A power distribution network post-disaster dynamic ad hoc network method, system, device and storage medium

Abstract

The present application relates to the technical field of power distribution network post-disaster recovery, and provides a power distribution network post-disaster dynamic ad hoc network method, system, device and storage medium, which comprises obtaining distributed power supply information, power grid load information and power grid topology of the power distribution network, adding a virtual root node in the power grid topology to establish a virtual branch between the virtual root node and each distributed power supply in the power grid topology to generate an augmented power distribution network, and solving a power distribution network post-disaster dynamic ad hoc network model based on the topology structure of the augmented power distribution network, with the maximum power grid recovery load as the optimization target, to obtain a target ad hoc network strategy including each distributed power supply ad hoc network cluster and recovery load. The present application can improve the topology stability, node collaboration and fault adaptability of the ad hoc network, provide reliable technical support for realizing fast, stable and efficient power supply recovery of the power distribution network after a disaster, and effectively improve the self-healing capability of the power distribution network after a disaster.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution network post-disaster recovery, in particular to a power distribution network post-disaster dynamic ad hoc network method, system, device and storage medium. BACKGROUND

[0002] As the part of power system directly facing users, the reliability of power distribution network is crucial to the normal operation of society. After natural disasters (such as earthquakes, typhoons, floods, etc.) or other major failures, the infrastructure of power distribution network is often damaged to varying degrees, leading to power outages in some areas and seriously affecting people's production and life.

[0003] Traditional post-disaster recovery strategies of power distribution network usually rely on manual inspection and gradual repair, which is inefficient and time-consuming. With the continuous development of smart grid technology, it has become a research hotspot to use distributed power sources (such as photovoltaic power generation, wind power generation, etc.) and intelligent control technology to realize the self-organizing network recovery of power distribution network. However, the existing power distribution network ad hoc network method still has many application problems when facing complex and variable post-disaster environment: 1) the network topology structure is unstable, the coordination control between nodes is difficult, and it is difficult to realize efficient power distribution and voltage regulation; 2) poor adaptability to faults, unable to quickly respond to the dynamic changes of network topology, etc. Therefore, it is urgent to provide a power distribution network ad hoc network method that can adapt to complex post-disaster environment, has high reliability and flexibility, to improve the post-disaster recovery capability and power supply reliability of power distribution network. SUMMARY

[0004] The purpose of the present application is to provide a power distribution network post-disaster dynamic ad hoc network method, which introduces a virtual root node in the topology of power distribution network to construct an augmented power distribution network, and takes the maximization of post-disaster power grid recovery load as the optimization objective, and constructs a power grid post-disaster dynamic ad hoc network model based on the constraint conditions provided by the virtual spanning tree technology to solve the optimal ad hoc network strategy suitable for the augmented power distribution network, which can improve the topology stability, node collaboration and fault adaptability of the ad hoc network, provide reliable technical support for the realization of fast, stable and efficient power supply recovery of power distribution network after disaster, and effectively improve the post-disaster self-healing capability of power distribution network.

[0005] In order to achieve the above purpose, it is necessary to provide a power distribution network post-disaster dynamic ad hoc network method, system, device and storage medium for the above technical problems.

[0006] In the first aspect, the embodiments of the present application provide a power distribution network post-disaster dynamic ad hoc network method, which comprises the following steps:

[0007] obtaining distributed power supply information, power grid load information and power grid topology of a power distribution network; the distributed power supply information comprises locations and capacities of various distributed power supplies; the power grid load information comprises active loads of various nodes of the power distribution network;

[0008] adding a virtual root node to the power grid topology and establishing virtual branches between the virtual root node and various distributed power supplies in the power grid topology to generate an augmented power distribution network;

[0009] solving a pre-constructed post-disaster dynamic ad hoc network model of the power distribution network according to the distributed power supply information and the power grid load information to obtain a target ad hoc network strategy; the post-disaster dynamic ad hoc network model of the power distribution network is a distributed power supply ad hoc network optimization model constructed based on a topology structure of the augmented power distribution network and with maximization of power grid recovery load as an optimization objective; the target ad hoc network strategy comprises ad hoc network clusters of various distributed power supplies and corresponding recovery load.

[0010] Further, the construction step of the post-disaster dynamic ad hoc network model of the power distribution network comprises:

[0011] maximizing a sum of recovery loads of all ad hoc network clusters after the distributed power supply ad hoc network is constructed as an objective to construct an ad hoc network cluster optimization objective function;

[0012] based on distributed power supply supply capacity, power distribution network node recovery process power supply condition and pre-set augmented power distribution network operation condition, constructing an ad hoc network cluster optimization constraint based on virtual spanning tree technology; the power distribution network node recovery process power supply condition is that any distributed power supply and any power distribution network node are only accessed to one ad hoc network cluster; the distributed power supply supply capacity is that distributed power supply capacity in each ad hoc network cluster meets load demand of all power distribution network nodes in the cluster; the augmented power distribution network operation condition comprises virtual spanning tree network operation condition, power grid radial operation condition and ad hoc network cluster connectivity condition;

[0013] constructing the post-disaster dynamic ad hoc network model of the power distribution network according to the ad hoc network cluster optimization objective function and the ad hoc network cluster optimization constraint.

[0014] Further, the ad hoc network cluster optimization objective function is expressed as:

[0015]

[0016] wherein, represents whether the power distribution network node i is accessed to the ad hoc network cluster c; represents the active load of the power distribution network node i; and respectively represent the number of ad hoc network clusters in the power distribution network and the number of power distribution network nodes; represents the maximum load capacity recovered by the ad hoc network cluster in the distribution network.

[0017] Further, the ad hoc network cluster optimization constraints include ad hoc network operation constraints, virtual network flow constraints, radial constraints, and network connectivity constraints.

[0018] The step of constructing the ad hoc network cluster optimization constraints based on the distributed power supply capacity, the distribution network node recovery process power supply conditions, and the augmented distribution network operation conditions includes:

[0019] Based on the distributed power supply capacity and the distribution network node recovery process power supply conditions, the ad hoc network operation constraints are constructed.

