Data center machine room parameter adjusting method and device, storage medium and electronic equipment

Abstract

The invention relates to a data center machine room parameter adjusting method and device, a storage medium and electronic equipment, and the method comprises the steps: constructing a three-dimensional physical model according to the actual building structure, equipment configuration, equipment space distribution characteristics and the physical interaction relation between equipment of a data center machine room; configuration parameters of all devices in the three-dimensional physical model and environment parameters of the data center machine room are obtained, parameter assignment is conducted on the three-dimensional physical model, fluid dynamics numerical simulation is conducted on the assigned three-dimensional physical model, and a numerical simulation model is obtained; obtaining current operation parameters, temperature and humidity parameters and environmental parameters of the data center machine room, inputting the parameters into the numerical simulation model to obtain a numerical simulation prediction data set, and obtaining a machine room regulation and control strategy based on the numerical simulation prediction data set and a pre-constructed mathematical model; and adjusting the temperature and humidity of the data center machine room according to the machine room regulation and control strategy. The operation efficiency of the data center machine room can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data center energy saving, and in particular to a data center room parameter adjustment method and device, a storage medium and electronic equipment. BACKGROUND

[0002] With the development of the Internet and cloud computing business, super-large scale data centers have grown explosively. In computer-laid dense data center rooms, in order to make computers in a relatively optimal operating state, the data center room parameters need to be controlled so that they operate in a suitable environment, for example, within a preset temperature and humidity range.

[0003] At present, most data center rooms rely on the temperature and humidity sensors built in the precision air conditioning system to monitor the temperature and humidity conditions in the data center room. Based on the difference between the preset temperature and humidity and the actual temperature and humidity detected by the temperature and humidity sensor, the fan speed and compressor load and other key energy consumption parameters of the air conditioning system are adjusted in a linear adjustment mode, so that the actual temperature and humidity in the data center room is consistent with the preset temperature and humidity. However, the temperature and humidity adjustment method of the data center room only adjusts according to the regional temperature and humidity detected by the laid temperature and humidity sensor, and does not fully consider various factors affecting the heat dissipation efficiency of the data center room, such as different computer layout densities in different regions, which will cause different temperature and humidity data in different regions, resulting in uneven temperature distribution in the data center room, which may cause the computers in the local area to not be in a suitable temperature and humidity range, reducing the operating efficiency of the data center room. Further, the adjustment method often operates the air conditioning system in a high load state, which not only affects the stability and equipment life of the data center room, but also causes a large amount of energy waste. SUMMARY

[0004] Therefore, the present application provides a data center room parameter adjustment method and device, a storage medium and electronic equipment.

[0005] Specifically, the present application is realized by the following technical solutions: According to a first aspect of the present application, a data center room parameter adjustment method is provided, which comprises: constructing a three-dimensional physical model according to the actual building structure, equipment configuration, equipment space distribution characteristics and physical interaction relationship between equipment of the data center room; obtaining configuration parameters of each equipment in the three-dimensional physical model and environmental parameters of the data center room, performing parameter assignment on the three-dimensional physical model, performing fluid dynamics numerical simulation on the assigned three-dimensional physical model, and obtaining a numerical simulation model; acquire current operation parameters, temperature and humidity parameters and environment parameters of the data center machine room, input the numerical simulation model to obtain a numerical simulation prediction data set, and acquire the machine room control strategy based on the numerical simulation prediction data set and a pre-constructed mathematical model; adjust the temperature and humidity of the data center machine room according to the machine room control strategy.

[0006] Optionally, the fluid dynamics numerical simulation on the assigned three-dimensional physical model is performed to acquire the numerical simulation model, including: a plurality of operation parameter groups of each device in the data center machine room are set; for each operation parameter group, historical temperature and humidity parameters and historical environment parameters of the data center machine room in a preset time period are acquired; the operation parameter group, the historical temperature and humidity parameters and the historical environment parameters at the same time are input into the assigned three-dimensional physical model, so that the assigned three-dimensional physical model performs fluid dynamics numerical simulation based on the input parameters to acquire a numerical simulation data set containing temperature and humidity parameters in the preset time period; based on the temperature and humidity parameters at a target time in the numerical simulation data set, and the historical temperature and humidity parameters at the target time acquired, the assigned three-dimensional physical model is subjected to a reverse transfer operation.

[0007] Optionally, after the numerical simulation prediction data set is obtained, before the machine room control strategy is acquired based on the numerical simulation prediction data set and the pre-constructed mathematical model, the method further includes: in response to the temperature and humidity parameter values in the numerical simulation prediction data set being within a pre-set temperature and humidity parameter value range, ending the process; in response to the temperature and humidity parameter values in the numerical simulation prediction data set being beyond the pre-set temperature and humidity parameter value range, performing the step of acquiring the machine room control strategy based on the numerical simulation prediction data set and the pre-constructed mathematical model.

