Filter window decision method and energy consumption data acquisition method, device and equipment

Abstract

The present invention provides a method for deciding a filter window and a method, device and equipment for obtaining energy consumption data. The decision-making method includes: setting multiple groups of control parameters including setting temperature and startup number and multiple alternative filter windows with different window widths; using one group of control parameters to control multiple temperature control devices to run for a control cycle; within the control cycle, each time an observation cycle is reached, collecting energy consumption data of multiple temperature control devices; taking the end time of the control cycle as the end time of the alternative filter window, obtaining the energy consumption data collected in each alternative filter window and filtering it; determining a first comparison result expected by comparing energy consumption data corresponding to different groups of control parameters; comparing energy consumption data corresponding to different groups of control parameters when using each alternative filter window to obtain a second comparison result; comparing the two comparison results corresponding to each alternative filter window for consistency, and deciding to use the alternative filter window corresponding to the second comparison result with the highest consistency.

Description

Technical Field

[0001] The present invention relates to the field of automation technology, and in particular to a filter window decision method and an energy consumption data acquisition method, device and equipment. Background Art

[0002] With the rapid development of big data and the ever-increasing amount of data processed, data centers are rapidly proliferating. Data centers typically consist of servers, equipment serving data center personnel (such as lighting and elevators), and cooling equipment for dissipating heat throughout the data center. Because servers generate significant heat during operation, cooling equipment consumes significant energy. To reduce cooling equipment energy consumption, precise control of its operating status is necessary to improve power usage effectiveness (PUE).

[0003] For air conditioning clusters, current research on group control focuses on two main areas: whole-unit group control and device-level group control. Whole-unit group control continues to be effective due to its low data communication requirements, high security, and wide applicability.

[0004] When controlling a group of air conditioners, a shorter observation cycle and a longer control cycle are typically used. The observation cycle is used to monitor and control the data center's environmental status, ensuring data center safety. The control cycle is used to adjust the number of active units and set temperatures in the air conditioner group to improve PUE.

[0005] In air conditioner group control, obtaining data such as PUE, measured temperature, and IT power after data center stability for each combination of running number and set temperature is highly valuable. Currently, variable-frequency air conditioners (VFAs), primarily used for data center cooling, primarily use the proportional-integral-differential (PID) control algorithm to control their operating state. This VFA's control effect is cumulative and gradual. That is, after selecting and using a specific running number and set temperature configuration, the data center does not immediately reach a stable state under the new configuration. Instead, the error gradually decreases, gradually approaching stability. The PID control algorithm ultimately results in VFA operating parameters oscillating around the desired values, causing transient energy consumption data to oscillate around the desired steady-state energy consumption data, resulting in noise. Furthermore, multiple VFAs can interact, increasing noise. Therefore, obtaining relatively accurate steady-state energy consumption data during VFA operation is crucial for VFA control. Summary of the Invention

[0006] The embodiments of the present invention provide a filter window decision method and an energy consumption data acquisition method, device, and apparatus, so as to solve the problem of acquiring relatively accurate steady-state energy consumption data of a variable-frequency air conditioner.

[0007] An embodiment of the present invention provides a method for determining a filter window for obtaining energy consumption data, the method comprising:

[0008] Setting multiple groups of control parameters and multiple alternative filter windows, wherein each group of control parameters includes setting temperature and number of startups, and the window widths of the multiple alternative filter windows are different;

[0009] Use a set of control parameters to control the duration of a control cycle for multiple temperature control devices;

[0010] During the control period, each time an observation period is reached, energy consumption data of the plurality of temperature control devices is collected;

[0011] Taking the end time of the control cycle as the end time of the candidate filter window, obtaining the energy consumption data collected in each candidate filter window;

[0012] Filter the energy consumption data collected in each alternative filtering window respectively;

[0013] Determining a first comparison result expected from comparing energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters;

[0014] Comparing energy consumption data of the plurality of temperature control devices under different control parameter groups when using the various alternative filter windows to obtain a second comparison result;

[0015] The second comparison results corresponding to each candidate filtering window are compared for consistency with the first comparison results, and the candidate filtering window corresponding to the second comparison result with the highest consistency is determined as the filtering window.

[0016] Optionally, filtering is performed on the energy consumption data collected in each candidate filtering window, including:

[0017] Perform mean filtering on the energy consumption data collected in each alternative filtering window;

[0018] Alternatively, median filtering is performed on the energy consumption data collected in each candidate filtering window.

[0019] Optionally, determining the candidate filtering window corresponding to the second comparison result with the highest consistency as the filtering window includes:

[0020] If there are multiple candidate filter windows with the highest consistency, the candidate filter window with the largest window width is selected as the filter window.

[0021] Optionally, the energy consumption data is power usage efficiency PUE or electric power.

[0022] Optionally, determining to compare energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters, the first comparison result expected to be obtained includes:

[0023] When it is determined that the power-on number s of the temperature control devices is the same, the energy consumption data corresponding to the set temperature T+|ΔT| is lower than the energy consumption data corresponding to the set temperature T;

[0024] Wherein, ΔT is the minimum change of the set temperature; s is a positive integer.

