Power system edge weight coefficient calculation method and system

Abstract

The present application provides a method and system for calculating edge weight coefficients of a power system, relating to the technical field of power system parameter calculation. The method comprises: calculating a node impedance matrix of a topological structure to calculate a first power change and a second power change based on elements in the node impedance matrix, wherein the first and second power changes are respectively the power changes on different lines caused by a first power change of a source-load node pair; obtaining a correlation coefficient based on the first and second power changes, wherein the correlation coefficient is the relationship between the power changes of two different lines when the source-load node pair changes power; calculating a third power change based on the correlation coefficient, wherein the third power change is the power change on all lines caused by a second power change of any line; and performing linear weighted superposition on the third power change to obtain an edge weight coefficient. Since no weights are required for calculation, the accuracy of the calculation results can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of power system parameter calculation, and in particular to a method and system for calculating edge weight coefficients of a power system. Background Art

[0002] As the core part of energy supply, the power system continues to expand in scale and its structure becomes increasingly complex. In order to ensure the stability and efficiency of power supply and effectively manage large-scale power systems, the power system will be reasonably divided into regions based on the principle of strong coupling within regions and weak coupling between regions.

[0003] However, when partitioning complex power systems, it is necessary to calculate the edge weight coefficients of the lines. The edge weight coefficient is a key indicator of the importance of lines in the power system and is directly related to the rationality and effectiveness of the partitioning. To balance the operating status and topological characteristics of the power system, a weighted index is often used to define the line edge weight coefficient. The edge weight coefficient is calculated as follows: Line edge weight coefficient = ω × power system operating status index + (1-ω) edge betweenness index. This calculation method combines the power system operating status index and the edge betweenness index, balancing their influence by adjusting the weight ω.

[0004] While this method reflects the comprehensive characteristics of power lines to a certain extent, the value of the weight ω is highly subjective. This means that the edge weight coefficients of power system lines are easily affected by subjective weight factors, resulting in inaccurate calculation results. This uncertainty not only affects the rationality of zoning but also has a negative impact on the operation and management of the power system. Summary of the Invention

[0005] The present application provides a method and system for calculating edge weight coefficients of a power system to solve the problem of inaccurate calculation results of edge weight coefficients.

[0006] In a first aspect, the present application provides a method for calculating edge weight coefficients of a power system, wherein a topological structure of the power system includes a power source node, a load node, a transmission node, and at least one line, wherein the power source node is connected to the load node via the line, and the transmission node is a node on the line; the method comprises:

[0007] Calculating a node impedance matrix of the topological structure to calculate a first power change and a second power change based on elements in the node impedance matrix; the first power change is a power change on one of the lines caused by a power change of a source-load node pair by a first magnitude; and the second power change is a power change on the other line caused by a power change of the source-load node pair by the first magnitude; the source-load node pair is any combination of a power source node and a load node;

[0008] Obtaining a correlation coefficient based on the first power change and the second power change, where the correlation coefficient is a relationship between power changes of one line and another line when the power of the source-load node pair changes;

[0009] Calculating a third power change according to the correlation coefficient, the third power change being the power change on all the lines caused when the power of any one of the lines changes by the second value;

[0010] Perform linear weighted superposition on the third power variation to obtain an edge weight coefficient.

[0011] Optionally, the first power variation is calculated by the following formula:

[0012] ;

[0013] Where s is the source node, t is the load node, st is the source-load node pair, ij is any line, i and j are the transmission nodes on line ij, is the first value, is the first power variation, is the element in the i-th row and s-th column of the node impedance matrix, is the element in the jth row and sth column of the node impedance matrix, is the element in the i-th row and t-th column of the node impedance matrix, is the element in the jth row and tth column of the node impedance matrix, is the reactance value of line ij.

[0014] Optionally, the second power variation is calculated by the following formula:

[0015] ;

[0016] Where mn is another line different from line ij, m and n are transmission nodes on line mn, is the second power variation, is the element in the mth row and sth column of the node impedance matrix, is the element in the nth row and sth column of the node impedance matrix, is the element in the mth row and tth column of the node impedance matrix, is the element in the nth row and tth column of the node impedance matrix, is the reactance value of line mn.

