A method, device, electronic device, and storage medium for comparative analysis of energy consumption data

Abstract

The present invention relates to a method, device, electronic device and storage medium for comparative analysis of energy consumption data, belonging to the technical field of energy consumption data analysis. The method includes obtaining first energy consumption data and first metering performance data of main equipment; analyzing the first energy consumption data to obtain an energy consumption change trend; determining multiple related equipment according to the first metering performance data to obtain second metering performance data of each related equipment; respectively comparing and analyzing the energy consumption change trend according to the second metering performance data to obtain a comparative analysis result of each related equipment. According to the present invention, the energy consumption change trend is obtained based on the first energy consumption data of the main equipment, the related equipment is determined according to the first metering performance data of the main equipment, and the second metering performance data of the related equipment is compared and analyzed with the energy consumption change trend to obtain the influence of the related equipment on the main equipment, achieving the purpose of further analyzing the energy consumption data and increasing the value expression form of the energy consumption data.

Description

Technical Field

[0001] The present invention relates to the technical field of energy consumption data analysis, and in particular, to a method, device, electronic device, and storage medium for comparative analysis of energy consumption data. Background Art

[0002] The monitoring and capture of carbon measurement data play an important role in guiding the regional economic and social development. Each region has collected energy consumption data of key energy-consuming units within its jurisdiction, and has also established institutions such as the National Energy Measurement Center through technical institutions to be responsible for carbon emission monitoring of key energy-consuming enterprises. However, the data collected currently only stays at the stage of statistics and display, lacking further analysis and utilization of the data. The energy consumption data is equivalent to an island among numerous data centers, and the form of expressing the data value is lacking.

[0003] Therefore, there is an urgent need to propose a method, device, electronic device, and storage medium for comparative analysis of energy consumption data to solve the technical problem in the prior art that after the carbon emissions of key energy-consuming enterprises are counted, the carbon emission data cannot be further analyzed, resulting in the lack of the form of expressing the value of energy consumption data. Summary of the Invention

[0004] In view of this, it is necessary to provide a method, device, electronic device, and storage medium for comparative analysis of energy consumption data to solve the technical problem in the prior art that after the carbon emissions of key energy-consuming enterprises are counted, the carbon emission data cannot be further analyzed, resulting in the lack of the form of expressing the value of energy consumption data.

[0005] To solve the above problems, the present invention provides a method for comparative analysis of energy consumption data, including:

[0006] Obtain the first energy consumption data and the first measurement performance data of the main equipment;

[0007] Analyze the first energy consumption data to obtain an energy consumption change trend;

[0008] Determine a plurality of related devices according to the first measurement performance data, and obtain the second measurement performance data of each related device;

[0009] Conduct a comparative analysis of the energy consumption change trend according to the second measurement performance data respectively to obtain the comparative analysis results of each related device.

[0010] In a possible implementation manner, the analyzing the first energy consumption data to obtain an energy consumption change trend includes:

[0011] Perform data desensitization and regression fitting on the first energy consumption data to obtain fitting data;

[0012] Draw an energy consumption change curve based on the fitting data;

[0013] Analyze the energy consumption change curve to obtain the energy consumption change trend.

[0014] In one possible implementation, the drawing of the energy consumption change curve based on the fitting data includes:

[0015] When the fitting data includes data of different parameters, determine the first fitting data corresponding to each parameter;

[0016] Draw the energy consumption change curve corresponding to each parameter according to the first fitting data corresponding to each parameter.

[0017] In one possible implementation, the first measurement performance data includes equipment historical calibration and detection data;

[0018] The determination of multiple related devices according to the first measurement performance data includes:

[0019] Analyze the equipment historical calibration and the detection data to obtain various measurement characteristics;

[0020] Draw the first measurement performance fluctuation curve corresponding to each measurement characteristic according to the first measurement performance data;

[0021] Analyze the first measurement performance fluctuation curve of each measurement characteristic respectively to determine the characteristic analysis result of each measurement characteristic;

[0022] Determine multiple related devices according to the characteristic analysis result.

