Distributed multi-source power grid full-spatio-temporal information model system

Abstract

The invention discloses a distributed multi-source power grid full-time-space information model system, and relates to the technical field of power grid data, the distributed multi-source power grid full-time-space information model system comprises a data acquisition module, the transmission end of the data acquisition module is connected with a first data storage module, and the transmission end of the first data storage module is connected with a data correction module; the output end of the data acquisition module is connected with a data cleaning module, the first data storage module and the data cleaning module are connected in parallel, and the output end of the data cleaning module is connected with a data verification module. According to the method, the data accuracy is ensured through data correction and verification, the accuracy and stability of a power grid model are kept through test comparison and model correction, and finally efficient and stable operation of the system is guaranteed through data arrangement and formulation and implementation of an optimization scheme.

Description

Technical Field

[0001] The present invention relates to the field of power grid data technology, and in particular to a distributed multi-source power grid full-time and space information model system. Background Art

[0002] The distributed multi-source power grid full-time and space information model system is an information model system used to describe and analyze distributed multi-source power grids. It can model and analyze various distributed power sources, energy storage equipment, loads, etc. in the power grid to achieve comprehensive monitoring, control and management of the power grid. By establishing a distributed multi-source power grid full-time and space information model system, comprehensive monitoring and management of the power grid can be achieved, the operating efficiency and reliability of the power grid can be improved, and strong support can be provided for the development of smart grids.

[0003] The existing distributed multi-source power grid full-time and space information model system will clean the data during operation, but recognition errors are likely to occur during the cleaning process, thereby cleaning out some of the required data, which will affect the subsequent system work and the data processing effect of the system work. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a distributed multi-source power grid full-time and space information model system, which can solve the problems mentioned in the background technology.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In the first aspect, the present invention provides a distributed multi-source power grid full-time and space information model system, which includes a data acquisition module, a transmission end of which is connected to a first data storage module, and the transmission end of the first data storage module is connected to a data correction module; the output end of the data acquisition module is connected to a data cleaning module, and the first data storage module and the data cleaning module are connected in parallel, and the output end of the data cleaning module is connected to a data verification module.

[0009] As a preferred solution of the distributed multi-source power grid full-time and space information model system described in the present invention, wherein: the output end of the data verification module is connected to the data conversion module, and the output end of the data conversion module is connected to the second data storage module; the output end of the data conversion module is connected to the power grid model, and the power grid model and the second data storage module are connected in parallel; the input end of the power grid model is connected to the test module, and the test module and the data conversion module are connected in parallel.

[0010] As a preferred solution of the distributed multi-source power grid full-time and space information model system described in the present invention, wherein: the input end of the power grid model is connected to an operation optimization module, and the operation optimization module and the test module are connected in parallel; the output end of the power grid model is connected to a visualization monitoring module, and the data conversion module, the power grid model and the visualization monitoring module are connected in series.

[0011] As a preferred solution of the distributed multi-source power grid full-time and space information model system described in the present invention, the test module includes a test data storage module, a test data reading module and a test result comparison module, and the output end of the test data storage module is connected to the test data reading module, and the output end of the test data reading module is connected to the test result comparison module.

[0012] As a preferred solution of the distributed multi-source power grid full-time and space information model system described in the present invention, the test module also includes a model correction module and an alarm module, and the output end of the test result comparison module is connected to the model correction module and the alarm module, and the model correction module and the alarm module are connected in parallel.

[0013] As a preferred solution of the distributed multi-source power grid full-time and space information model system described in the present invention, the operation optimization module includes a database, a data aggregation module and a data sorting module, and the output end of the database is connected to the data aggregation module, and the output end of the data aggregation module is connected to the data sorting module.

[0014] As a preferred solution of the distributed multi-source power grid full-time and space information model system described in the present invention, the operation optimization module also includes scheme formulation and model optimization, and the output end of the data sorting module is connected to the scheme formulation, and the output end of the scheme formulation is connected to the model optimization.

[0015] In the second aspect, the present invention provides a distributed multi-source power grid full-time and space information model method, which includes: a data acquisition module collects real-time data from the power grid, and transmits the real-time data to a first data storage module and a data cleaning module in parallel; the data cleaning module performs outlier detection and missing value processing on the real-time data, and the cleaned data is transmitted to a data verification module, while the data correction module verifies the real-time data based on the historical data in the first data storage module, and the verified data is also transmitted to the data verification module; the data verification module compares and verifies the data from two sources, and after ensuring the accuracy of the data, transmits the verified data to the data conversion module, the data conversion module converts the data into the format required by the power grid model, and stores it in the second data storage module, and transmits the converted data to the power grid model for further processing.

