Distribution network node importance evaluation method based on structural and electrical indexes

Abstract

The invention provides a power distribution network node importance evaluation method based on structural and electrical indexes. The method comprises the following steps: step 1, obtaining structural parameters and electrical parameters of a power network; step 2, constructing a node importance evaluation structural index and an electrical index based on a structural hole theory; and finally, based on the structural index and the electrical index, determining the weight of each index by adopting an objective weight empowerment method, and calculating the importance of each node by introducing an ideal solution of information divergence and grey relational degree. According to the above steps, the method analyzes and evaluates the node importance of the power distribution network. Considering the radial structural characteristics of the power distribution network and most of the adjacent nodes of each node are the same, aiming at the characteristics, the weights of structural hole theory nodes in an adjacent node set are adjusted, so that the difference degree of the importance of different nodes is improved when the importance of the nodes of the power distribution network is evaluated, and the evaluation accuracy of the importance of the nodes of the power distribution network is improved. The method has applicability and superiority of the importance degree of the power distribution network nodes.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system planning, and in particular relates to a method for evaluating the importance of distribution network nodes based on structural and electrical indicators. Background Art

[0002] With the development of new power systems, distributed energy is connected to distribution networks, and the structure of distribution networks is becoming more and more complex. Therefore, it is necessary to enhance the reliability of distribution network operation and evaluate the importance of distribution network nodes. It is of great significance to establish a node importance assessment system that can be applied to distribution network scenarios and to retain important power supply in the event of an accident to avoid large-scale power outages.

[0003] The evaluation indicators considered in the evaluation of node importance are mainly topological structural characteristic indicators and electrical operation characteristic indicators. From a structural perspective, there are currently indicators such as degree, betweenness, close centrality, and cohesion based on complex network theory. However, the distribution network structure mostly adopts closed-loop design and open-loop operation. The grid is radial, and there are fewer ring structures in the topological structure, resulting in many nodes with the same number of adjacent nodes. If the above structural indicators are still used, it will be impossible to accurately judge the structural importance of the node; from the perspective of electrical operation, the distribution network is functionally to provide power for various users, and the reliability requirements for loads and power supplies are very high. Therefore, it is necessary to select indicators that focus on loads and power supplies when establishing electrical indicators. In terms of evaluation algorithms, the hierarchical analysis method, TOPSIS method, and CRITIC method have been very mature, but when evaluating the power network, the uncertainty of the power network will be taken into account, and the parameters of gray correlation and information divergence will be added.

[0004] In summary, a method for evaluating the importance of distribution network nodes based on structural and electrical indicators is proposed. Based on the structural hole theory, structural indicators and electrical indicators for evaluating node importance are constructed. Structural indicators include the degree of node dependence on other nodes, the degree of node action on other nodes, and the overall impact of nodes on the network. Electrical indicators include the degree of influence of nodes on the voltage, power, and overall state of the power network. Finally, based on the structural and electrical indicators, the objective weighting method is used to determine the weight of each indicator, and then the importance of each node is calculated by introducing the ideal solution of information divergence and grey correlation. This method analyzes and evaluates the importance of distribution network nodes based on the above steps. Considering the radial structural characteristics of the distribution network, the number of adjacent nodes of each node is mostly the same. In view of this feature, this method adjusts the weight of the structural hole theory node in the adjacent node set to improve the difference in the importance of different nodes when evaluating the importance of distribution network nodes. It has the applicability and superiority of the importance of distribution network nodes. Summary of the invention

[0005] Aiming at the radial structural characteristics of the distribution network, the number of adjacent nodes of each node is mostly the same, and the difference in importance of different nodes is not obvious, the present invention proposes a distribution network node importance evaluation method based on structural and electrical indicators.

