Matrix simplification method applied to electromagnetic transient simulation and related device

Abstract

The application discloses a matrix simplification method and related device applied to electromagnetic transient simulation, and the method comprises the steps of: converting the component admittance matrix of the quantized power system into a graph structure to obtain a graph structure matrix, wherein the nodes of the graph structure matrix represent the matrix rows or columns, and the edges of the graph structure matrix represent the non-zero element connection relationship; performing an augmented path traversal search in the graph structure matrix based on the DFS algorithm, and recording the non-zero row serial numbers and the non-zero column serial numbers; performing reordering processing on the graph structure matrix according to the non-zero row serial numbers and the non-zero column serial 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. The application can solve the technical problems of high computational complexity, lack of numerical stability, increased difficulty in matrix understanding, long computation time and low electromagnetic transient simulation efficiency of the prior art.

Description

TECHNICAL FIELD

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

[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 to 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 row and column rearrangement, diagonal scaling, sparse matrix decomposition and sparse matrix compression operations. However, the 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, which directly affect the overall efficiency of electromagnetic transient simulation experiments, especially for large power system simulations. SUMMARY

[0004] The present application provides a matrix simplification method applied to electromagnetic transient simulation and a related device, which solves the technical problems of high computational complexity, lack of numerical stability, increased difficulty in understanding matrices, and time-consuming calculations in the prior art, resulting in low efficiency of electromagnetic transient simulation.

[0005] Therefore, 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] Performing augmented path traversal search in the graph structure matrix based on the DFS algorithm, and recording non-zero row sequence numbers and non-zero column sequence numbers;

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

[0009] 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.

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

[0011] finding any non-zero element node in the graph structure matrix based on the DFS algorithm, and performing adjacent non-zero element node traversal query from the non-zero element node as a starting point until an augmented path is generated;

[0012] Recording all non-zero element nodes on the augmented path to generate non-zero row and column sequence numbers.

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

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

[0015] According to the non-zero row and column sequence numbers, non-zero row and column reordering operation is performed on the non-zero diagonal matrix to generate a triangular block structure matrix.

[0016] Preferably, the DFS algorithm is used to perform path traversal search on the non-zero diagonal matrix along the main diagonal non-zero element node, and non-zero row and column reordering operation is performed to obtain a triangular block structure matrix, and then further including:

[0017] Based on the triangular block structure matrix, electromagnetic transient simulation calculation is performed to obtain simulation results.

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

[0019] A graph conversion unit is configured to convert a component admittance matrix quantized by a power system into a graph structure to obtain a graph structure matrix, wherein a node of the graph structure matrix represents a matrix row or column, and an edge of the graph structure matrix represents a non-zero element connection relationship.

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

[0021] A non-zero sorting unit is configured to perform reordering processing on the graph structure matrix according to the non-zero row and column sequence numbers to obtain a non-zero diagonal matrix.

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

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

[0024] Finding an arbitrary non-zero element node in the graph structure matrix based on the DFS algorithm, and performing adjacent non-zero element node traversal query from the non-zero element node as a starting point until an augmented path is generated;

[0025] Recording all non-zero element nodes on the augmented path to generate non-zero row and column sequence numbers.

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

[0027] Selecting an arbitrary main diagonal non-zero element node in the non-zero diagonal matrix based on the DFS algorithm, performing path traversal search from the main diagonal non-zero element node as a starting point, and recording non-zero row and column sequence numbers;

[0028] Performing non-zero row and column reordering operation on the non-zero diagonal matrix according to the non-zero row and column sequence numbers to generate a triangular block structure matrix.

[0029] Preferably, it further comprises:

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

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

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

[0033] The processor is configured to execute the instructions in the program code to perform the matrix simplification method applied to electromagnetic transient simulation according to the first aspect.

[0034] The fourth aspect of the present application provides a computer readable storage medium for storing program code, the program code being used to execute the matrix simplification method applied to electromagnetic transient simulation according to the first aspect.

