Topology real-time reconstruction platform for distributed multi-source power grid full space-time information model

Abstract

The invention discloses a distributed multi-source power grid full-time-space information model topology real-time reconstruction platform, and relates to the technical field of power grid data, and the platform comprises a data collection module, the output end of the data collection module is connected with a data classification module, and the output end of the data classification module is connected with a data cleaning module; the output end of the data cleaning module is connected with a data verification module, the output end of the data verification module is connected with a data integration module, the data classification module and the data integration module are connected in parallel, and the data acquisition module and the data verification module are connected in parallel. Through the data classification and cleaning module, the data processing quality and speed are improved; the data transmission efficiency is optimized through a transmission speed detection and network speed control module; data are regularly extracted for trend analysis, real-time model reconstruction is realized in combination with a topological optimization module, and efficient operation and response capability of the system are ensured.

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 topology real-time reconstruction platform. Background Art

[0002] The distributed multi-source power grid full-time and space information model topology real-time reconstruction platform is a technical platform for power grid systems. It can realize the real-time topology reconstruction of the full-time and space information model of the distributed multi-source power grid. By using the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform, power grid operators can better manage and monitor the operation of the power grid, improve the efficiency and reliability of the power grid, optimize the allocation of power resources, and ensure the safe and stable operation of the power system. The specific implementation methods and functions may vary depending on different application scenarios and requirements.

[0003] The existing distributed multi-source power grid full-time and space information model topology real-time reconstruction platform processes a large amount of data during operation, which may lead to data loss or missing data classification, thereby preventing the system from having problems due to insufficient data during processing. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the present invention provides a distributed multi-source power grid full-time and space information model topology real-time reconstruction platform, which can solve the problems mentioned in the background technology.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a distributed multi-source power grid full-time and space information model topology real-time reconstruction platform, comprising: a data acquisition module, the output end of the data acquisition module is connected to a data classification module, and the output end of the data classification module is connected to a data cleaning module, the output end of the data cleaning module is connected to a data verification module, and the output end of the data verification module is connected to a data integration module, the data classification module and the data integration module are connected in parallel, and the data acquisition module and the data verification module are connected in parallel.

[0007] As a preferred solution of the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform described in the present invention, wherein: the output end of the data integration module is connected to the first topology model, and the data verification module, the data integration module and the first topology model are connected in series; the output end of the data integration module is connected to the real-time optimization module, and the real-time optimization module and the first topology model are connected in parallel; the output end of the first topology model is connected to the visualization display module, and the visualization display module and the real-time optimization module are connected in parallel; the first topology model is connected to the real-time optimization module input and output, and the data integration module and the real-time optimization module are connected in parallel.

[0008] As an optimal solution of the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform described in the present invention, wherein: the visualization display module includes a transmission module, a transmission speed detection module and a network speed control module, and the output end of the transmission module is connected to the transmission speed detection module, and the output end of the transmission speed detection module is connected to the network speed control module.

[0009] As a preferred solution of the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform described in the present invention, wherein: the visualization display module also includes a display module and an identity authentication module, and the output end of the transmission module is connected to the display module, the display module and the transmission speed detection module are connected in parallel, and the input end of the display module is connected to the identity authentication module, and the transmission module and the identity authentication module are connected in parallel.

[0010] As an optimal solution of the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform described in the present invention, wherein: the real-time optimization module includes a data storage module, a data extraction module and a trend calculation module, and the output end of the data storage module is connected to the data extraction module, and the output end of the data extraction module is connected to the trend calculation module.

[0011] As a preferred solution of the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform described in the present invention, wherein: the real-time optimization module also includes a topology optimization module and a second topology model, and the output end of the trend calculation module is connected to the topology optimization module, and the output end of the topology optimization module is connected to the second topology model.

[0012] As a preferred solution of the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform described in the present invention, wherein: the real-time optimization module also includes a result verification module and a model replacement module, and the output end of the second topology model is connected to the result verification module, and the output end of the result verification module is connected to the model replacement module; in the case of power data, the data information obtained by sensors, monitoring equipment and other real-time data sources is aggregated, and multiple data streams are merged to reduce the data volume and processing complexity.

