Post-disaster urban power grid line first-aid repair resource scheduling optimization method

Abstract

The invention relates to the technical field of power grid first-aid repair, and discloses a post-disaster urban power grid line first-aid repair resource scheduling optimization method, which comprises the following steps: step 1, collecting network topology structure information of a power system, obtaining line damage information of the power system, and collecting the existing line first-aid repair resource reserve condition of each warehouse; step 2, calculating scheduling time from each warehouse node to a damaged line, and establishing a post-disaster toughness evaluation index of the urban power grid based on a node load demand; 3, based on the line damage condition of the urban power grid, establishing a post-disaster line repair resource scheduling optimization model; 4, performing linearization processing on nonlinear constraints in the optimization model to obtain a solvable mixed integer linear programming model; and step 5, according to a model solving result, outputting a post-disaster repair resource scheduling optimization strategy of the urban power grid. By adopting the method, the resource scheduling efficiency of the power system in the post-disaster recovery process can be effectively improved, and the toughness and disaster resistance of an urban power grid are enhanced.

Description

Technical Field

[0001] This application relates to the technical field of power grid emergency repair, and specifically to an optimization method for the dispatching of emergency repair resources for urban power grid lines after a disaster. Background Art

[0002] In modern cities, the stability and reliability of the power system are important foundations for ensuring the normal operation of society. However, the frequent occurrence of natural disasters, especially extreme weather such as earthquakes, floods, and typhoons, seriously threatens the power supply in cities. The emergency repair of urban power grid lines after a disaster has become an important task for power companies. How to efficiently dispatch repair resources and quickly restore power supply is an important link in enhancing urban resilience.

[0003] During the emergency repair process after a disaster, power companies usually reserve repair resources in multiple warehouses, including equipment, materials, and manpower. The resource allocation and geographical location of different warehouses have a direct impact on the emergency repair efficiency. Through reasonable resource dispatching, the emergency repair time can be effectively shortened, the recovery cost can be reduced, and the disaster resistance ability of the urban power grid can be improved. When the internal repair resources are insufficient to meet the emergency repair needs, resources need to be allocated from outside. This process involves multiple factors such as resource availability, transportation time, and cost. The rapid dispatching of external resources can significantly improve the emergency repair efficiency, but also requires an effective coordination and communication mechanism to ensure that the resources can arrive quickly and avoid delays caused by improper resource dispatching.

[0004] However, in actual applications, the configuration and dispatching of resources often lack flexibility. Existing strategies fail to fully consider the distribution of resources in different warehouses and their distance relationship with the damaged lines, resulting in low resource dispatching efficiency. In the emergency repair of power grid lines, the repair priorities of different lines have an important impact on the overall resilience of the power system. Prioritizing the repair of lines supplying power to important users (such as hospitals, fire departments, etc.) and critical infrastructure can restore the basic functions of social life in the shortest time. The optimized dispatching method needs to comprehensively consider the importance of the lines, the degree of damage, and the resources required for repair to formulate a scientific priority repair strategy.

[0005] Therefore, the current research on post-disaster resource dispatching strategies fails to comprehensively consider the complex environment of the power grid, resulting in inaccurate and inefficient deployment of post-disaster resources. Therefore, it is necessary to conduct more in-depth and systematic research to formulate a more scientific and practical post-disaster resource dispatching optimization method, so as to enhance the resilience and recovery ability of the urban power system in the face of disasters. Summary of the Invention

[0006] The purpose of this application is to provide an optimization method that can provide a dispatching strategy based on the resources required for line damage and the existing reserves in the warehouse after a disaster, so as to achieve the rapid restoration and resilience improvement of the urban power grid after a disaster.

[0007] To achieve the above object, the present application discloses the following technical solutions: An optimization method for post-disaster urban power grid line repair resource scheduling, the method comprising the following steps:

[0008] Step 1: Collect the network topology structure information of the power system, obtain the network topology and line damage information of the power system, and collect the existing line repair resource reserves in each warehouse;

[0009] Step 2: Calculate the scheduling time from each warehouse node to the damaged line, and establish a post-disaster resilience evaluation index for the urban power grid based on the node load demand;

[0010] Step 3: Based on the line damage situation of the urban power grid, establish an optimization model for post-disaster line repair resource scheduling;

[0011] Step 4: Linearize the non-linear constraints in the post-disaster line repair resource scheduling optimization model to obtain a solvable mixed-integer linear programming model;

[0012] Step 5: According to the result of solving the mixed-integer linear programming model, output the optimized strategy for post-disaster repair resource scheduling of the urban power grid.

