CN115712338A - Data center air conditioner power consumption control method and device and electronic equipment - Google Patents
Data center air conditioner power consumption control method and device and electronic equipment Download PDFInfo
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Abstract
The embodiment of the invention relates to the technical field of direct current power supply, and discloses a method and a device for controlling power consumption of a data center air conditioner and electronic equipment. The method comprises the following steps: determining the current variable quantity of the server power consumption in the data center; if the current variable quantity is larger than a preset variable quantity threshold value, determining the current adjustment quantity of the power consumption of an air conditioner, wherein the air conditioner is used for cooling the server; after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating value of the server; if the actual heating value is larger than a preset heating value threshold value, determining the actual adjustment amount of the air conditioner power consumption; and controlling the power consumption of the air conditioner according to the actual adjustment quantity. Through the mode, the embodiment of the invention saves the energy consumption of the air conditioner in the data center.
Description
Technical Field
The embodiment of the invention relates to the technical field of direct current power supply, in particular to a method and a device for controlling power consumption of a data center air conditioner and electronic equipment.
Background
With the continuous development of the internet, the scale of the data center is continuously enlarged. The air conditioning system in the data center is mainly used for cooling the server of the data center, so that the normal operation of the server is ensured.
In the related art, when the temperature of the server is high, the power consumption of the air conditioning system is increased, so that the temperature of the server can be effectively reduced; when the temperature of the server is low, the power consumption of the air conditioning system is reduced, and the electric energy efficiency of the data center can be improved. However, the inventors found in the course of implementing embodiments of the present invention that: due to the fact that the load of the server in the data center is changed continuously, the temperature change of the server cannot be predicted according to historical data, energy consumption of an air conditioning system in the data center cannot be adjusted in real time, and the electric energy efficiency of the data center is low.
Disclosure of Invention
In view of the above problems, embodiments of the present invention provide a method and an apparatus for controlling power consumption of a data center air conditioner, and an electronic device, so as to solve the problem in the prior art that the power efficiency of a data center is low.
According to an aspect of an embodiment of the present invention, there is provided a method for controlling power consumption of a data center air conditioner, the method including:
determining the current variable quantity of the server power consumption in the data center;
if the current variable quantity is larger than a preset variable quantity threshold value, determining the current adjustment quantity of the power consumption of an air conditioner, wherein the air conditioner is used for cooling the server;
after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating value of the server;
if the actual heating value is larger than a preset heating value threshold value, determining the actual adjustment quantity of the air conditioner power consumption;
and controlling the power consumption of the air conditioner according to the actual adjustment quantity.
In an alternative manner, the determining the current adjustment amount of the air conditioner power consumption includes:
and determining the current adjustment amount of the air conditioner power consumption according to the grade of the data center and the shelf loading rate of the server.
In an optional manner, the method further comprises:
and determining the data center grade according to the climate condition of the place where the data center is located and the average power density of the racks in the data center.
In an optional manner, the determining the actual adjustment amount of the air conditioner power consumption includes:
and inputting the current variable quantity, the shelf life of the server and the grade of the data center into a pre-training machine learning model so as to determine the actual adjustment quantity of the air conditioner power consumption.
In an optional manner, the determining the current amount of change in the power consumption of the server in the data center includes: respectively acquiring the current variable quantity of the power consumption of the servers in a plurality of cabinet areas in the service center;
the controlling the power consumption of the air conditioner according to the actual adjustment amount comprises: and respectively controlling the air conditioner power consumption of the corresponding cabinet areas according to the actual adjustment quantity corresponding to the different cabinet areas.
In an alternative manner, the determining the current amount of change in the power consumption of the server in the data center includes:
detecting the current of a direct current output cabinet/a rectification system;
and determining the current variable quantity of the power consumption of the server in the data center according to the current.
In an optional manner, the method further comprises:
acquiring a plurality of groups of training data, wherein each group of training data comprises the variable quantity of the power consumption of the server, the shelf life of the server and the grade of a data center;
determining the air conditioner power consumption adjustment amount corresponding to each group of training data;
and inputting each group of training data and the corresponding air conditioner power consumption adjustment quantity into a machine learning model to be trained for training so as to generate the pre-training machine learning model.
