CN116108376A - Monitoring system and method for preventing electricity stealing, electronic equipment and medium - Google Patents
Monitoring system and method for preventing electricity stealing, electronic equipment and medium Download PDFInfo
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Abstract
The disclosure provides a monitoring system, a method, electronic equipment and a medium for preventing electricity larceny, which relate to the technical field of electricity larceny and comprise the steps of obtaining electricity larceny sample data; extracting electricity stealing feature data in the electricity stealing sample data to construct an electricity stealing feature database; inputting the electricity larceny characteristic data into a suspected electricity larceny identification model, outputting an electricity larceny prevention detection result, comparing the electricity larceny prevention detection result with data in a characteristic database, and optimizing the electricity larceny identification model; collecting electricity consumption data of a user, inputting the electricity consumption data into a suspected electricity larceny identification model for analysis, and obtaining a suspected electricity larceny user list; and positioning the suspected electricity larceny user according to the suspected electricity larceny user list, and monitoring the electricity consumption behavior of the positioned suspected electricity larceny user. The problem that the electricity stealing behavior cannot be monitored in the prior art is solved.
Description
Technical Field
The disclosure relates to the technical field of anti-electricity-theft, in particular to an anti-electricity-theft monitoring system, an anti-electricity-theft monitoring method, electronic equipment and a medium.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The illegal electricity larceny is illegal action that illegal means are adopted to measure electricity irregularly or less, along with the increasing social electricity demand, some illegal operators and individual private owners are in the hope of getting privately, the national electric energy is larceny, the normal power supply order is disturbed, and electricity larceny means are continuously renovated along with the continuous progress of technology, so that the benefits of the national interests and the benefits of electric power management enterprises are seriously damaged, and the development of the electric power industry is hindered.
Based on the above, to monitor the electricity larceny behavior in the power supply behavior, in the existing monitoring mode, firstly, the monitoring is performed manually, the accuracy of the monitoring is not in place, and the vulnerability is unavoidable; secondly, the existing electricity stealing data is only aimed at the data acquisition of the electric energy meter, the model analysis is not carried out on the internal data, a suspected electricity stealing user list is difficult to accurately obtain, and the problem that the electricity stealing behavior cannot be monitored in the suspected electricity stealing user list is solved.
Disclosure of Invention
In order to solve the above problems, the disclosure provides a monitoring system, a method, an electronic device and a medium for preventing electricity theft, so as to solve the problem that the current electricity theft behavior cannot be monitored.
According to some embodiments, the present disclosure employs the following technical solutions:
a method of monitoring for anti-theft of electricity, comprising:
acquiring electricity stealing sample data;
extracting electricity stealing feature data in the electricity stealing sample data to construct an electricity stealing feature database;
inputting the electricity larceny characteristic data into a suspected electricity larceny identification model, outputting an electricity larceny prevention detection result, comparing the electricity larceny prevention detection result with data in a characteristic database, and optimizing the electricity larceny identification model;
collecting electricity consumption data of a user, inputting the electricity consumption data into a suspected electricity larceny identification model for analysis, and obtaining a suspected electricity larceny user list;
and positioning the suspected electricity larceny user according to the suspected electricity larceny user list, and monitoring the electricity consumption behavior of the positioned suspected electricity larceny user.
According to some embodiments, the present disclosure employs the following technical solutions:
a monitoring system for preventing electrical theft, comprising:
a data acquisition module configured to acquire electricity theft sample data;
a first construction module configured to extract electricity stealing feature data in the electricity stealing sample data to construct an electricity stealing feature database;
the second construction module is configured to input the electricity larceny characteristic data into a suspected electricity larceny identification model, output an electricity larceny detection result, compare the electricity larceny detection result with data in a characteristic database and optimize the electricity larceny identification model;
the acquisition and analysis module is configured to acquire electricity consumption data of a user, input the electricity consumption data into the suspected electricity larceny identification model for analysis, and obtain a suspected electricity larceny user list;
the monitoring module is configured to locate the suspected electricity larceny user according to the suspected electricity larceny user list and monitor the electricity consumption behavior of the located suspected electricity larceny user.
According to some embodiments, the present disclosure employs the following technical solutions:
an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method when the computer program is executed.
According to some embodiments, the present disclosure employs the following technical solutions:
a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method.
Compared with the prior art, the beneficial effects of the present disclosure are:
the method for monitoring the anti-electricity-theft in the present disclosure acquires an electricity-theft sample; extracting electricity stealing feature data based on the electricity stealing sample to construct an electricity stealing feature database; constructing a suspected electricity larceny identification model based on the electricity larceny characteristic database; collecting electricity consumption data of a user; inputting the electricity utilization data into a suspected electricity larceny identification model for analysis to obtain a suspected electricity larceny user list; and monitoring the electricity consumption behavior of the corresponding user based on the suspected electricity stealing user list, so that the problem that the electricity stealing behavior cannot be monitored in the prior art is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate and explain the exemplary embodiments of the disclosure and together with the description serve to explain the disclosure, and do not constitute an undue limitation on the disclosure.
