CN113902583A

CN113902583A - Distribution network side operation and maintenance method and system using low-voltage network equipment data

Info

Publication number: CN113902583A
Application number: CN202111106468.5A
Authority: CN
Inventors: 骆晨; 吴凯; 冯玉; 吴少雷; 吴钊贤; 谈俊; 宋磊; 戚振彪; 徐飞; 王江权; 赵成; 冯乔; 郭小东; 吴琼; 汪柏松; 江涛; 周建军
Original assignee: Electric Power Research Institute of State Grid Anhui Electric Power Co Ltd; State Grid Anhui Electric Power Co Ltd; Wuhu Power Supply Co of State Grid Anhui Electric Power Co Ltd
Current assignee: Electric Power Research Institute of State Grid Anhui Electric Power Co Ltd; State Grid Anhui Electric Power Co Ltd; Wuhu Power Supply Co of State Grid Anhui Electric Power Co Ltd
Priority date: 2021-09-22
Filing date: 2021-09-22
Publication date: 2022-01-07

Abstract

The invention discloses a distribution network side operation and maintenance method utilizing low-voltage network equipment data, which takes users as a correlation basis, realizes the network data of three operators, namely mobile operators, telecom operators and linkage operators, provides real-time user power utilization data and historical data for a distribution network side, can sense the power utilization condition of the users in real time without adding other additional equipment to the existing low-voltage power grid, provides a basis for the work of the distribution network side by means of the data, greatly improves the working efficiency and quality, and reduces the labor intensity.

Description

Distribution network side operation and maintenance method and system using low-voltage network equipment data

Technical Field

The invention relates to the technical field of data analysis, in particular to a distribution network side operation and maintenance method and system by using low-voltage network equipment data.

Background

The power supply reliability reflects the level of power supply development saving, the speed and the efficiency of power failure sensing are enhanced, the problem of rapid sensing and accurate positioning of power failure in a distribution area is solved, the line fault recovery time is effectively shortened, the operation and maintenance level of a power distribution network is improved, and the improvement of the overall quality of service of a user in the power industry is very necessary.

Along with social development, family broadband has been popularized comprehensively, and according to the statistical data of telecommunications and movement of Anhui province, the popularity rate of family broadband of Anhui province reaches 94.2% by the end of 2020. The urban household broadband utilization rate reaches 86%. When network devices such as the optical modem, the router, the set-top box and the like in the home broadband normally work, a handshake mechanism (for logging in a network operator control background or a third-party application background after the devices are started) and a heartbeat mechanism (for regularly sending a signal to the background to confirm the connection state of the devices) must exist. According to the project, heartbeat and handshake signals of the network equipment with the heartbeat mechanism are collected and analyzed, the power loss range of the low-voltage power grid can be rapidly sensed, rush repair is organized, power failure messages and power restoration plans are pushed to users at the first time, and the power supply service quality of a company is improved.

A method, a system and a machine readable storage medium for sensing low-voltage user faults as disclosed in application No. CN201910515769X, which belong to the field of power distribution and utilization intelligence. The method comprises the following steps: judging whether a heartbeat signal of a network of at least one low-voltage user in the same meter box or branch box of the power distribution area is received; and determining that the meter box or the branch box has a fault under the condition that any one heartbeat signal in the same meter box or the same branch box cannot be received. By the method, the system and the machine-readable storage medium, the power emergency repair center can actively sense whether a low-voltage user fails. According to the method, whether the electricity meter box or the branch box is powered off or not is judged only through network equipment data, but the value of the network equipment data at the user side is not fully exerted, and operation and maintenance work at the distribution network side still has multiple difficulties, such as inaccurate maintenance message pushing objects, insufficient consideration of user electricity utilization habits, large maintenance influence range, low-voltage topology disorder caused by private wire connection and the like due to the fact that residents with unified addresses are not the same person as an actual householder.

Disclosure of Invention

The invention aims to solve the technical problem of how to fully utilize the data of the network equipment at the user side and provide an operation and maintenance data basis for the distribution network side.

The invention solves the technical problems through the following technical means:

the distribution network side operation and maintenance method utilizing the low-voltage network equipment data comprises the following steps:

step 1, acquiring historical data and current data of power failure and power restoration of user network equipment, user network flow time interval data and historical data of power failure at a distribution network side; acquiring user information and power failure and restoration time according to the network equipment information;

step 2, carrying out low-voltage line topology identification and user electricity consumption behavior portrait portrayal; the low-voltage line topology identification method comprises the following steps:

step 2, grouping the power failure historical data of the network equipment at the user side according to cells, judging the address information of the power failure user according to the grouped data, and generating topological data at the user side;

step 2, step 22, searching corresponding outage line information from the distribution network side historical data according to the time and the cell of the user outage event at the user side, and if the corresponding outage line information can be searched, step 2, executing step 23; if not, executing step 24;

step 2, step 23, acquiring distribution network side topological data of the power-off line information, and associating the user side topological data with the distribution network side topology on the basis of user association to obtain low-voltage line topological data;

step 2, step 24 of step 2 stores user side topological data, and step 23 is executed again when corresponding power-off line information is acquired;

step 25, identifying the phase sequence relation between the distribution area and the user according to the topological data of the low-voltage line, and constructing and perfecting the topological relation of the low-voltage distribution network;

the method for portraying the electricity consumption behaviors of the user comprises the following steps:

step 21', constructing a data set, wherein the data set at least comprises power failure and power restoration data of user network equipment, user network flow time interval data, first-aid repair data of a distribution network side and user complaint data received by the distribution network side;

step 22', on the basis of a user, associating the power failure and power restoration data of the user network equipment with the emergency repair data on the distribution network side and the user complaint data received by the distribution network side to obtain power failure habit data of the user and regional power utilization habit data;

step 23', defining a user electricity consumption habit label definition according to user network flow time interval data and user power failure habit data, defining a regional electricity consumption habit label according to the regional electricity consumption habit data, and taking data with the label as a training sample;

step 24', training a random forest model by using a training sample to obtain a target model;

step 25', constructing a user electricity consumption portrait and a regional electricity consumption portrait by using the target model;

