A method and device for collaborative recovery of isolated microgrids in a power distribution cyber-physical system

Abstract

This invention provides a method and apparatus for collaborative recovery of isolated microgrids in a distribution cyber-physical system, relating to the power system field. The method includes: constructing an emergency resource scheduling model, a partitioning and recovery path model, a communication model, and a distribution network-communication network coupling model; solving the constructed models; and outputting instructions including an emergency resource scheduling scheme, a dynamically coupled partitioning and recovery path scheme, and a distribution network-communication network collaborative recovery strategy. This invention, employing the aforementioned method and apparatus for collaborative recovery of isolated microgrids in a distribution cyber-physical system, successfully solves the problems of low resource scheduling efficiency and unreasonable recovery paths in traditional methods. It significantly improves recovery speed and resource utilization efficiency during post-disaster recovery, providing strong support for the stable operation of the power system.

Description

Technical Field

[0001] This invention relates to the field of power systems, and in particular to a method and apparatus for the collaborative recovery of isolated microgrids in a power distribution cyber-physical system. Background Technology

[0002] Frequent extreme natural disasters pose a serious threat to the safe and stable operation of the Cyber-Physical Distribution System (CPDS), resulting in the paralysis of both power and communication systems.

[0003] Current disaster recovery strategies are mostly focused on static islanding and resource scheduling in a single area of ​​the power system, which are difficult to meet the complex conditions of dynamic changes in the power grid topology and communication network failures after a disaster.

[0004] Current disaster recovery strategies for distribution cyber-physical systems (CPS) suffer from several significant shortcomings: First, the disconnect between zoning strategies and communication network support capabilities leads to the failure of microgrid autonomy; second, the disconnect between zoning schemes and network topology evolution results in delayed dynamic disaster response; and third, the disconnect between resource scheduling and zoning decisions reduces the efficiency of collaborative recovery. These problems severely restrict the rapid recovery of CPS after disasters, necessitating a novel approach to overcome the deficiencies of existing technologies, comprehensively achieve collaborative optimization of power and communication network recovery, improve the stability, resilience, and recovery speed of the power grid after disasters, and ensure the reliable supply of critical loads and communication services. Summary of the Invention

[0005] The purpose of this invention is to provide a collaborative recovery method and apparatus for isolated microgrids in a power distribution cyber-physical system, addressing the problems of partition autonomy failure, response lag, and resource coordination disconnect in existing technologies. Through collaborative decision-making within a unified emergency resource model, path optimization and work sequence execution for construction teams and mobile communication vehicles are achieved. Operational instructions are dynamically generated based on partition boundaries, realizing closed-loop optimization of resource scheduling and partition decision-making. A dynamic evolution mechanism for partitions is established, incorporating topology optimization, resource allocation, and load priority into the optimization process, generating recovery paths that prioritize power supply to critical loads and restoration of local communication functions. A collaborative autonomous structure between the power microgrid and the communication local area network is established, accelerating recovery response speed and improving resource utilization efficiency, effectively reducing losses caused by power outages and communication interruptions.

[0006] To achieve the above objectives, the present invention provides a method for collaborative recovery of isolated microgrids in a power distribution cyber-physical system, comprising the following steps:

[0007] Based on the location of the fault, the characteristics of the local construction team and mobile communication vehicle are analyzed to construct an emergency resource scheduling model; the emergency resource scheduling model includes a unified emergency resource scheduling model and a time-space scheduling model.

[0008] Based on the topology, fault conditions, and real-time repair progress under the emergency resource scheduling model, partitions and recovery paths are dynamically set, and a partition and recovery path model is constructed; wherein, the partition and recovery path model includes a partition model and a recovery path model;

[0009] A communication model is established based on network availability and routing conditions, and the coupling dependency between the distribution network and the communication network is characterized, i.e., the distribution network-communication network coupling model, to ensure that communication control commands can be reached within the coupling zone;

[0010] With the goal of minimizing system load loss and communication loss, the system jointly solves the emergency resource scheduling model, the partitioning and recovery path model, the communication model, and the distribution network-communication network coupling model, and outputs instructions including emergency resource scheduling schemes, dynamic coupling partitioning and recovery path schemes, and distribution network-communication network collaborative recovery strategies.

