Matrix simplification method applied to electromagnetic transient simulation and related device

Abstract

The invention discloses a matrix simplification method applied to electromagnetic transient simulation and a related device, and the method comprises the steps: converting a quantified component admittance matrix of a power system into a graph structure, obtaining a graph structure matrix, enabling nodes of the graph structure matrix to represent matrix rows or columns, and enabling edges of the graph structure matrix to represent a non-zero element connection relation; performing augmented path traversal search in the graph structure matrix based on a DFS algorithm, and recording a non-zero line sequence number and a non-zero column sequence number; reordering the graph structure matrix according to the non-zero row sequence number and the non-zero column sequence number to obtain a non-zero diagonal matrix; and performing path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element nodes based on a DFS algorithm, and performing non-zero row and column reordering operation to obtain a triangular block structure matrix. The technical problem of low electromagnetic transient simulation efficiency caused by the problems of high calculation complexity, lack of stability of numerical values, increase of matrix understanding difficulty, time consumption of calculation and the like in the prior art can be solved.

Description

Technical Field

[0001] The present application relates to the technical field of electromagnetic transient simulation, and in particular to a matrix simplification method and related devices applied to electromagnetic transient simulation. Background Art

[0002] In electromagnetic transient simulation and simulation experiments, matrix preprocessing is a key step to improve computational efficiency, stability, and accuracy. Electromagnetic transient simulation usually involves large sparse matrices or asymmetric matrices, and preprocessing methods help reduce computational complexity, improve numerical stability, and accelerate the convergence of iterative algorithms.

[0003] The existing preprocessing methods for complex matrices in the electromagnetic transient simulation process include operations such as row and column rearrangement, diagonal scaling, sparse matrix decomposition and sparse matrix compression. However, these current matrix processing methods still have problems such as high computational complexity, lack of numerical stability, increased difficulty in understanding matrices, and time-consuming calculations. These problems will directly affect the overall efficiency of electromagnetic transient simulation experiments, especially the simulation of large power systems. Summary of the invention

[0004] The present application provides a matrix simplification method and related devices for electromagnetic transient simulation, which are used to solve the technical problems of low efficiency of electromagnetic transient simulation caused by high computational complexity, lack of numerical stability, increased difficulty in matrix understanding and time-consuming calculation in the prior art.

[0005] In view of this, the first aspect of the present application provides a matrix simplification method applied to electromagnetic transient simulation, comprising:

[0006] Converting the component admittance matrix quantized by the power system into a graph structure to obtain a graph structure matrix, wherein the nodes of the graph structure matrix represent matrix rows or columns, and the edges of the graph structure matrix represent non-zero element connection relationships;

[0007] Based on the DFS algorithm, an augmented path traversal search is performed in the graph structure matrix, and non-zero row numbers and non-zero column numbers are recorded;

[0008] Reordering the graph structure matrix according to the non-zero row numbers and the non-zero column numbers to obtain a non-zero diagonal matrix;

[0009] Based on the DFS algorithm, a path traversal search is performed on the non-zero diagonal matrix along the main diagonal non-zero element nodes, and a non-zero row and column reordering operation is performed to obtain a triangular block structure matrix.

[0010] Preferably, performing augmented path traversal search in the graph structure matrix based on the DFS algorithm and recording non-zero row numbers and non-zero column numbers includes:

[0011] Searching for any non-zero element node in the graph structure matrix based on the DFS algorithm, and performing traversal query on adjacent non-zero element nodes starting from the non-zero element node until an augmenting path is generated;

[0012] All non-zero element nodes on the augmenting path are recorded, and non-zero row numbers and non-zero column numbers are generated.

[0013] Preferably, the DFS algorithm is used to perform a path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element nodes, and a non-zero row and column reordering operation is performed to obtain a triangular block structure matrix, including:

[0014] Based on the DFS algorithm, any main diagonal non-zero element node is selected in the non-zero diagonal matrix, a path traversal search is performed with the main diagonal non-zero element node as the starting point, and non-zero row and column numbers are recorded;

[0015] The non-zero rows and columns of the non-zero diagonal matrix are reordered according to the non-zero row and column numbers to generate a triangular block structure matrix.