[0025] Optionally, determining to compare energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters, the first comparison result expected to be obtained includes:

[0026] When the same number of startups of the temperature control devices is traversed, the energy consumption data collected in each of the alternative filter windows at each set temperature are averaged;

[0027] Compare the average energy consumption data corresponding to different numbers of startups to determine whether the energy consumption data corresponding to the startup number s is higher or lower than the energy consumption data of the startup number s+1 when the set temperature is the same;

[0028] Where s is a positive integer.

[0029] Optionally, performing consistency comparison between the second comparison result corresponding to each candidate filtering window and the first comparison result includes:

[0030] Determine, among the multiple groups of control parameters, multiple first groups of control parameters having the same start-up number s and a set temperature difference of |ΔT|, and combine every two groups of the multiple first groups of control parameters to obtain multiple first combinations;

[0031] Determine, among the multiple groups of control parameters, multiple second groups of control parameters having the same temperature T and a power-on number s that differs by 1, and combine every two of the multiple second groups of control parameters to obtain multiple second combinations;

[0032] Setting a consistency statistic value, and setting an initial value of the consistency statistic value to zero;

[0033] Energy consumption data of a plurality of temperature control devices controlled by different groups of control parameters obtained within the same candidate filtering window are acquired and analyzed sequentially: whenever a second comparison result of the energy consumption data obtained by using a first combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1; whenever a second comparison result of the energy consumption data obtained by using a second combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1;

[0034] Compare the consistency statistics corresponding to each candidate filtering window with the total statistical value to obtain the consistency corresponding to each candidate filtering window, wherein the total statistical value is the total number of the first combination and the second combination corresponding to one candidate filtering window.

[0035] Based on the same inventive concept, an embodiment of the present invention further provides a method for obtaining energy consumption data, including:

[0036] Using the filter window decision method for obtaining energy consumption data, a filter window to be used is decided from a plurality of candidate filter windows;

[0037] In each control cycle, the end time of the control cycle is used as the end time of the filter window, and the energy consumption data collected in the filter window is obtained;

[0038] The energy consumption data collected within the filtering window is subjected to mean filtering to obtain energy consumption data.

[0039] Based on the same inventive concept, an embodiment of the present invention further provides a filter window decision device for obtaining energy consumption data, comprising:

[0040] A test data setting module is used to set multiple groups of control parameters and multiple alternative filter windows, wherein each group of control parameters includes setting temperature and number of startups, and the window widths of the multiple alternative filter windows are different;

[0041] A test operation module is used to control multiple temperature control devices to run a control cycle using a set of control parameters;

[0042] A data acquisition module, configured to collect energy consumption data of the plurality of temperature control devices once each observation period is reached within the control period;

[0043] A data acquisition module, configured to take the end time of the control cycle as the end time of the candidate filter window and acquire the energy consumption data collected in each candidate filter window;

[0044] A filtering module is used to filter the energy consumption data collected in each candidate filtering window respectively;

[0045] A first comparison result determination module is used to determine a first comparison result expected to be obtained by comparing energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters;

[0046] A second comparison result determination module is used to compare the energy consumption data of the plurality of temperature control devices when different groups of control parameters are used to control the operation of the plurality of temperature control devices when the candidate filter windows are adopted, to obtain a second comparison result;

[0047] The decision module is configured to compare the second comparison results corresponding to each candidate filtering window with the first comparison result for consistency, and decide the candidate filtering window corresponding to the second comparison result with the highest consistency as the filtering window.

[0048] Optionally, filtering is performed on the energy consumption data collected in each candidate filtering window, including:

[0049] Perform mean filtering on the energy consumption data collected in each alternative filtering window;

[0050] Alternatively, median filtering is performed on the energy consumption data collected in each candidate filtering window.

[0051] Optionally, determining the candidate filtering window corresponding to the second comparison result with the highest consistency as the filtering window includes:

[0052] If there are multiple candidate filter windows with the highest consistency, the candidate filter window with the largest window width is selected as the filter window.

[0053] Optionally, the energy consumption data is power usage efficiency PUE or electric power.

[0054] Optionally, determining to compare energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters, the first comparison result expected to be obtained includes:

[0055] When it is determined that the power-on number s of the temperature control devices is the same, the energy consumption data corresponding to the set temperature T+|ΔT| is lower than the energy consumption data corresponding to the set temperature T;

[0056] Wherein, ΔT is the minimum change of the set temperature; s is a positive integer.

[0057] Optionally, determining to compare energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters, the first comparison result expected to be obtained includes:

[0058] When the same number of startups of the temperature control devices is traversed, the energy consumption data collected in each of the alternative filter windows at each set temperature are averaged;

[0059] Compare the average energy consumption data corresponding to different numbers of startups to determine whether the energy consumption data corresponding to the startup number s is higher or lower than the energy consumption data of the startup number s+1 when the set temperature is the same;

[0060] Where s is a positive integer.

