Checking method of power grid digital design model

Abstract

The invention relates to the technical field of power grid digital checking, in particular to a checking method of a power grid digital design model, which comprises the following steps: S1, acquiring an initial parameter set of a to-be-checked power grid model; s2, performing data standardization processing on the initial parameter set; s3, constructing a three-dimensional topology verification model, and identifying abnormal nodes by using a spatial topology constraint algorithm; s4, mapping the real-time operation data to the three-dimensional topology verification model, and generating a dynamic parameter comparison matrix; s5, executing multi-dimensional check analysis, and generating a multi-dimensional difference report; s6, performing parameter replacement or topology reconstruction on the abnormal nodes, and outputting a final check result; according to the method, various power grid parameters are standardized in a unified manner, the accurate three-dimensional topology verification model is constructed, and automatic identification and quantitative correction of abnormal nodes are realized in combination with real-time data, so that the verification accuracy and operation reliability of the power grid model are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid digitalization checking, in particular to a checking method of a power grid digitalization design model. BACKGROUND

[0002] In the process of power grid digitalization construction, accurate checking and real-time monitoring of the power grid model is a key link to improve the safety of power grid operation and the efficiency of optimal dispatching; in the prior art, the power grid model usually only focuses on single-dimensional data representation, lacks multi-dimensional fusion of topological structure, electrical parameters and geographical environment parameters, resulting in deviation between the model and the actual operating conditions; in addition, the traditional checking method mainly uses single mathematical simulation or static comparison method, which cannot dynamically check massive real-time data, and cannot fully reflect the complexity and multi-factor influence of the power grid system operation, thereby reducing the accuracy and reliability of the power grid digitalization design model.

[0003] Based on the above background, the prior art still has multiple bottlenecks in the checking and correction of the power grid digitalization design model, mainly manifested as the lack of a mechanism for uniformly standardizing various parameter sets, and the difficulty in efficiently identifying and correcting abnormal topological nodes; if the topological structure, electrical parameters and geographical environment parameters cannot be uniformly integrated and dynamically fused, the coupling matching degree between multiple dimensions cannot be accurately calculated, and abnormal nodes cannot be effectively corrected according to real-time data; such defects cause differences between the power grid operating environment and the model, thereby affecting the safe and stable operation of the power grid and the dispatching efficiency. Based on this demand, a checking method of a power grid digitalization design model is proposed to solve the above problems. SUMMARY

[0004] Based on the above purpose, the present application provides a checking method of a power grid digitalization design model.

[0005] The checking method of the power grid digitalization design model comprises the following steps: S1: obtaining an initial parameter set of a power grid model to be checked, including a topological structure parameter set, an electrical parameter set and a geographical environment parameter set; S2: performing data standardization processing on the initial parameter set to generate a standardized data pool in a unified format; S3: constructing a three-dimensional topological checking model based on the standardized data pool, and identifying abnormal nodes by using a spatial topological constraint algorithm to generate an abnormal list containing topological abnormal coordinates and parameter deviation values; S4: accessing real-time operating data stream of the power grid, and mapping the real-time operating data to the three-dimensional topological checking model by using a dynamic data fusion engine to generate a dynamic parameter comparison matrix; S5: Perform multi-dimensional checking analysis, calculate the coupling matching degree between the topology structure parameter set, the electrical parameter set, and the geographical environment parameter set based on the dynamic parameter comparison matrix, and generate a multi-dimensional difference report; S6: Trigger the automatic correction module according to the multi-dimensional difference report, perform parameter replacement or topology reconstruction on the abnormal node, and output the final checking result.

[0006] Through the standardization processing of the initial parameter set of the power grid, the construction of the three-dimensional topology checking model based on the graph data structure, and the real-time checking of each node in the model by using the spatial topology constraint algorithm, the consistency of the data format and dimension between the topology structure, the electrical parameters and the geographical environment parameters is realized; The method maps the real-time power grid operation data to the three-dimensional model through the dynamic data fusion engine, constructs an accurate dynamic parameter comparison matrix, and can accurately calculate the spatial distance and parameter deviation between nodes, identify abnormal nodes in time and generate detailed multi-dimensional difference reports.

[0007] Optionally, the S1 specifically includes: S11: Obtain the topology structure data of the power grid through the data acquisition device, including the connection relationship of each node of the power grid, the location of the substation, the distribution information of the power transmission line, and collect and preliminarily integrate the data to form a topology structure parameter set; S12: Obtain the electrical parameter data of each device of the power grid by using the electrical measuring instrument, including voltage, current, power factor and load rate data, collect and summarize in real time through the sensor network to form an electrical parameter set; S13: Obtain the geographical environment data of the power grid operation area through remote sensing technology and geographic information system, including terrain, climate condition and soil property parameters, and convert them into numerical data form to generate a geographical environment parameter set; S14: Form the initial parameter set of the power grid model to be checked by the topology structure parameter set, the electrical parameter set and the geographical environment parameter set.