[0006] The solution of the present invention is: a method for evaluating the importance of distribution network nodes based on structural and electrical indicators, comprising the following steps:

[0007] Step 1: Obtain the power network structure parameters and electrical parameters. The structure parameters include the grid adjacency matrix and line length; the electrical parameters include network flow data, power capacity, load data and line impedance parameters;

[0008] Step 2: Starting from the three aspects of the degree of influence of nodes by other nodes, the degree of influence of nodes on the overall grid, and the degree of influence of nodes on other nodes, considering the radial structure characteristics of the distribution network, based on the structural hole theory, the weight parameter of the adjacent node set of a certain node in another node is introduced into the shortest distance and the denominator node set is expanded, so that it can describe the relationship between a certain node and another node at the overall grid level, and construct a structural indicator for node importance evaluation;

[0009] Step 3: In the importance evaluation of power network nodes, electrical indicators are introduced, including power network efficiency deviation, node voltage deviation, and node power.

[0010] Step 4: Construct a node importance evaluation model. First, calculate the index value, build a decision matrix, make the index positive and standardized, use the CRITIC method, use the Gini coefficient and Kendall correlation coefficient to represent the index contrast and the conflict between indicators, determine the weight of each indicator, and finally use the ideal solution method. Use information divergence and grey correlation to calculate the distance between each node solution and the positive and negative ideal solutions, so as to obtain the comprehensive importance of the node.

[0011] The node importance evaluation index system is divided into two categories, namely structural index and electrical index, which are composed of six indicators, namely:

[0012] The shortest distance is introduced to describe the network constraint number of the weight parameters between nodes, which shows the degree to which the object node is affected by other nodes;

[0013] Network performance - effective scale indicator of node degree, which shows the influence of the object node on the overall network;

[0014] Node efficiency index, which reflects the impact of the object node on other nodes;

[0015] The power network performance deviation index reflects the impact of the object node on the power network operation status;

[0016] The node voltage deviation index reflects the impact of the object node failure on the voltage stability of other nodes;

[0017] The node power index reflects the effect of the node on power transmission during operation.

[0018] This index system covers a wide range of angles and can provide a more comprehensive assessment of the importance of distribution network nodes.

[0019] In step 2, the structural hole theory indicator rule is:

[0020] First, the degree to which the node is affected by other nodes is represented by the network constraint number index:

[0021]

[0022] In the formula, p ij Represents the weight of node j in the set of adjacent nodes of node i; Represents the weight of the link between node i and node j.

[0023] Considering the radial structure of the distribution network, many nodes have the same number of adjacent nodes. The weight parameter of the adjacent node set of a certain node in another node is introduced into the shortest distance and the denominator node set is expanded to describe the relationship between a certain node and another node at the overall grid level, as follows:

[0024]

[0025] p i ' j = l ij / L i (4)

[0026]

[0027] In the formula, l ij represents the shortest distance from node i to node j, L i Represents the sum of the shortest distances from node i to other nodes in the grid.

[0028] The degree of influence of the node on the overall grid is expressed by the effective scale of the node:

[0029]

[0030] Where D i It represents the degree of node i and the number of adjacent nodes of node i.

[0031] Considering the radial structure of the distribution network, many nodes have the same number of adjacent nodes. Therefore, a new degree with node i as the center and the shortest distance passing through the line as the weight radius is introduced, and then combined with the network constraint number index, as follows:

[0032]

[0033] Where D i ' represents the newly defined degree of node i in the present invention, as follows:

[0034]

[0035] Where B a represents the node set whose number of paths through which the shortest distance to node i passes is a; n(B a ) means B a The number of nodes; k represents the maximum number of lines passing through the shortest distance in the grid; W a The weight of the node whose shortest distance to node i passes through is a.

[0036]

[0037] In the formula Represents the node set B a The sum of the shortest distances to node i.

[0038] The influence of the node on other nodes of the grid is expressed by the node efficiency index:

[0039] EF i '=1-(ES' i ×D' i ) / n (10)

[0040] Where ES' i Indicates the effective size of the node; D' i represents the new degree; n represents the number of nodes.

