A method and system for automatically identifying the network topology of a power system

Abstract

The present invention discloses a method and system for automatically identifying the network topology of a power system. The method includes: obtaining the power information of each node in the power system; analyzing the relevance between each node according to the power information of each node to obtain the associated nodes and independent nodes in the power system; determining the connection relationship between each node based on the associated nodes and the independent nodes, and constructing a network topology according to the connection relationship between each node; obtaining the real-time operating status of each node, and adjusting the network topology according to the real-time operating status of each node to obtain an updated topology. It can reduce manual intervention, lower operation and maintenance costs, improve the intelligent management level of the power system, realize the efficient operation of the power network and the optimal allocation of resources, and provide strong technical support for the development of the power industry.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems, and particularly relates to a method and system for automatically identifying the network topology of a power system. Background Art

[0002] With the development of power technology, power systems have become increasingly complex. The automatic identification of network topology is of great significance for the stable operation and fault diagnosis of power systems. Traditional network topology identification methods rely on manual operations, which are inefficient and error-prone. Therefore, it is particularly urgent to study and apply methods that can automatically identify the network topology of power systems.

[0003] There are still some deficiencies in the existing methods for automatically identifying the network topology of power systems. For example, they cannot accurately identify indirect connection relationships in complex networks, which may lead to incorrect judgments of network topology structures, thereby affecting the accuracy of fault diagnosis and the stability of power systems. To solve the above problems, the present invention proposes a method for automatically identifying the network topology of a power system to improve the accuracy of network topology structure identification. Summary of the Invention

[0004] The present invention provides a method and system for automatically identifying the network topology of a power system, which can accurately identify the direct and indirect connection relationships between various nodes in the power system, thereby improving the accuracy of network topology structure identification.

[0005] In a first aspect, the present invention provides a method for automatically identifying the network topology of a power system, including:

[0006] Obtaining the power information of each node in the power system, where the power information includes voltage parameters, current parameters, and power parameters;

[0007] Analyzing the correlation between each node based on the power information of each node to obtain the associated nodes and independent nodes in the power system;

[0008] Determining the connection relationship between each node based on the associated nodes and the independent nodes, and constructing a network topology structure according to the connection relationship between each node;

[0009] Obtaining the real-time operating status of each node, and adjusting the network topology structure according to the real-time operating status of each node to obtain an updated topology structure;

[0010] Performing a verification process on the updated topology structure, and storing the updated network topology structure in a database after the updated topology structure passes the verification.

[0011] In a second aspect, the present invention provides a system for automatically identifying the network topology of a power system, including:

[0012] An acquisition module, configured to acquire power information of each node in a power system, where the power information includes voltage parameters, current parameters, and power parameters;

[0013] An analysis module, configured to analyze the correlation between each node according to the power information of each node, and obtain associated nodes and independent nodes in the power system;

[0014] A construction module, configured to determine the connection relationship between each node based on the associated nodes and the independent nodes, and construct a network topology according to the connection relationship between each node;

[0015] An adjustment module, configured to acquire the real-time operating status of each node, and adjust the network topology according to the real-time operating status of each node to obtain an updated topology;

[0016] A verification module, configured to perform verification processing on the updated topology, and store the updated network topology in a database after the updated topology passes the verification.

[0017] In a third aspect, an electronic device is provided, which includes: at least one processor, and a memory communicatively connected to the at least one processor, where the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the power system network topology automatic recognition method according to any embodiment of the present invention.

[0018] In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the program instructions are executed by a processor, the processor is enabled to execute the steps of the power system network topology automatic recognition method according to any embodiment of the present invention.

[0019] The power system network topology automatic recognition method and system of the present application can timely discover and handle potential fault points by real-time monitoring and analyzing the operating status of each node in the power system, thereby improving the stability and reliability of the entire power system. By automatically identifying changes in the network topology, the system can quickly adapt to dynamic adjustments of the power network to ensure the continuity and security of power supply. In addition, the present invention can also reduce manual intervention, lower operation and maintenance costs, and improve the intelligent management level of the power system. Finally, through the method provided by the present invention, efficient operation of the power network and optimal allocation of resources can be achieved, providing strong technical support for the development of the power industry. Description of the Drawings

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 It is a flowchart of a method for automatically identifying the network topology of a power system provided by an embodiment of the present invention;

[0022] Figure 2 It is a structural block diagram of a system for automatically identifying the network topology of a power system provided by an embodiment of the present invention;

[0023] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Specific Embodiments

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0025] Please refer to Figure 1 , which shows a flowchart of a method for automatically identifying the network topology of a power system of the present application.

