CN113175740A - Control method and device of data center air conditioner and data center - Google Patents
Control method and device of data center air conditioner and data center Download PDFInfo
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- CN113175740A CN113175740A CN202110466550.2A CN202110466550A CN113175740A CN 113175740 A CN113175740 A CN 113175740A CN 202110466550 A CN202110466550 A CN 202110466550A CN 113175740 A CN113175740 A CN 113175740A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
- F24F11/74—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity
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- H—ELECTRICITY
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- H05K—PRINTED CIRCUITS; CASINGS OR CONSTRUCTIONAL DETAILS OF ELECTRIC APPARATUS; MANUFACTURE OF ASSEMBLAGES OF ELECTRICAL COMPONENTS
- H05K7/00—Constructional details common to different types of electric apparatus
- H05K7/20—Modifications to facilitate cooling, ventilating, or heating
- H05K7/20709—Modifications to facilitate cooling, ventilating, or heating for server racks or cabinets; for data centers, e.g. 19-inch computer racks
- H05K7/20718—Forced ventilation of a gaseous coolant
- H05K7/20745—Forced ventilation of a gaseous coolant within rooms for removing heat from cabinets, e.g. by air conditioning device
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
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Abstract
The invention is suitable for the technical field of machine room management, and provides a control method and a control device for a data center air conditioner and a data center, wherein the method comprises the following steps: acquiring the arrangement information of N cabinets and M air conditioning units in a data center and the load capacity of each cabinet; for each air-conditioning unit in the M air-conditioning units, determining a correlation coefficient of each cabinet relative to the air-conditioning unit according to the arrangement information of the N cabinets and the air-conditioning unit in the data center, and calculating the matching load capacity of the air-conditioning unit according to the correlation coefficient of each cabinet relative to the air-conditioning unit and the load capacity corresponding to each cabinet; determining target cooling capacity based on the matching load capacity of each air conditioning unit; and controlling each air conditioning unit to adjust the cooling capacity according to the corresponding target cooling capacity. The scheme can directly adjust the cold output of the air conditioner according to the load change of the cabinet, thereby avoiding the hysteresis of temperature reading and ensuring the stability of a cold channel temperature field of the data center.
Description
Technical Field
The invention belongs to the technical field of machine room management, and particularly relates to a control method and device for a data center air conditioner and a data center.
Background
The data center machine room is an intelligent center of the current information-oriented society, and the importance of the data center machine room is self-evident, and various precision devices in the data center machine room, including servers, storage, network switches and the like, have clear requirements on the environment. Strict standards are set by the countries and the industries, and the temperature is one of the most important environmental factors, and in order to ensure the normal operation of the equipment in the machine room, the air conditioning unit equipped in the machine room must work for 24 hours all day.
At present, an air conditioning unit in a machine room generally senses temperature change through a temperature and humidity sensor of the air conditioning unit and then controls the output of an air conditioner, but the temperature reading of the method has hysteresis, so that a cold channel temperature field of a data center is in a fluctuation state.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for controlling a data center air conditioner, and a data center, so as to solve the problem that the control efficiency of the data center air conditioner is low in the prior art.
The first aspect of the embodiments of the present invention provides a method for controlling a data center air conditioner, including:
acquiring the arrangement information of N cabinets and M air conditioning units in a data center and the load capacity of each cabinet; m is more than or equal to 1, and N is more than or equal to 1;
for each air-conditioning unit in the M air-conditioning units, determining a correlation coefficient of each cabinet relative to the air-conditioning unit according to the arrangement information of the N cabinets and the air-conditioning unit in the data center, and calculating the matching load capacity of the air-conditioning unit according to the correlation coefficient of each cabinet relative to the air-conditioning unit and the load capacity corresponding to each cabinet;
determining target cooling capacity corresponding to each air conditioning unit based on the matching load capacity of each air conditioning unit;
and controlling each air conditioning unit to adjust the cooling capacity according to the corresponding target cooling capacity.
