Power communication fusion network generation method based on improved modularity community division

Abstract

The present invention discloses a method for generating a power communication fusion network based on improved modularity community division, including: constructing a power network topology structure; establishing a line energy transmission stability index, an importance index of a line in the power network topology structure, and a line power betweenness index; establishing a node electrical association strength index; improving the modularity for evaluating the quality of communities in the complex network community division Louvain algorithm to obtain an electrical modularity; obtaining the number of communities and the community to which each node belongs; determining the number of core layer, backbone layer, and access layer nodes in the communication network; constructing a communication network topology structure; constructing a mathematical model of the power communication fusion network; constructing mathematical models of a double-star power communication fusion network and a mesh-type power communication fusion network; the present invention improves the rationality of the regional allocation of the power communication fusion network, proposes a method for generating a power communication fusion network that conforms to actual characteristics, and solves the problem of scarce research data in the power communication network.

Description

Technical Field

[0001] The present invention relates to the technical field of the safe and stable operation of power systems, and particularly to a method for generating a power communication fusion network based on improved modularity community division. Background Art

[0002] The core of the energy Internet lies in the deep coupling of information technology and physical systems. As the "backbone network" of the energy Internet, the power system has incomparable advantages in aspects such as energy transmission efficiency. After the intervention of an information system equipped with advanced power electronics technology, information technology, and intelligent management technology, the power system is gradually developing into a typical cyber-physical system, namely the electric cyber physical system (ECPS). ECPS connects power physical devices to the network, enabling power physical devices to possess five major functions such as computing, communication, precise control, remote coordination, and autonomy. At the same time, through the organic integration and in-depth cooperation of the core 3C technologies, real-time perception, dynamic control, and information services of the power system are realized, making the integrated fusion system more efficient and reliable, and having important and extensive application prospects. Therefore, it is very necessary to study ECPS.

[0003] However, due to the attributes of critical infrastructure possessed by the power system itself, it is almost impossible to obtain the actual network framework structure of the power communication network corresponding to the power system. Moreover, there are significant differences between the power physical information fusion network model built in the prior art and the characteristics of the actual system, and the provided basic network structure parameters are difficult to be used for subsequent research on ECPS.

[0004] Currently, domestic and foreign scholars' research on electric cyber physical systems is all based on standard example networks, such as IEEE standard networks, lacking the description of different characteristics of actual power grids. Therefore, some scholars have proposed applying complex network models to separately model different-level networks, and describing the internal and mutual influence effects of the networks as intra-layer connection edges and inter-layer dependency edges. The connection edges represent the internal connection relationships of each layer of the network, and the dependency edges are the interfaces and logical connections of the interactions between nodes in the networks. Modeling is carried out according to the quantity and node selection principles of inter-layer dependency edges established based on the interdependent network. However, the modeling method based on complex networks only focuses on the topological connection relationships of the system, abstracts the communication transmission process as the mutual connection lines between nodes, ignores the electrical characteristics of the system and the physical meaning of communication transmission, and there are obvious deviations from the characteristics of the actual system.

[0005] Therefore, to further develop the construction of electric cyber physical systems, it is very necessary to construct a new power communication fusion network model that comprehensively considers the topological structure and physical characteristics of the power grid. Summary of the Invention

[0006] To overcome the above technical deficiencies and solve the modeling problem based on complex networks, the present invention proposes a method for generating a power communication fusion network based on improved modularity community division, and constructs a power communication fusion network model that can intelligently manage and control the power grid, flexibly schedule, and conform to the actual situation.

[0007] The object of the present invention can be achieved by the following technical solutions:

[0008] A method for generating a power communication fusion network based on improved modularity community division includes the following steps;

[0009] Construct a power network topology structure, and abstract the power network into an undirected unweighted heterogeneous graph including power source nodes, transmission nodes, and generalized load nodes;

[0010] By defining the evaluation of the power transmission capacity of the power network, the power transmission capacity of the power network after a line is removed in the power network, and the impact resistance capacity of the neighborhood after a certain line in the power network is removed, establish an index for evaluating the line energy transmission stability after a line is disconnected in the power network;

[0011] By defining the topological connection difference of nodes in the power network and the topological connection difference of lines related to the nodes, establish an index for evaluating the importance of nodes in the power network topology and an index for evaluating the importance of lines in the power network topology structure;

[0012] Establish a line power betweenness index for evaluating the importance of lines in the power network under normal operating conditions;

[0013] For the index for evaluating the line energy transmission stability after a line is disconnected in the power network, the index for evaluating the importance of lines in the power network topology structure, and the line power betweenness index for evaluating the importance of lines in the power network under normal operating conditions, perform weighted balance ratio, and establish a node electrical correlation strength index;

[0014] Based on the node electrical correlation strength index, improve the modularity for evaluating the community quality in the Louvain algorithm for complex network community division to obtain the electrical modularity;

[0015] Based on the electrical modularity, use the Louvain algorithm with improved modularity to perform community division on the power network to obtain the number of communities and the community to which each node belongs;

[0016] According to the national power communication system partition management principle, and the number of communities and the community to which each node belongs obtained by performing community division on the power network using the Louvain algorithm, determine the number of core layer, backbone layer, and access layer nodes in the communication network;

[0017] Based on the hierarchical model of the communication network, construct the topological structure of the communication network, and abstract the communication network as an undirected and unweighted heterogeneous graph including access layer nodes, backbone layer nodes, and core layer nodes;

[0018] Based on the hierarchical model of the communication network and the power communication protocol, generate a double-star communication network topology and a mesh communication network topology respectively;

[0019] Fuse the power network topology and the communication network topology to construct a mathematical model of the power communication fusion network;

[0020] According to the double-star communication network topology and the mathematical model of the power communication coupling network, construct a mathematical model of the double-star power communication fusion network;

[0021] According to the mesh communication network topology and the mathematical model of the power communication coupling network, construct a mathematical model of the mesh power communication fusion network.