[0008] Optionally, the S2 specifically includes: S21: Perform data cleaning on the topology structure parameter set, extract node numbers and connection relationships by using regular expression pattern matching, eliminate duplicate records and illegal characters, and generate a cleaned topology structure parameter set; S22: Perform coordinate conversion processing on the geographical environment parameter set, convert discrete geographical coordinates into three-dimensional grid coordinates, and output a standardized three-dimensional coordinate set; S23: Perform unit system unification processing on the electrical parameter set, convert voltage, current and impedance parameters into dimensionless values respectively, and generate a dimensionless electrical parameter set; S24: Align the cleaned topology parameter set, the standardized three-dimensional coordinate set and the dimensionless electrical parameter set in time and space, and finally generate a standardized data pool.

[0009] Optionally, the S3 specifically comprises: S31: extracting the topological connection relationship, three-dimensional spatial coordinates and dimensionless electrical parameters from the standardized data pool, and reconstructing the power grid three-dimensional topological verification model by using the modeling method based on the graph data structure, wherein each node in the model corresponds to a power grid device, and the edge corresponds to the connection relationship between the devices; S32: checking the three-dimensional topological verification model by using the spatial topological constraint algorithm, and calculating the topological parameter deviation according to the position of each node in the three-dimensional space and the connection relationship between the adjacent nodes; S33: implementing abnormal marking on the node whose topological parameter deviation exceeds the predetermined tolerance threshold, determining the unique identification and corresponding three-dimensional spatial coordinates of the node, and recording the abnormal marking information; S34: summarizing the node information after the abnormal marking, including the unique identification, three-dimensional spatial coordinates and parameter deviation data of the abnormal node, and generating an abnormal list containing the topological abnormal coordinates and parameter deviation values.

[0010] Optionally, the S31 specifically comprises: S311: extracting the topological connection relationship, standardized three-dimensional spatial coordinates and dimensionless electrical parameters from the standardized data pool, and constructing a node set according to the power grid device information ; S312: constructing an edge set according to the topological connection relationship ; S313: constructing a weighted edge matrix , which is defined as follows: when the node has a direct connection relationship with the node , a weight value is assigned; when the node does not have a direct connection relationship with the node , a weight value is assigned; S314: constructing a graph data structure by using the node set , the edge set and the weighted edge matrix , wherein the graph data structure constitutes the power grid three-dimensional topological verification model; S315: assigning electrical properties to each node in the graph data structure , and calculating the electrical coupling index of the node ; ​​​S316: integrate the spatial position information and the electrical coupling index of each node in the graph data structure into the model as node attributes to form a complete power grid three-dimensional topology verification model.

[0011] Optionally, the S32 specifically includes: S321: extract the standardized three-dimensional spatial coordinates of each node from the graph data structure The actual spatial distance is calculated by using the following formula ; S322: determine the ideal spatial distance of each pair of directly connected nodes according to the preset power grid design standard , and calculate the distance deviation between nodes ; S323: compare the calculated with the preset spatial tolerance threshold , and determine that the connection relationship exists topology abnormality when is greater than ; S324: calculate the average distance deviation between each node and all directly connected nodes , and the formula is: , wherein represents the node set directly connected to the node , and is the number of nodes in the set; when is greater than the preset threshold , it is determined that the node exists topology abnormality.

[0012] Optionally, the S4 specifically includes: S41: access the real-time operation data stream of the power grid, obtain real-time electrical parameters including real-time voltage, real-time current, real-time power and real-time load rate from the power dispatching system, intelligent substation and various online monitoring equipment, and synchronize and align according to the time stamp; S42: perform unit normalization processing on the accessed real-time electrical parameters to ensure that the data format is consistent with the standardized data in the three-dimensional topology verification model; S43: based on the topology relationship of each node in the three-dimensional topology verification model, use a dynamic data fusion engine to match the normalized real-time electrical parameters with the topology structure parameter set to form a node electrical state vector; S44: construct a dynamic parameter comparison matrix ​​​Specifically, the electrical state vectors of all nodes are integrated into a matrix, with each row of the matrix corresponding to the real-time electrical parameter status of a node.

