Intelligent water cooling system energy efficiency analysis and optimization scheduling system

Abstract

The invention relates to the technical field of water-cooling heat dissipation, in particular to an energy efficiency analysis and optimal scheduling system for an intelligent water-cooling system. The system comprises a data preprocessing module used for obtaining a load power sequence, a temperature sequence and a water cooling power sequence; the target sequence establishing module is used for calculating power temperature proportionality coefficients according to data in the same time interval in the load power sequence and the temperature sequence, and correcting the power temperature proportionality coefficients to form a target sequence; the heat dissipation environment influence analysis module is used for calculating the environment influence degree according to the data in the data segment closest to the current adjusting moment on the left side and the corrected power temperature proportionality coefficient at the current adjusting moment; and the heat dissipation power calculation module is used for obtaining the heat dissipation demand degree at the next adjustment moment of the current adjustment moment and then obtaining the power of the water cooling system at the next adjustment moment of the current adjustment moment. The power of the water-cooling heat dissipation system can be adjusted, and energy consumption is reduced while the heat dissipation effect is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of water-cooled heat dissipation, and particularly to an energy efficiency analysis and optimal scheduling system for an intelligent water-cooled system. Background Art

[0002] A water-cooled system is a cooling method that uses a liquid (usually water or a coolant containing antifreeze) as a heat transfer medium. Its core is to remove the heat in the device or system through the flow of the liquid. This system is commonly used in scenarios that require efficient heat dissipation, such as high-performance CPU heat dissipation in the computer field, temperature control of large industrial equipment, and cooling of automobile engines. During operation, the heat dissipation system needs to perform real-time analysis based on various monitoring data to optimize the power scheduling of the water-cooled heat dissipation system in real time, so as to achieve the lowest energy consumption and cost while meeting the cooling requirements, extend the service life of the equipment, and improve the reliability of the system.

[0003] The existing water-cooled heat dissipation system mainly adjusts the radiator power by monitoring the temperature of the area to be cooled to maintain the required temperature level. However, this heat dissipation method may overly rely on the feedback of temperature sensors for adjustment. In actual heat dissipation, the heat dissipation effect may be affected by the ambient temperature and the air fluidity around the equipment, which may lead to untimely heat dissipation or unnecessary energy consumption of the water-cooled system. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide an energy efficiency analysis and optimal scheduling system for an intelligent water-cooled system, and the specific technical solutions adopted are as follows: An embodiment of the present invention provides an energy efficiency analysis and optimal scheduling system for an intelligent water-cooled system. The system includes: a data preprocessing module, which is used to collect the load power data, temperature data of the equipment heat dissipation area, and the power of the water-cooled system and align them to obtain a load power sequence, a temperature sequence, and a water-cooled power sequence; A target sequence establishment module, which is used to uniformly divide the load power sequence, the temperature sequence, and the water-cooled power sequence to obtain corresponding time intervals; calculate the power-temperature ratio coefficient according to the data in the same time interval in the load power sequence and the temperature sequence; correct each power-temperature ratio coefficient according to the data in each time interval in the water-cooled power sequence and form a target sequence; A heat dissipation environment impact analysis module, which is used to set the adjustment time; segment the target sequence using the extreme points in the target sequence to obtain the data segment closest to the current adjustment time on the left; calculate the environmental impact degree according to the data in the data segment closest to the current adjustment time on the left and the corrected power-temperature ratio coefficient at the current adjustment time; The heat dissipation power calculation module is used to obtain the heat dissipation demand degree at the next adjustment moment of the current adjustment moment according to the temperature and the environmental impact degree at the current adjustment moment; and obtain the power of the water cooling system at the next adjustment moment of the current adjustment moment according to the current moment, the heat dissipation demand degree at the next adjustment moment of the current adjustment moment, and the power of the water cooling system at the current adjustment moment.

[0005] Preferably, obtaining the load power sequence, the temperature sequence, and the water cooling power sequence includes: Setting the transmission delay of the temperature data of the equipment heat dissipation area; moving the data values at each moment in the collected load power data and the power of the water cooling system of the equipment heat dissipation area backward, and the moving duration is the transmission delay, to obtain the aligned load power data, temperature data, and the power of the water cooling system of the equipment heat dissipation area, and respectively form the load power sequence, the temperature sequence, and the water cooling power sequence.

