A method for evaluating the importance of a power dispatch data network network topology

Abstract

The application relates to a kind of importance evaluation methods based on power dispatch data network network topology structure.The method: establish abstract power dispatch data network network topology structure model, determine the communication path between each dispatch center and other power facilities;Using the influence difference between power dispatch services, using analytic hierarchy process to establish power dispatch service influence model;By analyzing the topology structure of power dispatch data network, the topology importance of all links in network in local and global service transmission is calculated;According to the communication load data of link, combined with power service influence model, the service importance of different links is calculated;Establish the importance weight between indexes, calculate the comprehensive importance of communication line in network;Based on comprehensive importance, combined with the topology difference of node, the comprehensive importance of all nodes is calculated.The method of the application has important theoretical and practical application value for improving the stability of data network.

Description

TECHNICAL FIELD

[0001] The present application relates to a method for evaluating the importance of the network topology of a power dispatch data network. BACKGROUND

[0002] A power dispatch data network is a data network for the production, dispatch and monitoring of related businesses in a power system, which is composed of dispatch centers at different levels and power plants, substations and other facilities in different areas. Different levels of dispatch businesses are transmitted in the power dispatch data network, such as power dispatch automation, which ensures the stable operation of the entire power system. Therefore, the stability of the power dispatch data network is crucial. When a fault occurs in the equipment in the dispatch data network, it may cause a delay or even a loss of power transmission, leading to a power grid safety accident. The importance of the equipment in the dispatch data network, including network nodes and communication links, is analyzed, and the structures with higher importance are specifically protected, which can well improve the stability of the entire data network. SUMMARY

[0003] The present application aims to provide a method for evaluating the importance of the network topology of a power dispatch data network, which can combine the topology of the power dispatch data network and business data to analyze the importance of different equipment in the communication network from multiple angles, thereby providing guidance for the maintenance and structure improvement of the equipment in the power dispatch data network, and having important theoretical and practical application value for improving the stability of the data network.

[0004] To achieve the above-mentioned purpose, the technical solution of the present application is as follows: a method for evaluating the importance of the network topology of a power dispatch data network, comprising the following steps:

[0005] Step 1: Abstract the dispatch data network and establish a business importance model;

[0006] Step 2: Analyze the topology structure and calculate the local and global topology importance of the link;

[0007] Step 3: Combine the power dispatch business data and the business importance model to calculate the business importance of the link;

[0008] Step 4: Analyze the similarity of each importance index and establish the weight of each index by using the information entropy weight method;

[0009] Step 5: Calculate the comprehensive importance of each link;

[0010] Step 6: Calculate the actual importance of each node.

[0011] Compared with the prior art, the application has the following beneficial effects: the application can combine the topology structure of the power dispatching data network and the service data, and perform importance analysis on different devices in the communication network from multiple angles, thereby providing guidance for device maintenance and structure improvement of the power dispatching data network, and having important theoretical and practical application value for improving the stability of the data network. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 The network topology model of the power dispatching data network in a certain region is constructed.

[0013] Figure 2 The method flowchart of the application. DETAILED DESCRIPTION

[0014] The technical solutions of the application will be specifically described below with reference to the drawings.

[0015] The application is a kind of importance evaluation method based on the network topology structure of the power dispatching data network, which specifically includes establishing an abstract power dispatching data network topology structure model, determining the communication path between each dispatching center and other power facilities. The influence difference between power dispatching services is used to establish a power dispatching service influence model using the analytic hierarchy process (AHP). By analyzing the topology structure of the power dispatching data network, the topology importance of all links in the network in local and global service transmission is calculated. According to the communication load data of the link, the service importance of different links is calculated in combination with the power service influence model. The information entropy weight method is used to analyze the internal similarity difference of the three indexes, and the importance weight between the indexes is established, so as to calculate the comprehensive importance of the communication line in the network. Based on the comprehensive importance of the link, the topology difference of the node is combined, so as to calculate the comprehensive importance of all nodes. As shown in the figure, the specific steps of the method of the application are as follows: Figure 2