[0041] The power network performance deviation index described in step 3 is specifically defined as:

[0042]

[0043] Where A represents the power network performance deviation index; N G Indicates the number of power supplies; N D represents the number of loads; D and G represent the set of load nodes and power nodes respectively; min(P Gi ,P Dj ) indicates that the smaller value of the active power of the generator node and the active power of the load node represents the maximum power that can be transmitted between the "generation-load" node pair; Z eqijRepresents the electrical distance between the “generation-load” node pair (i, j);

[0044] The node voltage deviation index is specifically defined as:

[0045]

[0046] Where RV i represents the risk of node voltage deviation after the i-th node exits; V i Represents the voltage of other nodes after node i exits, V j Represents the voltage of other nodes after node j exits; V o is the voltage qualified value;

[0047] The node power index is specifically defined as:

[0048] PF i =p i

[0049] Where PF i represents the vulnerability of node i; p i It represents the active power value flowing through the i-th node after the power flow calculation.

[0050] In step 4, the structural hole theory indicator rule is: introducing the Gini coefficient and the Kendall correlation coefficient to represent the indicator contrast and the conflict between indicators respectively, determining the weight of each indicator and introducing the grey correlation degree to characterize the distance between each node solution and the positive and negative ideal solutions.

[0051] First, sort out the index values ​​calculated above and synthesize the decision matrix

[0052]

[0053] In the formula, n represents the number of nodes, m represents the number of indicators, and m in the present invention is 6.

[0054] The second step is to make the indicators positive and standardized, and determine whether each indicator is an extremely large indicator or an extremely small indicator. If an indicator is an extremely small indicator, it will be converted to an extremely large indicator.

[0055] The third step is to determine the weight of each indicator, which is calculated using the CRITIC method. The CRITIC method comprehensively measures the objective weight of the indicator based on the comparative strength of the evaluation indicators and the conflict between the indicators. The present invention uses the Gini coefficient and the Kendall correlation coefficient to represent the indicator contrast and the conflict between the indicators, respectively.

[0056] The Gini coefficient of the jth indicator is as follows:

[0057]

[0058] In the formula Represents the average index value of the dth index.

[0059] The Kendall correlation coefficient between the jth indicator and the remaining indicators is as follows:

[0060]

[0061] Where Tau dt The Kendall coefficient between the dth index and the tth index; Tau d represents the total Kendall coefficient between the dth indicator and other indicators; M is the smaller value of the row and column of the matrix; C represents the number of consistent elements in the matrix composed of the two indicators, that is, (x cd >x kd , x ct >x kt ) or (x cd <x kd , x ct <x kt ); D represents the number of inconsistency elements in the matrix composed of the two indicators, that is, (x cd >x kd , x ct <x kt ) or (x cd <x kd , x ct >x kt ).

[0062] CRITIC method to determine weights:

[0063]

[0064] Step 4: Determine the positive and negative ideal solutions

[0065]

[0066] In the formula x cd Represents X c The element in the cth row and dth column of .

[0067] The fifth step uses information divergence to calculate the distance between the node and the positive and negative ideal solutions

[0068]

[0069] In the formula and Represent the information divergence distance value between node i and the positive and negative ideal solutions respectively.

[0070] The sixth step is to calculate the difference between the node solution and the positive and negative ideal solutions by taking into account the complex direct or indirect coupling relationship between the nodes of each line.

[0071]

[0072] Where h id ± represents the grey correlation coefficient between the ith node solution and the dth index; H i ± It represents the grey correlation degree of the i-node scheme; ρ is the resolution coefficient, which is generally 0.5.

[0073] Finally, the information divergence value and the grey correlation degree (the weight of each is 0.5) are combined to calculate the fit of each node with the positive and negative ideal solutions, so as to obtain the comprehensive fit of each node with the ideal solution.

[0074]

[0075] Where T i Represents the comprehensive closeness, the larger it is, the greater the importance of the node.

