An intelligent water cooling system energy efficiency analysis and optimization scheduling system

Abstract

The present application relates to the technical field of water cooling heat dissipation, and particularly relates to an intelligent water cooling system energy efficiency analysis and optimization scheduling system. The system comprises: a data preprocessing module, which is used to obtain a load power sequence, a temperature sequence and a water cooling power sequence; a target sequence establishing module, which is used to calculate power temperature proportionality coefficients according to data in the same time interval in the load power sequence and the temperature sequence, and correct each power temperature proportionality coefficient to form a target sequence; a heat dissipation environment influence analysis module, which is used to calculate an environment influence degree according to data in a data segment closest to data of a current adjustment time on the left and the power temperature proportionality coefficient corrected at the current adjustment time; and a heat dissipation power calculation module, which is used to obtain a heat dissipation demand degree of a next adjustment time of the current adjustment time, and then obtain a power of the water cooling system at the next adjustment time of the current adjustment time. The present application can adjust the power of the water cooling heat dissipation system, ensure the heat dissipation effect and reduce energy consumption.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water-cooling heat dissipation, in particular to an intelligent water-cooling system energy efficiency analysis and optimization scheduling system. BACKGROUND

[0002] A water-cooling system is a cooling method that uses liquid (usually water or coolant containing antifreeze) as a heat transfer medium to dissipate heat. Its core is to remove heat from equipment or systems through liquid flow. This system is commonly used in scenarios that require efficient heat dissipation, such as high-performance CPU cooling in the computer field, temperature control of large industrial equipment, cooling of automobile engines, etc. During operation, the cooling system needs to analyze real-time monitoring data to optimize and control the power scheduling of the water-cooling heat dissipation system in real time, thereby meeting cooling requirements while achieving the lowest energy consumption and cost, prolonging equipment life, and improving system reliability.

[0003] Existing water-cooling heat dissipation systems mainly adjust the radiator power by monitoring the temperature of the area that needs to be cooled to maintain the required temperature level. However, this cooling method may rely too much on temperature sensor feedback for adjustment, but the actual cooling effect may be affected by environmental temperature and air flow around the equipment, which may result in delayed cooling or unnecessary energy consumption of the water-cooling system. SUMMARY

[0004] To solve the above technical problems, the purpose of the present application is to provide an intelligent water-cooling system energy efficiency analysis and optimization scheduling system, and the technical solution adopted is as follows:

[0005] One embodiment of the present application provides an intelligent water-cooling system energy efficiency analysis and optimization scheduling system, which includes a data preprocessing module for collecting load power data, temperature data of the equipment cooling area, and the power of the water-cooling system and aligning to obtain load power sequence, temperature sequence, and water-cooling power sequence;

[0006] A target sequence establishing module is used to uniformly divide the load power sequence, temperature sequence, and water-cooling power sequence to obtain corresponding time intervals; calculate the power-temperature proportion coefficient according to the data in the same time interval in the load power sequence and temperature sequence; and correct each power-temperature proportion coefficient according to the data of each time interval in the water-cooling power sequence and compose a target sequence;

[0007] A heat dissipation environment influence analysis module is used to set the adjustment time; use the extreme points in the target sequence to segment the target sequence to obtain the left side closest to the current adjustment time data segment; calculate the environmental influence degree according to the data in the left side closest to the current adjustment time data segment and the corrected power-temperature proportion coefficient at the current adjustment time;

[0008] a heat dissipation power calculation module, configured to obtain a heat dissipation requirement degree of a next adjustment time of the current adjustment time according to a temperature of the current adjustment time and an environmental influence degree, and obtain a power of the water cooling system of the next adjustment time of the current adjustment time according to the power of the current adjustment time and the heat dissipation requirement degree of the next adjustment time of the current adjustment time.