[0011] The preferred model for unified emergency resource scheduling involves emergency resources starting from their initial location, sequentially proceeding to designated task points to perform tasks, and returning to the initial location or proceeding to the next target location after completion. This process must simultaneously satisfy path continuity, task independence, and node allocation, as uniformly described below:

[0012]

[0013] In the formula, Φ F The set of all nodes to be connected or repaired; t is the discrete time step, t = 1, 2, ...; T represents the sequence index during the recovery period; g refers to the emergency resource; i, j, and k are the node numbers of the communication network or distribution network; W is the initial parking position of the emergency resource; To determine whether emergency resource g travels from its initial position W to node i; Whether emergency resource g should be returned to its initial position W by node i; The movement state of emergency resource g between nodes i, j, and k; Φ R It is a collection of all emergency resources; This indicates whether node i is being repaired or connected by emergency resource g at time step t.

[0014] Preferably, the time-space scheduling model includes:

[0015] The mobile communication vehicle time-sharing scheduling model is as follows:

[0016]

[0017] In the formula, Φ J For mobile communication vehicle access points; To determine whether the mobile communication vehicle g leaves node i at time step t; T ig Let g be the time required for the mobile communication vehicle g to reach node i. Let τ be the duration of node i's access to mobile communication vehicle g; τ is the cumulative time summation variable; q i The access status of node i; p i,τ To determine whether to access node i at time step τ;

[0018] The construction team's time-of-use temperature model is as follows:

[0019]

[0020] In the formula, To determine whether construction team g has completed the repair at node i; For construction team g, at time step t, whether node i has started repairing; The repair time for construction team g at node i; Let i be the repair state of node i at time step t.

[0021] Preferably, local power supply and communication are maintained by utilizing network-type power sources and intelligent terminals within the partition, and dynamically adjusted as scheduling progresses. The general partition modeling content is as follows:

[0022]

[0023]

[0024] In the formula, and β represents the binary partition variables for nodes and lines, respectively. When node i and line ij belong to partition k at time step t, both partition variables are equal to 1; i,j,t The switching state of line ij; s i,j,t The line is under repair. Restore the node's state;

[0025] Taking the distribution network as an example, the specific distribution network recovery path model is as follows:

[0026]

[0027] In the formula, r i,j,t r j,i,t This represents the network recovery path; N is a large number, Ω GF For grid-type power supply collection; This refers to the switching status of power distribution line ij.

[0028] Preferably, based on the coupling dependency relationship between the distribution network and the communication network, a coupling model between the distribution network and the communication network is constructed, including:

[0029] In cyber-physical distribution systems, communication routers must be powered by the power grid to forward data and execute remote control commands. The modeling content is as follows:

[0030]

[0031] In the formula, u r,t This represents the availability state of the r-th communication router at time t; i(r) represents the node corresponding to communication router r; This represents the maximum load demand of node i at time t; P represents the load reduction on bus i at time t; r The power consumption of the communication router r is represented by M; M represents a large number used to establish heuristic constraints related to binary variables.

[0032] The closing of remote control switches depends not only on the control communication link, but is also affected by the operation duration and the time required to clear line faults. The status of remote control switches on each line is expressed by the following formula:

[0033]

[0034] In the formula, l(s) represents the line corresponding to the s-th remote control switch; Indicates the closing state of the remote control switch; r(s) represents the communication router controlling the s-th remote control switch; u r(s),t ΔT represents the availability status of the communication router controlling the s-th RCS; ΔT represents the scheduling time interval. This represents the troubleshooting time for all node units connected to the s-th RCS; This represents the duration required for the remote operation of the s-th remote control switch; This indicates the fault clearing time for nc remote control switches; Ω represents the set of NCs connected by the s-th remote control switch; RCS This represents a set of remote control switches.

[0035] Preferred communication models include:

[0036] The availability of a communication network is described by the status of routers and communication links, ensuring timely support for the distribution network after disaster recovery. Communication network availability model:

[0037]

[0038] In the formula, Link represents the communication link of the communication router; L represents the availability status of the k-th communication link of the r-th router; r,kU represents the set of network routers contained in the k-th network link of the r-th router; r,t This represents the availability status of the r-th communication router at time t; n represents the total number of communication links in the r-th router; r This represents the number of communication links for the r-th router;

[0039] If a communication route exists between network node i and the control center, two conditions must be met: the upstream node of node i must have a communication connection with the control center; and node i and its upstream nodes must have a physical connection. The routing model is as follows:

[0040] v OLT,t =1 (31);

[0041]

[0042] In the formula, v OLT,t Indicates the link status between the OLT node and the control center; v i,t Indicates the link status between node i and the control center; v j,t h represents the link status between node j and the control center. ij,t Indicates the repair status of the communication line; N IN N represents the set of communication nodes. ONU N represents the set of optical network unit nodes. POS N represents the set of passive physical device nodes. F The set of nodes representing the faulty component; δ i,t This represents the power supply status of node i at time t; k i,t This represents the communication status of node i at time t.

