CN114493926A - Line loss lean management and electricity larceny prevention method and system based on terminal edge calculation - Google Patents
Line loss lean management and electricity larceny prevention method and system based on terminal edge calculation Download PDFInfo
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Abstract
The invention belongs to the field of power equipment, and particularly relates to a line loss lean management and electricity larceny prevention method and system based on terminal edge calculation. The method comprises the following steps: s1: collecting power information of each power utilization node through a concentrator, and S2: deploying an edge calculation module in each concentrator, and then calculating the hour, day and month of the line loss rate corresponding to the current equipment node and the annual statistical result; s3: the concentrator sends the own equipment number, the real-time collected power information and the calculated line loss data statistical result to the cloud server; s4: the cloud server analyzes whether the line loss fault exists in the whole power utilization transformer area or not, and judges whether the transformer area has electricity stealing behavior or not when the line loss abnormal state exists; s5: and the cloud server sends the line loss fault result and the electricity stealing judgment conclusion to corresponding station area management personnel. The method and the system solve the problems that the line loss analysis is not timely in the conventional power management system, the cloud server has heavy processing tasks, the risk resistance is weak and the like.
Description
Technical Field
The invention belongs to the field of power equipment, and particularly relates to a line loss lean management and electricity larceny prevention method and system based on terminal edge calculation.
Background
In a power grid, the unreasonable configuration of the power transmission and distribution transformer can cause the power transmission and distribution transformer to be in an idle load or light load operation state for a long time, so that the power loss is greatly increased. The electric energy loss on the line is mainly caused by three parts, namely, three phases of a power grid are in accordance with unbalance, and the power factor is low. And secondly, the power grid layout is unreasonable, the power supply line is too long or the accuracy of the metering equipment is poor. And thirdly, the equipment management and maintenance are not standard, and the actions of electric leakage, electric larceny and the like exist.
Among them, there is a three-phase unbalanced load phenomenon in the distribution line, and when the three-phase unbalanced load degree is more than 20%, the current in the line will be greatly increased, resulting in a large increase of the power loss. For example, in an industrial and mining enterprise, many electric devices belong to inductive electric devices, and an inductive load absorbs active power of a system and simultaneously needs a power system to provide a large amount of reactive power to normally operate. In the process of transporting and distributing the reactive power provided by the system, when more power transmission lines are involved and need to be converted and transmitted by a transformer, the reactive power loss is easily increased, so that the power factor of the power grid is reduced.
In the construction of a power grid, if the transformer is not reasonably arranged, the power supply point and the load center are greatly deviated, and the problems of power supply in a circuitous mode or near-power and far-power transmission, or the problems of over-small wire section or long power supply radius and the like exist; a large increase in power consumption may be caused. Meanwhile, if the node metering equipment has the problem of poor accuracy during metering, the electric quantity is easily lost. The problems of unreasonable metering mode, high supply and low supply and the like often exist in partial electric quantity metering. In addition, the multiplying power of the electric energy meter or the mutual inductor has errors, the configuration of a metering loop is unreasonable and the like, and the electric energy loss is increased to different degrees.
Grid management irregularities are the most important human cause of line loss. If the equipment is not properly maintained, phenomena such as electric leakage and electric discharge can occur; accurate statistics is not carried out during reading and checking, and phenomena of estimated reading, less reading, missing reading and the like exist; the errors of the statistical power consumption and the actual power consumption can be larger, and the line loss statistical result is increased. Meanwhile, various electricity stealing behaviors exist in various places, and the electricity stealing behaviors are also one of the reasons for increasing line loss.
In an existing power management system, all power utilization nodes in a distribution room are generally required to be analyzed at a cloud server according to large-scale historical data, and then a comprehensive line loss analysis result of a line is estimated. By comparing the calculated theoretical line loss with the statistical actual line loss, the rationality of the structure and operation of the power supply network and the scientificity of power supply management can be identified. And problems in the aspects of metering devices, equipment performance, power consumption management, operation modes, theoretical calculation, reading statistics and the like are found in time so as to provide decision support for the economic operation of the power grid of the power operation enterprise by taking loss reduction measures.