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

[0036] In the present application, a matrix simplification method applied to electromagnetic transient simulation is provided, including: converting a component admittance matrix quantized by a power system into a graph structure to obtain a graph structure matrix, wherein a node of the graph structure matrix represents a matrix row or column, and an edge of the graph structure matrix represents a non-zero element connection relationship; performing an augmented path traversal search in the graph structure matrix based on a DFS algorithm, and recording non-zero row serial numbers and non-zero column serial numbers; performing reordering processing on the graph structure matrix according to the non-zero row serial numbers and the non-zero column serial numbers to obtain a non-zero diagonal matrix; and performing path traversal search on the non-zero diagonal matrix along a main diagonal non-zero element node 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 applied to electromagnetic transient simulation provided by the present application adopts the DFS algorithm to find an augmented path, can quickly find suitable row and column ordering, and reduces calculation time; the row and column reordering operation based on the row and column serial numbers of the augmented path can arrange the matrix into a diagonal line with all non-zero elements, which can avoid the situation that the determinant is zero in the subsequent calculation process, so as to ensure the stability of numerical calculation; in addition, the entire matrix simplification process has no requirements for the complexity, sparsity, shape and size of the matrix, so the method can be applied to various matrix calculation scenarios, meets more simulation application requirements; furthermore, the triangular block structure matrix obtained after arrangement is convenient for understanding and analysis, and does not increase the complexity of matrix understanding. Therefore, the present application can solve the technical problems of high calculation complexity, lack of numerical stability, increased difficulty of matrix understanding, and time-consuming calculation in the prior art, and low electromagnetic transient simulation efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 A flowchart of the matrix simplification method applied to electromagnetic transient simulation provided by the embodiment of the present application is shown in the figure;

[0039] Figure 2 A structural diagram of the matrix simplification device applied to electromagnetic transient simulation provided by the embodiment of the present application is shown in the figure;

[0040] Figure 3 A component relationship structure diagram of the power system simulation provided by the embodiment of the present application is shown in the figure;

[0041] Figure 4 A matrix ordering and block processing process example diagram provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0042] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application, so that those skilled in the art can better understand the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0043] For the convenience of understanding, please refer to Figure 1 The embodiment of the matrix simplification method for electromagnetic transient simulation provided by the present application comprises the following steps.

[0044] Step 101, 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 the matrix rows or columns, and the edges of the graph structure matrix represent the non-zero element connection relationship.

[0045] For the convenience of understanding, please refer to Figure 3 Among them , , , represent the admittance value of the simulation component abstracted from the power system equipment, and also represent each simulation component, which is a key parameter for simulation analysis, used to quantify the conductive capacity of the component under voltage difference, and the , , , represent the voltage nodes. Therefore, the admittance matrix conversion analysis of each simulation component of the power system is the key to simulation. After conversion, please refer to Table 1, wherein the non-diagonal position reflects the negative admittance value of the components connected by the lines.

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

[0047]

[0048] The embodiment is to simplify the matrix in the simulation process, thereby reducing the complexity of the matrix and improving the efficiency of the simulation calculation. Before simplifying the admittance matrix, the matrix needs to be converted into a graph structure, which describes the relationship between elements and elements with nodes and edges, and can be more clear and explicit in the subsequent analysis process. The nodes in the graph structure matrix of the present embodiment represent a row or a column in the matrix, and the edges represent the connection relationship between non-zero elements.

[0049] Step 102, performing an augmented path traversal search in the graph structure matrix based on the DFS algorithm, and recording the non-zero row sequence number and the non-zero column sequence number.

[0050] Further, step 102 comprises:

[0051] Based on the DFS algorithm, any non-zero element node in the graph structure matrix is found, and the adjacent non-zero element node is traversed and queried from the non-zero element node as the starting point until an augmented path is generated.

[0052] All non-zero element nodes on the augmented path are recorded to generate non-zero row sequence numbers and non-zero column sequence numbers.

