Machine room temperature control method and device, electronic equipment and computer program product

Abstract

The invention discloses a machine room temperature control method and device, electronic equipment and a computer program product. The method comprises the following steps: predicting target service power consumption of a server in a machine room in a target time period by using a preset energy consumption prediction model; the target service power consumption is analyzed through a preset refrigerating capacity prediction model, the target refrigerating capacity corresponding to the target service power consumption is obtained, and the preset refrigerating capacity prediction model is trained through machine learning by adopting multiple sets of second training data in advance; each group of second training data in the multiple groups of second training data comprises the preset service power consumption of the server and the preset refrigerating capacity of the air conditioner in the same historical period, and the preset refrigerating capacity is determined according to the operation parameters of the air conditioner in the historical period; and controlling an air conditioner in the machine room to adjust the temperature of the machine room according to the target refrigerating capacity in the target time period. The technical problem that in the prior art, air conditioner energy consumption of a machine room is wasted is solved.

Description

Technical Field

[0001] The present invention relates to the field of computers, and in particular to a method, device, electronic equipment, and computer program product for controlling the temperature of a computer room. Background Art

[0002] Computer modules, servers and other equipment are installed in the computer room. When the equipment is running, heat is generated, causing the temperature inside the computer room to rise. Once the temperature exceeds the temperature threshold of the equipment, it will affect the working efficiency of the equipment and even cause the equipment to shut down. Therefore, in order to ensure the normal operation of the equipment in the computer room, the temperature inside the computer room needs to be controlled within an appropriate temperature range.

[0003] However, the current method of temperature regulation in the computer room is based on real-time temperature feedback from the computer room, that is, the air conditioner will be controlled to cool down only when the temperature in the computer room exceeds the standard temperature, which makes the temperature regulation delayed and the temperature regulation effect poor. Furthermore, in order to ensure that the temperature of the computer room is within the safe temperature range, it is necessary to design a redundant safe temperature range to keep the temperature of the computer room within a lower temperature range, resulting in a waste of air conditioning cooling effect, thereby wasting the air conditioning energy consumption of the computer room.

[0004] With regard to the problem of the existing technology wasting the air conditioning energy consumption of the computer room, no effective solution has been proposed so far. Summary of the invention

[0005] The embodiments of the present invention provide a method, device, electronic equipment, and computer program product for controlling the temperature of a computer room, so as to at least solve the technical problem of the prior art that the air conditioning energy consumption of the computer room is wasted.

[0006] According to one aspect of an embodiment of the present invention, a method for controlling the temperature of a computer room is provided, comprising: using a preset energy consumption prediction model to predict the target service power consumption of a server in the computer room within a target time period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple groups of first training data, and each group of first training data in the multiple groups of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical time period; using a preset cooling capacity prediction model to analyze the target service power consumption to obtain a target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple groups of second training data, and each group of second training data in the multiple groups of second training data includes: the preset service power consumption of the server and the preset cooling capacity of the air conditioner in the same historical time period, and the preset cooling capacity is determined according to the operating parameters of the air conditioner in the historical time period; controlling the air conditioner in the computer room to adjust the computer room temperature according to the target cooling capacity within the target time period.

[0007] Optionally, controlling the air conditioner in the computer room to adjust the temperature of the computer room according to the target cooling capacity during the target time period includes: determining the target cooling power of the air conditioner during the target time period based on the target cooling capacity required by the computer room during the target time period; and controlling the air conditioner to adjust the temperature of the computer room based on the target cooling power.

[0008] Optionally, determining the cooling power of the air conditioner within the target time period based on the target cooling capacity required by the computer room within the target time period includes: obtaining the current cooling power of the air conditioner within the current time period, wherein the current time period is earlier than the target time period and adjacent to the target time period; determining the current cooling capacity within the current time period based on the current cooling power; determining the cooling power adjustment amount of the air conditioner within the target time period based on the cooling capacity difference between the target cooling capacity and the current cooling capacity; and adjusting the current cooling power according to the cooling power adjustment amount to obtain the target cooling power.

[0009] Optionally, determining the cooling power adjustment amount of the air conditioner within the target time period based on the cooling capacity difference between the target cooling capacity and the current cooling capacity includes: obtaining the current service power consumption of the server within the current time period; using the preset cooling capacity prediction model to determine the consumed cooling capacity corresponding to the current service power consumption, wherein the consumed cooling capacity represents the cooling capacity required to cool the server within the current time period; determining the cooling capacity difference between the current cooling capacity and the consumed cooling capacity as the remaining cooling capacity within the target time period; determining the cooling capacity difference between the target cooling capacity and the remaining cooling capacity as the cooling power adjustment amount of the air conditioner within the target time period.

[0010] Optionally, the method also includes: identifying a target server whose single-machine service power consumption is higher than a preset power consumption threshold among the multiple servers in the computer room; determining a target air conditioner corresponding to the target server among the multiple air conditioners arranged in the computer room, wherein each of the air conditioners arranged in the computer room is responsible for temperature regulation of a corresponding computer room area in the computer room, and the target server is in a target computer room area corresponding to the target air conditioner; and controlling the target air conditioner to adjust the temperature of the computer room.