[0008] Optionally, in response to the temperature and humidity parameter values in the numerical simulation prediction data set being beyond the pre-set temperature and humidity parameter value range, including: in response to the temperature and humidity parameter values of any computer device in the numerical simulation prediction data set being beyond the pre-set temperature and humidity parameter value range, confirming that the temperature and humidity parameter values in the numerical simulation prediction data set are beyond the pre-set temperature and humidity parameter value range.

[0009] Optionally, in response to the temperature and humidity parameter values in the numerical simulation prediction data set being beyond the pre-set temperature and humidity parameter value range, including: generate a temperature distribution cloud image and a humidity distribution cloud image inside the data center machine room based on the numerical simulation prediction data set; acquire a high temperature distribution value and a low temperature distribution value corresponding to a highest temperature area and a lowest temperature area in the temperature distribution cloud picture respectively, and acquire a high humidity distribution value and a low humidity distribution value corresponding to a highest humidity area and a lowest humidity area in the humidity distribution cloud picture respectively; In response to the high temperature distribution value and the low temperature distribution value being within the temperature parameter value range and the high humidity distribution value and the low humidity distribution value being within the humidity parameter value range, it is confirmed that the temperature and humidity parameter values in the numerical simulation prediction data set do not exceed the pre-set temperature and humidity parameter value range.

[0010] Optionally, the machine room regulation strategy is acquired based on the numerical simulation prediction data set and the pre-constructed mathematical model, and the machine room regulation strategy comprises: The numerical simulation prediction data set is input into the pre-constructed mathematical model, the numerical simulation prediction data set is run according to a pre-set optimization algorithm, and the machine room regulation strategy is acquired, wherein the temperature and humidity regulation parameter values in the machine room regulation strategy are within the pre-set temperature and humidity parameter value range.

[0011] Optionally, the configuration parameters comprise a power range, an electricity load, and a heat dissipation efficiency of the computer, and a cold water temperature range, a flow range of the air conditioning system, a supply air volume range of the fresh air system, a humidification volume range of the humidification system, a rated power of the automatic control system, and a rated power of the lighting system.

[0012] The data center machine room parameter regulation method in the technical solution comprises the following steps: constructing a three-dimensional physical model according to the actual building structure, equipment configuration, equipment space distribution characteristics, and physical interaction relationship between equipment of the data center machine room; acquiring configuration parameters of each equipment in the three-dimensional physical model and environment parameters of the data center machine room, performing parameter assignment on the three-dimensional physical model, performing fluid dynamics numerical simulation on the assigned three-dimensional physical model, and acquiring a numerical simulation model; acquiring current operation parameters, temperature and humidity parameters, and environment parameters of the data center machine room, inputting the numerical simulation model, obtaining a numerical simulation prediction data set, acquiring a machine room regulation strategy based on the numerical simulation prediction data set and a pre-constructed mathematical model, and adjusting the temperature and humidity of the data center machine room according to the machine room regulation strategy.

[0013] According to a second aspect of the present application, a data center room parameter adjustment device is provided, the data center room parameter adjustment device comprises: a model construction module configured to construct a three-dimensional physical model according to an actual building structure, equipment configuration, equipment space distribution characteristics and physical interaction relationship between equipment of the data center room; a model training module configured to obtain configuration parameters of each equipment in the three-dimensional physical model and environment parameters of the data center room, perform parameter assignment on the three-dimensional physical model, perform fluid dynamics numerical simulation on the assigned three-dimensional physical model, and obtain a numerical simulation model; a control strategy acquisition module configured to obtain current operation parameters, temperature and humidity parameters and environment parameters of the data center room, input the numerical simulation model, obtain a numerical simulation prediction data set, and obtain a room control strategy based on the numerical simulation prediction data set and a pre-constructed mathematical model; a parameter control module configured to adjust temperature and humidity of the data center room according to the room control strategy.

[0014] According to a third aspect of the present application, a storage medium having a computer program stored thereon is provided, the program being executed by a processor to implement steps of the data center room parameter adjustment method in any possible implementation manner of the first aspect.

[0015] According to a fourth aspect of the present application, an electronic device is provided, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing steps of the data center room parameter adjustment method in any possible implementation manner of the first aspect when executing the program. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application together with the specification.

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or related description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without creative labor.

[0018] Figure 1 A flowchart of a data center room parameter adjustment method provided by an embodiment of the present application; Figure 2 A schematic diagram of a data center room parameter adjustment device provided by an embodiment of the present application; Figure 3 A structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work belong to the protection scope of the present application.