[0053] The DFS algorithm is an algorithm for traversing or searching trees or graphs. The algorithm traverses the nodes of a tree along its depth, searching as deeply as possible along each branch of the tree. When all the edges from a node v have been explored or the node does not meet the conditions during the search, the search backtracks to the starting node of the edge that discovered node v. The entire process is repeated until all nodes have been visited.

[0054] Based on the DFS algorithm, an arbitrary non-zero element node in the graph structure matrix can be found, and the adjacent non-zero element node around this node is searched. 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", and if the current path search cannot continue, DFS will backtrack to the last node and try other paths. This process is repeated until a complete augmented path is found.

[0055] Once the augmented path is found, all non-zero element nodes on the augmented path need to be recorded to generate non-zero row sequence numbers and non-zero column sequence numbers; these node rows / columns are the rows and columns that can move the non-zero elements to the main diagonal line position through row and column exchange. This process ensures the non-zero nature of the main diagonal elements of the matrix.

[0056] Step 103, reordering the graph structure matrix according to the non-zero row sequence numbers and non-zero column sequence 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 element of the matrix according to the sequence number, and then adjust the matrix structure through row and row exchange and column and column exchange to adjust the non-zero element to the main diagonal line, ensuring the non-zero nature of the main diagonal line.

[0058] Suppose there is a non-zero element in the ith row, which is not on the main diagonal line of the ith row but in other positions, such as the hth column, and the main diagonal line position of the hth column has no non-zero element. Then the hth column can be exchanged with the column where the main diagonal line of the ith row is located, so that the non-zero element can be exchanged to the main diagonal line. Through multiple operations, a non-zero diagonal matrix can be obtained.

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

[0060] Further, step 104 comprises:

[0061] Selecting an arbitrary main diagonal non-zero element node in the non-zero diagonal matrix based on the DFS algorithm, path traversal search starting from the main diagonal non-zero element node, and recording the non-zero row and column sequence numbers;

[0062] Non-zero row and column reordering operation of the non-zero diagonal matrix according to the non-zero row and column sequence numbers to generate a triangular block structure matrix.

[0063] The purpose of the traversal search by the DFS algorithm here is to identify non-zero elements that are connected to each other in the non-zero diagonal matrix. When the DFS algorithm starts from a non-zero element node on the main diagonal, it does not search along one path, but through recursion, finds all non-zero nodes connected to the node. These nodes can be in the same row, the same column, or connected through other adjacent elements, and finally these non-zero nodes are regarded as a "block". After finding a block, it returns and continues to search for the next non-zero element node on the main diagonal that has not been accessed, and searches for the next "block". In the found block, if there is a strongly connected component, the row and column reordering operation of the matrix needs to be performed according to the non-zero row and column sequence numbers in the strongly connected component; the purpose is to concentrate the non-zero element nodes of the strongly connected component, i.e. concentrate the non-zero row and column, to form a smaller block structure. According to the sequence numbers after multiple searches, the reordering operation based on the block can be performed to generate a triangular block structure matrix, which can have multiple upper triangular blocks and lower triangular blocks; thus the simplification operation of the matrix is completed, the triangular block structure matrix is easy to understand and not complex, and the calculation speed is fast and the processing efficiency is high.

[0064] Please refer to Figure 4 The leftmost matrix can obtain the middle matrix after column ordering operation of the column sequence numbers {1, 5, 4, 3, 2}; the sequence numbers for the ordering operation are extracted from the augmented path in the search, which is the ordering result after the global search. In the matrix obtained after the ordering operation, 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, so that the matrix in the middle of the figure can be obtained. In the triangular block structure matrix generation stage, the blocks formed by the connected non-zero element nodes are determined based on the DFS algorithm search; then the sequence numbers of the nodes in the blocks are recorded, and the matrix can be reordered according to the sequence numbers to obtain multiple triangular structures, i.e. a matrix composed of upper triangular structures and lower triangular structures. Figure 4 The sequence numbers of the second stage ordering operation are expressed as {3, 1, 2, 5, 4}.

