Power distribution network multi-resource first-aid repair recovery method, system and device based on V2G pre-scheduling and medium

Abstract

The invention belongs to the technical field of power system emergency recovery, and discloses a power distribution network multi-resource first-aid repair recovery method, system and device based on V2G pre-scheduling, and a medium, so as to solve the problem that the potential of the V2G technology in post-disaster first-aid repair cannot be fully exerted. The method comprises the following steps: acquiring power distribution network information and fault line information; an electric vehicle owner income model is constructed, and electric vehicle pre-scheduling is completed based on the model; a post-disaster multi-resource cooperative first-aid repair recovery model is constructed, schedulable parameters are input, the minimum comprehensive first-aid repair recovery cost of the power distribution network is taken as an optimization target, electric vehicle constraints, new energy power supply constraints, first-aid repair team operation constraints and power flow constraints are planned as a whole, the post-disaster multi-resource cooperative first-aid repair recovery model is solved by using a Gurobi commercial solver, and the optimal power distribution network comprehensive first-aid repair recovery cost is obtained. And outputting an optimal scheme for fault recovery. According to the method, the load loss scale of the post-disaster power distribution network is remarkably reduced by coordinating the charging and discharging behaviors of the electric vehicle and the output of the distributed renewable power supply.

Description

Technical Field

[0001] The present invention belongs to the technical field of emergency restoration of power systems, and particularly relates to a method, system, device and medium for multi-resource emergency repair and restoration of a distribution network based on V2G pre-scheduling. Background Art

[0002] Traditional distribution networks adopt a unidirectional power supply mode, that is, electric power is unidirectionally transmitted from the power generation side to the user side through the transmission network. With the popularization of distributed energy and electric vehicles, Vehicle-to-Grid (V2G) technology has realized the bidirectional flow of electric energy, making electric vehicles become schedulable energy storage units. In extreme weather events such as typhoons, the distribution network often suffers from regional power outages due to structural damages such as tower collapses and wire breaks. Traditional emergency repair methods mainly rely on manual inspections and sectional restorations, which have problems such as slow response speed and low resource allocation efficiency, and are difficult to effectively handle scenarios with multiple fault points occurring simultaneously. Although Vehicle-to-Grid (V2G) technology can theoretically provide emergency power supply support, the existing technologies still have the following deficiencies: First, there is a lack of a pre-disaster pre-scheduling mechanism, making it difficult to ensure that electric vehicles can respond in a timely manner during disasters; second, the matching degree between the spatio-temporal distribution characteristics of electric vehicles and the power grid restoration requirements is not fully considered; third, the collaborative optimization of Vehicle-to-Grid (V2G) technology with distributed wind and solar power sources and emergency repair teams has not been effectively integrated; fourth, there is a lack of a quantitative evaluation model to balance the relationship between power supply costs and restoration efficiency. These defects have led to the potential of Vehicle-to-Grid (V2G) technology in post-disaster emergency repair not being fully exploited, thereby restricting the improvement of the rapid restoration ability of the distribution network. Summary of the Invention

[0003] Based on the above-mentioned drawbacks and deficiencies existing in the prior art, one of the objectives of the present invention is to at least solve one or more of the above problems existing in the prior art. In other words, one of the objectives of the present invention is to provide a method, system, device and medium for multi-resource emergency repair and restoration of a distribution network based on V2G pre-scheduling that meet one or more of the foregoing requirements, so as to achieve the purpose of improving the post-disaster emergency repair efficiency of the distribution network.

[0004] To achieve the above-mentioned invention objective, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for multi-resource emergency repair and restoration of a distribution network based on V2G pre-scheduling, including the steps of: S1, obtaining distribution network information and fault line information, including the distribution network grid structure, the load of each node in the distribution network, the location information of the fault line, the traffic passing time between nodes in the distribution network, the location information of the electric vehicle power supply ports, the parameters of wind turbine generators, the parameters of photovoltaic generator sets, and the starting point information of the emergency repair team; S2, constructing an electric vehicle owner revenue model and completing the pre-scheduling of electric vehicles based on this. The schedulable parameters of the electric vehicle owner revenue model include power supply incentives, power supply revenue coefficients, residence time, charging power, and road fee compensation; S3, constructing a post-disaster multi-resource collaborative emergency repair and restoration model and inputting the schedulable parameters, with the minimum comprehensive emergency repair and restoration cost of the distribution network as the optimization goal, and taking into account the constraints of electric vehicles, new energy power supply, emergency repair team operation, and power flow constraints, and using the Gurobi commercial solver to solve the post-disaster multi-resource collaborative emergency repair and restoration model to output the optimal fault recovery plan.

