Power distribution network emergency repair method and device, terminal equipment and storage medium

Abstract

The invention discloses a power distribution network emergency repair method and device, terminal equipment and a storage medium, and belongs to the technical field of repair recovery after a power distribution network fault. The method comprises the following steps: constructing a power distribution network emergency repair scheme generation model by taking the sum of the maximum node load recovery amount and the fault node recovery amount as an objective function and taking the scheduling state, the path scheduling state and the power distribution network operation parameters of three emergency resources of a mobile transformer, a mobile power supply and a construction team as decision variables; wherein the emergency resources comprise an emergency resource scheduling constraint, a recovery path scheduling constraint and a power distribution network operation constraint which are constructed for the power distribution network emergency repair scheme generation model; and solving the power distribution network emergency repair scheme generation model, generating a repair scheme, and performing repair on the power distribution network. According to the invention, the mobile transformer, the mobile power supply and the construction team emergency resources are creatively fused, efficient cooperation among different emergency resources is realized, and the emergency repair response speed is also improved.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency repair and restoration after distribution network faults, and particularly relates to a distribution network emergency repair method, device, terminal device, and storage medium. Background Art

[0002] Under the background of global climate change, frequent extreme disasters have led to an increase in distribution network faults. Extreme disaster events are becoming more frequent and intense, posing a great challenge to the safe and stable operation of the power grid. In actual distribution network emergency repair and restoration work, previous emergency repair methods usually relied on fixed power equipment and emergency repair personnel. This single response mode is difficult to meet the demand for rapid power restoration. In terms of coordinated emergency repair with multiple resources, although the importance of improving emergency repair efficiency is theoretically recognized, relevant research is scarce, lacking systematic research results and mature practical experience. Different types of emergency repair resources, such as mobile transformers, mobile power supply vehicles, construction teams, etc., often lack an effective linkage mechanism in actual dispatching and are difficult to achieve efficient coordinated operation.

[0003] In summary, traditional emergency repair technologies have the disadvantages of slow response speed and insufficient resource coordination. Summary of the Invention

[0004] The present invention provides a distribution network emergency repair method, device, terminal device, and storage medium to solve the technical problems of slow response speed and insufficient resource coordination in the prior art.

[0005] To solve the above technical problems, an embodiment of the present invention provides a distribution network emergency repair method, including:

[0006] Constructing a distribution network emergency repair plan generation model with the sum of the maximum node load recovery amount and the fault node recovery amount as the objective function, and the emergency resource scheduling state, path scheduling state, and distribution network operation parameters as decision variables; wherein, the emergency resource scheduling state is used to describe the access state of emergency resources; the emergency resources include: mobile transformers, mobile power supplies, and construction teams; the path scheduling state is used to describe the situation of whether the path is used as a recovery path; the distribution network operation parameters include: distributed power output, node load recovery amount, line power flow, substation output, mobile transformer output, and node voltage;

[0007] Construct emergency resource scheduling constraints, restoration path scheduling constraints, and distribution network operation constraints for the distribution network emergency repair plan generation model; among them, the emergency resource scheduling constraints are used to constrain the access status, power, output, fault repair status, commissioning status, and movement of emergency resources; the restoration path scheduling constraints are used to constrain the starting point selection of the restoration path, the uniqueness of the restoration path, the flow direction of the restoration path, and the number of upstream nodes of the nodes in the restoration path; the distribution network operation constraints are used to constrain the node voltage, node power, and line power flow capacity in the distribution network;

[0008] Solve the distribution network emergency repair plan generation model to obtain the emergency resource target scheduling status, path target scheduling status, and distribution network target operation parameters;

[0009] Dispatch emergency resources according to the emergency resource target scheduling status; construct a restoration path according to the path target scheduling status; and regulate the distribution network according to the distribution network target operation parameters.

[0010] As an optimal solution, the emergency resource scheduling constraints include: mobile transformer access status constraint, mobile transformer power output constraint, mobile transformer power linear constraint, mobile power access point access quantity constraint, mobile power access point access status constraint, mobile power output constraint, construction team repair status constraint, emergency resource single-point access constraint, emergency resource commissioning status constraint, and emergency resource movement constraint;

[0011] The expression of the mobile transformer access status constraint is:

[0012]

[0013] In the formula, represents the access status of mobile transformer k to substation i at time t, means that mobile transformer k is connected to substation i at time t, means that mobile transformer k is not connected to substation i at time t;

[0014] The expression of the mobile transformer power output constraint is:

[0015]

[0016] In the formula, represents the active power of the mobile transformer connected to substation i at time t; represents the reactive power of the mobile transformer connected to substation i at time t; represents the apparent power upper limit of mobile transformer k;

[0017] The expression of the mobile transformer power linear constraint is:

[0018]

[0019] The expression for the constraint on the number of access points of the mobile power supply is as follows:

[0020]

[0021] In the formula, represents the access status of the access point i of the mobile power supply at time t, represents that the access point i of the mobile power supply is connected to the mobile power supply at time t, represents that the access point i of the mobile power supply is not connected to the mobile power supply at time t; represents the access status of the mobile power supply k and the access point i of the mobile power supply at time t, represents that the mobile power supply k is connected to the access point i of the mobile power supply at time t, represents that the mobile power supply k is not connected to the access point i of the mobile power supply at time t;

[0022] The expression for the constraint on the access status of the access point of the mobile power supply is as follows:

[0023]

[0024] The expression for the constraint on the output of the mobile power supply is as follows:

[0025]

[0026] In the formula, represents the active power output of the mobile power supply connected to the access point i of the mobile power supply at time t; represents the reactive power output of the mobile power supply connected to the access point i of the mobile power supply at time t; represents the upper limit of the active power of the mobile power supply; represents the upper limit of the reactive power of the mobile power supply;

[0027] The expression for the constraint on the repair situation of the construction team is as follows:

[0028]

[0029] In the formula, represents the repair situation of the construction team k for the fault point i at time t, represents that the k-th construction team has completed the repair work for the fault point i at time t, represents that the k-th construction team has not completed the repair work for the fault point i at time t; represents whether the construction team k repairs the fault point i at time t, represents that the construction team k is repairing the fault point i at time t, Indicates that construction team k is not repairing fault point i at time t; Indicates the repair status of fault point i at time t, Indicates that fault point i has been repaired at time t, Indicates that fault point i has not been repaired at time t;

[0030] The expression of the single-point access constraint for emergency resources is:

[0031]

[0032] In the formula, Indicates the access status of emergency resource k and access location i at time t, d indicates that emergency resource k is a mobile power source, c indicates that emergency resource k is a construction team, and MT indicates that emergency resource k is a mobile transformer;

[0033] The expression of the operation status constraint for emergency resources is:

[0034]

[0035] In the formula, Indicates the operation status of emergency resource k at time t, Indicates that emergency resource k has been put into operation at time t, Indicates that emergency resource k has not been put into operation at time t, d indicates that emergency resource k is a mobile power source, c indicates that emergency resource k is a construction team, and MT indicates that emergency resource k is a mobile transformer;

[0036] The expression of the movement constraint for emergency resources is:

[0037]

[0038] In the formula, tr i,j Indicates the movement time from access point i to access point j; tr E,i Indicates the movement time from the emergency resource warehouse E to access point i.