[0065] Further, the step 104 further includes:

[0066] The electromagnetic transient simulation calculation is performed based on the triangular block structure matrix to obtain a simulation result.

[0067] The triangular block structure matrix is a simplified result obtained after DFS algorithm fast searching and matrix rearrangement, and has low complexity, so that the electromagnetic transient simulation calculation based on the matrix has high efficiency. Moreover, the non-zero elements are rearranged to the main diagonal line, so that singularity, i.e., determinant zero, can be avoided in the subsequent numerical solution process. For example, in electromagnetic transient simulation, the solver encounters division by zero when performing matrix decomposition, which leads to unstable calculation or divergent solution set, and the simulation result is unreliable. The matrix is preprocessed in advance by using the method of the embodiment, so that the above situation can be avoided. In addition, in the electromagnetic transient simulation process, there may be different network structures, different load or device configurations, which lead to differences in matrix sparsity, shape and size. The matrix simplification method provided in the embodiment does not have requirements or restrictions on the properties of the matrix, so the method of the embodiment can adapt to various matrix structures, realize path searching and row-column exchange, and ensure effective matrix rearrangement and block processing in different application scenarios.

[0068] The matrix simplification method applied to electromagnetic transient simulation provided in the embodiment of the application uses the DFS algorithm to search for an augmented path, can quickly find a suitable row-column order, and reduces the calculation time. The row-column rearrangement operation based on the row-column order of the augmented path can arrange the matrix into a diagonal line with non-zero elements, so that the situation of determinant zero in the subsequent calculation process can be avoided, and the numerical calculation stability can be ensured. In addition, the matrix simplification process does not have requirements on the complexity, sparsity, shape and size of the matrix, so the method can be applied to various matrix calculation scenarios and meet more simulation application requirements. Furthermore, the triangular block structure matrix obtained by arrangement is convenient for understanding and analysis, and does not increase the complexity of matrix understanding. Therefore, the embodiment of the application can solve the technical problems of high calculation complexity, lack of numerical stability, increased difficulty of matrix understanding, and time-consuming calculation in the prior art, which leads to low electromagnetic transient simulation efficiency.

[0069] For ease of understanding, please refer to Figure 2 The application provides an embodiment of a matrix simplification device applied to electromagnetic transient simulation, which includes:

[0070] The graph conversion unit 201 is configured to convert 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.

[0071] The augmented search unit 202 is configured to perform augmented path traversal search in the graph structure matrix based on the DFS algorithm, and record the non-zero row sequence number and the non-zero column sequence number.

[0072] The non-zero sorting unit 203 is configured to perform reordering processing on 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.

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

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

[0075] perform traversal search on adjacent non-zero element nodes from any non-zero element node in the graph structure matrix based on the DFS algorithm, until an augmented path is generated;

[0076] record all non-zero element nodes on the augmented path, to generate the non-zero row sequence number and the non-zero column sequence number.

[0077] Further, the triangular simplification unit 204 is specifically configured to:

[0078] select any main diagonal non-zero element node in the non-zero diagonal matrix based on the DFS algorithm, perform path traversal search from the main diagonal non-zero element node as a starting point, and record the non-zero row and column sequence number;

[0079] perform non-zero row and column reordering operation on the non-zero diagonal matrix according to the non-zero row and column sequence number, to generate the triangular block structure matrix.

[0080] Further, the device further comprises:

[0081] The simulation calculation unit 205 is configured to perform electromagnetic transient simulation calculation based on the triangular block structure matrix, to obtain a simulation result.

[0082] The application further provides a matrix simplification device applied to electromagnetic transient simulation, the device comprising a processor and a memory;

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

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

[0085] The application further provides a computer readable storage medium, the computer readable storage medium is configured to store program code, the program code is configured to execute the matrix simplification method applied to electromagnetic transient simulation in the method embodiments.

[0086] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other means. For example, the apparatus embodiments described above are merely illustrative, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some interfaces, apparatuses or units, and can be electrical, mechanical or other forms.