[0005] As a preferred solution: The expression of the electric vehicle owner revenue model is , where is the power supply incentive for electric vehicle , is the revenue coefficient, converting the power supplied by electric vehicle into power supply revenue, is the residence time of electric vehicle at the power supply point , is the charging power of electric vehicle , is the road fee compensation for electric vehicle .

[0006] As a preferred solution: The comprehensive emergency repair and restoration cost of the distribution network includes the electric vehicle power supply cost , the new energy power supply cost , the emergency repair team scheduling cost , and the load loss cost , then its expression is ; The new energy power supply cost includes the wind turbine generator power supply cost and the photovoltaic generator set power supply cost , that is ; The electric vehicle power supply cost is composed of all electric vehicle power supply incentives, and its expression is , where is the number of electric vehicles, The number of power supply points for electric vehicles; The power supply cost of the wind turbine generator set Consists of the power supply compensations of all wind turbine generator sets, and its expression is , where in the formula, is the number of wind turbine generator sets, is the power supply compensation of the wind turbine generator set, is the power supply time of the wind turbine generator set, is the power supply price coefficient of the wind turbine generator set, is the wind power output; The power supply cost of the photovoltaic generator set Consists of the power supply compensations of all photovoltaic generator sets, and its expression is , where in the formula is the number of photovoltaic generator sets, is the power supply compensation of the photovoltaic generator set, is the power supply time of the photovoltaic generator set, is the power supply price coefficient of the photovoltaic generator set, is the photovoltaic power output; The dispatching cost of the emergency repair team Consists of the dispatching fees of all emergency repair teams at all nodes, and its expression is , where in the formula, is the total number of nodes in the distribution network system, is the total number of emergency repair teams, is the distance coefficient, which converts the dispatching distance into the dispatching cost, is a decision variable, indicating whether the emergency repair team travels from node to node, is the distance between node and node; The load shedding cost Is quantified as the total economic loss caused by the load loss at each node during the post-disaster restoration stage of the distribution network, and its expression is , where in the formula, is all periods of emergency repair and restoration, is the price coefficient, which converts the load shedding power into the load shedding cost, is the node status variable, indicating node at the state at is node at the load shedding amount at the moment.

[0007] As a preferred solution, the electric vehicle constraints include: After the electric vehicle owner completes the power supply task, there is still enough power to meet the travel demand, that is , where, is the electric vehicle Arrival at the power supply point Its own capacity when For the electric vehicle Leaving the power supply point Its own capacity; The output power of the electric vehicle does not exceed the capacity limit of the power supply point, that is , where For the electric vehicle The maximum output active power of the access point at time ; For the electric vehicle The power factor of the access point at time ; During the emergency repair power supply process, the electric vehicle should meet the space-time constraints, and its expression is , where For the electric vehicle Whether it arrives at the power supply point at time , , For the electric vehicle Whether it leaves the power supply point at time , ; The time for the electric vehicle to participate in the emergency repair power supply should meet the continuity constraint, and its expression is , where Is a decision variable, indicating whether the electric vehicle Goes from node To node , Is the extreme value of the emergency repair time of the electric vehicle, Is the time when the electric vehicle arrives at node , Is the time spent by the electric vehicle in the emergency repair at node , For the electric vehicle From node To node The time spent.