[0039] As a preferred solution, the restoration path scheduling constraint includes: a restoration path start point constraint and a restoration path uniqueness constraint;

[0040] The expression of the restoration path start point constraint is:

[0041]

[0042] In the formula, f i,i,t Indicates whether node i is used as the start point of the restoration path at time t, f i,i,t =1 indicates that node i is the start point of the restoration path at time t, f i,i,t =0 indicates that node i is not the start point of the restoration path at time t; Indicates the access status of mobile transformer k to substation i at time t, Indicates that mobile transformer k is connected to substation i at time t, Indicates that mobile transformer k is not connected to substation i at time t; Indicates the repair situation of fault point i at time t, Indicates that fault point i has been repaired at time t, Indicates that fault point i has not been repaired at time t; Ω S Indicates the set of substations; Ω DG Indicates the set of distributed power sources;

[0043] The expression of the uniqueness constraint of the restoration path is:

[0044]

[0045] In the formula, f i,j,t Indicates whether there is a restoration path from node i to node j at time t, f i,j,t = 1 indicates that there is a restoration path from node i to node j at time t, f i,j,t = 0 indicates that there is no restoration path from node i to node j at time t; o i,j,k Indicates whether the line switch between node i and node j is closed, o i,j,k = 1 indicates that the line switch between node i and node j is closed, o i,j,k = 0 indicates that the line switch between node i and node j is open;

[0046] The expression of the node path flow direction constraint is:

[0047]

[0048] In the formula, N represents the total number of nodes in the distribution network;

[0049] The expression of the upstream node quantity constraint of the nodes in the restoration path is:

[0050]

[0051] As a preferred solution, the distribution network operation constraints include: distributed power source power constraints, node load restoration quantity constraints, line power flow capacity constraints, node power balance constraints, node voltage constraints, and fixed transformer power constraints in substations;

[0052] The expression of the distributed power source power constraint is:

[0053]

[0054] In the formula, Denote the active power output of distributed power source i at time t; Denote the reactive power output of distributed power source i at time t; Denote the upper limit of the active power output of distributed power source i at time t; Denote the upper limit of the reactive power output of distributed power source i at time t;

[0055] The expression of the node load recovery amount constraint is:

[0056]

[0057] In the formula, Denote the load recovery amount of node i at time t; Denote the maximum load demand of node i at time t;

[0058] The expression of the line power flow capacity constraint is:

[0059]

[0060] In the formula, f i,j,t Denote whether there is a recovery path from node i to node j at time t, f i,j,t = 1 indicates that there is a recovery path from node i to node j at time t, f i,j,t = 0 indicates that there is no recovery path from node i to node j at time t; P i.j,t Denote the active power flow on the line from node i to node j at time t; Q i.j,t Denote the reactive power flow on the line from node i to node j at time t; Denote the maximum active power flow capacity of the line from node i to node j; Denote the maximum reactive power flow capacity of the line from node i to node j;

[0061] The expression of the node power balance constraint is:

[0062]

[0063] In the formula, Denote the active power of substation i at time t; Denote the reactive power of substation i at time t; Denote the active power output of the mobile transformer connected to node i at time t; Denote the reactive power output of the mobile transformer connected to node i at time t; Denote the active power output of the mobile power vehicle connected to node i at time t; Denote the reactive power output of the mobile power vehicle connected to node i at time t; k i,tThe load power factor of node i at time t;

[0064] The expression of the node voltage constraint is:

[0065]

[0066] In the formula, U i,t represents the voltage of node i at time t; R i,j is the resistance coefficient of the line between node i and node j; X i,j is the reactance coefficient of the line between node i and node j; U i represents the lower voltage limit of node i; represents the upper voltage limit of node i;

[0067] The expression of the fixed transformer power constraint in the substation is:

[0068]

[0069] In the formula, represents whether substation i is repaired by the construction team at time t, represents that substation i is repaired at time t, represents that substation i is not repaired at time t; represents the upper limit of the active power output of the fixed transformer in substation i, represents the upper limit of the active power output of the fixed transformer in substation i.

[0070] As a preferred solution, the expression of the objective function is:

[0071]

[0072] In the formula, ρ i represents the load weight of node i; represents the load recovery amount of node i at time t; represents the repair situation of the fault point i at time t, represents that the fault point i is repaired at time t, represents that the fault point i is not repaired at time t.

[0073] As a preferred solution, solving the distribution network emergency repair plan generation model to obtain the emergency resource target scheduling status, path target scheduling status and distribution network target operation parameters includes:

[0074] Taking the objective function of maximizing the amount of fault node recovery as the upper-layer model, the decision variables of the upper-layer model as the emergency resource scheduling status and the path scheduling status, the constraints of the upper-layer model as the emergency resource scheduling constraints and the restoration path scheduling constraints, and the objective function of maximizing the amount of node load recovery as the lower-layer model, the decision variables of the lower-layer model as the distribution network operation parameters, and the constraints of the lower-layer model as the distribution network operation constraints, a two-layer solution model corresponding to the distribution network emergency repair plan generation model is constructed;

[0075] Repeat the iterative operation until the objective function of the lower-layer model converges to a preset value, and obtain the target scheduling status of emergency resources, the target scheduling status of paths, and the target operation parameters of the distribution network;

[0076] Among them, the iterative operation includes:

[0077] Solve the current upper-layer model to obtain the solution result of the upper-layer model;

[0078] Based on the solution result of the upper-layer model, solve the lower-layer model to obtain the solution result of the lower-layer model;

[0079] Judge whether the solution result of the lower-layer model satisfies the constraint conditions of the upper-layer model. If so, generate an optimal cutting plane according to the solution result of the lower-layer model. If not, generate a feasible cutting plane according to the solution result of the lower-layer model;

[0080] Add the optimal cutting plane or the feasible cutting plane to the constraint conditions of the upper-layer model and update the upper-layer model.

[0081] As an optimal solution, the expression of the upper-layer model is:

[0082] max x E T x + θ;

[0083] s.t. Ax ≥ b;

[0084] (h - Gx) T *π (v) ≤ θ;

[0085] (h - Gx) T *π (v) ≤ 0;

[0086] x ∈ {1, 0};

[0087] In the formula, x represents the decision variable vector of the upper-layer model; E TThe matrix of value coefficients representing the decision variable vector x; θ is the introduced continuous variable used to approximately optimize the solution result of the lower-level model; A represents the coefficient matrix in front of the decision variable vector x in the constraint conditions of the upper-level model; b represents the constant term matrix of the constraint conditions of the upper-level model; (h - Gx) T *π (v) (h - Gx) T *π (v) ≤ θ represents the optimal cutting plane added in the v-th iteration; (h - Gx)

[0088] The expression of the lower-level model is as follows:

[0089] max y F T y;

[0090] s.t. Gx + Ky ≥ h;

[0091] x = x (v) ;

[0092] y ≥ 0;

[0093] In the formula, y represents the decision variable vector of the lower-level model; F T represents the matrix of value coefficients of the decision variable vector y; G represents the coefficient matrix in front of the decision variable vector x in the constraint conditions of the lower-level model; K represents the coefficient matrix in front of the decision variable vector y in the constraint conditions of the lower-level model; h represents the constant term matrix of the constraint conditions of the lower-level model; x (v) represents the solution result of the upper-level model in the v-th iteration;

[0094] The expression for the objective function of the lower-level model to converge to a preset value is:

[0095] |θ - F T y| < ε;

[0096] In the formula, ε is a preset small constant value.

[0097] Based on the above embodiments, another embodiment of the present invention provides a distribution network emergency repair device, including: a model construction module, a constraint condition construction module, a solution module, and a scheduling module;

[0098] The model construction module is used to construct a model for generating a distribution network emergency repair plan with the sum of the maximum node load recovery amount and the fault node recovery amount as the objective function, and the emergency resource scheduling status, path scheduling status, and distribution network operation parameters as decision variables. Among them, the emergency resource scheduling status is used to describe the access status of emergency resources. The emergency resources include mobile transformers, mobile power supplies, and construction teams. The path scheduling status is used to describe whether a path is used as a recovery path. The distribution network operation parameters include distributed power generation output, node load recovery amount, line power flow, substation output, mobile transformer output, and node voltage.

[0099] The constraint condition construction module is used to construct emergency resource scheduling constraints, recovery path scheduling constraints, and distribution network operation constraints for the model for generating a distribution network emergency repair plan. Among them, the emergency resource scheduling constraints are used to constrain the access status, power, output situation, fault repair situation, commissioning status, and movement situation of emergency resources. The recovery path scheduling constraints are used to constrain the starting point selection situation of the recovery path, the uniqueness of the recovery path, the flow direction of the recovery path, and the number of upstream nodes of the nodes in the recovery path. The distribution network operation constraints are used to constrain the node voltage, node power, and line power flow capacity in the distribution network.

[0100] The solving module is used to solve the model for generating a distribution network emergency repair plan to obtain the target scheduling status of emergency resources, the target scheduling status of paths, and the target operation parameters of the distribution network.