[0013] Optionally, S5 specifically includes: S51: Extract the baseline parameters of each parameter set from the standardized data pool. The baseline parameters include the baseline values ​​of topology parameters, electrical parameters, and geographical environment parameters, and match them with the real-time parameter data corresponding to each node in the dynamic parameter comparison matrix. S52: For each node and parameter categories Calculate the difference index between real-time parameters and baseline parameters ; S53: Calculate the overall matching degree of each parameter set using a weighted average method. The formula is: ,in, For nodes The weight, This represents the total number of nodes in the power grid model. For parameter set Maximum allowable difference value, For parameter set The degree of coupling matching; S54: Calculate the comprehensive coupling matching degree based on the overall matching degree of each parameter set. The calculation formula is: ,in, and The preset coupling weight coefficients are given, and they satisfy the following conditions: ; S55: Generate a structured, multi-dimensional difference report based on the difference indicators of each node, the overall matching degree of each parameter set, and the comprehensive coupling matching degree.

[0014] Optionally, S6 specifically includes: S61: Receive multi-dimensional difference reports, analyze the parameter deviation data of each abnormal node in the report, determine whether each parameter index in the abnormal node exceeds the preset tolerance threshold, and determine the set of nodes to be corrected. S62: Trigger the automatic correction module and classify each abnormal node into abnormal nodes that need parameter replacement and abnormal nodes that need topology reconstruction based on the degree of deviation of each abnormal node. S63: Perform automatic parameter correction for anomalous nodes belonging to the parameter replacement category, for each anomalous node. Based on its set of direct adjacent nodes The original parameter values ​​of each node are weighted and averaged to determine the corrected parameter values. ; S64: the abnormal node belonging to the topology reconfiguration category is re-planned with a local reconfiguration algorithm to re-plan its connection relationship in the three-dimensional topology checking model, the local reconfiguration is performed in the abnormal node and a set of directly adjacent nodes to construct a local edge set , and the iteration adjustment is performed with the minimum cost function as the target; S65: the updated data after the parameter replacement and topology reconfiguration are fed back to the three-dimensional topology checking model, the parameters and connection relationship of the abnormal node are corrected, and a final checking result report containing the parameter data, connection relationship and correction operation record of each node before and after correction is generated.

[0015] Optionally, the S62 specifically comprises: S621: extracting the parameter deviation value and the topology structure deviation value of each abnormal node from the multi-dimensional difference report ; S622: setting the parameter deviation threshold value and the topology deviation threshold value , and classifying according to the following decision rules: when and , the node is classified as an abnormal node needing topology reconfiguration; when and , the node is classified as an abnormal node needing parameter replacement; when and , the node is classified as a comprehensive abnormal node, and parameter replacement and topology reconfiguration need to be performed simultaneously; S623: storing the classification result in the abnormal node classification table, and generating a classification report.

[0016] By triggering the automatic correction module based on the multi-dimensional difference report, the parameter replacement and topology reconfiguration are combined to accurately correct the abnormal node; the quantitative correction is realized through weighted average calculation and local reconfiguration cost function according to the parameter deviation value and the topology deviation value of each abnormal node, so that the corrected data is highly matched with the design standard.

[0017] The application realizes the unification of data format and dimension between the topological structure, electrical parameters and geographical environment parameters by the standardized processing of the initial parameter set of the power grid, the construction of the three-dimensional topological verification model based on the graph data structure and the real-time checking of each node in the model by using the spatial topological constraint algorithm; the method maps the real-time power grid operation data to the three-dimensional model through the dynamic data fusion engine, constructs an accurate dynamic parameter comparison matrix, and can accurately calculate the spatial distance and parameter deviation between nodes, identify abnormal nodes in time and generate a detailed multi-dimensional difference report.

[0018] The application triggers the automatic correction module based on the multi-dimensional difference report, accurately corrects the abnormal nodes by combining parameter replacement and topological reconstruction, realizes quantitative correction through weighted average calculation and local reconstruction cost function according to the parameter deviation value and topological deviation value of each abnormal node, and ensures that the corrected data is highly matched with the design standard. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only illustrate the application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0020] Fig. 1 The figure is a power grid digital design model checking method of the embodiment of the application. Fig. 2 The figure is a generation of abnormal list flow process of the embodiment of the application. DETAILED DESCRIPTION

[0021] The application will be described in detail below in combination with the drawings and specific embodiments. It should be noted that in order to make the embodiments more detailed, the following embodiments are the best, preferred embodiments, and other alternative ways can also be used by those skilled in the art to implement; and the drawings are only used to more specifically describe the embodiments, and are not intended to specifically limit the application.

[0022] It should be noted that in the specification, “one embodiment”, “embodiment”, “exemplary embodiment”, “some embodiments” and the like indicate that the described embodiments can include specific features, structures or characteristics, but not necessarily every embodiment includes the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in combination with an embodiment, it should be within the knowledge of those skilled in the art to realize this feature, structure or characteristic in combination with other embodiments (whether or not explicitly described).