[0013] Preferably, in the step 2, the post-disaster resilience evaluation index is used to measure the degree of satisfaction of the power grid with the weighted load demand of each node within a specific time period T after the disaster, which is the integral value of the ratio of the weighted load that can be satisfied within a period of time after the disaster to the weighted load demand of the node.

[0014] Preferably, the post-disaster resilience evaluation index is obtained by the following method:

[0015] Calculate the total weighted load that can be supplied by each warehouse node at each time point t

[0016] Calculate the total weighted load demand corresponding to all power grid nodes

[0017] Calculate the post-disaster resilience evaluation index

[0018] where w n represents the weight of node n, represents the load demand of node n, and d nt represents the load that can be supplied to node n within the time period t.

[0019] Preferably, the objective function of the post-disaster line repair resource scheduling optimization model is to minimize the weighted load not satisfied within a period of time after the disaster, which is expressed as:

[0020] Preferably, the constraint conditions of the post-disaster line repair resource scheduling optimization model include:

[0021] Condition 1: The total amount of resources dispatched from each warehouse to each damaged line does not exceed the existing reserve of the warehouse;

[0022] Condition 2: The total amount of resources supplied to each damaged line can meet its repair requirements;

[0023] Condition 3: At each time point t, the power income and expenditure of the power grid nodes are balanced;

[0024] Condition 4: According to the line status, limit the relationship between the power transmission on the line and the node phase angle difference, so that the line operates within a reasonable electrical range after repair;

[0025] Condition 5: According to the intact or damaged state of the line, limit the power passing through the line within a reasonable capacity range to avoid line overload or abnormal power transmission.

[0026] Condition 5: According to the intact or damaged state of the line, limit the power passing through the line within a reasonable capacity range to avoid line overload or abnormal power transmission.

[0027] Preferably, the constraint conditions of the post-disaster line repair resource scheduling optimization model further include:

[0028] Condition 6: The load demand of the node is greater than or equal to the actual consumption power;

[0029] Condition 7: Define the relationship between the line status variable and the actual and repaired states of the line, so that the representation of the line status is in line with the actual situation;

[0030] Condition 8: When the line repair is completed, the time t is greater than or equal to the sum of the line repair time and the resource scheduling time.

[0031] Preferably, the constraint conditions of the post-disaster line repair resource scheduling optimization model further include:

[0032] Condition 9: When a node is a power generation node, its power generation does not exceed its maximum power generation;

[0033] Condition 10: The amount of resources dispatched from the warehouse and the amount of resources dispatched from outside are not negative;

[0034] Condition 11: The power generation of the node, the operating power of the node, and the transmitted power on the line are not negative.

[0035] Preferably, the constraint conditions of the post-disaster line repair resource scheduling optimization model further include: Condition 12: The line status variable and the repair status variable are 0-1 variables.

[0036] Preferably, the condition 1 is specifically expressed as:

[0037] The condition 2 is specifically expressed as:

[0038] The condition 3 is specifically expressed as

[0039] The condition 4 is specifically expressed as: and

[0040] The condition 5 is specifically expressed as:

[0041] The condition 6 is specifically expressed as:

[0042] The condition 7 is specifically expressed as:

[0043] The condition 8 is specifically expressed as:

[0044] The condition 9 is specifically expressed as: and

[0045] The condition 10 is specifically expressed as:

[0046] The condition 11 is specifically expressed as:

[0047] The condition 12 is specifically expressed as:

