A power distribution network reconfiguration method and device, a terminal device and a storage medium

Abstract

The application discloses a power distribution network reconfiguration method and device, a terminal equipment and a storage medium, wherein the method comprises the following steps: constructing a two-stage robust optimization model as a power distribution network reconfiguration model, wherein a first-stage target function is to minimize a transmission line switch switching cost, and a second-stage target function is to minimize a load loss in a worst disaster scenario; constructing a first constraint set for the first-stage target function; constructing a second constraint set for the outer target function; constructing a third constraint set for the inner target function; solving the power distribution network reconfiguration model to obtain a solution result; and adjusting the switch of the transmission line of the power distribution network according to the solution result. The application provides a network reconfiguration scheme with low cost and low loss by constructing a two-stage robust optimization model, taking the minimization of the transmission line switch switching cost and the minimization of the load loss in the worst disaster scenario as the target functions of the first stage and the second stage respectively.

Description

Technical Field

[0001] This invention relates to the field of power distribution network dispatching and operation technology, and in particular to a power distribution network reconfiguration method, apparatus, terminal equipment, and storage medium. Background Technology

[0002] Faced with the frequent occurrence of extreme weather events caused by global climate change, especially the severe threat posed by typhoons to the power grid system, this increased uncertainty has brought unprecedented challenges to the stable operation of the power system. Ensuring the smooth operation of the power system is not only a matter of national importance and people's livelihood, but has also become an urgent and crucial issue. To ensure that users' electricity needs are met and to minimize the impact of extreme weather events, distribution network reconfiguration, as an important strategy to enhance the resilience and disaster resistance of the distribution network, can quickly restore power supply to critical loads. However, this process is particularly complex, requiring a suitable balance between the physical system and the economic market, ensuring the safe and stable operation of the power system while striving to minimize disaster losses and associated additional costs. How to develop a low-cost and low-loss network reconfiguration scheme remains an unresolved problem. Summary of the Invention

[0003] This invention provides a distribution network reconfiguration method, apparatus, terminal equipment, and storage medium to address the technical problem of how to formulate a network reconfiguration scheme with low cost and minimal losses.

[0004] To address the aforementioned technical problems, embodiments of the present invention provide a distribution network reconfiguration method, comprising:

[0005] A two-stage robust optimization model is constructed as a distribution network reconfiguration model, with the first-stage objective function being minimizing the cost of switching transmission lines and the second-stage objective function being minimizing load loss under the worst-case disaster scenario. The second-stage objective function is a two-layer optimization function, with the inner objective function minimizing load loss and the outer objective function maximizing load loss under disaster scenarios.

[0006] A first set of constraints is constructed for the objective function of the first stage; wherein, the first set of constraints includes: network radial constraints, maximum number of switches constraints, node power balance constraints, distributed 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 under disaster scenarios;

[0007] A second set of constraints is constructed for the outer objective function; wherein, the second set of constraints includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transition constraints under disaster scenarios, and failure recovery time constraints;

[0008] A third set of constraints is constructed for the inner objective function; wherein the third set of constraints includes: node power balance constraints, distributed power constraints, energy storage system power constraints, load active power constraints, and auxiliary variable constraints;

[0009] Based on the first constraint set, the second constraint set, and the third constraint set, the distribution network reconfiguration model is solved to obtain the target switching state of the transmission line after network reconfiguration when the switching cost of the transmission line is minimized and the load loss is minimized under the worst disaster scenario. This is used as the solution result.

[0010] Based on the solution results, the switching states of the transmission lines in the distribution network are adjusted.

[0011] As a preferred embodiment, a two-stage robust optimization model is constructed, with the first-stage objective function being minimizing the cost of switching transmission lines and the second-stage objective function being minimizing load loss under the worst-case disaster scenario. This model serves as the distribution network reconfiguration model and includes:

[0012] Obtain the following binary variables: the actual operating status of each transmission line in the distribution network under disaster scenarios, the cost of disconnecting the transmission line, the cost of connecting the transmission line, the actual load of each node in the distribution network, and the design load of each node in the distribution network;

[0013] Based on the binary variables of the actual operating state of each transmission line in the distribution network, the cost of disconnecting the transmission line, and the cost of connecting the transmission line, a function is constructed with the goal of minimizing the switching cost of the transmission line as the objective function for the first stage.

[0014] Based on the actual load and design load of each node in the distribution network, a function is constructed with the objective of minimizing load loss under the worst disaster scenario, which serves as the objective function for the second stage.

[0015] Based on the objective functions of the first and second stages, a two-stage robust optimization model is constructed as a reconfiguration model for the distribution network.

[0016] The expression for the objective function in the first stage is:

[0017]

[0018] In the formula, x represents the decision variable of the objective function in the first stage; Let l represent the first constraint set; l represent a transmission line in the distribution network; L represent the set of all transmission lines in the distribution network; C con Indicates the cost of transmission line connections; C dis Indicates the cost of disconnecting the transmission line; α l (t) is a binary variable representing the switching state of transmission line l at time t after network reconstruction, α l (t) = 1 indicates that transmission line l remains open after network reconstruction at time t, α l (t) = 0 indicates that the transmission line l did not remain open after network reconstruction at time t; A l Let A(t) be a binary variable representing the actual operating state of transmission line l at time t under the disaster scenario. l (t) = 1 indicates that the actual state of transmission line l at time t under the disaster scenario is that it is open. l (t) = 0 indicates that the actual state of transmission line l under the disaster scenario at time t is closed; η represents the total load loss of each node in the system;

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

[0020]

[0021] In the formula, u represents the decision variable of the outer objective function; Let represent the second constraint set; y represents the decision variables of the inner objective function; The third constraint set is represented; t represents a certain time; t n P represents the total duration of the disaster affecting the distribution network; i represents a node in the distribution network; N represents the set of all nodes in the distribution network; i D represents the design load of node i; This represents the actual load of node i at time t;

[0022] The expression for the distribution network reconfiguration model is as follows:

[0023]

[0024] As a preferred embodiment, the expression for the network radial constraint is:

[0025]

[0026] In the formula, t represents a certain moment; i represents a node in the distribution network; j represents a node in the distribution network; N represents the set of all nodes in the distribution network; N(i) represents the set of child nodes in the distribution network that may be linked to a node; β ij Let β(t) be 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.ij =1 indicates that the i-th node in the distribution network is the parent node of the j-th node at time t, β ij =0 indicates that the i-th node in the distribution network is not the parent node of the j-th node at time t; β ji Let β(t) be 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. ji =1 indicates that the j-th node in the distribution network is the parent node of the i-th node at time t, β ji =0 indicates that the j-th node in the distribution network is not the parent node of the i-th node at time t; α l (t) is a binary variable representing the switching state of transmission line l at time t after network reconstruction, α l (t) = 1 indicates that transmission line l remains open after network reconstruction at time t, α l (t) = 0 indicates that the switching state of transmission line l after network reconstruction at time t is not kept open; l represents a certain transmission line in the distribution network; L represents the set of all transmission lines in the distribution network;

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

[0028]

[0029] In the formula, A l Let A(t) be a binary variable representing the actual operating state of transmission line l at time t under the disaster scenario. l (t) = 1 indicates that the actual state of transmission line l at time t under the disaster scenario is that it is open. l (t) = 0 indicates that the actual state of transmission line l at time t under the disaster scenario is closed; SW max This indicates the maximum number of transmission lines whose operating state can be changed in the network reconfiguration strategy.