However, the conventional line loss analysis and evaluation are usually completed in a background data center such as a cloud server, and the cloud server needs to perform comprehensive analysis processing on mass data when a settlement period is reached. The data processing process of the management method is complicated, the management method highly depends on the cloud, and meanwhile the management method has the defect of lag in monitoring.
Disclosure of Invention
The problems that line loss analysis is not timely, the line loss analysis is highly dependent on a cloud server, the risk resistance is weak, the data volume in the line loss analysis process is too large, the data processing process is not flexible and the like in the conventional power management system are solved. The invention provides a line loss lean management and electricity larceny prevention method and system based on terminal edge calculation.
The invention is realized by adopting the following technical scheme:
a line loss lean management and electricity stealing prevention method based on terminal edge calculation is used for achieving electricity consumption information, statistics and analysis at a power equipment terminal, further lean management is conducted on line loss of a distribution room, line loss faults are responded timely, and electricity stealing behavior is prevented. The method for line loss lean management and electricity larceny prevention specifically comprises the following processes:
s1: and acquiring the power information of each power utilization node through the concentrator according to a preset acquisition frequency, wherein the power information comprises voltage, current, active power, reactive power and frozen electric quantity.
S2: and deploying an edge calculation module in each concentrator, and calculating the hour, day and month of the line loss rate corresponding to the current equipment node and the annual statistical result according to the historical information of the acquired power information within one hour after each acquisition.
S3: the concentrator sends the equipment number of the concentrator and the power information acquired in real time to the cloud server for backup storage, and meanwhile, sends the updated data of the calculated line loss data statistical result to the cloud server every hour.
S4: the cloud server analyzes whether line loss faults exist in the whole power utilization area or not according to the obtained line loss rate statistical results calculated by the concentrators, and judges whether electricity stealing behaviors exist in the area or not when the line loss abnormal state occurs;
s5: and the cloud server sends the analyzed line loss fault result, the analyzed electricity stealing judgment conclusion and the corresponding electricity utilization node information to corresponding station area management personnel and sends corresponding fault processing suggestions at the same time.
As a further improvement of the present invention, in step S1, the power information collected by the collector further includes hour freezing data of the electric meter, day freezing data of the electric meter, hour freezing data of the circuit breaker, and day freezing data of the circuit breaker.
As a further improvement of the present invention, the concentrator further includes a storage module. The storage module is used for storing historical information of the power information collected within one hour and calculating a line loss rate statistical result of the current equipment node according to the historical information.
As a further improvement of the present invention, in step S1, the storage module stores the history information collected by the concentrator and the calculated statistical result in specific storage units respectively; and the historical information of the stored power information is covered every other hour, and meanwhile, the statistical result of the line loss rate is updated.
As a further improvement of the present invention, in step S2, the statistical results of the line loss rate respectively include: the initial electric quantity of the equipment, the ending electric quantity of the equipment, the line loss rate in the last hour and the line loss rate in the last day; the last day A phase line loss rate, the last day B phase line loss rate, the last day C phase line loss rate, the current month bus loss rate, the current month A phase line loss rate, the current month B phase line loss rate, the current month C phase line loss rate, the current year bus loss rate, the current year A phase line loss rate, the current year B phase line loss rate and the current year C phase line loss rate.
As a further improvement of the present invention, the edge calculation module in the collector completes calculation of the line loss rate statistical result through a statistical model, model registration or update needs to be performed before the statistical model performs data interaction with the data center in the cloud server, and the registration or update process of the model is as follows:
s01: and the cloud server reads the latest version number and model name of the statistical model.