[0043] A collaborative recovery device for isolated microgrids in a power distribution cyber-physical system includes:

[0044] The model building module analyzes the characteristics of local construction teams and mobile communication vehicles based on the location of the fault point to build an emergency resource scheduling model;

[0045] Based on the topology, fault conditions, and real-time repair progress under the emergency resource scheduling model, partitions and recovery paths are dynamically set, and a partition and recovery path model is constructed.

[0046] A communication model is established based on network availability and routing conditions, and the coupling dependency between the distribution network and the communication network is characterized, i.e., the distribution network-communication network coupling model;

[0047] The solver module is used to jointly solve the emergency resource scheduling model, the partitioning and recovery path model, the communication model, and the distribution network-communication network coupling model with the goal of minimizing system load loss and communication loss.

[0048] The scheme output module is used to output instructions including emergency resource scheduling schemes, dynamic coupling zoning and recovery path schemes, and distribution network-communication network collaborative recovery strategies.

[0049] Therefore, the present invention employs the above-mentioned collaborative recovery method and device for isolated microgrids in a power distribution cyber-physical system, and the technical effects are as follows:

[0050] Efficient resource scheduling and collaborative operation: Through the collaborative operation of mobile communication vehicles and construction teams, combined with dynamic partitioning strategies, efficient collaboration among resources was achieved, enabling rapid restoration of critical loads and communication functions.

[0051] Optimized recovery path: The recovery path is dynamically optimized based on the recovery needs within the coupled partition to ensure that power and communication functions can be restored synchronously during the post-disaster recovery process, and to prioritize the protection of critical loads.

[0052] Dynamic zoning and resource scheduling schemes: By employing grid-type power supplies to ensure power supply to critical loads and utilizing smart terminals to provide local area communication within isolated areas, coupled zoning of the power microgrid and the communication local area network is achieved. This zoning scheme can be dynamically adjusted according to the progress of line repairs and resource scheduling, minimizing the loss of critical loads.

[0053] Enhanced system resilience: This method can effectively reduce the socio-economic losses caused by power outages and communication interruptions after disasters, improve the recovery speed of distribution networks and communication networks, and enhance the resilience of the entire power system.

[0054] In summary, this invention, by establishing a collaborative recovery method for isolated microgrids in a power distribution cyber-physical system based on dynamic coupling partitioning, successfully solves the problems of low resource scheduling efficiency and unreasonable recovery paths in traditional methods. It significantly improves recovery speed and resource utilization efficiency during post-disaster recovery, providing strong support for the stable operation of the power system. Attached Figure Description

[0055] Figure 1 This is a flowchart of a collaborative recovery method for isolated microgrids in a power distribution cyber-physical system according to the present invention;

[0056] Figure 2 Topology diagram for testing the improved IEEE 33-node distribution cyber-physical system;

[0057] Figure 3 This is a dynamic change diagram of the coupled partitions at time step 1 and time step 2. Figure 3 (a) shows the case of time step 1 coupled partition; Figure 3 (b) shows the case of time-step 2 coupled partitioning;

[0058] Figure 4 This is a dynamic change diagram of the coupled partitions at time step 3 and time step 5; Figure 4 (a) shows the case of time-step 3 coupled partitioning; Figure 4 (b) shows the case of time step 5 coupled partition;

[0059] Figure 5 This is a dynamic change diagram of the coupled partitions at time step 3 and time step 5; Figure 5 (a) shows the time-step 7 coupled partitioning case; Figure 5 (b) shows the case of time-step 9 coupled partitioning;

[0060] Figure 6 This diagram illustrates a comparison of load recovery results using different methods. Detailed Implementation

[0061] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0062] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0063] Example 1

[0064] like Figure 1 As shown, a collaborative recovery method for isolated microgrids in a power distribution cyber-physical system includes the following steps:

[0065] The working characteristics of construction teams and mobile communication vehicles were analyzed in depth. For mobile communication vehicles, the focus was on their communication bandwidth and flexibility in post-disaster recovery. For construction teams, the analysis primarily examined their arrival time, repair duration, and repair priority when repairing power distribution and communication networks, providing a basis for establishing a unified emergency resource scheduling model. This model includes a unified emergency resource scheduling model and a time-space scheduling model.

