Centralized acquisition method for multi-node electric energy meter data

Abstract

The invention discloses a centralized collection method for multi-node electric energy meter data, and relates to the technical field of electric energy meter collection, and the method comprises the steps: collecting data based on the information of each electric energy meter, obtaining a centralized collection region through employing a region analysis method and a grade analysis method, and classifying the electric energy meters; acquiring a centralized acquisition interval of each acquisition level; performing data acquisition on the electric energy meter based on the centralized acquisition interval and the total acquisition interval; the method is used for solving the problems that in an existing centralized collection method of electric energy meter data, when multiple operation environments exist due to wide distribution of electric energy meters and the difference of collected data is large, centralized collection cannot be efficiently carried out on all the electric energy meters; and the centralized collection time cannot be determined based on the actual collection condition of the electric energy meter, so that the data collection of the electric energy meter is distorted.

Description

Technical Field

[0001] This invention relates to the field of electricity meter data acquisition technology, specifically a method for centralized acquisition of data from multi-node electricity meters. Background Technology

[0002] Data collection from electricity meters mainly includes basic metering data, electricity consumption data, event records, operating status, and environmental parameters. Centralized data collection from electricity meters is achieved through a system composed of meter concentrators and collectors, which automatically collects, processes, and transmits electricity consumption data from multiple meters to enable remote monitoring and management. The collection methods mainly include timed collection, real-time collection, and automatic data replenishment. The purpose of centralized data collection from electricity meters is to facilitate data integration, remote monitoring, and fault diagnosis.

[0003] Existing methods for centralized data collection from electricity meters typically involve collecting feedback information, comparing the collected data, and assessing the accuracy of the collected data based on the collection frequency. Finally, by identifying deviation data, accurate data collection from electricity meters is achieved. While this approach improves accuracy, it faces challenges when electricity meters are widely distributed, resulting in diverse operating environments and significant data discrepancies. Even with deviation data identification, the sheer variety of deviation data makes it difficult to efficiently collect data from all meters. This leads to slow centralized collection efficiency and an inability to determine the timing of centralized collection based on the actual collection status of the electricity meters, resulting in data distortion. For example, as illustrated in patent application CN117499816A... The previous paper disclosed a data acquisition method for electricity meters based on HPLC communication. This method involves determining deviation data information by comparing and acquiring sub-task information, corresponding acquisition frequency information, and acquisition reference characteristic data of the electricity meter, matching and obtaining feedback information, and finally uploading the feedback information to the control backend. Other centralized acquisition methods for electricity meter data usually focus on improving acquisition stability. However, they still cannot solve the problem of inefficient centralized acquisition of all electricity meters when the electricity meters are widely distributed, resulting in various operating environments and large differences in the acquired data. This leads to slow centralized acquisition efficiency and the inability to determine the centralized acquisition time based on the actual acquisition status of the electricity meters, causing data acquisition distortion. Therefore, it is necessary to improve the existing centralized acquisition methods for electricity meter data. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art by proposing a centralized data acquisition method for multi-node electricity meters. This method addresses the issue that existing centralized data acquisition methods for electricity meters cannot efficiently collect data from all meters when the electricity meters are widely distributed, resulting in various operating environments and significant differences in the collected data. This leads to slow centralized acquisition efficiency and the inability to determine the centralized acquisition time based on the actual acquisition status of the electricity meters, resulting in data acquisition distortion.

[0005] To achieve the above objectives, this application provides a centralized data collection method for multi-node energy meters, comprising the following steps:

[0006] Acquire location data and information collection data of all electricity meters within the collection range; based on the information collection data of each electricity meter, use regional analysis and grade analysis to divide all electricity meters into regions and collection grades, and obtain multiple centralized collection areas based on the regional division, and classify all electricity meters based on the collection grade division. Among them, the centralized collection areas include special mode areas, regular mode areas, high intensity areas and low intensity areas.

[0007] Based on the location data of all centralized collection areas and each electricity meter, the centralized collection range of electricity meters corresponding to each collection level is obtained. The collection levels include high-meter, low-meter, and conventional meters.

[0008] The total collection interval is obtained based on all centralized collection intervals, and the electricity meter is centrally collected based on the centralized collection intervals and the total collection interval.

[0009] Furthermore, the location data and information collection data of all electricity meters within the collection range include:

[0010] The area where all the electricity meters collecting data are located is recorded as the collection range; the geographical locations of all the electricity meters collecting data within the collection range are obtained based on the map and recorded as the location data of the electricity meters;

[0011] For any given electricity meter: based on the data fed back from the location of the electricity meter during data acquisition, the metering data collected from the electricity meter is recorded as the core acquisition data, and the operating status and communication status fed back from the electricity meter are recorded as the auxiliary acquisition data. Among these, the core acquisition data and the auxiliary acquisition data are recorded as the information acquisition data of the electricity meter.

