One-site multi-user analysis method and device based on RPA technology

Abstract

A one-address multi-user analysis method and device based on RPA technology, the method uses a preset identity credential to log in to a designated power system through an RPA robot, and retrieves and extracts basic information of electricity users in the power system according to set rules; uses the collected basic information of electricity users in the power system, the electricity line information of electricity users in the power system, and the account contact information to identify a one-address multi-suspect electricity user object in the power system through a suspicious point algorithm logic; generates a one-address multi-suspect user file containing suspicious point information for the identified one-address multi-suspect electricity user object in the power system through an RPA robot, and sends the one-address multi-suspect user file to a designated review and processing terminal for subsequent manual review or processing. The present invention improves the efficiency of power system data management, enhances user satisfaction, and reduces operational risks.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system analysis, and specifically relates to a single-site multi-user analysis method and device based on RPA technology. Background Art

[0002] RPA technology is a business process automation technology based on software robots and artificial intelligence. RPA technology can automatically process repetitive tasks such as data entry and data processing, improve work efficiency and accuracy, and can link multiple business systems to achieve process reengineering. At the same time, RPA technology will not affect the functions and stability of existing IT systems, can balance efficiency and cost to the greatest extent, and has a short return on investment cycle.

[0003] At present, in the power industry, especially in the field of low-voltage marketing, there is often a situation of multiple households at one address, that is, there are multiple electricity users at the same address. For multiple electricity users at the same address, it is easy to lead to low power supply efficiency and high operating costs for a long time, and it is impossible to provide personalized services and accurate billing for electricity users. Therefore, identifying the situation of multiple users at one address has practical application significance for optimizing the power supply structure and line layout, improving the efficiency of the power system and user satisfaction. Summary of the invention

[0004] To this end, the present invention provides a one-site multi-user analysis method and device based on RPA technology, which can identify abnormal situations such as multiple households at one site, thereby optimizing the power supply structure and line layout, and improving the efficiency of the power system and user satisfaction.

[0005] In order to achieve the above object, the present invention provides the following technical solution: a one-address multi-user analysis method based on RPA technology, comprising:

[0006] Calling an RPA robot, using the RPA robot to log in to a specified power system using preset identity credentials, and retrieving and extracting basic information of electricity users in the power system according to set rules;

[0007] The RPA robot collects the power line information and account contact information of the power users in the power system, and uses the collected basic information of the power users in the power system, the power line information and account contact information of the power users in the power system to identify the one-address multiple-suspect power user objects in the power system through the suspicious point algorithm logic;

[0008] The RPA robot generates a multi-address user file containing suspicious information for the identified multi-address electricity customer object in the power system, and sends the multi-address user file to a designated review and processing terminal for subsequent manual review or processing.

[0009] As a preferred solution of the one-site multi-user analysis method based on RPA technology, the basic information of the electricity users in the power system retrieved and extracted according to the set rules includes user name, user number and electricity address.

[0010] As a preferred solution for the one-address multi-user analysis method based on RPA technology, the suspicious point algorithm logic includes customer grouping, address consistent customer screening, address level comparison and level comparison result screening.

[0011] As a preferred solution for the one-site multi-user analysis method based on RPA technology, during the customer grouping process:

[0012] The RPA robot captures the basic information, the power lines to which they belong, and the account contact information of all electricity users in the power system, and divides the electricity users located in the same power line and having the same account contact into one electricity customer group.

[0013] As a preferred solution for the one-address multi-user analysis method based on RPA technology, during the screening process of customers with the same address:

[0014] In each electricity customer group, electricity customers with exactly the same electricity usage addresses are screened out, and the screened out electricity customers with exactly the same electricity usage addresses are used as partial results of one-address multiple-suspect electricity customer objects in the power system.