26' the distribution network side makes a maintenance plan according to the user electricity image and the regional electricity image;

step 3, making a rush-repair operation and maintenance plan according to the current network equipment power failure data and the user portrait; the method specifically comprises the following steps:

step 31, acquiring power failure and power restoration data of the network equipment in real time, and studying and judging whether a power failure and power restoration event occurs according to the power failure and power restoration data;

step 32, if no power failure and power restoration event occurs, the research and judgment are finished; if a power failure and power restoration event occurs, the process proceeds to step 33;

step 33, analyzing event information according to the power failure recovery data, wherein the event information at least comprises an event type, an event area, a power failure account number and occurrence time;

step 34, judging whether the event is a power failure event or a power restoration event according to the event information, and if the event is the power failure event, simultaneously performing the processing of step 35 and step 38; if the power restoration event occurs, processing in step 39 is performed;

step 35, judging the influence range according to the event area, the power failure number and the power failure time information aiming at the power failure event;

step 36, acquiring the mobile phone number of the actually affected person and the mobile phone number of the householder according to the influence range;

step 37, pushing real-time power failure information to actually affected personnel and householders;

and step 38, acquiring a rush-repair team group of the corresponding area according to the event area, and pushing a rush-repair task to the rush-repair team group.

Step 39, for the power restoration event, pushing power restoration information to actual affected personnel and householders;

step 4, judging power failure and power restoration of the low-voltage power grid according to the power failure data of the user network, wherein the specific method comprises the following steps:

step 41, acquiring a power failure signal of user network equipment, judging whether the user power failure behavior is artificial power failure or equipment fault power failure, and if the user power failure behavior is artificial power failure, finishing analysis; if the equipment is failed and powered down, executing step 42;

step 42, according to the electricity meter box and the electricity failure time related to the electricity failure signal, taking the electricity meter box as a unit, and setting electricity failure users in a set time length as a group; determining that the number of the users with network equipment power failure in the same time range is smaller than a threshold value as the user artificial power failure; if the number of the users is larger than the threshold value, tracking and inquiring information of all users under the electric meter box, judging whether the electric meter box is powered off or not according to the power-off condition of network equipment of all the users, and if the electric meter box is judged to be powered off, executing the step 43;

step 43, associating branch box information to which the power-down ammeter boxes belong, acquiring all ammeter boxes under the branch box, acquiring network equipment power-down information of users to which all ammeter boxes under the branch box belong, repeatedly executing step 42 one by one to judge whether each ammeter box has power failure, judging whether the number of the power-down ammeter boxes is greater than a threshold value, and if the number of the power-down ammeter boxes is greater than the threshold value, judging that the branch box has power failure, executing step 44; otherwise, judging the program is finished;

and 44, associating the information of the station area to which the power-down branch box belongs, acquiring the information of all branch boxes under the station area, executing the step 43 one by one, judging whether the branch boxes have power failure, and if the number of the power-down branch boxes is greater than a set threshold value, judging that the station area has power failure.

The invention utilizes the network equipment at the user side and the overhaul data at the distribution network side, realizes the network data of three operators of mobile, telecommunication and linkage to provide the real-time data and the historical data of the power consumption of the user for the distribution network side on the basis of the association of the user, can sense the power consumption condition of the user in real time without adding other additional equipment to the existing low-voltage power grid, provides a basis for the work at the distribution network side by means of the data, greatly improves the working efficiency and the quality, and reduces the labor intensity.

Further, the power failure historical data of the distribution network side in the step 1 includes power failure line information of scheduled maintenance, switch reclosing in the morning and repair reporting.

Further, the specific process of step 21 is as follows:

according to the sn number and the equipment fingerprint of the power-down network equipment, the information of the city, the region, the cell, the building, the floor and the house number where the user side is located is obtained, and the topological data of the user side cell-building-floor-user is generated

Further, the specific process of step 22 is as follows: according to the power failure time and the power failure area of a user, searching power failure line information corresponding to scheduled maintenance, switch reclosing in the morning and repair reporting, acquiring topological data of a transformer area, a branch box, an electricity meter box and a user of the power failure line information, and taking the user as a correlation basis to obtain low-voltage line topological data which are the transformer area, the branch box, the electricity meter box, a distribution network side user and a user side user.

Further, the step 25 specifically includes:

and judging whether a private wire exists or not and whether the phase sequence relationship is reasonable or not according to the relationship between the user in the low-voltage line topology data and the upper-stage electric meter box.

Further, the step 23' is specifically to perform power consumption requirement and time interval label definition on the user according to the user network flow time interval data, and perform active power-off habit label definition on the user according to the user power consumption habit data.

Further, in the step 26', a maintenance plan with a small influence range is generated by the distribution network side according to the user electrical picture and by combining the current scheduling of the maintenance team.

Further, it is characterized in that,

the specific method for determining the influence range in step 35 is as follows:

35.1 judging that the power failure occurs in a large range when the distance does not exceed a set threshold value by combining the geographical position coordinates during the power failure within the set close time; overlapping the areas of the power failure events to be used as the influence range of the large-scale power failure event;

35.2 if only a single power failure event occurs in the close time or the close position, analyzing the building information corresponding to the power failure users according to the power failure user number, and if the power failure users are distributed in multiple buildings, judging that the power failure occurs in the residential area;

35.3 if the power failure users are distributed in a single building, continuously analyzing the power failure user distribution floors, if the power failure users are distributed on all the floors, judging that the building has power failure, and if not, judging that the floors have power failure.

Further, in step 36, if the power outage time is a non-floor power outage, the method for acquiring the mobile phone number of the actually affected person specifically includes:

the method 1, according to longitude and latitude information of a power failure event geographic position, combining received GPS positioning data of a user mobile phone to determine a mobile phone identification code of an affected person, combining an operator account with the mobile phone identification code to obtain user information, and determining a mobile phone number of the affected person;

the method 2 further determines the affected personnel according to the information of the base station accessed by the mobile phone of the user and the historical data of the GPS data:

the method 2.1 utilizes the historical data of the information of the access base station of the mobile phone of the user, screens the access base station with high frequency according to the access frequency and duration, and determines the geographic range and time of the resident user by combining the geographic position and the coverage range of the base station;

the method 2.2 obtains the action track of the user according to the GPS positioning function of the mobile phone of the user; determining a commonly used action track of the user according to data generated by superposition by superposing historical action tracks of the user;

the method 2.3 combines the user resident geographic range and the action track, further superposes the geographic information data, and the user resident area and the appearance time are accurate;

the method 2.4 is used for screening matched users according to the occurrence time of the power failure event and the longitude and latitude information of the geographic position and by combining the user resident area and the occurrence time obtained by analyzing in the method 2.3, and obtaining the mobile phone numbers of the users;

in the method 1 or the method 2, one of them is selected.

