Power distribution network optimization operation method and system based on GIS real-time monitoring

Abstract

The invention discloses a power distribution network optimization operation method and system based on GIS real-time monitoring, and relates to the technical field of power distribution network optimization, and the method comprises the steps: accessing power distribution network data of an area needing to be processed, carrying out the preliminary filtering processing of the data, extracting sensitive data in the data, and carrying out the calculation of the sensitive data. By arranging the GIS control module, the power distribution network data access module and the data operation module, power distribution network optimization management can be achieved through enterprise intranet cloud management and control, the intelligent level of power distribution network optimization management is improved, meanwhile, workers can conveniently inquire links one by one, the overall operation period is shortened, and the work efficiency is improved. Corresponding authority data are inquired and managed by setting corresponding authority, overall encryption is achieved, data leakage conditions are reduced, power resources are reasonably configured for the power distribution network, energy consumption and operation cost are reduced, spatial data management of the power distribution network is achieved through the GIS technology, and visual display of geographic information is provided. And work is helped to quickly identify a problem area.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution network optimization, and in particular to a power distribution network optimization operation method and system based on GIS real-time monitoring. Background Art

[0002] The distribution network is an important part of the power system, and the safe power supply of the distribution network is of great significance to people's daily life and social production. The distribution transformer is a key equipment in the distribution network. It undertakes the important tasks of voltage conversion and power distribution. At the same time, the distribution transformer directly faces the end users, so it has a vital impact on ensuring the safe power supply of the distribution network. Therefore, how to improve the reliability and service life of the distribution transformer in the distribution network and ensure the normal operation of the distribution network has positive significance for the safe and stable operation of the power system.

[0003] Chinese patent announcement number CN 105207210 B discloses a distribution network optimization operation method and system, wherein the method includes the following steps: obtaining the current load rate of the distribution transformer in the distribution network; determining the optimization objective function of the distribution network operation according to the current load rate; combining the optimization objective function and the genetic algorithm to calculate the optimization result; and operating the distribution network according to the optimization result. The above-mentioned distribution network optimization operation method selects the optimization target of the distribution network reconstruction according to the actual load rate state of the distribution transformer, avoiding the complex process of obtaining the optimization target by calculating the hot spot temperature of the distribution transformer, and at the same time operating the load equipment therein with the optimized distribution network structure, so as to achieve the purpose of extending the life of the distribution transformer and optimizing the safe operation of the distribution network.

[0004] However, when the above scheme is used, the following problems still exist: while optimizing the operation of the distribution network, the management of manual permissions is ignored, which makes data leakage easy to occur. When an abnormality occurs in one of the links, remote workers cannot obtain early warnings and reminders in the first time, which affects the intelligence of the overall operation and causes different degrees of impact on the actual operation. Therefore, the present invention needs to design a distribution network optimization operation method and system based on GIS real-time monitoring to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a distribution network optimization operation method and system based on GIS real-time monitoring in order to solve the above problems, thereby solving the problems mentioned in the background technology.

[0006] In order to solve the above problems, the present invention provides a technical solution:

[0007] A distribution network optimization operation method based on GIS real-time monitoring, comprising:

[0008] The GIS is a geographic information system;

[0009] S1. Access the distribution network data of the area to be processed, perform preliminary filtering on the data, remove sensitive data, use data analysis and processing algorithms to analyze real-time data, and evaluate the operating status of the distribution network;

[0010] S2. Perform multiple sets of simulation operations based on the parameters provided by the learning analysis model, encrypt different data under different permission queries at corresponding levels, and issue an early warning through an external warning device when there is a discrepancy between the permission and the query data level;

[0011] S3. Query and call out all the received data, perform imaging processing on the specified data, and generate corresponding tables for comparison according to requirements during imaging;

[0012] S4. Monitor and process the real-time operating data after starting each device, and collect the change data of the distribution network operating status through multiple sensors.

[0013] As a preferred technical solution, the sensitive data in step S1 includes confidential data, personnel identity information data, and virus data.

[0014] As a preferred technical solution, the external warning device in step S2 includes a buzzer and a warning light.