[0017] Optionally, acquiring a correlation coefficient according to the first power change and the second power change includes:

[0018] respectively acquiring a first correlation relationship between the first power variation and the first value and a second correlation relationship between the second power variation and the first value;

[0019] Eliminate the first value in the first association relationship and the second association relationship to obtain the association coefficient.

[0020] Optionally, the correlation coefficient is calculated by the following formula:

[0021] ;

[0022] in, is the correlation coefficient between line ij and line mn.

[0023] Optionally, the third power variation is calculated by the following formula:

[0024] ;

[0025] in, is the third power variation caused by line x, x and y are the lines respectively, a is the number of lines, is the correlation coefficient between line x and line y.

[0026] Optionally, the edge weight coefficient is calculated by the following formula:

[0027] ;

[0028] in, is the edge weight coefficient, G is the set of power nodes, L is the set of load nodes, Active power injected into the power node, is the active power consumed by the load node, The smaller value of the active power injected into the source node and the active power consumed by the load node.

[0029] Optionally, the method further includes:

[0030] Obtain a correspondence between the edge weight coefficients and the lines and the transmission nodes, so as to construct an edge weight coefficient matrix according to the edge weight coefficients.

[0031] A second aspect of the present application provides a power system edge weight coefficient calculation system, which is applied to the method described in the first aspect, wherein the topology of the power system includes a power source node, a load node, a transmission node, and at least one line, the power source node is connected to the load node via the line, and the transmission node is a node on the line; the system includes:

[0032] A first calculation module is configured to calculate a node impedance matrix of the topological structure, and calculate a first power change and a second power change based on elements in the node impedance matrix; the first power change is a power change on one of the lines caused by a power change of a source-load node pair by a first magnitude; the second power change is a power change on the other line caused by a power change of the source-load node pair by the first magnitude; the source-load node pair is any combination of a power source node and a load node;

[0033] A second calculation module is configured to obtain a correlation coefficient based on the first power change and the second power change, where the correlation coefficient is a relationship between the power changes of one line and another line when the power of the source-load node pair changes;

[0034] A third calculation module is configured to calculate a third power variation according to the correlation coefficient, wherein the third power variation is the power variation on all the lines caused when the power of any one of the lines changes by the second value;

[0035] The fourth calculation module is used to perform linear weighted superposition on the third power variation to obtain an edge weight coefficient.

[0036] The present application provides a method and system for calculating edge weight coefficients of a power system. The method includes: calculating a node impedance matrix of a topological structure to calculate a first power change and a second power change based on the elements in the node impedance matrix, wherein the first and second power changes are respectively the power changes caused on different lines when the power of the source-load node pair changes by a first value; obtaining a correlation coefficient based on the first and second power changes, wherein the correlation coefficient is the relationship between the power changes between two different lines when the power of the source-load node pair changes; calculating a third power change based on the correlation coefficient, wherein the third power change is the power change caused on all lines when the power of any line changes by a second value; and performing linear weighted superposition on the third power change to obtain an edge weight coefficient. When the power injected by a power source node or a load node in the power system changes, only the node injection power needs to be updated to obtain a new line edge weight coefficient, eliminating the need for repeated iterative power flow calculations and improving the efficiency of line edge weight coefficient calculation. Since no weights are required for calculation, the interference of subjective weight factors on the line edge weight coefficient calculation can be reduced, making the calculation results more accurate, and thus enabling more accurate partitioning of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0038] Figure 1 An equivalent model diagram of the power system provided in an embodiment of the present application;

[0039] Figure 2 Flowchart of the method for calculating edge weight coefficients of a power system provided in an embodiment of the present application;

[0040] Figure 3 A schematic diagram of a 5-node power system network topology structure provided in an embodiment of the present application;

[0041] Figure 4 Schematic diagram of the structure of the power system edge weight coefficient calculation system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] The following embodiments are described in detail, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numbers in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following embodiments are not intended to represent all possible implementations consistent with the present application. They are merely examples of systems and methods consistent with certain aspects of the present application, as detailed in the claims.

[0043] When using weighted indicators to define line edge weights, the calculation formula is as follows: Line edge weight = ω × Power System Operation Status Index + (1-ω) Edge Betweenness Index. This calculation method combines the power system operation status index and the edge betweenness index, balancing their influence by adjusting the weight ω. While this method can reflect the comprehensive characteristics of lines to a certain extent, the value of the weight ω is highly subjective. This means that the edge weight coefficients of power system lines are easily influenced by subjective weighting factors, resulting in inaccurate calculation results. This uncertainty not only affects the rationality of zoning but can also negatively impact the operation and management of the power system.