[0012] Furthermore, regional analysis methods include:

[0013] For any electricity meter: obtain all historical data corresponding to the operating status and communication status in the auxiliary acquisition data of the electricity meter, and record them as operating historical data and communication historical data respectively;

[0014] For historical operation data: obtain the number of abnormal events that occurred in the electricity meter in the historical operation data and record it as n. Abnormal events include power outages, overloads, and short circuits. Record the total operating time of the electricity meter in the historical operation data as T and the number of operating modes of the electricity meter as u. Record the value of T divided by u as the average mode duration.

[0015] Establish a Cartesian coordinate system, denoted as the operational analysis coordinate system. In the X-axis of the operational analysis coordinate system, the u coordinate points to the right of the origin are the names of all operating modes of the energy meter, and the unit of the Y-axis is h. With the name of the energy meter's operating mode as the abscissa and the time the energy meter was in the operating mode in the historical data as the ordinate, obtain the corresponding points for all operating modes of the energy meter in the operational analysis coordinate system and record them as mode time points.

[0016] The curve obtained by fitting all mode time points is recorded as the mode operation curve, and the straight line Y = average mode duration is recorded as the average measurement line in the operation analysis coordinate system; the area formed by the mode operation curve, the X-axis, X = 0 and X = u is recorded as the mode operation area, the area of ​​the mode operation area above the average measurement line is recorded as R1, the area of ​​the mode operation area below the average measurement line is recorded as R2, and the value of R1 divided by R2 is recorded as the mode operation ratio of the energy meter.

[0017] Furthermore, regional analysis methods also include:

[0018] For communication history data: Establish a Cartesian coordinate system, denoted as the signal analysis coordinate system, where the unit of the X-axis of the signal analysis coordinate system is h and the unit of the Y-axis is dB; Based on the signal strength of the electricity meter in the communication history data, plot the time for monitoring the signal strength of the electricity meter and the curve corresponding to the signal strength of the electricity meter during monitoring in the signal analysis coordinate system, and denot it as the signal strength curve;

[0019] The average of the ordinates of the highest and lowest points in the signal strength curve is denoted as D1; ​​the signal strength curve is fitted to a line segment, and the abscissa of the midpoint of the line segment is denoted as D2. The average of D1 and D2 is denoted as the average signal strength of the electricity meter.

[0020] Furthermore, regional analysis methods also include:

[0021] The average of the operating mode ratios of all energy meters is recorded as E1, and the average of the average signal strengths of all energy meters is recorded as E2; energy meters with an operating mode ratio greater than or equal to E1 are recorded as special mode meters, and energy meters with an operating mode ratio less than E1 are recorded as regular mode meters.

[0022] Electricity meters with an average signal strength greater than or equal to E2 are designated as high-intensity meters, and those with an average signal strength less than E2 are designated as low-intensity meters. The smallest circle enclosing all special-mode meters, regular-mode meters, high-intensity meters, and low-intensity meters on the map is obtained and designated as special-mode area, regular-mode area, high-intensity area, and low-intensity area, respectively.

[0023] Furthermore, the ranking analysis method includes:

[0024] For any electricity meter: Establish a Cartesian coordinate system, denoted as the metering analysis coordinate system, where the unit of the X-axis is h and the unit of the Y-axis is kWh; based on the core data collected by the electricity meter, plot the corresponding curves in the metering analysis coordinate system for the time of data collection and the corresponding electricity amount, and denot them as the metering data curve; denote the point with the largest slope in the metering data curve as point K, and denote the slope of point K as the metering slope;

[0025] The number of points in the measurement data curve whose slope is the measurement slope is denoted as j, and the product of j and the measurement slope is denoted as the measurement evaluation value.

[0026] Furthermore, the ranking analysis method also includes:

[0027] Obtain the metering slope and metering evaluation value of all electricity meters, and record the average of all metering slopes as the metering average value, and the average of all metering evaluation values ​​as the metering evaluation average value.

[0028] Electricity meters with a measurement slope greater than or equal to the average measurement value and a measurement evaluation value greater than or equal to the average measurement evaluation value are designated as high-meter meters; electricity meters with a measurement slope less than the average measurement value and a measurement evaluation value less than the average measurement value are designated as low-meter meters.

[0029] Electricity meters that are not recorded as high-meter or low-meter meters are recorded as conventional electricity meters.

