Monitoring method of single-phase intelligent electric energy meter error calibrating device

Abstract

The invention relates to the technical field of ammeter error monitoring, and discloses a monitoring method of a single-phase intelligent ammeter error calibrating device, which comprises the following steps: acquiring the electricity consumption of a target area and all target sub-areas, forming sub-electricity consumption data and total electricity consumption data, forming sub-area error data or area error data, determining a target judgment sub-area, and determining the error of the target judgment sub-area; according to the monitoring method of the single-phase intelligent electric energy meter error verification device, whether electricity consumption abnormity exists in the area or not is judged according to the electricity consumption of all the positions in the area and the electricity consumption of the whole area, and the single-phase intelligent electric energy meter error verification device is monitored according to the electricity consumption of all the positions in the area. According to the method, the reason for errors of the data collected by the electricity meter is determined, and missed judgment and misjudgment are reduced, so that the situation that when electricity consumption is abnormal, an area with abnormal electricity consumption cannot be prompted in time is avoided, potential safety hazards are reduced, and more serious electric power safety accidents are avoided.

Description

Technical Field

[0001] The invention relates to the technical field of electric meter error monitoring, and in particular to a monitoring method of an error detection device of a single-phase intelligent electric energy meter. Background Art

[0002] Single-phase smart energy meters are widely used in electricity measurement for households and small commercial users. With the development of smart grids, their position in the power market is becoming increasingly important. The monitoring method of the error verification device of single-phase smart energy meters has developed with the popularization of smart grids and smart energy meters. With the advancement of technology and the improvement of society's requirements for the accuracy of energy measurement, the verification and monitoring methods of energy meters will continue to be optimized and developed to ensure that they can still provide accurate and reliable measurement data in complex environments. Smart energy meters collect signals such as current and voltage and use a series of algorithms to measure electric energy in real time. Its intelligent features make data transmission and processing more efficient, but it also brings the problem that measurement accuracy needs to be further verified. The error of the energy meter may come from many aspects, including design defects of the meter itself, inconsistencies in manufacturing processes, environmental factors, changes in usage conditions, etc. These factors may cause deviations in the measurement of smart energy meters. Traditional calibration methods mostly use reference instruments such as mechanical or electric clocks to compare and calculate errors after measurement. This method is not only time-consuming, but also limited by the accuracy of manual operation, and it is difficult to ensure long-term stability and reliability. With the development of science and technology, more and more automated energy meter calibration devices have emerged. These devices can realize multi-point detection, automatic data collection, real-time monitoring, intelligent analysis and other functions, which greatly improves the efficiency and accuracy of calibration and adapts to the needs of modern power systems for high-precision measurement. The current monitoring method is not limited to the performance test of the equipment itself, but also extends to the monitoring of network environment, usage conditions, data communication and other aspects. This comprehensive monitoring ensures the accuracy of the energy meter while also ensuring the safety and stable operation of the smart grid. The existing monitoring method of the single-phase smart electricity meter error calibration device cannot judge whether there is abnormal electricity consumption in the area according to the electricity consumption in various places in the area and the overall electricity consumption in the area, and cannot judge whether there is error in the data collected by the electricity meter according to the electricity consumption in various places in the area and the overall electricity consumption in the area. It cannot determine the cause of the error in the data collected by the electricity meter according to the electricity consumption in various places in the area, and is prone to missed judgments and misjudgments, which leads to the failure to promptly prompt the area with abnormal electricity consumption when the electricity consumption is abnormal. There are certain safety hazards and its practicality has certain limitations. Summary of the invention

[0003] The present invention provides a monitoring method for a single-phase intelligent electric energy meter error detection device, which is used to promote the solution of the problems mentioned in the background technology.

[0004] The present invention provides the following technical solution: a monitoring method for a single-phase smart electric energy meter error detection device, comprising: Get the current power consumption of the target area and set it as the current power consumption of the area; Get all sub-regions in the target region and define them as target sub-regions; Execute the power consumption analysis strategy for each target sub-area to form sub-power consumption data; The sub-area power consumption data includes normal power consumption in the sub-area and abnormal power consumption in the sub-area; Execute regional analysis strategy for target areas to form total electricity consumption data; The total electricity consumption data includes normal electricity consumption in the target area and abnormal electricity consumption in the target area; If the power consumption in the sub-area is normal, the sub-area error determination strategy is executed to form sub-area error data; If the power consumption in the sub-area is abnormal but the power consumption in the target area is normal, the regional error determination strategy is executed to form regional error data; If the power consumption of the sub-region is abnormal and the power consumption of the target region is abnormal, the target sub-region is determined to have abnormal power consumption, and the target sub-region with abnormal power consumption of the determined target sub-region is obtained and identified as the target determination sub-region; According to the sub-region error data, a target sub-region where data collection of the target sub-region is biased is obtained and identified as the target determination sub-region; According to the regional error data, if it is determined that there is a deviation in the data collection of the target area, the target sub-area with abnormal power consumption in the determination sub-area in the target area is obtained and identified as the target determination sub-area; Execute the abnormal power consumption determination strategy on the target determination sub-area to form abnormal determination data; Based on the abnormal judgment data, determine the cause of abnormal power consumption and give corresponding abnormal prompts.