[0076] Therefore, the present invention has the following advantages:

[0077] Aiming at the problem that the original structural hole theory index cannot accurately reflect the node importance in a distribution network with a radial structure and the number of adjacent nodes is mostly the same, the present invention introduces the weight parameter of the adjacent node set of a certain node in the structural hole theory index into the shortest distance and expands the denominator node set, so that it can describe the relationship of a certain node to another node at the overall grid level, and introduces a new degree with a certain node as the center and the shortest distance passing line as the weight radius, so that the node importance evaluation at the structural level is more accurate.

[0078] In view of the fact that the distribution network is to provide power for various users and has very high requirements for the reliability of loads and power supplies, the present invention combines network performance deviation, voltage deviation and node power to construct electrical indicators. All three indicators fully involve power supplies and loads, making node importance assessment more targeted for distribution networks. At the same time, information divergence and gray correlation are introduced to describe the distance between node solutions and positive and negative ideal solutions, which is more in line with power network scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 Distribution network node importance evaluation index system;

[0080] Figure 2 Distribution network node importance assessment flow chart;

[0081] Figure 3 Seven-point radial network topology diagram;

[0082] Figure 4A comparison chart of the network constraint number index and the network constraint number of the present invention, a comparison chart of the effective scale index and the effective scale index of the present invention, and a comparison chart of the node efficiency index and the node efficiency index of the present invention;

[0083] Figure 5 IEEE39 node standard system grid diagram;

[0084] Figure 6 Indicator weight comparison chart;

[0085] Figure 7 Comparison of structural characteristic indicators;

[0086] Figure 8 Histogram of distribution network node importance evaluation results. DETAILED DESCRIPTION

[0087] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in each embodiment of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0088] The following are preferred embodiments of the present invention, and in conjunction with the accompanying drawings, the specific application of the present invention is further described.

[0089] The specific implementation of the present invention is to involve a distribution network node importance evaluation method based on structural and electrical indicators, specifically:

[0090] Step 1: The present invention adopts Figure 5 The IEEE39 node standard system grid is shown, and the power network structure parameters and electrical parameters are obtained. The structure parameters include the grid adjacency matrix and line length; the electrical parameters include network flow data, power capacity, load data and line impedance parameters.

[0091] Step 2: Construct structural indicators for node importance evaluation

[0092] (1) First, calculate the node network constraint number index:

[0093]

[0094] p i ' j = l ij / L i (twenty two)

[0095]

[0096] Where M(i) represents the set of nodes directly connected to node i, and M(j) represents the set of nodes directly connected to node j; p' ij represents the weight ratio of node j in M(i); where l ij represents the shortest distance from node i to node j, L i Represents the sum of the shortest distances from node i to other nodes in the grid.

[0097] (2) Calculate the effective scale index of the structural hole theory node:

[0098]

[0099] Where B a represents the node set whose shortest distance to node i passes through j nodes; n(B a ) means B a The number of nodes; k represents the maximum number of lines passing through the shortest distance in the grid; W a The weight of the node whose shortest distance to node i passes through is a; Represents the node set B a The sum of the shortest distances to node i.

[0100] (3) Calculate the theoretical node efficiency index of structural holes:

[0101] EF i '=1-(ES i '×D i ') / n (27)

[0102] Where ES i ' represents the effective size of the node after improvement; D i ' represents the degree of improvement; n represents the number of nodes.

[0103] The present invention is as follows Figure 3 The seven-point topological diagram of the invention compares the structural hole index proposed by the present invention with the traditional structural hole index, and the comparison results are shown in Table 1.

[0104] Table 1 Comparison results between the structural hole index proposed in this invention and the traditional structural hole index

[0105]

[0106] By the attached Figure 4 It can be concluded that the structural index of the present invention can distinguish nodes that cannot be distinguished by the traditional structural hole index, such as nodes 1, 2 and nodes 5, 6.

[0107] Step 3: Construct electrical indicators for node importance assessment

[0108] First, perform power flow calculation on the system and record its node voltage value, node power value, generator node and load node active power value.

[0109] Adopting the N-1 method, each time one of the nodes is removed, the flow calculation is performed on the remaining power network, and the node voltage value, node power value, generator node and load node active power value are recorded until each node has been removed once.

