A method and system for measuring and analyzing public transformer customer data and substation line loss

Abstract

The present invention discloses a method and system for measuring and analyzing public transformer customer data and substation line losses. The method includes: obtaining public transformer customer electricity meter data from a metering system, storing the electricity meter data in sequence through time tags, and obtaining an electricity meter database; calculating the electricity consumption of public transformer customers over a period of time to obtain first electricity consumption data, performing abnormal data calculation and data classification judgment based on the first data to obtain an abnormal data set; merging the abnormal data set with substation line loss data to perform line loss analysis on the substation. The solution of the present invention reduces a large amount of manual work through automation, improves the accuracy of data statistical judgment, and improves data analysis efficiency by integrating different types of calculation methods. By first statistically analyzing the abnormal data of public transformer customers and then merging it with the substation line loss for analysis, the working mode of manually passively discovering problems is changed, and at the same time, the cause of the substation abnormality can be quickly locked and judged, thereby reducing the cost of subsequent maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation, and in particular to a method and system for measuring and analyzing public transformer customer data and substation line losses. Background Art

[0002] During the work on the line losses in the public transformer substation during the same period, it was found that for the line losses in the substation during the same period: abnormal changes in customer power consumption in the system, new installation and replacement of meters and other data have some impact on the data in the line loss analysis of the metering system, and there are large deviations in the time of the electricity meter and the daily power consumption of public transformer customers are not easy to query. It is often necessary to query many modules of the metering system to obtain the above data, which makes it impossible for staff to make intuitive judgments during line loss analysis, which is time-consuming and labor-intensive.

[0003] Regarding customer service: If a customer's meter burns out, metering anomalies can occur, leading to excessively high electricity bills or significant power consumption anomalies. While the current system can capture on-site data, its monitoring and analysis capabilities are relatively weak. Manual screening and analysis are time-consuming and inefficient, leading to customer complaints regarding abnormal electricity bills. On-site meter verification by staff is inefficient, resulting in passive service and significant labor costs in communicating and explaining the situation to customers. Currently, the collection of various power consumption and line loss data is not only time-consuming and labor-intensive, but also prone to long-term repetitive work, resulting in missing data monitoring. Furthermore, the cause of the abnormality in the substation area cannot be quickly identified, leading to increased maintenance costs. Summary of the Invention

[0004] In view of the above-mentioned existing problems, the present invention is proposed. Therefore, the present invention provides a method for measuring and analyzing public transformer customer data and substation line losses to address the problems of traditional methods that require a lot of manual labor for statistical calculations, are difficult to query data, have long-term repetitive work leading to partial data monitoring loss, and are unable to quickly identify the cause of substation abnormalities, resulting in increased subsequent maintenance costs.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In a first aspect, the present invention provides a method for measuring and analyzing public transformer customer data and substation line losses, comprising:

[0007] Obtaining electricity meter data of public transformer customers in the metering system, wherein the electricity meter data is stored in sequence by time tags to obtain an electricity meter database;

[0008] Calculate the electricity consumption of the public transformer customer over a period of time to obtain first electricity consumption data, and perform abnormal data calculation and data classification judgment based on the first data to obtain an abnormal data set;

[0009] The abnormal data set is combined with the line loss data of the substation area to perform line loss analysis on the substation area.

[0010] As a preferred solution of the method for measuring and analyzing the customer data and line loss of a transformer area of the present invention, the electric energy meter data includes historical data, which is the data of the previous day;

[0011] Calculate the electricity consumption of the public transformer customer over a period of time to obtain first data, including:

[0012] The difference within a period of time is obtained by subtracting the historical data from the current day data, and the product of the difference and the transformer ratio is the first data.

[0013] As a preferred solution of the method for measuring and analyzing the customer data and line loss of the transformer area described in the present invention, wherein: abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, including abnormal calculation of customer power consumption, specifically including:

[0014] If the data for this month or last month does not exist, the first data is generated based on the data for the current day and the data for the previous day. If the first data is greater than a first threshold, the customer is determined to be a customer with abnormal electricity consumption.

