Electric traffic coupling cooperative scheduling method and terminal considering traffic network topology

Abstract

The invention relates to the technical field of power grid control, and discloses an electric traffic coupling cooperative scheduling method considering traffic network topology and a terminal. According to the method, a traffic system scheduling model is constructed based on current road topology information and road traffic flow of a traffic system, an electric power system scheduling model is constructed based on power generation information of an electric power system, and operation cost is solved through an electric traffic coupling system scheduling model constructed by the traffic system scheduling model and the electric power system scheduling model. And target road topology information and power generation data under the optimal operation cost are obtained, so that a cooperative scheduling scheme is generated. Compared with isolated scheduling processing of a power grid and a traffic network, the method makes full use of the flexibility of a traffic network topology structure, topology reconstruction is performed by adjusting road topology information of a traffic system, and redistribution of traffic flow is realized, so that the charging behavior of the electric vehicle is guided, and the charging efficiency is improved. Meanwhile, the power generation cost of a power grid and the travel cost of a traffic network are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid control, and in particular to a method and terminal for coordinated dispatching of power-traffic coupling taking into account the topology of a traffic network. Background Art

[0002] The global fossil energy crisis is attracting more and more attention, the widespread use of electric vehicles is still accelerating, and the rapid growth of electric vehicle ownership has made the connection between the power grid and the urban transportation network closer. Therefore, it is crucial to coordinate the dispatch of the power grid and the transportation network to achieve the optimal operation of the coupled system.

[0003] At present, the power dispatching of the power grid and the traffic dispatching of the transportation network are usually handled separately. This split dispatching mode can easily lead to power line overload and traffic congestion when facing the scenario of large-scale access to the power grid for charging of electric vehicles. On the one hand, as an important load of the power system, electric vehicles may uncontrollably choose the same charging station when charging their batteries during peak hours, resulting in over-limit of power line feed, which has an adverse impact on the safety and economic operation of the power system. On the other hand, a large number of electric vehicles may queue up near the same charging station at the same time, which not only increases the burden on the power system, but also easily leads to traffic jams near the charging station. Therefore, electric vehicles play a vital role in coupling the two systems. By reasonably guiding the charging behavior of electric vehicles, it is expected to significantly reduce the congestion and cost of the power grid and transportation network.

[0004] Although there have been studies dedicated to solving the problem of coordinated scheduling of electric-transport coupling and exploring the flexibility of electric vehicles and charging stations in the transportation network, these studies generally ignore the flexibility of the transportation network topology. In existing studies, the transportation network topology is often regarded as a fixed factor, but in fact, the topology of the transportation network can be reconstructed through strategies such as roadblock setting, personnel guidance, and signal light control. Therefore, in the problem of coordinated scheduling of electric-transport coupling, the use of transportation network topology reconstruction to improve the performance of the overall system has not been fully considered. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide an electric-traffic coupling coordinated scheduling method and terminal taking into account the topology of the transportation network, which realizes the redistribution of traffic flow through the topological reconstruction of the transportation network, thereby guiding the charging behavior of electric vehicles and reducing the power generation cost of the power grid and the travel cost of the transportation network.

[0006] In order to solve the above technical problems, a technical solution adopted by the present invention is: A method for coordinated dispatching of electric and traffic coupling taking into account traffic network topology, comprising: Acquire current road topology information and road traffic flow of a traffic system in the electric-traffic coupling system, and construct a traffic system scheduling model according to the current road topology information and the road traffic flow; Acquire power generation information of each generator set in the power system of the power-transport coupling system, and construct a power system dispatching model according to the power generation information; According to the traffic system dispatching model and the power system dispatching model, a dispatching model of the electric-traffic coupling system is constructed with minimization of operating cost as the optimization goal; The optimal operating cost obtained based on the solution of the electric-traffic coupling system scheduling model is used to calculate the traffic system scheduling model and the electric power system scheduling model respectively to obtain the reconstructed target road topology information and power generation data, and a collaborative scheduling plan is generated according to the target road topology information and the power generation data.

