Power distribution network reconstruction method and device considering typhoon disaster, terminal equipment and storage medium

Abstract

The invention discloses a power distribution network reconstruction method and device considering typhoon disasters, terminal equipment and a storage medium, and the method comprises the steps: predicting the line fault probability of each transmission line in a power distribution network according to typhoon data and the geographic position of each element in the power distribution network; and generating a plurality of fault scenes of the power distribution network according to the line fault probability, thereby realizing quantitative evaluation of the operation risk of the power distribution network under the typhoon disaster. According to the network topology model of the power distribution network and the fault scene set, constructing a two-stage network reconstruction model taking the minimization of the network reconstruction cost as a target and the minimization of the load loss of the power distribution network as a target, and solving the two-stage network reconstruction model; and finally obtaining a target network reconstruction strategy formed according to the target solution of each decision variable of the two-stage network reconstruction model. Therefore, the method can provide a network reconstruction strategy considering both economical efficiency and feasibility for the power distribution network in a specific scene of typhoon disasters.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a method, device, terminal equipment and storage medium for reconfiguring a distribution network taking into account typhoon disasters. Background Art

[0002] According to the statistics of the Global Change Data Laboratory, it is difficult to estimate the direct or indirect economic losses caused by natural disasters such as typhoons, tsunamis, earthquakes, and volcanic eruptions each year. With the increasing frequency of natural disasters, the normal supply of electricity, water, etc. will also be affected by more frequent destructive effects. Extreme meteorological disasters, especially typhoon disasters, pose a great threat to the power grid. It is very likely that the distribution network will have tower collapse, line breakage and other failures, which will lead to large-scale power outages, affect the stable operation of the power system, and cause considerable economic losses. When extreme meteorological disasters occur, how to ensure the normal operation of the power system is a very important issue. Enhancing the resilience of the distribution network is a necessary measure to minimize the impact of disaster events and ensure the normal power consumption of ordinary power users when they are affected by disasters. The network reconstruction of the distribution network, as a way of network reorganization, mainly through the reasonable configuration of the switching status of the section switch and the tie switch, and then the configuration of the decoupling point, adjust the topology of the distribution network, and then affect the system flow distribution, so as to ensure that the system load is not or less affected by the extreme disaster time, and improve the robustness and disaster resistance of the distribution network. However, in the specific scenario of typhoon disasters, how to provide the distribution network with a network reconstruction strategy that can both resist the impact of extreme weather and take into account economy and feasibility remains a challenging issue. Summary of the invention

[0003] The embodiments of the present invention provide a distribution network network reconstruction method, apparatus, terminal device and storage medium taking into account typhoon disasters, which can provide a distribution network with a network reconstruction strategy that takes into account both economy and feasibility in the specific scenario of typhoon disasters.

[0004] An embodiment of the present invention provides a method for reconfiguring a distribution network taking into account typhoon disasters, comprising:

[0005] Obtain typhoon data, network topology model of distribution network, and geographical locations of transmission lines and towers in distribution network;

[0006] Calculating the line failure probability of each of the transmission lines according to the typhoon data, the geographical location of the transmission lines, and the geographical locations of a number of towers connected to each transmission line;

[0007] According to the line failure probability, a set of fault scenarios of the distribution network is constructed; wherein the set of fault scenarios is composed of the fault scenarios of the distribution network at each moment; the fault scenarios define a number of fault lines of the distribution network that are affected by the typhoon and fail at a corresponding moment;

[0008] According to the network topology model and the set of fault scenarios, a two-stage network reconstruction model is constructed with the goal of minimizing the network reconstruction cost and the goal of minimizing the load loss of the distribution network; wherein the decision variables of the two-stage network reconstruction model include: a first variable representing the connection status of each of the transmission lines, a second variable representing the continuous change of the load of each node in the distribution network, and a third variable used to represent the impact of the typhoon on the distribution network;

[0009] Solving the two-stage network reconstruction model to obtain target solutions for each decision variable of the two-stage network reconstruction model;

[0010] A target network reconstruction strategy for the distribution network is generated according to the target solution; wherein the target network reconstruction strategy records the target switching state of the configuration switches of each transmission line in the distribution network.

[0011] Furthermore, the typhoon data includes: the typhoon's central movement track, the typhoon's gradient wind speed, and rainfall;

[0012] The calculating the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line, comprises:

[0013] Determine, at each moment, a first distance between the tower and the typhoon center, and a second distance between the transmission line and the typhoon center, according to the center movement trajectory, the geographical location of the transmission line, and the geographical location of the tower;

[0014] Calculate the first typhoon impact degree borne by the tower at each moment and the second typhoon impact degree borne by each transmission line at each moment according to the first distance, the second distance, the gradient wind speed, and the rainfall;

[0015] Calculating the tower failure probability of each of the towers at each moment according to the impact degree of the first typhoon;

[0016] Dividing each of the transmission lines into a plurality of sections, and calculating the section failure probability of each section at each moment according to the impact degree of the second typhoon;

[0017] According to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line, the line failure probability of each transmission line at each moment is calculated.

[0018] Furthermore, the calculating of the line failure probability of each transmission line at each moment according to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line includes:

[0019] The failure probability of the transmission line is calculated according to the following formula:

[0020]

[0021] Among them, Prob l (t) is the failure probability of the transmission line l at time t, n tw is the set of towers connected to the transmission line l, Prob tw,i (t) is the failure probability of the ith tower in the tower set at time t, n sg is the set of segments divided by the transmission line l, λ sg,j (t) is the failure probability of the jth segment in the segment set at time t.