[0020] Based on the virtual spanning tree network operation conditions, the virtual network flow constraints are constructed; the virtual spanning tree network operation conditions include that the sum of virtual flows of virtual branches and actual branches is equal, only connected branches pass through virtual flows, and bus virtual flows outside the virtual root node are balanced; the virtual network flow constraints include virtual flow injection constraints, virtual flow transmission constraints, and virtual flow balance constraints.

[0021] Based on the power grid radial operation conditions, the radial constraints are constructed; the power grid radial operation conditions include that the virtual root node is connected to the distributed power supply access node, the total number of ad hoc network recovery nodes is equal to the number of each ad hoc network cluster recovery node, the number of closed branches is equal to the number of recoverable nodes, and the distribution network branch can only be connected in one direction.

[0022] Based on the ad hoc network cluster connectivity conditions, the network connectivity constraints are constructed; the ad hoc network cluster connectivity conditions include that the head and tail nodes of the connected branch belong to the same ad hoc network cluster, the size of the connected branch virtual flow is limited, and there is only a single-direction virtual flow in the same connected branch within the cluster.

[0023] Further, the virtual flow injection constraint is represented as:

[0024]

[0025] wherein, represents the virtual root node; represents the virtual root node set; represents whether the i-th distribution network node is connected to the ad hoc network cluster c; represents whether the i-th distribution network node is connected to the ad hoc network cluster c; represents the parent node set of the distribution network node i; represents the virtual flow of the virtual branch i to the distribution network node j with the virtual root node k;

[0026] ​​​​The virtual flow balance constraint is represented as:

[0027]

[0028] wherein, represents the connection state of the distribution network branch with the parent node of the virtual flow to the distribution network node ; represents the connection state of the distribution network branch with the distribution network node of the virtual flow to the child node ; represents whether the distribution network node except the virtual root node is connected to the ad hoc network cluster c; represents the set of distribution network nodes; represents the set of nodes except the virtual root node; represents the set of child nodes of the distribution network node .

[0029] Further, the radial constraint is represented as:

[0030]

[0031] wherein, represents the virtual branch between the virtual root node and the distributed power supply; represents the set of virtual branches between the virtual root node and the distributed power supply; represents the number of distribution network nodes recovered in the ad hoc network cluster c; represents whether the th distribution network node is connected to the ad hoc network cluster c; represents the connection state of the distribution network branch ; represents the connection state of the distribution network branch ; represents the set of distribution network branches; represents the set of ad hoc network clusters in the distribution network; represents the set of distribution network nodes; represents the connection state of the virtual branch .

[0032] Further, the method further comprises:

[0033] After the post-disaster ad hoc network is started according to the target ad hoc network strategy, the periodically acquired ad hoc network cluster operation data are obtained, and when the ad hoc network cluster operation data do not satisfy preset stable operation conditions, the post-disaster dynamic ad hoc network model of the power distribution network is solved according to real-time distributed power supply information and real-time power grid load information to update the target ad hoc network strategy; the ad hoc network cluster operation data include actual recovery load amount, consumption rate and power supply cost of each ad hoc network cluster.

[0034] In a second aspect, an embodiment of the present application provides a post-disaster dynamic ad hoc network system of a power distribution network, and the system comprises:

[0035] An information acquisition module is configured to acquire distributed power supply information, power grid load information and power grid topology of the power distribution network; the distributed power supply information includes positions and capacities of each distributed power supply; the power grid load information includes active loads of each node of the power distribution network;

[0036] A power grid topology reconstruction module is configured to add a virtual root node in the power grid topology, and establish virtual branches between the virtual root node and each distributed power supply in the power grid topology to generate an augmented power distribution network.

[0037] An ad hoc network optimization module is configured to solve a pre-constructed post-disaster dynamic ad hoc network model of the power distribution network according to the distributed power supply information and the power grid load information to obtain a target ad hoc network strategy; the post-disaster dynamic ad hoc network model of the power distribution network is a distributed power supply ad hoc network optimization model constructed based on a topology structure of the augmented power distribution network with the optimization objective of maximizing grid recovery load amount; the target ad hoc network strategy includes an ad hoc network cluster of each distributed power supply and a corresponding recovery load amount.

[0038] In a third aspect, an embodiment of the present application further provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements steps of the above method when executing the computer program.

[0039] In a fourth aspect, an embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program implements steps of the above method when executed by a processor.

[0040] The application provides a power distribution network post-disaster dynamic ad hoc network method, system, computer device and storage medium, and realizes the technical scheme of obtaining distributed power supply information of the power distribution network including the positions and capacities of various distributed power supplies, power grid load information including active loads of various power distribution network nodes and a power grid topology, adding a virtual root node in the power grid topology, establishing virtual branches between the virtual root node and various distributed power supplies in the power grid topology to generate an augmented power distribution network, and solving a power distribution network post-disaster dynamic ad hoc network model constructed based on the topology structure of the augmented power distribution network in advance with the maximum power grid recovery load as the optimization target according to the distributed power supply information and the power grid load information, so as to obtain an ad hoc network cluster including various distributed power supplies and a target ad hoc network strategy corresponding to the recovery load. Compared with the prior art, the power distribution network post-disaster dynamic ad hoc network method can improve the topology stability, node collaboration and fault adaptability of the ad hoc network, provides reliable technical support for realizing fast, stable and efficient power supply recovery of the power distribution network after a disaster, and further effectively improves the self-healing ability of the power distribution network after a disaster. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 is a flowchart of the power distribution network post-disaster dynamic ad hoc network method in the embodiment of the application;

[0042] Figure 2 is an augmented power distribution network topology structure diagram of the IEEE33 node power distribution network system after adding a virtual root node in the embodiment of the application;

[0043] Figure 3 is a target ad hoc network strategy diagram generated by the power distribution network in the embodiment of the application by using the method of the application; Figure 2