[0101] The scheduling module is used to schedule emergency resources according to the target scheduling status of emergency resources, construct recovery paths according to the target scheduling status of paths, and regulate the distribution network according to the target operation parameters of the distribution network.

[0102] 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. When the processor executes the computer program, it implements the distribution network emergency repair method described in the above embodiments of the present invention.

[0103] Based on the above embodiments, another embodiment of the present invention provides a storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the storage medium is located to execute the distribution network emergency repair method described in the above embodiments of the present invention.

[0104] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0105] When conducting emergency repair of the distribution network, the present invention integrates three mobile emergency resources, namely mobile transformers, mobile power sources, and construction teams, overcomes the shortcomings of traditional technologies that rely on fixed equipment, and improves the repair response speed. The present invention also formulates constraint conditions for the three different emergency resources, avoids resource waste and scheduling chaos, improves resource utilization efficiency, ensures the smooth progress of the repair work, and solves the problem of insufficient resource coordination in traditional technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0106] Figure 1 is a schematic flowchart of a method for emergency repair of a distribution network provided by an embodiment of the present invention;

[0107] Figure 2 is a schematic diagram of the principle of a method for linearizing circular constraints using an inscribed square;

[0108] Figure 3 is a solution block diagram of a two-layer solution model;

[0109] Figure 4 is a schematic diagram of an improved IEEE 69-node test system;

[0110] Figure 5 is a schematic diagram of the scheduling of an emergency repair plan;

[0111] Figure 6 is a comparison chart of calculation time based on Benders decomposition;

[0112] Figure 7 is a schematic structural diagram of a device for emergency repair of a distribution network provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0113] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0114] Embodiment 1

[0115] Please refer to Figure 1 , which is a schematic flowchart of a method for emergency repair of a distribution network provided by an embodiment of the present invention, including:

[0116] S1. Construct a model for generating emergency repair plans for a distribution network, with the sum of maximizing the node load recovery amount and the fault node recovery amount as the objective function, and the emergency resource scheduling status, path scheduling status, and distribution network operation parameters as decision variables. Among them, the emergency resource scheduling status is used to describe the access status of emergency resources. The emergency resources include mobile transformers, mobile power sources, and construction teams. The path scheduling status is used to describe whether a path is used as a recovery path. The distribution network operation parameters include distributed power generation output, node load recovery amount, line power flow, substation output, mobile transformer output, and node voltage.

[0117] In a preferred embodiment, the expression of the objective function F is:

[0118]

[0119] In the formula, ρ i represents the load weight of node i; represents the load recovery amount of node i at time t; represents the repair situation of the fault point i at time t, represents that the fault point i has been repaired at time t, represents that the fault point i has not been repaired at time t.

[0120] It should be noted that in the case of extreme disasters causing faults in the urban distribution network, reasonably deploying three types of emergency resources, namely mobile power sources, construction teams, and mobile transformers, can flexibly adjust the operation mode of the distribution network. This adjustment helps to accelerate the repair process of the distribution network and reduce the load loss at the same time. In this process, the core goal of decision-making is to maximize the sum of the weighted load recovery amount and the fault recovery speed during the emergency repair period.

[0121] S2. Construct emergency resource scheduling constraints, recovery path scheduling constraints, and distribution network operation constraints for the model of generating emergency repair plans for the distribution network. Among them, the emergency resource scheduling constraints are used to restrict the access status, power, output situation, fault repair situation, commissioning status, and movement situation of emergency resources. The recovery path scheduling constraints are used to restrict the starting point selection situation of the recovery path, the uniqueness of the recovery path, the flow direction of the recovery path, and the number of upstream nodes of the nodes in the recovery path. The distribution network operation constraints are used to restrict the node voltage, node power, and line power flow capacity in the distribution network.

[0122] In a preferred embodiment, the emergency resource scheduling constraints include: mobile transformer access status constraints, mobile transformer power output constraints, mobile transformer power linear constraints, mobile power access point access quantity constraints, mobile power access point access status constraints, mobile power output constraints, construction team repair situation constraints, emergency resource single-point access constraints, emergency resource operation status constraints, and emergency resource movement constraints;

[0123] The expression of the mobile transformer access status constraint is:

[0124]

[0125] wherein, represents the access status of mobile transformer k and substation i at time t, means that mobile transformer k is connected to substation i at time t, means that mobile transformer k is not connected to substation i at time t;

[0126] The expression of the mobile transformer power output constraint is:

[0127]

[0128] wherein, represents the active power of the mobile transformer connected to substation i at time t; represents the reactive power of the mobile transformer connected to substation i at time t; represents the apparent power upper limit of mobile transformer k;

[0129] The expression of the mobile transformer power linear constraint is:

[0130]

[0131] The expression of the mobile power access point access quantity constraint is:

[0132]

[0133] wherein, represents the access status of mobile power access point i at time t, means that mobile power access point i is connected to a mobile power at time t, means that mobile power access point i is not connected to a mobile power at time t; represents the access status of mobile power k and mobile power access point i at time t, means that mobile power k is connected to mobile power access point i at time t, means that mobile power k is not connected to mobile power access point i at time t;

[0134] The expression for the access status constraint of the mobile power supply access point is:

[0135]

[0136] The expression for the output constraint of the mobile power supply is:

[0137]

[0138] In the formula, represents the active power output of the mobile power supply connected to the mobile power supply access point i at time t; represents the reactive power output of the mobile power supply connected to the mobile power supply access point i at time t; represents the upper limit of the active power of the mobile power supply; represents the upper limit of the reactive power of the mobile power supply;

[0139] The expression for the repair situation constraint of the construction team is:

[0140]

[0141] In the formula, represents the repair situation of the construction team k for the fault point i at time t, represents that the k-th construction team has completed the repair work for the fault point i at time t, represents that the k-th construction team has not completed the repair work for the fault point i at time t; represents whether the construction team k repairs the fault point i at time t, represents that the construction team k is repairing the fault point i at time t, represents that the construction team k is not repairing the fault point i at time t; represents the repair situation of the fault point i at time t, represents that the fault point i has been repaired at time t, represents that the fault point i has not been repaired at time t;

[0142] The expression for the single-point access constraint of the emergency resources is:

[0143]

[0144] In the formula, represents the access status of the emergency resource k and the access location i at time t, d represents that the emergency resource k is a mobile power supply, c represents that the emergency resource k is a construction team, and MT represents that the emergency resource k is a mobile transformer;

[0145] The expression for the operation status constraint of the emergency resources is:

[0146]

[0147] In the formula, represents the operation status of emergency resource k at time t, indicating that emergency resource k has been put into operation at time t, indicating that emergency resource k has not been put into operation at time t. d represents that emergency resource k is a mobile power source, c represents that emergency resource k is a construction team, and MT represents that emergency resource k is a mobile transformer;

[0148] The expression of the movement constraint of the emergency resource is:

[0149]

[0150] In the formula, tr i,j represents the movement time from access point i to access point j; tr E,i represents the movement time from the emergency resource warehouse E to access point i.

[0151] It should be noted that the present invention innovatively uses mobile transformers as emergency repair resources for the distribution network. In the complex operation framework of the urban distribution network, substation transformers, as core power conversion and distribution equipment, undertake the key tasks of converting high-voltage electrical energy into low-voltage electrical energy suitable for users and stably transmitting it to each load area. Their operating status is directly related to the power supply reliability and stability of the distribution network. Once a transformer fails, the power transmission link of the distribution network will be cut off, resulting in a large area of load power outage.

[0152] To minimize the power outage duration and quickly restore load power supply, temporary mobile transformers, as key equipment for emergency power supply, play an irreplaceable role in the repair and restoration process of the distribution network. It has the advantages of flexible deployment and rapid access, can quickly respond when the substation transformer fails, provide emergency power support for the power outage area, and relieve the imbalance between power supply and demand. The model constraints of mobile transformers are for power output limitation and access status limitation.