[0020] In the related art, the data center machine room relies on the temperature and humidity sensor built in the air conditioning system to monitor the temperature and humidity conditions in the data center machine room, and based on the difference between the preset temperature and humidity and the actual detected temperature and humidity of the region by the temperature and humidity sensor, the key energy consumption parameters such as the fan speed and the load of the compressor of the air conditioning system are adjusted in a linear adjustment mode, so that the actual temperature and humidity and the preset temperature and humidity are consistent. The data center machine room temperature and humidity adjustment method, since it only adjusts according to the temperature detected by the temperature and humidity sensor arranged in the air conditioning system, it fails to fully consider various factors affecting the heat dissipation efficiency of the data center machine room, for example, the following important influencing factors are not considered: Heat dissipation density of computers: different types of computers are arranged in the data center machine room, and the heat dissipation requirements of different types of computers are different, and the heat dissipation density directly affects the temperature distribution of the data center machine room, so that the temperature distribution of the data center machine room is uneven, which may cause the computers in the local area to be out of the appropriate temperature and humidity range.

[0021] Real-time change of load: with the fluctuation of the data center machine room traffic, the computing load of each computer will change in real time, thereby affecting the heat dissipation requirement, and the air conditioning system needs to respond to this change in time.

[0022] Influence of humidification system: humidification operation will change the humidity level in the data center machine room, indirectly affecting temperature perception and heat dissipation efficiency, which needs to be fully considered in the adjustment strategy.

[0023] Role of fresh air system: fresh air introduction not only concerns air quality, but also may have a significant impact on the temperature of the data center machine room, which needs to be considered in the current adjustment logic.

[0024] Airflow organization of data center machine room space: the airflow path and distribution inside the data center machine room are crucial to heat dissipation, and unreasonable airflow organization often leads to uneven temperature field.

[0025] Due to the fact that the above-mentioned influencing factors are not considered in the temperature and humidity regulation process, the temperature distribution in the data center room is often uneven, which may cause the computers in the local area to be out of the appropriate temperature and humidity range, thereby resulting in low operation efficiency of the data center room; further, the air conditioning system often operates in a high load state, which not only affects the stability and equipment life of the data center room, but also leads to a large amount of energy waste.

[0026] In the embodiment, a more intelligent and comprehensive temperature and humidity regulation strategy is explored to comprehensively optimize the heat dissipation management of the data center room, and a multi-dimensional environment perception adaptive regulation method based on the data center room is proposed. The environment control system such as the refrigeration system (air conditioning system), humidification system and fresh air system in the data center room is combined with the automatic control system, and according to data acquisition, numerical simulation analysis, mathematical model iterative calculation and automatic control, the overall energy saving of the data center room is realized, the energy consumption of the data center room is reduced, and the stability and operation efficiency of the data center room are improved.

[0027] In the embodiment, specifically, according to the structure, equipment layout and load of the data center room, a series of processes such as data acquisition, numerical simulation analysis, mathematical iterative calculation and automatic control are used to design an energy-saving method of comprehensive linkage of the refrigeration system, humidification system, fresh air system and automatic control system in the data center room, so as to propose a highly integrated and intelligent environment optimization and energy efficiency management solution for complex and variable data center room structure and equipment layout. The scheme realizes accurate prediction and dynamic regulation of the internal microenvironment of the data center room by constructing a refined physical model and deeply integrating advanced computational fluid dynamics (CFD, Computational Fluid Dynamics) numerical simulation technology, thereby maximizing the overall energy efficiency and operation stability of the data center room.

[0028] Referring to Figure 1 The embodiment of the present application provides a data center room parameter adjustment method, which can include the following steps: S101, according to the actual building structure, equipment configuration, equipment space distribution characteristics and physical interaction relationship between equipment of the data center room, a three-dimensional physical model is constructed; In this embodiment, as an optional implementation, the equipment configuration includes, but is not limited to: computers, air conditioning systems, humidification systems, fresh air systems, automatic control systems, and lighting systems. Based on the actual building structure, equipment configuration, spatial distribution characteristics, and physical interaction relationships between devices in the data center, a detailed three-dimensional physical model is constructed using high-precision three-dimensional modeling technology. This ensures that the constructed three-dimensional physical model not only accurately reflects the geometric shape of each device within the data center but also fully considers the physical interaction relationships between various devices (e.g., computers, air conditioning systems), making it consistent with the actual layout of the data center.

[0029] In this embodiment, as an optional implementation, a three-dimensional physical model containing the geometric shape of each device is constructed using computer-aided design (CAD), finite element method, finite difference method, and finite volume method.