[0008] As a preferred solution: The new energy power supply constraint includes a wind turbine constraint and a photovoltaic unit constraint; The wind turbine constraint includes a wind power output characteristic constraint, that is , , , , where Is the wind power output, Is the air density, Is the swept area of the wind turbine of the wind power generation unit, is the wind speed per hour, is the wind energy utilization coefficient, is a calculation parameter, is the pitch angle of the wind turbine, is the tip speed ratio of the wind turbine, is the rotor speed of the wind turbine, is the rotor radius, is the transmission ratio of the wind turbine; The wind turbine constraints also include wind speed constraints, that is , where is the cut-in wind speed of the wind turbine, is the cut-out wind speed of the wind turbine, is the wind speed at which the wind turbine just reaches its maximum output, is the maximum output power of the wind turbine; The wind turbine constraints also include upper and lower limits on wind power output, that is , where is the total number of wind turbines; The photovoltaic unit constraints include photovoltaic output characteristic constraints, that is , , , where is the output power of the photovoltaic generator per hour, is the solar radiation intensity, is the solar radiation intensity under standard test conditions, is the performance coefficient of the solar panel, is the power thermal coefficient, is the reference temperature under standard test conditions, is the temperature of the solar panel, , , , are all battery parameters; The photovoltaic unit constraints also include upper and lower limits on photovoltaic output, that is , where is the total number of photovoltaic units.

[0009] As a preferred solution, the repair team operation constraints include: In the repair task assignment, to ensure the independence of the repair team, each fault point is handled by only one team, that is , where indicates whether the node is selected by the repair team ; The repair team The movement path between fault points satisfies the flow conservation, that is , ; The time for the emergency repair team to participate in power supply emergency repair meets the continuity constraint, that is , where is the extreme value of the emergency repair time of the emergency repair team, is the time when the emergency repair team arrives at node , is the time spent by the emergency repair team in emergency repair at node , is the time when the emergency repair team from node to node ; The emergency repair team needs to complete the emergency repair scheduling of all fault points in the distribution network, that is , is the total number of fault points in the distribution network after typhoon disaster.

[0010] As a preferred solution, the power flow constraint includes: The operation of the distribution network needs to consider the power balance of each node itself, that is , , where and are the active power and reactive power input at node at moment, and are the active power and reactive power of the power supply at node at moment, and are the active power loss load power and reactive power loss load power at node at moment, and node at moment of active load and reactive load; The power of the transmission line should meet the upper and lower limit constraints, that is , , where and are the upper limits of active power and reactive power of the transmission line; The output of each generator set should meet the upper and lower limit constraints, that is , , where and are the upper limits of active power output and reactive power output of all generator sets at node .

[0011] In a second aspect, the present invention provides a multi-resource emergency repair and restoration system for a distribution network based on V2G pre-scheduling, which is used to implement the multi-resource emergency repair and restoration method for a distribution network as described in the first aspect.

[0012] In a third aspect, the present invention provides an electronic device, where the computer device includes a memory, a processor, and a computer program, and when the computer program is executed by the processor, it implements the multi-resource emergency repair and restoration method for a distribution network as described in the first aspect.

[0013] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by the processor, it implements the multi-resource emergency repair and restoration method for a distribution network as described in the first aspect.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. By constructing an electric vehicle owner benefit model, the present invention effectively improves the willingness of users to participate in the pre-scheduling of electric vehicles before disasters. This model fully considers the economic interests of vehicle owners, thus motivating more vehicle owners to actively cooperate with the scheduling arrangements before disasters.

[0015] 2. The present invention establishes a post-disaster multi-resource collaborative emergency repair and restoration model, which integrates key resources such as wind turbine generators, photovoltaic generator sets, and emergency repair teams. In terms of setting the optimization objective, the present invention is oriented towards minimizing the comprehensive emergency repair and restoration cost of the distribution network, and comprehensively considers the spatio-temporal constraints of electric vehicles, the output characteristics constraints of wind and light units, the operation constraints of emergency repair teams, and the power flow constraints of the power grid.

[0016] 3. During the solution process, the present invention uses a Gurobi commercial solver to efficiently solve the model, and finally forms an optimal emergency repair and restoration plan. This plan not only considers the reasonable allocation of resources but also ensures the orderly progress of emergency repair work.