[0044] In order to solve the problem of inaccurate edge weight coefficient calculation results, some embodiments of this application provide a method for calculating edge weight coefficients in a power system. Before describing the calculation method of this application, a brief description of the topology of the power system is given. The topology of the power system includes power nodes, load nodes, transmission nodes and at least one line. The power nodes are connected to the load nodes through the line, and the transmission nodes are nodes on the line. Figure 1 , Figure 1 is the equivalent model diagram of the power system, Figure 1In this example, s is the source node, t is the load node, i and j are transmission nodes on any one line, and m and n are transmission nodes on another line. Transmission nodes include both head-end nodes and end-end nodes. It can be understood that the transmission node closest to source node s is the head-end node, i and m are the head-end nodes on the line, and j and n are the end-end nodes on the line. The values ​​of s, t, i, j, m, and n can be 1, 2, 3, ..., N.

[0045] See also Figure 2 , the calculation method provided in this application includes:

[0046] S100: Calculate a node impedance matrix of a topological structure to calculate a first power variation and a second power variation according to elements in the node impedance matrix.

[0047] The node impedance matrix is ​​the inverse matrix of the node admittance matrix. The calculation process of the node impedance matrix can be obtained through existing technology and will not be described in detail in this application. The first power change is the power change caused on one of the lines when the power of the source-load node pair changes by a first value. The second power change is the power change caused on the other line when the power of the source-load node pair changes by a first value. The source-load node pair is any combination of a power source node and a load node. According to the power transmission distribution factor of the DC power flow model, it is assumed that the power is injected into the power node of the power system. , draws power at load node t , then the power change caused on line ij is:

[0048] ; (1)

[0049] Where s is the source node, t is the load node, st is the source-load node pair, ij is any line, i and j are the transmission nodes on line ij, is the element in the i-th row and s-th column of the node impedance matrix, is the element in the jth row and sth column of the node impedance matrix, is the element in the i-th row and t-th column of the node impedance matrix, is the element in the jth row and tth column of the node impedance matrix, is the reactance value of line ij. It can be understood that in the above formula (1), That is the first value, That is the first power variation.

[0050] Similarly, according to formula (1), the power change on line ij caused by the first power change of the source-load node pair st can be calculated by the following formula:

[0051] ; (2)

[0052] Where mn is another line different from line ij, m and n are transmission nodes on line mn, is the second power variation, is the element in the mth row and sth column of the node impedance matrix, is the element in the nth row and sth column of the node impedance matrix, is the element in the mth row and tth column of the node impedance matrix, is the element in the nth row and tth column of the node impedance matrix, is the reactance value of line mn.

[0053] S200: Obtain a correlation coefficient according to the first power variation and the second power variation.

[0054] In some embodiments, obtaining a correlation coefficient based on the first power change and the second power change includes: respectively obtaining a first correlation relationship between the first power change and the first value and a second correlation relationship between the second power change and the first value; and eliminating the first value in the first correlation relationship and the second correlation relationship to obtain the correlation coefficient. The correlation coefficient is the relationship between the power change of one line and the power change of another line when the power of the source-load node pair changes. It can be understood that the above formula (1) is the first correlation relationship, and formula (2) is the second correlation relationship.

[0055] The above formulas (1) and (2) respectively describe the relationship between the power changes of the two lines and the source-load node pair st in the power system, where and Respectively reflect the contribution of line ij and line mn to the power variation of st at the source-load node. and There are two problems with the edge weight coefficient of the line. On the one hand, the edge weight coefficient calculated by only one source-load node pair st cannot fully reflect the characteristics of the line. On the other hand, the source-load node pair st has no corresponding network topology expression in the power system. and It is not possible to correspond to the topological structure, which is not conducive to establishing a complete power system network topological structure model. Therefore, in the embodiment of the present application, formulas (1) and (2) are combined to eliminate the first value , we can get the relationship between the power variation of the two lines ij and line mn, which can not only reflect the influence of line ij on the power variation of the power system, but also correspond to the topological relationship of the lines. Combining formulas (1) and (2), we can eliminate the first value Then we can get the following formula:

[0056] ; (3)

[0057] but That is the correlation coefficient between line ij and line mn, let:

[0058] ; (4)

[0059] Combining formula (3) and formula (4), we have:

[0060] ; (5)

[0061] in, is the correlation coefficient between line ij and line mn. The above formula (5) describes the relationship between the power changes between any two lines ij and line mn under the influence of the source-load node pair st.