[0022] Furthermore, the topological structure of the power network adopts the topological graph G pn =(V pn , E pn ) to describe, where V pn represents the set of all nodes in the power network, and E pn represents the abstract set of all power lines in the power network. The number of nodes in the power network is N pn ;

[0023] The calculation process of the line energy transmission stability index STA(l ij ) after the line is disconnected in the power network is shown in Equation (1):

[0024]

[0025] In Equation (1), represents the power network energy transmission capacity, represents the power network energy transmission capacity after the line l ij in the power network is removed, represents the neighborhood shock resistance ability composed of all its adjacent lines after the line l ij in the power network is removed;

[0026] The calculation formula of the power network energy transmission capacity is shown in Equation (2):

[0027]

[0028] In Equation (2), L m represents the number of lines that can be actively disconnected, and L nDenote the number of lines affected by energy shock after line disconnection, S m Denote the set of lines in the power network, S n Denote the set of lines affected by energy shock after line disconnection Be the shock limit that line n affected by energy shock can withstand, Z mn Denote the electrical distance between line m in the power network and line n affected by energy shock;

[0029] The shock limit that the line n affected by energy shock can withstand The calculation formula is as shown in Equation (3):

[0030]

[0031] In Equation (3), P n,s 、Q n,s Respectively denote the initial active power flow and reactive power flow of line n affected by energy shock, Respectively denote the upper limits of the active power flow and reactive power flow of line n affected by energy shock, Respectively denote the upper and lower limits of the voltage phase angle difference of line n affected by energy shock, Respectively denote the upper and lower limits of the voltage amplitude difference of line n affected by energy shock.

[0032] For line l in the power network ij The neighborhood shock resistance ability of all its adjacent lines after removal The calculation formula is as shown in Equation (4):

[0033]

[0034] In Equation (4), i and j respectively denote the two end nodes of line l ij After removing line l ij , a is the common neighbor node of nodes i and j, Is the set of common neighbor nodes of nodes i and j, Is except Outside, the set of nodes adjacent to node i, Is except Outside, the set of nodes adjacent to node j.

[0035] Furthermore, the calculation formula for the importance index CON(l ij ) in the power network topology is as shown in Equation (5):

[0036]

[0037] In Equation (5), IM iDenote the line l ij The node importance of the two end nodes i, IM j Denote the line l ij The node importance of the two end nodes j;

[0038] For the line l ij The node importance IM of the two end nodes i i The calculation formula is as shown in Equation (6):

[0039]

[0040] In Equation (6), De i Denotes the node degree value of node i, P(De i ) denotes the probability that the node degree value is De i The probability, N pn Denotes the number of nodes in the power grid, Denotes the sum of the line weights of all adjacent lines of node i, Ω denotes the set of neighbor nodes of node i, IM i ′ denotes the topological connection difference between the node and the line in the power grid topological structure, calculates the average of the two, and its calculation formula is as shown in Equation (7):

[0041] IM′ i =(S i +D i ) / 2 (7)

[0042] In Equation (7), S i Denotes the topological connection difference of node i, and its calculation formula is as shown in Equation (8):

[0043] S i =[1 - P(De i )]N pn (8)

[0044] In Equation (7), D i Denotes the topological connection difference of the lines related to node i, and its calculation formula is as shown in Equation (9):

[0045]

[0046] Furthermore, the line power betweenness index POW(l ij ) used to evaluate the line importance in the normal operation state of the power grid has the calculation formula as shown in Equation (10):

[0047]

[0048] In Equation (10), Denotes the generator factor of the line power betweenness, The load factor representing the line power betweenness Denote the line l ij The power flow weight factor of, ω G Denote the weight of the generator factor, ω L Denote the weight of the load factor;

[0049] The generator factor of the line power betweenness The calculation formula is shown in Equation (11):

[0050]

[0051] The load factor of the line power betweenness The calculation formula is shown in Equation (12):

[0052]

[0053] The line l ij The power flow weight factor of The calculation formula is shown in Equation (13):

[0054]

[0055] In Equations (11) to (13), Denote the active power contributed by the generator node g to the line l ij Denote the betweenness of the line l ij , N G Denote l ij The number of generators contributing power to the line, N L Denote the number of loads drawing power from the line l ij Denote the active power drawn by the load node d from the line l ij Denote the actual power flow of the line l ij Denote the power transfer margin of the line l ij

[0056] Furthermore, the calculation formula of the node electrical correlation strength index f(l ij ) is shown in Equation (14):

[0057]

[0058] In Equation (14), using the AHP-entropy weight method and the grey correlation method, select ω 1 , ω 2 , ω 3 For STA(l ij ), CON(l​​​​​ij ) Assign weights to the three indicators of POW(l ij ) to balance the proportion of the role;

[0059] The electrical modularity Q f The calculation formula is shown in Equation (15):

[0060]

[0061] In Equation (15), M represents the total electrical correlation strength of the power network, and f′(l ij ) represents the electrical correlation strength between nodes i and j with an adjacent connection relationship, and k i represents the electrical degree of node i, and k j represents the electrical degree of node j;

[0062] The electrical degree k of node i i The calculation formula is shown in Equation (16):

[0063]

[0064] f′(l io ) represents the electrical correlation strength between nodes i and o, and S o represents the set of all nodes with an adjacent connection relationship with node i;

[0065] c i represents the community where node i is located, and c j represents the community where node j is located, and δ(c i , c j ) is defined as follows: If nodes i and j are in one community, then c i = c j , and δ(c i , c j ) is 1, otherwise δ(c i , c j ) is 0, and Σ in represents the total electrical correlation strength of all edges within community c, and Σ tot is the total electrical correlation strength of all edges in the entire power network topology that are associated with nodes in community c.

[0066] Furthermore, the specific steps for partitioning the power network using the improved Louvain algorithm for modularity include:

[0067] S1: Treat each node in the power network topology as a community, and the number of communities is the same as the number of nodes;

[0068] S2: Merge each node in the power network topology with its neighbor nodes in turn, and calculate their electrical modularity gain.

[0069] S3: Determine whether the electrical modularity gain is greater than 0. If it is greater than 0, put this node into the community where the neighbor node with the largest electrical modularity gain is located.

[0070] S4: Repeat S3 until the community to which each node in the power network topology belongs no longer changes.