[0061] Optionally, performing consistency comparison between the second comparison result corresponding to each candidate filtering window and the first comparison result includes:

[0062] Determine, among the multiple groups of control parameters, multiple first groups of control parameters having the same start-up number s and a set temperature difference of |ΔT|, and combine every two groups of the multiple first groups of control parameters to obtain multiple first combinations;

[0063] Determine, among the multiple groups of control parameters, multiple second groups of control parameters having the same temperature T and a power-on number s that differs by 1, and combine every two of the multiple second groups of control parameters to obtain multiple second combinations;

[0064] Setting a consistency statistic value, and setting an initial value of the consistency statistic value to zero;

[0065] Energy consumption data of a plurality of temperature control devices controlled by different groups of control parameters obtained within the same candidate filtering window are acquired and analyzed sequentially: whenever a second comparison result of the energy consumption data obtained by using a first combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1; whenever a second comparison result of the energy consumption data obtained by using a second combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1;

[0066] Compare the consistency statistics corresponding to each candidate filtering window with the total statistical value to obtain the consistency corresponding to each candidate filtering window, wherein the total statistical value is the total number of the first combination and the second combination corresponding to one candidate filtering window.

[0067] Based on the same inventive concept, an embodiment of the present invention further provides a device for obtaining energy consumption data, comprising:

[0068] A filter window determination module, configured to determine the filter window using the filter window decision method for obtaining energy consumption data;

[0069] A data acquisition module is used to acquire energy consumption data collected within each control period, taking the end time of the control period as the end time of the filter window;

[0070] The energy consumption data acquisition module is used to perform mean filtering on the energy consumption data collected in the filtering window to obtain energy consumption data.

[0071] Based on the same inventive concept, an embodiment of the present invention further provides an electronic device, comprising: a processor and a memory for storing instructions executable by the processor;

[0072] The processor is configured to execute the instructions to implement the filtering window decision method for obtaining energy consumption data and / or the method for obtaining energy consumption data.

[0073] Based on the same inventive concept, an embodiment of the present invention also provides a computer storage medium, which stores a computer program, and the computer program is used to implement the filtering window decision method for obtaining energy consumption data, and / or implement the method for obtaining energy consumption data.

[0074] The beneficial effects of the present invention are as follows:

[0075] The filter window decision method and energy consumption data acquisition method, device and equipment provided by the embodiment of the present invention compare the energy consumption data of multiple temperature control devices controlled by different groups of control parameters when using various alternative filter windows in the decision process to obtain a second comparison result, match it with the expected first comparison result, select the filter window with the highest matching rate, use the selected filter window for filtering during actual operation, and set the filter window width of a given denoising method offline; when the temperature control device is actually running, the control parameters change (for example, the control parameters are different from the control parameters used in the decision process), the energy consumption data obtained by filtering using the filter window obtained by the decision is still accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 Flowchart of a filter window decision method for obtaining energy consumption data in an embodiment of the present invention;

[0077] Figure 2 Schematic diagram of energy consumption data obtained in an embodiment of the present invention;

[0078] Figure 3 Schematic diagram of the filter window provided in an embodiment of the present invention;

[0079] Figure 4 Flowchart of a method for obtaining energy consumption data in an embodiment of the present invention;

[0080] Figure 5 A schematic diagram of the structure of a filter window decision device for obtaining energy consumption data in an embodiment of the present invention;

[0081] Figure 6 A schematic diagram of the structure of a device for acquiring energy consumption data in an embodiment of the present invention;

[0082] Figure 7 Schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0083] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention will be further described below with reference to the accompanying drawings and examples. However, the example embodiments can be implemented in various forms and should not be understood as being limited to the embodiments described herein; on the contrary, these embodiments are provided to make the present invention more comprehensive and complete, and to fully convey the concepts of the example embodiments to those skilled in the art. The same figure marks in the figures represent the same or similar structures, and their repeated descriptions will be omitted. The words expressing position and direction described in the present invention are all explained with reference to the accompanying drawings as examples, but changes can be made as needed, and the changes made are all included in the scope of protection of the present invention. The drawings of the present invention are only used to illustrate the relative position relationship and do not represent the true proportion.

[0084] It should be noted that specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can be implemented in a variety of ways different from those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below. The subsequent description of the specification is a preferred embodiment of the present application, but the description is for the purpose of illustrating the general principles of the present application and is not intended to limit the scope of the present application. The scope of protection of the present application shall be determined as defined by the appended claims.

[0085] The following describes in detail the filter window decision method and energy consumption data acquisition method, device, and equipment provided by the embodiments of the present invention in conjunction with the accompanying drawings.

[0086] The embodiment of the present invention provides a filter window decision method for obtaining energy consumption data, such as Figure 1 As shown, including:

[0087] S101, setting multiple groups of control parameters and multiple candidate filter windows, wherein each group of control parameters includes a set temperature and a start-up number, and the multiple candidate filter windows have different window widths;

[0088] S102, using a set of control parameters to control multiple temperature control devices to run for a control cycle;

[0089] S103, collecting energy consumption data of the plurality of temperature control devices once every observation period within the control period;

[0090] S104, taking the end time of the control cycle as the end time of the candidate filter window, and acquiring the energy consumption data collected in each candidate filter window;

[0091] S105, filtering the energy consumption data collected in each candidate filtering window respectively;

[0092] S106, determining whether all control parameter tests are completed; if yes, executing step S107; if no, executing step S102;

[0093] S107, determining a first comparison result expected to be obtained by comparing energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters;

[0094] S108, comparing energy consumption data of the plurality of temperature control devices when operating under different control parameter groups using the various alternative filter windows to obtain a second comparison result;

[0095] S109: Perform consistency comparison between the second comparison results corresponding to each candidate filtering window and the first comparison result, and decide the candidate filtering window corresponding to the second comparison result with the highest consistency as the filtering window.

