Typhoon pre-disaster and post-disaster interconnected distribution network restoration method based on reconfigurable soft switch

Abstract

The application discloses a typhoon pre-disaster and post-disaster interconnected distribution network recovery method based on a reconfigurable soft switch, which comprises the following steps: in the pre-disaster stage, considering the power support of electric buses, combining the reconfigurable soft switch with the collaborative change of the port topology of the interconnected distribution network, constructing an electric bus pre-disaster deployment model, so as to determine the stopping position of the electric bus before the fault occurs; in the post-disaster stage, considering the uncertainty of renewable energy and load in the interconnected distribution network continuous fault and recovery, using an event-driven mechanism, defining fault events and prediction error events, constructing an event-driven recovery model, so as to obtain an interconnected distribution network fault recovery strategy, so as to promote the fault recovery of the interconnected distribution network. The application can perform fault deduction before the disaster, reduce potential power loss load and accelerate the power supply recovery after the disaster; under the condition of the continuous fault after the disaster, the strategy update can be triggered in real time, and the uncertainty of the fault evolution and the renewable energy and load can be adapted.

Description

Technical Field

[0001] This invention belongs to the field of power distribution system fault recovery, specifically a method for restoring interconnected power distribution networks before and after typhoon disasters based on reconfigurable soft switches. Background Technology

[0002] A reliable and stable power supply is essential for the normal operation of modern society and is a primary goal pursued by the power industry for a long time. However, due to factors such as extreme natural disasters, infrastructure vulnerability, and uncertain external environments, power grids inevitably experience line faults and power outages.

[0003] Considering the persistent development of faults and the uncertainty of renewable energy and load during recovery, a reconfigurable soft switch R-SOP with asymmetric capacity design is introduced. Through its flexible feeder selection and port reconfiguration mechanism, flexible interconnection between multiple interconnected distribution networks and efficient utilization of converter capacity are achieved. Electric buses (EB), as a public resource, are widely present in interconnected distribution networks. With the development of vehicle-to-grid (V2G) technology, EB can function similarly to mobile energy storage devices (MESS) during recovery without increasing investment. However, existing research mainly focuses on single-instant fault scenarios, lacking consideration of the sustained destructive characteristics of natural disasters. In fact, natural disasters such as typhoons often last for hours or even longer, causing multiple permanent faults at different times and in different areas. By deploying pre-disaster electric bus parking locations, the post-disaster travel distance can be effectively reduced and the power loss load lowered.

[0004] Furthermore, existing research typically focuses on fault recovery within a single distribution network. In reality, due to operational cost constraints, the recovery resources of a single distribution network are limited, making effective self-healing difficult. Utilizing power electronic devices to interconnect multiple distribution networks can leverage the IDS (Integrated Distribution System) resources of the interconnected distribution network to address the problem of insufficient recovery resources and limited recovery performance of a single distribution network. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by proposing a method for restoring interconnected power distribution networks before and after typhoon disasters based on reconfigurable soft switches. This method aims to identify and prevent potential fault risks before a disaster, and then dynamically schedule restoration resources such as electric buses and reconfigurable soft switches based on the actual fault situation after the disaster, accelerating power restoration. Furthermore, a dynamic restoration method with an embedded event-driven mechanism is proposed. This method aims to adapt to the evolution of faults and the uncertainties of renewable energy and loads by real-time triggering of strategy updates under persistent post-disaster fault conditions through customized fault events and predicted error events, thus overcoming the limitations of existing methods based on static scenarios.

[0006] To achieve the above-mentioned objectives, the present invention adopts the following technical solution: The present invention provides a method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching, characterized by the following steps: S1: Obtain the operating status of the interconnected distribution network, including: the topology of the interconnected distribution network, the location of controllable switches installed in the interconnected distribution network, the load demand of the interconnected distribution network, the output of renewable energy, the operating information of electric buses, and the operating information of electric bus charging stations; S2: Based on the operating status of the interconnected distribution network, predict the path and impact range of the typhoon, and combine the fault probability of the interconnected distribution network lines affected by the typhoon to predict the fault scenarios and corresponding fault probabilities that will occur in the interconnected distribution network under the typhoon disaster. S3: In the pre-typhoon phase, establish a reconfigurable soft switch model based on the operational information of the reconfigurable soft switches installed in the interconnected distribution network; S4: Based on the predicted fault scenarios and probabilities of the interconnected distribution network, and based on the reconfigurable soft-switching model, construct a dynamic reconfiguration model of the interconnected distribution network port topology and a fault flow model of the interconnected distribution network containing reconfigurable soft switches. S5: Based on the operation information of electric buses and electric bus charging stations, first fix the stopping position of electric buses, and then establish an electric bus parking power operation model based on the charging station's operating power. S6: Based on the interconnected distribution network port topology dynamic reconfiguration model, the interconnected distribution network fault flow model, and the electric bus parking power operation model, establish an electric bus pre-disaster deployment model to determine the deployment location of electric buses before a typhoon disaster. S7: Utilize an event-driven mechanism to define interconnected distribution network fault events and prediction error events as event-driven triggering conditions. When the operating status of the interconnected distribution network triggers the event-driven mechanism, update the fault scenario to respond to persistent faults in the interconnected distribution network under the continuous impact of typhoons and the uncertainty of renewable energy and load in the fault recovery of the interconnected distribution network. S8: In the post-typhoon phase, based on the pre-disaster deployment locations of electric buses, a time-sharing scheduling model for electric buses is constructed based on the operating power of charging stations. This model includes an electric bus routing model and an electric bus cruising power operation model to determine the driving routes and power plans of electric buses. S9: Construct an event-driven recovery model based on the interconnected distribution network fault events, interconnected distribution network prediction error events, and electric bus time-sharing scheduling model; S10: Establish and solve the precise scheduling power model for electric buses to obtain the power scheduling plan for each electric bus; S11: Transform the electric bus pre-disaster deployment model and event-driven recovery model into a mixed integer second-order cone programming model and solve it to obtain an interconnected power distribution network recovery scheme based on the power scheduling plan of each electric bus.