[0066] An emergency resource unified scheduling model is proposed, in which the path planning of construction teams and mobile communication vehicles follows similar scheduling constraints. By introducing the path continuity and independence of emergency resources, a closed-loop path is formed, starting from the initial position and passing through various task points. Emergency resources start from their initial position, proceed sequentially to designated task points to perform tasks, and return to the initial position or proceed to the next target location after completion. This process must simultaneously satisfy path continuity, task independence, and node allocation, which can be uniformly expressed as follows:

[0067] To ensure that resources originate from the resident point and complete all node accesses in a closed-loop manner, the following statements apply:

[0068]

[0069] To maintain the continuity of the movement process, the following statements apply:

[0070]

[0071] To prevent multiple resources from performing duplicate operations on the same node at the same time, the following statement applies:

[0072]

[0073] In the formula, Φ F The set of all nodes to be connected or repaired; t is the discrete time step, t = 1, 2, ...; T represents the sequence index during the recovery period; g refers to emergency resources (construction teams and emergency communication vehicles); i, j, and k are the node numbers of the communication network or distribution network; W is the initial parking position of the emergency resources; To determine whether emergency resource g travels from its initial position W to node i; Whether emergency resource g should be returned to its initial position W by node i; The movement state of emergency resource g between nodes i, j, and k; Φ R It is a collection of all emergency resources; This indicates whether node i is being repaired or connected by emergency resource g at time step t.

[0074] The time-space temperature control model includes:

[0075] Mobile communication vehicle dispatching needs to comprehensively consider factors such as communication coverage requirements and node power supply status. The mobile communication vehicle time-sharing scheduling model is as follows:

[0076] The access and departure times of the mobile communication vehicle at each access point are used to coordinate its power supply tasks, as detailed below:

[0077]

[0078] The access status of mobile communication vehicle g at node i is specifically represented as follows:

[0079]

[0080] In the formula, Φ J For mobile communication vehicle access points; To determine whether the mobile communication vehicle g leaves node i at time step t; T i g Let g be the time required for the mobile communication vehicle g to reach node i. Let τ be the duration of node i's access to mobile communication vehicle g; τ is the cumulative time summation variable; q i The access status of node i; p i,τ To determine whether to access node i at time step τ;

[0081] Depending on their specialization, construction teams are divided into power distribution network and communication network construction teams. Both need to consider factors such as the arrival time of the faulty line, the repair time, and the repair status. The construction team's time-sharing scheduling model is as follows:

[0082] To ensure that the order of tasks and the time arrangement are logical, the following statement is made:

[0083]

[0084] To characterize the repair status of each fault point, the following statement is used:

[0085]

[0086] In the formula, To determine whether construction team g has completed the repair at node i; For construction team g, at time step t, whether node i has started repairing; The repair time for construction team g at node i; Let i be the repair state of node i at time step t.

[0087] Based on the recovery requirements of the distribution network and communication network, a zoning and recovery path model is constructed to plan the recovery path. This model includes a zoning model and a recovery path model. It not only considers the independent recovery of the distribution network and communication network but also introduces dynamic adjustments to the allocation of power supply and communication resources within each zoning zone. By realizing the restoration of power and communication functions within each zone, priority restoration of critical loads is ensured, and the zoning strategy is dynamically adjusted based on real-time fault data and recovery progress.

[0088] By utilizing network-type power supplies and intelligent terminals within the partition, local power supply and communication are maintained, and dynamic adjustments are made as scheduling progresses. The general partitioning model is as follows:

[0089] Each node and line is limited to belonging to a maximum of one area, as detailed below:

[0090]

[0091] A prerequisite for a line to be included in a partition is that both of its endpoints belong to the same partition, as shown below:

[0092]

[0093] This indicates that the state of the line switch is determined based on the partition variable, as shown below:

[0094]

[0095] This indicates that the faulty circuit cannot be closed before it is repaired, as shown below:

[0096]

[0097] This indicates that the partition variable is limited by the node recovery state, specifically as follows:

[0098]

[0099] In the formula, and β represents the binary partition variables for nodes and lines, respectively. When node i and line ij belong to partition k at time step t, both partition variables are equal to 1; i,j,t The switching state of line ij; s i,j,t The line is under repair. Restore the node's state;