[0030] S102. Obtain the configuration parameters of each device in the three-dimensional physical model and the environmental parameters of the data center computer room, assign parameter values ​​to the three-dimensional physical model, perform fluid dynamics numerical simulation on the assigned three-dimensional physical model, and obtain the numerical simulation model. In this embodiment, as an optional implementation, the configuration parameters include, but are not limited to: the power range, electrical load, and heat dissipation efficiency of the computer; the chilled water temperature range and flow rate range of the air conditioning system; the air supply volume range of the fresh air system; the humidification capacity range of the humidification system; the rated power of the automatic control system; and the rated power of the lighting system. The environmental parameters of the data center include, but are not limited to: the temperature and humidity inside the data center and the temperature and humidity outside the data center.

[0031] In this embodiment, the three-dimensional physical model is initialized according to the configuration parameters and environmental parameters, that is, the parameters of each device contained in the three-dimensional physical model are assigned values.

[0032] In this embodiment, as an optional embodiment, a fluid dynamics numerical simulation is performed on the assigned three-dimensional physical model to obtain a numerical simulation model, including: Configure multiple operating parameter groups for each device in the data center computer room; For each set of operating parameters, obtain the historical temperature and humidity parameters and historical environmental parameters of the data center within a preset time period; The three-dimensional physical model is assigned values ​​for the same set of operating parameters, historical temperature and humidity parameters, and historical environmental parameters at the same time. The assigned three-dimensional physical model performs fluid dynamics numerical simulation based on the input parameters to obtain a numerical simulation dataset containing temperature and humidity parameters within a preset time period. Based on the temperature and humidity parameters of the target time in the numerical simulation data set, and the historical temperature and humidity parameters obtained at the target time, the assigned three-dimensional physical model is subjected to a reverse transfer operation.

[0033] In this embodiment, the assigned three-dimensional physical model is subjected to iterative operation training. By obtaining training data sets corresponding to different sets of operating parameters, each set of operating parameters corresponds to a training data set. By setting the operating parameters of the data center room, the devices in the data center room operate according to the respectively set operating parameters for a pre-set time period. During the time period, the temperature and humidity parameters and the environmental parameters are sampled according to the set sampling period. As an optional embodiment, the historical operating parameters of the computer equipment, the cold water temperature and flow of the air conditioning system, the supply air volume of the fresh air system, the humidification volume of the humidification system, the power of the lighting system, and the historical environmental parameters of the data center room, such as temperature and humidity, are obtained. In addition, the historical temperature and humidity parameters of each computer equipment are obtained. The historical operating parameters, historical environmental parameters, and historical temperature and humidity parameters are spliced to construct a key parameter set, which is input into the assigned three-dimensional physical model as a boundary condition. According to the pre-set CFD numerical simulation algorithm, multi-dimensional and high-precision environmental simulation is performed to obtain a numerical simulation data set for a future time period. As an optional embodiment, the numerical simulation data set includes temperature and humidity parameters.

[0034] In this embodiment, as an optional embodiment, the CFD numerical simulation algorithm includes but is not limited to: Semi-Implicit Method for Pressure-Linked Equations (SMPLE, Semi-Implicit Method for Pressure-Linked Equations) algorithm, SIMPLE-Consistent (SMPLEC, SIMPLE-Consistent) algorithm, and Pressure Implicit with Splitting of Operators (PISO, Pressure Implicit with Splitting of Operators) algorithm.

[0035] S103, obtaining the current operating parameters, temperature and humidity parameters, and environmental parameters of the data center room, inputting the numerical simulation model, obtaining a numerical simulation prediction data set, and based on the numerical simulation prediction data set and the pre-constructed mathematical model, obtaining a room control strategy; In this embodiment, as an optional embodiment, the data center room parameters include but are not limited to: operating parameters, temperature and humidity parameters, and environmental parameters. Based on the data center room parameters, fluid dynamics numerical simulation is performed using the numerical simulation model to obtain a numerical simulation prediction data set. The numerical simulation prediction data set is input into the pre-constructed mathematical model, and through the calculation and analysis of the complex algorithm in the mathematical model, the optimal room control strategy is obtained.

[0036] In this embodiment, as an optional embodiment, after obtaining the numerical simulation prediction data set, before obtaining the machine room regulation strategy based on the numerical simulation prediction data set and the pre-constructed mathematical model, the method further comprises: in response to the temperature and humidity parameter values in the numerical simulation prediction data set being within the pre-set temperature and humidity parameter value range, ending the process; in response to the temperature and humidity parameter values in the numerical simulation prediction data set exceeding the pre-set temperature and humidity parameter value range, performing the step of obtaining the machine room regulation strategy based on the numerical simulation prediction data set and the pre-constructed mathematical model.

[0037] In this embodiment, as an optional embodiment, in response to the temperature and humidity parameter values in the numerical simulation prediction data set exceeding the pre-set temperature and humidity parameter value range, comprising: in response to the temperature and humidity parameter values of any computer device in the numerical simulation prediction data set exceeding the pre-set temperature and humidity parameter value range, confirming that the temperature and humidity parameter values in the numerical simulation prediction data set exceed the pre-set temperature and humidity parameter value range.