[0016] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, the steps of implementing a distributed multi-source power grid full-time and space information model system are implemented.

[0017] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, the steps of implementing a distributed multi-source power grid full-time and space information model system are implemented.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: first, the present invention extracts data from the data acquisition module and the first data storage module through the data correction module, thereby relying on the historical data in the first data storage module to verify the data detected by the data acquisition module, thereby ensuring the accuracy of the data output by the data acquisition module, and then transmitting the verified data to the data verification module for comparison and verification with the data cleaned by the data cleaning module, thereby ensuring that important content in the data cleaned by the data cleaning module is not lost.

[0019] Secondly, the present invention extracts data from the test data storage module through the test data reading module, and transmits the data to the test result comparison module after the data is processed by the power grid model. Then, the data detection result in the test data storage module is transmitted to the test result comparison module through the test data reading module, so that the test result comparison module compares the result of the power grid model with the original result. If there is a deviation between the two results, an alarm will be issued through the alarm module to enable the staff to discover the problem. At the same time, the model correction module will also correct the power grid model, so that the power grid model is restored to ensure the normal operation of the power grid model.

[0020] Finally, the present invention organizes the summarized data through the data sorting module, and then formulates an optimization plan for the power grid model according to the sorted data through plan formulation, and transmits the optimization plan to the model optimization. After the staff checks the optimization plan, the power grid model is optimized through model optimization to ensure the stable operation of the entire system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 It is a flow chart of the system of the present invention;

[0023] Figure 2 This is a system flow chart of the test module of the present invention;

[0024] Figure 3 A system flow chart of the operation optimization module of the present invention. DETAILED DESCRIPTION

[0025] In order to make the above-mentioned purposes, features and advantages of the present invention more understandable, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0026] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0027] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0028] Example 1, reference Figure 1-Figure 3 , which is the first embodiment of the present invention, and provides a distributed multi-source power grid full-time and space information model system, including:

[0029] The data acquisition module has a delivery end connected to the first data storage module, and the delivery end of the first data storage module is connected to the data correction module. The output end of the data acquisition module is connected to the data cleaning module, and the first data storage module and the data cleaning module are connected in parallel, and the output end of the data cleaning module is connected to the data verification module.

[0030] This technology performs data cleaning, specifically optimizing the load and power generation data in the power data:

[0031] Calculate the first quartile (Q1) and the third quartile (Q3):

[0032] Q1=P 25 (X),Q3=P 75 (X);

[0033] Calculate the interquartile range (IQR):

[0034] IQR=Q3-Q1

[0035] Set bounds on outliers:

[0036] LowerBound = Q1-1.5×IQR;

[0037] Upper Bound = Q3 + 1.5 × IQR;

[0038] Detect and handle outliers:

[0039] X cleaned={XNaN ifX∈[LowerBound,UpperBound];

[0040] otherwise

[0041]

[0042] Optimize the above missing values;

[0043] Calculate the mean:

[0044]

[0045] Fill missing values:

[0046]

[0047] Rationality of outlier detection in the present invention:

[0048] a. Using quartiles (Q1 and Q3) and IQR methods

[0049] Robustness: Quartiles are not affected by extreme values ​​and can effectively reflect the center position and dispersion of the data. Compared with the mean and standard deviation, the IQR method is more robust to outliers.

[0050] Adaptability: The IQR method can be applied to different data sets, especially when the data distribution deviates from the normal distribution. By setting the Lower Bound and Upper Bound, extreme values ​​can be effectively identified and processed.

[0051] b. Set limits on outliers

[0052] Scientificity: Generally speaking, 1.5 times the IQR is widely considered to be a reasonable threshold for identifying outliers, which is consistent with statistical principles. This choice is based on empirical rules and can cover the variation range of most data to a certain extent.

[0053] Clarity: Through clear boundaries (Lower Bound and Upper Bound), it is clear which data points are considered abnormal, which facilitates subsequent processing.

[0054] c. Detect and handle outliers

[0055] Simplicity: Using NaN to replace outliers makes the data cleaning process clear and these outliers can be easily ignored in subsequent analysis.

[0056] Lossless: Replacing outliers with NaN instead of directly deleting them can preserve the structure and length of the dataset, providing more comprehensive information for subsequent analysis.