[0007] In order to solve the above technical problems, another technical solution adopted by the present invention is: A terminal for coordinated dispatching of electric and traffic coupling taking into account the topology of a traffic network comprises a memory, a processor and a computer program stored in the memory and running on the processor. When the processor executes the computer program, each step of the above-mentioned method for coordinated dispatching of electric and traffic coupling taking into account the topology of a traffic network is implemented.

[0008] The beneficial effects of the present invention are: a traffic system dispatching model is constructed based on the current road topology information and road traffic flow of the traffic system, and a power system dispatching model is constructed based on the power generation information of the power system. The operation cost is solved by the traffic system dispatching model and the electric-traffic coupling system dispatching model constructed by the power system dispatching model to obtain the target road topology information and power generation data under the optimal operation cost, thereby generating a coordinated dispatching scheme. Compared with the isolated dispatching processing of the power grid and the traffic network, the present invention makes full use of the flexibility of the topological structure of the traffic network, and reconstructs the topology by adjusting the road topology information of the traffic system, thereby realizing the redistribution of traffic flow, thereby guiding the charging behavior of electric vehicles, and reducing the power generation cost of the power grid and the travel cost of the traffic network. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A flowchart of the steps of a method for coordinated dispatching of electric and traffic coupling taking into account traffic network topology provided by an embodiment of the present invention; Figure 2 A schematic diagram of the structure of an electric-traffic coupling collaborative dispatching terminal taking into account the transportation network topology provided by an embodiment of the present invention; Description of labels: 100. An electric-traffic coupling coordinated dispatching terminal taking into account the topology of the transportation network; 101. a memory; 102. a processor. DETAILED DESCRIPTION

[0010] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0011] An embodiment of the present invention provides a method for coordinated scheduling of electric and traffic coupling taking into account traffic network topology, including: Acquire current road topology information and road traffic flow of a traffic system in the electric-traffic coupling system, and construct a traffic system scheduling model according to the current road topology information and the road traffic flow; Acquire power generation information of each generator set in the power system of the power-transport coupling system, and construct a power system dispatching model according to the power generation information; According to the traffic system dispatching model and the power system dispatching model, a dispatching model of the electric-traffic coupling system is constructed with minimization of operating cost as the optimization goal; The optimal operating cost obtained based on the solution of the electric-traffic coupling system scheduling model is used to calculate the traffic system scheduling model and the electric power system scheduling model respectively to obtain the reconstructed target road topology information and power generation data, and a collaborative scheduling plan is generated according to the target road topology information and the power generation data.

[0012] From the above description, it can be seen that the beneficial effects of the present invention are: constructing a traffic system scheduling model based on the current road topology information and road traffic flow of the traffic system, and constructing a power system scheduling model based on the power generation information of the power system, solving the operation cost through the traffic system scheduling model and the electric-traffic coupling system scheduling model constructed by the power system scheduling model, so as to obtain the target road topology information and power generation data under the optimal operation cost, thereby generating a collaborative scheduling plan. Compared with the isolated scheduling processing of the power grid and the traffic network, the present invention makes full use of the flexibility of the topological structure of the traffic network, reconstructs the topology by adjusting the road topology information of the traffic system, realizes the redistribution of traffic flow, thereby guiding the charging behavior of electric vehicles, and reducing the power generation cost of the power grid and the travel cost of the traffic network.

[0013] Furthermore, constructing a traffic system scheduling model according to the current road topology information and the road traffic flow includes: Constructing a lane topology reconstruction model according to the current road topology information; A traffic system scheduling model is constructed according to the road traffic flow and the lane topology reconstruction model.

[0014] From the above description, we can see that through strategies such as roadblock setting, personnel guidance, and signal light control, the road topology can be adjusted to achieve the expansion and reduction of road traffic flow. Combining the road traffic flow demand of the current traffic system and the lane topology reconstruction model to build a traffic system scheduling model effectively utilizes the flexibility of the road topology.

[0015] Further, the current road topology information includes original road capacity, current road direction and current road quantity; Constructing a lane topology reconstruction model according to the current road topology information includes: Constructing a road reverse model in which the original road capacity is adjusted to the target road capacity based on the current road direction and the current road quantity; The road direction constraint condition and the road quantity constraint condition for adjusting the traffic system from the original road capacity to the target road capacity are determined.