[0038] In this embodiment, as another optional embodiment, in response to the temperature and humidity parameter values in the numerical simulation prediction data set exceeding the pre-set temperature and humidity parameter value range, comprising: generating a temperature distribution cloud map and a humidity distribution cloud map of the internal environment of the data center machine room based on the numerical simulation prediction data set; obtaining high temperature distribution values and low temperature distribution values corresponding to the highest temperature region and the lowest temperature region in the temperature distribution cloud map, and high humidity distribution values and low humidity distribution values corresponding to the highest humidity region and the lowest humidity region in the humidity distribution cloud map; in response to the high temperature distribution values and the low temperature distribution values being within the temperature parameter value range, and the high humidity distribution values and the low humidity distribution values being within the humidity parameter value range, confirming that the temperature and humidity parameter values in the numerical simulation prediction data set do not exceed the pre-set temperature and humidity parameter value range.

[0039] In this embodiment, based on the numerical simulation prediction data set, an airflow organization vector diagram can also be generated, so that based on the temperature distribution cloud map, the humidity distribution cloud map and the airflow organization vector diagram, the subtle differences and potential problem points of the data center machine room environment can be intuitively displayed.

[0040] In this embodiment, as an optional embodiment, obtaining the machine room regulation strategy based on the numerical simulation prediction data set and the pre-constructed mathematical model comprises: inputting the numerical simulation prediction data set into the pre-constructed mathematical model, running the numerical simulation prediction data set according to the pre-set optimization algorithm, and obtaining the machine room regulation strategy, wherein the temperature and humidity adjustment parameter values in the machine room regulation strategy are within the pre-set temperature and humidity parameter value range.

[0041] In this embodiment, as an optional embodiment, the mathematical model can be obtained by corresponding and targeted retraining according to the numerical simulation model. For example, by setting the temperature and humidity adjustment parameter value in the parameter value range of the temperature and humidity parameter value output by the numerical simulation model, the numerical simulation is performed according to the input numerical simulation prediction data set to obtain other parameter values, for example, the cold water temperature and flow of the air conditioning system, the supply air volume of the fresh air system, and the humidification amount of the humidification system, wherein the other parameter values do not include the running parameters of the computer equipment and the power of the lighting system. The numerical simulation is performed based on this mode to obtain the corresponding mathematical model.

[0042] S104, adjusting the temperature and humidity of the data center machine room according to the machine room regulation strategy.

[0043] In this embodiment, as an optional embodiment, the machine room regulation strategy is input into the server of the automatic control system, so that the server adjusts the temperature and humidity of the data center machine room according to the machine room regulation strategy.

[0044] In this embodiment, the machine room regulation strategy is imported into the corresponding server of the automatic control system (automatic control system). The server adaptively sends accurate corresponding instructions to the devices such as the air conditioning system, the fresh air unit of the fresh air system, the chiller unit, and the humidifier of the humidification system according to the calculation result of the machine room regulation strategy, dynamically adjusts the running parameters such as refrigerating capacity, fan speed, humidification amount, refrigeration load, valve opening degree, and supply air volume, to realize accurate control of the environmental parameters.

[0045] The data center machine room parameter adjustment method of this embodiment has high adaptability and feedback mechanism. Specifically, when the power load of the computer equipment in the data center machine room fluctuates due to changes in computing tasks or the water supply conditions change due to external environmental factors (such as outdoor temperature and fresh air temperature and humidity) due to external disturbances, the changes (current running parameters, temperature and humidity parameters, and environmental parameters) are captured and collected in real time or according to the set collection period, input into the numerical simulation model to automatically adjust the boundary conditions of the numerical simulation in the numerical simulation model, and re-perform numerical simulation calculation to generate a new machine room regulation scheme or machine room regulation strategy, thereby forming a closed-loop, self-circulating iterative optimization system, ensuring that the data center machine room environment (temperature and humidity) is always maintained in an optimal state, and effectively improving the energy efficiency ratio and operation efficiency.

[0046] In this embodiment, through data center machine room physical model establishment, boundary data collection for CFD numerical simulation, simulation results into mathematical model calculation, and automatic control of the power and environmental equipment by the automatic control system guided by the calculated optimal machine room regulation strategy, a repeated iterative cycle process is formed.

[0047] The following takes a specific embodiment as an example to explain the method of the embodiment in detail.

[0048] The method of the embodiment is applied to two data center rooms with an area of 500 square meters and an IT load of about 600 KW. After calculation and statistics, the auxiliary facility load of the two data center rooms is reduced by 23.1 kW and 27.5.3 kW respectively, and the average monthly energy saving is 18749 degrees and 21799 degrees respectively. It is predicted that the two data center rooms can save 477,000 degrees of energy per year.