[0005] As an optional solution of the monitoring method of the single-phase smart energy meter error detection device of the present invention, the power consumption analysis strategy is specifically: Obtain the current power consumption of the target sub-area and define it as the power consumption of the sub-area; Get the current time point; Set the data collection duration; Calculate the data collection time point, data collection time point = current time point - data collection duration; The data collection time point is taken as the starting time and the current time point is taken as the ending time to form a data collection period; Set the collection period; Taking the data collection time point as the starting time, a data collection point is formed every collection cycle; Obtain the data collection time points of the target sub-area within the data collection period and the corresponding power consumption of each data collection point, which are defined as the sub-historical power consumption; Calculate the sub-determined electricity consumption, which is the sum of all sub-historical electricity consumption during the data collection period ÷ (the total number of data collection points during the data collection period + 1); If the power consumption of the sub-area is ≥ the sub-determined power consumption × (1 + 30%), the power consumption of the sub-area is determined to be abnormal; If the sub-area power consumption is less than the sub-determination power consumption × (1 + 30%), it is determined that the sub-area power consumption is normal.

[0006] As an optional solution of the monitoring method of the single-phase smart energy meter error detection device of the present invention, the regional analysis strategy is specifically: Get the current power consumption of the area; Get the data collection period and all data collection points; Obtain the data collection time points of the target area within the data collection period and the corresponding power consumption of each data collection point, which are defined as the historical power consumption of the area; Calculate the regional determined electricity consumption, regional determined electricity consumption = the sum of historical electricity consumption of all regions during the data collection period ÷ (the total number of data collection points during the data collection period + 1); If the current power consumption of the area ≥ the determined power consumption of the area × (1 + 30%), the target area is judged to have abnormal power consumption; If the current power consumption of the area is less than the determined power consumption of the area × (1 + 30%), the power consumption of the target area is determined to be normal.

[0007] As an optional solution of the monitoring method of the single-phase smart energy meter error detection device of the present invention, the sub-region error determination strategy is specifically as follows: Get all users in the target sub-area and define them as target users; Execute the user analysis strategy for each target user in the target sub-area; Obtaining power consumption determination data for each target user in the target sub-area; The power consumption determination data includes normal power consumption of the user and abnormal power consumption of the user; If all target users in the target sub-area are judged to have normal electricity consumption, the data collection of the target sub-area is judged to be normal, and no abnormal prompt is given at this time; If there is a target user in the target sub-area determined to be abnormal user electricity consumption, the target sub-area data collection is determined to be abnormal, and A1-A8 is executed; A1. Obtain target users who are determined to have abnormal electricity usage and define them as abnormal users; A2. Obtain the current power consumption and determined power consumption of the abnormal user; A3. Calculate the abnormal difference of abnormal users, abnormal difference = user's current power - user's determined power × (1 + 30%); A4. Obtain all target users except abnormal users in the target sub-area and define them as analysis users; A5. Obtain the current power consumption and user-determined power consumption of each analyzed user; A6. Calculate the difference in usage for each analyzed user. Difference in usage = user-determined power × (1-30%) - user's current power. The sum of all the underused differences in the target sub-area is defined as the total underused difference value; A7. If the total difference is greater than or equal to the abnormal difference, it is determined that there is a deviation in the data collection of the target sub-area, and the abnormal power consumption determination strategy is executed; A8. If the total difference is less than the abnormal difference, it is determined that the electric meter in the target sub-area is abnormal and needs to be repaired.

[0008] As an optional solution of the monitoring method of the single-phase smart energy meter error detection device of the present invention, the user analysis strategy is specifically: Get the current power consumption of the target user and set it as the current power consumption of the user; Get the data collection period and all data collection points; Obtain the data collection time points of the target user within the data collection period and the power consumption corresponding to each data collection point, which are defined as the user's historical power consumption; Calculate the user's determined power consumption, which is the sum of all users' historical power consumption during the data collection period / (the total number of data collection points during the data collection period + 1); If the user's current power consumption ≥ the user's determined power consumption × (1 + 30%), the user's power consumption is considered abnormal; If the user's current power consumption is less than the user's determined power consumption × (1 + 30%), the user's power consumption is determined to be normal.

[0009] As an optional solution of the monitoring method of the single-phase smart energy meter error detection device of the present invention, the regional error determination strategy is specifically: Obtain a target sub-region with abnormal power consumption in the target region and define it as an abnormal region; Obtaining the sub-region power consumption and sub-determination power consumption of the abnormal region, and defining them as abnormal sub-power consumption and abnormal sub-determination power consumption respectively; Calculate the regional anomaly difference of the abnormal area, regional anomaly difference = abnormal sub-power - abnormal sub-judgment power × (1 + 30%); Obtain all target sub-areas in the target area except the abnormal area and define them as the analysis area; Obtaining the sub-region power consumption and sub-determination power consumption of each analysis region, which are respectively defined as analysis sub-power consumption and analysis sub-determination power consumption; Calculate the regional underutilization difference of each analysis area, regional underutilization difference = analysis sub-determination power × (1-30%) - analysis sub-power; The sum of all regional underutilization differences within the target area is defined as the total regional underutilization difference; If the total regional difference value is greater than or equal to the regional abnormal difference value, it is determined that there is a deviation in the data collection of the target area; If the total regional difference is less than the regional abnormal difference, it is determined that the electric meter in the target area is abnormal and needs to be repaired.