[0016] From the above description, it can be seen that the road reverse model is constructed to increase the road capacity in the driving direction with heavy traffic, so that vehicles can pass faster and reduce the driving time cost of vehicles, thereby guiding electric vehicles to charge at charging stations that are far away but have surplus power load, avoiding road congestion while reducing the burden on the power system.

[0017] Further, constructing a road reverse model for adjusting the original road capacity to the target road capacity based on the current road direction and the current road quantity includes: ; in, Indicates the road a Adjusted target road capacity, Indicates the road a The original road capacity before adjustment, Representation and Road in opposite direction a Adjusted target road capacity, Representation and Road in opposite direction a The original road capacity before adjustment, and Represents two roads in opposite directions a The number of roads that have their directions reversed, A represents the road set; Determining the road direction constraint condition and the road quantity constraint condition for adjusting the traffic system from the original road capacity to the target road capacity includes: ; ; in, and is a binary variable, indicating the road a different directions, Indicates the total number of roads.

[0018] From the above description, it can be seen that by flexibly adjusting the driving direction of the road, the road capacity is increased, so that vehicles can pass faster. In addition, in the process of adjusting the road direction, the road direction constraint and the road quantity constraint are met to avoid affecting normal traffic driving and ensure the normal operation of the transportation system.

[0019] Furthermore, constructing a traffic system scheduling model according to the road traffic flow and the lane topology reconstruction model includes: Determine the travel time cost of the road according to the road traffic flow, and set the objective function of the traffic system scheduling model according to the road traffic flow and the travel time cost: ; ; in, Indicates the road a of traffic volume, Indicates the road a In traffic volume The travel time cost is , A represents the road set, Represents the economic value of time, represents the free flow travel time, Indicates the road a Adjusted target road capacity.

[0020] From the above description, it can be seen that the traffic system scheduling model aims to minimize the total time cost of all vehicles traveling, which can ensure that electric vehicles travel through the current section of road in the shortest time and reduce unnecessary energy consumption, thereby guiding electric vehicles to charge at charging stations that are far away but have surplus power load, thereby reducing the load on the charging stations.

[0021] Furthermore, constructing a traffic system scheduling model according to the road traffic volume and the lane topology reconstruction model also includes: Determine the constraint conditions of the road traffic flow in the transportation system based on the path allocation.

[0022] From the above description, it can be seen that setting constraint conditions for allocating road traffic flow based on paths can guide vehicles to choose paths more reasonably, thereby alleviating traffic congestion, while effectively optimizing the road topology and improving the throughput capacity of traffic flow.

[0023] Furthermore, the power generation information includes the power generation and power generation cost of each generator set; Constructing a power system dispatch model according to the power generation information includes: According to the power generation power of each generator set, a power system dispatching model with minimization of power generation cost as an objective function is constructed; Determine the power upper and lower limit constraints, the energy storage power constraints, and the active power balance constraints of the nodes including the electric vehicle charging station in the power system.

[0024] From the above description, it can be seen that setting upper and lower power limit constraints can ensure the safe operation of the power grid, setting energy storage power constraints can ensure the charging and discharging balance of energy storage nodes, and electric vehicle charging stations are coupling nodes between the power system and the transportation system. Setting active power balance constraints for nodes containing electric vehicle charging stations can fully consider the coupling interaction between the power system and the transportation system, that is, considering the impact of electric vehicle charging demand on the power system, ensuring the stable operation of the power system, and the three constraints can effectively ensure the reliability of the power system operation.

[0025] Furthermore, constructing an electric-traffic coupling system scheduling model according to the traffic system scheduling model and the power system scheduling model includes: The coupling objective function of the electric-traffic coupling system scheduling model is set based on the objective function of the traffic system scheduling model, the objective function of the electric power system scheduling model and the lane topology reconstruction cost: ; represents the coupling objective function, Represents the objective function of the traffic system scheduling model ， represents the objective function of the power system dispatch model, represents the lane topology reconstruction cost; in, Indicates i The generating capacity of the generator set is The cost of electricity generation at Indicates i Generator sets in t The power generation of the time period, S represents the set of generator sets, represents the traffic volume on road a, Indicates the road a In traffic volume The travel time cost is , A represents the road set, and is a binary variable, indicating the road a different directions, Indicates the unit cost of changing lane direction.

