Power system network topology automatic identification method and system

Abstract

The invention discloses a power system network topology automatic identification method and system. The method comprises the following steps: acquiring power information of each node in a power system; analyzing relevance among the nodes according to the power information of the nodes to obtain associated nodes and independent nodes in the power system; determining a connection relationship between the nodes based on the associated nodes and the independent nodes, and constructing a network topology structure according to the connection relationship between the nodes; and obtaining a real-time operation state of each node, and adjusting the network topology structure according to the real-time operation state of each node to obtain an updated topology structure. Manual intervention can be reduced, the operation and maintenance cost can be reduced, the intelligent management level of an electric power system can be improved, efficient operation of an electric power network and optimal configuration of resources can be achieved, and powerful technical support is provided for development of the electric power industry.

Description

Technical Field

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

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

[0003] The existing method for automatic identification of power system network topology still has some shortcomings. For example, it is impossible to accurately identify the indirect connection relationship in a complex network, which will lead to incorrect judgment of the network topology structure, and further affect the accuracy of fault diagnosis and the stability of the power system. In order to solve the above problems, the present invention proposes a method for automatic identification of power system network topology to improve the recognition accuracy of the network topology structure. Summary of the invention

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

[0005] In a first aspect, the present invention provides a method for automatically identifying a power system network topology, comprising: Acquire power information of each node in the power system, wherein the power information includes voltage parameters, current parameters and power parameters; Analyzing the correlation between the nodes according to the power information of the nodes to obtain the associated nodes and independent nodes in the power system; Determine the connection relationship between the nodes based on the associated nodes and the independent nodes, and construct a network topology structure according to the connection relationship between the nodes; Acquiring 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; The updated topology structure is verified, and after the updated topology structure passes the verification, the updated network topology structure is stored in a database.

[0006] In a second aspect, the present invention provides a system for automatically identifying a power system network topology, comprising: An acquisition module, configured to acquire power information of each node in the power system, wherein the power information includes voltage parameters, current parameters and power parameters; An analysis module, configured to analyze the correlation between the nodes according to the power information of the nodes, and obtain the associated nodes and independent nodes in the power system; A construction module, configured to determine a connection relationship between each node based on the associated node and the independent node, and to construct a network topology structure according to the connection relationship between each node; An adjustment module is configured to 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; The verification module is configured to perform verification processing on the updated topology structure, and after the updated topology structure passes the verification, store the updated network topology structure in a database.

[0007] According to a third aspect, an electronic device is provided, comprising: 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 so that the at least one processor can perform the steps of the method for automatic identification of power system network topology according to any embodiment of the present invention.

[0008] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the steps of the method for automatic identification of power system network topology of any embodiment of the present invention.

[0009] The method and system for automatic identification of power system network topology of the present application can timely discover and handle potential fault points by real-time monitoring and analysis of 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 structure, the system can quickly adapt to the dynamic adjustment of the power network to ensure the continuity and safety of power supply. In addition, the present invention can also reduce manual intervention, reduce 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1A flowchart of a method for automatically identifying a power system network topology provided by an embodiment of the present invention; Figure 2 A structural block diagram of a power system network topology automatic identification system provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0013] See also Figure 1 , which shows a flow chart of a method for automatic identification of power system network topology of the present application.

[0014] like Figure 1 As shown, the method for automatically identifying the power system network topology specifically includes the following steps: Step S101, acquiring power information of each node in the power system, wherein the power information includes voltage parameters, current parameters and power parameters.

