A method for improving the resilience of a power distribution network and a terminal

Abstract

The application provides a power distribution network resilience improvement method and a terminal. In a fault repair process, the uncertainty of the power distribution network fault repair time is considered, a weighted minimum power supply shortage is taken as a target, a multi-stage fault recovery model of the power distribution network is established, repair personnel scheduling and mobile emergency power supply vehicle scheduling are taken as optimization variables, and the repair personnel and the mobile emergency power supply vehicle are coordinated and scheduled according to a model solution result. Compared with the prior art which considers the fault repair time as a known condition and ignores the coupling influence process between the post-disaster repair personnel scheduling, the mobile emergency power supply vehicle scheduling and the fault repair time, the application comprehensively considers the uncertainty of the fault repair time and the multi-stage process of the load recovery, ensures the rapid recovery of the key load after the disaster, and thus comprehensively improves the resistance and recovery ability of the power distribution terminal to extreme weather.

Description

Technical Field

[0001] This invention relates to the field of power distribution network technology, and in particular to a method and terminal for improving the resilience of power distribution networks. Background Technology

[0002] In recent years, extreme weather events such as typhoons have become increasingly frequent, causing severe damage to power infrastructure and triggering numerous large-scale power outages. The distribution network, as the final link between the main grid and loads, is crucial for end-users' safe and reliable operation. Therefore, effectively improving the distribution network's ability to cope with extreme weather disasters has become a critical issue that urgently needs to be addressed. Utilizing MEG (Mobile Emergency Power Vehicles) to create autonomous power supply islands after a disaster can effectively reduce the impact of faults and provide favorable conditions for the rapid restoration of critical loads. However, in most cases, it is impossible to accurately estimate the repair time required for each damaged component of the distribution network. The specific repair time for each faulty component can only be obtained after maintenance personnel arrive at the fault location and conduct inspections. Therefore, after an accident, the affected area will dynamically change due to network reconstruction and the fault repair process. Comprehensively considering the coupling effects between MEG (Mobile Emergency Power Vehicle) dispatch, maintenance personnel dispatch, and fault repair processes is of great significance for accelerating the recovery of critical loads. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and terminal for improving the resilience of a power distribution network, taking into account the uncertainty of the repair time of faulty components in the power distribution network, optimizing the coordination and scheduling between power distribution network maintenance personnel and mobile emergency power vehicles, and comprehensively improving the resilience and recovery capabilities of the power distribution network against extreme weather.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0005] A method for improving the resilience of a power distribution network includes:

[0006] Obtain information on the power distribution network, faults, and resources;

[0007] Based on the aforementioned distribution network information, fault information, and resource information, a multi-stage fault recovery model for the distribution network is constructed with the goal of minimizing the weighted power shortage in the distribution network.

[0008] Construct maintenance personnel scheduling constraints, mobile emergency power vehicle scheduling constraints, and fault repair constraints that take into account the uncertainty of fault repair time;

[0009] Based on the aforementioned maintenance personnel scheduling constraints, mobile emergency power vehicle scheduling constraints, and fault repair constraints, the multi-stage fault recovery model of the power distribution network is solved, and the maintenance personnel and mobile emergency power vehicles are coordinated and scheduled according to the solution results.

[0010] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows:

[0011] A distribution network resilience enhancement terminal includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the various steps in the aforementioned distribution network resilience enhancement method.

[0012] The beneficial effects of this invention are as follows: It considers the uncertainty of power distribution network fault repair time during the fault repair process, aims to minimize the weighted power shortage, establishes a multi-stage fault recovery model for the power distribution network, and uses the scheduling of maintenance personnel and mobile emergency power vehicles as optimization variables. Based on the model's solution results, it coordinates the scheduling of maintenance personnel and mobile emergency power vehicles. Compared to existing technologies that treat fault repair time as a known condition and ignore the coupling effect between post-disaster maintenance personnel scheduling, mobile emergency power vehicle scheduling, and fault repair time, this invention comprehensively considers the uncertainty of fault repair time and the multi-stage process of load recovery. By optimizing the scheduling of maintenance personnel for fault repair and coordinating the real-time scheduling of mobile emergency power vehicles to form restorative islands, it ensures the rapid recovery of critical loads after a disaster, thereby comprehensively improving the resilience and recovery capabilities of the power distribution terminal against extreme weather. Attached Figure Description

[0013] Figure 1 A flowchart illustrating the steps of a method for improving the resilience of a power distribution network, as provided in an embodiment of the present invention.

[0014] Figure 2 A flowchart illustrating a method for enhancing the resilience of a power distribution network, as provided in an embodiment of the present invention.