Further, if the power outage time is non-floor power outage, the method for acquiring the mobile phone number of the actually affected person may further be:

and 3, summarizing the mobile phone numbers of the affected personnel obtained by the methods 1 and 2.4, removing repeated data, and determining the mobile phone numbers of the affected personnel finally.

Further, in step 36, if the power failure event is a floor power failure, the SN number of the network device installed on the corresponding floor in the power failure area and the mobile phone identification code of the connection device thereof are acquired through the operator account, and the user information is acquired according to the mobile phone identification code and the operator account, so as to determine the mobile phone number of the affected person.

Further, in step 41, it is determined whether the power down behavior is artificial power down or equipment failure power down according to the user profile.

Furthermore, in the step 42, if the number of users to which the electricity meter box belongs is greater than the threshold value in the case of power failure, but only some users are powered down, whether the users without power failure have power failure behavior before the current time period needs to be traced, and if the users without power failure behavior before the current time period have power failure and power failure is not restored, it is determined that all the users to which the current electricity meter box belongs have power failure, and the electricity meter box is determined to have power failure; if the network equipment is in the power restoration state before the power failure signal occurs, the real-time performance and accuracy of the network equipment signal of the user need to be judged.

Further, the method for judging the real-time performance and the accuracy of the power-down signal of the user network equipment comprises the following steps:

a. judging in real time, waiting for the next power down signal interface period, and judging whether the next power down signal interface period is in the next power down signal data; b. and (4) judging the accuracy, namely judging whether the power failure signal of the user and the pair and the sequence of the power restoration signal are normal or not according to historical data.

Corresponding to the method, the invention also provides a distribution network side operation and maintenance system using the low-voltage network equipment data, which comprises the following steps:

the data acquisition module is used for acquiring the power failure and restoration historical data and the current data of the user network equipment, the user network flow time interval data and the distribution network side power failure historical data; acquiring user information and power failure and restoration time according to the network equipment information;

the matching module is used for matching the corresponding ammeter boxes according to the user information and matching the network side power failure historical data according to the power failure time;

the user topological relation building module is used for carrying out low-voltage line topological identification and user power consumption behavior portrait portrayal according to the information obtained by the matching module; the low-voltage line topology identification method comprises the following steps:

the emergency repair operation and maintenance plan making module is used for making an emergency repair operation and maintenance plan according to the current network equipment power failure data and the user portrait; the method specifically comprises the following steps:

the power grid power failure and restoration judging module is used for judging power failure and restoration of the low-voltage power grid according to power failure data of a user network, and the specific method comprises the following steps:

Further, the power failure historical data of the power distribution network side in the data acquisition module comprises power failure line information of scheduled maintenance, switch reclosing in the morning and repair reporting.

Further, the specific process of step 21 is as follows:

Further, the step 25 specifically includes:

Further, it is characterized in that,

23. The distribution network side operation and maintenance system using low-voltage network device data as claimed in claim 15, wherein in step 36, if the power outage time is non-floor power outage, the method for acquiring the mobile phone number of the actually affected person specifically comprises:

in the method 1 or the method 2, one of them is selected.

a. judging in real time, waiting for the next power down signal interface period, and judging whether the next power down signal interface period is in the next power down signal data;

b. and (4) judging the accuracy, namely judging whether the power failure signal of the user and the pair and the sequence of the power restoration signal are normal or not according to historical data.

The invention has the advantages that:

The method provided by the invention associates the existing network equipment of the user with the data of active power failure, fault power failure and the like of the distribution network side, so that the automatic identification of the low-voltage line topology can identify the phase sequence relation between a distribution area and the user, construct and perfect the topological relation between a distribution transformer, a branch box and a meter user, effectively avoid the problems of three-phase imbalance, single-phase overload, low voltage and the like, and improve the operation level of the distribution network;

the method provided by the invention utilizes the power grid operation and inspection daily work such as power failure events of the power distribution network, scheduled maintenance, early switch reclosing operation and the like, does not need to modify power grid lines and equipment, does not increase the workload of maintenance personnel, and has the advantages of low investment cost and quick response.

According to the method, the distribution network side data is used as verification according to the user power consumption data, the user power consumption behaviors such as regular power failure, network flow use time and the like are obtained, so that labels such as regular power consumption requirements and time periods of the user power consumption are counted, model training is carried out by using the labeled data, a target portrait model is obtained, the user portrait is calculated by using the target portrait model, the distribution network side counts and analyzes the influence of maintenance operation according to the user power consumption portrait, a maintenance plan with small influence range and low economic loss is made, and the service quality of the distribution network is improved.

The invention utilizes the power-off and power-on data of the user network equipment, has high data accuracy and improves the user portrait depicting precision. Importantly, the method has the advantages of no need of additional equipment and low cost.

The method utilizes the existing network equipment of the user to study and judge the power failure and the power restoration of the low-voltage distribution network, does not need to modify the power grid line and the equipment, is simple and easy to apply, does not influence the power utilization of the user, and has low investment cost; and the user portrait can be used for accurately judging whether the current user network equipment is powered down artificially or is powered down in a fault, so that part of artificial power down behaviors can be screened out, and the workload of operation and maintenance personnel is reduced. And according to the topological structure of the low-voltage distribution network, the power failure conditions of the electric meter box, the branch box and the distribution room can be traced upwards.

The invention combines the research and judgment result of the real-time power failure and power restoration, senses the occurrence of the power failure and power restoration events in real time, utilizes the operator GPS or the network equipment base station to access and position actual personnel in the corresponding area, accurately senses the personnel influenced by the power failure events, combines the progress feedback of the emergency repair personnel and the verification of the power restoration events, pushes the emergency repair condition to the actual influenced users in real time, realizes the accurate and humanized pushing of the information, improves the service quality and reduces the occurrence of complaint events.