[0022] Furthermore, the two-stage network reconstruction model is:

[0023]

[0024] in, is the first objective function with the goal of minimizing the network reconstruction cost, is a second objective function with the goal of minimizing the load loss of the distribution network, x is the first variable, is a preset first constraint condition set of the first variable, L is a transmission line set of the distribution network, l is the lth transmission line in the transmission line set, C connect () is the cost required when the switching state of the configuration switch of the transmission line l is connected, C dis () is the cost required when the switching state of the configuration switch of the transmission line l is disconnected, α l is a binary variable representing the switching state of the configuration switch of the transmission line l, A l is a binary variable representing the actual operating state of the transmission line 1, y is the second variable, is a preset second constraint set of the second variable, u is the third variable, is a third constraint condition set of the third variable generated according to the fault scenario set, N is a node set of the distribution network, P iD is the design load at node i, is the actual load at node i.

[0025] Further, the first set of constraint conditions includes: a network radial constraint for constraining a transmission line topology, a transmission line number constraint for constraining a transmission line that can change an operating state in the distribution network, a line maximum power flow constraint, a node power balance constraint for constraining a power load balance of the distribution network, a distributed power source power constraint, an energy storage power constraint, and an active power constraint;

[0026] The second constraint condition set includes: the node power balance constraint, the distributed power source power constraint, the energy storage power constraint, the active power constraint, and the line maximum power flow constraint;

[0027] The third constraint condition set includes: a fault probability threshold constraint, a maximum number of faulty lines constraint, a line fault state transfer constraint, and a faulty line restoration constraint.

[0028] Furthermore, solving the two-stage network reconstruction model to obtain target solutions for each decision variable of the two-stage network reconstruction model includes:

[0029] Linearizing the two-stage network reconstruction model to generate a main problem generated by the first objective function and a sub-problem generated by the second objective function;

[0030] Determine, from the set of fault scenarios, an initial fault scenario that has the greatest impact on the distribution network;

[0031] According to the initial fault scenario, the main problem, and the sub-problems, an iterative solution operation is performed on the two-stage network reconstruction model until a target solution of each decision variable of the two-stage network reconstruction model is generated;

[0032] The iterative solution operation includes:

[0033] Obtain a scenario to be identified; wherein, initially, the scenario to be identified is an initial fault scenario, the upper bound of the solution set of the two-stage network reconstruction model is positive infinity, the lower bound of the solution set is negative infinity, the set of identified fault scenarios is an empty set, and the set of newly added constraints is empty;

[0034] Under the first set of constraints and the newly added set of constraints, the main problem is solved according to the scenario to be identified, a first solution set of the first variable and the newly added constraints are generated, and the lower bound of the solution set is updated according to the first solution set and the newly added constraints; wherein the first solution set is a network reconstruction strategy for the distribution network to respond to the scenario to be identified with the minimum network reconstruction cost;

[0035] Under the second set of constraints and the third set of constraints, the subproblem is solved according to the first solution set to generate a second solution set of the second variable and a third solution set of the third variable; wherein the second solution set is the load loss caused by the distribution network under the network reconstruction strategy corresponding to the first solution set, and the third solution set is the worst fault scenario evolved by the distribution network after applying the network reconstruction strategy corresponding to the first solution set, and the worst fault scenario is not in the identified scenario set;

[0036] updating the upper bound of the solution set according to the second solution set and the third solution set;

[0037] Determine whether the upper bound of the solution set and the lower bound of the solution set converge to a preset range threshold;

[0038] If not, adding the scene to be identified to the set of identified scenes, adding the newly added constraint to the set of newly added constraints, and using the third solution set as the scene to be identified required for the next round of iterative solution operation;

[0039] If so, the first solution set, the second solution set, and the third solution set are used as the target solutions of the first variable, the second variable, and the third variable, respectively.

[0040] Another embodiment of the present invention provides a distribution network reconstruction device taking into account typhoon disasters, comprising:

[0041] A data acquisition module is used to obtain typhoon data, a network topology model of the distribution network, and the geographical locations of transmission lines and towers in the distribution network;

[0042] A data calculation module, used to calculate the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line;

[0043] A scenario construction module, used to construct a set of fault scenarios of the distribution network according to the line failure probability; wherein the set of fault scenarios is composed of the fault scenarios of the distribution network at each moment; the fault scenarios define a number of fault lines of the distribution network that are affected by the typhoon and fail at the corresponding moment;

[0044] A model construction module, for constructing a two-stage network reconstruction model with the goal of minimizing the network reconstruction cost and the goal of minimizing the load loss of the distribution network according to the network topology model and the set of fault scenarios; wherein the decision variables of the two-stage network reconstruction model include: a first variable representing the connection status of each of the transmission lines, a second variable representing the continuous change of the load of each node in the distribution network, and a third variable used to represent the impact of the typhoon on the distribution network;

[0045] A model solving module, used to solve the two-stage network reconstruction model to obtain a target solution for each decision variable of the two-stage network reconstruction model;

[0046] A strategy generation module is used to generate a target network reconstruction strategy for the distribution network according to the target solution; wherein the target network reconstruction strategy records the target switching state of the configuration switches of each transmission line in the distribution network.