[0016] Step 1, abstract the dispatching data network, and establish a service importance model;

[0017] Step 2, analyze the topology structure, and calculate the local and global topology importance of the link;

[0018] Step 3, combine the power dispatching service data and the service importance model, and calculate the service importance of the link;

[0019] Step 4, analyze the similarity of each index, and use the information entropy weight method to establish the weight of each index;

[0020] Step 5, calculate the comprehensive importance of each link;

[0021] Step 6, calculate the actual importance of each node. ​

[0022] Step 1, according to the connection relationship between the dispatch center and other production and communication facilities, the power dispatch data network is abstracted as a topological structure diagram of nodes and edges. And, according to the importance relationship of the power service actually transmitted in the communication network, a service importance model is established. Figure 1 The network topology model of the power dispatch data network in a certain region is constructed.

[0023] The power dispatch data network is constructed as a topological graph G=(V, E) with stations as nodes and communication links as edges, wherein V=1, 2, …, n is a node set, n is the number of nodes. E is a link set, and m is the number of links. The importance of the power service actually transmitted in the power dispatch data network is analyzed, and then a service importance model is established according to the analytic hierarchy process. Since different services have different functions, they also have different requirements for communication performance indicators such as delay and error rate. According to the requirements of different services in safety and reliability, the importance of different services is first judged, the judgment evidence of the analytic hierarchy process is established, and then the actual importance of different services is obtained. At the same time, in order to facilitate calculation, different power dispatch services are classified. The model result established according to the analytic hierarchy process is shown in Table 1.

[0024] Table 1

[0025]

[0026]

[0027] Step 2, according to the topological structure diagram of the power dispatch data network, the correlation between each link in the network and the network communication performance is analyzed, and the local and global topological importance of the link is calculated.

[0028] The local topological property of the link represents the influence of the link on the local area connectivity capability in the network. For two adjacent i, j connected by a link e ij , if there is a short distance redundant line connecting them in addition to the link e ij , the importance of the link e ij for the communication of i, j will be reduced. In addition to the direct connection, the shortest path in the network is a two-hop path. If there is such a path between i, j, a triangle will be formed in the network. Therefore, the number of triangles in which the edge participates is inversely proportional to the degree of its contribution to the network communication capability. The local importance E1 of the link can be calculated according to the following formula.

[0029]

[0030] Wherein:

[0031]

[0032] In the formula: E1(e ij ) indicates link e ij Local importance, d i d j Let i and j represent the degrees of nodes i and j respectively, and c represent the link e. ij The number of triangles that participate in forming the network.

[0033] Besides local communication, the communication network also contains a large number of cross-regional power dispatching services. In this case, a large amount of dispatching data is carried by a small number of nodes and links connecting different blocks, namely "bridging nodes" and "bridging links". The topological importance of different links in global communication is obtained by calculating how many pairs of nodes a link e lies on the shortest path, i.e., the edge betweenness. The global importance E2 of a link is calculated as follows.

[0034]

[0035] In the formula: E2(e ij ) indicates link e ij Global importance, EBC(e ij ) represents edge e ij The number of edge intermediaries.

[0036] Step 3: Based on the long-term operating power business data in the power dispatch data network and combined with the power business importance model, calculate the business importance of each link in the network.

[0037] If a power link carries a large amount of high-value power services, then a link failure will have a severe impact on the power system. Let link e be an example. ij The number of units of the type l service transmitted uplink is k. eijl A total of q types of power services are transmitted. Based on the actual situation of the service data carried by the links in the communication network, this paper assigns higher importance to the links. The method for calculating the service importance E3 of a link is as follows.

[0038]

[0039] in,

[0040]

[0041] In the formula: E3(e ij Link e ij Business importance, θ l This represents the unit importance of the l-th type of business, obtained according to the power business importance model.