[0011] Optionally, the method also includes: monitoring the ambient air field in the computer room, wherein the ambient air field includes at least: an air flow velocity field representing the flow of cold air and a temperature field representing the temperature distribution; when an abnormal area appears in the ambient air field, turning on an air conditioning auxiliary module, wherein the abnormal area is an area in the computer room where the flow velocity of cold air is lower than a preset velocity threshold, or an area in the computer room where the temperature is higher than a preset temperature threshold, and the air conditioning auxiliary module is installed at the air outlet of the air conditioner to increase the air supply volume of the air conditioner.

[0012] Optionally, when the ambient air field is: the air flow velocity field, when an abnormal area appears in the ambient air field, turning on the air conditioning auxiliary module includes: based on the air flow velocity field, determining a low flow velocity area in the computer room where the flow velocity of cold air is lower than the preset speed threshold, and the air flow direction in the low flow velocity area; according to the air flow direction, turning on a target air conditioning auxiliary module corresponding to the low flow velocity area among multiple air conditioning auxiliary modules arranged in the computer room, wherein the target air conditioning auxiliary module is located upwind of the low flow velocity area, and is used to control the air flow velocity in the target direction, and the low flow velocity area is within the target direction.

[0013] According to another aspect of an embodiment of the present invention, a device for controlling the temperature of a computer room is also provided, comprising: a first prediction module, used to use a preset energy consumption prediction model to predict the target service power consumption of a server in the computer room within a target time period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple groups of first training data, and each group of first training data in the multiple groups of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical time period; a second prediction module, used to use a preset cooling capacity prediction model to analyze the target service power consumption to obtain a target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple groups of second training data, and each group of second training data in the multiple groups of second training data includes: the preset service power consumption of the server and the preset cooling capacity of the air conditioner in the same historical time period, and the preset cooling capacity is determined according to the operating parameters of the air conditioner in the historical time period; a control module, used to control the air conditioner in the computer room to adjust the computer room temperature according to the target cooling capacity within the target time period.

[0014] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-mentioned method for controlling the temperature of a computer room through the computer program.

[0015] According to another aspect of an embodiment of the present invention, a computer program product is provided, including computer instructions, which implement the steps of the above-mentioned method for controlling the temperature of a computer room when executed by a processor.

[0016] In the embodiment of the present invention, since the heat of the computer room is mainly generated by the server, the higher the power consumption of the server, the more heat is generated. Therefore, the more cooling capacity the air conditioner needs to generate. Then, the target service power consumption of the server in the computer room within the target period is predicted by a preset energy consumption prediction model, and the target cooling capacity of the air conditioner is adjusted according to the predicted target service power consumption. The computer room temperature can be adjusted in advance, and then the computer room can complete the good adjustment of the computer room temperature based on less cooling capacity, avoiding the waste of cooling capacity generated by the air conditioner, thereby achieving the technical effect of reducing the air conditioning energy consumption of the computer room, and then solving the technical problem of wasting the air conditioning energy consumption of the computer room in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 is a flow chart of a method for controlling temperature of a computer room according to an embodiment of the present invention;

[0019] Figure 2 is a schematic diagram of a device for controlling temperature of a computer room according to an embodiment of the present invention;

[0020] Figure 3 It is a structural block diagram of a computer terminal according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] According to an embodiment of the present invention, an embodiment of a method for controlling the temperature of a computer room is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] Figure 1 is a flow chart of a method for controlling the temperature of a computer room according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0025] Step S102, using a preset energy consumption prediction model to predict the target service power consumption of the server in the computer room within the target period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple sets of first training data, and each set of first training data in the multiple sets of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical period;

[0026] Step S104, using a preset cooling capacity prediction model to analyze the target service power consumption to obtain a target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple sets of second training data, and each set of second training data in the multiple sets of second training data includes: a preset service power consumption of the server and a preset cooling capacity of the air conditioner in the same historical period, and the preset cooling capacity is determined according to the operating parameters of the air conditioner in the historical period;

[0027] Step S106, controlling the air conditioner in the computer room to adjust the temperature of the computer room according to the target cooling capacity within the target time period.

[0028] In the embodiment of the present invention, since the heat of the computer room is mainly generated by the server, the higher the power consumption of the server, the more heat is generated. Therefore, the more cooling capacity the air conditioner needs to generate. Then, the target service power consumption of the server in the computer room within the target period is predicted by a preset energy consumption prediction model, and the target cooling capacity of the air conditioner is adjusted according to the predicted target service power consumption. The computer room temperature can be adjusted in advance, and then the computer room can complete the good adjustment of the computer room temperature based on less cooling capacity, avoiding the waste of cooling capacity generated by the air conditioner, thereby achieving the technical effect of reducing the air conditioning energy consumption of the computer room, and then solving the technical problem of wasting the air conditioning energy consumption of the computer room in the prior art.

[0029] In the above step S102, multiple servers may be pre-arranged in the computer room.

[0030] In the above step S102, the preset energy consumption prediction model can be determined according to the historical operating parameters of the computer room, and the historical operating parameters include: the preset service energy consumption of each server in the computer room in each historical period.

[0031] It should be noted that the heat generated by the server increases as the service energy consumption of the server increases.

[0032] In the above step S104, the target cooling capacity is used to offset the heat generated by the servers in the computer room during the target period when they are running according to the target service power consumption, that is, the cold air required by the computer room during the target period, such as the required cold air temperature and air volume.