[0110]

[0111] △A i =A 0 -A i (29)

[0112]

[0113] PF i =p i (31)

[0114] Where N G Indicates the number of power supplies, N D represents the number of loads; D and G represent the set of load nodes and power nodes respectively; min(P Gi ,P Dj ) indicates that the smaller value of the active power of the generator node and the active power of the load node represents the maximum power that can be transmitted between the "generation-load" node pair; Z eqij Represents the electrical distance between the "generation-load" node pair (i, j), that is, the impedance value of the shortest line between the nodes; RV i represents the risk of node voltage deviation after the i-th node exits; V i represents the voltage of other nodes after node i exits; p i It represents the active power value flowing through the i-th node after the power flow calculation.

[0115] Step 4: Construct a node importance evaluation model

[0116] (1) Arrange the index values ​​calculated above and synthesize the decision matrix

[0117]

[0118] Where n represents the number of nodes, and m represents the number of indicators.

[0119] (2) Positive and standardized indicators

[0120] Determine whether each indicator is an extremely large indicator or an extremely small indicator. If an indicator is an extremely small indicator, use the following formula to positively transform it into an extremely large indicator.

[0121]

[0122] Where max(Y d )=max{y cd |1≤i≤n}.

[0123] The normalized indicator matrix is ​​standardized to obtain a new decision matrix X = n × m [x cd ]

[0124]

[0125] The standardized decision matrix is ​​shown in Table 2.

[0126] Table 2 Standardized decision matrix

[0127]

[0128]

[0129] (3) Determine the weight of each indicator

[0130] The CRITIC method is used for calculation. The CRITIC method comprehensively measures the objective weight of the indicator based on the contrast strength of the evaluation indicators and the conflict between the indicators. The Gini coefficient and the Kendall correlation coefficient are used in the present invention to represent the indicator contrast and the conflict between the indicators respectively.

[0131] The Gini coefficient of the jth indicator is as follows:

[0132]

[0133] In the formula Represents the average index value of the dth index.

[0134] The Kendall correlation coefficient between the jth indicator and the remaining indicators is as follows:

[0135]

[0136] Where Tau dt The Kendall coefficient between the dth index and the tth index; Tau d represents the total Kendall coefficient between the dth indicator and other indicators; M is the smaller value of the row and column of the matrix; C represents the number of consistent elements in the matrix composed of the two indicators, that is, (x cd >x kd , x ct >x kt ) or (x cd <x kd , x ct <x kt ); D represents the number of inconsistency elements in the matrix composed of the two indicators, that is, (xcd >x kd , x ct <x kt ) or (x cd <x kd , x ct >x kt ).

[0137] CRITIC method to determine weights:

[0138]

[0139] The weights of each indicator are calculated, as shown in Table 3.

[0140] Table 3 Index weights

[0141]

[0142] (4) Determine positive and negative ideal solutions

[0143]

[0144] In the formula x cd Represents X c The element in the cth row and dth column of .

[0145] (5) Use information divergence to calculate the distance between the node and the positive and negative ideal solutions

[0146]

[0147] In the formula and Represent the information divergence distance value between node i and the positive and negative ideal solutions respectively.

[0148] (6) Considering the complex direct or indirect coupling relationship between each line node, the grey correlation degree is calculated to express the difference between the node solution and the positive and negative ideal solutions.

[0149]

[0150] Where h id ± represents the grey correlation coefficient between the ith node solution and the dth index; H i ± It represents the grey correlation degree of the i-node scheme; ρ is the resolution coefficient, which is generally 0.5.

[0151] (7) By combining the information divergence value and the grey correlation degree (the weight of the present invention is selected as 0.5 each), the fit degree of each node with the positive and negative ideal solutions is calculated, thereby obtaining the comprehensive fit degree of each node with the ideal solution.

[0152]

[0153] Where T i Represents the comprehensive closeness, the larger it is, the greater the importance of the node.