[0062] S300: Calculate a third power variation according to the correlation coefficient.

[0063] The third power change is the power change on all lines caused by the power change of any line by the second value. In some embodiments, the second value can be unit power. If it is necessary to establish a relationship between the power change of line ij and all lines in the power system, it is necessary to accumulate the power changes of each line. Define the line with the first end node i and the end node j as line x, and the line with the first end node m and the end node n as line y, where the values ​​of x and y can be 1, 2, 3..., a. According to formula (5), we have:

[0064] ; (6)

[0065] in, is the first power variation of line x, is the correlation coefficient between line x and line y, is the second power variation of line y.

[0066] definition When only the source-load node pair st is affected, the power change of each line in the entire network caused by the unit power change of line x, that is, the second value, is the third power change. The third power change can be calculated by the following formula:

[0067] ; (7)

[0068] in, is the third power change caused by line x, x and y are the lines respectively, a is the number of lines, when x=y, .

[0069] S400: Performing linear weighted superposition on the third power variation to obtain an edge weight coefficient.

[0070] It is understandable that since there are not unique source-load node pairs in the power system, the impact of all source-load node pairs on the line should be added together to fully reflect the impact of the line on the power change of the power system. The impact of all source-load node pairs, including the source-load node pair st, is linearly weighted and superimposed, where the weight is the smaller value of the power at the source node s and the load node t. The calculation formula for the edge weight coefficient is as follows:

[0071] ; (8)

[0072] in, is the edge weight coefficient, G is the set of power nodes, L is the set of load nodes, Active power injected into the power node, is the active power consumed by the load node, The smaller value of the active power injected into the source node and the active power consumed by the load node. It reflects the impact of all source-load node pairs on the power changes of all lines in the entire network when the power of line x changes. Therefore, it can be used as the weight coefficient to characterize the importance of line x, that is, the edge weight coefficient of the line.

[0073] The calculation method provided in this application uses the power change as the calculation parameter of the line edge weight coefficient to establish a weighted network model of the power system. When the power injected into the power source node or load node of the power system changes, it is only necessary to update the node injection power to obtain a new line edge weight coefficient, thereby updating the weighted network model of the power system. The line edge weight coefficient calculated by the above method can be updated according to the power change of the power system node. Since there is no need to use weights for calculation and it is not affected by subjective factors, it can not only reflect the actual operation status of the power system, but also improve the accuracy of the calculation results, thereby more accurately partitioning the power system. And since the above calculation process does not need to rely on the power system flow calculation results and perform repeated iterative flow calculations, it can also improve the efficiency of the line edge weight coefficient calculation.

[0074] In order to establish a complete weighted network model of the power system, the transmission nodes, lines and edge weight coefficients of the power system are matched one by one. Construct edge weight coefficient matrix (edge ​​weight coefficient matrix of M-node power system is an M-order square matrix), so in some embodiments, the method further includes: obtaining the corresponding relationship between the edge weight coefficient and the line and the transmission node to construct an edge weight coefficient matrix based on the edge weight coefficient. The element in row i and column j It can be expressed as:

[0075] ; (9)

[0076] The influence of the power change of the line with the first end node i and the last end node j on the power change of all lines in the whole network is obviously , edge weight coefficient matrix Is a symmetric matrix. Edge weight coefficient matrix It not only includes the edge weight coefficients of each line, but also reflects the relationship between different transmission nodes (when there is a line connecting the head node i and the terminal node j, It is not zero, otherwise it is zero), and it also includes the structural characteristics and operating status characteristics of the power system.

[0077] See also Figure 3 , l1-l6 are transmission lines, p1-p5 are transmission nodes, G1-G4 are power supply nodes, and Figure 3 Taking the power system in as an example, the calculation method of this application is used to calculate the edge weight coefficient of the line. The parameters of the power system are shown in Table 1-Table 2, and the calculated edge weight coefficients of each line are shown in Table 3.