[0023] Generally, terms can be understood at least partly from their use in context. For example, depending at least partly on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in a singular sense, or a combination of features, structures, or characteristics in a plural sense. Additionally, the term "based on" can be understood not necessarily to convey an exclusive set of factors, but rather, alternatively, depending at least partly on the context, to allow for the presence of other factors that are not necessarily explicitly described.

[0024] like Figs. 1-2 As shown, the verification method for the digital design model of the power grid includes the following steps: S1: Obtain the initial parameter set of the power grid model to be checked, including the topology parameter set, electrical parameter set, and geographical environment parameter set; S2: Perform data standardization on the initial parameter set to generate a standardized data pool with a unified format; S3: Construct a three-dimensional topology verification model based on a standardized data pool, and use a spatial topology constraint algorithm to identify abnormal nodes and generate an anomaly list containing topology anomaly coordinates and parameter deviation values. S4: Access the real-time operation data stream of the power grid, and map the real-time operation data to the three-dimensional topology verification model through the dynamic data fusion engine to generate a dynamic parameter comparison matrix; S5: Perform multi-dimensional verification analysis, calculate the coupling matching degree between the topology parameter set, electrical parameter set, and geographical environment parameter set based on the dynamic parameter comparison matrix, and generate a multi-dimensional difference report; S6: Trigger the automatic correction module based on the multi-dimensional difference report to perform parameter replacement or topology reconstruction on abnormal nodes and output the final verification result.

[0025] S1 specifically includes: S11: Acquire the topology data of the power grid through data acquisition equipment, including the nodes of the power grid and their connection relationships, the location of substations, and the distribution information of transmission lines. The collected data is then preliminarily integrated and processed to form a set of topology parameters. S12: Use electrical measuring instruments to acquire electrical parameter data of various devices in the power grid, including voltage, current, power factor and load rate data, collect and summarize them in real time through sensor network to form electrical parameter set; S13: Obtain geographic environmental data of the power grid operation area through remote sensing technology and geographic information system (GIS), including topography, climate conditions and soil property parameters, and convert them into numerical data to generate a set of geographic environmental parameters; S14: Form the initial parameter set of the power grid model to be verified by combining the topological structure parameter set, electrical parameter set, and geographical environment parameter set, ensuring the interoperability and compatibility of the data in each parameter set. By standardizing the detailed acquisition steps of the initial parameter set of the power grid model to be verified, the accuracy and consistency of various parameter data can be ensured, further providing reliable basic data for subsequent verification and optimization, and improving the accuracy and efficiency of verification analysis.

[0026] S2 specifically includes: S21: Perform data cleaning on the topological structure parameter set, extract node numbers and connection relationships using regular expression pattern matching, remove duplicate records and illegal characters, and generate the cleaned topological structure parameter set. S22: Perform coordinate conversion on the geographical environment parameter set, convert discrete geographical coordinates to three-dimensional grid coordinates, and output the standardized three-dimensional coordinate set. The conversion formula is: , where is the axis coordinate value in the standardized three-dimensional grid coordinate system, is the central meridian offset; is the radius of curvature of the prime vertical; is the scale factor; is the radian value of the longitude difference; is the latitude value of the coordinate to be converted; ; is the second eccentricity; S23: Perform unit system unification on the electrical parameter set, convert voltage, current, and impedance parameters to per-unit values respectively, and generate a dimensionless electrical parameter set. The conversion rules are: ; where is the actually measured impedance value; is the base impedance value; is the base voltage; is the base capacity; S24: Align the cleaned topological parameter set, standardized three-dimensional coordinate set, and dimensionless electrical parameter set in time and space, and finally generate a standardized data pool. The above steps ensure the consistency of various parameter data in format, dimension, and spatial dimension through data cleaning, coordinate conversion, and unit unification, significantly improving the accuracy of data time and space alignment and the reliability and accuracy of subsequent model verification.

[0027] S3 specifically includes: S31: Extract the topological connection relationship, three-dimensional space coordinates, and per-unit electrical parameters from the standardized data pool, and reconstruct the three-dimensional topological verification model of the power grid using a graph data structure-based modeling method, where each node in the model corresponds to a power grid device and each edge corresponds to the connection relationship between devices. S32: The spatial topology constraint algorithm is used to verify the three-dimensional topology verification model. The deviation of topology parameters is calculated based on the position of each node in the three-dimensional space and its connection relationship with adjacent nodes. S33: Mark nodes whose topology parameter deviations exceed the predetermined tolerance threshold, determine their unique identifier and corresponding three-dimensional spatial coordinates, and record the anomaly marking information; S34: Summarize the node information after anomaly marking, including the unique identifier of the anomaly node, its three-dimensional spatial coordinates and parameter deviation data, and generate an anomaly list containing topological anomaly coordinates and parameter deviation values, providing data basis for the subsequent automatic correction module; The above steps utilize a standardized data pool to construct a three-dimensional topology verification model and use a spatial topology constraint algorithm to verify each node in the model, which can accurately identify anomaly nodes in the topology structure and improve the accuracy and reliability of the verification of the digital design model of the power grid.