[0010] As an optional solution of the monitoring method of the single-phase smart energy meter error detection device of the present invention, the abnormal power consumption determination strategy is specifically: Get the target determination sub-region; Obtain all users in the target determination sub-area and identify them as target users; Execute the user analysis strategy for each target user in the target determination sub-area; Extract target users whose power consumption is abnormal in the target determination sub-area and define them as abnormal users; Extract all electrical equipment of abnormal users and define them as analysis equipment; Obtain the interface location of the power supply line to which each analysis device is connected, and define it as the device location; Obtain the location of the power source of the power supply line and define it as the line power source location; Obtain the distance between each device location and the line power location, and define it as the power supply distance; Sort all analyzed devices from small to large according to the value of power supply distance to form a power consumption set; Extract the analysis equipment corresponding to the first element and the last element in the electricity consumption set, and define them as short-line equipment and long-line equipment respectively; Extract the positions of short-line equipment and long-line equipment and define them as short-line positions and long-line positions respectively; Get the distance between the long-line position and the short-line position, and define it as the analysis distance; Obtain the distance between the short-line position and the line power position, and define it as the determination distance; Obtain power supply data of the determination device; If the analysis distance is less than or equal to the determination distance ÷ 3, it is determined that the line power loss is small, and the power data of the interface connected to the power supply line is obtained and determined as the interface power data; Acquire power data of the power supply line and define it as power supply data; At this time, the interface power data = power supply data, and it is determined that the power supply of the abnormal user is error-free; If the analysis distance is greater than the determination distance ÷ 3, it is determined that the line power loss is large and the error analysis strategy is executed.

[0011] As an optional solution of the monitoring method of the single-phase smart energy meter error detection device of the present invention, the error analysis strategy is specifically: Get the electricity consumption collection; Extract the number of elements in the electricity usage collection; Calculate the number of analyses, number of analyses = number of elements ÷ 2; Calculate the analysis order value, analysis order value = 1 + analysis quantity; Extract the elements corresponding to the analysis order values ​​in the electricity consumption set and define them as analysis elements; The analytical device corresponding to the extracted analytical element is defined as the median device; Get the position corresponding to the median device and set it as the midline position; Get short-term and long-term positions; Execute power data analysis strategies for short-term, mid-term, and long-term positions; Obtain power supply data, short-term power data, medium-term power data, and long-term power data; If the short-circuit data is less than or equal to the power supply data × 95%, and the medium-circuit data is less than or equal to the power supply data × 95%, then it is determined that there is no error in the power supply at the short-circuit location, and if the long-circuit data is less than or equal to the power supply data × 95%, then it is determined that there is no error in the power supply at the abnormal user; If the short-term power supply data>power supply data×95%, or the medium-term power supply data>power supply data×95%, or the long-term power supply data>power supply data×95%, it is determined that there is an error in the power supply of the abnormal user; Then a line power supply abnormality prompt will be given.

[0012] As an optional solution of the monitoring method of the single-phase smart energy meter error detection device of the present invention, wherein: the neutral line position is specifically: Obtain analysis distance and judgment distance; Calculate the centerline distance, centerline distance = analysis distance ÷ 2 Obtain line resistance data corresponding to the determination distance and define it as first resistance data; Obtain line resistance data corresponding to the analysis distance and define it as second resistance data; Obtain line resistance data corresponding to the center line distance and set it as the third resistance data; Obtain current data of power supply lines; Get power supply data; Calculate the short-circuit data corresponding to the short-circuit position, where the short-circuit data = power supply data - (current data × first resistance data); Calculate the long-line data corresponding to the long-line position, long-line data = power supply data - (current data × first resistance data) - (current data × second resistance data); Calculate the power data corresponding to the neutral position, the power data = power supply data - (current data × first resistance data) - (current data × third resistance data).

[0013] The present invention has the following beneficial effects: 1. The monitoring method of the single-phase smart energy meter error calibration device obtains the overall power consumption of the area to determine whether there is any abnormality in the overall power consumption of the area, obtains the power consumption of each sub-area in the area, and determines whether there is any abnormality in the power consumption of each sub-area in the area. If the overall power consumption of the area and the power consumption of each sub-area in the area are normal, it means that there is no problem with the data collected by each meter. If there is an abnormality in any data of the overall power consumption of the area or the power consumption of each sub-area in the area, it means that the data collected by a certain meter may have errors and further judgment is needed to determine the cause of the abnormal power consumption in the area corresponding to the abnormal situation, reduce missed judgments and misjudgments, thereby avoiding the situation where the area with abnormal power consumption cannot be promptly prompted when the power consumption is abnormal, reduce safety hazards, and avoid more serious power safety accidents.