[0015] If data for this month exists, the number of days of data for this month is read; if the number of days of data for this month is greater than a second threshold, the average power consumption for this month is calculated;

[0016] If the data for this month does not exist, then the number of days of data for the previous month is read; if the number of days of data for the previous month is greater than a second threshold, then the average power consumption for the previous month is calculated;

[0017] An abnormality judgment value is obtained, where the abnormality judgment value is the product of the average power consumption and the third threshold value. If the power consumption on that day is greater than the abnormality judgment value, it is considered abnormal, and the abnormal data is extracted into the abnormal data set.

[0018] As a preferred solution of the method for measuring and analyzing public transformer customer data and substation line loss of the present invention, wherein: abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, the method further includes:

[0019] The judgment of the data of newly installed and replaced meters specifically includes:

[0020] If the difference between the number of public change customers on that day and the number of public change customers in history is not 0, and there is no historical data, it is determined that the table is newly installed, and the newly installed customers are extracted to the abnormal data set;

[0021] Compare the customer's electricity user number and meter number in the public change customer data of the day with the historical public change customer data. If any number is inconsistent, it is determined that the customer has replaced the meter, and the new meter replacement customer is extracted to the abnormal data set.

[0022] As a preferred solution of the method for measuring and analyzing public transformer customer data and substation line loss of the present invention, wherein: abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, the method further includes:

[0023] The calculation of the electric energy meter time with large deviation or late return data includes:

[0024] Compare the return time of the public transformer customer's electricity meter data with the preset time point, and determine it as abnormal if it is later than the preset time point;

[0025] Reverse metering data, specifically including the reverse data base value of the day minus the historical reverse data base value multiplied by the transformer multiplier, to obtain the reverse metering data power consumption. If the power consumption of this part is not "0", it is judged as abnormal and triggers an abnormal warning prompt;

[0026] The forward power is calculated as a negative value, which is manifested as the first data being a negative value and is determined to be abnormal;

[0027] A customer in an area with no electricity consumption and low electricity consumption data, specifically including a customer whose first data is 0 or greater than 0 and less than a fourth threshold, is determined to be abnormal;

[0028] Extract various types of abnormal data and customers into abnormal data sets respectively.

[0029] As a preferred solution of the method for measuring and analyzing public transformer customer data and substation line losses described in the present invention, abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, and also includes a judgment on missing power data, specifically including, when calculating the first data, if any missing data of the day or historical data occurs, the customers involved are marked as missing, and the missing customers are extracted and stored in the abnormal data set.

[0030] As a preferred solution of the method for measuring and analyzing the public transformer customer data and the substation line loss of the present invention, wherein: combining the abnormal data set with the substation line loss data to perform line loss analysis on the substation, including:

[0031] Clean the line loss data of the substation area to obtain cleaned data;

[0032] Merge the cleaned data with the anomaly dataset, including,

[0033] Classify each abnormal data by station area and calculate the number of customers with each abnormal data;

[0034] The calculated number of customers is added to the cleaned data according to the abnormal category and named with the abnormal type name, and finally a data breakdown is formed for each substation, and the substation is marked according to the abnormal situation.

[0035] In a second aspect, the present invention provides a system for measuring and analyzing public transformer customer data and substation line losses, including an acquisition module for acquiring public transformer customer electric energy meter data of a metering system, wherein the electric energy meter data is sequentially stored by time tags to obtain an electric energy meter database;

[0036] An abnormal data judgment module is used to calculate the electricity consumption of the public transformer customer over a period of time to obtain first electricity consumption data, and perform abnormal data calculation and data classification judgment based on the first data to obtain an abnormal data set;

[0037] The substation line loss analysis module is used to combine the abnormal data set with the substation line loss data to perform line loss analysis on the substation area.