[0017] 4. By coordinating the charging and discharging behaviors of electric vehicles with the output of distributed renewable energy sources, the present invention significantly reduces the load shedding scale of the post-disaster distribution network. This innovation not only improves the disaster resistance ability of the distribution network but also provides strong support for post-disaster power restoration.

[0018] Furthermore, more detailed beneficial effects will be described in combination with specific embodiments in the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0020] Figure 1 It is a schematic flowchart of the multi-resource emergency repair and restoration method for the distribution network according to the embodiments of the present invention.

[0021] Figure 2 It is a diagram of the system fault situation in XY City according to Embodiment 1 of the present invention.

[0022] Figure 3 It is a wind speed detection diagram according to Embodiment 1 of the present invention.

[0023] Figure 4 It is a solar radiation intensity monitoring diagram according to Embodiment 1 of the present invention.

[0024] Figure 5 It is a temperature monitoring diagram according to Embodiment 1 of the present invention.

[0025] Figure 6 It is a pre-scheduling result diagram of electric vehicles according to Embodiment 1 of the present invention.

[0026] Figure 7 It is a diagram of the output of various resources according to Embodiment 1 of the present invention.

[0027] Figure 8 It is a scheduling result diagram of the emergency repair team according to Embodiment 1 of the present invention.

[0028] Figure 9 It is a structural diagram of the electronic device according to the embodiments of the present invention.

[0029] Reference numerals in the drawings: 900, electronic device; 901, processor; 902, communication bus; 903, user interface; 904, network interface; 905, memory. Detailed implementation manners

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention.

[0031] In the following description, multiple embodiments of the present invention are provided, and different embodiments can be replaced or combined. Therefore, the present invention can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then the present invention should also be considered to include embodiments that contain one or more of all other possible combinations of A, B, C, and D, even though such embodiments may not be explicitly described in the following content in words.

[0032] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes can be made to the functions and arrangements of the described elements without departing from the scope of the content of the present invention. Various processes or components can be appropriately omitted, substituted, or added in each example. For example, the described method can be executed in a different order than the described order, and various steps can be added, omitted, or combined. In addition, the features described for some examples can be combined into other examples.

[0033] To facilitate a better understanding of the embodiments of the present invention, before explaining and illustrating the specific implementation manners of the present invention in detail, its application scenarios will be described first.

[0034] The multi-resource emergency repair and restoration method for the distribution network described in the embodiments of this specification is applied to the emergency repair process of distribution network failures caused by natural disasters (such as typhoons, heavy rains, earthquakes, etc.). In these scenarios, the application of the multi-resource emergency repair and restoration method for the distribution network aims to quickly restore power supply, optimize resource utilization, and enhance response capabilities.

[0035] Embodiment 1: This embodiment provides a multi-resource emergency repair and restoration method for the distribution network based on V2G pre-scheduling. This embodiment is combined with Figures 1 to 8 the introduction based on its actual application scenario, and the specific steps are as follows: Step S1: Obtain distribution network information and fault line information, including at least obtaining the distribution network grid structure, the load of each node in the distribution network, the location information of the fault line, the traffic line passing time of each node in the distribution network, the electric vehicle power supply ports, and the starting points of the repair teams. This embodiment is applied to the IEEE 33-node distribution system, which has a total of 13 fault nodes, 3 V2G power supply ports, and 1 starting point of the repair team. Among them, the 13 distribution network fault points are shown in Table 1, the V2G power supply ports 1-3 are located at nodes 13, 19, and 30 respectively, the wind turbine generator is located at node 33, the photovoltaic generator is located at node 21, the starting point of the repair team is located at node 32, and the XY city system fault situation diagram is as Figure 2 shown, the wind speed detection diagram is as Figure 3 shown, the solar radiation intensity monitoring diagram is as Figure 4 shown, and the temperature monitoring diagram is asFigure 5 As shown in the figure, the travel times of traffic lines at each node of the distribution network are shown in Table 2.