[0026] As Figure 1 shown, the method for automatically identifying the network topology of a power system specifically includes the following steps:

[0027] Step S101, obtain the power information of each node in the power system, where the power information includes voltage parameters, current parameters, and power parameters.

[0028] In this step, after obtaining the power information of each node in the power system, preprocess the power information. The preprocessing steps include:

[0029] Obtain the power information of each node and perform filtering processing on the power information to eliminate noise and interference;

[0030] Perform standardization processing on the filtered power information to unify the consistency and comparability of the power information;

[0031] Perform normalization processing on the power information after standardization processing to determine the comparability of the power information under different magnitudes and dimensions;

[0032] Specifically, in a power system, the power information of each node is crucial data. To ensure the accuracy and reliability of the power information, a series of preprocessing steps are required. First, the power information is obtained from each node. The power information may contain various noises and interferences, so filtering processing is needed to eliminate these unnecessary components. The filtering processing can be achieved through various algorithms, such as low-pass filters, high-pass filters, or band-pass filters, etc. The specific selection depends on the characteristics of the power information and the type of noise. To ensure the consistency and comparability of the power information, the filtered data needs to be standardized. The standardization process usually involves converting the data into a form with zero mean and unit variance, which can eliminate the influence brought by different magnitudes and dimensions, making the data more consistent in subsequent analysis. There are many methods of standardization, such as min-max standardization, Z-score standardization, etc. The selection of the appropriate method depends on the distribution characteristics of the data and the analysis requirements. Finally, to further improve the comparability of the power information under different magnitudes and dimensions, normalization processing is also required. The normalization processing usually means scaling the data to a specific range or mapping the data to a specific distribution, with the aim of ensuring the comparability of the data at different nodes and different time points, facilitating further analysis and processing. The methods of normalization include linear normalization, logarithmic normalization, etc. The specific selection depends on the characteristics of the data and the analysis objectives.

[0033] Step S102: Analyze the correlation between each node based on the power information of each node to obtain the associated nodes and independent nodes in the power system.

[0034] In this step, by continuously monitoring the power information of each node, it is possible to identify which nodes are correlated, that is, associated nodes, and which nodes operate independently, that is, independent nodes. Based on this, the premise for constructing the network topology structure is determined. Among them, the steps of analyzing the correlation between each node based on the power information of each node include:

[0035] Obtain the preprocessed power information of each node and extract the load characteristics of each node;

[0036] Obtain the load characteristic values of each node, and the load characteristic value is the average load value of each node;

[0037] Calculate the correlation coefficient between different nodes based on the load characteristic values, and determine the correlation between each node based on the correlation coefficient;

[0038] Specifically, in order to analyze the correlation between each node, it is first necessary to obtain the preprocessed power information of each node. After obtaining the preprocessed power information, the load characteristics of each node will be further extracted. The load characteristics may include historical load data. Then, the load characteristic values of each node will be calculated. The load characteristic values are usually obtained by calculating the average load value of each node within a certain period of time. The average load value can reflect the overall load level of the node within a period of time. Finally, the correlation coefficient between different nodes will be calculated based on the load characteristic values. By calculating the correlation coefficient, the correlation between different nodes can be quantitatively evaluated, providing a basis for further analysis and decision-making. Among them, the steps of determining the correlation state between each node based on the correlation coefficient include:

[0039] Obtain the load characteristic values of different nodes and record them as precondition parameters;

[0040] Construct a sample period, set multiple sampling nodes within the sample period, and synchronously collect the precondition parameters corresponding to different nodes under each sampling node;

[0041] Obtain a correlation measurement function, input the precondition parameters under the same sampling node into the correlation measurement function, and record the output result of the correlation measurement function as a transition condition parameter;

[0042] Perform an averaging process on the transition condition parameters and record the average value of the transition condition parameters as a parameter to be evaluated;

[0043] Obtain an evaluation threshold and compare the evaluation threshold with the parameter to be evaluated;

[0044] When the parameter to be evaluated is greater than or equal to the evaluation threshold, it is determined that there is a correlation between the nodes, and the corresponding nodes are recorded as associated nodes;

[0045] When the parameter to be evaluated is less than the evaluation threshold, it is determined that there is no correlation between the nodes, and the corresponding nodes are recorded as independent nodes.