[0154] The results are shown in Table 4, which shows the comparison of the top ten node importance results of the method of the present invention and other methods. The node importance ranking histogram of the present invention is shown in the attached figure. Figure 8 .

[0155] Table 4 Results of the top ten nodes in node importance evaluation

[0156]

[0157]

[0158] The Gini coefficient can characterize the conflict of index values. From Table 1, the Gini coefficients of the original structural hole indexes are 0.0659, 0.0631, and 0.0511, respectively, while the Gini coefficients of the structural index values ​​of the present invention are 0.0732, 0.0767, and 0.0791, respectively. It can be seen that the conflict of the structural index values ​​in the present invention becomes greater, and can better reflect the differences in nodes.

[0159] By the attached Figure 7 From Table 2, we can see that the distribution characteristics of the three structural characteristic indicators at each node are relatively consistent, with the highest point at node 16 and the lowest at nodes 30-38. From the IEEE39 node diagram, we can see that these points are at the edge of the network, which also confirms that the structural indicators tend to be nodes in the center of the network structure and are not friendly to the importance assessment of edge nodes. Although the distribution of the three indicators is roughly the same, there are some differences. For example, for nodes 3, 4, and 5, it can be found that the node efficiency indicators of these three nodes are smaller than the other two indicators. This is because the node efficiency indicator focuses on the impact of the node on other nodes, and the degree of 3, 4, and 5 is 2, which is not dominant.

[0160] By the attached Figure 8 From Table 4, we can see the final node importance evaluation results obtained by the present invention. We can see that compared with other methods, the top ten nodes have the same nodes such as 16, 26, 19, 4, 3, 6, and 14, which shows that the indicators and methods adopted by the present invention are effective. However, there are also differences. For example, nodes 26 and 19 are ranked higher in the present invention, mainly because these two nodes are connected to multiple loads and power supplies. In addition, node 29 appears in the top ten, and it can be seen that the node is on the edge of the node, but its ranking is higher because the 38 nodes connected to it have power supplies and loads. From the entire importance distribution diagram, we can see that due to the multi-faceted consideration of the indicators, the node importance evaluation is globally considered. For example, although 35 and 36 are on the edge, they still have good evaluation values.

Claims

1. A method for evaluating the importance of distribution network nodes based on structural and electrical indicators, characterized in that: The following steps are involved: Step 1: Obtain the power network structural parameters and electrical parameters. The structural parameters include the grid adjacency matrix and line length. Electrical parameters include network flow data, power supply capacity, load data and line impedance parameters; Step 2: Starting from the three aspects of the degree of influence of nodes by other nodes, the degree of influence of nodes on the overall grid, and the degree of influence of nodes on other nodes, considering the radial structure characteristics of the distribution network, based on the structural hole theory, the weight parameter of the adjacent node set of a certain node in another node is introduced into the shortest distance and the denominator node set is expanded, so that it can describe the relationship between a certain node and another node at the overall grid level, and construct a structural indicator for node importance evaluation; Step 3: In the importance evaluation of power network nodes, electrical indicators are introduced, including power network performance deviation, node voltage deviation, and node power. Step 4: Construct a node importance evaluation model. First, calculate the index value, build a decision matrix, make the index positive and standardized, use the CRITIC method, and determine the weight of each index through the structural hole theory index rules. Finally, use the ideal solution method, use information divergence and grey correlation calculation to characterize the distance between each node solution and the positive and negative ideal solutions, so as to obtain the comprehensive importance of the node.

2. The method for evaluating the importance of distribution network nodes based on structural and electrical indicators according to claim 1 is characterized in that: The node importance evaluation index system is divided into two categories, namely structural index and electrical index, which are composed of six indicators, namely: The shortest distance is introduced to describe the network constraint number of the weight parameters between nodes, which shows the degree to which the object node is affected by other nodes; Network performance - effective scale indicator of node degree, which shows the influence of the object node on the overall network; Node efficiency index, which reflects the impact of the object node on other nodes; The power network performance deviation index reflects the impact of the object node on the power network operation status; The node voltage deviation index reflects the impact of the object node failure on the voltage stability of other nodes; The node power index reflects the effect of the node on power transmission during operation; This index system covers a wide range of angles and can provide a more comprehensive assessment of the importance of distribution network nodes.

