An intelligent refrigeration control method and system for a dynamic environment system of an intelligent computer room

Abstract

The present invention discloses an intelligent refrigeration control method and system for a dynamic environment system of an intelligent computing room, and relates to the technical field of air conditioning and refrigeration control. The method comprises the following steps: obtaining a cable wiring diagram in a computer room, and adjusting the partitions of the intelligent computing room in real time by combining the electric and thermal parameters obtained by combining the load status value and the temperature change rate of the equipment in the computer room; setting an air outlet allocation strategy to allocate an air outlet to each partition in the intelligent computing room; setting an air volume intelligent control algorithm to control the angle and wind intensity of each air outlet according to the load status value and the temperature change rate of the equipment in each partition in the computer room; the present invention solves the blockage of the cooling air flow path caused by excessive cable concentration, and improves the cooling efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioning and refrigeration control, and specifically to an intelligent refrigeration control method and system for a dynamic environment system of an intelligent computer room. Background Art

[0002] As data centers continue to expand and computing density increases, thermal management issues in computer rooms are becoming increasingly prominent. As an efficient data center solution, intelligent computing rooms integrate a large number of high-performance servers and network equipment, which generate a lot of heat. Traditional refrigeration systems often use a unified cooling method, which is difficult to dynamically adjust according to the changes in heat load in different areas, resulting in high energy consumption, low efficiency, and even equipment failure due to local overheating.

[0003] In recent years, the development of artificial intelligence technology and Internet of Things technology has provided new possibilities for improving the energy efficiency of data centers. By integrating advanced sensor networks, big data analysis and machine learning algorithms, refined management and intelligent control of the data center environment can be achieved, thereby significantly reducing energy consumption and improving the operating efficiency of the refrigeration system; however, the current refrigeration system usually relies on manual experience or simple control algorithms for refrigeration control, which makes it difficult to achieve precise cooling control of different areas and cannot effectively cope with the dynamic changes of equipment loads in the computer room. Based on this, an intelligent refrigeration control system is proposed, which can monitor the thermal state of each area in the computer room in real time and dynamically adjust the refrigeration strategy to achieve efficient and energy-saving refrigeration management.

[0004] For example, the existing Chinese patent with the publication number CN114997058A discloses an auxiliary method for intelligent control of air conditioners, which solves the technical problem of energy saving by intelligently controlling the air conditioner to cool the main equipment through AI algorithms; obtains the original energy consumption data of the main equipment in the computer room, and establishes a typical energy consumption model of the main equipment; obtains the operating temperature data of the main equipment in the computer room, and establishes a suitable temperature parameter model of the main equipment; predicts the energy consumption development trend of the main equipment in the computer room; divides the computer room into different partitions according to the functional classification of the main equipment, and performs energy consumption portrait modeling for each partition of the computer room according to the energy consumption development trend of the main equipment in the computer room; matches the most suitable operating temperature of the main equipment in the computer room through the suitable temperature parameter model of the main equipment, and the AI ​​algorithm mines the overall improvement space of the computer room temperature; according to the typical energy consumption model of the main equipment, establishes an energy consumption comparison self-learning question library, and automatically discovers and audits low-efficiency equipment in the computer room online. However, this design does not take into account the problem of complex cable wiring and equipment layout cooling airflow path blockage in the computer room. Therefore, the present invention provides an intelligent refrigeration control method and system for the dynamic environment system of the intelligent computing computer room. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent refrigeration control method and system for the dynamic environment system of an intelligent computer room to solve the existing problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: an intelligent refrigeration control method for a dynamic environment system of an intelligent computer room, comprising the following steps:

[0007] S1. Obtain the cable wiring diagram in the computer room, and adjust the partition of the intelligent computing room in real time by combining the electric and thermal parameters obtained by combining the load status value and temperature change rate of the equipment in the computer room;

[0008] S2. Setting an air outlet allocation strategy to allocate an air outlet to each partition in the intelligent computing room partition;

[0009] S3. Set up an intelligent air volume control algorithm to control the angle and wind intensity of each air outlet according to the equipment load status value and temperature change rate of each partition in the computer room.