[0015] As a preferred solution of the one-address multi-user analysis method based on RPA technology, in the address level comparison process, after filtering out the electricity users with exactly the same electricity usage addresses in each electricity user group, the remaining electricity users are compared at the address level. The address level comparison step includes:

[0016] Exclude electricity users of preset types, including those whose "neighborhood / village committee" and "road / street" parts in the electricity usage address are either empty;

[0017] For the remaining electricity users after excluding the preset types of electricity users, the five levels of "district", "street", "residential / village committee", "road" and "street" are compared layer by layer. If the values ​​of the current level are the same, the values ​​of the next level are compared. If the values ​​of the current level are different, it is determined that the addresses of the electricity users currently being compared are inconsistent, and the electricity users with inconsistent addresses are excluded from the results of the electricity users with multiple suspicious points at one address.

[0018] If both values ​​of the two compared electricity customers at the current level are empty, or one of the values ​​is empty, the comparison of the current level is skipped and the comparison is performed directly at the next level.

[0019] As a preferred solution for the one-address multi-user analysis method based on RPA technology, in the process of screening the hierarchical comparison results, after completing the comparison of the five levels of "district", "street", "neighborhood / village committee", "road" and "street", the electricity users whose address information is consistent or similar more than 4 times in all compared levels are screened out, and the electricity users whose address information is consistent or similar more than 4 times in all compared levels are classified into the results of one-address multi-suspect electricity customer objects in the power system.

[0020] The present invention also provides a one-address multi-user analysis device based on RPA technology, comprising:

[0021] An electricity customer information retrieval and extraction module is used to call an RPA robot, through which the RPA robot uses preset identity credentials to log in to a specified power system, and retrieve and extract basic information of electricity customers in the power system according to set rules;

[0022] A suspicious electricity customer object identification module is used to collect the power line information and account contact information of the electricity customers in the power system through the RPA robot, and use the collected basic information of the electricity customers in the power system, the power line information and account contact information of the electricity customers in the power system to identify multiple suspicious electricity customer objects with one address in the power system through suspicious algorithm logic;

[0023] The suspicious user file processing module is used to generate a one-address multiple-suspect user file containing suspicious information for the identified one-address multiple-suspect electricity customer object in the power system through the RPA robot, and send the one-address multiple-suspect user file to the designated review and processing terminal for subsequent manual review or processing.

[0024] As a preferred solution of a one-site multi-user analysis device based on RPA technology, in the electricity customer information retrieval and extraction module, the basic information of the electricity customers in the power system retrieved and extracted according to the set rules includes the user name, user number and electricity address;

[0025] The suspicious electricity customer object identification module includes a customer grouping submodule, a customer screening submodule with consistent addresses, an address level comparison submodule and a level comparison result screening submodule.

[0026] As a preferred solution for a single-site multi-user analysis device based on RPA technology, in the customer grouping submodule, the RPA robot captures the basic information, the power lines and the account contact information of all electricity users in the power system, and divides the electricity users located on the same power line and with the same account contact into one electricity customer group.

[0027] As a preferred solution of the one-address multi-user analysis device based on RPA technology, in the address-consistent customer screening submodule, in each electricity customer group, electricity customers with exactly the same electricity usage addresses are screened out, and the screened out electricity customers with exactly the same electricity usage addresses are used as partial results of one-address multi-suspect electricity customer objects in the power system.

[0028] As a preferred solution of a one-address multi-user analysis device based on RPA technology, the address level comparison submodule includes:

[0029] A preset type customer exclusion unit is used to exclude preset type electricity users, including electricity users whose "neighborhood / village committee" and "road / street" parts in the electricity address are either empty;

[0030] The address layer-by-layer comparison unit is used to compare the remaining electricity users after excluding the preset type of electricity users in the order of "district", "street", "residential / village committee", "road" and "street". If the values ​​of the current layer are the same, the value of the next layer is compared; if the values ​​of the current layer are different, it is determined that the addresses of the electricity users currently being compared are inconsistent, and the electricity users with inconsistent addresses are excluded from the result of the electricity user object with multiple suspicious points at one address;

[0031] In the address layer-by-layer comparison unit, if both values ​​of the two compared electricity users at the current layer are empty, or one of the values ​​is empty, the comparison at the current layer is skipped and the comparison at the next layer is directly performed;

[0032] In the hierarchical comparison result screening submodule, after completing the comparison of the five hierarchical levels of "district", "street", "neighborhood / village committee", "road" and "street", electricity users whose address information is consistent or similar more than 4 times in all compared levels are screened out, and the electricity users whose address information is consistent or similar more than 4 times in all compared levels are classified into the results of one-address multiple-suspect electricity user objects in the power system.