[0033] In the above step S104, the operating parameters of the air conditioner include the compressor power of the air conditioner, that is, the cooling power, and the fan power of the air conditioner, that is, the air supply power. The higher the cooling power, the greater the cooling capacity, and the higher the air supply power, the greater the air volume.

[0034] It should be noted that if the air conditioner only has a compressor working and the fan is not working, the air conditioner will only cool a small area of ​​air where the air conditioner is located. The air flow rate in this area is low, and the lower the temperature in this area, the smaller the temperature change in this area, and the slower the change in cooling capacity, resulting in a waste of energy. Therefore, by having the fan work in conjunction with the compressor, the flow rate in the area where the air conditioner is located can be increased, the speed at which the cooling capacity increases can be increased, and the energy consumption of the air conditioner can be reduced.

[0035] As an optional embodiment, controlling the air conditioner in the computer room to adjust the temperature of the computer room according to the target cooling capacity during the target time period includes: determining the target cooling power of the air conditioner during the target time period according to the target cooling capacity required by the computer room during the target time period; and controlling the air conditioner to adjust the temperature of the computer room according to the target cooling power.

[0036] In the above embodiments of the present application, the cooling power of the air conditioner represents the energy consumption of the air conditioner in generating cold air. According to the target cooling capacity required by the computer room within the target period, the target cooling power of the air conditioner in the computer room can be controlled so that the air conditioner can generate cold air that meets the target cooling capacity when operating according to the target cooling power.

[0037] As an optional embodiment, determining the cooling power of the air conditioner within the target time period according to the target cooling capacity required by the computer room within the target time period includes: obtaining the current cooling power of the air conditioner within the current time period, wherein the current time period is earlier than the target time period and adjacent to the target time period; determining the current cooling capacity within the current time period according to the current cooling power; determining the cooling power adjustment amount of the air conditioner within the target time period according to the cooling capacity difference between the target cooling capacity and the current cooling capacity; and adjusting the current cooling power according to the cooling power adjustment amount to obtain the target cooling power.

[0038] In the above embodiment of the present application, the current time period is earlier than the target time period and is adjacent to the target time period. During the current time period, the air conditioner can operate according to the current cooling power, and then when the current time period reaches the preset time period, the cooling power of the air conditioner can be adjusted based on the current cooling power. Therefore, assuming that the air conditioner operates according to the current cooling power during the target time period and can still produce cold air according to the current cooling capacity, the current cooling power of the air conditioner is adjusted according to the cooling capacity difference between the target cooling capacity and the current cooling capacity, so as to obtain the target cooling power that meets the target cooling capacity.

[0039] As an optional embodiment, determining the cooling power adjustment amount of the air conditioner within the target time period based on the cooling capacity difference between the target cooling capacity and the current cooling capacity includes: obtaining the current service power consumption of the server within the current time period; using a preset cooling capacity prediction model to determine the consumed cooling capacity corresponding to the current service power consumption, wherein the consumed cooling capacity represents the cooling capacity required to cool the server within the current time period; determining the cooling capacity difference between the current cooling capacity and the consumed cooling capacity as the remaining cooling capacity within the target time period; determining the cooling capacity difference between the target cooling capacity and the remaining cooling capacity as the cooling power adjustment amount of the air conditioner within the target time period.

[0040] In the above-mentioned embodiment of the present application, the computer room can exchange heat between the cold air generated by the air conditioner and the hot air generated by the server in each time period; however, after the air in each time period is heat exchanged, there may be a surplus of cooling capacity, that is, the surplus cooling capacity, and then the cooling power adjustment amount of the air conditioner in the target time period is determined according to the cooling capacity difference between the target cooling capacity required for the target time period and the surplus cooling capacity, and then the cooling power adjustment amount can realize the precise adjustment of the cooling power of the air conditioner to avoid wasting the power consumption of the air conditioner.

[0041] Optionally, if the cooling capacity of the air conditioner is greater than the heat output of the server during a certain period of time, there is a surplus of cooling capacity, and the value of the surplus cooling capacity is a positive number; if the heat output of the server is greater than the cooling capacity of the air conditioner during a certain period of time, there is a shortage of cooling capacity, and the value of the surplus cooling capacity is a negative number.

[0042] As an optional embodiment, the method also includes: identifying a target server whose single-machine service power consumption is higher than a preset power consumption threshold among multiple servers in the computer room; determining a target air conditioner corresponding to the target server among multiple air conditioners arranged in the computer room, wherein each air conditioner arranged in the computer room is responsible for temperature regulation of a corresponding computer room area in the computer room, and the target server is in the target computer room area corresponding to the target air conditioner; and controlling the target air conditioner to adjust the temperature of the computer room.

[0043] In the above-mentioned embodiment of the present application, multiple servers and multiple air conditioners can be deployed in the computer room. When the single-machine service power consumption of a target server in the computer room is too high, it means that the heat generated by the target server is too high. Then, the temperature is adjusted by controlling the target air conditioner corresponding to the target server so that the cold air generated by the target air conditioner can be directly used on the target server. The temperature can be adjusted quickly and accurately, avoiding turning on all the air conditioners in the computer room and avoiding waste of air conditioning energy.