[0038] In a third aspect, the present invention provides a computing device, comprising:

[0039] memory and processor;

[0040] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for measuring and analyzing public transformer customer data and substation line losses are implemented.

[0041] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for measuring and analyzing public transformer customer data and substation line losses.

[0042] Compared with the existing technology, the present invention has the following beneficial effects: the solution of the present invention reduces a large amount of manual work through automation, improves the accuracy of data statistics, analysis, and judgment by integrating different types of calculation methods, reduces the differences in data judgment technology between departments, and improves the efficiency of data acquisition and analysis. By first collecting statistics on abnormal data of public transformer customers and then combining it with the line loss analysis of the substation, the previous working mode of manually discovering problems is changed to actively discover abnormal problems and issue early warnings. At the same time, it can quickly identify and determine the cause of the substation abnormality, reducing subsequent maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0044] Figure 1The figure is a schematic diagram of the overall process of the method for measuring and analyzing public transformer customer data and substation line loss according to one embodiment of the present invention. DETAILED DESCRIPTION

[0045] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0046] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0047] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0048] The present invention is described in detail with reference to schematic diagrams. For ease of illustration, cross-sectional views of device structures may be partially enlarged and not to scale when describing embodiments of the present invention. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0049] Furthermore, in the description of the present invention, it should be noted that the terms "upper, lower, inner, and outer" and other references to orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the systems or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0050] In this disclosure, unless otherwise specified or limited, the terms "mounted," "connected," and "connected" should be interpreted broadly. For example, they may refer to fixed, removable, or integral connections. They may also refer to mechanical, electrical, or direct connections, indirect connections through an intermediary, or internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in this disclosure.

[0051] Example 1

[0052] Reference Figure 1 , which is an embodiment of the present invention, provides a method for measuring and analyzing public transformer customer data and substation line losses, including:

[0053] S1: Obtain the electricity meter data of the public transformer customers in the metering system. The electricity meter data is stored in sequence by time tags to obtain the electricity meter database;

[0054] Furthermore, the electricity meter data includes historical data, which is the data of the previous day;

[0055] Preferably, the acquired electric energy meter data is base meter data;

[0056] It should be noted that in the process of obtaining data, the local data will first be checked to see if there is data from the previous day. If not, the data from the previous day will be obtained first, and then the data from the current day will be obtained to ensure the subsequent data calculation;

[0057] Also, each day's data is stored in sequence by time tags when it is saved, specifically:

[0058] Linked to "year, month, day", such as: today is "January 1, 2023". In terms of data saving: except for summary data which is saved with "01" as the month name, all other data are saved as "January 1, 2023", which is "today's" data. File reading is also linked to "year, month, day", but the difference is that, for example: today is "January 1, 2023", "01" appears in the month and "01" appears at the same time, then "yesterday's" data is: "December 31, 2022". For "yesterday's" data, the system will search in the folder corresponding to the date based on each month, year, and day.

[0059] It should be noted that the data file can be in Excel format, and the data can be directly and automatically input into this format file for subsequent calculations.

[0060] Calculate the electricity consumption of the public transformer customer over a period of time to obtain first data, including:

[0061] The difference within a period of time is obtained by subtracting the historical data from the current day data, and the product of the difference and the transformer multiplication factor is the first data.

[0062] It should be noted that the calculation of the first data is a preparation for the subsequent abnormal data prompting and data classification.

[0063] S2: Calculate the electricity consumption of the public transformer customer over a period of time to obtain first electricity consumption data, and perform abnormal data calculation and data classification based on the first data to obtain an abnormal data set;

[0064] Furthermore, abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, including abnormal calculation of customer power consumption, specifically including:

[0065] If the data for this month or last month does not exist, first data is generated based on the data for the current day and the data for the previous day. If the first data is greater than a first threshold, the customer is determined to be a customer with abnormal electricity consumption.