[0047] Furthermore, the typhoon data includes: the typhoon's central movement track, the typhoon's gradient wind speed, and rainfall;

[0048] The data calculation module calculates the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line, including:

[0049] Determine, at each moment, a first distance between the tower and the typhoon center, and a second distance between the transmission line and the typhoon center, according to the center movement trajectory, the geographical location of the transmission line, and the geographical location of the tower;

[0050] Calculate the first typhoon impact degree borne by the tower at each moment and the second typhoon impact degree borne by each transmission line at each moment according to the first distance, the second distance, the gradient wind speed, and the rainfall;

[0051] Calculating the tower failure probability of each of the towers at each moment according to the impact degree of the first typhoon;

[0052] Dividing each of the transmission lines into a plurality of sections, and calculating the section failure probability of each section at each moment according to the impact degree of the second typhoon;

[0053] According to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line, the line failure probability of each transmission line at each moment is calculated.

[0054] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a distribution network reconstruction method taking into account typhoon disasters as described in any one of the embodiments is implemented.

[0055] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a distribution network reconstruction method taking into account typhoon disasters as described in any of the above embodiments.

[0056] The following beneficial effects are achieved by implementing the present invention:

[0057] The present invention discloses a method, device, terminal equipment and storage medium for network reconstruction of a distribution network taking into account typhoon disasters. The method predicts the line failure probability of each transmission line in the distribution network according to typhoon data and the geographical location of each component in the distribution network, and then generates several fault scenarios of the distribution network according to the line failure probability, so as to achieve quantitative evaluation of the operation risk of the distribution network under typhoon disasters. Then, according to the network topology model of the distribution network and the set of fault scenarios, a two-stage network reconstruction model with the goal of minimizing the network reconstruction cost and the goal of minimizing the load loss of the distribution network is constructed, and solved to obtain a target network reconstruction strategy formed by the target solution of each decision variable of the two-stage network reconstruction model. After the distribution network is reconstructed according to the target network reconstruction strategy, that is, after the topology structure of the distribution network is adjusted according to the target switching state of the configuration switch of each transmission line, the impact of the disaster on the distribution network can be minimized while ensuring that the network reconstruction cost required is the lowest. Therefore, the present invention can provide a network reconstruction strategy that takes into account both economy and feasibility for the distribution network in the specific scenario of typhoon disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a flowchart of a method for reconfiguring a distribution network taking into account typhoon disasters provided by an embodiment of the present invention.

[0059] Figure 2 It is a structural schematic diagram of a distribution network reconstruction device taking typhoon disasters into consideration provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0062] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0063] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0064] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0065] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0066] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0067] See also Figure 1 , is a flow chart of a method for reconfiguring a distribution network taking into account typhoon disasters provided by an embodiment of the present invention, comprising:

[0068] S1. Obtain typhoon data, network topology model of distribution network, and geographical locations of transmission lines and towers in distribution network;

[0069] S2. Calculating the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line;

[0070] Preferably, the typhoon data includes: the central movement track of the typhoon, the gradient wind speed of the typhoon, and the rainfall;

[0071] The calculating the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line, comprises:

[0072] S21, determining, at each moment, a first distance between the tower and the typhoon center, and a second distance between the transmission line and the typhoon center according to the center movement trajectory, the geographical location of the transmission line, and the geographical location of the tower;

[0073] S22, calculating the first typhoon impact degree borne by the tower at each moment and the second typhoon impact degree borne by each transmission line at each moment according to the first distance, the second distance, the gradient wind speed, and the rainfall;

[0074] S23, calculating the tower failure probability of each tower at each moment according to the impact degree of the first typhoon;

[0075] S24, dividing each of the transmission lines into a plurality of segments, and calculating the segment failure probability of each segment at each moment according to the impact degree of the second typhoon;

[0076] S25. Calculate the line failure probability of each transmission line at each moment according to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line.

[0077] Preferably, the calculating of the line failure probability of each transmission line at each moment according to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line comprises:

[0078] S251. Calculate the failure probability of the transmission line according to the following formula:

[0079]

[0080] Among them, Prob l (t) is the failure probability of the transmission line l at time t, n tw is the set of towers connected to the transmission line l, Prob tw,i (t) is the failure probability of the ith tower in the tower set at time t, n sg is the set of segments divided by the transmission line l, λ sg,j (t) is the failure probability of the jth segment in the segment set at time t.

[0081] In a preferred embodiment of the present invention, the operation risk of the distribution network under typhoon disasters is modeled as a Bernoulli distribution with time-varying parameters, the line failure probability is integrated, and the disaster-affected failures and recovery are introduced into a robust uncertainty set with chance constraints.

[0082] Specifically, at a distance r (unit: km) from the typhoon center, calculate the gradient wind speed V G (r,t)

[0083]

[0084] B(t)=b1-b2R wm (t)-b3ψ(t)+ε B ;

[0085]

[0086] f r =2Ωsinφ r ;

[0087] In the formula, A(r,t) is an auxiliary variable, f r is the Coriolis coefficient. wm(t) is the radius of maximum wind speed, unit: km, which can be expressed as a function of Δp and ψ(t). B(t) is the shape parameter of the Holland pressure contour. ρ is the air density. Ω is the Earth's rotation rate. φ r is the latitude of the location, unit: °. ε B ,ε lnRwm is the error coefficient. b1, b2, b3, b4, b5 are the coefficients obtained from historical typhoon data.

[0088] The rainfall at a distance r (km) from the typhoon center can be expressed as RA (r, t), unit: mm·h -1 :

[0089] RA(r,t)=k(t)k1(t)s(t)R(r,t);

[0090] k(t)=k2Δp(t)-k3 k≥1;

[0091]

[0092] R(r,t) is an auxiliary variable, dp(t) / dt represents the rate of change of central pressure, unit: mb·h -1 k(t), k1(t), s(t) all represent correction coefficients. k2, k3, k4, k5, k6, k7, k8, k9, k 10 Both represent coefficients obtained from historical data.