[0010] A further improvement of the present invention is that the cable wiring diagram in the computer room is used to define the connecting cables of the server cabinets and network switches as the main roads, and the intelligent computing room is preliminarily divided into areas according to the main roads to obtain preliminary intelligent computing room partitions; the i-th preliminary intelligent computing room partition is divided into N×M grids, the size of each embedded grid is n×n, and the mean value of the electrothermal parameters of all equipment in each embedded grid and the cable distribution density are calculated and weighted summed to obtain the heat dissipation influence value of each embedded grid; the electrothermal parameters of the equipment are obtained by weighted summation of the load state value and the temperature change rate of the equipment in the computer room.

[0011] The present invention is further improved in that S1 also includes setting a heat dissipation impact difference threshold, recording the upper left corner embedded grid of the i-th preliminary intelligent computer room partition as the first initial traversal grid, traversing the surrounding embedded grids with an embedded grid size as the radius from the first initial traversal grid, and recording the average value ahdi of the heat dissipation impact value of the newly added embedded grid each time traversal, and the calculation formula is: ,in represents the heat dissipation impact value of the jth embedded grid traversed during the kth traversal, where k represents the number of traversals at this time; calculate the heat dissipation impact value of the first initial traversal grid and The absolute value of the difference is used to obtain the traversal heat dissipation impact difference value. When the traversal heat dissipation impact difference value is less than the heat dissipation impact difference threshold, the traversal continues. When the traversal heat dissipation impact difference value is greater than or equal to the heat dissipation impact difference threshold, the traversal is stopped, and the embedded grid before the k-th traversal is recorded as the first partition of the i-th preliminary intelligent computing room partition, and the embedded grid corresponding to the maximum heat dissipation impact during the k-th traversal is extracted as the second initial traversal grid of the i-th preliminary intelligent computing room partition. The traversal is performed in the same way as above to obtain the second partition of the i-th preliminary intelligent computing room partition, and so on until all the embedded grids in the i-th preliminary intelligent computing room partition are traversed. Then the i-th preliminary intelligent computing room partition is obtained. partitions.

[0012] A further improvement of the present invention is that the air outlet allocation strategy includes extracting the distance between the center point of any partition and each air outlet, and based on the principle of closest distance, allocating one or p air outlets to each partition to obtain an air outlet sequence for any partition. When two or more air outlets are at the same distance from the center point of the partition, a wind direction determination area is set, and the wind direction determination area is obtained by extracting the connected area between the two vertices of the area closest to the air outlet and the center point of the air outlet; it is determined whether there is a main road in the wind direction determination area, and if so, the corresponding air outlet is removed from the air outlet sequence of the partition.

[0013] The present invention is further improved in that the specific steps of the air volume intelligent control algorithm include:

[0014] S31. Set the air volume for each air outlet ,in Indicates the mean value of the electric and thermal parameters of the area corresponding to the air outlet, Indicates the target value of the electric and thermal parameters, represents the initial air volume, Indicates the set air volume adjustment coefficient. ;

[0015] S32. Set the angle adjustment parameters for each air outlet , ,in represents the initial angle, Indicates the outlet The electric and thermal parameters of each zone, , npa indicates the number of partitions corresponding to the outlet, Indicates the set air volume adjustment coefficient. ;

[0016] S33, dynamically adjust the air volume angle through the PID air volume controller, the calculation formula is:

[0017] ;

[0018] ;

[0019] in, , represents the current electric and thermal parameter error, Indicates the dynamic adjustment parameters of air volume. Indicates the angle dynamic adjustment parameter; , , Proportional parameters, integral parameters and differential parameters representing dynamic adjustment of air volume; , , It represents the proportional parameter, integral parameter and differential parameter of the dynamic adjustment of the angle, and t represents the time interval between two adjacent deviation samplings;

[0020] S34, obtaining the air volume output of the air volume intelligent control algorithm , angle output , indicating the deflection of the zone corresponding to the maximum value of the electric and thermal parameters in the zone under the jurisdiction of the outlet .