[0026] From the above description, it can be seen that the scheduling model of the electric-traffic coupling system aims to minimize the sum of the vehicle's travel time cost, the power generation cost of the power grid and the road topology reconstruction cost. It can take into account the vehicle's travel time cost and the traffic topology reconstruction cost while minimizing the power generation cost, thereby realizing the coordinated optimization of the electric and traffic systems.

[0027] Furthermore, based on the optimal operating cost obtained by solving the electric-traffic coupling system scheduling model, the traffic system scheduling model and the power system scheduling model are calculated respectively, and the reconstructed target road topology information and power generation data are obtained, including: Based on the optimal operating cost, the traffic system dispatching model and the power system dispatching model are respectively calculated to obtain target road traffic flow and power generation data; Substitute the target road traffic flow into the lane topology reconstruction model to solve and calculate to obtain the target road topology information.

[0028] From the above description, it can be seen that the power generation data corresponding to the power system and the target road traffic flow corresponding to the traffic system are used to determine the optimal operating cost, so that the final lane topology structure is determined based on the target road traffic flow corresponding to the traffic system. Based on the final lane topology structure, the topology of the traffic network is reconstructed to increase the road capacity to the required target road traffic flow, thereby improving the comprehensive benefits of the power-traffic coupling system.

[0029] Another embodiment of the present invention provides an electric-transportation coupling collaborative scheduling terminal taking into account the topology of the transportation network, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the processor implements each step of the above-mentioned electric-transportation coupling collaborative scheduling method taking into account the topology of the transportation network when executing the computer program.

[0030] From the above description, it can be seen that the beneficial effects of the present invention are: constructing a traffic system scheduling model based on the current road topology information and road traffic flow of the traffic system, and constructing a power system scheduling model based on the power generation information of the power system, solving the operation cost through the traffic system scheduling model and the electric-traffic coupling system scheduling model constructed by the power system scheduling model, so as to obtain the target road topology information and power generation data under the optimal operation cost, thereby generating a collaborative scheduling plan. Compared with the isolated scheduling processing of the power grid and the traffic network, the present invention makes full use of the flexibility of the topological structure of the traffic network, reconstructs the topology by adjusting the road topology information of the traffic system, realizes the redistribution of traffic flow, thereby guiding the charging behavior of electric vehicles, and reducing the power generation cost of the power grid and the travel cost of the traffic network.

[0031] The above-mentioned electric-traffic coupling coordinated scheduling method and terminal considering the transportation network topology of the present invention can be applied to power grid operation and control scenarios containing multiple energy forms, and are described below through specific implementation methods: Please refer to Figure 1 , Embodiment 1 of the present invention is: A method for coordinated dispatching of electric and traffic coupling taking into account traffic network topology, comprising: S1. Acquire current road topology information and road vehicle flow of a traffic system in an electric-traffic coupling system, and construct a traffic system scheduling model according to the current road topology information and the road vehicle flow.

[0032] Specifically, in step S1, constructing a traffic system scheduling model according to the current road topology information and the road traffic flow includes: S11. Constructing a lane topology reconstruction model according to the current road topology information.

[0033] The current road topology information includes original road capacity, current road direction and current road quantity. Step S11 includes: S111. Constructing a road reverse model for adjusting the original road capacity to the target road capacity based on the current road direction and the current road quantity.

[0034] Specifically, step S111 includes: ; in, Indicates the road a Adjusted target road capacity, Indicates the road a The original road capacity before adjustment, Representation and Road in opposite direction a Adjusted target road capacity, Representation and Road in opposite direction a The original road capacity before adjustment, and Represents two roads in opposite directions a The number of roads that reverse direction, A represents the road set.

