CN112614012A - User electricity stealing identification method and device - Google Patents
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Abstract
The invention discloses a method and a device for identifying electricity stealing of a user. Wherein, the method comprises the following steps: acquiring power utilization data of a user, wherein the power utilization data comprises a plurality of items of data; establishing an analysis model according to the power utilization data, and determining the probability that a plurality of items of data are respectively the electricity stealing probability of the user; respectively adding weights to the multiple items of data; and determining whether the user corresponding to the electricity utilization data is a power stealing user or not according to the probability and the weight of the corresponding data. The invention solves the technical problems of low efficiency and larger error in the related technology that the power system artificially carries out statistical analysis on the power consumption data of the user to determine the electricity stealing mode of the user.
Description
Technical Field
The invention relates to the field of power grid safety, in particular to a method and a device for identifying electricity stealing of a user.
Background
In the supply and collection marketing system of electric power, a large amount of user data is formed. By means of the data, the low-voltage resident users can be screened for preventing electricity stealing, various indexes are formed, and the low-voltage resident electricity stealing prevention analysis model is generated by integrating the various indexes. Because the quantity of low-voltage resident users is large, data acquisition is difficult, the current electricity stealing prevention analysis on the low-voltage users invests considerable manpower to arrange and analyze the data, and a large amount of human resources are consumed from data extraction to report formation by using analysis tools such as EXCEL, so that the efficiency is low, and errors caused by human errors easily occur in the work, thereby consuming unnecessary economic cost. With the popularization of informatization and datamation in the traditional industry, the traditional method is more and more unconscious, so that the problem of low efficiency and large error exists in the determination of electricity stealing of users.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a method and a device for identifying electricity stealing of a user, which at least solve the technical problems of low efficiency and larger error caused by the fact that a power system artificially carries out statistical analysis on electricity consumption data of the user to determine the way of electricity stealing of the user in the related technology.
According to an aspect of an embodiment of the present invention, there is provided a user electricity stealing identification method, including: acquiring power utilization data of a user, wherein the power utilization data comprises a plurality of items of data; establishing an analysis model according to the electricity utilization data, and determining the probability that the plurality of items of data are respectively the electricity stealing probability of the user; adding weights to the plurality of items of data respectively; and determining whether the user corresponding to the electricity utilization data is an electricity stealing user or not according to the probability and the weight of the corresponding data.
Optionally, the acquiring the power consumption data of the user includes: periodically extracting electricity utilization data from a predetermined webpage or a database; and storing the electricity utilization data locally.
Optionally, before establishing an analysis model according to the power consumption data and determining the probability that a plurality of items of data steal power for the user, the method further includes: pre-processing the electricity usage data, wherein the pre-processing comprises at least one of: and removing invalid data, screening data and correcting data.
Optionally, the adding weights to the plurality of items of data respectively includes: and determining weights corresponding to multiple items of data of the electricity utilization data according to the regression model and verified users of the electricity utilization data.
Optionally, determining, by the probability and the weight of the corresponding data, whether the user corresponding to the electricity consumption data is an electricity stealing user includes: determining a suspicious electricity stealing value of the user of the electricity utilization data according to the probability and the weight of the corresponding data; determining the user of the electricity utilization data as an electricity stealing user under the condition that the electricity stealing suspicious value exceeds a preset value; and under the condition that the suspicious electricity stealing value does not exceed the preset value, determining that the user of the electricity utilization data is a non-electricity stealing user.
Optionally, after determining whether the user corresponding to the electricity consumption data is an electricity stealing user according to the probability and the weight of the corresponding data, the method further includes: generating a report based on analytical process data of the electricity usage data, wherein the analytical process data includes at least one of: the weight corresponding to the multiple data and the electricity stealing suspicious value; storing the report locally.
According to another aspect of the embodiments of the present invention, there is also provided a user electricity stealing identification apparatus, including: the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring power utilization data of a user, and the power utilization data comprises a plurality of items of data; the determining module is used for establishing an analysis model according to the power utilization data and determining the probability that the plurality of items of data are power stealing of the user respectively; the weighting module is used for adding weights to the plurality of items of data respectively; and the judging module is used for determining whether the user corresponding to the electricity utilization data is an electricity stealing user or not according to the probability and the weight of the corresponding data.
Optionally, the determining module includes: the determining unit is used for determining a power stealing suspicious value of the user of the power utilization data through the probability and the weight of the corresponding data; the first judgment unit is used for determining that the user of the electricity utilization data is an electricity stealing user under the condition that the electricity stealing suspicious value exceeds a preset value; and the second judging unit is used for determining that the user of the power utilization data is a non-power stealing user under the condition that the power stealing suspicious value does not exceed the preset value.