[0153] In the academic research scope of power system operation optimization, the circular constraint in the traditional transformer power output model has complex non-linear characteristics, which greatly increases the difficulty of solving the optimal power output strategy and severely restricts the improvement of calculation efficiency and accuracy. To overcome this problem, this study innovatively proposes a method of linearizing the circular constraint using a circumscribed square, and the schematic diagram of its principle is as Figure 2As shown in the figure. Based on rigorous mathematical principles, this method ingeniously transforms the circular constraint that is difficult to directly solve into a linear constraint form that is convenient for calculation. It not only effectively simplifies complex mathematical operations but also significantly improves the calculation efficiency and accuracy of optimizing the power output of transformers under multi-variable coupling and complex working conditions. By constructing a circumscribed square constraint, mathematical expressions closely related to the power output of the transformer are established. These expressions accurately describe the quantitative relationship between the circumscribed square constraint and each parameter of the transformer power output, and are constructed into a linear constraint for the mobile transformer power. Avoiding the introduction of non-linear constraints makes the entire calculation model more stable and reliable. When dealing with large-scale distribution network problems, accurate results can be obtained more quickly, providing more powerful support for the actual work such as the optimal operation and fault repair of the distribution network.

[0154] During the process of fault repair in the distribution network, considering that the power outage area cannot resume normal power supply before the repair of the faulty line is completed, mobile power sources are integrated into the multi-type repair resource system as emergency power sources. It can be connected to important loads to ensure the continuity of power supply to users, thereby significantly shortening the load power outage duration. The operation model of the mobile power vehicle contains a series of constraint conditions to ensure its reasonable role in the repair of the distribution network.

[0155] The constraints of the mobile power source are defined from multiple key aspects:

[0156] (1) It is stipulated that only one mobile power vehicle is allowed to be connected to a single mobile power source access point at the same time to avoid resource conflicts and management chaos;

[0157] (2) The access status of the mobile power source access point is clarified to provide a clear basis for overall power distribution;

[0158] (3) The upper limit constraint of the active power output of the mobile power vehicle is set to ensure that its active power output is within a safe and reasonable range;

[0159] (4) The upper limit constraint of the reactive power output of the mobile power vehicle is formulated to ensure that the reactive power output also meets the system operation requirements.

[0160] During the process of carrying out the fault repair work of the distribution network, considering the complexity and urgency of the repair work of the faulty line and the transformer, the repair construction team is incorporated into the multi-type repair resource coordination system as the key execution force. They start from the designated starting point, complete a series of repair tasks of the faulty line and the transformer in an orderly manner and then return to the starting point. Their work efficiency directly affects the time for the distribution network to resume power supply. To ensure the high efficiency and orderliness of the repair construction team's work, a series of rigorous constraint conditions are set when constructing its work model.

[0161] The constraints of the construction team standardize the operation process of the construction team from different levels, specifically including:

[0162] (1) Obtain the status of whether the fault point repair is completed according to the time steps required for repairing the fault point;

[0163] (2) It is clearly stipulated that after the fault repair is completed, the repair status will always be maintained as repaired;

[0164] (3) The equation relationship between the status of the fault point and whether the construction team has completed the repair of the fault point;

[0165] (4) Limit that a single fault is only responsible for being repaired by a unique construction team, avoiding multiple construction teams from repeating operations for the same fault, thereby optimizing resource allocation and improving the emergency repair efficiency.

[0166] Although different types of emergency supplies have their own specific functions and applications, during the repair process of the distribution network, their dispatching processes follow a unified framework. All emergency supplies start from the warehouse starting point and go to each fault point in turn according to the predetermined route to participate in the emergency repair task, and return to the starting point after completing the task. Although the dispatching processes of these emergency supplies are different, they can be integrated through a general model in the emergency resource integration and allocation planning module of the present invention. This model can cover the mobile time factor and optimize resource allocation, thereby improving the overall efficiency of the distribution network repair process.

[0167] The dispatching and access process of emergency vehicles is restricted by several constraint conditions, and these constraint conditions include:

[0168] (1) Single-point access restriction of a single emergency vehicle: At any moment, each emergency vehicle can only be assigned to a specific access point;

[0169] (2) Corresponding relationship between dispatching variables and access status: The relationship between the dispatching decision of the emergency vehicle and the access status;

[0170] (3) Dispatching path and time estimation of emergency vehicles: Describe the path selection and mobile time estimation of emergency vehicles starting from the warehouse and passing through different access points

[0171] In a preferred embodiment, the restoration path dispatching constraints include: restoration path starting point constraint and restoration path uniqueness constraint;

[0172] The expression of the restoration path starting point constraint is:

[0173]

[0174]

[0175] In the formula, f i,i,t represents the situation of whether node i is used as the starting point of the restoration path at time t, f i,i,t= 1 indicates that node i is the starting point of the restoration path at time t, f i,i,t = 0 indicates that node i is not the starting point of the restoration path at time t; represents the connection status of mobile transformer k to substation i at time t, indicates that mobile transformer k is connected to substation i at time t, indicates that mobile transformer k is not connected to substation i at time t; represents the repair situation of fault point i at time t, indicates that fault point i has been repaired at time t, indicates that fault point i has not been repaired at time t; Ω S represents the set of substations; Ω DG represents the set of distributed power sources;

[0176] The expression of the uniqueness constraint of the restoration path is:

[0177]

[0178] In the formula, f i,j,t represents whether there is a restoration path from node i to node j at time t, f i,j,t = 1 indicates that there is a restoration path from node i to node j at time t, f i,j,t = 0 indicates that there is no restoration path from node i to node j at time t; o i,j,k represents whether the line switch between node i and node j is closed, o i,j,k = 1 indicates that the line switch between node i and node j is closed, o i,j,k = 0 indicates that the line switch between node i and node j is open;

[0179] The expression of the node path flow direction constraint is:

[0180]

[0181] In the formula, N represents the total number of nodes in the distribution network;

[0182] The expression of the upstream node quantity constraint of the nodes in the restoration path is:

[0183]

[0184] It should be noted that by analyzing the topological structure, equipment status and load distribution of the distribution network, a reasonable distribution network restoration path is constructed. First, the module starts from the substation or distributed power source and plans the power restoration path. During this process, the power supply to key load areas such as hospitals and transportation hubs is prioritized to ensure that these key facilities resume power supply as soon as possible. By optimizing the restoration path and operating parameters, the power grid restoration can be completed in the shortest time.

[0185] The generation of the distribution network restoration path is a key link in the distribution network fault restoration. By deeply analyzing the topological structure, real-time status of equipment, and load distribution of the distribution network, a scientific and reasonable power restoration path is constructed. When planning the path, the substation or distributed power source is preferentially used as the starting point. For a substation, if it is in normal operation or successfully accesses a mobile transformer, it is eligible to be used as the starting point. From the perspective of the mathematical model, when specific constraints are met, it can be determined as the starting point. For a distributed power source, assuming it has the black start ability and is located in a non-fault area, it can also be used as the starting point of the restoration path to provide power support for important loads and reduce power outage losses. During the path construction process, multiple constraints are set to ensure the rationality and effectiveness of the restoration path. In terms of path uniqueness, it is stipulated that there can be at most one restoration path on a closed line. In terms of the flow direction of the node path, it is required that a distribution network node must have a restoration path flowing in before a restoration path is allowed to flow out. In terms of maintaining the network structure, the radial constraint is used to ensure that the distribution network maintains a tree structure during restoration, so that each node has at most one upstream node of the restoration path. Through these constraints, combined with the starting point selection strategy, a restoration path that provides power support for important loads can be effectively planned, thereby reducing power outage losses.

