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

Abstract

The invention discloses a power distribution network reconstruction method and device, terminal equipment and a storage medium, and the method comprises the steps: constructing a two-stage robust optimization model as a power distribution network reconstruction model, the target function in the second stage is to minimize the load loss in the worst disaster scene; constructing a first constraint set for the first-stage objective function; constructing a second constraint set for the outer objective function; constructing a third constraint set for the inner-layer objective function; solving the network reconstruction model of the power distribution network to obtain a solving result; and adjusting a switch of a transmission line of the power distribution network according to a solving result. According to the method, the two-stage robust optimization model is constructed, and the minimum transmission line switch switching cost and the minimum load loss in the worst disaster scene are used as the target functions of the first stage and the second stage, so that a network reconstruction scheme with low cost and less loss is provided.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network dispatching and operation, and in particular to a distribution network network reconstruction method, device, terminal equipment and storage medium. Background Art

[0002] Faced with the frequent occurrence of extreme weather events caused by global climate change, especially the serious threat of typhoons to the power grid system, the increased uncertainty has made the stable operation of the power system face unprecedented challenges. Ensuring the smooth operation of the power system is not only related to the national economy and people's livelihood, but also has become an urgent and important issue. In order to ensure that users' electricity needs are met and the impact of extreme weather events is minimized, as an important strategy to enhance the resilience and disaster resistance of the distribution network, the network reconstruction of the distribution network can quickly restore the power supply of critical loads. However, this process is particularly complex. It requires finding a suitable balance between the physical system and the economic market, ensuring the safe and stable operation of the power system, and striving to minimize the disaster losses and the accompanying additional costs. How to formulate a low-cost and low-loss network reconstruction plan is still an unresolved problem. Summary of the invention

[0003] The present invention provides a distribution network reconstruction method, an apparatus, a terminal device and a storage medium to solve the technical problem of how to formulate a network reconstruction plan with low cost and low loss.

[0004] In order to solve the above technical problems, an embodiment of the present invention provides a distribution network reconstruction method, including:

[0005] Taking minimizing the switching cost of transmission line switches as the first-stage objective function and minimizing the load loss under the worst disaster scenario as the second-stage objective function, a two-stage robust optimization model is constructed as a distribution network reconstruction model; wherein the second-stage objective function is a two-layer optimization function, the inner objective function of the second-stage objective function takes minimizing the load loss as the objective function, and the outer objective function of the second-stage objective function takes maximizing the load loss under the disaster scenario as the objective function;

[0006] Constructing a first constraint set for the first stage objective function; wherein the first constraint set includes: network radial constraint, maximum switch number constraint, node power balance constraint, distributed power supply power constraint, energy storage system power constraint, energy storage system power change constraint, load active power constraint, auxiliary variable constraint and iterative algorithm constraint; the auxiliary variable is the active power flow between nodes after the transmission line is disconnected in the disaster scenario;

[0007] Constructing a second constraint set for the outer objective function; wherein the second constraint set includes: a transmission line failure probability constraint, a constraint on the number of transmission lines that fail at the same time, a transmission line state transition constraint under a disaster scenario, and a fault recovery time constraint;

[0008] Constructing a third constraint set for the inner objective function; wherein the third constraint set includes: node power balance constraint, distributed power source power constraint, energy storage system power constraint, load active power constraint and auxiliary variable constraint;

[0009] Solving the distribution network reconstruction model according to the first constraint set, the second constraint set and the third constraint set, and obtaining the target switch state of the transmission line after network reconstruction when the switching cost of the transmission line is minimized and the load loss is minimized under the worst disaster scenario as a solution result;

[0010] According to the solution result, the switch state of the transmission line of the distribution network is adjusted.

[0011] As a preferred solution, the first-stage objective function is to minimize the switching cost of transmission line switches, and the second-stage objective function is to minimize the load loss under the worst disaster scenario, and to construct a two-stage robust optimization model as a distribution network reconstruction model, including:

[0012] Obtaining binary variables of actual operating status of each transmission line in the distribution network under a disaster scenario, a transmission line disconnection cost, a transmission line connection cost, an actual load of each node in the distribution network, and a design load of each node in the distribution network;

[0013] According to the actual operation state binary variable of each transmission line in the distribution network, the transmission line disconnection cost and the transmission line connection cost, constructing a function with the goal of minimizing the transmission line switch switching cost as the first stage objective function;

[0014] According to the actual load and the design load of each node in the distribution network, constructing a function with the goal of minimizing the load loss under the worst disaster scenario as the second stage objective function;

[0015] According to the first-stage objective function and the second-stage objective function, a two-stage robust optimization model is constructed as a distribution network reconstruction model;

[0016] Among them, the expression of the objective function of the first stage is:

[0017]

[0018] In the formula, x represents the decision variable of the objective function in the first stage; represents the first constraint set; l represents a transmission line in the distribution network; L represents the set of all transmission lines in the distribution network; C con represents the transmission line connection cost; C dis represents the transmission line disconnection cost; α l (t) is a binary variable representing the switch state of the transmission line l after the network reconstruction at time t, α l (t) = 1 means that the switch state of the transmission line l remains open after the network reconstruction at time t, α l (t) = 0 means that the switch state of the transmission line l does not remain open after the network reconstruction at time t; A l (t) is a binary variable representing the actual operating status of the transmission line l under the disaster scenario at time t, A l (t) = 1 means that the actual state of the transmission line l in the disaster scenario at time t is open, A l (t) = 0 means that the actual state of the transmission line l in the disaster scenario at time t is closed; η represents the sum of the load losses of each node in the system;

[0019] The expression of the second stage objective function is:

[0020]

[0021] In the formula, u represents the decision variable of the outer objective function; represents the second constraint set; y represents the decision variable of the inner objective function; represents the third constraint set; t represents a certain moment; t n represents the total duration of the distribution network being affected by the disaster; i represents a node in the distribution network; N represents the set of all nodes in the distribution network; P i D represents the design load of node i; represents the actual load of node i at time t;

[0022] The expression of the distribution network reconstruction model is:

[0023]

[0024] As a preferred solution, the expression of the network radial constraint is:

[0025]

[0026] In the formula, t represents a certain time; i represents a certain node in the distribution network; j represents a certain node in the distribution network; N represents the set of all nodes in the distribution network; N(i) represents the set of sub-nodes in the distribution network that may be linked to the node; β ij(t) is a binary variable representing the parent-child relationship between the i-th node and the j-th node in the distribution network at time t, β ij =1 means that the i-th node in the distribution network is the parent node of the j-th node at time t, β ij =0 means that the i-th node in the distribution network is not the parent node of the j-th node at time t; β ji (t) is a binary variable representing the parent-child relationship between the i-th node and the j-th node in the distribution network at time t, β ji =1 means that the jth node in the distribution network is the parent node of the ith node at time t, β ji =0 means that the jth node in the distribution network is not the parent node of the ith node at time t; α l (t) is a binary variable representing the switch state of the transmission line l after the network reconstruction at time t, α l (t) = 1 means that the switch state of the transmission line l remains open after the network reconstruction at time t, α l (t) = 0 indicates that the switch state of the transmission line l does not remain open after the network reconstruction at time t; l indicates a transmission line in the distribution network; L indicates the set of all transmission lines in the distribution network;

[0027] The expression of the maximum number of switches constraint is:

[0028]