[0048] wherein, N represents the set of nodes in the urban power grid; A represents the set of lines; N g represents the set of power generation nodes; T represents the set of time series; O(l) represents the starting node of line l ∈ A; D(l) represents the terminating node of line l ∈ A; δ C represents 1 when the condition C is satisfied, otherwise 0; r i line represents the existing reserve resources of warehouse i ∈ I; represents the repair resources required for the damaged line l ∈ A; x lt represents the reactance of line l ∈ A; represents the upper limit of the allowable capacity of line l ∈ A; m l represents the post-disaster line state, where 0 indicates line damage and 1 indicates the line is intact; ts l represents the repair time required in the case of line l ∈ A being damaged; Denote the time required to dispatch emergency repair resources from warehouse \(i\in I\) to damaged line \(l\in A\); Denote the time required to dispatch emergency repair resources for lines from outside to damaged line \(l\in A\); \(P\) n Denote the maximum power generation of node \(n\in N\); Denote the amount of resources dispatched from warehouse \(i\in I\) to damaged line \(l\in A\); Denote the amount of resources dispatched from outside to damaged line \(l\in A\); \(g\) nt Denote the power generation of node \(n\in N\); \(d\) nt Denote the power consumption of node \(n\in N\); \(f\) lt Denote the amount of electricity passing through line \(l\in A\) during time period \(t\in T\); \(\theta\) nt Denote the phase angle of node \(n\in N\); \(s\) lt Denote the state of line \(l\in A\) during time period \(t\in T\). When it is 1, it means the line is intact or the line repair is completed; otherwise, it is 0; Denote whether the damaged line \(l\in A\) has been repaired during time period \(t\in T\). When it is 1, it means the line repair is completed; otherwise, it is 0.

[0049] 7. The optimized method for dispatching emergency repair resources for urban power grid lines after a disaster according to claim 6, wherein in step 4, the linearization process specifically includes:

[0050] St1: Let Convert condition 8 into:

[0051] St2: Based on the converted result, linearize the equation as follows:

[0052]

[0053] St3: Linearize the equation as follows:

[0054]

[0055] St4: Linearize the equations and respectively as follows:

[0056]

[0057] St5: Complete the linearization process.

[0058] Compared with the prior art, the method for optimizing the dispatching of emergency repair resources for urban power grid lines after disasters in this application can efficiently dispatch repair resources based on the line damage situation and warehouse resource reserves, significantly improving the resilience of the power system during post-disaster recovery. This method comprehensively considers the node load demand of the power system and the distribution of emergency repair resources, providing practical decision-making support for power companies, helping managers quickly restore power supply, and ensuring the normal operation of society. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0060] Figure 1 It is a schematic flow chart of the method for optimizing the dispatching of emergency repair resources for urban power grid lines after disasters provided in this embodiment;

[0061] Figure 2 It is a schematic diagram of an exemplary power system provided in this embodiment;

[0062] Figure 3 It is a schematic diagram of the dispatching strategy for emergency repair resources of urban power grid lines provided in this embodiment;

[0063] Figure 4 It shows the load situation of demand nodes satisfied at different time periods of the urban power grid after disasters provided in this embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0065] In this article, the term "including" is intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such a process, method, article, or device. Without further limitations, the elements defined by the statement "including..." do not exclude the existence of additional identical elements in the process, method, article, or device including the elements.

[0066] Such as Figure 1As shown in the figure, an optimized method for dispatching emergency repair resources of urban power grid lines after a disaster according to the present invention includes the following steps:

[0067] Step 1: Collect the network topology structure information of the urban power grid (load information on network nodes, connection relationships of the network, etc.), obtain the line damage information of the urban power grid (line damage status, emergency repair resources required for damaged lines), and at the same time collect the existing reserve situation of line emergency repair resources in each warehouse;

[0068] In this embodiment, Figure 2 the power system topology structure with 25 nodes shown in

[0069] Figure 2 is used as the analysis object. Nodes 1, 7, and 22 are substation nodes, with a voltage of 1.05Un and an active power of 6.76 MW for the network.

[0070] Table 1

[0071]

[0072]

[0073] Table 2

[0074]

[0075]

[0076] In this embodiment, there are three warehouses. The latitude and longitude positions and warehouse capacities of the three warehouses are shown in Table 3.