[0044] As an optional embodiment, the method also includes: monitoring the ambient air field in the computer room, wherein the ambient air field includes at least: an air flow velocity field representing the flow of cold air and a temperature field representing the temperature distribution; when an abnormal area appears in the ambient air field, turning on the air conditioning auxiliary module, wherein the abnormal area is an area in the computer room where the flow velocity of cold air is lower than a preset velocity threshold, or an area in the computer room where the temperature is higher than a preset temperature threshold, and the air conditioning auxiliary module is installed at the air outlet of the air conditioner to increase the air supply of the air conditioner.

[0045] In the above-mentioned embodiments of the present application, the air-conditioning auxiliary module is used to increase air flow and assist the air conditioner in heat exchange. Different air-conditioning auxiliary modules can control the air flow in different areas of the computer room. Therefore, when the cold air flow rate is too low or the temperature in a certain area of ​​the computer room is too high, the air-conditioning auxiliary module can be turned on to increase the air flow rate in the computer room, speed up the heat exchange of the air conditioner in the computer room, and keep the temperature of each area in the computer room balanced.

[0046] As an optional embodiment, when the ambient air field is: an air flow velocity field, when an abnormal area appears in the ambient air field, turning on the air conditioning auxiliary module includes: based on the air flow velocity field, determining a low flow velocity area in the computer room where the flow velocity of cold air is lower than a preset velocity threshold, and the air flow direction in the low flow velocity area; according to the air flow direction, turning on a target air conditioning auxiliary module corresponding to the low flow velocity area among multiple air conditioning auxiliary modules arranged in the computer room, wherein the target air conditioning auxiliary module is located upwind of the low flow velocity area, and is used to control the air flow velocity in the target direction, and the low flow velocity area is within the target direction.

[0047] In the above-mentioned embodiments of the present application, the air-conditioning auxiliary module can adjust the air flow rate in a certain direction. When a certain area in the computer room is an abnormal area, a target air-conditioning auxiliary module that can perform air conditioning on the abnormal area can be selected, and then the target air-conditioning auxiliary module can be turned on to adjust the temperature of the abnormal area more quickly and accurately.

[0048] The present invention also provides a preferred embodiment, which provides an energy-saving solution for a computer room, takes the air conditioners installed in the computer room as the main tuning target, uses big data analysis and intelligent AI control as the main technical means to carry out energy conservation and emission reduction in the data center, obtains sensor readings at the IT module level, including: data from air conditioners, temperature and humidity sensors, and display cabinets, and then uses AI algorithms to match the appropriate total IT refrigeration input, and accurately and frequently controls the cooling output of the air conditioner. On the premise of ensuring the temperature and humidity safety of the computer room, the efficiency of cooling and use of the computer room is maximized, the energy consumption of air conditioner operation is reduced, and the problem that the actual operating energy consumption of the data center is far higher than the design indicators and the level of manual energy efficiency management in operations is generally unsatisfactory is solved.

[0049] It should be noted that from the perspective of the entire IT equipment layout in the computer room, due to the large area of ​​the computer room, considering its circulating air volume and reducing the local temperature dead corners in the computer room, as well as the dynamic changes in the power consumption of the load equipment, it is impossible to achieve manual control of the air conditioner to operate according to demand. The heat generation of the computer room has no regular changes to follow. All indoor fans run at full speed, and the compressor is controlled by each air conditioner according to its own needs. This operation mode is not economical and energy-saving from the perspective of operating costs. If the redundant equipment in the air conditioning group is forced to shut down, it is difficult to control the airflow organization and temperature change rules of the computer room, and it is difficult to ensure the safety of the computer room by manually controlling the start and shutdown of the air conditioner. Therefore, there may be a phenomenon of uncontrollable local temperature. Through adaptive control energy-saving technology, the temperature, humidity and equipment load in the computer room are monitored in real time, and the operating status of the air conditioning system is automatically adjusted. The computer room air conditioning group control plays a vital role in energy saving in the computer room.

[0050] As an optional embodiment, under the premise of ensuring the normal operation of the equipment in the computer room, the energy consumption of the entire computer room is reduced by reducing the operating time of redundant air-conditioning equipment, realizing the round-robin function of the air-conditioning system, avoiding competition operation function, delayed self-start function, etc.

[0051] As another optional embodiment, the air conditioning cluster is centrally managed in combination with the energy consumption monitoring system, and the power consumption of each row of servers is calculated using an algorithm. The working status of the air conditioners at the corresponding locations is accurately controlled according to the load distribution and air conditioning distribution, which mainly includes the start and stop of the compressor and the start and stop of the fan of the air conditioner indoor unit.

[0052] Optionally, a computer room heat dissipation and airflow organization model can be established. Computational fluid dynamics technology can be used to conduct numerical analysis and model experiments on the airflow organization characteristics of the central computer room air conditioner, and to deeply analyze the airflow velocity field and temperature field distribution inside the central computer room. On this basis, a reasonable cooling capacity allocation design plan can be obtained to obtain the best supply and return air state to meet the cooling needs of the equipment, while reducing the air conditioning load and obtaining the optimal cooling capacity configuration effect.

[0053] As an optional example, the auxiliary air conditioning module ADU, when the air supply distance is long and the air supply efficiency is low, will lead to insufficient cooling capacity and air volume at the air outlet, and cannot meet the heat dissipation requirements of local equipment. In view of this situation, an active air outlet device ADU is installed at the air outlet. Through this active air supply device, the air supply efficiency of the air conditioner can be improved, so that the number of air conditioners turned on can be reduced while meeting the requirements of cooling capacity and air volume, achieving the effect of energy saving and consumption reduction.