[0029] In the formula, A l (t) is a binary variable representing the actual operating status of the transmission line l under the disaster scenario at time t, A l (t) = 1 means that the actual state of the transmission line l in the disaster scenario at time t is open, A l (t) = 0 means that the actual state of the transmission line l in the disaster scenario at time t is closed; SW max Indicates the maximum number of transmission lines that can change their operating status in the network reconstruction strategy;

[0030] The expression of the node power balance constraint is:

[0031]

[0032] In the formula, is the active power flow between node i and node j at time t after considering the disconnection state of the transmission line; represents the actual load of node i at time t; represents the active power of the energy storage system at node i at time t; represents the active power of distributed generation at node i at time t;

[0033] The expression of the distributed generation power constraint is:

[0034]

[0035] In the formula, represents the maximum active power of the distributed generation at node i; N DG Represents the set of nodes connected to distributed generation in the distribution network;

[0036] The expression of the energy storage system power constraint is:

[0037]

[0038] In the formula, represents the maximum charging active power of the energy storage system at node i; represents the maximum discharge active power of the energy storage system at node i; represents the actual capacity of the energy storage system at node i at time t; Indicates the maximum capacity of the energy storage system; N ESS Represents the set of nodes in the distribution network connected to the energy storage system;

[0039] The expression of the energy storage system power variation constraint is:

[0040]

[0041] In the formula, represents the charging active power of the energy storage system at node i at time t; represents the active power of the energy storage system discharged at node i at time t; η chi represents the charging efficiency of the energy storage system at node i; η disi represents the discharge efficiency of the energy storage system at node i;

[0042] The expression of the load active power constraint is:

[0043]

[0044] Where P i D represents the design load of node i;

[0045] The expression of the auxiliary variable constraint is:

[0046]

[0047] In the formula, p ij (t) is the active power flow between nodes i and j at time t without considering the disconnection of the transmission line, if and only if α l (t)=1 and u l(t) = 1 is a binary variable representing the switch state of transmission line l under the worst disaster scenario at time t, u l (t) = 1 means that the switch state of the transmission line l is open in the worst disaster scenario at time t, u l (t) = 0 means that the switch state of the transmission line l is closed in the worst disaster scenario at time t; max Indicates the maximum active power that the transmission line l can carry;

[0048] The expression of the iterative algorithm constraint is:

[0049]

[0050] In the formula, represents the actual load of node i under the worst disaster scenario at time t; represents the newly added variables in the iterative process of the algorithm using columns and constraints.

[0051] As a preferred solution, the expression of the transmission line failure probability constraint is:

[0052]

[0053] In the formula, t represents a certain moment; Prob l (t) represents the time-varying fault probability of transmission line l at time t; ∏ is the preset time-varying fault probability threshold; is a binary variable representing the fault condition of transmission line l at time t, It means that the transmission line l is damaged and fails at time t. It means that the transmission line l is damaged but not faulty at time t;

[0054] The expression for the constraint on the number of transmission lines failing at the same time is:

[0055]

[0056] In the formula, I l (t) is a binary variable representing the disaster availability of transmission line l under the disaster scenario generated at time t, I l I (t) = 1 means that the transmission line l is damaged but still usable in the disaster scenario generated at time t. l (t) = 1 means that the transmission line l is damaged and unavailable in the disaster scenario generated at time t; l represents a transmission line in the distribution network; L represents the set of all transmission lines in the distribution network; Num L Indicates the total number of transmission lines in the distribution network; OFF max It indicates the maximum total number of transmission lines that are allowed to fail due to disasters at the same time;

[0057] The expression of the transmission line state transition constraint under the disaster scenario is:

[0058]

[0059] In the formula, I l (t-1) is a binary variable representing the disaster availability of transmission line l under the disaster scenario generated at time t-1, I l (t-1) = 1 means that the transmission line l is damaged but still usable in the disaster scenario generated at time t-1. l (t-1)=1 means that the transmission line l is damaged and unavailable in the disaster scenario generated at time t-1; is a binary variable representing the disappearance of the impact of the disaster scenario on the affected transmission line l at time t, It means that the damaged transmission line l before time t-RT is restored at time t. It means that there is no fault recovery process in the transmission line l at time t;

[0060] The expression of the fault recovery time constraint is:

[0061]

[0062] In the formula, is a binary variable representing the disappearance of the impact of the disaster scenario on the affected transmission line l at time t+RT, It means that the damaged transmission line l before time t is restored at time t+RT. It indicates that the transmission line l has no fault recovery process at time t+RT; RT represents the preset recovery time.

[0063] As a preferred solution, the step of constructing a second constraint set for the outer objective function includes:

[0064] For each transmission line in the distribution network, obtain the tower wind speed and the tower precipitation at each tower on the transmission line; divide the transmission line into a plurality of sections, and obtain the section wind speed and the section precipitation at each section;

[0065] Calculate the equivalent wind speed at each tower based on the wind speed at each tower and the precipitation at the tower;

[0066] According to the equivalent wind speed at each tower, calculate the tower failure probability of each tower in the disaster scenario;

[0067] According to the wind speed and precipitation at each segment, the segment failure probability of each segment under the disaster scenario is calculated;

[0068] Calculating the transmission line failure probability of the transmission line according to the tower failure probability of all towers and the segment failure probability of all segments on the transmission line;

[0069] constructing the second constraint set according to the transmission line failure probability;

[0070] Wherein, the calculation formula of the equivalent wind speed is:

[0071]

[0072] Where V * (r tw (t),t,h d ) represents the equivalent wind speed at the tower; t represents the time when the disaster lasts, and t = 0 when the disaster occurs; r tw (t) represents the distance from the tower to the typhoon center; h d Indicates the height of the basic wind speed in the disaster area; V(r tw (t),t,h d ) represents the wind speed at the tower; RA(r tw (t), t) represents the precipitation at the tower; v0, v1, v2, v3, v4 and v5 are all preset constants;

[0073] The calculation formula of the tower failure probability is:

[0074]

[0075] Where Prob tw,i (t) represents the tower failure probability of the i-th tower on the transmission line at time t; x tw,i (t) is the auxiliary substitution quantity, defined as the equivalent wind speed The natural logarithm of μ tw,i Represents x tw,i The average value of (t); σ tw,i Represents x tw,i (t) standard deviation;

[0076] The calculation formula of the segment failure probability is:

[0077]

[0078] In the formula, λ sg,j (t) represents the segment failure probability of the jth segment on the transmission line at time t; L sg Indicates the length of the segment; V(r sg (t),t,h d ) represents the wind speed at the segment; RA(r sg (t), t) represents the precipitation at the segment; V sgdIndicates the design wind speed of the segment; RA sgd Indicates the design precipitation of the segment; a sg 、b sg 、c sg and d sg All are preset constants;

[0079] The calculation formula of the transmission line failure probability is:

[0080]

[0081] Where Prob l (t) represents the failure probability of transmission line l at time t; n tw Represents the total number of towers on the transmission line; n sg Indicates the total number of segments on the transmission line.