[0016] Preferably, the method further comprises performing a path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element nodes based on the DFS algorithm, and performing a non-zero row and column reordering operation to obtain a triangular block structure matrix, and then further comprising:

[0017] Electromagnetic transient simulation calculation is performed based on the triangular block structure matrix to obtain simulation results.

[0018] The second aspect of the present application provides a matrix simplification device for electromagnetic transient simulation, comprising:

[0019] A graph conversion unit, used to convert the component admittance matrix of the power system quantization into a graph structure to obtain a graph structure matrix, wherein the nodes of the graph structure matrix represent matrix rows or columns, and the edges of the graph structure matrix represent non-zero element connection relationships;

[0020] An augmented search unit, used to perform augmented path traversal search in the graph structure matrix based on a DFS algorithm, and record non-zero row numbers and non-zero column numbers;

[0021] A non-zero sorting unit, used for re-sorting the graph structure matrix according to the non-zero row numbers and the non-zero column numbers to obtain a non-zero diagonal matrix;

[0022] The triangle simplification unit is used to perform a path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element nodes based on the DFS algorithm, and perform a non-zero row and column reordering operation to obtain a triangle block structure matrix.

[0023] Preferably, the augmented search unit is specifically used for:

[0024] Searching for any non-zero element node in the graph structure matrix based on the DFS algorithm, and performing traversal query on adjacent non-zero element nodes starting from the non-zero element node until an augmenting path is generated;

[0025] All non-zero element nodes on the augmenting path are recorded, and non-zero row numbers and non-zero column numbers are generated.

[0026] Preferably, the triangle simplification unit is specifically used for:

[0027] Based on the DFS algorithm, any main diagonal non-zero element node is selected in the non-zero diagonal matrix, a path traversal search is performed with the main diagonal non-zero element node as the starting point, and non-zero row and column numbers are recorded;

[0028] The non-zero rows and columns of the non-zero diagonal matrix are reordered according to the non-zero row and column numbers to generate a triangular block structure matrix.

[0029] Preferably, it also includes:

[0030] The simulation calculation unit is used to perform electromagnetic transient simulation calculation based on the triangular block structure matrix to obtain simulation results.

[0031] A third aspect of the present application provides a matrix simplification device for electromagnetic transient simulation, the device comprising a processor and a memory;

[0032] The memory is used to store program code and transmit the program code to the processor;

[0033] The processor is used to execute the matrix simplification method for electromagnetic transient simulation described in the first aspect according to the instructions in the program code.

[0034] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store program code, and the program code is used to execute the matrix simplification method for electromagnetic transient simulation described in the first aspect.

[0035] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0036] In the present application, a matrix simplification method for electromagnetic transient simulation is provided, including: converting the quantized component admittance matrix of the power system into a graph structure to obtain a graph structure matrix, wherein the nodes of the graph structure matrix represent matrix rows or columns, and the edges of the graph structure matrix represent non-zero element connection relationships; performing augmented path traversal search in the graph structure matrix based on a DFS algorithm, and recording non-zero row numbers and non-zero column numbers; reordering the graph structure matrix according to the non-zero row numbers and non-zero column numbers to obtain a non-zero diagonal matrix; performing path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element nodes based on the DFS algorithm, and performing non-zero row and column reordering operations to obtain a triangular block structure matrix.

[0037] The matrix simplification method for electromagnetic transient simulation provided by the present application uses the DFS algorithm to find the augmented path, which can quickly find the appropriate row and column ordering and reduce the calculation time; and the row and column rearrangement operation based on the row and column numbers of the augmented path can arrange the matrix so that the diagonal elements are all non-zero elements, which can avoid the situation where the determinant is zero in the subsequent calculation process, so the stability of the numerical calculation can be ensured; in addition, the entire matrix simplification process has no requirements on the complexity, sparsity, shape and size of the matrix, so this method can be applied to a variety of matrix calculation scenarios to meet more simulation application needs; furthermore, the triangular block structure matrix obtained by arrangement is easy to understand and analyze, and will not increase the complexity of matrix understanding. Therefore, the present application can solve the technical problems of the existing technology with high computational complexity, lack of numerical stability, increased difficulty in matrix understanding and time-consuming calculation, which lead to low efficiency of electromagnetic transient simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A schematic diagram of a flow chart of a matrix simplification method for electromagnetic transient simulation provided in an embodiment of the present application;