[0077] Table 3

[0078] storage_number longitude latitude capacity 1 102.2 29.5 3 2 103.2 30 9 3 102.8 30.6 4

[0079] Step 2: First, calculate the distances from each warehouse node to the damaged lines. Assuming the resource transportation speed is 60 km / h, then calculate the time from each warehouse to the damaged lines. Define the urban power grid post-disaster resilience evaluation index F as the integral value of the ratio of the weighted load that can be satisfied to the weighted load demand of nodes within a certain period of time after the disaster. This index aims to measure the degree to which the power grid can meet the weighted load demands of each node within a specific time period T after the disaster. By calculating the ratio of the total weighted load actually available at all nodes to the total weighted load demand at all nodes at each time point t and integrating over the entire time period T, the closer this ratio is to 1, the better the power grid can meet the load demands of each node after the disaster, and the stronger the resilience. Specifically expressed as:

[0080]

[0081] Among them, w n represents the weight of node n ∈ N, represents the load demand of node n ∈ N, d nt represents the load that can be supplied to node n ∈ N within time period t ∈ T.

[0082] Step 3: Based on the line damage situation of the urban power grid, for the post-disaster line repair resource scheduling optimization model, since disasters may cause some lines to be damaged, which in turn affects the power supply of nodes and makes the load demands of some nodes unable to be met. Therefore, the objective function adopted is to minimize the weighted load that is not satisfied within a certain period after the disaster. This objective function sums the weighted load differences for each time point t and each node n, aiming to find a resource scheduling strategy that minimizes the total sum of the weighted loads not satisfied by all nodes within the entire time period T, so as to ensure the power supply of each node as much as possible and improve the operation performance and recovery ability of the power grid after the disaster. Specifically expressed as:

[0083] In the construction of the post-disaster line repair resource scheduling optimization model, the following constraint conditions are involved:

[0084] Condition 1: The total amount of resources dispatched from each warehouse to each damaged line does not exceed the existing reserves of the warehouse, expressed as: The principle is: The existing reserve resources of warehouse i are limited. This constraint ensures that the total amount of resources dispatched from each warehouse to each damaged line does not exceed the existing reserves of the warehouse, guaranteeing the feasibility and rationality of resource scheduling;

[0085] Condition 2: The total amount of resource supply to each damaged line can meet its repair requirements, expressed as: The principle is: A certain amount of repair resources are required for damaged line l to resume normal operation. This constraint ensures that the total amount of resource supply to each damaged line can meet its repair requirements, ensuring that the line can be effectively repaired;

[0086] Condition 3: At each time point t, the power income and expenditure of the power grid nodes are balanced, expressed as: The principle is: In the operation of the power grid, the power generation power, consumption power of node n, and the power transmission situation of the lines connected to this node need to satisfy the power balance relationship. This constraint ensures that at each time point t, the power income and expenditure of the node are balanced, maintaining the stable operation of the power grid;

[0087] Condition 4: According to the line state, limit the relationship between the power transmission on the line and the phase angle difference of the nodes, so that the line operates within a reasonable electrical range after repair, expressed as: The principle is as follows: By combining two constraint conditions and introducing a large constant M, the relationship between the power transmission on the line and the phase angle difference of the nodes is restricted according to the line state, ensuring that the line operates within a reasonable electrical range and guaranteeing the safe and stable operation of the power grid;

[0088] Condition 5: According to the intact or damaged state of the line, restrict the power passing through the line within a reasonable capacity range to avoid line overload or abnormal power transmission, expressed as: The principle is as follows: This constraint restricts the power passing through the line within a reasonable capacity range according to the intact or damaged state of the line, preventing line overload or abnormal power transmission, and ensuring the safe operation of the line;

[0089] Condition 6: The load demand of the node is greater than or equal to the actual consumption power, expressed as: The principle is that the load demand of node n should be greater than or equal to the actual consumption power. This is because in the operation of the power grid, the power actually supplied to the node cannot exceed its demand, otherwise it will affect the stable operation of the power grid. This constraint reflects the basic requirement for the power supply of the node;

[0090] Condition 7: Define the relationship between the line state variable and the actual state and repair state of the line, so that the representation of the line state is its actual situation, expressed as: The principle is as follows: This constraint condition describes the relationship between the line state variable and the actual state and repair state of the line, ensuring that the representation of the line state conforms to the actual situation and facilitating accurate analysis and calculation in the model;