S02: the cloud server checks and compares the model name corresponding to the current version number in the concentrator with the model name corresponding to the latest version number in the cloud server, judges whether the model names are consistent with each other, and makes the following decision:
(1) and when the version number of the current version number is consistent with the version number of the current version number, judging that the model of the current version number is valid, and reading the specified model content.
(2) And when the two are not consistent, judging that the model of the current version number is invalid, and updating the statistical model in the concentrator according to the statistical model of the latest version in the cloud server.
S03: the cloud server reads registration information of the statistical model in the concentrator.
S04: the cloud server checks whether the statistical model is registered, and makes the following decision:
(1) if yes, the registration or update process is determined to be completed.
(2) Otherwise, the setting of the model registration process is completed again.
S05: after the model registration is completed, the concentrator requests parameter information for calculating a line loss rate statistical result from the server.
As a further improvement of the present invention, in steps S2 and S3, the data processing procedure of the statistical model is as follows:
s001: requesting original data used for calculating a line loss rate statistical result, and judging whether the data is successfully acquired:
(1) if yes, go to the next step.
(2) Otherwise, the calculation process is interrupted, and error information containing the data acquisition error reason is printed.
S002: calculating the statistical result of the line loss rate according to the original data obtained in the previous step, and judging whether the calculation result is legal:
(1) if yes, go to the next step.
(2) Otherwise, the data uploading is interrupted, and error information containing illegal data types is printed.
S003: and (3) the statistical result of the line loss rate calculated in the previous step is sent to a cloud server, and whether the uploading is successful or not is judged according to the return information of the cloud server:
(1) if yes, the printing data is uploaded successfully.
(2) Otherwise, printing the reason of uploading failure.
As a further improvement of the present invention, in step S4, a fault analysis tool is run in the cloud server, and the fault analysis tool is used for analyzing a possible line loss fault or electricity stealing behavior in the whole distribution area or in the power supply network according to historical statistical data of the line loss rate of each node. And positioning to corresponding risk nodes, and issuing early warning signals aiming at the risk nodes.
The invention also comprises a line loss lean management and electricity stealing prevention system based on the terminal edge calculation, which adopts the line loss lean management and electricity stealing prevention method based on the terminal edge calculation to manage the line loss of all the nodes in the distribution area, process the line loss fault and monitor the electricity stealing behavior in time. The line loss lean management and electricity larceny prevention system comprises: the device comprises a concentrator, an edge computing module and a cloud server.
The concentrator is installed at each power utilization node in the power supply area, is used for collecting power information of each node in the power supply area, and sends the power information to an edge computing module and a cloud server.
The edge calculation module is electrically connected with the concentrator and used for receiving the electric power information collected by the concentrator and calculating a statistical result of the line loss rate in the current node according to historical data of the electric power information in a preset period; and sending the line loss rate statistical result to a cloud server.
The cloud server is used for storing the power information of each power utilization node and the statistical result of the line loss rate. The cloud server also comprises an electricity stealing behavior analysis tool which is used for judging whether line loss faults or electricity stealing behaviors exist in the power supply area or the whole power supply network according to the statistical result of the line loss rate of each node; and positioning to corresponding risk nodes, and issuing early warning signals aiming at the risk nodes.
As a further improvement of the invention, the line loss lean management and electricity stealing prevention system also comprises a management terminal, and the management terminal is in communication connection with the cloud server; the management area of each management terminal corresponds to one or more power utilization nodes in the power utilization area. The management terminal is distributed to corresponding management personnel, and when the cloud server is positioned to the risk node, an early warning signal is sent to the corresponding management terminal; the management terminal is a special terminal or a general mobile terminal running with a power management APP; the management terminal is also used for inquiring the historical data of each node in the management area.