[0039] Figure 2 A schematic diagram of the structure of a matrix simplification device for electromagnetic transient simulation provided in an embodiment of the present application;

[0040] Figure 3 A schematic diagram of the relationship structure of power system simulation components provided in an embodiment of the present application;

[0041] Figure 4 This is an example diagram of the matrix sorting and block processing process provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0043] For easier understanding, see Figure 1 , an embodiment of a matrix simplification method for electromagnetic transient simulation provided by the present application includes:

[0044] Step 101: Convert the component admittance matrix of the power system quantized into a graph structure to obtain a graph structure matrix, wherein the nodes of the graph structure matrix represent matrix rows or columns, and the edges of the graph structure matrix represent non-zero element connection relationships.

[0045] See also Figure 3 ,in , , , Represents the admittance value of the simulation component abstracted from the power system equipment, and also represents each simulation component. This is a key parameter in the simulation analysis, used to quantify the conductivity of the component under voltage difference, the connection between components , , , Represents a voltage node. Therefore, the key to the simulation is to perform an admittance matrix conversion analysis on each simulation component of the power system. After the conversion, please refer to Table 1, where the non-diagonal positions reflect the negative admittance values ​​of the components connected to each other through these lines.

[0046] Table 1 Admittance conversion relationship between power system simulation components

[0047]

[0048] This embodiment simplifies the matrix in the simulation process, thereby reducing the complexity of the matrix and improving the efficiency of the simulation calculation. Before simplifying the matrix by taking the admittance matrix as an example, the matrix needs to be converted into a graph structure, in which nodes and edges are used to describe the relationship between elements, which can be clearer in the subsequent analysis process. The nodes in the graph structure matrix of this embodiment represent a row or a column in the matrix, and the edges represent the connection relationship between non-zero elements.

[0049] Step 102: perform augmented path traversal search in the graph structure matrix based on the DFS algorithm, and record non-zero row numbers and non-zero column numbers.

[0050] Further, step 102 includes:

[0051] Based on the DFS algorithm, find any non-zero element node in the graph structure matrix, and start from the non-zero element node to traverse and query the adjacent non-zero element nodes until an augmenting path is generated;

[0052] Record all non-zero element nodes on the augmenting path and generate non-zero row numbers and non-zero column numbers.

[0053] The DFS algorithm is an algorithm for traversing or searching a tree or graph. The algorithm traverses the nodes of the tree along the depth of the tree, searching the branches of the tree as deeply as possible. When all the edges where the node v is located have been explored, or the node does not meet the conditions during the search, the search will backtrack to the starting node of the edge where the node v was found. The whole process is repeated until all nodes have been visited.

[0054] Based on the DFS algorithm, you can find an arbitrary non-zero element node in the graph structure matrix, use this node as the starting point, and search for adjacent non-zero element nodes around it. If there is a non-zero element connected to the current node, such as node j, and node j has not been visited, DFS will continue searching along this edge. This means that the non-zero elements found in the matrix will form a "path". If the current path search cannot continue, DFS will backtrack to the previous node and try other paths. This process will be repeated until a complete augmenting path is found.

[0055] Once the augmenting path is found, it is necessary to record all non-zero element nodes on the augmenting path and generate non-zero row numbers and non-zero column numbers; these node rows / columns are the rows and columns that can move non-zero elements to the main diagonal position through row-column swaps. This process ensures the non-zero nature of the main diagonal elements of the matrix.

[0056] Step 103: reorder the graph structure matrix according to the non-zero row numbers and the non-zero column numbers to obtain a non-zero diagonal matrix.

[0057] The reordering process of the graph structure matrix is ​​actually to find the position of the non-zero elements of the matrix according to the serial number, and then adjust the matrix structure by simulating the exchange of rows and columns, and adjust the non-zero elements to the main diagonal to ensure the non-zero nature of the main diagonal.