[0023] In one possible implementation, the comparative analysis of the energy consumption change trends according to the second measurement performance data to obtain the comparative analysis result of each related device includes:

[0024] Obtain the second measurement performance fluctuation curve corresponding to each related device according to the second measurement performance data corresponding to each related device;

[0025] Compare and analyze the second measurement performance fluctuation curve of each related device with the energy consumption change curve of the energy consumption change trend to determine the change analysis result of each related device.

[0026] In one possible implementation, the comparing and analyzing the second measurement performance fluctuation curve of each related device with the energy consumption change curve of the energy consumption change trend to determine the change analysis result of each related device includes:

[0027] Judge each of the relevant devices respectively to determine whether the data corresponding to the energy consumption change curve changes when the second measurement performance fluctuation curve changes at the same time;

[0028] If so, determine that the change analysis result of the corresponding relevant device has an impact, and improve the performance of the corresponding relevant device;

[0029] If not, determine that the change analysis result of the corresponding relevant device has no impact.

[0030] In a possible implementation, after obtaining the first energy consumption data and the first measurement performance data of the main device, it further includes:

[0031] List the data of external factors that affect the energy consumption index of the main device in the first energy consumption data to obtain the first measurement performance data.

[0032] On the other hand, the present invention also provides an energy consumption data comparison and analysis device, including:

[0033] A data acquisition module for acquiring the first energy consumption data and the first measurement performance data of the main device;

[0034] A trend analysis module for analyzing the first energy consumption data to obtain an energy consumption change trend;

[0035] A device determination module for determining a plurality of relevant devices according to the first measurement performance data and obtaining the second measurement performance data of each relevant device;

[0036] A result analysis module for respectively comparing and analyzing the energy consumption change trend according to the second measurement performance data to obtain the comparison and analysis result of each relevant device.

[0037] On the other hand, an embodiment of the present invention discloses an electronic device, including: a processor, a memory, and a computer program stored on the memory and capable of running on the processor. When the computer program is executed by the processor, it implements each step of the above-mentioned energy consumption data comparison and analysis method embodiment.

[0038] On the other hand, an embodiment of the present invention discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements each step of the above-mentioned energy consumption data comparison and analysis method embodiment.

[0039] The beneficial effects of the present invention are as follows: After obtaining the first energy consumption data of the main device, the present invention can obtain the energy consumption change trend of the main device based on the first energy consumption data, and can also obtain the first metrological performance data of the main device. Furthermore, the related devices affecting the main device can be determined based on the first metrological performance data. After obtaining the second metrological performance data of the main device, the second metrological performance data can be compared and analyzed with the energy consumption change trend of the main device, and then the impacts of the related devices on the main device can be obtained, realizing further analysis of the energy consumption data and increasing the value expression form of the energy consumption data. Description of the Drawings

[0040] Figure 1 It is a schematic flowchart of an embodiment of the energy consumption data comparison and analysis method provided by the present invention;

[0041] Figure 2 For the present invention Figure 1 It is a schematic flowchart of an embodiment of step S103 in the present invention;

[0042] Figure 3 It is a schematic flowchart of an embodiment of the uncertainty curve provided by the present invention;

[0043] Figure 4 It is a schematic coordinate diagram of an embodiment of the curve of the DC voltage indication error provided by the present invention;

[0044] Figure 5 It is a schematic coordinate diagram of an embodiment of the curve of the DC current indication error provided by the present invention;

[0045] Figure 6 It is a schematic structural diagram of an embodiment of the energy consumption data comparison and analysis device provided by the present invention;

[0046] Figure 7 It is a schematic structural diagram of an embodiment of the electronic device provided by the present invention. Detailed Embodiments

[0047] The preferred embodiments of the present invention will be specifically described below with reference to the accompanying drawings. The accompanying drawings form a part of this application and are used together with the embodiments of the present invention to explain the principles of the present invention, rather than to limit the scope of the present invention.

[0048] As Figure 1 shown, a specific embodiment of the present invention discloses an energy consumption data comparison and analysis method, including:

[0049] S101. Obtain the first energy consumption data and the first metrological performance data of the main device;

[0050] S102. Analyze the first energy consumption data to obtain the energy consumption change trend;

[0051] S103. Determine multiple related devices according to the first measurement performance data, and obtain the second measurement performance data of each related device;

[0052] S104. Compare and analyze the energy consumption change trends respectively according to the second measurement performance data to obtain the comparative analysis results of each related device.