[0057] Rationality of missing value processing in this invention

[0058] a. Calculate the mean

[0059] Easy to use: Calculating the mean is a widely used filling method, especially when the proportion of missing values ​​is small, which can effectively maintain the overall characteristics of the data set.

[0060] Maintain data consistency: Mean filling ensures that the filled data remains within the general range of the data, avoiding the introduction of new biases.

[0061] b. Fill in missing values

[0062] Adaptability: Mean imputation is suitable for most cases, especially when the data is close to a normal distribution and the mean can represent the central tendency of the data set.

[0063] Computational efficiency: Calculating the mean is relatively simple, especially when dealing with large-scale data, it is efficient and easy to implement quickly.

[0064] That is, the present invention has a good effect on data integrity. The above algorithm improves the integrity and validity of data through outlier detection and missing value processing, laying a solid foundation for subsequent data analysis and modeling. It has a good theoretical basis and practical verification, and is suitable for the characteristics of power data.

[0065] The data correction module is used to extract data from the data acquisition module and the first data storage module, thereby verifying the data detected by the data acquisition module with the historical data in the first data storage module to ensure the accuracy of the data output by the data acquisition module. The verified data is then transmitted to the data verification module for comparison and verification with the data cleaned by the data cleaning module to ensure that important content in the data cleaned by the data cleaning module is not lost.

[0066] like Figure 1 As shown, the output end of the data verification module is connected to the data conversion module, and the output end of the data conversion module is connected to the second data storage module, the output end of the data conversion module is connected to the power grid model, and the power grid model and the second data storage module are connected in parallel, the input end of the power grid model is connected to the test module, and the test module and the data conversion module are connected in parallel, the input end of the power grid model is connected to the operation optimization module, and the operation optimization module and the test module are connected in parallel, the output end of the power grid model is connected to the visualization monitoring module, and the data conversion module, the power grid model and the visualization monitoring module are connected in series.

[0067] The data verification module compares and verifies the data corrected by the data correction module with the data cleaned by the data cleaning module to ensure that important content in the data cleaned by the data cleaning module is not lost. The data conversion module converts the cleaned data into data that is convenient for the power grid model to process. The second data storage module will store and retrieve the converted data. The test module can test the power grid model to ensure the normal operation of the power grid model. The results of the power grid model processing will be displayed through the visual monitoring module. The operation optimization module can optimize the power grid model based on big data.

[0068] like Figure 2 As shown, the test module includes a test data storage module, a test data reading module and a test result comparison module, and the output end of the test data storage module is connected to the test data reading module, and the output end of the test data reading module is connected to the test result comparison module. The test module also includes a model correction module and an alarm module, and the output end of the test result comparison module is connected to the model correction module and the alarm module, and the model correction module and the alarm module are connected in parallel.

[0069] The test data reading module extracts data from the test data storage module, and after the data is processed by the power grid model, it is transmitted to the test result comparison module. Then, the test data reading module transmits the data detection result in the test data storage module to the test result comparison module, so that the test result comparison module compares the result of the power grid model with the original result. If there is a deviation between the two results, an alarm will be issued through the alarm module to enable the staff to discover the problem. At the same time, the model correction module will also correct the power grid model to restore the power grid model and ensure the normal operation of the power grid model.

[0070] like Figure 3 As shown, the operation optimization module includes a database, a data aggregation module and a data sorting module, and the output end of the database is connected to the data aggregation module, and the output end of the data aggregation module is connected to the data sorting module. The operation optimization module also includes program formulation and model optimization, and the output end of the data sorting module is connected to program formulation, and the output end of the program formulation is connected to model optimization.

[0071] The summarized data is sorted through the data sorting module, and then an optimization plan for the power grid model is formulated according to the sorted data, and the optimization plan is transmitted to the model optimization. After the staff checks the optimization plan, the power grid model is optimized through model optimization to ensure the stable operation of the entire system.

[0072] Working principle: First, the data acquisition module is used to detect the data input and output of various distributed power sources, energy storage devices, loads, etc. in the power grid, and the electrical quantity, non-electrical quantity, equipment status and other data in the power grid are detected, so as to realize the detection of the full-time and space information of the equipment in the power grid. The data detected by the data acquisition module is transmitted to the first data storage module for storage. At the same time, the data of the data acquisition module will also be transmitted to the data cleaning module for cleaning, so as to clean up the interference elements in the data, thereby improving the quality of the data and enabling the system to better utilize the data.