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

[0031]

[0032] In the formula, To take into account the active power flow between node i and node j at time t after the transmission line is disconnected; This represents the actual load of node i at time t; This represents the active power of the energy storage system at node i at time t; This represents the active power of the distributed power source at node i at time t;

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

[0034]

[0035] In the formula, N represents the maximum active power of the distributed power source at node i; DG This represents the set of nodes in a distribution network that are connected to distributed generation sources.

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

[0037]

[0038]

[0039] In the formula, This represents the maximum active power of the energy storage system at node i. This represents the maximum active power of the energy storage system at node i. This represents the actual capacity of the energy storage system at node i at time t; N represents the maximum capacity of the energy storage system. ESS This represents the set of nodes in a distribution network that are connected to an energy storage system.

[0040] The expression for the power variation constraint of the energy storage system is:

[0041]

[0042] In the formula, This represents the active power of the energy storage system at node i at time t. η represents the active power of the energy storage system discharging at node i at time t; chi Indicates the charging efficiency of the energy storage system at node i; η disi This represents the discharge efficiency of the energy storage system at node i;

[0043] The expression for the load active power constraint is:

[0044]

[0045] In the formula, P i D Indicates the design load of node i;

[0046] The expression for the auxiliary variable constraint is:

[0047]

[0048] In the formula, p ij (t) represents the active power flow between node i and node j at time t without considering the transmission line disconnection state, if and only if α l (t)=1 and u l When (t) = 1 u l Let u(t) be a binary variable representing the switching state of transmission line l under the worst-case disaster scenario at time t. l (t) = 1 indicates that in the worst-case disaster scenario at time t, the transmission line l is in the open state. l (t) = 0 indicates that in the worst-case disaster scenario at time t, the transmission line l is in the off state; P max This indicates the maximum active power that transmission line l can carry;

[0049] The expression for the constraint of the iterative algorithm is:

[0050]

[0051] In the formula, This represents the actual load of node i under the worst disaster scenario at time t; it also represents the new variables added during the iteration process of the column and constraint generation algorithm.

[0052] As a preferred embodiment, the expression for the transmission line fault probability constraint is:

[0053]

[0054] In the formula, t represents a certain moment; Prob l (t) represents the time-varying failure probability of transmission line l at time t; Π is the preset time-varying failure probability threshold. Let the binary variable represent the transmission line l suffering a fault at time t. This indicates that transmission line l was damaged at time t, causing a failure. This indicates that transmission line l was damaged but not faulty at time t;

[0055] The expression for the constraint on the number of simultaneously faulty transmission lines is:

[0056]

[0057] In the formula, I l Let (t) be a binary variable representing the disaster availability of transmission line l under the disaster scenario generated at time t. l (t) = 1 indicates that transmission line l is affected by a disaster scenario generated at time t but is still usable. l (t) = 1 indicates that transmission line l becomes unusable due to a disaster scenario generated at time t; l represents a single 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 This indicates the maximum total number of transmission lines that are allowed to fail due to a disaster at the same time.

[0058] The expression for the transmission line state transition constraint under the disaster scenario is as follows:

[0059]

[0060] 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. l (t-1) = 1 indicates that transmission line l is affected by a disaster scenario generated at time t-1 but is still usable. l (t-1) = 1 indicates that transmission line l is unusable due to a disaster scenario generated at time t-1; To represent the binary variable representing the diminishing impact of a disaster scenario on the affected transmission line l at time t, This indicates that the transmission line l that was damaged before time t-RT was restored at time t. This indicates that transmission line l has no fault recovery process at time t;

[0061] The expression for the fault recovery time constraint is:

[0062]

[0063] In the formula, Let be a binary variable representing the diminishing impact of a disaster scenario on the affected transmission line l at time t+RT. This indicates that the transmission line l affected by the disaster before time t was restored at time t+RT. This indicates that transmission line l has no fault recovery process at time t+RT; RT represents the preset recovery time.

[0064] As a preferred embodiment, constructing a second constraint set for the outer objective function includes:

[0065] For each transmission line in the power distribution network, the wind speed and precipitation at each tower on the transmission line are obtained; the transmission line is divided into several segments, and the wind speed and precipitation at each segment are obtained.

[0066] Calculate the equivalent wind speed at each tower based on the wind speed and precipitation at each tower location.

[0067] Calculate the probability of tower failure for each tower under disaster scenarios based on the equivalent wind speed at each tower.

[0068] Calculate the segment failure probability of each segment under disaster scenarios based on the wind speed and precipitation at each segment.

[0069] The transmission line failure probability is calculated based on the tower failure probability of all towers and the segment failure probability of all segments on the transmission line.

[0070] Based on the transmission line failure probability, construct the second constraint set;

[0071] The formula for calculating the equivalent wind speed is as follows:

[0072] V * (r tw (t),t,h d )=

[0073] V(r tw (t),t,h d )+v0(v1(RA(r tw (t),t)) v2 )·

[0074] (exp(v3V(r tw (t),t,h d ))-v4exp(v5V(r tw (t),t,h d )));

[0075] In the formula, V * (r tw (t),t,h d () represents the equivalent wind speed at the tower; t represents the duration of the disaster, denoted as t=0 when the disaster occurs; r tw (t) represents the distance from the tower location to the center of the typhoon; h d The altitude representing the basic wind speed in the affected 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;

[0076] The formula for calculating the tower failure probability is as follows:

[0077]

[0078]

[0079] In the formula, Prob tw,i (t) represents the probability of tower failure 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 x representstw,i The average value of (t); σ tw,i x represents tw,i The standard deviation of (t);

[0080] The formula for calculating the segment failure probability is as follows:

[0081]

[0082] In the formula, λ sg,j (t) represents the segment failure probability of the j-th segment on the transmission line at time t; L sg V(r) represents the length of the segment; 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 for a segment; a sg b sg c sg and d sg All are preset constants;

[0083] The formula for calculating the probability of transmission line failure is as follows:

[0084]

[0085] In the formula, Prob l (t) represents the probability of failure of transmission line l at time t; n tw n represents the total number of poles and towers on the transmission line. sg This indicates the total number of segments on the transmission line.

[0086] As a preferred embodiment, the expression for the node power balance constraint is:

[0087]

[0088] 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 child nodes in the distribution network that may be linked to a node. To take into account the active power flow between node i and node j at time t after the transmission line is disconnected; This represents the actual load of node i at time t; This represents the active power of the energy storage system at node i at time t; This represents the active power of the distributed power source at node i at time t;

[0089] The expression for the power constraint of the distributed power source is:

[0090]

[0091] In the formula, N represents the maximum active power of the distributed power source at node i; DG This represents the set of nodes in a distribution network that are connected to distributed generation sources.