3. The method for evaluating the importance of distribution network nodes based on structural and electrical indicators according to claim 1 is characterized in that: In step 2, structural indicators are constructed based on the structural hole theory from three aspects. The structural hole theory indicator rules are: First, the degree to which the node is affected by other nodes is represented by the network constraint number index: In the formula, C i represents the network constraint index of node i, p ij represents the weight of node j in the set of adjacent nodes of node i; p iq represents the weight of node q in the set of adjacent nodes of node i; p qj represents the weight of node j in the set of neighboring nodes of node q; m(i) represents the set of neighboring nodes of node i; m(j) represents the neighboring set of node j; Represents the weight of the line between node i and node j; Considering the radial structure of the distribution network, many nodes have the same number of adjacent nodes. The weight parameter of the adjacent node set of a certain node in another node is introduced into the shortest distance and the denominator node set is expanded to describe the relationship between a certain node and another node at the overall grid level, as follows: p i ' j =l ij / L i (4) In the formula, C i ' represents the improved network constraint index of node i, p ij ' represents the weight of node j in the adjacent node set of node i after improvement; p iq ' represents the weight of the improved node q in the adjacent node set of node i; p qj ' represents the weight of node j in the adjacent node set of node q after improvement; l ih It represents the ratio of the shortest distance between node i and node h to the sum of the shortest distances from node i to other nodes; l ij represents the shortest distance from node i to node j, L i Represents the sum of the shortest distances from node i to other nodes in the grid; The degree of influence of the node on the overall grid is expressed by the effective scale of the node: Where ES i represents the traditional effective scale of node i; D i represents the degree of node i, which represents the number of adjacent nodes of node i; Considering the radial structure of the distribution network, many nodes have the same number of adjacent nodes. Therefore, a new degree with node i as the center and the shortest distance passing through the line as the weight radius is introduced, and then combined with the network constraint number index, as follows: Where ES i ' represents the effective scale newly defined by the present invention for node i; D i ' represents the newly defined degree of node i in the present invention, as follows: Where B a represents the node set whose number of paths through which the shortest distance to node i passes is a; n(B a ) means B a The number of nodes; k represents the maximum number of lines passing through the shortest distance in the grid; W a The weight of the node whose shortest distance to node i passes through is a; In the formula Represents the node set B a The sum of the shortest distances to node i; The influence of the node on other nodes of the grid is expressed by the node efficiency index: EF i '=1-(ES i '×D i ') / n (10) Where ES i ' indicates the effective size of the node; D i ' represents the new degree; n represents the number of nodes.

4. The method for evaluating the importance of distribution network nodes based on structural and electrical indicators according to claim 1 is characterized in that: The power network performance deviation index described in step 3 is specifically defined as: Where A represents the power network performance deviation index; N G Indicates the number of power supplies; N D represents the number of loads; D and G represent the set of load nodes and power nodes respectively; min(P Gi ,P Dj ) indicates that the smaller value of the active power of the generator node and the active power of the load node represents the maximum power that can be transmitted between the "generation-load" node pair; Z eqij Represents the electrical distance between the "generation-load" node pair (i, j); The node voltage deviation index is specifically defined as: Where RV i represents the risk of node voltage deviation after the i-th node exits; V i Represents the voltage of other nodes after node i exits, V j Represents the voltage of other nodes after node j exits; V o is the voltage qualified value; The node power index is specifically defined as: PF i =p i Where PF i represents the vulnerability of node i; p i It represents the active power value flowing through the i-th node after the power flow calculation.