[0009] Preferably, the load power sequence, the temperature sequence and the water cooling power sequence are obtained by:

[0010] a transfer time delay of the temperature data of the device heat dissipation area is set, and the collected load power data of the device heat dissipation area and the power data of the water cooling system at each time are moved backward by the transfer time delay, to obtain the aligned load power data of the device heat dissipation area, the temperature data and the power of the water cooling system, and form the load power sequence, the temperature sequence and the water cooling power sequence respectively.

[0011] Preferably, the power-temperature proportionality coefficient is calculated according to the data in the same time interval in the load power sequence and the temperature sequence, including:

[0012] the sum of the load power data in each time interval in the load power sequence is calculated, and the sum of the load power data in each time interval is mapped by using an exponential function with a natural constant as a base to obtain a first mapping result corresponding to each time interval; the sum of the temperature data in each time interval in the temperature sequence is calculated, and the sum of the temperature data in each time interval is mapped by using an exponential function with a natural constant as a 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 proportionality coefficient.

[0013] Preferably, the power-temperature proportionality coefficients are corrected according to the data in each time interval in the water cooling power sequence and form a target sequence, including:

[0014] the sum of the power data in each time interval in the water cooling power sequence is calculated, and the sum of the power data in each time interval is mapped by using an exponential function with a natural constant as a base to obtain a third mapping result corresponding to each time interval; the third mapping result corresponding to each time interval is multiplied by the power-temperature proportionality coefficient to obtain a corrected power-temperature proportionality coefficient; the corrected power-temperature proportionality coefficient corresponding to each time interval forms the target sequence in time sequence.

[0015] Preferably, the environmental influence degree is calculated, including:

[0016] taking the reciprocal of the corrected power-temperature proportional coefficient corresponding to the current adjustment time; taking the average of the ratio of each two adjacent data in the leftmost data segment closest to the current adjustment time, to obtain an average value, wherein the ratio of each two adjacent data is the ratio of the data at the previous time to the data at the next time; the product of the reciprocal and the average value is the environmental influence degree at the current adjustment time.

[0017] Preferably, obtaining the heat dissipation requirement degree of the next adjustment time of the current adjustment time according to the temperature of the current adjustment time and the environmental influence degree comprises:

[0018] The product of the temperature of the current adjustment time and the environmental influence degree is the heat dissipation requirement degree of the next adjustment time of the current adjustment time.

[0019] Preferably, obtaining the power of the water cooling system of the next adjustment time of the current adjustment time comprises:

[0020] Taking the ratio of the heat dissipation requirement degree of the next adjustment time of the current adjustment time to the heat dissipation requirement degree of the current adjustment time, and the product of the ratio and the power of the water cooling system at the current adjustment time is the power of the water cooling system of the next adjustment time of the current adjustment time.

[0021] Preferably, before the leftmost data segment closest to the current adjustment time is obtained by segmenting the target sequence using the extreme points in the target sequence, the method further comprises:

[0022] The target sequence is filtered and smoothed by using a Savitzky-Golay filter.

[0023] The embodiment of the present application has at least the following beneficial effects: the present application first collects the load power data, temperature data and the power of the water cooling system of the heat dissipation area of the equipment and aligns them to obtain the load power sequence, temperature sequence and water cooling power sequence, which facilitates subsequent analysis; further, the load power sequence, temperature sequence and water cooling power sequence are comprehensively analyzed to obtain the corrected power-temperature proportional coefficient and form a target sequence, which improves the accuracy and comprehensiveness of the power-temperature proportional coefficient; then the adjustment time is set and the target sequence is segmented and analyzed to calculate the environmental influence degree at the current adjustment time; then further analysis is performed to obtain the heat dissipation requirement degree of the next adjustment time of the current adjustment time, and then the power of the water cooling system of the next adjustment time of the current adjustment time is calculated, and the calculated power is used to adjust the power of the water cooling system at the next adjustment time of the current adjustment time, so that the power of the water cooling system is more accurately and timely adjusted and controlled, and the energy efficiency ratio of the heat dissipation process is improved. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0025] Figure 1 The system block diagram of the intelligent water cooling system energy efficiency analysis and optimization scheduling system provided by the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0026] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific implementation, structure, features and effects of the intelligent water cooling system energy efficiency analysis and optimization scheduling system according to the present application are described in detail as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0028] The specific scheme of the intelligent water cooling system energy efficiency analysis and optimization scheduling system provided by the present application is specifically described below with reference to the drawings.