[0033] The beneficial effects of the present invention are as follows: calling an RPA robot, using the preset identity credentials to log in to the designated power system through the RPA robot, and searching and extracting the basic information of the power customers in the power system according to the set rules; collecting the power line information and account contact information of the power customers in the power system through the RPA robot, using the collected basic information of the power customers in the power system, the power line information and account contact information of the power customers in the power system, and identifying the one-address multi-suspect power customer object in the power system through the suspicious point algorithm logic; generating a one-address multi-suspect user file containing suspicious point information for the identified one-address multi-suspect power customer object in the power system through the RPA robot, and sending the one-address multi-suspect user file to the designated review and processing terminal for subsequent manual review or processing. The present invention reduces manual intervention and error rate based on the use of RPA robots, while increasing the speed of data processing; it can adapt to different data formats and structures, has good versatility and adaptability, improves the efficiency of power system data management, and enhances user satisfaction and reduces operational risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for the implementation methods or the prior art descriptions are briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0035] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment of size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0036] Figure 1 A schematic diagram of a single-site multi-user analysis method based on RPA technology provided in an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of the technical architecture of a one-site multi-user analysis method based on RPA technology provided in an embodiment of the present invention;

[0038] Figure 3 A logical flow chart of a suspicious point algorithm in a single-address multi-user analysis method based on RPA technology provided in an embodiment of the present invention;

[0039] Figure 4 An architecture diagram of a single-site multi-user analysis device based on RPA technology provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following is a description of the implementation of the present invention by specific embodiments. People familiar with the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Example 1

[0042] See also Figure 1 , Figure 2 and Figure 3 Embodiment 1 of the present invention provides a method for analyzing multiple users at one address based on RPA technology, comprising the following steps:

[0043] S1. Calling an RPA robot, using the RPA robot to log in to a specified power system using preset identity credentials, and retrieving and extracting basic information of electricity users in the power system according to set rules;

[0044] S2. The RPA robot is used to collect the power line information and account contact information of the power users in the power system, and the basic information of the power users in the power system, the power line information and account contact information of the power users in the power system are collected, and the one-address multiple-suspect power user objects in the power system are identified through the doubt algorithm logic;

[0045] S3. The RPA robot generates a user file with multiple suspicious addresses containing suspicious information for the identified electricity customer object with multiple suspicious addresses in the power system, and sends the user file with multiple suspicious addresses to a designated review and processing terminal for subsequent manual review or processing.

[0046] In this embodiment, in step S1, the RPA robot automatically logs into the power system using the preset credentials, and then retrieves and extracts the basic information of the electricity users in the power system, including the user name, user number and electricity address, according to the set rules. In addition, the RPA robot is also responsible for collecting the electricity line information and account contact information of the electricity users. Then in step S2, after successfully obtaining all the electricity user data, the RPA robot will conduct an in-depth analysis of the basic information of the electricity users in the power system, the electricity line information of the electricity users in the power system, and the account contact information based on the doubt algorithm logic to identify potential problems such as multiple households at one address.

[0047] See also Figure 3 In this embodiment, in step S2, the doubt algorithm logic includes customer grouping, address consistent customer screening, address level comparison and level comparison result screening.

[0048] Specifically, during the customer grouping process:

[0049] The RPA robot captures the basic information (including user name, user number and electricity address), the power line and account contact information of all electricity users in the power system, and divides the electricity users on the same power line and with the same account contact into one electricity customer group.