[0092] The expression for the power constraint of the energy storage system is:

[0093]

[0094] In the formula, This represents the maximum active power of the energy storage system at node i. This represents the maximum active power of the energy storage system at node i. This represents the actual capacity of the energy storage system at node i at time t; N represents the maximum capacity of the energy storage system. ESS This represents the set of nodes in a distribution network that are connected to an energy storage system.

[0095] The expression for the load active power constraint is:

[0096]

[0097] In the formula, P i D Indicates the design load of node i;

[0098] The expression for the auxiliary variable constraint is:

[0099]

[0100] In the formula, p ij (t) represents the active power flow between node i and node j at time t without considering the transmission line disconnection state, if and only if α l (t)=1 and u l When (t) = 1 u l Let u(t) be a binary variable representing the switching state of transmission line l under the worst-case disaster scenario at time t. l (t) = 1 indicates that in the worst-case disaster scenario at time t, the transmission line l is in the open state. l (t) = 0 indicates that in the worst-case disaster scenario at time t, the transmission line l is in the off state; P max This indicates the maximum active power that transmission line l can carry.

[0101] As a preferred embodiment, adjusting the switching states of the transmission lines of the distribution network based on the solution results includes:

[0102] Based on the solution results and the actual operating status of the transmission lines at the initial moment under the disaster scenario, a switching adjustment strategy for each transmission line is generated.

[0103] According to the switching adjustment strategy, the switching state of each transmission line is adjusted.

[0104] Based on the above embodiments, another embodiment of the present invention provides a power distribution network reconfiguration device, including: an objective function construction module, a constraint set construction module, a solution module, and an adjustment module;

[0105] The objective function construction module is used to construct a two-stage robust optimization model as a distribution network reconfiguration model, with the first-stage objective function being minimizing the cost of switching transmission lines and the second-stage objective function being minimizing the load loss under the worst disaster scenario. The second-stage objective function is a two-layer optimization function, with the inner objective function minimizing the load loss and the outer objective function maximizing the load loss under the disaster scenario.

[0106] The constraint set construction module is used to construct a first constraint set for the objective function of the first stage; wherein the first constraint set includes: network radial constraints, maximum number of switches constraints, node power balance constraints, distributed 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 a disaster scenario; constructing a second constraint set for the outer objective function; wherein the second constraint set includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transition constraints in a disaster scenario, and failure recovery time constraints; constructing a third constraint set for the inner objective function; wherein the third constraint set includes: node power balance constraints, distributed power constraints, energy storage system power constraints, load active power constraints, and auxiliary variable constraints;

[0107] The solution module is used to solve the power distribution network reconfiguration model based on the first constraint set, the second constraint set, and the third constraint set, and obtain the solution result.

[0108] The adjustment module is used to adjust the switches of the transmission lines of the distribution network according to the solution results.

[0109] Based on the above embodiments, another embodiment of the present invention provides a terminal device, the terminal device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the power distribution network reconfiguration method described in the above embodiments of the invention.

[0110] Based on the above embodiments, another embodiment of the present invention provides a storage medium, the storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the power distribution network reconfiguration method described in the above embodiments of the invention.

[0111] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0112] This invention constructs a two-stage robust optimization model as a distribution network reconfiguration model. The objective function of the first stage is to minimize the switching cost of transmission line switches, and the objective function of the second stage is to minimize the load loss under the worst-case disaster scenario. A first set of constraints is constructed for the objective function of the first stage. The first set of constraints includes: network radial constraints, maximum number of switches constraints, node power balance constraints, distributed 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 consider the active power flow between nodes after the transmission line is disconnected under the disaster scenario. A second set of constraints is constructed for the outer objective function; wherein the second set of constraints includes: transmission line fault probability constraints, simultaneous faulty transmission line number constraints, transmission line state transition constraints under disaster scenarios, and fault recovery time constraints; a third set of constraints is constructed for the inner objective function; wherein the third set of constraints includes: node power balance constraints, distributed power constraints, energy storage system power constraints, load active power constraints, and auxiliary variable constraints; the distribution network reconfiguration model is solved based on the first, second, and third set of constraints to obtain the solution results; the switching of transmission lines in the distribution network is adjusted based on the solution results. This invention, by constructing a two-stage robust optimization model, uses minimizing the cost of transmission line switching and minimizing the load loss under the worst disaster scenario as the objective functions for the first and second stages, respectively, providing a low-cost and low-loss network reconfiguration scheme that can minimize disaster losses and associated additional costs. Attached Figure Description

[0113] Figure 1 This is a flowchart illustrating a power distribution network reconfiguration method according to an embodiment of the present invention;

[0114] Figure 2This is a schematic diagram of the structure of a power distribution network reconfiguration device provided in an embodiment of the present invention. Detailed Implementation

[0115] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0116] Example 1

[0117] Please refer to Figure 1 The above is a flowchart illustrating a distribution network reconfiguration method according to an embodiment of the present invention, comprising:

[0118] S1. A two-stage robust optimization model is constructed, with the first-stage objective function being minimizing the cost of switching transmission lines and the second-stage objective function being minimizing the load loss under the worst disaster scenario. This model serves as the reconfiguration model for the distribution network. The second-stage objective function is a two-layer optimization function. The inner objective function of the second-stage objective function aims to minimize the load loss, while the outer objective function aims to maximize the load loss under the disaster scenario.

[0119] In step S1, the present invention constructs a two-stage robust optimization model. The objective function of the model can be divided into a first stage, a second stage outer layer, and a second stage inner layer, each with corresponding objective functions and constraints.

[0120] In a preferred embodiment, the construction of a two-stage robust optimization model, using minimizing the cost of switching transmission lines as the first-stage objective function and minimizing load loss under the worst-case disaster scenario as the second-stage objective function, as the distribution network reconfiguration model, includes:

[0121] Obtain the following binary variables: the actual operating status of each transmission line in the distribution network under disaster scenarios, the cost of disconnecting the transmission line, the cost of connecting the transmission line, the actual load of each node in the distribution network, and the design load of each node in the distribution network;

[0122] Based on the binary variables of the actual operating state of each transmission line in the distribution network, the cost of disconnecting the transmission line, and the cost of connecting the transmission line, a function is constructed with the goal of minimizing the switching cost of the transmission line as the objective function for the first stage.

[0123] Based on the actual load and design load of each node in the distribution network, a function is constructed with the objective of minimizing load loss under the worst disaster scenario, which serves as the objective function for the second stage.

[0124] Based on the objective functions of the first and second stages, a two-stage robust optimization model is constructed as a reconfiguration model for the distribution network.