[0035] Among them, in step S111 and The specific method for determining is: ; in, and is a binary variable, indicating the road a different directions, represents the number of lanes with variable directions. If If it is 1, the direction of all lanes on the road will be changed. If it is 0.6, the direction of (0.6*total number of lanes) lanes in the road will be changed. In this embodiment, is 0.5.

[0036] S112: Determine the road direction constraint condition and the road quantity constraint condition for adjusting the traffic system from the original road capacity to the target road capacity.

[0037] Specifically, step S112 includes: ; ; in, and is a binary variable, indicating the road a different directions, Indicates the total number of roads.

[0038] S12: constructing a traffic system scheduling model according to the road traffic volume and the lane topology reconstruction model.

[0039] Specifically, step S12 includes: S121, determining the travel time cost of the road according to the road traffic flow, and setting the objective function of the traffic system scheduling model according to the road traffic flow and the travel time cost: ; ; in, Indicates the road a of traffic volume, Indicates the road a In traffic volume The travel time cost is , A represents the road set, Represents the economic value of time, represents the free flow travel time, Indicates the road a Adjusted target road capacity.

[0040] S122: Determine the constraint conditions of the road traffic flow in the traffic system based on the path allocation.

[0041] Specifically, step S122 includes: Constraint 1: The sum of the traffic volume of all paths between any O (origin) - D (destination) pair is equal to the total travel demand of the OD pair, which can be expressed as: ; in, Indicates OD i In the path r The traffic volume on , Indicates that electric vehicles are in OD i The travel demand in I represents the set of OD pairs, Indicates OD i A collection of paths.

[0042] Constraint 2: The road traffic volume is equal to the total traffic volume passing through the road section on all paths between OD pairs, which can be expressed as: A; in, Indicates road segment a Is it a path? i ,like =1 road section a Belong to the path i ,like =0 road section a Belongs to other paths.

[0043] S2. Obtain power generation information of each generator set in the power system in the power-transport coupling system, and construct a power system dispatching model according to the power generation information.

[0044] The power generation information includes the power generation power and power generation cost of each generator set.

[0045] Specifically, in step S2, constructing a power system dispatching model according to the power generation information includes: S21. Constructing a power system dispatching model with minimization of power generation cost as an objective function according to the power generation power of each generator set.

[0046] Wherein, step S21 is specifically as follows: , )+ ), Indicates i Generator sets in t The power generation during the period, and Respectively represent i The first-order cost coefficient and the second-order cost coefficient of each generator set.

[0047] S22. Determine the constraints of the upper and lower limits of power in the power system, the constraints of the electric energy storage power, and the constraints of the active power balance of the nodes including the electric vehicle charging station.

[0048] Specifically, the constraints of the upper and lower power limits are: ; ; in, Indicates line ij The power, Indicates line ij The power upper limit, H represents the line set, Indicates i Generator sets in t The power generation during the period, Representation Node i The output power lower limit of the generator set is Representation Node i The output power limit of the generator set is set.

[0049] Specifically, the constraints on the electric energy storage power are: ; , ; in, Indicates the energy storage charging power, Indicates the discharge power of the electric energy storage, represents the charging power of node i, S char Represents the set of nodes in the power grid connected to the charging station.

[0050] The constraints of active power balance of nodes containing electric vehicle charging stations are as follows: first determine the active power balance constraints of the power system, then determine the power balance constraints of the charging stations, and finally substitute the power balance constraints of the charging stations into the active power balance constraints of the power system to obtain the constraints of active power balance of nodes containing electric vehicle charging stations. Specifically, the active power balance constraints of the power system are: ; ; Among them, S represents the set of generator sets, H represents the set of lines, Indicates i Generator sets in t The power generation during the period, Representation Node i The total load power, Indicates line ij The power, Representation Node i The charging power, and Respectively represent nodes i and nodes j exist t The phase angle of the time period, and =0, Indicates line ij The electrical conductivity.

[0051] Specifically, the power balance constraint of the charging station is: , ; , , ; in, Representation Node i The total load power, Representation Node i The charging power, represents the charging power of each electric vehicle, Representation Node i The original load power, S char represents the set of nodes in the power grid connected to the charging station, A char Represents the set of roads with charging stations in the transportation network.