[0096] The control cycle in the present invention refers to a cycle for adjusting control parameters of the temperature control device. The observation cycle in the present invention refers to a cycle for collecting data from the temperature control device. One control cycle includes multiple observation cycles.

[0097] In the specific implementation process, the order of the control parameters in step S102 can be used to control the temperature control device in sequence according to the order of the set control parameters, or a group of control parameters can be randomly selected from the unused control parameters to control the temperature control device until all the control parameters have been used. There is no limitation here.

[0098] In a specific implementation process, the window width of the candidate filter window can be determined based on the number of observation cycles N0 in the control cycle to determine the window width N of multiple different candidate filter windows. Figure 3 As shown, one control cycle is 1 hour, one observation cycle is 5 minutes, and one control cycle includes 12 observation cycles. Then the window width N of the alternative filter window can be an integer from 1 to 12. For example, three integers 2, 4, and 6 are selected as the window widths N of the three alternative filter windows respectively.

[0099] Specifically, take the temperature control device as a variable frequency air conditioner, and the variable frequency air conditioner is used to dissipate heat for a data center as an example. At the beginning of the control cycle shown in the diagram, the ambient temperature of the data center is 30°C, and the set temperature is 25°C. After the variable frequency air conditioner has been running for a certain period of time through a control algorithm (for example, a PID algorithm), the temperature of the data center will fluctuate around 25°C, and accordingly, the energy consumption data of the variable frequency air conditioner will also fluctuate around a specific value. During the control cycle, the energy consumption data of the variable frequency air conditioner is collected once each time an observation cycle is reached, and the collected energy consumption data is Figure 2 As shown in .

[0100] During the specific implementation process, in step S104, the energy consumption data collected within each alternative filter window is obtained. It is possible to obtain only the energy consumption data collected within each alternative filter window, or directly obtain the energy consumption data collected in all observation periods within each control period, including the energy consumption data collected within each filter window. Since the energy consumption data outside each filter window will be removed when the alternative filter window is used to filter the collected energy consumption data, the two acquisition methods have no effect on the final result. Each time an observation period is reached, after collecting the energy consumption data of the multiple temperature control devices, safety inspections and safety adjustments can be performed on the multiple temperature control devices based on the energy consumption data to avoid safety hazards such as overheating of the equipment.

[0101] In this way, the filter window width of a given denoising method can be set offline through the above method. When the temperature control device is actually operating and the control parameters change (for example, the control parameters are different from the control parameters used in the decision-making process), the energy consumption data obtained by filtering using the filter window determined by the decision still has accuracy and reliability.

[0102] Optionally, the step S105 of filtering the energy consumption data collected in each candidate filtering window may be implemented in any of the following ways:

[0103] (1) The energy consumption data collected in each alternative filter window are respectively subjected to mean filtering.

[0104] (2) Perform median filtering on the energy consumption data collected in each alternative filtering window.

[0105] Optionally, in step S109, deciding the candidate filtering window corresponding to the second comparison result with the highest consistency as the filtering window includes:

[0106] If there are multiple candidate filter windows with the highest consistency, the candidate filter window with the largest window width is selected as the filter window.

[0107] In this way, by determining the candidate filtering window with the largest window width and the highest consistency as the filtering window, more accurate energy consumption data can be obtained when the collected energy consumption data is subsequently filtered using the filtering window.

[0108] Optionally, the energy consumption data is PUE or electric power.

[0109] Optionally, determining to compare energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters, the first comparison result expected to be obtained includes:

[0110] When it is determined that the power-on number s of the temperature control device is the same, the energy consumption data corresponding to the set temperature T+|ΔT| is lower than the energy consumption data corresponding to the set temperature T; wherein ΔT is the minimum change of the set temperature; and s is a positive integer.

[0111] During the specific implementation process, the temperature control device is used to maintain the temperature of the control area (for example, a data center computer room) at the set temperature. Generally, the set temperature will be lower than the uncontrolled temperature when the temperature control device is not used in the control area. Then, when the number of times the temperature control device is turned on is certain, when the set temperature is lower, the greater the temperature difference between the set temperature and the uncontrolled temperature, the more energy the temperature control device consumes, and the greater the PUE or electric power. For example, when the number of times the temperature control device is turned on is the same, the PUE / electric power corresponding to the set temperature of 20°C is lower than the PUE / electric power corresponding to the set temperature of 19°C.

[0112] Optionally, determining to compare energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters, and expecting to obtain a first comparison result further includes:

[0113] When the same number of startups of the temperature control devices is traversed, the energy consumption data collected in each of the alternative filter windows at each set temperature are averaged.

[0114] Compare the average values ​​of energy consumption data corresponding to different numbers of startups to determine whether the energy consumption data corresponding to the number of startups s is higher or lower than the energy consumption data of the number of startups s+1 when the set temperature is the same.

