Power grid load node-based importance evaluation method and device, terminal equipment and storage medium

Abstract

The invention discloses an importance evaluation method and device based on a power grid load node, terminal equipment and a storage medium, and the method comprises the steps: calculating a topology coefficient index of the load node according to a node parameter and a line parameter of the load node, so as to evaluate the structure importance of each load node in a power transmission network, and calculating a power failure loss index of the load node according to the user type and the power utilization information of the load node so as to evaluate the importance of each load node in social and economic aspects. And finally, according to the adjusting capacity and the adjusting speed of each adjustable load type in the load nodes, calculating an adjustable capability index of the load nodes so as to evaluate the importance of each load node in the aspect of keeping the stable operation of the power grid. In conclusion, the importance of each load node is comprehensively evaluated from the aspects of the structure of the load node, the social economy and the maintenance of stable operation of the power grid, a theoretical basis is provided for subsequent power resource configuration, and the reliability and the stability of a power system are improved.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a method, device, terminal equipment and storage medium for evaluating the importance of power grid load nodes. Background Art

[0002] The power system provides standard electricity to all types of users and is the cornerstone of national and social prosperity. With the diversification of grid load types and the continuous expansion of the scale of the power system, ensuring a continuous and high-quality power supply has become more challenging. At the same time, the rapid development of new energy has gradually integrated new energy such as wind energy and solar energy into the power system. The future power system will be more diversified, which puts forward new requirements for maintaining the stable operation of the power grid. At present, by evaluating the importance of load nodes and giving priority to the power supply of load nodes with high importance when allocating power resources, the reliability and stability of the entire power system can be ensured.

[0003] However, most of the current research on the importance of load nodes is carried out from the perspective of topological structure characteristics, and less consideration is given to some electrical characteristic indicators. For example, in the research on grid reconstruction, although the level of load nodes is taken into consideration when selecting power supply restoration load nodes, the importance of loads is only expressed by the proportion of different load levels, which is not precise enough in the current situation where the types of loads are increasing. Therefore, how to evaluate the importance of load nodes from multiple aspects has become an urgent problem to be solved. Summary of the invention

[0004] The embodiments of the present invention provide a method, apparatus, terminal device and storage medium for evaluating the importance of load nodes in a power grid. The method accurately evaluates the importance of each load node from multiple aspects, including the structure, socio-economic aspects and maintaining stable operation of the power grid. This provides a theoretical basis for accurately prioritizing the power supply of load nodes with high importance during the subsequent configuration of power resources, thereby improving the reliability and stability of the entire power system.

[0005] An embodiment of the present invention provides a method for evaluating the importance of a power grid load node, comprising:

[0006] Obtain node parameters, line parameters, user types, and power consumption information of several load nodes in the power grid;

[0007] Calculate the topology coefficient index of each load node according to the node parameters and the line parameters; wherein the topology coefficient index is used to characterize the degree of connection between each load node and other nodes;

[0008] Calculating a power outage loss index of each load node according to the user type and the power consumption information;

[0009] Filtering load power usage information of several adjustable load types of each load node from the power usage information, and calculating the adjustment capacity and adjustment speed of each adjustable load type according to the load power usage information;

[0010] Calculating the adjustable capacity index of each load node according to the adjustable capacity and the adjustable speed;

[0011] The importance score of each load node is calculated according to the topology coefficient index, the power outage loss index, and the adjustable capacity index.

[0012] Furthermore, the calculating of the topological coefficient index of each load node according to the node parameters and the line parameters includes:

[0013] Determine the total number of connection nodes connected to each of the load nodes and the number of connection lines between each of the load nodes and each connection node according to the node parameters and the line parameters;

[0014] Calculating the initial clustering coefficient of each load node according to the total number of nodes and the number of connection lines;

[0015] Calculating a clustering coefficient for a clustering scale of each of the load nodes according to the initial clustering coefficient and the total number of nodes of a plurality of connection nodes of each of the load nodes;

[0016] Calculating the center coefficient of each load node according to the shortest connection distance between each load node and each connection node;

[0017] The topological coefficient index of each load node is calculated according to the central coefficient and the clustering coefficient.