[0053] It should be understood that the first energy consumption data and the first measurement performance data of the main device obtained in step S101 can be historical stored data or the latest obtained data.

[0054] In a specific embodiment of the present invention, the first energy consumption data of the main device within a time period can be obtained. For example, the annual energy consumption data of a boiler is plotted to obtain a curve, and the measurement performances of devices such as pressure gauges, flow meters, and temperature boxes used in the entire boiler system are analyzed and plotted to analyze with the energy consumption curve to study which parameters or which combinations of parameters have an impact on the energy consumption fluctuation. Among them, objective factor influences such as environment, personnel operation, and raw material purity change are marked. A comparison of one parameter or multiple parameters can be performed. The main device can be an energy consumption device used in production activities, and the related devices can range from small pressure gauges to large high-pressure boilers, etc. These all need to be periodically verified and calibrated by a qualified third-party unit, and this time period varies depending on the device type and working conditions. The carbon dioxide or sulfur dioxide discharged per hour by the main device can be obtained, and data can be obtained once a day. The specific first energy consumption data and the acquisition time can be set according to the actual situation, and the embodiments of the present invention do not limit this here.

[0055] After the present invention obtains the first energy consumption data of the main device, it can obtain the energy consumption change trend of the main device according to the first energy consumption data, and can also obtain the first measurement performance data of the main device. Furthermore, it can determine the related devices affecting the main device according to the first measurement performance data. After obtaining the second measurement performance data of the main device, the second measurement performance data can be compared and analyzed with the energy consumption change trend of the main device, and then it can be obtained what impacts the related devices have on the main device, realizing further analysis of the energy consumption data and increasing the value expression form of the energy consumption data.

[0056] It should be noted that in order to analyze the accuracy of the results, external factor influences can be excluded or quantified. In some embodiments of the present invention, after obtaining the first energy consumption data and the first measurement performance data of the main device, it further includes:

[0057] List the data of external factors affecting the energy consumption index of the main device in the first energy consumption data to obtain the first measurement performance data.

[0058] In a specific embodiment of the present invention, during the detection and analysis of the main equipment, factors that can significantly affect the change of the energy consumption index of the main equipment can be listed according to conditions such as the work experience of the operator. For example, changes in the process and production materials, which may include manual operations (replacing an old master with a new one), weather changes, improvement of natural gas purity, etc. These factors will affect the energy consumption of the main equipment, so the influence of these external factors can be excluded or quantified to obtain the listed external factors. The listed external factors can be the first measurement performance parameters of the main equipment, and then the data corresponding to each first measurement performance parameter can be obtained. The purpose is to adapt to the change of the energy consumption curve through the change of the performance parameters, and if they match, the energy utilization rate can be improved by adopting methods to improve the measurement performance of the equipment.

[0059] It should be noted that: in order to analyze the first energy consumption data, in some embodiments of the present invention, step S102 includes:

[0060] Perform data desensitization and regression fitting on the first energy consumption data to obtain fitting data;

[0061] Draw an energy consumption change curve according to the fitting data;

[0062] Analyze the energy consumption change curve to obtain the energy consumption change trend.

[0063] In a specific embodiment of the present invention, due to the large amount of energy consumption data and high data recording frequency, after obtaining the first energy consumption data, it is necessary to perform data desensitization and data cleaning on the first energy consumption data, and the units of the data can also be unified. Furthermore, the first energy consumption data can be protected through data desensitization, and redundant data and invalid data in the first energy consumption data can be removed through data cleaning. For example, when the equipment is always shut down or started up, some invalid data that does not affect the performance will appear. The specific implementation process of data desensitization and data cleaning can be set according to the actual situation, and the embodiments of the present invention do not limit this here. The first energy consumption data after data desensitization and data cleaning can also be subjected to regression fitting, and then a curve representing the energy consumption trend can be drawn, so that an energy consumption change curve can be obtained, and thus the energy consumption change trend of the main equipment can be analyzed. For example, the x-axis of the energy consumption change curve is the time axis, and the y-axis represents the energy consumption characteristics of the equipment: such as the emissions of gases such as carbon dioxide, carbon monoxide, sulfur dioxide, and water vapor, or the consumption of coal and electricity.