[0125] The expression for the objective function in the first stage is:

[0126]

[0127] In the formula, x represents the decision variable of the objective function in the first stage; Let l represent the first constraint set; l represent a transmission line in the distribution network; L represent the set of all transmission lines in the distribution network; C con Indicates the cost of transmission line connections; C dis Indicates the cost of disconnecting the transmission line; α l (t) is a binary variable representing the switching state of transmission line l at time t after network reconstruction, α l (t) = 1 indicates that transmission line l remains open after network reconstruction at time t, α l (t) = 0 indicates that the transmission line l did not remain open after network reconstruction at time t; A l Let A(t) be a binary variable representing the actual operating state of transmission line l at time t under the disaster scenario. l (t) = 1 indicates that the actual state of transmission line l at time t under the disaster scenario is that it is open. l (t) = 0 indicates that the actual state of transmission line l under the disaster scenario at time t is closed; η represents the total load loss of each node in the system;

[0128] The expression for the objective function in the second stage is:

[0129]

[0130] In the formula, u represents the decision variable of the outer objective function; Let represent the second constraint set; y represents the decision variables of the inner objective function; The third constraint set is represented; t represents a certain time; t n P represents the total duration of the disaster affecting the distribution network; i represents a node in the distribution network; N represents the set of all nodes in the distribution network; i D Indicates the design load of node i; This represents the actual load of node i at time t;

[0131] The expression for the distribution network reconfiguration model is as follows:

[0132]

[0133] In this embodiment, a distribution network reconfiguration model considering the uncertainty of disaster conditions is established. This invention introduces binary variables and α. l (t) and A l (t). α l This is a binary variable representing the switching state of each line l after network reconstruction. It takes the value 1 if line l remains on after reconstruction, and 0 otherwise. A l The variable is a binary variable describing the actual operating status of each line l under the influence of typhoon disaster. If the operating status of line l is "on" after the disaster, it is taken as 1, otherwise it is taken as 0.

[0134] S2. Construct a first set of constraints for the objective function of the first stage; wherein, the first set of constraints includes: network radial constraints, maximum number of switches constraints, node power balance constraints, distributed 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 under disaster scenarios.

[0135] In a preferred embodiment, the expression for the network radial constraint is:

[0136]

[0137]

[0138] In the formula, t represents a certain moment; i represents a node in the distribution network; j represents a node in the distribution network; N represents the set of all nodes in the distribution network; N(i) represents the set of child nodes in the distribution network that may be linked to a node; β ij Let β(t) be 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. ij =1 indicates that the i-th node in the distribution network is the parent node of the j-th node at time t, β ij =0 indicates that the i-th node in the distribution network is not the parent node of the j-th node at time t; β ji Let β(t) be 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. ji =1 indicates that the j-th node in the distribution network is the parent node of the i-th node at time t, β ji =0 indicates that the j-th node in the distribution network is not the parent node of the i-th node at time t; α l (t) is a binary variable representing the switching state of transmission line l at time t after network reconstruction, αl (t) = 1 indicates that transmission line l remains open after network reconstruction at time t, α l (t) = 0 indicates that the switching state of transmission line l after network reconstruction at time t is not kept open; l represents a certain transmission line in the distribution network; L represents the set of all transmission lines in the distribution network;

[0139] The expression for the maximum number of switches constraint is:

[0140]

[0141] In the formula, A l Let A(t) be a binary variable representing the actual operating state of transmission line l at time t under the disaster scenario. l (t) = 1 indicates that the actual state of transmission line l at time t under the disaster scenario is that it is open. l (t) = 0 indicates that the actual state of transmission line l at time t under the disaster scenario is closed; SW max This indicates the maximum number of transmission lines whose operating state can be changed in the network reconfiguration strategy.

[0142] The expression for the node power balance constraint is:

[0143]

[0144] In the formula, To take into account the active power flow between node i and node j at time t after the transmission line is disconnected; This represents the actual load of node i at time t; This represents the active power of the energy storage system at node i at time t; This represents the active power of the distributed power source at node i at time t;

[0145] The expression for the power constraint of the distributed power source is:

[0146]

[0147] In the formula, N represents the maximum active power of the distributed power source at node i; DG This represents the set of nodes in a distribution network that are connected to distributed generation sources.

[0148] The expression for the power constraint of the energy storage system is:

[0149]

[0150] In the formula, This represents the maximum active power of the energy storage system at node i. This represents the maximum active power of the energy storage system at node i. This represents the actual capacity of the energy storage system at node i at time t; N represents the maximum capacity of the energy storage system. ESS This represents the set of nodes in a distribution network that are connected to an energy storage system.

[0151] The expression for the power variation constraint of the energy storage system is:

[0152]

[0153] In the formula, This represents the active power of the energy storage system at node i at time t. η represents the active power of the energy storage system discharging at node i at time t; chi Indicates the charging efficiency of the energy storage system at node i; η disi This represents the discharge efficiency of the energy storage system at node i;

[0154] The expression for the load active power constraint is:

[0155]

[0156] In the formula, P i D Indicates the design load of node i;

[0157] The expression for the auxiliary variable constraint is:

[0158]

[0159] In the formula, p ij (t) represents the active power flow between node i and node j at time t without considering the transmission line disconnection state, if and only if α l (t)=1 and u l When (t) = 1 u l Let u(t) be a binary variable representing the switching state of transmission line l under the worst-case disaster scenario at time t. l (t) = 1 indicates that in the worst-case disaster scenario at time t, the transmission line l is in the open state. l (t) = 0 indicates that in the worst-case disaster scenario at time t, the transmission line l is in the off state; P max This indicates the maximum active power that transmission line l can carry;

[0160] The expression for the constraint of the iterative algorithm is:

[0161]

[0162] In the formula, This represents the actual load of node i under the worst disaster scenario at time t; it also represents the new variables added during the iteration process of the column and constraint generation algorithm.

[0163] In this embodiment, when constructing the radial constraints of the network, the present invention defines the dimension as the total number of distribution network nodes Num. N Let β be a square matrix, where the element in the i-th row and j-th column is a binary variable β. ij The value is 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 is 0.

[0164]

[0165] From auxiliary quantity β ij A binary variable α can be defined. l (If the line remains open after reconstruction, take 1; otherwise, take 0):

[0166]

[0167] S3. Construct a second set of constraints for the outer objective function; wherein the second set of constraints includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transition constraints under disaster scenarios, and failure recovery time constraints.

[0168] It should be noted that the outer-layer decision variable in the second stage is u. The set of constraints it needs to satisfy is the uncertainty set U generated by probability.

[0169] In a preferred embodiment, the expression for the transmission line fault probability constraint is:

[0170]

[0171] In the formula, t represents a certain moment; Prob l (t) represents the time-varying failure probability of transmission line l at time t; ∏ is the preset time-varying failure probability threshold; Let the binary variable represent the transmission line l suffering a fault at time t. This indicates that transmission line l was damaged at time t, causing a failure. This indicates that transmission line l was damaged but not faulty at time t;

[0172] The expression for the constraint on the number of simultaneously faulty transmission lines is:

[0173]

[0174] In the formula, I lLet I(t) be a binary variable representing the disaster availability of transmission line l under the disaster scenario generated at time t. l (t) = 1 indicates that transmission line l is affected by a disaster scenario generated at time t but is still usable. l (t) = 1 indicates that transmission line l becomes unusable due to a disaster scenario generated at time t; l represents a single 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 This indicates the maximum total number of transmission lines that are allowed to fail due to a disaster at the same time.