[0015] Figure 3 A dispatch route diagram for maintenance personnel and mobile emergency power supply vehicles is provided in this embodiment of the invention;

[0016] Figure 4 This is a schematic diagram of the structure of a distribution network resilience enhancement terminal provided in an embodiment of the present invention;

[0017] Label Explanation:

[0018] 201. Memory; 202. Processor. Detailed Implementation

[0019] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0020] Please refer to Figure 1 This invention provides a method for improving the resilience of a power distribution network, comprising:

[0021] Obtain information on the power distribution network, faults, and resources;

[0022] Based on the aforementioned distribution network information, fault information, and resource information, a multi-stage fault recovery model for the distribution network is constructed with the goal of minimizing the weighted power shortage in the distribution network.

[0023] Construct maintenance personnel scheduling constraints, mobile emergency power vehicle scheduling constraints, and fault repair constraints that take into account the uncertainty of fault repair time;

[0024] Based on the aforementioned maintenance personnel scheduling constraints, mobile emergency power vehicle scheduling constraints, and fault repair constraints, the multi-stage fault recovery model of the power distribution network is solved, and the maintenance personnel and mobile emergency power vehicles are coordinated and scheduled according to the solution results.

[0025] As described above, the beneficial effects of this invention are as follows: It considers the uncertainty of power distribution network fault repair time during the fault repair process, aims to minimize the weighted power shortage, establishes a multi-stage fault recovery model for the power distribution network, uses the scheduling of maintenance personnel and mobile emergency power vehicles as optimization variables, and coordinates the scheduling of maintenance personnel and mobile emergency power vehicles based on the model's solution results. Compared to existing technologies that consider fault repair time as a known condition and ignore the coupling effect between post-disaster maintenance personnel scheduling, mobile emergency power vehicle scheduling, and fault repair time, this invention comprehensively considers the uncertainty of fault repair time and the multi-stage process of load recovery. By optimizing the scheduling of maintenance personnel for fault repair and coordinating the real-time scheduling of mobile emergency power vehicles to form restorative islands, it ensures the rapid recovery of critical loads after a disaster, thereby comprehensively improving the resilience and recovery capabilities of the power distribution terminal against extreme weather.

[0026] Furthermore, the acquisition of distribution network information, fault information, and resource information specifically includes:

[0027] Obtaining distribution network information includes obtaining distribution network structure parameters;

[0028] Obtaining fault information includes obtaining a set of faulty lines and an uncertain set of fault repair times;

[0029] The resource information obtained includes the initial location of maintenance personnel and mobile emergency power vehicles, as well as the transfer time matrix of maintenance personnel and mobile emergency power vehicles.

[0030] As described above, the maintenance plan is determined by the distribution network structure parameters and the set of faulty lines, while simultaneously obtaining the uncertain set of fault maintenance times to account for the uncertainty of maintenance time. Furthermore, based on the initial positions of maintenance personnel and mobile emergency power vehicles before maintenance and the transfer time matrix, the rationality and effectiveness of scheduling maintenance personnel and mobile emergency power vehicles are coordinated and optimized.

[0031] Furthermore, the construction of a multi-stage fault recovery model for the distribution network based on the distribution network information, fault information, and resource information, with the objective of minimizing the weighted power shortage of the distribution network, specifically includes:

[0032]

[0033] Among them, Ω T This is the set of time periods during the distribution network restoration process, where each time period is Δt minutes; Ω B Let ω be the set of nodes in the distribution network; j Node load weights; The nodes experience active power loss during the recovery process.

[0034] As described above, under the influence of extreme weather, in order to ensure the minimum power supply shortage of the distribution network, while achieving basic power supply, it is possible to ensure the optimal maintenance efficiency, thereby improving the recovery capability of the distribution network.

[0035] Furthermore, the aforementioned constraints for constructing maintenance personnel scheduling are specifically as follows:

[0036]

[0037]

[0038]

[0039] Among them, Ω F For the set of faulty lines; Ω CR Assemble the maintenance team; Ω DE A collection of locations for maintenance personnel's warehouse; Ω RT Ω is the location where the maintenance team can gather. RT =Ω DE ∪Ω F ;α k,m,n Let α be a variable of 0 or 1, representing the transfer path of the maintenance team. If the k-th maintenance team is dispatched from position m to position n, then α kmn =1, otherwise it is 0; Let be a variable of 0 or 1. If the k-th maintenance team was in warehouse m before the disaster, then... Conversely, it is 0.

[0040] As described above, under the influence of extreme weather events, the power distribution system may experience multiple faults simultaneously, leading to large-scale power outages. Therefore, it is necessary to dispatch maintenance personnel to repair damaged components as quickly as possible and restore power supply to the distribution network. In actual fault situations, the number of faulty components often exceeds the number of maintenance teams. The order in which faulty components are repaired affects the speed of post-disaster recovery of the distribution network. Reasonably planning and scheduling the fault repair routes for maintenance personnel can ensure the rapid restoration of critical loads in the distribution network.

[0041] Furthermore, the construction of the mobile emergency power vehicle scheduling constraints specifically includes:

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050]

[0051]

[0052] Among them, Ω MEG For mobile emergency power supply vehicles; Ω M A collection of candidate busbars for mobile emergency power supply vehicles; Ω D A collection of mobile emergency power supply vehicles and warehouses; β k,i,j β is a variable that can be either 0 or 1. If the mobile emergency power supply vehicle k is transferred from bus i to bus j, then β k,i,j =1, otherwise 0; The variable is either 0 or 1. If the mobile emergency power supply vehicle k was in warehouse i before the disaster, then... Conversely, it is 0; δ i The moment when the mobile emergency power supply vehicle connects to bus i; The time required for the mobile emergency power supply vehicle to move from bus i to bus j; r i run μ is the total operating time of the mobile emergency power supply vehicle at bus i; k,i,j Let μ be a variable of 0 or 1. If the mobile emergency power supply vehicle k is put into operation at node i at time t, then μk,i,j =1, otherwise 0.

[0053] As described above, after a fault occurs in a distribution network component, the emergency command center will issue a command to control the circuit breaker to trip and isolate the fault in order to minimize the impact of the fault. Simultaneously, some non-faulty loads lose their connection to the main grid due to the circuit breaker tripping and cannot receive power. Therefore, before the fault is repaired, the emergency command center will dispatch an emergency power supply vehicle to restore power to these loads. Thus, rationally planning and dispatching the mobile emergency power supply vehicle's movement path to provide timely power to non-faulty loads enhances the distribution network's resilience to extreme weather events.

[0054] Furthermore, the construction of fault repair constraints that consider the uncertainty of fault repair time specifically includes:

[0055] If the fault repair time is not obtained, then a fault repair constraint is constructed based on the uncertain time required to repair the fault.

[0056] If the fault repair time is obtained, then fault repair constraints are constructed based on the fault repair time.

[0057] As described above, after extreme weather strikes the power distribution system, multiple faults may occur simultaneously. Before maintenance personnel reach the fault location, fault repair constraints are established based on the uncertain time required to repair the fault. After maintenance personnel arrive at the fault location and obtain the accurate fault repair time through fault detection, fault repair constraints are established based on the accurate repair time of the fault and the uncertain repair times of other faults. This updates the subsequent dispatch plan for maintenance personnel and mobile emergency power vehicles, and simultaneously adjusts the power distribution network operation plan and network reconfiguration plan to promote the rapid recovery of critical loads in the power distribution network.

[0058] Furthermore, if the fault repair time is not obtained, a fault repair constraint is constructed based on the uncertain time required to repair the fault, specifically as follows:

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065] Where M is a sufficiently large positive number; τ m The repair time for faulty line m; The time required for maintenance personnel to move from position m to position n; The uncertain time required to repair fault n; τ0 is the moment when resource scheduling and fault repair measures can begin; U is the uncertain set of fault repair times; and These are the upper and lower bounds of the estimated repair time for the faulty component, respectively; f m,t The variable is either 0 or 1, indicating whether line m is in a fault state at time t during the post-disaster recovery process. If so, then f m,t =1, otherwise 0; Ω T This refers to a set of time periods in the post-disaster recovery process.

[0066] As described above, before obtaining an accurate fault repair time, fault repair constraints are established based on the uncertainty range of the estimated repair time of damaged components, i.e., the upper and lower bounds of the expected fault repair time. This allows for the coordination and scheduling of maintenance personnel and mobile emergency power vehicles, optimizing the maintenance routes of maintenance personnel and the power supply routes of mobile emergency power vehicles, and improving the recovery and resilience of the power distribution network.

[0067] Furthermore, if the fault repair time is obtained, then a fault repair constraint is constructed based on the fault repair time, specifically as follows:

[0068]

[0069]

[0070]

[0071] Where M is a sufficiently large positive number; τ m The repair time for faulty line m; The time required for maintenance personnel to move from position m to position n; τ represents the fault repair time; τ0 represents the moment when resource scheduling and fault repair measures are allowed to begin; U represents the uncertain set of fault repair times. and These represent the upper and lower bounds of the estimated repair time for the faulty component, respectively; Ω F / n represents the set of fault scenarios that do not include fault location n.

[0072] As described above, after obtaining the accurate fault repair time for a fault, its uncertain fault repair time is replaced with a definite fault repair time, while other faults are still represented by uncertain fault repair times. At the same time, the fault locations with already determined fault repair times are removed from the uncertain set. In this way, fault repair constraints at different stages are realized, thereby achieving coordinated scheduling of maintenance personnel and mobile emergency power vehicles at different stages. This achieves multi-stage scheduling that takes into account the uncertainty of fault repair time, ensuring the rapid recovery of critical loads after a disaster.

[0073] Furthermore, the process of coordinating and dispatching maintenance personnel and mobile emergency power vehicles for the power distribution network based on the solution results includes:

[0074] Determine whether the uncertain time still exists in the distribution network fault. If so, return to the step of solving the multi-stage fault recovery model of the distribution network.

[0075] Otherwise, the fault repair of the power distribution network has been completed.

[0076] As described above, when there is still an uncertain time in the distribution network fault, it means that there are still faults in the distribution network to be repaired. Therefore, it is necessary to update the dispatch plan of maintenance personnel and mobile emergency power vehicles in a timely manner so that maintenance personnel and mobile emergency power vehicles can go to the designated location according to the new dispatch plan and repeat the above process until all faults are repaired. In this way, multi-stage dispatch of maintenance personnel and mobile emergency power vehicles can be achieved based on the uncertainty of fault repair time.

[0077] Please refer to Figure 4 Another embodiment of the present invention provides a distribution network resilience enhancement terminal, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements each step of the above-described distribution network resilience enhancement method.

[0078] As described above, the beneficial effects of this invention are as follows: It considers the uncertainty of power distribution network fault repair time during the fault repair process, aims to minimize the weighted power shortage, establishes a multi-stage fault recovery model for the power distribution network, uses the scheduling of maintenance personnel and mobile emergency power vehicles as optimization variables, and coordinates the scheduling of maintenance personnel and mobile emergency power vehicles based on the model's solution results. Compared to existing technologies that consider fault repair time as a known condition and ignore the coupling effect between post-disaster maintenance personnel scheduling, mobile emergency power vehicle scheduling, and fault repair time, this invention comprehensively considers the uncertainty of fault repair time and the multi-stage process of load recovery. By optimizing the scheduling of maintenance personnel for fault repair and coordinating the real-time scheduling of mobile emergency power vehicles to form restorative islands, it ensures the rapid recovery of critical loads after a disaster, thereby comprehensively improving the resilience and recovery capabilities of the power distribution terminal against extreme weather.

[0079] This invention provides a method and terminal for enhancing the resilience of power distribution networks. It can be used to improve fault repair in power distribution systems under extreme weather conditions. Taking into account the uncertainty of repair time for faulty components in the power distribution network, it coordinates and optimizes the dispatching scheme of power distribution network maintenance personnel and mobile emergency power vehicles, accelerating the recovery of critical loads in the power distribution system and enhancing the resilience of the power distribution network to extreme weather. Specific embodiments are described below:

[0080] Please refer to Figures 1 to 3 Embodiment 1 of the present invention is as follows:

[0081] A method for improving the resilience of a power distribution network includes:

[0082] S1. Obtain information on the power distribution network, faults, and resources.

[0083] The above step S1 is specifically as follows:

[0084] S11. Obtaining distribution network information includes obtaining distribution network structure parameters.

[0085] S12. Obtaining fault information includes obtaining a set of faulty lines and an uncertain set of fault repair times.

[0086] S13. Obtaining resource information includes obtaining the initial positions of maintenance personnel and mobile emergency power vehicles, as well as the transfer time matrix of maintenance personnel and mobile emergency power vehicles.

[0087] S2. Based on the aforementioned distribution network information, fault information, and resource information, construct a multi-stage fault recovery model for the distribution network with the objective of minimizing the weighted power shortage of the distribution network.

[0088] The specific steps of S2 above are as follows:

[0089]

[0090] Among them, Ω T This is the set of time periods during the distribution network restoration process, where each time period is Δt minutes; Ω B Let ω be the set of nodes in the distribution network; j Node load weights; The nodes experience active power loss during the recovery process.

[0091] S3. Construct maintenance personnel scheduling constraints, mobile emergency power vehicle scheduling constraints, and fault repair constraints that take into account the uncertainty of fault repair time.

[0092] Under the influence of extreme weather events, power distribution systems may experience multiple faults simultaneously, leading to large-scale power outages. Therefore, it is necessary to dispatch maintenance personnel to repair damaged components as quickly as possible and restore power supply to the distribution network. In actual fault scenarios, the number of faulty components often exceeds the number of maintenance teams. The order in which faulty components are repaired affects the speed of post-disaster recovery of the distribution network. Therefore, it is necessary to rationally plan and schedule maintenance personnel's fault repair paths, i.e., to establish maintenance personnel scheduling constraints, thereby ensuring the rapid restoration of critical loads in the distribution network.

[0093] In step S3 above: S31, constructing maintenance personnel scheduling constraints specifically means:

[0094]

[0095]

[0096]

[0097] Among them, Ω F For the set of faulty lines; Ω CR Assemble the maintenance team; Ω DE A collection of locations for maintenance personnel's warehouse; Ω RT Ω is the location where the maintenance team can gather. RT =Ω DE ∪Ω F ;α k,m,n Let α be a variable of 0 or 1, representing the transfer path of the maintenance team. If the k-th maintenance team is dispatched from position m to position n, then α k,m,n =1, otherwise it is 0; Let be a variable of 0 or 1. If the k-th maintenance team was in warehouse m before the disaster, then... Conversely, it is 0.

[0098] It should be noted that the maintenance personnel scheduling constraint (2) indicates that if the k-th maintenance personnel team is scheduled from position m to position n, then maintenance personnel k should arrive at position m first. The maintenance personnel scheduling constraint (3) stipulates that maintenance personnel must first depart from the warehouse location they were in before the disaster. The maintenance personnel scheduling constraint (4) indicates that each faulty line will be repaired by one maintenance personnel team.

[0099] After a fault occurs in a distribution network component, the emergency command center will issue a command to trip switches to isolate the fault in order to minimize its impact. Simultaneously, some non-faulty loads will lose connection to the main grid due to the switch tripping and will not receive power. Therefore, before the fault is repaired, the emergency command center will rationally dispatch mobile emergency power vehicles to restore power to these non-faulty loads. This establishes mobile emergency power vehicle dispatch constraints to enhance the distribution network's resilience to extreme weather events.

[0100] In step S3 above: S32, constructing the scheduling constraints for the mobile emergency power supply vehicle specifically means:

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111] Among them, Ω MEG For mobile emergency power supply vehicles; Ω M A collection of candidate busbars for mobile emergency power supply vehicles; Ω D A collection of mobile emergency power supply vehicles and warehouses; β k,i,j β is a variable that can be either 0 or 1. If the mobile emergency power supply vehicle k is transferred from bus i to bus j, then β k,i,j =1, otherwise 0; The variable is either 0 or 1. If the mobile emergency power supply vehicle k was in warehouse i before the disaster, then... Conversely, it is 0; δ iThe moment when the mobile emergency power supply vehicle connects to bus i; The time required for the mobile emergency power supply vehicle to move from bus i to bus j; r i run μ is the total operating time of the mobile emergency power supply vehicle at bus i; k,i,j Let μ be a variable of 0 or 1. If the mobile emergency power supply vehicle k is put into operation at node i at time t, then μ k,i,j =1, otherwise 0.

[0112] It should be noted that the mobile emergency power vehicle scheduling constraint (5) indicates that if MEG (mobile emergency power vehicle) k is scheduled from bus i to bus j, then MEG k should first reach bus i. The mobile emergency power vehicle scheduling constraint (6) indicates that MEG can only depart from its candidate warehouse. The mobile emergency power vehicle scheduling constraint (7) is used to prevent self-association of MEG candidate buses. The mobile emergency power vehicle scheduling (8) and (9) indicate that if MEG is transferred from bus i to bus j, then the time when MEG arrives at bus j is equal to the time when MEG arrives at bus i, the transfer time between the two buses ij, and the running time of MEG on bus i. The mobile emergency power vehicle scheduling (10) to (12) indicate that MEG k at δ j to The mobile emergency power supply vehicle is always in operation in the power distribution system, forming an autonomous power supply island. The mobile emergency power supply vehicle dispatch (13) indicates that each MEG is at most on one candidate bus at any given time. The mobile emergency power supply vehicle dispatch (14) is a capacity constraint on the candidate bus of the MEG.

[0113] Therefore, the dispatch routes for maintenance personnel and mobile emergency power vehicles are unknown conditions; that is, the dispatch route for maintenance personnel is determined by α. k,m,n The variable is represented by β, and the dispatch path of the mobile emergency power supply vehicle is determined by β. k,i,j Representing variables can effectively solve the problem of optimal scheduling path planning for post-disaster maintenance personnel and mobile emergency power vehicles.

[0114] Once the emergency command center dispatches a maintenance team to the fault location, the team immediately conducts rapid fault detection, assesses the repair time for the faulty component, and reports this information to the emergency command center. Based on the updated fault repair information, the emergency command center replaces some uncertain repair times with existing, definitive repair times, thus constructing fault repair constraints that account for the uncertainty of repair time. This updates the fault repair paths for subsequent maintenance teams, further optimizes the dispatch of mobile emergency power vehicles, adjusts the operating status of the power distribution system, and accelerates the restoration of critical loads.

[0115] In step S3 above: S33, constructing fault repair constraints that consider the uncertainty of fault repair time specifically means:

[0116] S331. If the fault repair time is not obtained, then construct fault repair constraints based on the uncertain time required to repair the fault.

[0117] The above step S331 is specifically as follows:

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124] Where M is a sufficiently large positive number; τ m The repair time for faulty line m; The time required for maintenance personnel to move from position m to position n; The uncertain time required to repair fault n; τ0 is the moment when resource scheduling and fault repair measures can begin; U is the uncertain set of fault repair times; and These are the upper and lower bounds of the estimated repair time for the faulty component, respectively; f m,t The variable is either 0 or 1, indicating whether line m is in a fault state at time t during the post-disaster recovery process. If so, then f m,t =1, otherwise 0; Ω T This refers to a set of time periods in the post-disaster recovery process.

[0125] It should be noted that the fault repair constraints (15) and (16) are coupled constraints between the scheduling of maintenance personnel and the fault repair time. That is, if the k-th maintenance personnel team moves from position m to position n, then the time when the faulty line n is repaired is equal to the time when the faulty line m is repaired (or the time when the maintenance personnel team departs), the sum of the time required for the maintenance personnel team to move from the faulty line m to n, and the time required to repair the faulty line n. The fault repair constraints (17) and (18) indicate that the faulty line m will be in τ m It was subsequently repaired. Fault repair constraint (19) states that once a faulty line is repaired, no secondary fault will occur during the subsequent recovery process.

[0126] S332. If the fault repair time is obtained, then construct fault repair constraints based on the fault repair time.

[0127] The above step S332 specifically refers to:

[0128]

[0129]

[0130]

[0131] Where M is a sufficiently large positive number; τ m The repair time for faulty line m; The time required for maintenance personnel to move from position m to position n; τ represents the fault repair time; τ0 represents the moment when resource scheduling and fault repair measures are allowed to begin; U represents the uncertain set of fault repair times. and These represent the upper and lower bounds of the estimated repair time for the faulty component, respectively; Ω F / n represents the set of fault scenarios that do not include fault location n.

[0132] It should be noted that the fault repair constraint (21) indicates that the specific fault repair time at fault location n is obtained. Then, the uncertain time required to repair fault n in fault repair constraints (15) and (16) Replaced with a defined fault repair time Fault repair constraint (22) indicates that the specific fault repair time at other fault locations h that were not obtained is... Still using an uncertain time The fault repair constraint (23) indicates that the uncertain time of the fault location n is represented. Remove from the uncertain set U.

[0133] Therefore, in the fault repair constraints, the maintenance personnel scheduling time dimension (i.e. ) and fault repair time dimension (i.e. and This allows the power distribution network to operate in two independent time dimensions, thereby enhancing the flexibility of the power distribution network dispatching process, further promoting the rapid recovery of critical loads in the power distribution network, and strengthening the resilience of the power distribution system.

[0134] S4. Based on the maintenance personnel scheduling constraints, mobile emergency power vehicle scheduling constraints, and fault repair constraints, solve the multi-stage fault recovery model of the power distribution network, and coordinate the scheduling of maintenance personnel and mobile emergency power vehicles for the power distribution network according to the solution results.

[0135] S5. Determine whether the uncertain time still exists in the distribution network fault. If yes, return to step S4; otherwise, the fault repair of the distribution network has been completed.

[0136] It should be noted that after extreme weather strikes the power distribution system, multiple faults may occur simultaneously. After obtaining fault location information, the emergency command center estimates the uncertainty range of repair time for damaged components, i.e. and By utilizing maintenance personnel scheduling constraints and mobile emergency power vehicle scheduling constraints, the scheduling scheme for maintenance personnel to sequentially travel to the fault location to repair damaged components and the scheduling scheme for mobile emergency power vehicles to supply power to non-faulty loads are optimized. After the maintenance personnel arrive at the fault location A, the fault is detected to obtain the accurate fault repair time. Based on the accurate repair time of this fault and the uncertain repair time of other faults, the emergency command center updates the subsequent scheduling schemes for maintenance personnel and mobile emergency power vehicles, and simultaneously adjusts the distribution network operation scheme and network reconfiguration scheme to promote the rapid recovery of critical loads in the distribution network. Specifically, as shown in fault repair constraints (21) and (22), after the emergency command center knows the specific repair time at the fault location A, the uncertain time required to repair fault A in fault repair constraints (15) and (16) is adjusted. Replaced with a defined fault repair time Other fault repair times were not obtained. The fault location B still uses an uncertain time. The time of the fault location A is represented. Meanwhile, as shown in the fault repair constraint (23), the uncertain time of the fault location A is... Removed from the uncertain set U. After the maintenance team repairs the damaged component at fault location A, they proceed to fault location B according to the new scheduling plan, repeating the above process until all faults are repaired. Thus, considering the uncertainty of fault repair time, multi-stage scheduling of maintenance personnel and mobile emergency power vehicles is achieved.

[0137] In some embodiments, such as Figure 3 As shown in the figure, in the actual application scenario, the current distribution network includes 5 faulty lines, 2 maintenance personnel teams, and 2 mobile emergency power vehicles; the uncertain set of fault repair time for the set of faulty lines is shown in Table 1.

[0138] Table 1. Fault Repair Time for Faulted Lines in Distribution Network

[0139] Line 10-15 [80,120] 110 Line 55-56 [70,120] 120 Line 69-70 [90,150] 100 Line 73-77 [70,100] 90 Line 88-89 [60,90] 80

[0140] The multi-stage fault recovery model of the distribution network, constructed based on the aforementioned distribution network information, fault information, and resource information, is then solved. Based on the solution results, maintenance personnel and mobile emergency power vehicles are coordinated and dispatched within the distribution network. Specifically:

[0141] like Figure 3As shown, for safety reasons, resource transfer and fault repair are not allowed during time period t=1. Resource transfer and fault repair are allowed from time period t=2 onwards. Due to the fault at line 69-70, MEG1 cannot supply power to its area, so MEG1 begins to transfer to node 94. During time period t=4, MEG1 transfers to node 94, forming a restorative island. During time period t=5, the faults at lines 10-15 and 69-70 are repaired, and MEG2 begins to transfer to node 79. During time period t=8, MEG2 transfers to node 79, forming a restorative island, and the fault at line 88-89 is repaired. During time period t=9, the fault at line 73-77 is repaired. During time period t=11, the fault at line 55-56 is repaired. At this point, all loads in the distribution network have been restored.

[0142] Please refer to Figure 4 Embodiment two of the present invention is as follows:

[0143] A distribution network resilience enhancement terminal includes a memory 201, a processor 202, and a computer program stored in the memory 201 and running on the processor 202. When the processor 202 executes the computer program, it implements the various steps of the distribution network resilience enhancement method described in Embodiment 1.

[0144] In summary, this invention provides a method and terminal for enhancing the resilience of a power distribution network. After extreme weather events impact the distribution system, multiple faults may occur simultaneously. Upon obtaining the set of faulty lines, the uncertainty range of repair time for damaged components is estimated. Through constraints on maintenance personnel scheduling and mobile emergency power vehicle scheduling, the scheduling scheme for maintenance personnel to sequentially travel to the fault locations to repair damaged components and the scheduling scheme for mobile emergency power vehicles to supply power to non-faulty loads are optimized. Simultaneously, based on the uncertainty of fault repair time, fault repair constraints are constructed. Once maintenance personnel arrive at the fault location, detect the fault, and obtain the accurate fault repair time, the subsequent scheduling schemes for maintenance personnel and mobile emergency power vehicles are updated in a timely manner based on the accurate repair time of this fault and the uncertain repair times of other faults. The distribution network operation scheme and network reconfiguration scheme are adjusted synchronously to promote the rapid recovery of critical loads in the distribution network. That is, after maintenance personnel repair the damaged components at the fault location, they can travel to other fault locations according to the new scheduling scheme, continuously repeating the above process until all faults are repaired. Therefore, by leveraging the uncertainty of fault repair time, multi-stage scheduling of maintenance personnel and mobile emergency power vehicles is achieved to ensure the rapid restoration of critical loads after a disaster, thereby comprehensively improving the power distribution system's resilience and recovery capabilities against extreme weather.