[0006] Preferably, calculating the power-temperature proportionality coefficient according to the data in the same time interval in the load power sequence and the temperature sequence includes: Calculating the sum of the load power data in each time interval in the load power sequence, and using the exponential function with the natural constant as the base to map the sum of the load power data in each time interval to obtain the first mapping result corresponding to each time interval; calculating the sum of the temperature data in each time interval in the temperature sequence, and using the exponential function with the natural constant as the base to map the sum of the temperature data in each time interval to obtain the second mapping result corresponding to each time interval; the ratio of the first mapping result and the second mapping result corresponding to the same time interval is the power-temperature proportionality coefficient.

[0007] Preferably, correcting each power-temperature proportionality coefficient according to the data in each time interval in the water cooling power sequence and forming a target sequence includes: Calculating the sum of the power data in each time interval in the water cooling power sequence, and using the exponential function with the natural constant as the base to map the sum of the power data in each time interval to obtain the third mapping result corresponding to each time interval; multiplying the third mapping result corresponding to each time interval by the power-temperature proportionality coefficient to obtain the corrected power-temperature proportionality coefficient; the corrected power-temperature proportionality coefficients corresponding to each time interval are arranged in chronological order to form the target sequence.

[0008] Preferably, calculating the environmental impact degree includes: Taking the reciprocal of the corrected power-temperature proportionality coefficient corresponding to the current adjustment moment; averaging the ratios of every two adjacent data in the data segment closest to the current adjustment moment on the left to obtain the average value, where the ratio of every two adjacent data is the ratio of the data at the previous moment to the data at the next moment; the product of the reciprocal and the average value is the environmental impact degree at the current adjustment moment.

[0009] Preferably, obtaining the heat dissipation demand degree of the next adjustment moment at the current adjustment moment according to the temperature and the degree of environmental influence at the current adjustment moment includes: The product of the temperature at the current adjustment moment and the degree of environmental influence is the heat dissipation demand degree of the next adjustment moment at the current adjustment moment.

[0010] Preferably, obtaining the power of the water cooling system at the next adjustment moment at the current adjustment moment includes: Obtaining the ratio of the heat dissipation demand degree of the next adjustment moment at the current adjustment moment to the heat dissipation demand degree at the current adjustment moment, and the product result of the ratio and the power of the water cooling system at the current adjustment moment is the power of the water cooling system at the next adjustment moment at the current adjustment moment.

[0011] Preferably, before segmenting the target sequence using the extreme points in the target sequence to obtain the data segment closest to the current adjustment moment on the left, it further includes: Filtering and smoothing the target sequence using a Savitzky-Golay filter.

[0012] The embodiments of the present invention have at least the following beneficial effects: The present invention first collects the load power data, temperature data, and the power of the water cooling system in the heat dissipation area of the device and aligns them to obtain a load power sequence, a temperature sequence, and a water cooling power sequence, which is convenient for subsequent analysis; further, comprehensively analyzing the load power sequence, the temperature sequence, and the water cooling power sequence to obtain a corrected power-temperature proportionality coefficient and forming a target sequence, improving the accuracy and comprehensiveness of the power-temperature proportionality coefficient; then setting the adjustment moment and segmenting and analyzing the target sequence to calculate the degree of environmental influence at the current adjustment moment; then further analyzing to obtain the heat dissipation demand degree of the next adjustment moment at the current adjustment moment, and then calculating the power of the water cooling system at the next adjustment moment at the current adjustment moment, and using the calculated power to adjust the power of the water cooling system at the next adjustment moment at the current adjustment moment, and by controlling and adjusting the heat dissipation power of the water cooling system in real time, to achieve more accurate and real-time adjustment and control of the power of the water cooling system and improve the energy efficiency ratio of the heat dissipation process. Description of the Drawings

[0013] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0014] Figure 1This is a system block diagram of an intelligent water-cooling system energy efficiency analysis and optimization scheduling system provided by an embodiment of the present invention. Detailed implementation manners

[0015] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following combines the accompanying drawings and preferred embodiments to specifically describe a system for analyzing the energy efficiency and optimizing the scheduling of an intelligent water-cooling system according to the present invention, including its specific implementation manners, structures, features, and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0016] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0017] The following specifically describes the specific solution of a system for analyzing the energy efficiency and optimizing the scheduling of an intelligent water-cooling system provided by the present invention with reference to the accompanying drawings.