[0029] Embodiment:

[0030] The main application scenario of the present application is:

[0031] The traditional water cooling heat dissipation method may excessively rely on temperature sensor feedback for adjustment, but in the actual heat dissipation process, the heat dissipation effect may be affected by environmental temperature and air flow around the device, etc., which may cause the water cooling system to dissipate heat not in time or unnecessary energy consumption, etc.

[0032] Please refer to Figure 1 , which shows the system block diagram of the intelligent water cooling system energy efficiency analysis and optimization scheduling system provided by the embodiments of the present application, which includes the following modules:

[0033] The data preprocessing module is used to collect the load power data, temperature data of the device heat dissipation area and the power of the water cooling system, and align to obtain the load power sequence, temperature sequence and water cooling power sequence.

[0034] When equipment is working, some components or modules require water cooling to dissipate heat due to high heat generation. Using air cooling may damage these components, such as the CPU of a computer and the engine of a vehicle. These components that require heat dissipation are referred to as heat dissipation areas, and the water cooling system is connected to these heat dissipation areas.

[0035] This example uses a water-cooling system in a computer device for analysis; the analysis principle for water-cooling systems in other devices is similar. When current passes through a conductor or component in a device, heat is generated due to resistance. This heat is then transferred to the heat sink through thermally conductive materials, and the coolant in the water-cooling system dissipates the heat from the heat sink.

[0036] Furthermore, temperature data of the equipment's heat dissipation area (CPU), load power data of the equipment's heat dissipation area, and power of the water cooling system are collected by temperature sensors and power monitoring software, respectively. The frequency of data collection needs to be set by the implementer according to the actual situation.

[0037] In actual heat dissipation, the temperature of the device is mainly generated when the device is working. There is a certain delay between the temperature being generated and being detected. Here, the temperature transmission time delay is set to t seconds. Preferably, in this embodiment of the invention, the transmission delay is set to 0.5 seconds. Different devices can be set according to the actual heat conduction rate.

[0038] Then, based on the set transmission delay, the collected load power data, temperature data, and water cooling system power of the equipment's heat dissipation area are aligned. The alignment method involves shifting the data value of each moment in the collected load power data of the equipment's heat dissipation area and the power of the water cooling system to the next time step, which becomes the data value at the corresponding moment after the shift. The shift duration (step size) is the transmission delay, which is 0.5 seconds. This aligns the three types of data, resulting in aligned load power data, temperature data, and water cooling system power for the equipment's heat dissipation area, which are then used to form load power sequences, temperature sequences, and water cooling power sequences, respectively.

[0039] The target sequence establishment module is used to uniformly divide the load power sequence, temperature sequence, and water-cooled power sequence into corresponding time intervals; calculate the power-temperature ratio coefficient based on the data in the same time interval of the load power sequence and temperature sequence; and correct the power-temperature ratio coefficient based on the data in each time interval of the water-cooled power sequence to form the target sequence.

[0040] The water cooling system is a kind of heat transfer medium through liquid (usually water or coolant containing antifreeze) to remove the heat generated by the heat dissipation object during the work in time. The traditional water cooling heat dissipation method generally uses temperature sensor to sense the temperature of the heat dissipation area, so as to control the water cooling system to work and dissipate heat. Because the heat in the heat dissipation area is mainly converted into heat energy when the components in the heat dissipation area work, the effect of heat dissipation may be affected by the ambient temperature and air flow, which may cause the heat dissipation not in time or unnecessary energy consumption during the heat dissipation of the water cooling system.