[0015] In this step, after obtaining the power information of each node in the power system, the power information is preprocessed. The preprocessing steps include: Obtain the power information of each node and filter the power information to eliminate noise and interference; Standardize the filtered power information to unify the consistency and comparability of the power information; Normalize the standardized power information to determine the comparability of the power information at different levels and dimensions; Specifically, in the power system, the power information of each node is crucial data. In order to ensure the accuracy and reliability of power information, a series of preprocessing is required. First, the power information is obtained from each node. The power information may contain various noises and interferences, so filtering is required to eliminate these unnecessary components. Filtering can be implemented by 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. In order to ensure the consistency and comparability of power information, the filtered data needs to be standardized. Standardization usually involves converting the data into a form with zero mean and unit variance, so as to eliminate the influence of different magnitudes and dimensions, making the data more consistent in subsequent analysis. There are many methods of standardization, such as minimum-maximum standardization, Z-score standardization, etc. The selection of a suitable method depends on the distribution characteristics of the data and the analysis requirements. Finally, in order to further improve the comparability of power information at different magnitudes and dimensions, normalization is also required. Normalization usually refers to scaling the data to a specific range or mapping the data to a specific distribution. Its purpose is to ensure the comparability of the data at different nodes and different time points, so as to facilitate further analysis and processing. Normalization methods include linear normalization, logarithmic normalization, etc. The specific choice depends on the characteristics of the data and the analysis objectives.

[0016] Step S102: analyzing the correlation between the nodes according to the power information of the nodes to obtain the associated nodes and independent nodes in the power system.

[0017] In this step, by continuously monitoring the power information of each node, it is possible to identify which nodes are mutually related, i.e., related nodes, and which nodes are independently operated, i.e., independent nodes, based on which the premise for constructing the network topology structure is determined. The step of analyzing the correlation between each node according to the power information of each node includes: Obtaining pre-processed power information of each node and extracting load characteristics of each node; Obtain the load characteristic value of each node, where the load characteristic value is the average load value of each node; Calculate the correlation coefficients between different nodes based on the load characteristic values, and determine the relevance between the nodes based on the correlation coefficients; Specifically, in order to analyze the correlation between each node, it is first necessary to obtain the pre-processed power information of each node. After obtaining the pre-processed power information, the load characteristics of each node will be further extracted. The load characteristics may include historical load data. Then, the load characteristic value of each node will be calculated. The load characteristic value is 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 value. By calculating the correlation coefficient, the correlation between different nodes can be quantitatively evaluated to provide a basis for further analysis and decision-making. Among them, the step of determining the correlation state between each node based on the correlation coefficient includes: Obtain the load characteristic values ​​of different nodes and record them as precondition parameters; Constructing a sample period, setting a plurality of sampling nodes within the sample period, and synchronously collecting precondition parameters corresponding to different nodes under each of the sampling nodes; Obtaining an associated measurement function, and inputting the precondition parameters under the same sampling node into the associated measurement function, and recording the output result of the associated measurement function as a transition condition parameter; Taking an average value of the transition condition parameter, and recording the average value of the transition condition parameter 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, it is determined that there is an association between the nodes, and the corresponding node is recorded as an associated node; When the parameter to be evaluated is less than the evaluation threshold, it is determined that there is no association between the nodes, and the corresponding nodes are recorded as independent nodes.

[0018] Specifically, in order to determine the association status between each node, it is necessary to first obtain the load characteristic values ​​of different nodes and record them as precondition parameters for subsequent analysis. At the same time, a sample period is constructed. The selection of the sample period should be able to fully reflect the operating status of the power system and ensure the accuracy of the analysis results. It is set according to actual needs. In the sample period, multiple sampling nodes are set. The distribution of the sampling nodes is uniform. Under each sampling node, the precondition parameters corresponding to different nodes are synchronously collected, that is, the previously recorded load characteristic values. Then, a preset association measurement function needs to be obtained. The expression of the association measurement function is: , where represents the transition condition parameter, Indicates the amount of historical load data, and Represents the historical load data of different nodes. and Indicates the corresponding precondition parameters under different nodes, and then inputs the recorded precondition parameters into the association measurement function and performs calculation. After the calculation is completed, the output result of the association measurement function is recorded as the transition condition parameter for further analysis and judgment. Here, after the transition condition parameter is output, the transition condition parameter is averaged to smooth the load fluctuation caused by accidental factors and improve the accuracy of the analysis. After that, the average value of the transition condition parameter can be recorded as the parameter to be evaluated, and then a preset evaluation threshold is introduced. The evaluation threshold is a pre-set standard used to determine whether the degree of association between nodes has reached a certain level. The parameter to be evaluated is compared with the evaluation threshold to determine the association state between the 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 the two nodes. In this case, the two nodes are recorded as associated nodes, indicating that they are mutually influential 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 the two nodes. In this case, the two nodes are recorded as independent nodes, indicating that they are independent of each other in the power system and have no obvious mutual influence.