[0091] Condition 8: When the line repair is completed, the time t is greater than or equal to the sum of the line emergency repair time and the resource scheduling time, expressed as: The principle is as follows: This constraint means that only when the line repair is completed, the time t meets a certain condition, that is, it is greater than or equal to the sum of the line emergency repair time and the resource scheduling time (depending on whether resources are scheduled from the warehouse or externally), ensuring that the time relationship considering resource scheduling and line repair conforms to the actual situation and guaranteeing the rationality of the model;

[0092] Condition 9: When a node is a power generation node, its power generation does not exceed its maximum power generation, expressed as: The principle is: N g represents the set of power generation nodes. For non-power generation nodes its power generation should be 0, while for the power generation node n ∈ N g , its power generation cannot exceed its maximum power generation. These two constraint conditions ensure that the power generation of the power generation node is within a reasonable range, maintaining the power balance and stable operation of the power grid;

[0093] Condition 10: The amounts of resources dispatched from the warehouse and from external sources are not negative, expressed as: The principle is that the amounts of resources dispatched from the warehouse and from external sources cannot be negative, which is a basic physical requirement for resource dispatching to ensure the rationality and feasibility of resource amounts.

[0094] Condition 11: The power generation of a node, the operating power of a node, and the transmitted electricity on a line are not negative, expressed as: The principle is that it conforms to the basic physical laws of power grid operation, ensuring the rationality and stability of power grid operation.

[0095] Condition 12: The line state variable and the repair state variable are 0-1 variables, expressed as: The principle is that it can simply and clearly represent the two states of a line (intact or damaged, repaired or unrepaired), facilitating logical judgment and calculation in the model, and conforming to the conventional setting of such variables in modeling.

[0096] In the above description, N represents the set of nodes in the urban power grid, A represents the set of lines, N g represents the set of power generation nodes, T represents the set of time series, O(l) represents the starting node of line l ∈ A, D(l) represents the terminating node of line l ∈ A, δ C equals 1 when condition C is satisfied, otherwise 0, r i line represents the existing reserve resources of warehouse i ∈ I, represents the emergency repair resources required for damaged line l ∈ A, x lt represents the reactance of line l ∈ A, represents the upper limit of the capacity allowed to pass through line l ∈ A, m l is a 0-1 variable representing the post-disaster line state, 0 indicates the line is damaged, 1 indicates the line is intact, ts l represents the emergency repair time required in the case of line l ∈ A being damaged, represents the time required to dispatch emergency repair resources from warehouse i ∈ I to damaged line l ∈ A, represents the time required to dispatch external line emergency repair resources to damaged line l ∈ A, P n represents the maximum power generation of node n ∈ N, represents the amount of resources dispatched from warehouse i ∈ I to damaged line l ∈ A, represents the amount of resources dispatched from external sources to damaged line l ∈ A, g nt represents the power generation of node n ∈ N, d nt represents the consumption power of node n ∈ N, f lt represents the electricity quantity passing through line l ∈ A during time period t ∈ T, θ ntDenote the phase angle of node n ∈ N, s lt is a 0-1 variable representing the status of line l ∈ A during time period t ∈ T. 1 indicates that the line is intact or the line repair is completed; otherwise, it is 0. is a 0-1 variable representing whether the damaged line l ∈ A has been repaired during time period t ∈ T. 1 indicates that the line repair is completed; otherwise, it is 0.

[0097] Through this model, the optimal post-disaster resource scheduling strategy of the urban power grid can be calculated. However, the non-linear constraints in the model will cause great difficulties in the solution process. Therefore, in step 4, a linearization method is adopted for processing.

[0098] Step 4: Linearize the non-linear constraints in the optimization model, which is specifically expressed as:

[0099] Let Condition 8 is transformed into:

[0100]

[0101] First, linearize the equation as follows:

[0102] The principle is: by introducing a new variable and establishing this inequality relationship, the original non-linear constraint is transformed into a linear form, which is convenient for subsequent model solution. This inequality represents the linear relationship between α lt and the line emergency repair time and resource scheduling time, ensuring the reasonable representation and constraint of the time relationship under different line repair and resource scheduling scenarios.