A second aspect of an embodiment of the present invention provides a data center, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the control method of the data center air conditioner as described above when executing the computer program.
A third aspect of embodiments of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the control method of the data center air conditioner as described above.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: in the embodiment, firstly, the arrangement information of N cabinets and M air conditioning units in a data center and the load capacity of each cabinet are obtained; for each air-conditioning unit in the M air-conditioning units, determining a correlation coefficient of each cabinet relative to the air-conditioning unit according to the arrangement information of the N cabinets and the air-conditioning unit in the data center, and calculating the matching load capacity of the air-conditioning unit according to the correlation coefficient of each cabinet relative to the air-conditioning unit and the load capacity corresponding to each cabinet; determining target cooling capacity corresponding to each air conditioning unit based on the matching load capacity of each air conditioning unit; and controlling each air conditioning unit to adjust the cooling capacity according to the corresponding target cooling capacity. The scheme can directly adjust the cold output of the air conditioner according to the load change of the cabinet, thereby avoiding the hysteresis of temperature reading and ensuring the stability of a cold channel temperature field of the data center.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a control method of a data center air conditioner according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an arrangement of data center equipment provided by an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a control device of a data center air conditioner according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a data center provided in an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
An execution subject of the embodiment is a data center moving loop monitoring system, as shown in fig. 1, fig. 1 shows an implementation flow of a control method of a data center air conditioner, and a process thereof is detailed as follows:
s101: acquiring the arrangement information of N cabinets and M air conditioning units in a data center and the load capacity of each cabinet; m is more than or equal to 1, and N is more than or equal to 1.
In this embodiment, as shown in fig. 2, fig. 2 shows a typical configuration of cabinets and air conditioning units in a data room, and as shown in fig. 2, the data center micro module includes four air conditioning units, which are inter-row air conditioners 1 to 4, respectively, and includes 18 cabinets, which are IT cabinets 1 to 18, respectively, and the inter-row air conditioners are uniformly distributed between the cabinets, and each air conditioning unit includes at least one air conditioner.
Specifically, the moving loop monitoring system acquires the arrangement information and the load according to a preset period. The preset period may be selected to be 15 minutes. The configuration information can include position information of each cabinet and each air conditioning unit and airflow distribution conditions of the data center, and the configuration information can be manually input information by a user according to actual conditions and can also be information obtained by monitoring the moving loop monitoring system through a field positioning device.
S102: and for each air-conditioning unit in the M air-conditioning units, determining a correlation coefficient of each cabinet relative to the air-conditioning unit according to the arrangement information of the N cabinets and the air-conditioning unit in the data center, and calculating the matching load capacity of the air-conditioning unit according to the correlation coefficient of each cabinet relative to the air-conditioning unit and the load capacity corresponding to each cabinet.
In an embodiment, the specific implementation flow of S102 includes:
s201: acquiring partitions corresponding to the cabinets, and determining cabinet load coefficients of the cabinets relative to the corresponding partitions according to the arrangement information of the N cabinets and the corresponding partitions;
s202: calculating partition coefficients of the partitions relative to the air conditioning unit; and obtaining the correlation coefficient of each cabinet relative to the air conditioning unit according to the cabinet load coefficient of each cabinet relative to the corresponding subarea and the subarea coefficient of each subarea relative to the air conditioning unit.
In one embodiment, the partition coefficient calculating process in S202 includes:
s301: and calculating the partition coefficient of each partition relative to the air conditioning unit according to the arrangement information of each partition and the air conditioning unit.
In this embodiment, the moving loop monitoring system may obtain the partition corresponding to each cabinet according to the airflow distribution condition of the data center and the arrangement condition of each device. For example, as shown in fig. 2, in the same row of equipment, a plurality of partitions are determined as division by inter-row air conditioning. And then, calculating the partition coefficient of each partition relative to the air conditioning unit according to the arrangement information of each partition and a certain air conditioning unit.