[0058] Suppose that there is a non-zero element found in the i-th row, and the element is not on the main diagonal of the i-th row, but in other positions, such as the h-th column, and there is no non-zero element on the main diagonal position of the h-th column, then the h-th column can be exchanged with the column on the main diagonal of the i-th row, so that the non-zero element can be exchanged to the main diagonal. After multiple operations, a non-zero diagonal matrix can be obtained.

[0059] Step 104: Based on the DFS algorithm, a path traversal search is performed on the non-zero diagonal matrix along the non-zero element nodes of the main diagonal, and a non-zero row and column reordering operation is performed to obtain a triangular block structure matrix.

[0060] Furthermore, step 104 includes:

[0061] Based on the DFS algorithm, select any main diagonal non-zero element node in the non-zero diagonal matrix, perform path traversal search starting from the main diagonal non-zero element node, and record the non-zero row and column numbers;

[0062] The non-zero rows and columns of the non-zero diagonal matrix are reordered according to the non-zero row and column numbers to generate a triangular block structure matrix.

[0063] The purpose of using the DFS algorithm for traversal search here is to identify the interconnected non-zero elements in the non-zero diagonal matrix. When DFS starts from a non-zero element node on a main diagonal, it not only searches along a path, but also finds all non-zero nodes connected to the node through recursion. These nodes may be in the same row, the same column, or connected through other adjacent elements. Eventually, these non-zero nodes will be regarded as a "block"; after finding a block, it will return and continue to look for the next non-zero element node on the main diagonal that has not been visited, and find the next "block". In the found block, if there is a strongly connected component, it is necessary to rearrange the rows and columns of the matrix according to the non-zero row and column numbers in the strongly connected component; the purpose is to gather the non-zero element nodes of the strongly connected component together, that is, to gather the non-zero rows and columns together to form a smaller block structure. According to the numbers after multiple searches, a block-based rearrangement operation can be performed to generate a triangular block structure matrix. There may be multiple upper triangular blocks and lower triangular blocks in the matrix; at this point, the matrix simplification operation is completed. The triangular block structure matrix is ​​easy to understand, not complicated, fast in calculation speed, and high in processing efficiency.

[0064] See also Figure 4 , the leftmost matrix can be obtained after the column sorting operation of column numbers {1,5,4,3,2}. The order number is extracted from the augmented path of the search, which is the sorting result after the global search. In the matrix obtained after sorting, the first column corresponds to the first column in the original matrix, the second column corresponds to the fifth column in the original matrix, and so on, to obtain the matrix in the middle of the figure. In the triangular block structure matrix generation stage, the search based on the DFS algorithm is also performed to determine the block formed by the connected non-zero element nodes; then the order number of each node in the block is recorded, and the matrix can be rearranged according to the order number to obtain multiple triangular structures, that is, the matrix composed of the upper triangular structure and the lower triangular structure. Figure 4 The sequence number of the second stage of sorting is expressed as {3,1,2,5,4}.

[0065] Furthermore, step 104 further includes:

[0066] Electromagnetic transient simulation calculation is performed based on the triangular block structure matrix to obtain the simulation results.

[0067] The triangular block structure matrix is ​​a simplified result obtained after fast search based on the DFS algorithm and matrix rearrangement. The matrix complexity is low, so the electromagnetic transient simulation based on this matrix has high computational efficiency; moreover, the non-zero elements are rearranged to the main diagonal; in this way, singularity, that is, the situation where the determinant is zero, can be avoided in the subsequent numerical solution process. For example, in electromagnetic transient simulation, the solver will encounter the problem of division by zero when performing matrix decomposition, resulting in unstable calculation or divergence of the solution set, and unreliable simulation results; the method of this embodiment is used to pre-process the matrix in advance to avoid such a thing. In addition, in the process of electromagnetic transient simulation, there may be different network structures, different loads or equipment configurations, resulting in differences in the sparsity, shape and size of the generated matrix; and the matrix simplification method provided in this embodiment does not require or restrict the properties of the matrix, so the method of this embodiment can adapt to various matrix structures, realize path finding and row and column exchange, and ensure that effective matrix rearrangement and block processing can be performed in different application scenarios.