[0082] As a preferred solution, the expression of the node power balance constraint is:

[0083]

[0084] In the formula, t represents a certain moment; i represents a certain node in the distribution network; j represents a certain node in the distribution network; N represents the set of all nodes in the distribution network; N(i) represents the set of sub-nodes in the distribution network that may be linked to the node; is the active power flow between node i and node j at time t after considering the disconnection state of the transmission line; represents the actual load of node i at time t; represents the active power of the energy storage system at node i at time t; represents the active power of distributed generation at node i at time t;

[0085] The expression of the distributed generation power constraint is:

[0086]

[0087] In the formula, represents the maximum active power of the distributed generation at node i; N DG Represents the set of nodes connected to distributed generation in the distribution network;

[0088] The expression of the energy storage system power constraint is:

[0089]

[0090] In the formula, represents the maximum charging active power of the energy storage system at node i; represents the maximum discharge active power of the energy storage system at node i; represents the actual capacity of the energy storage system at node i at time t; Indicates the maximum capacity of the energy storage system; N ESS Represents the set of nodes in the distribution network connected to the energy storage system;

[0091] The expression of the load active power constraint is:

[0092]

[0093] Where P i D represents the design load of node i;

[0094] The expression of the auxiliary variable constraint is:

[0095]

[0096] In the formula, p ij (t) is the active power flow between nodes i and j at time t without considering the disconnection of the transmission line, if and only if α l (t)=1 and u l (t) = 1 u l (t) is a binary variable representing the switch state of transmission line l under the worst disaster scenario at time t, u l (t) = 1 means that the switch state of the transmission line l is open in the worst disaster scenario at time t, u l (t) = 0 means that the switch state of the transmission line l is closed in the worst disaster scenario at time t; max Indicates the maximum active power that the transmission line l can carry.

[0097] As a preferred solution, adjusting the switch state of the transmission line of the distribution network according to the solution result includes:

[0098] Combining the solution results with the actual operating status of the transmission line at the initial moment in the disaster scenario, generating a switch adjustment strategy for each transmission line;

[0099] According to the switch adjustment strategy, the switch state of each transmission line is adjusted.

[0100] Based on the above embodiment, another embodiment of the present invention provides a distribution network reconstruction device, including: an objective function construction module, a constraint set construction module, a solution module and an adjustment module;

[0101] The objective function construction module is used to construct a two-stage robust optimization model as a distribution network reconstruction model by minimizing the switching cost of transmission line switches as the first-stage objective function and minimizing the load loss under the worst disaster scenario as the second-stage objective function; wherein the second-stage objective function is a two-layer optimization function, the inner layer objective function of the second-stage objective function is to minimize the load loss as the objective function, and the outer layer objective function of the second-stage objective function is to maximize the load loss under the disaster scenario as the objective function;

[0102] The constraint set construction module is used to construct a first constraint set for the first stage objective function; wherein the first constraint set includes: network radial constraints, maximum switch number constraints, node power balance constraints, distributed power supply power constraints, energy storage system power constraints, energy storage system power change constraints, load active power constraints, auxiliary variable constraints and iterative algorithm constraints; the auxiliary variable is the active power flow between nodes after the transmission line is disconnected in the disaster scenario; construct a second constraint set for the outer layer objective function; wherein the second constraint set includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transfer constraints in disaster scenarios and fault recovery time constraints; construct a third constraint set for the inner layer objective function; wherein the third constraint set includes: node power balance constraints, distributed power supply power constraints, energy storage system power constraints, load active power constraints and auxiliary variable constraints;

[0103] The solving module is used to solve the distribution network reconstruction model according to the first constraint set, the second constraint set and the third constraint set to obtain a solution result;

[0104] The regulating module is used to regulate switches of the transmission lines of the distribution network according to the solution result.

[0105] Based on the above embodiments, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the distribution network reconstruction method described in the above invention embodiments is implemented.

[0106] Based on the above embodiments, 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 the distribution network reconstruction method described in the above invention embodiment.

[0107] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0108] The present invention constructs a two-stage robust optimization model as a distribution network reconstruction model, wherein the first-stage objective function is to minimize the switching cost of transmission line switches, and the second-stage objective function is to minimize the load loss under the worst disaster scenario; a first constraint set is constructed for the first-stage objective function; wherein the first constraint set includes: network radial constraints, maximum switch quantity constraints, node power balance constraints, distributed power supply power constraints, energy storage system power constraints, energy storage system power change constraints, load active power constraints, auxiliary variable constraints and iterative algorithm constraints; the auxiliary variables are active power flow between nodes after the transmission line is disconnected in the disaster scenario; Construct a second constraint set for the outer objective function; wherein the second constraint set includes: transmission line failure probability constraint, simultaneous fault transmission line number constraint, transmission line state transfer constraint under disaster scenario and fault recovery time constraint; construct a third constraint set for the inner objective function; wherein the third constraint set includes: node power balance constraint, distributed power source power constraint, energy storage system power constraint, load active power constraint and auxiliary variable constraint; solve the distribution network network reconstruction model according to the first constraint set, the second constraint set and the third constraint set to obtain a solution result; according to the solution result, adjust the switches of the transmission lines of the distribution network. The present invention constructs a two-stage robust optimization model, and takes minimizing the switching cost of transmission line switches and minimizing the objective function and minimizing the load loss under the worst disaster scenario as the objective functions of the first stage and the second stage, respectively, to provide a low-cost and low-loss network reconstruction solution that can minimize disaster losses and the accompanying additional costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0109] Figure 1 It is a flow chart of a distribution network reconstruction method provided by an embodiment of the present invention;

[0110] Figure 2 It is a structural schematic diagram of a distribution network reconstruction device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0111] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0112] Embodiment 1

[0113] Please refer to Figure 1 , is a flow chart of a distribution network reconstruction method provided by an embodiment of the present invention, comprising:

[0114] S1. Taking minimizing the switching cost of transmission line switches as the first-stage objective function and minimizing the load loss under the worst disaster scenario as the second-stage objective function, a two-stage robust optimization model is constructed as a distribution network reconstruction model; wherein, the second-stage objective function is a two-layer optimization function, the inner objective function of the second-stage objective function is to minimize the load loss as the objective function, and the outer objective function of the second-stage objective function is to maximize the load loss under the disaster scenario as the objective function.

[0115] In step S1, the present invention constructs a two-stage robust optimization model, the objective function of which can be divided into a first stage, a second stage outer layer, and a second stage inner layer, each having a corresponding objective function and constraint conditions.

[0116] In a preferred embodiment, the first-stage objective function is to minimize the switching cost of transmission line switches, and the second-stage objective function is to minimize the load loss under the worst disaster scenario, and a two-stage robust optimization model is constructed as a distribution network reconstruction model, including:

[0117] Obtaining binary variables of actual operating status of each transmission line in the distribution network under a disaster scenario, a transmission line disconnection cost, a transmission line connection cost, an actual load of each node in the distribution network, and a design load of each node in the distribution network;

[0118] According to the actual operation state binary variable of each transmission line in the distribution network, the transmission line disconnection cost and the transmission line connection cost, constructing a function with the goal of minimizing the transmission line switch switching cost as the first stage objective function;

[0119] According to the actual load and the design load of each node in the distribution network, constructing a function with the goal of minimizing the load loss under the worst disaster scenario as the second stage objective function;

[0120] According to the first-stage objective function and the second-stage objective function, a two-stage robust optimization model is constructed as a distribution network reconstruction model;

[0121] Among them, the expression of the objective function of the first stage is:

[0122]

[0123] In the formula, x represents the decision variable of the objective function in the first stage; represents the first constraint set; l represents a transmission line in the distribution network; L represents the set of all transmission lines in the distribution network; C con represents the transmission line connection cost; C disrepresents the transmission line disconnection cost; α l (t) is a binary variable representing the switch state of the transmission line l after the network reconstruction at time t, α l (t) = 1 means that the switch state of the transmission line l remains open after the network reconstruction at time t, α l (t) = 0 means that the switch state of the transmission line l does not remain open after the network reconstruction at time t; A l (t) is a binary variable representing the actual operating status of the transmission line l under the disaster scenario at time t, A l (t) = 1 means that the actual state of the transmission line l in the disaster scenario at time t is open, A l (t) = 0 means that the actual state of the transmission line l in the disaster scenario at time t is closed; η represents the sum of the load losses of each node in the system;