Drawings

Fig. 1 is a logic diagram of a method for automatically identifying a topology of a low-voltage line by using power-down data of a network terminal in embodiment 1 of the present invention;

fig. 2 is a schematic flow chart of a method for automatically identifying a topology of a low-voltage line by using power-down data of a network terminal in embodiment 2 of the present invention;

fig. 3 is a schematic overall flow chart of a method for automatically identifying a topology of a low-voltage line by using power-down data of a network terminal in embodiment 2 of the present invention;

fig. 4 is a flowchart of a method for generating an electricity consumption habit figure and a maintenance plan for a user by using power failure restoration data of network equipment in embodiment 3 of the present invention;

fig. 5 is a flow chart of a low-voltage power grid emergency maintenance operation and maintenance management method according to the real-time power failure and restoration information in embodiment 4 of the present invention;

fig. 6 is a flowchart of a method for studying and determining power failure and power restoration of a low-voltage power grid by using power failure and power restoration data of network equipment in embodiment 5 of the present invention;

fig. 7 is a power-down flow chart of a trace-back branch box using power-down restoration data of network equipment in embodiment 5 of the present invention;

fig. 8 is a power-down flow chart of a tracing area using power-down restoration data of a network device in embodiment 5 of the present invention;

FIG. 9 is a flowchart of address matching according to embodiment 6 of the present invention;

FIG. 10 is a flowchart of address segmentation in embodiment 6 of the present invention;

FIG. 11 is a flowchart of forward maximum matching in embodiment 6 of the present invention;

fig. 12 is an overview of data collection services in embodiment 7 of the present invention;

FIG. 13 is a flowchart of data collection in example 7 of the present invention;

fig. 14 is a diagram of a data acquisition platform according to embodiment 7 of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example 1: distribution network side operation and maintenance method using low-voltage network data

The embodiment provides a distribution network side operation and maintenance method using low-voltage network data. At present, the network almost covers urban and rural areas and mountain areas. By utilizing the high coverage rate of the network, a data basis can be provided for daily operation and maintenance of the distribution network side. The specific method comprises the following steps as shown in figure 1:

Corresponding to the above method, this embodiment further provides a system, specifically: utilize distribution network side operation and maintenance system of low pressure network equipment data, its characterized in that includes:

The following detailed description is for each subsystem:

example 2: method for automatically identifying low-voltage line topology by utilizing network terminal power failure data

As shown in fig. 2 and fig. 3, the embodiment discloses a method for automatically identifying a low-voltage line topology by using network terminal power-down data, determining a power-off area by using the network terminal power-down data, and automatically identifying and continuously improving the low-voltage line topology by combining measures such as plan information and manual first-aid repair verification. The method comprises the following steps:

step 1, acquiring power failure historical data of network equipment at a user side, power failure historical data at a distribution network side, and filtering invalid data;

whether the fault is power failure, or planned maintenance on the distribution network side and switch reclosing operation in the morning can cause the power failure of user network equipment. The network operator may save all network device power down data. The grid company also stores circuit outage data caused by scheduled maintenance, switch reclosing operation in the morning, fault repair reporting and the like. The network equipment data stored by the network operator at least comprises the sn number of the network equipment, fingerprint information, the floor, building, district, area, city, power failure time and other specific information of the corresponding user. The power failure data of the power grid company at least comprises information such as users, electric meter boxes, branch boxes, transformer areas, power failure time and the like.

The historical data acquired in the step needs to be subjected to preliminary processing, so that invalid data is filtered, and data with empty key fields such as sn numbers, fingerprint information, power failure time and the like cannot be used for later judgment, so that the data can be directly filtered.

Step 2, grouping power failure historical data of the network equipment at the user side according to cells, judging address information of power failure users according to the grouped data, and generating topological data at the user side: cell-building-floor-user.

Step 3, according to the time and the cell of the power failure event of the user at the user side, searching corresponding power failure line information from historical data at the distribution network side, and if the corresponding power failure line information can be searched, executing step 4; if the search is not available, executing step 5;

and step 4, according to the power failure time and the power failure area of the user, searching power failure line information corresponding to scheduled maintenance, switch reclosing in the morning and repair reporting, acquiring topological data of a transformer area, a branch box, an electricity meter box and a user of the power failure line information, and taking the user as a correlation basis to obtain low-voltage line topological data which are the transformer area, the branch box, the electricity meter box, a user on the distribution network side and a user on the user side.

Step 5, storing the user side topological data, and executing the step 4 again when the corresponding power-off line information is obtained; this step is primarily hysteresis of the test data.

And 6, identifying the phase sequence relation between the distribution area and the user according to the topological data of the low-voltage line, and constructing and perfecting the topological relation of the low-voltage distribution network. Whether private wiring exists or not and whether the phase sequence relationship is reasonable or not are judged according to the relationship between a user in the low-voltage line topology data and the upper-stage electric meter box.

The method provided by the embodiment can be used for automatically identifying the low-voltage line topology by combining the existing network equipment of the user, identifying the phase sequence relation between a distribution area and the user by using the synchronism of means such as switch reclosing operation and the like and a handshake signal of the user in the morning, constructing and perfecting the topological relation between the distribution transformer, the branch box and the meter user, effectively avoiding the problems of three-phase imbalance, single-phase overload, low voltage and the like, and improving the operation level of a distribution network;

according to the method provided by the embodiment, the power grid operation and inspection daily work such as power failure events of the power distribution network, scheduled maintenance and switch reclosing operation in the morning is utilized, the power grid lines and equipment do not need to be modified, the workload of maintenance personnel does not need to be increased, the investment cost is low, and the effect is fast.

This example further illustrates the above method by the following case:

assuming the same building, 8 dwellings per floor, 101 users A are privately connected to 3-floor electricity meter boxes. The historical data of the network operator side contains 101 network equipment power-down data, the corresponding actual power-down line of the distribution network side is a 3-floor electricity meter box, and 8 users on 3 floors are all disconnected. By using the method, when the network power failure data of 101 user A and the network power failure data of 8 house types in the 3 rd building are obtained, the power failure data of the electricity meter box in the 3 rd building on the distribution network side is matched according to the occurrence time and the cell of the power failure event, and the final low-voltage line topological data obtained by user association are as follows: the power station area, the distribution box, the electric meter box, 3 floors, 8 users and 101 users A. According to the low-voltage line topological data, the phase sequence relation and whether the condition of private power lines exists can be judged by combining the low-voltage line topological data with the low-voltage line topological data of other power failure events of other same buildings, and the improvement can be completed.