[0028] S31 specifically includes: S311: Extract topological connectivity, standardized 3D spatial coordinates, and per-unit electrical parameters from the standardized data pool, and construct a node set based on power grid equipment information. Each node in the set corresponds to a power grid device. S312: Construct an edge set based on topological connectivity. Connect the corresponding nodes pairwise according to their direct connection relationships, and for each pair of directly connected nodes... and Calculate its spatial distance using three-dimensional coordinates The calculation formula is: ,in, and For nodes Coordinate values ​​in a standardized three-dimensional coordinate system and For nodes Coordinate values ​​in a standardized three-dimensional coordinate system For nodes With nodes The Euclidean distance between them; S313: Construct the weighted edge matrix Defined as: when node With nodes When a direct connection exists, assign a weight. When node With nodes When no direct connection exists, assign weights. ; S314: Set the nodes edge set and weighted edge matrix Graph data structure The data structure of this diagram constitutes the three-dimensional topology verification model of the power grid; S315: Graph Data Structures Each node is assigned electrical properties, and the node electrical coupling index is calculated. The formula is: ,in, For nodes The electrical coupling index; and They are nodes and nodes The per-unit impedance value; Represents nodes The set of directly connected nodes; This represents the number of nodes in the set. S316: Graph data structure The spatial location information and electrical coupling index of each node are integrated into the model as node attributes to form a complete three-dimensional topology verification model of the power grid, providing accurate data support for subsequent identification of abnormal nodes using spatial topology constraint algorithms.

[0029] S32 specifically includes: S321: From graph data structures Extract the standardized 3D spatial coordinates of each node, and for each pair of directly connected nodes... and Calculate the actual spatial distance using the following formula The formula is: ,in, and For nodes Coordinate values ​​in a standardized three-dimensional coordinate system and For nodes Coordinate values ​​in a standardized three-dimensional coordinate system; S322: Determine the ideal spatial distance for each pair of directly connected nodes based on the preset power grid design standards. And calculate the distance deviation between nodes. The formula is: ,in, For nodes With nodes Distance deviation between; S323: Calculated by comparing each side pair With respect to the preset space tolerance threshold ,when Greater than When determining if there is a topological anomaly in the connection relationship: S324: For each node Calculate the average distance deviation between it and all directly connected nodes. The formula is: ,in, Represents nodes The set of directly connected nodes. The number of nodes in the set; when Greater than the preset threshold Time-determined node There are topological anomalies; the above steps verify the three-dimensional topology verification model by using a spatial topology constraint algorithm, which can accurately calculate the spatial distance deviation between each node and determine the topology anomalies based on the preset tolerance threshold, thereby achieving accurate identification and marking of abnormal nodes.

[0030] S4 specifically includes: S41: Access to real-time grid operation data stream, acquiring real-time electrical parameters, including real-time voltage, from power dispatching systems, smart substations, and various online monitoring devices. Real-time current Real-time power and real-time load rate And synchronize and align according to timestamps; S42: Perform unit normalization on the connected real-time electrical parameters to ensure that their data format is consistent with the standardized data in the three-dimensional topology verification model. The normalization calculation formula is: ,in, These are the normalized electrical parameter values. These are the electrical parameter values ​​collected in real time. and These are the minimum and maximum values ​​of the parameter in historical data, respectively; S43: Based on the topological relationships of each node in the 3D topology verification model, a dynamic data fusion engine is used to match the normalized real-time electrical parameters with the topology parameter set to form node electrical state vectors. , is represented as: ; S44: Constructing a dynamic parameter alignment matrix Specifically, the electrical state vectors of all nodes are integrated into a matrix, where each row corresponds to the real-time electrical parameter state of a node, and its expression is: , in, The above steps, by accessing the real-time operation data stream of the power grid and using a dynamic data fusion engine for normalization and topology matching, can construct an accurate dynamic parameter comparison matrix, providing high-precision real-time data support for subsequent verification analysis, thereby improving the timeliness and accuracy of the verification of the digital design model of the power grid.