[0007] The characteristic of the typhoon-induced pre- and post-disaster interconnected distribution network restoration method based on reconfigurable soft switching described in this invention is that step S4 includes: S4-1: Construct a dynamic reconfiguration model of the port topology of an interconnected distribution network containing reconfigurable soft switches using equations (1)-(5); (1) (2) (3) (4) (5) In equations (1)-(5), Represents the set of all branches; It is a binary variable representing a node. and its adjacent nodes Whether they are connected, if =1 indicates a connection; if =0 indicates disconnection; Represents the set of all nodes; Represents a node Is it powered on? =1 indicates that electricity is applied; if =0 indicates disconnection; Indicates the number of power supplies; This represents the set of nodes that can be connected to the VSC converter; It is a binary variable representing a node. Whether the reconfigurable soft switch R-SOP connected at the point of connection is converted into a virtual power supply; Represents a node and its adjacent nodes Branch roads between Virtual trends on the internet; Represents a node Virtual power flow transmitted by virtual power source; It is a positive number; This indicates that for all directed nodes The nodes sum the injected power. This indicates that for all slave nodes The nodes sum the absorbed power; Dynamic variation constraints for the reconfigurable soft-switching R-SOP are constructed using equations (6) and (7): (6) (7) In equations (6)-(7), It is the smaller of the number of ports and the number of converters in the reconfigurable soft-switching R-SOP; It is a collection of converters; Indicates converter feeder With nodes Select the on / off state of the switch between them. =1 indicates a closed loop. =0 indicates disconnection; The energization state constraints of the nodes are constructed using equation (8): (8) In equation (8), It is a collection of disconnectable circuits, that is, the locations where tie switches and sectionalizing switches are installed. , Represents a node and its adjacent nodes The energized state; S4-2: Constructing a fault flow model for an interconnected distribution network with reconfigurable soft switching: S4-2-1: Using equation (9) to construct the voltage constraint of the VSC fault-side node of the converter: (9) In equation (9), Preset the voltage for voltage-frequency control mode; It is a node The voltage; S4-2-2: Establishing a fault flow model for an interconnected distribution network containing reconfigurable soft switches using equations (10)-(18): (10) (11) (12) (13) (14) (15) (16) (17) (18) In equations (10)-(18), and They are at time Flowing through the side road Active power and reactive power; and They are at time Inflow node Active power and reactive power; and They are branch roads Resistance and reactance; It is a moment Photovoltaic energy at nodes Output active power; At any moment Internal photovoltaic energy at nodes The output reactive power; It is a moment Charging station node Output active power; At any moment Static var compensator is a node Provided reactive power support; and They are time points node The active and reactive power losses of the load; Representative moment Time node If the switch status of the load connection is as follows: =1 indicates a connection; if =0 indicates disconnection; and These represent the upper and lower limits of the node voltage, respectively.

[0008] Furthermore, in step S5, the electric bus parking power operation model based on the charging station's operating power is obtained using equations (19)-(26): (19) (20) (twenty one) (twenty two) (twenty three) (twenty four) (25) (26) In equations (19)-(26), It is a collection of charging stations; , Representing time respectively charging station The charging and discharging power; , These represent the maximum allowable charging and discharging power for electric buses, respectively. Indicates charging station The number of parked electric buses; , Representing time respectively charging station The charging and discharging states; This indicates the total number of electric buses; This is the maximum number of electric buses that a charging station is allowed to park. Indicates time charging station The energized state, if =1 indicates that electricity is applied; if =0 indicates no power is supplied; Indicates time charging station The power; , These represent the charging and discharging efficiencies of the charging station, respectively. Indicates time charging station Stores electrical energy; Indicates the initial state of nuclear power; Indicates the battery level of the unit's electric buses; Indicates the minimum nuclear power state; This indicates the highest nuclear power state.

[0009] Furthermore, S6 includes: S6-1: Constructing the objective function of the electric bus pre-disaster deployment model using equations (27) and (28) : (27) (28) In equations (27)-(28), It is a collection of fault scenarios; It is a fault scenario The probability of occurrence; It is a fault scenario The resulting load shearing; It is a fault scenario Operating losses of the interconnected distribution network; It optimizes the length of the time period; It is the energy consumption of an electric bus per unit distance traveled. Indicates charging station to charging station The distance; It is a moment Fault Scenario Next node The total power loss of the reconfigurable soft switch R-SOP connected at the point; Indicates charging station The number of parked electric buses; , , There are 3 weighting coefficients; S6-2: Equations (1) to (8) are used as port and topology change constraints in the pre-disaster deployment model of electric buses; Equations (9) to (18) are used as system safety operation constraints in the pre-disaster deployment model of electric buses; and Equations (19) to (26) are used as electric bus constraints in the pre-disaster deployment model of electric buses.

[0010] Furthermore, S8 includes: S8-1: Establish an electric bus routing model using equations (29)-(33): (29) (30) (31) (32) (33) In equations (29)-(33), Indicates electric bus From charging station Move to charging station ; Indicates electric bus Whether to deploy at charging stations ; Indicates electric bus The target node is the charging station. ; Indicates electric bus Arrived at the charging station Time; Indicates that the electric bus departed from the charging station Move to charging station Travel time; Indicates time electric buses Is it at a charging station? Place; It is a constant; S8-2: Constructing a power operation model for electric bus cruising using equations (34)-(39): (34) (35) (36) (37) (38) (39) In equations (34)-(39), , Representing time respectively charging station The charging and discharging power; , These represent the maximum allowable charging and discharging power for electric buses, respectively. Indicates time charging station The number of parked electric buses; This refers to a collection of electric buses; , Representing time respectively charging station The charging and discharging states; This is the maximum number of electric buses that a charging station is allowed to park. Indicates time charging station The energized state, if =1 indicates that electricity is applied; if =0 indicates no power is supplied; Indicates time charging station The power; , These represent the charging and discharging efficiency and the electrical efficiency of the charging station, respectively. Using equations (40)-(45), we construct constraints that consider energy losses caused by electric buses traveling on the road: (40) (41) (42) (43) (44) (45) In equations (40)-(45), Indicates time New charging stations available The battery level of the electric bus; Indicates heading to a charging station electric buses The remaining battery power upon arrival at the charging station; Indicates that the electric bus departed from the charging station Move to charging station Travel distance; Indicates time charging station Stores electrical energy.

