherein the airflow organization is provided by a pre-deployed air conditioning system in the target building; An adjustment unit is configured to, based on the simulation results indicating the presence of local abnormal data, control the preset air conditioning system to adjust the airflow organization. The adjustment device further includes: a first division module, used to divide the building digital twin model into M regions after simulating the airflow organization based on all the grid block data and obtaining the simulation results, where M is a positive integer; a first configuration module, used to configure the parameter threshold range of each region based on the functional requirements of each region; a fifth determination module, used to determine the region to which each grid block belongs; and a sixth determination module, used to determine that the target grid block data is the local abnormal data when the target grid block data does not belong to the target parameter threshold range, wherein the target parameter threshold range is the parameter threshold range corresponding to the target region to which the target grid block indicated by the target grid block data belongs. The adjustment unit includes: a seventh determining module, used to execute step 1, determining a target air conditioner based on the air conditioner sorting result of the target grid block, wherein the target air conditioner is the air conditioner closest to the target grid block, and the air conditioner sorting result is obtained by sorting the distances between the center point position of the center point of each grid block and the center point position of the air conditioner center point of each air conditioner in the preset air conditioning system; a first adjusting module, used to execute step 2, adjusting the air conditioning parameters of the target air conditioner until the simulation result indicates that there is no local abnormal data or the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold; a fourth selecting module, used to execute step 3, selecting the next air conditioner based on the air conditioner sorting result and adjusting the air conditioning parameters of the next air conditioner when the air conditioning parameters of the target air conditioner are adjusted to the maximum threshold, wherein the next air conditioner is the air conditioner closest to the target grid block in the preset air conditioning system other than the air conditioner whose air conditioning parameters have been adjusted, and the next air conditioner is characterized as the new target air conditioner; and a first execution module, used to repeat step 3 until the simulation result indicates that there is no local abnormal data or the air conditioning parameters of all air conditioners in the preset air conditioning system are adjusted to the maximum threshold.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform the airflow organization adjustment method according to any one of claims 1 to 6.

9. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the airflow organization adjustment method according to any one of claims 1 to 6.

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