5. The method for evaluating the importance of distribution network nodes based on structural and electrical indicators according to claim 1 is characterized in that: In step 4, a node importance evaluation model is constructed, and the structural hole theory indicator rule is as follows: the Gini coefficient and the Kendall correlation coefficient are introduced to represent the indicator contrast and the conflict between indicators respectively, the weight of each indicator is determined, and the grey correlation degree is introduced to represent the distance between each node solution and the positive and negative ideal solutions; First, sort out the index values ​​calculated above and synthesize the decision matrix Where n represents the number of nodes, and m represents the number of indicators; The second step is to make the indicators positive and standardized, and determine whether each indicator is an extremely large indicator or an extremely small indicator. If an indicator is an extremely small indicator, it will be converted to an extremely large indicator. The conversion formula is as follows: Where x ij It is a very small indicator. is the index after conversion; The third step is to determine the weight of each indicator, which is calculated using the CRITIC method. The CRITIC method comprehensively measures the objective weight of the indicator based on the comparative strength of the evaluation indicators and the conflict between the indicators. The Gini coefficient and Kendall correlation coefficient are used to represent the indicator contrast and the conflict between the indicators respectively. The Gini coefficient of the jth indicator is as follows: Where x cd represents the element in the cth row and dth column of Y; x kd represents the element in the kth row and dth column of Y; x cd -x kd | represents the absolute value between two elements; n z Indicates the total number of indicators; represents the average index value of the dth index; The Kendall correlation coefficient between the jth indicator and the remaining indicators is as follows: Where Tau dt The Kendall coefficient between the dth index and the tth index; Tau d represents the total Kendall coefficient between the dth indicator and other indicators; M is the smaller value of the row and column of the matrix; C represents the number of consistent elements in the matrix composed of the two indicators, that is, (x cd >x kd , x ct >x kt ) or (x cd <x kd , x ct <x kt ); D represents the number of inconsistency elements in the matrix composed of the two indicators, that is, (x cd >x kd , x ct <x kt ) or (x cd <x kd , x ct >x kt ); CRITIC method to determine weights: Where ω d is the weight coefficient of indicator d; Step 4: Determine the positive and negative ideal solutions In the formula x cd represents the element in the cth row and dth column of Y; The fifth step uses information divergence to calculate the distance between the node and the positive and negative ideal solutions Where x id represents the element in the i-th row and d-th column of Y; and Respectively represent the information divergence distance value between node i and the positive and negative ideal solutions; The sixth step is to calculate the difference between the node solution and the positive and negative ideal solutions by taking into account the complex direct or indirect coupling relationship between the nodes of each line. Where h ij ± It represents the grey correlation coefficient between the i-th node solution and the j-th index; Indicates the extreme value of the elements in Y; h id ± represents the grey correlation coefficient between the ith node solution and the dth index; H i ± Represents the grey correlation degree of the i-node scheme; ρ is the resolution factor, generally 0.5; Finally, the information divergence value and the grey correlation degree are combined, and the weights are selected as 0.5 for each, and the fit degree of each node with the positive and negative ideal solutions is calculated, so as to obtain the comprehensive fit degree of each node with the ideal solution; In the formula Indicates the closeness of the weighted information divergence of node i to the positive ideal solution; Indicates the comprehensive closeness between node i and the positive ideal solution; H i + Represents the grey relational degree of node i for the positive ideal solution; Indicates the closeness of the weighted information divergence of node i to the negative ideal solution; Indicates the comprehensive closeness between node i and the negative ideal solution; H i - represents the grey relational degree of node i for the negative ideal solution; a q The weight coefficient that represents the closeness of the weighted information divergence to the positive ideal solution and the negative ideal solution; b q Represents the weight coefficient of the grey correlation degree of the node for the positive ideal solution and the negative ideal solution; T i Represents the comprehensive closeness, the larger it is, the greater the importance of the node.

6. The method for evaluating the importance of distribution network nodes based on structural and electrical indicators according to claim 1 is characterized in that: In formula (11), m=6.

7. The method for evaluating the importance of distribution network nodes based on structural and electrical indicators according to claim 1 is characterized in that: In formula (18), ρ is 0.5.

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