[0015] As a preferred technical solution, the sensor in step S4 includes a current sensor, a power sensor, a voltage sensor, a vibration sensor and a frequency sensor.

[0016] As a preferred technical solution, the changed data in step S4 includes parameters such as current, voltage, and load.

[0017] A distribution network optimization operation system based on GIS real-time monitoring, the distribution network optimization operation system comprises a GIS control module, a real-time monitoring module, a distribution network data access module and a data operation module, the output end of the distribution network data access module is communicatively connected to the input end of the data operation module, and the output end of the data operation module is communicatively connected to the input end of the GIS control module.

[0018] As a preferred technical solution, the GIS control module includes a visualization unit, a storage management unit and a learning analysis model, and the output ends of the storage management unit and the learning analysis model are both communicatively connected to the input end of the visualization unit;

[0019] The visualization unit is used to query and call out all the received data, perform imaging processing on the specified data, and generate a corresponding table for comparison according to the needs during imaging;

[0020] The storage management unit is used to store and manage the geospatial data of the power distribution network locally and remotely, respectively, and set corresponding access permission folders. The staff with corresponding permissions can only access the folders with corresponding permissions to view the required geospatial data;

[0021] The learning analysis model is used to manually set a learning direction, continuously fill in the learning goals to be achieved, conduct autonomous learning, and set a threshold at the same time. When the learning analysis model deviates from the set direction, the remote staff is reminded to make adjustments.

[0022] As a preferred technical solution, the real-time monitoring module includes a historical data monitoring unit, a real-time operation monitoring unit and a multi-level access verification unit, the multi-level access verification unit is bidirectionally connected to the real-time operation monitoring unit, and the historical data monitoring unit is bidirectionally connected to the real-time operation monitoring unit;

[0023] The historical data monitoring unit is used to monitor the historical data stored locally. When data loss or data ambiguity occurs, it performs self-cutting processing to prevent affecting other modules and units. When a certain section of historical data needs to be used, the corresponding query instruction is input through the historical data monitoring unit to perform subsequent operations;

[0024] The real-time operation monitoring unit is used to monitor and process the real-time operation data of the power distribution network optimization operation system after startup, and collect the change data of the power distribution network operation status through multiple sensors, including current, voltage, load and other parameters. When data loss or data ambiguity occurs, self-cut-off processing is performed to prevent affecting other modules and units;

[0025] The multi-level access verification unit is used to receive the identity information authentication operation of the staff, thereby granting corresponding access rights.

[0026] As a preferred technical solution, the power distribution network data access module includes a power distribution network data access unit, an optimization resource control unit and other data access units, and the output ends of the power distribution network data access unit and the other data access units are respectively communicatively connected to the input end of the optimization resource control unit;

[0027] The power distribution network data access unit is used to access the power distribution network data of the required processing area, perform preliminary filtering on the data, and remove sensitive data therein. Keywords and general content of the sensitive data can be set in advance;

[0028] The resource optimization control unit is used to analyze real-time data using data analysis and processing algorithms, evaluate the operating status of the power distribution network, and thus optimize the operation of the power distribution network;

[0029] The other data access unit is used to access data from other industries, fields and related data.

[0030] As a preferred technical solution, the data operation module includes a simulation operation unit, a data encryption unit and a spatial data analysis unit, the output end of the spatial data analysis unit is communicatively connected to the input end of the simulation operation unit, and the data encryption unit is bidirectionally communicatively connected to the simulation operation unit and the spatial data analysis unit respectively;

[0031] The simulation operation unit is used to perform multiple groups of simulation operation operations according to the parameters provided by the learning analysis model, observe the differences between the multiple groups of operation results and the problems that occur in the simulation process, make corresponding records, sort the problems according to their importance, generate charts and corresponding generation dates, and facilitate manual management and query;

[0032] The data encryption unit is used to encrypt different data under different authority queries at corresponding levels. When the authority and the query data level are inconsistent, an external warning device is used to issue an early warning;

[0033] The spatial data analysis unit is used to provide an optimized operation strategy for the power distribution network by using optimization algorithms and models.