[0068] The matrix simplification method for electromagnetic transient simulation provided by the embodiment of the present application adopts the DFS algorithm to find the augmented path, which can quickly find the appropriate row and column ordering and reduce the calculation time; and the row and column rearrangement operation based on the row and column numbers of the augmented path can arrange the matrix so that the diagonal elements are all non-zero elements, which can avoid the situation where the determinant is zero in the subsequent calculation process, so the stability of the numerical calculation can be ensured; in addition, the entire matrix simplification process has no requirements on the complexity, sparsity, shape and size of the matrix, so the method can be applied to a variety of matrix calculation scenarios to meet more simulation application needs; furthermore, the triangular block structure matrix obtained by arrangement is easy to understand and analyze, and will not increase the complexity of matrix understanding. Therefore, the embodiment of the present application can solve the technical problems of low efficiency of electromagnetic transient simulation caused by the high computational complexity, lack of numerical stability, increased difficulty in matrix understanding and time-consuming calculation in the prior art.

[0069] For easier understanding, see Figure 2 The present application provides an embodiment of a matrix simplification device for electromagnetic transient simulation, including:

[0070] A graph conversion unit 201 is used to convert the component admittance matrix of the power system quantization into a graph structure to obtain a graph structure matrix, wherein the nodes of the graph structure matrix represent the rows or columns of the matrix, and the edges of the graph structure matrix represent the connection relationship of non-zero elements;

[0071] An augmented search unit 202, configured to perform augmented path traversal search in the graph structure matrix based on a DFS algorithm, and record non-zero row numbers and non-zero column numbers;

[0072] A non-zero sorting unit 203 is used to re-sort the graph structure matrix according to the non-zero row numbers and the non-zero column numbers to obtain a non-zero diagonal matrix;

[0073] The triangle simplification unit 204 is used to perform a path traversal search for the non-zero diagonal matrix along the main diagonal non-zero element nodes based on the DFS algorithm, and perform a non-zero row and column reordering operation to obtain a triangle block structure matrix.

[0074] Further, the augmented search unit 202 is specifically configured to:

[0075] Based on the DFS algorithm, find any non-zero element node in the graph structure matrix, and start from the non-zero element node to traverse and query the adjacent non-zero element nodes until an augmenting path is generated;

[0076] Record all non-zero element nodes on the augmenting path and generate non-zero row numbers and non-zero column numbers.

[0077] Furthermore, the triangle simplification unit 204 is specifically used for:

[0078] Based on the DFS algorithm, select any main diagonal non-zero element node in the non-zero diagonal matrix, perform path traversal search starting from the main diagonal non-zero element node, and record the non-zero row and column numbers;

[0079] The non-zero rows and columns of the non-zero diagonal matrix are reordered according to the non-zero row and column numbers to generate a triangular block structure matrix.

[0080] Furthermore, it also includes:

[0081] The simulation calculation unit 205 is used to perform electromagnetic transient simulation calculation based on the triangular block structure matrix to obtain simulation results.

[0082] The present application also provides a matrix simplification device for electromagnetic transient simulation, the device comprising a processor and a memory;

[0083] The memory is used to store the program code and transmit the program code to the processor;

[0084] The processor is used to execute the matrix simplification method applied to electromagnetic transient simulation in the above method embodiment according to the instructions in the program code.

[0085] The present application also provides a computer-readable storage medium, which is used to store program codes, and the program codes are used to execute the matrix simplification method applied to electromagnetic transient simulation in the above method embodiment.

[0086] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0087] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0088] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0089] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions for executing all or part of the steps of the method described in each embodiment of the present application through a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (full name in English: Read-Only Memory, English abbreviation: ROM), random access memory (full name in English: Random Access Memory, English abbreviation: RAM), disk or optical disk and other media that can store program codes.

[0090] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application 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 application.