In this embodiment, the partition coefficient may be determined according to the air outlet intensity and the distance of the air conditioner to each partition, and the closer the air conditioner unit is to the cabinet, the larger the partition coefficient is, and the farther the distance is, the smaller the partition coefficient is. For example, the partition coefficient of each partition adjacent to the first air conditioning unit with respect to the first air conditioning unit is set to β 0, β 0> 0; and setting the partition coefficient of each partition not adjacent to the first air conditioning unit to 0 relative to the first air conditioning unit, wherein the first air conditioning unit is any one of the air conditioning units.
For example, in fig. 2, the partition coefficients of the IT partition 1, the IT partition 2, the IT partition 5, and the IT partition 6 with respect to the inter-column air conditioners 1 may be β 0, and the partition coefficients of the IT partition 3 and the IT partition 4 with respect to the inter-column air conditioners 1 may be 0.
As can be seen from the above embodiments, in this embodiment, the partition responsible for each air conditioning unit can be determined by setting the partition coefficient, so that when a load of a certain partition changes, the strongly correlated air conditioning unit can be directly adjusted to match the load change of the air conditioning unit.
In an embodiment, the partition coefficient calculating process in S202 may further include:
s401: acquiring current temperature data of each subarea;
s402: calculating the difference value between the current temperature data of each partition and a preset temperature threshold value to obtain a partition temperature deviation value corresponding to each partition;
s403: and obtaining the partition coefficient of each partition relative to the air conditioning unit according to the partition temperature deviation value corresponding to each partition and a preset temperature deviation value-partition coefficient calculation formula.
In this embodiment, when the data center moving loop monitoring system determines the initial partition coefficient, the method of S301 may be adopted, and after the cold quantity adjustment of the current period is completed according to the initial partition coefficient, the current temperature data of each partition is collected in the next period, and the corresponding partition coefficient is determined according to the difference between the fed-back current temperature data and the preset temperature threshold.
Specifically, the preset temperature deviation value-partition coefficient calculation formula is a calculation formula for fitting the temperature deviation value and the partition coefficient of each partition, which are obtained by the early-stage workers according to experiments. The formula of calculation can be
Where x represents the instantaneous value of the partition coefficient, a represents the spatial state matrix of the partition coefficient, B represents the spatial state matrix of the temperature deviation value, and u represents the spatial state matrix of the temperature deviation value.
The partition coefficient updating method can continuously optimize the partition coefficient according to the feedback condition of the cold quantity regulation, thereby further improving the accuracy of the cold quantity regulation.
In one embodiment, the range of values of the rack load factor of each rack relative to the corresponding partition is
Wherein alpha isnkRepresenting a rack load factor for an nth rack of the data center relative to a kth zone.
In an embodiment, the S202 specifically includes:
by calculating cni＝αnk·βkiObtaining the correlation coefficient of each cabinet relative to the air conditioning unit;
wherein alpha isnkThe cabinet load factor of the nth cabinet relative to the kth zone is shown, and β ki represents the zone factor of the kth zone relative to the ith air conditioning unit.
In one embodiment, the implementation flow of S102 in fig. 1 further includes:
by passing
Calculating the matching load of each air conditioning unit；
Wherein Qi represents a matching load amount of the i-th air conditioning unit, ITn represents a load amount corresponding to the nth cabinet, and cni represents a correlation coefficient of the nth cabinet with respect to the i-th air conditioning unit.
Illustratively, for the 1 st inter-row air conditioner in fig. 2, the matching load amount is:
the term having a partition coefficient of 0 is not shown in the above formula.
S103: and determining the target cooling capacity corresponding to each air conditioning unit based on the matching load capacity of each air conditioning unit.
S104: and controlling each air conditioning unit to adjust the cooling capacity according to the corresponding target cooling capacity.