[0019] Step S103: determining the connection relationship between the nodes based on the associated nodes and the independent nodes, and constructing a network topology structure according to the connection relationship between the nodes.

[0020] In this step, after determining the connection relationship between each node, a network topology will be constructed based on the connection relationship between the nodes. The network topology will intuitively display the logical relationship between each node in the power system, providing convenience for subsequent analysis and management. The step of determining the connection relationship between each node based on associated nodes and independent nodes includes: Get the position relationship of all associated nodes and independent nodes; If the associated nodes are adjacent, the connection relationship between the adjacent associated nodes is defined as a direct connection; If the associated nodes are not adjacent, it is determined whether there is a common associated node between the associated nodes. If so, the common associated node is used as an intermediary to define an indirect connection relationship. Otherwise, it is defined as a non-connection relationship.

[0021] The connection relationship between independent nodes is directly defined as no connection relationship; 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 the connection relationship between them can be directly defined as a direct connection. Direct connection means that there is a direct path or relationship between the two nodes, and they can interact or transmit information without going 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 is a common associated node between the non-adjacent associated nodes. If there is a common associated node, then the common associated node can be used as an intermediary to define an indirect connection relationship. The 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 process that there is no common associated node between the non-adjacent associated nodes, then the connection relationship between them can be directly defined as a non-connected relationship, which means that there is no direct or indirect path or relationship between the two nodes, and they cannot interact or transmit information. As for independent nodes, since they are independent in definition, the connection relationship between them is directly defined as a non-connected relationship. There is no direct or indirect path or relationship between the independent nodes, and they cannot interact or transmit information.

[0022] Step S104: acquiring 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.

[0023] In this step, in order to ensure the accuracy and real-time performance 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 a normal state, each node can operate normally, while an abnormal state may include overload, failure, etc. At this time, the network topology needs to be adjusted accordingly to reflect the actual operation of the node, and the adjusted network topology is recorded as an updated topology. The step of monitoring the operating status of each node in real time includes: Obtain the load characteristic value of each node and record it as the parameter to be evaluated; Obtaining an evaluation threshold, and comparing 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 state of the corresponding node is recorded as an abnormal state; 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 a normal state; After the abnormal state is output, a monitoring period is constructed with the node where the abnormal state is issued as the starting node; If the parameter to be evaluated is greater than the evaluation threshold value during the monitoring period, an alarm signal is output and the determination result of the abnormal state is maintained; If the parameter to be evaluated is continuously less than or equal to the evaluation threshold value during 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 a normal state, and the determination result of the abnormal state is released.

[0024] If the parameter to be evaluated is less than or equal to the evaluation threshold, it indicates that the corresponding node is running normally, and the running state of the corresponding node is recorded as a normal state.