[0034] The beneficial effects of the present invention are as follows: the present invention constructs a complete distribution network optimization operation system by setting up a GIS control module, a real-time monitoring module, a distribution network data access module and a data operation module. In actual use, by accessing the distribution network data of the required processing area, the data is preliminarily filtered and processed, and the sensitive data therein is proposed. The real-time data is analyzed by using data analysis and processing algorithms to evaluate the operation status of the distribution network. According to the parameters provided by the learning analysis model, multiple groups of simulation operations are performed, and different data under different authority queries are encrypted at corresponding levels. When the authority is inconsistent with the query data level, an external warning device is used to issue an early warning, and all the received data are queried and called out. The designated data is imaged and processed, and the imaging can be performed according to the needs. Generate corresponding tables for comparison operations, monitor and process real-time running data after starting each device, collect change data on the distribution network operation status through multiple sensors, manage, visualize and store distribution network optimization data and corresponding analysis results, which will help to achieve distribution network optimization management through enterprise intranet cloud management and control, improve the intelligence level of distribution network optimization management, and facilitate staff to query each link, shortening the overall operation cycle. By setting corresponding authority to query and manage corresponding authority data, overall encryption is achieved, reducing data leakage, and reducing energy consumption and operating costs through reasonable allocation of power resources in the distribution network. GIS technology is used to achieve spatial data management of the distribution network, providing a visual display of geographic information to help workers quickly identify problem areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] For ease of explanation, the present invention is described in detail with reference to the following specific implementations and the accompanying drawings.

[0036] Figure 1 This is a distribution network optimization operation method based on GIS real-time monitoring and a system overall process step diagram of the present invention;

[0037] Figure 2 The invention discloses an overall structural topology diagram of a power distribution network optimization operation method and system based on GIS real-time monitoring. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of this application clearer, this application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0039] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0040] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0041] It should be understood that although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0042] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0043] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0044] It should be particularly noted that any symbols and / or numbers in the specification that are not marked in the accompanying drawings are not drawing marks.

[0045] The optional embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0046] like Figure 1 and Figure 2 As shown, this specific implementation adopts the following technical solutions:

[0047] A distribution network optimization operation method based on GIS real-time monitoring, comprising:

[0048] The GIS is a geographic information system;

[0049] S1. Access the distribution network data of the area to be processed, perform preliminary filtering on the data, remove sensitive data, use data analysis and processing algorithms to analyze real-time data, and evaluate the operating status of the distribution network. Sensitive data includes confidential data, personnel identity information data, and virus data;

[0050] S2. Perform multiple sets of simulation operations based on the parameters provided by the learning analysis model, encrypt different data under different permission queries at corresponding levels, and issue an early warning through external warning devices when there is inconsistency between the permission and the query data level. The external warning devices include buzzers and warning lights.

[0051] S3. Query and call out all the received data, perform imaging processing on the specified data, and generate corresponding tables for comparison according to requirements during imaging;

[0052] S4. Monitor and process the real-time running data after starting each device, and collect the change data of the distribution network operation status through multiple sensors. The sensors include current sensors, power sensors, voltage sensors, vibration sensors and frequency sensors. The change data includes current, voltage, load and other parameters.

[0053] A distribution network optimization operation system based on GIS real-time monitoring, the distribution network optimization operation system comprises a GIS control module, a real-time monitoring module, a distribution network data access module and a data operation module, the output end of the distribution network data access module is communicatively connected to the input end of the data operation module, and the output end of the data operation module is communicatively connected to the input end of the GIS control module.

[0054] In this solution, the GIS control module includes a visualization unit, a storage management unit and a learning analysis model, and the output ends of the storage management unit and the learning analysis model are both communicatively connected to the input end of the visualization unit; the visualization unit is used to query and call out all the received data, and to perform imaging processing on the specified data. When imaging, corresponding tables can be generated according to needs for comparison operations; the storage management unit is used to store and manage the geographic spatial data of the distribution network locally and remotely, and set corresponding access permission folders. The staff with corresponding permissions can only access the folders with corresponding permissions to view the required geographic spatial data; the learning analysis model is used to manually set a learning direction, continuously fill in the learning goals to be achieved, conduct autonomous learning, and set thresholds. When the learning analysis model deviates from the set direction, the remote staff is reminded to make adjustments.