[0031] S5 specifically includes: S51: Extract the baseline parameters of each parameter set from the standardized data pool. The baseline parameters include the baseline values ​​of topology parameters, electrical parameters, and geographical environment parameters, and match them with the real-time parameter data corresponding to each node in the dynamic parameter comparison matrix. S52: For each node and parameter categories (in (Representing topological, electrical, or geographic parameters respectively) Calculate the difference index between real-time parameters and baseline parameters. Its calculation formula is ,in, For nodes In parameter set Real-time normalized parameter values ​​in the data. For nodes In parameter set The reference parameter values ​​in; S53: Calculate the overall matching degree of each parameter set using a weighted average method. The formula is: ,in, For nodes The weight, This represents the total number of nodes in the power grid model. For parameter set Maximum allowable difference value, For parameter set The degree of coupling matching; S54: Calculate the comprehensive coupling matching degree based on the overall matching degree of each parameter set. The calculation formula is: ,in, and The preset coupling weight coefficients are given, and they satisfy the following conditions: ; S55: Based on the difference indicators of each node, the overall matching degree of each parameter set, and the comprehensive coupling matching degree, a structured multi-dimensional difference report is generated. Through the above steps, the calculation of multi-dimensional coupling matching degree based on the dynamic parameter comparison matrix is ​​realized, which can accurately assess the consistency between topology, electrical parameters and geographical environment parameters, and generate a structured multi-dimensional difference report, providing high-precision real-time data basis for the verification of the power grid digital design model.

[0032] S6 specifically includes: S61: Receive multi-dimensional difference reports, analyze the parameter deviation data of each abnormal node in the report, determine whether each parameter index in the abnormal node exceeds the preset tolerance threshold, and determine the set of nodes to be corrected. S62: Trigger the automatic correction module and classify each abnormal node into abnormal nodes that need parameter replacement and abnormal nodes that need topology reconstruction based on the degree of deviation of each abnormal node. S63: Perform automatic parameter correction for anomalous nodes belonging to the parameter replacement category, for each anomalous node. Based on its set of direct adjacent nodes The original parameter values ​​of each node are weighted and averaged to determine the corrected parameter values. The calculation formula is as follows: ,in, Represents a node The parameter value after parameter replacement; Represents a node The original parameter values; Represents a node With nodes The weighting coefficients between them are determined based on spatial distance and connection strength; Represents nodes The set of directly connected nodes; S64: For anomalous nodes belonging to the topology reconstruction category, a local reconstruction algorithm is used to re-plan their connectivity in the 3D topology verification model. Local reconstruction is performed on anomalous nodes... and its set of direct adjacent nodes Internal structure local edge set and minimize the cost function The cost function is calculated by iteratively adjusting the target: ,in, Represents a node With nodes The actual Euclidean distance between them; Represents a node With nodes The pre-defined ideal Euclidean distance between them; This represents the set of edges used for local topology reconstruction. S65: Feed the updated data after parameter replacement and topology reconstruction back to the three-dimensional topology verification model, correct the parameters and connections of abnormal nodes, and generate a final verification result report containing the parameter data, connection relationships, and correction operation records of each node before and after correction. The above steps trigger the automatic correction module based on the multi-dimensional difference report, and combine the weighted average formula and the local reconstruction cost function to perform parameter replacement and topology reconstruction on abnormal nodes, thereby achieving accurate optimization of the three-dimensional topology verification model of the power grid and ensuring the accuracy of the parameters and connections of each node.

[0033] S62 specifically includes: S621: Extract parameter deviation values ​​for each outlier node from the multi-dimensional difference report. and its topological deviation value ,in, Represents a node The parameter deviation value is defined as: ,in, Indicates the node in parameter category Real-time values ​​in (topology, electrical, and geographic environmental parameters) This indicates its corresponding baseline value; Represents a node The topological deviation value is defined as follows: ,in, Represents a node With nodes The actual Euclidean distance between them Represents a node With nodes The pre-defined ideal Euclidean distance between them; S622: Set parameter deviation threshold and topology deviation threshold And classified according to the following decision rules: when and At that time, the node These are classified as abnormal nodes that require topology refactoring. when and At that time, the node These are classified as abnormal nodes that require parameter replacement. when and At that time, the node This node is classified as a comprehensive anomaly and requires both parameter replacement and topology reconstruction to be performed simultaneously. S623: Store the classification results in the abnormal node classification table and generate a classification report to provide input data for the subsequent automatic correction module. The above steps, through quantitative calculation based on parameter deviation value and topology deviation value, and combined with the set threshold for classification, can effectively distinguish abnormal nodes that need to perform parameter replacement and topology reconstruction, improve the accuracy and automation of the verification method, and thus improve the efficiency and reliability of power grid topology data correction.