[0078] Table 1: Parameters of 5-node power system line

[0079]

[0080] Table 2: Parameters of transmission nodes in a 5-node power system

[0081]

[0082] Table 3: Line edge weight coefficients for a 5-node power system

[0083]

[0084] Change the active power injected into the power node G2 The power of the transmission node p3 can be changed so that the active power injected by the power node G2 is =100MW, other parameters remain unchanged, and the calculated line edge weight coefficients are shown in Table 4. In Tables 3 and 4, the results of electrical betweenness and power flow betweenness are calculated using the weight ω.

[0085] Table 4: Line edge weight coefficients of the 5-node power system after changing the injection power of the transmission node p3

[0086]

[0087] Compare the line edge weight coefficients and electrical betweenness and flow betweenness in Tables 3 and 4. It can be seen from the data in Tables 3 and 4 that in the traditional calculation of edge weight coefficients, since the value of the weight ω is highly subjective, it has a significant impact on the line edge weight coefficient, resulting in the line edge weight coefficient obtained by weighted calculation of flow betweenness and electrical betweenness being inaccurate. Moreover, the electrical betweenness will not change when the power injected into the power supply node of the power system changes, and cannot reflect the actual operation of the power system. Although the flow betweenness can reflect the impact of the change in the power injected into the power system on the line edge weight coefficient, the calculation process involves iterative flow calculation, and the calculation cycle is significantly longer than the edge weight coefficient calculation method in this application, for example Figure 3 The calculation time for the power system edge weight coefficient is shown to be 0.0313 seconds, and the calculation time for the power flow betweenness is 1.42 seconds. The calculation method provided by this application can update the edge weight coefficient of the power system line when the power injected by the power source node changes, reflecting the actual operation of the power system and providing more accurate calculation results.

[0088] Based on the above method, some embodiments of the present application also provide a power system edge weight coefficient calculation system, which is applied to the method provided in the above embodiment, wherein the topology of the power system includes a power source node, a load node, a transmission node and at least one line, the power source node is connected to the load node through the line, and the transmission node is a node on the line. Figure 4 , the system includes:

[0089] The first calculation module is used to calculate the node impedance matrix of the topological structure, so as to calculate the first power variation and the second power variation according to the elements in the node impedance matrix.

[0090] Among them, the first power change is the power change on one of the lines caused by the power change of the source-load node pair by the first value, and the second power change is the power change on the other line caused by the power change of the source-load node pair by the first value; the source-load node pair is any combination of a power source node and a load node.

[0091] The second calculation module is configured to obtain a correlation coefficient according to the first power variation and the second power variation.

[0092] The correlation coefficient is the relationship between the power change of one line and another line when the power of the source-load node pair changes.

[0093] The third calculation module is used to calculate the third power variation according to the correlation coefficient.

[0094] The third power change is the power change on all lines caused when the power of any one line changes by the second value.

[0095] The fourth calculation module is used to perform linear weighted superposition on the third power variation to obtain an edge weight coefficient.

[0096] As can be seen from the above technical solutions, the embodiment of the present application provides a method and system for calculating the edge weight coefficient of an electric power system. The method includes: calculating the node impedance matrix of the topological structure to calculate the first power change and the second power change according to the elements in the node impedance matrix, wherein the first and second power changes are respectively the power changes caused on different lines when the power of the source-load node pair changes by a first value; obtaining a correlation coefficient according to the first and second power changes, wherein the correlation coefficient is the relationship between the power changes between two different lines when the power of the source-load node pair changes; calculating a third power change according to the correlation coefficient, wherein the third power change is the power change caused on all lines when the power of any line changes by a second value; performing linear weighted superposition on the third power change to obtain the edge weight coefficient. When the power injected by the power source node or the load node of the electric power system changes, it is only necessary to update the node injection power to obtain a new line edge weight coefficient, without the need for repeated iterative flow calculations, and the efficiency of the line edge weight coefficient calculation can be improved. Since there is no need to use weights for calculation, the interference of subjective weight factors on the line edge weight coefficient calculation can be reduced, making the calculation results more accurate, and thus the power system can be partitioned more accurately.

[0097] Similar parts between the embodiments provided in this application can be referenced to each other. The specific implementation methods provided above are only a few examples under the overall concept of this application and do not constitute a limitation on the scope of protection of this application. For those skilled in the art, any other implementation methods expanded based on the scheme of this application without expending creative work shall fall within the scope of protection of this application.