[0124] The expression of the second stage objective function is:

[0125]

[0126] In the formula, u represents the decision variable of the outer objective function; represents the second constraint set; y represents the decision variable of the inner objective function; represents the third constraint set; t represents a certain moment; t n represents the total duration of the distribution network being affected by the disaster; i represents a node in the distribution network; N represents the set of all nodes in the distribution network; P i D represents the design load of node i; represents the actual load of node i at time t;

[0127] The expression of the distribution network reconstruction model is:

[0128]

[0129] In this embodiment, a distribution network reconstruction model considering the uncertainty of disaster situations is established. The present invention introduces binary variables and α l (t) and A l (t). α l It is a binary variable representing the switch status of each line l after network reconstruction. If line l remains open after reconstruction, it takes 1, otherwise it takes 0. l It is a binary variable that describes the actual operating status of each line l under the influence of typhoon disasters. If the operating status of line l after the disaster is open, it takes 1, otherwise it takes 0.

[0130] S2. Construct a first constraint set for the objective function of the first stage; wherein the first constraint set includes: network radial constraint, maximum number of switches constraint, node power balance constraint, distributed power supply power constraint, energy storage system power constraint, energy storage system power change constraint, load active power constraint, auxiliary variable constraint and iterative algorithm constraint; the auxiliary variable is the active power flow between nodes after the transmission line is disconnected in a disaster scenario.

[0131] In a preferred embodiment, the expression of the network radial constraint is:

[0132]

[0133] In the formula, t represents a certain time; i represents a certain node in the distribution network; j represents a certain node in the distribution network; N represents the set of all nodes in the distribution network; N(i) represents the set of sub-nodes in the distribution network that may be linked to the node; β ij (t) is a binary variable representing the parent-child relationship between the i-th node and the j-th node in the distribution network at time t, β ij =1 means that the i-th node in the distribution network is the parent node of the j-th node at time t, β ij =0 means that the i-th node in the distribution network is not the parent node of the j-th node at time t; β ji (t) is a binary variable representing the parent-child relationship between the i-th node and the j-th node in the distribution network at time t, β ji =1 means that the jth node in the distribution network is the parent node of the ith node at time t, β ji =0 means that the jth node in the distribution network is not the parent node of the ith node at time t; α l (t) is a binary variable representing the switch state of the transmission line l after the network reconstruction at time t, α l (t) = 1 means that the switch state of the transmission line l remains open after the network reconstruction at time t, α l (t) = 0 indicates that the switch state of the transmission line l does not remain open after the network reconstruction at time t; l indicates a transmission line in the distribution network; L indicates the set of all transmission lines in the distribution network;

[0134] The expression of the maximum number of switches constraint is:

[0135]

[0136] In the formula, A l (t) is a binary variable representing the actual operating status of the transmission line l under the disaster scenario at time t, A l (t) = 1 means that the actual state of the transmission line l in the disaster scenario at time t is open, A l(t) = 0 means that the actual state of the transmission line l in the disaster scenario at time t is closed; SW max Indicates the maximum number of transmission lines that can change their operating status in the network reconstruction strategy;

[0137] The expression of the node power balance constraint is:

[0138]

[0139] In the formula, is the active power flow between node i and node j at time t after considering the disconnection state of the transmission line; represents the actual load of node i at time t; represents the active power of the energy storage system at node i at time t; represents the active power of distributed generation at node i at time t;

[0140] The expression of the distributed generation power constraint is:

[0141]

[0142] In the formula, represents the maximum active power of the distributed generation at node i; N DG Represents the set of nodes connected to distributed generation in the distribution network;

[0143] The expression of the energy storage system power constraint is:

[0144]

[0145] In the formula, represents the maximum charging active power of the energy storage system at node i; represents the maximum discharge active power of the energy storage system at node i; represents the actual capacity of the energy storage system at node i at time t; Indicates the maximum capacity of the energy storage system; N ESS Represents the set of nodes in the distribution network connected to the energy storage system;

[0146] The expression of the energy storage system power variation constraint is:

[0147]

[0148] In the formula, represents the charging active power of the energy storage system at node i at time t; represents the active power of the energy storage system discharged at node i at time t; η chi represents the charging efficiency of the energy storage system at node i; η disirepresents the discharge efficiency of the energy storage system at node i;

[0149] The expression of the load active power constraint is:

[0150]

[0151] Where P i D represents the design load of node i;

[0152] The expression of the auxiliary variable constraint is:

[0153]

[0154] In the formula, p ij (t) is the active power flow between nodes i and j at time t without considering the disconnection of the transmission line, if and only if α l (t)=1 and u l (t) = 1 is a binary variable representing the switch state of transmission line l under the worst disaster scenario at time t, u l (t) = 1 means that the switch state of the transmission line l is open in the worst disaster scenario at time t, u l (t) = 0 means that the switch state of the transmission line l is closed in the worst disaster scenario at time t; max Indicates the maximum active power that the transmission line l can carry;

[0155] The expression of the iterative algorithm constraint is:

[0156]

[0157] In the formula, represents the actual load of node i under the worst disaster scenario at time t; represents the newly added variables in the iterative process of the algorithm using columns and constraints.

[0158] In this embodiment, when constructing the network radial constraint, the present invention defines the dimension as the total number of distribution network nodes Num N The square matrix β, where the element in the i-th row and j-th column is a binary variable β ij , takes 1 if and only if node j is the parent node of node i, indicating that the transmission line connecting node j to node i exists and is connected, otherwise it takes 0,

[0159]

[0160] By auxiliary quantity β ij We can define a binary variable α l (If the line remains open after reconstruction, it takes 1, otherwise it takes 0):

[0161]

[0162] S3. Construct a second constraint set for the outer objective function; wherein the second constraint set includes: transmission line failure probability constraint, simultaneous failure transmission line number constraint, transmission line state transfer constraint under disaster scenario and failure recovery time constraint.

[0163] It should be noted that the outer variable to be decided in the second stage is u. The set of constraints that need to be satisfied is the uncertainty set U generated by probability.

[0164] In a preferred embodiment, the expression of the transmission line failure probability constraint is:

[0165]

[0166] In the formula, t represents a certain moment; Prob l (t) represents the time-varying fault probability of transmission line l at time t; ∏ is the preset time-varying fault probability threshold; is a binary variable representing the fault condition of transmission line l at time t, It means that the transmission line l is damaged and fails at time t. It means that the transmission line l is damaged but not faulty at time t;

[0167] The expression for the constraint on the number of transmission lines failing at the same time is:

[0168]

[0169] In the formula, I l (t) is a binary variable representing the disaster availability of transmission line l under the disaster scenario generated at time t, I l I (t) = 1 means that the transmission line l is damaged but still usable in the disaster scenario generated at time t. l (t) = 1 means that the transmission line l is damaged and unavailable in the disaster scenario generated at time t; l represents a transmission line in the distribution network; L represents the set of all transmission lines in the distribution network; Num L Indicates the total number of transmission lines in the distribution network; OFF max It indicates the maximum total number of transmission lines that are allowed to fail due to disasters at the same time;

[0170] The expression of the transmission line state transition constraint under the disaster scenario is:

[0171]

[0172] In the formula, I l(t-1) is a binary variable representing the disaster availability of transmission line l under the disaster scenario generated at time t-1, I l (t-1) = 1 means that the transmission line l is damaged but still usable in the disaster scenario generated at time t-1. l (t-1)=1 means that the transmission line l is damaged and unavailable in the disaster scenario generated at time t-1; is a binary variable representing the disappearance of the impact of the disaster scenario on the affected transmission line l at time t, It means that the damaged transmission line l before time t-RT is restored at time t. It means that there is no fault recovery process in the transmission line l at time t;

[0173] The expression of the fault recovery time constraint is:

[0174]

[0175] In the formula, is a binary variable representing the disappearance of the impact of the disaster scenario on the affected transmission line l at time t+RT, It means that the damaged transmission line l before time t is restored at time t+RT. It indicates that the transmission line l has no fault recovery process at time t+RT; RT represents the preset recovery time.