Example 3: method for carrying out power consumption habit portrait and making maintenance plan on user by utilizing power failure and power restoration data of network equipment

The embodiment provides a method for drawing electricity consumption habit and making a maintenance plan for a user by using power failure and power restoration data of network equipment, as shown in fig. 4, the method comprises the following steps:

step 1, constructing a data set, wherein the data set comprises at least user side electricity utilization data and distribution network side overhaul data, the user side electricity utilization data comprises user network equipment power loss and recovery data and user network flow time period data, and the distribution network side data comprises distribution network side emergency repair data and user complaint data received by a distribution network side;

step 2, on the basis of a user, associating the power failure and power restoration data of the user network equipment with the first-aid repair data on the distribution network side and the user complaint data received by the distribution network side to obtain power failure habit data of the user and regional power utilization habit data;

the method specifically comprises the following steps: according to the sn number of the user power-down network equipment and the equipment fingerprint, the city where the user side is located is obtained, the region, the district, the building, the floor and the house number information, according to the power failure time of the user and the power failure region, the power failure circuit information corresponding to planned maintenance, switch reclosing in the morning and repair is searched, the power failure circuit information corresponding to repair is searched on the basis of the user, whether the planned maintenance corresponds to is searched, switch reclosing in the morning and repair is found, if so, the power failure is determined as passive power failure, if not, the power failure is determined as autonomous power failure, and the corresponding power recovery behavior is also the autonomous power recovery behavior.

And 3, carrying out power utilization requirement and time interval label definition on the user according to the network flow time interval data of the user, and carrying out active power-off habit label definition on the user according to the power utilization habit data of the user.

Step 4, training a random forest model by using a training sample to obtain a target model; the height of the decision tree of the random forest algorithm is h, and the number of the decision trees is N. The height h and the number N are set depending on the data size and the task. The task is set to h 4 and N100.

Step 5, constructing a user electricity consumption portrait and a regional electricity consumption portrait by using the target model;

and 6, generating a maintenance plan with a small influence range by combining the current scheduling of the maintenance team according to the user electrical portrait at the distribution network side.

According to the embodiment, according to the power consumption data of the user, the data of the distribution network side is used for verification, the power consumption behaviors of the user are obtained, such as regular power failure and network flow use time period, labels such as regular power consumption demand rules and time period of the user are counted, model training is carried out by using the data with the labels, a target portrait model is obtained, the user portrait is calculated by using the target portrait model, the distribution network side counts, analyzes and examines the influence of maintenance operation according to the power consumption data of the user, then the influence range is small, the maintenance plan with low economic loss is formulated, and the service quality of the distribution network is improved.

Example 4: low-voltage power grid first-aid repair, operation and maintenance management method combining real-time power failure and power restoration information

The embodiment discloses a low-voltage power grid first-aid repair, operation and maintenance management method combining real-time power failure and power restoration information, which comprises the following steps as shown in fig. 5:

acquiring power failure and power restoration data of network equipment in real time, and studying and judging whether a power failure and power restoration event occurs according to the power failure and power restoration data;

step two, if no power failure and power restoration event occurs, the research and judgment are finished; if a power failure and power restoration event occurs, processing in the third step is carried out;

analyzing event information according to the power failure recovery data, wherein the event information at least comprises an event type, an event area, a power failure account number and occurrence time;

step four, judging whether the event is power failure or power restoration according to the event information, and if the event is a power failure event, simultaneously performing the processing of the step five and the step eight; if the power restoration event occurs, processing in the ninth step is carried out;

fifthly, judging the influence range according to the event area, the power failure house number and the power failure time information aiming at the power failure event;

the specific judgment method comprises the following steps:

5.1 when each power failure occurs within a set close time (such as 1 minute), and the distance does not exceed a set threshold (such as 2 kilometers) by combining the geographic position coordinates, determining a large-range power failure event; overlapping the areas of the power failure events to be used as the influence range of the large-scale power failure event;

5.2 if only a single power failure event occurs in the close time or the close position, analyzing the building information corresponding to the power failure users according to the power failure user number, and if the power failure users are distributed in multiple buildings, judging that the power failure occurs in the community;

and 5.3, if the power failure users are distributed in a single building, continuously analyzing the distribution floors of the power failure users, and if the power failure users are distributed on all the floors, judging that the building has power failure, otherwise, judging that the floors have power failure.

Step six, acquiring the mobile phone number of the actually affected person and the mobile phone number of the householder according to the influence range; the method specifically comprises the following steps:

case 1

If the power failure time is non-floor power failure, the method for acquiring the mobile phone number of the actually affected person specifically comprises the following steps:

In this embodiment, the method 1, the method 2, or the method 3 may be selected alternatively, where the method 3 is optimal, so as to avoid missing resident information.

Case 2

And if the power failure event is floor power failure, acquiring the SN number of the network equipment installed on the corresponding floor of the power failure area and the mobile phone identification code of the connecting equipment thereof through the operator account, acquiring user information according to the mobile phone identification code and the operator account, and determining the mobile phone number of the affected personnel.

Step seven, pushing real-time power failure information to actually affected personnel and householders;

step eight, according to the event region, acquiring a corresponding region rush-repair team group, and pushing a rush-repair task to the rush-repair team group, specifically:

firstly, calling a basic ledger according to an event area, acquiring a responsible person and an emergency repair team of a corresponding area, automatically appointing an emergency repair plan according to task arrangement of each emergency repair team, assigning the emergency repair team, and sending a power failure event and emergency repair task information to the responsible person and a person responsible for the emergency repair team; and checking the detailed plan and the task arrangement by related personnel of the emergency repair team, timely arriving at the site for emergency repair, and performing site verification, emergency repair progress and emergency repair result feedback to a responsible person in real time.

And step nine, after the first-aid repair work is finished, the power restoration information is pushed to actual affected personnel and householders.

Example 5: method for studying and judging power failure and power restoration of low-voltage power grid by using power failure and power restoration data of network equipment

As shown in fig. 6, the embodiment discloses a method for studying and judging power failure and power restoration of a low-voltage power grid by using power failure and power restoration data of network equipment. The network device in this embodiment may be a modem, a set-top box, or the like. The judging process specifically comprises the following steps:

step 1, acquiring a power failure signal of user network equipment, judging whether the user power failure behavior is artificial power failure or equipment fault power failure, and if the user power failure behavior is artificial power failure, finishing analysis; if the equipment is in failure and power failure, executing the step 2;

in this embodiment, the user power-down behavior includes artificial power-down and equipment fault power-down. The artificial power failure generally means that a user disconnects a home electric main gate every day when going to work and then gets on the home; a certain user goes on business and closes a home electric power distribution gate and the like at the beginning of each month, and the target model judges whether the power failure is artificial power failure or equipment failure power failure according to the power failure behavior habit of the user.