According to another aspect of the embodiments of the present invention, there is provided a data center air conditioner power consumption control apparatus, including:
the first determining module is used for determining the current variable quantity of the power consumption of the server in the data center;
the second determining module is used for determining the current adjustment amount of the power consumption of the air conditioner if the current variation is larger than a preset variation threshold, wherein the air conditioner is used for cooling the server;
the third determining module is used for determining the actual heating value of the server after the power consumption of the air conditioner is adjusted according to the current adjustment amount;
the fourth determining module is used for determining the actual adjustment quantity of the air conditioner power consumption if the actual heating value is larger than a preset heating value threshold;
and the control module is used for controlling the power consumption of the air conditioner according to the actual adjustment quantity.
According to another aspect of the embodiments of the present invention, there is provided an electronic device including: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface are communicated with each other through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation of the data center air conditioner power consumption control method.
According to another aspect of the embodiments of the present invention, there is provided a computer-readable storage medium having at least one executable instruction stored therein, where the executable instruction, when executed on an electronic device, causes the electronic device to perform the operations of the above-mentioned data center air conditioner power consumption control method.
In the embodiment of the invention, the current variable quantity of the power consumption of a server in a data center is determined, and if the current variable quantity is greater than a preset variable quantity threshold value, the current adjustment quantity of the power consumption of an air conditioner is determined; after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating amount of the server; and if the actual heating value of the server is greater than the preset heating value threshold value, determining the actual adjustment amount of the air conditioner power consumption, and controlling the air conditioner power consumption according to the actual adjustment amount. Through the mode, the embodiment of the invention can carry out real-time control on the power consumption of the air conditioner according to the actual heating value of the server, effectively reduce the electric energy loss of the air conditioning system in the data center and improve the electric energy efficiency of the data center.
The foregoing description is only an overview of the technical solutions of the embodiments of the present invention, and in order that the technical solutions of the embodiments of the present invention can be clearly understood, the embodiments of the present invention can be implemented according to the content of the description, and the above and other objects, features, and advantages of the embodiments of the present invention can be more clearly understood, the detailed description of the present invention is provided below.
Drawings
The drawings are only for purposes of illustrating embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a schematic structural diagram of a data center power supply device provided in an embodiment of the present invention;
fig. 2 is a schematic flow chart illustrating a method for controlling power consumption of an air conditioner in a data center according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram illustrating a method and an apparatus for controlling power consumption of a data center air conditioner according to an embodiment of the present invention;
fig. 4 shows a schematic structural diagram of an electronic device provided in an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein.
The Panama power supply is a high-efficiency direct-current power supply system which directly converts 10kV voltage into 240V/336V voltage, integrates traditional equipment such as 10kV alternating-current power distribution, a transformer, low-voltage power distribution, 240V/336V uninterruptible power supply and output power distribution units, has the remarkable advantages of high efficiency, safety, reliability, space saving, low cost, easiness in installation and maintenance and the like, and can meet the requirements of large and ultra-large cloud computing data centers, large communication machine room power distribution and uninterruptible power supply systems. In the prior art, a direct current voltage output by a panama power supply is adopted to supply power to a server, and the direct current voltage output by the panama power supply is inverted into a 380V alternating current voltage to supply power to an air conditioner. However, the prior art panama power supply has many drawbacks. For example, when the ac voltage is inverted from the dc voltage output from the panama Power supply to the ac voltage to supply Power to the air conditioner, the 380V ac voltage capacity cannot be larger than 50% of the system capacity, resulting in a large PUE (Power Usage efficiency). According to the data center power supply device provided by the embodiment of the invention, the tail end of the air conditioner is continuously refrigerated by adopting a mode of supplying power to the air conditioner by replacing 380V alternating current with direct current power supply, so that the problem that the capacity of a 380V alternating current power supply cannot be larger than the capacity of a system by 50% can be solved. Meanwhile, the 2N type power supply mode is adopted, so that the loss of half of the backup time of the storage battery and the downtime risk of important rear-end equipment caused by high temperature when single-path mains supply is adopted can be avoided, the system safety is effectively improved, and the system cost is saved.
Fig. 1 shows a schematic structural diagram of a data center power supply device according to an embodiment of the present invention. As shown in fig. 1, the power supply device includes: the system comprises a first commercial power input cabinet (incoming cabinet), a second commercial power input cabinet (incoming cabinet), a first voltage transformer cabinet, a second voltage transformer cabinet, a first rectifying system, a second rectifying system, a first direct current output cabinet, a second direct current output cabinet, a first air conditioner/DC rectifying cabinet, a second air conditioner/DC rectifying cabinet, a first storage battery pack and a second storage battery pack.