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

[0088] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0089] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part of the prior art that makes a contribution or the whole or part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for executing all or part of the steps of the method described in each embodiment of the present application by a computer device (which can be a personal computer, a server, or a network device, etc.). The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (English full name: Read-Only Memory, English abbreviation: ROM), a random access memory (English full name: Random Access Memory, English abbreviation: RAM), a magnetic disk or an optical disk, and various program code storage media.

[0090] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A matrix simplification method applied to electromagnetic transient simulation, characterized in that, include: The component admittance matrix of the power system is quantified and transformed into a graph structure to obtain a graph structure matrix. 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 between non-zero elements. Based on the Depth-First Search (DFS) algorithm, augmenting path traversal is performed in the graph structure matrix, and non-zero row and column indices are recorded. The specific process is as follows: Based on the DFS algorithm, find any non-zero element node in the graph structure matrix, and traverse and query adjacent non-zero element nodes starting from the non-zero element node until an augmenting path is generated. Record all non-zero element nodes on the augmenting path, and generate non-zero row and column indices; The graph structure matrix is ​​reordered according to the non-zero row and column indices to obtain a non-zero diagonal matrix. Based on the DFS algorithm, a path traversal search is performed along the non-zero element nodes of the main diagonal matrix, and the non-zero rows and columns are reordered to obtain a triangular block structure matrix. The specific process is as follows: Based on the DFS algorithm, select any non-zero element node on the main diagonal of the non-zero diagonal matrix, perform path traversal search starting from the non-zero element node on the main diagonal, and record the non-zero row and column indices. The non-zero diagonal matrix is ​​reordered according to the non-zero row and column indices to generate a triangular block structure matrix.

2. The matrix simplification method for electromagnetic transient simulation according to claim 1, characterized in that, The process involves performing a path traversal search along the non-zero elements of the main diagonal matrix using the DFS algorithm, followed by a reordering of the non-zero rows and columns to obtain a triangular block structure matrix. This process further includes: Electromagnetic transient simulation calculations were performed based on the aforementioned triangular block structure matrix, and simulation results were obtained.

3. A matrix simplification device for electromagnetic transient simulation, characterized in that, include: The graph conversion unit is used to convert the component admittance matrix of the power system quantization into a graph structure to obtain a graph structure matrix. 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. An augmenting search unit is used to perform augmenting path traversal search in the graph structure matrix based on the DFS algorithm, and to record non-zero row indices and non-zero column indices. Specifically, the augmenting search unit is used for: Based on the DFS algorithm, find any non-zero element node in the graph structure matrix, and traverse and query adjacent non-zero element nodes starting from the non-zero element node until an augmenting path is generated. Record all non-zero element nodes on the augmenting path, and generate non-zero row and column indices; A non-zero sorting unit is used to reorder the graph structure matrix according to the non-zero row number and the non-zero column number to obtain a non-zero diagonal matrix. The triangular simplification unit is used to perform path traversal search along the non-zero element nodes of the main diagonal matrix based on the DFS algorithm, and to perform non-zero row and column reordering operations to obtain a triangular block structure matrix. Specifically, the triangular simplification unit is used for: Based on the DFS algorithm, select any non-zero element node on the main diagonal of the non-zero diagonal matrix, perform path traversal search starting from the non-zero element node on the main diagonal, and record the non-zero row and column indices. The non-zero diagonal matrix is ​​reordered according to the non-zero row and column indices to generate a triangular block structure matrix.

4. The matrix simplification device for electromagnetic transient simulation according to claim 3, characterized in that, Also includes: The simulation calculation unit is used to perform electromagnetic transient simulation calculations based on the triangular block structure matrix and obtain simulation results.

5. A matrix simplification device for electromagnetic transient simulation, characterized in that, The device includes a processor and a memory; The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the matrix simplification method for electromagnetic transient simulation as described in any one of claims 1-2 according to the instructions in the program code.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code for executing the matrix simplification method for electromagnetic transient simulation as described in any one of claims 1-2.

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