[0115] For example, if the set temperatures are set to 18°C, 19°C, 20°C, and 21°C, the number of startups is 5, 6, and 7, and the window width N of the alternative filter window is 3, 6, and 9, then there are 12 groups of control parameters, and 36 energy consumption data are finally obtained. The average value of the energy consumption data of all 12 energy consumption data under each startup number is calculated respectively to obtain the average value of the energy consumption data for 3 different startup numbers. According to the 3 average values ​​of the energy consumption data, the expected first comparison result between the startup number and the energy consumption data can be determined. For example, the more startup numbers, the higher the energy consumption data, that is, the energy consumption data corresponding to the startup number s+1 is higher than the energy consumption data corresponding to the startup number s. Or the more startup numbers, the lower the energy consumption data, that is, the energy consumption data corresponding to the startup number s+1 is lower than the energy consumption data corresponding to the startup number s.

[0116] In this way, by comparing the second comparison results corresponding to each candidate filtering window with the first comparison result for consistency, the candidate filtering window corresponding to the second comparison result with the highest consistency is decided as the filtering window, so as to obtain the filtering window closest to the ideal filtering window.

[0117] Optionally, in step S109, performing consistency comparison between the second comparison result corresponding to each candidate filtering window and the first comparison result includes:

[0118] Determine, among the multiple groups of control parameters, multiple first groups of control parameters having the same start-up number s and a set temperature difference of |ΔT|, and combine every two groups of the multiple first groups of control parameters to obtain multiple first combinations;

[0119] Determine, among the multiple groups of control parameters, multiple second groups of control parameters having the same temperature T and a power-on number s that differs by 1, and combine every two of the multiple second groups of control parameters to obtain multiple second combinations;

[0120] Setting a consistency statistic value, and setting an initial value of the consistency statistic value to zero;

[0121] Energy consumption data of a plurality of temperature control devices controlled by different groups of control parameters obtained within the same candidate filtering window is obtained and analyzed sequentially: whenever the second comparison result of the energy consumption data obtained by using the first combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1; whenever the second comparison result of the energy consumption data obtained by using the second combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1;

[0122] Compare the consistency statistics corresponding to each candidate filtering window with the total statistical value to obtain the consistency corresponding to each candidate filtering window, wherein the total statistical value is the total number of the first combination and the second combination corresponding to one candidate filtering window.

[0123] In a specific implementation, statistical tables such as those shown in Tables 1 and 2 can be established to implement the above steps. In Table 2, combinations where the second comparison result of the first and second combinations is identical to the first comparison result are marked as 1, and combinations where the comparison result does not match are marked as 0. m, x, and y are positive integers.

[0124] Table 1 Energy consumption data collected in each alternative filter window obtained by the temperature control device

[0125]

[0126] Table 2 Consistency statistics

[0127]

[0128] For example, the energy consumption data collected in each candidate filter window obtained by the temperature control device is shown in Table 3 below:

[0129] Table 3 Energy consumption data collected in each alternative filter window obtained by the temperature control device

[0130]

[0131]

[0132] In this example, the minimum change in the set temperature is ΔT=±1°C.

[0133] Then, according to Table 1, the first comparison result when the number of startups s is the same is first determined: when the number of startups s is the same, the PUE when the temperature is set to T+1°C is less than the PUE when the temperature is set to T°C.

[0134] Then, the average energy consumption data of all set temperatures (18°C, 19°C, 20°C) and all filter windows (2, 4, 6) when the number of startups is 2 is calculated as follows:

[0135] (1.2882+1.2972+1.2984+1.2527+1.2443+1.2414+1.2399+1.2414+1.2481) / 9≈1.2613

[0136] The average energy consumption data of all set temperatures (18°C, 19°C, 20°C) and all filter windows (2, 4, 6) when the number of startups is 3 is calculated as follows:

[0137] (1.3356+1.3753+1.3804+1.3410+1.3459+1.3473+1.3269+1.3269+1.3237) / 9=1.3447

[0138] Since 1.2613<1.3447, the first comparison result when the set temperatures are the same is determined: when the set temperatures are the same, the PUE when the number of powered-on computers is 2 is less than the PUE when the number of powered-on computers is 3.

[0139] Then, the following Table 4 can be established, where combinations where the second comparison results corresponding to the first combination and the second combination match the first comparison result are marked as 1, and combinations where they do not match are marked as 0, and the consistency statistics of the first combination and the second combination are counted.

[0140] Table 4 Consistency statistics

[0141]

[0142]

[0143] Among them, P(s, T) in Table 4 represents the energy consumption data corresponding to the startup number being s and the set temperature being T.

[0144] Since the sum of the first and second combinations corresponding to the same filter window is 7, by comparing the consistency statistics corresponding to each candidate filter window with the total statistical value, we can obtain the matching rates of the three filter windows as 85.7%, 100%, and 85.7%, respectively. This can determine the final filter window to be used for the candidate filter window position with a window width of 4.

[0145] Based on the same inventive concept, the embodiment of the present invention also provides a method for obtaining energy consumption data, such as Figure 4 As shown, including:

[0146] S201, using the filtering window decision method for obtaining energy consumption data to determine the filtering window;

[0147] S202: In each control cycle, the end time of the control cycle is used as the end time of the filter window, and the energy consumption data collected in the filter window is obtained;

[0148] S203: Filter the energy consumption data collected within the filter window to obtain energy consumption data.

[0149] In a specific implementation, after the decision is made, the control period and observation period of the temperature control device are the same as the control period and observation period during the decision process. In step S203, the energy consumption data collected within the filter window is filtered, which is a mean filter or median filter that is the same as the filter window decision method for obtaining the energy consumption data.

