CN116406137A - Differential pressure self-adaptive adjustment method, system and equipment based on temperature sensing change - Google Patents
Differential pressure self-adaptive adjustment method, system and equipment based on temperature sensing change Download PDFInfo
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Abstract
The invention relates to the technical field of water-cooled equipment control, in particular to a differential pressure self-adaptive adjustment method, a differential pressure self-adaptive adjustment system and differential pressure self-adaptive equipment based on temperature change, wherein the method comprises the following steps: collecting differential pressure data at the water-cooling unit end and temperature sensing data in a data center machine room to form a basic data set; performing data preprocessing on the basic data set to form an original data set; performing visual analysis and linear fitting on the original data set; setting up and down confidence intervals of differential pressure floating, and determining a translation range of a fitting straight line; and determining the pressure difference value setting range of the water cooling equipment according to the alarm threshold value of the temperature sense. The method is easy to collect data, does not need a large number of calculation and complex models, and is simple and efficient; the intelligent control system can be flexibly adjusted according to the real-time condition and the target state of the target machine room, and meets different safety and energy-saving requirements. In addition, the method has the advantages of fast calculation, fast model iteration, capability of meeting the change of different seasons and environments and strong adaptability.
Description
Technical Field
The invention relates to the technical field of water-cooled equipment control, in particular to a differential pressure self-adaptive adjustment method, system and equipment based on temperature sensing change.
Background
Data centers, one of the most important infrastructures for contemporary social life, carry a great deal of network computing, network communication tasks. With the rapid development of communication technology, the rapid popularization of 5G technology, and the gradual expansion of large data application scale, the data processing capability, data computing capability, network communication capability and the like of a data center have become a particularly critical ring in economic development and social life. Meanwhile, the working, learning and shopping modes of people are greatly changed, a large number of online live broadcast group purchase, online education and remote office work are greatly developed, and a data center is used as a core foundation of the application, so that the national high attention is paid.
Although the status of data centers is increasing, the energy consumption for their operation is enormous. The national data size in 2020 is 6.4 kilowatts ZB, and the power consumption of the data center is 2045 hundred million kilowatt-hours; the data size of 2030 is expected to reach 409.6 kzb, the electricity consumption will reach 4000 hundred million kilowatt-hours, which will account for more than 4% of the national electricity consumption. Therefore, the energy conservation and emission reduction of the data center have great economic value and social significance.
Most of the existing machine rooms of the data center are traditional precise air conditioners with the tail end achieving refrigeration through compressors and fans and water-cooling air conditioning systems with high-efficiency refrigerating units. In the case of a water cooling system, the water cooling unit cools the cooling water to a certain value and then conveys the cooling water to the water inlet pipeline of each machine room through the hydraulic pump, so as to provide a cold source for each machine room. However, due to different IT loads in each machine room and different IT energy consumption in different time periods, the heat sources can have different distributions in time and space. Most of the existing systems ensure the cold energy source of the machine room through lower water temperature and larger water flow, and the problem of uneven heat source distribution in space-time is solved to a certain extent, but larger energy consumption is also brought.
Aiming at the problems, a method for adjusting the water supply quantity of the water cooling unit end based on the real-time environment temperature of the machine room needs to be developed so as to solve the problem of saving cold energy and conveying the cold energy maximally.
Disclosure of Invention
Aiming at the problem that the energy consumption is large because the IT load quantity and the load energy consumption of different machine rooms are unevenly distributed in time and space at present, the differential pressure self-adaptive adjustment method, system and equipment based on temperature sensing change are provided, the temperature data of each sensor of the machine rooms are associated with the differential pressure data of the machine set end, and the ideal differential pressure data of the water cooling machine set is found through statistical analysis and data mining of historical data.