[0018] Embodiment: The main application scenarios of the present invention are as follows: Traditional water-cooling methods may rely too much on the feedback of temperature sensors for adjustment. However, in the actual heat dissipation process, the heat dissipation effect may be affected by factors such as the ambient temperature and the air fluidity around the equipment, which may lead to untimely heat dissipation or unnecessary energy consumption in the water-cooling system.

[0019] Please refer to Figure 1 , which shows a system block diagram of an intelligent water-cooling system energy efficiency analysis and optimization scheduling system provided by an embodiment of the present invention. The system includes the following modules: A data preprocessing module, which is used to collect the load power data, temperature data, and the power of the water-cooling system in the heat dissipation area of the equipment and align them to obtain a load power sequence, a temperature sequence, and a water-cooling power sequence.

[0020] When the equipment is working, some components or modules need water-cooling for heat dissipation because they generate a high amount of heat. If air-cooling is used, it is very likely to cause damage to the components. For example, the CPU of a computer and the engine of a vehicle. The components that need to be cooled in these devices are recorded as the heat dissipation area, and the water-cooling system is connected to the heat dissipation area.

[0021] In this example, the water-cooling system in a computer device is taken as an example for analysis, and the analysis principle of the water-cooling systems of other devices is similar. When an electric current passes through the conductors or components in the equipment, heat is generated due to resistance, and this heat is transmitted to the heat sink through heat-conducting materials, and the coolant of the water-cooling system is used to transfer the heat of the heat sink.

[0022] Further, the temperature data of the device heat dissipation area (CPU), the load power data of the device heat dissipation area, and the power of the water cooling system are collected through a temperature sensor and power monitoring software respectively. The collection frequency needs to be set by the implementer according to the actual situation.

[0023] During the actual heat dissipation process, the temperature of the device is mainly generated when the device is working. There is a certain delay time from the generation of the temperature to its detection, which is set here as the temperature transfer time delay of t seconds. Preferably, in the embodiment of the present invention, the transfer time delay is set to 0.5 seconds, and different devices can be set according to the actual heat conduction rate.

[0024] Furthermore, according to the set transfer time delay, the load power data, temperature data, and the power of the water cooling system of the device heat dissipation area collected are aligned. The alignment method is to move the data value at each moment in the load power data and the power of the water cooling system of the device heat dissipation area collected backward as the data value at the corresponding moment after the movement. The duration (step size) of the movement is the transfer time delay, that is, 0.5 seconds. Thus, the above three types of data are aligned to obtain the aligned load power data, temperature data, and the power of the water cooling system of the device heat dissipation area, and they are respectively formed into a load power sequence, a temperature sequence, and a water cooling power sequence.

[0025] The target sequence establishment module is used to respectively perform uniform interval division on the load power sequence, the temperature sequence, and the water cooling power sequence to obtain corresponding time intervals; calculate the power-temperature ratio coefficient according to the data in the same time interval in the load power sequence and the temperature sequence; correct each power-temperature ratio coefficient according to the data in each time interval in the water cooling power sequence and form a target sequence.

[0026] The water cooling system is a system that uses a liquid (usually water or a coolant containing antifreeze) as a heat transfer medium to conduct away the heat generated during the working process of the heat dissipation object in a timely manner. The traditional water cooling heat dissipation method generally senses the temperature of the heat generating area through a temperature sensor, so as to control the water cooling system to work for heat dissipation. Since the heat in the heat dissipation area is generally mainly due to the energy of the components in the heat dissipation area not being completely converted during operation, and thus is converted into the form of heat energy, etc. During the heat dissipation process, the heat dissipation effect may be affected by the external environmental temperature and air fluidity, which may lead to untimely heat dissipation or unnecessary energy consumption during the heat dissipation process of the water cooling system.