According to another aspect of the embodiments of the present invention, there is also provided a computer storage medium, where the computer storage medium includes a stored program, and when the program runs, the apparatus where the computer storage medium is located is controlled to execute any one of the above methods for identifying electricity stealing by a user.
According to another aspect of the embodiments of the present invention, there is also provided a processor, configured to execute a program, where the program executes to perform the method for identifying electricity stealing by a user as described in any one of the above.
In the embodiment of the invention, the electricity utilization data of a user is acquired, wherein the electricity utilization data comprises a plurality of items of data; establishing an analysis model according to the power utilization data, and determining the probability that a plurality of items of data are respectively the electricity stealing probability of the user; respectively adding weights to the multiple items of data; through the probability and the weight of the corresponding data, whether the user corresponding to the electricity utilization data is the electricity stealing user or not is determined, and the purpose of rapidly and accurately determining the electricity stealing user is achieved, so that the technical effects of improving the accuracy and the efficiency of determining the electricity stealing of the user are achieved, and the technical problems that in the related technology, the power utilization data of the user is artificially subjected to statistical analysis by a power system, the manner of determining the electricity stealing of the user is low in efficiency and large in error are solved.
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 application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flowchart of a method for identifying theft of electricity by a user according to an embodiment of the present invention;
fig. 2 is a schematic view of a user electricity stealing recognition apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present invention, there is provided a method embodiment of a user theft identification method, it should be noted that the steps illustrated in the flowchart of the accompanying drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that herein.
Fig. 1 is a flowchart of a user electricity stealing identification method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, acquiring power utilization data of a user, wherein the power utilization data comprises a plurality of items of data;
step S104, establishing an analysis model according to the electricity consumption data, and determining the probability that a plurality of items of data are respectively the electricity stealing probability of the user;
step S106, adding weights to the multiple items of data respectively;
and S108, determining whether the user corresponding to the electricity utilization data is an electricity stealing user or not according to the probability and the weight of the corresponding data.
Through the steps, the electricity utilization data of the user are obtained, wherein the electricity utilization data comprise a plurality of items of data; establishing an analysis model according to the power utilization data, and determining the probability that a plurality of items of data are respectively the electricity stealing probability of the user; respectively adding weights to the multiple items of data; through the probability and the weight of the corresponding data, whether the user corresponding to the electricity utilization data is the electricity stealing user or not is determined, and the purpose of rapidly and accurately determining the electricity stealing user is achieved, so that the technical effects of improving the accuracy and the efficiency of determining the electricity stealing of the user are achieved, and the technical problems that in the related technology, the power utilization data of the user is artificially subjected to statistical analysis by a power system, the manner of determining the electricity stealing of the user is low in efficiency and large in error are solved.
The electricity consumption data of the user comprises a plurality of items of data, and the plurality of items of data can comprise electricity consumption time, electricity consumption change conditions within certain time and the like.
The analysis model may be an analysis model established according to historical electricity consumption data, and the analysis model may be an analysis model established by a regression analysis method, and the electricity consumption behavior of the user is analyzed to obtain probabilities that a plurality of items of data in the electricity consumption data of the user are electricity stealing behaviors of the user respectively.
The above-mentioned addition of the weight to each of the plurality of items of data may be a weight ratio that is given to different items of data according to an existing regression model.
The probability and the weight of the corresponding data are used for determining whether the user corresponding to the electricity utilization data is an electricity stealing user or not, different result possibilities can be calculated for integrating multiple items of data and corresponding weights, the accuracy of an analysis result can be further improved on the basis of a traditional analysis means, and the function of the part is to use an algorithm integrated by a development language and endow different data item weight values with the data of a verified result.
Therefore, the technical effects of improving the accuracy and efficiency of determining the electricity stealing of the user are achieved, and the technical problems that in the related technology, the power system artificially performs statistical analysis on the electricity consumption data of the user to determine the electricity stealing mode of the user, the efficiency is low, and the error is large are solved.
Optionally, the acquiring the power consumption data of the user includes: periodically extracting electricity utilization data from a predetermined webpage or a database; and storing the electricity utilization data locally.
The traditional method is to manually extract the files from the web pages or the database and store the files in the local area. Periodically extracting electricity utilization data from a predetermined webpage or a database; the electricity consumption data is stored locally, the written program can be operated regularly, the data file can be automatically extracted and stored in a local folder, and the method can be realized by linking a database and a simulation browser through a programming language.
Optionally, before establishing an analysis model according to the power consumption data and determining the probability that the plurality of items of data steal power for the user, the method further includes: pre-processing the electricity consumption data, wherein the pre-processing comprises at least one of: and removing invalid data, screening data and correcting data.
The electricity utilization data are preprocessed through a Python language technology, and specifically, functions of removing invalid data, screening and cleaning the data and the like can be realized through simple setting of parameters. No manual intervention is needed after the initial setting.