[0175] The expression for the transmission line state transition constraint under the disaster scenario is as follows:

[0176]

[0177] 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. l (t-1) = 1 indicates that transmission line l is affected by a disaster scenario generated at time t-1 but is still usable. l (t-1) = 1 indicates that transmission line l is unusable due to a disaster scenario generated at time t-1; To represent the binary variable representing the diminishing impact of a disaster scenario on the affected transmission line l at time t, This indicates that the transmission line l that was damaged before time t-RT was restored at time t. This indicates that transmission line l has no fault recovery process at time t;

[0178] The expression for the fault recovery time constraint is:

[0179]

[0180] In the formula, Let be a binary variable representing the diminishing impact of a disaster scenario on the affected transmission line l at time t+RT. This indicates that the transmission line l affected by the disaster before time t was restored at time t+RT. This indicates that transmission line l has no fault recovery process at time t+RT; RT represents the preset recovery time.

[0181] In this embodiment, binary variables I l (t) and Auxiliary variables introduced for describing disaster conditions in this invention:

[0182] (1) Let K be the binary variable representing the recovery of the line fault caused by the typhoon at time t. l (t), if line l recovers at time t after a fault, then K l (t) = 1, otherwise take 0;

[0183] (2) The binary variable I represents the availability of disaster-affected lines under the disaster scenario generated at time t. l (t), if line l is available under the worst-case disaster scenario, then I l (t) = 1, otherwise take 0;

[0184] (3) The binary variable X represents the fault in the affected line. l (t), if line l fails, then X l (t) = 1, otherwise take 0.

[0185] X l (t) satisfies the probability of transmission line l failure at time t. l The Bernoulli distribution of (t) is as follows:

[0186] X l (t)~B(1,Prob l (t));

[0187] The above variables need to satisfy the following constraints:

[0188] A probability threshold Π is set to determine whether the transmission line is damaged due to typhoon disaster:

[0189]

[0190] The maximum total number of transmission lines that fail simultaneously due to a disaster:

[0191]

[0192] In the formula, L represents the set of all lines in the distribution network, and l represents a specific line in the distribution network. Num L OFF represents the total number of distribution network lines. max This represents the maximum total number of failures allowed due to a disaster at any given time.

[0193] The state transition relationship of the line can be expressed by the following formula:

[0194]

[0195] The transmission line will automatically recover from a fault after a certain period of time (RT).

[0196]

[0197] It should be noted that if a line experiences a fault due to a typhoon at time t, it will be restored at time t+RT. However, if the fault probability of the line at time t+RT is still greater than a set threshold, the line will immediately enter a new round of faults at time t+RT while simultaneously restoring the fault at time t. The new round of faults may not be restored until time t+2RT.

[0198] This invention quantifies the operational risk of uncertainties, establishes the relationship between disaster conditions and operational failure probabilities, and achieves a quantitative assessment of the operational risk of disaster-affected distribution networks. This invention models the operational risk of distribution networks under typhoon disasters as a Bernoulli distribution with time-varying parameters, integrates the line fault probability, and introduces disaster-affected faults and recovery into a robust uncertainty set with chance constraints. In subsequent processes, this is used to establish a distribution network reconfiguration model that considers the uncertainty of disaster conditions.

[0199] In a preferred embodiment, constructing a second constraint set for the outer objective function includes:

[0200] For each transmission line in the power distribution network, the wind speed and precipitation at each tower on the transmission line are obtained; the transmission line is divided into several segments, and the wind speed and precipitation at each segment are obtained.

[0201] Calculate the equivalent wind speed at each tower based on the wind speed and precipitation at each tower location.

[0202] Calculate the probability of tower failure for each tower under disaster scenarios based on the equivalent wind speed at each tower.

[0203] Calculate the segment failure probability of each segment under disaster scenarios based on the wind speed and precipitation at each segment.

[0204] The transmission line failure probability is calculated based on the tower failure probability of all towers and the segment failure probability of all segments on the transmission line.

[0205] Based on the transmission line failure probability, construct the second constraint set;

[0206] The formula for calculating the equivalent wind speed is as follows:

[0207]

[0208] In the formula, V * (r tw (t),t,h d () represents the equivalent wind speed at the tower; t represents the duration of the disaster, denoted as t=0 when the disaster occurs; r tw(t) represents the distance from the tower location to the center of the typhoon; h d The altitude representing the basic wind speed in the affected 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;

[0209] The formula for calculating the tower failure probability is as follows:

[0210]

[0211]

[0212] In the formula, Prob tw,i (t) represents the probability of tower failure 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 x represents tw,i The average value of (t); σ tw,i x represents tw,i The standard deviation of (t);

[0213] The formula for calculating the segment failure probability is as follows:

[0214]

[0215] In the formula, λ sg,j (t) represents the segment failure probability of the j-th segment on the transmission line at time t; L sg V(r) represents the length of the segment; 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 for a segment; a sg b sg c sg and d sg All are preset constants;

[0216] The formula for calculating the probability of transmission line failure is as follows:

[0217]

[0218] In the formula, Prob l (t) represents the probability of failure of transmission line l at time t; n twn represents the total number of poles and towers on the transmission line. sg This indicates the total number of segments on the transmission line.

[0219] 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.

[0220] 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, and v5 = -0.1921 can be taken. The transmission line is divided into several 50m long segments so that each segment is located in the same terrain and has the same typhoon wind speed and precipitation.

[0221] S4. Construct a third set of constraints for the inner objective function; wherein the third set of constraints includes: node power balance constraints, distributed power constraints, energy storage system power constraints, load active power constraints, and auxiliary variable constraints.

[0222] In a preferred embodiment, the expression for the node power balance constraint is:

[0223]

[0224] 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 child nodes in the distribution network that may be linked to a node. To take into account the active power flow between node i and node j at time t after the transmission line is disconnected; This represents the actual load of node i at time t; This represents the active power of the energy storage system at node i at time t; This represents the active power of the distributed power source at node i at time t;

[0225] The expression for the power constraint of the distributed power source is:

[0226]

[0227] In the formula, N represents the maximum active power of the distributed power source at node i; DG This represents the set of nodes in a distribution network that are connected to distributed generation sources.

[0228] The expression for the power constraint of the energy storage system is:

[0229]

[0230] In the formula, This represents the maximum active power of the energy storage system at node i. This represents the maximum active power of the energy storage system at node i. This represents the actual capacity of the energy storage system at node i at time t; N represents the maximum capacity of the energy storage system. ESS This represents the set of nodes in a distribution network that are connected to an energy storage system.