[0027] Since the heat generated during the operation of the heat dissipation area has a certain proportional relationship with the change in the detected temperature data without being affected by the external environmental temperature and heat loss. However, in the actual heat dissipation process, the fluidity of air and the environmental temperature may cause changes in the relationship between the two. Therefore, in order to more accurately analyze the impact of the environment on the heat dissipation efficiency of the heat dissipation system, it is necessary to analyze the data in the load power sequence and temperature sequence.

[0028] Furthermore, uniformly divide the load power sequence, temperature sequence, and water-cooling power sequence into intervals to obtain corresponding time intervals. The length of the time interval is 0.5 seconds, and the implementer can select an appropriate length according to the actual situation. Then, calculate the proportional relationship between the load power data and temperature data in each time interval in the load power sequence and temperature sequence. Specifically, calculate the sum of the load power data in each time interval in the load power sequence, and use the exponential function with the natural constant as the base to map the sum of the load power data in each time interval to obtain the first mapping result corresponding to each time interval; calculate the sum of the temperature data in each time interval in the temperature sequence, and use the exponential function with the natural constant as the base to map the sum of the temperature data in each time interval to obtain the second mapping result corresponding to each time interval; the ratio of the first mapping result and the second mapping result corresponding to the same time interval is the power-temperature proportionality coefficient.

[0029] Then the specific calculation formula for the power-temperature proportionality coefficient of each time interval is: , where, represents the power-temperature proportionality coefficient corresponding to the a-th time interval; e represents the natural constant; represents the s-th load power data in the a-th time interval in the load power sequence; represents the s-th temperature data in the a-th time interval in the temperature sequence; represents the number of data in the a-th time interval. represents the cumulative sum of the load power data in the a-th time interval, represents the first mapping result corresponding to the a-th time interval, represents the cumulative sum of the temperature data in the a-th time interval, represents the second mapping result corresponding to the a-th time interval. Using the natural constant e to map the cumulative sum is to prevent the denominator from being 0. The power-temperature proportionality coefficient of each time interval can represent the proportional relationship between the load power data and temperature data of the heat generation area in a time interval.

[0030] The proportional relationship between the load power data and the temperature data for any time interval is thus obtained, which is the power-temperature proportionality coefficient. During the actual monitoring process, the water-cooling system may also operate for heat dissipation. Therefore, in order to eliminate the situation where the heat dissipation of the water-cooling system causes the above coefficient to change, and thus improve the accuracy of the analysis of environmental impact factors. Therefore, it is necessary to further correct the above proportionality coefficient in combination with the power of the water-cooling system for heat dissipation.

[0031] Specifically, calculate the sum of the power data within each time interval in the water-cooling power sequence, and use the exponential function with the natural constant as the base to map the sum of the power data for each time interval to obtain the third mapping result corresponding to each time interval; multiply the third mapping result corresponding to each time interval by the power-temperature proportionality coefficient to obtain the corrected power-temperature proportionality coefficient. The specific calculation formula is: , where, represents the corrected power-temperature proportionality coefficient for the a-th time interval; represents the power-temperature proportionality coefficient corresponding to the a-th time interval before correction; the s-th power data within the a-th time interval in the water-cooling power sequence; represents the sum of the power data within the a-th time interval, represents the third mapping result corresponding to the a-th time interval, which is used as the correction coefficient for the proportionality coefficient between the load power data and the temperature data within the a-th interval.

[0032] Thus, the corrected power-temperature proportionality coefficient corresponding to each time interval can be obtained. The corrected power-temperature proportionality coefficients corresponding to each time interval form a target sequence in chronological order. The timestamp of each data in the target sequence is the last time node within the time interval corresponding to each data. Therefore, the timestamp of each data in the target sequence also corresponds to a moment.

[0033] The heat dissipation environment impact analysis module is used to set the adjustment moment, segment the target sequence using the extreme points in the target sequence to obtain the data segment closest to the current adjustment moment on the left; calculate the environmental impact degree based on the data in the data segment closest to the current adjustment moment on the left and the corrected power-temperature proportionality coefficient at the current adjustment moment.