[0150] In a specific implementation, the control parameters used for the temperature control device during the process of acquiring energy consumption data may be the same as or different from the control parameters used in the filter window decision process (i.e., the control parameters used after the decision was made were not used in the decision process). Thus, the filter window width for a given denoising method can be set offline using the above method. When the temperature control device is actually operating and the control parameters change (e.g., the control parameters are different from the control parameters used in the decision process), the energy consumption data obtained by filtering using the filter window obtained by the decision still remains accurate and reliable.

[0151] Based on the same inventive concept, the embodiment of the present invention also provides a filter window decision device for obtaining energy consumption data, such as Figure 5 Shown, including:

[0152] The test data setting module M101 is used to set multiple groups of control parameters and multiple alternative filter windows, wherein each group of control parameters includes setting temperature and number of startups, and the window widths of the multiple alternative filter windows are different;

[0153] The test operation module M102 is used to control multiple temperature control devices to run a control cycle using a set of control parameters;

[0154] The data acquisition module M103 is used to collect energy consumption data of the plurality of temperature control devices once every observation period within the control period;

[0155] The data acquisition module M104 is configured to acquire the energy consumption data collected in each candidate filtering window by taking the end time of the control cycle as the end time of the candidate filtering window;

[0156] The filtering module M105 is used to filter the energy consumption data collected in each candidate filtering window respectively;

[0157] A first comparison result determination module M106 is used to determine a first comparison result expected to be obtained by comparing the energy consumption data of the multiple temperature control devices controlled by different sets of control parameters;

[0158] A second comparison result determination module M107 is configured to compare the energy consumption data of the temperature control devices when operating under different control parameters using the various candidate filter windows to obtain a second comparison result;

[0159] The decision module M108 is configured to compare the second comparison results corresponding to the candidate filtering windows with the first comparison results for consistency, and decide the candidate filtering window corresponding to the second comparison result with the highest consistency as the filtering window.

[0160] Optionally, filtering is performed on the energy consumption data collected in each candidate filtering window, including:

[0161] The energy consumption data collected in each alternative filtering window is subjected to mean filtering processing respectively.

[0162] Optionally, filtering is performed on the energy consumption data collected in each candidate filtering window, including:

[0163] The energy consumption data collected in each alternative filtering window is subjected to median filtering processing respectively.

[0164] Optionally, determining the candidate filtering window corresponding to the second comparison result with the highest consistency as the filtering window includes:

[0165] If there are multiple candidate filter windows with the highest consistency, the candidate filter window with the largest window width is selected as the filter window.

[0166] Optionally, the energy consumption data is power usage efficiency PUE or electric power.

[0167] Optionally, determining to compare energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters, the first comparison result expected to be obtained includes:

[0168] When it is determined that the power-on number s of the temperature control devices is the same, the energy consumption data corresponding to the set temperature T+|ΔT| is lower than the energy consumption data corresponding to the set temperature T;

[0169] Wherein, ΔT is the minimum change of the set temperature; s is a positive integer.

[0170] Optionally, determining to compare energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters, the first comparison result expected to be obtained includes:

[0171] When the same number of startups of the temperature control devices is traversed, the energy consumption data collected in each of the alternative filter windows at each set temperature are averaged;

[0172] Compare the average energy consumption data corresponding to different numbers of startups to determine whether the energy consumption data corresponding to the startup number s is higher or lower than the energy consumption data of the startup number s+1 when the set temperature is the same;

[0173] Where s is a positive integer.

[0174] Optionally, performing consistency comparison between the second comparison result corresponding to each candidate filtering window and the first comparison result includes:

[0175] Determine, among the multiple groups of control parameters, multiple first groups of control parameters having the same start-up number s and a set temperature difference of |ΔT|, and combine every two groups of the multiple first groups of control parameters to obtain multiple first combinations;

[0176] Determine, among the multiple groups of control parameters, multiple second groups of control parameters having the same temperature T and a power-on number s that differs by 1, and combine every two of the multiple second groups of control parameters to obtain multiple second combinations;

[0177] Setting a consistency statistic value, and setting an initial value of the consistency statistic value to zero;

[0178] Energy consumption data of a plurality of temperature control devices controlled by different groups of control parameters obtained within the same candidate filtering window are acquired and analyzed sequentially: whenever a second comparison result of the energy consumption data obtained by using a first combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1; whenever a second comparison result of the energy consumption data obtained by using a second combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1;

[0179] Compare the consistency statistics corresponding to each candidate filtering window with the total statistical value to obtain the consistency corresponding to each candidate filtering window, wherein the total statistical value is the total number of the first combination and the second combination corresponding to one candidate filtering window.

[0180] Based on the same inventive concept, the embodiment of the present invention also provides a device for obtaining energy consumption data, such as Figure 6 As shown, including:

[0181] A filter window determination module M201 is configured to determine the filter window using the filter window determination method for obtaining energy consumption data;

[0182] The data acquisition module M202 is used to acquire the energy consumption data collected within each control period, taking the end time of the control period as the end time of the filter window;

[0183] The energy consumption data acquisition module M203 is used to perform mean filtering on the energy consumption data collected within the filtering window to obtain energy consumption data.