The first rectifying system comprises a first rectifying frame and a second rectifying frame, and the second rectifying system comprises a third rectifying frame and a fourth rectifying frame. The first commercial power input cabinet is connected with the input of the first voltage transformation cabinet through a cable, and the output of the first voltage transformation cabinet is connected with the input of the first rectifying frame and the input of the third rectifying frame. The second commercial power input cabinet is connected with the input of the second voltage transformation cabinet through a cable, and the output of the second voltage transformation cabinet is connected with the input of the second rectifying frame and the input of the fourth rectifying frame. The output of the first rectifying frame and the output of the second rectifying frame are connected with the input of the first direct current output cabinet, and the output of the first direct current output cabinet is connected with the first storage battery pack and the load. The output of the third rectifying frame and the output of the fourth rectifying frame are connected with the input of a second direct current output cabinet, and the output of the second direct current output cabinet is connected with a second storage battery pack and a load; the input of the first air conditioner/DC rectifier cabinet is connected with the output of the first voltage variable cabinet, and the input of the second air conditioner/DC rectifier cabinet is connected with the output of the second voltage variable cabinet. The output of the first air conditioner/DC rectifier cabinet is connected with an air conditioner, and the input of the second air conditioner/DC rectifier cabinet is connected with the air conditioner.
The PUE of the data center is the ratio of the total energy consumption of the data center to the energy consumption of IT equipment of the data center. The total energy consumption of the data center comprises the energy consumption of IT equipment and the energy consumption of systems such as an air conditioner, a power distribution system and the like, the value of the total energy consumption is larger than 1, and the closer to 1, the less the energy consumption of non-IT equipment is, and the better the energy efficiency level is. Air conditioning system in the data center is used for cooling to IT equipment (server) in the data center to accelerate the heat dissipation of server, guarantee server normal operating. Because the service conditions of the data center server equipment are changed continuously, and the heat productivity of the server is different in different time periods, the air conditioning system of the data center needs to be controlled in real time according to the heat productivity of the server, so that the energy consumption of an air conditioner is saved, and the PUE of the data center is reduced.
Fig. 2 is a flowchart illustrating a method for controlling power consumption of an air conditioner in a data center according to an embodiment of the present invention, where the method is applied to the power supply device in the data center and is executed by an electronic device. The memory of the electronic equipment stores at least one executable instruction, and the executable instruction enables the processor of the electronic equipment to execute the operation of the data center air conditioner power consumption control method.
As shown in fig. 2, the method comprises the steps of:
step 110: determining a current amount of change in server power consumption in the data center.
Wherein, the current variation of the server power consumption within the preset time length can be determined. The power consumption of the server is different according to the utilization rate of the server. If the utilization rate of the server is high, the power consumption is high, and if the utilization rate of the server is low, the power consumption is low. Further, when the current variation of the power consumption of the server in the data center is determined, the current of the direct current output cabinet/the DC rectifier cabinet can be detected; and determining the current variable quantity of the power consumption of the server in the data center according to the current.
It should be noted that, servers in a data center are generally disposed in a cabinet, and power consumption conditions of servers in different cabinet areas generally differ. When the current variation of the power consumption of the server in the data center is determined, the current variation of the power consumption of the server in a plurality of cabinet areas in the service center can be respectively obtained.
Step 120: and if the current variable quantity is larger than a preset variable quantity threshold value, determining the current adjustment quantity of the power consumption of the air conditioner, wherein the air conditioner is used for cooling the server.
If the current variation of the power consumption of the server is larger than the preset variation threshold, the power consumption of the air conditioner needs to be adjusted. For example, when the server power consumption increases, the air conditioner power consumption needs to be reduced, and when the server power consumption decreases, the air conditioner power consumption needs to be increased. Further, when the current variation is larger than a preset variation threshold, the current adjustment amount of the air conditioner power consumption can be determined according to the data center level and the server shelf life. The data center level can comprise a level A, a level B and a level C, wherein the level A is an error-tolerant type and has a higher level; the B level is a redundant type and has moderate level; the C level is basic type and has lower grade. Further, the data center rank may be determined based on the climate conditions at the data center location and the average power density of the racks in the data center.
Step 130: and after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating value of the server.