In order to achieve the above object, the present invention is realized by the following technical scheme:
a differential pressure adaptive adjustment method based on temperature sensing variation, the method comprising:
collecting differential pressure data at the water-cooling unit end and temperature sensing data in a data center machine room to form a basic data set;
performing data preprocessing on the basic data set to form an original data set;
performing visual analysis and linear fitting on the original data set;
setting up and down confidence intervals of differential pressure floating, and determining a translation range of a fitting straight line;
and determining the pressure difference value setting range of the water cooling equipment according to the alarm threshold value of the temperature sense.
As a preferable scheme of the invention, the differential pressure data is specifically the difference value of the pressure of a water inlet pipe and a water outlet pipe at the end of the water cooling unit, and the temperature sensing data is specifically the temperature sensing temperature data of a cold channel of which the tail end is a precision air conditioner.
As a preferred embodiment of the present invention, the data preprocessing includes data cleansing, data integration, and data conversion.
As a preferable scheme of the invention, the data cleaning comprises the steps of carrying out missing value and abnormal value processing on data in a basic data set, and removing outliers and abnormal values; and determining a distribution interval according to the data distribution, setting the data exceeding the interval range as a null value, screening the data, and carrying out interpolation supplementation when less than 5 continuous missing values exist, and filling the missing values by using the average value of the adjacent points.
As a preferred embodiment of the present invention, the method for performing visual analysis and linear fitting on an original data set specifically includes: performing correlation detection on the preprocessed temperature sensing temperature data and the differential pressure data, and combining the temperature sensing temperature data and the differential pressure data with correlation less than-0.8 into a visualized data set for visualization analysis, wherein the visualized data set is visualizedxThe axis is the differential pressure data,ythe axis is temperature sensing temperature data; according to the data distribution in the visualization, performing linear fitting on the screened temperature sensing temperature data and the differential pressure data to obtain a fitting straight liney=kx+bWhereinkThe slope is indicated as such,brepresenting the intercept.
As a preferred scheme of the present invention, the method for setting the upper and lower confidence intervals of the differential pressure floating and determining the translation range of the fitting straight line includes: calculating all data point distance fitting straight line in visual data sety=kx+bDistance value of (2)dDistance valuedThe calculation formula of (2) is as follows:
distance valuedAt positive values, the data points are in straight linesy=kx+bUpper, distance valuedAt negative values, the data points are in straight linesy=kx+bBelow, according to the distance valuedIs to repartition of data in a visual dataset into two datasetsu 1 Andu 2 the method comprises the steps of carrying out a first treatment on the surface of the Setting data setsu 1 Has a section expansion coefficient ofa 1 Data setu 2 Has a section expansion coefficient ofa 2 ，a 1 、a 2 ∈[0,2]The method comprises the steps of carrying out a first treatment on the surface of the Use of data setsu 1 Andu 2 upper quartile->
And lower quartile->
Is the difference of (a)a 1 Multiplication and additiona 2 The multiple is used as the upper confidence interval and the lower confidence interval of the differential pressure floating, and the fitting straight line is determinedy=kx+bIs limited by the translation range of (2)b r The method comprises the following steps:
according to the translation rangeb r Respectively obtain fitting straight linesy=kx+bIs a straight line of translation of (2)
,/>
;/>
,/>
。
As a preferable scheme of the invention, the setting range of the differential pressure value of the water cooling equipment is determined according to the alarm threshold value of the temperature sense, and the method specifically comprises the following steps: according to the alarm threshold value of temperature sensing and fitting straight liney=kx+bStraight line of translationl 1 、l 2 And (3) obtaining three values of the differential pressure by three intersection points obtained by intersection, and obtaining the finally determined differential pressure adjustable range.
As a preferable scheme of the invention, when the temperature sensing temperature of the machine room is higher, the temperature sensing temperature is increaseda 1 Value, decreasea 2 The value of the pressure difference is increased, and the pressure difference is the upper limit value of the adjustable range, namelyl 1 The cold water pumped in the machine room is increased, namely the cold energy is increased, by the intersection point value obtained by intersection; when the temperature sensing temperature of the machine room is lower, the temperature is reduceda 1 Value of increasea 2 The value of the pressure difference is reduced, and the pressure difference is the lower limit value of the adjustable range, namelyl 2 And the cold water entering the machine room is reduced by the intersection point value obtained by intersection, so that the purpose of energy saving is realized.