[0184] Since the principles of the filtering window decision device for obtaining energy consumption data and the device for obtaining energy consumption data are similar to the corresponding methods, the implementation of the device can refer to the implementation of the corresponding method, and the repeated parts will not be repeated.

[0185] Based on the same inventive concept, an embodiment of the present invention further provides an electronic device, such as Figure 7As shown, it includes: a processor 110 and a memory 120 for storing executable instructions of the processor 110; wherein, the processor 110 is configured to execute the instructions to implement the filtering window decision method for obtaining energy consumption data, and / or the method for obtaining energy consumption data.

[0186] In a specific implementation, the device may have relatively large differences due to different configurations or performances, and may include one or more processors 110 and memories 120, and one or more storage media 130 storing applications 131 or data 132. The memories 120 and storage media 130 may be temporary storage or permanent storage. The application 131 stored in the storage medium 130 may include one or more of the above units ( Figure 7 (not shown), each module may include a series of instruction operations in the device. Further, the processor 110 may be configured to communicate with the storage medium 130 and execute a series of instruction operations in the storage medium 130 on the device. The device may also include one or more power supplies ( Figure 7 one or more network interfaces 140, wherein the network interfaces 140 include a wired network interface 141 and / or a wireless network interface 142; one or more input and output interfaces 143; and / or one or more operating systems 133, such as Windows, Mac OS, Linux, IOS, Android, Unix, FreeBSD, etc.

[0187] Based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, which stores a computer program, and the computer program is used to implement the filtering window decision method for obtaining energy consumption data and / or the method for obtaining energy consumption data.

[0188] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0189] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0190] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0191] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0192] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for determining a filter window for obtaining energy consumption data, characterized in that: The method includes: Setting multiple groups of control parameters and multiple alternative filter windows, wherein each group of control parameters includes setting temperature and number of startups, and the window widths of the multiple alternative filter windows are different; Use a set of control parameters to control the duration of a control cycle for multiple temperature control devices; During the control period, each time an observation period is reached, energy consumption data of the plurality of temperature control devices is collected; Taking the end time of the control cycle as the end time of the candidate filter window, obtaining the energy consumption data collected in each candidate filter window; Filter the energy consumption data collected in each alternative filtering window respectively; Determining a first comparison result expected from comparing energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters; Comparing energy consumption data of the plurality of temperature control devices under different control parameter groups when using the various alternative filter windows to obtain a second comparison result; The second comparison results corresponding to each candidate filtering window are compared for consistency with the first comparison results, and the candidate filtering window corresponding to the second comparison result with the highest consistency is determined as the filtering window.

2. The method according to claim 1, wherein The energy consumption data collected in each alternative filter window is filtered separately, including: Perform mean filtering on the energy consumption data collected in each alternative filtering window; Alternatively, median filtering is performed on the energy consumption data collected in each candidate filtering window.

3. The method according to claim 1, wherein The candidate filtering window corresponding to the second comparison result with the highest consistency is determined as the filtering window, including: If there are multiple candidate filter windows with the highest consistency, the candidate filter window with the largest window width is selected as the filter window.

4. The method according to claim 1, wherein The energy consumption data is power usage efficiency PUE or electric power.

5. The method according to claim 1, wherein Determine and compare the energy consumption data of multiple temperature control devices controlled by different groups of control parameters. The first comparison results expected to be obtained include: When it is determined that the power-on number s of the temperature control devices is the same, the energy consumption data corresponding to the set temperature T+|ΔT| is lower than the energy consumption data corresponding to the set temperature T; Wherein, ΔT is the minimum change of the set temperature; s is a positive integer.

6. The method according to claim 1, wherein Determine and compare the energy consumption data of multiple temperature control devices controlled by different groups of control parameters. The first comparison results expected to be obtained include: When the same number of startups of the temperature control devices is traversed, the energy consumption data collected in each of the alternative filter windows at each set temperature are averaged. Compare the average energy consumption data corresponding to different numbers of startups to determine whether the energy consumption data corresponding to the startup number s is higher or lower than the energy consumption data of the startup number s+1 when the set temperature is the same; Where s is a positive integer.

7. The method according to claim 1, wherein Performing consistency comparison between the second comparison result corresponding to each candidate filtering window and the first comparison result, including: Determine, among the multiple groups of control parameters, multiple first groups of control parameters having the same start-up number s and a set temperature difference of |ΔT|, and combine every two groups of the multiple first groups of control parameters to obtain multiple first combinations; Determine, among the multiple groups of control parameters, multiple second groups of control parameters having the same temperature T and a power-on number s that differs by 1, and combine every two of the multiple second groups of control parameters to obtain multiple second combinations; Setting a consistency statistic value, and setting an initial value of the consistency statistic value to zero; Energy consumption data of a plurality of temperature control devices controlled by different groups of control parameters obtained within the same candidate filtering window are acquired and analyzed sequentially: whenever a second comparison result of the energy consumption data obtained by using a first combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1; whenever a second comparison result of the energy consumption data obtained by using a second combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1; Compare the consistency statistics corresponding to each candidate filtering window with the total statistical value to obtain the consistency corresponding to each candidate filtering window, wherein the total statistical value is the total number of the first combination and the second combination corresponding to one candidate filtering window.