In this embodiment, matching capacity corresponding to each air conditioning unit can be obtained by multiplying the capacity and the correlation coefficient of each air conditioning unit, then the target cooling capacity of the air conditioning unit is calculated based on the matching capacity, a cooling capacity adjusting signal is generated and sent to the air conditioning unit, and the cooling capacity adjusting signal is used for controlling the air conditioning unit to adjust the cooling capacity output per se according to the target cooling capacity.
Known from the above embodiments, in this embodiment, the correlation coefficient is calculated through two steps of partition coefficient calculation and cabinet load coefficient calculation, so that the calculated amount of the air conditioner control process can be reduced, the adaptability of the scheme of this embodiment is wider, and meanwhile, the cooling capacity and the load capacity are directly related, so that the hysteresis of temperature regulation is avoided, the air conditioner control efficiency is improved, and the stability of the temperature field of the data center cold channel is ensured.
IT can be known from the above embodiments that, in the present embodiment, the relationship between each air conditioning unit in the micro module and the IT cabinet load strongly influenced by the temperature is established through the airflow organization distribution of the data center air conditioning function. The method comprehensively considers the airflow direction and the action position, combines the cabinet load coefficient and the partition coefficient to embody the strong correlation between the air conditioner and the load, and the load amount to be born by each air conditioning unit is obtained according to the strong correlation between the air conditioner and the load amount of each cabinet, the cold output of the air conditioning unit is controlled through the load amount, can realize the direct linkage of the adjustment of the air conditioner of the data center and the heat source of the partitioned load, lead the air conditioner to quickly respond to the load change to make control adjustment, effectively reduce the adjustment hysteresis caused by the indirect temperature adjustment method, avoid the continuous fluctuation of a cold channel temperature field of the data center, ensure the stable operation of data center equipment, the control method is established on all the bottom-layer control logic architectures, does not interfere the equipment bottom-layer control logic architecture, and has the characteristics of wide application range, strong engineering adaptability and the like.
In one embodiment, the method further comprises:
acquiring temperature data of a plurality of temperature monitoring points in the cold channel of the data center;
and if the temperature data of the temperature monitoring points exceed the conventional temperature range, sending an air volume adjusting instruction to each air conditioning unit so that each air conditioning unit adjusts the output air volume according to the air volume adjusting instruction.
In this embodiment, if there is a temperature monitoring point in the cold aisle where the temperature data exceeds the normal temperature range, the abnormal point is eliminated by adjusting the output air volume of the air conditioner.
For example, if a hot spot exists in the cold channel, the moving loop monitoring system controls all the air conditioning units to increase the output air volume by 10% until the cold quantity adjusting signal of the next period comes.
In the embodiment, the load-cold capacity adjusting method is assisted by temperature adjustment, so that the large fluctuation of a cold channel temperature field of the data center can be avoided, and hot spots of individual parts can be avoided, thereby further ensuring the normal temperature of the data center.
In one embodiment, as shown in fig. 3, fig. 3 shows a structure of a control device 100 of a data center air conditioner provided in the present embodiment, which includes:
the information acquisition module 110 is configured to acquire arrangement information of N cabinets and M air conditioning units in the data center, and load amounts of the cabinets; m is more than or equal to 1, and N is more than or equal to 1;
a matching load amount calculation module 120, configured to determine, for each air conditioning unit of the M air conditioning units, a correlation coefficient of each cabinet with respect to the air conditioning unit according to the arrangement information of the N cabinets and the air conditioning unit in the data center, and calculate a matching load amount of the air conditioning unit according to the correlation coefficient of each cabinet with respect to the air conditioning unit and a load amount corresponding to each cabinet;
the target cooling capacity calculation module 130 is configured to determine a target cooling capacity corresponding to each air conditioning unit based on the matching load capacity of each air conditioning unit;
and the cold quantity control module 140 is used for controlling each air conditioning unit to adjust the cold quantity according to the corresponding target cold quantity.