[0100] Whether it's a distribution network or a communication network, the ultimate goal of the recovery path is to "repair faulty lines and restore connectivity." A unified model is used for the recovery path, with differentiated constraints set based on the characteristics of both. Taking the distribution network as an example, the specific distribution network recovery path model is as follows:

[0101] To ensure that the recovery path originates from the grid-connected power source, the specific expression is set as follows:

[0102]

[0103] To ensure that a node can only have a recovery path outflow if there is an inflow of recovery path, the specific expression is set as follows:

[0104]

[0105] To ensure that there is at most one recovery path on each closed loop, the specific expression is set as follows:

[0106]

[0107] To indicate that a node can be restored if a recovery path exists, the specific expression is set as follows:

[0108]

[0109] To ensure that there are sufficient recovery paths for each non-networked power access node i within the partition, the specific expression is set as follows:

[0110]

[0111] To ensure the radial recovery path of the distribution network and avoid the formation of loops, the recovery path modeling of the communication network is not subject to this constraint, and the specific expression is set as follows:

[0112]

[0113] In the formula, r i,j,t r j,i,t This represents the network recovery path; N is a large number, Ω GF For grid-type power supply collection; This refers to the switching status of power distribution line ij.

[0114] A communication model is established based on network availability and routing conditions, and the coupling dependency between the distribution network and the communication network is characterized, i.e., the distribution network-communication network coupling model, to ensure that communication control commands can be reached within the coupled area.

[0115] Based on the coupling dependency between the distribution network and the communication network, a distribution network-communication network coupling model is constructed. This model, by describing the mutual requirements of communication routers and power facilities, ensures the reachability of communication control commands after a disaster. The recovery paths of the distribution network and the communication network work in coordination through the coupling model, ensuring effective control of remote switches in the initial stage of communication network recovery and gradually restoring the coordinated operation of the power grid and the communication network. This includes:

[0116] The demands of communication networks on the power grid:

[0117] In cyber-physical distribution systems, communication routers must be powered by the power grid to forward data and execute remote control commands. The modeling content is as follows:

[0118]

[0119] In the formula, u r,t This represents the availability state of the r-th communication router at time t; i(r) represents the node corresponding to communication router r; This represents the maximum load demand of node i at time t; P represents the load reduction on bus i at time t; r The power consumption of the communication router r is represented by M; M represents a large number used to establish heuristic constraints related to binary variables.

[0120] The power grid's demand on the communication network:

[0121] The closing of remote control switches depends not only on the control communication link, but also on the operation duration and the time required to clear line faults. The status of remote control switches on each line is expressed by the following formula:

[0122]

[0123] In the formula, l(s) represents the line corresponding to the s-th remote control switch; Indicates the closing state of the remote control switch; r(s) represents the communication router controlling the s-th remote control switch; u r(s),tΔT represents the availability status of the communication router controlling the s-th RCS; ΔT represents the scheduling time interval. This represents the troubleshooting time for all node units connected to the s-th RCS; This represents the duration required for the remote operation of the s-th remote control switch; This indicates the fault clearing time for nc remote control switches; Ω represents the set of NCs connected by the s-th remote control switch; RCS This represents a set of remote control switches.

[0124] Communication models, including:

[0125] The availability of a communication network is described by the status of routers and communication links, ensuring timely support for the distribution network after disaster recovery. Communication network availability model:

[0126] This means that the entire communication link is considered connected only when all routers in the link are in an available state.

[0127]

[0128] This means that a router's effective operation requires at least one network link to remain open between it and the control center.

[0129]

[0130] In the formula, Link represents the communication link of the communication router; L represents the availability status of the k-th communication link of the r-th router; r,k U represents the set of network routers contained in the k-th network link of the r-th router; r,t This represents the availability status of the r-th communication router at time t; n represents the total number of communication links in the r-th router; r This represents the number of communication links for the r-th router;

[0131] If a communication route exists between network node i and the control center, two conditions must be met: the upstream node of node i must have a communication connection with the control center; and node i and its upstream nodes must have a physical connection. The routing model is as follows:

[0132] The optical line terminal node is always connected to the control center because it is protected within the backbone network and will not experience failures. Specifically:

[0133] v OLT,t =1 (31);

[0134] If neither node i nor its upstream node j is damaged, the link state of node i depends on the state of node j, specifically as follows:

[0135]

[0136] The connection state of node i is affected by both the state of its upstream node j and whether the line connecting the two nodes has been repaired, specifically as follows:

[0137]

[0138] A communication connection can only be established if and only if there is a physical path between the intelligent electronic device / optical network unit node i and the control center and a sufficient power supply is available, specifically as follows:

[0139]

[0140] The communication state of passive optical splitter node i depends only on the variable, specifically:

[0141]

[0142] In the formula, v OLT,t Indicates the link status between the OLT node and the control center; v i,t Indicates the link status between node i and the control center; v j,t h represents the link status between node j and the control center. ij,t Indicates the repair status of the communication line; N IN N represents the set of communication nodes. ONU N represents the set of optical network unit nodes. POS N represents the set of passive physical device nodes. F The set of nodes representing the faulty component; δ i,t This represents the power supply status of network node i at time t; k i,t This represents the communication status of node i at time t.