[0011] Furthermore, S9 includes: S9-1: Construct the objective function of the event-driven recovery model using equations (46) and (47). : (46) (47) In equations (46)-(47), This indicates the amount of electricity lost while the electric bus is in operation; Indicates the number of times the switch has been toggled; It is a fault scenario The resulting load shearing; It is a fault scenario System operating losses; It is the energy consumption of an electric bus per unit distance traveled. Indicates electric bus From charging station Move to charging station ,like =1 indicates movement; if =0 indicates no movement; Indicates that the electric bus departed from the charging station Move to charging station Travel distance; and It is an introduced 0 / 1 type auxiliary variable, representing the time... Converter feeder With nodes The switching state changes of the selector switch and at time [time] branch road The status changes of the remotely controllable switch on the upper system; , , , There are four weighting coefficients; S9-2: Using equations (48)-(49), construct the state change constraints of the feeder selection switch and the remotely controllable switch in the event-driven recovery model: (48) (49) In equations (48)-(49), Indicates time Converter feeder With nodes Select the on / off state of the switch between them; This represents a set of branches connected to a remotely controllable switch; Indicates at time branch road The on / off status of the remotely controllable switch on the upper system; S9-3: Equations (1)-(8) are used as port and topology change constraints in the event-driven recovery model, Equations (9)-(18) and (48)-(49) are used as system operation safety constraints in the event-driven recovery model, and Equations (29)-(45) are used as electric bus constraints in the event-driven recovery model.

[0012] Furthermore, step S10 includes: S10-1: Objective function for constructing a precise scheduling power model for electric buses using equation (50) : (50) In equation (50), , They are time points charging station The calculation error of charging and discharging power at the location; S10-2: Precise power operation constraints for constructing a precise scheduling power model for electric buses using equations (51)-(55): (51) (52) (53) (54) (55) In equations (51)-(55), , Representing time respectively The charging and discharging power of electric buses; , Representing time respectively charging station The charging and discharging states; Indicates time electric buses The amount of electricity; S10-3: Power correlation constraints for constructing a precise scheduling power model for electric buses using equations (56)-(59): (56) (57) (58) (59) In equations (56)-(59), , Representing time respectively electric buses At the charging station The charging and discharging power; , They are time points charging station Errors in calculating charging and discharging power at the location.

[0013] Furthermore, step S11 includes: S11-1: Constructing linearization constraints for the dynamic reconfiguration part of the interconnected distribution network using equations (60)-(63): (60) (61) (62) (63) In equations (60)-(63), branch road Auxiliary variables of the energized state; S11-2: Linearization constraints for constructing an electric bus operating power model based on charging station operating power using equations (64)-(66): (64) (65) (66) In equations (64)-(66), For a moment charging station The auxiliary variable of charging power; S11-3: Linearize equation (41) using equations (67)-(69): (67) (68) (69) In equations (67)-(69), For a moment electric buses At the charging station The amount of electricity.

[0014] The present invention provides an electronic device, including a memory and a processor, characterized in that the memory is used to store a program supporting the processor in performing the method described therein, and the processor is configured to execute the program stored in the memory.

[0015] The present invention discloses a computer-readable storage medium storing a computer program, characterized in that the computer program is executed by a processor to perform the steps of the method described thereon.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention effectively improves fault recovery efficiency. By utilizing the flexible resource coordination and scheduling between the interconnected distribution network supported by reconfigurable soft switches and distributed energy resources, the problem of insufficient recovery resources in a single distribution network is solved, achieving faster and more coordinated power supply restoration.

[0017] 2. This invention enhances adaptability and robustness. The event-driven mechanism dynamically updates the recovery strategy based on the continuous evolution of the fault and the operational uncertainties of distributed renewable energy and loads, maintaining reliable system operation even during continuous extreme events.

[0018] 3. This invention enhances system resilience. By combining pre-disaster prevention with post-disaster adaptive recovery, it strengthens the system's ability to resist, absorb, and recover from extreme disasters, ensuring stable and sustainable operation. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching. Figure 2 It is an improved 102-node system topology; Figure 3 It refers to the fault recovery effect of the interconnected distribution network under the actual implementation of the recovery strategy; Figure 4 It is the time when the event response occurs; Figure 5 It is the power curve of R-SOP during the recovery process; Figure 6This is a diagram showing the changes in the VSC control mode of the converter for the R-SOP optional feeder node during fault recovery. Figure 7 This is the scheduling path for EBs; Figure 8 It refers to the charging and discharging power of the charging station during the recovery process; Figure 9 It is a diagram showing the extreme values ​​of node voltages and voltage distribution in the power distribution system during the recovery process. Detailed Implementation

[0020] This embodiment presents a typhoon-induced pre- and post-disaster recovery method for interconnected power distribution networks based on reconfigurable soft switches. The method comprises two phases: pre-disaster prevention and post-disaster recovery. Before the disaster, potential typhoon-induced faults to the power distribution system are predicted. Stochastic planning ensures minimal load loss under fault conditions, thereby determining the pre-disaster deployment locations of electric buses and reducing their travel distance after the disaster to minimize power outage time. Considering the persistent impact of typhoons on the interconnected power distribution network, an event-driven recovery framework is embedded in the post-disaster recovery phase. Pre-set fault and error events respond to changes in the interconnected power distribution network's state. After each event is triggered, the fault recovery strategy is redefined based on the actual operating state of the interconnected power distribution network, updating the electric bus routes to fully utilize the electric bus capacity to support the network's fault recovery. Simultaneously, reconfigurable soft switches enable dynamic interconnection of multiple interconnected power distribution networks, maximizing power restoration to the affected areas using the network's reserve capacity. Specifically, the implementation process is as follows: Figure 1 As shown, it includes the following steps: S1: Obtain the operating status of the interconnected distribution network, including: the topology of the interconnected distribution network, the location of controllable switches installed in the interconnected distribution network, the load demand of the interconnected distribution network, the output of renewable energy, the operating information of electric buses, and the operating information of electric bus charging stations; S2: Based on the operating status of the interconnected distribution network, predict the path and impact range of the typhoon, and combine the fault probability of the interconnected distribution network lines affected by the typhoon to predict the fault scenarios and corresponding fault probabilities that will occur in the interconnected distribution network under the typhoon disaster. S3: In the pre-typhoon phase, establish a reconfigurable soft switch model based on the operational information of the reconfigurable soft switches installed in the interconnected distribution network.