[0066] Preferably, the first threshold can be set to 50 degrees.

[0067] If data for this month exists, the number of days of data for this month is read. If the number of days of data for this month is greater than the second threshold, the average power consumption for this month is calculated.

[0068] If the data for this month does not exist, the number of days of data for the previous month is read. If the number of days of data for the previous month is greater than the second threshold, the average power consumption for the previous month is calculated.

[0069] Preferably, the second threshold can be set to 5 days;

[0070] It should be noted that the reading statistics for the number of days can be obtained through the len function.

[0071] Obtain an abnormal judgment value, which is the product of the average power consumption and the third threshold. If the power consumption on that day is greater than the abnormal judgment value, it is considered abnormal, and the abnormal data is extracted to the abnormal data set.

[0072] Preferably, the third threshold value can be set to 1.7. Normally, if the average power consumption is less than 60 degrees and greater than or equal to 40 degrees, the third threshold value is set to 1.7.

[0073] It should be noted that the less the electricity consumption, the larger the third threshold multiplied by it should be, and the more the electricity consumption, the smaller the third threshold multiplied by it should be.

[0074] Furthermore, abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, which also includes:

[0075] The judgment of the data of newly installed and replaced meters specifically includes:

[0076] If the difference between the number of public change customers on that day and the number of public change customers in history is not 0, and there is no historical data, it is determined that the table is newly installed, and the newly installed customers are extracted to the abnormal data set;

[0077] Compare the customer's electricity user number and meter number in the public change customer data of the day with the historical public change customer data. If any number is inconsistent, it is determined that the customer has replaced the meter, and the new meter replacement customer is extracted to the abnormal data set.

[0078] It should be noted that the reading statistics of the number of customers can be obtained through the len function.

[0079] Furthermore, abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, which also includes:

[0080] The calculation of the electric energy meter time with large deviation or late return data includes:

[0081] Compare the return time of the public transformer customer's electricity meter data with the preset time point, and determine it as abnormal if it is later than the preset time point;

[0082] It should be noted that deviations in time data can lead to time errors in the calculation of substation line losses, which is equivalent to errors in electricity consumption. Similarly, the metering system does not indicate this data. Only when obtaining the base data of the public transformer customer does this data have a return time, so the return time is used as the basis for judgment.

[0083] Preferably, the preset time can be set to a suitable time point such as 3:00 or 4:00.

[0084] Reverse metering data, specifically including the reverse data base value of the day minus the historical reverse data base value multiplied by the transformer multiplier, to obtain the reverse metering data power consumption. If the power consumption of this part is not "0", it is judged as abnormal and triggers an abnormal warning prompt;

[0085] It should be noted that the warning prompts generated by reverse metering data are due to metering anomalies (such as the meter is about to burn out) or customers moving the metering equipment on their own. They are the key targets for investigation in electricity inspections and substation line loss work.

[0086] The forward power calculation is negative, which is reflected as the first data being negative and is judged as abnormal;

[0087] It should be noted that any occurrence of this data is an abnormal warning, usually a precursor to meter failure, and is also a key focus of electricity inspections and line losses in substations.

[0088] A customer in an area with no electricity consumption and low electricity consumption data, specifically including a customer whose first data is 0 or greater than 0 and less than a fourth threshold, is determined to be abnormal;

[0089] It should be noted that during the electricity usage inspection, the above data must be checked first, as some of these customers may be engaging in "electricity theft".

[0090] Extract various types of abnormal data and customers into abnormal data sets respectively.

[0091] Furthermore, abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, which also includes judgment on missing power data. Specifically, when calculating the first data, if any missing data of the day or historical data occurs, the customers involved will be marked as missing, and the missing customers will be extracted and stored in the abnormal data set.

[0092] It should be noted that various types of abnormal data, missing data and customer-to-abnormal data sets can be extracted through the len function, and its main purpose is to facilitate subsequent statistics, aggregation and prompting.