[0093] The gradient wind speed at the location of the element (transmission line and tower) is converted by the gust factor, and the expression is as follows:

[0094]

[0095] Where, Vr cm (t),t,h d / represents the wind speed at the location of the element after the gust factor conversion. α cm The power law index representing the location of the element. d is the height of the basic wind speed in the area. τ is the gust factor.

[0096] In the tower damage failure analysis, the equivalent wind speed is defined as follows:

[0097]

[0098] In the formula, r tw (t) is the first distance from the tower location to the typhoon center, unit: km. * .r tw (t),t,h d / represents the equivalent wind speed at the tower, unit: m / s. Vr tw (t),t,h d / indicates the wind speed at the tower, unit: m / s. RA.r tw (t),t,h d / indicates the precipitation at the tower, unit: mm / h. v0, v1, v2, v3, v4, v5 are all historical parameters.

[0099] The failure probability of towers under extreme typhoon disasters is as follows:

[0100]

[0101]

[0102] Among them, Prob tw,i (t) is the tower failure probability. tw,i (t) is an auxiliary variable, μ tw,i ,σ tw,i For x tw,i (t) The mean and standard deviation.

[0103] Divide the transmission line into sufficiently short segments, assuming that segment j is in the same terrain and exposed to the same typhoon wind speed and precipitation. Then the failure probability of segment j is as follows:

[0104]

[0105] Among them, L sg is the length of the segment, unit: km. V(r sg (t),t,h d ) is the wind speed at segment j, unit: m / s. RA(r sg (t), t) is the precipitation at segment j, unit: mm / h. V sgd RA is the design wind speed of segment j, unit: m / s. sgd is the design precipitation at segment j, unit: mm / h. sg ,b sg ,c sg ,d sg It is a parameter calculated based on historical data.

[0106] Finally, the failure probability of a transmission line l is as follows:

[0107]

[0108] Where n tw is the total number of towers on transmission line l, n sg is the total number of conductor segments in the transmission line l.

[0109] S3. Constructing a set of fault scenarios of the distribution network according to the line failure probability; wherein the set of fault scenarios is composed of the fault scenarios of the distribution network at each moment; the fault scenarios define several fault lines of the distribution network that are affected by the typhoon and fail at the corresponding moment;

[0110] In a preferred embodiment of the present invention, two sets of auxiliary variables are introduced: binary variables representing the impact of typhoon on line failure recovery and a binary variable representing the affected line fault The latter satisfies the failure probability Prob of transmission line l at time t l (t) is the Bernoulli distribution, that is:

[0111]

[0112] The above variables need to satisfy the third set of constraints:

[0113] Fault probability threshold constraint: By setting the probability threshold Π, it is determined whether the transmission line fails due to the typhoon disaster:

[0114]

[0115] The maximum number of faulty lines constraint is the maximum total number of transmission lines that are affected and fail at the same time:

[0116]

[0117] In the formula, L is the set of all lines in the distribution network, and l is a line in the distribution network. l (t) represents the binary variable of the availability of the affected line in the disaster scenario generated at time t. L is the total number of lines in the distribution network, OFF max The maximum total number of failures allowed due to disasters at the same time.

[0118] Line fault state transition constraints, the state transition relationship of the line can be expressed as follows:

[0119]

[0120] Fault line recovery constraint: the damaged transmission line will automatically recover after a certain period of time RT.

[0121]

[0122] S4. According to the network topology model and the set of fault scenarios, a two-stage network reconstruction model is constructed with the goal of minimizing the network reconstruction cost and the goal of minimizing the load loss of the distribution network; wherein the decision variables of the two-stage network reconstruction model include: a first variable characterizing the connection status of each of the transmission lines, a second variable characterizing the continuous change of the load of each node in the distribution network, and a third variable used to characterize the impact of the typhoon on the distribution network;

[0123] Preferably, the two-stage network reconstruction model is:

[0124]

[0125] in, is the first objective function with the goal of minimizing the network reconstruction cost, is a second objective function with the goal of minimizing the load loss of the distribution network, x is the first variable, is a preset first constraint condition set of the first variable, L is a transmission line set of the distribution network, l is the lth transmission line in the transmission line set, C connect () is the cost required when the switching state of the configuration switch of the transmission line l is connected, C dis () is the cost required when the switching state of the configuration switch of the transmission line l is disconnected, α l is a binary variable representing the switching state of the configuration switch of the transmission line l, A l is a binary variable representing the actual operating state of the transmission line 1, y is the second variable, is a preset second constraint set of the second variable, u is the third variable, is a third constraint condition set of the third variable generated according to the fault scenario set, N is a node set of the distribution network, P i D is the design load at node i, is the actual load at node i.

[0126] The first set of constraint conditions includes: a network radial constraint for constraining a transmission line topology, a transmission line number constraint for constraining transmission lines that can change operating states in the distribution network, a line maximum power flow constraint, a node power balance constraint for constraining power load balance of the distribution network, a distributed power source power constraint, an energy storage power constraint, and an active power constraint;

[0127] The second constraint condition set includes: the node power balance constraint, the distributed power source power constraint, the energy storage power constraint, the active power constraint, and the line maximum power flow constraint;

[0128] The third constraint condition set includes: a fault probability threshold constraint, a maximum number of faulty lines constraint, a line fault state transfer constraint, and a faulty line restoration constraint.