[0186] In a preferred embodiment, the distribution network operation constraints include: distributed power source power constraint, node load restoration amount constraint, line power flow capacity constraint, node power balance constraint, node voltage constraint, and fixed transformer power constraint in the substation;

[0187] The expression of the distributed power source power constraint is:

[0188]

[0189] In the formula, represents the active power output of distributed power source i at time t; represents the reactive power output of distributed power source i at time t; represents the upper limit of the active power output of distributed power source i at time t; represents the upper limit of the reactive power output of distributed power source i at time t;

[0190] The expression of the node load restoration amount constraint is:

[0191]

[0192] In the formula, represents the load restoration amount of node i at time t; represents the maximum load demand of node i at time t;

[0193] The expression of the line power flow capacity constraint is as follows:

[0194]

[0195] In the formula, f i,j,t represents whether there is a restoration path from node i to node j at time t. f i,j,t = 1 indicates that there is a restoration path from node i to node j at time t. f i,j,t = 0 indicates that there is no restoration path from node i to node j at time t; P i.j,t represents the active power flow on the line from node i to node j at time t; Q i.j,t represents the reactive power flow on the line from node i to node j at time t; represents the maximum active power flow capacity of the line from node i to node j; represents the maximum reactive power flow capacity of the line from node i to node j;

[0196] The expression of the node power balance constraint is as follows:

[0197]

[0198] In the formula, represents the active power of substation i at time t; represents the reactive power of substation i at time t; represents the active output of the mobile transformer connected to node i at time t; represents the reactive output of the mobile transformer connected to node i at time t; represents the active output of the mobile power vehicle connected to node i at time t; represents the reactive output of the mobile power vehicle connected to node i at time t; k i,t is the load power factor of node i at time t;

[0199] The expression of the node voltage constraint is as follows:

[0200]

[0201] In the formula, U i,t represents the voltage of node i at time t; R i,j is the resistance coefficient of the line between node i and node j; X i,j is the reactance coefficient of the line between node i and node j; U i represents the lower voltage limit of node i; represents the upper voltage limit of node i;

[0202] The expression of the fixed transformer power constraint in the substation is:

[0203]

[0204] In the formula, Indicates whether substation i has been repaired by the construction team at time t, Indicates that substation i has been repaired at time t, It means that substation i is not repaired at time t; represents the upper limit of active output of the fixed transformer in substation i, Represents the upper limit of active output of the fixed transformer in substation i.

[0205] It should be noted that the present invention models the constraints such as the output of distributed power sources, line flow, and node voltage in the distribution network. During the recovery of the distribution network, distributed power sources can be used to provide power support for important loads. When the distribution network node is restored, the node load can be restored to power supply and needs to be limited to the maximum load limit. For line flow, line power only exists when there is a recovery path on the line, and it cannot exceed the line flow capacity. During the recovery of the distribution network, for line nodes, it is necessary to ensure the balance of active and reactive power. During the recovery of the distribution network, for line nodes, it is necessary to ensure voltage balance and the voltage must be within the deviation range.

[0206] It should also be noted that the present invention ensures that after a fault occurs, a response and emergency repair can be carried out in the shortest possible time by allowing three types of emergency resources, namely mobile transformers, mobile power supplies and construction teams, to work together efficiently. In-depth research on the characteristics of various resources is conducted to build an effective linkage mechanism to avoid resource waste and scheduling confusion, improve resource utilization efficiency, and give full play to the maximum efficiency of each resource in the emergency repair process.

[0207] S3. Solve the distribution network emergency repair plan generation model to obtain the emergency resource target scheduling state, path target scheduling state and distribution network target operation parameters.

[0208] In a preferred embodiment, solving the distribution network emergency repair plan generation model to obtain the emergency resource target scheduling state, the path target scheduling state and the distribution network target operating parameters includes:

[0209] Taking maximizing the amount of fault node recovery as the objective function of the upper model, taking the emergency resource scheduling state and the path scheduling state as the decision variables of the upper model, taking the emergency resource scheduling constraints and the recovery path scheduling constraints as the constraints of the upper model, taking maximizing the amount of node load recovery as the objective function of the lower model, taking the distribution network operation parameters as the decision variables of the lower model, and taking the distribution network operation constraints as the constraints of the lower model, a two-layer solution model corresponding to the distribution network emergency repair plan generation model is constructed;

[0210] Repeat the iterative operation until the objective function of the lower-layer model converges to a preset value, and obtain the emergency resource target scheduling state, the path target scheduling state, and the distribution network target operating parameters;

[0211] Among them, the iterative operation includes:

[0212] Solve the current upper-layer model to obtain the upper-layer model solution result;

[0213] Based on the upper-layer model solution result, solve the lower-layer model to obtain the lower-layer model solution result;

[0214] Determine whether the lower-layer model solution result satisfies the constraint conditions of the upper-layer model. If so, generate an optimal cutting plane according to the lower-layer model solution result. If not, generate a feasible cutting plane according to the lower-layer model solution result;

[0215] Add the optimal cutting plane or the feasible cutting plane to the constraint conditions of the upper-layer model and update the upper-layer model.

[0216] It should be noted that the present invention uses the Benders Decomposition optimization method to construct a unique two-layer restoration strategy solution model, and its detailed solution framework is as Figure 3 shown. This two-layer structure design is specifically used to overcome the solution difficulties brought by large-scale mixed integer linear programming (MILP) problems in the distribution network fault repair optimization strategy.

[0217] In the upper-layer model part, its core task is to handle the main problem of repair and restoration, and uses integer programming to optimize the repair and restoration plan. In this process, the scheduling and operation of construction teams, mobile power sources, mobile transformers, and line switches are involved. These key decision variables are represented by x and are restricted by the constraints related to the main problem. The upper-layer model focuses on the reasonable allocation of repair tasks and the effective scheduling of resources. These discrete decisions directly affect the overall planning of the repair work. However, since the upper-layer model relaxes the constraint conditions of the lower-layer model during solution, the optimal solution obtained is only an upper bound estimate of the optimal solution of the initial problem. The lower-layer model mainly focuses on the operation optimization of the distribution network, fully considering the impact of source-load fluctuations on the grid operation, and is a linear programming problem. The decision variables of the lower-layer model cover parameters such as node load, line power flow, and voltage that have an important impact on the distribution network operation state. The decision variables of the lower-layer model are: P i,j,t 、Q i,j,t 、 and U i,t , and these variables need to follow the constraints related to the sub-problem.

[0218] The problem of optimizing the emergency repair strategy for distribution networks is a large-scale MILP problem, which is complex to solve. The Benders decomposition method is used to decompose the original problem into an upper layer and a lower layer. The upper layer problem is a mixed integer programming, and the lower layer problem is a linear programming.

[0219] It should also be noted that traditional emergency repair strategy optimization methods, such as experience-based methods or simple mathematical programming methods, are difficult to find the optimal solution or approximate optimal solution in a short time when facing such complex calculation problems, and cannot meet the strict requirements for timeliness in emergency situations. If a scientific and reasonable emergency repair plan cannot be formulated in time, it will further prolong the power outage time and increase economic losses and social impacts. Therefore, the present invention uses the optimization algorithm of Benders Decomposition to calculate the two-layer solution model, breaking through the complex calculation problem. By constructing a two-layer restoration strategy solution model, the upper layer model is responsible for optimizing the emergency repair restoration plan, the lower layer model considers the source-load fluctuation to optimize the operation of the distribution network, and uses the state similarity method to reduce the calculation amount and accelerate the solution efficiency. The upper and lower layer models are iterated with each other. The upper layer provides the solution for the lower layer to guide the operation optimization, and the lower layer feeds back the power flow calculation results to optimize the upper layer solution, quickly generating a scientific, reasonable and feasible emergency repair plan in the emergency scenario, meeting the strict requirements for timeliness and scientificity of the power system emergency repair, and enhancing the resilience and reliability of the power grid.