[0042] Step 4, according to the link importance index data obtained in the previous two steps, using information entropy weight method to calculate the reasonable weight of each index.

[0043] The importance shown by the link in different aspects is not the same as its contribution to the actual importance. In order to distinguish the importance of different indexes, we use information entropy weight method to calculate the objective weight of each index. Generally speaking, the greater the difference between the sample data of a certain index, the more information it provides, and the greater the corresponding weight. Therefore, first calculate the degree of disorder of each index data, that is, information entropy. Then, according to the information entropy, the objective weight of each index is obtained. The objective weights of importance indexes E1, E2 and E3 are represented as w1, w2 and w3 respectively. Their calculation formulas are as follows.

[0044]

[0045]

[0046]

[0047] wherein a ij represents the i-th attribute value of the j-th index, p ij represents the proportion of the i-th attribute value under the j-th index, N represents the number of attribute values, E j represents the information entropy of the j-th index, m represents the number of indexes, w j represents the weight of the j-th index.

[0048] Step 5, according to the importance of each index of the link and the objective weight, calculate the comprehensive importance of all links in the network.

[0049] In order to accurately judge the actual importance of a link, we comprehensively analyze it from the perspectives of local topology importance, global topology importance and business importance, so as to calculate the comprehensive importance I of a link. The greater the comprehensive importance of a link, the higher its correlation with the stability of the network, and the more it is worth protecting.

[0050] I eij = w1E1(e ij ) + w2E2(e ij ) + w3E3(e ij )

[0051] Step 6, according to the comprehensive importance of the link, calculate the actual importance of the nodes in the power dispatching data network.

[0052] Besides link protection, node protection is also important. The more important the links adjacent to a node are, the more important the node itself is. We assign a real importance to a node according to the comprehensive importance of the adjacent links, and assign a higher weight to a hub node in order to highlight the role of the hub node. The formula for calculating the real importance IV(i) of a node is

[0053]

[0054] where N(i) represents the set of neighbor nodes of node i.

[0055] The above is the preferred embodiment of the present application. Any change made according to the technical solution of the present application, as long as the function does not exceed the scope of the technical solution of the present application, is within the protection scope of the present application.

Claims

1. A method for evaluating the importance of a power dispatch data network topology, characterized in that, Includes the following steps: Step 1: Abstract the scheduling data network and establish a business importance model; Step 2: Analyze the topology and calculate the local and global topological importance of the links; Step 3: Calculate the service importance of the link by combining power dispatching business data and the service importance model; Step 4: Analyze the similarity of each importance index and use the information entropy weighting method to determine the weight of each index; Step 5: Calculate the overall importance of each link; Step 6: Calculate the actual importance of each node; Step 1 is implemented as follows: Based on the connection relationship between the dispatch center and other production and communication facilities, the power dispatch data network is abstracted into a topological structure diagram of nodes and edges; and, based on the importance relationship of the actual power services transmitted in the dispatch data network, a service importance model is established, specifically: The dispatch data network is constructed as a topology graph G = (V, E) with stations as nodes and communication links as edges, where V = 1, 2, ..., n is the node set, n is the number of nodes, E is the link set, and m is the number of links. An importance analysis is performed on the actual power services transmitted in the dispatch data network, and then a service importance model is established based on the analytic hierarchy process (AHP). Based on the security and reliability requirements of different power services, the importance of different power services is first determined, and an AHP decision-making evidence is established to obtain the actual importance of different power services. Power services are divided into five categories: real-time power dispatch production data, anti-misoperation system data, relay protection data, hydropower and new energy data, and dispatch plans. The importance of the five types of power services are 0.98, 0.83, 0.55, 0.33, and 0.15, respectively.