[0129] In a preferred embodiment of the present invention, a two-stage network reconstruction model for distribution network reconstruction considering the uncertainty of disaster situations is established, and the model is composed of an objective function and constraint conditions. The specific steps are as follows:

[0130] The two-stage network reconstruction model is determined as follows:

[0131]

[0132] in, is the first objective function with the goal of minimizing the network reconstruction cost, is a second objective function with the goal of minimizing the load loss of the distribution network, x is the first variable, is a preset first constraint condition set of the first variable, L is a transmission line set of the distribution network, l is the lth transmission line in the transmission line set, C connect () is the cost required when the switching state of the configuration switch of the transmission line l is connected, C dis () is the cost required when the switching state of the configuration switch of the transmission line l is disconnected, α l is a binary variable representing the switching state of the configuration switch of the transmission line l, A l is a binary variable representing the actual operating state of the transmission line 1, y is the second variable, is a preset second constraint set of the second variable, u is the third variable, is a third constraint condition set of the third variable generated according to the fault scenario set, N is a node set of the distribution network, P i D is the design load at node i, is the actual load at node i.

[0133] Furthermore, the two-stage network reconstruction model can be divided into the first stage, the second stage outer layer, and the second stage inner layer, each with its corresponding objective function and constraints. The details are as follows:

[0134] Phase 1:

[0135] The objective function expression of the first stage is:

[0136]

[0137] Among them, η is a new variable added in the iterative process of the column and constraint generation algorithm, which represents the sum of the load losses of each node in the system.

[0138] The first stage constraint set include:

[0139] Network radial constraints:

[0140]

[0141] Among them, i and j represent the nodes of the distribution network respectively, N is the set of all nodes in the distribution network system, and N(i) is the set of sub-nodes in the distribution network that may be connected to node i.

[0142] By auxiliary variable β ij A binary variable α can be defined to describe the network reconstruction l :

[0143]

[0144] Among them, i is the starting node of line l, and j is the ending node of line l.

[0145] Transmission line number constraints:

[0146]

[0147] Among them, SW max Indicates the maximum number of lines whose operating status can be changed in the network reconstruction strategy.

[0148] Node power balance constraints:

[0149]

[0150] Among them, i and j represent the nodes of the distribution network respectively. is an auxiliary variable. is the actual load at node i. is the active power of the energy storage system at node i. is the active power of the distributed generation at node i.

[0151] Distributed power generation constraints in distribution networks, namely distributed power generation constraints:

[0152]

[0153] Among them, N DG It is a collection of nodes connected to distributed power sources. is the active power of the distributed generation at node i, is the maximum active power of the distributed generation at node i.

[0154] The power constraint of the energy storage system in the distribution network, that is, the energy storage power constraint:

[0155]

[0156] Where N ESS It is a set of nodes connected to the energy storage system. is the active power of the energy storage system at node i, is the maximum charging active power of the distributed generation at node i, is the maximum discharge active power of the distributed generation at node i.

[0157] Active power constraint:

[0158]

[0159] Among them, P i D is the design load at node i, is the actual load at node i.

[0160] Auxiliary variables Definition and constraint of , that is, the maximum power flow constraint of the line:

[0161]

[0162] In the formula, p ij is the active power flow between nodes i and j. l It is a binary variable representing the switch state of each line l under network reconstruction. l It represents the worst scenario of the distribution network affected by typhoon disaster. max Indicates the maximum active power that the transmission line l can carry.

[0163] Second stage outer layer:

[0164] The second stage outer layer variable to be decided is u, which is the second stage outer layer; the set of constraints that need to be satisfied is the set of fault scenarios generated by probability The constraints that need to be met are consistent with the S3 expression of the same embodiment and will not be repeated here.

[0165] Second stage inner layer:

[0166] The second stage inner objective function:

[0167]

[0168] Among them, P i D is the design load at node i, is the actual load at node i. y is the inner layer decision variable in the second stage, which is a continuous variable representing the actual load and actual power of the distribution network, mainly the actual load at node i And auxiliary variables The set of constraints that the decision variable y needs to satisfy is

[0169] The set of constraints in the inner layer of the second stage Mainly include:

[0170] Node power balance constraints:

[0171]

[0172] Power constraints of distributed generation in distribution network:

[0173]

[0174] Power constraints of energy storage systems in distribution networks:

[0175]

[0176] Load active power constraint:

[0177]

[0178] Auxiliary variables Definition and constraints:

[0179]

[0180] S5, solving the two-stage network reconstruction model to obtain target solutions for each decision variable of the two-stage network reconstruction model;

[0181] Preferably, solving the two-stage network reconstruction model to obtain a target solution for each decision variable of the two-stage network reconstruction model includes:

[0182] S51, linearizing the two-stage network reconstruction model to generate a main problem generated by the first objective function and a sub-problem generated by the second objective function;

[0183] S52, determining an initial fault scenario that has the greatest impact on the distribution network from the set of fault scenarios;

[0184] S53, performing an iterative solution operation on the two-stage network reconstruction model according to the initial fault scenario, the main problem, and the sub-problem, until a target solution of each decision variable of the two-stage network reconstruction model is generated;

[0185] The iterative solution operation includes:

[0186] S531, obtaining a scenario to be identified; wherein, initially, the scenario to be identified is an initial fault scenario, the upper bound of the solution set of the two-stage network reconstruction model is positive infinity, the lower bound of the solution set is negative infinity, the set of identified fault scenarios is an empty set, and the set of newly added constraints is empty;

[0187] S532. Under the first set of constraints and the newly added set of constraints, solve the main problem according to the scenario to be identified, generate a first solution set of the first variable and the newly added constraints, and update the lower bound of the solution set according to the first solution set and the newly added constraints; wherein the first solution set is a network reconstruction strategy for the distribution network to respond to the scenario to be identified with the minimum network reconstruction cost;