[0220] In a preferred embodiment, the expression of the upper layer model is:

[0221] max x E T x + θ;

[0222] s.t. Ax ≥ b;

[0223] (h - Gx) T *π (v) ≤ θ;

[0224] (h - Gx) T *π (v) ≤ 0;

[0225] x ∈ {1, 0};

[0226] In the formula, x represents the decision variable vector of the upper layer model; E T represents the value coefficient matrix of the decision variable vector x; θ is the introduced continuous variable, used to approximately optimize the solution result of the lower layer model; A represents the coefficient matrix in front of the decision variable vector x in the constraint condition of the upper layer model; b represents the constant term matrix of the constraint condition of the upper layer model; (h - Gx) T *π (v) ≤ θ represents the optimal cutting plane added in the v-th iteration; (h - Gx) T *π (v)≤0 represents the feasible cutting plane added in the v-th iteration;

[0227] The expression of the lower-layer model is as follows:

[0228] max y F T y;

[0229] s.t. Gx + Ky ≥ h;

[0230] x = x (v) ;

[0231] y ≥ 0;

[0232] In the formula, y represents the decision variable vector of the lower-layer model; F T represents the value coefficient matrix of the decision variable vector y; G represents the coefficient matrix in front of the decision variable vector x in the constraint conditions of the lower-layer model; K represents the coefficient matrix in front of the decision variable vector y in the constraint conditions of the lower-layer model; h represents the constant term matrix of the constraint conditions of the lower-layer model; x (v) represents the solution obtained by solving the upper-layer model in the v-th iteration;

[0233] The expression for the objective function of the lower-layer model to converge to a preset value is:

[0234] |θ - F T y| < ε;

[0235] In the formula, ε is a preset small constant value.

[0236] It should be noted that when the objective function reaches the optimum, the corresponding values of x and y represent the resource scheduling variables and the distribution network operation parameter variables respectively, which intuitively reflect the repair and restoration strategy. Based on the value of x, it is possible to accurately know the location and status of various resources at each time point; and according to the value of y, it is possible to clearly understand the operation status of the distribution network at each moment, such as the output of each unit, etc. Combining x and y constitutes a complete and specific repair and restoration plan, providing comprehensive guidance for emergency repair work.

[0237] In each iteration, the upper-layer model calculates a solution based on the current parameters and constraint conditions and passes it to the lower-layer model as a scheduling strategy. The lower-layer model, based on this scheduling strategy and combined with its own constraint conditions, that is, the relevant constraints of the distribution network operation optimization module, performs distribution network operation optimization calculations. If the lower-layer sub-problem is feasible, an optimal cutting plane will be generated and fed back to the upper-layer model. After receiving this optimal cut, the upper-layer model adds it to its own constraint conditions to form a new upper-layer problem. This new upper-layer problem is further refined and optimized on the original basis, making more accurate plans for the scheduling and operation decisions of resources such as construction teams, mobile power sources, mobile transformers, and line switches.

[0238] As the iteration progresses, the upper-layer model continuously adds the optimal cuts feedback from the lower-layer model, gradually narrowing the search space, making the solution of the upper-layer model closer and closer to the optimal solution of the original problem. Each iteration is an improvement and refinement of the previous result. In the process of continuously adding cuts, the upper-layer model gradually takes into account more actual operating conditions and constraints reflected by the lower-layer model, making the generated scheduling strategy more reasonable and effective.

[0239] In the iteration process, corresponding convergence conditions will be set. When the iteration process meets the set convergence conditions, it means that the interaction between the upper and lower layer models reaches a relatively stable state, and at this time it is considered that a result close enough to the optimal solution of the original problem has been found.

[0240] It should also be noted that in the complex scenario of the emergency repair of the distribution network with mobile transformers linking multiple types of resources, a large number of 0-1 variables and continuous variables are intertwined, resulting in extremely high problem complexity. The Benders decomposition method adopted by this module has significant advantages. This method decomposes the originally large-scale complex problem into an upper-layer model and a lower-layer model, greatly reducing the calculation difficulty and time cost. The upper-layer model focuses on discrete decision-making, mainly responsible for key tasks such as task allocation and resource scheduling, such as reasonably arranging construction teams, allocating mobile power sources and mobile transformers and other resources, and controlling the operation of line switches. The lower-layer model focuses on dealing with the complex constraints in the operation of the power system, such as the capacity constraints of lines, the output of power plants, the volatility of source loads, and the load response characteristics. The upper and lower layer models cooperate closely, and through continuous information interaction and iterative optimization, the amount of calculation is reduced, and a faster emergency repair plan for the distribution network with mobile transformers linking multiple types of resources can be generated.

[0241] S4. Schedule emergency resources according to the emergency resource target scheduling status; construct a restoration path according to the path target scheduling status; and regulate the distribution network according to the distribution network target operating parameters.

[0242] It should be noted that in order to fully verify the effectiveness and reliability of the method for quickly generating the distribution network repair strategy proposed by the present invention, an improved IEEE69-node system is specifically selected as an implementation example, as Figure 4 shown. In this system, 101-103 are substation buses, and distributed power sources are respectively set at nodes 25, 44, and 50. These distributed power sources can play an important role in the restoration process of the distribution network and provide additional power support for some areas.

[0243] Suppose the distribution network is hit by an extreme disaster, resulting in 2 substation failures and 8 line failures in the system, which has a serious impact on power supply. To achieve rapid power outage recovery after distribution network failures and ensure the stability of power supply, 1 mobile transformer vehicle, 1 mobile power supply vehicle and 2 groups of emergency repair teams are deployed to participate in this emergency repair work.

[0244] During this simulated emergency repair process, the entire recovery process is divided into 20 time steps, and each time step is set to 30 minutes. Such a time setting not only meets the time scale requirements in actual emergency repair work but also facilitates detailed simulation and analysis of the emergency repair process. Within each time step, according to the technical solution described in the present invention, each module works in coordination. The data acquisition and preprocessing module collects fault information and system operation data in real time; the scenario construction and feature extraction module quickly constructs the current fault scenario; the similar scenario matching and screening module quickly screens out similar historical scenarios; the emergency repair plan optimization module based on the Benders decomposition two-layer model combines the results of the previous modules to quickly generate and optimize the emergency repair plan, determine the deployment and operation strategies of various emergency resources (mobile transformer vehicle, mobile power supply vehicle, emergency repair team), as well as the distribution network recovery path and operation optimization plan.

[0245] Through the simulated emergency repair of the improved IEEE69-node system under the above fault scenario, data such as the emergency repair progress of each time step, the operation status of the distribution network (such as changes in parameters such as node voltage and line power flow), and the load recovery situation are detailedly recorded and analyzed. Compared with the traditional emergency repair strategy generation method, the method of the present invention shows significant advantages in aspects such as the emergency repair plan generation time, the degree of reduction in power outage time, the improvement effect of power supply reliability, and the reduction amplitude of economic losses, which strongly verifies the effectiveness and superiority of the method proposed in the present invention in actual distribution network fault emergency repair. The generated emergency repair plan is as follows:

[0246] In the post-disaster stage, to effectively restore the power outage load of the distribution network, various resources need to be reasonably dispatched according to the fault scenario. In terms of mobile power supply dispatching, the mobile power supply vehicle M4 is in the microgrid island area where node 25 is located and can be connected to node 22 at time step 3 to provide emergency power support for the surrounding area; the mobile power supply vehicle M5 is located in the microgrid island area where node 44 is located and can be connected to node 40 at time step 4 to ensure the power supply of the power outage load in this area.

[0247] The dispatching of construction teams is also crucial. Construction team 1 will repair F5 and F6 successively. After the repair of fault F5 is completed, by closing line 18 - 19, the connection between nodes 18 - 22 in the islanded microgrid and the main grid can be restored, realizing the restoration of the de - energized load. Construction team 2 will repair faults F7 and F8 successively. After the repair of fault F7 is completed, the connection between nodes 57 - 60 in the islanded microgrid and the main grid can be restored by closing line 56 - 57. Although faults F6 and F8 do not cause load - fault power outages, construction team 1 and construction team 2 will still complete the fault repair work at time step 8 and time step 9 respectively, helping the distribution network to resume its original structure. In addition, during the emergency repair of the post - disaster distribution network, the dispatching schedule of 1 mobile transformer vehicle, 1 mobile power supply vehicle, 1 group of switch operators and 2 groups of construction teams can be drawn according to the actual situation, where the colored squares are used to represent the access time of the mobile power supply and the operation time of the construction teams, and the white squares represent the movement time or the time to return to the maintenance center. The schematic diagram of the emergency repair plan is shown in Figure 5 。

[0248] To verify the effectiveness of the Benders decomposition method in generating the emergency repair plan for the distribution network, a numerical example comparison was made with other optimization methods.