Optionally, the adding weights to the plurality of items of data respectively includes: and determining weights corresponding to the plurality of items of the electricity consumption data according to the regression model and the verified users of the electricity consumption data.
Therefore, different weight proportions are given to different data items according to the existing regression model, then different result possibilities are calculated by integrating multiple items of data and corresponding weights, the accuracy of an analysis result can be further improved on the basis of the traditional analysis means, and the function of the part is to give different weight values to the data items through the data of a verified result by utilizing an algorithm integrated by a development language.
Optionally, determining whether the user corresponding to the power consumption data is a power stealing user according to the probability and the weight of the corresponding data includes: determining a suspicious electricity stealing value of a user using the electricity data according to the probability and the weight of the corresponding data; determining the user of the electricity utilization data as an electricity stealing user under the condition that the suspicious electricity stealing value exceeds a preset value; and under the condition that the suspicious electricity stealing value does not exceed the preset value, determining the user using the electricity data as a non-electricity stealing user.
The purpose of quickly and accurately determining the electricity stealing users is achieved, the technical effects of improving the accuracy and efficiency of determining electricity stealing of the users are achieved, and the technical problems that in the related technology, the mode of determining electricity stealing of the users is low in efficiency and large in error due to the fact that the power system artificially carries out statistical analysis on the electricity consumption data of the users are solved.
Optionally, after determining whether the user corresponding to the electricity consumption data is an electricity stealing user according to the probability and the weight of the corresponding data, the method further includes: generating a report based on the analytical process data of the electricity usage data, wherein the analytical process data includes at least one of: the weight corresponding to the multiple data and the electricity stealing suspicious value; the report is stored locally.
And generating a report in a Word file form and information stored in Excel according to the picture and the text description of the process data obtained by analysis, and storing the report in a specified position. This can be done by calling a storage facility for the file in the development language function.
It should be noted that the present application also provides an alternative implementation, and the details of the implementation are described below.
The embodiment aims to solve the current situation that the generation of the report wastes time and labor and improve the screening accuracy of the low-voltage electricity-stealing-prevention user. The method is developed by using a programming language, and the automatic generation of the report and the accuracy of the electricity stealing prevention work of low-voltage residents are realized from the extraction of data to the analysis and then to the automatic execution of the formed report, so that a large amount of labor and time cost is saved.
The embodiment provides a method for automatically generating a report, which is specifically developed into a program by using a Python programming language, so that the automation of the whole process from data extraction to report generation is realized.
The first step is data extraction, and the traditional method is to manually extract files from a webpage or a database and store the files in a local file. In the scheme of the invention, only a written program is operated regularly, the data file can be automatically extracted and then stored in the local folder, and the realization of the function depends on the technical scheme of linking the database with the programming language and simulating the browser.
And the second step is to preprocess the data, which is realized mainly by a Python language technology, and can realize the functions of removing invalid data, screening and cleaning the data and the like by simply setting parameters. No manual intervention is needed after the initial setting.
And thirdly, establishing an analysis model according to data obtained by history, giving different weight ratios to different data items according to an existing regression model, and finally, integrating the data items and corresponding weights to calculate different result possibilities.
And finally, generating a report in a Word file form and information stored in Excel according to the pictures and the text descriptions obtained by analysis, and storing the report in a specified position. The function of this step is to call the storage tool for the file in the development language function.
The method of the embodiment is applied to the low-voltage user electricity stealing prevention work, the problem that the low-voltage electricity stealing user is difficult to find is solved, the low-voltage electricity stealing user can be positioned by a salesman only by running a program, and the method has higher efficiency and accuracy in the low-voltage user electricity stealing prevention work process.
Fig. 2 is a schematic view of a user electricity stealing identification apparatus according to an embodiment of the present invention, and as shown in fig. 2, according to another aspect of the embodiment of the present invention, there is also provided a user electricity stealing identification apparatus including: an acquisition module 22, a determination module 24, a weighting module 26, and a decision module 28, which are described in detail below.
The acquisition module 22 is configured to acquire power consumption data of a user, where the power consumption data includes multiple items of data; a determining module 24, connected to the acquiring module 22, for establishing an analysis model according to the power consumption data, and determining the probability that a plurality of items of data are power stealing of the user; a weighting module 26, connected to the determining module 24, for adding weights to the plurality of items of data respectively; and a decision module 28, connected to the weighting module 26, for determining whether the user corresponding to the power consumption data is a power stealing user according to the probability and the weight of the corresponding data.