[0188] S533. Under the second set of constraints and the third set of constraints, solve the subproblem according to the first solution set to generate a second solution set of the second variable and a third solution set of the third variable; wherein the second solution set is the load loss caused by the distribution network under the network reconstruction strategy corresponding to the first solution set, and the third solution set is the worst fault scenario evolved by the distribution network after applying the network reconstruction strategy corresponding to the first solution set, and the worst fault scenario is not in the identified scenario set;

[0189] S534, updating the upper bound of the solution set according to the second solution set and the third solution set;

[0190] S535, determining whether the upper bound of the solution set and the lower bound of the solution set converge to a preset range threshold;

[0191] S536: If not, add the scene to be identified to the set of identified scenes, add the newly added constraint to the set of newly added constraints, and use the third solution set as the scene to be identified required for the next round of iterative solution operation;

[0192] S537: If yes, the first solution set, the second solution set, and the third solution set are used as target solutions of the first variable, the second variable, and the third variable, respectively.

[0193] In a preferred embodiment of the present invention, the two-stage network reconstruction model is linearized as follows:

[0194]

[0195]

[0196] In the above formula, a T ,b Tis the transpose of the objective function coefficient vector. G, E, M are the corresponding linear matrices in the constraints, and h is the corresponding linear vector. y Constraint Set The constraints in are only related to the decision variables y.

[0197] The main question is:

[0198]

[0199] Ex≥h-Mu ο -Gy ο ;

[0200] The calculation subproblem using the Karush-Kuhn-Tucker condition (KKT condition) equation group is:

[0201] SP2:maxb T y;

[0202]

[0203] G T z≤b;

[0204]

[0205] Iterate the solution until the upper and lower bounds converge, and obtain the distribution network reconstruction strategy. The general process is as follows:

[0206] Step 1: Iteration initialization. Set the lower bound LB = -∞ and the upper bound UB = +∞. Initialize the number of iterations n = 0 and initialize the set of scenarios identified by the subproblem.

[0207] Step 2: Solve the first relaxed solution of the main problem and update the lower bound. Customize a worst disaster scenario u, solve the main problem, and get the relaxed solution x n:1 ,η n:1 ,x 1 ……x n . Update the lower bound to LB = a T x n:1 +η n:1 .

[0208] Step 3: Solve for the current x n:1 Subproblems under this problem and update the upper bound. n:1 Substitute into the subproblem and find the possible worst case u n:1 , and get the corresponding y n:1 The updated upper bound is

[0209] UB=a T x n:1 +bT y n:1 .

[0210] Step 4: Solve and update the upper bound after adding constraints to the main problem. Add the constraints to the main problem and replace the u obtained from the subproblem with n:1 and the corresponding y n:1 Substitute, update the number of iterations n = n + 1 and the set of scenarios identified for the subproblem Continue to solve the main problem and get x n:1 ,η n:1 . Update the lower bound to

[0211] LB=a T x n:1 +η n:1 .

[0212] Step 5: Repeat steps 3 and 4 until the difference between the upper and lower bounds is small enough, that is, converges to the preset range threshold.

[0213] It should be noted that the new constraints of the column and constraint generation algorithm iterative algorithm are:

[0214]

[0215] Among them, P i D is the design load at node i, is the actual load at node i. is the actual load at node i in the second stage, i.e. the worst scenario. η is the variable added in the iterative process of the column and constraint generation algorithm.

[0216] S6. Generate a target network reconstruction strategy for the distribution network according to the target solution; wherein the target network reconstruction strategy records the target switching state of the configuration switches of each transmission line in the distribution network.

[0217] This embodiment provides a method for network reconstruction of a distribution network taking into account typhoon disasters. The line failure probability of each transmission line in the distribution network is predicted according to typhoon data and the geographical location of each component in the distribution network, and then several fault scenarios of the distribution network are generated according to the line failure probability, so as to achieve a quantitative assessment of the operation risk of the distribution network under typhoon disasters. Then, according to the network topology model of the distribution network and the set of fault scenarios, a two-stage network reconstruction model with the goal of minimizing the network reconstruction cost and the goal of minimizing the load loss of the distribution network is constructed, and solved to obtain a target network reconstruction strategy formed by the target solution of each decision variable of the two-stage network reconstruction model. After the distribution network is reconstructed according to the target network reconstruction strategy, that is, after the topology of the distribution network is adjusted according to the target switching state of the configuration switches of each transmission line, the impact of the disaster on the distribution network can be minimized while ensuring that the network reconstruction cost required is the lowest. Therefore, the present invention can provide a network reconstruction strategy for the distribution network that takes into account both economy and feasibility in the specific scenario of typhoon disasters.

[0218] See also Figure 2 , is a schematic diagram of a structure of a distribution network reconstruction device taking into account typhoon disasters provided by an embodiment of the present invention, comprising:

[0219] A data acquisition module is used to obtain typhoon data, a network topology model of the distribution network, and the geographical locations of transmission lines and towers in the distribution network;

[0220] A data calculation module, used to calculate the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line;

[0221] A scenario construction module, used to construct a set of fault scenarios of the distribution network according to the line failure probability; wherein the set of fault scenarios is composed of the fault scenarios of the distribution network at each moment; the fault scenarios define a number of fault lines of the distribution network that are affected by the typhoon and fail at the corresponding moment;

[0222] A model construction module, for constructing a two-stage network reconstruction model with the goal of minimizing the network reconstruction cost and the goal of minimizing the load loss of the distribution network according to the network topology model and the set of fault scenarios; wherein the decision variables of the two-stage network reconstruction model include: a first variable representing the connection status of each of the transmission lines, a second variable representing the continuous change of the load of each node in the distribution network, and a third variable used to represent the impact of the typhoon on the distribution network;

[0223] A model solving module, used to solve the two-stage network reconstruction model to obtain a target solution for each decision variable of the two-stage network reconstruction model;

[0224] A strategy generation module is used to generate a target network reconstruction strategy for the distribution network according to the target solution; wherein the target network reconstruction strategy records the target switching state of the configuration switches of each transmission line in the distribution network.