[0055] In the present solution, the real-time monitoring module includes a historical data monitoring unit, a real-time operation monitoring unit and a multi-level access verification unit. The multi-level access verification unit is connected to the real-time operation monitoring unit in a two-way communication manner, and the historical data monitoring unit is connected to the real-time operation monitoring unit in a two-way communication manner; the historical data monitoring unit is used to monitor the historical data stored locally, and when data loss or data ambiguity occurs, self-cut-off processing is performed to prevent affecting other modules and units. When a certain section of historical data is needed, the corresponding query instruction is input through the historical data monitoring unit to perform subsequent operations; the real-time operation monitoring unit is used to monitor and process the real-time operation data of the distribution network optimization operation system after startup, and collects the change data of the distribution network operation status through multiple sensors, including current, voltage, load and other parameters. When data loss or data ambiguity occurs, self-cut-off processing is performed to prevent affecting other modules and units; the multi-level access verification unit is used to receive the identity information authentication operation of the staff, thereby granting corresponding access rights.

[0056] In the present solution, the distribution network data access module includes a distribution network data access unit, an optimization resource control unit and other data access units, and the output ends of the distribution network data access unit and the other data access units are respectively communicatively connected to the input end of the optimization resource control unit; the distribution network data access unit is used to access the distribution network data of the required processing area, perform preliminary filtering and processing on the data, and propose sensitive data therein, and the sensitive data can be set with keywords and general content in advance; the optimization resource control unit is used to adopt data analysis and processing algorithms to analyze real-time data, evaluate the operating status of the distribution network, and thus optimize the operation of the distribution network; the other data access units are used to access data from other industries, fields and related data.

[0057] In the present scheme, the data operation module includes a simulation operation unit, a data encryption unit and a spatial data analysis unit. The output end of the spatial data analysis unit is communicatively connected to the input end of the simulation operation unit, and the data encryption unit is bidirectionally communicatively connected to the simulation operation unit and the spatial data analysis unit respectively; the simulation operation unit is used to perform multiple groups of simulation operation operations according to the parameters provided by the learning analysis model, observe the differences between the results of multiple groups of operations and the problems encountered in the simulation process, make corresponding records, sort the problems according to their importance, generate charts and corresponding generation dates, and facilitate manual management and query; the data encryption unit is used to encrypt different data under different authority queries at corresponding levels, and when the authority and query data levels are inconsistent, an external warning device is used to issue an early warning; the spatial data analysis unit is used to use optimization algorithms and models to provide optimized operation strategies for distribution networks.

[0058] Example

[0059] When GIS real-time monitoring is connected to distribution network optimization management:

[0060] S1. The staff will check the required equipment one by one. After checking that everything is correct, the distribution network optimization operation system will be started. The distribution network data access unit will access the distribution network data of the required processing area, perform preliminary filtering on the data, and propose the sensitive data therein. The keywords and general content of the sensitive data can be set in advance. Sensitive data include confidential data, personnel identity information data, and virus data. The optimization resource control unit uses data analysis and processing algorithms to analyze real-time data and evaluate the operating status of the distribution network, thereby optimizing the operation of the distribution network. Other data access units access data from other industries, fields and related data;

[0061] S2. The simulation operation unit performs multiple groups of simulation operation operations according to the parameters provided by the learning analysis model, observes the gaps between the results of the multiple groups of operations and the problems that occur in the simulation process, makes corresponding records, sorts the problems according to their importance, generates charts and corresponding generation dates, and facilitates manual management and query. The data encryption unit encrypts different data under different authority queries at corresponding levels. When the authority and query data levels are inconsistent, an external warning device is used to issue an early warning. The external warning device includes a buzzer and a warning light. The spatial data analysis unit is used to use optimization algorithms and models to provide an optimized operation strategy for the distribution network.