[0050] Specifically, during the screening process of customers with consistent addresses:

[0051] In each electricity customer group, electricity customers with exactly the same electricity usage addresses are screened out. Since the address information of the electricity customers completely matches, the screened out electricity customers with exactly the same electricity usage addresses are used as part of the result of a multiple-suspect electricity customer object with one address in the power system.

[0052] Specifically, in the address level comparison process, after filtering out electricity users with exactly the same electricity usage addresses in each electricity user group, address level comparison is performed on the remaining electricity users, and the address level comparison step includes:

[0053] The preset types of electricity users are excluded, and the preset types of electricity users include electricity users whose "residential / village committee" and "road / street" parts in the electricity usage address are either empty; that is, if either the "residential / village committee" or "road / street" part in the electricity usage address is empty, the corresponding electricity user is regarded as a special electricity user, and the special electricity user is excluded from the comparison process;

[0054] For the remaining electricity users after excluding the preset types of electricity users, the five levels of "district", "street", "residential / village committee", "road" and "street" are compared layer by layer. If the values ​​of the current level are the same, the values ​​of the next level are compared. If the values ​​of the current level are different, it is determined that the addresses of the electricity users currently being compared are inconsistent, and the electricity users with inconsistent addresses are excluded from the results of the electricity users with multiple suspicious points at one address.

[0055] If both values ​​of the two compared electricity customers at the current level are empty, or one of the values ​​is empty, the comparison of the current level is skipped and the comparison is performed directly at the next level.

[0056] Specifically, in the process of screening the hierarchical comparison results, after completing the comparison of the five levels of "district", "street", "neighborhood / village committee", "road" and "street", electricity users whose address information is consistent or similar more than 4 times in all compared levels are screened out, and the electricity users whose address information is consistent or similar more than 4 times in all compared levels are classified into the results of one-address multiple-suspect electricity customer objects in the power system.

[0057] Thus, the suspicious point algorithm logic can accurately identify those electricity users whose address information is highly similar or completely consistent, while excluding those electricity users whose address information is incomplete or has obvious differences. The use of suspicious point algorithm logic helps to improve the accuracy of address matching and can effectively handle the null value situation in address information.

[0058] In this embodiment, in step S3, after the logical analysis of the suspicious point algorithm is completed, the RPA robot will generate a one-address multi-suspect point user file containing suspicious point information for subsequent manual review or further automated processing, thereby significantly improving the automation level of power system data management, improving the efficiency and accuracy of data processing, and helping to quickly locate and solve problems in power supply and management.

[0059] The use of RPA robots reduces manual intervention, reduces the error rate, and increases the speed of data processing. The design of the suspicious point algorithm logic reflects a deep understanding of the characteristics of power system data, can adapt to different data formats and structures, and has good versatility and adaptability. The implementation of this method can bring an efficiency and accuracy innovation to the power industry, which is of great significance to improving the service level and operation quality of the entire power industry.