[0044] Figure 4 is a topology structure diagram of the IEEE69 node power distribution network system in the embodiment of the application;

[0045] Figure 5 is a target ad hoc network strategy diagram generated by the power distribution network in the embodiment of the application by using the method of the application; Figure 4

[0046] Figure 6 is a structure diagram of the power distribution network post-disaster dynamic ad hoc network system in the embodiment of the application;

[0047] Figure 7 is an internal structure diagram of the computer device in the embodiment of the application;

[0048] REFERENCE SIGNS:

[0049] Among them, 101, information acquisition module; 102, power grid topology reconstruction module; 103, ad hoc network optimization module.​​ DETAILED DESCRIPTION

[0050] In order to make the purposes, technical solutions and beneficial effects of the present application clearer, further detailed description will be given below in combination with the drawings and examples. Obviously, the following described examples are part of the embodiments of the present application and are only used to illustrate the present application, but not to limit the scope of the present application. Based on the examples in the present application, all other examples obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0051] The power distribution network post-disaster dynamic ad hoc network method provided by the present application can be understood as a kind of power distribution network ad hoc network method for extreme power outage situation caused by extreme disaster, which can adapt to complex post-disaster environment, has high reliability and flexibility, and can quickly, stably and efficiently restore power supply of the power distribution network after disaster. The following examples will describe the power distribution network post-disaster dynamic ad hoc network method in detail.

[0052] In one embodiment, as shown in Figure 1 A power distribution network post-disaster dynamic ad hoc network method is provided, comprising the following steps:

[0053] S101, acquiring distributed power supply information, power grid load information and power grid topology of the power distribution network; wherein the distributed power supply information can be understood as the relevant deployment information of all distributed power supplies (Distributed Power Generation, DG) existing in the power distribution network system to be recovered after disaster, the position and capacity of each distributed power supply, wherein the position of the distributed power supply can be understood as the position of the power distribution network node where the distributed power supply is connected, which directly restricts the position of the virtual flow injection into the power distribution network system in subsequent modeling; the capacity of the corresponding distributed power supply can be understood as the existing access capacity configured in the power distribution network, which can also be reset according to the actual post-disaster recovery scene demand. The power grid load information includes the active load of each power distribution network node, which can be understood as the active load demand of the power distribution network node, which can be determined based on the relevant active load data collected by the relevant monitoring system before the power distribution network failure; it should be noted that the distributed power supply information, power grid load information and power grid topology of the power distribution network can be acquired based on the power distribution automation master station, and the specific acquisition method is not limited here.

[0054] S102, adding a virtual root node in the power grid topology, and establishing a virtual branch between the virtual root node and each distributed power supply in the power grid topology to generate an augmented power distribution network; wherein the augmented power distribution network can be understood as a virtual network topology obtained by adding a virtual node as a virtual energy supply point of the entire power distribution network system in the existing power grid topology, and connecting it with each distributed power supply in the power grid topology to build a virtual branch Figure 2 As shown in the power grid topology, it is convenient for subsequent comprehensive analysis of the entire power distribution network node ad hoc network. It should be noted that, Figure 2 In the formula, r represents the virtual root node introduced in the power grid topology, DG represents the distributed power supply, represents the power distribution network node, and the blue dashed line between r and each DG represents the virtual branch between the virtual root node and each distributed power supply, that is, Figure 2 A virtual network topology is shown, in which the virtual root node r provides power for the entire augmented power distribution network.

[0055] S103, according to the distributed power supply information and the power grid load information, solving the pre-constructed power distribution network post-disaster dynamic ad hoc network model to obtain a target ad hoc network strategy; wherein the power distribution network post-disaster dynamic ad hoc network model can be understood as an optimization model for obtaining the optimal ad hoc network construction strategy based on the distributed power supply in the power distribution network for the power distribution network node to supply power, in order to minimize the power loss and influence caused by the power distribution network post-disaster failure, and to consider the topology stability, node collaboration and fault adaptability requirements, the embodiment preferably adopts a distributed power supply ad hoc network optimization model based on the topology structure of the augmented power distribution network, which maximizes the power grid recovery load as the optimization target, to accurately and efficiently obtain the target ad hoc network strategy, that is, to obtain the self-organizing network cluster of each distributed power supply and the corresponding recovery load, and each self-organizing network cluster can be understood as a set of power distribution network nodes powered by the distributed power supply in the self-organizing network cluster.

[0056] The above-mentioned power distribution network post-disaster dynamic ad hoc network model can be understood as an ad hoc network optimization model constructed based on the virtual spanning tree model with the maximum system recovery load after extreme disaster as the target and given optimization constraints, to solve the post-disaster ad hoc network strategy applicable to the power distribution network; specifically, the construction steps of the power distribution network post-disaster dynamic ad hoc network model include:

[0057] Maximizing the sum of the recovery loads of all self-organizing network clusters after the distributed power supply ad hoc network as the target, to construct a self-organizing network cluster optimization objective function; that is, the self-organizing network cluster optimization objective function is represented as:

[0058]

[0059] Wherein, is a 0-1 variable, indicating whether the ith distribution network node is connected to the ad hoc network cluster c, and if yes, its value is 1, otherwise, it is 0, and , ; represents the active load of the ith distribution network node; and respectively represent the number of ad hoc network clusters in the distribution network and the number of distribution network nodes; represents the maximum load capacity recovered by the ad hoc network cluster in the distribution network; represents the maximum function.

[0060] Based on the distributed power supply capacity, the distribution network node recovery process power supply condition and the preset augmented distribution network operation condition, the ad hoc network cluster optimization constraint is constructed based on the virtual spanning tree technology; the distribution network node recovery process power supply condition is that any distributed power supply and any distribution network node are only connected to one ad hoc network cluster; the distributed power supply capacity is that the distributed power supply capacity in each ad hoc network cluster meets the load demand of all distribution network nodes in the cluster; and the augmented distribution network operation condition includes virtual spanning tree network operation condition, power grid radial operation condition and ad hoc network cluster connectivity condition.