[0064] In some embodiments of the present invention, drawing an energy consumption change curve according to the fitting data includes:

[0065] When the fitting data includes data of different parameters, determine the first fitting data corresponding to each parameter;

[0066] According to the first fitting data corresponding to each parameter, an energy consumption change curve corresponding to each parameter is plotted.

[0067] In a specific embodiment of the present invention, after performing regression fitting on the first energy consumption data, fitting data can be obtained. Among them, the fitting data can include at least one parameter of a main device. When the fitting data includes multiple different parameters, curves can be plotted for the data corresponding to each parameter in the fitting data respectively to obtain an energy consumption change curve corresponding to each parameter. For example, the parameter can be data such as current and voltage, and then an energy consumption change curve of the current data and an energy consumption change curve of the voltage can be obtained.

[0068] Furthermore, after obtaining the energy consumption change curve, the energy consumption change curve can be analyzed to obtain the energy consumption change trend of the main device. Specifically, it can be: determining whether there is a positive correlation or a negative correlation in the energy consumption change curve, and then the energy consumption change trend can be seen based on the positive correlation or the negative correlation.

[0069] As Figure 2 shown, in some embodiments of the present invention, the first measurement performance data includes device historical calibration and detection data; step S103 includes:

[0070] S201. Analyze the device historical calibration and detection data to obtain various measurement characteristics;

[0071] S202. According to the first measurement performance data, plot a first measurement performance fluctuation curve corresponding to each measurement characteristic;

[0072] S203. Analyze the first measurement performance fluctuation curve of each measurement characteristic respectively to determine the characteristic analysis result of each measurement characteristic;

[0073] S204. Determine multiple related devices according to the characteristic analysis result.

[0074] In a specific embodiment of the present invention, the first measurement performance data can include device historical calibration and detection data, and various measurement characteristics can include characteristics such as stability, repeatability, and uncertainty. For example, as Figure 3 shown, Figure 3 is an uncertainty curve, the x-axis is time (month), the y-axis is uncertainty, and the characteristics corresponding to the uncertainty can be analyzed according to Figure 3 the uncertainty curve. The stability of the voltmeter is as Figure 4 shown, Figure 4 is a curve of the DC voltage indication error, the x-axis is time (month), the y-axis is the DC voltage indication, and the stability of the voltmeter can be analyzed according to Figure 4 this, and the stability of the ammeter is as Figure 5As shown Figure 5 is the curve of the DC current indication error. The x-axis is time (month), and the y-axis is the DC current indication. The stability of the ammeter can be analyzed according to Figure 5 The equipment historical calibration and detection data of the main equipment can be obtained. Among them, the equipment historical calibration can be the data of calibrating the main equipment within a certain period of time, and the detection data can be the data obtained by sending the equipment historical calibration and other data of the main equipment to a third-party testing agency for testing according to a fixed period. Generally, the fixed period is three months, six months or one year. When conducting a physical examination of the main equipment by a third-party testing agency, other relevant equipment can be judged. For example, it can be judged whether the voltmeter meets the production standards. The physical examination period of the same equipment varies in different industries. If it does not meet the production standards, the corresponding relevant equipment can be determined as invalid equipment. For example, if the elevator is the main equipment and maintenance is carried out on the elevator, the physical examination results of the elevator and other relevant equipment can be obtained. If the data generated by a certain relevant equipment does not affect the performance of the elevator or does not meet the production standards, the corresponding relevant equipment can be determined as invalid equipment, and then multiple effective relevant equipment can be obtained.