[0071] S5: Take each community in S4 as an equivalent node, the sum of the electrical degrees of the nodes within the original community as the electrical degree of this equivalent node, and the sum of the electrical association strengths between the nodes within the original community and the nodes within another community as the electrical association strength between different equivalent nodes.

[0072] S6: Regard the equivalent nodes in S5 and the nodes not assigned to any community as the updated power network topology.

[0073] S7: Repeat S1 - S6 until the optimal community partition result is obtained. The community partition result includes the optimal number of communities, the community to which each node belongs, and the electrical modularity of the optimal community.

[0074] The electrical modularity gain ΔQ brought by putting node i into community c f is calculated by the formula shown in Equation (17):

[0075]

[0076] In Equation (17), k i,in represents the sum of the electrical association strengths of all the edges connecting from node i to the nodes in community c.

[0077] Furthermore, the communication network includes core layer nodes V c cn , backbone layer nodes and access layer nodes The number of core layer nodes is The number of backbone layer nodes is The number of access layer nodes is

[0078] The communication network topology is described by the topology graph G cn =(V cn , E cn ), where V cn represents the set of all nodes in the communication network, and E cn represents the abstract set of all power lines in the communication network.

[0079] The setting of the number of nodes in the core layer, backbone layer, and access layer of the communication network includes:

[0080] The number of nodes in the core layer of the double-star communication network The number of nodes in the core layer of the mesh communication network

[0081] The number of nodes in the backbone layer of the communication network is determined according to the number of communities obtained by the Louvain algorithm of the improved modularity, where the number of nodes in the backbone layer of the double-star communication network The number of nodes in the backbone layer of the mesh communication network Among them, represents the optimal number of communities;

[0082] The number of nodes in the access layer of the double-star communication network The number of nodes in the access layer of the mesh communication network

[0083] Furthermore, the specific generation principles of the double-star communication network topology and the mesh communication network topology include determining the internal connection methods and inter-layer connection methods of each level of the core layer, backbone layer, and access layer according to the number of nodes in the core layer, backbone layer, and access layer of the communication network.

[0084] Furthermore, the mathematical model of the power communication fusion network is G pn-cn =(V pn-cn , E pn-cn ), where V pn-cn represents the set of all nodes in the power communication fusion network, and E pn-cn represents the abstract set of all power lines in the power communication fusion network, and A pn-cn represents the coupling adjacency matrix of the topological connection relationship in the power communication fusion network;

[0085] The mathematical model of the double-star power communication fusion network is expressed as in Equation (18):

[0086]

[0087] In Equation (18), A pn-pn represents the node adjacency matrix of the power layer of the power network, represents the node adjacency matrix of the access layer of the communication network, represents the node adjacency matrix of the core layer of the communication network, represents the node coupling adjacency matrix between the power layer of the power network and the access layer of the communication network, represents the node coupling adjacency matrix between the access layer of the communication network and the backbone layer of the communication network, It represents the node coupling adjacency matrix between the backbone layer and the core layer of the communication network. It represents the node coupling adjacency matrix between the access layer and the backbone layer of the communication network.

[0088] Furthermore, the mesh-type power communication fusion network model is expressed as in Equation (19):

[0089]

[0090] In Equation (19), A pn-pn represents the node adjacency matrix of the power layer of the power network, represents the node adjacency matrix of the access layer of the communication network, represents the node adjacency matrix of the backbone layer of the communication network, represents the node adjacency matrix of the core layer of the communication network, represents the node coupling adjacency matrix between the power layer of the power network and the access layer of the communication network, represents the node coupling adjacency matrix between the access layer and the backbone layer of the communication network, represents the node coupling adjacency matrix between the backbone layer and the core layer of the communication network.

[0091] Based on the topological structure and physical characteristics of the power network, the main innovation points of the present invention are:

[0092] (1) A method for generating a power communication fusion network model that conforms to the characteristics of the real power communication network and provides reliable network topology data is constructed, focusing on the deep coupling problem between the power network and the communication network.

[0093] (2) Considering the topological structure and physical characteristics of the power network, an electrical correlation strength is established by comprehensively considering three indicators: the stability of line energy transmission, the importance of line topology, and the line power betweenness, and then the electrical modularity is used to perform community division on the power grid.

[0094] (3) Based on the hierarchical model of the communication network, the backbone layer of the communication network is determined based on the results of the community division of the electrical modularity, and further the number of nodes in each layer of the communication network is determined; according to the communication network planning principle and the actual architecture characteristics, the generation methods of the double-star power communication fusion network and the mesh-type power communication fusion network are finally given.

[0095] Compared with the existing technologies, the beneficial effects of the present invention are:

[0096] (1) For the power communication fusion network generated based on the improved modularity community division, the topological characteristics and physical characteristics of the power network are comprehensively considered, making the regional allocation result of the power communication fusion network have higher reliability and rationality;

[0097] (2) The generated network is consistent with the network topology characteristics of the real power communication network. Compared with the communication networks generated by the existing technologies, it has more obvious small-world characteristics and scale-free characteristics, that is, it is more in line with the statistical characteristics of the real power communication network. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] Figure 1 It is a flowchart of a method for generating a power communication fusion network based on improved modularity community division;

[0099] Figure 2 It is a simplified power network topology diagram of the IEEE 14-node system;

[0100] Figure 3 It is a schematic diagram of a communication network hierarchical model;

[0101] Figure 4 It is a schematic diagram of a double-star communication network topology structure;

[0102] Figure 5 It is a schematic diagram of a mesh communication network topology structure; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0103] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts, any modifications, equivalent replacements, improvements, etc., shall be included in the protection scope of the present invention.