[0021] S4: Based on the predicted fault scenarios and probabilities of the interconnected distribution network, and based on the reconfigurable soft-switching model, construct a dynamic reconfiguration model of the interconnected distribution network port topology and a fault flow model of the interconnected distribution network containing reconfigurable soft switches. S4-1: A dynamic reconfiguration model of a distribution network with reconfigurable soft-switching is established using modified virtual power flow constraints, wherein the reconfigurable soft-switching ports can be used as virtual power sources in the virtual power flow according to operational requirements.

[0022] A dynamic reconfiguration model of the port topology of an interconnected distribution network containing reconfigurable soft switches is constructed using equations (1)-(5). (1) (2) (3) (4) (5) In equations (1)-(5), Represents the set of all branches; It is a binary variable representing a node. and its adjacent nodes Whether they are connected, if =1 indicates a connection; if =0 indicates disconnection; Represents the set of all nodes; Represents a node Is it powered on? =1 indicates that electricity is applied; if =0 indicates disconnection; Indicates the number of power supplies; This represents the set of nodes that can be connected to the VSC converter; It is a binary variable representing a node. Whether the reconfigurable soft switch R-SOP connected at the point of connection is converted into a virtual power supply; Represents a node and its adjacent nodes Branch roads between Virtual trends on the internet; Represents a node Virtual power flow transmitted by virtual power source; It is a positive number. This indicates that for all directed nodes The nodes sum the injected power. This indicates that for all slave nodes Sum of the nodes absorbing power.

[0023] Reconfigurable soft switches can achieve feeder selection and port reconfiguration. In actual operation, they are not fixedly connected to certain feeders. Therefore, when modeling the reconfiguration of interconnected distribution networks containing reconfigurable soft switches, their dynamic changes must be considered. That is, the reconfiguration model needs to consider the operating state of the feeder selection switch to make it more realistic. The dynamic change constraints of the reconfigurable soft switch R-SOP are constructed using equations (6)-(7): (6) (7) In equations (6)-(7), It is the smaller of the number of ports and the number of converters in the reconfigurable soft-switching R-SOP; It is a collection of converters; Indicates converter feeder With nodes Select the on / off state of the switch between them. =1 indicates a closed loop. =0 indicates disconnection.

[0024] For lines with remote control switches installed, the switch state can only be changed when there is power supply on one side of the line. For lines without remote control switches installed, the energized state is consistent with the states of the nodes on both sides. The energized state constraints of the nodes are constructed using equation (8): (8) In equation (8), It is a collection of disconnectable circuits, that is, the locations where tie switches and sectionalizing switches are installed. , Represents a node and its adjacent nodes The energized state.

[0025] S4-2: Constructing a fault flow model for an interconnected distribution network with reconfigurable soft switching: S4-2-1: When a fault occurs in the interconnected distribution network, the reconfigurable soft switch can switch the feeder selection switch state to achieve feeder selection and converter (VSC) reconfiguration, and switch the control mode of the converter connected to the fault area to voltage-frequency control mode, providing voltage and frequency support for the fault area and protecting the voltage safety of the fault area. The fault-side node voltage of the converter using voltage-frequency control mode must meet the following constraints. The node voltage constraints of the VSC fault side of the converter are constructed using equation (9): (9) In equation (9), Preset the voltage for voltage-frequency control mode; It is a node The voltage.

[0026] S4-2-2: Since the Distributed Network Operator (DNO) is more concerned with load recovery after a fault occurs, a simplified model is used in this embodiment. Equations (10)-(18) are used to establish a fault flow model of the Distributed Network with reconfigurable soft switches: (10) (11) (12) (13) (14) (15) (16) (17) (18) In equations (10)-(18), and They are at time Flowing through the side road Active power and reactive power; and They are at time Inflow node Active power and reactive power; and They are branch roads Resistance and reactance; It is a moment Photovoltaic energy at nodes Output active power; At any moment Internal photovoltaic energy at nodes The output reactive power; It is a moment Charging station node Output active power; At any moment Static var compensator is a node Provided reactive power support; and They are at time At the node The active and reactive power losses of the load; Representative moment Time node If the switch status of the load connection is as follows: =1 indicates a connection; if =0 indicates disconnection; and These represent the upper and lower limits of the node voltage, respectively.

[0027] S5: Based on the operation information of electric buses and electric bus charging stations, first fix the stopping position of electric buses, and then establish an electric bus parking power operation model based on the charging station's operating power. The number of electric buses configured in the interconnected power distribution network area is large. Directly modeling the operating power of each electric bus would significantly increase the scale of variables in the fault recovery problem. Usually, the number of charging stations is much smaller than the number of electric buses. For the power modeling of charging stations, the energy loss generated by electric buses on the road also needs to be considered. When deploying pre-disaster parking locations, it is assumed that all electric buses at charging stations are external. If there are already electric buses parked at the charging station, it is assumed that these electric buses arrive at the charging station at a cost of 0. At the same time, the deployment location of electric buses is set to be fixed. Using equations (19)-(26), the electric bus parking power operation model based on the operating power of charging stations is used: (19) (20) (twenty one) (twenty two) (twenty three) (twenty four) (25) (26) In equations (19)-(26), It is a collection of charging stations; , Representing time respectively charging station The charging and discharging power; , These represent the maximum allowable charging and discharging power for electric buses, respectively. Indicates charging station The number of parked electric buses; , Representing time respectively charging station The charging and discharging states; This indicates the total number of electric buses; This is the maximum number of electric buses that a charging station is allowed to park. Indicates time charging station The energized state, if =1 indicates that electricity is applied; if =0 indicates no power is supplied; Indicates time charging station The power; , These represent the charging and discharging efficiencies of the charging station, respectively. Indicates time charging station Stores electrical energy; Indicates the initial state of nuclear power; Indicates the battery level of the unit's electric buses; Indicates the minimum nuclear power state; This indicates the highest nuclear power state.