[0052] In summary, the constraints for active power balance of nodes containing electric vehicle charging stations are: , .

[0053] S3. Constructing an electric-traffic coupling system scheduling model based on the traffic system scheduling model and the power system scheduling model with minimization of operating cost as the optimization goal.

[0054] Specifically, step S3 includes: S31, setting the coupling objective function of the electric-traffic coupling system scheduling model based on the objective function of the traffic system scheduling model, the objective function of the electric power system scheduling model and the lane topology reconstruction cost: ; represents the coupling objective function, Represents the objective function of the traffic system scheduling model ， represents the objective function of the power system dispatch model, represents the lane topology reconstruction cost; in, Indicates i The generating capacity of the generator set is The cost of electricity generation at Indicates i Generator sets in t The power generation of the time period, S represents the set of generator sets, Indicates the road a of traffic volume, Indicates the road a In traffic volume The travel time cost is , A represents the road set, and is a binary variable, indicating the road a different directions, Indicates the unit cost of changing lane direction.

[0055] S4. Based on the optimal operating cost obtained by solving the electric-traffic coupling system scheduling model, the transportation system scheduling model and the power system scheduling model are calculated respectively to obtain the reconstructed target road topology information and power generation data, and a collaborative scheduling plan is generated according to the target road topology information and the power generation data.

[0056] Specifically, step S4 includes: S41, based on the optimal operating cost, respectively calculating the traffic system dispatching model and the power system dispatching model to obtain target road traffic flow and power generation data; S42: Substitute the target road traffic flow into the lane topology reconstruction model to calculate and obtain target road topology information.

[0057] Please refer to Figure 2 , Embodiment 2 of the present invention is: A terminal 100 for coordinated dispatching of electric and traffic coupling taking into account traffic network topology comprises a memory 101, a processor 102 and a computer program stored in the memory 101 and running on the processor 102. When the processor executes the computer program, each step of the method for coordinated dispatching of electric and traffic coupling taking into account traffic network topology as described in Embodiment 1 is implemented.

[0058] In summary, the present invention provides a method and terminal for coordinated dispatching of electric-traffic coupling taking into account the topology of the traffic network. By acquiring the current road topology information of the traffic system and the road traffic flow, the traffic system dispatching model is constructed, which makes full use of the flexibility of the traffic network topology structure, can adjust the road topology information according to the actual situation, and realize the redistribution of traffic flow, which helps to guide electric vehicles and other vehicles to travel more efficiently and reduce unnecessary energy consumption and road congestion. At the same time, the power generation information of each generator set in the power system is obtained, and the power system dispatching model is constructed accordingly, which fully considers the constraints such as the upper and lower limits of power, the power of electric energy storage, and the active power balance of nodes containing electric vehicle charging stations, so as to ensure the safe and stable operation of the power system, and also fully considers the impact of electric vehicle charging demand on the power system. In addition, the present invention combines the traffic system dispatching model and the power system dispatching model to construct the dispatching model of the electric-traffic coupling system, comprehensively considers the interactive influence of the traffic system and the power system, and realizes the coordinated optimization between the two systems, which can not only improve the utilization efficiency of roads and power facilities and reduce operating costs, but also improve the convenience of transportation and the stability of the power system.

[0059] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for coordinated dispatching of electric and traffic coupling taking into account traffic network topology, characterized in that: include: Acquire current road topology information and road traffic flow of a traffic system in the electric-traffic coupling system, and construct a traffic system scheduling model according to the current road topology information and the road traffic flow; Acquire power generation information of each generator set in the power system of the power-transport coupling system, and construct a power system dispatching model according to the power generation information; According to the traffic system dispatching model and the power system dispatching model, a dispatching model of the electric-traffic coupling system is constructed with minimization of operating cost as the optimization goal; The optimal operating cost obtained based on the solution of the electric-traffic coupling system scheduling model is used to calculate the traffic system scheduling model and the electric power system scheduling model respectively to obtain the reconstructed target road topology information and power generation data, and a collaborative scheduling plan is generated according to the target road topology information and the power generation data.