The technical scheme provided by the invention has the following beneficial effects:
according to the invention, a data processing module with edge computing capability is deployed in a concentrator for automatically acquiring and uploading electric power information, the data acquisition is uploaded by the concentrator, related data is acquired at the same time, and the calculation process of the line loss statistical result in the current node is completed locally by using the related data. And simultaneously uploading the line loss data of the current node to a cloud server. The line loss statistical result of each node can be obtained immediately after the collected data of the concentrator is generated; therefore, the timeliness of the speed limit data is greatly improved, and a foundation is laid for rapidly processing line loss faults and timely discovering electric larceny behaviors.
The method of the invention changes the centralized processing of the data processing method for evaluating the line loss in the power supply network into a distributed processing mode based on the calculation capability of the edge of the terminal. The operation pressure of the background data center can be greatly reduced; meanwhile, the influence of faults such as downtime of the background server on the normal operation of the power supply network can be reduced, and the overall safety and fault-tolerant capability of the system are improved.
Although the line loss data statistics task of each node is not completed in the background server, the line loss fault analysis and electricity stealing behavior judgment behaviors of the power supply network based on all the node data are still completed by the background server. And the background server enables the judgment result to be sent to each concentrator or management terminal, so that management personnel can conveniently process faults and eliminate risks in time.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart illustrating steps of a method for line loss lean management and electricity larceny prevention based on terminal edge calculation according to an embodiment 1 of the present invention;
FIG. 2 is a flowchart of a process of registering or updating a statistical model according to embodiment 1 of the present invention;
fig. 3 is a flowchart of a data processing procedure of the statistical model in embodiment 1 of the present invention.
Fig. 4 is a system block diagram of a system for line loss lean management and power stealing prevention based on terminal edge calculation according to embodiment 2 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
As shown in fig. 1, this embodiment provides a line loss lean management and electricity stealing prevention method based on terminal edge calculation, which is used to implement electricity consumption information, statistics, and analysis at a power equipment terminal, further perform lean management on line loss of a distribution room, timely cope with line loss faults, and prevent electricity stealing behavior.
The method provided by the embodiment can be implemented by the basic micro application or software running on the smart core or Huawei system platform. In the implementation process of the method, key data such as voltage, current, active power and frozen electric quantity of a sebastiscus sebastus node in the whole platform area can be monitored in real time through upgrading of distribution network intelligent equipment and centralized comprehensive coverage of acquisition sensing equipment. Meanwhile, based on the computing capability of the edge computing module on one side of the terminal, the method of the embodiment can be used for locally developing a display stand to distinguish route loss statistical analysis and timely sending abnormal conditions such as line loss super-errors to the data center of the cloud and the server. And further provides a data base for fault analysis and electricity stealing troubleshooting. The processing mode that provides through this embodiment both can realize carrying out real-time supervision to the low-voltage line loss, effectively supports the line loss to administer, steal work such as electric check and develop. The data processing pressure of the cloud server can be reduced, and the influence of the downtime of server equipment at the cloud end or other faults on the operation stability of the power grid is eliminated.
The method for line loss lean management and electricity larceny prevention provided by the embodiment specifically comprises the following processes:
s1: and acquiring the power information of each power utilization node through the concentrator according to a preset acquisition frequency, wherein the power information comprises voltage, current, active power, reactive power and frozen electric quantity.
S2: and deploying an edge calculation module in each concentrator, and calculating the hour, day and month of the line loss rate corresponding to the current equipment node and the annual statistical result according to the historical information of the acquired power information within one hour after each acquisition.
Specifically, the statistical results of the line loss rate respectively include: the initial electric quantity of the equipment, the ending electric quantity of the equipment, the line loss rate in the last hour and the line loss rate in the last day; the last day A phase line loss rate, the last day B phase line loss rate, the last day C phase line loss rate, the current month bus loss rate, the current month A phase line loss rate, the current month B phase line loss rate, the current month C phase line loss rate, the current year bus loss rate, the current year A phase line loss rate, the current year B phase line loss rate and the current year C phase line loss rate.