[0028] S6: Based on the interconnected distribution network port topology dynamic reconfiguration model, the interconnected distribution network fault flow model, and the electric bus parking power operation model, establish an electric bus pre-disaster deployment model to determine the deployment location of electric buses before a typhoon disaster. S6-1: Constructing the objective function of the electric bus pre-disaster deployment model using equations (27) and (28) : (27) (28) In equations (27)-(28), It is a collection of fault scenarios; It is a fault scenario The probability of occurrence; It is a fault scenario The resulting load shearing; It is a fault scenario Operating losses of the interconnected distribution network; It is the energy consumption of an electric bus per unit distance traveled. Indicates charging station to charging station The distance; It is a moment Fault scenarios Next node The total power loss of the reconfigurable soft switch R-SOP connected at the point; Indicates charging station The number of parked electric buses; , , There are 3 weighting coefficients.

[0029] S6-2: Equations (1) to (8) are used as port and topology change constraints in the pre-disaster deployment model of electric buses; Equations (9) to (18) are used as system safety operation constraints in the pre-disaster deployment model of electric buses; and Equations (19) to (26) are used as electric bus constraints in the pre-disaster deployment model of electric buses.

[0030] S7: Utilize an event-driven mechanism to define interconnected distribution network fault events and prediction error events as event-driven triggering conditions. When the operating status of the interconnected distribution network triggers the event-driven mechanism, update the fault scenario to respond to persistent faults in the interconnected distribution network under the continuous impact of typhoons and the uncertainty of renewable energy and load during the fault recovery of the interconnected distribution network.

[0031] S8: In the post-typhoon phase, based on the pre-disaster deployment locations of electric buses, a time-based scheduling model for electric buses is constructed based on the operating power of charging stations. This model includes an electric bus routing model and an electric bus cruising power operation model to determine the electric bus routes and power plans.

[0032] S8-1: Establish an electric bus routing model using equations (29)-(33): (29) (30) (31) (32) (33) In equations (29)-(33), Indicates electric bus From charging station Move to charging station ; Indicates electric bus Whether to deploy at charging stations ; Indicates electric bus The target node is the charging station. ; Indicates electric bus Arrived at the charging station Time; Indicates that the electric bus departed from the charging station Move to charging station Travel time; Indicates time electric buses Is it at a charging station? Place; It is a constant.

[0033] S8-2: Constructing a power operation model for electric bus cruising using equations (34)-(39): (34) (35) (36) (37) (38) (39) In equations (34)-(39), , Representing time respectively charging station The charging and discharging power; , These represent the maximum allowable charging and discharging power for electric buses, respectively. Indicates time charging station The number of parked electric buses; This refers to a collection of electric buses; , Representing time respectively charging station The charging and discharging states; This is the maximum number of electric buses that a charging station is allowed to park. Indicates time charging station The energized state, if =1 indicates that electricity is applied; if =0 indicates no power is supplied; Indicates time charging station The power; , These represent the charging and discharging efficiency and the electrical efficiency of the charging station, respectively.

[0034] Using equations (40)-(45), we construct constraints that consider energy losses caused by electric buses traveling on the road: (40) (41) (42) (43) (44) (45) In equations (40)-(45), Indicates time New charging stations available The battery level of the electric bus; Indicates heading to a charging station electric buses The remaining battery power upon arrival at the charging station; Indicates that the electric bus departed from the charging station Move to charging station Travel distance; Indicates time charging station Stores electrical energy.

[0035] S9: Construct an event-driven recovery model based on the interconnected distribution network fault events, interconnected distribution network prediction error events, and electric bus time-sharing scheduling model; S9-1: Construct the objective function of the event-driven recovery model using equations (46) and (47). : (46) (47) In equations (46)-(47), This indicates the amount of electricity lost while the electric bus is in operation; Indicates the number of times the switch has been toggled; It is a fault scenario The resulting load shearing; It is a fault scenario System operating losses; It is the energy consumption of an electric bus per unit distance traveled. Indicates electric bus From charging station Move to charging station ,like =1 indicates movement; if =0 indicates no movement; Indicates that the electric bus departed from the charging station Move to charging station Travel distance; and It is an introduced 0 / 1 type auxiliary variable, representing the time... Converter feeder With nodes The switching state changes of the selector switch and at time [time] branch road The status changes of the remotely controllable switch on the upper system; , , , There are four weighting coefficients.

[0036] S9-2: Using equations (48)-(49), construct the state change constraints of the feeder selection switch and the remotely controllable switch in the event-driven recovery model: (48) (49) In equations (48)-(49), Indicates time Converter feeder With nodes Select the on / off state of the switch between them; This represents a set of branches connected to a remotely controllable switch; Indicates at time branch road The on / off status of the remotely controllable switch on the system.

[0037] S9-3: Equations (1)-(8) are used as port and topology change constraints in the event-driven recovery model, Equations (9)-(18) and (48)-(49) are used as system operation safety constraints in the event-driven recovery model, and Equations (29)-(45) are used as electric bus constraints in the event-driven recovery model.

[0038] S10: Establish a precise scheduling power model for electric buses and solve for the power scheduling plan for each electric bus.

[0039] S10-1: Objective function for constructing a precise scheduling power model for electric buses using equation (50) : (50) In equation (50), , They are time points charging station Errors in calculating charging and discharging power at the location.

[0040] S10-2: Precise power operation constraints for constructing a precise scheduling power model for electric buses using equations (51)-(55): (51) (52) (53) (54) (55) In equations (51)-(55), , Representing time respectively The charging and discharging power of electric buses; , Representing time respectively charging station The charging and discharging states; Indicates time electric buses The amount of electricity.

[0041] S10-3: By solving the event-driven recovery model, the operating power of each charging station can be obtained. The obtained charging and discharging power of the charging station is correlated with the charging and discharging power of the electric bus. The power correlation constraints of the precise scheduling power model of the electric bus are constructed using equations (56)-(59): (56) (57) (58) (59) In equations (56)-(59), , Representing time respectively electric buses At the charging station The charging and discharging power; , They are time points charging station Errors in calculating charging and discharging power at the location.