A differential pressure adaptive adjustment system based on temperature sensing changes, the system comprising:
the data acquisition module is used for acquiring differential pressure data of the water cooling unit end and temperature sensing temperature data in a data center machine room;
the data processing module is used for carrying out data preprocessing on the differential pressure data and the temperature sensing data to form an original data set;
the data analysis mining module is used for carrying out visual analysis and linear fitting on the original data set;
the floating interval definition module is used for setting up upper and lower confidence intervals of differential pressure floating, determining a translation range of a fitting straight line, and determining a differential pressure value setting range of the water cooling equipment according to an alarm threshold value of temperature sensation;
the pressure difference self-adaptive adjusting module is used for automatically adjusting the pressure difference according to the temperature change, thereby controlling the water supply quantity at the water cooling unit end.
A differential pressure adaptive adjustment device based on a change in temperature sensation, the differential pressure adaptive adjustment device comprising a processor and a memory, wherein at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement a differential pressure adaptive adjustment method based on a change in temperature sensation as described above.
Compared with the prior art, the invention has the following beneficial effects: according to the differential pressure self-adaptive adjustment method based on temperature-sensing temperature change, temperature-sensing temperature data of a machine room and differential pressure data of a machine set end are obtained in real time, a model is obtained through statistical analysis and data mining of historical data, ideal differential pressure data of the machine set end is adjusted in real time, and self-adaptive adjustment of differential pressure is achieved. The main power consumption of the water cooling system is reflected in the setting of the water outlet temperature and the water quantity conveyed to each machine room by the water pump, namely, the frequency of the pump is regulated by the pressure difference, and the water inlet quantity of each machine room is controlled, so that the frequency of the water pump at the water cooling unit end can be reduced as much as possible to save energy from the unit end under the condition that the temperature sensing temperature in the machine room does not exceed the set threshold, and the excessive cold water is prevented from being pumped into the pipeline of the machine room, thereby causing resource waste. When the temperature sensor is used, only the temperature data of the temperature sensor and the pressure difference data of the unit are required to be collected, the data are easy to collect, a large number of calculation and complex models are not required, and the temperature sensor is simple and efficient; and the real-time condition and the target state of the target machine room can be flexibly adjusted, so that different safety and energy-saving requirements are met. In addition, the method has the advantages of fast calculation, fast model iteration, capability of meeting the change of different seasons and environments and strong adaptability.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a flow chart of a method for determining the pressure differential adjustable range in an embodiment of the invention;
fig. 3 is a system configuration diagram of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
As shown in fig. 1, in an embodiment of the present invention, a differential pressure adaptive adjustment method based on temperature variation is provided, which specifically includes the following steps:
s1: collecting differential pressure data at the water-cooling unit end and temperature sensing data in a data center machine room to form a basic data set;
in one embodiment, the differential pressure data is specifically a difference value between the pressure of a water inlet pipe and the pressure of a water outlet pipe at the end of the water cooling unit, and the temperature sensing data is specifically temperature sensing temperature data of a cold channel of which the end is a precision air conditioner;
the invention mainly focuses on the temperature sense of the cold channel of the precise air conditioner at the tail end, and the hot channel and the mixed channel have no visual effect on the refrigerating effect of the cold channel, so that the two temperature senses of the hot channel and the mixed channel are not considered.
S2: performing data preprocessing on the basic data set, wherein the data preprocessing comprises data cleaning, data integration and data conversion to form an original data set;
the data cleaning comprises the steps of carrying out missing value and abnormal value processing on data in a basic data set, and removing outliers and abnormal values; and determining a distribution interval according to the data distribution, setting the data exceeding the interval range as a null value, screening the data, and carrying out interpolation supplementation when less than 5 continuous missing values exist, and filling the missing values by using the average value of the adjacent points.