In one embodiment, the matching load amount calculation module 120 includes:
the equipment cabinet load coefficient calculation unit is used for acquiring the partition corresponding to each equipment cabinet and determining the equipment cabinet load coefficient of each equipment cabinet relative to the corresponding partition according to the arrangement information of the N equipment cabinets and the corresponding partition;
a correlation coefficient calculation unit for calculating a partition coefficient of each partition with respect to the air conditioning unit; and obtaining the correlation coefficient of each cabinet relative to the air conditioning unit according to the cabinet load coefficient of each cabinet relative to the corresponding subarea and the subarea coefficient of each subarea relative to the air conditioning unit.
In one embodiment, the correlation coefficient calculation unit includes:
and calculating the partition coefficient of each partition relative to the air conditioning unit according to the arrangement information of each partition and the air conditioning unit.
In one embodiment, the correlation coefficient calculation unit includes:
the current temperature data acquisition unit is used for acquiring current temperature data of each subarea;
the deviation value calculation unit is used for calculating the difference value between the current temperature data of each partition and a preset temperature threshold value to obtain a partition temperature deviation value corresponding to each partition;
and the partition coefficient calculation unit is used for obtaining the partition coefficient of each partition relative to the air conditioning unit according to the partition temperature deviation value corresponding to each partition and a preset temperature deviation value-partition coefficient calculation formula.
In one embodiment, the range of values of the rack load factor of each rack relative to the corresponding partition is
Wherein alpha isnkRepresenting a rack load factor for an nth rack of the data center relative to a kth zone.
In one embodiment, the correlation coefficient calculation unit further includes:
by calculating cni＝αnk·βkiObtaining the correlation coefficient of each cabinet relative to the air conditioning unit;
wherein alpha isnkThe cabinet load factor of the nth cabinet relative to the kth zone is shown, and β ki represents the zone factor of the kth zone relative to the ith air conditioning unit.
In one embodiment, the matching load amount calculation module 120 further includes:
a load amount matching unit for passing
Calculating the matching load capacity of each air conditioning unit;
wherein Qi represents a matching load amount of the i-th air conditioning unit, ITn represents a load amount corresponding to the nth cabinet, and cni represents a correlation coefficient of the nth cabinet with respect to the i-th air conditioning unit.
In an embodiment, the control device 100 of the data center air conditioner provided in this embodiment further includes an output air volume adjusting module, configured to:
acquiring temperature data of a plurality of temperature monitoring points in the cold channel of the data center;
and if the temperature data of the temperature monitoring points exceed the conventional temperature range, sending an air volume adjusting instruction to each air conditioning unit so that each air conditioning unit adjusts the output air volume according to the air volume adjusting instruction.
Fig. 4 is a schematic diagram of a data center according to an embodiment of the present invention. As shown in fig. 4, the data center 4 of this embodiment includes: a processor 40, a memory 41 and a computer program 42 stored in said memory 41 and executable on said processor 40. The processor 40, when executing the computer program 42, implements the steps in the above-described embodiments of the control method for the data center air conditioner, such as the steps 101 to 104 shown in fig. 1. Alternatively, the processor 40, when executing the computer program 42, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the modules 110 to 140 shown in fig. 3.
The computer program 42 may be partitioned into one or more modules/units that are stored in the memory 41 and executed by the processor 40 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 42 in the data center 4.
The data center 4 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The data center may include, but is not limited to, a processor 40, a memory 41. Those skilled in the art will appreciate that fig. 4 is merely an example of a data center 4, and does not constitute a limitation of data center 4, and may include more or fewer components than shown, or some components in combination, or different components, e.g., the data center may also include input-output devices, network access devices, buses, etc.