[0143] A collaborative recovery device for isolated microgrids in a power distribution cyber-physical system includes:

[0144] The model building module analyzes the characteristics of local construction teams and mobile communication vehicles based on the location of the fault point to build an emergency resource scheduling model;

[0145] Based on the topology, fault conditions, and real-time repair progress under the emergency resource scheduling model, partitions and recovery paths are dynamically set, and a partition and recovery path model is constructed.

[0146] A communication model is established based on network availability and routing conditions, and the coupling dependency between the distribution network and the communication network is characterized, i.e., the distribution network-communication network coupling model;

[0147] The solver module is used to jointly solve the emergency resource scheduling model, the partitioning and recovery path model, the communication model, and the distribution network-communication network coupling model with the goal of minimizing system load loss and communication loss.

[0148] The scheme output module is used to output instructions including emergency resource scheduling schemes, dynamic coupling zoning and recovery path schemes, and distribution network-communication network collaborative recovery strategies.

[0149] Comparative Test

[0150] The above method was tested on an improved IEEE 33-node distribution cyber-physical system. The test system topology is shown below. Figure 2 As shown, the base voltage on the distribution side is 12.66kV, the total load is 3.71MW + 1.50MVar, and the allowable voltage deviation at each node is controlled within ±5%. The system has 33 nodes, with three grid-connected power supplies (600kW, 800kW, and 700kW rated power) connected to nodes 6, 13, and 16 respectively. Since the power distribution lines and communication cables are laid in parallel, the communication network also contains 33 nodes; node 1 serves as the communication master station. Edge intelligent terminals with a computing performance of 10TFLOPS are configured at communication nodes 4, 6, and 16. The unit of communication is bit / s, the wired link bandwidth is set at 100Mbps, and the mobile communication vehicle can temporarily provide a 500Mbps wireless link.

[0151] Assume an extreme natural disaster causes power distribution lines D4-5, D8-9, D15-16, D20-21, and D29-30 to fail, while communication lines C4-5, C8-9, C15-16, C2-19, and C6-26 are simultaneously interrupted. To expedite repairs, two specialized teams are pre-positioned: one responsible for power distribution network repairs, and the other focused on communication network restoration; a mobile communication vehicle is also deployed to provide initial coverage support. The restoration process is divided into 13 time steps, each lasting 20 minutes.

[0152] The emergency resource dispatch plan is shown in Table 1. Different colors are used to distinguish the fault repair or access status of the construction team or mobile communication vehicle at each time step, and the symbol "→" indicates the process of the mobile communication vehicle and construction team returning to the warehouse after moving or completing the repair.

[0153] Table 1 Emergency Resource Allocation Plan

[0154]

[0155] Figure 3 , Figure 4 and Figure 5The dynamic changes of the coupled partitions at each time step are displayed. The method dynamically optimizes partitioning and resource scheduling based on real-time topology and fault information, achieving a coordinated power-communication balance within the partition. When some communication nodes are not yet repaired or have insufficient computing power, a mobile communication vehicle provides a remote access channel to coordinate cross-regional information flow, significantly improving early load recovery speed and system stability.

[0156] For a detailed comparison of the different methods, please refer to [link / reference]. Figure 6 The proposed method was compared with three other methods that do not consider construction teams, mobile communication vehicles, and coordinated restoration of the power distribution network and communication network. The results in the figure show that the proposed method is significantly superior to the other three methods in both load restoration speed and restoration effect. Furthermore, observations were made regarding communication coverage and information transmission, showing that the proposed method can restore data interaction at remote nodes earlier.