[0176] In this example, the binary variable I l (t) and Auxiliary variables introduced by the present invention to describe the disaster situation:

[0177] (1) The binary variable K represents the recovery of the typhoon fault on the line at time t l (t), if line l is restored at time t after failure, then K l (t) = 1, otherwise 0;

[0178] (2) A binary variable I representing the availability of the affected line under the disaster scenario generated at time t l (t), if line l is available in the worst disaster scenario, then I l (t) = 1, otherwise 0;

[0179] (3) A binary variable X representing the fault of the affected line l (t), if line l fails, then X l (t)=1, otherwise it is 0.

[0180] X l (t) satisfies the probability of failure of transmission line l at time t Prob l(t) is the Bernoulli distribution, that is:

[0181] X l (t)~B(1,Prob l (t));

[0183] The above variables need to satisfy the following constraints:

[0184] By setting the probability threshold Π, it is determined whether the transmission line fails due to the typhoon disaster:

[0185]

[0186] The maximum total number of transmission lines that are affected and fail at the same time:

[0187]

[0188] Where L is the collection of all lines in the distribution network, and l is a line in the distribution network. 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.

[0189] The state transition relationship of the line can be expressed as follows:

[0190]

[0191] The damaged transmission line will automatically recover after a certain period of time RT:

[0192]

[0193] It should be noted that if a line fails due to a typhoon disaster at time t, the line will be restored at time t+RT. However, if the failure probability of the line at time t+RT is still greater than the set threshold, the line will immediately enter a new round of failures at time t+RT while recovering from the failure at time t. The new round of failures may not be restored until time t+2RT.

[0194] The present invention quantitatively evaluates the uncertain operation risk, establishes the relationship between the disaster situation and the probability of operation failure, and realizes the quantitative evaluation of the operation risk of the disaster-affected distribution network. The present invention models the operation risk of the distribution network under typhoon disasters as a Bernoulli distribution with time-varying parameters, integrates the line failure probability, introduces the disaster failure and recovery into a robust uncertainty set with opportunity constraints, and establishes a distribution network reconstruction model that takes into account the uncertainty of the disaster situation in the subsequent process.

[0195] In a preferred embodiment, constructing a second constraint set for the outer objective function includes:

[0196] For each transmission line in the distribution network, obtain the tower wind speed and the tower precipitation at each tower on the transmission line; divide the transmission line into a plurality of sections, and obtain the section wind speed and the section precipitation at each section;

[0197] Calculate the equivalent wind speed at each tower based on the wind speed at each tower and the precipitation at the tower;

[0198] According to the equivalent wind speed at each tower, calculate the tower failure probability of each tower in the disaster scenario;

[0199] According to the wind speed and precipitation at each segment, the segment failure probability of each segment under the disaster scenario is calculated;

[0200] Calculating the transmission line failure probability of the transmission line according to the tower failure probability of all towers and the segment failure probability of all segments on the transmission line;

[0201] constructing the second constraint set according to the transmission line failure probability;

[0202] Wherein, the calculation formula of the equivalent wind speed is:

[0203]

[0204] Where V * (r tw (t),t,h d ) represents the equivalent wind speed at the tower; t represents the time when the disaster lasts, and t = 0 when the disaster occurs; r tw (t) represents the distance from the tower to the typhoon center; h d Indicates the height of the basic wind speed in the disaster area; V(r tw (t),t,h d ) represents the wind speed at the tower; RA(r tw (t), t) represents the precipitation at the tower; v0, v1, v2, v3, v4 and v5 are all preset constants;

[0205] The calculation formula of the tower failure probability is:

[0206]

[0207] Where Prob tw,i (t) represents the tower failure probability of the i-th tower on the transmission line at time t; x tw,i (t) is the auxiliary substitution quantity, defined as the equivalent wind speed V t * w (r tw(t),t,h d )’s natural logarithm; μ tw,i Represents x tw,i The average value of (t); σ tw,i Represents x tw,i (t) standard deviation;

[0208] The calculation formula of the segment failure probability is:

[0209]

[0210] In the formula, λ sg,j (t) represents the segment failure probability of the jth segment on the transmission line at time t; L sg Indicates the length of the segment; V(r sg (t),t,h d ) represents the wind speed at the segment; RA(r sg (t), t) represents the precipitation at the segment; V sgd Indicates the design wind speed of the segment; RA sgd Indicates the design precipitation of the segment; a sg 、b sg 、c sg and d sg All are preset constants;

[0211] The calculation formula of the transmission line failure probability is:

[0212]

[0213] Where Prob l (t) represents the failure probability of transmission line l at time t; n tw Represents the total number of towers on the transmission line; n sg Indicates the total number of segments on the transmission line.

[0214] In this embodiment, when constructing the second constraint set, a physical model of the disaster event is first constructed, including data such as the movement trajectory and direction of the typhoon disaster.

[0215] It should be noted that v0, v1, v2, v3, v4 and v5 are all obtained by fitting historical data. In this embodiment, v0 = 1.4411, v1 = 0.009376, v2 = 0.7087, v3 = 0.004484, v4 = 1.2486, v5 - 0.1921. The transmission line is divided into several 50m long sections so that each section is in the same terrain and has the same typhoon wind speed and precipitation.

[0216] S4. Construct a third constraint set for the inner objective function; wherein the third constraint set includes: node power balance constraints, distributed power supply power constraints, energy storage system power constraints, load active power constraints and auxiliary variable constraints.

[0217] In a preferred embodiment, the expression of the node power balance constraint is:

[0218]

[0219] In the formula, t represents a certain moment; i represents a certain node in the distribution network; j represents a certain node in the distribution network; N represents the set of all nodes in the distribution network; N(i) represents the set of sub-nodes in the distribution network that may be linked to the node; is the active power flow between node i and node j at time t after considering the disconnection state of the transmission line; represents the actual load of node i at time t; represents the active power of the energy storage system at node i at time t; represents the active power of distributed generation at node i at time t;

[0220] The expression of the distributed generation power constraint is:

[0221]

[0222] In the formula, represents the maximum active power of the distributed generation at node i; N DG Represents the set of nodes connected to distributed generation in the distribution network;

[0223] The expression of the energy storage system power constraint is:

[0224]

[0225] In the formula, represents the maximum charging active power of the energy storage system at node i; represents the maximum discharge active power of the energy storage system at node i; represents the actual capacity of the energy storage system at node i at time t; Indicates the maximum capacity of the energy storage system; N ESS Represents the set of nodes in the distribution network connected to the energy storage system;

[0226] The expression of the load active power constraint is:

[0227]

[0228] Where P i D represents the design load of node i;

[0229] The expression of the auxiliary variable constraint is:

[0230]

[0231] In the formula, p ij (t) is the active power flow between nodes i and j at time t without considering the disconnection of the transmission line, if and only if α l (t)=1 and u l (t) = 1 u l (t) is a binary variable representing the switch state of transmission line l under the worst disaster scenario at time t, u l (t) = 1 means that the switch state of the transmission line l is open in the worst disaster scenario at time t, u l (t) = 0 means that the switch state of the transmission line l is closed in the worst disaster scenario at time t; max Indicates the maximum active power that the transmission line l can carry.