[0021] The present invention is further improved in that the cable distribution density calculation process includes: the branch cables branched from the main road are branch trunks, and the first The number of branch trunk connection points in the partition, cpn, and the number of cables corresponding to each connection point, cpcn; the first partition of the i-th preliminary intelligent computer room is calculated by nonlinear cable wiring density calculation strategy. Calculate the cable density by partition and get the cable distribution density D. , the calculation formula is:

[0022] ;

[0023] in, represents a positive number, , represents the normalization factor of the cable connection point, , represents the weighted sum of the number of cables at each connection point, Indicates the minimum cable density set, Indicates the maximum cable density of the setting.

[0024] A further improvement of the present invention is that the acquisition of the weighted sum of the number of cables at each connection point includes: obtaining the mean of the equipment load conditions of the devices connected to each cable connection point to obtain a cable connection point equipment load mean data set, calculating the proportion of the mean equipment load of each cable connection point in the sum of the data in the cable connection point equipment load mean data set to obtain the weight of each cable connection point, and then obtaining the weighted sum of the number of cables at each connection point.

[0025] A further improvement of the present invention is that the calculation formula of the equipment load state value els is:

[0026] ;

[0027] in, Indicates the device read and write speed. Indicates the device read and write speed weight, Indicates the amount of device memory. Indicates the weight of device memory. Indicates device IOPS. Indicates the device IOPS weight. Indicates the device delay. Indicates the device delay weight;

[0028] The device read and write speed is obtained by calculating the ratio of the total amount of data read or written by the device during operation to the total time required; the memory capacity is obtained by combining the ratio of the currently used memory capacity of the system to the total memory capacity; the device IOPS represents the number of read and write times of the device per second; the delay is obtained by calculating the average of the difference between the request time and the request completion time within one hour.

[0029] The present invention is further improved in that the temperature change rate is calculated by installing a temperature sensor on each device in the computer room and extracting the temperature of each device at a time interval of tt seconds within an hour starting from the current time. , floor() means round down, Indicates the temperature of the first device collected; the temperature change rate of the device ,in Indicates The temperature of the device, .

[0030] On the other hand, the present invention provides an intelligent refrigeration control system for a dynamic environment system of an intelligent computer room, comprising:

[0031] The computer room partition module obtains the cable wiring diagram in the computer room and adjusts the partition of the intelligent computing computer room in real time by combining the electric and thermal parameters obtained from the load status value and temperature change rate of the equipment in the computer room;

[0032] An air outlet allocation module is used to set an air outlet allocation strategy and allocate an air outlet to each partition in the intelligent computing room partition;

[0033] The air volume intelligent control module sets the air volume intelligent control algorithm to control the angle and wind intensity of each air outlet according to the equipment load status value and temperature change rate of each partition in the computer room.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1. The present invention first obtains the cable wiring diagram in the computer room, and adjusts the computer room intelligent computing room partition in real time in combination with the equipment load status value and temperature change rate, so as to avoid the problem of cooling airflow path blockage caused by excessive cable concentration, resulting in reduced cooling efficiency, improve the overall heat dissipation capacity of the computer room, and reduce the generation of hot spots;

[0036] 2. Through the air outlet allocation strategy, one or more air outlets are intelligently allocated to each partition, and the allocation of air outlets is dynamically adjusted according to the heat dissipation requirements of the partition, ensuring that cold air can be effectively transported to the heat concentration area and improving the cooling efficiency;

[0037] 3. Utilize the intelligent air volume control algorithm and dynamically adjust the air volume and air outlet angle through the PID controller, so that the cold air can be concentrated in the area with higher heat load, improve the response speed and effect of the refrigeration system, reduce energy consumption, and ensure that the refrigeration system can be accurately adjusted according to the actual heat load to avoid excessive or insufficient cooling. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a flow chart of an intelligent refrigeration control method for a dynamic environment system of an intelligent computer room according to the present invention;

[0039] Figure 2 This is a flow chart of intelligent computer room partitioning for an intelligent refrigeration control method of a dynamic environment system of an intelligent computer room according to the present invention;

[0040] Figure 3 This is a flow chart of the air volume intelligent control algorithm of the present invention;

[0041] Figure 4 This is a framework diagram of an intelligent refrigeration control system for a dynamic environment system of an intelligent computer room according to the present invention. DETAILED DESCRIPTION

[0042] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0043] The term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " generally indicates that the related objects are in an "or" relationship.