[0018] Furthermore, the calculating of the topological coefficient index of each load node according to the central coefficient and the clustering coefficient includes:

[0019] Comparing the central coefficients and clustering coefficients of the load nodes respectively, and determining the maximum central coefficient and the maximum clustering coefficient among the load nodes;

[0020] The topological coefficient index of each load node is calculated by the following formula:

[0021]

[0022] Among them, R i is the topological coefficient index of the i-th load node, C i is the center coefficient of the i-th load node, C maxis the maximum center coefficient, J i is the clustering coefficient of the i-th load node, J max is the maximum clustering coefficient.

[0023] Furthermore, the calculating of the power outage loss index of each load node according to the user type and the power consumption information includes:

[0024] According to the user type and the electricity consumption information, calculating the unit price of power outage loss for each user type;

[0025] Calculate the power consumption of each user at each load node at each moment according to the power consumption information;

[0026] The power outage loss index of each load node is calculated according to the power outage loss unit price and the power consumption.

[0027] Furthermore, the power outage loss index of each load node is calculated according to the power outage loss unit price and the power consumption, including:

[0028] The power outage loss index of each load node is calculated according to the following formula:

[0029]

[0030] Among them, D lose,i is the power outage loss index of the ith load node, d lose,j is the unit price of power outage loss of the jth user type in the i-th load node, P t,j is the power consumption of the jth user in the i-th load node at time t, and N is the total number of users in the i-th load node.

[0031] Furthermore, the calculating the importance score of each load node according to the topology coefficient index, the power outage loss index, and the adjustable capacity index includes:

[0032] According to the topology coefficient index, the power outage loss index, and the adjustable capacity index, an importance decision matrix is ​​constructed; wherein each row of the importance decision matrix is ​​composed of the topology coefficient index, the power outage loss index, and the adjustable capacity index of the same load node;

[0033] The Gini coefficient method and the Kendall correlation coefficient method are used to calculate the Gini coefficient and the Kendall correlation coefficient of each column of the importance decision matrix;

[0034] Determine, according to the Gini coefficient and the Kendall correlation coefficient, a first weight of the topology coefficient index, a second weight of the power outage loss index, and a third weight of the adjustable capacity index;

[0035] The importance score of each load node is calculated according to the first weight, the second weight, the third weight, and the importance decision matrix.

[0036] Another embodiment of the present invention provides a device for evaluating the importance of a power grid load node, comprising:

[0037] A data acquisition module is used to obtain node parameters, line parameters, user types, and power consumption information of several load nodes in the power grid;

[0038] A first index calculation module is used to calculate the topology coefficient index of each load node according to the node parameters and the line parameters; wherein the topology coefficient index is used to characterize the degree of connection between each load node and other nodes;

[0039] A second index calculation module, used to calculate the power outage loss index of each load node according to the user type and the power consumption information;

[0040] A data calculation module, used to filter out load power consumption information of several adjustable load types of each load node from the power consumption information, and calculate the adjustment capacity and adjustment speed of each adjustable load type according to the load power consumption information;

[0041] A third indicator calculation module, used to calculate the adjustable capacity indicator of each load node according to the adjustment capacity and the adjustment speed;

[0042] The importance evaluation module is used to calculate the importance score of each load node according to the topology coefficient index, the power outage loss index, and the adjustable capacity index.

[0043] Furthermore, the calculating of the topological coefficient index of each load node according to the node parameters and the line parameters includes:

[0044] Determine the total number of connection nodes connected to each of the load nodes and the number of connection lines between each of the load nodes and each connection node according to the node parameters and the line parameters;

[0045] Calculating the initial clustering coefficient of each load node according to the total number of nodes and the number of connection lines;

[0046] Calculating a clustering coefficient for a clustering scale of each of the load nodes according to the initial clustering coefficient and the total number of nodes of a plurality of connection nodes of each of the load nodes;

[0047] Calculating the center coefficient of each load node according to the shortest connection distance between each load node and each connection node;

[0048] The topological coefficient index of each load node is calculated according to the central coefficient and the clustering coefficient.

[0049] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements a method for evaluating the importance of power grid load nodes based on any one of the embodiments.