[0157] In contrast, this method, through the coordinated scheduling of mobile communication vehicles and construction teams, combined with a coupled partitioning strategy to allocate limited resources, gradually restores critical loads and communication functions, thereby improving post-disaster recovery speed and resource utilization efficiency. As shown in the figure, this method significantly outperforms the other three methods in terms of initial load recovery speed, achieving approximately 62% load recovery by time step 4. The load recovery rate continues to improve in the mid-to-late stages, reaching nearly 100% recovery by time step 9, fully demonstrating the significant advantages of this method in the collaborative post-disaster recovery of power distribution cyber-physical systems.

[0158] Simulation Experiments and Result Analysis

[0159] The simulation environment and hardware configuration in this example are as follows:

[0160] The simulation environment uses a Win10 64-bit operating system, an Intel Core i5 CPU 3.50GHz, 16GB RAM, and MATLAB R2023b. This simulation environment is not limited to the one described above; other simulation environments can also be used as needed.

[0161] Experimental Setup: Simulation experiments were conducted based on the improved IEEE 33-node distribution cyber-physical system, setting up various representative fault scenarios and different levels of disaster intensity. The performance of traditional methods and this method was compared in key indicators such as load restoration effect, repair time, and resource utilization.

[0162] Results Analysis: Experimental results show that the method proposed in this invention can significantly improve the emergency repair and restoration efficiency of the post-disaster power distribution cyber-physical system. Compared with traditional methods, in terms of load restoration, the restoration speed is faster and the restoration volume is greater, effectively reducing power outages and communication losses; in terms of resource utilization, by optimizing scheduling and coordination mechanisms, the utilization efficiency of construction teams and mobile communication vehicles is improved, reducing resource waste.

[0163] Therefore, the present invention adopts the above-mentioned method and device for collaborative recovery of isolated microgrids in power distribution cyber-physical systems, which solves the problems of low resource scheduling efficiency and unreasonable recovery paths in traditional methods. It significantly improves the recovery speed and resource utilization efficiency in the post-disaster recovery process, and provides strong support for the stable operation of the power system.

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A collaborative recovery method for isolated microgrids in a power distribution cyber-physical system, characterized in that, Includes the following steps: Based on the location of the fault, the characteristics of the local construction team and mobile communication vehicle are analyzed, and an emergency resource scheduling model is constructed. The emergency resource scheduling model includes a unified emergency resource scheduling model and a time-space scheduling model. Based on the topology, fault conditions, and real-time repair progress under the emergency resource scheduling model, partitions and recovery paths are dynamically set, and a partition and recovery path model is constructed; wherein, the partition and recovery path model includes a partition model and a recovery path model; A communication model is established based on network availability and routing conditions, and the coupling dependency between the distribution network and the communication network is characterized, i.e., the distribution network-communication network coupling model, to ensure that communication control commands can be reached within the coupling zone; With the goal of minimizing system load loss and communication loss, the emergency resource scheduling model, partitioning and recovery path model, communication model and distribution network-communication network coupling model are jointly solved, and the output includes instructions including emergency resource scheduling scheme, dynamic coupled partitioning and recovery path scheme and distribution network-communication network collaborative recovery strategy. The unified emergency resource scheduling model involves emergency resources starting from their initial location, sequentially proceeding to designated task points to perform tasks, and returning to the initial point or moving to the next target location after completion. This process must simultaneously satisfy path continuity, task independence, and node allocation, as uniformly described below: （1）； （2）； （3）； （4）； （5）； In the formula, The set of all nodes to be connected or repaired; t is the discrete time step, t=1, 2, …; T represents the sequence index during the recovery period; g refers to the emergency resource; i, j and k are the node numbers of the communication network or distribution network; W is the initial parking position of the emergency resource; To determine whether emergency resource g travels from its initial position W to node i; Whether emergency resource g should be returned to its initial position W by node i; , This represents the movement status of emergency resource g between nodes i, j, and k. It is a collection of all emergency resources; This indicates whether node i is being repaired or connected by emergency resource g at time step t.

2. The method for collaborative recovery of isolated microgrids in a power distribution cyber-physical system according to claim 1, characterized in that, The time-space temperature control model includes: The mobile communication vehicle time-sharing scheduling model is as follows: （6）； （7）； In the formula, For mobile communication vehicle access points; To determine whether the mobile communication vehicle g leaves node i at time step t; Let g be the time required for the mobile communication vehicle g to reach node i. The duration for which node i accesses mobile communication vehicle g; For the cumulative time summation variable; This represents the access status of node i; Whether or not in time step Access node i at time; The construction team's air conditioning temperature model is as follows: （8）； （9）； In the formula, To determine whether construction team g has completed the repair at node i; For construction team g, at time step t, whether node i has started repairing; The repair time for construction team g at node i; Let i be the repair state of node i at time step t. =0.