The Processor 40 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may be an internal storage unit of the data center 4, such as a hard disk or a memory of the data center 4. The memory 41 may also be an external storage device of the data center 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the data center 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the data center 4. The memory 41 is used for storing the computer programs and other programs and data required by the data center. The memory 41 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided by the present invention, it should be understood that the disclosed apparatus/data center and method may be implemented in other ways. For example, the above-described apparatus/data center embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A control method of a data center air conditioner is characterized by comprising the following steps:
acquiring the arrangement information of N cabinets and M air conditioning units in a data center and the load capacity of each cabinet; m is more than or equal to 1, and N is more than or equal to 1;
for each air-conditioning unit in the M air-conditioning units, determining a correlation coefficient of each cabinet relative to the air-conditioning unit according to the arrangement information of the N cabinets and the air-conditioning unit in the data center, and calculating the matching load capacity of the air-conditioning unit according to the correlation coefficient of each cabinet relative to the air-conditioning unit and the load capacity corresponding to each cabinet;
determining target cooling capacity corresponding to each air conditioning unit based on the matching load capacity of each air conditioning unit;
and controlling each air conditioning unit to adjust the cooling capacity according to the corresponding target cooling capacity.
2. The method for controlling the air conditioner of the data center according to claim 1, wherein the determining the correlation coefficient of each cabinet relative to the air conditioning unit according to the arrangement information of the N cabinets and the air conditioning unit in the data center comprises:
acquiring partitions corresponding to the cabinets, and determining cabinet load coefficients of the cabinets relative to the corresponding partitions according to the arrangement information of the N cabinets and the corresponding partitions;
calculating partition coefficients of the partitions relative to the air conditioning unit; and obtaining the correlation coefficient of each cabinet relative to the air conditioning unit according to the cabinet load coefficient of each cabinet relative to the corresponding subarea and the subarea coefficient of each subarea relative to the air conditioning unit.
3. The method of claim 2, wherein the calculating partition coefficients for each partition relative to the air conditioning unit comprises:
and calculating the partition coefficient of each partition relative to the air conditioning unit according to the arrangement information of each partition and the air conditioning unit.
4. The method of claim 2, wherein the calculating partition coefficients for each partition relative to the air conditioning unit comprises:
acquiring current temperature data of each subarea;
calculating the difference value between the current temperature data of each partition and a preset temperature threshold value to obtain a partition temperature deviation value corresponding to each partition;
and obtaining the partition coefficient of each partition relative to the air conditioning unit according to the partition temperature deviation value corresponding to each partition and a preset temperature deviation value-partition coefficient calculation formula.
5. The method according to claim 2, wherein the range of the cabinet load factor of each cabinet with respect to the corresponding zone is as follows
Wherein alpha isnkRepresenting a rack load factor for an nth rack of the data center relative to a kth zone.
6. The method for controlling the air conditioner of the data center as claimed in claim 2, wherein the obtaining of the correlation coefficient of each cabinet with respect to the air conditioning unit according to the cabinet load coefficient of each cabinet with respect to the corresponding zone and the zone coefficient of each zone with respect to the air conditioning unit comprises:
by calculating cni＝αnk·βkiObtaining the correlation coefficient of each cabinet relative to the air conditioning unit;
wherein alpha isnkThe cabinet load factor of the nth cabinet relative to the kth zone is shown, and β ki represents the zone factor of the kth zone relative to the ith air conditioning unit.
7. The method for controlling the air conditioner of the data center according to claim 1, wherein the calculating the matching load amount of the air conditioning unit according to the correlation coefficient of each cabinet relative to the air conditioning unit and the corresponding load amount of each cabinet comprises:
by passing
Calculating the matching load capacity of each air conditioning unit;
wherein Qi represents a matching load amount of the i-th air conditioning unit, ITn represents a load amount corresponding to the nth cabinet, and cni represents a correlation coefficient of the nth cabinet with respect to the i-th air conditioning unit.
8. The method for controlling an air conditioner in a data center according to any one of claims 1 to 7, further comprising:
acquiring temperature data of a plurality of temperature monitoring points in the cold channel of the data center;
and if the temperature data of the temperature monitoring points exceed the conventional temperature range, sending an air volume adjusting instruction to each air conditioning unit so that each air conditioning unit adjusts the output air volume according to the air volume adjusting instruction.
9. A data center comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor implements the steps of the method according to any one of claims 1 to 8 when executing said computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.
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