[0050] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a method for evaluating the importance of power grid load nodes based on any one of the above embodiments.

[0051] The following beneficial effects are achieved by implementing the present invention:

[0052] The present invention discloses a method, device, terminal equipment and storage medium for evaluating the importance of load nodes in a power grid. The method calculates a topological coefficient index for characterizing the degree of connection between each load node and other nodes according to the node parameters and line parameters of several load nodes to evaluate the structural importance of each load node in the power transmission network. Further, according to the user types and power consumption information of several load nodes, the power outage loss index of each load node is calculated to evaluate the importance of each load node in social and economic aspects. Finally, according to the adjustment capacity and adjustment speed of each adjustable load type in each load node, the adjustable capacity index of each load node is calculated to evaluate the importance of each load node in maintaining the stable operation of the power grid. In summary, the present invention accurately evaluates the importance of each load node in terms of structure, social economy and maintaining the stable operation of the power grid, and provides a theoretical basis for accurately and preferentially guaranteeing the power supply of load nodes with high importance when configuring power resources in the future, thereby improving the reliability and stability of the entire power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of a method for evaluating the importance of power grid load nodes provided by one embodiment of the present invention.

[0054] Figure 2 It is a structural diagram of a power grid load node-based importance assessment device provided by one embodiment of the present invention.

[0055] Figure 3This is a daily load curve diagram of various types of users provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0058] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0059] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0060] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0061] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0062] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0063] See also Figure 1 , is a flow chart of a method for evaluating the importance of a power grid load node provided by an embodiment of the present invention, comprising:

[0064] S1. Obtain node parameters, line parameters, user types, and power consumption information of several load nodes in the power grid;

[0065] S2. Calculate the topology coefficient index of each load node according to the node parameters and the line parameters; wherein the topology coefficient index is used to characterize the degree of connection between each load node and other nodes;

[0066] Preferably, the calculating of the topological coefficient index of each load node according to the node parameters and the line parameters includes:

[0067] S21, determining the total number of connection nodes connected to each of the load nodes and the number of connection lines between each of the load nodes and each connection node according to the node parameters and the line parameters;

[0068] S22, calculating the initial clustering coefficient of each load node according to the total number of nodes and the number of connection lines;

[0069] In a preferred embodiment of the present invention, the calculation formula of the load aggregation coefficient is as follows:

[0070]

[0071] Among them, c i is the load aggregation coefficient of node i; D i is the degree of node i, that is, the number of nodes connected to node i; l i D of node i i The actual number of edges between neighboring nodes.

[0072] S23, calculating a clustering coefficient for a clustering scale of each of the load nodes according to the initial clustering coefficient and the total number of nodes of a plurality of connection nodes of each of the load nodes;

[0073] In a preferred embodiment of the present invention, since the initial clustering coefficient can only reflect the degree of clustering of nodes but cannot reflect the scale of neighboring nodes, the scale of neighboring nodes is taken into account to improve the initial clustering coefficient.

[0074]

[0075] In the formula, θ i is the normalization function, λ i is the sum of the degree of node i and the degrees of all its neighboring nodes;

[0076] The topological characteristics of loads in power networks need to be considered from two perspectives: their location information in the grid and their degree of connection with other nodes. The clustering coefficient comprehensively considers the influence of neighbor node information and node clustering degree information.

[0077] S24, calculating the center coefficient of each load node according to the shortest connection distance between each load node and each connection node;

[0078] In a preferred embodiment of the present invention, the calculation formula of load proximity centrality is as follows:

[0079]

[0080] Among them, J i is the center coefficient of the i-th load node; d ij is the shortest distance between node i and node j.

[0081] S25. Calculate the topological coefficient index of each load node according to the central coefficient and the clustering coefficient.

[0082] Preferably, the calculating of the topological coefficient index of each load node according to the central coefficient and the clustering coefficient includes:

[0083] S251, respectively comparing the central coefficients and clustering coefficients of the load nodes, and determining the maximum central coefficient and the maximum clustering coefficient among the load nodes;

[0084] S252. Calculate the topological coefficient index of each load node by the following formula:

[0085]

[0086] Among them, R i is the topological coefficient index of the i-th load node, C i is the clustering coefficient of the ith load node, C max is the maximum clustering coefficient, J i is the center coefficient of the i-th load node, Jmax is the maximum center coefficient.