[0041] Because the heat generated by the heat dissipation area when it works is proportional to the change of the detected temperature data under the condition that the heat dissipation area is not affected by the ambient temperature and heat loss. But the flow of air and the ambient temperature in the actual heat dissipation process may change the relationship between the above two. Therefore, in order to more accurately analyze the influence of the environment on the heat dissipation efficiency of the heat dissipation system, the data in the load power sequence and the temperature sequence need to be analyzed.

[0042] Further, the load power sequence, the temperature sequence and the water cooling power sequence are uniformly divided into intervals to obtain corresponding time intervals, and the length of the time interval is 0.5 seconds. The implementer can select the appropriate length according to the actual situation. Then the proportional relationship of the load power data and the temperature data in each time interval is calculated in the load power sequence and the temperature sequence. Specifically, the sum of the load power data in each time interval is calculated in the load power sequence, and the sum of the load power data in each time interval is mapped by using the exponential function with natural constant as the base to obtain the corresponding first mapping result of each time interval. The sum of the temperature data in each time interval is calculated in the temperature sequence, and the sum of the temperature data in each time interval is mapped by using the exponential function with natural constant as the base to obtain the corresponding second mapping result of 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.

[0043] The calculation formula of the power temperature proportionality coefficient of each time interval is specifically:

[0044] ,

[0045] Wherein, The power temperature proportionality coefficient corresponding to the a th time interval is represented; e represents the natural constant; The s th load power data in the a th time interval in the load power sequence is represented; The s th temperature data in the a th time interval in the temperature sequence is represented; The number of data in the a th time interval is represented. a cumulative sum of load power data in the a-th time interval, a first mapping result corresponding to the a-th time interval, a cumulative sum of temperature data in the a-th time interval, a third mapping result corresponding to the a-th time interval. The cumulative sum is mapped with the natural constant e 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 the temperature data of the heating area in a time interval.

[0046] Thus, the proportional relationship between the load power data and the temperature data of any time interval, i.e., the power-temperature proportionality coefficient, is obtained. In actual monitoring, the water cooling system may also work to dissipate heat. Therefore, in order to remove the heat dissipation of the water cooling system and thus change the above-mentioned coefficient, and further improve the accuracy of the analysis of environmental impact factors, the power size of the water cooling system is combined to further correct the above-mentioned proportionality coefficient.

[0047] Specifically, the sum of the power data in each time interval in the water cooling power sequence is calculated, the sum of the power data in each time interval is mapped with an exponential function with a natural constant as the base to obtain a third mapping result corresponding to each time interval; and the third mapping result corresponding to each time interval is multiplied by the power-temperature proportionality coefficient to obtain a corrected power-temperature proportionality coefficient. The specific calculation formula is:

[0048]

[0049] wherein, the a-th time interval corrected power-temperature proportionality coefficient; the a-th time interval corresponding power-temperature proportionality coefficient before correction; the s-th power data in the a-th time interval in the water cooling power sequence; the sum of the power data in the a-th time interval, the third mapping result corresponding to the a-th time interval, as a correction coefficient of the proportional relationship between the load power data and the temperature data in the a-th interval.

[0050] Thus, the corrected power-temperature proportionality coefficient corresponding to each time interval can be obtained. The corrected power-temperature proportionality coefficient corresponding to each time interval constitutes a target sequence in chronological order, wherein the time stamp of each data in the target sequence is the last time node in the time interval corresponding to each data. Therefore, the time stamp of each data in the target sequence also corresponds to a time.

[0051] ​The heat dissipation environment influence analysis module is configured to set an adjustment time, segment the target sequence using extreme points in the target sequence to obtain a left data segment closest to the current adjustment time, and calculate the environment influence degree according to data in the left data segment closest to the current adjustment time and the power-temperature proportional coefficient after the current adjustment time is corrected.