[0075] Among them, the results of the verification and calibration of each measurement characteristic will be evaluated according to the performance of the equipment at that moment, and a verification and calibration report will be issued. The data in the report is the basis for drawing the first measurement performance fluctuation curve of the equipment. Different equipment will be detected according to the corresponding regulations / specifications. For example, for a biosafety cabinet, parameters such as particle concentration, air flow velocity, and illuminance will be measured; for a constant temperature bath, parameters such as the maximum temperature difference in the working area and temperature fluctuation will be detected; for a high-temperature furnace, parameters such as pressure fluctuation, temperature fluctuation, and indication error will be detected; the x-axis of the first measurement performance fluctuation curve of the equipment is the time axis, and the y-axis is the representation of the measurement characteristic.

[0076] In some embodiments of the present invention, step S104 includes:

[0077] Obtain the second measurement performance fluctuation curve corresponding to each relevant equipment according to the second measurement performance data corresponding to each relevant equipment;

[0078] Compare and analyze the second measurement performance fluctuation curve of each relevant equipment with the energy consumption change curve of the energy consumption change trend to determine the change analysis result of each relevant equipment.

[0079] In a specific embodiment of the present invention, after determining each relevant device, the second measurement performance data corresponding to each relevant device can be obtained. Furthermore, a curve can be plotted based on the second measurement performance data corresponding to each relevant device, and the second measurement performance fluctuation curve corresponding to each relevant device can be obtained, achieving multi-dimensional decomposition and simplifying the problem. For example, if a flow meter and a pressure gauge both affect the energy consumption of the main device (boiler), the abscissa can be time and the ordinate can be unrestricted. By taking the derivative and integral, the second measurement performance fluctuation curve of the flow meter for one year or the second measurement performance fluctuation curve of the pressure gauge for one year can be obtained. Among them, multi-dimensional decomposition is to separately plot the historical fluctuation data of each relevant device as a curve. Within the same time period, compare it with the energy consumption curve of the main device to see if there is a correlation in the curve trend, whether the increase or decrease in energy consumption data is caused by the fluctuation of a certain measurement characteristic of the relevant device, or whether the fluctuation of energy consumption data can early warn of the deviation of the measurement performance of the device and early warn of safe production. Simplifying the problem can be explained from the analysis method. First, the control variable method is used to study the change trend or possible influence of a single variable on the energy consumption of the device; second, multi-variable superposition, where the changes of multiple measurement performance parameters are superimposed to cause the fluctuation of the energy consumption curve; third, external factor superposition, considering the objective influence of factors such as weather, environment, raw materials, and personnel operation on the energy-consuming device. Therefore, simplification from the perspective of method research is a simplification of the problem, and the process is not simplified.

[0080] In some embodiments of the present invention, the second measurement performance fluctuation curve of each relevant device is compared and analyzed with the energy consumption change curve of the energy consumption change trend to determine the change analysis result of each relevant device, including:

[0081] Each relevant device is judged separately to determine whether the data corresponding to the energy consumption change curve changes when the second measurement performance fluctuation curve changes at the same time;

[0082] If so, the change analysis result of the corresponding relevant device is determined to have an impact, and the performance of the corresponding relevant device is improved;

[0083] If not, the change analysis result of the corresponding relevant device is determined to have no impact.

[0084] In a specific embodiment of the present invention, after obtaining the second metering performance fluctuation curve of each relevant device, the second metering performance fluctuation curve of each relevant device can be respectively compared and analyzed with the energy consumption change curve of the energy consumption change trend of the main device. For example, if the relevant device is a flow meter and the main device is a boiler, it can be determined whether there is an interaction relationship. For example, when analyzing whether the data in the energy consumption change curve changes at the same time when the flow data in the second metering performance fluctuation curve changes. If so, it can be determined that the flow meter has an impact on the energy consumption of the boiler, and the performance of the flow meter can be improved to achieve the purpose of reducing the energy consumption of the boiler. For example, for a photovoltaic device, when the DC voltage stability of the device decreases and the indication error is obvious, its energy consumption level will increase. Therefore, the energy consumption of the device can be improved by improving the voltage stability of the device. If the data in the energy consumption change curve does not change at the same time when the flow data in the second metering performance fluctuation curve changes, the influence of the flow meter on the energy consumption of the boiler can be excluded. It is also possible to judge indicators such as the curve slope, curvature, and change acceleration within the same time period, which are not limited in the embodiments of the present invention.