[0062] S3. The learning analysis model is used to manually set a learning direction, continuously fill in the learning goals to be achieved, conduct autonomous learning, and set thresholds. When the learning analysis model deviates from the set direction, it reminds remote staff to make adjustments. The visualization unit queries and calls out all the received data, and performs imaging processing on the specified data. When imaging, the corresponding table can be generated according to the needs for comparison operations. The storage management unit is used to store and manage the geographic spatial data of the distribution network locally and remotely, and set corresponding access permission folders. Staff with corresponding permissions can only access the folders with corresponding permissions to view the required geographic spatial data;

[0063] S4. The historical data monitoring unit monitors the historical data stored locally. When data loss or data ambiguity occurs, it performs self-cut-off processing to prevent affecting other modules and units. When a certain section of historical data is needed, the corresponding query instruction is input through the historical data monitoring unit to perform subsequent operations. The real-time operation monitoring unit monitors and processes the real-time operation data of the distribution network optimization operation system after startup. The change data of the distribution network operation status is collected through multiple sensors, including current, voltage, load and other parameters. The sensors include current sensors, power sensors, voltage sensors, vibration sensors and frequency sensors. When data loss or data ambiguity occurs, it performs self-cut-off processing to prevent affecting other modules and units. The multi-level access verification unit receives the identity information authentication operation of the staff, thereby granting corresponding access rights.

[0064] Specifically: In actual applications, there are multiple distribution network data access modules, which are respectively used in conjunction with the GIS control module, the real-time monitoring module and the data operation module. The multiple distribution network data access modules are respectively located in different geographical locations. The present invention constructs a complete distribution network optimization operation system by setting up the GIS control module, the real-time monitoring module, the distribution network data access module and the data operation module. In actual use, by accessing the distribution network data of the required processing area, the data is preliminarily filtered and processed, and the sensitive data therein is eliminated. The real-time data is analyzed using data analysis and processing algorithms to evaluate the operating status of the distribution network. According to the parameters provided by the learning analysis model, multiple groups of simulation operations are performed, and different data under different authority queries are encrypted at corresponding levels. When the authority is inconsistent with the query data level, an external warning device is used to issue an early warning, and all the received data is checked. Query and call out operations, image the specified data, generate corresponding tables for comparison operations according to needs during imaging, monitor and process the real-time running data after starting each device, collect change data of the distribution network operation status through multiple sensors, manage, visualize and store the distribution network optimization data and corresponding analysis results, which is helpful to realize the optimization management of the distribution network through the enterprise intranet cloud management and control, improve the intelligence level of the distribution network optimization management, and facilitate the staff to query one link at a time, shorten the overall operation cycle, and manage the corresponding permission data by setting corresponding permission queries, so as to realize overall encryption and reduce data leakage. By reasonably allocating power resources to the distribution network, energy consumption and operating costs are reduced. The spatial data management of the distribution network is realized through GIS technology, and a visual display of geographic information is provided to help the work quickly identify problem areas. The enterprise intranet is the local area network used within the enterprise.

[0065] Those skilled in the art will appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0066] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices, equipment and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0067] In the several embodiments provided in the present application, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or units can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or equipment, which can be electrical, mechanical or other forms.

[0068] The modules for GIS control, real-time monitoring, power distribution network data access and data operation may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0069] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0070] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage media include: U disk, mobile hard disk, read-only storage server, random access storage server, disk or optical disk, and other media that can store program instructions.

[0071] In addition, it should be noted that the combination of the various technical features in this case is not limited to the combination described in the claims of this case or the combination described in the specific embodiments. All technical features described in this case can be freely combined or combined in any way unless there is a contradiction between them.

[0072] It should be noted that the above examples are only specific embodiments of the present invention, and the present invention is obviously not limited to the above examples, and there are many similar variations. All variations directly derived or associated from the contents disclosed by the technicians in this field should fall within the protection scope of the present invention.