[0042] S11: Based on the electric bus pre-disaster deployment model and event-driven recovery model, the model is a mixed integer nonlinear programming problem. It is transformed into a mixed integer second-order cone programming problem and solved. Combined with the power scheduling plan of each electric bus, a complete interconnected power distribution network recovery scheme is obtained.

[0043] S11-1: Constructing linearization constraints for the dynamic reconfiguration part of the interconnected distribution network using equations (60)-(63): (60) (61) (62) (63) In equations (60)-(63), These are auxiliary variables introduced for the line.

[0044] S11-2: Linearization constraints for constructing an electric bus operating power model based on charging station operating power using equations (64)-(66): (64) (65) (66) In equations (64)-(66), For the moment charging station The auxiliary variable of charging power; By introducing auxiliary variables, the linearization of (41) is achieved using equations (67)-(69), as follows.

[0045] (67) (68) (69) In equations (67)-(69), For a moment A single electric bus At the charging station The amount of electricity; The remaining reconfigurable soft-switching model, interconnected distribution network fault flow model, electric bus routing model, event-driven recovery model, and electric bus precise scheduling power model can be transformed into mixed integer second-order cone programming problems and solved by means of variable substitution, introduction of auxiliary variables, second-order cone relaxation, and big-M method.

[0046] In this embodiment, an electronic device includes a memory and a processor. The memory stores a program that supports the processor in executing the above-described method, and the processor is configured to execute the program stored in the memory.

[0047] In this embodiment, a computer-readable storage medium stores a computer program, which is executed by a processor to perform the steps of the above method.

[0048] To enable those skilled in the art to better understand the present invention, the numerical example analysis includes the following components: I. Case Description and Simulation Result Analysis To verify its effectiveness, this invention used, for example... Figure 2The modified IEEE 102-node fault system topology diagram shown is used for example analysis. The system reference voltage is 12.66kV, the voltage safety range is set to 0.95pu-1.05pu, and the slack node voltage is 1.05pu. The total capacity of the equipped 4-port reconfigurable soft switches is 2MVA, and the capacity ratio of each VSC port is "0.5:0.309:0.118:0.073". The feeder nodes selectable by the R-SOP feeder selection switch are located at nodes 27, 35, 54, 81, and 91. The system additionally deploys photovoltaics at nodes 17, 46, 65, 76, and 97, each with a capacity of 2MVA and a power factor of 0.8. SVG is installed at nodes 68, 86, and 101, with a maximum reactive power output of 0.25MVar. Charging stations were set up at nodes 10, 18, 60, 73, and 99, each accommodating a maximum of 10 electric buses. The test system consisted of 30 electric buses. As the typhoon continuously struck the interconnected power distribution network, it caused multiple permanent faults in different areas of the network at different times. This paper assumes that the typhoon continuously affects the distribution area for 8 hours and uses the method described to achieve self-healing recovery of the power distribution system faults. The threshold for error events was set to 15%. The simulation calculations relied on the MATLAB 2024b (R2024b) software environment, where the optimization model was built using the YALMIP toolbox and solved using the Gurobi solver. The hardware environment consisted of a computer workstation configured with an Intel Core i7-8700 processor and 16 GB of memory.

[0049] like Figure 3 As shown, the actual load recovery rate in the interconnected distribution network scenario differs from the expected load recovery rate. This is because there will be an error between the predicted scenario and the actual scenario, and the range of prediction error usually increases with the increase of prediction time. Therefore, the actual load recovery rate under the implementation of the formulated recovery method is less than the expected load recovery rate, which is unavoidable. Therefore, we considered error events when formulating response events. When the cumulative error between the predicted scenario and the actual scenario exceeds an acceptable level, the system will update the predicted scenario.

[0050] like Figure 4 As shown, during the restoration of the interconnected distribution network, in addition to the preset fault events caused by the typhoon, preset error events were also triggered multiple times. This can avoid formulating restoration strategies that deviate too much from the actual scenario.

[0051] like Figure 5As shown, at 8:00, the interconnected distribution network experienced its first fault, resulting in a large-scale power island due to damage to the power supply lines. To facilitate power restoration in the power-out area, the R-SOP switchover of the feeder selection switch status enabled flexible interconnection between the two distribution networks, allowing the load in the power-out area to be restored through power transfer between feeder 91 and feeder 27.

[0052] like Figure 6 As shown in section (a), to maximize transmission power, the reconfigurable soft switch allocates converter capacity only to feeders 91 and 27. Subsequently, as the disaster continues to develop, the reconfigurable soft switch can dynamically adjust the converter allocation strategy according to the fault location using the event response mechanism, and rationally formulate a power plan.

[0053] like Figure 6 As shown in section (b), the converters connected to each feeder maintain the same control mode and change Vf control according to the fault location. During the recovery process when new fault islands are generated in the interconnected distribution network due to faults at 8:00, 10:15, and 13:15, the converters configured on feeders 91, 81, 54, and 27 connected to the islanded area switch to Vf control accordingly.

[0054] like Figure 7 and Figure 8 As shown, electric buses are dynamically dispatched to the fault area based on the actual fault scenario, working in conjunction with reconfigurable soft switches to support load restoration. At 8:00, the first fault occurred, and electric buses parked at charging stations 4 and 5 discharged power, working with the reconfigurable soft switches to facilitate load restoration in the power-loss area. At 10:15, a second fault occurred in the interconnected distribution network, creating a new power island. The reconfigurable soft switches reconfigured the converters, allocating some converters to feeder 54. The power received by feeders 81 and 91 from the reconfigurable soft switches was significantly reduced. At this time, charging station 4 significantly increased its power generation to support load demand.

[0055] like Figure 9 As shown in section (a), during the recovery process, the voltage at the interconnected distribution network nodes remained within the range of [0.95, 1.05] pu. Figure 9 As shown in part (b), the node voltages are mostly distributed near the standard value and higher values, which indicates that the proposed event-driven fault recovery method can effectively handle the uncertainties of photovoltaics and loads, and ensure voltage safety during the recovery process of interconnected distribution networks under continuous faults.

[0056] In this specification, the illustrative descriptions of the invention are not necessarily directed at the same embodiments or examples. Those skilled in the art can combine and integrate the different embodiments or examples described in this specification. Furthermore, the embodiments in this specification are merely enumerations of implementation forms of the inventive concept, and the scope of protection of the invention should not be considered as limited to the specific forms stated in the embodiments. The scope of protection of the invention also includes equivalent technical means that can be conceived by those skilled in the art based on the inventive concept.