[0052] Through the above analysis, the target sequence is obtained. 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 flowability is poor, the target sequence may show a downward trend. At this time, it is indicated that the heat dissipation area is affected by the external environment temperature, resulting in poor heat dissipation effect. Therefore, it is necessary to further improve the heat dissipation power of the water cooling system to achieve effective heat dissipation. Conversely, it is indicated that the heat dissipation effect is good at this time. The water cooling system can be assisted by the environment for heat dissipation, and the heat dissipation power can be appropriately reduced to avoid unnecessary energy consumption due to excessive heat dissipation. At the same time, the adjustment time of the water cooling system is set. In the present application, the adjustment is performed once every 0.5 seconds, which is recorded as the adjustment time. The implementer can adjust the adjustment time according to the actual situation, for example, the adjustment can be performed once every 1 second.

[0053] Therefore, in order to obtain the change trend and relationship in the target sequence corresponding to the current adjustment time, it is necessary to use the Savitzky-Golay filter on the target sequence to filter and smooth the target sequence, so as to better analyze the trend change of the target sequence. The Savitzky-Golay filter is a mathematical algorithm for data smoothing. The signal is smoothed by polynomial fitting, while the characteristics of the data (such as peak value and waveform) are maintained as much as possible.

[0054] Further, the extreme points in the processed target sequence are obtained according to the points where the first derivative is 0 and the second derivative is not 0. The extreme points are used as the dividing points to segment the target sequence, and the left data segment closest to the current adjustment time is obtained. The time corresponding to the last data in the left data segment closest to the current adjustment time is the current adjustment time. Then, the environment influence degree of the current adjustment time is obtained by analyzing the left data segment closest to the current adjustment time. Thus, the influence factors of the heat dissipation area of the device on the heat dissipation process at the latest time are understood, so as to adjust the heat dissipation strategy of the water cooling system in the subsequent process.

[0055] The data segment on the left closest to the current adjustment time is defined as the timestamp of the last data point in the target sequence within that segment. An adjustment time within its corresponding left-closest data segment is not necessarily the first time point; it can only be the last time point or any time point between the first and last time points.

[0056] Specifically, the reciprocal of the corrected power-temperature proportionality coefficient corresponding to the current adjustment time is obtained; the ratio of every two adjacent data points in the data segment closest to the current adjustment time on the left is averaged to obtain the average value, where the ratio of every two adjacent data points is the ratio of the data at the previous time point to the data at the next time point; the product of the reciprocal and the average value is the degree of environmental impact at the current adjustment time.

[0057] The specific formula for calculating the degree of environmental impact at the current adjustment time is as follows:

[0058] ,

[0059] Where K represents the degree of environmental influence at the current adjustment moment; This represents the power-temperature proportional gain after correction at the current adjustment time; g represents the number of data points in the data segment on the left closest to the current adjustment time. This represents the corrected power-temperature scaling factor corresponding to the r-th time in the data segment on the left that is closest to the current adjustment time. The corrected power-temperature scaling factor is shown for the (r+1)th time in the data segment closest to the current adjustment time on the left. The smaller the value, the better. A higher value indicates that the current heat dissipation is affected by the external environment, resulting in poorer heat dissipation efficiency. This represents the ratio of the r-th data point to the (r+1)-th data point in the data segment closest to the current adjustment time on the left. The larger this value, the more obvious the downward trend between the two data points. Averaging this value can indicate whether the overall downward trend of the data segment closest to the current adjustment time on the left is obvious. If the overall downward trend is obvious, it indicates that the current heat dissipation area may be affected by external environmental interference, resulting in a worse heat dissipation effect.

[0060] Therefore, the above results show the degree of influence of the external environment at the current adjustment time. The greater the degree of environmental influence, the more likely it is that additional heat dissipation power may be needed to cool the equipment. Conversely, the power of the heat dissipation system can be reduced to save energy.

[0061] The heat dissipation power calculation module is configured to obtain the heat dissipation demand degree of the next adjustment time of the current adjustment time according to the temperature of the current adjustment time and the environmental influence degree of the current adjustment time; and obtain the power of the water cooling system of the next adjustment time of the current adjustment time according to the heat dissipation demand degree of the current time and the next adjustment time of the current adjustment time, the heat dissipation demand degree of the next adjustment time of the current adjustment time, and the power of the water cooling system of the current adjustment time.