[0030] Furthermore, based on the location data of all centralized collection areas and each electricity meter, the centralized collection intervals of the electricity meters corresponding to each collection level are obtained, including:

[0031] For any centralized collection area: Based on the location data of all electricity meters, obtain all electricity meters existing in the centralized collection area and record them as regional electricity meters; When the centralized collection area is a special mode area, set the provisional collection time of the electricity meters in the centralized collection area as the start time of the high-energy mode of the electricity meters, where the high-energy mode is the abscissa corresponding to the mode time point with the largest ordinate in the operation analysis coordinate system of the electricity meters.

[0032] When the centralized data collection area is a normal mode area, the provisional data collection time of the electricity meters in the centralized data collection area is set to the time when the electricity meters switch operating modes.

[0033] When the centralized collection area is a high-intensity area, the provisional collection time of the electricity meter in the centralized collection area is set as the high operating time of the electricity meter. The high operating time is the time within 24 hours corresponding to the horizontal axis of the peak in the signal strength curve of the electricity meter.

[0034] When the centralized collection area is a low-intensity area, the provisional collection time of the electricity meter in the centralized collection area is set as the low operating time of the electricity meter. The low operating time is the time within 24 hours corresponding to the horizontal axis of the trough in the signal strength curve of the electricity meter.

[0035] Furthermore, based on the location data of all centralized collection areas and each electricity meter, obtaining the centralized collection interval of the electricity meter corresponding to each collection level also includes:

[0036] For any collection level, the closed interval formed by the maximum and minimum values ​​of all provisional collection times corresponding to all energy meters is denoted as the centralized collection interval of all energy meters corresponding to the collection level.

[0037] Furthermore, the process of obtaining the total collection interval based on all centralized collection intervals, and then performing centralized data collection from the electricity meter based on both the centralized collection intervals and the total collection interval, includes:

[0038] When there are overlapping time intervals among all centralized collection intervals, the overlapping time intervals are recorded as the total collection interval, and the centralized collection intervals that include the total collection interval are recorded as the phased collection intervals.

[0039] For centralized collection intervals that are recorded as phased collection intervals: data is collected from all electricity meters corresponding to the centralized collection intervals during the time periods that are recorded as total collection intervals and during the time periods that are not recorded as total collection intervals.

[0040] For centralized collection intervals that are not recorded as eligible for phased data collection: Data is collected from the electricity meters corresponding to the centralized collection intervals within the centralized collection intervals.

[0041] The beneficial effects of this invention are as follows: This application first acquires the location data and information collection data of all electricity meters within the collection range; based on the information collection data of each electricity meter, it uses regional analysis and hierarchical analysis to divide all electricity meters into regions and collection levels, and obtains multiple centralized collection areas based on the regional division. Based on the collection level division, all electricity meters are classified. The advantage of this approach is that by using regional analysis to divide the electricity meters into regions, it is possible to effectively divide the areas where the electricity meters are located, especially when there are a large number of electricity meters to be collected and they are widely distributed. This ensures that the electricity meters in each region are in a relatively consistent collection environment, thereby eliminating the influence of the operating environment on the centralized collection of electricity meters and ensuring that each electricity meter is collected within a time period that conforms to its own operating characteristics. Furthermore, by using hierarchical analysis to divide the collection levels, it is possible to effectively divide the electricity meters based on their data collection status, thus uniformly collecting data from the same type of electricity meters during centralized collection, achieving efficient centralized collection of all electricity meters based on their actual collection status.

[0042] This application also obtains the centralized collection interval for each collection level of electricity meter based on the location data of all centralized collection areas and each electricity meter; finally, it obtains the total collection interval based on all centralized collection intervals, and performs centralized data collection on the electricity meters based on the centralized collection interval and the total collection interval. The advantage of this is that by obtaining the centralized collection interval and the total collection interval, after analyzing the environment where the electricity meter is located and the data collected by the electricity meter, the data collection time period corresponding to each type of electricity meter can be obtained, so as to realize centralized collection of different types of electricity meters. At the same time, the centralized collection time period is the time period when the operating characteristics of the electricity meter are more obvious, thereby effectively preventing the distortion of the data collection of the electricity meter. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating the steps of the method of the present invention;

[0044] Figure 2 This is a schematic diagram of the operating curve of the present invention;

[0045] Figure 3 This is a schematic diagram illustrating the acquisition of the total acquisition range in this invention;

[0046] Figure 4 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Example 1, please refer to Figure 1 As shown, this application provides a centralized data acquisition method for multi-node energy meters, including the following steps:

[0049] Step S1: Obtain the location data and information collection data of all electricity meters within the collection range; based on the information collection data of each electricity meter, use the regional analysis method and the level analysis method to divide all electricity meters into regions and collection levels, and obtain multiple centralized collection areas based on the regional division, and classify all electricity meters based on the collection level division. Among them, the centralized collection areas include special mode areas, regular mode areas, high intensity areas and low intensity areas.