[0232] S5. Solve the distribution network reconstruction model according to the first constraint set, the second constraint set and the third constraint set, and obtain the target switching state of the transmission line after network reconstruction when the switching cost of the transmission line is minimized and the load loss is minimized under the worst disaster scenario as the solution result.

[0233] S6. According to the solution result, the switch state of the transmission line of the distribution network is adjusted.

[0234] In a preferred embodiment, adjusting the switch state of the transmission line of the distribution network according to the solution result includes:

[0235] Combining the solution results with the actual operating status of the transmission line at the initial moment in the disaster scenario, generating a switch adjustment strategy for each transmission line;

[0236] According to the switch adjustment strategy, the switch state of each transmission line is adjusted.

[0237] In this embodiment, during the solution process, the original problem can be equivalent to:

[0238] min x∈X a T x+max u∈U min y∈Y b T y;

[0239] stx∈X;

[0240] Y=Y(x,u)={y∈Sy ∶Gy≥h-Ex-Mu};

[0241] In the formula, a T ,b T is 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 is the constraint condition in the constraint set Y that is only related to the decision variable y.

[0242] The main question is:

[0243]

[0244]

[0245]

[0246] The sub-problems are:

[0247] SP:max u∈U min y b T y;

[0248] sty∈Y;

[0249] Gy ≥ h-Ex-Mu;

[0250] In order to calculate and solve the above two-level optimization subproblem, the Karush-Kuhn-Tucker (KKT condition) equation group is added to transform it into a single-level optimization problem:

[0251] SP2:maxb T y;

[0252] sty∈Y,u∈U,z≥0;

[0253] Gy ≥ h-Ex-Mu u∈U;

[0254] G T z≤b;

[0255]

[0256] Iterate the solution until the upper and lower bounds converge, and obtain the distribution network reconstruction strategy. The general process is as follows:

[0257] Iteration initialization. Set the lower bound LB = -∞, the upper bound UB = +∞. Initialize the number of iterations n = 0, and initialize the set of scenarios identified by the subproblem

[0258] Solve the first relaxed solution of the master problem and update the lower bound. Customize a worst disaster scenario u, solve the master problem represented by MP, and obtain 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 .

[0259] Solve for the current x n+1 Subproblems under this problem and update the upper bound. n+1 Substitute the subproblem expressed in the single-layer optimization problem SP2 and find the possible worst case u n+1 , and get the corresponding y n+1 Update the upper bound to UB = a T x n+1 +b T y n +1 .

[0260] After adding constraints to the main problem, solve it and update the upper bound. Add the iterative algorithm constraints to the main problem represented by MP, and add the u obtained from the subproblem 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 O = O∪(n + 1), continue to solve the main problem, and get x n +1 ,η n+1 . Update the lower bound to LB = a T x n +1 +η n+1 .

[0261] Repeat steps 3 and 4 until the difference between the upper and lower bounds is small enough, that is, we can consider the result to converge.

[0262] The above iterative solution process is to continuously solve sub-problems and main problems under the conditions of minimizing load loss and minimizing switching cost through cyclic iteration, and continuously narrow the range of the worst disaster scenarios that can be considered in the possible disaster scenario set. The final convergence result is a worst scenario u in the possible disaster scenario set and the line operation state α after reconstruction by the strategy of minimizing load loss and switching cost. l α l As a binary variable representing the switch state of each line l after network reconstruction, if the line l remains open after reconstruction, it takes 1, otherwise it takes 0. land represents the line as a binary variable A describing the initial operating state of each line l under the influence of typhoon disaster l (If the running state of line l after the disaster is open, it takes 1, otherwise it takes 0) By comparison, the line number that should be connected or disconnected at each moment can be obtained, that is, the network reconstruction strategy at each moment.

[0263] The method for dynamic risk assessment and switching strategy formulation considering disaster uncertainty according to an embodiment of the present invention is aimed at probabilistic modeling of distribution network operation risks under typical typhoon extreme disasters, generates a scenario of possible failure of the distribution network under typhoon disasters, and constructs an uncertainty set considering the disaster recovery process for the scenario. On this basis, a robust optimization model that minimizes load losses is constructed, and a network reconstruction strategy that minimizes the line switch switching cost corresponding to the distribution network is formulated to improve the power supply stability under typhoon disasters.

[0264] Embodiment 2

[0265] Please refer to Figure 2 , is a schematic diagram of the structure of a distribution network reconstruction device provided by an embodiment of the present invention, comprising: an objective function construction module, a constraint set construction module, a solution module and an adjustment module;

[0266] The objective function construction module is used to construct a two-stage robust optimization model as a distribution network reconstruction model by minimizing the switching cost of transmission line switches as the first-stage objective function and minimizing the load loss under the worst disaster scenario as the second-stage objective function; wherein the second-stage objective function is a two-layer optimization function, the inner layer objective function of the second-stage objective function is to minimize the load loss as the objective function, and the outer layer objective function of the second-stage objective function is to maximize the load loss under the disaster scenario as the objective function;

[0267] The constraint set construction module is used to construct a first constraint set for the first stage objective function; wherein the first constraint set includes: network radial constraints, maximum switch number constraints, node power balance constraints, distributed power supply power constraints, energy storage system power constraints, energy storage system power change constraints, load active power constraints, auxiliary variable constraints and iterative algorithm constraints; the auxiliary variable is the active power flow between nodes after the transmission line is disconnected in the disaster scenario; construct a second constraint set for the outer layer objective function; wherein the second constraint set includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transfer constraints in disaster scenarios and fault recovery time constraints; construct a third constraint set for the inner layer objective function; wherein the third constraint set includes: node power balance constraints, distributed power supply power constraints, energy storage system power constraints, load active power constraints and auxiliary variable constraints;

[0268] The solving module is used to solve the distribution network reconstruction model according to the first constraint set, the second constraint set and the third constraint set to obtain a solution result;

[0269] The regulating module is used to regulate switches of the transmission lines of the distribution network according to the solution result.

[0270] Embodiment 3

[0271] Accordingly, an embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements the distribution network reconstruction method described in the above-mentioned embodiment of the invention.

[0272] Embodiment 4

[0273] Accordingly, an 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 the distribution network reconstruction method described in the above-mentioned embodiment of the invention.