[0087] In a preferred embodiment of the present invention, based on complex network theory, it is known that the closeness centrality of a node reflects the closeness of the connection between the node and other nodes in the network.

[0088] The calculation formula of the topological coefficient index is as follows:

[0089]

[0090] Among them, C max and J max It is the maximum value of load clustering coefficient and load proximity centrality.

[0091] S3. Calculating a power outage loss index of each load node according to the user type and the power consumption information;

[0092] Preferably, the calculating the power outage loss index of each load node according to the user type and the power consumption information includes:

[0093] S31, calculating the unit price of power outage loss for each user type according to the user type and the electricity consumption information;

[0094] S32, calculating the power consumption of each user at each load node at each moment according to the power consumption information;

[0095] S33. Calculate the power outage loss index of each load node according to the power outage loss unit price and the power consumption.

[0096] Preferably, the calculating of the power outage loss index of each load node according to the power outage loss unit price and the power consumption includes:

[0097] S331. Calculate the power outage loss index of each load node according to the following formula:

[0098]

[0099] Among them, D lose,i is the power outage loss index of the ith load node, d lose,j is the unit price of power outage loss of the jth user type in the i-th load node, P t,j is the power consumption of the jth user in the i-th load node at time t, and N is the total number of users in the i-th load node.

[0100] In a preferred embodiment of the present invention, user type information and power consumption information in the load node on the grid are obtained to construct a load power outage loss index;

[0101] Generally, loads are classified into industrial, commercial, residential and agricultural categories, but this classification is too general. Different users in the same category may be very different. For example, although the semiconductor industry and metal production belong to the same industry, the semiconductor industry is more sensitive to power outages than metal production. Therefore, if the two are grouped together to analyze the power outage loss, the error will be large. Therefore, the present invention adopts a more refined user classification method as shown in Table 1.

[0102] Table 1 Industry breakdown table;

[0103]

[0104]

[0105] Table 2 User classification results;

[0106]

[0107]

[0108] From the classification in Table 1, it can be seen that different industries have different sensitivities to losses caused by power outages. Among them, the losses caused by power outages in the semiconductor and pharmaceutical industries are much higher than those in other industries.

[0109] According to the classification method in Table 1, 165 electricity users of various types were selected from users in a certain place and classified by industry. The classification results are shown in Table 2.

[0110] According to the classification of users in Table 2, combined with the daily load curve of each user in this group in July 2017, the power outage loss is calculated. The daily load curve of some users is shown in the figure below: Figure 3 .

[0111] Assume that a load node in the grid contains N users, including industries such as industry and commerce, and residents. If there is a power outage for one hour, the loss can be calculated using the following formula.

[0112]

[0113] Among them, D lose,i represents the power outage loss of load i in the grid; d lose,j P represents the unit price of power outage loss of the jth user in the load node; t,j represents the electricity consumption of user j at time t.

[0114] S4, filtering out load power usage information of several adjustable load types of each load node from the power usage information, and calculating the adjustment capacity and adjustment speed of each adjustable load type according to the load power usage information;

[0115] In a preferred embodiment of the present invention, the controllable load is the main body of the load with adjustable capacity, which can be specifically divided into discrete adjustable load, continuously adjustable load and time-shift adjustable load. Considering several typical adjustable loads, for example, industrial adjustable loads such as electrolytic aluminum, silicon carbide, titanium alloy and civil loads such as electric vehicles, the load adjustable capacity index is calculated.

[0116] Table 3 Typical adjustable load regulation characteristic parameters;

[0117]

[0118] S5. Calculate the adjustable capacity index of each load node according to the adjustment capacity and the adjustment speed;

[0119] In a preferred embodiment of the present invention, since there are many loads that can participate in grid regulation in a district, the load regulation capability is calculated for a typical adjustable load in a district. Since the greater the regulation depth (regulation capacity) of the adjustable load, the better the regulation capability, and the greater the regulation speed, the better the regulation capability, the load regulation capability index is constructed with the regulation depth and regulation speed. The specific calculation expression is as follows:

[0120]

[0121] Among them, A i represents the load adjustable capacity index of load node i in the grid; P AL,j , P C,j , P Ti,j and P E,j They represent the adjustable depths of electrolytic aluminum, silicon carbide, titanium alloy and electric vehicle users in load node i respectively; v AL 、v C 、v Ti and v E They represent the load adjustment rates (adjustable amount per minute) of electrolytic aluminum, silicon carbide, titanium alloy and electric vehicle users in load node i respectively.