[0054] According to an embodiment of the present invention, a device embodiment of a computer room temperature control is also provided. It should be noted that the device embodiment of the computer room temperature control can be used to execute the method for controlling the computer room temperature in the embodiment of the present invention, and the method for controlling the computer room temperature in the embodiment of the present invention can be executed in the device embodiment of the computer room temperature control.

[0055] Figure 2 is a schematic diagram of a device for controlling the temperature of a computer room according to an embodiment of the present invention. Figure 2As shown, the device may include: a first prediction module 22, used to use a preset energy consumption prediction model to predict the target service power consumption of the server in the computer room within the target time period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple groups of first training data, and each group of first training data in the multiple groups of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical time period; a second prediction module 24, used to use a preset cooling capacity prediction model to analyze the target service power consumption to obtain the target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple groups of second training data, and each group of second training data in the multiple groups of second training data includes: the preset service power consumption of the server in the same historical time period and the preset cooling capacity of the air conditioner, and the preset cooling capacity is determined according to the operating parameters of the air conditioner in the historical time period; a control module 26, used to control the air conditioner in the computer room to adjust the computer room temperature according to the target cooling capacity within the target time period.

[0056] It should be noted that the first prediction module 22 in this embodiment can be used to execute step S102 in the embodiment of the present application, the second prediction module 24 in this embodiment can be used to execute step S104 in the embodiment of the present application, the control module 26 in this embodiment can be used to execute step S106 in the embodiment of the present application, and the first closing module 78 in this embodiment can be used to execute step S108 in the embodiment of the present application. The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiments.

[0057] In the embodiment of the present invention, since the heat of the computer room is mainly generated by the server, the higher the power consumption of the server, the more heat is generated. Therefore, the more cooling capacity the air conditioner needs to generate. Then, the target service power consumption of the server in the computer room within the target period is predicted by a preset energy consumption prediction model, and the target cooling capacity of the air conditioner is adjusted according to the predicted target service power consumption. The computer room temperature can be adjusted in advance, and then the computer room can complete the good adjustment of the computer room temperature based on less cooling capacity, avoiding the waste of cooling capacity generated by the air conditioner, thereby achieving the technical effect of reducing the air conditioning energy consumption of the computer room, and then solving the technical problem of wasting the air conditioning energy consumption of the computer room in the prior art.

[0058] As an optional embodiment, the control module includes: a determination unit, used to determine the target cooling power of the air conditioner within the target period according to the target cooling capacity required by the computer room within the target period; and a control unit, used to control the air conditioner to adjust the temperature of the computer room according to the target cooling power.

[0059] As an optional embodiment, the determination unit includes: a first acquisition unit, used to acquire the current cooling power of the air conditioner in the current time period, wherein the current time period is earlier than the target time period and adjacent to the target time period; a second determination unit, used to determine the current cooling capacity in the current time period according to the current cooling power; a third determination unit, used to determine the cooling power adjustment amount of the air conditioner in the target time period according to the cooling capacity difference between the target cooling capacity and the current cooling capacity; and an adjustment unit, used to adjust the current cooling power according to the cooling power adjustment amount to obtain the target cooling power.

[0060] As an optional embodiment, the third determination unit includes: a second acquisition unit, used to acquire the current service power consumption of the server in the current time period; a fourth determination unit, used to analyze the target service power consumption using a preset cooling capacity prediction model to obtain the target cooling capacity corresponding to the target service power consumption, wherein the consumed cooling capacity represents the cooling capacity required to cool the server in the current time period; a fifth determination subunit, used to determine the cooling capacity difference between the current cooling capacity and the consumed cooling capacity as the remaining cooling capacity in the target time period; the fifth determination subunit, used to determine the cooling capacity difference between the target cooling capacity and the remaining cooling capacity as the cooling power adjustment amount of the air conditioner in the target time period.

[0061] As an optional embodiment, the device includes: an identification submodule, used to identify a target server whose single-machine service power consumption is higher than a preset power consumption threshold among multiple servers in a computer room; a determination submodule, used to determine a target air conditioner corresponding to the target server among multiple air conditioners arranged in the computer room, wherein each air conditioner arranged in the computer room is responsible for temperature regulation of a corresponding computer room area in the computer room, and the target server is in the target computer room area corresponding to the target air conditioner; and a control submodule, used to control the target air conditioner to adjust the temperature of the computer room.

[0062] As an optional embodiment, the device also includes: a monitoring submodule, used to monitor the ambient air field in the computer room, wherein the ambient air field includes at least: an air flow velocity field representing the flow of cold air and a temperature field representing the temperature distribution; a turning on submodule, used to turn on the air conditioning auxiliary module when an abnormal area appears in the ambient air field, wherein the abnormal area is an area in the computer room where the flow velocity of cold air is lower than a preset velocity threshold, or an area in the computer room where the temperature is higher than a preset temperature threshold, and the air conditioning auxiliary module is installed at the air outlet of the air conditioner to increase the air supply of the air conditioner.