[0046] Specifically, in order to determine the correlation state between each node, it is first necessary to obtain the load characteristic values of different nodes and record them as precondition parameters for subsequent analysis. At the same time, construct a sample period. The selection of the sample period should be able to fully reflect the operating state of the power system to ensure the accuracy of the analysis results. It is specifically set according to actual needs. Within the sample period, set multiple sampling nodes. The distribution method of the sampling nodes is uniform distribution. Under each sampling node, synchronously collect the precondition parameters corresponding to different nodes, that is, the previously recorded load characteristic values. Then, it is necessary to obtain a preset correlation measurement function. The expression of the correlation measurement function is: , where, Represents the transition condition parameter, Represents the quantity of historical load data, and Represents the historical load data under different nodes, and Represents the corresponding precondition parameter under different nodes. Then, input the recorded precondition parameter into the associated measurement function and perform calculations. After the calculation is completed, record the output result of the associated measurement function as the transition condition parameter for further analysis and judgment. Here, after the transition condition parameter is output, perform an averaging process on the transition condition parameter to smooth the load fluctuations caused by accidental factors and improve the accuracy of analysis. Then, the average value of the transition condition parameter can be recorded as the parameter to be evaluated. Then, introduce a preset evaluation threshold. The evaluation threshold is a preset standard used to determine whether the association degree between nodes has reached a certain level. Comparing the parameter to be evaluated with this evaluation threshold can determine the association status between nodes. Specifically, if the parameter to be evaluated is greater than or equal to the evaluation threshold, it can be determined that there is an association between these two nodes. In this case, record these two nodes as associated nodes, indicating that they affect each other in the power system. On the contrary, if the parameter to be evaluated is less than the evaluation threshold, it can be determined that there is no association between these two nodes. In this case, record these two nodes as independent nodes, indicating that they are independent of each other in the power system and have no obvious mutual influence.

[0047] Step S103, determine the connection relationship between each node based on the associated nodes and the independent nodes, and construct a network topology structure according to the connection relationship between each node.

[0048] In this step, after determining the connection relationship between each node, construct a network topology structure based on the connection relationship between the nodes. The network topology structure will intuitively display the logical relationship between each node in the power system, providing convenience for subsequent analysis and management. Among them, the step of determining the connection relationship between each node based on the associated nodes and the independent nodes includes:

[0049] Obtain the positional relationship of all associated nodes and independent nodes;

[0050] If the associated nodes are adjacent, define the connection relationship between the adjacent associated nodes as a direct connection;

[0051] If the associated nodes are not adjacent, determine whether there is a common associated node between the associated nodes. If so, use this common associated node as a mediator to define an indirect connection relationship. Otherwise, define it as a non-connection relationship.

[0052] The connection relationship between independent nodes is directly defined as a non-connection relationship;

[0053] Specifically, in the process of determining the connection relationship between each node, it is necessary to obtain the positional relationship between all associated nodes and independent nodes. First, it is necessary to check whether the associated nodes are adjacent. If two associated nodes are adjacent in space, then their connection relationship can be directly defined as a direct connection. A direct connection means that there is a direct path or relationship between these two nodes, and they can interact or transmit information without passing through other nodes. However, if the associated nodes are not adjacent, further judgment is required. In this case, it is necessary to check whether there are common associated nodes between the non-adjacent associated nodes. If there are common associated nodes, then the common associated nodes can be used as intermediaries to define an indirect connection relationship. An indirect connection relationship means that two originally non-adjacent nodes can indirectly interact or transmit information through one or more intermediary nodes. If it is found during the inspection that there are no common associated nodes between the non-adjacent associated nodes, then their connection relationship can be directly defined as a non-connection relationship, which means that there is no direct or indirect path or relationship between these two nodes, and they cannot interact or transmit information. As for independent nodes, since they are independent by definition, the connection relationship between them is directly defined as a non-connection relationship. There is no direct or indirect path or relationship between independent nodes, and they cannot interact or transmit information.