[0225] Furthermore, the typhoon data includes: the typhoon's central movement track, the typhoon's gradient wind speed, and rainfall;

[0226] The data calculation module calculates the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line, including:

[0227] Determine, at each moment, a first distance between the tower and the typhoon center, and a second distance between the transmission line and the typhoon center, according to the center movement trajectory, the geographical location of the transmission line, and the geographical location of the tower;

[0228] Calculate the first typhoon impact degree borne by the tower at each moment and the second typhoon impact degree borne by each transmission line at each moment according to the first distance, the second distance, the gradient wind speed, and the rainfall;

[0229] Calculating the tower failure probability of each of the towers at each moment according to the impact degree of the first typhoon;

[0230] Dividing each of the transmission lines into a plurality of sections, and calculating the section failure probability of each section at each moment according to the impact degree of the second typhoon;

[0231] According to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line, the line failure probability of each transmission line at each moment is calculated.

[0232] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0233] Those skilled in the art can clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0234] Another preferred embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a distribution network reconstruction method taking into account typhoon disasters as described in any one of the above embodiments.

[0235] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0236] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0237] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0238] Another preferred embodiment of the present invention provides a storage medium, the storage medium is a computer-readable storage medium, the computer program is stored in the computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0239] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for reconfiguring a distribution network taking into account typhoon disasters, characterized in that: include: Obtain typhoon data, network topology model of distribution network, and geographical locations of transmission lines and towers in distribution network; Calculating the line failure probability of each of the transmission lines according to the typhoon data, the geographical location of the transmission lines, and the geographical locations of a number of towers connected to each transmission line; According to the line failure probability, a set of fault scenarios of the distribution network is constructed; wherein the set of fault scenarios is composed of the fault scenarios of the distribution network at each moment; the fault scenarios define a number of fault lines of the distribution network that are affected by the typhoon and fail at a corresponding moment; According to the network topology model and the set of fault scenarios, a two-stage network reconstruction model is constructed with the goal of minimizing the network reconstruction cost and the goal of minimizing the load loss of the distribution network; wherein the decision variables of the two-stage network reconstruction model include: a first variable representing the connection status of each of the transmission lines, a second variable representing the continuous change of the load of each node in the distribution network, and a third variable used to represent the impact of the typhoon on the distribution network; Solving the two-stage network reconstruction model to obtain target solutions for each decision variable of the two-stage network reconstruction model; A target network reconstruction strategy for the distribution network is generated according to the target solution; wherein the target network reconstruction strategy records the target switching state of the configuration switches of each transmission line in the distribution network.

2. A method for reconfiguring a distribution network taking into account typhoon disasters as claimed in claim 1, characterized in that: The typhoon data includes: the typhoon's central movement track, the typhoon's gradient wind speed, and rainfall; The calculating the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line includes: Determine, at each moment, a first distance between the tower and the typhoon center, and a second distance between the transmission line and the typhoon center, according to the center movement trajectory, the geographical location of the transmission line, and the geographical location of the tower; Calculating the first typhoon impact degree borne by the tower at each moment and the second typhoon impact degree borne by each transmission line at each moment according to the first distance, the second distance, the gradient wind speed, and the rainfall; Calculating the tower failure probability of each of the towers at each moment according to the impact degree of the first typhoon; Dividing each of the transmission lines into a plurality of sections, and calculating the section failure probability of each section at each moment according to the impact degree of the second typhoon; According to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line, the line failure probability of each transmission line at each moment is calculated.

3. A method for reconfiguring a distribution network taking into account typhoon disasters as claimed in claim 2, characterized in that: The calculating of the line failure probability of each transmission line at each moment according to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line comprises: The failure probability of the transmission line is calculated according to the following formula: Among them, Prob l (t) is the failure probability of the transmission line l at time t, n tw is the set of towers connected to the transmission line l, Prob tw,i (t) is the failure probability of the ith tower in the tower set at time t, n sg is the set of segments divided by the transmission line l, λ sg,j (t) is the failure probability of the jth segment in the segment set at time t.

4. A method for reconfiguring a distribution network taking into account typhoon disasters as claimed in claim 3, characterized in that: The two-stage network reconstruction model is: in, is the first objective function with the goal of minimizing the network reconstruction cost, is a second objective function with the goal of minimizing the load loss of the distribution network, x is the first variable, is a preset first constraint condition set of the first variable, L is a transmission line set of the distribution network, l is the lth transmission line in the transmission line set, C connect () is the cost required when the switching state of the configuration switch of the transmission line l is connected, C dis () is the cost required when the switching state of the configuration switch of the transmission line l is disconnected, α l is a binary variable representing the switching state of the configuration switch of the transmission line l, A l is a binary variable representing the actual operating state of the transmission line 1, y is the second variable, is a preset second constraint set of the second variable, u is the third variable, is a third constraint condition set of the third variable generated according to the fault scenario set, N is a node set of the distribution network, P i D is the design load at node i, is the actual load at node i.