[0014] 2. The monitoring method of the single-phase smart electricity meter error calibration device, when the power consumption in a sub-area is abnormal but the overall power consumption in the area is normal, by obtaining the power consumption situation of each sub-area, it is determined whether there is a situation where one sub-area consumes more power and the other sub-area consumes less power, so as to determine whether there is an error in the overall power consumption data of the area that cancels each other out and causes failure to prompt in time, reduce the situation of missed judgment and misjudgment, and avoid the situation where the power consumption abnormality cannot be promptly prompted when the power consumption is abnormal, reduce safety hazards, and avoid more serious power safety accidents.

[0015] 3. The monitoring method of the single-phase smart electricity meter error calibration device, when the electricity consumption in the sub-area is normal, by obtaining the electricity consumption situation of each sub-area, it is determined whether there is a situation in which one user in a sub-area consumes more electricity and another user consumes less electricity. If all electricity consumption in the sub-area is normal, it means that there is no problem with the electricity consumption data collected by the meter. If there is abnormal electricity consumption in the sub-area, it means that there is an error in the electricity consumption data in the sub-area due to the mutual offset of the data, resulting in failure to prompt in time, reducing the situation of missed judgment and misjudgment, thereby avoiding the situation in which the abnormal electricity consumption area cannot be prompted in time when the electricity consumption is abnormal, reducing safety hazards, and avoiding more serious power safety accidents.

[0016] 4. The monitoring method of the single-phase smart electricity meter error calibration device determines whether the abnormal power consumption in the sub-area is caused by equipment failure by obtaining the sub-area with abnormal power consumption and the power consumption situation in the sub-area, and at the same time obtains the length of the power supply lines at various locations in the sub-area, determines the power loss of the power supply lines at various locations in the sub-area, and determines whether the equipment failure is caused by the mismatch between the voltage used by the equipment and its rated voltage due to power loss, and makes corresponding abnormal prompts to reduce missed judgments and misjudgments, thereby avoiding the situation where the area with abnormal power consumption cannot be prompted in time when abnormal power consumption occurs, reducing safety hazards and avoiding more serious power safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The present invention is a flow chart of the monitoring method of the single-phase smart energy meter error detection device. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Embodiment 1, a monitoring method of a single-phase smart energy meter error detection device, referring to Figure 1 ,include: Get the current power consumption of the target area and set it as the current power consumption of the area; Get all sub-regions in the target region and define them as target sub-regions; Execute the power consumption analysis strategy for each target sub-area to form sub-power consumption data; The sub-area power consumption data includes normal power consumption in the sub-area and abnormal power consumption in the sub-area; Execute regional analysis strategy for target areas to form total electricity consumption data; The total electricity consumption data includes normal electricity consumption in the target area and abnormal electricity consumption in the target area; If the power consumption in the sub-area is normal, the sub-area error determination strategy is executed to form sub-area error data; If the power consumption in the sub-area is abnormal but the power consumption in the target area is normal, the regional error determination strategy is executed to form regional error data; If the power consumption of the sub-region is abnormal and the power consumption of the target region is abnormal, the target sub-region is determined to have abnormal power consumption, and the target sub-region with abnormal power consumption of the determined target sub-region is obtained and identified as the target determination sub-region; According to the sub-region error data, a target sub-region where data collection of the target sub-region is biased is obtained and identified as the target determination sub-region; According to the regional error data, if it is determined that there is a deviation in the data collection of the target area, the target sub-area with abnormal power consumption in the determination sub-area in the target area is obtained and identified as the target determination sub-area; Execute the abnormal power consumption determination strategy on the target determination sub-area to form abnormal determination data; Based on the abnormal judgment data, determine the cause of abnormal power consumption and give corresponding abnormal prompts.

[0020] Through the above method, it is possible to judge whether there is abnormal electricity consumption in the area based on the electricity consumption in various places in the area and the overall electricity consumption in the area, and to judge whether there is error in the data collected by the electric meter based on the electricity consumption in various places in the area and the overall electricity consumption in the area. According to the electricity consumption in various places in the area, the cause of the error in the data collected by the electric meter is determined, and the cases of missed judgments and misjudgments are reduced, thereby avoiding the situation where the area with abnormal electricity consumption cannot be promptly notified when abnormal electricity consumption occurs, reducing safety hazards and avoiding more serious power safety accidents.

[0021] Embodiment 2: This embodiment is an improvement made on the basis of embodiment 1. The monitoring method of the single-phase smart energy meter error detection device and the power consumption analysis strategy are specifically as follows: Obtain the current power consumption of the target sub-area and define it as the power consumption of the sub-area; Get the current time point; Set the data collection period, which is 30 days; Calculate the data collection time point, data collection time point = current time point - data collection duration; The data collection time point is taken as the starting time and the current time point is taken as the ending time to form a data collection period; Set the collection period, which is 24 hours; Taking the data collection time point as the starting time, a data collection point is formed every collection cycle, wherein the data collection point includes the current time point, and the data collection point does not include the data collection time point; Obtain the data collection time points of the target sub-area within the data collection period and the corresponding power consumption of each data collection point, which are defined as the sub-historical power consumption; Calculate the sub-determined electricity consumption, which is the sum of all sub-historical electricity consumption during the data collection period ÷ (the total number of data collection points during the data collection period + 1); If the power consumption of the sub-area is ≥ the sub-determined power consumption × (1 + 30%), the power consumption of the sub-area is determined to be abnormal; If the sub-area power consumption is less than the sub-determination power consumption × (1 + 30%), it is determined that the sub-area power consumption is normal.