[0104] A method for generating a power communication fusion network based on improved modularity community division specifically includes the following steps:

[0105] As Figure 1 shown, a method for generating a power communication fusion network based on improved modularity community division includes the following steps;

[0106] Construct a power network topology structure, and abstract the power network into an undirected unweighted heterogeneous graph including power source nodes, transmission nodes, and generalized load nodes;

[0107] By defining the evaluation of the power network energy transmission ability, the power network energy transmission ability after a line in the power network is removed, and the anti-impact ability of the neighborhood of a certain line in the power network after the line is removed, establish an index for evaluating the line energy transmission stability after a line in the power network is disconnected;

[0108] By defining the topological connection differences of nodes in the power network and the topological connection differences of lines associated with the nodes, an importance index for evaluating nodes in the power network topology and an importance index for evaluating lines in the power network topology structure are established;

[0109] An index of line power betweenness for evaluating the importance of lines in the power network under normal operating conditions is established;

[0110] The line energy transmission stability index after disconnecting the lines in the power network, the importance index of lines in the power network topology structure, and the line power betweenness index for evaluating the importance of lines in the power network under normal operating conditions are weighted and balanced to establish a node electrical correlation strength index;

[0111] Based on the node electrical correlation strength index, the modularity for evaluating the quality of communities in the Louvain algorithm for complex network community division is improved to obtain the electrical modularity;

[0112] Based on the electrical modularity, the Louvain algorithm with improved modularity is used to divide the power network into communities to obtain the number of communities and the community to which each node belongs;

[0113] According to the national power communication system zoning management principle, and the number of communities and the community to which each node belongs obtained by dividing the power network into communities using the Louvain algorithm, the number of core layer, backbone layer, and access layer nodes in the communication network is determined;

[0114] Based on the communication network hierarchical model, a communication network topology structure is constructed, and the communication network is abstracted into an undirected unweighted heterogeneous graph including access layer nodes, backbone layer nodes, and core layer nodes;

[0115] Based on the communication network hierarchical model and the power communication protocol, a double-star communication network topology and a mesh communication network topology are respectively generated;

[0116] The power network topology and the communication network topology are fused to construct a mathematical model of the power communication fusion network;

[0117] According to the double-star communication network topology and the mathematical model of the power communication coupling network, a mathematical model of the double-star power communication fusion network is constructed;

[0118] According to the mesh communication network topology and the mathematical model of the power communication coupling network, a mathematical model of the mesh power communication fusion network is constructed.

[0119] The power network topology structure adopts a topological graph G pn =(V pn,E pn ) is described, where V pn represents the set of all nodes in the power network, and E pn represents the abstract set of all power lines in the power network. The number of nodes in the power network is N pn ;

[0120] To further simplify the network and highlight the importance of the research object, taking the IEEE 14-node system as an example, as Figure 2 shown, the present invention makes the following assumptions about the power network topology: ① Merge multiple lines between the same node pair to eliminate duplicate edges; ② Do not consider the self-loops of nodes; ③ If a single bus is connected to multiple power sources, loads, or substations, it is regarded as a single node.

[0121] The calculation process of the line energy transmission stability index STA(l ij ) after a line is disconnected in the power network is shown in Equation (1):

[0122]

[0123] In Equation (1), represents the power network energy transmission capacity, represents the power network energy transmission capacity after line l ij in the power network is removed, represents the neighborhood shock resistance ability of all adjacent lines after line l ij in the power network is removed;

[0124] The power network energy transmission capacity is calculated by Equation (2) as follows:

[0125]

[0126] In Equation (2), L m represents the number of lines that can be actively disconnected, L n represents the number of lines affected by energy shock after a line is disconnected, S m represents the set of power network lines, and S n represents the set of lines affected by energy shock after a line is disconnected, is the shock limit that the line n affected by energy shock can withstand, and Z mn represents the electrical distance between the power network line m and the line n affected by energy shock;

[0127] The shock limit that the line n affected by energy shock can withstand is calculated by Equation (3) as follows:

[0128]

[0129] In Equation (3), P n,s , Q n,s respectively represent the initial active power flow and reactive power flow of line n affected by energy impact, respectively represent the upper limits of the active power flow and reactive power flow of line n affected by energy impact, respectively represent the upper and lower limits of the voltage phase angle difference of line n affected by energy impact, respectively represent the upper and lower limits of the voltage amplitude difference of line n affected by energy impact.

[0130] For the neighborhood impact resistance ability of all adjacent lines of line l in the power grid after its removal ij , the calculation formula is as shown in Equation (4): The calculation formula is as shown in Equation (4):

[0131]

[0132] In Equation (4), i and j respectively represent the two end nodes of line l ij . After removing line l ij , a is the common neighbor node of nodes i and j, is the set of common neighbor nodes of nodes i and j, is except , the set of nodes adjacent to node i, is except , the set of nodes adjacent to node j.

[0133] The calculation formula for the importance index CON(l ij ) to evaluate the importance of a line in the power grid topology is as shown in Equation (5):

[0134]

[0135] In Equation (5), IM i represents the node importance of node i at both ends of line l ij , and IM j represents the node importance of node j at both ends of line l ij ;

[0136] For the node importance IM ij of node i at both ends of the line l i , the calculation formula is as shown in Equation (6):

[0137]

[0138] In Equation (6), De iDenotes the node degree value of node i, reflecting the status of the node in the power network topology, P(De i ) represents the probability that the node degree value is De i , N pn represents the number of nodes in the power network, denotes the sum of the line weights of all adjacent lines of node i, Ω represents the set of neighbor nodes of node i, IM′ i represents the topological connection difference between the node and the line in the power network topology, calculates the average of the two, and its calculation formula is shown in Equation (7):

[0139] IM′ i =(S i +D i ) / 2 (7)

[0140] In Equation (7), S i represents the topological connection difference of node i, and its calculation formula is shown in Equation (8):

[0141] S i =[1 - P(De i )]N pn (8)

[0142] In Equation (7), D i represents the topological connection difference of the lines related to node i, and its calculation formula is shown in Equation (9):

[0143]

[0144] Further analyze the influence of transmission lines on generator nodes and load nodes under the normal operation state of the power network, consider the number and power of generators contributing power to the line, as well as the number and power of loads drawing power from the line, and at the same time consider the actual power flow of the line and the power flow upper limit, to obtain the line power betweenness index POW(l ij ) for evaluating the importance of lines in the power network under the normal operation state, and its calculation formula is shown in Equation (10):

[0145]

[0146] In Equation (10), represents the generator factor of the line power betweenness, represents the load factor of the line power betweenness, represents the power flow weight factor of line l ij , ω G represents the weight of the generator factor, ω LIndicates the weight of the load factor; Considering the operation of the entire power grid, the influence of the line on both the power generation end and the power receiving end is equal. Therefore, the weight factors of both are preferably set to 0.5.