[0061] The ad hoc network cluster optimization constraint in the embodiment can be understood as an ad hoc network strategy optimization condition constructed based on the virtual spanning tree technology under the application demand of the ad hoc network in full consideration of the distributed power supply capacity and the power supply constraint in the node recovery process, to ensure the normalization and feasibility of the recovery process, and to ensure the normalization of the distribution network operation. Preferably, the ad hoc network cluster optimization constraint includes ad hoc network operation constraint, virtual network flow constraint, radial constraint and network connectivity constraint. Specifically, the step of constructing the ad hoc network cluster optimization constraint based on the distributed power supply capacity, the distribution network node recovery process power supply condition and the augmented distribution network operation condition includes:

[0062] Based on the distributed power supply capacity and the distribution network node recovery process power supply condition, the ad hoc network operation constraint is constructed; the ad hoc network operation constraint includes distributed power supply ad hoc network operation constraint, load node ad hoc network operation constraint and distributed power supply ad hoc network capacity constraint, and is specifically represented as follows:

[0063] 1) Distributed power supply ad hoc network operation constraint, used to limit each ad hoc network cluster to contain only one distributed power supply, to ensure the resource utilization rate of the distributed power supply, and can be represented as:

[0064]

[0065] wherein, represents the distributed power supply access node Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0;

[0066] 2) Load node self-organizing network operation constraint, which is used to limit that any load node in the power distribution network system is only allowed to access to one cluster in the network organization process, and can be represented as:

[0067]

[0068] wherein, Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0;

[0069] 3) Distributed power self-organizing network capacity constraint, which is used to limit that the capacity of the distributed power in each network organization cluster meets the load demand of all nodes in the cluster, and can be represented as:

[0070]

[0071] wherein, Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0;

[0072] Based on the virtual spanning tree network operation condition, the virtual network flow constraint is constructed; wherein the virtual spanning tree network operation condition includes that the sum of virtual flows of virtual branches and actual branches is equal, only the connected branch passes through the virtual flow, and the bus virtual flow balance outside the virtual root node; correspondingly, the virtual network flow constraint includes virtual flow injection constraint, virtual flow transmission constraint and virtual flow balance constraint, which are specifically represented as follows:

[0073] 1) Virtual flow injection constraint, which is used to limit that the sum of virtual flows on all virtual branches in the virtual spanning tree network is equal to the sum of virtual flows on all actual branches, and can be represented as:

[0074]

[0075] wherein, Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; Yicis a 0-1 variable, which equals to 1 if the distribution network node i is connected to the cluster c, otherwise 0; ​virtual branch virtual root node virtual flow number of virtual branches number of distributed generation units connected to distribution network nodes;

[0076] 2) virtual flow transmission constraint, which is used to limit the virtual flow to pass through only the connected branch, and can be expressed as:

[0077]

[0078] wherein, virtual flow connected to distribution network nodes; virtual flow connected to distribution network nodes; connection state of distribution network branch , which is a 0-1 variable, and is 1 if connected, otherwise 0; a very large positive number; set of distribution network branches.

[0079] 3) virtual flow balance constraint, which is used to limit the virtual flow balance of all buses passing through the virtual flow except the virtual root node, and can be expressed as:

[0080]

[0081] wherein, virtual flow connected to parent node connected to distribution network nodes; virtual flow connected to child node connected to distribution network nodes; whether the distribution network node connected to child node connected to self-organizing network cluster c except the virtual root node; set of nodes except the virtual root node; set of child nodes of distribution network node .

[0082] ​constructing the radial constraint based on the radial operation condition of the power grid; wherein the radial operation condition of the power grid comprises that a virtual root node is in communication with a distributed power supply access node, a total number of self-organizing network restoration nodes is equal to a number of self-organizing network cluster restoration nodes, a number of closed branches is equal to a number of recoverable nodes, and a distribution network branch can only be in one-way communication; correspondingly, the radial constraint comprises a virtual branch state constraint, a restoration node quantity constraint, and a branch communication constraint, and is specifically represented as follows:

[0083] 1) The virtual branch state constraint is used for limiting that a virtual branch between the virtual root node and the distributed power supply access position is definitely in communication, and can be represented as:

[0084]

[0085] In the formula, represents a connection state of a virtual branch , is a 0-1 variable, and is 1 if the connection is connected, and is 0 otherwise; represents a virtual branch between a virtual root node and a distributed power supply, in actual application, there is one virtual root node and multiple distributed power supplies, and correspondingly, there are multiple virtual branches A set of virtual branches between the virtual root node and the distributed power supply.

[0086] 2) The restoration node quantity constraint is used for limiting that a number of nodes recovered through a self-organizing network in a virtual spanning tree network is equal to a sum of numbers of nodes that can be recovered in each cluster, and can be represented as:

[0087]

[0088] In the formula, represents a number of distribution network nodes recovered in a self-organizing network cluster c; represents whether an i-th distribution network node is accessed to the self-organizing network cluster c.

[0089] 3) The branch communication constraint is used for limiting that a number of closed branches in the virtual spanning tree network is equal to a number of recoverable nodes in an actual network, and when the branch is in communication, the branch can only satisfy one of that a node i is a parent node of a node j or that the node j is the parent node of the node i (the distribution network branch can only be in one-way communication), and can be represented as:

[0090]

[0091] In the formula, represents a connection state of a distribution network branch ; represents a connection state of a distribution network branch ;​​ denotes a set of branches of the power distribution network; denotes a set of ad hoc network clusters in the power distribution network; denotes a set of nodes of the power distribution network.