Step 2, setting power-down users in a set time length as a group by taking the electric meter box as a unit according to the electric meter box and the power-down time related to the power-down signal; determining that the number of the users with network equipment power failure in the same time range is smaller than a threshold value as the user artificial power failure; if the number of households is larger than the threshold value, the user information hung under the electric meter box is tracked and inquired through the electric meter box, if 8 users are hung under a certain electric meter box, wherein 5 users are mobile broadband users, and 4 currently received optical modem power-down signals exist, the users who do not receive the optical modem power-down signals can be traced forward, if the users have power-down before the batch optical modem power-down signals occur in the current time and do not perform power-restoration operation, the batch optical modem power-down can be judged to be that all mobile users in the current electric meter box have power-down at the same time, and the possibility of power-down of the electric meter box is 100%; if the house is in a power restoration state before the batch optical modem power failure signal occurs and the power failure signal is not received in the batch power failure, the real-time performance and the accuracy of the optical modem signal need to be judged (a, real-time judgment needs to wait for the next power failure signal interface period and see whether the optical modem signal interface period is in the next power failure signal data, and b, accuracy judgment needs to judge whether the power failure signal of the house and the pair and the sequence of the power restoration signal are normal according to historical data), and the power failure possibility of the electric meter box is subjected to power reduction treatment.

Step 3, as shown in fig. 7, if it is determined that the electric meter box has a power failure, the information of the branch box to which the electric meter box belongs can be traced through a low-voltage power grid topological model, through a topological relation, the power failure information of all users to which the electric meter box belongs under the branch box belongs is firstly obtained, the logic in the step 2 is repeated one by one for the electric meter boxes, the power failure possibility of each electric meter box is determined, if it is determined that the electric meter box has no power failure possibility, the branch box is jumped out for determination, and no power failure occurs in the branch box; if all the electric meter boxes are judged to have power failure, the branch box can be judged to have power failure; if a part of the electric meter boxes judge power failure and the possibility of power failure of a part of the electric meter boxes exists (if the power failure possibility of the electric meter boxes in the step 2 is less than 100%), obtaining the power failure possibility of the branch boxes according to a designed threshold;

step 4, as shown in fig. 8, if it is determined that a branch box has a power failure, the information of the area to which the branch box belongs can be traced back through a low-voltage power grid topology model, through a topology relation, the system first obtains the information of all branch boxes under the area, the logic in the step 3 is repeated one by one, the power failure possibility of each branch box is determined, if there is a branch box, the branch box is determined to have no power failure possibility, the branch box is jumped out for determination, and the power failure does not occur in the area; if all branch boxes are judged to have power failure, the power failure in the distribution area can be judged; if a part of branch boxes judge that power failure exists and a part of branch boxes have power failure possibility (if the power failure possibility of the branch boxes in step 3 is less than 100%), the power failure possibility of the transformer area needs to be obtained according to a designed threshold value.

In this embodiment, the user profile is determined from embodiment 3 to determine whether the power outage is an artificial power outage or an equipment failure power outage.

In the foregoing, in the power failure determination of the electric meter box, the branch box and the distribution room, when the power failure condition of a single user needs to be analyzed and the real-time performance and accuracy of a single optical modem signal need to be determined, the accuracy of the power failure signal can be deduced by means of the neural network algorithm analysis result, more accurate power failure possible information is provided, for example, a certain user disconnects a home electric main gate when going to work every day and then gets home; a user can go on business and close a home electric main gate and the like at the beginning of a month, the system can be compared with the current occurrence time and range of power down signals according to multi-level data model establishment and algorithm analysis, and if the current batch of optical modem power down signals occur in a time period which is the time of regular artificial power failure of the user, the weights of the electric meter boxes passing through the connection nodes in the established network structure diagram are added, namely the possibility of power failure of the current electric meter boxes is added.

The method utilizes the existing network equipment of the user to study and judge the power failure and the power restoration of the low-voltage distribution network, does not need to modify the power grid lines and the equipment, is simple and easy to apply, does not influence the power utilization of the user, and has low investment cost;

example 6: address matching

The present embodiment provides an address matching method, which aims to provide an accurate address for event matching between a user side and a distribution network side, and as shown in fig. 9, fig. 10, and fig. 11, the specific method is as follows:

forming a 7-level address classification dictionary by constructing address word segmentation dictionary elements, wherein the 7-level address classification dictionary comprises primary part-of-speech state elements such as provinces, communities, buildings, house numbers and the like, constructing secondary dictionaries such as texts, special characters, numbers and the like for each primary part-of-speech state, calculating a forward maximum matching model and a reverse maximum matching model for an address to be matched by adopting a bidirectional maximum matching model, and outputting the address with consistent word segmentation as a standard address:

HMM algorithm recognition is carried out on the address to be matched with the inconsistent address word segmentation, state value recognition is achieved, and address word segmentation is completed according to the Vibe algorithm

Step 1: configuring a first-level address word segmentation element list

The method comprises the steps of forming a first-level word segmentation word bank construction for provincial, road and community names by combining network map data through standard files such as national administrative district division, national road name management standard and the like, commodity room record registration management data registered by the national room administration and community name data of a second-hand room transaction platform, and adopting a whole word segmentation interface to construct a word segmentation table structure

Step 2: construction second-level address word division dimension table

Defining and segmenting words for elements such as numbers, special symbols and the like possibly existing in the first-level segmentation element list, and avoiding influence on analysis results caused by writing habits and the appearance of special symbols in addresses

And step 3: address word segmentation recognition by adopting forward maximum matching algorithm

Identifying the address to be matched according to the primary and secondary address word segmentation element dictionaries, judging the filling specifications of provinces, cities and districts in the address to be matched, if the address is ended according to the Chinese word segmentation in the province, city, district and primary address word segmentation dictionary, judging the address to be the standard address, directly segmenting words, if the address is not standard, checking according to the word tails of the province, city and district segmented words in the dictionary, if the word tails are the same, supplementing one bit forward for checking, and iterating to obtain the complete address word segmentation

And 4, step 4: hierarchical word segmentation recognition

Carrying out grading word segmentation matching on the address, wherein the grading size of the address is as follows: the province, city, district, road and cell name 5 level word recognition function supplements missing levels in the address, such as: 1 Huangshan Lugui garden 101 in Hefei city needs to be added to the 'district' level after grading word segmentation and recognition, and the address after matching is as follows: 1 garden district of Huangshan Lu Gui garden in Shushan district of Hefei city 101

And 5: bidirectional maximum matching algorithm check address participle

Performing word segmentation on the address to be matched by adopting a reverse maximum matching algorithm, comparing the word segmentation result with the word segmentation result of the forward maximum matching algorithm, and if the word segmentation result is consistent, determining the address to be matched as a standard grading address; if the word segments are different, the address is a non-standard hierarchical address

Step 6: and training an HMM address hierarchical prediction model to realize 5-level hierarchical prediction of province, city, district, road and cell names of the non-standard hierarchical addresses.