[0050] Step S1 includes: Step S101, recording the area where all the electricity meters collecting data are located as the collection range; obtaining the geographical locations of all the electricity meters collecting data within the collection range based on the map, and recording them as the location data of the electricity meters;

[0051] Step S102: For any electricity meter: Based on the data fed back from the location of the electricity meter during data acquisition, the metering data collected from the electricity meter is recorded as core acquisition data, and the operating status and communication status fed back from the electricity meter are recorded as auxiliary acquisition data. Among them, the core acquisition data and auxiliary acquisition data are recorded as the information acquisition data of the electricity meter.

[0052] In the specific implementation process, this embodiment only analyzes the operating status and communication status fed back by the electricity meter. If there are large environmental differences between the electricity meters that are actually collecting data, such as large temperature differences or large humidity differences in the environment, environmental status can be added to the auxiliary data collection to achieve more-dimensional analysis of the electricity meter and ensure the accuracy of the area division of the electricity meter during subsequent centralized data collection.

[0053] Step S103, the area analysis method includes: Step S1031, for any energy meter: obtain all historical data corresponding to the operating status and communication status in the auxiliary acquisition data of the energy meter, and record them as operating historical data and communication historical data respectively;

[0054] Step S1032, for historical operation data: obtain the number of abnormal events that occurred in the electricity meter in the historical operation data and record it as n, where abnormal events include power outage, overload and short circuit; record the total operation time of the electricity meter in the historical operation data as T, and record the number of working modes of the electricity meter as u; record the value of T divided by u as the average mode duration;

[0055] In the specific implementation process, it is assumed that all electricity meters have the same number of operating modes. For example, in one analysis, it is found that the operating mode of an electricity meter is controlled by the electricity price at different times, that is, the electricity price is the same from 7:00 to 18:00, the electricity price is the same from 18:00 to 22:00, and the electricity price is the same from 22:00 to 7:00, and the electricity price at different times is different. Then the number of operating modes of the electricity meter is 3, that is, the value of u is 3. If the total operating time of the electricity meter is 300h, then the average mode duration can be calculated to be 100h.

[0056] Step S1033: Establish a Cartesian coordinate system, denoted as the operation analysis coordinate system. In the X-axis of the operation analysis coordinate system, the u coordinate points to the right of the origin are the names of all working modes of the energy meter, and the unit of the Y-axis is h. With the name of the working mode of the energy meter as the abscissa and the time when the energy meter is working in the working mode in the operation history data as the ordinate, obtain the corresponding points of all working modes of the energy meter in the operation analysis coordinate system and record them as mode time points.

[0057] In the specific implementation process, for example, during a data analysis, the names of all the working modes of the electricity meter are daytime mode, evening mode and nighttime mode, and the corresponding working times of the electricity meter are 1200h, 600h and 1000h, respectively. Then the mode time points can be marked as (daytime mode, 1200h), (evening mode, 600h), (nighttime mode, 1000h).

[0058] Step S1034: The curves obtained by fitting all mode time points are recorded as mode operation curves, and the straight line Y = average mode duration is recorded as the average measurement line in the operation analysis coordinate system; the area formed by the mode operation curve, the X-axis, X = 0 and X = u is recorded as the mode operation area; the area of ​​the mode operation area above the average measurement line is recorded as R1, the area of ​​the mode operation area below the average measurement line is recorded as R2, and the value of R1 divided by R2 is recorded as the mode operation ratio of the energy meter.

[0059] In the specific implementation process, for example, during a data analysis, the obtained pattern operation curve is as follows: Figure 2As shown by the curve MY, and the average measurement line is a straight line PH, it can be determined through analysis that region MX is the mode operation region, the area of ​​region MM1 is R1, and the area of ​​region MM2 is R2. By obtaining R1 and R2, the operating status of each operating mode of the energy meter can be obtained. If the ratio of R1 to R2 is large, it indicates that there are points in the mode operation curve with a large difference between the vertical axis and the average mode duration, that is, there are one or more operating modes in the energy meter with a long operating time. If the ratio of R1 to R2 is small, it indicates that the points with higher vertical axes in the mode operation curve have a small difference from the average mode duration, and the operating time of all operating modes in the energy meter is relatively average. Thus, the energy meter can be initially classified.