Claims

1. A matrix simplification method for electromagnetic transient simulation, characterized in that: include: Converting the component admittance matrix quantized by the power system into a graph structure to obtain a graph structure matrix, wherein the nodes of the graph structure matrix represent matrix rows or columns, and the edges of the graph structure matrix represent non-zero element connection relationships; Based on the DFS algorithm, an augmented path traversal search is performed in the graph structure matrix, and non-zero row numbers and non-zero column numbers are recorded; Reordering the graph structure matrix according to the non-zero row numbers and the non-zero column numbers to obtain a non-zero diagonal matrix; Based on the DFS algorithm, a path traversal search is performed on the non-zero diagonal matrix along the main diagonal non-zero element nodes, and a non-zero row and column reordering operation is performed to obtain a triangular block structure matrix.

2. The matrix simplification method for electromagnetic transient simulation according to claim 1, characterized in that: The augmented path traversal search is performed in the graph structure matrix based on the DFS algorithm, and non-zero row numbers and non-zero column numbers are recorded, including: Searching for any non-zero element node in the graph structure matrix based on the DFS algorithm, and performing traversal query on adjacent non-zero element nodes starting from the non-zero element node until an augmenting path is generated; All non-zero element nodes on the augmenting path are recorded, and non-zero row numbers and non-zero column numbers are generated.

3. The matrix simplification method for electromagnetic transient simulation according to claim 1, characterized in that: The method of performing a path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element nodes based on the DFS algorithm and performing a non-zero row and column reordering operation to obtain a triangular block structure matrix includes: Based on the DFS algorithm, any main diagonal non-zero element node is selected in the non-zero diagonal matrix, a path traversal search is performed with the main diagonal non-zero element node as the starting point, and non-zero row and column numbers are recorded; The non-zero rows and columns of the non-zero diagonal matrix are reordered according to the non-zero row and column numbers to generate a triangular block structure matrix.

4. The matrix simplification method for electromagnetic transient simulation according to claim 1, characterized in that: The method further comprises: performing a path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element nodes based on the DFS algorithm, and performing a non-zero row and column reordering operation to obtain a triangular block structure matrix, and then further comprising: Electromagnetic transient simulation calculation is performed based on the triangular block structure matrix to obtain simulation results.

5. A matrix simplification device for electromagnetic transient simulation, characterized in that: include: A graph conversion unit, used to convert the component admittance matrix of the power system quantization into a graph structure to obtain a graph structure matrix, wherein the nodes of the graph structure matrix represent matrix rows or columns, and the edges of the graph structure matrix represent non-zero element connection relationships; An augmented search unit, used to perform augmented path traversal search in the graph structure matrix based on a DFS algorithm, and record non-zero row numbers and non-zero column numbers; A non-zero sorting unit, used for re-sorting the graph structure matrix according to the non-zero row numbers and the non-zero column numbers to obtain a non-zero diagonal matrix; The triangle simplification unit is used to perform a path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element nodes based on the DFS algorithm, and perform a non-zero row and column reordering operation to obtain a triangle block structure matrix.

6. The matrix simplification device for electromagnetic transient simulation according to claim 5, characterized in that: The augmented search unit is specifically used for: Searching for any non-zero element node in the graph structure matrix based on the DFS algorithm, and performing traversal query on adjacent non-zero element nodes starting from the non-zero element node until an augmenting path is generated; All non-zero element nodes on the augmenting path are recorded, and non-zero row numbers and non-zero column numbers are generated.

7. The matrix simplification device for electromagnetic transient simulation according to claim 5, characterized in that: The triangle simplification unit is specifically used for: Based on the DFS algorithm, any main diagonal non-zero element node is selected in the non-zero diagonal matrix, a path traversal search is performed with the main diagonal non-zero element node as the starting point, and non-zero row and column numbers are recorded; The non-zero rows and columns of the non-zero diagonal matrix are reordered according to the non-zero row and column numbers to generate a triangular block structure matrix.

8. The matrix simplification device for electromagnetic transient simulation according to claim 5, characterized in that: Also includes: The simulation calculation unit is used to perform electromagnetic transient simulation calculation based on the triangular block structure matrix to obtain simulation results.

9. A matrix simplification device for electromagnetic transient simulation, characterized in that: The device comprises a processor and a memory; The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the matrix simplification method for electromagnetic transient simulation according to any one of claims 1 to 4 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program codes, and the program codes are used to execute the matrix simplification method for electromagnetic transient simulation according to any one of claims 1 to 4.

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