[0034] The target sequence is obtained through the above analysis. When the heat dissipation area is not affected by the external environment during the heat dissipation process, the target sequence is relatively stable. If the external temperature is high or the air circulation is poor, the target sequence may show a downward trend. This indicates that the heat dissipation area is affected by the external environmental temperature, resulting in poor heat dissipation effect. In this case, it may be necessary to further increase the heat dissipation power of the water cooling system to achieve effective heat dissipation. On the contrary, it means that the heat dissipation effect is relatively good at this time. Then the water cooling system can use environmental auxiliary heat dissipation and appropriately reduce the heat dissipation power to avoid unnecessary energy consumption caused by excessive heat dissipation. At the same time, it is also necessary to set the moment for the water cooling system to adjust. In the present invention, it is set to adjust once every 0.5 seconds, which is recorded as the adjustment moment. The implementer can adjust the adjustment moment according to the actual situation. For example, it can be set to adjust once every 1 second.

[0035] Therefore, in order to obtain the change trend and relationship in the target sequence corresponding to the current adjustment moment, it is necessary to use the Savitzky-Golay filter to filter and smooth the target sequence to ensure better analysis of the trend change of the target sequence. The Savitzky-Golay filter is a mathematical algorithm for data smoothing. It smooths the signal by polynomial fitting while trying to maintain the characteristics of the data (such as peaks and waveforms).

[0036] Furthermore, for the processed target sequence, according to the points where the first derivative is 0 and the second derivative is not 0, the extreme points in the processed target sequence are obtained. The extreme points are used as demarcation points to segment the target sequence, and the data segment closest to the current adjustment moment on the left is obtained. The time corresponding to the last data in the data segment closest to the current adjustment moment on the left is the current adjustment moment. Then, the data segment closest to the current adjustment moment on the left is analyzed to obtain the degree of environmental influence at the current adjustment moment. Thus, the influencing factors of the external environment on the heat dissipation process of the device's heat dissipation area at the latest moment can be understood, so as to facilitate subsequent adjustment of the heat dissipation strategy of the water cooling system.

[0037] Among them, for the data segment closest to the current adjustment moment on the left, the current adjustment moment is the timestamp of the last data in the data segment closest to the current adjustment moment on the left in the target sequence. The position of an adjustment moment in the data segment closest to it on the left is not the first moment, but can only be the last moment or any moment between the first moment and the last moment.

[0038] Specifically, obtain the reciprocal of the corrected power-temperature proportionality coefficient corresponding to the current adjustment moment; calculate the average of the ratios of every two adjacent data in the data segment on the left that is closest to the current adjustment moment, where the ratio of every two adjacent data is the ratio of the data at the previous moment to the data at the next moment; the product of the reciprocal and the average value is the degree of environmental influence at the current adjustment moment.

[0039] The specific calculation formula for the degree of environmental influence at the current adjustment moment is: , where K represents the degree of environmental influence at the current adjustment moment; represents the corrected power-temperature proportionality coefficient at the current adjustment moment; g represents the number of data in the data segment on the left that is closest to the current adjustment moment; represents the corrected power-temperature proportionality coefficient corresponding to the r-th moment in the data segment on the left that is closest to the current adjustment moment; represents the corrected power-temperature proportionality coefficient corresponding to the (r + 1)-th moment in the data segment on the left that is closest to the current adjustment moment. The smaller the value of, that is, the larger the value, then it indicates that the current heat dissipation is affected by the external environment, resulting in a worse heat dissipation efficiency. represents the ratio of the r-th data to the (r + 1)-th data in the data segment on the left that is closest to the current adjustment moment. The larger this value, the more obvious the downward trend between the two. Taking the average can represent whether the overall downward trend of the data segment on the left that is closest to the current adjustment moment is obvious. If the overall downward trend is obvious, then it indicates that the current heat dissipation area may be disturbed by the external environment, resulting in a worse heat dissipation effect.

[0040] Therefore, through the above, the value of the degree of influence by the external environment corresponding to the current adjustment moment is obtained. When the degree of environmental influence is greater, then it may be necessary to additionally increase the heat dissipation power or, for the purpose of cooling the device. Conversely, the power of the heat dissipation system can be reduced to save energy consumption.

[0041] The heat dissipation power calculation module is used to obtain the heat dissipation demand degree at the next adjustment moment corresponding to the current adjustment moment according to the temperature and the degree of environmental influence at the current adjustment moment; obtain the power of the water cooling system at the next adjustment moment corresponding to the current adjustment moment according to the current moment, the heat dissipation demand degree at the next adjustment moment corresponding to the current adjustment moment, and the power of the water cooling system at the current adjustment moment.