Claims

1. A method for calculating edge weight coefficients of a power system, characterized in that: The topology of the power system includes a power source node, a load node, a transmission node, and at least one line, wherein the power source node is connected to the load node via the line, and the transmission node is a node on the line; the method includes: Calculating a node impedance matrix of the topological structure to calculate a first power change and a second power change based on elements in the node impedance matrix; the first power change is a power change on one of the lines caused by a power change of a source-load node pair by a first magnitude; and the second power change is a power change on the other line caused by a power change of the source-load node pair by the first magnitude; the source-load node pair is any combination of a power source node and a load node; Obtaining a correlation coefficient based on the first power change and the second power change, where the correlation coefficient is a relationship between power changes of one line and another line when the power of the source-load node pair changes; Calculating a third power change according to the correlation coefficient, the third power change being the power change on all the lines caused when the power of any one of the lines changes by the second value; The third power variation is calculated by the following formula: in, is the third power variation caused by line x, x and y are the lines respectively, a is the number of lines, is the correlation coefficient between line x and line y; Performing linear weighted superposition on the third power variation to obtain an edge weight coefficient; The edge weight coefficient is calculated by the following formula: Among them, K x is the edge weight coefficient, G is the set of power nodes, L is the set of load nodes, P s Active power injected into the power node, P t is the active power consumed by the load node, min(P s ,P t ) is the smaller value between the active power injected into the power source node and the active power consumed by the load node.

2. The method for calculating edge weight coefficients of a power system according to claim 1, characterized in that: The first power variation is calculated by the following formula: Where s is the source node, t is the load node, st is the source-load node pair, ij is any line, i and j are the transmission nodes on line ij, ΔP st is the first value, is the first power variation, X is is the element in the ith row and sth column of the node impedance matrix, X js is the element in the jth row and sth column of the node impedance matrix, X it is the element in the ith row and tth column of the node impedance matrix, X jt is the element in the jth row and tth column of the node impedance matrix, x ij is the reactance value of line ij.

3. The method for calculating edge weight coefficients of a power system according to claim 2, characterized in that: The second power variation is calculated by the following formula: Where mn is another line different from line ij, m and n are transmission nodes on line mn, is the second power variation, X ms is the element in the mth row and sth column of the node impedance matrix, X ns is the nth row and sth column element in the node impedance matrix, X mt is the element in the mth row and tth column of the node impedance matrix, X nt is the element in the nth row and tth column of the node impedance matrix, x mn is the reactance value of line mn.

4. The method for calculating edge weight coefficients of a power system according to claim 3, characterized in that: The acquiring of the correlation coefficient according to the first power variation and the second power variation includes: respectively acquiring a first correlation relationship between the first power variation and the first value and a second correlation relationship between the second power variation and the first value; Eliminate the first value in the first association relationship and the second association relationship to obtain the association coefficient.

5. The method for calculating edge weight coefficients of a power system according to claim 3, characterized in that: The correlation coefficient is calculated by the following formula: in, is the correlation coefficient between line ij and line mn.

6. The method for calculating edge weight coefficients of a power system according to claim 1, characterized in that: The method further comprises: Obtain a correspondence between the edge weight coefficients and the lines and the transmission nodes, so as to construct an edge weight coefficient matrix according to the edge weight coefficients.

7. A power system edge weight coefficient calculation system, characterized in that: The method applied to any one of claims 1 to 6, wherein the topology of the power system includes a power source node, a load node, a transmission node, and at least one line, the power source node is connected to the load node via the line, and the transmission node is a node on the line; the system includes: A first calculation module is configured to calculate a node impedance matrix of the topological structure, and calculate a first power change and a second power change based on elements in the node impedance matrix; the first power change is a power change on one of the lines caused by a power change of a source-load node pair by a first magnitude; the second power change is a power change on the other line caused by a power change of the source-load node pair by the first magnitude; the source-load node pair is any combination of a power source node and a load node; A second calculation module is configured to obtain a correlation coefficient based on the first power change and the second power change, where the correlation coefficient is a relationship between the power changes of one line and another line when the power of the source-load node pair changes; A third calculation module is configured to calculate a third power variation according to the correlation coefficient, wherein the third power variation is the power variation on all the lines caused when the power of any one of the lines changes by the second value; The fourth calculation module is used to perform linear weighted superposition on the third power variation to obtain an edge weight coefficient.

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