[0049] Based on the same inventive concept, as shown in Figure 2 The embodiment of the application also provides a data center room parameter adjusting device, which comprises: The model construction module 201 is configured to construct a three-dimensional physical model according to the actual building structure, equipment configuration, equipment space distribution characteristics and physical interaction relationship between the equipment in the data center room. In the embodiment, as an optional embodiment, the model construction module 201 is specifically configured to: set a plurality of operating parameter groups of the equipment in the data center room; For each operating parameter group, historical temperature and humidity parameters and historical environment parameters of the data center room in a preset time period are obtained; The operating parameter group, the historical temperature and humidity parameters and the historical environment parameters at the same time are input into the assigned three-dimensional physical model, so that the assigned three-dimensional physical model performs fluid dynamics numerical simulation based on the input parameters to obtain a numerical simulation data set containing temperature and humidity parameters in the preset time period; Based on the temperature and humidity parameters in the numerical simulation data set for the target time and the obtained historical temperature and humidity parameters at the target time, the assigned three-dimensional physical model is subjected to a reverse transfer operation.

[0050] The model training module 202 is configured to obtain configuration parameters of the equipment in the three-dimensional physical model and environment parameters of the data center room, perform parameter assignment on the three-dimensional physical model, perform fluid dynamics numerical simulation on the assigned three-dimensional physical model, and obtain a numerical simulation model. In the embodiment, as an optional embodiment, the configuration parameters include: power range, power load and heat dissipation efficiency of the computer, cold water temperature range and flow range of the air conditioning system, air supply range of the fresh air system, humidification range of the humidification system, rated power of the automatic control system and rated power of the lighting system.

[0051] The control strategy acquisition module 203 is configured to acquire the current operation parameters, the temperature and humidity parameters and the environmental parameters of the data center room, input the numerical simulation model, obtain a numerical simulation prediction data set, and acquire the room control strategy based on the numerical simulation prediction data set and a pre-constructed mathematical model. In this embodiment, as an optional embodiment, the control strategy acquisition module 203 is specifically configured to: input the numerical simulation prediction data set into the pre-constructed mathematical model, run the numerical simulation prediction data set according to a pre-set optimization algorithm, and acquire the room control strategy, wherein the temperature and humidity adjustment parameter values in the room control strategy are within the pre-set temperature and humidity parameter value range.

[0052] In this embodiment, as an optional embodiment, the control strategy acquisition module 203 is further configured to: end the process in response to the temperature and humidity parameter values in the numerical simulation prediction data set being within the pre-set temperature and humidity parameter value range; execute the step of acquiring the room control strategy based on the numerical simulation prediction data set and the pre-constructed mathematical model in response to the temperature and humidity parameter values in the numerical simulation prediction data set being out of the pre-set temperature and humidity parameter value range.

[0053] In this embodiment, as an optional embodiment, in response to the temperature and humidity parameter values in the numerical simulation prediction data set being out of the pre-set temperature and humidity parameter value range, the control strategy acquisition module 203 is further configured to: confirm that the temperature and humidity parameter values in the numerical simulation prediction data set are out of the pre-set temperature and humidity parameter value range in response to the temperature and humidity parameter values of any computer device in the numerical simulation prediction data set being out of the pre-set temperature and humidity parameter value range.

[0054] In this embodiment, as another optional embodiment, the control strategy acquisition module 203 is further configured to: generate a temperature distribution cloud image and a humidity distribution cloud image of the data center room based on the numerical simulation prediction data set; acquire a high temperature distribution value and a low temperature distribution value corresponding to a highest temperature region and a lowest temperature region in the temperature distribution cloud image respectively, and a high humidity distribution value and a low humidity distribution value corresponding to a highest humidity region and a lowest humidity region in the humidity distribution cloud image respectively; confirm that the temperature and humidity parameter values in the numerical simulation prediction data set are within the pre-set temperature and humidity parameter value range in response to the high temperature distribution value and the low temperature distribution value being within the temperature parameter value range and the high humidity distribution value and the low humidity distribution value being within the humidity parameter value range.

[0055] The parameter control module 204 is configured to adjust the temperature and humidity of the data center room according to the room control strategy.

[0056] In this embodiment, as an optional embodiment, adjusting the temperature and humidity of the data center machine room according to the machine room regulation strategy includes but is not limited to: dynamically adjusting the operating parameters of the air conditioning system, the humidification system, and the fresh air system in the data center machine room, such as refrigerating capacity, fan speed, humidification capacity, refrigeration load, valve opening degree, and air supply amount, and adjusting to the corresponding parameter values in the machine room regulation strategy. For example, the first fan speed is 1500 revolutions per minute and the second fan speed is 1200 revolutions per minute in the machine room regulation strategy, so the first fan speed is adjusted from the current speed to 1500 revolutions per minute and the second fan speed is adjusted from the current speed to 1200 revolutions per minute.