When the power consumption of the server changes, the heating value of the server also changes. For example, power consumption of the server increases, and the amount of heat generation also increases. After the power consumption of the air conditioner is adjusted according to the current adjustment amount, the heating value of the server changes. Further, a mathematical model of the heat generation of the server can be established according to the heat generation condition of the server to determine the actual heat generation amount of the server.
When a mathematical model of the heat generation of the server is established, temperature tests can be carried out on all parts of the server to determine components which generate more heat in the server. In order to test the highest temperature that each component of the server may reach, the temperature of the server is tested after the server is fully operated for a period of time by using an IXIA tester. During testing, the ambient temperature of the server is 25 ℃, the lowest component temperature of the tested server is 24.6 ℃, the highest component temperature is 50.5 ℃, and the average temperature is 27.3 ℃. Tests show that the energy consumption and the heat productivity of the memory part of the server, the south bridge and the north bridge of the mainboard and the I/O chip part are higher. The embodiment of the invention is based on different operation modes of the server, the operation state of the server is divided into an unloaded state and a full-load state, and energy consumption component researches are carried out on the CPU, the memory, the south bridge and the north bridge of the mainboard and the I/O chip part of each server under the unloaded state and the full-load state of the server, so that an energy consumption model of each cabinet server can be obtained.
The energy consumption of the server in the no-load state and the full-load state can be calculated according to the parameters of the server and the working current of the server, and when the parameters of the server are determined, the change of the current can reflect the change of the power consumption. When the parameters and the current of the server are determined, the power consumption of the server in the no-load state and the full-load state can be determined. The embodiment of the present invention does not limit the specific values of the power consumption of the server in the no-load state and the full-load state, and those skilled in the art can correspondingly determine the power consumption according to specific server parameters. Under the same heat dissipation condition, the higher the utilization rate of the server is, the higher the energy consumption temperature of the server is. Especially, the core frequency of the existing server product can be automatically adjusted, when the utilization rate is low, the core frequency can be adjusted downwards, the power consumption is obviously reduced, and the energy consumption and the heat productivity are little. On the contrary, when the utilization rate is increased, the CPU frequency of the server is increased to reach the maximum frequency or even the Rui frequency, and the power energy consumption and the heat productivity are obviously improved. In one embodiment of the invention, the power consumption of the server under the condition of power-on and power-off is 16.7 watts, the peak power consumption at the moment of starting the server is 295.0 watts, the no-load power consumption of the server is 192.5 watts, and the full-load power consumption of the server is 250.5 watts. Specifically, when the server is empty and full, the power consumption (heat generation amount) of the server can be calculated by the following formula:
wherein, W is the heating value of the server,
is the instantaneous heating value of the server, F L Energy consumption heat of server CPU and memory, F i Energy consumption of the north and south bridges of the main board, F io Consuming heat for the I/O chip. To F L 、F i And in F io Performing product on corresponding timeAnd obtaining the server heating value in the corresponding time range. Further, the transient heating value of the server can be calculated by using the following formula:
wherein, the first and the second end of the pipe are connected with each other,
for the adjustment function, I is the operating current of the server, d el Adjustment value of Rui frequency, F L In order to be the core frequency, the frequency of the core,
the energy consumption heat of the CPU and the memory and the energy consumption heat of the south bridge and the north bridge of the mainboard and the I/O chip, delta is the transient energy consumption ratio, and w is e For the power consumption heat function after the CPU frequency rises to the maximum frequency even Rui frequency, T is the transient time, w ei The sum of the instantaneous energy consumption heating values for the server no-load and full-load systems,
and τ is constant.
Step 140: and if the actual heating value is larger than a preset heating value threshold value, determining the actual adjustment amount of the air conditioner power consumption.
If the actual heating value of the server is greater than the preset heating value threshold, the air conditioner power consumption needs to be further adjusted. When the actual adjustment amount of the air conditioner power consumption is determined, the current variation, the shelf life of the server and the grade of the data center can be input into the pre-training machine learning model to determine the actual adjustment amount of the air conditioner power consumption.
Further, the machine learning model to be trained may also be trained to generate a pre-trained machine learning model. For example, acquiring multiple sets of training data, wherein each set of training data comprises the variation of the power consumption of a server, the shelving rate of the server and the grade of a data center; determining the air conditioner power consumption adjustment amount corresponding to each group of training data; and inputting each group of training data and the corresponding air conditioner power consumption adjustment amount into a machine learning model to be trained for training so as to generate a pre-training machine learning model.