[0060] The regional analysis method also includes: step S1035, for communication history data: establish a plane rectangular coordinate system, denoted as the signal analysis coordinate system, wherein the unit of the X-axis of the signal analysis coordinate system is h, and the unit of the Y-axis is dB; based on the signal strength of the electricity meter in the communication history data, plot the time for monitoring the signal strength of the electricity meter and the curve corresponding to the signal strength of the electricity meter during monitoring in the signal analysis coordinate system, and denot it as the signal strength curve;

[0061] Step S1036: The average of the ordinates of the highest and lowest points in the signal strength curve is recorded as D1; ​​the signal strength curve is fitted into a line segment, and the abscissa of the midpoint of the line segment is recorded as D2; the average of D1 and D2 is recorded as the average signal strength of the energy meter.

[0062] In the specific implementation process, by determining the average signal strength by D1 and D2, the average signal strength can better match the average value of the signal strength in the signal strength curve. That is, the maximum and minimum points of the vertical axis in the signal strength curve are taken into account, ensuring that the average signal strength matches the average value of the actual signal of the electricity meter.

[0063] The regional analysis method also includes: step S1037, recording the average of the mode operation ratio of all energy meters as E1, and the average of the average signal strength of all energy meters as E2; recording energy meters with a mode operation ratio greater than or equal to E1 as mode special meters, and recording energy meters with a mode operation ratio less than E1 as mode regular meters.

[0064] Step S1038: Record the electricity meters with an average signal strength greater than or equal to E2 as high-intensity meters, and record the electricity meters with an average signal strength less than E2 as low-intensity meters; obtain the smallest circle that encloses all mode special meters, mode regular meters, high-intensity meters and low-intensity meters in the map, and record them as mode special area, mode regular area, high-intensity area and low-intensity area respectively.

[0065] In the specific implementation process, by acquiring special mode areas, normal mode areas, high intensity areas, and low intensity areas, the area where the electricity meter is located can be divided based on the operating status of the electricity meter's operating mode and the signal strength of the electricity meter. This makes it easier to delineate corresponding areas for different types of electricity meters, thereby achieving centralized data collection.

[0066] Step S104, the grade analysis method includes: Step S1041, for any electricity meter: establish a plane rectangular coordinate system, and denot it as the metering analysis coordinate system, where the unit of the X-axis of the metering analysis coordinate system is h, and the unit of the Y-axis is kWh; based on the core data collected by the electricity meter, for the time of the metering data collection and the electricity corresponding to the collected metering data, draw the corresponding curve in the metering analysis coordinate system, and denot it as the metering data curve; denot the point with the largest slope in the metering data curve as point K, and denot the slope of point K as the metering slope;

[0067] In the specific implementation process, for example, if the slope of point K is 2 during a data analysis, and there are 4 points with a slope of 2 in the metering data curve, then the metering evaluation value can be recorded as 8. In this embodiment, the larger the metering slope, the greater the maximum rate of change of the electricity recorded by the electricity meter, and the larger the metering evaluation value, the more frequent the rate of change of the electricity recorded by the electricity meter.

[0068] Step S1042: The number of points in the measurement data curve whose slope is the measurement slope is recorded as j, and the product of j and the measurement slope is recorded as the measurement evaluation value.

[0069] Step S1043: Obtain the metering slope and metering evaluation value of all electricity meters, and record the average of all metering slopes as the metering average value and the average of all metering evaluation values ​​as the metering evaluation average value.

[0070] Step S1044: Electricity meters with a measurement slope greater than or equal to the average measurement value and a measurement judgment value greater than or equal to the average measurement judgment value are recorded as high-meter meters; electricity meters with a measurement slope less than the average measurement value and a measurement judgment value less than the average measurement judgment value are recorded as low-meter meters.

[0071] In the specific implementation process, the larger the metering slope and the larger the metering evaluation value, the larger the overall rate of change of the electricity recorded by the electricity meter. Therefore, the electricity meter can be recorded as a high metering meter to facilitate subsequent classification and centralized data collection. Low metering meters and conventional electricity meters correspond to electricity meters with smaller overall rates of change of electricity and more average overall rates of change of electricity.

[0072] Step S1045: Record the electricity meters that are not recorded as high-meter or low-meter meters as regular electricity meters.

[0073] Step S2: Based on the location data of all centralized collection areas and each electricity meter, obtain the centralized collection range of electricity meters corresponding to each collection level. The collection level includes high metering meters, low metering meters and conventional metering meters.

[0074] Step S2 includes: Step S201, for any centralized collection area: based on the location data of all electricity meters, acquire all electricity meters existing in the centralized collection area and record them as regional electricity meters; when the centralized collection area is a special mode area, set the provisional collection time of the electricity meters in the centralized collection area as the start time of the high-energy mode of the electricity meters, wherein the high-energy mode is the abscissa corresponding to the mode time point with the largest ordinate in the operation analysis coordinate system of the electricity meters;

[0075] In the specific implementation process, the provisional collection time of the electricity meters in each centralized collection area conforms to the time point when the electricity meters in each centralized collection area are most affected by the auxiliary collection data. In actual application, the provisional collection time of the electricity meters in each centralized collection area can be set based on the actual situation of each centralized collection area.