And the edge calculation model completes the data updating of the line loss rate of the last hour every 1 h. Finishing data updating of the last day line loss rate, the last day A line loss rate, the last day B line loss rate and the last day C line loss rate every 24 hours; finishing data updating of the bus loss rate in the current month, the phase loss rate in the current month A, the phase loss rate in the current month B and the phase loss rate in the current month C every 28-31d (determined by the date in the current month); and finishing data updating of the current-year bus loss rate, the current-year A phase line loss rate, the current-year B phase line loss rate and the current-year C phase line loss rate every other one year.
S3: the concentrator sends the equipment number of the concentrator and the power information acquired in real time to the cloud server for backup storage, and meanwhile, sends the updated data of the calculated line loss data statistical result to the cloud server every hour.
S4: the cloud server analyzes whether the line loss fault exists in the whole power utilization station area or not according to the obtained line loss rate statistical result calculated by each concentrator, and judges whether the electricity stealing behavior exists in the station area or not when the line loss abnormal state occurs;
the cloud server is provided with a fault analysis tool in operation, and the fault analysis tool is used for analyzing line loss faults or electricity stealing behaviors which may exist in the whole transformer area or the power supply network according to historical statistical data of the line loss rate of each node. And positioning to corresponding risk nodes, and issuing early warning signals aiming at the risk nodes.
S5: and the cloud server sends the analyzed line loss fault result, the analyzed electricity stealing judgment conclusion and the corresponding electricity utilization node information to corresponding station area management personnel and sends corresponding fault processing suggestions at the same time.
In the edge computing module of this embodiment, the computation of the line loss rate statistical result is completed through a statistical model, and before the statistical model performs data interaction with the data center in the cloud server, model registration or update needs to be performed first, as shown in fig. 2, a registration or update process of the statistical model is as follows:
s01: and the cloud server reads the latest version number and model name of the statistical model.
S02: the cloud server checks and compares the model name corresponding to the current version number in the concentrator with the model name corresponding to the latest version number in the cloud server, judges whether the model names are consistent with each other, and makes the following decision:
(1) and when the version number of the current version number is consistent with the version number of the current version number, judging that the model of the current version number is valid, and reading the specified model content.
(2) And when the two are not consistent, judging that the model of the current version number is invalid, and updating the statistical model in the concentrator according to the statistical model of the latest version in the cloud server.
S03: the cloud server reads registration information of the statistical model in the concentrator.
S04: the cloud server checks whether the statistical model is registered, and makes the following decision:
(1) if yes, the registration or update process is determined to be completed.
(2) Otherwise, the setting of the model registration process is completed again.
S05: after the model registration is completed, the concentrator requests parameter information for calculating a line loss rate statistical result from the server.
After the statistical model is registered, data statistics and calculation tasks can be normally carried out, and the calculation process is finished on a local terminal close to the collection. As shown in fig. 3, the data processing procedure of the statistical model is roughly as follows:
s001: requesting original data used for calculating a line loss rate statistical result, and judging whether the data is successfully acquired:
(1) if yes, go to the next step.
(2) Otherwise, the calculation process is interrupted, and error information containing the data acquisition error reason is printed.
S002: calculating the statistical result of the line loss rate according to the original data obtained in the previous step, and judging whether the calculation result is legal:
(1) if yes, go to the next step.
(2) Otherwise, the data uploading is interrupted, and error information containing illegal data types is printed.
S003: and (3) the statistical result of the line loss rate calculated in the previous step is sent to a cloud server, and whether the uploading is successful or not is judged according to the return information of the cloud server:
(1) if yes, printing the message that the data uploading is successful.
(2) Otherwise, printing the reason of uploading failure.