Step 150: and controlling the power consumption of the air conditioner according to the actual adjustment amount.
The target areas of the first rectifier cabinet, the second rectifier cabinet, the first air conditioner/DC rectifier cabinet and the second air conditioner/DC rectifier cabinet can be predetermined, power consumption distribution of the first rectifier cabinet, the second rectifier cabinet, the first air conditioner/DC rectifier cabinet and the second air conditioner/DC rectifier cabinet is controlled, and a distribution adjustment relation between power consumption change of the server and power consumption of the air conditioner is established, so that power consumption of the air conditioner is controlled. The distribution adjustment relationship between the server power consumption change and the air conditioner power consumption can be expressed as:
wherein the content of the first and second substances,
for server power consumption variation, beta wv For adjusting the power consumption of the air conditioner, W ep The heat productivity of the CPU and the memory of the server, the south bridge and the north bridge of the mainboard and the I/O chip. Furthermore, when the power consumption of the air conditioner is controlled according to the actual adjustment quantity, the power consumption of the air conditioner corresponding to the cabinet areas can be controlled according to the actual adjustment quantity corresponding to different cabinet areas.
In the embodiment of the invention, the current variable quantity of the power consumption of a server in a data center is determined, and if the current variable quantity is greater than a preset variable quantity threshold value, the current adjustment quantity of the power consumption of an air conditioner is determined; after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating value of the server; and if the actual heating value of the server is greater than the preset heating value threshold value, determining the actual adjustment amount of the air conditioner power consumption, and controlling the air conditioner power consumption according to the actual adjustment amount. Through the mode, the embodiment of the invention can carry out real-time control on the power consumption of the air conditioner according to the actual heating value of the server, effectively reduce the electric energy loss of the air conditioning system in the data center and improve the electric energy efficiency of the data center.
Fig. 3 is a schematic structural diagram illustrating a power consumption control device of an air conditioner in a data center according to an embodiment of the present invention. As shown in fig. 3, the apparatus 300 includes: a first determination module 310, a second determination module 320, a third determination module 330, a fourth determination module 340, and a control module 350.
The first determining module 310 is configured to determine a current amount of change in power consumption of a server in the data center; the second determining module 320 is configured to determine a current adjustment amount of power consumption of an air conditioner if the current variation is greater than a preset variation threshold, where the air conditioner is configured to cool the server; the third determining module 330 is configured to determine an actual heating value of the server after the power consumption of the air conditioner is adjusted according to the current adjustment amount; the fourth determining module 340 is configured to determine an actual adjustment amount of the power consumption of the air conditioner if the actual heating value is greater than a preset heating value threshold; the control module 350 is configured to control the power consumption of the air conditioner according to the actual adjustment amount.
In an alternative manner, the second determining module 320 is configured to:
and determining the current adjustment quantity of the air conditioner power consumption according to the grade of the data center and the shelf life of the server.
In an alternative manner, the second determining module 320 is configured to:
and determining the data center grade according to the climate condition of the place where the data center is located and the average power density of the racks in the data center.
In an alternative manner, the fourth determining module 340 is configured to:
and inputting the current variable quantity, the shelf life of the server and the grade of the data center into a pre-training machine learning model so as to determine the actual adjustment quantity of the air conditioner power consumption.
In an optional manner, the first determining module 310 is configured to obtain current variation amounts of server power consumption of multiple cabinet areas in the service center, respectively; the control module 350 is configured to control the power consumption of the air conditioner in the corresponding cabinet area according to the actual adjustment amount corresponding to the different cabinet areas.
In an alternative manner, the first determining module 310 is configured to:
detecting the current of the direct current output cabinet/rectification system;
and determining the current variable quantity of the power consumption of the server in the data center according to the current.
In an optional manner, the apparatus 300 further comprises a training module for:
acquiring a plurality of groups of training data, wherein each group of training data comprises the variable quantity of the power consumption of the server, the shelf life of the server and the grade of a data center;
determining the air conditioner power consumption adjustment amount corresponding to each group of training data;
and inputting each group of training data and the corresponding air conditioner power consumption adjustment amount into a machine learning model to be trained for training so as to generate the pre-training machine learning model.