[0249] Optimization method Computation time (s) Only using commercial solver 6502.6s Benders decomposition method 4129.15s

[0250] The above table shows the comparison results of the IEEE69 system. It can be seen from the above table that in terms of calculation time, when only using the commercial solver, the calculation took 6502.6 seconds; when using the Benders decomposition method, the calculation time was 4129.15 seconds. Compared with only using the commercial solver, the Benders decomposition method significantly reduced the calculation time to 63.5% of the original, significantly improving the calculation efficiency. The proportion of the solution time of each part is shown in Figure 6 。

[0251] Example 2

[0252] Please refer to Figure 2 , which is the structural schematic diagram of a distribution network emergency repair device provided by an embodiment of the present invention, including: a model construction module, a constraint condition construction module, a solution module and a dispatching module;

[0253] The model construction module is used to construct a model for generating a distribution network emergency repair plan with the sum of the maximum node load recovery amount and the fault node recovery amount as the objective function, and the emergency resource scheduling status, the path scheduling status, and the distribution network operation parameters as decision variables. Among them, the emergency resource scheduling status is used to describe the access status of emergency resources. The emergency resources include mobile transformers, mobile power supplies, and construction teams. The path scheduling status is used to describe whether a path is used as a recovery path. The distribution network operation parameters include distributed power output, node load recovery amount, line power flow, substation output, mobile transformer output, and node voltage.

[0254] The constraint condition construction module is used to construct emergency resource scheduling constraints, recovery path scheduling constraints, and distribution network operation constraints for the model for generating a distribution network emergency repair plan. Among them, the emergency resource scheduling constraints are used to constrain the access status, power, output, fault repair status, commissioning status, and movement status of emergency resources. The recovery path scheduling constraints are used to constrain the starting point selection of the recovery path, the uniqueness of the recovery path, the flow direction of the recovery path, and the number of upstream nodes of the nodes in the recovery path. The distribution network operation constraints are used to constrain the node voltage, node power, and line power flow capacity in the distribution network.

[0255] The solution module is used to solve the model for generating a distribution network emergency repair plan to obtain the target scheduling status of emergency resources, the target scheduling status of paths, and the target operation parameters of the distribution network.

[0256] The scheduling module is used to schedule emergency resources according to the target scheduling status of emergency resources, construct recovery paths according to the target scheduling status of paths, and regulate the distribution network according to the target operation parameters of the distribution network.

[0257] It should be noted that the device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the attached drawings of the device embodiments provided by the present invention, the connection relationships between the modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement without creative efforts.

[0258] Embodiment III

[0259] 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. When the processor executes the computer program, the method for emergency repair of a distribution network described in the above embodiment of the present invention is implemented.

[0260] Embodiment 4

[0261] Accordingly, an embodiment of the present invention provides a storage medium, which includes a stored computer program. When the computer program runs, the device where the storage medium is located is controlled to execute the method for emergency repair of a distribution network described in the above embodiment of the present invention.

[0262] The terminal device may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory. The processor may be a central processing unit, or may also be other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may also be any conventional processor, etc. The processor is the control center of the device, and connects various parts of the entire device through various interfaces and lines. The memory may be used to store the computer program. The processor realizes various functions of the device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area. Among them, the program storage area may store an operating system, application programs required for at least one function, etc.; the data storage area may store data created according to the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card, a secure digital card, a flash memory card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices. The storage medium is a storage medium, and the computer program is stored in the storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be realized. Among them, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disc, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content included in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

Claims

1. A distribution network emergency repair method, characterized in that: include: Taking the maximum sum of node load recovery and fault node recovery as the objective function, and taking the emergency resource scheduling state, path scheduling state and distribution network operation parameters as decision variables, a distribution network emergency repair plan generation model is constructed; wherein, the emergency resource scheduling state is used to describe the access status of emergency resources; the emergency resources include: mobile transformers, mobile power sources and construction teams; the path scheduling state is used to describe whether the path is used as a recovery path; the distribution network operation parameters include: distributed power supply output, node load recovery, line flow, substation output, mobile transformer output and node voltage; Construct emergency resource scheduling constraints, restoration path scheduling constraints and distribution network operation constraints for the distribution network emergency repair plan generation model; wherein the emergency resource scheduling constraints are used to constrain the access status, power, output, fault repair, commissioning status and movement of emergency resources; the restoration path scheduling constraints are used to constrain the starting point selection of the restoration path, the uniqueness of the restoration path, the flow direction of the restoration path and the number of upstream nodes of the nodes in the restoration path; the distribution network operation constraints are used to constrain the node voltage, node power and line flow capacity in the distribution network; Solving the distribution network emergency repair plan generation model to obtain the emergency resource target scheduling state, the path target scheduling state and the distribution network target operation parameters; According to the emergency resource target scheduling state, emergency resources are dispatched; according to the path target scheduling state, a recovery path is constructed; according to the distribution network target operating parameters, the distribution network is regulated.

2. The distribution network emergency repair method according to claim 1, characterized in that: The emergency resource scheduling constraints include: mobile transformer access status constraints, mobile transformer power output constraints, mobile transformer power linear constraints, mobile power access point access quantity constraints, mobile power access point access status constraints, mobile power output constraints, construction team repair status constraints, emergency resource single point access constraints, emergency resource commissioning status constraints and emergency resource mobility constraints; The expression of the mobile transformer access state constraint is: In the formula, represents the connection status of mobile transformer k and substation i at time t, It means that the mobile transformer k is connected to the substation i at time t. It means that the mobile transformer k is not connected to the substation i at time t; The expression of the mobile transformer power output constraint is: In the formula, represents the active power of the mobile transformer connected to substation i at time t; represents the reactive power of the mobile transformer connected to substation i at time t; represents the upper limit of apparent power of mobile transformer k; The expression of the linear constraint of the mobile transformer power is: The expression of the access quantity constraint of the mobile power access point is: In the formula, represents the access status of mobile power access point i at time t, It means that the mobile power access point i is connected to the mobile power at time t. Indicates that the mobile power access point i is not connected to the mobile power at time t; represents the connection status between mobile power supply k and mobile power supply access point i at time t, It means that the mobile power supply k is connected to the mobile power supply access point i at time t. Indicates that the mobile power supply k is not connected to the mobile power supply access point i at time t; The expression of the access state constraint of the mobile power access point is: The expression of the mobile power output constraint is: In the formula, represents the active output of the mobile power source connected to the mobile power access point i at time t; represents the reactive power output of the mobile power source connected to the mobile power source access point i at time t; Indicates the upper limit of active power of the mobile power supply; Indicates the upper limit of reactive power of mobile power source; The expression of the construction team's repair situation constraint is: In the formula, represents the repair status of the fault point i by the construction team k at time t, It means that the kth construction team has completed the repair work for the fault point i at time t. It means that the kth construction team has not completed the repair work for the fault point i at time t; Indicates whether construction team k repairs fault point i at time t, It means that construction team k is repairing fault point i at time t. It means that construction team k is not repairing fault point i at time t; represents the repair status of fault point i at time t, Indicates that the fault point i has been repaired at time t, Indicates that the fault point i has not been repaired at time t; The expression of the emergency resource single-point access constraint is: In the formula, represents the access status of the emergency resource k and the access location i at time t, d represents that the emergency resource k is a mobile power source, c represents that the emergency resource k is a construction team, and MT represents that the emergency resource k is a mobile transformer; The expression of the emergency resource operation status constraint is: In the formula, represents the operational status of emergency resource k at time t, means that emergency resource k has been put into operation at time t, indicates that the emergency resource k is not put into operation at time t, d indicates that the emergency resource k is a mobile power source, c indicates that the emergency resource k is a construction team, and MT indicates that the emergency resource k is a mobile transformer; The expression of the emergency resource movement constraint is: In the formula, tr i,j represents the travel time from access point i to access point j; tr E,i represents the travel time from the emergency resource warehouse E to the access point i.