Claims

1. A method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching, characterized in that, Includes the following steps: S1: Obtain the operating status of the interconnected distribution network, including: the topology of the interconnected distribution network, the location of controllable switches installed in the interconnected distribution network, the load demand of the interconnected distribution network, the output of renewable energy, the operating information of electric buses, and the operating information of electric bus charging stations; S2: Based on the operating status of the interconnected distribution network, predict the path and impact range of the typhoon, and combine the fault probability of the interconnected distribution network lines affected by the typhoon to predict the fault scenarios and corresponding fault probabilities that will occur in the interconnected distribution network under the typhoon disaster. S3: In the pre-typhoon phase, establish a reconfigurable soft switch model based on the operational information of the reconfigurable soft switches installed in the interconnected distribution network; S4: Based on the predicted fault scenarios and probabilities of the interconnected distribution network, and based on the reconfigurable soft-switching model, construct a dynamic reconfiguration model of the interconnected distribution network port topology and a fault flow model of the interconnected distribution network containing reconfigurable soft switches. S5: Based on the operation information of electric buses and electric bus charging stations, first fix the stopping position of electric buses, and then establish an electric bus parking power operation model based on the charging station's operating power. S6: Based on the aforementioned interconnected distribution network port topology dynamic reconfiguration model, interconnected distribution network fault flow model, and electric bus parking power operation model, establish an electric bus pre-disaster deployment model to determine the deployment location of electric buses before a typhoon disaster. S7: Utilize an event-driven mechanism to define interconnected distribution network fault events and prediction error events as event-driven triggering conditions. When the operating status of the interconnected distribution network triggers the event-driven mechanism, update the fault scenario to respond to persistent faults in the interconnected distribution network under the continuous impact of typhoons and the uncertainty of renewable energy and load in the fault recovery of the interconnected distribution network. S8: In the post-typhoon phase, based on the pre-disaster deployment locations of electric buses, a time-sharing scheduling model for electric buses is constructed based on the operating power of charging stations. This model includes an electric bus routing model and an electric bus cruising power operation model to determine the driving routes and power plans of electric buses. S9: Construct an event-driven recovery model based on the interconnected distribution network fault events, interconnected distribution network prediction error events, and electric bus time-sharing scheduling model; S10: Establish and solve the precise scheduling power model for electric buses to obtain the power scheduling plan for each electric bus; S11: Transform the electric bus pre-disaster deployment model and event-driven recovery model into a mixed integer second-order cone programming model and solve it to obtain an interconnected power distribution network recovery scheme based on the power scheduling plan of each electric bus.

2. The method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching as described in claim 1, characterized in that: Step S4 includes: S4-1: Construct a dynamic reconfiguration model of the port topology of an interconnected distribution network containing reconfigurable soft switches using equations (1)-(5); (1) (2) (3) (4) (5) In equations (1)-(5), Represents the set of all branches; It is a binary variable representing a node. and its adjacent nodes Whether they are connected, if =1 indicates a connection; if =0 indicates disconnection; Represents the set of all nodes; Represents a node Is it powered on? =1 indicates that electricity is applied; if =0 indicates disconnection; Indicates the number of power supplies; This represents the set of nodes that can be connected to the VSC converter; It is a binary variable representing a node. Whether the reconfigurable soft switch R-SOP connected at the point of connection is converted into a virtual power supply; Represents a node and its adjacent nodes Branch roads between Virtual trends on the internet; Represents a node Virtual power flow transmitted by virtual power source; It is a positive number; This indicates that for all directed nodes The nodes sum the injected power. This indicates that for all slave nodes The nodes sum the absorbed power; Dynamic variation constraints for the reconfigurable soft-switching R-SOP are constructed using equations (6) and (7): (6) (7) In equations (6)-(7), It is the smaller of the number of ports and the number of converters in the reconfigurable soft-switching R-SOP; It is a collection of converters; Indicates converter feeder With nodes Select the on / off state of the switch between them. =1 indicates a closed loop. =0 indicates disconnection; The energization state constraints of the nodes are constructed using equation (8): (8) In equation (8), It is a collection of disconnectable circuits, that is, the locations where tie switches and sectionalizing switches are installed. , Represents a node and its adjacent nodes The energized state; S4-2: Constructing a fault flow model for an interconnected distribution network with reconfigurable soft switching: S4-2-1: Using equation (9) to construct the voltage constraint of the VSC fault-side node of the converter: (9) In equation (9), Preset the voltage for voltage-frequency control mode; It is a node The voltage; S4-2-2: Establishing a fault flow model for an interconnected distribution network containing reconfigurable soft switches using equations (10)-(18): (10) (11) (12) (13) (14) (15) (16) (17) (18) In equations (10)-(18), and They are at time Flowing through the side road Active power and reactive power; and They are at time Inflow node Active power and reactive power; and They are branch roads Resistance and reactance; It is a moment Photovoltaic energy at nodes Output active power; At any moment Internal photovoltaic energy at nodes The output reactive power; It is a moment Charging station node Output active power; At any moment Static var compensator is a node Provided reactive power support; and They are time points node The active and reactive power losses of the load; Representative moment Time node If the switch status of the load connection is as follows: =1 indicates a connection; if =0 indicates disconnection; and These represent the upper and lower limits of the node voltage, respectively.

3. The method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching as described in claim 1, characterized in that, In step S5, the electric bus parking power operation model based on the charging station operating power is used, according to equations (19)-(26): (19) (20) (21) (22) (23) (24) (25) (26) In equations (19)-(26), It is a collection of charging stations; , Representing time respectively charging station The charging and discharging power; , These represent the maximum allowable charging and discharging power for electric buses; Indicates charging station The number of parked electric buses; , Representing time respectively charging station The charging and discharging states; This indicates the total number of electric buses; This is the maximum number of electric buses that a charging station is allowed to park. Indicates time charging station The energized state, if =1 indicates that electricity is applied; if =0 indicates no power is supplied; Indicates time charging station The power; , These represent the charging and discharging efficiency of the charging station, respectively. Indicates time charging station Stores electrical energy; Indicates the initial state of nuclear power; Indicates the battery level of the unit's electric buses; Indicates the minimum nuclear power state; This indicates the highest nuclear power state.