In one embodiment, a temperature sensing temperature distribution interval is determined according to the cold channel temperature sensing data distribution, and the temperature sensing temperature data exceeding the interval range is set to be a null value, wherein the interval range of the temperature sensing is [10,35]. And screening the differential pressure data according to the adjustable value range of the unit end control system, and then interpolating and supplementing null values in a small range, wherein specifically, when less than 5 continuous missing values exist, the missing values are filled by using the average value of adjacent points.
S3: performing visual analysis and linear fitting on the original data set;
in one embodiment, the correlation of the preprocessed temperature-sensitive temperature data and the pressure difference data is detected, and the temperature-sensitive temperature data and the pressure difference data with correlation less than-0.8 are combined into a visual data set for visual analysis, wherein the visual analysis is performedxThe axis is the differential pressure data,ythe axis is temperature sensing temperature data; according to the data distribution in the visualization, performing linear fitting on the screened temperature sensing temperature data and the differential pressure data to obtain a fitting straight liney=kx+bWhereinkThe slope is indicated as such,brepresenting the intercept.
S4: setting up upper and lower confidence intervals of differential pressure floating, and determining a translation range of a fitting straight line, wherein the method comprises the following specific steps of:
calculating all data point distance fitting straight line in visual data sety=kx+bDistance value of (2)dDistance valuedThe calculation formula of (2) is as follows:
distance valuedAt positive values, the data points are in straight linesy=kx+bUpper, distance valuedAt negative values, the data points are in straight linesy=kx+bBelow, according to the distance valuedIs to repartition of data in a visual dataset into two datasetsu 1 Andu 2 the method comprises the steps of carrying out a first treatment on the surface of the Setting data setsu 1 Has a section expansion coefficient ofa 1 Data setu 2 Has a section expansion coefficient ofa 2 ，a 1 、a 2 ∈[0,2]The method comprises the steps of carrying out a first treatment on the surface of the Use of data setsu 1 Andu 2 upper quartile->
And lower quartile->
Is the difference of (a)a 1 Multiplication and additiona 2 The multiple is used as the upper confidence interval and the lower confidence interval of the differential pressure floating, and the fitting straight line is determinedy=kx+bIs limited by the translation range of (2)b r The method comprises the following steps:
according to the calculation, we can obtain three straight lines, namely fitting straight linesy=kx +bAnd a translation straight line thereof +.>
，/>
；/>
，
。
S5: and determining the pressure difference adjustable range of the water cooling equipment according to the alarm threshold value of the temperature sense.
According to the alarm threshold value of temperature sensing and fitting straight liney=kx+bStraight line of translationl 1 、l 2 Three intersection points obtained by intersection are used for obtaining three values of the differential pressure, and finally, a final differential pressure adjustable range is obtained;
in one embodiment, as shown in fig. 2, when the temperature of the machine room is higher, we can increase the temperature appropriatelya 1 Value, decreasea 2 Value of the value ofl 1 、l 2 The whole is inclined to the right of the coordinate axis, so that when the temperature sensing alarm threshold value is intersected, the obtained pressure difference adjustable range is closer to the right of the coordinate axis, a larger pressure difference is obtained, and the pressure difference selects the upper limit value of the adjustable range, namely, the pressure difference is matched with the temperature sensing alarm threshold valuel 1 The cold water pumped in the machine room is increased, namely the cold energy is increased, by the intersection point value obtained by intersection; similarly, when the temperature sensing temperature of the machine room is lower, the temperature sensing temperature can be properly reduceda 1 Value of increasea 2 Value of the value ofl 1 、l 2 The whole is inclined to the left of the coordinate axis, so that when the temperature sensing alarm threshold value is intersected, the obtained pressure difference adjustable range is closer to the left of the coordinate axis, and therefore one can be obtainedA small pressure difference, in which case the pressure difference selects the lower limit value of the adjustable range, i.e. andl 2 and the cold water entering the machine room is reduced by the intersection point value obtained by intersection, so that the purpose of energy saving is realized. Alarm threshold value of temperature sensing and fitting straight liney=kx+bThe intersection point of (2) can be used as an intermediate adjustment value, i.e. when the adjustment range is too large, a two-step adjustment can be accomplished.