3. The distribution network emergency repair method according to claim 1, characterized in that: The restoration path scheduling constraints include: restoration path starting point constraints, restoration path uniqueness constraints, node path flow constraints, and upstream node quantity constraints of nodes in the restoration path; The expression of the starting point constraint of the recovery path is: In the formula, f i,i,t Indicates whether node i is the starting point of the recovery path at time t, f i,i,t =1 means that node i is the starting point of the recovery path at time t, f i,i,t =0 means that node i is not the starting point of the recovery path at time t; represents the connection status of mobile transformer k and substation i at time t, It means that the mobile transformer k is connected to the substation i at time t. It means that the mobile transformer k is not connected to the substation i at time t; represents the repair status of fault point i at time t, Indicates that the fault point i has been repaired at time t, Indicates that the fault point i is not repaired at time t; Ω S represents the substation set; Ω DG represents a collection of distributed power sources; The expression of the recovery path uniqueness constraint is: In the formula, f i,j,t Indicates whether there is a recovery path from node i to node j at time t, f i,j,t =1 indicates that there is a recovery path from node i to node j at time t, f i,j,t =0 means that there is no recovery path from node i to node j at time t; o i,j,k Indicates whether the line switch between node i and node j is closed, o i,j,k =1 means the line switch between node i and node j is closed, o i,j,k =0 means the line switch between node i and node j is disconnected; The expression of the node path flow constraint is: Where N represents the total number of nodes in the distribution network; The expression for the constraint on the number of upstream nodes of the node in the recovery path is:

4. The distribution network emergency repair method according to claim 1, characterized in that: The distribution network operation constraints include: distributed power generation constraints, node load recovery constraints, line flow capacity constraints, node power balance constraints, node voltage constraints and fixed transformer power constraints in substations; The expression of the distributed generation power constraint is: In the formula, represents the active output of distributed generation i at time t; represents the reactive power output of distributed generation i at time t; represents the upper limit of active output of distributed generation i at time t; represents the upper limit of reactive power output of distributed generation i at time t; The expression of the node load recovery constraint is: In the formula, represents the load recovery amount of node i at time t; represents the maximum load demand of node i at time t; The expression of the line power flow capacity constraint is: In the formula, f i,j,t Indicates whether there is a recovery path from node i to node j at time t, f i,j,t =1 indicates that there is a recovery path from node i to node j at time t, f i,j,t = 0 means that there is no recovery path from node i to node j at time t; P i.j,t represents the active power flow on the line from node i to node j at time t; Q i.j,t represents the reactive power flow on the line from node i to node j at time t; represents the maximum active power flow capacity of the line from node i to node j; represents the maximum reactive power flow capacity of the line from node i to node j; The expression of the node power balance constraint is: In the formula, represents the active power of substation i at time t; represents the reactive power of substation i at time t; represents the active output of the mobile transformer connected to node i at time t; represents the reactive power output of the mobile transformer connected to node i at time t; represents the active output of the mobile power vehicle connected to node i at time t; represents the reactive power output of the mobile power vehicle connected to node i at time t; k i,t is the load power factor of node i at time t; The expression of the node voltage constraint is: Where U i,t represents the voltage of node i at time t; R i,j is the resistance coefficient of the line between node i and node j; X i,j is the reactance coefficient of the line between node i and node j; U i represents the lower voltage limit of node i; represents the voltage upper limit of node i; The expression of the fixed transformer power constraint in the substation is: In the formula, Indicates whether substation i has been repaired by the construction team at time t, Indicates that substation i has been repaired at time t, It means that substation i is not repaired at time t; represents the upper limit of active output of the fixed transformer in substation i, Represents the upper limit of active output of the fixed transformer in substation i.

5. The distribution network emergency repair method according to claim 1, characterized in that: The expression of the objective function is: In the formula, ρ i represents the load weight of node i; represents the load recovery amount of node i at time t; represents the repair status of fault point i at time t, Indicates that the fault point i has been repaired at time t, It means that the fault point i has not been repaired at time t.

6. The distribution network emergency repair method according to claim 1, characterized in that: The method of solving the distribution network emergency repair plan generation model to obtain the emergency resource target scheduling state, the path target scheduling state and the distribution network target operation parameters includes: Taking maximizing the amount of fault node recovery as the objective function of the upper model, taking the emergency resource scheduling state and the path scheduling state as the decision variables of the upper model, taking the emergency resource scheduling constraints and the recovery path scheduling constraints as the constraints of the upper model, taking maximizing the amount of node load recovery as the objective function of the lower model, taking the distribution network operation parameters as the decision variables of the lower model, and taking the distribution network operation constraints as the constraints of the lower model, a two-layer solution model corresponding to the distribution network emergency repair plan generation model is constructed; Repeat the iterative operation until the objective function of the lower model converges to the preset value, and obtain the emergency resource target scheduling state, path target scheduling state and distribution network target operation parameters; The iterative operation includes: Solve the current upper model and obtain the solution result of the upper model; Solve the lower model based on the solution result of the upper model to obtain the solution result of the lower model; Determine whether the solution result of the lower model satisfies the constraint conditions of the upper model. If so, generate an optimal cutting plane according to the solution result of the lower model. If not, generate a feasible cutting plane according to the solution result of the lower model. The optimal cutting plane or the feasible cutting plane is added to the constraint condition of the upper model, and the upper model is updated.

7. The distribution network emergency repair method according to claim 6, characterized in that: The expression of the upper model is: max x E T X+θ; stAx ≥ b; (h-Gx) T *p (v) ≤θ; (h-Gx) T *p (v) ≤0; x∈{1,0}； In the formula, x represents the decision variable vector of the upper model; E T represents the value coefficient matrix of the decision variable vector x; θ is the introduced continuous variable used to approximate the optimization result of the lower model; A represents the coefficient matrix in front of the decision variable vector x in the constraint conditions of the upper model; b represents the constant term matrix of the constraint conditions of the upper model; (h-Gx) T *π (v) ≤θ represents the optimal cutting plane added in the vth iteration; (h-Gx) T *π (v) ≤0 indicates the feasible cutting plane added in the vth iteration; The expression of the lower model is: max y F T y; stGx+Ky≥h; x=x (v) ; y≥0； Where y represents the decision variable vector of the lower model; F T represents the value coefficient matrix of the decision variable vector y; G represents the coefficient matrix in front of the decision variable vector x in the constraints of the lower model; K represents the coefficient matrix in front of the decision variable vector y in the constraints of the lower model; h represents the constant term matrix of the constraints of the lower model; x (v) Indicates the solution result of the upper model at the vth iteration; The objective function of the lower model converges to the preset value as follows: |θ-F T y|<e; In the formula, ε is a preset small constant value.

8. A distribution network emergency repair device, characterized in that: include: Model building module, constraint building module, solution module and scheduling module; The model building module is used to build a distribution network emergency repair plan generation model with the maximum sum of the node load recovery amount and the fault node recovery amount as the objective function and the emergency resource scheduling state, path scheduling state and distribution network operation parameters as decision variables; wherein the emergency resource scheduling state is used to describe the access state of emergency resources; the emergency resources include: mobile transformers, mobile power sources and construction teams; the path scheduling state is used to describe whether the path is used as a recovery path; the distribution network operation parameters include: distributed power supply output, node load recovery amount, line flow, substation output, mobile transformer output and node voltage; The constraint condition construction module is used to construct emergency resource scheduling constraints, restoration path scheduling constraints and distribution network operation constraints for the distribution network emergency repair plan generation model; wherein the emergency resource scheduling constraints are used to constrain the access status, power, output status, fault repair status, commissioning status and movement status of emergency resources; the restoration path scheduling constraints are used to constrain the starting point selection of the restoration path, the uniqueness of the restoration path, the flow direction of the restoration path and the number of upstream nodes of the nodes in the restoration path; the distribution network operation constraints are used to constrain the node voltage, node power and line flow capacity in the distribution network; The solution module is used to solve the distribution network emergency repair plan generation model to obtain the emergency resource target scheduling state, the path target scheduling state and the distribution network target operation parameters; The scheduling module is used to schedule emergency resources according to the emergency resource target scheduling state; to build a recovery path according to the path target scheduling state; and to regulate the distribution network according to the distribution network target operating parameters.

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 method for emergency repair of a distribution network as claimed in any one of claims 1 to 7 is implemented.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is executed, the device where the storage medium is located is controlled to execute the distribution network emergency repair method according to any one of claims 1 to 7.

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