[0044] Example 1

[0045] Figure 1 A flowchart of an intelligent refrigeration control method for a dynamic environment system of an intelligent computer room disclosed in this embodiment is shown, and the steps are as follows:

[0046] S1. Obtain the cable wiring diagram in the computer room, and adjust the partition of the intelligent computing room in real time by combining the electric and thermal parameters obtained by combining the load status value and temperature change rate of the equipment in the computer room;

[0047] Calculate the cable distribution density, the process includes branch cables branched from the main road as branch trunks, extract the first The number of branch trunk connection points in the partition, cpn, and the number of cables corresponding to each connection point, cpcn; Since the cable wiring diagram mainly focuses on the specifications and models of cables and the connection relationship between them, rather than the specific physical width of cables or wires, in order to obtain the cable density in the cable area, the nonlinear cable wiring density calculation strategy is used to calculate the first partition of the i-th preliminary intelligent computer room. Calculate the cable density by partition and get the cable distribution density D. , since the weighted cable connection point number is already a relative value, it can be directly mapped to the density range. In this embodiment, linear mapping is used to obtain the cable distribution density, and the calculation formula is:

[0048] ;

[0049] in, Indicates the maximum number of cables. Indicates the minimum number of cables, due to and It is difficult to obtain directly. In order to avoid this problem, this embodiment uses the maximum and minimum values ​​of the number of cable connection points in the partition to indirectly estimate. The density calculation formula is adjusted by the ratio of cpn:

[0050] ;

[0051] in, represents a positive number, , represents the normalization factor of the cable connection point, , represents the weighted sum of the number of cables at each connection point, Indicates the minimum cable density set, Indicates the maximum cable density set;

[0052] The weighted sum of the number of cables at each connection point is obtained by obtaining the mean of the equipment load conditions of the devices connected to each cable connection point to obtain the cable connection point equipment load mean data set. The weight of each cable connection point is obtained by calculating the proportion of the mean equipment load of each cable connection point in the sum of the data in the cable connection point equipment load mean data set, and then the weighted sum of the number of cables at each connection point is obtained.

[0053] The calculation formula of the equipment load status value els is:

[0054] ;

[0055] in, Indicates the device read and write speed. Indicates the device read and write speed weight, Indicates the amount of device memory. Indicates the weight of device memory. Indicates device IOPS. Indicates the device IOPS weight. Indicates the device delay. Indicates the device delay weight;

[0056] The device read and write speed is obtained by calculating the ratio of the total amount of data read or written by the device during operation to the total time required; the memory capacity is obtained by combining the ratio of the currently used memory capacity of the system to the total memory capacity; the device IOPS represents the number of read and write times of the device per second; the delay is obtained by calculating the average of the difference between the request time and the request completion time within one hour.

[0057] The temperature change rate is calculated by installing a temperature sensor on each device in the computer room and extracting the temperature of each device at a time interval of tt seconds within an hour starting from the current time. , floor() means round down, represents the temperature of the first device collected, and the temperature change rate of the device is expressed as ,in Indicates The temperature of the device, .

[0058] Based on the above parameters, the intelligent computing room is partitioned. The specific process includes:

[0059] The cable wiring diagram in the computer room is used to define the connecting cables of the server cabinet and the network switch as the main road, and the intelligent computing room is preliminarily divided into regions according to the main road to obtain preliminary intelligent computing room partitions; the i-th preliminary intelligent computing room partition is divided into N×M grids, and the size of each embedded grid is n×n;

[0060] Since cable wiring affects airflow, a large number of cables in the computer room may block the path of the cooling airflow, thereby reducing the cooling efficiency. Therefore, the mean value of the electrothermal parameters of all equipment in each embedded grid and the cable distribution density are calculated and weighted summed to obtain the heat dissipation impact value of each embedded grid; the electrothermal parameters of the equipment are obtained by weighted summation of the load state value and temperature change rate of the equipment in the computer room.