By the method, when the machine room needs more cooling capacity, the pressure difference can be increased at the machine set end, and more cooling water is provided for the machine room to cool; when the machine room is at low temperature, the pressure difference can be reduced, the supply quantity of cold water can be reduced, the consumption of a machine set end can be reduced, and the purpose of energy saving can be achieved.
As shown in fig. 3, an embodiment of the present invention provides a differential pressure adaptive adjustment system based on temperature variation, which specifically includes:
the data acquisition module is used for acquiring differential pressure data of the water cooling unit end and temperature sensing temperature data in a data center machine room;
the data processing module is used for carrying out data preprocessing on the differential pressure data and the temperature sensing data to form an original data set;
the data analysis mining module is used for carrying out visual analysis and linear fitting on the original data set;
the floating interval definition module is used for setting up upper and lower confidence intervals of differential pressure floating, determining a translation range of a fitting straight line, and determining a differential pressure value setting range of the water cooling equipment according to an alarm threshold value of temperature sensation;
the pressure difference self-adaptive adjusting module is used for automatically adjusting the pressure difference according to the temperature change, thereby controlling the water supply quantity at the water cooling unit end.
The invention further provides a differential pressure self-adaptive adjustment device based on temperature change, which comprises a processor and a memory, wherein at least one instruction, at least one section of program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one section of program, the code set or the instruction set is loaded and executed by the processor to realize the differential pressure self-adaptive adjustment method based on temperature change.
In summary, according to the differential pressure self-adaptive adjustment method based on temperature-sensing temperature change, temperature-sensing temperature data of a machine room and differential pressure data of a machine set end are obtained in real time, a model is obtained through statistical analysis and data mining of historical data, ideal differential pressure data of the machine set end is adjusted in real time, and self-adaptive adjustment of differential pressure is achieved. The main power consumption of the water cooling system is reflected in the setting of the water outlet temperature and the water quantity conveyed to each machine room by the water pump, namely, the frequency of the pump is regulated by the pressure difference, and the water inlet quantity of each machine room is controlled, so that the frequency of the water pump at the water cooling unit end can be reduced as much as possible to save energy from the unit end under the condition that the temperature sensing temperature in the machine room does not exceed the set threshold, and the excessive cold water is prevented from being pumped into the pipeline of the machine room, thereby causing resource waste. When the temperature sensor is used, only the temperature data of the temperature sensor and the pressure difference data of the unit are required to be collected, the data are easy to collect, a large number of calculation and complex models are not required, and the temperature sensor is simple and efficient; and the real-time condition and the target state of the target machine room can be flexibly adjusted, so that different safety and energy-saving requirements are met. In addition, the method has the advantages of fast calculation, fast model iteration, capability of meeting the change of different seasons and environments and strong adaptability.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the methods of the embodiments described above may be performed by a program that, when executed, comprises one or a combination of the steps of the method embodiments, instructs the associated hardware to perform the method.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules described above, if implemented in the form of software functional modules and sold or used as a stand-alone product, may also be stored in a computer-readable storage medium. The storage medium may be a read-only memory, a magnetic disk, an optical disk, or the like.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
Claims (10)
1. A differential pressure self-adaptive adjustment method based on temperature sensing change, which is characterized by comprising the following steps:
collecting differential pressure data at the water-cooling unit end and temperature sensing data in a data center machine room to form a basic data set;
performing data preprocessing on the basic data set to form an original data set;
performing visual analysis and linear fitting on the original data set;
setting up and down confidence intervals of differential pressure floating, and determining a translation range of a fitting straight line;
and determining the pressure difference value setting range of the water cooling equipment according to the alarm threshold value of the temperature sense.
2. The adaptive differential pressure adjusting method based on temperature sensing change according to claim 1, wherein the differential pressure data is specifically a difference value between the pressure of a water inlet pipe and the pressure of a water outlet pipe at the end of a water cooling unit, and the temperature sensing data is specifically temperature sensing temperature data of a cold channel of which the end is a precision air conditioner.