In this example, the collector includes a data storage module. The electric power information collected by the collector further comprises hour freezing data of the electric meter, day freezing data of the electric meter, hour freezing data of the circuit breaker and day freezing data of the circuit breaker. The storage module respectively stores the historical information collected by the concentrator and the calculated statistical result in a specific storage unit; and the historical information of the stored power information is covered every other hour, and meanwhile, the statistical result of the line loss rate is updated. In the storage module, the types of the stored data cards are shown in table 1:
table 1: statistical table of collected and calculated line loss rate related data
In this embodiment, a data processing module with edge computing capability is deployed in a concentrator that automatically collects and uploads power information, and acquires relevant data while collecting data on the concentrator, and locally completes a computation process of a line loss statistical result in a current node by using the relevant data. And simultaneously uploading the line loss data of the current node to a cloud server. The line loss statistical result of each node can be obtained immediately after the collected data of the concentrator is generated; therefore, the timeliness of the speed limit data is greatly improved, and a foundation is laid for rapidly processing line loss faults and timely discovering electric larceny behaviors.
The method provided by the embodiment changes the centralized processing of the data processing method for evaluating the line loss in the power supply network into a distributed processing mode based on the terminal edge computing capability. The operation pressure of the background data center can be greatly reduced; meanwhile, the influence of faults such as downtime of the background server on the normal operation of the power supply network can be reduced, and the overall safety and fault-tolerant capability of the system are improved.
Although the line loss data statistics task of each node is not completed in the background server, the line loss fault analysis and electricity stealing behavior determination behaviors of the power supply network based on all node data are still completed by the background server. And the background server enables the judgment result to be sent to each concentrator or management terminal, so that management personnel can conveniently process faults and eliminate risks in time.
Example 2
The present embodiment provides a line loss lean management and electricity larceny prevention system based on terminal edge calculation, which manages the line loss of all nodes in a distribution room, and timely handles line loss faults and monitors electricity larceny behavior by using the line loss lean management and electricity larceny prevention method based on terminal edge calculation as in embodiment 1.
As shown in fig. 4, the system for lean line loss management and electricity larceny prevention includes: the device comprises a concentrator, an edge computing module and a cloud server.
The concentrator is installed at every power consumption node in the power supply district, and the concentrator is used for gathering the electric power information of each node in the power supply district, and electric power information sends to in an edge calculation module and the cloud ware. The concentrator also includes a storage module. The storage module is used for storing historical information of the power information collected within one hour and calculating a line loss rate statistical result of the current equipment node according to the historical information.
The concentrator in this embodiment is an existing device capable of remotely reading meters. The concentrator is internally provided with a memory for storing the collected data and a communication system connected with the cloud server in the background data. The concentrator and the cloud server are in communication connection through a communication network based on broadband power line carrier (HPLC) or electricity operators.
The edge calculation module is electrically connected with the concentrator and used for receiving the electric power information collected by the concentrator and calculating a statistical result of the line loss rate in the current node according to historical data of the electric power information in a preset period; and sending the line loss rate statistical result to a cloud server.
The edge calculation model in this embodiment is a small-sized processor, and the processor may be connected to the concentrator to directly obtain each item of collected data collected by the concentrator. And completes data processing and operations.
The cloud server is used for storing the power information of each power utilization node and the statistical result of the line loss rate. The cloud server also comprises an electricity stealing behavior analysis tool which is used for judging whether line loss faults or electricity stealing behaviors exist in the power supply area or the whole power supply network according to the statistical result of the line loss rate of each node; and positioning to corresponding risk nodes, and issuing early warning signals aiming at the risk nodes.