[0061] Figure 2 The intelligent refrigeration control method of the dynamic environment system of an intelligent computing room in this embodiment is shown, and the intelligent computing room partition flow chart is shown; a heat dissipation impact difference threshold is set, and the upper left corner embedded grid of the i-th preliminary intelligent computing room partition is recorded as the first initial traversal grid, and the surrounding embedded grids are traversed from the first initial traversal grid with an embedded grid size as the radius. Each time the traversal is performed, the mean value ahdi of the heat dissipation impact value of the newly added embedded grid is recorded, and the calculation formula is: ,in represents the heat dissipation impact value of the jth embedded grid traversed during the kth traversal, where k represents the number of traversals at this time; calculate the heat dissipation impact value of the first initial traversal grid and The absolute value of the difference is used to obtain the traversal heat dissipation impact difference value. When the traversal heat dissipation impact difference value is less than the heat dissipation impact difference threshold, the traversal continues. When the traversal heat dissipation impact difference value is greater than or equal to the heat dissipation impact difference threshold, the traversal is stopped, and the embedded grid before the k-th traversal is recorded as the first partition of the i-th preliminary intelligent computing room partition, and the embedded grid corresponding to the maximum heat dissipation impact during the k-th traversal is extracted as the second initial traversal grid of the i-th preliminary intelligent computing room partition. The traversal is performed in the same way as above to obtain the second partition of the i-th preliminary intelligent computing room partition, and so on until all the embedded grids in the i-th preliminary intelligent computing room partition are traversed. Then the i-th preliminary intelligent computing room partition is obtained. partitions.

[0062] S2. Set an air outlet allocation strategy to allocate air outlets to each partition in the intelligent computer room partition; including extracting the distance between the center point of any partition and each air outlet, and based on the principle of the closest distance, allocate one or p air outlets to each partition to obtain the air outlet sequence of any partition. When two or more air outlets are at the same distance from the center point of the partition, set a wind direction determination area, and the wind direction determination area is obtained by extracting the connected area between the two vertices closest to the air outlet and the center point of the air outlet; determine whether there is a main road in the wind direction determination area, and if so, exclude the corresponding air outlet from the air outlet sequence of the partition. The cables in the main road will generate a lot of heat, which will generate a lot of water vapor when confronted with the cold air. Therefore, this design can avoid the harm of excessive air humidity caused by unreasonable air outlet allocation.

[0063] S3. Set up an intelligent air volume control algorithm to control the angle and wind intensity of each air outlet according to the equipment load status value and temperature change rate of each partition in the computer room.

[0064] Figure 3 The flow chart of the air volume intelligent control algorithm of this embodiment is shown; the specific steps of the air volume intelligent control algorithm include:

[0065] S31. Set the air volume for each air outlet ,in Indicates the mean value of the electric and thermal parameters of the area corresponding to the air outlet, Indicates the target value of the electric and thermal parameters, represents the initial air volume, Indicates the set air volume adjustment coefficient. ;

[0066] S32. Set the angle adjustment parameters for each air outlet , which is determined by the deviation between the electric and thermal parameters of the corresponding partition and the target electric and thermal parameters. The calculation formula is: ,in represents the initial angle, Indicates the outlet The electric and thermal parameters of each zone, , npa indicates the number of partitions corresponding to the outlet, Indicates the set air volume adjustment coefficient. ;

[0067] S33, dynamically adjust the air volume angle through the PID air volume controller, the calculation formula is:

[0068] ;

[0069] ;

[0070] in, , represents the current electric and thermal parameter error, Indicates the dynamic adjustment parameters of air volume. Indicates the angle dynamic adjustment parameter; , , Proportional parameters, integral parameters and differential parameters representing dynamic adjustment of air volume; , , It represents the proportional parameter, integral parameter and differential parameter of the dynamic adjustment of the angle, and t represents the time interval between two adjacent deviation samplings;

[0071] S34, obtaining the air volume output of the air volume intelligent control algorithm , angle output , indicating the deflection of the zone corresponding to the maximum value of the electric and thermal parameters in the zone under the jurisdiction of the outlet .

[0072] The threshold and weight settings can be set by the operator.