5. A method for reconfiguring a distribution network taking into account typhoon disasters as claimed in claim 4, characterized in that: The first set of constraint conditions includes: a network radial constraint for constraining a transmission line topology, a transmission line number constraint for constraining transmission lines that can change operating states in the distribution network, a line maximum power flow constraint, a node power balance constraint for constraining power load balance of the distribution network, a distributed power source power constraint, an energy storage power constraint, and an active power constraint; The second constraint condition set includes: the node power balance constraint, the distributed power source power constraint, the energy storage power constraint, the active power constraint, and the line maximum power flow constraint; The third constraint condition set includes: a fault probability threshold constraint, a maximum number of faulty lines constraint, a line fault state transfer constraint, and a faulty line recovery constraint.

6. A method for reconfiguring a distribution network taking into account typhoon disasters as claimed in claim 5, characterized in that: The step of solving the two-stage network reconstruction model to obtain a target solution for each decision variable of the two-stage network reconstruction model includes: Linearizing the two-stage network reconstruction model to generate a main problem generated by the first objective function and a sub-problem generated by the second objective function; Determine, from the set of fault scenarios, an initial fault scenario that has the greatest impact on the distribution network; According to the initial fault scenario, the main problem, and the sub-problems, an iterative solution operation is performed on the two-stage network reconstruction model until a target solution of each decision variable of the two-stage network reconstruction model is generated; The iterative solution operation includes: Obtain a scenario to be identified; wherein, initially, the scenario to be identified is an initial fault scenario, the upper bound of the solution set of the two-stage network reconstruction model is positive infinity, the lower bound of the solution set is negative infinity, the set of identified fault scenarios is an empty set, and the set of newly added constraints is empty; Under the first set of constraints and the newly added set of constraints, the main problem is solved according to the scenario to be identified, a first solution set of the first variable and the newly added constraints are generated, and the lower bound of the solution set is updated according to the first solution set and the newly added constraints; wherein the first solution set is a network reconstruction strategy for the distribution network to respond to the scenario to be identified with the minimum network reconstruction cost; Under the second set of constraints and the third set of constraints, the subproblem is solved according to the first solution set to generate a second solution set of the second variable and a third solution set of the third variable; wherein the second solution set is the load loss caused by the distribution network under the network reconstruction strategy corresponding to the first solution set, and the third solution set is the worst fault scenario evolved by the distribution network after applying the network reconstruction strategy corresponding to the first solution set, and the worst fault scenario is not in the identified scenario set; updating the upper bound of the solution set according to the second solution set and the third solution set; Determine whether the upper bound of the solution set and the lower bound of the solution set converge to a preset range threshold; If not, adding the scene to be identified to the set of identified scenes, adding the newly added constraint to the set of newly added constraints, and using the third solution set as the scene to be identified required for the next round of iterative solution operation; If so, the first solution set, the second solution set, and the third solution set are used as the target solutions of the first variable, the second variable, and the third variable, respectively.

7. A distribution network reconstruction device taking into account typhoon disasters, characterized in that: include: A data acquisition module is used to obtain typhoon data, a network topology model of the distribution network, and the geographical locations of transmission lines and towers in the distribution network; A data calculation module, used to calculate the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line; A scenario construction module, used to construct a set of fault scenarios of the distribution network according to the line failure probability; wherein the set of fault scenarios is composed of the fault scenarios of the distribution network at each moment; the fault scenarios define a number of fault lines of the distribution network that are affected by the typhoon and fail at the corresponding moment; A model construction module, for constructing a two-stage network reconstruction model with the goal of minimizing the network reconstruction cost and the goal of minimizing the load loss of the distribution network according to the network topology model and the set of fault scenarios; wherein the decision variables of the two-stage network reconstruction model include: a first variable representing the connection status of each of the transmission lines, a second variable representing the continuous change of the load of each node in the distribution network, and a third variable used to represent the impact of the typhoon on the distribution network; A model solving module, used to solve the two-stage network reconstruction model to obtain a target solution for each decision variable of the two-stage network reconstruction model; A strategy generation module is used to generate a target network reconstruction strategy for the distribution network according to the target solution; wherein the target network reconstruction strategy records the target switching state of the configuration switches of each transmission line in the distribution network.

8. A distribution network reconstruction device taking typhoon disasters into consideration as claimed in claim 7, characterized in that: The typhoon data includes: the typhoon's central movement track, the typhoon's gradient wind speed, and rainfall; The data calculation module calculates the line failure probability of each transmission line according to the typhoon data, the geographical location of the transmission line, and the geographical locations of a number of towers connected to each transmission line, including: Determine, at each moment, a first distance between the tower and the typhoon center, and a second distance between the transmission line and the typhoon center, according to the center movement trajectory, the geographical location of the transmission line, and the geographical location of the tower; Calculating the first typhoon impact degree borne by the tower at each moment and the second typhoon impact degree borne by each transmission line at each moment according to the first distance, the second distance, the gradient wind speed, and the rainfall; Calculating the tower failure probability of each of the towers at each moment according to the impact degree of the first typhoon; Dividing each of the transmission lines into a plurality of sections, and calculating the section failure probability of each section at each moment according to the impact degree of the second typhoon; According to the failure probabilities of several sections of each transmission line and the tower failure probability of the tower connected to each transmission line, the line failure probability of each transmission line at each moment is calculated.

9. A terminal device, characterized in that: It comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a distribution network reconstruction method taking into account typhoon disasters as described in any one of claims 1 to 7 is implemented.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a distribution network reconstruction method taking into account typhoon disasters as described in any one of claims 1 to 7.

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