2. The method according to claim 1, characterized in that Constructing a traffic system scheduling model according to the current road topology information and the road traffic flow includes: Constructing a lane topology reconstruction model according to the current road topology information; A traffic system scheduling model is constructed according to the road traffic flow and the lane topology reconstruction model.

3. The method according to claim 2, characterized in that The current road topology information includes original road capacity, current road direction and current road quantity; Constructing a lane topology reconstruction model according to the current road topology information includes: Constructing a road reverse model in which the original road capacity is adjusted to the target road capacity based on the current road direction and the current road quantity; The road direction constraint condition and the road quantity constraint condition for adjusting the traffic system from the original road capacity to the target road capacity are determined.

4. The method according to claim 3, characterized in that Constructing a road reverse model in which the original road capacity is adjusted to the target road capacity based on the current road direction and the current road quantity includes: ； in, Indicates the road a Adjusted target road capacity, Indicates the road a The original road capacity before adjustment, Representation and Road in opposite direction a Adjusted target road capacity, Representation and Road in opposite direction a The original road capacity before adjustment, and Represents two roads in opposite directions a The number of roads that have their directions reversed, A represents the road set; Determining the road direction constraint condition and the road quantity constraint condition for adjusting the traffic system from the original road capacity to the target road capacity includes: ； ； in, and is a binary variable, indicating the road a different directions, Indicates the total number of roads.

5. The method according to claim 2, characterized in that: Constructing a traffic system scheduling model according to the road traffic flow and the lane topology reconstruction model includes: Determine the travel time cost of the road according to the road traffic flow, and set the objective function of the traffic system scheduling model according to the road traffic flow and the travel time cost: ； ； in, Indicates the road a of traffic volume, Indicates the road a In traffic volume The travel time cost is , A represents the road set, Represents the economic value of time, represents the free flow travel time, Indicates the road a Adjusted target road capacity.

6. The method according to claim 5, characterized in that Constructing a traffic system scheduling model according to the road traffic volume and the lane topology reconstruction model also includes: Determine the constraint conditions of the road traffic flow in the transportation system based on the path allocation.

7. The method according to claim 1, characterized in that The power generation information includes the power generation power and power generation cost of each generator set; Constructing a power system dispatch model according to the power generation information includes: According to the power generation power of each generator set, a power system dispatching model with minimization of power generation cost as an objective function is constructed; Determine the power upper and lower limit constraints, the energy storage power constraints, and the active power balance constraints of the nodes including the electric vehicle charging station in the power system.

8. The method according to claim 2, characterized in that: Constructing the electric-traffic coupling system dispatch model according to the traffic system dispatch model and the electric power system dispatch model includes: The coupling objective function of the electric-traffic coupling system scheduling model is set based on the objective function of the traffic system scheduling model, the objective function of the electric power system scheduling model and the lane topology reconstruction cost: ； represents the coupling objective function, Represents the objective function of the traffic system scheduling model ， represents the objective function of the power system dispatch model, represents the lane topology reconstruction cost; in, Indicates i The generating capacity of the generator set is The cost of electricity generation at Indicates i Generator sets in t The power generation of the time period, S represents the set of generator sets, Indicates the road a of traffic volume, Indicates the road a In traffic volume The travel time cost is , A represents the road set, and is a binary variable, indicating the road a different directions, Indicates the unit cost of changing lane direction.

9. The method according to claim 8, characterized in that The optimal operating cost obtained by solving the electric-traffic coupling system scheduling model is used to calculate the traffic system scheduling model and the electric power system scheduling model respectively, and the reconstructed target road topology information and power generation data are obtained, including: Based on the optimal operating cost, the traffic system dispatching model and the power system dispatching model are respectively calculated to obtain target road traffic flow and power generation data; Substitute the target road traffic flow into the lane topology reconstruction model to solve and calculate to obtain the target road topology information.

10. An electric-traffic coupling coordinated dispatching terminal taking into account the topology of a traffic network, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, each step of the method for coordinated scheduling of electric and traffic coupling taking into account the traffic network topology as claimed in any one of claims 1 to 9 is implemented.

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