[0076] Step S202: When the centralized collection area is a normal mode area, the provisional collection time of the electricity meter in the centralized collection area is set to the time when the electricity meter switches the operating mode.

[0077] Step S203: When the centralized collection area is a high-intensity area, the provisional collection time of the electricity meter in the centralized collection area is set as the high operating time of the electricity meter, wherein the high operating time is the time within 24 hours corresponding to the horizontal axis of the peak in the signal strength curve of the electricity meter.

[0078] Step S204: When the centralized collection area is a low-intensity area, the provisional collection time of the electricity meter in the centralized collection area is set as the low operating time of the electricity meter, wherein the low operating time is the time within 24 hours corresponding to the horizontal axis of the trough in the signal strength curve of the electricity meter.

[0079] Step S205: For all energy meters corresponding to any acquisition level: the closed interval formed by the maximum and minimum values ​​among all provisional acquisition times corresponding to all energy meters is recorded as the centralized acquisition interval of all energy meters corresponding to the acquisition level.

[0080] In the specific implementation process, for example, during a data analysis, the provisional collection times for all energy meters corresponding to high-meter levels are 18h, 19h, 18h, 20h, 21h, 20h, 21h, and 22h, respectively. Then, the centralized collection interval for all energy meters corresponding to high-meter levels can be set to [18h, 22h]. That is, in subsequent centralized collection, all energy meters with high-meter levels will be collected centrally within the interval [18h, 22h].

[0081] Step S3: Obtain the total collection interval based on all centralized collection intervals, and perform centralized data collection on the electricity meter based on the centralized collection intervals and the total collection interval.

[0082] Step S3 includes: Step S301, when there are overlapping time intervals among all centralized collection intervals, the overlapping time intervals are recorded as the total collection interval, and the centralized collection intervals containing the total collection interval are recorded as the stageable collection intervals.

[0083] Step S302: For the centralized collection intervals that are recorded as phased collection intervals: collect data from all electricity meters corresponding to the centralized collection intervals during the time periods that are recorded as total collection intervals and during the time periods that are not recorded as total collection intervals.

[0084] In a specific implementation process, for example, during a data analysis, if the centralized data collection interval corresponding to the high-level meter is [18h, 22h], and the centralized data collection interval corresponding to the low-level meter is [21h, 7h], then it can be derived from... Figure 3 The total collection interval is [21h, 22h]. The concentrated collection intervals for high-level and low-level meters can be recorded as the phased collection intervals. Concentrated collection is performed on all energy meters with high collection levels in [18h, 21h) and [21h, 22h], and on all energy meters with low collection levels in [21h, 22h] and [22h, 7h], respectively. The advantage of this is that an additional concentrated collection can be performed during the time period when energy meters with multiple collection levels are being collected simultaneously, so as to collect more accurate collection information and make the concentrated collection more comprehensive.

[0085] Step S303: For centralized collection intervals that are not recorded as eligible for phased data collection: Data is collected from the electricity meters corresponding to the centralized collection intervals within the centralized collection intervals.

[0086] Example 2, please refer to Figure 4 As shown, Figure 4A schematic diagram of an electronic device is provided, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, which the processor can call. When the processor executes a computer-readable instruction, it performs steps similar to those in a centralized data acquisition method for multi-node energy meters to achieve the following functions: First, it acquires the location data and information acquisition data of all energy meters within the acquisition range; based on the information acquisition data of each energy meter, it uses regional analysis and hierarchical analysis to divide all energy meters into regions and acquisition levels, and obtains multiple centralized acquisition regions based on the regional divisions, and classifies all energy meters based on the acquisition level divisions; then, based on all centralized acquisition regions and the location data of each energy meter, it obtains the centralized acquisition interval corresponding to each acquisition level; finally, it obtains the total acquisition interval based on all centralized acquisition intervals, and performs centralized data acquisition from the energy meters based on the centralized acquisition intervals and the total acquisition interval.

[0087] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0088] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute a centralized data acquisition method for multi-node energy meters provided by the above methods. The method includes: first, acquiring the location data and information acquisition data of all energy meters within the acquisition range; based on the information acquisition data of each energy meter, using regional analysis and hierarchical analysis methods to divide all energy meters into regions and acquisition levels, and obtaining multiple centralized acquisition regions based on the regional division, and classifying all energy meters based on the acquisition level division; then, based on all centralized acquisition regions and the location data of each energy meter, acquiring the centralized acquisition interval of the energy meter corresponding to each acquisition level; finally, acquiring the total acquisition interval based on all centralized acquisition intervals, and performing centralized data acquisition of the energy meters based on the centralized acquisition intervals and the total acquisition interval.