[0057] In this embodiment, by comprehensively collecting various parameters of the data center machine room, including but not limited to: data center machine room structure, equipment layout, power load, chilled water temperature, and air flow organization, and then using numerical simulation, mathematical iterative calculation, and automatic control technology, automatic adjustment of the power and environmental equipment (specifically including chiller units, air conditioning systems, humidification systems, and fresh air systems) in the data center machine room is realized, ensuring that the power and environmental equipment in the data center machine room can realize precise dynamic regulation, so that the data center machine room environment can be continuously maintained in the optimal state.

[0058] Based on the same inventive concept, the embodiment of the present application also provides a storage medium having a computer program stored thereon, and the program is executed by a processor to realize the steps of the data center machine room parameter adjustment method in any possible implementation manner described above.

[0059] Alternatively, the storage medium can be a non-transitory computer readable storage medium, for example, a non-transitory computer readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0060] Based on the same inventive concept, referring to Figure 3 , the embodiment of the present application also provides an electronic device, which includes a memory 101 (for example, a non-volatile memory), a processor 102, and a computer program stored in the memory 101 and executable on the processor 102, and the processor 102 executes the program to realize the steps of the data center machine room parameter adjustment method in any possible implementation manner described above, which can be equivalent to the data center machine room parameter adjustment device as described above, of course, the processor can also be used to process other data or calculation. The electronic device can be a PC, a server, a terminal, etc.

[0061] As Figure 3 shown, the electronic device generally also includes: a memory 103, a network interface 104, and an internal bus 105. In addition to these components, other hardware can also be included, which will not be described here.

[0062] It should be noted that the above data center machine room parameter adjusting device can be realized by software, and as a logically meaningful device, it is formed by reading the computer program instructions stored in the non-volatile memory into the memory 103 through the processor 102 of the electronic device where it is located.

[0063] Embodiments of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, in tangibly-embodied computer software or firmware, in computer hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a tangible non-transitory program carrier for execution by, or to control the operation of, data processing apparatus. Alternatively or in addition, the program instructions can be encoded on an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. The computer storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of them.

[0064] The processes and logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output. The processes and logic flows can also be performed by special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit), and the apparatus can be a special purpose logic circuitry. The processes and logic flows can also be performed by a general purpose computer selectively activated or reconfigured by a computer program stored in the computer.

[0065] Suitable computers for the execution of a computer program include, by way of example, general and / or special purpose microprocessors, or any other kind of central processing unit. Generally, a central processing unit will receive instructions and data from a read-only memory and / or a random access memory. The essential elements of a computer are a central processing unit for performing or executing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, e.g., a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device (e.g., a universal serial bus (USB) flash drive), to name just a few.

[0066] Computer readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

[0067] While the specification contains many specifics, these should not be construed as limiting the scope of any invention or of the required claims in any way. The specification and the described embodiments are merely illustrative of specific ways to make and use the many inventive features and the broadest scope of the present inventions should not be limited to the exact construction and arrangements described. Certain features described herein in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment can also be implemented in multiple embodiments or in any suitable sub-combination. Moreover, although features can be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination and the claimed combination can be directed to a sub-combination or variation of a sub-combination.

[0068] Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring this particular order, or sequential order, to achieve the desired results. In certain circumstances, multitasking and parallel processing can be advantageous. Moreover, the separation of various system modules and components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0069] Accordingly, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the process depicted in the accompanying figures can not be required to be performed in the specific order shown, or in sequential order, to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous.

[0070] It has to be noted that, in the present document, relational terms are intended only to convey a possible relationship between elements or

[0071] The foregoing is considered as illustrative only of the principles of the application. Numerous modifications and changes will readily occur to those skilled in the art, which modifications and changes are to be understood as intended to be encompassed by the general scope of the application. Accordingly, the application is not to be limited to the above described or illustrated embodiments, but is intended to encompass all embodiments consistent with the principles of the application.

Claims

1. A method for adjusting parameters in a data center computer room, characterized in that, The method comprises the following steps: constructing a three-dimensional physical model according to the actual building structure, equipment configuration, equipment space distribution characteristics and physical interaction relationship between equipment in the data center room; obtaining configuration parameters of each equipment in the three-dimensional physical model and environmental parameters of the data center room, performing parameter assignment on the three-dimensional physical model, performing fluid dynamics numerical simulation on the assigned three-dimensional physical model, and obtaining a numerical simulation model; obtaining current operating parameters, temperature and humidity parameters and environmental parameters of the data center room, inputting the numerical simulation model, obtaining a numerical simulation prediction data set, and obtaining a room control strategy based on the numerical simulation prediction data set and a pre-constructed mathematical model; adjusting the temperature and humidity of the data center room according to the room control strategy.