[0060] In summary, the embodiment of the present invention calls an RPA robot, through which the RPA robot uses preset identity credentials to log in to a designated power system, and retrieves and extracts basic information of electricity users in the power system according to set rules; the RPA robot collects power line information and account contact information of electricity users in the power system, and uses the collected basic information of electricity users in the power system, the power line information and account contact information of electricity users in the power system to identify a single-address multi-suspect power customer object in the power system through a suspicious point algorithm logic; the RPA robot generates a single-address multi-suspect user file containing suspicious point information for the identified single-address multi-suspect power customer object in the power system, and sends the single-address multi-suspect user file to a designated review and processing terminal for subsequent manual review or processing. The suspicious point algorithm logic includes customer grouping, screening of customers with consistent addresses, address level comparison and level comparison result screening; in the customer grouping process: the RPA robot captures the basic information of all electricity customers in the power system, the electricity lines they belong to and the account contact information, and divides the electricity customers located on the same electricity line and with the same account contact into one electricity customer group; in the screening of customers with consistent addresses: in each electricity customer group, screen out electricity customers with exactly the same electricity addresses, and use the screened out electricity customers with exactly the same electricity addresses as part of the result of one-address-multiple-suspicious-point-electricity-customer-objects in the power system; in the address level comparison process, after screening out electricity customers with exactly the same electricity addresses in each electricity customer group, perform address level comparison on the remaining electricity customers, and the address level comparison step includes: excluding electricity customers of preset types, and the preset types of electricity customers include customers with either the "neighborhood / village committee" or the "road / street" part in the electricity address as Empty electricity users; for the remaining electricity users after excluding the preset types of electricity users, compare them layer by layer in the order of "district", "street", "residential / village committee", "road" and "street". If the values ​​of the current layer are the same, continue to compare the values ​​of the next layer; if the values ​​of the current layer are different, it is determined that the addresses of the currently compared electricity users are inconsistent, and the electricity users with inconsistent addresses are excluded from the results of the single-address multiple-suspect electricity user object; if the two values ​​of the two compared electricity users at the current layer are both empty, or one of the values ​​is empty, skip the comparison of the current layer and directly enter the next layer for comparison; in the process of screening the hierarchical comparison results, after completing the comparison of the five layers of "district", "street", "residential / village committee", "road" and "street", screen out the electricity users whose address information is consistent or similar for more than 4 times in all compared layers, and classify the electricity users whose address information is consistent or similar for more than 4 times in all compared layers into the results of the single-address multiple-suspect electricity user object in the power system.The present invention reduces manual intervention and error rates based on the use of RPA robots, while increasing the speed of data processing; it can adapt to different data formats and structures, has good versatility and adaptability, improves the efficiency of power system data management, and at the same time enhances user satisfaction and reduces operational risks.

[0061] It should be noted that the method of the embodiment of the present disclosure can be performed by a single device, such as a computer or a server. The method of the present embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete the described method.

[0062] It should be noted that the above describes some embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0063] Example 2

[0064] See also Figure 4 Embodiment 2 of the present invention provides a single-address multi-user analysis device based on RPA technology, including:

[0065] The electricity customer information retrieval and extraction module 001 is used to call the RPA robot, log in to the specified power system through the RPA robot using the preset identity credentials, and retrieve and extract the basic information of the electricity customers in the power system according to the set rules;

[0066] The suspicious electricity customer object identification module 002 is used to collect the power line information and account contact information of the electricity customers in the power system through the RPA robot, and use the collected basic information of the electricity customers in the power system, the power line information and account contact information of the electricity customers in the power system to identify multiple suspicious electricity customer objects with one address in the power system through suspicious algorithm logic;

[0067] The suspicious user file processing module 003 is used to generate a one-address multiple-suspect user file containing suspicious information for the identified one-address multiple-suspect electricity customer object in the power system through the RPA robot, and send the one-address multiple-suspect user file to the designated review and processing terminal for subsequent manual review or processing.

[0068] In the present embodiment, in the electricity customer information retrieval and extraction module 001, the basic information of the electricity customer in the power system retrieved and extracted according to the set rules includes the user name, user number and electricity address;

[0069] The suspicious electricity customer object identification module 002 includes a customer grouping submodule 201 , a customer screening submodule 202 with consistent addresses, an address level comparison submodule 203 and a level comparison result screening submodule 204 .

[0070] In this embodiment, in the customer grouping submodule 201, the RPA robot captures the basic information, the power lines to which they belong, and the account contact information of all electricity users in the power system, and divides the electricity users located on the same power line and with the same account contact into one electricity customer group.

[0071] In this embodiment, in the address consistent customer screening submodule 202, in each electricity customer group, electricity customers with exactly the same electricity usage addresses are screened out, and the screened out electricity customers with exactly the same electricity usage addresses are used as part of the result of a multiple-suspect-address electricity customer object in the power system.