[0054] Step S104, obtain the real-time operating status of each node, and adjust the network topology according to the real-time operating status of each node to obtain an updated topology.

[0055] In this step, in order to ensure the accuracy and real-time nature of the network topology, it is necessary to monitor the operating status of each node in real time. The operating status includes a normal state and an abnormal state. In the normal state, each node can operate normally, while the abnormal state may include situations such as overload and failure. At this time, the network topology needs to be adjusted accordingly to reflect the actual operating conditions of the nodes, and the adjusted network topology is recorded as the updated topology. Among them, the steps of monitoring the operating status of each node in real time include:

[0056] Obtain the load characteristic value of each node and record it as a parameter to be evaluated;

[0057] Obtain an evaluation threshold and compare the evaluation threshold with the parameter to be evaluated;

[0058] If the parameter to be evaluated is greater than the evaluation threshold, the operation of the corresponding node is abnormal, and the operating status of the corresponding node is recorded as the abnormal state;

[0059] If the parameter to be evaluated is less than or equal to the evaluation threshold, the operation of the corresponding node is normal, and the operation state of the corresponding node is recorded as the normal state;

[0060] Wherein, after the abnormal state is output, a monitoring period is constructed with the node that issues the abnormal state as the starting node;

[0061] If there is a parameter to be evaluated greater than the evaluation threshold within the monitoring period, an alarm signal is output, and the determination result of the abnormal state is maintained;

[0062] If the parameter to be evaluated continuously is less than or equal to the evaluation threshold within the monitoring period, it indicates that there is an instantaneous fluctuation in the operation of the corresponding node, and the operation state of the corresponding node is restored to the normal state, and the determination result of the abnormal state is lifted.

[0063] If the parameter to be evaluated is less than or equal to the evaluation threshold, it indicates that the operation of the corresponding node is normal, and the operation state of the corresponding node is recorded as the normal state.

[0064] Specifically, in order to monitor the operation state of each node in real time, first, the load characteristic values of each node and a preset evaluation threshold need to be obtained. The evaluation threshold is set according to the standard of the normal operation of the system and is used to judge whether the node is in the normal operation state. The evaluation threshold is compared with the parameter to be evaluated recorded previously. After the comparison, it will enter the judgment stage. If the parameter to be evaluated is greater than the evaluation threshold, it means that the operation state of the node exceeds the normal range and there may be abnormal conditions. In this case, the operation state of the corresponding node is recorded as the abnormal state. On the contrary, if the parameter to be evaluated is less than or equal to the evaluation threshold, it indicates that the operation state of the corresponding node is within the normal range and there is no abnormal condition. In this case, the operation state of the corresponding node is recorded as the normal state. In addition, after the abnormal state is output, in order to ensure the accuracy of the determination result, a monitoring period is constructed with the node that issues the abnormal state as the starting node. The length of the monitoring period can be set according to the actual situation to ensure that the change of the operation state of the node can be accurately captured. Within the monitoring period, the load characteristic value of the node is continuously obtained and compared with the evaluation threshold. If the parameter to be evaluated continuously is greater than the evaluation threshold within the monitoring period, an alarm signal is output, and the determination result of the abnormal state is maintained. At this time, the operator needs to immediately take corresponding measures to check and repair the abnormal node to avoid possible failures or accidents. If the parameter to be evaluated continuously is less than or equal to the evaluation threshold within the monitoring period, it can be judged that the abnormal operation of the node may be caused by instantaneous fluctuations. At this time, the operation state of the corresponding node is restored to the normal state, and the determination result of the abnormal state is lifted. In addition, the steps of adjusting the network topology structure according to the operation state of each node to obtain the updated topology structure include:

[0065] Obtain the running status of each node, extract the nodes with abnormal running status, and synchronously mark them as abnormal nodes;