[0036] Table 1:

[0037] Table 2:

[0038] Step S2: Construct an electric vehicle owner's revenue model to enhance user participation willingness and complete the pre-scheduling of electric vehicles before a disaster. The electric vehicle owner's revenue model is:

[0039] Among them, is the power supply incentive for electric vehicles, is the revenue coefficient, , convert the power supplied by the electric vehicle into power supply revenue, is the residence time of the electric vehicle at the power supply point, is the charging power of the electric vehicle, , is the road fee compensation for electric vehicles.

[0040] Step S3: Establish a post-disaster multi-resource collaborative repair and restoration model, integrate wind turbine generators, photovoltaic generator sets, and repair team resources, with the goal of minimizing the comprehensive repair and restoration cost of the distribution network, taking into account the spatio-temporal constraints of electric vehicles, the power supply constraints of new energy sources, the operation constraints of repair teams, and the power flow constraints, and use the Gurobi commercial solver to solve the model.

[0041] The post-disaster multi-resource collaborative repair and restoration model described in Step S3 is specifically as follows: Step S3.1: Take the minimum of the comprehensive repair and restoration cost of the post-disaster distribution network as the objective function, and the specific expression is:

[0042] Among them, is the comprehensive repair and restoration cost of the distribution network, is the power supply cost of electric vehicles, is the power supply cost of new energy sources, which consists of and , is the power supply cost of wind turbine generators, is the power supply cost of photovoltaic generator sets, is the scheduling cost of repair teams, is the loss-of-load cost.

[0043] (1) The power supply cost of electric vehicles is composed of all power supply incentives for electric vehicles:

[0044] Among them, is the number of electric vehicles, , is the number of power supply points for electric vehicles, .

[0045] (2) The power supply cost of wind turbine generators consists of the power supply compensation of all wind turbine generators:

[0046] Among them, is the number of wind turbine generators, , is the power supply compensation of wind turbine generators, is the power supply time of wind turbine generators, , is the power supply price coefficient of wind turbine generators, , is the wind power output.

[0047] (3) The power supply cost of photovoltaic generator sets consists of the power supply compensation of all photovoltaic generator sets:

[0048] Among them, is the number of photovoltaic generator sets, , is the power supply compensation of photovoltaic generator sets, is the power supply time of photovoltaic generator sets, , is the power supply price coefficient of photovoltaic generator sets, , is the photovoltaic power output.

[0049] (4) The dispatching cost of the emergency repair team is:

[0050] Among them, is all nodes of the system, , is the total number of emergency repair teams, , is the distance coefficient, which converts the dispatching distance into the dispatching cost, , is the decision variable, indicating whether the emergency repair team travels from node to node, is the distance between node and node.

[0051] (5) The load shedding cost during the post-disaster restoration stage of the distribution network can be quantified as the total economic loss caused by the load loss at each node:

[0052] Among them, is for all periods of emergency repair and restoration, is the electricity price coefficient, which converts the load shedding power into the load shedding cost, , is the node status variable, indicating the node at time, is the node at time.

[0053] Step S3.2: The electric vehicle constraint conditions that the post-disaster multi-resource collaborative emergency repair and restoration model needs to meet are: (1) When electric vehicles participate in the dispatching of power distribution network power supply restoration, it is necessary to ensure that electric vehicle owners can still retain sufficient power to meet travel needs after completing the power supply task:

[0054] Among them, is the capacity of the electric vehicle when it arrives at the power supply point , is the capacity of the electric vehicle when it leaves the power supply point .

[0055] The output power of electric vehicles should not exceed the capacity limit of the power supply point:

[0056] Among them, is the maximum output active power of the access point at the time of the electric vehicle, is the power coefficient of the access point at the time of the electric vehicle.

[0057] (3) Electric vehicles should meet spatio-temporal constraints during the emergency repair power supply process:

[0058] Among them, is whether the electric vehicle arrives at the power supply point at the time , is whether the electric vehicle leaves the power supply point at the time .

[0059] (4)The time for electric vehicles to participate in emergency power repair should meet the continuity constraint:

[0060] Among them, is a decision variable, indicating whether the electric vehicle travels from node to node . is the extreme value of the emergency repair time of the electric vehicle, , is the time when the electric vehicle arrives at node , is the time spent on emergency repair by the electric vehicle at node , is the time spent by the electric vehicle traveling from node to node .