8. A method for obtaining energy consumption data, characterized in that: include: Using the filter window decision method for obtaining energy consumption data according to any one of claims 1 to 7, a filter window to be used is decided from a plurality of candidate filter windows; In each control cycle, the end time of the control cycle is used as the end time of the filter window, and the energy consumption data collected in the filter window is obtained; The energy consumption data collected within the filtering window is subjected to mean filtering to obtain energy consumption data.

9. A filter window decision device for obtaining energy consumption data, characterized in that: include: A test data setting module is used to set multiple groups of control parameters and multiple alternative filter windows, wherein each group of control parameters includes setting temperature and number of startups, and the window widths of the multiple alternative filter windows are different; A test operation module is used to control multiple temperature control devices to run a control cycle using a set of control parameters; A data acquisition module, configured to collect energy consumption data of the plurality of temperature control devices once each observation period is reached within the control period; A data acquisition module, configured to take the end time of the control cycle as the end time of the candidate filter window and acquire the energy consumption data collected in each candidate filter window; A filtering module is used to filter the energy consumption data collected in each candidate filtering window respectively; A first comparison result determination module is used to determine a first comparison result expected to be obtained by comparing energy consumption data of a plurality of temperature control devices controlled by different sets of control parameters; A second comparison result determination module is used to compare the energy consumption data of the plurality of temperature control devices when different groups of control parameters are used to control the operation of the plurality of temperature control devices when the candidate filter windows are adopted, to obtain a second comparison result; The decision module is configured to compare the second comparison results corresponding to each candidate filtering window with the first comparison result for consistency, and decide the candidate filtering window corresponding to the second comparison result with the highest consistency as the filtering window.

10. The device according to claim 9, wherein The energy consumption data collected in each alternative filter window is filtered separately, including: Perform mean filtering on the energy consumption data collected in each alternative filtering window; Alternatively, median filtering is performed on the energy consumption data collected in each candidate filtering window.

11. The device according to claim 9, wherein The candidate filtering window corresponding to the second comparison result with the highest consistency is determined as the filtering window, including: If there are multiple candidate filter windows with the highest consistency, the candidate filter window with the largest window width is selected as the filter window.

12. The device according to claim 9, wherein The energy consumption data is power usage efficiency PUE or electric power.

13. The device according to claim 9, wherein Determine and compare the energy consumption data of multiple temperature control devices controlled by different groups of control parameters. The first comparison results expected to be obtained include: When it is determined that the power-on number s of the temperature control devices is the same, the energy consumption data corresponding to the set temperature T+|ΔT| is lower than the energy consumption data corresponding to the set temperature T; Wherein, ΔT is the minimum change of the set temperature; s is a positive integer.

14. The device according to claim 9, wherein Determine and compare the energy consumption data of multiple temperature control devices controlled by different groups of control parameters. The first comparison results expected to be obtained include: When the same number of startups of the temperature control devices is traversed, the energy consumption data collected in each of the alternative filter windows at each set temperature are averaged. Compare the average energy consumption data corresponding to different numbers of startups to determine whether the energy consumption data corresponding to the startup number s is higher or lower than the energy consumption data of the startup number s+1 when the set temperature is the same; Where s is a positive integer.

15. The device according to claim 9, wherein Performing consistency comparison between the second comparison result corresponding to each candidate filtering window and the first comparison result, including: Determine, among the multiple groups of control parameters, multiple first groups of control parameters having the same start-up number s and a set temperature difference of |ΔT|, and combine every two groups of the multiple first groups of control parameters to obtain multiple first combinations; Determine, among the multiple groups of control parameters, multiple second groups of control parameters having the same temperature T and a power-on number s that differs by 1, and combine every two of the multiple second groups of control parameters to obtain multiple second combinations; Setting a consistency statistic value, and setting an initial value of the consistency statistic value to zero; Energy consumption data of a plurality of temperature control devices controlled by different groups of control parameters obtained within the same candidate filtering window are acquired and analyzed sequentially: whenever a second comparison result of the energy consumption data obtained by using a first combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1; whenever a second comparison result of the energy consumption data obtained by using a second combination is found to be the same as the first comparison result, the consistency statistic is incremented by 1; Compare the consistency statistics corresponding to each candidate filtering window with the total statistical value to obtain the consistency corresponding to each candidate filtering window, wherein the total statistical value is the total number of the first combination and the second combination corresponding to one candidate filtering window.

16. A device for acquiring energy consumption data, characterized in that: include: a filtering window determination module, configured to determine the filtering window using the filtering window decision method for obtaining energy consumption data according to any one of claims 1 to 7; A data acquisition module is used to acquire energy consumption data collected within each control period, taking the end time of the control period as the end time of the filter window; The energy consumption data acquisition module is used to perform mean filtering on the energy consumption data collected in the filtering window to obtain energy consumption data.

17. An electronic device, characterized in that: include: a processor and a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the filtering window decision method for obtaining energy consumption data according to any one of claims 1 to 7, and / or the method for obtaining energy consumption data according to claim 8.

18. A computer storage medium, characterized in that The computer storage medium stores a computer program, which is used to implement the filtering window decision method for obtaining energy consumption data according to any one of claims 1 to 7, and / or the method for obtaining energy consumption data according to claim 8.

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