4. The method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching, as described in claim 2 or claim 3, is characterized in that... S6 includes: S6-1: Constructing the objective function of the electric bus pre-disaster deployment model using equations (27) and (28) : (27) (28) In equations (27)-(28), It is a collection of fault scenarios; It is a fault scenario The probability of occurrence; It is a fault scenario The resulting load shearing; It is a fault scenario Operating losses of the interconnected distribution network; It optimizes the length of the time period; It is the energy consumption of an electric bus per unit distance traveled. Indicates charging station To the charging station The distance; It is a moment Fault Scenario Next node Total power loss of the reconfigurable soft switch R-SOP connected at the point; Indicates charging station The number of parked electric buses; , , There are 3 weighting coefficients; S6-2: Equations (1)-(8) are used as port and topology change constraints in the pre-disaster deployment model of electric buses; Equations (9)-(18) are used as system safety operation constraints in the pre-disaster deployment model of electric buses; and Equations (19)-(26) are used as electric bus constraints in the pre-disaster deployment model of electric buses.

5. The method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching as described in claim 1, characterized in that, S8 include: S8-1: Establish an electric bus routing model using equations (29)-(33): (29) (30) (31) (32) (33) In equations (29)-(33), Indicates electric bus From charging station Move to charging station ; Indicates electric bus Whether to deploy at charging stations ; Indicates electric bus The target node is the charging station. ; Indicates electric bus Arrived at the charging station Time; Indicates that the electric bus departed from the charging station Move to charging station Travel time; Indicates time electric buses Is it at a charging station? Place; It is a constant; S8-2: Constructing a power operation model for electric bus cruising using equations (34)-(39): (34) (35) (36) (37) (38) (39) In equations (34)-(39), , Representing time respectively charging station The charging and discharging power; , These represent the maximum allowable charging and discharging power for electric buses; Indicates time charging station The number of parked electric buses; This refers to a collection of electric buses; , Representing time respectively charging station The charging and discharging states; This is the maximum number of electric buses that a charging station is allowed to park. Indicates time charging station The energized state, if =1 indicates that electricity is applied; if =0 indicates no power is supplied; Indicates time charging station The power; , These represent the charging and discharging efficiency of the charging station, respectively. Using equations (40)-(45), we construct constraints that consider energy losses caused by electric buses traveling on the road: (40) (41) (42) (43) (44) (45) In equations (40)-(45), Indicates time New charging stations available The battery level of the electric bus; Indicates heading to a charging station electric buses The remaining battery power upon arrival at the charging station; Indicates that the electric bus departed from the charging station Move to charging station Travel distance; Indicates time charging station Stores electrical energy.

6. The method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching as described in claim 5, characterized in that, S9 include: S9-1: Construct the objective function of the event-driven recovery model using equations (46) and (47). : (46) (47) In equations (46)-(47), This indicates the amount of electricity lost while the electric bus is in operation; Indicates the number of times the switch has been toggled; It is a fault scenario The resulting load shearing; It is a fault scenario System operating losses; It is the energy consumption of an electric bus per unit distance traveled. Indicates electric bus From charging station Move to charging station ,like =1 indicates movement; if =0 indicates no movement; Indicates that the electric bus departed from the charging station Move to charging station Travel distance; and It is an introduced 0 / 1 type auxiliary variable, representing the time... Converter feeder With nodes The switching state changes of the selector switch and at time [time] branch road The status changes of the remotely controllable switch on the upper system; , , , There are four weighting coefficients; S9-2: Using equations (48)-(49), construct the state change constraints of the feeder selection switch and the remotely controllable switch in the event-driven recovery model: (48) (49) In equations (48)-(49), Indicates time Converter feeder With nodes Select the on / off state of the switch between them; This refers to a set of branches connected to a remotely controllable switch; Indicates at time branch road The on / off status of the remotely controllable switch on the upper system; S9-3: Equations (1) to (8) are used as port and topology change constraints in the event-driven recovery model, Equations (9) to (18) and (48) to (49) are used as system operation safety constraints in the event-driven recovery model, and Equations (29) to (45) are used as electric bus constraints in the event-driven recovery model.

7. The method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching as described in claim 1, characterized in that, Step S10 includes: S10-1: Objective function for constructing a precise scheduling power model for electric buses using equation (50) : (50) In equation (50), , They are time points charging station The calculation error of the charging and discharging power at the location; S10-2: Precise power operation constraints for constructing a precise scheduling power model for electric buses using equations (51)-(55): (51) (52) (53) (54) (55) In equations (51)-(55), , Representing time respectively The charging and discharging power of electric buses; , Representing time respectively charging station The charging and discharging states; Indicates time electric buses The amount of electricity; S10-3: Power correlation constraints for constructing a precise scheduling power model for electric buses using equations (56)-(59): (56) (57) (58) (59) In equations (56)-(59), , Representing time respectively electric buses At the charging station The charging and discharging power; , They are time points charging station The calculation error of the charging and discharging power at that point.

8. The method for restoring interconnected distribution networks before and after typhoon disasters based on reconfigurable soft switching as described in claim 1, characterized in that, Step S11 includes: S11-1: Constructing linearization constraints for the dynamic reconfiguration part of the interconnected distribution network using equations (60)-(63): (60) (61) (62) (63) In equations (60)-(63), branch road Auxiliary variables of the energized state; S11-2: Linearization constraints for constructing an electric bus operating power model based on charging station operating power using equations (64)-(66): (64) (65) (66) In equations (64)-(66), For a moment charging station The auxiliary variable of charging power; S11-3: Linearize equation (41) using equations (67)-(69): (67) (68) (69) In equations (67)-(69), For a moment electric buses At the charging station The amount of electricity.

9. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store a program that supports a processor in executing the method of any one of claims 1-8, the processor being configured to execute the program stored in the memory.

10. A computer-readable storage medium storing a computer program thereon, characterized in that, The computer program is executed by the processor to perform the steps of the method according to any one of claims 1-8.

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