[0042] Further, based on the calculated environmental impact degree at the current adjustment moment and combined with the temperature at the current adjustment moment, calculate the heat dissipation demand degree at the next adjustment moment of the current adjustment moment. The product of the temperature and the environmental impact degree at the current adjustment moment is the heat dissipation demand degree at the next adjustment moment of the current adjustment moment.

[0043] The specific calculation formula is: , Wherein, represents the heat dissipation demand degree at the next adjustment moment of the current adjustment moment; represents the temperature at the current adjustment moment; K represents the environmental impact degree at the current adjustment moment. The greater the temperature at the current adjustment moment, it indicates that the temperature is higher at this time, and the greater the power required for the water-cooled heat dissipation system to work at the next moment. The greater the environmental impact degree, it indicates that the environmental impact on the heat dissipation effect may be poor, and then the greater the power of the heat dissipation system for heat dissipation.

[0044] Then, based on the heat dissipation demand degree at the next adjustment moment of the current adjustment moment, the heat dissipation demand degree at the current adjustment moment, and the power of the water-cooled system at the current adjustment moment, obtain the power of the water-cooled system at the next adjustment moment of the current adjustment moment. Specifically, obtain the ratio of the heat dissipation demand degree at the next adjustment moment of the current adjustment moment to the heat dissipation demand degree at the current adjustment moment. The product result of the ratio and the power of the water-cooled system at the current adjustment moment is the power of the water-cooled system at the next adjustment moment of the current adjustment moment. The specific calculation formula is: , Wherein, represents the power of the water-cooled system at the next adjustment moment of the current adjustment moment; represents the power of the water-cooled system at the current adjustment moment; represents the heat dissipation demand degree at the next adjustment moment of the current adjustment moment; represents the heat dissipation demand degree at the current adjustment moment. The way to obtain the heat dissipation demand degree at the current adjustment moment is the same as that of the heat dissipation demand degree at the next adjustment moment of the current adjustment moment. When calculating, the temperature and environmental impact degree of the previous adjustment moment of the current adjustment moment are used.

[0045] represents the ratio of the heat dissipation demand degree value of the water-cooled heat dissipation system at the next adjustment moment of the current adjustment moment to the heat dissipation demand degree value of the water-cooled heat dissipation system at the current adjustment moment. The larger this value is, it indicates that the heat dissipation demand degree of the water-cooled heat dissipation system at the next adjustment moment increases, and then the greater its heat dissipation power may be to improve the heat dissipation effect. On the contrary, it indicates that the heat dissipation demand at the next adjustment moment is smaller, and the heat dissipation power of the water-cooled heat dissipation system is smaller to avoid waste of energy consumption caused by excessive heat dissipation at high power.

[0046] Through the above, the predicted output power of the water-cooled heat dissipation system at the next adjustment moment of the device's current adjustment moment can be obtained. After obtaining the predicted value, then using the control system of the water-cooled heat dissipation system in the device, the predicted heat dissipation power is output at the next moment, so as to achieve the purpose of adjusting the coolant flow rate and cooling rate in the water-cooled system, so as to realize more accurate and real-time adjustment and control of the power of the water-cooled system and improve the energy efficiency ratio of the heat dissipation process.

[0047] It should be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of this specification have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0048] Each embodiment in this specification is described in a progressive manner. The same or similar parts between each embodiment can be referred to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

[0049] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent water cooling system energy efficiency analysis and optimization scheduling system, characterized in that: The system includes: The data preprocessing module is used to collect the load power data, temperature data and the power of the water cooling system in the equipment heat dissipation area and align them to obtain the load power sequence, temperature sequence and water cooling power sequence; The target sequence establishment module is used to evenly divide the load power sequence, temperature sequence and water cooling power sequence into corresponding time intervals; calculate the power-temperature proportional coefficient according to the data in the same time interval in the load power sequence and temperature sequence; and modify each power-temperature proportional coefficient according to the data in each time interval in the water cooling power sequence to form a target sequence; The heat dissipation environment impact analysis module is used to set the adjustment time; segment the target sequence using the extreme value points in the target sequence to obtain the data segment closest to the current adjustment time on the left; calculate the environmental impact degree based on the data in the data segment closest to the current adjustment time on the left and the power-temperature proportional coefficient corrected at the current adjustment time; The heat dissipation power calculation module is used to obtain the heat dissipation requirement at the next adjustment moment after the current adjustment moment according to the temperature and environmental impact degree at the current adjustment moment; and obtain the power of the water cooling system at the next adjustment moment after the current adjustment moment according to the heat dissipation requirement at the current moment and the next adjustment moment after the current adjustment moment, and the power of the water cooling system at the current adjustment moment.