In this embodiment, the line loss lean management and electricity stealing prevention system further includes a management terminal, and the management terminal is in communication connection with the cloud server. The management area of each management terminal corresponds to one or more power utilization nodes in the power utilization area. And the management terminal is distributed to corresponding management personnel, and when the cloud server is positioned to the risk node, an early warning signal is sent to the corresponding management terminal. The management terminal provided by this embodiment may be a dedicated terminal or a general mobile terminal, such as a mobile phone and a tablet computer, running with a power management APP. For different concentrators or power utilization nodes. In the power management APP of the embodiment, node login can be performed in modes such as code scanning, and historical monitoring data of each node in a management area can be inquired through the management terminal.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A line loss lean management and electricity stealing prevention method based on terminal edge calculation is used for realizing electricity consumption information, statistics and analysis at a power equipment terminal, further performing lean management on line loss of a distribution room, coping with line loss faults in time and preventing electricity stealing behaviors; the method is characterized in that: the line loss lean management and electricity larceny prevention method comprises the following processes:
s1: acquiring power information of each power utilization node through a concentrator according to a preset acquisition frequency, wherein the power information comprises voltage, current, active power, reactive power and frozen electric quantity;
s2: an edge calculation module is deployed in each concentrator, and then after each acquisition is finished, according to historical information of the acquired power information in one hour, the hour, day and month of the line loss rate corresponding to the current equipment node and the annual statistical result are calculated;
s3: the concentrator sends the equipment number of the concentrator and the power information acquired in real time to a cloud server for backup storage, and sends the updated data of the calculated line loss data statistical result to the cloud server every hour;
s4: the cloud server analyzes whether the line loss fault exists in the whole power utilization station area or not according to the obtained line loss rate statistical result calculated by each concentrator, and judges whether the electricity stealing behavior exists in the station area or not when the line loss abnormal state occurs;
s5: and the cloud server sends the analyzed line loss fault result, the analyzed electricity stealing judgment conclusion and the corresponding electricity utilization node information to corresponding station area management personnel and sends corresponding fault processing suggestions at the same time.
2. The method for line loss lean management and electricity stealing prevention based on terminal edge calculation as claimed in claim 1, wherein: in step S1, the power information collected by the collector further includes hour freezing data of the electric meter, day freezing data of the electric meter, hour freezing data of the circuit breaker, and day freezing data of the circuit breaker.
3. The method for line loss lean management and electricity larceny prevention based on terminal edge calculation as claimed in claim 1, wherein: the concentrator also comprises a storage module; the storage module is used for storing historical information of the power information collected within one hour and calculating a line loss rate statistical result of the current equipment node according to the historical information.
4. The method for line loss lean management and electricity stealing prevention based on terminal edge calculation as claimed in claim 3, wherein: in step S1, the storage module stores the historical information collected by the concentrator and the calculated statistical result in specific storage units respectively; and the historical information of the stored power information is covered every other hour, and meanwhile, the statistical result of the line loss rate is updated.
5. The method for line loss lean management and electricity stealing prevention based on terminal edge calculation as claimed in claim 1, wherein: in step S2, the line loss rate statistics result includes: the initial electric quantity of the equipment, the ending electric quantity of the equipment, the line loss rate in the last hour and the line loss rate in the last day; the last day A phase line loss rate, the last day B phase line loss rate, the last day C phase line loss rate, the current month bus loss rate, the current month A phase line loss rate, the current month B phase line loss rate, the current month C phase line loss rate, the current year bus loss rate, the current year A phase line loss rate, the current year B phase line loss rate and the current year C phase line loss rate.
6. The method for line loss lean management and electricity stealing prevention based on terminal edge calculation as claimed in claim 1, wherein: the edge calculation module in the collector completes calculation of a line loss rate statistical result through a statistical model, model registration or updating needs to be performed before the statistical model performs data interaction with a data center in a cloud server, and the registration or updating process of the model is as follows:
s01: the cloud server reads the latest version number and model name of the statistical model;
s02: the cloud server checks and compares the model name corresponding to the current version number in the concentrator with the model name corresponding to the latest version number in the cloud server, judges whether the model names are consistent with each other, and makes the following decision:
(1) when the version number of the current version number is consistent with the version number of the current version number, judging that the model of the current version number is valid, and reading the specified model content;
(2) when the two are not consistent, judging that the model of the current version number is invalid, and updating the statistical model in the concentrator according to the statistical model of the latest version in the cloud server;
s03: the cloud server reads the registration information of the statistical model in the concentrator;
s04: the cloud server checks whether the statistical model is registered, and makes the following decision:
(1) if yes, judging that the registration or updating process is finished;
(2) otherwise, the setting of the model registration process is completed again;
s05: after the model registration is completed, the concentrator requests parameter information for calculating a line loss rate statistical result from the server.