[0093] S3: Combine the abnormal data set with the substation line loss data to perform line loss analysis on the substation area.

[0094] Furthermore, the abnormal data set is combined with the line loss data of the substation area to conduct line loss analysis of the substation area, including:

[0095] Clean the line loss data of the substation area to obtain cleaned data;

[0096] It should be noted that (1) during the cleaning process, the device address will be judged. If the device address appears twice in the entire data and the two numbers are the same, the two lines of data will be merged and placed in the last line of the entire data to form a line of "new data". At the same time, the "old data" will be deleted to avoid data duplication. (2) during the cleaning process, the device address will be judged. If the two lines of numbers are the same in the entire data but the device addresses are inconsistent, the two lines of data will be merged and placed in the last line of the entire data to form a line of "new data". At the same time, the "old data" will be deleted to avoid data duplication. (3) during the cleaning process, if key data, such as a device number, is found to be missing, it will be determined as a "new area" and its data will not be counted.

[0097] Merge the cleaned data with the anomaly dataset, including,

[0098] Classify each abnormal data by station area and calculate the number of customers with each abnormal data;

[0099] The calculated number of customers is added to the cleaned data according to the abnormal category and named with the abnormal type name, finally forming a data breakdown for each substation and marking it according to the abnormal situation of the substation.

[0100] It should be noted that the abnormal data can be classified by station area through the for function loop classification, and the number of customers of each abnormal data can be calculated through the len function.

[0101] It should also be noted that the method also includes data aggregation, which includes abnormal data aggregation and substation line loss aggregation.

[0102] Take Excel for example to summarize abnormal data:

[0103] First, it will determine whether there is a summary Excel sheet named after this month in the summary folder corresponding to this month. If not, it will be created. The data on the first day after creation will be the electricity consumption calculated after "today" and "yesterday", and the name corresponding to the header will be named after the date "today". If there is a summary Excel sheet named after this month in the summary folder corresponding to this month, the sheet will be read first, and then it will be determined whether the header of the last column of data is the date "today". If so, no summary will be performed; if not, the electricity consumption data calculated for "today" will be added to the last column of the Excel data corresponding to each household. For data marked with "new installation" and "change table", they will be placed in the last row of the table in order. For data marked with "change table", the original historical data row will be deleted after the data is placed to avoid data duplication; customers marked with "missing data" before summary will also be appended with "missing data".

[0104] Take Excel as an example to summarize the line loss data of the substation area:

[0105] The purpose of summarizing here is to facilitate viewing the trend of line loss data in abnormal substations. After the above content is completed, the Excel data in the path will be judged. First, if the "today" data is "01", a new Excel file will be created in the corresponding monthly folder to form the data details of each substation in rows. The data value is: basic data plus abnormality rate. At the same time, if the substation is abnormal, the abnormality rate will be marked in red, and the header will be changed to "today" date. If today's data is not "01", but there is no Excel file in the folder of this month, a new Excel will be created. If there is an Excel file in the folder of this month, the file will be read, and it will be determined whether the header date of the last column of the file is the same as the "today" date. If not, the data obtained from the statistical analysis of the line loss of the "today" substation will be used to extract the abnormality rate, add it in the last column according to the corresponding substation, and mark the abnormal substation in red at the line loss rate for prompting. During the statistical summary process, if the summary data for this month exists and the header date of the last column is different from today, the "Statistical Analysis of Line Loss in Today's Substation" data will be compared with the summary data. If the numbers are consistent, it means there is no newly installed data. If the numbers are inconsistent, the missing data in the summary table will be added to the last row, and the words "Newly Installed Substation" will be marked in the entire row as a reminder.