[0231] The expression for the load active power constraint is:

[0232]

[0233] In the formula, P i D Indicates the design load of node i;

[0234] The expression for the auxiliary variable constraint is:

[0235]

[0236] In the formula, p ij (t) represents the active power flow between node i and node j at time t without considering the transmission line disconnection state, if and only if α l (t)=1 and u l When (t) = 1 u l Let u(t) be a binary variable representing the switching state of transmission line l under the worst-case disaster scenario at time t. l (t) = 1 indicates that in the worst-case disaster scenario at time t, the transmission line l is in the open state. l (t) = 0 indicates that in the worst-case disaster scenario at time t, the transmission line l is in the off state; P max This indicates the maximum active power that transmission line l can carry.

[0237] S5. Based on the first constraint set, the second constraint set, and the third constraint set, solve the distribution network reconfiguration model to obtain the target switching state of the transmission line after network reconfiguration when the switching cost of the transmission line is minimized and the load loss is minimized under the worst disaster scenario, and use this as the solution result.

[0238] S6. Based on the solution results, adjust the switching status of the transmission lines in the distribution network.

[0239] In a preferred embodiment, adjusting the switching state of the transmission lines of the distribution network based on the solution result includes:

[0240] Based on the solution results and the actual operating status of the transmission lines at the initial moment under the disaster scenario, a switching adjustment strategy for each transmission line is generated.

[0241] According to the switching adjustment strategy, the switching state of each transmission line is adjusted.

[0242] In this embodiment, during the solution process, the original problem can be equivalently represented as:

[0243] min x∈X a T x+max u∈U min y∈Y b T y;

[0244] stx∈X;

[0245] Y = Y(x, u) = {y ∈ S} y ∶Gy≥h-Ex-Mu};

[0246] In the formula, a T ,b T Let S be the transpose of the coefficient vector of the objective function. G, E, and M are the corresponding linear matrices in the constraints, and h is the corresponding linear vector. y These are constraints in the constraint set Y that are only related to the decision variable y.

[0247] The main question is:

[0248] MP:min x,η a T x+η;

[0249]

[0250]

[0251]

[0252] Ex≥h-Mu ο -Gy ο ;

[0253] The subproblems are:

[0254] SP:max u∈U min y b T y;

[0255] sty∈Y;

[0256] Gy≥h-Ex-Mu;

[0257] To compute and solve the above two-level optimization subproblem, the Karush-Kuhn-Tucker (KKT conditions) equations are added to transform it into a single-level optimization problem:

[0258] SP2:maxb T y;

[0259] sty∈Y,u∈U,z≥0;

[0260] Gy≥h-Ex-Mu u∈U;

[0261] G T z≤b;

[0262]

[0263]

[0264] The solution is iteratively applied until the upper and lower bounds converge, yielding the distribution network reconfiguration strategy. The general process is as follows:

[0265] Iterative initialization. Set the lower bound LB = -∞ and the upper bound UB = +∞. Initialize the iteration count n = 0 and initialize the set of scenarios identified for the subproblem.

[0266] Find the first relaxed solution to the main problem and update the lower bound. Define a worst-case disaster scenario u, solve the main problem in MP representation, 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 .

[0267] Solve for the current x n+1 The subproblems are then solved and the upper bound is updated. The x obtained from the main problem is then used to solve the subproblems. n+1 Find the worst-case scenario u in the subproblems expressed by the substitution-based single-layer optimization problem SP2. n+1 , to obtain the corresponding y n+1 Update the upper bound to UB = a. T x n+1 +b T y n +1 .

[0268] 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 expression, and then solve the u obtained from the subproblems. n+1 and the corresponding y n+1Substitute the values, update the iteration count n = n+1 and the set of identified subproblems O = O∪(n+1), and continue solving the main problem to obtain x. n+1 ,η n+1 Update the lower bound to LB = a. T x n+1 +η n+1 .

[0269] 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 have converged.

[0270] The iterative solution process described above involves continuously solving sub-problems and the main problem through iterative iteration, while minimizing load loss and switching costs. This process continuously narrows down the range of the worst-case scenarios to be considered from the set of possible disaster scenarios. The final convergence result is the worst-case scenario u from the set of possible disaster scenarios and the line operating state α after reconstructing using the strategy of minimizing load loss and switching costs. l α l As a binary variable representing the switching state of each line l after network reconstruction, it takes the value 1 if line l remains on after reconstruction, and 0 otherwise. Let α... l Let A represent a binary variable describing the initial operating state of each line l under the influence of typhoon disaster. l (If line l is in an open state after the disaster, take 1; otherwise, take 0.) By comparison, we can obtain the line number that should be connected or disconnected at each time, which is the network reconstruction strategy at each time.

[0271] According to the embodiments of the present invention, the dynamic risk assessment and switching strategy formulation method considering disaster uncertainty is used to probabilistically model the risk of distribution network operation under typical typhoon extreme disasters, generate scenarios of possible failures of the distribution network under typhoon disasters, and construct an uncertainty set considering the disaster recovery process for the scenario. Based on this, a robust optimization model that minimizes load loss is constructed, and a network reconfiguration strategy that minimizes the switching cost of line switches for the distribution network is formulated to improve the power supply stability under typhoon disasters.

[0272] Example 2

[0273] Please refer to Figure 2 This is a schematic diagram of the structure of a power distribution network reconfiguration device according to an embodiment of the present invention, including: an objective function construction module, a constraint set construction module, a solution module, and an adjustment module;

[0274] The objective function construction module is used to construct a two-stage robust optimization model as a distribution network reconfiguration model, with the first-stage objective function being minimizing the cost of switching transmission lines and the second-stage objective function being minimizing the load loss under the worst disaster scenario. The second-stage objective function is a two-layer optimization function, with the inner objective function minimizing the load loss and the outer objective function maximizing the load loss under the disaster scenario.

[0275] The constraint set construction module is used to construct a first constraint set for the objective function of the first stage; wherein the first constraint set includes: network radial constraints, maximum number of switches constraints, node power balance constraints, distributed 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 a disaster scenario; constructing a second constraint set for the outer objective function; wherein the second constraint set includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transition constraints in a disaster scenario, and failure recovery time constraints; constructing a third constraint set for the inner objective function; wherein the third constraint set includes: node power balance constraints, distributed power constraints, energy storage system power constraints, load active power constraints, and auxiliary variable constraints;

[0276] The solution module is used to solve the power distribution network reconfiguration model based on the first constraint set, the second constraint set, and the third constraint set, and obtain the solution result.

[0277] The adjustment module is used to adjust the switches of the transmission lines of the distribution network according to the solution results.

[0278] Example 3

[0279] Accordingly, this 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. When the processor executes the computer program, it implements the power distribution network reconfiguration method described in the above-described embodiments of the invention.

[0280] Example 4

[0281] Accordingly, embodiments of the present invention provide a storage medium, the storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the power distribution network reconfiguration method described in the above embodiments of the invention.