[0147] The generator factor of the line power betweenness The calculation formula is as shown in Equation (11):

[0148]

[0149] The load factor of the line power betweenness The calculation formula is as shown in Equation (12):

[0150]

[0151] The line l ij The power flow weight factor The calculation formula is as shown in Equation (13):

[0152]

[0153] In Equations (11) to (13), Indicates the active power contributed by the generator node g to the line l ij , Indicates the betweenness of the line l ij , N G Indicates l ij The number of generators contributing power to the line, N L Indicates the number of loads drawing power from the line l ij , Indicates the active power drawn by the load node d from the line l ij , Indicates the line l ij The actual power flow, Indicates the line l ij The power transfer margin.

[0154] The calculation formula of the node electrical correlation strength index f(l ij ) is as shown in Equation (14):

[0155]

[0156] In Equation (14), using the AHP-entropy weight method and the grey correlation method, ω 1 , ω 2 , ω 3 are selected to balance the proportion of the weighting effect on the three indicators of STA(l ij ), CON(l ij ), and POW(l ij );

[0157] The electrical module degree Q f The calculation formula is as shown in Equation (15):

[0158]

[0159] In Equation (15), M represents the total electrical correlation strength of the power network, and f′(l ij ) represents the electrical correlation strength between nodes i and j with an adjacent connection relationship, and k i represents the electrical degree of node i, and k j represents the electrical degree of node j;

[0160] The electrical degree k of node i i The calculation formula is as shown in Equation (16):

[0161]

[0162] f′(l io ) represents the electrical correlation strength between nodes i and o, and S o represents the set of all nodes having an adjacent connection relationship with node i;

[0163] c i represents the community where node i is located, and c j represents the community where node j is located. The value of δ(c i , c j ) is defined as follows: If nodes i and j are in the same community, then c i = c j , and δ(c i , c j ) is 1; otherwise, δ(c i , c j ) is 0. Σ in represents the total electrical correlation strength of all edges within community c, and Σ tot is the total electrical correlation strength of all edges associated with the nodes in community c in the entire power network topology structure.

[0164] The specific steps of using the Louvain algorithm with improved modularity to perform community division on the power network include:

[0165] S1: Treat each node in the power network topology structure as a community, and the number of communities is the same as the number of nodes;

[0166] S2: Sequentially merge each node in the power network topology structure with its neighbor nodes and calculate their electrical modularity gain;

[0167] S3: Determine whether the electrical modularity gain is greater than 0. If it is greater than 0, place the node in the community where the neighbor node with the maximum electrical modularity gain is located;

[0168] S4: Repeat S3 until the community to which each node in the power network topology belongs no longer changes;

[0169] S5: Take each community in S4 as an equivalent node, the sum of the electrical degrees of the nodes within the original community as the electrical degree of this equivalent node, and the sum of the electrical association strengths between the nodes within the original community and the nodes within another community as the electrical association strength between different equivalent nodes;

[0170] S6: Regard the equivalent nodes in S5 and the nodes not assigned to any community as the updated power network topology;

[0171] S7: Repeat S1 - S6 until the optimal community partition result is obtained. The community partition result includes the optimal number of communities, the community to which each node belongs, and the electrical modularity of the optimal community;

[0172] The electrical modularity gain ΔQ brought by placing node i in community c f is calculated as shown in Equation (17):

[0173]

[0174] In Equation (17), k i,in represents the sum of the electrical association strengths on all the edges connecting node i to the nodes in community c.

[0175] As Figure 3 shown, the hierarchical model of the communication network includes a core layer, a backbone layer, and an access layer, and has the characteristics of distributed acquisition, hierarchical transmission, and centralized aggregation. Among them, the core layer is the convergence center of the whole network communication service, including a main dispatching center and a standby dispatching center, responsible for massive and high-speed data exchange, and leading the safe operation and optimal dispatching of the entire power grid; the backbone layer is located between the core layer and the access layer, responsible for receiving data from the access layer, aggregating the data in a ring between stations, submitting it upward to the core layer, and at the same time performing regional and inter - regional dispatching, mainly composed of substations located at the hub of the optical fiber transmission network; the access layer is at the bottom of the hierarchical model, mainly responsible for data acquisition and the issuance of remote control commands, and is composed of the remaining stations except for the stations in the core layer and the backbone layer of the communication network.

[0176] The communication network includes core layer nodes V c cn , backbone layer nodes and access layer nodes The number of core layer nodes is The number of backbone layer nodes is The number of access layer nodes is

[0177] The communication network topology adopts the topology graph G cn =(V cn , E cn ) to describe, where V cn represents the set of all nodes in the communication network, and E cn represents the abstract set of all power lines in the communication network;

[0178] The settings of the number of nodes in the core layer, backbone layer and access layer in the communication network include:

[0179] The number of nodes in the core layer of the double-star communication network The number of nodes in the core layer of the mesh communication network

[0180] The number of nodes in the backbone layer of the communication network is determined according to the number of communities obtained by the Louvain algorithm of the improved modularity. Among them, the number of nodes in the backbone layer of the double-star communication network The number of nodes in the backbone layer of the mesh communication network Among them, represents the optimal number of communities;

[0181] The number of nodes in the access layer of the double-star communication network The number of nodes in the access layer of the mesh communication network

[0182] Based on the hierarchical model of the communication network, combined with the principle that "the central node and the slave node in the star structure in the Power Communication Protocol must communicate directly, and the communication between slave nodes must be forwarded through the central node" and the actual architecture method, a double-star communication network topology is generated, such as Figure 4As shown in the figure. Among them, the internal connection methods of each layer of the double-star communication network include: the nodes of the access layer of the double-star communication network correspond one-to-one with the nodes of the power network, and the internal connection is the same as that of the power network; there is no direct connection relationship between the nodes of the backbone layer of the double-star communication network. It satisfies the single-link principle with the upper-level slave nodes (core layer control center nodes) and the lower-level slave nodes (power plant and substation nodes in the access layer), and the nodes of the double-star backbone layer need to communicate through the core layer control center nodes; the two control center nodes of the core layer of the double-star communication network are directly connected. The inter-layer connection methods of each layer of the double-star communication network include: the substation nodes of the access layer of the double-star communication network are first single-attributed to the backbone layer partition control center nodes, and the power plant nodes of the access layer are first directly attributed to the backbone layer partition control center nodes where they are located, and then randomly connected to one of the core layer control center nodes, with the connection probability P(c)=50%; the nodes of the backbone layer of the double-star communication network are double-attributed to the two control center nodes of the core layer.