[0063] As an optional embodiment, when the ambient air field is: an air flow velocity field, the opening submodule includes: a determination subunit, used to determine, based on the air flow velocity field, a low flow velocity area in the computer room where the cold air flow velocity is lower than a preset velocity threshold, and the air flow direction in the low flow velocity area; an opening unit, used to open a target air-conditioning auxiliary module corresponding to the low flow velocity area among multiple air-conditioning auxiliary modules arranged in the computer room according to the air flow direction, wherein the target air-conditioning auxiliary module is located upwind of the low flow velocity area, and is used to control the air flow velocity in the target direction, and the low flow velocity area is within the target direction.

[0064] An embodiment of the present invention may provide an electronic device, which may be a computer terminal, and the computer terminal may be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal may also be replaced by a terminal device such as a mobile terminal.

[0065] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0066] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the method for controlling the temperature of the computer room: using a preset energy consumption prediction model to predict the target service power consumption of the server in the computer room within the target time period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple groups of first training data, and each group of first training data in the multiple groups of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical time period; using a preset cooling capacity prediction model to analyze the target service power consumption to obtain the target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple groups of second training data, and each group of second training data in the multiple groups of second training data includes: the preset service power consumption of the server in the same historical time period and the preset cooling capacity of the air conditioner, and the preset cooling capacity is determined according to the operating parameters of the air conditioner in the historical time period; controlling the air conditioner in the computer room to adjust the computer room temperature according to the target cooling capacity within the target time period.

[0067] Figure 3 is a structural block diagram of a computer terminal according to an embodiment of the present invention. Figure 3 As shown, the computer terminal 30 may include: one or more (only one is shown in the figure) processors 32 , and a memory 34 .

[0068] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the method and device for controlling the temperature of the computer room in the embodiment of the present invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the above-mentioned method for controlling the temperature of the computer room. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the terminal 30 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0069] The processor can call the information and application programs stored in the memory through the transmission device to perform the following steps: use a preset energy consumption prediction model to predict the target service power consumption of the server in the computer room within the target time period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple groups of first training data, and each group of first training data in the multiple groups of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical time period; use a preset cooling capacity prediction model to analyze the target service power consumption to obtain the target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple groups of second training data, and each group of second training data in the multiple groups of second training data includes: the preset service power consumption of the server in the same historical time period and the preset cooling capacity of the air conditioner, and the preset cooling capacity is determined according to the operating parameters of the air conditioner in the historical time period; control the air conditioner in the computer room to adjust the computer room temperature according to the target cooling capacity within the target time period.

[0070] Optionally, the processor may also execute program codes of the following steps: determining a target cooling power of the air conditioner within the target period according to a target cooling capacity required by the computer room within the target period; and controlling the air conditioner to adjust the temperature of the computer room according to the target cooling power.

[0071] Optionally, the processor may also execute the program code of the following steps: obtaining the current cooling power of the air conditioner in the current time period, wherein the current time period is earlier than the target time period and adjacent to the target time period; determining the current cooling capacity in the current time period based on the current cooling power; determining the cooling power adjustment amount of the air conditioner in the target time period based on the cooling capacity difference between the target cooling capacity and the current cooling capacity; and adjusting the current cooling power according to the cooling power adjustment amount to obtain the target cooling power.

[0072] Optionally, the processor may also execute the program code of the following steps: obtaining the current service power consumption of the server in the current time period; using a preset cooling capacity prediction model to determine the consumed cooling capacity corresponding to the current service power consumption, wherein the consumed cooling capacity represents the cooling capacity required to cool the server in the current time period; determining the cooling capacity difference between the current cooling capacity and the consumed cooling capacity as the remaining cooling capacity in the target time period; determining the cooling capacity difference between the target cooling capacity and the remaining cooling capacity as the cooling power adjustment amount of the air conditioner in the target time period.

[0073] Optionally, the processor may also execute program code of the following steps: among multiple servers in the computer room, identify a target server whose single-machine service power consumption is higher than a preset power consumption threshold; among multiple air conditioners arranged in the computer room, determine a target air conditioner corresponding to the target server, wherein each air conditioner arranged in the computer room is responsible for temperature regulation of a corresponding computer room area in the computer room, and the target server is in the target computer room area corresponding to the target air conditioner; and control the target air conditioner to adjust the temperature of the computer room.

[0074] Optionally, the processor may also execute the program code of the following steps: monitoring the ambient air field in the computer room, wherein the ambient air field includes at least: an air flow velocity field representing the flow of cold air and a temperature field representing the temperature distribution; when an abnormal area appears in the ambient air field, turning on the air conditioning auxiliary module, wherein the abnormal area is an area in the computer room where the flow velocity of cold air is lower than a preset velocity threshold, or an area in the computer room where the temperature is higher than a preset temperature threshold, and the air conditioning auxiliary module is installed at the air outlet of the air conditioner to increase the air supply of the air conditioner.

[0075] Optionally, when the ambient air field is: an air flow velocity field, the above-mentioned processor can also execute the program code of the following steps: based on the air flow velocity field, determine the low flow velocity area in the computer room where the cold air flow velocity is lower than a preset velocity threshold, and the air flow direction in the low flow velocity area; according to the air flow direction, among the multiple air-conditioning auxiliary modules arranged in the computer room, turn on the target air-conditioning auxiliary module corresponding to the low flow velocity area, wherein the target air-conditioning auxiliary module is located upwind of the low flow velocity area, and is used to control the air flow velocity in the target direction, and the low flow velocity area is within the target direction.