[0061] Step S3.3: The wind turbine constraint conditions that the post-disaster multi-resource collaborative emergency repair and restoration model needs to meet are: (1)Wind power output:

[0062]

[0063]

[0064]

[0065] Among them: is the wind power output; is the air density, , is the swept area of the wind turbine rotor, , is the wind speed per hour, is the wind energy utilization coefficient, is a calculation parameter, is the pitch angle of the wind turbine, , is the tip speed ratio of the wind turbine, is the rotor speed of the wind turbine, is the rotor radius, , is the transmission ratio of the wind turbine, .

[0066] (2)The wind turbine output should meet the wind speed constraint:

[0067] Among them: is the cut-in wind speed of the wind turbine generator set, , is the cut-out wind speed of the wind turbine generator set, , is the wind speed at which the wind turbine generator set just reaches its maximum output, is the maximum output power of the wind turbine generator set, .

[0068] (3) The wind turbine generator set should satisfy the upper and lower limits of output constraint:

[0069] Step S3.4: The constraint conditions that the post-disaster multi-resource collaborative repair and restoration model needs to satisfy for the photovoltaic generator set are: (1) Output of the photovoltaic generator set:

[0070]

[0071]

[0072] Among them: is the output power of the photovoltaic generator set per hour, is the solar radiation intensity, is the solar radiation intensity under standard test conditions, , is the performance coefficient of the battery panel, is the power thermal coefficient, , is the reference temperature under standard test conditions, , is the battery panel temperature, 、 、 、 are all battery parameters , , , .

[0073] (2) The output of the photovoltaic generator set should satisfy the upper and lower limits of output constraint:

[0074] Among them: is the upper limit of the output of the photovoltaic generator set, .

[0075] Step S3.5: The constraint conditions that the post-disaster multi-resource collaborative repair and restoration model needs to satisfy for the repair team are: (1) In the emergency repair task allocation, to ensure the independence of the emergency repair teams, it is necessary to ensure that each fault point is handled by only one team:

[0076] Among them, indicates whether the node is selected by the emergency repair team.

[0077] (2) The movement path of the emergency repair team between fault points needs to satisfy the flow conservation:

[0078]

[0079] (3) The time for the emergency repair team to participate in power supply emergency repair should satisfy the continuity constraint:

[0080] Among them, is the extreme value of the emergency repair time of the emergency repair team, , is the emergency repair team arriving at node time, is the emergency repair team at node emergency repair time spent, is the emergency repair team from node to node time spent.

[0081] (4) The emergency repair team needs to complete the emergency repair scheduling of all fault points in the distribution network:

[0082] Among them, is the total number of fault points in the distribution network after the typhoon disaster.

[0083] Step S3.6: The power flow constraint conditions that the post-disaster multi-resource collaborative emergency repair and restoration model needs to satisfy are: (1) The operation of the distribution network needs to consider the power balance of each node itself:

[0084]

[0085] Among them, and are the active power and reactive power input by node at time, and are the active power and reactive power output by node At the active power and reactive power of the power supply at the moment, and is the node At the active power loss load and reactive power loss load at the moment, and the node At the active load and reactive load at the moment.

[0086] (2) The power of the transmission line should satisfy the upper and lower limit constraints:

[0087]

[0088] Among them, and are the upper limits of the active power and reactive power of the transmission line.

[0089] (3) The output of each generator set should satisfy the upper and lower limit constraints:

[0090]

[0091] Among them, and are the upper limits of the active power output and reactive power output of all generator sets at node .

[0092] Step S3.7: Use the Gurobi solver to solve the linearized model and output the optimal solution for the repair and restoration of the distribution network. The pre-scheduling result diagram of electric vehicles is as shown in Figure 6 , the output diagram of various resources is as shown in Figure 7 , and the scheduling result diagram of the repair team is as shown in Figure 8 .