[0085] To better implement the energy consumption data comparison and analysis method in the embodiments of the present invention, correspondingly, based on the energy consumption data comparison and analysis method, the embodiments of the present invention also provide an energy consumption data comparison and analysis device, as Figure 6 shown. The energy consumption data comparison and analysis device 600 includes:

[0086] A data acquisition module 601, configured to acquire first energy consumption data and first metering performance data of the main device;

[0087] A trend analysis module 602, configured to analyze the first energy consumption data to obtain an energy consumption change trend;

[0088] A device determination module 603, configured to determine a plurality of relevant devices according to the first metering performance data, and obtain second metering performance data of each relevant device;

[0089] A result analysis module 604, configured to respectively compare and analyze the energy consumption change trend according to the second metering performance data to obtain a comparison and analysis result of each relevant device.

[0090] The energy consumption data comparison and analysis device 600 provided in the above embodiment can implement the technical solutions described in the embodiments of the above energy consumption data comparison and analysis method. The specific implementation principles of the above modules or units can be referred to the corresponding content in the embodiments of the above energy consumption data comparison and analysis method, which will not be elaborated here.

[0091] As Figure 7As shown, the present invention also correspondingly provides an electronic device 700. The electronic device 700 includes a processor 701, a memory 702, and a display 703. Figure 7 Only some components of the electronic device 700 are shown, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented.

[0092] In some embodiments, the memory 702 may be an internal storage unit of the electronic device 700, such as the hard disk or memory of the electronic device 700. In other embodiments, the memory 702 may also be an external storage device of the electronic device 700, such as a plug-in hard disk equipped on the electronic device 700, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc.

[0093] Furthermore, the memory 702 may also include both the internal storage unit and the external storage device of the electronic device 700. The memory 702 is used to store the application software installed in the electronic device 700 and various types of data.

[0094] In some embodiments, the processor 701 may be a Central Processing Unit (CPU), a microprocessor, or other data processing chips, and is used to run the program code stored in the memory 702 or process data, such as the energy consumption data comparison and analysis method in the present invention.

[0095] In some embodiments, the display 703 may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. The display 703 is used to display the information of the electronic device 700 and to display a visual user interface. The components 701 - 703 of the electronic device 700 communicate with each other through a system bus.

[0096] In some embodiments of the present invention, when the processor 701 executes the energy consumption data comparison and analysis program in the memory 702, the following steps can be implemented:

[0097] Obtain the first energy consumption data and the first metering performance data of the main device;

[0098] Analyze the first energy consumption data to obtain the energy consumption change trend;

[0099] Determine multiple related devices according to the first metering performance data, and obtain the second metering performance data of each related device;

[0100] According to the second measurement performance data, the energy consumption change trends are respectively compared and analyzed to obtain the comparison and analysis results of each relevant device.

[0101] It should be understood that when the processor 701 executes the energy consumption data comparison and analysis program in the memory 702, in addition to the above functions, other functions can also be realized. For specific details, reference can be made to the description of the corresponding method embodiments above.

[0102] Furthermore, the embodiments of the present invention do not specifically limit the type of the mentioned electronic device 700. The electronic device 700 can be a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, or other portable electronic devices. Exemplary embodiments of the portable electronic device include, but are not limited to, portable electronic devices equipped with IOS, android, microsoft, or other operating systems. The above portable electronic devices can also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (such as a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 700 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (such as a touch panel).

[0103] Correspondingly, the embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium is used to store computer-readable programs or instructions. When the programs or instructions are executed by a processor, the method steps or functions of the energy consumption data comparison and analysis method provided by the above-mentioned method embodiments can be realized.

[0104] Those skilled in the art can understand that all or part of the processes of implementing the methods of the above embodiments can be completed by instructing relevant hardware (such as a processor, a controller, etc.) through a computer program. The computer program can be stored in a computer-readable storage medium. Among them, the computer-readable storage medium is a magnetic disk, an optical disk, a read-only memory, or a random access memory, etc.