FIG. 1 is a flow chart of a method of monitoring for anti-electricity-theft of the present disclosure;
FIG. 2 is a block diagram of a monitoring system of the present disclosure that is anti-electricity-theft;
fig. 3 is a schematic diagram of an entity structure of an electronic device provided in the present disclosure.
The specific embodiment is as follows:
the disclosure is further described below with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments in accordance with the present disclosure. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Example 1
An embodiment of the present disclosure provides a method for monitoring an anti-electricity-theft device, including:
step 1: acquiring electricity stealing sample data;
step 2: extracting electricity stealing feature data in the electricity stealing sample data to construct an electricity stealing feature database;
step 3: inputting the electricity larceny characteristic data into a suspected electricity larceny identification model, outputting an electricity larceny prevention detection result, comparing the data in a fish characteristic database of the electricity larceny prevention detection result, and optimizing the electricity larceny identification model;
step 4: collecting electricity consumption data of a user, inputting the electricity consumption data into a suspected electricity larceny identification model for analysis, and obtaining a suspected electricity larceny user list;
step 5: and positioning the suspected electricity larceny user according to the suspected electricity larceny user list, and monitoring the electricity consumption behavior of the positioned suspected electricity larceny user.
In step 1, obtaining electricity theft sample data, specifically including:
collecting historical electricity utilization data of a user; the historical electricity utilization data of the user comprises attribute parameters of the electricity utilization user and electricity utilization behavior parameters corresponding to the electricity utilization user; the electricity stealing behavior of the user is analyzed and predicted through a large amount of historical electricity utilization data.
Analyzing the historical electricity utilization data to obtain abnormal electricity utilization data; including but not limited to deleting invalid data and merging data of the same type.
Screening, cleaning and converting the abnormal electricity utilization data, and extracting characteristic information of the abnormal electricity utilization data; extracting characteristic information of the abnormal electricity utilization data according to the abnormal electricity utilization data;
and extracting, selecting and analyzing the characteristic information to obtain a power stealing sample. And determining a corresponding electricity stealing method according to the corresponding electricity stealing characteristics, generating an electricity stealing sample of the user according to electricity consumption data or electricity consumption phenomena of the electricity stealing user and electricity stealing information, and summarizing the electricity stealing sample to form an electricity stealing sample library.
In the step 2, electricity stealing feature data in electricity stealing sample data are extracted to construct an electricity stealing feature database;
specifically, clustering analysis is carried out on the electricity stealing samples based on a density K-means algorithm, and electricity stealing characteristic data are obtained.
The K-means clustering algorithm (K-means clustering algorithm) is an iterative solution clustering analysis algorithm, and comprises the steps of dividing data into K groups, randomly selecting K objects as initial clustering centers, calculating the distance between each object and each seed clustering center, and distributing each object to the closest clustering center. The cluster centers and the objects assigned to them represent a cluster. For each sample assigned, the cluster center of the cluster is recalculated based on the existing objects in the cluster. This process will repeat until a certain termination condition is met, which may be that no (or a minimum number of) objects are reassigned to different clusters, no (or a minimum number of) cluster centers change again, and the square of the error and the local minimum.
In step 3, the electricity larceny characteristic data is input into a suspected electricity larceny identification model, an electricity larceny detection result is output, the electricity larceny detection result is compared with data in a characteristic database, the suspected electricity larceny identification model is optimized, and an electricity larceny identification model is constructed.
In step 4, collecting electricity consumption data of a user, inputting the electricity consumption data into a suspected electricity larceny identification model for analysis, and obtaining a suspected electricity larceny user list, wherein the method comprises the following steps:
and acquiring electricity consumption data of a user in the area to be monitored, wherein the electricity consumption data comprises voltage data and current data.
And evaluating the electricity utilization data to obtain the reliability score of the real-time electricity utilization of the user.
And inputting the electricity utilization data into an optimized suspected electricity larceny identification model, identifying suspected electricity larceny users based on the suspected electricity larceny identification model, and judging a suspected electricity larceny mode and time.
In step 5, locating the suspected electricity larceny user according to the suspected electricity larceny user list, and monitoring the electricity consumption behavior of the located suspected electricity larceny user, including:
specifically, a suspected electricity larceny user is positioned based on a suspected electricity larceny user list, the electricity consumption behavior of the positioned suspected electricity larceny user is monitored, the monitored electricity consumption behavior of the suspected electricity larceny user is converted into visual information, the electricity consumption behavior of the suspected electricity larceny user is analyzed based on the visual information, if the analysis result is abnormal electricity consumption behavior, the suspected electricity larceny user is reported, and corresponding treatment measures are adopted.