[0122] S6. Calculate the importance score of each load node according to the topology coefficient index, the power outage loss index, and the adjustable capacity index.

[0123] Preferably, calculating the importance score of each load node according to the topology coefficient index, the power outage loss index, and the adjustable capacity index includes:

[0124] S61, constructing an importance decision matrix according to the topology coefficient index, the power outage loss index, and the adjustable capacity index; wherein each row of the importance decision matrix is ​​composed of the topology coefficient index, the power outage loss index, and the adjustable capacity index of the same load node;

[0125] In a preferred embodiment of the present invention, the index value of each load is first calculated by the above index calculation method, and the decision matrix is ​​obtained:

[0126]

[0127] Among them, n represents the number of load nodes, m represents the number of indicators, and the column vector [x 1,m ,x 2,m ,…x n,m ] T Represents the mth index value vector of each load.

[0128] S62, using the Gini coefficient method and the Kendall correlation coefficient method to calculate the Gini coefficient and the Kendall correlation coefficient of each column of the importance decision matrix;

[0129] S63, determining a first weight of the topology coefficient index, a second weight of the power outage loss index, and a third weight of the adjustable capacity index according to the Gini coefficient and the Kendall correlation coefficient;

[0130] In a preferred embodiment of the present invention, the CRITIC method is used to determine the weight of each indicator. The Gini coefficient and the Kendall correlation coefficient are used in the present invention to represent the indicator contrast and the conflict between indicators respectively.

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

[0132]

[0133] Among them, x cd represents the element in the cth row and dth column of X; x kd represents the element in the kth row and dth column of X; |x cd -x kd | represents the absolute value between two elements; Represents the average index value of the dth index.

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

[0135]

[0136] Among them, Tau dt The Kendall coefficient between the dth index and the tth index; Taud 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 ).

[0137] CRITIC method to determine weights:

[0138]

[0139] Among them, ω d is the weight coefficient of indicator d.

[0140] S64. Calculate the importance score of each load node according to the first weight, the second weight, the third weight, and the importance decision matrix.

[0141] In a preferred embodiment of the present invention, the decision matrix is ​​normalized by combining the indicator weights to obtain a standardized weighted normative matrix Z, and the calculation formula is as follows:

[0142]

[0143] in, represents the normalization of the i-th load of the j-th indicator, x jmax With x jmin Represent the maximum and minimum values ​​of the j-th index respectively.

[0144] Furthermore, positive and negative ideal solutions are determined:

[0145]

[0146] in, x cd Represents the element in the cth row and dth column of X.

[0147] Furthermore, the information divergence is used to calculate the distance between the load scheme and the positive and negative ideal solutions:

[0148]

[0149] Among them, x id represents the element in the i-th row and d-th column of X; and Respectively represent the information divergence distance value between load scheme i and the positive and negative ideal solutions.

[0150] Furthermore, considering the various complex direct or indirect coupling relationships in the grid, the grey correlation degree is introduced to express the difference between the load scheme and the positive and negative ideal solutions:

[0151]

[0152] Among them, 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 X; h id ± represents the grey correlation coefficient between the ith load scheme and the dth index; H i ± It represents the grey correlation degree of load scheme i; ρ is the resolution coefficient, which is generally 0.5.

[0153] Finally, the information divergence value and the grey correlation degree (the weight of the present invention is selected as 0.5 each) are combined to calculate the fit of each load scheme with the positive and negative ideal solutions, so as to obtain the comprehensive fit of each node with the ideal solution.