[0092] construct the network connectivity constraint based on the ad hoc network cluster connectivity condition; the ad hoc network cluster connectivity condition includes that the head and tail nodes of a connected branch belong to the same ad hoc network cluster, a virtual flow size limit of a connected branch, and only a unidirectional virtual flow exists in the same connected branch within a cluster; the network connectivity constraint includes a branch connectivity constraint, a virtual flow and branch state relationship constraint, and a connectivity constraint within a network cluster, and is specifically represented as follows:

[0093] 1) the branch connectivity constraint, which is used to limit that if a branch is connected, the head and tail nodes of the branch belong to the same cluster, that is, only if the head and tail nodes of the branch are located in one cluster, the branch is connected, and can be represented as:

[0094]

[0095] In the formula, denotes the connection state of the power distribution network branch . denotes the connection state of the power distribution network branch . denotes a set of branches of the power distribution network; denotes whether the i-th power distribution network node is connected to the ad hoc network cluster c; denotes whether the i-th power distribution network node is connected to the ad hoc network cluster c.

[0096] 2) the virtual flow and branch state relationship constraint, which is used to limit the relationship between the virtual flow and the branch state, that is, the virtual flow can only flow through a closed branch, and can be represented as:

[0097]

[0098] In the formula, denotes whether the branch ij can flow through the virtual flow, which is a 0-1 variable, and is 1 if yes, and 0 otherwise; denotes the virtual flow of the power distribution network node on the branch ij to the power distribution network node ; denotes the connection state of the power distribution network branch , which is a 0-1 variable, and is 1 if connected, and 0 otherwise; denotes a very large positive number; denotes a set of branches of the power distribution network.

[0099] ​​​3) Networking cluster connectivity constraints, used to limit the existence of only one virtual flow flow direction between two power distribution network nodes, which can be expressed as:

[0100]

[0101] In the formula, represents the power distribution network branch whether the virtual flow can flow; represents the power distribution network branch whether the virtual flow can flow, is a 0-1 variable, if yes, it is 1, otherwise, it is 0.

[0102] The self-organizing network operation constraints provided by the embodiment can effectively ensure the normativity, feasibility of the power distribution network load recovery process and the availability of distributed energy by fully considering the distributed power supply capacity and the power supply constraints in the node recovery process; The virtual network flow constraint designed is the core constraint condition for function implementation, which is based on adding a virtual root node and introducing a virtual flow, realizes the description of self-organizing network operation with the feasible path of virtual flow, facilitates the simulation of real power flow in the power distribution network, and ensures the practicability of the self-organizing network strategy; At the same time, the designed radial constraint and networking connectivity constraint can ensure the specification of the power distribution network operation. Through the design of the above four constraint conditions, it can effectively ensure that the optimal self-organizing network formed by the distributed power supply can be fully utilized to provide continuous and reliable power supply under the condition of dynamic change of post-disaster topology.

[0103] According to the self-organizing network cluster optimization objective function and the self-organizing network cluster optimization constraint, the post-disaster dynamic self-organizing network model of the power distribution network is constructed.

[0104] The post-disaster dynamic self-organizing network model of the power distribution network constructed by the above method can be directly solved quickly by using existing commercial solving software such as Cplex, Gurobi, etc. based on distributed power supply information and power grid load information, to obtain the required target self-organizing network strategy, including the self-organizing network result of each power distribution network node and the recovery situation of the corresponding load. It should be noted that the solving process of the specific post-disaster dynamic self-organizing network model of the power distribution network can be realized by referring to the related prior art, which will not be described in detail here.

[0105] The power distribution network post-disaster dynamic ad hoc network method provided by the embodiment, by fully considering the distributed power supply access position and capacity constraints, introducing a virtual root node in the power distribution network topology to construct an augmented power distribution network, taking the maximum load recovery of the post-disaster power grid as the optimization target of the ad hoc network, combining the virtual spanning tree technology to generate a feasible path that can guarantee the normative and feasibility of the power distribution network load recovery process, the availability of distributed energy and the operation specification of the power distribution network, and the virtual flow-based feasible path to depict the ad hoc network operation, facilitating the simulation of the power flow in the real power distribution network, ensuring the practicability of the ad hoc network optimization constraint condition, constructing a post-disaster dynamic ad hoc network model for solving the optimal ad hoc network strategy of the post-disaster complex scenario of the power distribution network, which can improve the topology stability, node collaboration and fault adaptability of the ad hoc network, provide reliable technical support for the fast, stable and efficient recovery of power supply of the power distribution network after the disaster, and effectively improve the self-healing ability of the power distribution network after the disaster.

[0106] In order to verify the effectiveness of the application of the power distribution network post-disaster dynamic ad hoc network method proposed by the application, the embodiment takes the IEEE33 node power distribution network system shown in Figure 2 and the IEEE69 node power distribution network system shown in Figure 4 as examples to verify the post-disaster dynamic ad hoc network.

[0107] As shown in Figure 2 , the IEEE33 node power distribution network system has 33 power distribution network nodes and 37 branches, wherein, n 29 , n 22 , n 12 , n 21 , n 25 , n 29 are tie lines. In the normal operation state, the tie lines are in the disconnected state to ensure the radial operation of the system; Figure 2 the solid line indicates that the power distribution branch is closed, the dashed line indicates that the power distribution branch is disconnected, and the distributed power supply is connected to nodes n 10 , n 26 . Assuming that an extreme fault occurs in branch n1-n2, if there is no distributed power supply in the system, all nodes lose connection with the power supply. If there is a distributed power supply in the system, the distributed power supply can be used as a power supply to restore system power supply in the form of an ad hoc network. A virtual root node r is introduced to establish a virtual branch between the virtual root node and all distributed power supplies in the system to form an augmented power distribution network based on the virtual spanning tree model. As shown in Figure 3As shown, the virtual root node r and the distributed power nodes in the system form three virtual branches. Virtual flows are injected from the virtual root node, and the virtual flows pass along the closed branches in the system, considering the distributed power access location and capacity constraints. The feasible paths of the virtual flows in the system explicitly represent the meshing results, and the three meshing areas formed are as shown in Figure 3 Based on the obtained meshing recovery strategy, the distributed power nodes n2 to n9, the distributed power nodes n 23 to the distributed power nodes n 25 and the distributed power nodes n 19 to the distributed power nodes n 22 are grouped into the meshing cluster of the distributed power accessed at the node n2. The distributed power nodes n 10 to the distributed power nodes n 18 are grouped into the meshing cluster of the distributed power accessed at the node n 10 . The distributed power nodes n 26 to the distributed power nodes n 33 are grouped into the meshing cluster of the distributed power accessed at the node n 26 , and all the loads can be recovered.