[0025] Specifically, in order to monitor the operating status of each node in real time, it is first necessary to obtain the load characteristic value of each node and the pre-set evaluation threshold. The evaluation threshold is set according to the standard of normal operation of the system and is used to determine whether the node is in a normal operating state. The evaluation threshold is compared with the previously recorded parameter to be evaluated. After the comparison, the judgment stage will be entered. If the parameter to be evaluated is greater than the evaluation threshold, it means that the operating status of the node exceeds the normal range and there may be an abnormal situation. In this case, the operating status of the corresponding node is recorded as a normal state. On the contrary, if the parameter to be evaluated is less than or equal to the evaluation threshold, it indicates that the operating status of the corresponding node is within the normal range and no abnormal situation occurs. In this case, the operating status of the corresponding node is recorded as a normal state. In addition, after the abnormal state is output, in order to ensure the accuracy of the judgment result, the node that issues the abnormal state will be used as the starting node. Point, construct a monitoring period, the length of the monitoring period can be set according to the actual situation to ensure that the operation status change of the node can be accurately captured. During the monitoring period, the load characteristic value of the node will be continuously obtained and compared with the evaluation threshold. If the parameter to be evaluated is continuously greater than the evaluation threshold during the monitoring period, an alarm signal will be output and the judgment result of the abnormal state will be maintained. At this time, the operator needs to take corresponding measures immediately to inspect and repair the abnormal node to avoid possible failures or accidents. If the parameter to be evaluated is continuously less than or equal to the evaluation threshold during the monitoring period, it can be judged that the operation abnormality of the node may be caused by instantaneous fluctuations. At this time, the operation status of the corresponding node will be restored to a normal state, and the judgment result of the abnormal state will be released. In addition, the network topology structure is adjusted according to the operation status of each node to obtain the steps of updating the topology structure, including: Obtain the running status of each node, extract the nodes with abnormal running status, and synchronously mark them as abnormal nodes; Obtain 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 directly connected, it means that the network topology 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 failure 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 failure points in the network topology, and the connection relationship between the nodes to be evaluated should be adjusted; Specifically, in order to ensure the stability and reliability of the network, it is necessary to dynamically adjust the network topology according to the operating status of each node. First, extract the nodes in the abnormal state and mark them as abnormal nodes synchronously. Secondly, obtain the nodes marked as abnormal nodes in the network topology at the same time 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 expressed as direct connections, then it can be considered that the current network topology is normal and there is no need to adjust. However, if the association relationship between the nodes to be evaluated is expressed as an indirect connection, it indicates that there may be potential failure points in the network topology, 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 that the information can be transmitted smoothly. If the nodes to be evaluated are independent nodes without any association relationship, this also indicates that there may be potential failure points in the network topology. In this case, it is also necessary to adjust the connection relationship between these independent nodes to ensure the integrity and reliability of the network.

[0026] Step S105: verify the updated topology structure, and after the updated topology structure passes the verification, store the updated network topology structure in a database.

[0027] 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. The step of verifying the updated topology structure includes: Obtain the updated topology structure, and compare and analyze it with the original network topology structure to obtain the updated nodes; Constructing a verification period, and counting the number of occurrences of the update node within the verification period, and recording it as a verification condition parameter; Obtaining a verification threshold, and comparing the verification threshold with a verification condition parameter; If the verification condition parameter is greater than the verification threshold, it indicates that the updated node is effectively updated 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 invalidly updated, and the original node in the original network topology structure is retained in the updated topology structure; When counting the number of occurrences of the update nodes, update nodes caused by abnormal states caused by instantaneous fluctuations are eliminated.

[0028] Specifically, in the process of updating the network topology, it is very important to ensure the correctness and effectiveness of the update. First, it is necessary to obtain the updated topology. After obtaining the updated topology, it will be compared and analyzed with the original network topology. 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, a verification period needs to be constructed. The verification period refers to the time range for observing and analyzing the update nodes within a specific time period. During the verification period, the number of concurrent occurrences of the update nodes will be counted and recorded as verification condition parameters. Here, it should be noted that when counting the number of concurrent occurrences of the update nodes, those update nodes caused by abnormal conditions caused by instantaneous fluctuations are eliminated, because they only temporarily deviate from the normal state and do not represent real changes in the network topology. In order to further ensure more The new validity requires the introduction of a preset verification threshold. The verification threshold is a pre-set standard value used to determine whether the updated node meets the expected update conditions. Specifically, the verification threshold is compared with the verification condition parameters obtained by previous statistics. Through this comparison, it can be determined whether the updated node meets the update standard. If the verification condition parameter is greater than the verification threshold, it means that the number of times the updated node occurs within the specified verification period exceeds the preset standard. In this case, the updated node can be considered valid and should be retained in the updated topology. On the contrary, if the verification condition parameter is less than or equal to the verification threshold, it means that the number of times the updated node occurs does not meet the expected standard. In this case, the updated node is considered invalid. Therefore, the original nodes in the original network topology should be retained and retained in the updated update topology to avoid accidental updates affecting the stability of the network topology.