[0154]

[0155] in, 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 correlation degree of node i for the negative ideal solution; a represents the weight coefficient of the weighted information divergence and the closeness between the positive ideal solution and the negative ideal solution; b represents the weight coefficient of the grey correlation degree of the node for the positive ideal solution and the negative ideal solution; T i It represents the comprehensive closeness, which is used to indicate the importance of each load. The larger the value, the greater the load importance.

[0156] According to the data calculated in the above steps, the comparison results of the load node importance evaluated by this embodiment and the load node importance evaluated by other existing methods are as follows:

[0157] Among them, the literature [1] is Zhao Yuxuan, Han Chang, Lin Zhenzhi, Yang Li, Wang Lei, Huang Jingjing. Two-stage core backbone grid optimization strategy for power system with renewable energy [J]. Power System Technology, 2019, 43(02);

[0158]

[0159] It can be observed from the above table that this embodiment comprehensively considers the topological characteristics and electrical characteristics of the load when calculating the comprehensive importance of the load. The top 10 load nodes include 7 in the comprehensive importance of the load, namely loads 3, 4, 16, 20, 21, 23, and 25, and these nodes are also ranked in the top 10 in the clustering coefficient index. However, although these 7 load nodes remain in the top ten, their relative rankings have changed. For example, for loads 3 and 4, the power outage loss index of load 4 is higher, resulting in its comprehensive ranking exceeding that of load 3; similarly, the ranking of load 25 has dropped because its power outage loss index and load regulation capacity index are not significant enough. In addition, although some load nodes are located in the central area, their comprehensive importance does not enter the top ten due to the lack of special enterprises such as semiconductors and relatively low load power, such as nodes 26, 29, and 24. This shows that the increase in the clustering coefficient means that the more central the load location is, the higher its importance is overall. However, the comprehensive importance is still affected by the power outage loss and load regulation capacity indicators.

[0160] The power outage loss index has the largest weight among these indicators and is therefore the most important indicator for evaluating load importance. Among the top ten loads with power outage loss indicators, nine also appear in the top ten of comprehensive importance. However, their rankings are also different. For example, for loads 23 and 25, load 20 has a higher clustering coefficient and similar load regulation capabilities, so load 25 ranks higher than load 23 in the comprehensive importance. Similarly, load 21 ranks lower due to the weaker indicators except for the power outage loss index.

[0161] The load regulation capability index is related to whether there is an industrial adjustable load in the load area. When evaluating the importance of loads, the load regulation capability index is not the most critical factor, but it still affects the comprehensive importance of the load to a certain extent. Among the top ten load regulation capability indicators, only 6 appear in the top ten of the comprehensive importance of loads. Although the weight of this indicator is low, it affects the evaluation of comprehensive importance to a certain extent. For example, load 16 ranks first in the comprehensive importance of loads due to its excellent regulation capability and outstanding load position.

[0162] Comparing the results of this study with the method in reference [1], it is found that 8 nodes are the same in the top ten loads, 3 nodes are the same in the top six, and the highest-ranked load node is load 16, which shows that the method of this study is feasible. However, there are still differences in the ranking of some nodes, such as load node 39, which ranks second in this study. This is mainly because load node 39 contains adjustable loads and conventional electronic manufacturing loads, and its rated capacity is relatively high. Another example is load nodes 8 and 20. Because they contain power outage-sensitive users, such as electronic manufacturing users, and the total load power is large and the power outage loss is high, and load 20 also contains adjustable industrial power supplies, their importance rankings have increased. By comparing the two methods, we can see that the method of this study not only considers the characteristics of the load nodes, but also the characteristics of the loads themselves, making the evaluation results more comprehensive.

[0163] In summary, refining the user types within the load area is closer to the actual situation than the usual evaluation based on indicators such as load location and total power of the load area.

[0164] This embodiment provides a method for evaluating the importance of load nodes in a power grid. The topological coefficient index used to characterize the degree of connection between each load node and other nodes is calculated according to the node parameters and line parameters of several load nodes to evaluate the structural importance of each load node in the power transmission network. Furthermore, the power outage loss index of each load node is calculated according to the user type and power consumption information of several load nodes to evaluate the importance of each load node in social and economic aspects. Finally, according to the adjustment capacity and adjustment speed of each adjustable load type in each load node, the adjustable capacity index of each load node is calculated to evaluate the importance of each load node in maintaining the stable operation of the power grid. In summary, the present invention accurately evaluates the importance of each load node from multiple aspects, including the structural aspects, social and economic aspects, and maintaining the stable operation of the power grid, so as to provide a theoretical basis for accurately and preferentially guaranteeing the power supply of load nodes with high importance when configuring power resources in the future, thereby improving the reliability and stability of the entire power system.