3. The differential pressure adaptive adjustment method based on temperature sensing variation according to claim 1, wherein the data preprocessing comprises data cleansing, data integration and data conversion.
4. The adaptive differential pressure adjustment method based on temperature variation according to claim 3, wherein the data cleaning comprises the steps of performing missing value and outlier processing on data in a basic data set, and removing outliers and outliers; and determining a distribution interval according to the data distribution, setting the data exceeding the interval range as a null value, screening the data, and carrying out interpolation supplementation when less than 5 continuous missing values exist, and filling the missing values by using the average value of the adjacent points.
5. The adaptive pressure difference adjustment method based on temperature sensing variation according to claim 1, wherein the method for performing visual analysis and linear fitting on the raw data set specifically comprises: performing correlation detection on the preprocessed temperature sensing temperature data and the differential pressure data, and combining the temperature sensing temperature data and the differential pressure data with correlation less than-0.8 into a visualized data set for visualization analysis, wherein the visualized data set is visualizedxThe axis is the differential pressure data,ythe axis is temperature sensing temperature data; according to the data distribution in the visualization, performing linear fitting on the screened temperature sensing temperature data and the differential pressure data to obtain a fitting straight liney=kx+ bWhereinkThe slope is indicated as such,brepresenting the intercept.
6. The adaptive adjustment method of differential pressure based on temperature variation according to claim 5, wherein the method for setting the upper and lower confidence intervals of differential pressure floating and determining the translation range of the fitting straight line comprises: calculating all data point distance fitting straight line in visual data sety=kx+bDistance value of (2)dDistance valuedThe calculation formula of (2) is as follows:
distance valuedAt positive values, the data points are in straight linesy=kx+bUpper, distance valuedAt negative values, the data points are in straight linesy=kx+bBelow, according to the distance valuedIs to repartition of data in a visual dataset into two datasetsu 1 Andu 2 the method comprises the steps of carrying out a first treatment on the surface of the Setting data setsu 1 Interval of (2)Expansion coefficient is as followsa 1 Data setu 2 Has a section expansion coefficient ofa 2 ，a 1 、a 2 ∈[0,2]The method comprises the steps of carrying out a first treatment on the surface of the Use of data setsu 1 Andu 2 upper quartile->
And lower quartile->
Is the difference of (a)a 1 Multiplication and additiona 2 The multiple is used as the upper confidence interval and the lower confidence interval of the differential pressure floating, and the fitting straight line is determinedy=kx+bIs limited by the translation range of (2)b r The method comprises the following steps: />
According to the translation rangeb r Respectively obtain fitting straight linesy=kx+bIs +.>
，
；/>
，/>
。
7. The adaptive adjustment method of differential pressure based on temperature change according to claim 6, wherein the determining the differential pressure value setting range of the water cooling device according to the alarm threshold of temperature change is specifically: according to the alarm threshold value of temperature sensing and fitting straight liney=kx+bStraight line of translationl 1 、l 2 Three intersection points obtained by intersection are used for obtaining three values of the differential pressure, and finally obtaining the finally determined differential pressure adjustable rangeAnd (5) enclosing.
8. The adaptive differential pressure regulating method based on temperature variation as set forth in claim 7, wherein when the machine room temperature is higher, the differential pressure is increaseda 1 Value, decreasea 2 The value of the pressure difference is increased, and the pressure difference is the upper limit value of the adjustable range, namelyl 1 The cold water pumped in the machine room is increased, namely the cold energy is increased, by the intersection point value obtained by intersection; when the temperature sensing temperature of the machine room is lower, the temperature is reduceda 1 Value of increasea 2 The value of the pressure difference is reduced, and the pressure difference is the lower limit value of the adjustable range, namelyl 2 And the cold water entering the machine room is reduced by the intersection point value obtained by intersection, so that the purpose of energy saving is realized.