[0072] In this embodiment, the address level comparison submodule 203 includes:

[0073] A preset type customer exclusion unit 231 is used to exclude preset type electricity users, where the preset type of electricity users include electricity users whose "neighborhood / village committee" and "road / street" parts in the electricity address are either empty;

[0074] The address layer-by-layer comparison unit 232 is used to compare the remaining electricity users after excluding the preset type of electricity users in the order of "district", "street", "residential / village committee", "road" and "street". If the values ​​of the current layer are the same, the value of the next layer is compared; if the values ​​of the current layer are different, it is determined that the addresses of the electricity users currently being compared are inconsistent, and the electricity users with inconsistent addresses are excluded from the result of the electricity user object with multiple suspicious points at one address;

[0075] In the address layer-by-layer comparison unit 232, if both values ​​of the two compared electricity users at the current layer are empty, or one of the values ​​is empty, the comparison at the current layer is skipped and the comparison at the next layer is directly performed;

[0076] In the hierarchical comparison result screening submodule 204, after the comparison of the five hierarchical levels of "district", "sub-district", "residential / village committee", "road" and "street" is completed, electricity users whose address information is consistent or similar for more than 4 times in all compared levels are screened out, and the electricity users whose address information is consistent or similar for more than 4 times in all compared levels are classified into the result of one-address multiple-suspect electricity user objects in the power system.

[0077] It should be noted that the information interaction, execution process, etc. between the modules / units of the above-mentioned device are based on the same concept as the method embodiment in Example 1 of the present application, and the technical effects they bring are the same as those of the method embodiment of the present application. For specific contents, please refer to the description in the method embodiment shown in the previous part of the present application, and will not be repeated here.

[0078] Example 3

[0079] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, in which a program code of a single-address multi-user analysis method based on RPA technology is stored, and the program code includes instructions for executing embodiment 1 or any possible implementation method of the single-address multi-user analysis method based on RPA technology.

[0080] Computer-readable storage media can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0081] Example 4

[0082] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0083] The processor and the memory communicate with each other via a bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the one-site multi-user analysis method based on RPA technology of Example 1 or any possible implementation thereof.

[0084] Specifically, the processor can be implemented by hardware or by software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor can be a general-purpose processor implemented by reading software codes stored in a memory. The memory can be integrated in the processor or can be located outside the processor and exist independently.

[0085] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center.

[0086] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0087] Although the present invention has been described in detail above by general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made to the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. A one-site multi-user analysis method based on RPA technology, characterized in that: include: Calling an RPA robot, using the RPA robot to log in to a specified power system using preset identity credentials, and retrieving and extracting basic information of electricity users in the power system according to set rules; The RPA robot collects the power line information and account contact information of the power users in the power system, and uses the collected basic information of the power users in the power system, the power line information and account contact information of the power users in the power system to identify the one-address multiple-suspect power user objects in the power system through the suspicious point algorithm logic; Generate a multi-address user file containing suspicious information for the identified multi-address electricity customer object in the power system by the RPA robot, and send the multi-address user file to a designated review and processing terminal for subsequent manual review or processing; The doubt algorithm logic includes customer grouping, address-consistent customer screening, address level comparison, and level comparison result screening; During the customer grouping process: The RPA robot captures the basic information, the power lines to which they belong, and the account contact information of all the power users in the power system, and divides the power users located in the same power line and having the same account contact into one power user group; The address is consistent with the customer screening process: In each electricity customer group, electricity customers with exactly the same electricity usage addresses are screened out, and the screened out electricity customers with exactly the same electricity usage addresses are used as partial results of one-address multiple-suspect electricity customer objects in the power system; In the address level comparison process, after filtering out electricity users with exactly the same electricity usage addresses in each electricity user group, address level comparison is performed on the remaining electricity users. The address level comparison step includes: Exclude the preset types of electricity users, including those whose "Residential / Village Committee" and "Road / Street" parts in the electricity usage address are empty; For the remaining electricity users after excluding the preset types of electricity users, the five levels of "district", "street", "neighborhood / village committee", "road" and "street" are compared layer by layer. If the values ​​of the current level are the same, the values ​​of the next level are compared. If the values ​​of the current level are different, it is determined that the addresses of the electricity users currently being compared are inconsistent, and the electricity users with inconsistent addresses are excluded from the results of the electricity users with multiple suspicious points at one address object. If both values ​​of the two compared electricity customers at the current level are empty, or one of the values ​​is empty, the comparison at the current level is skipped and the comparison at the next level is performed directly; During the screening process of the hierarchical comparison results, after completing the comparison of the five levels of "district", "street", "neighborhood / village committee", "road" and "street", electricity users whose address information is consistent or similar more than 4 times in all compared levels are screened out, and the electricity users whose address information is consistent or similar more than 4 times in all compared levels are classified into the results of one-address multiple-suspect electricity user objects in the power system.