[0022] This embodiment also provides that the regional analysis strategy is specifically: Get the current power consumption of the area; Get the data collection period and all data collection points; Obtain the data collection time points of the target area within the data collection period and the corresponding power consumption of each data collection point, which are defined as the historical power consumption of the area; Calculate the regional determined electricity consumption, regional determined electricity consumption = the sum of historical electricity consumption of all regions during the data collection period ÷ (the total number of data collection points during the data collection period + 1); If the current power consumption of the area ≥ the determined power consumption of the area × (1 + 30%), the target area is judged to have abnormal power consumption; If the current power consumption of the area is less than the determined power consumption of the area × (1 + 30%), the power consumption of the target area is determined to be normal.

[0023] Embodiment 3: This embodiment is an improvement made on the basis of Embodiment 2. In this embodiment, the sub-region error determination strategy is specifically as follows: Get all users in the target sub-area and define them as target users; Execute the user analysis strategy for each target user in the target sub-area; Obtaining power consumption determination data for each target user in the target sub-area; The power consumption determination data includes normal power consumption of the user and abnormal power consumption of the user; If all target users in the target sub-area are judged to have normal electricity consumption, the data collection of the target sub-area is judged to be normal, and no abnormal prompt is given at this time; If there is a target user in the target sub-area determined to be abnormal user electricity consumption, the target sub-area data collection is determined to be abnormal, and A1-A8 is executed; A1. Obtain target users who are determined to have abnormal electricity usage and define them as abnormal users; A2. Obtain the current power consumption and determined power consumption of the abnormal user; A3. Calculate the abnormal difference of abnormal users, abnormal difference = user's current power - user's determined power × (1 + 30%); A4. Obtain all target users except abnormal users in the target sub-area and define them as analysis users; A5. Obtain the current power consumption and user-determined power consumption of each analyzed user; A6. Calculate the difference in usage for each analyzed user. Difference in usage = user-determined power × (1-30%) - user's current power. The sum of all the underused differences in the target sub-area is defined as the total underused difference value; A7. If the total difference is greater than or equal to the abnormal difference, it is determined that there is a deviation in the data collection of the target sub-area, and the abnormal power consumption determination strategy is executed; A8. If the total difference is less than the abnormal difference, it is determined that the electric meter in the target sub-area is abnormal and needs to be repaired.

[0024] The user analysis strategy is specifically: Get the current power consumption of the target user and set it as the current power consumption of the user; Get the data collection period and all data collection points; Obtain the data collection time points of the target user within the data collection period and the power consumption corresponding to each data collection point, which are defined as the user's historical power consumption; Calculate the user's determined power consumption, which is the sum of all users' historical power consumption during the data collection period / (the total number of data collection points during the data collection period + 1); If the user's current power consumption ≥ the user's determined power consumption × (1 + 30%), the user's power consumption is considered abnormal; If the user's current power consumption is less than the user's determined power consumption × (1 + 30%), the user's power consumption is determined to be normal.

[0025] This embodiment also provides the regional error determination strategy, specifically: Obtain a target sub-region with abnormal power consumption in the target region and define it as an abnormal region; Obtaining the sub-region power consumption and sub-determination power consumption of the abnormal region, and defining them as abnormal sub-power consumption and abnormal sub-determination power consumption respectively; Calculate the regional anomaly difference of the abnormal area, regional anomaly difference = abnormal sub-power - abnormal sub-judgment power × (1 + 30%); Obtain all target sub-areas in the target area except the abnormal area and define them as the analysis area; Obtaining the sub-region power consumption and sub-determination power consumption of each analysis region, which are respectively defined as analysis sub-power consumption and analysis sub-determination power consumption; Calculate the regional underutilization difference of each analysis area, regional underutilization difference = analysis sub-determination power × (1-30%) - analysis sub-power; The sum of all regional underutilization differences within the target area is defined as the total regional underutilization difference; If the total regional difference value is greater than or equal to the regional abnormal difference value, it is determined that there is a deviation in the data collection of the target area; If the total regional difference is less than the regional abnormal difference, it is determined that the electric meter in the target area is abnormal and needs to be repaired.