[0183] Based on the hierarchical model of the communication network, referring to the mesh topology connection principle in the "Power Communication Protocol", considering the characteristics of the high ring formation rate among the nodes of the mesh power communication network and the actual architecture method, a mesh communication network topology is generated, as Figure 5 shown. Among them, the internal connection methods of each layer of the mesh communication network include: the nodes of the access layer of the mesh communication network correspond one-to-one with the nodes of the power network, and the internal connection is the same as that of the power network; the nodes of the backbone layer of the mesh communication network are connected in a ring, and the connections between the nodes in different regions are used as partition liaison lines. The connection relationship between the backbone layer partition control nodes is the same as that of the partition liaison lines, and there is a direct connection between the partition control node in the partition and the selected backbone layer substation node; the two control center nodes of the core layer of the mesh communication network are directly connected. The inter-layer connection methods of each layer of the mesh communication network include: the power plant nodes of the access layer of the mesh communication network are double-attributed to the backbone layer partition control center node and the backbone layer substation node where they are located. At the same time, the backbone layer substation node with the second highest degree value in the region is selected to be connected to the backbone layer partition control center node, so that the backbone layer substation nodes and the backbone layer nodes in the partition are in a ring; there is no direct connection relationship between the nodes of the access layer and the core layer of the mesh communication network.

[0184] The mathematical model of the power communication fusion network is G pn-cn =(V pn-cn , E pn-cn ), where V pn-cn represents the set of all nodes in the power communication fusion network, and E pn-cn represents the abstract set of all power lines in the power communication fusion network, and A pn-cn represents the coupling adjacency matrix of the topological connection relationship in the power communication fusion network;

[0185] The double-star power communication fusion network model As shown in Equation (18):

[0186]

[0187] In Equation (18), A pn-pn represents the node adjacency matrix of the power layer of the power network, represents the node adjacency matrix of the access layer of the communication network, represents the node adjacency matrix of the core layer of the communication network, represents the node coupling adjacency matrix between the power layer of the power network and the access layer of the communication network, represents the node coupling adjacency matrix between the access layer of the communication network and the backbone layer of the communication network, represents the node coupling adjacency matrix between the backbone layer of the communication network and the core layer of the communication network, represents the node coupling adjacency matrix between the access layer of the communication network and the backbone layer of the communication network.

[0188] The mesh-type power communication fusion network model As shown in Equation (19):

[0189]

[0190] In Equation (19), A pn-pn represents the node adjacency matrix of the power layer of the power network, represents the node adjacency matrix of the access layer of the communication network, represents the node adjacency matrix of the backbone layer of the communication network, represents the node adjacency matrix of the core layer of the communication network, represents the node coupling adjacency matrix between the power layer of the power network and the access layer of the communication network, represents the node coupling adjacency matrix between the access layer of the communication network and the backbone layer of the communication network, represents the node coupling adjacency matrix between the backbone layer of the communication network and the core layer of the communication network.

[0191] As shown in Table 1(a) and Table 1(b), simulation experiments were carried out in the IEEE 39-bus test system and the IEEE 118-bus test system respectively, and the simulation results of community division using the Louvain algorithm based on the improved electrical modularity proposed in the present invention were obtained. It can be seen from Table 1(a) that the electrical modularity in the IEEE 39-bus test system is 0.7155, and it can be seen from Table 1(b) that the electrical modularity in the IEEE 118-bus test system is 0.7174, both of which are much larger than the modularity evaluation criterion of 0.3, indicating that the communities generated by the method of community division using the Louvain algorithm based on the improved electrical modularity proposed in the present invention have higher quality, and the power network area allocation results have reliability and rationality.

[0192] As shown in Table 2, it describes by selecting including network density Ψ, average degree <k>, Feature path length <l>and the average clustering coefficient <c>Results of topological feature analysis of the double-star communication network and the mesh communication network constructed in the present invention based on complex network topological feature parameter indicators such as. As can be seen from Table 2, both the double-star communication network and the mesh communication network constructed in the present invention have a short characteristic path length and a high average clustering coefficient, which conforms to the small-world characteristics of an actual communication network. Compared with the reference [1] The mesh communication network generated, the double-star communication network and the mesh communication network constructed in the present invention have a smaller characteristic path length and a larger average clustering coefficient, and have more obvious small-world characteristics.

[0193] Table 1(a) Community partition results of IEEE 39-bus test system

[0194]

[0195] Table 1(b) Community partition results of IEEE 118-bus test system

[0196]

[0197] Table 2 Complex network topological feature parameters of power networks and communication networks

[0198]

[0199] As shown in Table 3, it describes by selecting including network density Ψ, average degree <k>, Feature path length <l>, Average clustering coefficient <c>Results of topological feature analysis of the double-star power communication fusion network and the mesh-type power communication fusion network constructed in the present invention, including complex network topological feature parameter indicators such as network degree distribution. As can be seen from Table 3, by analyzing the network density and the network characteristic path length, it can be known that the double-star power communication fusion network constructed in the present invention has a large density and a small characteristic path length. In addition, by analyzing the network characteristic path length, the average clustering coefficient, and the network degree distribution, it can be known that both the double-star power communication fusion network and the mesh-type power communication fusion network constructed in the present invention have small-world characteristics and partial scale-free characteristics, which are basically consistent with the actual power communication network model.