[0062] Further, the heat dissipation demand degree of the next adjustment time of the current adjustment time is calculated according to the calculated environmental influence degree of the current adjustment time and the temperature of the current adjustment time, and the product of the temperature of the current adjustment time and the environmental influence degree of the current adjustment time is the heat dissipation demand degree of the next adjustment time of the current adjustment time.

[0063] The specific calculation formula is:

[0064] ,

[0065] wherein, represents the heat dissipation demand degree of the next adjustment time of the current adjustment time; represents the temperature of the current adjustment time; and K represents the environmental influence degree of the current adjustment time. The greater the temperature of the current adjustment time, the higher the temperature at this time, and the greater the power required for the water cooling heat dissipation system to work at the next time. The greater the environmental influence degree, the worse the environmental influence on the heat dissipation effect, and the greater the power of the heat dissipation system.

[0066] Then, the power of the water cooling system of the next adjustment time of the current adjustment time is obtained according to the heat dissipation demand degree of the next adjustment time of the current adjustment time, the heat dissipation demand degree of the current adjustment time, and the power of the water cooling system of the current adjustment time. Specifically, the ratio of the heat dissipation demand degree of the next adjustment time of the current adjustment time to the heat dissipation demand degree of the current adjustment time is obtained, and the product of the ratio and the power of the water cooling system of the current adjustment time is the power of the water cooling system of the next adjustment time of the current adjustment time. The specific calculation formula is:

[0067] ,

[0068] wherein, represents the power of the water cooling system of the next adjustment time of the current adjustment time; represents the power of the water cooling system of the current adjustment time; represents the heat dissipation demand degree of the next adjustment time of the current adjustment time; represents the heat dissipation demand degree of the current adjustment time. The heat dissipation demand degree of the current adjustment time is obtained in the same way as the heat dissipation demand degree of the next adjustment time of the current adjustment time, and the temperature and the environmental influence degree of the last adjustment time of the current adjustment time are used for calculation.

[0069] The ratio of the heat dissipation demand degree value of the water-cooled heat dissipation system at the next adjustment moment to the heat dissipation demand degree value of the water-cooled heat dissipation system at the current adjustment moment, the greater the value, the higher the heat dissipation demand degree of the water-cooled heat dissipation system at the next adjustment moment, and the greater the heat dissipation power, so as to improve the heat dissipation effect, and vice versa, the smaller the heat dissipation demand at the next adjustment moment, the smaller the heat dissipation power of the water-cooled heat dissipation system, so as to avoid the waste of energy consumption caused by high-power excessive heat dissipation.

[0070] The output power prediction value of the water-cooled heat dissipation system at the next adjustment moment of the current adjustment moment of the device can be obtained through the above. After obtaining the prediction value, the predicted heat dissipation power is output at the next moment by using the control system of the water-cooled heat dissipation system in the device, so as to achieve the purpose of adjusting the cooling liquid flow rate and the 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 heat dissipation.

[0071] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes a specific embodiment of the present application. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or may be advantageous.

[0072] Each embodiment in the present application is described in a progressive manner, and the same and similar parts between each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments.