[0013] To further solve the above technical problems, the present invention provides the following technical solutions: a method for real-time reconstruction of the topology of a distributed multi-source power grid full-time and spatiotemporal information model, comprising: acquiring data of the multi-source power grid, the data of the multi-source power grid including power grid operation status data, environmental data and user demand data; based on the data of the multi-source power grid, constructing a full-time and spatiotemporal information model of the power grid using distributed computing resources to form an initial power grid topology structure; based on the initial power grid topology, dynamically adjusting the topology of the power grid by real-time monitoring and analyzing changes in the power grid operation status to reflect the most realistic current operation status of the power grid.

[0014] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform as described above are implemented.

[0015] 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 topology real-time reconstruction platform as described above are implemented.

[0016] Beneficial effects of the present invention: First, the present invention classifies the data collected by the data acquisition module through the data classification module, so that the collected data can be divided into different parts according to its content, and then the data cleaning module cleans the divided data. The classification and cleaning method is convenient for the system to carry out targeted data processing, which can make the data cleaning effect better. At the same time, the data is classified and different types of data are cleaned synchronously, which can increase the data processing speed of the device. Secondly, during the transmission process of the transmission module, the present invention will detect the data transmission speed of the transmission module through the transmission speed detection module, and then control the state of the network through the network speed control module. If the speed detected by the transmission speed detection module is slow, the system will regulate the entire internal network and give priority to the use of this system. If the transmission speed is still very slow when the entire internal network is used, the external network will be used to work together for transmission, so as to give priority to ensuring the data transmission speed in the system, thereby ensuring the transmission speed of the device and increasing the transmission effect of the device. Finally, after working for a period of time, the present invention will extract the data generated in this time period from the data storage module through the data extraction module, and then transmit the data to the trend calculation module for deduction, and calculate the subsequent data situation according to the data change trend, and then formulate an optimization plan according to the situation calculated by the trend calculation module through the topology optimization module, and optimize the first topology model according to the optimization plan to form a second topology model, thereby realizing the real-time model reconstruction function. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 This is a system flow chart of a distributed multi-source power grid full-time and space information model topology real-time reconstruction platform proposed by the present invention;

[0019] Figure 2 A system flow chart of a visualization display module in a distributed multi-source power grid full-time and space information model topology real-time reconstruction platform proposed by the present invention;

[0020] Figure 3 The present invention is a system flow chart of a real-time optimization module in a distributed multi-source power grid full-time and space information model topology real-time reconstruction platform. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, 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 the embodiments. 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.

[0022] 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.

[0023] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides a distributed multi-source power grid full-time and space information model topology real-time reconstruction platform.

[0024] Reference Figure 1 The present invention provides a technical solution: comprising a data acquisition module, wherein the output end of the data acquisition module is connected to a data classification module, and the output end of the data classification module is connected to a data cleaning module, the output end of the data cleaning module is connected to a data verification module, and the output end of the data verification module is connected to a data integration module, the data classification module and the data integration module are connected in parallel, and the data acquisition module and the data verification module are connected in parallel;

[0025] The data collected by the data acquisition module is classified through the data classification module, so that the collected data can be divided into different parts according to its content, and then the divided data is cleaned by the data cleaning module. The classification and cleaning method is convenient for the system to carry out targeted data processing, which can make the data cleaning effect better. At the same time, the data can be classified and different types of data can be cleaned synchronously, which can increase the data processing speed of the equipment.

[0026] like Figure 1 As shown, the output end of the data integration module is connected to the first topology model, and the data verification module, the data integration module and the first topology model are connected in series, the output end of the data integration module is connected to the real-time optimization module, and the real-time optimization module and the first topology model are connected in parallel, the output end of the first topology model is connected to the visualization display module, and the visualization display module and the real-time optimization module are connected in parallel, the first topology model is connected to the real-time optimization module input and output, and the data integration module and the real-time optimization module are connected in parallel.

[0027] like Figure 2 As shown, the visualization display module includes a transmission module, a transmission speed detection module and a network speed control module, and the output end of the transmission module is connected to the transmission speed detection module, and the output end of the transmission speed detection module is connected to the network speed control module. The visualization display module also includes a display module and an identity authentication module, and the output end of the transmission module is connected to the display module, the display module and the transmission speed detection module are connected in parallel, and the input end of the display module is connected to the identity authentication module, and the transmission module and the identity authentication module are connected in parallel.