[0106] The above is a schematic diagram of a method for measuring and analyzing public transformer customer data and substation line losses according to this embodiment. It should be noted that the technical solution of this system for measuring and analyzing public transformer customer data and substation line losses is based on the same concept as the technical solution of the aforementioned method for measuring and analyzing public transformer customer data and substation line losses. For details not described in detail in the technical solution of the system for measuring and analyzing public transformer customer data and substation line losses according to this embodiment, please refer to the description of the technical solution of the aforementioned method for measuring and analyzing public transformer customer data and substation line losses.

[0107] The public transformer customer data and substation line loss measurement and analysis system in this embodiment includes:

[0108] The acquisition module is used to obtain the electricity meter data of the public transformer customers of the metering system. The electricity meter data is stored in sequence by time tags to obtain the electricity meter database;

[0109] An abnormal data judgment module is used to calculate the electricity consumption of the public transformer customer over a period of time to obtain first electricity consumption data, and perform abnormal data calculation and data classification judgment based on the first data to obtain an abnormal data set;

[0110] The substation line loss analysis module is used to combine the abnormal data set with the substation line loss data to perform line loss analysis on the substation area.

[0111] This embodiment further provides a computing device suitable for measuring and analyzing public transformer customer data and substation line losses, including:

[0112] Memory and processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the method for measuring and analyzing public transformer customer data and substation line losses as proposed in the above embodiment.

[0113] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the method for measuring and analyzing public transformer customer data and substation line losses as proposed in the above embodiment.

[0114] The storage medium proposed in this embodiment and the method for realizing the measurement and analysis of public transformer customer data and substation line loss proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0115] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented with the help of software and necessary general-purpose hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer's floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0116] Example 2

[0117] Referring to Table 1, an embodiment of the present invention provides a method for measuring and analyzing public transformer customer data and substation line losses. In order to verify its beneficial effects, a scientific demonstration is conducted through comparative experiments.

[0118] Table 1 Comparison results

[0119]

[0120] As can be seen from Table 1, prior to the invention, data monitoring for public transformer customers was performed manually by staff. For example, for 30,000 sets of data, to achieve a series of operations such as data monitoring, aggregation, and classification and storage, a staff member would need to spend 90 to 120 minutes per day to perform data export, Excel calculations, classification, aggregation, and other related operations. However, with the present invention, this part of the operation only takes about 5 minutes to achieve the purpose, and no manual intervention is required. In the statistical analysis of line loss data for the same period in the substation, manual statistical analysis of one abnormal substation takes about 30 minutes, while the present invention can complete the statistical analysis of 300 data in 2 minutes. This shows that traditional manual methods require a total of more than 150 minutes to achieve the same purpose as the present invention, especially when the number of substation line loss analyses is small. However, this invention only takes about 7 minutes. In terms of field work, if there is no data prompt to check abnormal metering and find the cause of the abnormality in the substation on a household basis, a substation with less than 100 households would take at least 3 days. However, the present invention uses a direct investigation method, which means that it can rely on data, without having to check each household, changing the previous practice of passively discovering abnormalities and directly investigating where the abnormal data appears.

[0121] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for measuring and analyzing public transformer customer data and area line loss, characterized in that: include: Obtaining electricity meter data of public transformer customers in the metering system, wherein the electricity meter data is stored in sequence by time tags to obtain an electricity meter database; Calculate the electricity consumption of the public transformer customer over a period of time to obtain first electricity consumption data, and perform abnormal data calculation and data classification judgment based on the first data to obtain an abnormal data set; The abnormal data set includes: abnormal customer power consumption data, new meter installation and replacement data, large deviation in electricity meter time or late return data data, and missing power data; Among them, the calculation of the data with large deviation or late return time of the electric energy meter includes: Compare the return time of the public transformer customer's electricity meter data with the preset time point, and determine it as abnormal if it is later than the preset time point; Reverse metering data, specifically including the reverse data base value of the day minus the historical reverse data base value multiplied by the transformer multiplier, to obtain the reverse metering data power consumption. If the power consumption of this part is not "0", it is judged as abnormal and triggers an abnormality warning prompt; The forward power is calculated as a negative value, which is manifested as the first data being a negative value and is determined to be abnormal; A customer in an area with no electricity consumption and low electricity consumption data, specifically including a customer whose first data is 0 or greater than 0 and less than a fourth threshold, is determined to be abnormal; Extract various types of abnormal data and customers to abnormal data sets respectively; Combine the abnormal data set with the area line loss data to perform line loss analysis on the area, including: Clean the line loss data of the substation area to obtain cleaned data; Merge the cleaned data with the anomaly dataset, including, Classify each abnormal data by station area and calculate the number of customers with each abnormal data; The calculated number of customers is added to the cleaned data according to the abnormal category and named with the abnormal type name, and finally a data breakdown is formed for each substation, and the substation is marked according to the abnormal situation.