[0093] Based on the above, this embodiment verifies the effectiveness of a distribution network multi-resource repair and restoration method based on V2G pre-scheduling in this specification.

[0094] Embodiment 2: This embodiment provides a distribution network multi-resource repair and restoration system based on V2G pre-scheduling, which is used to implement the distribution network multi-resource repair and restoration method described in Embodiment 1.

[0095] Embodiment 3: As shown in Figure 9As shown in the figure, this embodiment provides an electronic device, which may include: at least one processor, at least one network interface, a user interface, a memory, and at least one communication bus.

[0096] Among them, the communication bus can be used to realize the connection and communication of the above-mentioned components.

[0097] Among them, the user interface may include buttons, and the optional user interface may further include a standard wired interface and a wireless interface.

[0098] Among them, the network interface can but is not limited to including a Bluetooth module, an NFC module, a Wi-Fi module, etc.

[0099] Among them, the processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts within the entire electronic device, and by running or executing instructions, programs, code sets, or instruction sets stored in the memory, and by calling data stored in the memory, it executes various functions of the electronic device and processes data. Optionally, the processor may be implemented in at least one of the hardware forms of DSP, FPGA, and PLA. The processor may integrate one or several combinations of CPU, GPU, and modem, etc. Among them, the CPU mainly processes the operating system, user interface, and application programs, etc.; the GPU is responsible for the rendering and drawing of the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor and may be implemented separately by a single chip.

[0100] Among them, the memory may include RAM and may also include ROM. Optionally, the memory includes a non-transitory computer-readable medium. The memory can be used to store instructions, programs, code, code sets, or instruction sets. The memory may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store the data involved in the above-mentioned various method embodiments, etc. Optionally, the memory may also be at least one storage device located far from the aforementioned processor. As a computer storage medium, the memory may include an operating system, a network communication module, a user interface module, and a repair and recovery application program. The processor can be used to call the repair and recovery application program stored in the memory and execute the repair and recovery steps mentioned in the foregoing embodiments.

[0101] Embodiment Four: This embodiment provides a computer-readable storage medium, in which instructions are stored. When they run on a computer or a processor, the computer or the processor is caused to execute the above Figure 1Steps of one or more of the illustrated embodiments. If each component module of the above electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in the computer-readable storage medium.

[0102] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this specification are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a Digital Versatile Disc (DVD)), or a semiconductor medium (for example, a Solid State Disk (SSD)), etc.

[0103] Those of ordinary skill in the art can understand that all or part of the processes of implementing the method in the above Embodiment 1 can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above various methods. The aforementioned storage medium includes: various media such as ROM, RAM, magnetic disks, or optical discs that can store program codes. Without conflict, the technical features in this embodiment and the implementation solutions can be combined arbitrarily.

[0104] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present invention is not limited by the described order of actions, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0105] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0106] The foregoing are only exemplary embodiments of the present invention and should not be used to limit the scope of the present invention. That is, any equivalent changes and modifications made in accordance with the teachings of the present invention still fall within the scope covered by the present invention. After considering the specification and practicing the disclosure herein, those skilled in the art will readily conceive of other embodiments of the present invention. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common general knowledge or conventional technical means in the technical field not recorded in the present invention. The specification and embodiments are only regarded as exemplary, and the scope and spirit of the present invention are defined by the claims.

Claims

1. A method for multi-resource emergency repair and restoration of a distribution network based on V2G pre-scheduling, characterized in that, Includes steps: S1. Obtain distribution network information and fault line information, including distribution network grid structure, load of each node of distribution network, location information of fault line, traffic travel time between distribution network nodes, location information of electric vehicle power supply port, parameters of wind turbine generator set, parameters of photovoltaic generator set and departure point information of emergency repair team; S2. Constructing an electric vehicle owner's profit model and completing electric vehicle pre-dispatch based on the model, wherein the dispatchable parameters of the electric vehicle owner's profit model include power supply incentives, power supply profit coefficients, stay time, charging power, and road fee compensation; S3. Construct a post-disaster multi-resource collaborative repair and recovery model and input the dispatchable parameters. Take the minimization of the comprehensive repair and recovery cost of the distribution network as the optimization goal, coordinate the electric vehicle constraints, new energy power supply constraints, repair team operation constraints and power flow constraints, and use the Gurobi commercial solver to solve the post-disaster multi-resource collaborative repair and recovery model to output the optimal fault recovery plan.