[0165] See also Figure 2 , is a schematic structural diagram of a device for evaluating the importance of a power grid load node according to an embodiment of the present invention, comprising:

[0166] A data acquisition module is used to obtain node parameters, line parameters, user types, and power consumption information of several load nodes in the power grid;

[0167] A first index calculation module is used to calculate the topology coefficient index of each load node according to the node parameters and the line parameters; wherein the topology coefficient index is used to characterize the degree of connection between each load node and other nodes;

[0168] A second index calculation module, used to calculate the power outage loss index of each load node according to the user type and the power consumption information;

[0169] A data calculation module, used to filter out load power consumption information of several adjustable load types of each load node from the power consumption information, and calculate the adjustment capacity and adjustment speed of each adjustable load type according to the load power consumption information;

[0170] A third indicator calculation module, used to calculate the adjustable capacity indicator of each load node according to the adjustment capacity and the adjustment speed;

[0171] The importance evaluation module is used to calculate the importance score of each load node according to the topology coefficient index, the power outage loss index, and the adjustable capacity index.

[0172] Furthermore, the calculating of the topological coefficient index of each load node according to the node parameters and the line parameters includes:

[0173] Determine the total number of connection nodes connected to each of the load nodes and the number of connection lines between each of the load nodes and each connection node according to the node parameters and the line parameters;

[0174] Calculating the initial clustering coefficient of each load node according to the total number of nodes and the number of connection lines;

[0175] Calculating a clustering coefficient for a clustering scale of each of the load nodes according to the initial clustering coefficient and the total number of nodes of a plurality of connection nodes of each of the load nodes;

[0176] Calculating the center coefficient of each load node according to the shortest connection distance between each load node and each connection node;

[0177] The topological coefficient index of each load node is calculated according to the central coefficient and the clustering coefficient.

[0178] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0179] Those skilled in the art can clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0180] Another preferred embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a method for evaluating the importance of power grid load nodes based on any one of the above embodiments.

[0181] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0182] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0183] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0184] Another preferred embodiment of the present invention provides a storage medium, the storage medium is a computer-readable storage medium, the computer program is stored in the computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0185] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for evaluating the importance of power grid load nodes, characterized in that: include: Obtain node parameters, line parameters, user types, and power consumption information of several load nodes in the power grid; Calculate the topology coefficient index of each load node according to the node parameters and the line parameters; wherein the topology coefficient index is used to characterize the degree of connection between each load node and other nodes; Calculating a power outage loss index of each load node according to the user type and the power consumption information; Filtering load power usage information of several adjustable load types of each load node from the power usage information, and calculating the adjustment capacity and adjustment speed of each adjustable load type according to the load power usage information; Calculating the adjustable capacity index of each load node according to the adjustable capacity and the adjustable speed; The importance score of each load node is calculated according to the topology coefficient index, the power outage loss index, and the adjustable capacity index.

2. A method for evaluating the importance of power grid load nodes according to claim 1, characterized in that: The calculating of the topological coefficient index of each load node according to the node parameters and the line parameters includes: Determine the total number of connection nodes connected to each of the load nodes and the number of connection lines between each of the load nodes and each connection node according to the node parameters and the line parameters; Calculating the initial clustering coefficient of each load node according to the total number of nodes and the number of connection lines; Calculating a clustering coefficient for a clustering scale of each of the load nodes according to the initial clustering coefficient and the total number of nodes of a plurality of connection nodes of each of the load nodes; Calculating the center coefficient of each load node according to the shortest connection distance between each load node and each connection node; The topological coefficient index of each load node is calculated according to the central coefficient and the clustering coefficient.