Selecting 5-level standard address training data of provinces, cities, districts, roads and cells after manual marking, training an HMM prediction model, and establishing a probability map mapping relation from a non-standard hierarchical address to a standard hierarchical address, so that the non-standard hierarchical address is predicted to be the standard hierarchical address. Such as: the 5-level addresses are respectively predicted through an HMM model, and the results are the Luoyang street four-channel road and the Hangzhou road intersection Binghuxin garden in the Baoyu river area of the Hebei city.

And 7: standard participle address verification

And manually checking the word segmentation result, and if the word segmentation address has deviation, adjusting a word segmentation dictionary to complete the matching of the address word segmentation.

The implementation is well implemented by building a primary and secondary word segmentation element word bank, the word segmentation rules of texts such as numbers, special characters and the like which possibly influence word segmentation results in the regular word segmentation are perfected, lost data are filled in addresses according to a hierarchical word segmentation mode, a mixed word segmentation mode is adopted, the regular word segmentation and statistical word segmentation are combined, the advantages of the two word segmentation modes are combined, and the efficiency and the accuracy of address word segmentation are improved

Example 7: data acquisition

In this embodiment, because there is a high requirement for real-time performance of data in actual work and data standardization, combination and improvement of the collected data with the power grid are required, as shown in fig. 12 and 13, the specific method is as follows:

step 1: obtaining power down/power back alarm data of broadband equipment

According to the identification code of the broadband equipment, relevant data of power failure/power restoration alarm of onu equipment, such as power failure time, power failure data server time, equipment identification code, equipment power restoration time and the like, are realized

The TL1 command is sent and responded through a socket based on TCP/IP, so that the power failure and power restoration information of the equipment can be timely acquired.

1. An Operation Support System (OSS) initiates a request to establish a connection to a PON EMS (Element Management System).

EMS is used as a server end to provide an available TCP SOCKET interface, monitor and accept the connection request of the OSS system and establish connection.

3. When the connection is established and the login authentication is passed, the OSS system may initiate a TL1 command to the EMS, and the EMS executes the corresponding command and returns the result

Step 2: device data forwarding

And after receiving the equipment performance data, the network management support system completes alarm standardization on the performance data according to the required equipment power failure/power restoration alarm data and then pushes the performance data to the MQ. And the data sharing platform encapsulates the MQ into an API for downstream calling. Meanwhile, the API source Address adopts VIP (Virtual IP Address/Virtual IP Address), and actually adopts three servers which are mutually active and standby, so that the reliability of data forwarding is ensured.

And step 3: sending MQ messages to kafka platform

The Flink (Apache Flink is an open source stream processing framework developed by an Apache software foundation, and the core of the framework is a distributed stream data stream engine written by Java and Scala, the Flink executes any stream data program in a data parallel and pipeline mode, and a pipeline runtime system of the Flink can execute batch processing and stream processing programs) to consume message data in MQ in real time and push the message data to an application Kafka cluster in real time after the message data is processed by specific service logic in the Flink.

The data transmission method of the embodiment realizes real-time data acquisition and transmission in the low-voltage power failure perception system, and in the data transmission process, an MQ message mode is selected, so that compared with an API interface provided after database query, the data transmission method can write the message into a message queue at a higher speed, and the response speed is accelerated. Decoupling between applications is met, and the upstream interface and the downstream interface are not influenced mutually any more. The expansibility is improved, and a plurality of downstream manufacturers are supported to subscribe and consume at the same time. The original API interface requires different manufacturers to develop different interfaces.

ActiveMQ is selected from MQ, and because activeMQ belongs to a mature and stable product in various MQ, the method can meet the current message processing requirement.

Example 8: distribution network side operation and maintenance system using low-voltage network data

Corresponding to the foregoing embodiment 1, this embodiment provides a distribution network side operation and maintenance system using low-voltage network data. At present, the network almost covers urban and rural areas and mountain areas. By utilizing the high coverage rate of the network, a data basis can be provided for daily operation and maintenance of the distribution network side. The method comprises the following steps:

the topology identification module is used for identifying the topology of the low-voltage line according to the user network equipment data and the historical data of the distribution network side, and the specific method comprises the following steps:

step 21, grouping power failure historical data of the network equipment at the user side according to cells, judging address information of a power failure user according to the grouped data, and generating topological data at the user side;

step 22, according to the time and the cell of the power failure event of the user at the user side, searching corresponding power failure line information from the historical data at the distribution network side, and if the corresponding power failure line information can be searched, executing step 23; if not, executing step 24;

step 23, acquiring distribution network side topology data of the power-off line information, and associating the user side topology data with the distribution network side topology on the basis of user association to obtain low-voltage line topology data;

step 24, storing user side topological data, and executing step 23 again when corresponding power-off line information is acquired;

the user portrait depicting module is used for depicting the power consumption portrait of the user by utilizing the user network equipment data and the historical data of the distribution network side, and the specific method comprises the following steps:

step 24', training a random forest model by using a training sample to obtain a target model; step 25', constructing a user electricity consumption portrait and a regional electricity consumption portrait by using the target model;

the maintenance operation plan making module is used for making a first-aid maintenance operation plan according to the current network equipment power failure data and the user portrait; the method specifically comprises the following steps:

the low-voltage power grid power failure and restoration judging module is used for judging power failure and restoration of the low-voltage power grid according to power failure data of a user network, and the specific method comprises the following steps:

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. The distribution network side operation and maintenance method utilizing the low-voltage network equipment data is characterized by comprising the following steps of:

2. The distribution network side operation and maintenance method using low-voltage network equipment data as claimed in claim 1, wherein the distribution network side power failure historical data in step 1 includes power failure line information of scheduled maintenance, early switch reclosing, and repair reporting.