[0066] Obtain the nodes marked as abnormal nodes in the network topology structure and record them as nodes to be evaluated;

[0067] If the nodes to be evaluated are associated nodes and the association relationship is a direct connection, it indicates that the network topology structure is normal and no adjustment is required;

[0068] If the nodes to be evaluated are associated nodes and the association relationship is an indirect connection relationship, it indicates that there are potential fault points in the network topology structure, and the connection relationship between the nodes to be evaluated is adjusted;

[0069] If the nodes to be evaluated are independent nodes, it indicates that there are potential fault points in the network topology structure, and the connection relationship between the nodes to be evaluated is adjusted;

[0070] Specifically, in order to ensure the stability and reliability of the network, it is necessary to dynamically adjust the network topology structure according to the running status of each node. First, extract the nodes in the abnormal state and synchronously mark these nodes as abnormal nodes. Second, obtain the nodes that are synchronously marked as abnormal nodes in the network topology structure and record them as nodes to be evaluated. Then, analyze the relationship between the nodes to be evaluated. If there is an association relationship between the nodes to be evaluated and these association relationships are manifested as direct connections, then it can be considered that the current network topology structure is normal and there is no need to adjust. However, if the association relationship between the nodes to be evaluated is manifested as an indirect connection, it indicates that there may be potential fault points in the network topology structure, that is, the nodes between the indirect connection relationships may not be able to interact directly, and the connection relationship between these nodes needs to be adjusted to ensure the smooth transmission of information. If the nodes to be evaluated are independent nodes without any association relationship, this also indicates that there may be potential fault points in the network topology structure. In this case, the connection relationship between these independent nodes also needs to be adjusted to ensure the integrity and reliability of the network.

[0071] Step S105, perform a verification process on the updated topology structure, and after the updated topology structure passes the verification, store the updated network topology structure in the database.

[0072] In this step, through the corresponding verification process, it can be ensured that the updated topology structure meets the predetermined standards and requirements. Once the verification is passed, the updated topology structure will be stored in the database for future query, analysis, and decision-making. Among them, the steps for performing a verification process on the updated topology structure include:

[0073] Obtain the updated topology structure, compare and analyze it with the original network topology structure to obtain updated nodes;

[0074] Construct a verification period, count the occurrence times of the updated nodes during the verification period, and record them as verification condition parameters;

[0075] Obtain a verification threshold and compare the verification threshold with the verification condition parameters;

[0076] If the verification condition parameter is greater than the verification threshold, it indicates that the updated node is a valid update and is retained in the updated topology structure;

[0077] If the verification condition parameter is less than or equal to the verification threshold, it indicates that the updated node is an invalid update, and the original nodes in the original network topology structure are retained in the updated topology structure;

[0078] Among them, when counting the occurrence times of the updated nodes, the updated nodes caused by abnormal states triggered by instantaneous fluctuations are excluded.

[0079] Specifically, during the process of updating the network topology structure, it is very important to ensure the correctness and effectiveness of the update. First, it is necessary to obtain the updated topology structure. After obtaining the updated topology structure, it will be compared and analyzed with the original network topology structure. Through this comparison, it is possible to identify which nodes have changed during the update process. The changed nodes will be recorded as updated nodes. After that, it is necessary to construct a verification period. The verification period refers to the time range during which the updated nodes are observed and analyzed within a specific time period. During the verification period, the number of concurrent occurrences of the updated nodes will be counted and recorded as a verification condition parameter. Here, it should be noted that when counting the number of concurrent occurrences of the updated nodes, those updated nodes caused by abnormal states triggered by instantaneous fluctuations will be excluded because they only temporarily deviate from the normal state and do not represent the real changes in the network topology structure. To further ensure the effectiveness of the update, a preset verification threshold needs to be introduced. The verification threshold is a preset standard value used to determine whether the updated nodes meet the expected update conditions. Specifically, the verification threshold is compared with the verification condition parameter obtained previously. Through this comparison, it can be determined whether the updated nodes meet the update standard. If the verification condition parameter is greater than the verification threshold, it means that the number of occurrences of the updated nodes within the specified verification period exceeds the preset standard. In this case, it can be considered that the updated nodes are effective and should be retained in the updated topology structure. On the contrary, if the verification condition parameter is less than or equal to the verification threshold, it indicates that the number of occurrences of the updated nodes does not reach the expected standard. In this case, it is considered that the updated nodes are invalid. Therefore, the original nodes in the original network topology structure should be retained and kept in the updated topology structure to avoid accidental updates affecting the stability of the network topology structure.