[0028] During the transmission process of the transmission module, the data transmission speed of the transmission module will be detected by the transmission speed detection module, and then the network status will be controlled by the network speed control module. If the speed detected by the transmission speed detection module is slow, the system will regulate the entire internal network and give priority to the use of this system. If the transmission speed is still very slow when the entire internal network is used, the external network will be used to work together for transmission, so as to give priority to ensuring the data transmission speed in the system, thereby ensuring the transmission speed of the equipment and increasing the transmission effect of the equipment.

[0029] like Figure 3As shown, the real-time optimization module includes a data storage module, a data extraction module and a trend calculation module, and the output end of the data storage module is connected to the data extraction module, and the output end of the data extraction module is connected to the trend calculation module. The real-time optimization module also includes a topology optimization module and a second topology model, and the output end of the trend calculation module is connected to the topology optimization module, and the output end of the topology optimization module is connected to the second topology model. The real-time optimization module also includes a result verification module and a model replacement module, and the output end of the second topology model is connected to the result verification module, and the output end of the result verification module 806 is connected to the model replacement module.

[0030] In the case of power data, data information obtained from sensors, monitoring equipment and other real-time data sources is aggregated to merge multiple data streams to reduce data volume and processing complexity;

[0031] By setting a window size W and a sliding step size S, the aggregate value within the window can be calculated;

[0032] Window sum:

[0033]

[0034] Window average:

[0035]

[0036] Among them, X i is the data value at time point i; S TOTAL (t) is the window sum, the sum of all data values ​​in the window at time point t; S AVG (t) is the window mean, the average of all data values ​​in the window at time point t.

[0037] Sliding window aggregation can be updated in real time and is suitable for processing dynamically changing data streams. At each time step, the algorithm only needs to consider the data within the window, so it can quickly respond to data changes and provide instant analysis results. For power systems, this can quickly reflect the real-time status of parameters such as current and voltage, making it easier to make timely decisions.

[0038] The computational complexity of sliding window aggregation is relatively small, especially when incremental updates are used, so the aggregation results can be updated efficiently. For example, when new data arrives, only the new value needs to be added to the aggregation and the expired value needs to be removed, without having to recalculate the entire window:

[0039] Update steps:

[0040] S new =S old +X new -X old ;

[0041] Among them, S new is the updated window sum, that is, the new sum of all data values ​​in the window after the new data is added; S old is the sum of the current window, that is, the sum of all data values ​​in the window before new data is added; X new is the data value newly added to the window, that is, the latest data point arriving as the data stream advances; X old It is the data value that is moved out of the window, that is, when the window slides forward, the data point that first enters the window has now exceeded the window range.

[0042] This means that each operation takes only constant time O(1)O(1), which is especially important when the amount of data is very large.

[0043] Sliding window aggregation effectively simplifies data processing by aggregating large amounts of data into a small amount of key statistical information, which can reduce the complexity of subsequent analysis and storage, especially when data traffic is large and storage is limited.

[0044] After working for a period of time, the data generated in this time period will be extracted from the data storage module through the data extraction module, and then the data will be sent to the trend calculation module for deduction. The subsequent data situation will be calculated according to the data change trend. Then, the topology optimization module will formulate an optimization plan based on the situation calculated by the trend calculation module, and optimize the first topology model according to the optimization plan to form a second topology model, thereby realizing real-time model reconstruction function.

[0045] Working principle: First, the data acquisition module is used to collect power grid data from multiple data sources, including the status of power equipment, electrical quantity measurement, topological structure and other information. Then, the data collected by the data acquisition module is classified by the data classification module, so that the collected data can be divided into different parts according to its content. Then, the data cleaning module is used to clean the segmented data. The classification and cleaning method is used to facilitate the system to carry out targeted data processing, which can make the data cleaning effect better. At the same time, the data can be classified and different types of data can be cleaned synchronously, which can increase the data processing speed of the equipment.

[0046] When the data cleaning module has completed data cleaning, it will verify the cleaned data through the data verification module to ensure that all types of data exist to prevent data type loss. If the data verification module finds that data is missing, it will feedback to the data classification module, find the corresponding classified data through the data classification module, and then re-import the corresponding classified data into the data cleaning module for cleaning. If the data verification module verifies that there is no missing data, the cleaned data will be directly sent to the data integration module for integration.

[0047] The data integration module integrates the data, and the data integrated by the data integration module is transmitted to the first topological model for processing to obtain the required conclusion.