[0026] Embodiment 4: This embodiment is an improvement made on the basis of Embodiment 3. In this embodiment, the abnormal power consumption determination strategy is specifically as follows: Get the target determination sub-region; Obtain all users in the target determination sub-area and identify them as target users; Execute the user analysis strategy for each target user in the target determination sub-area; Extract target users whose power consumption is abnormal in the target determination sub-area and define them as abnormal users; Extract all electrical equipment of abnormal users and define them as analysis equipment; Obtain the interface location of the power supply line to which each analysis device is connected, and define it as the device location; Obtain the location of the power source of the power supply line and define it as the line power source location; Obtain the distance between each device location and the line power location, and define it as the power supply distance; Sort all analyzed devices from small to large according to the value of power supply distance to form a power consumption set; Extract the analysis equipment corresponding to the first element and the last element in the electricity consumption set, and define them as short-line equipment and long-line equipment respectively; Extract the positions of short-line equipment and long-line equipment and define them as short-line positions and long-line positions respectively; Get the distance between the long-line position and the short-line position, and define it as the analysis distance; Obtain the distance between the short-line position and the line power position, and define it as the determination distance; Obtain power supply data of the determination device; If the analysis distance is less than or equal to the determination distance ÷ 3, it is determined that the line power loss is small, and the power data of the interface connected to the power supply line is obtained, which is defined as the interface power data, and the power data is the voltage value; Acquire power data of the power supply line and define it as power supply data; At this time, the interface power data = power supply data, and it is determined that the power supply of the abnormal user has no error, that is, the abnormal power consumption of the user may be caused by the damage of the equipment due to other reasons or the sudden use of more power-consuming equipment, rather than the error in the power supply, which causes the equipment to be damaged due to long-term use of mismatched power supply, resulting in abnormal power consumption of the user; If the analysis distance is greater than the determination distance ÷ 3, it is determined that the line power loss is large and the error analysis strategy is executed.

[0027] The error analysis strategy is specifically as follows: Get the electricity consumption collection; Extract the number of elements in the electricity usage collection; Calculate the number of analyses, number of analyses = number of elements ÷ 2; Calculate the analysis order value, analysis order value = 1 + analysis quantity; Extract the elements corresponding to the analysis order values ​​in the electricity consumption set and define them as analysis elements; The analytical device corresponding to the extracted analytical element is defined as the median device; Get the position corresponding to the median device and set it as the midline position; Get short-term and long-term positions; Execute power data analysis strategies for short-term, mid-term, and long-term positions; Obtain power supply data, short-term power data, medium-term power data, and long-term power data; If the short-circuit data is less than or equal to the power supply data × 95%, and the medium-circuit data is less than or equal to the power supply data × 95%, then it is determined that there is no error in the power supply at the short-circuit location, and if the long-circuit data is less than or equal to the power supply data × 95%, then it is determined that there is no error in the power supply of the abnormal user, that is, the abnormal power consumption of the user may be caused by the damage of the equipment due to other reasons or the sudden use of more power-consuming equipment, rather than the abnormal power consumption of the user caused by the error in the power supply, resulting in the damage of the equipment due to the long-term use of mismatched power supply; If the short-term power supply data>power supply data×95%, or the medium-term power supply data>power supply data×95%, or the long-term power supply data>power supply data×95%, it is determined that there is an error in the power supply of the abnormal user; Then a line power supply abnormality prompt will be given.

[0028] The midline position is specifically: Obtain analysis distance and judgment distance; Calculate the centerline distance, centerline distance = analysis distance ÷ 2 Obtaining line resistance data corresponding to the determination distance as first resistance data, wherein the line resistance data is the resistance corresponding to each length of the power supply line used by the user; Obtain line resistance data corresponding to the analysis distance and define it as second resistance data; Obtain line resistance data corresponding to the center line distance and set it as the third resistance data; Obtain current data of power supply lines; Get power supply data; Calculate the short-circuit data corresponding to the short-circuit position, where the short-circuit data = power supply data - (current data × first resistance data); Calculate the long-line data corresponding to the long-line position, long-line data = power supply data - (current data × first resistance data) - (current data × second resistance data); Calculate the power data corresponding to the neutral position, the power data = power supply data - (current data × first resistance data) - (current data × third resistance data).

[0029] In this embodiment, it is determined whether there is abnormal power consumption in the area based on the power consumption in various places in the area and the power consumption in the area as a whole, and whether there is error in the data collected by the electric meter based on the power consumption in various places in the area and the power consumption in the area as a whole. According to the power consumption in various places in the area, the cause of the error in the data collected by the electric meter is determined, and the cases of missed judgments and misjudgments are reduced, thereby avoiding the situation where the area with abnormal power consumption cannot be promptly notified when abnormal power consumption occurs, reducing safety hazards and avoiding more serious power safety accidents.