7. The method for line loss lean management and electricity stealing prevention based on terminal edge calculation as claimed in claim 1, wherein: in steps S2 and S3, the data processing procedure of the statistical model is as follows:
s001: requesting original data used for calculating a statistical result of the line loss rate, and judging whether the data is successfully acquired: if yes, entering the next step; otherwise, interrupting the calculation process and printing error information containing the data acquisition error reason;
s002: calculating the statistical result of the line loss rate according to the original data obtained in the previous step, and judging whether the calculation result is legal: if yes, entering the next step, otherwise, interrupting the data uploading and printing error information containing illegal data types;
s003: and (3) the statistical result of the line loss rate calculated in the previous step is sent to a cloud server, and whether the uploading is successful or not is judged according to the return information of the cloud server: if so, printing a message that the data uploading is successful, otherwise, printing the reason of the uploading failure.
8. The method for line loss lean management and electricity stealing prevention based on terminal edge calculation as claimed in claim 1, wherein: in step S4, a fault analysis tool is operated in the cloud server, and the fault analysis tool is used for analyzing a line loss fault or a power stealing behavior that may exist in the whole distribution area or the power supply network according to historical statistical data of the line loss rate of each node; and positioning to corresponding risk nodes, and issuing early warning signals aiming at the risk nodes.
9. A line loss lean management and electricity stealing prevention system based on terminal edge calculation is characterized in that: the method for managing the line loss of all the nodes in the transformer area, processing line loss faults and monitoring electricity stealing behaviors in time by adopting the method for managing the line loss lean management and electricity stealing prevention based on the terminal edge calculation according to any one of claims 1 to 8; the line loss lean management and electricity larceny prevention system comprises:
the concentrator is installed at each power utilization node in the power supply area, and is used for collecting power information of each node in the power supply area, and the power information is sent to one edge computing module and the cloud server;
the edge calculation module is electrically connected with the concentrator and used for receiving the electric power information collected by the concentrator and calculating a statistical result of the line loss rate in the current node according to historical data of the electric power information in a preset period; sending the line loss rate statistical result to the cloud server; and
the cloud server is used for storing the power information of each power utilization node and the statistical result of the line loss rate; the cloud server also comprises an electricity stealing behavior analysis tool which is used for judging whether line loss faults or electricity stealing behaviors exist in the power supply area or the whole power supply network according to the statistical result of the line loss rate of each node; and positioning to corresponding risk nodes, and issuing early warning signals aiming at the risk nodes.
10. The terminal edge computation-based line loss lean management and power stealing system of claim 9, wherein: the line loss lean management and electricity stealing prevention system further comprises management terminals, the management terminals are in communication connection with the cloud server, and the management area of each management terminal corresponds to one or more electricity utilization nodes in the electricity utilization platform area; the management terminal is distributed to corresponding management personnel, and when the cloud server is positioned to the risk node, an early warning signal is sent to the corresponding management terminal; the management terminal is a special terminal or a general mobile terminal running with an electric power management APP; the management terminal is also used for inquiring the historical data of each node in the management area.
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| CN115766398A (en) * | 2022-11-29 | 2023-03-07 | 国网江苏省电力有限公司南通供电分公司 | Platform district power consumption information acquisition fault analysis system based on edge calculation |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115766398A (en) * | 2022-11-29 | 2023-03-07 | 国网江苏省电力有限公司南通供电分公司 | Platform district power consumption information acquisition fault analysis system based on edge calculation |
| CN115766398B (en) * | 2022-11-29 | 2023-09-22 | 国网江苏省电力有限公司南通供电分公司 | Station area electricity consumption information acquisition fault analysis system based on edge calculation |
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