[0048] The conclusion drawn from the first topology model will be transmitted to the display module through the transmission module for display. During the transmission process of the transmission module, the data transmission speed of the transmission module will be detected by the transmission speed detection module, and then the network status will be controlled by the network speed control module. If the speed detected by the transmission speed detection module is slow, the system will regulate the entire internal network and give priority to the use of this system. If the transmission speed is still very slow when the entire internal network is used, the external network will be used to work together for transmission, so as to give priority to ensuring the data transmission speed in the system and facilitate the work of the system. When all information is transmitted to the display module for display, the staff is also required to verify their identity through the identity authentication module. Only internal personnel who meet the identity requirements can view the system data through the display module. At the same time, the display module does not have a storage function, so the application itself needs to re-transmit the data every time it views the data, which can avoid residual data leakage on the hardware device.

[0049] During the operation of this system, the data integrated by the data integration module will be transmitted to the data storage module for storage. After the system works for a period of time, the data generated in the time period will be extracted from the data storage module through the data extraction module, and then the data will be transmitted to the trend calculation module for deduction. The subsequent data situation will be deduced according to the data change trend. Then, the topology optimization module will formulate an optimization plan based on the situation deduced by the trend calculation module, and the first topology model will be optimized according to the optimization plan to form a second topology model, so that the calculation method of the second topology model conforms to the subsequent data change trend. At this time, the second topology model will be verified through the next detection data of the system. When the data detected by the second topology model is consistent with the data of the first topology model, the operation of the second topology model is correct, so that the model replacement module replaces the first topology model. The second topology model is the calculation model for subsequent data, which is calculated according to the existing data. Therefore, the calculation result of the second topology model when it is first used should be consistent with the settlement structure of the first topology model. Later, the subsequent data will be adapted according to the calculated trend. Therefore, the results generated by the first topology model and the second topology model are consistent during verification. It is only because the calculation trend of the first topology model is outdated and does not conform to the subsequent change trend, so it is necessary to replace it with the second topology model.

[0050] Embodiment 2 is an embodiment of the present invention, which provides a method for real-time reconstruction of topology of a distributed multi-source power grid full-time and space information model, including:

[0051] S1: Acquire data from multiple power grids, including power grid operation status data, environmental data, and user demand data;

[0052] S2: Based on the data of multi-source power grids, the full-time and space information model of the power grid is constructed using distributed computing resources to form the initial power grid topology structure;

[0053] S3: Based on the initial grid topology, the grid topology is dynamically adjusted through real-time monitoring and analysis of changes in grid operation status to reflect the most realistic current grid operation status.

[0054] Embodiment 3 is an embodiment of the present invention, which is different from the previous embodiment in that: if the function is implemented in the form of a software function unit and sold or used as an independent product, it 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, which 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 method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0055] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0056] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0057] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0058] Embodiment 4 is an embodiment of the present invention, which provides a distributed multi-source power grid full-time and space information model topology real-time reconstruction platform. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0059] In order to verify the effectiveness and superiority of the present invention on the real-time reconstruction platform of the topology of the full-time and space information model of the distributed multi-source power grid, this embodiment designs a series of theoretical experiments to compare the performance of the present invention and the prior art solutions in terms of data processing speed, data transmission efficiency and model optimization effect. First, this embodiment constructs a simulated power grid environment, which contains multiple data collection points to simulate a large amount of real-time data generated in the actual power grid operation. In the experiment, this embodiment applies the present invention and the prior art solution to the same data set to compare the data processing time, data transmission speed and stability of the power grid operation after model optimization. Specifically, the experiment is divided into three stages: data processing stage, data transmission stage and model optimization stage. In the data processing stage, this embodiment records the time required for the whole process from data collection to data cleaning, classification, verification and integration; in the data transmission stage, this embodiment monitors the transmission rate of data from integration to transmission to each module; in the model optimization stage, this embodiment evaluates the efficiency and stability of the power grid operation before and after model optimization.

[0060] Table 1 Comparison of data processing efficiency

[0061] stage Invention time (s) Prior art time(s) Data classification 1.2 2.5 Data cleaning 1.8 4.3 Data Validation 0.5 1.2 Data Integration 1.0 2.1 total 4.5 10.1

[0062] As can be seen from Table 1, the present invention shows obvious advantages in all stages of data processing, especially in data cleaning and data classification, the time consumption is reduced by 58% and 52% respectively, which is due to the classification cleaning method adopted by the present invention, making data processing more efficient. Overall, the total data processing time of the present invention is only 4.5 seconds, which is 55.4% higher than the 10.1 seconds of the prior art. This result shows that the present invention has significant superiority in data processing speed.