[0073] The above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing the operation of a power distribution network based on GIS real-time monitoring, characterized in that: The operation method comprises: S1. Access the distribution network data of the area to be processed, perform preliminary filtering on the data, remove sensitive data, use data analysis and processing algorithms to analyze real-time data, and evaluate the operating status of the distribution network; S2. Perform multiple sets of simulation operations based on the parameters provided by the learning analysis model, encrypt different data under different permission queries at corresponding levels, and issue an early warning through an external warning device when there is a discrepancy between the permission and the query data level; S3. Query and call out all the received data, perform imaging processing on the specified data, and generate corresponding tables for comparison according to requirements during imaging; S4. Monitor and process the real-time operating data after starting each device, and collect the change data of the distribution network operating status through multiple sensors.

2. The method for optimizing the operation of a power distribution network based on GIS real-time monitoring according to claim 1, characterized in that: The sensitive data in step S1 includes confidential data, personnel identity information data, and virus data.

3. The method for optimizing the operation of a power distribution network based on GIS real-time monitoring according to claim 1 is characterized in that: The external warning device in step S2 includes a buzzer and a warning light.

4. The method for optimizing the operation of a power distribution network based on GIS real-time monitoring according to claim 1 is characterized in that: The sensors in step S4 include a current sensor, a power sensor, a voltage sensor, a vibration sensor and a frequency sensor.

5. The method for optimizing the operation of a power distribution network based on GIS real-time monitoring according to claim 1 is characterized in that: The changed data in step S4 include parameters such as current, voltage, and load.

6. A distribution network optimization operation system based on GIS real-time monitoring, used to implement a distribution network optimization operation method based on GIS real-time monitoring as claimed in any one of claims 1 to 5, characterized in that: The distribution network optimization operation system includes a GIS control module, a real-time monitoring module, a distribution network data access module and a data operation module. The output end of the distribution network data access module is communicatively connected to the input end of the data operation module, and the output end of the data operation module is communicatively connected to the input end of the GIS control module.

7. The power distribution network optimization operation system based on GIS real-time monitoring according to claim 6 is characterized in that: The GIS control module includes a visualization unit, a storage management unit and a learning analysis model, and the output ends of the storage management unit and the learning analysis model are both communicatively connected to the input end of the visualization unit; The visualization unit is used to query and call out all the received data; The storage management unit is used to store and manage the geospatial data of the power distribution network locally and remotely respectively; The learning analysis model is used to manually set a learning direction and generate a corresponding model.

8. The power distribution network optimization operation system based on GIS real-time monitoring according to claim 6 is characterized in that: The real-time monitoring module includes a historical data monitoring unit, a real-time operation monitoring unit and a multi-level access verification unit, the multi-level access verification unit is bidirectionally connected to the real-time operation monitoring unit, and the historical data monitoring unit is bidirectionally connected to the real-time operation monitoring unit; The historical data monitoring unit is used to monitor the historical data stored locally; The real-time operation monitoring unit is used to monitor and process the real-time operation data of the power distribution network optimization operation system after startup, and collect the change data of the power distribution network operation status through multiple sensors; The multi-level access verification unit is used to receive the identity information authentication operation of the staff.

9. The power distribution network optimization operation system based on GIS real-time monitoring according to claim 6 is characterized in that: The power distribution network data access module includes a power distribution network data access unit, an optimization resource control unit and other data access units, and the output ends of the power distribution network data access unit and other data access units are respectively communicatively connected to the input end of the optimization resource control unit; The power distribution network data access unit is used to access the power distribution network data of the required processing area, perform preliminary filtering on the data, and remove sensitive data therein; The resource optimization control unit is used to analyze the real-time data using data analysis and processing algorithms; The other data access unit is used to access data from other industries, fields and related data.

10. The power distribution network optimization operation system based on GIS real-time monitoring according to claim 6 is characterized in that: The data operation module includes a simulation operation unit, a data encryption unit and a spatial data analysis unit, wherein the output end of the spatial data analysis unit is communicatively connected to the input end of the simulation operation unit, and the data encryption unit is bidirectionally communicatively connected to the simulation operation unit and the spatial data analysis unit respectively; The simulation operation unit is used to perform multiple groups of simulation operation operations according to the parameters provided by the learning analysis model; The data encryption unit is used to encrypt different data under different authority queries at corresponding levels; The spatial data analysis unit is used to utilize optimization algorithms and models.

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