[0282] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for reconfiguring a power distribution network, characterized in that, include: A two-stage robust optimization model is constructed as the distribution network reconfiguration model, with the first-stage objective function being minimizing the cost of switching transmission lines and the second-stage objective function being minimizing load loss under the worst-case disaster scenario. The second-stage objective function is a two-layer optimization function, with the inner layer minimizing load loss and the outer layer maximizing load loss under disaster scenarios. Minimizing the cost of switching transmission lines is the main problem, while minimizing load loss under the worst-case disaster scenario is the sub-problem. A first set of constraints is constructed for the objective function of the first stage; wherein, the first set of constraints includes: network radial constraints, maximum number of switches constraints, node power balance constraints, distributed 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 under disaster scenarios; A second set of constraints is constructed for the outer objective function; wherein, the second set of constraints includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transition constraints under disaster scenarios, and failure recovery time constraints; A third set of constraints is constructed for the inner objective function; wherein the third set of constraints includes: node power balance constraints, distributed power constraints, energy storage system power constraints, load active power constraints, and auxiliary variable constraints; Based on the first constraint set, the second constraint set, and the third constraint set, the distribution network reconfiguration model is solved to obtain the target switching state of the transmission line after network reconfiguration when the switching cost of the transmission line is minimized and the load loss is minimized under the worst disaster scenario. This is used as the solution result. Based on the solution results, the switching states of the transmission lines in the distribution network are adjusted.

2. The distribution network reconfiguration method as described in claim 1, characterized in that, The first-stage objective function is to minimize the cost of switching transmission lines, and the second-stage objective function is to minimize the load loss under the worst-case disaster scenario. A two-stage robust optimization model is constructed as the distribution network reconfiguration model, comprising: Obtain the following binary variables: the actual operating status of each transmission line in the distribution network under disaster scenarios, the cost of disconnecting the transmission line, the cost of connecting the transmission line, the actual load of each node in the distribution network, and the design load of each node in the distribution network; Based on the binary variables of the actual operating state of each transmission line in the distribution network, the cost of disconnecting the transmission line, and the cost of connecting the transmission line, a function is constructed with the goal of minimizing the switching cost of the transmission line as the objective function for the first stage. Based on the actual load and design load of each node in the distribution network, a function is constructed with the objective of minimizing load loss under the worst disaster scenario, which serves as the objective function for the second stage. Based on the objective functions of the first and second stages, a two-stage robust optimization model is constructed as a reconfiguration model for the distribution network. The expression for the objective function in the first stage is: ； In the formula, The decision variables represent the objective function of the first stage; Represents the first constraint set; This refers to a transmission line in a power distribution network; It represents the set of all transmission lines in a power distribution network; This indicates the cost of the transmission line connection; Indicates the cost of disconnecting the transmission line; To indicate transmission lines At any moment The binary variable representing the switching states after network reconstruction. Indicates transmission line At any moment The switch remains on after network reconstruction. Indicates transmission line At any moment The switch did not remain on after network reconstruction; To indicate transmission lines At any moment A binary variable representing the actual operational state under disaster scenarios. Indicates transmission line At any moment In disaster scenarios, the actual status is "on". Indicates transmission line At any moment In disaster scenarios, the actual status is "off". This represents the sum of load losses at all nodes in the system; The expression for the objective function in the second stage is: ； In the formula, The decision variables represent the outer objective function; Represents the second set of constraints; The decision variables represent the inner objective function; Represents the third constraint set; Indicates a specific moment in time; Indicates the total duration of the power distribution network affected by the disaster; This represents a node in a power distribution network; This represents the set of all nodes in a power distribution network. Represents a node Design load; Represents a node At any moment The actual load; The expression for the distribution network reconfiguration model is as follows: 。 3. The distribution network reconfiguration method as described in claim 1, characterized in that, The expression for the radial constraint of the network is: ； ； In the formula, Indicates a specific moment in time; This represents a node in a power distribution network; This represents a node in a power distribution network; This represents the set of all nodes in a power distribution network. This represents the set of child nodes that may be linked to a node in a distribution network; To represent the first in the distribution network The node and the first Each node at time... A binary variable representing the parent-child relationship. Indicating the first in the distribution network Each node at time... For the first The parent node of each node. Indicating the first in the distribution network Each node at time... Not for the first The parent node of each node; To represent the first in the distribution network The node and the first Each node at time... A binary variable representing the parent-child relationship. Indicating the first in the distribution network Each node at time... For the first The parent node of each node. Indicating the first in the distribution network Each node at time... Not for the first The parent node of each node; To indicate transmission lines At any moment The binary variable representing the switching states after network reconstruction. Indicates transmission line At any moment The switch remains on after network reconstruction. Indicates transmission line At any moment The switch did not remain on after network reconstruction; This refers to a transmission line in a power distribution network; It represents the set of all transmission lines in a power distribution network; The expression for the maximum number of switches constraint is: ； In the formula, To indicate transmission lines At any moment A binary variable representing the actual operational state under disaster scenarios. Indicates transmission line At any moment In disaster scenarios, the actual status is "on". Indicates transmission line At any moment In disaster scenarios, the actual status is "off". This indicates the maximum number of transmission lines whose operating state can be changed in the network reconfiguration strategy. The expression for the node power balance constraint is: ； In the formula, To account for the situation where the transmission line is disconnected at time... Time node and nodes The active power flow between them; Represents a node At any moment The actual load; Represents a node At any moment The active power of the energy storage system; Represents a node At any moment The active power of the distributed power source at that time; The expression for the power constraint of the distributed power source is: ； In the formula, Represents a node Maximum active power of distributed power source; This represents the set of nodes in a distribution network that are connected to distributed generation sources. The expression for the power constraint of the energy storage system is: ； ； In the formula, Represents a node The maximum active power for charging the energy storage system; Represents a node The maximum active power of the energy storage system during discharge; Indicates at time Time node The actual capacity of the energy storage system; Indicates the maximum capacity of the energy storage system; This represents the set of nodes in a distribution network that are connected to an energy storage system. The expression for the power variation constraint of the energy storage system is: ； In the formula, Indicates at time Time node Active power for charging the energy storage system; Indicates at time Time node The active power of the energy storage system during discharge; Represents a node Energy storage system charging efficiency; Represents a node Discharge efficiency of the energy storage system; The expression for the load active power constraint is: ； In the formula, Represents a node Design load; The expression for the auxiliary variable constraint is: ； ； In the formula, For cases where the transmission line is disconnected at time 10:00 Time node and nodes The active power flow between them, if and only if and hour ; To indicate at time Transmission lines in the worst disaster scenarios A binary variable representing the switch state. Indicates at time Transmission lines in the worst disaster scenarios The switch is in the ON state. Indicates at time Transmission lines in the worst disaster scenarios The switch is in the off state; Indicates transmission line The maximum active power it can carry; The expression for the constraint of the iterative algorithm is: ； ； In the formula, Indicates at time Nodes in the worst disaster scenarios The actual load; This represents the total load loss of each node in the system.