By the device, the acquisition module 22 is used for acquiring the electricity utilization data of the user, wherein the electricity utilization data comprises a plurality of items of data; the determining module 24 establishes an analysis model according to the power utilization data, and determines the probability that a plurality of items of data are respectively power stealing of the user; the weighting module 26 adds weights to the plurality of items of data respectively; the judging module 28 determines whether the user corresponding to the power consumption data is the power stealing user or not through the probability and the weight of the corresponding data, so as to achieve the purpose of quickly and accurately determining the power stealing user, thereby achieving the technical effect of improving the accuracy and efficiency of determining the power stealing of the user, and further solving the technical problems of low efficiency and large error caused by the fact that the power consumption data of the user is artificially subjected to statistical analysis by a power system in the related technology to determine the power stealing mode of the user.
Optionally, the determining module includes: the determining unit is used for determining the electricity stealing suspicious value of the user using the electricity data according to the probability and the weight of the corresponding data; the first judgment unit is used for determining the user of the electricity utilization data as an electricity stealing user under the condition that the suspicious electricity stealing value exceeds a preset value; and the second judgment unit is used for determining that the user of the power utilization data is a non-power-stealing user under the condition that the suspicious value of power stealing does not exceed the preset value.
According to another aspect of the embodiments of the present invention, there is also provided a computer storage medium including a stored program, wherein when the program runs, an apparatus in which the computer storage medium is located is controlled to execute the user electricity stealing identification method of any one of the above.
According to another aspect of the embodiments of the present invention, there is also provided a processor, configured to execute a program, where the program executes the method for identifying electricity stealing by a user according to any one of the above methods.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method for identifying theft of electricity by a user, comprising:
acquiring power utilization data of a user, wherein the power utilization data comprises a plurality of items of data;
establishing an analysis model according to the electricity utilization data, and determining the probability that the plurality of items of data are respectively the electricity stealing probability of the user;
adding weights to the plurality of items of data respectively;
and determining whether the user corresponding to the electricity utilization data is an electricity stealing user or not according to the probability and the weight of the corresponding data.
2. The user electricity stealing identification method according to claim 1, wherein obtaining electricity usage data of the user comprises:
periodically extracting electricity utilization data from a predetermined webpage or a database;
and storing the electricity utilization data locally.
3. The method for identifying electricity stealing according to claim 1, wherein before establishing an analysis model according to the electricity consumption data and determining the probability that a plurality of items of data are electricity stealing by the user, the method further comprises:
pre-processing the electricity usage data, wherein the pre-processing comprises at least one of:
and removing invalid data, screening data and correcting data.
4. The method of claim 1, wherein the adding of the weight to the plurality of items of data respectively comprises:
and determining weights corresponding to multiple items of data of the electricity utilization data according to the regression model and verified users of the electricity utilization data.
5. The method for identifying electricity stealing according to claim 4, wherein determining whether the user corresponding to the electricity consumption data is an electricity stealing user according to the probability and the weight of the corresponding data comprises:
determining a suspicious electricity stealing value of the user of the electricity utilization data according to the probability and the weight of the corresponding data;
determining the user of the electricity utilization data as an electricity stealing user under the condition that the electricity stealing suspicious value exceeds a preset value;
and under the condition that the suspicious electricity stealing value does not exceed the preset value, determining that the user of the electricity utilization data is a non-electricity stealing user.
6. The method for identifying electricity stealing according to claim 5, wherein after determining whether the user corresponding to the electricity consumption data is an electricity stealing user according to the probability and the weight of the corresponding data, the method further comprises:
generating a report based on analytical process data of the electricity usage data, wherein the analytical process data includes at least one of: the weight corresponding to the multiple data and the electricity stealing suspicious value;
storing the report locally.
7. A user electricity stealing identification device, comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring power utilization data of a user, and the power utilization data comprises a plurality of items of data;
the determining module is used for establishing an analysis model according to the power utilization data and determining the probability that the plurality of items of data are power stealing of the user respectively;
the weighting module is used for adding weights to the plurality of items of data respectively;
and the judging module is used for determining whether the user corresponding to the electricity utilization data is an electricity stealing user or not according to the probability and the weight of the corresponding data.
8. The user electricity stealing identification device according to claim 7, wherein the decision module comprises:
the determining unit is used for determining a power stealing suspicious value of the user of the power utilization data through the probability and the weight of the corresponding data;
the first judgment unit is used for determining that the user of the electricity utilization data is an electricity stealing user under the condition that the electricity stealing suspicious value exceeds a preset value;
and the second judging unit is used for determining that the user of the power utilization data is a non-power stealing user under the condition that the power stealing suspicious value does not exceed the preset value.
9. A computer storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the computer storage medium is located to perform the method of identifying electricity stealing by a user according to any one of claims 1 to 6.
10. A processor, characterized in that the processor is configured to run a program, wherein the program is configured to execute the method of identifying electricity stealing according to any one of claims 1 to 6.
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| CN113222624A (en) * | 2021-05-31 | 2021-08-06 | 江苏新智合电力技术有限公司 | Intelligent analysis method and system for preventing electricity stealing |
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