[0076] By adopting the embodiment of the present invention, a control scheme for the temperature of a computer room is provided. In the embodiment of the present invention, since the heat of the computer room is mainly generated by the server, the higher the power consumption of the server, the more heat is generated, and therefore, the more cooling capacity the air conditioner needs to generate, and then the target service power consumption of the server in the computer room within the target period is predicted by a preset energy consumption prediction model, and the target cooling capacity of the air conditioner is adjusted according to the predicted target service power consumption, so that the temperature of the computer room can be adjusted in advance, and then the computer room can complete a good adjustment of the temperature of the computer room based on less cooling capacity, avoiding waste of the cooling capacity generated by the air conditioner, thereby achieving the technical effect of reducing the air conditioning energy consumption of the computer room, and then solving the technical problem of wasting the air conditioning energy consumption of the computer room in the prior art.

[0077] It can be understood by those skilled in the art that Figure 3 The structure shown is for illustration only, and the computer terminal may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a handheld computer, a mobile Internet device (Mobile Internet Devices, MID), a PAD, or other terminal devices. Figure 3 The structure of the electronic device is not limited. For example, the computer terminal 30 may also include Figure 3 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 3 Different configurations are shown.

[0078] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a computer program. The computer program can be stored in a non-volatile medium. The non-volatile storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0079] The embodiment of the present invention further provides a non-volatile storage medium. Optionally, in this embodiment, the non-volatile storage medium can be used to store the program code executed by the method for controlling the temperature of a computer room provided in the embodiment.

[0080] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0081] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: using a preset energy consumption prediction model to predict the target service power consumption of the server in the computer room within a target time period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple groups of first training data, and each group of first training data in the multiple groups of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical time period; using a preset cooling capacity prediction model to analyze the target service power consumption to obtain a target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple groups of second training data, and each group of second training data in the multiple groups of second training data includes: the preset service power consumption of the server and the preset cooling capacity of the air conditioner within the same historical time period, and the preset cooling capacity is determined according to the operating parameters of the air conditioner within the historical time period; controlling the air conditioner in the computer room to adjust the computer room temperature according to the target cooling capacity within the target time period.

[0082] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: determining a target cooling power of the air conditioner within the target period based on a target cooling capacity required by the computer room within the target period; and controlling the air conditioner to adjust the temperature of the computer room based on the target cooling power.

[0083] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: obtaining a current cooling power of the air conditioner in a current time period, wherein the current time period is earlier than a target time period and is adjacent to the target time period; determining a current cooling capacity in the current time period based on the current cooling power; determining a cooling power adjustment amount of the air conditioner in the target time period based on a cooling capacity difference between the target cooling capacity and the current cooling capacity; and adjusting the current cooling power according to the cooling power adjustment amount to obtain a target cooling power.

[0084] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for executing the following steps: obtaining the current service power consumption of the server in the current time period; using a preset cooling capacity prediction model to determine the consumed cooling capacity corresponding to the current service power consumption, wherein the consumed cooling capacity represents the cooling capacity required to cool the server in the current time period; determining the cooling capacity difference between the current cooling capacity and the consumed cooling capacity as the remaining cooling capacity in the target time period; determining the cooling capacity difference between the target cooling capacity and the remaining cooling capacity as the cooling power adjustment amount of the air conditioner in the target time period.

[0085] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: among multiple servers in a computer room, identifying a target server whose single-machine service power consumption is higher than a preset power consumption threshold; among multiple air conditioners arranged in the computer room, determining a target air conditioner corresponding to the target server, wherein each air conditioner arranged in the computer room is responsible for temperature regulation of a corresponding computer room area in the computer room, and the target server is in a target computer room area corresponding to the target air conditioner; and controlling the target air conditioner to adjust the temperature of the computer room.

[0086] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: monitoring the ambient air field in the computer room, wherein the ambient air field includes at least: an air flow velocity field representing the flow of cold air and a temperature field representing the temperature distribution; in the event of an abnormal area in the ambient air field, turning on the air conditioning auxiliary module, wherein the abnormal area is an area in the computer room where the flow velocity of cold air is lower than a preset velocity threshold, or an area in the computer room where the temperature is higher than a preset temperature threshold, and the air conditioning auxiliary module is installed at the air outlet of the air conditioner to increase the air supply of the air conditioner.

[0087] Optionally, in this embodiment, when the ambient air field is: an air flow velocity field, the non-volatile storage medium is configured to store program codes for executing the following steps: based on the air flow velocity field, determining a low flow velocity area in the computer room where the flow velocity of cold air is lower than a preset velocity threshold, and the air flow direction in the low flow velocity area; according to the air flow direction, among multiple air-conditioning auxiliary modules arranged in the computer room, turning on a target air-conditioning auxiliary module corresponding to the low flow velocity area, wherein the target air-conditioning auxiliary module is located upwind of the low flow velocity area, and is used to control the air flow velocity in the target direction, and the low flow velocity area is within the target direction.

[0088] The embodiment of the present invention further provides a computer program product, including a computer program. Optionally, in this embodiment, when the computer program is executed by a processor, the steps of the method for controlling the temperature of a computer room provided in the above embodiment are implemented.