3. The collaborative recovery method for isolated microgrids in a power distribution cyber-physical system according to claim 1, characterized in that, By utilizing network-type power supplies and intelligent terminals within the partition, local power supply and communication are maintained, and dynamically adjusted as scheduling progresses. The general partition modeling content is as follows: (10)； (11)； (12)； (13)； (14)； (15)； (16)； (17)； In the formula, and These are binary partition variables for nodes and lines, respectively. When node i and line ij belong to partition k at time step t, the partition variables are both equal to 1. This represents the switching state of line ij; The line is under repair. Restore the node's state; Taking the distribution network as an example, the specific distribution network recovery path model is as follows: (18)； (19)； (20)； (21)； (22)； (23)； (24)； In the formula, , This represents the network recovery path; N is a large number. For grid-type power supply collection; This refers to the switching status of power distribution line ij.

4. The method for collaborative recovery of isolated microgrids in a power distribution cyber-physical system according to claim 1, characterized in that, Based on the coupling dependency between the distribution network and the communication network, a coupling model between the distribution network and the communication network is constructed, including: In cyber-physical distribution systems, communication routers must be powered by the power grid to forward data and execute remote control commands. The modeling content is as follows: (25)； (26)； In the formula, This represents the availability status of the r-th communication router at time t; The node corresponding to the communication router r; This represents the maximum load demand of node i at time t; This represents the load reduction on bus i at time t; The power consumption of the communication router r is represented by M; M represents a large number used to establish heuristic constraints related to binary variables. The closing of remote control switches depends not only on the control communication link, but also on the operation duration and the time required to clear line faults. The status of remote control switches on each line is expressed by the following formula: (27)； (28)； In the formula, l ( s ) represents the circuit corresponding to the s-th remote control switch; This indicates the closing status of the remote control switch; r(s) represents the communication router that controls the s-th remote control switch. This indicates the availability status of the communication router controlling the s-th RCS; Indicates the scheduling time interval; This represents the troubleshooting time for all node units connected to the s-th RCS; This represents the duration required for the remote operation of the s-th remote control switch; This indicates the fault clearing time for nc remote control switches; This represents the set of NCs connected by the s-th remote control switch; This represents a set of remote control switches.

5. The method for collaborative recovery of isolated microgrids in a power distribution cyber-physical system according to claim 1, characterized in that, Communication models, including: The availability of a communication network is described by the status of routers and communication links, ensuring timely support for the distribution network after disaster recovery. Communication network availability model: (29)； (30)； In the formula, Link represents the communication link of the communication router; This indicates the availability status of the k-th communication link of the r-th router; This represents the set of network routers included in the k-th network link of the r-th router; This represents the availability status of the r-th communication router at time t; This represents the total number of communication links in the r-th router; This represents the number of communication links for the r-th router; If a communication route exists between network node i and the control center, two conditions must be met: the upstream node of node i must have a communication connection with the control center; and node i and its upstream nodes must have a physical connection. The routing model is as follows: (31)； (32)； (33)； (34)； (35)； In the formula, This indicates the link status between the OLT node and the control center; This indicates the link status between node i and the control center; This indicates the link status between node j and the control center. Indicates the repair status of the communication line; N IN Represents a set of communication nodes. N ONU Represents the set of optical network unit nodes. N POS Represents the set of passive physical device nodes. N F The set of nodes representing the faulty component; This represents the power supply status of node i at time t; This represents the communication status of node i at time t.

6. A collaborative recovery device for isolated microgrids in a power distribution cyber-physical system, characterized in that, include: The model building module analyzes the characteristics of local construction teams and mobile communication vehicles based on the location of the fault point to build an emergency resource scheduling model; Based on the topology, fault conditions, and real-time repair progress under the emergency resource scheduling model, partitions and recovery paths are dynamically set, and a partition and recovery path model is constructed. A communication model is established based on network availability and routing conditions, and the coupling dependency between the distribution network and the communication network is characterized, i.e., the distribution network-communication network coupling model; The solver module is used to jointly solve the emergency resource scheduling model, the partitioning and recovery path model, the communication model, and the distribution network-communication network coupling model with the goal of minimizing system load loss and communication loss. The scheme output module is used to output instructions including emergency resource scheduling schemes, dynamic coupling zoning and recovery path schemes, and distribution network-communication network collaborative recovery strategies.

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