According to the method for monitoring the anti-electricity-theft, an electricity-theft characteristic database is constructed by acquiring an electricity-theft sample and extracting electricity-theft characteristic data based on the electricity-theft sample; constructing a suspected electricity larceny identification model based on the electricity larceny characteristic database; collecting electricity consumption data of a user; inputting the electricity utilization data into a suspected electricity larceny identification model for analysis to obtain a suspected electricity larceny user list; monitoring the electricity utilization behavior of a corresponding user based on the suspected electricity stealing user list; the problem that the electricity stealing behavior cannot be monitored in the prior art is solved.
Example 2
In one embodiment of the present disclosure, there is provided a monitoring system for preventing electricity larceny, comprising:
a data acquisition module 10 configured to acquire electricity theft sample data;
a first construction module 20 configured to extract electricity theft feature data in the electricity theft sample data to construct an electricity theft feature database;
a second construction module 30 configured to input the electricity larceny feature data into a suspected electricity larceny identification model, output an electricity larceny detection result, compare the electricity larceny detection result with data in a feature database, and optimize the electricity larceny identification model;
the collection 40 and analysis module 50 is configured to collect electricity consumption data of a user, input the electricity consumption data into the suspected electricity larceny identification model for analysis, and obtain a suspected electricity larceny user list;
the monitoring module 60 is configured to locate the suspected electricity larceny user according to the suspected electricity larceny user list and monitor the electricity consumption behavior of the located suspected electricity larceny user.
After collecting historical electricity utilization data of a user, analyzing the historical electricity utilization data to obtain abnormal electricity utilization data; screening, cleaning and converting the abnormal electricity utilization data, and extracting characteristic information of the abnormal electricity utilization data; and extracting, selecting and analyzing the characteristic information to obtain a power stealing sample.
And carrying out cluster analysis on the electricity stealing samples based on a density K-means algorithm to obtain electricity stealing characteristic data.
Inputting data in the electricity larceny feature database into a suspected electricity larceny identification model, and outputting an electricity larceny detection result according to the suspected electricity larceny identification model; and comparing the anti-electricity-theft detection result with data in an electricity-theft feature database, and optimizing a suspected electricity-theft identification model according to the comparison result.
And acquiring electricity consumption data of a user in the area to be monitored, wherein the electricity consumption data comprises voltage data and current data.
And evaluating the electricity utilization data to obtain the reliability score of the real-time electricity utilization of the user.
And inputting the electricity utilization data into an optimized suspected electricity larceny identification model, identifying suspected electricity larceny users based on the suspected electricity larceny identification model, and judging a suspected electricity larceny mode and time.
The anti-electricity-theft monitoring system comprises an acquisition module, a first construction module, a second construction module, an acquisition module, an analysis module and a monitoring module, wherein the acquisition module acquires electricity-theft samples, the first construction module is used for extracting electricity-theft characteristic data based on the electricity-theft samples to construct an electricity-theft characteristic database, the second construction module is used for constructing a suspected electricity-theft identification model based on the electricity-theft characteristic database, the acquisition module is used for acquiring electricity-use data of a user, the analysis module is used for inputting the electricity-use data into the suspected electricity-theft identification model to analyze the electricity-use data to obtain a suspected electricity-theft user list, and the monitoring module is used for monitoring electricity-use behaviors of corresponding users based on the suspected electricity-theft user list; the problem that the electricity stealing behavior cannot be monitored in the prior art is solved.
Example 3
In one embodiment of the disclosure, an electronic device is provided that includes a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method when executing the computer program.
Fig. 3 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the disclosure, as shown in fig. 3, an electronic device 70 includes: a processor 701, a memory 702, and a bus 703;
wherein, the processor 701 and the memory 702 complete communication with each other through the bus 703;
the processor 701 is configured to invoke program instructions in the memory 702 to perform the methods provided by the above-described method embodiments, for example, including: obtaining an electricity stealing sample; extracting electricity stealing feature data based on the electricity stealing sample to construct an electricity stealing feature database; constructing a suspected electricity larceny identification model based on the electricity larceny characteristic database; collecting electricity consumption data of a user; inputting the electricity utilization data into a suspected electricity larceny identification model for analysis to obtain a suspected electricity larceny user list; and monitoring the electricity utilization behavior of the corresponding user based on the suspected electricity stealing user list.