[0029] In summary, the method 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 the dynamic adjustment of the power network to ensure the continuity and safety of power supply. In addition, the present invention can also reduce manual intervention, reduce 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.

[0030] See also Figure 2 , which shows a structural block diagram of an automatic identification system for power system network topology of the present application.

[0031] like Figure 2 As shown, the power system network topology automatic identification system 200 includes an acquisition module 210 , an analysis module 220 , a construction module 230 , an adjustment module 240 and a verification module 250 .

[0032] Among them, the acquisition module 210 is configured to acquire the power information of each node in the power system, wherein 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, and 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 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; the verification module 250 is configured to verify the updated topology structure, and after the updated topology structure passes the verification, the updated network topology structure is stored in the database.

[0033] It should be understood that Figure 2 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects are also applicable to Figure 2 The modules in it will not be described in detail here.

[0034] In some other embodiments, the embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor is caused to execute the method for automatically identifying the power system network topology in any of the above method embodiments; As an implementation mode, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows: Acquire power information of each node in the power system, wherein the power information includes voltage parameters, current parameters and power parameters; Analyzing the correlation between the nodes according to the power information of the nodes to obtain the associated nodes and independent nodes in the power system; Determine the connection relationship between the nodes based on the associated nodes and the independent nodes, and construct a network topology structure according to the connection relationship between the nodes; Acquiring 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; The updated topology structure is verified, and after the updated topology structure passes the verification, the updated network topology structure is stored in a database.

[0035] The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the power system network topology automatic identification 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 disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the power system network topology automatic identification system via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0036] Figure 3 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Figure 3 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also 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 may be connected via a bus or other means. Figure 3 The example of the connection via bus is taken. 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 the non-volatile software programs, instructions and modules stored in the memory 320, that is, the method for automatically identifying the network topology of the power system in the above-mentioned method embodiment is realized. The input device 330 can receive input digital or character information, and generate key signal input related to user settings and function control of the automatic identification system of the power system network topology. The output device 340 may include display devices such as display screens.

[0037] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0038] As an implementation mode, the electronic device is applied to a power system network topology automatic identification system, and is used for a client, and includes: at least one processor; and a memory connected to the at least one processor in communication; wherein 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: Acquire power information of each node in the power system, wherein the power information includes voltage parameters, current parameters and power parameters; Analyzing the correlation between the nodes according to the power information of the nodes to obtain the associated nodes and independent nodes in the power system; Determine the connection relationship between the nodes based on the associated nodes and the independent nodes, and construct a network topology structure according to the connection relationship between the nodes; Acquiring 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; The updated topology structure is verified, and after the updated topology structure passes the verification, the updated network topology structure is stored in a database.

[0039] Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on such an understanding, the above technical solution can essentially or in other words be embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for 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 embodiment.

[0040] Finally, 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for automatically identifying power system network topology, characterized in that: include: Acquire power information of each node in the power system, wherein the power information includes voltage parameters, current parameters and power parameters; Analyzing the correlation between the nodes according to the power information of the nodes to obtain the associated nodes and independent nodes in the power system; Determine the connection relationship between the nodes based on the associated nodes and the independent nodes, and construct a network topology structure according to the connection relationship between the nodes; Acquiring 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; The updated topology structure is verified, and after the updated topology structure passes the verification, the updated network topology structure is stored in a database.

2. A method for automatically identifying power system network topology according to claim 1, characterized in that: Analyzing the correlation between the nodes according to the power information of the nodes to obtain the associated nodes and independent nodes in the power system includes: Obtain power information for each node and extract load characteristics of each node; Obtain a load characteristic value of each node, wherein the load characteristic value is an average load value of each node; The correlation coefficients between different nodes are calculated according to the load characteristic values, and the correlation between the nodes is determined according to the correlation coefficients to obtain the associated nodes and independent nodes in the power system.