[0274] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A distribution network reconstruction method, characterized in that: include: Taking minimizing the switching cost of transmission line switches as the first-stage objective function and minimizing the load loss under the worst disaster scenario as the second-stage objective function, a two-stage robust optimization model is constructed as a distribution network reconstruction model; wherein the second-stage objective function is a two-layer optimization function, the inner objective function of the second-stage objective function takes minimizing the load loss as the objective function, and the outer objective function of the second-stage objective function takes maximizing the load loss under the disaster scenario as the objective function; Constructing a first constraint set for the first stage objective function; wherein the first constraint set includes: network radial constraint, maximum switch number constraint, node power balance constraint, distributed power supply power constraint, energy storage system power constraint, energy storage system power change constraint, load active power constraint, auxiliary variable constraint and iterative algorithm constraint; the auxiliary variable is the active power flow between nodes after the transmission line is disconnected in the disaster scenario; Constructing a second constraint set for the outer objective function; wherein the second constraint set includes: a transmission line failure probability constraint, a constraint on the number of transmission lines that fail at the same time, a transmission line state transition constraint under a disaster scenario, and a fault recovery time constraint; Constructing a third constraint set for the inner objective function; wherein the third constraint set includes: node power balance constraint, distributed power source power constraint, energy storage system power constraint, load active power constraint and auxiliary variable constraint; Solving the distribution network reconstruction model according to the first constraint set, the second constraint set and the third constraint set, and obtaining the target switch state of the transmission line after network reconstruction when the switching cost of the transmission line is minimized and the load loss is minimized under the worst disaster scenario as a solution result; According to the solution result, the switch state of the transmission line of the distribution network is adjusted.

2. The method for reconfiguring a power distribution network according to claim 1, wherein: The first-stage objective function is to minimize the switching cost of transmission line switches, and the second-stage objective function is to minimize the load loss under the worst disaster scenario. A two-stage robust optimization model is constructed as a distribution network reconstruction model, including: Obtaining binary variables of actual operating status of each transmission line in the distribution network under a disaster scenario, a transmission line disconnection cost, a transmission line connection cost, an actual load of each node in the distribution network, and a design load of each node in the distribution network; According to the actual operation state binary variable of each transmission line in the distribution network, the transmission line disconnection cost and the transmission line connection cost, constructing a function with the goal of minimizing the transmission line switch switching cost as the first stage objective function; According to the actual load and the design load of each node in the distribution network, constructing a function with the goal of minimizing the load loss under the worst disaster scenario as the second stage objective function; According to the first-stage objective function and the second-stage objective function, a two-stage robust optimization model is constructed as a distribution network reconstruction model; Among them, the expression of the objective function of the first stage is: In the formula, x represents the decision variable of the objective function in the first stage; represents the first constraint set; l represents a transmission line in the distribution network; L represents the set of all transmission lines in the distribution network; C con represents the transmission line connection cost; C dis represents the transmission line disconnection cost; α l (t) is a binary variable representing the switch state of the transmission line l after the network reconstruction at time t, α l (t) = 1 means that the switch state of the transmission line l remains open after the network reconstruction at time t, α l (t) = 0 means that the switch state of the transmission line l does not remain open after the network reconstruction at time t; A l (t) is a binary variable representing the actual operating status of the transmission line l under the disaster scenario at time t, A l (t) = 1 means that the actual state of the transmission line l in the disaster scenario at time t is open, A l (t) = 0 means that the actual state of the transmission line l in the disaster scenario at time t is closed; η represents the sum of the load losses of each node in the system; The expression of the second stage objective function is: In the formula, u represents the decision variable of the outer objective function; represents the second constraint set; y represents the decision variable of the inner objective function; represents the third constraint set; t represents a certain moment; t n represents the total duration of the distribution network being affected by the disaster; i represents a node in the distribution network; N represents the set of all nodes in the distribution network; P i D represents the design load of node i; represents the actual load of node i at time t; The expression of the distribution network reconstruction model is:

3. The method for reconfiguring a power distribution network according to claim 1, wherein: The expression of the network radial constraint is: In the formula, t represents a certain time; i represents a certain node in the distribution network; j represents a certain node in the distribution network; N represents the set of all nodes in the distribution network; N(i) represents the set of sub-nodes in the distribution network that may be linked to the node; β ij (t) is a binary variable representing the parent-child relationship between the i-th node and the j-th node in the distribution network at time t, β ij =1 means that the i-th node in the distribution network is the parent node of the j-th node at time t, β ij =0 means that the i-th node in the distribution network is not the parent node of the j-th node at time t; β ji (t) is a binary variable representing the parent-child relationship between the i-th node and the j-th node in the distribution network at time t, β ji =1 means that the jth node in the distribution network is the parent node of the ith node at time t, β ji =0 means that the jth node in the distribution network is not the parent node of the ith node at time t; α l (t) is a binary variable representing the switch state of the transmission line l after the network reconstruction at time t, α l (t) = 1 means that the switch state of the transmission line l remains open after the network reconstruction at time t, α l (t) = 0 indicates that the switch state of the transmission line l does not remain open after the network reconstruction at time t; l indicates a transmission line in the distribution network; L indicates the set of all transmission lines in the distribution network; The expression of the maximum number of switches constraint is: In the formula, A l (t) is a binary variable representing the actual operating status of the transmission line l under the disaster scenario at time t, A l (t) = 1 means that the actual state of the transmission line l in the disaster scenario at time t is open, A l (t) = 0 means that the actual state of the transmission line l in the disaster scenario at time t is closed; SW max Indicates the maximum number of transmission lines that can change their operating status in the network reconstruction strategy; The expression of the node power balance constraint is: In the formula, is the active power flow between node i and node j at time t after considering the disconnection state of the transmission line; represents the actual load of node i at time t; represents the active power of the energy storage system at node i at time t; represents the active power of distributed generation at node i at time t; The expression of the distributed generation power constraint is: In the formula, represents the maximum active power of the distributed generation at node i; N DG Represents the set of nodes connected to distributed generation in the distribution network; The expression of the energy storage system power constraint is: In the formula, represents the maximum charging active power of the energy storage system at node i; represents the maximum discharge active power of the energy storage system at node i; represents the actual capacity of the energy storage system at node i at time t; Indicates the maximum capacity of the energy storage system; N ESS Represents the set of nodes in the distribution network connected to the energy storage system; The expression of the energy storage system power variation constraint is: In the formula, represents the charging active power of the energy storage system at node i at time t; represents the active power discharged by the energy storage system at node i at time t; η chi represents the charging efficiency of the energy storage system at node i; η disi represents the discharge efficiency of the energy storage system at node i; The expression of the load active power constraint is: Where P i D represents the design load of node i; The expression of the auxiliary variable constraint is: In the formula, p ij (t) is the active power flow between nodes i and j at time t without considering the disconnection of the transmission line, if and only if α l (t)=1 and u l (t) = 1 u l (t) is a binary variable representing the switch state of transmission line l under the worst disaster scenario at time t, u l (t) = 1 means that the switch state of the transmission line l is open in the worst disaster scenario at time t, u l (t) = 0 means that the switch state of the transmission line l is closed in the worst disaster scenario at time t; max Indicates the maximum active power that the transmission line l can carry; The expression of the iterative algorithm constraint is: In the formula, represents the actual load of node i under the worst disaster scenario at time t; represents the newly added variables in the iterative process of the algorithm using columns and constraints.