9. A system based on a differential pressure adaptive adjustment method based on temperature sensing variation as claimed in any one of claims 1-8, characterized in that the system comprises:
the data acquisition module is used for acquiring differential pressure data of the water cooling unit end and temperature sensing temperature data in a data center machine room;
the data processing module is used for carrying out data preprocessing on the differential pressure data and the temperature sensing data to form an original data set;
the data analysis mining module is used for carrying out visual analysis and linear fitting on the original data set;
the floating interval definition module is used for setting up upper and lower confidence intervals of differential pressure floating, determining a translation range of a fitting straight line, and determining a differential pressure value setting range of the water cooling equipment according to an alarm threshold value of temperature sensation;
the pressure difference self-adaptive adjusting module is used for automatically adjusting the pressure difference according to the temperature change, thereby controlling the water supply quantity at the water cooling unit end.
10. A differential pressure adaptive adjustment device based on a change in temperature, the differential pressure adaptive adjustment device comprising a processor and a memory, the memory storing at least one instruction, at least one program, a set of codes, or a set of instructions, the at least one instruction, the at least one program, the set of codes, or the set of instructions being loaded and executed by the processor to implement a differential pressure adaptive adjustment method based on a change in temperature as claimed in any one of claims 1 to 8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117858479A (en) * | 2024-03-06 | 2024-04-09 | 南京群顶科技股份有限公司 | Method for updating weight relation of air conditioner on environmental temperature in real time |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100280680A1 (en) * | 2009-04-29 | 2010-11-04 | International Business Machines Corporation | Processor cooling management |
| CN111836524A (en) * | 2020-07-24 | 2020-10-27 | 广州亿效能科技有限公司 | IT load change-based method for regulating and controlling variable air volume of precision air conditioner between data center columns |
| US11096316B1 (en) * | 2018-09-05 | 2021-08-17 | Amazon Technologies, Inc. | Discrete set-point-based datacenter cooling based on evaporative cooling status |
| CN114963414A (en) * | 2022-06-08 | 2022-08-30 | 山东润一智能科技有限公司 | Air conditioning system intelligent regulation and control device based on AI data analysis |
| CN115003140A (en) * | 2022-08-04 | 2022-09-02 | 浩鲸云计算科技股份有限公司 | Cooperative control energy-saving method for air conditioner at tail end of water cooling unit of data center machine room |
| CN115796066A (en) * | 2022-09-06 | 2023-03-14 | 东南大学 | Energy-saving method of data center air conditioning system based on pre-refrigeration |
-
2023
- 2023-04-23 CN CN202310439208.2A patent/CN116406137B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100280680A1 (en) * | 2009-04-29 | 2010-11-04 | International Business Machines Corporation | Processor cooling management |
| US11096316B1 (en) * | 2018-09-05 | 2021-08-17 | Amazon Technologies, Inc. | Discrete set-point-based datacenter cooling based on evaporative cooling status |
| CN111836524A (en) * | 2020-07-24 | 2020-10-27 | 广州亿效能科技有限公司 | IT load change-based method for regulating and controlling variable air volume of precision air conditioner between data center columns |
| CN114963414A (en) * | 2022-06-08 | 2022-08-30 | 山东润一智能科技有限公司 | Air conditioning system intelligent regulation and control device based on AI data analysis |
| CN115003140A (en) * | 2022-08-04 | 2022-09-02 | 浩鲸云计算科技股份有限公司 | Cooperative control energy-saving method for air conditioner at tail end of water cooling unit of data center machine room |
| CN115796066A (en) * | 2022-09-06 | 2023-03-14 | 东南大学 | Energy-saving method of data center air conditioning system based on pre-refrigeration |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117858479A (en) * | 2024-03-06 | 2024-04-09 | 南京群顶科技股份有限公司 | Method for updating weight relation of air conditioner on environmental temperature in real time |
| CN117858479B (en) * | 2024-03-06 | 2024-05-03 | 南京群顶科技股份有限公司 | Method for updating weight relation of air conditioner on environmental temperature in real time |
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