[0073] Example 2

[0074] Figure 4 The framework diagram of an intelligent refrigeration control system of a dynamic environment system of an intelligent computing room in this embodiment is shown. Based on the same inventive concept as that of embodiment 1, the present invention provides an intelligent refrigeration control system of a dynamic environment system of an intelligent computing room, including:

[0075] The computer room partition module obtains the cable wiring diagram in the computer room and adjusts the partition of the intelligent computing computer room in real time by combining the electric and thermal parameters obtained from the load status value and temperature change rate of the equipment in the computer room;

[0076] An air outlet allocation module is used to set an air outlet allocation strategy and allocate an air outlet to each partition in the intelligent computing room partition;

[0077] The air volume intelligent control module sets the air volume intelligent control algorithm to control the angle and wind intensity of each air outlet according to the equipment load status value and temperature change rate of each partition in the computer room.

[0078] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0080] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0082] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. An intelligent refrigeration control method for a dynamic environment system of an intelligent computer room, characterized in that: The following steps are involved: S1. Obtain the cable wiring diagram in the computer room, and adjust the partition of the intelligent computing room in real time by combining the electric and thermal parameters obtained by combining the load status value and temperature change rate of the equipment in the computer room; S2. Setting an air outlet allocation strategy to allocate an air outlet to each partition in the intelligent computing room partition; S3. Set up an intelligent air volume control algorithm to control the angle and wind intensity of each air outlet according to the equipment load status value and temperature change rate of each partition in the computer room; The cable wiring diagram in the computer room is used to define the connecting cables of the server cabinets and the network switches as the main roads, and the intelligent computing room is preliminarily divided into regions according to the main roads to obtain preliminary intelligent computing room partitions; the i-th preliminary intelligent computing room partition is divided into N×M grids, and the size of each embedded grid is n×n. The mean value of the electrical and thermal parameters of all equipment in each embedded grid and the cable distribution density are calculated, and then the weighted sum is performed to obtain the heat dissipation impact value of each embedded grid; The electrical and thermal parameters of the equipment are obtained by weighted summation of the equipment load status value and the temperature change rate in the computer room; The specific steps of the air volume intelligent control algorithm include: S31. Set the air volume for each air outlet ,in Indicates the mean value of the electric and thermal parameters of the area corresponding to the air outlet, Indicates the target value of the electric and thermal parameters, represents the initial air volume, Indicates the set air volume adjustment coefficient. ; S32. Set the angle adjustment parameters for each air outlet , ,in represents the initial angle, Indicates the outlet The electric and thermal parameters of each zone, , npa indicates the number of partitions corresponding to the outlet, Indicates the set air volume adjustment coefficient. ; S33, dynamically adjust the air volume angle through the PID air volume controller, the calculation formula is: ； ； in, , represents the current electric and thermal parameter error, Indicates the dynamic adjustment parameters of air volume. Indicates the angle dynamic adjustment parameter; , , Proportional parameters, integral parameters and differential parameters representing dynamic adjustment of air volume; , , It represents the proportional parameter, integral parameter and differential parameter of the dynamic adjustment of the angle, and t represents the time interval between two adjacent deviation samplings; S34, obtaining the air volume output of the air volume intelligent control algorithm , angle output , indicating the deflection of the zone corresponding to the maximum value of the electric and thermal parameters in the zone under the jurisdiction of the outlet ; The cable distribution density calculation process includes: extracting the branch cables branched from the main road as branch trunks, The number of branch trunk connection points in the partition, cpn, and the number of cables corresponding to each connection point, cpcn; the first partition of the i-th preliminary intelligent computer room is calculated by nonlinear cable wiring density calculation strategy. Calculate the cable density by partition and get the cable distribution density D. , the calculation formula is: ； in, represents a positive number, , represents the normalization factor of the cable connection point, , represents the weighted sum of the number of cables at each connection point, Indicates the minimum cable density set, Indicates the maximum cable density of the setting.