[0080] In summary, the method of the present application can timely detect and handle potential fault points by real-time monitoring and analyzing the operating states of each node in the power system, thereby improving the stability and reliability of the entire power system. By automatically identifying changes in the network topology structure, the system can quickly adapt to the dynamic adjustment of the power network and ensure the continuity and security of power supply. In addition, the present invention can also reduce manual intervention, lower operation and maintenance costs, and improve the intelligent management level of the power system. Finally, through the method provided by the present invention, the efficient operation of the power network and the optimal allocation of resources can be achieved, providing strong technical support for the development of the power industry.

[0081] Please refer to Figure 2 , which shows the structural block diagram of a power system network topology automatic recognition system of the present application.

[0082] As Figure 2As shown, the power system network topology automatic recognition system 200 includes an acquisition module 210, an analysis module 220, a construction module 230, an adjustment module 240, and a verification module 250.

[0083] Among them, the acquisition module 210 is configured to acquire the power information of each node in the power system, where the power information includes voltage parameters, current parameters, and power parameters; the analysis module 220 is configured to analyze the correlation between each node according to the power information of each node to obtain the associated nodes and independent nodes in the power system; the construction module 230 is configured to determine the connection relationship between each node based on the associated nodes and the independent nodes, and construct a network topology structure according to the connection relationship between each node; the adjustment module 240 is configured to acquire the real-time operation status of each node, and adjust the network topology structure according to the real-time operation status of each node to obtain an updated topology structure; the verification module 250 is configured to perform verification processing on the updated topology structure, and store the updated network topology structure in the database after the updated topology structure passes the verification.

[0084] It should be understood that Figure 2 the modules described in Figure 1 correspond to the respective steps in the method described in the reference Figure 2 Therefore, the operations, features, and corresponding technical effects described above for the method also apply to

[0085] In some other embodiments, the embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored. When the program instructions are executed by a processor, the processor is caused to execute the power system network topology automatic recognition method in any of the above method embodiments;

[0086] As an implementation manner, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are set as:

[0087] Acquire the power information of each node in the power system, where the power information includes voltage parameters, current parameters, and power parameters;

[0088] Analyze the correlation between each node according to the power information of each node to obtain the associated nodes and independent nodes in the power system;

[0089] Determine the connection relationship between each node based on the associated nodes and the independent nodes, and construct a network topology structure according to the connection relationship between each node;

[0090] Obtain the real-time operating status of each node, and adjust the network topology structure according to the real-time operating status of each node to obtain an updated topology structure;

[0091] Perform a verification process on the updated topology structure, and after the updated topology structure passes the verification, store the updated network topology structure in the database.

[0092] A computer-readable storage medium may include a storage program area and a storage data area. Among them, the storage program area can store an operating system and application programs required for at least one function; the storage data area can store data created according to the use of the power system network topology automatic recognition system, etc. In addition, the computer-readable storage medium may include a high-speed random access memory, and may also include a memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the computer-readable storage medium may optionally include a memory remotely provided with respect to the processor, and these remote memories can be connected to the power system network topology automatic recognition system through a network. Examples of the above networks include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0093] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. As Figure 3 shown, the device includes: a processor 310 and a memory 320. The electronic device may further include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330, and the output device 340 can be connected through a bus or other means. Figure 3 Taking the connection through the bus as an example. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running non-volatile software programs, instructions, and modules stored in the memory 320, that is, implements the power system network topology automatic recognition method in the above method embodiment. The input device 330 can receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the power system network topology automatic recognition system. The output device 340 may include a display device such as a display screen.

[0094] The above electronic device can execute the method provided by the embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the method provided by the embodiment of the present invention.