[0108] As shown in Figure 4 , the distribution network node 1 is a substation node, the branches 11-66, 13-21, 15-69, 39-48, and 27-25 are tie lines, and in the normal operating state, the tie lines are in the open state to ensure the radial operation of the system. Three distributed powers in the system are connected to the distribution network node 3, the distribution network node 23, and the distribution network node 43, and the capacities are 1200 kVA, 1000 kVA, and 2000 kVA respectively. It is assumed that an extreme fault occurs on the branch 1-2, and all the nodes in the system lose connection with the power supply. A virtual root node r is established, virtual branches are established between the virtual root node and all the distributed powers in the system, and an augmented distribution network based on the virtual spanning tree model is formed. The virtual root node r is taken as a virtual power supply, and virtual flows are injected into the system. The feasible paths of the virtual flows in the system explicitly represent the meshing recovery strategy, as shown in Figure 5 , the system is divided into three meshing areas for fault recovery. Based on the obtained meshing recovery strategy, the distributed power nodes n2 to n7, the distributed power nodes n to the distributed power nodes n and the distributed power nodes n to the distributed power nodes n are grouped into the meshing cluster of the distributed power accessed at the distribution network node 3. The distributed power nodes n to the distributed power nodes n and the distributed power nodes n to the distributed power nodes n are grouped into the meshing cluster of the distributed power accessed at the distribution network node 23. The distributed power nodes n to the distributed power nodes n are grouped into the meshing cluster of the distributed power accessed at the distribution network node 43, and all the loads can be recovered.

[0109] In addition, considering the fluctuation of distributed power output and the change of power grid load in the process of actual distribution network ad hoc network operation, in order to avoid the rigidity of static networking application, and to ensure the continuous efficiency and reliability of the operation of the distribution network ad hoc network, the embodiment preferably periodically detects the ad hoc network operation state of the distribution network after the post-disaster load restoration of the distribution network based on the target ad hoc network strategy obtained in the above embodiment, so as to timely and dynamically adjust in the case of low distributed power consumption rate or low load recovery. Specifically, in one embodiment, the method further comprises:

[0110] After starting the post-disaster ad hoc network according to the target ad hoc network strategy, the periodically obtained ad hoc network cluster operation data, and when the ad hoc network cluster operation data does not meet the preset stable operation condition, the post-disaster dynamic ad hoc network model of the distribution network is solved according to the real-time distributed power information and the real-time power grid load information, so as to update the target ad hoc network strategy; the ad hoc network cluster operation data includes the actual recovery load amount, the consumption rate and the power supply cost of each ad hoc network cluster.

[0111] The actual recovery load amount in the embodiment can be obtained based on the actual active load of all distribution network nodes in the ad hoc network cluster collected by the existing monitoring system of the distribution network, and can be used to evaluate the actual load recovery situation; the consumption rate can be understood as the ratio of the actual output of the distributed power in the ad hoc network cluster to the maximum output (configured capacity), and can be used to evaluate the resource utilization rate of the distributed power in the ad hoc network cluster; the power supply cost can be understood as the operation cost of the distributed power in the ad hoc network cluster, and is used to evaluate the power supply economy of the load recovery of the ad hoc network cluster, and can be calculated based on the related prior art, which is not described in detail here.

[0112] In order to ensure that the power distribution network self-organizing network can be timely adjusted based on the change of the power distribution network operation environment, and at the same time, the scientificity and rationality of the adjustment can be ensured as much as possible, the preset stable operation condition can be set as the actual recovery load amount, the consumption rate and the power supply cost of the self-organizing network cluster being not more than the average index value of the entire power distribution network. In actual application, after the self-organizing network cluster operation data obtained periodically, whether the actual recovery load amount, the consumption rate and the power supply cost of each self-organizing network cluster reach the corresponding preset network adjustment threshold is judged respectively. If any index of any self-organizing network cluster reaches, the power distribution network post-disaster dynamic self-organizing network model is solved according to the real-time distributed power information and the real-time power grid load information, so as to update the target self-organizing network strategy, so as to ensure the rationality and reliability of the operation of the power distribution network self-organizing network. Otherwise, the actual recovery load amount, the consumption rate and the power supply cost of each self-organizing network cluster are compared with the corresponding index control threshold range respectively, so as to count the number of self-organizing network clusters whose actual recovery load amount, consumption rate and power supply cost exceed the corresponding index control threshold range, and when the number of self-organizing network clusters whose any index exceeds the index control threshold range reaches the first preset proportion, or the number of self-organizing network clusters whose two indexes exceed the index control threshold range reaches the second preset proportion, or the number of self-organizing network clusters whose three indexes exceed the index control threshold range reaches the third preset proportion, the power distribution network post-disaster dynamic self-organizing network model is solved according to the real-time distributed power information and the real-time power grid load information, so as to update the target self-organizing network strategy. It should be noted that in actual application, the specific values of the first preset proportion, the second preset proportion and the third preset proportion can be set according to actual application requirements, but the first preset proportion should be greater than the second preset proportion, and the second preset proportion should be greater than the third preset proportion, so as to realize hierarchical control of self-organizing network update, ensure the rationality and scientificity of adaptive adjustment, and ensure the stability of the operation of the power distribution network self-organizing network.

[0113] It should be noted that although each step in the above flowchart is displayed in sequence according to the direction of the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise stated herein, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders.

[0114] In one embodiment, as shown in FIG. 1, Figure 6 A power distribution network post-disaster dynamic self-organizing network system is provided, which comprises:

[0115] An information acquisition module 101 is configured to acquire distributed power information, power grid load information and power grid topology of the power distribution network. The distributed power information includes the location and capacity of each distributed power source. The power grid load information includes the active load of each power distribution network node.