[0089] Example 4: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the steps of the above-described method for centralized acquisition of multi-node energy meter data to achieve the following functions: First, it acquires the location data and information acquisition data of all energy meters within the acquisition range; based on the information acquisition data of each energy meter, it uses regional analysis and hierarchical analysis to divide all energy meters into regions and acquisition levels, and obtains multiple centralized acquisition areas based on the regional division, and classifies all energy meters based on the acquisition level division; then, based on all centralized acquisition areas and the location data of each energy meter, it acquires the centralized acquisition interval of the energy meter corresponding to each acquisition level; finally, it acquires the total acquisition interval based on all centralized acquisition intervals, and performs centralized data acquisition of the energy meters based on the centralized acquisition intervals and the total acquisition interval.

[0090] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0091] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for centralized data collection from multi-node energy meters, characterized in that, Includes the following steps: Acquire location data and information collection data of all electricity meters within the collection range; based on the information collection data of each electricity meter, use regional analysis and grade analysis to divide all electricity meters into regions and collection grades, and obtain multiple centralized collection areas based on the regional division, and classify all electricity meters based on the collection grade division. Among them, the centralized collection areas include special mode areas, regular mode areas, high intensity areas and low intensity areas. Based on the location data of all centralized collection areas and each electricity meter, the centralized collection range of electricity meters corresponding to each collection level is obtained. The collection levels include high-meter, low-meter, and conventional meters. The total collection interval is obtained based on all centralized collection intervals, and the electricity meter is centrally collected based on the centralized collection intervals and the total collection interval.

2. The method for centralized data collection from multi-node energy meters according to claim 1, characterized in that, The location data and information collected for all electricity meters within the collection range include: The area where all the electricity meters collecting data are located is recorded as the collection range; the geographical locations of all the electricity meters collecting data within the collection range are obtained based on the map and recorded as the location data of the electricity meters; For any given electricity meter: based on the data fed back from the location of the electricity meter during data acquisition, the metering data collected from the electricity meter is recorded as the core acquisition data, and the operating status and communication status fed back from the electricity meter are recorded as the auxiliary acquisition data. Among these, the core acquisition data and the auxiliary acquisition data are recorded as the information acquisition data of the electricity meter.

3. The method for centralized data collection from multi-node energy meters according to claim 2, characterized in that, Regional analysis methods include: For any electricity meter: obtain all historical data corresponding to the operating status and communication status in the auxiliary acquisition data of the electricity meter, and record them as operating historical data and communication historical data respectively; For historical operation data: obtain the number of abnormal events that occurred in the electricity meter in the historical operation data and record it as n. Abnormal events include power outages, overloads, and short circuits. Record the total operating time of the electricity meter in the historical operation data as T and the number of operating modes of the electricity meter as u. Record the value of T divided by u as the average mode duration. Establish a Cartesian coordinate system, denoted as the operational analysis coordinate system. In the X-axis of the operational analysis coordinate system, the u coordinate points to the right of the origin are the names of all operating modes of the energy meter, and the unit of the Y-axis is h. With the name of the energy meter's operating mode as the abscissa and the time the energy meter was in the operating mode in the historical data as the ordinate, obtain the corresponding points for all operating modes of the energy meter in the operational analysis coordinate system and record them as mode time points. The curve obtained by fitting all mode time points is recorded as the mode operation curve, and the straight line Y = average mode duration is recorded as the average measurement line in the operation analysis coordinate system; the area formed by the mode operation curve, the X-axis, X = 0 and X = u is recorded as the mode operation area, the area of ​​the mode operation area above the average measurement line is recorded as R1, the area of ​​the mode operation area below the average measurement line is recorded as R2, and the value of R1 divided by R2 is recorded as the mode operation ratio of the energy meter.

4. The method for centralized data collection from multi-node energy meters according to claim 3, characterized in that, Regional analysis methods also include: For communication history data: Establish a Cartesian coordinate system, denoted as the signal analysis coordinate system, where the unit of the X-axis of the signal analysis coordinate system is h and the unit of the Y-axis is dB; Based on the signal strength of the electricity meter in the communication history data, plot the time for monitoring the signal strength of the electricity meter and the curve corresponding to the signal strength of the electricity meter during monitoring in the signal analysis coordinate system, and denot it as the signal strength curve; The average of the ordinates of the highest and lowest points in the signal strength curve is denoted as D1; ​​the signal strength curve is fitted to a line segment, and the abscissa of the midpoint of the line segment is denoted as D2. The average of D1 and D2 is denoted as the average signal strength of the electricity meter.