[0073] The above only describes the preferred embodiments of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An intelligent water cooling system energy efficiency analysis and optimal scheduling system, characterized in that, The system comprises: a data preprocessing module for collecting load power data, temperature data of a device heat dissipation area and power of a water cooling system and aligning to obtain a load power sequence, a temperature sequence and a water cooling power sequence; a target sequence establishing module for dividing each of the load power sequence, the temperature sequence and the water cooling power sequence into uniform intervals to obtain corresponding time intervals, calculating a power-temperature proportionality coefficient according to data in the same time interval in the load power sequence and the temperature sequence, and correcting each power-temperature proportionality coefficient according to data of each time interval in the water cooling power sequence and composing a target sequence; a heat dissipation environment influence analysis module for setting an adjustment time; segmenting the target sequence by using extreme points in the target sequence to obtain a left data segment closest to the current adjustment time; calculating an environment influence degree according to data in the left data segment closest to the current adjustment time and the corrected power-temperature proportionality coefficient at the current adjustment time, including: taking an inverse of the corrected power-temperature proportionality coefficient corresponding to the current adjustment time; averaging a ratio of each two adjacent data in the left data segment closest to the current adjustment time to obtain an average value, wherein the ratio of each two adjacent data is a ratio of data at a previous time to data at a next time; and multiplying the inverse and the average value to obtain the environment influence degree at the current adjustment time; a heat dissipation power calculation module for obtaining a heat dissipation requirement degree at a next adjustment time of the current adjustment time according to a temperature at the current adjustment time and the environment influence degree, including: multiplying the temperature at the current adjustment time and the environment influence degree to obtain the heat dissipation requirement degree at the next adjustment time of the current adjustment time; and obtaining a power of the water cooling system at the next adjustment time of the current adjustment time according to the heat dissipation requirement degree at the next adjustment time of the current adjustment time, a current time, a power of the water cooling system at the current adjustment time. 2.The intelligent water cooling system energy efficiency analysis and optimal scheduling system of claim 1, wherein, The obtaining of the load power sequence, the temperature sequence and the water cooling power sequence comprises: setting a transmission time delay of the temperature data of the device heat dissipation area; moving each time data value in the collected load power data of the device heat dissipation area and the power of the water cooling system backward by the transmission time delay to obtain the aligned load power data of the device heat dissipation area, the temperature data and the power of the water cooling system, and respectively composing the load power sequence, the temperature sequence and the water cooling power sequence. 3.The intelligent water cooling system energy efficiency analysis and optimal scheduling system of claim 1, wherein, The calculating of the power-temperature proportionality coefficient according to the data in the same time interval in the load power sequence and the temperature sequence comprises: calculating a sum of the load power data in each time interval in the load power sequence, mapping the sum of the load power data in each time interval by using an exponential function with a natural constant as a base to obtain a first mapping result corresponding to each time interval; calculating a sum of the temperature data in each time interval in the temperature sequence, mapping the sum of the temperature data in each time interval by using the exponential function with the natural constant as the base to obtain a second mapping result corresponding to each time interval; and taking a ratio of the first mapping result and the second mapping result corresponding to the same time interval as the power-temperature proportionality coefficient. 4.The intelligent water cooling system energy efficiency analysis and optimal scheduling system of claim 1, wherein, The power temperature proportional coefficient is corrected according to the data of each time interval in the water cooling power sequence, and a target sequence is formed, comprising: The sum of power data is calculated in each time interval in the water cooling power sequence, and the sum of power data in each time interval is mapped by using an exponential function with a natural constant as a base to obtain a third mapping result corresponding to each time interval; the third mapping result corresponding to each time interval is multiplied by the power temperature proportional coefficient to obtain a corrected power temperature proportional coefficient; the corrected power temperature proportional coefficient corresponding to each time interval is arranged in time sequence to form a target sequence.

5. The intelligent water cooling system energy efficiency analysis and optimal scheduling system according to claim 1, characterized in that, The power of the water cooling system at the next adjustment time of the current adjustment time is obtained, comprising: The ratio of the heat dissipation demand degree at the next adjustment time of the current adjustment time to the heat dissipation demand degree at the current adjustment time is obtained, and the product of the ratio and the power of the water cooling system at the current adjustment time is the power of the water cooling system at the next adjustment time of the current adjustment time. 6.The intelligent water cooling system energy efficiency analysis and optimal scheduling system of claim 1, wherein, Before the target sequence is segmented to obtain a data segment closest to the current adjustment time on the left side by using an extreme point in the target sequence, it further comprises: The target sequence is filtered and smoothed by using a Savitzky-Golay filter.

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