2. The data center room parameter adjustment method of claim 1, wherein, The method comprises the following steps: setting a plurality of operating parameter groups of each equipment in the data center room; for each operating parameter group, obtaining historical temperature and humidity parameters of the data center room and historical environmental parameters of the data center room within a preset time period; inputting the operating parameter group, the historical temperature and humidity parameters and the historical environmental parameters at the same time into the assigned three-dimensional physical model, so that the assigned three-dimensional physical model performs fluid dynamics numerical simulation based on the input parameters, and obtains a numerical simulation data set containing temperature and humidity parameters within the preset time period; performing reverse transfer operation on the assigned three-dimensional physical model based on the temperature and humidity parameters for the target time in the numerical simulation data set and the obtained historical temperature and humidity parameters for the target time.

3. The method of claim 1, wherein, After obtaining the numerical simulation prediction data set, before obtaining the room control strategy based on the numerical simulation prediction data set and the pre-constructed mathematical model, the method further comprises the following steps: in response to the temperature and humidity parameter values in the numerical simulation prediction data set being within the pre-set temperature and humidity parameter value range, ending the process; in response to the temperature and humidity parameter values in the numerical simulation prediction data set exceeding the pre-set temperature and humidity parameter value range, performing the step of obtaining the room control strategy based on the numerical simulation prediction data set and the pre-constructed mathematical model.

4. The data center room parameter adjustment method of claim 3, wherein, In response to the temperature and humidity parameter values in the numerical simulation prediction data set exceeding the pre-set temperature and humidity parameter value range, the method comprises the following steps: in response to the temperature and humidity parameter values of any computer equipment in the numerical simulation prediction data set exceeding the pre-set temperature and humidity parameter value range, confirming that the temperature and humidity parameter values in the numerical simulation prediction data set exceed the pre-set temperature and humidity parameter value range.

5. The method of claim 3, wherein, In response to the temperature and humidity parameter values in the numerical simulation prediction data set exceeding the pre-set temperature and humidity parameter value range, the method comprises the following steps: generating a temperature distribution cloud map and a humidity distribution cloud map inside the data center room based on the numerical simulation prediction data set; obtaining a high temperature distribution value and a low temperature distribution value corresponding to a highest temperature region and a lowest temperature region in the temperature distribution cloud map, and a high humidity distribution value and a low humidity distribution value corresponding to a highest humidity region and a lowest humidity region in the humidity distribution cloud map; In response to the fact that the high and low temperature distribution values ​​are within the range of temperature parameter values, and the high and low humidity distribution values ​​are within the range of humidity parameter values, it is confirmed that the temperature and humidity parameter values ​​in the numerical simulation prediction dataset do not exceed the preset temperature and humidity parameter value range.

6. The method of claim 1 to 5, wherein, The method for obtaining data center control strategies based on numerical simulation prediction datasets and pre-built mathematical models includes: The numerical simulation prediction dataset is input into a pre-built mathematical model, and the numerical simulation prediction dataset is run according to a pre-set optimization algorithm to obtain the data center control strategy. The temperature and humidity adjustment parameter values ​​in the data center control strategy are within the pre-set temperature and humidity parameter value range.

7. The method of claim 1 to 5, wherein, The configuration parameters include: the power range, electrical load, and heat dissipation efficiency of the computer; the chilled water temperature range and flow rate range of the air conditioning system; the air supply volume range of the fresh air system; the humidification volume range of the humidification system; the rated power of the automatic control system; and the rated power of the lighting system.

8. A data center room parameter adjustment apparatus, characterized by, The data center parameter adjustment device includes: The model building module is used to build a three-dimensional physical model based on the actual building structure, equipment configuration, equipment spatial distribution characteristics, and physical interaction relationships between equipment in the data center. The model training module is used to obtain the configuration parameters of each device in the 3D physical model and the environmental parameters of the data center, assign parameter values ​​to the 3D physical model, perform fluid dynamics numerical simulation on the assigned 3D physical model, and obtain the numerical simulation model. The control strategy acquisition module is used to acquire the current operating parameters, temperature and humidity parameters and environmental parameters of the data center, input them into the numerical simulation model, obtain the numerical simulation prediction dataset, and acquire the control strategy of the data center based on the numerical simulation prediction dataset and the pre-built mathematical model. The parameter control module is used to adjust the temperature and humidity of the data center according to the data center control strategy.

9. A storage medium, characterized by The storage medium stores a program or instructions, which are executed by a processor to implement the steps of the data center parameter adjustment method as described in any one of claims 1 to 7.

10. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the data center computer room parameter adjustment method according to any one of claims 1 to 7.

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