[0034] This invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. To provide the public with a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments; however, those skilled in the art will fully understand the invention even without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0035] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A verification method for a digital design model of a power grid, characterized in that, Includes the following steps: S1: Obtain the initial parameter set of the power grid model to be checked, including the topology parameter set, electrical parameter set, and geographical environment parameter set; S2: Perform data standardization on the initial parameter set to generate a standardized data pool with a unified format; S3: Construct a three-dimensional topology verification model based on a standardized data pool, and use a spatial topology constraint algorithm to identify abnormal nodes and generate an anomaly list containing topology anomaly coordinates and parameter deviation values. S4: Access the real-time operation data stream of the power grid, and map the real-time operation data to the three-dimensional topology verification model through the dynamic data fusion engine to generate a dynamic parameter comparison matrix; S5: Perform multi-dimensional verification analysis, calculate the coupling matching degree between the topology parameter set, electrical parameter set, and geographical environment parameter set based on the dynamic parameter comparison matrix, and generate a multi-dimensional difference report; S6: Trigger the automatic correction module based on the multi-dimensional difference report to perform parameter replacement or topology reconstruction on abnormal nodes and output the final verification result.

2. The verification method for the digital design model of the power grid according to claim 1, characterized in that, S1 specifically includes: S11: Acquire the topology data of the power grid through data acquisition equipment, including the nodes of the power grid and their connection relationships, the location of substations, and the distribution information of transmission lines. The collected data is then preliminarily integrated and processed to form a set of topology parameters. S12: Use electrical measuring instruments to acquire electrical parameter data of various devices in the power grid, including voltage, current, power factor and load rate data, collect and summarize them in real time through sensor network to form electrical parameter set; S13: Obtain geographic environmental data of the power grid operation area through remote sensing technology and geographic information system, including topography, climate conditions and soil property parameters, and convert them into numerical data to generate a set of geographic environmental parameters; S14: Combine the topology parameter set, electrical parameter set, and geographical environment parameter set to form the initial parameter set of the power grid model to be verified.

3. The verification method for the digital design model of the power grid according to claim 1, characterized in that, S2 specifically includes: S21: Perform data cleaning on the topology parameter set, use regular expression pattern matching to extract node numbers and connection relationships, remove duplicate records and illegal characters, and generate a cleaned topology parameter set; S22: Perform coordinate transformation on the set of geographic environmental parameters, converting discrete geographic coordinates into three-dimensional grid coordinates and outputting a standardized three-dimensional coordinate set; S23: Perform unit system standardization processing on the electrical parameter set, converting voltage, current, and impedance parameters into per-unit values ​​respectively, and generating a dimensionless electrical parameter set; S24: The cleaned topology parameter set, standardized three-dimensional coordinate set, and dimensionless electrical parameter set are spatiotemporally aligned to finally generate a standardized data pool.

4. The verification method for the digital design model of the power grid according to claim 1, characterized in that, S3 specifically includes: S31: Extract topological connectivity, three-dimensional spatial coordinates, and per-unit electrical parameters from the standardized data pool, and reconstruct the three-dimensional topological verification model of the power grid using a graph data structure-based modeling method. In the model, each node corresponds to a power grid device, and the edges correspond to the connection relationships between devices. S32: The spatial topology constraint algorithm is used to verify the three-dimensional topology verification model. The deviation of topology parameters is calculated based on the position of each node in the three-dimensional space and its connection relationship with adjacent nodes. S33: Mark nodes whose topology parameter deviations exceed the predetermined tolerance threshold, determine their unique identifier and corresponding three-dimensional spatial coordinates, and record the anomaly marking information; S34: Summarize the node information after anomaly marking, including the unique identifier of the anomaly node, its three-dimensional spatial coordinates and parameter deviation data, and generate an anomaly list containing topological anomaly coordinates and parameter deviation values.

5. The verification method for the digital design model of the power grid according to claim 4, characterized in that, S31 specifically includes: S311: Extract topological connectivity, standardized 3D spatial coordinates, and per-unit electrical parameters from the standardized data pool, and construct a node set based on power grid equipment information. Each node in the set corresponds to a power grid device. S312: Construct an edge set based on topological connectivity. Connect the corresponding nodes pairwise according to their direct connection relationships, and for each pair of directly connected nodes... and Calculate its spatial distance using three-dimensional coordinates ; S313: Construct the weighted edge matrix Defined as: when node With nodes When a direct connection exists, assign a weight. When node With nodes When no direct connection exists, assign weights. ; S314: Set the nodes edge set and weighted edge matrix Graph data structure The data structure of this diagram constitutes the three-dimensional topology verification model of the power grid; S315: Graph Data Structures Each node is assigned electrical properties, and the node electrical coupling index is calculated. ; S316: Graph data structure The spatial location information and electrical coupling index of each node are integrated into the model as node attributes to form a complete three-dimensional topology verification model of the power grid.