[0095] As an implementation manner, the above-mentioned electronic device is applied to an automatic identification system for power system network topology and is used for a client, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0096] Obtain the power information of each node in the power system, where the power information includes voltage parameters, current parameters, and power parameters;

[0097] Analyze the relevance between each node according to the power information of each node to obtain the associated nodes and independent nodes in the power system;

[0098] Determine the connection relationship between each node based on the associated nodes and the independent nodes, and construct a network topology according to the connection relationship between each node;

[0099] Obtain the real-time operating status of each node, and adjust the network topology according to the real-time operating status of each node to obtain an updated topology;

[0100] Perform a verification process on the updated topology, and after the updated topology passes the verification, store the updated network topology in the database.

[0101] Through the description of the above implementation manners, those skilled in the art can clearly understand that each implementation manner can be realized by means of software plus a necessary general hardware platform, and of course, it can also be realized by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disc, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiments.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A method for automatically identifying the network topology of a power system, characterized in that, Including: Obtaining power information of each node in a power system, where the power information includes voltage parameters, current parameters, and power parameters; Analyzing the correlation between each node based on the power information of each node to obtain associated nodes and independent nodes in the power system, where the analyzing the correlation between each node based on the power information of each node to obtain associated nodes and independent nodes in the power system includes: Obtaining the power information of each node and extracting the load characteristics of each node; Obtaining the load characteristic values of each node, where the load characteristic value is the average load value of each node; Calculating the correlation coefficient between different nodes based on the load characteristic values, and determining the correlation between each node based on the correlation coefficient to obtain associated nodes and independent nodes in the power system; The determining the correlation between each node based on the correlation coefficient to obtain associated nodes and independent nodes in the power system includes: Obtaining the load characteristic values of different nodes and recording them as precondition parameters; Constructing a sample period, setting multiple sampling nodes within the sample period, and synchronously collecting the precondition parameters corresponding to different nodes under each sampling node; Obtaining an association measurement function, inputting the precondition parameters under the same sampling node into the association measurement function, and recording the output result of the association measurement function as a transition condition parameter; Performing an averaging process on the transition condition parameters and recording the average value of the transition condition parameters as a parameter to be evaluated; Obtaining an evaluation threshold and comparing the evaluation threshold with the parameter to be evaluated; When the parameter to be evaluated is greater than or equal to the evaluation threshold, determining that there is an association between the nodes and recording the corresponding nodes as associated nodes; When the parameter to be evaluated is less than the evaluation threshold, determining that there is no association between the nodes and recording the corresponding nodes as independent nodes; Determining the connection relationship between each node based on the associated nodes and the independent nodes, and constructing a network topology according to the connection relationship between each node; Obtaining the real-time operating status of each node, and adjusting the network topology according to the real-time operating status of each node to obtain an updated topology; Performing a verification process on the updated topology, and storing the updated network topology in a database after the updated topology passes the verification.

2. The automatic recognition method for the network topology of a power system according to claim 1, wherein The determining the connection relationship between each node based on the associated nodes and the independent nodes includes: Obtaining the positional relationship of all the associated nodes and independent nodes; If two associated nodes are adjacent, defining the connection relationship between the two adjacent associated nodes as a direct connection; If two associated nodes are not adjacent, determining whether there are common associated nodes between the two associated nodes. If so, using the common associated node as a mediator to define an indirect connection relationship, otherwise, defining it as a non-connection relationship; Directly defining the connection relationship between independent nodes as a non-connection relationship.

3. A method for automatically identifying the network topology of a power system according to claim 1, characterized in that The obtaining the real-time operating status of each node includes: Obtaining the load characteristic values of each node and recording them as parameters to be evaluated; Obtain an evaluation threshold and compare the evaluation threshold with the parameter to be evaluated; If the parameter to be evaluated is greater than the evaluation threshold, the operation of the corresponding node is abnormal, and the operation status of the corresponding node is recorded as an abnormal status; If the parameter to be evaluated is less than or equal to the evaluation threshold, the operation of the corresponding node is normal, and the operation status of the corresponding node is recorded as a normal status; Among them, after the abnormal status is output, a monitoring period is constructed with the node that issues the abnormal status as the starting node; If there is a parameter to be evaluated greater than the evaluation threshold within the monitoring period, an alarm signal is output, and the determination result of the abnormal status is maintained; If the parameter to be evaluated is continuously less than or equal to the evaluation threshold within the monitoring period, it indicates that there is an instantaneous fluctuation in the operation of the corresponding node, and the operation status of the corresponding node is restored to the normal status, and the determination result of the abnormal status is lifted.