Claims

1. A monitoring method for a single-phase smart energy meter error detection device, characterized in that: include: Get the current power consumption of the target area and set it as the current power consumption of the area; Get all sub-regions in the target region and define them as target sub-regions; Execute the power consumption analysis strategy for each target sub-area to form sub-power consumption data; The sub-area power consumption data includes normal power consumption in the sub-area and abnormal power consumption in the sub-area; Execute regional analysis strategy for target areas to form total electricity consumption data; The total electricity consumption data includes normal electricity consumption in the target area and abnormal electricity consumption in the target area; If the power consumption in the sub-area is normal, the sub-area error determination strategy is executed to form sub-area error data; If the power consumption in the sub-area is abnormal but the power consumption in the target area is normal, the regional error determination strategy is executed to form regional error data; If the power consumption of the sub-region is abnormal and the power consumption of the target region is abnormal, the target sub-region is determined to have abnormal power consumption, and the target sub-region with abnormal power consumption of the determined target sub-region is obtained and identified as the target determination sub-region; According to the sub-region error data, a target sub-region where data collection of the target sub-region is biased is obtained and identified as the target determination sub-region; According to the regional error data, if it is determined that there is a deviation in the data collection of the target area, the target sub-area with abnormal power consumption in the determination sub-area in the target area is obtained and identified as the target determination sub-area; Execute the abnormal power consumption determination strategy on the target determination sub-area to form abnormal determination data; Based on the abnormal judgment data, determine the cause of abnormal power consumption and give corresponding abnormal prompts.

2. The monitoring method of the single-phase smart energy meter error detection device according to claim 1 is characterized in that: The power consumption analysis strategy is specifically as follows: Obtain the current power consumption of the target sub-area and define it as the power consumption of the sub-area; Get the current time point; Set the data collection duration; Calculate the data collection time point, data collection time point = current time point - data collection duration; The data collection time point is taken as the starting time and the current time point is taken as the ending time to form a data collection period; Set the collection cycle; Taking the data collection time point as the starting time, a data collection point is formed every collection cycle; Obtain the data collection time points of the target sub-area within the data collection period and the corresponding power consumption of each data collection point, which are defined as the sub-historical power consumption; Calculate the sub-determined electricity consumption, which is the sum of all sub-historical electricity consumption during the data collection period ÷ (the total number of data collection points during the data collection period + 1); If the power consumption of the sub-area is ≥ the sub-determined power consumption × (1 + 30%), the power consumption of the sub-area is determined to be abnormal; If the sub-area power consumption is less than the sub-determination power consumption × (1 + 30%), it is determined that the sub-area power consumption is normal.

3. The monitoring method of the single-phase smart energy meter error detection device according to claim 1 is characterized in that: The regional analysis strategy is specifically as follows: Get the current power consumption of the area; Get the data collection period and all data collection points; Obtain the data collection time points of the target area within the data collection period and the corresponding power consumption of each data collection point, which are defined as the historical power consumption of the area; Calculate the regional determined electricity consumption, regional determined electricity consumption = the sum of historical electricity consumption of all regions during the data collection period ÷ (the total number of data collection points during the data collection period + 1); If the current power consumption of the area ≥ the determined power consumption of the area × (1 + 30%), the target area is judged to have abnormal power consumption; If the current power consumption of the area is less than the determined power consumption of the area × (1 + 30%), the power consumption of the target area is determined to be normal.

4. The monitoring method of the single-phase smart energy meter error detection device according to claim 1 is characterized in that: The sub-region error determination strategy is specifically as follows: Get all users in the target sub-area and define them as target users; Execute the user analysis strategy for each target user in the target sub-area; Obtaining power consumption determination data for each target user in the target sub-area; The power consumption determination data includes normal power consumption of the user and abnormal power consumption of the user; If all target users in the target sub-area are judged to have normal electricity consumption, the data collection of the target sub-area is judged to be normal, and no abnormal prompt is given at this time; If there is a target user in the target sub-area determined to be abnormal user electricity consumption, the target sub-area data collection is determined to be abnormal, and A1-A8 is executed; A1. Obtain target users who are determined to have abnormal electricity usage and define them as abnormal users; A2. Obtain the current power consumption and determined power consumption of the abnormal user; A3. Calculate the abnormal difference of abnormal users, abnormal difference = user's current power - user's determined power × (1 + 30%); A4. Obtain all target users except abnormal users in the target sub-area and define them as analysis users; A5. Obtain the current power consumption and user-determined power consumption of each analyzed user; A6. Calculate the difference in usage for each analyzed user. Difference in usage = user-determined power × (1-30%) - user's current power. The sum of all the underused differences in the target sub-area is defined as the total underused difference value; A7. If the total difference is greater than or equal to the abnormal difference, it is determined that there is a deviation in the data collection of the target sub-area, and the abnormal power consumption determination strategy is executed; A8. If the total difference is less than the abnormal difference, it is determined that the electric meter in the target sub-area is abnormal and needs to be repaired.

5. The monitoring method of the single-phase smart energy meter error detection device according to claim 4 is characterized in that: The user analysis strategy is specifically: Get the current power consumption of the target user and set it as the current power consumption of the user; Get the data collection period and all data collection points; Obtain the data collection time points of the target user within the data collection period and the power consumption corresponding to each data collection point, which are defined as the user's historical power consumption; Calculate the user's determined power consumption, which is the sum of all users' historical power consumption during the data collection period / (the total number of data collection points during the data collection period + 1); If the user's current power consumption ≥ the user's determined power consumption × (1 + 30%), the user's power consumption is considered abnormal; If the user's current power consumption is less than the user's determined power consumption × (1 + 30%), the user's power consumption is determined to be normal.