[0073] Then, the data in the data acquisition module and the first data storage module are extracted through the data correction module, so as to verify the data detected by the data acquisition module with the historical data in the first data storage module to ensure the accuracy of the data output by the data acquisition module. The verified data is then transmitted to the data verification module for comparison and verification with the data cleaned by the data cleaning module to ensure that important content in the data cleaned by the data cleaning module is not lost. If it is found that useful data is lost in the data cleaned by the data cleaning module, it will be fed back to the data cleaning module to make the data cleaning module work again and clean the data again.

[0074] After the data verification module completes the data verification of the data cleaning module, the cleaned data is transmitted to the data conversion module for data conversion, so that the converted data is more convenient for the processing of the power grid model, thereby facilitating the operation of the entire system. At the same time, the data converted by the data conversion module will also be transmitted to the second data storage module for storage, so that the staff can extract the data in the second data storage module in subsequent inspections and check the operation of the system.

[0075] The power grid model processes the data from the data conversion module and then transmits the processing results to the visual monitoring module for display, making it easier for staff to observe the operation of the power grid.

[0076] After the power grid model has been running for a period of time, the data in the test data storage module is extracted through the test data reading module and then transmitted to the power grid model. After the data is processed by the power grid model, it is transmitted to the test result comparison module. Then, the data detection result in the test data storage module is transmitted to the test result comparison module through the test data reading module, so that the test result comparison module compares the result of the power grid model with the original result. If the two results are consistent, it means that the power grid model is operating normally. If there is a deviation between the two results, an alarm will be issued through the alarm module to enable the staff to discover the problem. At the same time, the model correction module will also correct the power grid model to restore the power grid model, so as to facilitate the long-term correct operation of the system.

[0077] When the power grid model is operating normally, the data detected by the data acquisition module will be transmitted to the data aggregation module. At the same time, the data aggregation module extracts historical data in the database and Internet data, thereby aggregating various data together, and then organizes the aggregated data through the data collation module, so as to formulate an optimization plan for the power grid model according to the organized data through plan formulation, and transmit the optimization plan to the model optimization. After the staff checks the optimization plan, they will optimize the power grid model through model optimization to ensure the stable operation of the entire system.

[0078] Furthermore, this embodiment also provides a distributed multi-source power grid full-time and space information model method, including:

[0079] S1: The data acquisition module collects real-time data from the power grid and transmits the real-time data to the first data storage module and the data cleaning module in parallel;

[0080] S2: The data cleaning module performs outlier detection and missing value processing on the real-time data. The cleaned data is transmitted to the data verification module. Meanwhile, the data correction module verifies the real-time data based on the historical data in the first data storage module. The verified data is also transmitted to the data verification module.

[0081] S3: The data verification module compares and verifies the data from the two sources. After ensuring the accuracy of the data, the verified data is transmitted to the data conversion module. The data conversion module converts the data into the format required by the power grid model and stores it in the second data storage module. At the same time, the converted data is transmitted to the power grid model for further processing.

[0082] This embodiment also provides a computer device, which may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 2 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a distributed multi-source power grid full-time and space information model system is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0083] This embodiment further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0084] Embodiment 2 is the second embodiment of the present invention. This embodiment provides a distributed multi-source power grid full-time and space information model system. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0085] In order to verify the effectiveness and superiority of the present invention, a series of theoretical experiments were designed, covering multiple dimensions such as data processing accuracy, data processing speed, and model stability. First, in terms of data processing accuracy, by constructing a simulated data set, which includes a large number of outliers and missing values, the data cleaning method of the present invention is compared with the existing technical solution, and the accuracy changes of the two solutions before and after data cleaning are measured. Secondly, in terms of data processing speed, the above-mentioned simulated data set is also used to record the time required for the present invention and the existing technical solution to process data sets of the same scale, so as to evaluate the efficiency advantage of the present invention. Finally, in terms of model stability, through long-term running tests, the performance of the present invention and the existing technical solution under different load conditions is collected, including but not limited to key indicators such as model prediction error and system response time, so as to verify the stability and reliability of the present invention in practical applications.

[0086] Table 1: Comparison of data processing accuracy

[0087]

[0088]

[0089] Table 1 shows the comparison results of data processing accuracy. Both the present invention and the prior art solution can improve the accuracy of data after data cleaning. However, the accuracy of the present invention after data cleaning reaches 95%, which is 10 percentage points higher than the original 85%, while the prior art solution only improves by 5 percentage points. This shows that the present invention has obvious advantages in improving data quality, and can more effectively handle outliers and missing values ​​to ensure data accuracy.