[0089] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0090] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0092] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0093] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0094] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a non-volatile storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned non-volatile storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0095] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for controlling the temperature of a machine room, characterized in that: include: Use a preset energy consumption prediction model to predict the target service power consumption of the server in the computer room within the target time period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple sets of first training data, and each set of first training data in the multiple sets of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical time period; The target service power consumption is analyzed using a preset cooling capacity prediction model to obtain a target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple sets of second training data, and each set of second training data in the multiple sets of second training data includes: a preset service power consumption of the server and a preset cooling capacity of the air conditioner in the same historical period, and the preset cooling capacity is determined according to operating parameters of the air conditioner in the historical period; The air conditioner in the computer room is controlled to adjust the temperature of the computer room according to the target cooling capacity within the target time period.

2. The method according to claim 1, characterized in that Controlling the air conditioner in the computer room to adjust the temperature of the computer room according to the target cooling capacity within the target time period includes: Determining a target cooling power of the air conditioner within the target period according to the target cooling capacity required by the computer room within the target period; According to the target cooling power, the air conditioner is controlled to adjust the temperature of the computer room.

3. The method according to claim 2, characterized in that Determining the cooling power of the air conditioner within the target time period according to the target cooling capacity required by the computer room within the target time period includes: Acquire the current cooling power of the air conditioner in a current time period, wherein the current time period is earlier than the target time period and is adjacent to the target time period; Determining a current cooling capacity within the current period according to the current cooling power; Determining a cooling power adjustment amount of the air conditioner within the target time period according to a cooling capacity difference between the target cooling capacity and the current cooling capacity; The current refrigeration power is adjusted according to the refrigeration power adjustment amount to obtain the target refrigeration power.

4. The method according to claim 3, characterized in that Determining the cooling power adjustment amount of the air conditioner within the target time period according to the cooling capacity difference between the target cooling capacity and the current cooling capacity includes: Obtaining the current service power consumption of the server in the current time period; Using the preset cooling capacity prediction model, determining the consumed cooling capacity corresponding to the current service power consumption, wherein the consumed cooling capacity represents the cooling capacity required to cool the server in the current period; Determine the difference between the current cooling capacity and the consumed cooling capacity as the remaining cooling capacity within the target period; The cooling capacity difference between the target cooling capacity and the remaining cooling capacity is determined as the cooling power adjustment amount of the air conditioner in the target time period.

5. The method according to claim 1, characterized in that: The method further comprises: Among the plurality of servers in the computer room, identifying a target server whose single-machine service power consumption is higher than a preset power consumption threshold; Determine a target air conditioner corresponding to the target server among a plurality of air conditioners arranged in the computer room, wherein each of the air conditioners arranged in the computer room is responsible for temperature regulation of a corresponding computer room area in the computer room, and the target server is in the target computer room area corresponding to the target air conditioner; The target air conditioner is controlled to adjust the temperature of the computer room.

6. The method according to claim 1, characterized in that The method further comprises: Monitoring the ambient air field in the equipment room, wherein the ambient air field at least includes: an air flow velocity field representing the flow of cold air and a temperature field representing the temperature distribution; When an abnormal area appears in the ambient air field, the air conditioning auxiliary module is turned on, wherein the abnormal area is an area in the computer room where the flow speed of cold air is lower than a preset speed threshold, or an area in the computer room where the temperature is higher than a preset temperature threshold, and the air conditioning auxiliary module is installed at the air outlet of the air conditioner to increase the air supply of the air conditioner.

7. The method according to claim 6, characterized in that When the ambient air field is: the air flow velocity field, and when an abnormal area appears in the ambient air field, starting the air conditioning auxiliary module includes: Based on the air flow velocity field, determining a low velocity area in the computer room where the flow velocity of cold air is lower than the preset velocity threshold, and an air flow direction in the low velocity area; According to the air flow direction, among the multiple air-conditioning auxiliary modules arranged in the computer room, the target air-conditioning auxiliary module corresponding to the low flow velocity area is turned on, wherein the target air-conditioning auxiliary module is located upwind of the low flow velocity area, and is used to control the air flow velocity in the target direction, and the low flow velocity area is within the target direction.

8. A device for controlling the temperature of a machine room, characterized in that: include: A first prediction module is used to use a preset energy consumption prediction model to predict the target service power consumption of the server in the computer room within the target period, wherein the preset energy consumption prediction model is pre-trained by machine learning using multiple sets of first training data, and each set of first training data in the multiple sets of first training data includes: the preset service power consumption corresponding to the server in the computer room in each historical period; a second prediction module, configured to analyze the target service power consumption using a preset cooling capacity prediction model to obtain a target cooling capacity corresponding to the target service power consumption, wherein the preset cooling capacity prediction model is pre-trained by machine learning using multiple sets of second training data, and each set of second training data in the multiple sets of second training data includes: a preset service power consumption of the server and a preset cooling capacity of the air conditioner in the same historical period, and the preset cooling capacity is determined according to an operating parameter of the air conditioner in the historical period; The control module is used to control the air conditioner in the computer room to adjust the temperature of the computer room according to the target cooling capacity within the target time period.

9. An electronic device, comprising a memory and a processor, characterized in that: The memory stores a computer program, and the processor is configured to execute the method for controlling the temperature of a computer room according to any one of claims 1 to 7 through the computer program.

10. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by the processor, the steps of the method for controlling the temperature of a computer room described in any one of claims 1 to 7 are implemented.

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