6. The verification method for the digital design model of the power grid according to claim 5, characterized in that, Specifically, S32 includes: S321: From graph data structures Extract the standardized 3D spatial coordinates of each node, and for each pair of directly connected nodes... and Calculate the actual spatial distance using the following formula ; S322: Determine the ideal spatial distance for each pair of directly connected nodes based on the preset power grid design standards. And calculate the distance deviation between nodes. ; S323: Calculated by comparing each side pair With respect to the preset space tolerance threshold ,when Greater than When determining if there is a topological anomaly in the connection relationship: S324: For each node Calculate the average distance deviation between it and all directly connected nodes. The formula is: ,in, Represents nodes The set of directly connected nodes. The number of nodes in the set; when Greater than the preset threshold Time-determined node A topological anomaly exists.

7. The verification method for the digital design model of the power grid according to claim 1, characterized in that, S4 specifically includes: S41: Access the real-time operation data stream of the power grid, obtain real-time electrical parameters from the power dispatching system, smart substations and various online monitoring equipment, including real-time voltage, real-time current, real-time power and real-time load rate, and synchronize them according to timestamps; S42: Perform unit normalization on the real-time electrical parameters connected to ensure that their data format is consistent with the standardized data in the three-dimensional topology verification model; S43: Based on the topological relationship of each node in the three-dimensional topology verification model, the normalized real-time electrical parameters are matched with the topology parameter set using a dynamic data fusion engine to form a node electrical state vector. S44: Constructing a dynamic parameter alignment matrix Specifically, the electrical state vectors of all nodes are integrated into a matrix, with each row of the matrix corresponding to the real-time electrical parameter status of a node.

8. The verification method for the digital design model of the power grid according to claim 1, characterized in that, S5 specifically includes: S51: Extract the baseline parameters of each parameter set from the standardized data pool. The baseline parameters include the baseline values ​​of topology parameters, electrical parameters, and geographical environment parameters, and match them with the real-time parameter data corresponding to each node in the dynamic parameter comparison matrix. S52: For each node and parameter categories Calculate the difference index between real-time parameters and baseline parameters ; S53: Calculate the overall matching degree of each parameter set using a weighted average method. The formula is: ,in, For nodes The weight, This represents the total number of nodes in the power grid model. For parameter set Maximum allowable difference value, For parameter set The degree of coupling matching; S54: Calculate the comprehensive coupling matching degree based on the overall matching degree of each parameter set. The calculation formula is: ,in, and The preset coupling weight coefficients are given, and they satisfy the following conditions: ; S55: Generate a structured, multi-dimensional difference report based on the difference indicators of each node, the overall matching degree of each parameter set, and the comprehensive coupling matching degree.

9. The verification method for the digital design model of the power grid according to claim 1, characterized in that, S6 specifically includes: S61: Receive multi-dimensional difference reports, analyze the parameter deviation data of each abnormal node in the report, determine whether each parameter index in the abnormal node exceeds the preset tolerance threshold, and determine the set of nodes to be corrected. S62: Trigger the automatic correction module and classify each abnormal node into abnormal nodes that need parameter replacement and abnormal nodes that need topology reconstruction based on the degree of deviation of each abnormal node. S63: Perform automatic parameter correction for anomalous nodes belonging to the parameter replacement category, for each anomalous node. Based on its set of direct adjacent nodes The original parameter values ​​of each node are weighted and averaged to determine the corrected parameter values. ; S64: For anomalous nodes belonging to the topology reconstruction category, a local reconstruction algorithm is used to re-plan their connectivity in the 3D topology verification model. Local reconstruction is performed on anomalous nodes... and its set of direct adjacent nodes Internal structure local edge set and minimize the cost function Iterative adjustments are made to achieve the target; S65: Feed the updated data after parameter replacement and topology reconstruction back to the 3D topology verification model, correct the parameters and connections of abnormal nodes, and generate a final verification result report containing the parameter data, connection relationships and correction operation records of each node before and after correction.

10. The verification method for the digital design model of the power grid according to claim 9, characterized in that, S62 specifically includes: S621: Extract parameter deviation values ​​for each outlier node from the multi-dimensional difference report. and its topological deviation value ; S622: Set parameter deviation threshold and topology deviation threshold And classified according to the following decision rules: when and At that time, the node These are classified as abnormal nodes that require topology refactoring. when and At that time, the node These are classified as abnormal nodes that require parameter replacement. when and At that time, the node This node is classified as a comprehensive anomaly and requires both parameter replacement and topology reconstruction to be performed simultaneously. S623: Store the classification results in the abnormal node classification table and generate a classification report.

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