2. The method for evaluating the importance of a power dispatch data network topology according to claim 1, characterized in that, Step 2 is implemented as follows: Based on the topology of the scheduling data network, analyze the correlation between each link in the scheduling data network and the network communication performance, and calculate the local and global topological importance of the links, specifically: The local topology attribute of a link represents its influence on the connectivity of a local area in the scheduling data network; for a link e ij For two adjacent i and j connected, if excluding link e ij In addition, there is a short-distance redundant link connecting the two, then link e ij The importance of communication between i and j will decrease; Besides direct connections, the shortest path in the network is a two-hop path; if such a path exists between i and j, it will form a triangle in the network; therefore, the number of triangles an edge participates in is inversely proportional to its contribution to the network's communication capacity; the local importance E1 of a link is calculated according to the following formula: in: In the formula: E1(e ij ) indicates link e ij Local importance, d i d j Let i and j represent the degrees of nodes i and j respectively, and c represent the degree of link e. ij The number of triangles that participate in forming the network; Besides local communication, the dispatch data network also includes cross-regional power dispatching services. In this case, dispatch data is carried by nodes and links connecting different blocks, namely "bridging nodes" and "bridging links." The calculation of a link e... ij The number of node pairs on the shortest path, i.e., the edge betweenness, determines the topological importance of different links in global communication; calculate link e. ij The global importance E2 is determined as follows: In the formula: E2(e ij ) indicates link e ij Global importance, EBC(e ij ) indicates link e ij The number of edge intermediaries.

3. The method for evaluating the importance of a power dispatch data network topology according to claim 1, characterized in that, Step 3 is implemented as follows: Based on the long-term operating power business data in the dispatch data network and combined with the business importance model, the business importance of each link in the dispatch data network is calculated, specifically: Suppose there is a link e ij The number of units of the type l service transmitted uplink is k. eijl A total of q types of power services are transmitted; Based on the actual situation of the service data carried by the links in the scheduling data network, higher importance is assigned to the links; the method for calculating the service importance E3 of a link is as follows: in, In the formula: E3(e ij Link e ij Business importance, θ l This represents the unit importance of the l-th type of business, obtained according to the business importance model.

4. The method for evaluating the importance of a power dispatch data network topology according to claim 1, characterized in that, Step 4 is implemented as follows: To differentiate the importance of different indicators, the information entropy weighting method is used to calculate the objective weight of each indicator. First, the degree of disorder in the data for each indicator, i.e., information entropy, is calculated. Then, based on the information entropy, the objective weight of each indicator is obtained. (The last sentence appears to be incomplete and possibly refers to a different method or approach.) ij Local importance E1, link e ij Global importance E2, link e ij The objective weights of the business importance E3 are represented as w1, w2, and w3, respectively; the calculation formula is as follows: Among them, a ij p represents the value of the i-th attribute of the j-th indicator. ij E represents the proportion of the i-th attribute value under the j-th indicator, N represents the number of attribute values, and E represents the proportion of the i-th attribute value. j Let w represent the information entropy of the j-th indicator, m represent the number of indicators, and w represent the information entropy of the j-th indicator. j This represents the weight of the j-th indicator.

5. The method for evaluating the importance of a power dispatch data network topology according to claim 1, characterized in that, Step 5 is implemented as follows: Based on the importance of each link and its objective weight, the overall importance of all links in the scheduling data network is calculated; specifically: A comprehensive analysis is conducted from the perspectives of local topological importance, global topological importance, and business importance to calculate the overall importance I of a link. eij ; The greater the overall importance of a link, the stronger its correlation with network stability, and the more worthy it is of protection. I eij =w1E1(e ij )+w2E2(e ij )+w3E3(e ij ) Where E1 is link e ij Local importance, E2 is the link e ij Global importance, E3 for link e ij Business importance, w j This represents the weight of the j-th importance indicator, where j = 1, 2, 3.

6. The method for evaluating the importance of a power dispatch data network topology according to claim 5, characterized in that, The implementation method for step 6 is as follows: Nodes are assigned actual importance based on the combined importance of adjacent links. The formula for calculating the actual importance IV(i) of a node is as follows: Where, d i d j Let i and j represent the degree of nodes i and j respectively, and N(i) represent the set of neighboring nodes of node i.

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