[0105] The above has introduced in detail the energy consumption data comparison and analysis method, device, electronic device, and storage medium provided by the present invention. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those skilled in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for comparing and analyzing energy consumption data, characterized in that: include: Obtaining first energy consumption data and first metering performance data of main equipment; Analyzing the first energy consumption data to obtain an energy consumption change trend; Determine a plurality of related devices according to the first metrological performance data, and obtain second metrological performance data of each related device; Comparatively analyzing the energy consumption change trends respectively according to the second metering performance data to obtain comparative analysis results of each relevant device; The first metrological performance data includes historical equipment calibration and testing data; The determining of a plurality of related devices according to the first metrological performance data comprises: Analyze the historical calibration of the equipment and the test data to obtain various metrological characteristics; Draw a first metrological performance fluctuation curve corresponding to each metrological characteristic according to the first metrological performance data; Analyzing the first metrological performance fluctuation curve of each metrological characteristic respectively to determine a characteristic analysis result of each metrological characteristic; According to the characteristic analysis result, a plurality of related devices are determined.

2. The energy consumption data comparison and analysis method according to claim 1 is characterized in that: The analyzing the first energy consumption data to obtain the energy consumption change trend includes: Performing data desensitization and regression fitting on the first energy consumption data to obtain fitting data; According to the fitting data, drawing an energy consumption change curve; The energy consumption variation curve is analyzed to obtain the energy consumption variation trend.

3. The energy consumption data comparison and analysis method according to claim 2 is characterized in that: Drawing an energy consumption change curve according to the fitting data includes: When the fitting data includes data of different parameters, determining first fitting data corresponding to each parameter; According to the first fitting data corresponding to each parameter, an energy consumption change curve corresponding to each parameter is drawn.

4. The energy consumption data comparison and analysis method according to claim 2 is characterized in that: The comparing and analyzing the energy consumption change trends respectively according to the second metering performance data to obtain the comparative analysis results of each relevant device includes: Obtaining a second metrology performance fluctuation curve corresponding to each relevant device according to the second metrology performance data corresponding to each relevant device; The second metering performance fluctuation curve of each relevant device is compared and analyzed with the energy consumption change curve of the energy consumption change trend to determine the change analysis result of each relevant device.

5. The energy consumption data comparison and analysis method according to claim 4 is characterized in that: The comparing and analyzing the second metering performance fluctuation curve of each relevant device with the energy consumption change curve of the energy consumption change trend to determine the change analysis result of each relevant device includes: Determine each of the related devices respectively to determine whether the data corresponding to the energy consumption change curve changes when the second metering performance fluctuation curve changes at the same time; If yes, the change analysis result of the corresponding related equipment is determined to be influential, and the performance of the corresponding related equipment is improved; If not, the change analysis results of the corresponding related equipment will be determined as having no impact.

6. The energy consumption data comparison and analysis method according to claim 1, characterized in that: After obtaining the first energy consumption data and the first metering performance data of the main equipment, the method further includes: The data of external factors affecting the energy consumption index of the main equipment in the first energy consumption data are listed to obtain first metering performance data.

7. An energy consumption data comparison and analysis device, characterized in that: include: A data acquisition module, used to acquire first energy consumption data and first metering performance data of main equipment; A trend analysis module, used for analyzing the first energy consumption data to obtain an energy consumption change trend; A device determination module, used to determine a plurality of related devices according to the first metrology performance data, and obtain second metrology performance data of each related device; A result analysis module, used for performing comparative analysis on the energy consumption change trends according to the second metering performance data, and obtaining comparative analysis results of each relevant device; The first metrological performance data includes historical equipment calibration and testing data; The device determination module is further used to analyze the device historical calibration and the detection data to obtain various metrological characteristics; draw a first metrological performance fluctuation curve corresponding to each metrological characteristic according to the first metrological performance data; analyze the first metrological performance fluctuation curve of each metrological characteristic respectively to determine the characteristic analysis result of each metrological characteristic; According to the characteristic analysis result, a plurality of related devices are determined.

8. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of the energy consumption data comparison and analysis method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the energy consumption data comparison and analysis method according to any one of claims 1 to 6 are implemented.

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