2. According to the RPA technology-based one-site multi-user analysis method of claim 1, it is characterized in that: The basic information of the electricity users in the power system retrieved and extracted according to the set rules includes user name, user number and electricity address.

3. A one-site multi-user analysis device based on RPA technology, characterized in that: include: An electricity customer information retrieval and extraction module is used to call an RPA robot, through which the RPA robot uses preset identity credentials to log in to a specified power system, and retrieve and extract basic information of electricity customers in the power system according to set rules; A suspicious electricity customer object identification module is used to collect the power line information and account contact information of the electricity customers in the power system through the RPA robot, and use the collected basic information of the electricity customers in the power system, the power line information and account contact information of the electricity customers in the power system to identify multiple suspicious electricity customer objects with one address in the power system through suspicious algorithm logic; A suspicious user file processing module is used to generate a one-address multiple suspicious user file containing suspicious information for the identified one-address multiple suspicious electricity customer object in the power system through the RPA robot, and send the one-address multiple suspicious user file to a designated review and processing terminal for subsequent manual review or processing; The suspicious electricity customer object identification module includes a customer grouping submodule, a consistent address customer screening submodule, an address level comparison submodule and a level comparison result screening submodule; In the customer grouping submodule, the RPA robot captures the basic information, the power lines to which they belong, and the account contact information of all electricity users in the power system, and divides the electricity users located in the same power line and having the same account contact into one electricity customer group; In the address consistent customer screening submodule, in each electricity customer group, electricity customers with exactly the same electricity usage addresses are screened out, and the screened out electricity customers with exactly the same electricity usage addresses are used as partial results of the one-address multiple-suspect electricity customer objects in the power system; The address level comparison submodule includes: A preset type customer exclusion unit is used to exclude preset type electricity users, including electricity users whose "neighborhood / village committee" and "road / street" parts in the electricity address are either empty; The address layer-by-layer comparison unit is used to compare the remaining electricity users after excluding the preset type of electricity users in the order of "district", "street", "residential / village committee", "road" and "street". If the values ​​of the current layer are the same, the value of the next layer is compared; if the values ​​of the current layer are different, it is determined that the addresses of the electricity users currently being compared are inconsistent, and the electricity users with inconsistent addresses are excluded from the result of the electricity user object with multiple suspicious points at one address; In the address layer-by-layer comparison unit, if both values ​​of the two compared electricity users at the current layer are empty, or one of the values ​​is empty, the comparison at the current layer is skipped and the comparison at the next layer is directly performed; In the hierarchical comparison result screening submodule, after completing the comparison of the five levels of "district", "street", "neighborhood / village committee", "road" and "street", electricity users whose address information is consistent or similar more than 4 times in all compared levels are screened out, and the electricity users whose address information is consistent or similar more than 4 times in all compared levels are classified into the results of one-address multiple-suspect electricity user objects in the power system.

4. The one-address multi-user analysis device based on RPA technology according to claim 3 is characterized in that: In the electricity customer information retrieval and extraction module, the basic information of the electricity customers in the power system retrieved and extracted according to the set rules includes the user name, user number and electricity address.

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