[0200] Table 3 Complex network topological feature parameters of the power communication fusion network

[0201]

[0202] References

[0203] [1] Wang Tao, Sun Cong, Gu Xueping, et al. Modeling and vulnerability analysis of power communication coupled networks [J]. Proceedings of the CSEE, 2018, 38(12): 12.< / c> < / l> < / k> < / c> < / l> < / k>

Claims

1. Method for generating power communication fusion network based on improved modularity community division, Characterized in that, The method for generating the power communication fusion network specifically Includes the following steps; Construct a power network topology structure, and abstract the power network into an undirected unweighted heterogeneous graph containing power source nodes, transmission nodes and generalized load nodes; By defining the evaluation of the power network energy transmission capacity, the power network energy transmission capacity after a line in the power network is removed, and the anti-impact capacity of the neighborhood after a certain line in the power network is removed, establish an index for evaluating the line energy transmission stability after a line in the power network is disconnected; By defining the topological connection difference of nodes in the power network and the topological connection difference of lines related to the nodes, establish an index for evaluating the importance of nodes in the power network topology and an index for evaluating the importance of lines in the power network topology structure; Establish a line power betweenness index for evaluating the importance of lines in the power network under normal operating conditions; Perform weighted balance ratio on the index for evaluating the line energy transmission stability after a line in the power network is disconnected, the index for evaluating the importance of lines in the power network topology structure, and the line power betweenness index for evaluating the importance of lines in the power network under normal operating conditions, and establish a node electrical association strength index; Based on the node electrical association strength index, improve the modularity used to evaluate the community quality in the Louvain algorithm for complex network community division to obtain the electrical modularity; Based on the electrical modularity, use the Louvain algorithm with improved modularity to perform community division on the power network to obtain the number of communities and the community to which each node belongs; According to the national power communication system partition management principle, as well as the number of communities obtained by performing community division on the power network using the Louvain algorithm and the community to which each node belongs, determine the number of core layer, backbone layer and access layer nodes in the communication network; Based on the communication network hierarchical model, construct a communication network topology structure, and abstract the communication network into an undirected unweighted heterogeneous graph including access layer nodes, backbone layer nodes and core layer nodes; Based on the communication network hierarchical model and power communication protocols, generate a double-star communication network topology and a mesh communication network topology respectively; Fuse the power network topology and the communication network topology to construct a mathematical model of the power communication fusion network; According to the double-star communication network topology and the mathematical model of the power communication coupling network, construct a mathematical model of the double-star power communication fusion network; According to the mesh communication network topology and the mathematical model of the power communication coupling network, construct a mathematical model of the mesh power communication fusion network.

2. The method for generating a power communication fusion network based on improved modularity community division according to claim 1, Characterized in that, The power network topology structure adopts the topology graph G pn =(V pn , E pn ), where V pn represents the set of all nodes in the power network, and E pn represents the abstract set of all power lines in the power network. The number of nodes in the power network is N pn ; Evaluate the line energy transfer stability index STA(l ij ) after a line is disconnected in the power grid. The calculation process is shown in Equation (1) as follows: In formula (1), represents the energy transmission capacity of the power network, represents the energy transmission capacity of the power network after removing line l ij in the power network, represents the anti-impact capacity of the neighborhood composed of all adjacent lines after removing line l ij in the power network; The power network energy transmission capacity The calculation formula is as shown in Equation (2): In formula (2), L m represents the number of lines that can be actively disconnected, and L n represents the number of lines that are subjected to energy impact after disconnection. S m represents the set of power network lines, and S n represents the set of lines that are subjected to energy impact after disconnection. is the impact limit that the line n subjected to energy impact can withstand. Z mn represents the electrical distance between the power network line m and the line n subjected to energy impact; The impact limit that the energy-impacted circuit n can withstand The calculation formula is as shown in Equation (3): In formula (3), P n,s and Q n,s respectively represent the initial active power flow and reactive power flow of line n subjected to energy impact, respectively represent the upper limits of the active power flow and reactive power flow of line n subjected to energy impact, respectively represent the upper and lower limits of the voltage phase angle difference of line n subjected to energy impact, respectively represent the upper and lower limits of the voltage amplitude difference of line n subjected to energy impact; Line l in the power grid ij The anti-impact ability of the neighborhood composed of all its adjacent lines after removal The calculation formula is as shown in Equation (4): In formula (4), i and j respectively represent the two end nodes of line l ij After removing line l ij a is the common neighbor node of nodes i and j, is the set of common neighbor nodes of nodes i and j, is except outside, the set of nodes adjacent to node i, is except outside, the set of nodes adjacent to node j.

3. The method for generating a power communication fusion network based on improved modularity community division according to claim 2, Characterized in that, The importance index CON(l ij ) for evaluating the line in the power grid in the power grid topology is calculated as shown in Equation (5): In formula (5), IM i represents the node importance of node i at both ends of line l ij , and IM j represents the node importance of node j at both ends of line l ij ; The line l ij The node importance IM of the two end nodes i i The calculation formula is as shown in Equation (6): In formula (6), De i represents the node degree value of node i, and P(De i ) represents the probability that the node degree value is De i . N pn represents the number of nodes in the power grid, represents the sum of the line weights of all adjacent lines of node i, Ω represents the set of neighbor nodes of node i, and IM i ′ represents the topological connection difference between the node and the line in the power grid topological structure, and calculates the average of the two. The calculation formula is shown in formula (7): IM i ′ = (S i + D i ) / 2(7) In formula (7), S i represents the topological connection difference of node i, and its calculation formula is shown in formula (8): S i = [1 - P(De i )]N pn (8) In formula (7), D i represents the topological connection difference of the lines related to node i, and its calculation formula is shown in formula (9):