4. The distribution network reconfiguration method as described in claim 1, characterized in that, The expression for the transmission line fault probability constraint is: ； In the formula, Indicates a specific moment in time; Indicates transmission line At any moment The time-varying failure probability; The preset time-varying fault probability threshold; To indicate transmission lines At any moment The binary variable of disaster failure, Indicates transmission line At any moment The disaster caused the malfunction. Indicates transmission line At any moment Damaged but not malfunctioning; The expression for the constraint on the number of simultaneously faulty transmission lines is: ； In the formula, To indicate transmission lines At any moment The generated binary variable for disaster availability under disaster scenarios. Indicates transmission line At any moment The generated disaster scenario is affected but still usable. Indicates transmission line At any moment The generated disaster scenario renders the system unusable due to a disaster. This refers to a transmission line in a power distribution network; It represents the set of all transmission lines in a power distribution network; This indicates the total number of transmission lines in the distribution network; This indicates the maximum total number of transmission lines that are allowed to fail due to a disaster at the same time. The expression for the transmission line state transition constraint under the disaster scenario is as follows: ； In the formula, To indicate transmission lines At any moment The generated binary variable for disaster availability under disaster scenarios. Indicates transmission line At any moment The generated disaster scenario is affected but still usable. Indicates transmission line At any moment The generated disaster scenario renders the system unusable due to a disaster. To represent the disaster scene at any given time For the damaged transmission lines The binary variable affecting the decay, Indicates the affected transmission lines At any moment The fault caused by the disaster before RT was restored at time t. Indicates transmission line There is no fault recovery process at time t; The expression for the fault recovery time constraint is: ； In the formula, To represent the disaster scene at any given time For the damaged transmission lines The binary variable affecting the decay, Indicates the affected transmission lines At any moment The malfunction caused by the previous disaster at time t recover, Indicates transmission line At time t There is no fault recovery process; This indicates the preset recovery time.

5. The distribution network reconfiguration method as described in claim 4, characterized in that, The construction of the second constraint set for the outer objective function includes: For each transmission line in the power distribution network, the wind speed and precipitation at each tower on the transmission line are obtained; the transmission line is divided into several segments, and the wind speed and precipitation at each segment are obtained. Calculate the equivalent wind speed at each tower based on the wind speed and precipitation at each tower location. Calculate the probability of tower failure for each tower under disaster scenarios based on the equivalent wind speed at each tower. Calculate the segment failure probability of each segment under disaster scenarios based on the wind speed and precipitation at each segment. The transmission line failure probability is calculated based on the tower failure probability of all towers and the segment failure probability of all segments on the transmission line. Based on the transmission line failure probability, construct the second constraint set; The formula for calculating the equivalent wind speed is as follows: ； In the formula, This indicates the equivalent wind speed at the tower. Indicates the duration of a disaster and records the time when the disaster occurred. ; Indicates the distance from the tower location to the center of the typhoon; The altitude indicating the basic wind speed in the affected area; Indicates the wind speed at the tower; Indicates the amount of precipitation at the tower; , , , , and All are preset constants; The formula for calculating the tower failure probability is as follows: ； ； In the formula, Indicates at time The first time on the transmission line The probability of tower failure for each tower; The auxiliary substitution quantity is defined as the equivalent wind speed. The natural logarithm; express The average value; express Standard deviation; The formula for calculating the segment failure probability is as follows: ； In the formula, Indicates at time The first time on the transmission line The probability of segment failure in each segment; Indicates the length of the segment; Indicates the wind speed at the segment; Indicates the precipitation at a specific segment; Indicates the design wind speed of the segment; Indicates the design precipitation for the segment; , , and All are preset constants; The formula for calculating the probability of transmission line failure is as follows: ； In the formula, Indicates at time Time transmission line The probability of failure; This indicates the total number of poles and towers on the transmission line; This indicates the total number of segments on the transmission line.

6. The distribution network reconfiguration method as described in claim 1, characterized in that, The expression for the node power balance constraint is: ； In the formula, Indicates a specific moment in time; This represents a node in a power distribution network; This represents a node in a power distribution network; This represents the set of all nodes in a power distribution network. This represents the set of child nodes that may be linked to a node in a distribution network; To account for the situation where the transmission line is disconnected at time... Time node and nodes The active power flow between them; Represents a node At any moment The actual load; Represents a node At any moment The active power of the energy storage system; Represents a node At any moment The active power of the distributed power source at that time; The expression for the power constraint of the distributed power source is: ； In the formula, Represents a node Maximum active power of distributed power source; This represents the set of nodes in a distribution network that are connected to distributed generation sources. The expression for the power constraint of the energy storage system is: ； ； In the formula, Represents a node The maximum active power for charging the energy storage system; Represents a node The maximum active power of the energy storage system during discharge; Indicates at time Time node The actual capacity of the energy storage system; Indicates the maximum capacity of the energy storage system; This represents the set of nodes in a distribution network that are connected to an energy storage system. The expression for the load active power constraint is: ； In the formula, Represents a node Design load; The expression for the auxiliary variable constraint is: ； ； In the formula, For cases where the transmission line is disconnected at time 10:00 Time node and nodes The active power flow between them, if and only if and hour ; To indicate at time Transmission lines in the worst disaster scenarios A binary variable representing the switch state. Indicates at time Transmission lines in the worst disaster scenarios The switch is in the ON state. Indicates at time Transmission lines in the worst disaster scenarios The switch is in the off state; Indicates transmission line The maximum active power it can carry.

7. The distribution network reconfiguration method as described in claim 1, characterized in that, The step of adjusting the switching states of transmission lines in the distribution network based on the solution results includes: Based on the solution results and the actual operating status of the transmission lines at the initial moment under the disaster scenario, a switching adjustment strategy for each transmission line is generated. According to the switching adjustment strategy, the switching state of each transmission line is adjusted.

8. A power distribution network reconfiguration device, characterized in that, include: Objective function construction module, constraint set construction 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 reconfiguration model, with the first-stage objective function being minimizing the cost of transmission line switching and the second-stage objective function being minimizing the load loss under the worst-case disaster scenario. The second-stage objective function is a two-layer optimization function, with the inner objective function minimizing the load loss and the outer objective function maximizing the load loss under the disaster scenario. Minimizing the cost of transmission line switching and the second-stage objective function are the main problems, while minimizing the load loss under the worst-case disaster scenario is a sub-problem. The constraint set construction module is used to construct a first constraint set for the objective function of the first stage; wherein the first constraint set includes: network radial constraints, maximum number of switches constraints, node power balance constraints, distributed 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 a disaster scenario; constructing a second constraint set for the outer objective function; wherein the second constraint set includes: transmission line failure probability constraints, simultaneous failure transmission line number constraints, transmission line state transition constraints in a disaster scenario, and failure recovery time constraints; constructing a third constraint set for the inner objective function; wherein the third constraint set includes: node power balance constraints, distributed power constraints, energy storage system power constraints, load active power constraints, and auxiliary variable constraints; The solution module is used to solve the power distribution network reconfiguration model based on the first constraint set, the second constraint set, and the third constraint set, and obtain the solution result. The adjustment module is used to adjust the switches of the transmission lines of the distribution network according to the solution results.

9. A terminal device, characterized in that, The method includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the power distribution network reconfiguration method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device where the storage medium is located to perform the power distribution network reconfiguration method as described in any one of claims 1 to 7.

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