In the embodiment of the invention, the current variable quantity of the power consumption of a server in a data center is determined, and if the current variable quantity is larger than a preset variable quantity threshold, the current adjustment quantity of the power consumption of an air conditioner is determined; after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating value of the server; and if the actual heating value of the server is greater than the preset heating value threshold value, determining the actual adjustment amount of the air conditioner power consumption, and controlling the air conditioner power consumption according to the actual adjustment amount. Through the mode, the embodiment of the invention can control the power consumption of the air conditioner in real time according to the actual heating value of the server, effectively reduce the electric energy loss of the air conditioning system in the data center and improve the electric energy efficiency of the data center.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and the specific embodiment of the present invention does not limit the specific implementation of the electronic device.
As shown in fig. 4, the electronic device may include: a processor (processor) 402, a Communications Interface 404, a memory 406, and a Communications bus 408.
Wherein: the processor 402, communication interface 404, and memory 406 communicate with each other via a communication bus 408. A communication interface 404 for communicating with network elements of other devices, such as clients or other servers. The processor 402 is configured to execute the program 410, and may specifically execute the relevant steps in the embodiment of the method for controlling power consumption of an air conditioner in a data center.
In particular, program 410 may include program code comprising computer-executable instructions.
The processor 402 may be a central processing unit CPU, or an Application Specific Integrated Circuit ASIC (Application Specific Integrated Circuit), or one or more Integrated circuits configured to implement an embodiment of the present invention. The electronic device comprises one or more processors, which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
And a memory 406 for storing a program 410. Memory 406 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 410 may specifically be invoked by the processor 402 to cause the electronic device to perform the following operations:
determining the current variable quantity of the server power consumption in the data center;
if the current variable quantity is larger than a preset variable quantity threshold value, determining the current adjustment quantity of the power consumption of an air conditioner, wherein the air conditioner is used for cooling the server;
after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating value of the server;
if the actual heating value is larger than a preset heating value threshold value, determining the actual adjustment amount of the air conditioner power consumption;
and controlling the power consumption of the air conditioner according to the actual adjustment amount.
In an alternative, the program 410 is invoked by the processor 402 to cause the electronic device to perform the following operations:
and determining the current adjustment quantity of the air conditioner power consumption according to the grade of the data center and the shelf life of the server.
In an alternative, the program 410 is invoked by the processor 402 to cause the electronic device to perform the following operations:
and determining the data center grade according to the climate condition of the place where the data center is located and the average power density of the racks in the data center.
In an alternative, the program 410 is invoked by the processor 402 to cause the electronic device to perform the following operations:
and inputting the current variable quantity, the shelf life of the server and the grade of the data center into a pre-training machine learning model so as to determine the actual adjustment quantity of the air conditioner power consumption.
In an alternative, the program 410 is invoked by the processor 402 to cause the electronic device to perform the following operations:
respectively acquiring the current variable quantity of the power consumption of the servers in a plurality of cabinet areas in the service center;
and respectively controlling the air conditioner power consumption of the corresponding cabinet areas according to the actual adjustment quantity corresponding to the different cabinet areas.
In an alternative, the program 410 is invoked by the processor 402 to cause the electronic device to perform the following operations:
detecting the current of a direct current output cabinet/a rectification system;
and determining the current variable quantity of the power consumption of the server in the data center according to the current.
In an alternative, the program 410 is invoked by the processor 402 to cause the electronic device to perform the following operations:
acquiring a plurality of groups of training data, wherein each group of training data comprises the variable quantity of the power consumption of the server, the shelving rate of the server and the grade of the data center;
determining the air conditioner power consumption adjustment amount corresponding to each group of training data;
and inputting each group of training data and the corresponding air conditioner power consumption adjustment amount into a machine learning model to be trained for training so as to generate the pre-training machine learning model.
In the embodiment of the invention, the current variable quantity of the power consumption of a server in a data center is determined, and if the current variable quantity is greater than a preset variable quantity threshold value, the current adjustment quantity of the power consumption of an air conditioner is determined; after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating value of the server; and if the actual heating value of the server is larger than the preset heating value threshold value, determining the actual adjustment amount of the air conditioner power consumption, and controlling the air conditioner power consumption according to the actual adjustment amount. Through the mode, the embodiment of the invention can carry out real-time control on the power consumption of the air conditioner according to the actual heating value of the server, effectively reduce the electric energy loss of the air conditioning system in the data center and improve the electric energy efficiency of the data center.
An embodiment of the present invention provides a computer-readable storage medium, where the storage medium stores at least one executable instruction, and when the executable instruction runs on an electronic device, the electronic device is enabled to execute a power consumption control method for a data center air conditioner in any of the above method embodiments.