4. The method for reconfiguring a power distribution network according to claim 1, wherein: The expression of the transmission line failure probability constraint is: In the formula, t represents a certain moment; Prob l (t) represents the time-varying fault probability of transmission line l at time t; Π is the preset time-varying fault probability threshold; is a binary variable representing the fault condition of transmission line l at time t, It means that the transmission line l is damaged and fails at time t. It means that the transmission line l is damaged but not faulty at time t; The expression for the constraint on the number of transmission lines failing at the same time is: In the formula, I l (t) is a binary variable representing the disaster availability of transmission line l under the disaster scenario generated at time t, I l I (t) = 1 means that the transmission line l is damaged but still usable in the disaster scenario generated at time t. l (t) = 1 means that the transmission line l is damaged and unavailable in the disaster scenario generated at time t; l represents a transmission line in the distribution network; L represents the set of all transmission lines in the distribution network; Num L represents the total number of transmission lines in the distribution network; OFF max It indicates the maximum total number of transmission lines that are allowed to fail due to disasters at the same time; The expression of the transmission line state transition constraint under the disaster scenario is: In the formula, I l (t-1) is a binary variable representing the disaster availability of transmission line l under the disaster scenario generated at time t-1, I l (t-1) = 1 means that the transmission line l is damaged but still usable in the disaster scenario generated at time t-1. l (t-1)=1 means that the transmission line l is damaged and unavailable in the disaster scenario generated at time t-1; is a binary variable representing the disappearance of the impact of the disaster scenario on the affected transmission line l at time t, It means that the damaged transmission line l before time t-RT is restored at time t. It means that there is no fault recovery process in the transmission line l at time t; The expression of the fault recovery time constraint is: In the formula, is a binary variable representing the disappearance of the impact of the disaster scenario on the affected transmission line l at time t+RT, It means that the damaged transmission line l before time t is restored at time t+RT. It indicates that the transmission line l has no fault recovery process at time t+RT; RT represents the preset recovery time.

5. The method for reconfiguring a power distribution network according to claim 4, characterized in that: The step of constructing a second constraint set for the outer objective function includes: For each transmission line in the distribution network, obtain the tower wind speed and the tower precipitation at each tower on the transmission line; divide the transmission line into a plurality of sections, and obtain the section wind speed and the section precipitation at each section; Calculate the equivalent wind speed at each tower based on the wind speed at each tower and the precipitation at the tower; According to the equivalent wind speed at each tower, calculate the tower failure probability of each tower in the disaster scenario; According to the wind speed and precipitation at each segment, the segment failure probability of each segment under the disaster scenario is calculated; Calculating the transmission line failure probability of the transmission line according to the tower failure probability of all towers and the segment failure probability of all segments on the transmission line; constructing the second constraint set according to the transmission line failure probability; Wherein, the calculation formula of the equivalent wind speed is: Where V * (r tw (t),t,h d ) represents the equivalent wind speed at the tower; t represents the time when the disaster lasts, and t = 0 when the disaster occurs; r tw (t) represents the distance from the tower to the typhoon center; h d Indicates the height of the basic wind speed in the disaster area; V(r tw (t),t,h d ) represents the wind speed at the tower; RA(r tw (t), t) represents the precipitation at the tower; v0, v1, v2, v3, v4 and v5 are all preset constants; The calculation formula of the tower failure probability is: Where Prob tw,i (t) represents the tower failure probability of the i-th tower on the transmission line at time t; x tw,i (t) is the auxiliary substitution quantity, defined as the equivalent wind speed The natural logarithm of μ tw,i Represents x tw,i The average value of (t); σ tw,i Represents x tw,i (t) standard deviation; The calculation formula of the segment failure probability is: In the formula, λ sg,j (t) represents the segment failure probability of the jth segment on the transmission line at time t; L sg Indicates the length of the segment; V(r sg (t),t,h d ) represents the wind speed at the segment; RA(r sg (t), t) represents the precipitation at the segment; V sgd Indicates the design wind speed of the segment; RA sgd Indicates the design precipitation of the segment; a sg 、b sg 、c sg and d sg All are preset constants; The calculation formula of the transmission line failure probability is: Where Prob l (t) represents the failure probability of transmission line l at time t; n tw Represents the total number of towers on the transmission line; n sg Indicates the total number of segments on the transmission line.

6. The method for reconfiguring a power distribution network according to claim 1, wherein: The expression of the node power balance constraint is: In the formula, t represents a certain moment; i represents a certain node in the distribution network; j represents a certain node in the distribution network; N represents the set of all nodes in the distribution network; N(i) represents the set of sub-nodes in the distribution network that may be linked to the node; is the active power flow between node i and node j at time t after considering the disconnection state of the transmission line; represents the actual load of node i at time t; represents the active power of the energy storage system at node i at time t; represents the active power of distributed generation at node i at time t; The expression of the distributed generation power constraint is: In the formula, represents the maximum active power of the distributed generation at node i; N DG Represents the set of nodes connected to distributed generation in the distribution network; The expression of the energy storage system power constraint is: In the formula, represents the maximum charging active power of the energy storage system at node i; represents the maximum discharge active power of the energy storage system at node i; represents the actual capacity of the energy storage system at node i at time t; Indicates the maximum capacity of the energy storage system; N ESS Represents the set of nodes in the distribution network connected to the energy storage system; The expression of the load active power constraint is: Where P i D represents the design load of node i; The expression of the auxiliary variable constraint is: In the formula, p ij (t) is the active power flow between nodes i and j at time t without considering the disconnection of the transmission line, if and only if α l (t)=1 and u l (t) = 1 u l (t) is a binary variable representing the switch state of transmission line l under the worst disaster scenario at time t, u l (t) = 1 means that the switch state of the transmission line l is open in the worst disaster scenario at time t, u l (t) = 0 means that the switch state of the transmission line l is closed in the worst disaster scenario at time t; max Indicates the maximum active power that the transmission line l can carry.

7. The method for reconfiguring a power distribution network according to claim 1, characterized in that: The step of adjusting the switch state of the transmission line of the distribution network according to the solution result includes: Combining the solution results with the actual operating status of the transmission line at the initial moment in the disaster scenario, generating a switch adjustment strategy for each transmission line; According to the switch adjustment strategy, the switch state of each transmission line is adjusted.

8. A distribution network reconstruction device, characterized in that: include: Objective function building module, constraint set building module, solution module and adjustment module; The objective function construction module is used to construct a two-stage robust optimization model as a distribution network reconstruction model by minimizing the switching cost of transmission line switches as the first-stage objective function and minimizing the load loss under the worst disaster scenario as the second-stage objective function; wherein the second-stage objective function is a two-layer optimization function, the inner layer objective function of the second-stage objective function is to minimize the load loss as the objective function, and the outer layer objective function of the second-stage objective function is to maximize the load loss under the disaster scenario as the objective function; The constraint set construction module is used to construct a first constraint set for the first stage objective function; wherein the first constraint set includes: network radial constraints, maximum switch number constraints, node power balance constraints, distributed power supply power constraints, energy storage system power constraints, energy storage system power change constraints, load active power constraints, auxiliary variable constraints and iterative algorithm constraints; the auxiliary variable is the active power flow between nodes after the transmission line is disconnected in the disaster scenario; construct a second constraint set for the outer layer objective function; wherein the second constraint set includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transfer constraints in disaster scenarios and fault recovery time constraints; construct a third constraint set for the inner layer objective function; wherein the third constraint set includes: node power balance constraints, distributed power supply power constraints, energy storage system power constraints, load active power constraints and auxiliary variable constraints; The solving module is used to solve the distribution network reconstruction model according to the first constraint set, the second constraint set and the third constraint set to obtain a solution result; The regulating module is used to regulate switches of the transmission lines of the distribution network according to the solution result.

9. A terminal device, characterized in that: The method 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, the distribution network reconstruction method according to 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 executed, the device where the storage medium is located is controlled to execute the distribution network reconstruction method according to any one of claims 1 to 7.

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