[0063] Table 2 Comparison of data transmission efficiency and model optimization effect

[0064] index The present invention Prior art Data transfer rate (Mbps) 120 80 Model optimization time(s) 15 30 Optimized grid stability (failure rate%) 0.2 0.8

[0065] The data in Table 2 further confirm the advantages of the present invention in practical applications. In terms of data transmission rate, the present invention reaches 120Mbps, which is 50% higher than the prior art, thanks to the intelligent control of the transmission speed detection and network speed control modules in the present invention. In addition, in terms of model optimization, the present invention not only shortens the optimization time by half, but also significantly improves the stability of the power grid after optimization, and reduces the failure rate by 75%. These results fully demonstrate the effectiveness of the present invention in improving data transmission efficiency and power grid operation stability.

[0066] 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 may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A distributed multi-source power grid full-time and space information model topology real-time reconstruction platform, characterized by: include: A data acquisition module, wherein the output end of the data acquisition module is connected to a data classification module, and the output end of the data classification module is connected to a data cleaning module, the output end of the data cleaning module is connected to a data verification module, and the output end of the data verification module is connected to a data integration module, the data classification module and the data integration module are connected in parallel, and the data acquisition module and the data verification module are connected in parallel.

2. The distributed multi-source power grid full-time and space information model topology real-time reconstruction platform according to claim 1, characterized in that: The output end of the data integration module is connected to the first topological model, and the data verification module, the data integration module and the first topological model are connected in series; The output end of the data integration module is connected to a real-time optimization module, and the real-time optimization module and the first topology model are connected in parallel; The output end of the first topology model is connected to a visualization display module, and the visualization display module and the real-time optimization module are connected in parallel; The first topology model is connected to the real-time optimization module input and output, and the data integration module and the real-time optimization module are connected in parallel.

3. The distributed multi-source power grid full-time and space information model topology real-time reconstruction platform according to claim 2, characterized in that: The visual display module includes a transmission module, a transmission speed detection module and a network speed control module, and the output end of the transmission module is connected to the transmission speed detection module, and the output end of the transmission speed detection module is connected to the network speed control module.

4. The distributed multi-source power grid full-time and space information model topology real-time reconstruction platform according to claim 3, characterized in that: The visualization display module also includes a display module and an identity authentication module, and the output end of the transmission module is connected to the display module, the display module and the transmission speed detection module are connected in parallel, and the input end of the display module is connected to the identity authentication module, and the transmission module and the identity authentication module are connected in parallel.

5. The distributed multi-source power grid full-time and space information model topology real-time reconstruction platform according to claim 4, characterized in that: The real-time optimization module includes a data storage module, a data extraction module and a trend calculation module, and the output end of the data storage module is connected to the data extraction module, and the output end of the data extraction module is connected to the trend calculation module.

6. The distributed multi-source power grid full-time and space information model topology real-time reconstruction platform according to claim 5, characterized in that: The real-time optimization module also includes a topology optimization module and a second topology model, and the output end of the trend calculation module is connected to the topology optimization module, and the output end of the topology optimization module is connected to the second topology model.

7. The distributed multi-source power grid full-time and space information model topology real-time reconstruction platform according to claim 6, characterized in that: The real-time optimization module further includes a result checking module and a model replacement module, and the output end of the second topology model is connected to the result checking module, and the output end of the result checking module is connected to the model replacement module; In the case of power data, data information obtained from sensors, monitoring equipment and other real-time data sources is aggregated to merge multiple data streams to reduce data volume and processing complexity.

8. A distributed multi-source power grid full-time and space information model topology real-time reconstruction method, based on the distributed multi-source power grid full-time and space information model topology real-time reconstruction platform according to any one of claims 1 to 7, characterized in that: include, Acquire data of a multi-source power grid, including power grid operation status data, environmental data, and user demand data of the multi-source power grid; Based on the data of multi-source power grids, the full-time and space information model of the power grid is constructed using distributed computing resources to form the initial power grid topology structure; Based on the initial grid topology, the grid topology is dynamically adjusted by real-time monitoring and analysis of changes in grid operation status to reflect the most realistic current grid operation status.

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 topology real-time reconstruction platform described in 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 topology real-time reconstruction platform described in any one of claims 1 to 7 are implemented.

Images