3. A method for evaluating the importance of power grid load nodes according to claim 2, characterized in that: The calculating of the topological coefficient index of each load node according to the central coefficient and the clustering coefficient includes: Comparing the central coefficients and clustering coefficients of the load nodes respectively, and determining the maximum central coefficient and the maximum clustering coefficient among the load nodes; The topological coefficient index of each load node is calculated by the following formula: Among them, R i is the topological coefficient index of the i-th load node, C i is the center coefficient of the i-th load node, C max is the maximum center coefficient, J i is the clustering coefficient of the i-th load node, J max is the maximum clustering coefficient.

4. A method for evaluating the importance of power grid load nodes according to claim 3, characterized in that: The calculating, according to the user type and the electricity usage information, a power outage loss index of each load node includes: According to the user type and the electricity consumption information, calculating the unit price of power outage loss for each user type; Calculate the power consumption of each user at each load node at each moment according to the power consumption information; The power outage loss index of each load node is calculated according to the power outage loss unit price and the power consumption.

5. A method for evaluating the importance of power grid load nodes according to claim 4, characterized in that: The calculating the power outage loss index of each load node according to the power outage loss unit price and the power consumption includes: The power outage loss index of each load node is calculated according to the following formula: Among them, D lose,i is the power outage loss index of the i-th load node, d lose,j is the unit price of power outage loss of the jth user type in the i-th load node, P t,j is the power consumption of the jth user in the i-th load node at time t, and N is the total number of users in the i-th load node.

6. A method for evaluating the importance of power grid load nodes according to claim 5, characterized in that: The calculating the importance score of each load node according to the topology coefficient index, the power outage loss index, and the adjustable capacity index includes: According to the topology coefficient index, the power outage loss index, and the adjustable capacity index, an importance decision matrix is ​​constructed; wherein each row of the importance decision matrix is ​​composed of the topology coefficient index, the power outage loss index, and the adjustable capacity index of the same load node; The Gini coefficient method and the Kendall correlation coefficient method are used to calculate the Gini coefficient and the Kendall correlation coefficient of each column of the importance decision matrix; Determine, according to the Gini coefficient and the Kendall correlation coefficient, a first weight of the topology coefficient index, a second weight of the power outage loss index, and a third weight of the adjustable capacity index; The importance score of each load node is calculated according to the first weight, the second weight, the third weight, and the importance decision matrix.

7. A device for evaluating the importance of power grid load nodes, characterized in that: include: A data acquisition module is used to obtain node parameters, line parameters, user types, and power consumption information of several load nodes in the power grid; A first index calculation module is used to calculate the topology coefficient index of each load node according to the node parameters and the line parameters; wherein the topology coefficient index is used to characterize the degree of connection between each load node and other nodes; A second index calculation module, used to calculate the power outage loss index of each load node according to the user type and the power consumption information; A data calculation module, used to filter out load power consumption information of several adjustable load types of each load node from the power consumption information, and calculate the adjustment capacity and adjustment speed of each adjustable load type according to the load power consumption information; A third indicator calculation module, used to calculate the adjustable capacity indicator of each load node according to the adjustment capacity and the adjustment speed; The importance evaluation module is used to calculate the importance score of each load node according to the topology coefficient index, the power outage loss index, and the adjustable capacity index.

8. The importance assessment device based on power grid load nodes according to claim 7, characterized in that: The calculating of the topological coefficient index of each load node according to the node parameters and the line parameters includes: Determine the total number of connection nodes connected to each of the load nodes and the number of connection lines between each of the load nodes and each connection node according to the node parameters and the line parameters; Calculating the initial clustering coefficient of each load node according to the total number of nodes and the number of connection lines; Calculating a clustering coefficient for a clustering scale of each of the load nodes according to the initial clustering coefficient and the total number of nodes of a plurality of connection nodes of each of the load nodes; Calculating the center coefficient of each load node according to the shortest connection distance between each load node and each connection node; The topological coefficient index of each load node is calculated according to the central coefficient and the clustering coefficient.

9. A terminal device, characterized in that: It comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a method for evaluating the importance of power grid load nodes as described in any one of claims 1 to 6.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is executed, the device where the storage medium is located is controlled to execute the importance assessment method based on power grid load nodes as described in any one of claims 1 to 6.

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