3. The distribution network side operation and maintenance method using low-voltage network device data according to claim 1, wherein the specific process of step 21 is as follows:

according to the sn number and the equipment fingerprint of the power-down network equipment, the information of a city, an area, a cell, a building, a floor and a house number where the user side is located is obtained, and topological data of the user side cell-building-floor-user are generated.

4. The distribution network side operation and maintenance method using low-voltage network device data according to claim 3, wherein the specific process of the step 22 is as follows: according to the power failure time and the power failure area of a user, searching power failure line information corresponding to scheduled maintenance, switch reclosing in the morning and repair reporting, acquiring topological data of a transformer area, a branch box, an electricity meter box and a user of the power failure line information, and taking the user as a correlation basis to obtain low-voltage line topological data which are the transformer area, the branch box, the electricity meter box, a distribution network side user and a user side user.

5. The distribution network side operation and maintenance method using low-voltage network device data according to claim 4, wherein the step 25 specifically comprises:

6. The distribution network side operation and maintenance method using low-voltage network device data as claimed in claim 1, wherein the step 23' is specifically to perform power demand and time interval label definition on the user according to the user network traffic time interval data, and perform active power-off habit label definition on the user according to the user power consumption habit data.

7. The distribution network side operation and maintenance method using low-voltage network device data as claimed in claim 1, wherein the step 26' is specifically that the distribution network side generates a maintenance plan with a small influence range according to the user electrical representation and the current scheduling of the maintenance team.

8. The method of claim 1, wherein the network side operation and maintenance method using low voltage network device data,

9. The distribution network side operation and maintenance method using low-voltage network device data as claimed in claim 1, wherein in the step 36, if the power outage time is non-floor power outage, the method for acquiring the mobile phone number of the actually affected person specifically comprises:

in the method 1 or the method 2, one of them is selected.

10. The distribution network side operation and maintenance method using low-voltage network device data as claimed in claim 9, wherein if the power outage time is non-floor power outage, the method for acquiring the mobile phone number of the actually affected person may further be:

11. The distribution network side operation and maintenance method using low-voltage network device data as claimed in claim 1, wherein in step 36, if the power failure event is a floor power failure, the SN number of the network device and the mobile phone identification code of the connection device installed on the corresponding floor of the power failure area are obtained through an operator account, and the mobile phone number of the affected person is determined by obtaining the user information according to the mobile phone identification code and the operator account.

12. The method as claimed in claim 1, wherein the step 41 is performed to determine whether the power down behavior is an artificial power down or a device failure power down according to the user profile.

13. The distribution network side operation and maintenance method using low-voltage network device data according to claim 12, wherein in step 42, if the number of users to which the electricity meter box belongs is greater than a threshold value, but only some users are powered down, it is necessary to trace whether the users without power down have power down behavior before the current time period, and if yes and not power up again, it is determined that all users to which the current electricity meter box belongs are powered down, and the electricity meter box is determined as powered down; if the network equipment is in the power restoration state before the power failure signal occurs, the real-time performance and accuracy of the network equipment signal of the user need to be judged.

14. The distribution network side operation and maintenance method using low-voltage network device data as claimed in claim 13, wherein the method for judging the real-time performance and accuracy of the power-down signal of the user network device comprises:

15. Utilize distribution network side operation and maintenance system of low pressure network equipment data, its characterized in that includes:

16. The system of claim 15, wherein the power distribution network side power failure history data in the data acquisition module comprises power line information for scheduled maintenance, early switch reclosing, and repair reporting.

17. The system of claim 15, wherein the specific process of step 21 is as follows:

18. The system of claim 17, wherein the specific process of step 22 is as follows: according to the power failure time and the power failure area of a user, searching power failure line information corresponding to scheduled maintenance, switch reclosing in the morning and repair reporting, acquiring topological data of a transformer area, a branch box, an electricity meter box and a user of the power failure line information, and taking the user as a correlation basis to obtain low-voltage line topological data which are the transformer area, the branch box, the electricity meter box, a distribution network side user and a user side user.

19. The distribution network side operation and maintenance system using low-voltage network device data according to claim 18, wherein the step 25 specifically comprises:

20. The distribution network side operation and maintenance system using low-voltage network device data as claimed in claim 15, wherein the step 23' is specifically to perform power demand and time interval label definition on the user according to the user network traffic time interval data, and perform active power-off habit label definition on the user according to the user power consumption habit data.

21. The distribution network side operation and maintenance system using low-voltage network device data as claimed in claim 15, wherein the step 26' is specifically that the distribution network side generates a maintenance plan with a small influence range according to the user electrical representation and the current scheduling of the maintenance team.

22. The system of claim 15, wherein the network side operation and maintenance system using low voltage network device data,

in the method 1 or the method 2, one of them is selected.

24. The distribution network side operation and maintenance system using low-voltage network device data as claimed in claim 23, wherein if the power outage time is a non-floor power outage, the method for acquiring the mobile phone number of the actually affected person may further be:

25. The distribution network side operation and maintenance system using low-voltage network device data according to claim 15, wherein in step 36, if the power failure event is a floor power failure, the SN number of the network device and the mobile phone identification code of the connection device installed on the corresponding floor in the power failure area are obtained through an operator account, and the mobile phone number of the affected person is determined by obtaining the user information according to the mobile phone identification code and the operator account.

26. The system of claim 15, wherein the power down behavior is determined to be an artificial power down or a device failure power down according to the user profile in step 41.

27. The distribution network side operation and maintenance system using low-voltage network device data according to claim 26, wherein in step 42, if the number of users to which the electricity meter box belongs is greater than a threshold value, but only some users are powered down, it is necessary to trace whether the users without power down have power down behavior before the current time period, and if yes and not power up again, it is determined that all users to which the current electricity meter box belongs are powered down, and the electricity meter box is determined as powered down; if the network equipment is in the power restoration state before the power failure signal occurs, the real-time performance and accuracy of the network equipment signal of the user need to be judged.

28. The distribution network side operation and maintenance system using low voltage network device data of claim 27, wherein the method for determining the real-time and accuracy of the power down signal of the user network device comprises: