A multi-micronet-power distribution network post-disaster collaborative recovery method and related device

Abstract

This invention discloses a method and related equipment for post-disaster collaborative recovery of a multi-microgrid-distribution network, relating to the field of distribution network control. It includes: acquiring post-disaster faulty component information, maintenance resource information, and multi-microgrid support resource information; dividing the recovery process into multiple recovery periods; and determining the maintenance task arrangement and completion time for each faulty component based on maintenance resources; establishing the repair status of the faulty component within each recovery period based on the completion time; and determining the availability of support resources by combining the electrical connectivity between support resources and the distribution network. Based on this, frequency security opportunity constraints are established and deterministically transformed, only including support resources in an available state in the equivalent frequency support capacity construction, so that the frequency security constraints change dynamically with the recovery progress; and linking the frequency security constraints with distribution network topology reconstruction and multi-microgrid operation scheduling to form a feasible recovery operation domain, thereby determining the maintenance path, network reconstruction scheme, and power supply recovery strategy.

Description

Technical Field

[0001] This invention relates to the field of distribution network control, specifically to a method and related equipment for post-disaster collaborative recovery of multi-microgrid-distribution networks. Background Technology

[0002] Extreme natural disasters or sudden faults may lead to multiple points of damage to the distribution network, power outages in the main grid, and localized islanding operations. Meanwhile, with the integration of multiple microgrids and a high proportion of renewable energy sources, the distribution network has the capability to achieve emergency power supply and resilience enhancement through distributed power sources, energy storage, controllable loads, and grid reconfiguration. However, renewable energy output and load demand exhibit significant random fluctuations, especially during microgrid switching and islanding operations, where system inertia and primary frequency regulation support capabilities are limited, significantly increasing the risk of frequency exceedances. Existing research indicates that transforming frequency opportunity constraints into a deterministic margin for frequency-to-power imbalance based on aggregated parameters such as droop coefficient, equivalent damping coefficient, and equivalent inertia can avoid extensive random sampling calculations and achieve higher solution efficiency.

[0003] On the other hand, the post-disaster recovery process has a strong coupling characteristic of "repair-reconstruction-operation": the arrival time of maintenance personnel and the completion time of repair determine the availability of lines and power sources, which in turn affects the reconfigurable topology of the distribution network and the mutual assistance capability of microgrids. Existing practices often solve the vehicle routing problem (VRP) and the power grid operation scheduling separately. The repair sequence does not consider the frequency over-limit risk of multiple microgrids under low inertia and weak frequency support conditions. The operation scheduling does not utilize the "future repair progress" to configure backup in advance, resulting in (1) the repair sequence is mainly based on the recovery of load or repair time, ignoring the "frequency risk reduction brought about by the improvement of mutual assistance capability"; (2) the operation scheduling lacks consideration of the future repair progress, and the frequency safety constraint is prone to infeasibility or excessively conservative backup, thereby reducing the recovery efficiency. At the same time, the feasibility of frequency opportunity constraints depends on the equivalent frequency support capability (whether primary frequency regulation / energy storage / droop resources are "available"), and "availability" is determined by the repair completion status + network connectivity / topology. Repair / reconstruction decisions will change the frequency constraint margin, and conversely, frequency risk should be included in the repair priority and scheduling model. Therefore, it is necessary to propose a collaborative recovery method that unifies maintenance dispatch, topology reconfiguration, and multi-microgrid operation scheduling into a unified model, and ensures frequency security under uncertainty. Summary of the Invention

[0004] The technical problem this invention aims to solve is that, in the post-disaster recovery process of multi-microgrid-connected distribution networks, existing recovery methods typically handle maintenance scheduling, network reconfiguration, and operational safety constraints separately. This makes it difficult to dynamically reflect the impact of changes in the availability of supporting resources on system frequency security during the uncertain evolution of the gradual repair of faulty components. Consequently, the recovery path arrangement and power supply strategy lack a coordinated response to frequency stability constraints, resulting in conservative recovery decisions or implicit operational risks. The purpose is to provide a multi-microgrid-distribution network post-disaster collaborative recovery method and related equipment, which solves the problem of how to dynamically characterize the availability of supporting resources based on the repair progress of faulty components during the post-disaster recovery process, and embed frequency security constraints into the collaborative decision-making of maintenance scheduling, topology reconfiguration, and operational scheduling as the recovery state evolves.

[0005] This invention is achieved through the following technical solution:

[0006] A method for collaborative post-disaster recovery of multi-microgrid-distribution networks includes:

[0007] Obtain information on faulty components and repair resources after a disaster, as well as support resources in the multi-microgrid;

[0008] The post-disaster recovery process is divided into multiple recovery periods, and the maintenance task arrangement for each faulty component is determined based on the maintenance resource information.

[0009] The repair completion time of the faulty component is determined according to the maintenance task schedule, and the repair status of the faulty component during the recovery period is determined by the repair completion time.

[0010] The availability of support resources during each recovery period is determined based on the repair status and the electrical connection between support resources and the distribution network, and resources with primary frequency regulation or rapid power regulation capabilities are identified from the available support resources.

[0011] Establish frequency security opportunity constraints and perform deterministic transformation on them. In the process of deterministic transformation, only the support resources in the availability state are included in the construction of equivalent frequency support capabilities, so that the frequency security constraints change dynamically with the repair status.

[0012] By combining the frequency security constraints with distribution network topology reconfiguration and multi-microgrid operation scheduling, a feasible domain for restoring operation that meets frequency security requirements is formed.

[0013] Under the feasible domain for recovery, determine the maintenance path, network reconstruction scheme, and power restoration strategy.

[0014] Furthermore, the maintenance resource information includes a set of maintenance teams, the departure point of each maintenance team, travel time parameters, and repair time parameters corresponding to each faulty component; based on the maintenance resource information, a route decision for the maintenance teams is formed, and the arrival time of each maintenance team to the corresponding faulty component is determined accordingly.

[0015] Furthermore, the repair completion time for each faulty component is determined by the arrival time of the repair team and the repair time, and the repair status of the faulty component during the recovery period is determined based on the completion time.

[0016] Furthermore, a repair status variable is constructed by mapping the repair completion time to the recovery period. The repair status variable is used to indicate whether the faulty component has been repaired within each recovery period.

[0017] Furthermore, the equivalent frequency support capability is formed by the aggregation of support resources that are available and electrically connected to the distribution network, including power sources, energy storage, or controllable loads with droop control capabilities.

[0018] Furthermore, the availability of support resources is gated by repairing state variables and branch switch states, so that only support resources in an available state can participate in the construction of equivalent frequency support capabilities.

[0019] Furthermore, frequency security opportunity constraints are transformed into frequency margins after deterministic transformation. These frequency margins are dynamically updated as the availability of supporting resources changes. When the frequency margin is positive, it indicates that the system meets the frequency security requirements. When the frequency margin is negative, it indicates that there is a risk of frequency exceeding the limit. The repair contribution is evaluated based on the change in frequency margin before and after the faulty component is repaired, so as to adjust the maintenance task arrangement.

[0020] This invention also provides a multi-microgrid-distribution network post-disaster collaborative recovery system for implementing the aforementioned multi-microgrid-distribution network post-disaster collaborative recovery method, comprising:

[0021] The information acquisition module is used to acquire information on faulty components after a disaster, maintenance resources, and support resources in the multi-microgrid.

[0022] The maintenance scheduling module is used to make path decisions for the maintenance team based on the maintenance resource information and determine the maintenance completion time for each faulty component.

[0023] The state evolution module is used to determine the repair status of the faulty component during the recovery period based on the repair completion time.

[0024] The availability determination module is used to determine the availability of the support resources in each recovery period based on the repair status and the electrical connection relationship between the support resources and the power distribution network.

[0025] The frequency security analysis module is used to construct equivalent frequency support capabilities based on support resources that are in an available state and electrically connected to the distribution network, and to form frequency security constraints that are dynamically updated with the repair status.

[0026] The recovery decision module is used to combine distribution network topology reconfiguration and multi-microgrid operation scheduling under the frequency security constraints to determine maintenance paths, network reconfiguration schemes, and power supply recovery strategies.

[0027] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the multi-microgrid-distribution network post-disaster collaborative recovery method as described above.

[0028] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-microgrid-distribution network post-disaster collaborative recovery method as described above.

[0029] Compared with existing technologies, this invention has the following advantages and beneficial effects: By incorporating the repair status of faulty components into the determination of support resource availability, this invention enables frequency security constraints to be dynamically updated during the post-disaster recovery process. This avoids the conservatism or potential operational risks associated with statically setting frequency constraints in traditional methods, thereby improving the adaptability of recovery decisions to changes in the actual system state. Based on available and electrically connected support resources, this invention constructs equivalent frequency support capabilities, effectively quantifying the rapid adjustment capabilities of multi-microgrids during post-disaster recovery. This allows frequency stability analysis to truly reflect changes in resource access conditions, enhancing the accuracy of operational safety assessment during recovery. By utilizing the change in frequency margin before and after faulty component repair to assess its repair contribution, this invention enables maintenance task scheduling to directly serve the system's frequency security objectives, establishing a coupling relationship between maintenance scheduling and operational stability, and improving the targeting and effectiveness of recovery path selection. This invention synergistically integrates dynamic frequency security constraints with distribution network topology reconfiguration and multi-microgrid operation scheduling, achieving integrated decision-making for recovery strategy formulation and operational safety assurance. This helps to improve power supply recovery efficiency while suppressing frequency limit exceedance risks, enhancing the overall reliability and safety of the post-disaster recovery process.

[0030] In summary, this invention can achieve a balance between recovery efficiency and frequency security in complex and uncertain post-disaster environments. Attached Figure Description

[0031] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0032] Figure 1 A flowchart illustrating the specific implementation of the multi-microgrid-distribution network post-disaster collaborative recovery method;

[0033] Figure 2 This is a diagram showing the structure and damage / tethering of the multi-microgrid-distribution network group in Example 1;

[0034] Figure 3 This is a schematic diagram of the completed discretization and repair state construction in Example 1;

[0035] Figure 4 This is a schematic diagram illustrating the coupling between reconstructed connectivity and indicator constraints in Example 1;

[0036] Figure 5 The flowchart for frequency opportunity constraint determination and frequency risk scoring in Example 1 is shown. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0038] Example 1

[0039] A method for collaborative post-disaster recovery of multi-microgrid-distribution networks, such as Figure 1 As shown, the method of this invention can form frequency security opportunity constraints through post-disaster assessment and source-load uncertainty modeling, and obtain frequency security constraints that can be embedded in recovery decisions through deterministic processing; on this basis, the completion time of faulty components is determined through maintenance evolution constraints, and a repair state is constructed accordingly; further, the availability of support resources is gated based on the repair state, so that the frequency security constraints change dynamically with the recovery process; finally, the dynamic frequency security constraints are linked with distribution network topology reconfiguration and multi-microgrid operation scheduling to determine the maintenance path, network reconfiguration scheme, and power supply recovery strategy within the recovery operation feasible domain, specifically including:

[0040] Obtain information on faulty components and repair resources after a disaster, as well as support resources in the multi-microgrid;

[0041] The post-disaster recovery process is divided into multiple recovery periods. Based on the maintenance resource information, the maintenance task arrangement for each faulty component is determined. The maintenance resource information includes the set of maintenance teams, the departure point of each maintenance team, the travel time parameters, and the repair time parameters corresponding to each faulty component. Based on the maintenance resource information, the route decision of the maintenance teams is formed, and the arrival time of each maintenance team to the corresponding faulty component is determined accordingly.

[0042] The repair completion time of the faulty component is determined according to the maintenance task arrangement, and the repair status of the faulty component during the recovery period is determined by the repair completion time; the repair completion time of each faulty component is jointly determined by the arrival time of the maintenance team and the repair time, and the repair status of the faulty component during the recovery period is determined based on the completion time.

[0043] The availability of supporting resources in each recovery period is determined based on the repair status and the electrical connection between supporting resources and the distribution network, and resources with primary frequency regulation or rapid power regulation capability are identified from the available supporting resources; a repair status variable is constructed by mapping the repair completion time to the recovery period, and the repair status variable is used to indicate whether the faulty component has been repaired in each recovery period.

[0044] Frequency security opportunity constraints are established and transformed deterministically. During this transformation, only support resources in an available state are included in the construction of equivalent frequency support capacity, allowing frequency security constraints to dynamically change with the repair status. Equivalent frequency support capacity is formed by aggregating support resources in an available state and electrically connected to the distribution network. Available support resources include power sources, energy storage, or controllable loads with droop control capabilities. The availability of support resources is jointly gated by repair state variables and branch switch states, ensuring that only support resources in an available state participate in the construction of equivalent frequency support capacity.

[0045] By combining the frequency security constraints with distribution network topology reconfiguration and multi-microgrid operation scheduling, a feasible domain for restoring operation that meets frequency security requirements is formed.

[0046] Within the feasible recovery domain, maintenance paths, network reconfiguration schemes, and power restoration strategies are determined. Frequency security opportunity constraints are transformed into frequency margins, which are dynamically updated according to the availability of supporting resources. A positive frequency margin indicates that the system meets frequency security requirements, while a negative frequency margin indicates a risk of frequency exceeding limits. The contribution of repair to the repair is evaluated based on the change in frequency margin before and after the faulty component is repaired, in order to adjust the maintenance task schedule.

[0047] In a preferred embodiment, the post-disaster recovery process is discretized into multiple recovery periods, each corresponding to a preset time length. In practical applications, the recovery periods can be dynamically divided using a rolling update method according to scheduling requirements. That is, several future recovery periods are predicted and decided within each scheduling cycle, and the maintenance task arrangements and operation plans within the recovery periods are periodically updated as the system operating status changes, so that the recovery strategy can be adjusted according to the progress of fault repair and changes in resource status.

[0048] In the post-disaster recovery process, the implementation of recovery strategies may include:

[0049] Isolate the damaged lines to prevent the fault from spreading;

[0050] Temporary power supply paths are established via interconnection switches;

[0051] Initial support is provided by energy storage or distributed power sources with rapid adjustment capabilities;

[0052] Gradually restore the load while meeting frequency safety constraints;

[0053] After the faulty component is repaired, a switchback operation is performed to restore the original power supply structure.

[0054] The above process is implemented in a coordinated manner at different times, taking into account the maintenance progress and the status of support resources.

[0055] By discretizing the completion time of faulty component repair into a recovery period to form a repair status variable, the operational constraint expression of "faulty component cannot be put into operation before repair, but can be continuously used after repair" can be realized. The repair status is used to control the commissioning conditions of related lines, equipment and support resources, so that the recovery operation plan can be consistent with the maintenance progress.

[0056] During the topology reconfiguration of the power distribution network, network connectivity can be characterized by virtual connectivity constraints and state indicator variables, so that the restored power supply structure maintains its radiation characteristics and meets operational safety requirements. The connectivity characterization is only used to ensure the feasibility of the restored structure and does not correspond to the actual power transmission process.

[0057] The fault component repair contribution calculated based on the frequency margin change can be used to assess the impact of different maintenance tasks on system frequency security. In one implementation, the repair contribution can be used as a basis for adjusting maintenance priorities to optimize maintenance paths and task sequences.

[0058] During the recovery process, the system status can be reassessed according to a preset cycle, and the maintenance task arrangement and operation plan can be re-determined based on the updated repair status and frequency risk situation, so that the recovery process forms a dynamic closed loop, thereby achieving a synergistic improvement in power supply recovery efficiency and frequency safety.

[0059] In one implementation, the recovery process is dynamically adjusted using a rolling update mechanism.

[0060] This invention incorporates the repair status of faulty components into the determination of support resource availability, enabling frequency security constraints to be dynamically updated during the post-disaster recovery process. This avoids the conservatism or potential operational risks associated with statically setting frequency constraints in traditional methods, thereby improving the adaptability of recovery decisions to changes in the actual system state. Based on available and electrically connected support resources, this invention constructs equivalent frequency support capabilities, effectively quantifying the rapid adjustment capabilities of multi-microgrids during post-disaster recovery. This allows frequency stability analysis to accurately reflect changes in resource access conditions, enhancing the accuracy of operational safety assessments during recovery. By utilizing the change in frequency margin before and after faulty component repair to assess its repair contribution, this invention enables maintenance task scheduling to directly serve the system's frequency security objectives, establishing a coupling relationship between maintenance scheduling and operational stability, and improving the targeting and effectiveness of recovery path selection. This invention synergistically integrates dynamic frequency security constraints with distribution network topology reconfiguration and multi-microgrid operation scheduling, achieving integrated decision-making for recovery strategy formulation and operational safety assurance. This helps to improve power restoration efficiency while suppressing frequency limit exceedance risks, enhancing the overall reliability and safety of the post-disaster recovery process.

[0061] In specific implementation, such as Figure 1 As shown, it includes the following steps:

[0062] Step (1): Obtain the post-disaster fault assessment results, and determine the set of faulty components, the set of operable switches, and the set of multi-microgrids based on the post-disaster fault assessment results; obtain the set of maintenance sites and maintenance teams, and obtain the travel time parameters and repair time parameters related to the execution of maintenance tasks; at the same time, obtain the load importance weight, line capacity parameters, and multi-microgrid adjustable resource information (including distributed power sources, energy storage, and controllable loads) and their prediction information related to the restoration of operation, so as to support subsequent maintenance scheduling, repair status construction, support capacity calculation, and the formation of the feasible domain for restoration of operation.

[0063] Step (2): To characterize the impact of source load uncertainty on frequency security during post-disaster recovery, a set of data is generated during the recovery period. Within, for each microgrid The load and renewable energy output prediction errors are statistically analyzed to form an uncertainty quantity characterizing the net power imbalance. Let the time period... The load forecast error is The prediction errors for wind power and photovoltaic power are respectively , Define the net power imbalance random variable:

[0064]

[0065] In one implementation, the net power imbalance can be approximated using a zero-mean normal distribution, and expressed as:

[0066]

[0067] In the formula This represents the standard deviation of the net power imbalance, used to characterize the intensity of source-load uncertainty during this period. If the errors are approximately independent, then:

[0068]

[0069] Step (3): Establish frequency security opportunity constraints and perform deterministic transformation to form frequency security constraints that can be embedded in recovery decisions under source load uncertainty. To characterize the microgrid's ability to rapidly suppress net power imbalance during the recovery period, various resources within the microgrid that can provide primary frequency regulation or rapid power regulation capabilities are aggregated into an equivalent frequency support capability. Let the microgrid... During the period The equivalent frequency support capability is:

[0070]

[0071] In the formula It can be a collection of resources that can be quickly adjusted (such as vertical control power, energy storage, etc.). This is the resource equivalent drop coefficient. Indicates the resource during the time period Availability / operation status (its value will be determined jointly by "Repair Status and Connectivity"). Frequency-sensitive load damping should be considered. The frequency deviation during the first frequency modulation stage can be expressed by a linear equivalent relationship as follows:

[0072]

[0073] In the formula, To allow frequency offset limits, The rated frequency; This is the planned bias term (formed by planned power imbalance, measurement deviation, or control bias). This indicates a net deficit, leading to a decrease in frequency.

[0074] To constrain the risk of frequency exceeding limits under uncertainty, frequency security opportunity constraints are imposed on each microgrid and each time period, as follows:

[0075]

[0076] In the formula , These are the upper and lower limits of the frequency. The confidence level.

[0077] The chance constraints are transformed into deterministic constraints to obtain frequency security constraints in the form of deterministic margins, with symmetric frequency bands. This can be equivalently written as a deterministic margin constraint:

[0078]

[0079] In the formula, It is the quantile function of the standard normal distribution; This is the allowable frequency deviation threshold.

[0080] like Figure 2 As shown in the figure, the process of post-disaster maintenance scheduling and the formation of repair status is illustrated. The figure includes maintenance sites, maintenance team routes, locations of faulty components, and maintenance operation sequences. The arrival time is determined by the route arrangement of the maintenance team among each faulty component, and the maintenance completion time of each faulty component is obtained by combining the corresponding repair time. The completion time is further discretized into recovery periods to form the repair status of the faulty components within each recovery period.

[0081] Based on the above process, the time sequence of faulty component repair progress can be expressed, providing a basis for subsequent support resource availability determination.

[0082] Step (4): Determine the maintenance task arrangement based on maintenance resource information, and accordingly determine the maintenance completion time of the faulty component. Introduce maintenance team path decision variables. Used to indicate a repair team From the mission point Drive to the mission point (The task point includes the damaged component and the starting point). To ensure that each damaged component is serviced by the repair team exactly once, constraints are used to ensure that each damaged component is covered by the repair task during the recovery process, represented as:

[0083]

[0084] In the formula It is a set of nodes (including sites and damaged components). This is a collection of damaged components.

[0085] Each maintenance team satisfies path flow conservation:

[0086]

[0087] If each team starts from its respective station Departure and return can be written as:

[0088]

[0089] To constrain path feasibility and avoid unexpected sub-loops, access order variables can be introduced to eliminate sub-loops. (Indicates that the damaged component is in the team) The order of visits in the route is defined, and constraints are applied, as follows:

[0090]

[0091] Based on this, combined with travel time Repair time Arrival time can be established Recurrence constraints:

[0092]

[0093] And based on this, the faulty component can be identified. Completion time , is represented as:

[0094]

[0095] In the formula Indicator element By team implement.

[0096] Step (5): Construct the repair status based on the repair completion time and place the repair status into the resource availability and operational feasibility domain. To connect the continuous completion time with the discrete recovery period, a completion period variable is introduced. And used for gating:

[0097]

[0098]

[0099] Based on this, a repair state sequence is constructed:

[0100]

[0101] This allows subsequent operational models to directly reference the state variable "whether the component has been repaired in time period t".

[0102] Furthermore, the repair state variable is obtained based on the completion time variable. And obtained from the completion time variable:

[0103]

[0104] and the status of the line switch With critical power status and Coupling ensures that a line / equipment can only be put into operation after the corresponding component has been repaired; the constraint relationship is expressed as follows:

[0105]

[0106] In the formula, Indicates that the line / switch is closed; This indicates that key equipment such as DG / energy storage is ready for operation.

[0107] like Figure 3 As shown in the figure, the availability determination relationship of support resources based on repair status is illustrated. The figure includes repaired components, unrepaired components, the nodes where the support resources are located, and their electrical connections with the distribution network. When a faulty component is repaired and a valid connection path is formed, the corresponding support resource is in an available state; when the component is not repaired or a connection is not formed, the corresponding support resource cannot be put into operation. Based on this determination mechanism, support resources in an available state can be included in the construction of equivalent frequency support capacity.

[0108] Step (6): Combine the distribution network topology reconfiguration with the multi-microgrid operation and scheduling, and together with the frequency security constraints and repair state coupling constraints formed in steps (3)–(5), constitute the feasible region for restored operation. The feasible region for restored operation includes node power balance constraints and line power flow capacity constraints, expressed as:

[0109]

[0110]

[0111] In the formula, This refers to the node's load loss. Power exchange between the microgrid and the external environment; For line power flow; Line capacity; , Each is based on a node This is a set of lines at the end / beginning.

[0112] To ensure that the distribution network meets the requirements for radial structure and connectivity during the restoration process, connectivity constraints can be established using a virtual network connectivity representation method, expressed as:

[0113]

[0114]

[0115] In the formula, For virtual flows on line l, virtual flows are only used to characterize topological connectivity and do not correspond to actual power flow variables; This is the set of root nodes.

[0116] like Figure 4 As shown in the figure, the connectivity structure of the distribution network after topology reconfiguration during post-disaster recovery and its operational feasibility constraints are illustrated. The figure includes the power supply path of each node, the line connection status, and the network structure formed by switch control. By determining the connection relationships between nodes, it can be identified whether each load node can connect to a power supply node or supporting resource node with power supply capability through an effective path.

[0117] Furthermore, by imposing connectivity constraints on the aforementioned connections, it can be ensured that the restored network structure meets operational requirements, meaning that each restored load node has at least one reachable power supply path, while avoiding the formation of uncontrollable loop structures. The connectivity determination can be expressed by combining state indicator variables to represent the line commissioning status, and the topological feasibility of the network can be characterized through virtual connectivity relationships.

[0118] Based on the above connectivity determination results, the network structure that meets the power supply path requirements and frequency security constraints can be included in the feasible domain for recovery operation, so that the resulting recovery scheme is feasible in terms of topology and can support the execution of subsequent power supply recovery strategies.

[0119] Step (7): Under the constraints of the above-mentioned feasible region for restoration operation, a joint decision-making model is formed to determine the restoration strategy. During each restoration period, the power flow and supply scheme are determined based on the line commissioning status and operational constraints, and boundary constraints are applied to the microgrid and external switching power. Based on the commissioning status Determine the power flow and supply scheme. To control the model size, linearized active power flow is adopted. Let the nodes... During the period The loss of load is ,line The meritorious trend is The microgrid's external power exchange satisfies the following boundary conditions:

[0120]

[0121] Simultaneously, the frequency security opportunity constraint determination result of step (3) is incorporated as an operational feasibility constraint to ensure that mutual assistance power, load restoration intensity, and supporting resource input meet the grid operation constraints and frequency security constraints. To comprehensively evaluate candidate restoration schemes, a comprehensive index J considering load restoration, switching action costs, and repair timing can be constructed, and maintenance paths, network reconfiguration schemes, and power supply restoration strategies can be determined based on this comprehensive index.

[0122]

[0123] In the formula, As the weight of load importance; This is the switching action cost coefficient; Used to suppress excessive delays in repair. Used to reflect the benefits of prioritizing the repair of frequency risks; Prioritize repair scores based on frequency risk.

[0124] like Figure 5 As shown in the figure, the mechanism for assessing the repair contribution of faulty components and adjusting maintenance priorities based on frequency risk is illustrated. The figure includes changes in system frequency margin, corresponding frequency risk gaps, and changes in risk before and after faulty component repair during each recovery period. By comparing the changes in frequency risk gaps before and after faulty component repair, the repair contribution of each faulty component can be determined.

[0125] Furthermore, by combining repair arrival time and repair time with other repair cost factors, a comprehensive repair score can be generated to characterize the priority of each faulty component during the recovery process.

[0126] Based on the comprehensive repair score, the maintenance task arrangement during the subsequent recovery period can be dynamically adjusted, so that the maintenance path and repair sequence can prioritize reducing system frequency risks, thereby achieving synergy between maintenance decisions and frequency security objectives during the post-disaster recovery process.

[0127] Step (8): Establish a contribution assessment mechanism for priority repair of frequency risks, and adjust the maintenance task schedule in a closed loop accordingly. Based on the frequency security constraint determinization results of step (3), define the microgrid. Time period Frequency margin:

[0128]

[0129] like This indicates that the frequency safety margin is satisfied at the confidence level; if This indicates the presence of frequency risk. The degree of frequency risk is defined as follows:

[0130]

[0131] Repair components In the evaluation options Internal comparison of its "changes before and after repair" defines frequency contribution:

[0132]

[0133] Further, the contribution and repair costs (arrival time and repair time) are factored in to obtain a score:

[0134]

[0135] In the formula To avoid extremely small positive numbers with a denominator of zero, , Components The arrival time and repair cost are considered. A higher score indicates that the component should be repaired with higher priority (usually corresponding to critical tie lines, critical feeder segments, or critical support equipment). Based on the score, the maintenance path and repair priority can be adjusted in subsequent recovery periods to achieve a consistent drive of "enhanced mutual support capability" and "reduced frequency risk".

[0136] In summary, this implementation discretizes the repair completion time of faulty components into recovery periods, forming a repair status. Based on the repair status and the relationship between the network electrical connectivity, it determines the availability of supporting resources, enabling the equivalent frequency support capability to be dynamically updated as the recovery process progresses. Furthermore, by establishing and defining frequency security opportunity constraints, frequency stability requirements are embedded into distribution network topology reconfiguration and multi-microgrid operation scheduling, forming a feasible recovery operation domain that satisfies frequency security constraints. Moreover, based on frequency margin and risk gap, the contribution of faulty component repair is evaluated, achieving coordinated decision-making and closed-loop adjustment of maintenance paths, network reconfiguration, and power supply recovery strategies.

[0137] Through the above mechanism, the impact of the repair progress on the support capacity can be reflected in a timely manner. Changes in the support capacity further affect the frequency security constraints and guide the recovery decision in reverse. This enables the post-disaster recovery process to improve the efficiency of power supply restoration while taking into account the safety of frequency operation, thereby achieving dynamic consistency and overall reliability of the post-disaster collaborative recovery of multiple microgrids and distribution networks.

[0138] Example 2

[0139] A multi-microgrid-distribution network post-disaster collaborative recovery system, used to implement the multi-microgrid-distribution network post-disaster collaborative recovery method of Embodiment 1, is characterized by comprising:

[0140] The information acquisition module is used to acquire information on faulty components after a disaster, maintenance resources, and support resources in the multi-microgrid.

[0141] The maintenance scheduling module is used to make path decisions for the maintenance team based on the maintenance resource information and determine the maintenance completion time for each faulty component.

[0142] The state evolution module is used to determine the repair status of the faulty component during the recovery period based on the repair completion time.

[0143] The availability determination module is used to determine the availability of the support resources in each recovery period based on the repair status and the electrical connection relationship between the support resources and the power distribution network.

[0144] The frequency security analysis module is used to construct equivalent frequency support capabilities based on support resources that are in an available state and electrically connected to the distribution network, and to form frequency security constraints that are dynamically updated with the repair status.

[0145] The recovery decision module is used to combine distribution network topology reconfiguration and multi-microgrid operation scheduling under the frequency security constraints to determine maintenance paths, network reconfiguration schemes, and power supply recovery strategies.

[0146] Example 3

[0147] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the multi-microgrid-distribution network post-disaster collaborative recovery method as described in Embodiment 1.

[0148] Example 4

[0149] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-microgrid-distribution network post-disaster collaborative recovery method as described in Example 1.

[0150] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0151] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0152] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0153] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0154] Those skilled in the art will understand that all or part of the steps in the above facts and methods can be implemented by a program instructing related hardware. The program or the program described therein can be stored in a computer-readable storage medium. When the program is executed, it includes the following steps: at this time, the corresponding method steps are introduced. The storage medium can be ROM / RAM, magnetic disk, optical disk, etc.

[0155] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for post-disaster collaborative recovery of multi-microgrid-distribution networks, characterized in that, include: Obtain information on faulty components and repair resources after a disaster, as well as support resources in the multi-microgrid; The post-disaster recovery process is divided into multiple recovery periods, and the maintenance task arrangement for each faulty component is determined based on the maintenance resource information. The repair completion time of the faulty component is determined according to the maintenance task schedule, and the repair status of the faulty component during the recovery period is determined by the repair completion time. The availability of support resources during each recovery period is determined based on the repair status and the electrical connection between support resources and the distribution network, and resources with primary frequency regulation or rapid power regulation capabilities are identified from the available support resources. Establish frequency security opportunity constraints and perform deterministic transformation on them. In the process of deterministic transformation, only the support resources in the availability state are included in the construction of equivalent frequency support capabilities, so that the frequency security constraints change dynamically with the repair status. By combining the frequency security constraints with distribution network topology reconfiguration and multi-microgrid operation scheduling, a feasible domain for restoring operation that meets frequency security requirements is formed. Under the feasible domain for recovery, determine the maintenance path, network reconstruction scheme, and power restoration strategy.

2. The multi-microgrid-distribution network post-disaster collaborative recovery method according to claim 1, characterized in that, The maintenance resource information includes a set of maintenance teams, the departure point of each maintenance team, travel time parameters, and repair time parameters corresponding to each faulty component; based on the maintenance resource information, a route decision is made for the maintenance teams, and the arrival time of each maintenance team to the corresponding faulty component is determined accordingly.

3. The method for post-disaster collaborative recovery of multi-microgrid-distribution network according to claim 2, characterized in that, The repair completion time for each faulty component is determined by the arrival time of the repair team and the repair time, and the repair status of the faulty component during the recovery period is determined based on the completion time.

4. The multi-microgrid-distribution network post-disaster collaborative recovery method according to claim 3, characterized in that, A repair status variable is constructed by mapping the repair completion time to the recovery period. The repair status variable is used to indicate whether the faulty component has been repaired in each recovery period.

5. The method for post-disaster collaborative recovery of multi-microgrid-distribution network according to claim 1, characterized in that, Equivalent frequency support capacity is formed by the aggregation of support resources that are available and electrically connected to the distribution network, including power sources, energy storage, or controllable loads with droop control capabilities.

6. The method for post-disaster collaborative recovery of multi-microgrid-distribution network according to claim 1, characterized in that, The availability of support resources is gated by repairing state variables and branch switch states, so that only support resources in the available state can participate in the construction of equivalent frequency support capabilities.

7. The method for post-disaster collaborative recovery of multi-microgrid-distribution network according to claim 1, characterized in that, Frequency security opportunity constraints are transformed into frequency margins through deterministic transformation. These frequency margins are dynamically updated as the availability of supporting resources changes. A positive frequency margin indicates that the system meets frequency security requirements, while a negative frequency margin indicates a risk of frequency exceeding limits. The repair contribution is evaluated based on the change in frequency margin before and after the faulty component is repaired, so as to adjust the maintenance task schedule.

8. A multi-microgrid-distribution network post-disaster collaborative recovery system, used to implement the multi-microgrid-distribution network post-disaster collaborative recovery method as described in claims 1-7, characterized in that, include: The information acquisition module is used to acquire information on faulty components after a disaster, maintenance resources, and support resources in the multi-microgrid. The maintenance scheduling module is used to make path decisions for the maintenance team based on the maintenance resource information and determine the maintenance completion time for each faulty component. The state evolution module is used to determine the repair status of the faulty component during the recovery period based on the repair completion time. The availability determination module is used to determine the availability of the support resources in each recovery period based on the repair status and the electrical connection relationship between the support resources and the power distribution network. The frequency security analysis module is used to construct equivalent frequency support capabilities based on support resources that are in an available state and electrically connected to the distribution network, and to form frequency security constraints that are dynamically updated with the repair status. The recovery decision module is used to combine distribution network topology reconfiguration and multi-microgrid operation scheduling under the frequency security constraints to determine maintenance paths, network reconfiguration schemes, and power supply recovery strategies.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the multi-microgrid-distribution network post-disaster collaborative recovery method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the multi-microgrid-distribution network post-disaster collaborative recovery method as described in any one of claims 1 to 7.

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