3. A method for automatically identifying power system network topology according to claim 2, characterized in that: Determining the correlation between the nodes according to 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; Constructing a sample period, setting a plurality of sampling nodes within the sample period, and synchronously collecting precondition parameters corresponding to different nodes under each of the sampling nodes; Obtaining an associated measurement function, and inputting the precondition parameters under the same sampling node into the associated measurement function, and recording the output result of the associated measurement function as a transition condition parameter; Taking an average value of the transition condition parameter, and recording the average value of the transition condition parameter 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, it is determined that there is an association between the nodes, and the corresponding node is recorded as an associated node; When the parameter to be evaluated is less than the evaluation threshold, it is determined that there is no association between the nodes, and the corresponding nodes are recorded as independent nodes.

4. The method for automatically identifying power system network topology according to claim 1, characterized in that: The determining of the connection relationship between the nodes based on the associated nodes and the independent nodes includes: Obtaining the positional relationship between all the associated nodes and the independent nodes; If two associated nodes are adjacent, the connection relationship between the two adjacent associated nodes is defined as a direct connection; If two associated nodes are not adjacent, it is determined whether there is a common associated node between the two associated nodes. If so, the common associated node is used as an intermediary to define an indirect connection relationship. Otherwise, it is defined as a non-connection relationship. The connection relationship between independent nodes is directly defined as a non-connected relationship.

5. The method for automatically identifying power system network topology according to claim 1, characterized in that: The obtaining of the real-time running status of each node includes: Obtain the load characteristic value of each node and record it as the parameter to be evaluated; Obtaining an evaluation threshold, and comparing 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 state of the corresponding node is recorded as an abnormal state; 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 a normal state; After the abnormal state is output, a monitoring period is constructed with the node where the abnormal state is issued as the starting node; If the parameter to be evaluated is greater than the evaluation threshold value during the monitoring period, an alarm signal is output and the determination result of the abnormal state is maintained; If the parameter to be evaluated is continuously less than or equal to the evaluation threshold value during 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 a normal state, and the determination result of the abnormal state is released.

6. The method for automatically identifying power system network topology according to claim 1, characterized in that: The adjusting the network topology structure according to the real-time operating status of each node to obtain an updated topology structure includes: Obtaining the operating status of each node, extracting the nodes with abnormal operating status, and synchronously marking them as abnormal nodes; Obtain 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 is normal and does not need to be adjusted; If the nodes to be evaluated are associated nodes, and the association relationship is an indirect connection relationship, it indicates that there is a potential failure point 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 failure points in the network topology structure, and the connection relationship between the nodes to be evaluated is adjusted.

7. The method for automatically identifying power system network topology according to claim 1, characterized in that: The verifying process of the updated topology structure comprises: Obtain the updated topology structure, and compare and analyze it with the original network topology structure to obtain the updated nodes; Constructing a verification period, and counting the number of occurrences of the update node within the verification period, and recording it as a verification condition parameter; Obtaining a verification threshold, and comparing the verification threshold with a verification condition parameter; If the verification condition parameter is greater than the verification threshold, it indicates that the updated node is effectively updated 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 invalidly updated, and the original node in the original network topology structure is retained in the updated topology structure; When counting the number of occurrences of the update nodes, update nodes caused by abnormal states caused by instantaneous fluctuations are eliminated.

8. An automatic identification system for power system network topology, characterized in that: include: An acquisition module, configured to acquire power information of each node in the power system, wherein the power information includes voltage parameters, current parameters and power parameters; An analysis module, configured to analyze the correlation between the nodes according to the power information of the nodes, and obtain the associated nodes and independent nodes in the power system; A construction module, configured to determine a connection relationship between each node based on the associated node and the independent node, and to construct a network topology structure according to the connection relationship between each node; An adjustment module is configured to 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; The verification module is configured to perform verification processing on the updated topology structure, and after the updated topology structure passes the verification, store the updated network topology structure in a database.

9. An electronic device, characterized in that: include: 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 described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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