2. A method for multi-resource emergency repair and restoration of a distribution network based on V2G pre-scheduling according to claim 1, characterized in that, The expression of the electric vehicle owner's profit model is: ， Wherein, is the power supply excitation of the electric vehicle , is the revenue coefficient, which converts the power supplied by the electric vehicle into power supply revenue is the time the electric vehicle stays at the power supply point , is the charging power of the electric vehicle , is the road toll compensation of the electric vehicle .

3. According to claim 2, a distribution network multi-resource emergency repair and recovery method based on V2G pre-dispatching is characterized in that: The comprehensive repair and restoration cost of the distribution network includes the electric vehicle power supply cost, the new energy power supply cost, the repair team dispatch cost and the load loss cost; The new energy power supply cost includes the power supply cost of wind turbines and photovoltaic power generation units; The electric vehicle power supply cost is composed of all electric vehicle power supply incentives; The power supply cost of the wind turbine generator set is composed of the power supply compensation of all wind turbine generator sets; The power supply cost of the photovoltaic generator set is composed of the power supply compensation of all photovoltaic generator sets; The repair team dispatching cost is composed of all repair team dispatching costs of all nodes; The load loss cost is quantified as the total economic loss caused by the load loss of each node in the distribution network post-disaster recovery phase.

4. A method for multi-resource emergency repair and restoration of a distribution network based on V2G pre-scheduling according to claim 3, characterized in that The electric vehicle constraints include: Electric car owners still have enough power to meet travel needs after completing the power supply task; The output power of the electric vehicle does not exceed the capacity limit of the power supply point; The space-time constraint is expressed as ， Wherein, is an electric vehicle at whether the power supply point is reached at the moment , is an electric vehicle at whether the power supply point is left at the moment ; The continuity constraint is expressed as ， In the formula, is a decision variable, indicating whether the electric vehicle travels from node to node , is the extreme value of the emergency repair time of the electric vehicle, is the time when the electric vehicle arrives at node , is the time spent on emergency repair of the electric vehicle at node , is the time spent by the electric vehicle traveling from node to node .

5. According to claim 4, a distribution network multi-resource emergency repair and recovery method based on V2G pre-dispatching is characterized in that: The renewable energy power supply constraints include wind turbine constraints and photovoltaic turbine constraints; The wind turbine constraints include wind output characteristic constraints, wind speed constraints, and wind output upper and lower limit constraints; The photovoltaic unit constraints include photovoltaic output characteristic constraints and photovoltaic output upper and lower limit constraints.

6. A method for multi - resource emergency repair and restoration of a distribution network based on V2G pre - scheduling according to claim 5, characterized in that, The repair team operation constraints include: In order to ensure the independence of the repair teams in the allocation of repair tasks, each fault point is handled by only one team; The movement path of the repair team between fault points satisfies the flow conservation principle; The time that the emergency repair team participates in the emergency power supply repair meets the continuity constraint; The emergency repair team needs to complete the emergency repair dispatch of all fault points in the distribution network.

7. A method for multi-resource emergency repair and restoration of a distribution network based on V2G pre-scheduling according to claim 6, characterized in that The power flow constraints include: The operation of the distribution network needs to consider the power balance of each node; The transmission line power should meet the upper and lower limit constraints; The output of each generator set should meet the upper and lower limit constraints.

8. A multi-resource emergency repair and restoration system for a distribution network based on V2G pre-scheduling, characterized in that, Used to implement the distribution network multi-resource emergency repair and recovery method as described in any one of claims 1 to 7.

9. A computer device, the computer device comprising a memory, a processor, and a computer program, characterized in that, When the computer program is executed by a processor, it implements the multi-resource emergency repair and restoration method for a distribution network according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the multi-resource emergency repair and restoration method for a distribution network according to any one of claims 1 to 7.

Images