5. The centralized data acquisition method for multi-node energy meters according to claim 4, characterized in that, Regional analysis methods also include: The average of the operating mode ratios of all energy meters is recorded as E1, and the average of the average signal strengths of all energy meters is recorded as E2; energy meters with an operating mode ratio greater than or equal to E1 are recorded as special mode meters, and energy meters with an operating mode ratio less than E1 are recorded as regular mode meters. Electricity meters with an average signal strength greater than or equal to E2 are designated as high-intensity meters, and those with an average signal strength less than E2 are designated as low-intensity meters. The smallest circle enclosing all special-mode meters, regular-mode meters, high-intensity meters, and low-intensity meters on the map is obtained and designated as special-mode area, regular-mode area, high-intensity area, and low-intensity area, respectively.

6. The method for centralized data collection of multi-node energy meters according to claim 5, characterized in that, Hierarchical analysis includes: For any electricity meter: Establish a Cartesian coordinate system, denoted as the metering analysis coordinate system, where the unit of the X-axis is h and the unit of the Y-axis is kWh; based on the core data collected by the electricity meter, plot the corresponding curves in the metering analysis coordinate system for the time of data collection and the corresponding electricity amount, and denot them as the metering data curve; denote the point with the largest slope in the metering data curve as point K, and denote the slope of point K as the metering slope; The number of points in the measurement data curve whose slope is the measurement slope is denoted as j, and the product of j and the measurement slope is denoted as the measurement evaluation value.

7. The centralized data acquisition method for multi-node energy meters according to claim 6, characterized in that, The ranking analysis method also includes: Obtain the metering slope and metering evaluation value of all electricity meters, and record the average of all metering slopes as the metering average value, and the average of all metering evaluation values ​​as the metering evaluation average value. Electricity meters with a measurement slope greater than or equal to the average measurement value and a measurement evaluation value greater than or equal to the average measurement evaluation value are designated as high-meter meters; electricity meters with a measurement slope less than the average measurement value and a measurement evaluation value less than the average measurement value are designated as low-meter meters. Electricity meters that are not recorded as high-meter or low-meter meters are recorded as conventional electricity meters.

8. The method for centralized data collection of multi-node energy meters according to claim 7, characterized in that, Based on the location data of all centralized collection areas and each electricity meter, the centralized collection intervals for each collection level are obtained, including: For any centralized collection area: Based on the location data of all electricity meters, obtain all electricity meters existing in the centralized collection area and record them as regional electricity meters; When the centralized collection area is a special mode area, set the provisional collection time of the electricity meters in the centralized collection area as the start time of the high-energy mode of the electricity meters, where the high-energy mode is the abscissa corresponding to the mode time point with the largest ordinate in the operation analysis coordinate system of the electricity meters. When the centralized data collection area is a normal mode area, the provisional data collection time of the electricity meters in the centralized data collection area is set to the time when the electricity meters switch operating modes. When the centralized collection area is a high-intensity area, the provisional collection time of the electricity meter in the centralized collection area is set as the high operating time of the electricity meter. The high operating time is the time within 24 hours corresponding to the horizontal axis of the peak in the signal strength curve of the electricity meter. When the centralized collection area is a low-intensity area, the provisional collection time of the electricity meter in the centralized collection area is set as the low operating time of the electricity meter. The low operating time is the time within 24 hours corresponding to the horizontal axis of the trough in the signal strength curve of the electricity meter.

9. The centralized data acquisition method for multi-node energy meters according to claim 8, characterized in that, Based on the location data of all centralized collection areas and each electricity meter, obtaining the centralized collection range of the electricity meter corresponding to each collection level also includes: For any collection level, the closed interval formed by the maximum and minimum values ​​of all provisional collection times corresponding to all energy meters is denoted as the centralized collection interval of all energy meters corresponding to the collection level.

10. The method for centralized data collection of multi-node energy meters according to claim 9, characterized in that, The total collection interval is obtained based on all centralized collection intervals, and centralized data collection from the electricity meter is performed based on the centralized collection intervals and the total collection interval, including: When there are overlapping time intervals among all centralized collection intervals, the overlapping time intervals are recorded as the total collection interval, and the centralized collection intervals that include the total collection interval are recorded as the phased collection intervals. For centralized collection intervals that are recorded as phased collection intervals: data is collected from all electricity meters corresponding to the centralized collection intervals during the time periods that are recorded as total collection intervals and during the time periods that are not recorded as total collection intervals. For centralized collection intervals that are not recorded as eligible for phased data collection: Data is collected from the electricity meters corresponding to the centralized collection intervals within the centralized collection intervals.

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