6. The monitoring method of the single-phase smart energy meter error detection device according to claim 1 is characterized in that: The regional error determination strategy is specifically as follows: Obtain a target sub-region with abnormal power consumption in the target region and define it as an abnormal region; Obtaining the sub-region power consumption and sub-determination power consumption of the abnormal region, and defining them as abnormal sub-power consumption and abnormal sub-determination power consumption respectively; Calculate the regional anomaly difference of the abnormal area, regional anomaly difference = abnormal sub-power - abnormal sub-judgment power × (1 + 30%); Obtain all target sub-areas in the target area except the abnormal area and define them as the analysis area; Obtaining the sub-region power consumption and sub-determination power consumption of each analysis region, which are respectively defined as analysis sub-power consumption and analysis sub-determination power consumption; Calculate the regional underutilization difference of each analysis area, regional underutilization difference = analysis sub-determination power × (1-30%) - analysis sub-power; The sum of all regional underutilization differences within the target area is defined as the total regional underutilization difference; If the total regional difference value is greater than or equal to the regional abnormal difference value, it is determined that there is a deviation in the data collection of the target area; If the total regional difference is less than the regional abnormal difference, it is determined that the electric meter in the target area is abnormal and needs to be repaired.

7. The monitoring method of the single-phase smart energy meter error detection device according to claim 5 is characterized by: The abnormal power consumption determination strategy is specifically as follows: Get the target determination sub-area; Obtain all users in the target determination sub-area and identify them as target users; Execute the user analysis strategy for each target user in the target determination sub-area; Extract target users whose power consumption is abnormal in the target determination sub-area and define them as abnormal users; Extract all electrical equipment of abnormal users and define them as analysis equipment; Obtain the interface location of the power supply line to which each analysis device is connected, and define it as the device location; Obtain the location of the power source of the power supply line and define it as the line power source location; Obtain the distance between each device location and the line power location, and define it as the power supply distance; Sort all analyzed devices from small to large according to the value of power supply distance to form a power consumption set; Extract the analysis equipment corresponding to the first element and the last element in the electricity consumption set, and define them as short-line equipment and long-line equipment respectively; Extract the positions of short-line equipment and long-line equipment and define them as short-line positions and long-line positions respectively; Get the distance between the long-line position and the short-line position, and define it as the analysis distance; Obtain the distance between the short-line position and the line power position, and define it as the determination distance; Obtain power supply data of the determination device; If the analysis distance is less than or equal to the determination distance ÷ 3, it is determined that the line power loss is small, and the power data of the interface connected to the power supply line is obtained and determined as the interface power data; Acquire power data of the power supply line and define it as power supply data; At this time, the interface power data = power supply data, and it is determined that the power supply of the abnormal user is error-free; If the analysis distance is greater than the determination distance ÷ 3, it is determined that the line power loss is large and the error analysis strategy is executed.

8. The monitoring method of the single-phase smart energy meter error detection device according to claim 7 is characterized in that: The error analysis strategy is specifically as follows: Get the electricity consumption collection; Extract the number of elements in the electricity usage collection; Calculate the number of analyses, number of analyses = number of elements ÷ 2; Calculate the analysis order value, analysis order value = 1 + analysis quantity; Extract the elements corresponding to the analysis order values ​​in the electricity consumption set and define them as analysis elements; The analytical device corresponding to the extracted analytical element is defined as the median device; Get the position corresponding to the median device and set it as the midline position; Get short-term and long-term positions; Execute power data analysis strategies for short-term, mid-term, and long-term positions; Obtain power supply data, short-term power data, medium-term power data, and long-term power data; If the short-circuit data is less than or equal to the power supply data × 95%, and the medium-circuit data is less than or equal to the power supply data × 95%, then it is determined that there is no error in the power supply at the short-circuit location, and if the long-circuit data is less than or equal to the power supply data × 95%, then it is determined that there is no error in the power supply at the abnormal user; If the short-term power supply data>power supply data×95%, or the medium-term power supply data>power supply data×95%, or the long-term power supply data>power supply data×95%, it is determined that there is an error in the power supply of the abnormal user; Then a prompt will be given for abnormal power supply of the line.

9. The monitoring method of the single-phase smart energy meter error detection device according to claim 8 is characterized in that: The midline position is specifically: Obtain analysis distance and judgment distance; Calculate the centerline distance, centerline distance = analysis distance ÷ 2 Obtain line resistance data corresponding to the determination distance and define it as first resistance data; Obtain line resistance data corresponding to the analysis distance and set it as second resistance data; Obtain line resistance data corresponding to the center line distance and set it as the third resistance data; Obtain current data of power supply lines; Get power supply data; Calculate the short-circuit data corresponding to the short-circuit position, where short-circuit data = power supply data - (current data × first resistance data); Calculate the long-line data corresponding to the long-line position, long-line data = power supply data - (current data × first resistance data) - (current data × second resistance data); Calculate the power data corresponding to the neutral position, the power data = power supply data - (current data × first resistance data) - (current data × third resistance data).

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