Example 4
In one embodiment of the present disclosure, a computer readable medium is provided, where a non-transitory computer readable medium stores computer instructions that cause a computer to perform the methods provided by the method embodiments described above, for example, including: obtaining an electricity stealing sample; extracting electricity stealing feature data based on the electricity stealing sample to construct an electricity stealing feature database; constructing a suspected electricity larceny identification model based on the electricity larceny characteristic database; collecting electricity consumption data of a user; inputting the electricity utilization data into a suspected electricity larceny identification model for analysis to obtain a suspected electricity larceny user list; and monitoring the electricity utilization behavior of the corresponding user based on the suspected electricity stealing user list.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the specific embodiments of the present disclosure have been described above with reference to the drawings, it should be understood that the present disclosure is not limited to the embodiments, and that various modifications and changes can be made by one skilled in the art without inventive effort on the basis of the technical solutions of the present disclosure while remaining within the scope of the present disclosure.
Claims (10)
1. A method of monitoring for anti-theft of electricity, comprising:
acquiring electricity stealing sample data;
extracting electricity stealing feature data in the electricity stealing sample data to construct an electricity stealing feature database;
inputting the electricity larceny characteristic data into a suspected electricity larceny identification model, outputting an electricity larceny prevention detection result, comparing the electricity larceny prevention detection result with data in a characteristic database, and optimizing the electricity larceny identification model;
collecting electricity consumption data of a user, inputting the electricity consumption data into a suspected electricity larceny identification model for analysis, and obtaining a suspected electricity larceny user list;
and positioning the suspected electricity larceny user according to the suspected electricity larceny user list, and monitoring the electricity consumption behavior of the positioned suspected electricity larceny user.
2. The method for monitoring anti-theft electricity according to claim 1, wherein the acquiring electricity theft sample data comprises:
collecting historical electricity utilization data of a user;
analyzing the historical electricity utilization data to obtain abnormal electricity utilization data;
screening, cleaning and converting the abnormal electricity utilization data, and extracting characteristic information of the abnormal electricity utilization data;
and extracting, selecting and analyzing the characteristic information to obtain a power stealing sample.
3. The method of claim 1, wherein extracting the electricity larceny feature data from the electricity larceny sample data creates an electricity larceny feature database, comprising:
clustering analysis is carried out on the electricity stealing samples based on a density K-means algorithm, and electricity stealing characteristic data are obtained; and constructing a suspected electricity larceny identification model based on the electricity larceny characteristic database.
4. The method for monitoring electricity larceny as set forth in claim 1, wherein said collecting electricity usage data of the user comprises:
acquiring electricity consumption data of a user in an area to be monitored;
and evaluating the electricity utilization data to obtain the reliability score of the real-time electricity utilization of the user.
5. The method of claim 4, wherein the electricity consumption data includes voltage data and current data.
6. The method for monitoring anti-electricity-theft according to claim 1, wherein the step of inputting the electricity consumption data into a suspected electricity-theft identification model for analysis to obtain a suspected electricity-theft user list comprises the steps of:
and inputting the electricity utilization data into an optimized suspected electricity larceny identification model, identifying suspected electricity larceny users based on the suspected electricity larceny identification model, and judging a suspected electricity larceny mode and time.
7. The method of claim 1, wherein locating suspected electricity larceny users based on the list of suspected electricity larceny users and monitoring the electricity usage of the located suspected electricity larceny users comprises: converting the monitored electricity consumption behavior of the suspected electricity larceny user into visual information, analyzing the electricity consumption behavior of the suspected electricity larceny user based on the visual information, reporting the suspected electricity larceny user if the analysis result is the abnormal electricity consumption behavior, and taking corresponding treatment measures.
8. A monitoring system for preventing theft of electricity, comprising:
a data acquisition module configured to acquire electricity theft sample data;
a first construction module configured to extract electricity stealing feature data in the electricity stealing sample data to construct an electricity stealing feature database;
the second construction module is configured to input the electricity larceny characteristic data into a suspected electricity larceny identification model, output an electricity larceny detection result, compare the electricity larceny detection result with data in a characteristic database and optimize the electricity larceny identification model;
the acquisition and analysis module is configured to acquire electricity consumption data of a user, input the electricity consumption data into the suspected electricity larceny identification model for analysis, and obtain a suspected electricity larceny user list;
the monitoring module is configured to locate the suspected electricity larceny user according to the suspected electricity larceny user list and monitor the electricity consumption behavior of the located suspected electricity larceny user.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 7 when the computer program is executed.
10. A computer readable medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 7.
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| CN117611393A (en) * | 2024-01-24 | 2024-02-27 | 国网安徽省电力有限公司合肥供电公司 | Big data-based anti-electricity-stealing data acquisition method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117611393A (en) * | 2024-01-24 | 2024-02-27 | 国网安徽省电力有限公司合肥供电公司 | Big data-based anti-electricity-stealing data acquisition method |
| CN117611393B (en) * | 2024-01-24 | 2024-04-05 | 国网安徽省电力有限公司合肥供电公司 | Big data-based anti-electricity-stealing data acquisition method |
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