The embodiment of the invention provides a power consumption control device of a data center air conditioner, which is used for executing the power consumption control method of the data center air conditioner.
Embodiments of the present invention provide a computer program, where the computer program can be called by a processor to enable an electronic device to execute the method for controlling power consumption of a data center air conditioner in any of the above method embodiments.
Embodiments of the present invention provide a computer program product, where the computer program product includes a computer program stored on a computer-readable storage medium, and the computer program includes program instructions, when the program instructions are run on a computer, the computer is caused to execute the method for controlling power consumption of a data center air conditioner in any of the above-mentioned method embodiments.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed to reflect the intent: rather, the invention as claimed requires more features than are expressly recited in each claim.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specified otherwise.
Claims (10)
1. A power consumption control method for a data center air conditioner is characterized by comprising the following steps:
determining the current variable quantity of the server power consumption in the data center;
if the current variable quantity is larger than a preset variable quantity threshold value, determining the current adjustment quantity of the power consumption of an air conditioner, wherein the air conditioner is used for cooling the server;
after the power consumption of the air conditioner is adjusted according to the current adjustment amount, determining the actual heating value of the server;
if the actual heating value is larger than a preset heating value threshold value, determining the actual adjustment amount of the air conditioner power consumption;
and controlling the power consumption of the air conditioner according to the actual adjustment quantity.
2. The method of claim 1, wherein determining the current adjustment for air conditioner power consumption comprises:
and determining the current adjustment quantity of the air conditioner power consumption according to the grade of the data center and the shelf life of the server.
3. The method of claim 2, further comprising:
and determining the data center grade according to the climate condition of the place where the data center is located and the average power density of the racks in the data center.
4. The method of any of claims 1 to 3, wherein the determining the actual adjustment amount for the air conditioner power consumption comprises:
and inputting the current variable quantity, the shelf-loading rate of the server and the grade of the data center into a pre-training machine learning model so as to determine the actual adjustment quantity of the air conditioner power consumption.
5. The method according to any one of claims 1 to 3,
the determining the current amount of change in the power consumption of the server in the data center comprises: respectively obtaining the current variable quantity of the power consumption of the servers in a plurality of cabinet areas in the service center;
the controlling the power consumption of the air conditioner according to the actual adjustment amount comprises: and respectively controlling the air conditioner power consumption of the corresponding cabinet areas according to the actual adjustment quantity corresponding to the different cabinet areas.
6. The method of any of claims 1 to 3, wherein determining the current amount of change in server power consumption in the data center comprises:
detecting the current of a direct current output cabinet/a rectification system;
and determining the current variable quantity of the power consumption of the server in the data center according to the current.
7. The method of claim 4, further comprising:
acquiring a plurality of groups of training data, wherein each group of training data comprises the variable quantity of the power consumption of the server, the shelving rate of the server and the grade of the data center;
determining the air conditioner power consumption adjustment amount corresponding to each group of training data;
and inputting each group of training data and the corresponding air conditioner power consumption adjustment quantity into a machine learning model to be trained for training so as to generate the pre-training machine learning model.
8. A power consumption control device for a data center air conditioner, the device comprising:
the first determining module is used for determining the current variable quantity of the power consumption of the server in the data center;
the second determining module is used for determining the current adjustment amount of the power consumption of the air conditioner if the current variation is larger than a preset variation threshold, wherein the air conditioner is used for cooling the server;
the third determining module is used for determining the actual heating value of the server after the power consumption of the air conditioner is adjusted according to the current adjustment amount;
the fourth determining module is used for determining the actual adjustment quantity of the air conditioner power consumption if the actual heating value is larger than a preset heating value threshold;
and the control module is used for controlling the power consumption of the air conditioner according to the actual adjustment amount.
9. An electronic device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation of the data center air conditioner power consumption control method according to any one of claims 1-7.
10. A computer-readable storage medium having stored therein at least one executable instruction that, when executed on an electronic device, causes the electronic device to perform operations of the data center air conditioner power consumption control method according to any one of claims 1 to 7.
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| CN202110949366.3A CN115712338A (en) | 2021-08-18 | 2021-08-18 | Data center air conditioner power consumption control method and device and electronic equipment |
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| CN202110949366.3A CN115712338A (en) | 2021-08-18 | 2021-08-18 | Data center air conditioner power consumption control method and device and electronic equipment |
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