4. A method for automatically identifying the network topology of a power system according to claim 1, characterized in that, The adjustment of the network topology structure according to the real-time operation status of each node to obtain an updated topology structure includes: Obtain the operation status of each node, extract the nodes with the operation status being abnormal, and synchronously mark them as abnormal nodes; Obtain the nodes marked as abnormal nodes in the network topology structure and record them as nodes to be evaluated; If the nodes to be evaluated are associated nodes and the association relationship is a direct connection, it indicates that the network topology structure is normal and no adjustment is required; If the nodes to be evaluated are associated nodes and the association relationship is an indirect connection relationship, it indicates that there are potential fault points in the network topology structure, and the connection relationship between the nodes to be evaluated is adjusted; If the nodes to be evaluated are independent nodes, it indicates that there are potential fault points in the network topology structure, and the connection relationship between the nodes to be evaluated is adjusted.

5. A method for automatically identifying the network topology of a power system according to claim 1, characterized in that The verification process for the updated topology structure includes: Obtain the updated topology structure, compare and analyze it with the original network topology structure to obtain updated nodes; Construct a verification period, count the occurrence times of the updated nodes within the verification period, and record them as verification condition parameters; Obtain a verification threshold and compare the verification threshold with the verification condition parameters; If the verification condition parameter is greater than the verification threshold, it indicates that the updated node is a valid update and is retained in the updated topology structure; If the verification condition parameter is less than or equal to the verification threshold, it indicates that the updated node is an invalid update, and the original nodes in the original network topology structure are retained in the updated topology structure; Among them, when counting the occurrence times of the updated nodes, the updated nodes caused by the abnormal status triggered by instantaneous fluctuations are excluded.

6. A power system network topology automatic recognition system, characterized in that, Include: An acquisition module configured to acquire the power information of each node in the power system, where the power information includes voltage parameters, current parameters, and power parameters; An analysis module configured to analyze the correlation between each node according to the power information of each node to obtain the associated nodes and independent nodes in the power system, where the analysis of the correlation between each node according to the power information of each node to obtain the associated nodes and independent nodes in the power system includes: Obtain the power information of each node and extract the load characteristics of each node; Obtain the load characteristic values of each node, where the load characteristic values are the average load values of each node; Calculate the correlation coefficient between different nodes based on the load characteristic values, and determine the correlation between each node based on the correlation coefficient to obtain the associated nodes and independent nodes in the power system; The determining the correlation between each node based on the correlation coefficient to obtain the associated nodes and independent nodes in the power system includes: Obtain the load characteristic values of different nodes and record them as precondition parameters; Construct a sample period, set multiple sampling nodes within the sample period, and synchronously collect the precondition parameters corresponding to different nodes under each sampling node; Obtain an association measurement function, input the precondition parameters under the same sampling node into the association measurement function, and record the output result of the association measurement function as a transition condition parameter; Perform an averaging process on the transition condition parameters and record the average value of the transition condition parameters as a parameter to be evaluated; Obtain an evaluation threshold and compare the evaluation threshold with the parameter to be evaluated; When the parameter to be evaluated is greater than or equal to the evaluation threshold, determine that there is an association between the nodes and record the corresponding nodes as associated nodes; When the parameter to be evaluated is less than the evaluation threshold, determine that there is no association between the nodes and record the corresponding nodes as independent nodes; A construction module configured to determine the connection relationship between each node based on the associated nodes and the independent nodes, and construct a network topology according to the connection relationship between each node; An adjustment module configured to obtain the real-time operating status of each node and adjust the network topology according to the real-time operating status of each node to obtain an updated topology; A verification module configured to perform a verification process on the updated topology, and store the updated network topology in a database after the updated topology passes the verification.

7. An electronic device, characterized in that, Includes: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program, when executed by a processor, implements the method according to any one of claims 1 to 5.

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