[0090] Table 2: Data processing speed comparison

[0091] method Average processing time (seconds) Prior art 30 The present invention 20

[0092] Table 2 shows the comparison of data processing speed. The average processing time of the present invention is 20 seconds, while the prior art solution requires 30 seconds. This means that the present invention not only performs well in improving data processing accuracy, but also has significant advantages in processing speed. This efficiency improvement is crucial for practical applications, especially in scenarios where large amounts of data need to be processed in real time, which can greatly reduce waiting time and resource consumption and improve the overall performance of the system.

[0093] Table 3: Comparison of model stability

[0094] method Average prediction error (%) System response time (ms) Prior art 3.5 100 The present invention 2.5 70

[0095] The data in Table 3 further confirm the superiority of the present invention in terms of model stability. In terms of model prediction error, the average prediction error of the present invention is 2.5%, which is lower than the 3.5% of the prior art solution; in terms of system response time, the performance of the present invention is also better than the prior art, with an average response time of 70 milliseconds, while the prior art solution is 100 milliseconds. These data fully demonstrate the effectiveness of the present invention in improving model prediction accuracy and accelerating system response speed, and reflect its stability and efficiency in practical applications.

[0096] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

[0097] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0098] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0099] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0100] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0101] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0102] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A distributed multi-source power grid full-time and space information model system, characterized by: A data acquisition module, a delivery end of which is connected to a first data storage module, and a delivery end of the first data storage module is connected to a data correction module; The output end of the data acquisition module is connected to a data cleaning module, and the first data storage module and the data cleaning module are connected in parallel. The output end of the data cleaning module is connected to a data verification module.

2. The distributed multi-source power grid full-time and space information model system according to claim 1, characterized in that: The output end of the data verification module is connected to the data conversion module, and the output end of the data conversion module is connected to the second data storage module; The output end of the data conversion module is connected to a power grid model, and the power grid model is connected in parallel with the second data storage module; The input end of the power grid model is connected to a test module, and the test module and the data conversion module are connected in parallel.

3. The distributed multi-source power grid full-time and space information model system according to claim 2, characterized in that: The input end of the power grid model is connected to an operation optimization module, and the operation optimization module and the test module are connected in parallel; The output end of the power grid model is connected to a visual monitoring module, and the data conversion module, the power grid model and the visual monitoring module are connected in series.

4. The distributed multi-source power grid full-time and space information model system according to claim 3, characterized in that: The test module includes a test data storage module, a test data reading module and a test result comparison module, and the output end of the test data storage module is connected to the test data reading module, and the output end of the test data reading module is connected to the test result comparison module.

5. The distributed multi-source power grid full-time and space information model system according to claim 4, characterized in that: The test module also includes a model correction module and an alarm module, and the output end of the test result comparison module is connected to the model correction module and the alarm module, and the model correction module and the alarm module are connected in parallel.

6. The distributed multi-source power grid full-time and space information model system according to claim 5, characterized in that: The operation optimization module includes a database, a data summary module and a data sorting module, and the output end of the database is connected to the data summary module, and the output end of the data summary module is connected to the data sorting module.

7. The distributed multi-source power grid full-time and space information model system according to claim 6, characterized in that: The operation optimization module also includes program formulation and model optimization, and the output end of the data sorting module is connected to the program formulation, and the output end of the program formulation is connected to the model optimization.

8. A distributed multi-source power grid full-time and space information model method, based on the distributed multi-source power grid full-time and space information model system according to any one of claims 1 to 7, characterized in that: include, The data acquisition module collects real-time data from the power grid, and transmits the real-time data to the first data storage module and the data cleaning module in parallel; The data cleaning module performs outlier detection and missing value processing on the real-time data, and the cleaned data is transmitted to the data verification module. Meanwhile, the data correction module verifies the real-time data based on the historical data in the first data storage module, and the verified data is also transmitted to the data verification module. The data verification module compares and verifies the data from the two sources. After ensuring the accuracy of the data, the verified data is transmitted to the data conversion module. The data conversion module converts the data into the format required by the power grid model and stores it in the second data storage module. At the same time, the converted data is transmitted to the power grid model for further processing.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the distributed multi-source power grid full-time and space information model system according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the distributed multi-source power grid full-time and space information model system according to any one of claims 1 to 7 are implemented.

Images