[0145] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for improving the resilience of a power distribution network, characterized in that, include: Obtain information on the power distribution network, faults, and resources; Based on the aforementioned distribution network information, fault information, and resource information, a multi-stage fault recovery model for the distribution network is constructed with the goal of minimizing the weighted power shortage in the distribution network. Construct maintenance personnel scheduling constraints, mobile emergency power vehicle scheduling constraints, and fault repair constraints that take into account the uncertainty of fault repair time; Based on the aforementioned maintenance personnel scheduling constraints, mobile emergency power vehicle scheduling constraints, and fault repair constraints, the multi-stage fault recovery model of the power distribution network is solved, and maintenance personnel and mobile emergency power vehicles are coordinated and scheduled according to the solution results. The construction of fault repair constraints that take into account the uncertainty of fault repair time is specifically as follows: If the fault repair time is not obtained, then a fault repair constraint is constructed based on the uncertain time required to repair the fault. If the fault repair time is obtained, then fault repair constraints are constructed based on the fault repair time; If the fault repair time is not obtained, a fault repair constraint is constructed based on the uncertain time required to repair the fault, specifically: ； ； ； ； ； ； Where M is a sufficiently large positive number; The repair time for faulty line m; The time required for maintenance personnel to move from position m to position n; The indefinite time required to repair fault n; The moment when resource scheduling and fault repair measures are allowed to begin; U is an uncertain set of fault repair times; and These are the upper and lower bounds of the estimated repair time for the faulty component; This is a variable of 0 or 1, indicating whether line m is in a fault state at time t during the post-disaster recovery process. If so, then... Conversely, it is 0; This refers to a set of time periods in the post-disaster recovery process. If the fault repair time is obtained, then a fault repair constraint is constructed based on the fault repair time, specifically as follows: ； ； ； Where M is a sufficiently large positive number; The repair time for faulty line m; The time required for maintenance personnel to move from position m to position n; This refers to the time required for fault repair. The moment when resource scheduling and fault repair measures are allowed to begin; U is an uncertain set of fault repair times; and These are the upper and lower bounds of the estimated repair time for the faulty component; This represents the set of fault scenarios that do not include fault location n; The process of coordinating and dispatching maintenance personnel and mobile emergency power vehicles for the power distribution network based on the solution results includes: Determine whether the uncertain time still exists in the distribution network fault. If so, return to the step of solving the multi-stage fault recovery model of the distribution network. Otherwise, the fault repair of the power distribution network has been completed.

2. The method for improving the resilience of a power distribution network according to claim 1, characterized in that, The acquisition of distribution network information, fault information, and resource information specifically includes: Obtaining distribution network information includes obtaining distribution network structure parameters; Obtaining fault information includes obtaining a set of faulty lines and an uncertain set of fault repair times; The resource information obtained includes the initial location of maintenance personnel and mobile emergency power vehicles, as well as the transfer time matrix of maintenance personnel and mobile emergency power vehicles.

3. A method for improving the resilience of a distribution network according to claim 1 or 2, characterized in that, The multi-stage fault recovery model for the distribution network, constructed based on the distribution network information, fault information, and resource information, with the objective of minimizing the weighted power shortage in the distribution network, is as follows: ； in, This is a set of time periods during the distribution network restoration process, where each time period is... minute; For the set of nodes in the distribution network; Node load weights; The nodes experience active power loss during the recovery process.

4. The method for improving the resilience of a power distribution network according to claim 1, characterized in that, The aforementioned constraints for constructing maintenance personnel scheduling are specifically as follows: ； ； ； in, A set of faulty lines; Assemble the maintenance team; A collection of locations for maintenance personnel's warehouse; Meet at a location accessible to the maintenance team. ; The variable is either 0 or 1, representing the transfer path of the maintenance team. If the k1th maintenance team is dispatched from position m to position n, then... Conversely, it is 0; Let be a variable of 0 or 1. If the k1th maintenance team was in warehouse m before the disaster, then Conversely, it is 0.

5. The method for improving the resilience of a power distribution network according to claim 1, characterized in that, The specific details of constructing the mobile emergency power vehicle scheduling constraints are as follows: ； ； ； ； ； ； ； ； ； ； in, A collection of mobile emergency power supply vehicles; A collection of candidate busbars for mobile emergency power supply vehicles; A collection of mobile emergency power supply vehicles and warehouses; The variable is either 0 or 1. If the mobile emergency power supply vehicle k2 is transferred from bus i to bus j, then... Conversely, it is 0; The variable is either 0 or 1. If the mobile emergency power supply vehicle k2 was in warehouse i before the disaster, then... Conversely, it is 0; The moment when mobile emergency power supply vehicle k2 connects to bus i; The time required for the mobile emergency power supply vehicle to move from bus i to bus j; The total operating time of the mobile emergency power supply vehicle at bus i; Let be a variable of 0 or 1. If the mobile emergency power supply vehicle k2 is put into operation at node i at time t, then Conversely, it is 0.

6. A resilience enhancement terminal for a distribution network, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that the processor, when executing the computer program, implements each step of the method for improving the resilience of a power distribution network as described in any one of claims 1-5.

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