4. The method for generating a power communication fusion network based on improved modularity community division according to claim 3, Characterized in that, Line power betweenness index POW(l) for evaluating the importance of lines in the normal operation state of the power network ij ) is calculated as shown in Equation (10): In formula (10), the generator factor representing the line power interconnection factor, the load factor representing the line power interconnection factor, represents the power flow weight factor of line l ij , ω G represents the weight of the generator factor, ω L represents the weight of the load factor; The generator factor of the line power intermedium The calculation formula is as shown in Equation (11): The load factor of the line power mediation factor The calculation formula is shown in Equation (12): The line l ij with a power flow weight factor has a calculation formula as shown in Equation (13): In formulas (11) to (13), represents the active power contributed by generator node g to line l ij ; represents the betweenness of line l, N ij ; G represents the number of generators contributing power to line l, N ij ; L represents the number of loads drawing power from line l ij ; represents the active power drawn by load node d from line l ij ; represents the actual power flow of line l ij ; represents the power transfer margin of line l ij ; 5. The method for generating a power communication fusion network based on improved modularity community division according to claim 4, wherein, The electrical association strength index f(l ij ) of the node is calculated as shown in Equation (14): In formula (14), the AHP-entropy weight method and the grey relational method are used to select ω 1 , ω 2 , ω 3 to balance the proportion of the weighting effect on the three indicators of STA(l ij ), CON(l ij ), and POW(l ij ); The electrical module degree Q f is calculated by the formula shown in Equation (15) as follows: In formula (15), M represents the total electrical correlation strength of the power network, and f′(l ij ) represents the electrical correlation strength between nodes i and j with an adjacent connection relationship, where k i represents the electrical degree of node i, and k j represents the electrical degree of node j; The electrical degree k of the node i i The calculation formula is shown in Equation (16) as follows: f′(l io ) represents the electrical association strength between node i and node o, and S o represents the set of all nodes having an adjacent connection relationship with node i; c i represents the community where node i is located, c j represents the community where node j is located, δ(c i , c j ) is defined as follows: if nodes i and j are in the same community, then c i = c j , and δ(c i , c j ) is 1; otherwise, δ(c i , c j ) is 0. Σ in represents the total electrical association strength of all the edges within community c, and Σ tot is the total electrical association strength of all the edges connected to the nodes within community c in the entire power network topology.

6. The method for generating a power communication fusion network based on improved modularity community division according to claim 5, wherein, The specific steps of using the Louvain algorithm with improved modularity to perform community division on the power network include: S1: Treat each node in the power network topology as a community, and the number of communities is the same as the number of nodes; S2: Sequentially merge each node in the power network topology with its neighbor nodes and calculate their electrical modularity gain; S3: Determine whether the electrical modularity gain is greater than 0. If it is greater than 0, place the node in the community where the neighbor node with the largest electrical modularity gain is located; S4: Repeat S3 until the community to which each node in the power network topology belongs no longer changes; S5: Take each community in S4 as an equivalent node, and the sum of the electrical degrees of the nodes within the original community is used as the electrical degree of this equivalent node, and the sum of the electrical association strengths between the nodes within the original community and the nodes within another community is used as the electrical association strength between different equivalent nodes; S6: Regard the equivalent nodes in S5 and the nodes not assigned to any community as the updated power network topology; S7: Repeat S1 to S6 until the optimal community division result is obtained. The community division result includes the optimal number of communities, the community to which each node belongs, and the electrical modularity of the optimal community; The electrical modularity gain ΔQ brought by putting node i into community c f is calculated by the formula shown in Equation (17) as follows: In formula (17), k i,in represents the total electrical association strength of all the edges connecting node i to the nodes within community C.

7. The method for generating a power communication fusion network based on improved modularity community division according to claim 6, wherein, The communication network includes core layer nodes backbone layer nodes and access layer nodes The number of core layer nodes is The number of backbone layer nodes is The number of access layer nodes is The communication network topology structure adopts a topology graph G cn =(V cn , E cn ), where Vcn represents the set of all nodes in the communication network, and E cn represents the abstract set of all power lines in the communication network; The setting of the number of nodes in the core layer, backbone layer, and access layer in the communication network includes: Number of core layer nodes in a dual-star communication network Number of core layer nodes in a mesh communication network The number of nodes in the backbone layer of the communication network is determined according to the number of communities obtained by the Louvain algorithm for improving modularity, where the number of nodes in the backbone layer of the double-star communication network The number of nodes in the backbone layer of the mesh communication network Among them, represents the optimal number of communities; Number of access layer nodes in a dual-star communication network Number of access layer nodes in a mesh communication network 8. The method for generating a power communication fusion network based on improved modularity community division according to claim 7, wherein, The specific generation principles of the double-star communication network topology and the mesh communication network topology include determining the internal connection methods and inter-layer connection methods of each level of the core layer, backbone layer, and access layer according to the number of nodes in the core layer, backbone layer, and access layer in the communication network.

9. The method for generating a power communication fusion network based on improved modularity community division according to claim 8, wherein, The mathematical model of the power communication fusion network is G pn-cn =(V pn-cn , E pn-cn ), where V pn-cn represents the set of all nodes in the power communication fusion network, and E pn-cn represents the abstract set of all power lines in the power communication fusion network. A pn-cn represents the coupling adjacency matrix of the topological connection relationship in the power communication fusion network; The mathematical model of the double-star power communication fusion network As shown in Equation (18): In Equation (18), A pn-pn represents the node adjacency matrix of the power layer of the power network, represents the node adjacency matrix of the access layer of the communication network, represents the node adjacency matrix of the core layer of the communication network, represents the node coupling adjacency matrix between the power layer of the power network and the access layer of the communication network, represents the node coupling adjacency matrix between the access layer of the communication network and the backbone layer of the communication network, represents the node coupling adjacency matrix between the backbone layer of the communication network and the core layer of the communication network, represents the node coupling adjacency matrix between the access layer of the communication network and the backbone layer of the communication network.

10. The method for generating a power communication fusion network based on improved modularity community division according to claim 9, wherein, The described mesh-type power communication fusion network model As shown in Equation (19): In formula (19), A pn-pn represents the node adjacency matrix of the power layer of the power grid, represents the node adjacency matrix of the access layer of the communication network, represents the node adjacency matrix of the backbone layer of the communication network, represents the node adjacency matrix of the core layer of the communication network, represents the node coupling adjacency matrix between the power layer of the power grid and the access layer of the communication network, represents the node coupling adjacency matrix between the access layer of the communication network and the backbone layer of the communication network, represents the node coupling adjacency matrix between the backbone layer of the communication network and the core layer of the communication network.

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