[0103] The principle is: β l is a reference value calculated based on the line emergency repair time and resource scheduling time. This inequality ensures that α lt does not exceed this reference value, further restricting the value range of α lt and making the linearized constraint more reasonable and accurate.

[0104] The principle is: this inequality, together with the previous two inequalities, constitutes a complete linear constraint on α lt . When the line is not repaired, this inequality ensures that the relationship between α lt and β l and is in line with the actual situation, that is, α lt cannot be less than a specific value, thus accurately describing the constraint relationship of the time variable under different line repair states and ensuring that the linearized constraint can accurately reflect the logic of the original non-linear constraint.

[0105] Secondly, linearize the equation as follows:

[0106] The principle is as follows: indicates whether the situation of dispatching resources from warehouse i to line l occurs. When λ il = 1, it means that there is resource dispatching. By introducing λ il , the maximum function in the original equation is transformed into a linear form, enabling the accurate representation of the relationship between β l and ts l and when considering different warehouse resource dispatching situations, ensuring that the linearized constraints conform to the actual resource dispatching logic.

[0107] The principle is the same as above. This inequality comprehensively considers the impacts of internal and external resource dispatching on β l , ensuring the accuracy of linearization.

[0108] and The principle is as follows: Introduce u i and u 0 as 0-1 variables. Further restrict the value range of β l through these two inequalities to make it more accurate when considering different resource dispatching situations. When u i is 1 or u 0 is 1, they respectively correspond to the situations of dispatching resources from the warehouse or externally. By combining with M (a relatively large constant), ensure that in various situations, the relationship between β l and ts l , or conforms to the actual logic, avoiding unreasonable values.

[0109] The principle is as follows: This inequality ensures that at least one resource dispatching method (from the warehouse or externally) is considered, guaranteeing that no omission occurs in the resource dispatching model and enabling the model to comprehensively cover all possible resource acquisition channels.

[0110]

[0111] Furthermore, linearize the equations and respectively as follows:

[0112]

[0113] Therefore, a mixed-integer optimization model is obtained based on the linearization method, which is specifically expressed as:

[0114]

[0115]

[0116] Through this model, the rapid solution of the post-disaster resource scheduling optimization model for the urban power grid can be achieved.

[0117] Step 5: According to the calculation results in Step 4, output the optimized strategy for the post-disaster repair resource scheduling of the urban power grid, as Figure 3 shown, where the blue line indicates the scheduling of repair resources from the warehouse to the damaged line. The load conditions of the demand nodes in different time periods of the post-disaster urban power grid are as Figure 4 shown. The resilience evaluation result in this embodiment is 0.6152.

[0118] Finally, it should be noted that the above are only the preferred embodiments of the present application and are not used to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster, characterized in that: The method comprises the following steps: Step 1: Collect network topology information of the power system, obtain network topology and line damage information of the power system, and collect the existing line repair resource reserves of each warehouse; Step 2: Calculate the dispatch time from each warehouse node to the damaged line and establish the post-disaster resilience assessment index of the urban power grid based on the node load demand; Step 3: Based on the line damage of the urban power grid, establish a post-disaster line repair resource scheduling optimization model; Step 4: Linearize the nonlinear constraints in the post-disaster line repair resource scheduling optimization model to obtain a solvable mixed integer linear programming model; Step 5: Based on the solution results of the mixed integer linear programming model, output the optimization strategy for dispatching emergency repair resources after the urban power grid disaster.

2. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 1 is characterized in that: In step 2, the post-disaster resilience assessment index is used to measure the degree to which the power grid meets the weighted load demand of each node within a specific time period T after the disaster, which is the integral value of the ratio of the weighted load that can be met within a period of time after the disaster to the weighted load demand of the node.

3. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 2 is characterized in that: The post-disaster resilience assessment indicators are obtained through the following methods: Calculate the total weighted load that each warehouse node can supply at each time point t Calculate the sum of weighted load demands corresponding to all grid nodes Calculating Disaster Resilience Assessment Indicators Among them, w n represents the weight of node n, represents the load demand of node n, d nt represents the load that can be supplied to node n during time period t.

4. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 1 is characterized in that: The objective function of the post-disaster line repair resource scheduling optimization model is to minimize the unmet weighted load within a period of time after the disaster, which is expressed as:

5. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 4 is characterized in that: The constraints of the post-disaster line repair resource scheduling optimization model include: Condition 1: The total amount of resources dispatched from each warehouse to each damaged line does not exceed the existing reserve of the warehouse; Condition 2: The total amount of resources supplied to each damaged line can meet its repair needs; Condition 3: At each time point t, the power balance of the grid nodes is balanced; Condition 4: Limit the relationship between the power transmission on the line and the node phase angle difference according to the line status, so that the line can operate within a reasonable electrical range after emergency repair; Condition 5: Based on the integrity or damage status of the line, limit the amount of electricity passing through the line to a reasonable capacity range to avoid line overload or abnormal power transmission.

6. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 5 is characterized in that: The constraints of the post-disaster line repair resource scheduling optimization model also include: Condition 6: The load demand of the node is greater than or equal to the actual power consumption; Condition 7: The relationship between the line state variables and the actual and repaired state of the line is clarified, so that the line state is represented as its actual state; Condition 8: When the line repair is completed, time t is greater than or equal to the sum of the line repair time and the resource scheduling time.

7. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 6 is characterized in that: The constraints of the post-disaster line repair resource scheduling optimization model also include: Condition 9: When a node is a power generation node, its power generation power does not exceed its maximum power generation capacity; Condition 10: The amount of resources dispatched from the warehouse and the amount of resources dispatched from the outside are not negative; Condition 11: The node's power generation, node operating power, and transmission power on the line are not negative.

8. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 7 is characterized in that: The constraints of the post-disaster line repair resource scheduling optimization model also include: Condition 12: The line state variable and the repair state variable are 0-1 variables.

9. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 8 is characterized in that: The condition 1 is specifically expressed as: The condition 2 is specifically expressed as: The condition 3 is specifically expressed as The condition 4 is specifically expressed as: and The condition 5 is specifically expressed as: The condition 6 is specifically expressed as: The condition 7 is specifically expressed as: The condition 8 is specifically expressed as: The condition 9 is specifically expressed as: and The condition 10 is specifically expressed as: The condition 11 is specifically expressed as: The condition 12 is specifically expressed as: Where N represents the node set in the urban power grid; A represents the line set; N g represents the set of power generation nodes; T represents the set of time series; O(l) represents the starting node of line l∈A; D(l) represents the ending node of line l∈A; δ C Indicates when the condition C If satisfied, it is equal to 1, otherwise it is 0; r i line represents the existing reserve resources of warehouse i∈I; represents the repair resources required for the damaged line l∈A; x lt represents the reactance of line l∈A; represents the upper limit of the capacity allowed to pass through line l∈A; m l Indicates the line status after the disaster. When it is 0, it means the line is damaged, and when it is 1, it means the line is intact. l It represents the repair time required when line l∈A is damaged; represents the time required to dispatch emergency repair resources from warehouse i∈I to the damaged line l∈A; represents the time required from external dispatching line repair resources to the damaged line l∈A; P n represents the maximum power generation of node n∈N; represents the amount of resources scheduled from warehouse i∈I to the damaged line l∈A; represents the amount of resources from external scheduling resources to the damaged line l∈A; g nt represents the power generation of node n∈N; d nt represents the power consumption of node n∈N; f lt represents the amount of electricity passing through line l∈A in time period t∈T; θ nt represents the phase angle of node n∈N; s lt Indicates the status of line l∈A in time period t∈T. When it is 1, it means the line is intact or the line repair is completed, otherwise it is 0; Indicates whether the damaged line l∈A has been repaired in the time period t∈T. If it is 1, it means the line repair is complete, otherwise it is 0.

10. The method for optimizing resource scheduling for emergency repair of urban power grid lines after a disaster according to claim 9 is characterized in that: In step 4, the linearization process specifically includes: St1: Order Transform condition 8 into: St2: Based on the transformed results, Eq. Perform linearization: St3: Change the equation Perform linearization: St4: Transform the equation and Linearization is performed separately: St5: Complete linearization processing.

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