[0116] The power grid topology reconfiguration module 102 is configured to add a virtual root node in the power grid topology, and establish a virtual branch between the virtual root node and each distributed power supply in the power grid topology, to generate an augmented power distribution network.

[0117] The ad hoc network optimization module 103 is configured to solve a pre-constructed post-disaster dynamic ad hoc network model of the power distribution network according to the distributed power supply information and the power grid load information, to obtain a target ad hoc network strategy; the post-disaster dynamic ad hoc network model of the power distribution network is a distributed power supply ad hoc network optimization model constructed based on a topology structure of the augmented power distribution network, with a maximized power grid recovery load as an optimization objective; and the target ad hoc network strategy includes an ad hoc network cluster of each distributed power supply and a corresponding recovery load.

[0118] In one embodiment, the system further includes:

[0119] The dynamic updating module is configured to, after starting the post-disaster ad hoc network according to the target ad hoc network strategy, periodically acquire ad hoc network cluster operation data, and when the ad hoc network cluster operation data does not satisfy a preset stable operation condition, solve the post-disaster dynamic ad hoc network model of the power distribution network according to real-time distributed power supply information and real-time power grid load information, to update the target ad hoc network strategy; the ad hoc network cluster operation data includes an actual recovery load, a consumption rate and a power supply cost of each ad hoc network cluster.

[0120] The specific limitations of the post-disaster dynamic ad hoc network system of the power distribution network can refer to the limitations of the post-disaster dynamic ad hoc network method of the power distribution network, and the corresponding technical effects can also be obtained equally, which will not be repeated here. Each module in the above post-disaster dynamic ad hoc network system of the power distribution network can be realized by software, hardware and combinations thereof, in whole or in part. Each module can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each module.

[0121] Figure 7 An internal structure diagram of a computer device in one embodiment is shown, which can be a terminal or a server. As shown in FIG. 6, the computer device includes a processor 601, a memory 602, a communication interface 603 and a communication bus 604. The communication bus 604 is configured to connect the processor 601, the memory 602 and the communication interface 603 to each other. Figure 7As shown, the computer device includes a processor, a memory, a network interface, a display, a camera and an input device connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The network interface of the computer device is configured to communicate with an external terminal through a network connection. The computer program, when executed by the processor, can implement the power distribution network post-disaster dynamic ad hoc network method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0122] Those skilled in the art can understand that, Figure 7 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. A specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have the same component arrangement.

[0123] In one embodiment, a computer device is provided, including a memory, a processor and a computer program stored on the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program.

[0124] In one embodiment, a computer readable storage medium is provided, which stores a computer program, and the computer program, when executed by a processor, implements the steps of the above method.

[0125] In summary, the power distribution network post-disaster dynamic ad hoc network method, system, device and storage medium provided by the embodiments of the present application can improve the topology stability, node collaboration and fault adaptability of the ad hoc network by introducing a virtual root node into the power distribution network topology to construct an augmented power distribution network, taking the maximization of the post-disaster power grid recovery load as the optimization objective, and constructing a power grid post-disaster dynamic ad hoc network model for solving the optimal ad hoc network strategy suitable for the augmented power distribution network in combination with the constraint conditions provided based on the virtual spanning tree technology, thereby providing reliable technical support for realizing the fast, stable and efficient recovery of power supply of the power distribution network after a disaster, and effectively improving the self-healing ability of the power distribution network after a disaster.

[0126] Various embodiments are described herein with reference to the drawings, wherein each embodiment is described in a progressive manner, and each embodiment directly or indirectly refers to each other, and each embodiment focuses on the differences from other embodiments. In particular, the system embodiments are described more simply because they are basically similar to the method embodiments, and the relevant parts can be referred to the description of the method embodiments. It should be noted that the technical features of the above embodiments can be combined in any manner, and in order to make the description simple, not all possible combinations of the technical features of the above embodiments are described, but as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the description.

[0127] The above-described embodiments only express several preferred embodiments of the present application, which are described in a more specific and detailed manner, but should not be understood as limiting the scope of the patent. It should be noted that for ordinary skilled in the art, several improvements and replacements can be made without departing from the technical principles of the present application, and these improvements and replacements should be considered as the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the protection scope of the claims.

Claims

1. A method for dynamic self-organizing distribution networks after disasters, characterized in that, The method includes the following steps: Acquire distributed generation information, grid load information, and grid topology of the distribution network; the distributed generation information includes the location and capacity of each distributed generation; the grid load information includes the active power load of each distribution network node; Add a virtual root node to the power grid topology and establish virtual branches between the virtual root node and each distributed power source in the power grid topology to generate an augmented distribution network. Based on the distributed power source information and the power grid load information, the pre-constructed post-disaster dynamic self-organizing network model of the distribution network is solved to obtain the target self-organizing network strategy. The post-disaster dynamic self-organizing network model of the distribution network is a distributed power source self-organizing network optimization model constructed based on the topology of the augmented distribution network with the optimization objective of maximizing the power grid recovery load. The target self-organizing network strategy includes the self-organizing network clusters of each distributed power source and the corresponding recovery load. The construction steps of the post-disaster dynamic self-organizing network model of the distribution network include: To maximize the sum of recovery loads of all self-organizing clusters after the distributed power source self-organizes, an optimization objective function for self-organizing clusters is constructed. Based on the power supply capacity of distributed generation sources, the power supply conditions during the recovery process of distribution network nodes, and the preset operating conditions of augmented distribution networks, an optimization constraint for ad hoc network clusters is constructed using virtual spanning tree (VPS) technology. The power supply conditions during the distribution network node recovery process stipulate that any distributed generation source and any distribution network node are connected to only one ad hoc network cluster. The power supply capacity of distributed generation sources ensures that the capacity of distributed generation sources within each ad hoc network cluster meets the load requirements of all distribution network nodes within the cluster. The operating conditions of the augmented distribution network include VPS network operating conditions, radial grid operating conditions, and ad hoc network cluster connectivity conditions. The virtual spanning tree network... The network operation conditions include that the sum of the virtual flows of virtual branches and actual branches is equal, only connected branches are balanced by virtual flows, and the virtual flows of buses other than virtual root nodes are balanced; the radial operation conditions of the power grid include that virtual root nodes are connected to distributed power source access nodes, the total number of self-organizing network recovery nodes is equal to the number of recovery nodes in each self-organizing network cluster, the number of closed branches is equal to the number of recoverable nodes, and distribution network branches can only be connected in one direction; the self-organizing network cluster connectivity conditions include that the first and last nodes of a connected branch belong to the same self-organizing network cluster, the virtual flow size of a connected branch is limited, and only unidirectional virtual flows exist in the same connected branch within the cluster; Based on the self-organizing network cluster optimization objective function and the self-organizing network cluster optimization constraints, the post-disaster dynamic self-organizing network model of the distribution network is constructed.