2. The method for measuring and analyzing public transformer customer data and substation line loss according to claim 1, characterized in that: The electric energy meter data includes historical data, which is data from the previous day; Calculate the electricity consumption of the public transformer customer over a period of time to obtain the first data, including: The difference within a period of time is obtained by subtracting the historical data from the current day data, and the product of the difference and the transformer ratio is the first data.

3. The method for measuring and analyzing public transformer customer data and transformer area line loss according to claim 1 or 2, characterized in that: Abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, including abnormal customer power consumption calculation, specifically including: If the data for this month or last month does not exist, the first data is generated based on the data for the current day and the data for the previous day. If the first data is greater than a first threshold, the customer is determined to be a customer with abnormal electricity consumption. If data for this month exists, the number of days of data for this month is read; if the number of days of data for this month is greater than a second threshold, the average power consumption for this month is calculated; If the data for this month does not exist, then the number of days of data for the previous month is read; if the number of days of data for the previous month is greater than a second threshold, then the average power consumption for the previous month is calculated; An abnormality judgment value is obtained, where the abnormality judgment value is the product of the average power consumption and the third threshold value. If the power consumption on that day is greater than the abnormality judgment value, it is considered abnormal, and the abnormal data is extracted into the abnormal data set.

4. The method for measuring and analyzing public transformer customer data and transformer area line loss according to claim 3, characterized in that: Abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, which also includes: The judgment of data for newly installed and replaced meters specifically includes: If the difference between the number of public change customers on that day and the number of public change customers in history is not 0, and there is no historical data, it is determined that the table is newly installed, and the newly installed customers are extracted to the abnormal data set; Compare the customer's electricity user number and meter number in the public change customer data of the day with the historical public change customer data. If any number is inconsistent, it is determined that the customer has replaced the meter, and the new meter replacement customer is extracted to the abnormal data set.

5. The method for measuring and analyzing public transformer customer data and substation line loss according to claim 4, characterized in that: Abnormal data calculation and data classification judgment are performed based on the first data to obtain an abnormal data set, which also includes: judgment on missing power data, specifically including, when calculating the first data, if any missing data of the day or historical data occurs, the customers involved are marked as missing, and the missing customers are extracted and stored in the abnormal data set.

6. A system for measuring and analyzing public transformer customer data and substation line loss, applying the method according to any one of claims 1 to 5, characterized in that: include: An acquisition module is used to acquire the electric energy meter data of the public transformer customers of the metering system, wherein the electric energy meter data is stored in sequence by time tags to obtain an electric energy meter database; An abnormal data judgment module is used to calculate the electricity consumption of the public transformer customer over a period of time to obtain first electricity consumption data, and perform abnormal data calculation and data classification judgment based on the first data to obtain an abnormal data set; The substation line loss analysis module is used to combine the abnormal data set with the substation line loss data to perform line loss analysis on the substation area.

7. An electronic device comprising: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for measuring and analyzing public transformer customer data and substation line losses are implemented as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for measuring and analyzing public transformer customer data and substation line losses as claimed in any one of claims 1 to 5.

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