2. According to claim 1, the intelligent water cooling system energy efficiency analysis and optimization scheduling system is characterized in that: The step of obtaining a load power sequence, a temperature sequence and a water cooling power sequence comprises: Set the transmission delay of the temperature data of the equipment heat dissipation area; move the data value of the collected load power data of the equipment heat dissipation area and the power of the water cooling system at each moment backward, and the length of the movement is the transmission delay, and obtain the aligned load power data, temperature data of the equipment heat dissipation area and the power of the water cooling system, and form a load power sequence, temperature sequence and water cooling power sequence respectively.

3. According to claim 1, the intelligent water cooling system energy efficiency analysis and optimization scheduling system is characterized in that: The power-temperature proportionality coefficient is calculated based on the data in the same time interval in the load power sequence and the temperature sequence, including: The sum of the load power data of each time interval is calculated in the load power sequence, and the sum of the load power data of each time interval is mapped using an exponential function with a natural constant as the base to obtain a first mapping result corresponding to each time interval; the sum of the temperature data of each time interval is calculated in the temperature sequence, and the sum of the temperature data of each time interval is mapped using an exponential function with a natural constant as the base to obtain a second mapping result corresponding to each time interval; the ratio of the first mapping result and the second mapping result corresponding to the same time interval is the power-temperature proportional coefficient.

4. The intelligent water cooling system energy efficiency analysis and optimization scheduling system according to claim 1 is characterized in that: The method of correcting each power-temperature proportional coefficient according to the data of each time interval in the water-cooling power sequence and forming a target sequence includes: The sum of power data is calculated in each time interval in the water-cooled power sequence, and the sum of power data in each time interval is mapped using an exponential function with a natural constant as the base to obtain a third mapping result corresponding to each time interval; the third mapping result corresponding to each time interval and the power-temperature proportional coefficient are multiplied to obtain a corrected power-temperature proportional coefficient; the corrected power-temperature proportional coefficient corresponding to each time interval is organized into a target sequence in chronological order.

5. The intelligent water cooling system energy efficiency analysis and optimization scheduling system according to claim 1 is characterized in that: The computing environment impact degree includes: Take the reciprocal of the corrected power-temperature proportional coefficient corresponding to the current adjustment moment; average the ratio of every two adjacent data in the data segment on the left closest to the current adjustment moment to obtain an average value, where the ratio of every two adjacent data is the ratio of the data at the previous moment to the data at the next moment; the product of the reciprocal and the average value is the degree of environmental impact at the current adjustment moment.

6. The intelligent water cooling system energy efficiency analysis and optimization scheduling system according to claim 1 is characterized in that: The step of obtaining the heat dissipation requirement at the next adjustment moment after the current adjustment moment according to the temperature at the current adjustment moment and the degree of environmental influence includes: The product of the temperature at the current adjustment moment and the degree of environmental impact is the heat dissipation requirement degree at the next adjustment moment after the current adjustment moment.

7. The intelligent water cooling system energy efficiency analysis and optimization scheduling system according to claim 1 is characterized in that: The obtaining of the power of the water cooling system at the next adjustment time of the current adjustment time includes: The ratio of the heat dissipation requirement at the next adjustment moment to the current adjustment moment is obtained, and the product of the ratio and the power of the water cooling system at the current adjustment moment is the power of the water cooling system at the next adjustment moment to the current adjustment moment.

8. The intelligent water cooling system energy efficiency analysis and optimization scheduling system according to claim 1 is characterized in that: Before segmenting the target sequence using the extreme value points in the target sequence to obtain the data segment closest to the current adjustment time on the left, the method further includes: The target sequence is filtered and smoothed using the Savitzky-Golay filter.

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