2. The method for dynamic self-organizing distribution networks after disasters as described in claim 1, characterized in that, The objective function for optimizing the self-organizing network cluster is expressed as follows: in, Indicates whether distribution network node i is connected to the ad hoc network cluster c; This represents the active load of node i in the distribution network; and These represent the number of ad hoc network clusters and the number of distribution network nodes, respectively. This indicates the maximum load that can be restored within the distribution network through the self-organizing network cluster.

3. The method for dynamic self-organizing distribution networks after disasters as described in claim 1, characterized in that, The self-organizing network cluster optimization constraints include self-organizing network operation constraints, virtual network flow constraints, radial constraints, and network connectivity constraints. The steps for constructing optimization constraints for ad hoc network clusters based on distributed power supply capacity, power supply conditions during distribution network node recovery, and augmented distribution network operation conditions include: Based on the power supply capacity of the distributed power source and the power supply conditions during the recovery process of the distribution network nodes, the self-organizing network operation constraints are constructed; the self-organizing network operation constraints include distributed power source self-organizing network operation constraints, load node self-organizing network operation constraints, and distributed power source self-organizing network capacity constraints. Based on the operating conditions of the virtual spanning tree network, the virtual network flow constraints are constructed; the virtual network flow constraints include virtual flow injection constraints, virtual flow transit constraints, and virtual flow balance constraints. Based on the aforementioned radial operating conditions of the power grid, the radial constraints are constructed; the radial constraints include virtual branch state constraints, recovery node quantity constraints, and branch connectivity constraints. Based on the self-organizing network cluster connectivity conditions, the network connectivity constraints are constructed; the network connectivity constraints include branch connectivity constraints, virtual flow and branch state relationship constraints, and network cluster intra-connectivity constraints.

4. The method for dynamic self-organizing distribution networks after disasters as described in claim 3, characterized in that, The virtual stream injection constraint is expressed as follows: in, Indicates a virtual root node; Represents the set of virtual root nodes; Indicates distribution network node Whether to connect to the self-organizing network cluster c; Indicates distribution network node The set of parent nodes; Indicates virtual branch There is a virtual root node. Flow to distribution network nodes Virtual stream; The virtual flow balance constraint is expressed as: in, Indicates distribution network branch There is a parent node Flow to distribution network nodes Virtual stream; Indicates distribution network branch There are distribution network nodes. Flow to child nodes Virtual stream; Represents distribution network nodes other than the virtual root node. Whether to connect to the self-organizing network cluster c; This represents the set of nodes excluding the virtual root node. Represents the set of nodes in a distribution network; Indicates distribution network node The set of child nodes.

5. The method for dynamic self-organizing distribution networks after disasters as described in claim 3, characterized in that, The radial constraint is represented as follows: in, This represents a virtual branch between the virtual root node and the distributed power source. A collection of virtual branches between the virtual root node and the distributed power source; This indicates the number of distribution network nodes that have been restored within the self-organizing cluster c; Indicates distribution network node Whether to connect to the self-organizing network cluster c; Indicates distribution network branch The connection status; Indicates distribution network branch The connection status; Represents the set of branches in a power distribution network; Represents a set of ad hoc network clusters within a distribution network; Represents the set of nodes in a distribution network; Indicates virtual branch The connection status.

6. The method for dynamic self-organizing distribution networks after disasters as described in claim 1, characterized in that, The method further includes: After the post-disaster self-organizing network is activated according to the target self-organizing network strategy, the self-organizing network cluster operation data is acquired periodically. When the self-organizing network cluster operation data does not meet the preset stable operation conditions, the post-disaster dynamic self-organizing network model of the distribution network is solved based on real-time distributed power source information and real-time grid load information to update the target self-organizing network strategy. The self-organizing network cluster operation data includes the actual restored load, absorption rate and power supply cost of each self-organizing network cluster.

7. A dynamic self-organizing network system for post-disaster distribution networks, characterized in that, The system, employing the post-disaster dynamic self-organizing network method for distribution networks as described in claim 1, comprises: The information acquisition module is used to acquire distributed power source information, grid load information, and grid topology of the distribution network; the distributed power source information includes the location and capacity of each distributed power source; the grid load information includes the active power load of each distribution network node; The power grid topology reconfiguration module is used to add virtual root nodes to the power grid topology and establish virtual branches between the virtual root nodes and each distributed power source in the power grid topology to generate an augmented distribution network. The self-organizing network optimization module is used to solve the pre-constructed post-disaster dynamic self-organizing network model of the distribution network based on the distributed power source information and the grid load information to obtain the target self-organizing network strategy. The post-disaster dynamic self-organizing network model of the distribution network is a distributed power source self-organizing network optimization model constructed based on the topology of the augmented distribution network with the optimization objective of maximizing the grid recovery load. The target self-organizing network strategy includes the self-organizing network clusters of each distributed power source and the corresponding recovery load.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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