2. According to claim 1, the intelligent refrigeration control method of the dynamic environment system of an intelligent computer room is characterized by: The S1 also includes setting a heat dissipation impact difference threshold, recording the upper left corner embedded grid of the i-th preliminary intelligent computer room partition as the first initial traversal grid, traversing the surrounding embedded grids with an embedded grid size as the radius from the first initial traversal grid, and recording the average heat dissipation impact value of the newly added embedded grid once each traversal, and the calculation formula is: ,in represents the heat dissipation impact value of the jth embedded grid traversed during the kth traversal, where k represents the number of traversals at this time; calculate the heat dissipation impact value of the first initial traversal grid and The absolute value of the difference is used to obtain the traversal heat dissipation impact difference value. When the traversal heat dissipation impact difference value is less than the heat dissipation impact difference threshold, the traversal continues. When the traversal heat dissipation impact difference value is greater than or equal to the heat dissipation impact difference threshold, the traversal is stopped, and the embedded grid before the k-th traversal is recorded as the first partition of the i-th preliminary intelligent computing room partition, and the embedded grid corresponding to the maximum heat dissipation impact during the k-th traversal is extracted as the second initial traversal grid of the i-th preliminary intelligent computing room partition. The traversal is performed in the same way as above to obtain the second partition of the i-th preliminary intelligent computing room partition, and so on until all the embedded grids in the i-th preliminary intelligent computing room partition are traversed. Then the i-th preliminary intelligent computing room partition is obtained. partitions.

3. According to claim 2, the intelligent refrigeration control method of the dynamic environment system of an intelligent computer room is characterized by: The air outlet allocation strategy includes extracting the distance between the center point of any partition and each air outlet, and based on the principle of the closest distance, allocating one or p air outlets to each partition to obtain the air outlet sequence of any partition. When two or more air outlets are at the same distance from the center point of the partition, a wind direction determination area is set, and the wind direction determination area is obtained by extracting the connected area between the two vertices of the area closest to the air outlet and the center point of the air outlet; judging whether there is a main road in the wind direction determination area, and if so, excluding the corresponding air outlet from the air outlet sequence of the partition.

4. According to claim 3, the intelligent refrigeration control method of the dynamic environment system of an intelligent computer room is characterized in that: The method of obtaining the weighted sum of the number of cables at each connection point includes: obtaining the mean of the equipment load conditions of the devices connected to each cable connection point to obtain a cable connection point equipment load mean data set, calculating the proportion of the mean equipment load of each cable connection point in the sum of the data in the cable connection point equipment load mean data set to obtain the weight of each cable connection point, and then obtaining the weighted sum of the number of cables at each connection point.

5. According to claim 4, the intelligent refrigeration control method of the dynamic environment system of an intelligent computer room is characterized in that: The calculation formula of the equipment load status value els is: ； in, Indicates the device read and write speed. Indicates the device read and write speed weight, Indicates the amount of device memory. Indicates the weight of device memory. Indicates device IOPS. Indicates the device IOPS weight. Indicates the device delay. Indicates the device delay weight; The device read and write speed is obtained by calculating the ratio of the total amount of data read or written by the device during operation to the total time required; the memory capacity is obtained by combining the ratio of the currently used memory capacity of the system to the total memory capacity; the device IOPS represents the number of read and write times of the device per second; the delay is obtained by calculating the average of the difference between the request time and the request completion time within one hour.

6. The intelligent refrigeration control method of the dynamic environment system of an intelligent computer room according to claim 5 is characterized in that: The temperature change rate is calculated by installing a temperature sensor on each device in the computer room and extracting the temperature of each device at a time interval of tt seconds within an hour starting from the current time. , floor() means round down, Indicates the temperature of the first device collected; the temperature change rate of the device ,in Indicates The temperature of the device, .

7. An intelligent refrigeration control system for a dynamic environment system of an intelligent computer room, used to implement an intelligent refrigeration control method for a dynamic environment system of an intelligent computer room as described in any one of claims 1 to 6, characterized in that: include: The computer room partition module obtains the cable wiring diagram in the computer room and adjusts the partition of the intelligent computing computer room in real time by combining the electric and thermal parameters obtained from the load status value and temperature change rate of the equipment in the computer room; An air outlet allocation module is used to set an air outlet allocation strategy and allocate an air outlet to each partition in the intelligent computing room partition; The air volume intelligent control module sets the air volume intelligent control algorithm to control the angle and wind intensity of each air outlet according to the equipment load status value and temperature change rate of each partition in the computer room.

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