Mobile energy storage vehicle dynamic scheduling method, system and device for multi-region power utilization and medium

Abstract

The invention discloses a mobile energy storage vehicle dynamic scheduling method, system, device and medium for multi-region power utilization, and the method comprises the steps: firstly constructing a mobile energy storage vehicle dynamic scheduling optimization model with the minimum total overload cost and total transportation cost of each region as the target, and then solving the mobile energy storage vehicle dynamic scheduling optimization model; and finally, carrying out dynamic scheduling based on the optimal scheduling scheme of the mobile energy storage vehicles among the regions. According to the method, the power supply pressure of multiple regions is balanced as much as possible, the stability of the power system is improved, the complexity of the model is reduced, and the optimal scheduling scheme can be solved by traversing the feasible set.

Description

Technical Field

[0001] The present invention belongs to the field of mobile energy storage vehicle scheduling of power grids, and specifically relates to a dynamic scheduling method, system, equipment and medium for mobile energy storage vehicles for multi-regional electricity consumption. Background Art

[0002] In modern cities, there are often multiple areas with large power supply demands, and the size of the power demand in each area will change over time. When the power demand in a certain area is large, it will put a lot of pressure on the power supply in that area. When the power demand is small, the power supply capacity of the power supply system cannot be fully utilized, thereby reducing the energy utilization rate of the power supply system in disguise. The emergence of mobile energy storage vehicles provides a feasible solution for the flexible scheduling of electricity between different regions. Through the reasonable scheduling of mobile energy storage vehicles, it will be possible to take electricity from areas in the low power consumption period and discharge it in areas in the peak power consumption period, thereby balancing the power pressure in different areas and reducing the occurrence of regional power supply overload.

[0003] However, the current model design for the dynamic scheduling problem of multiple mobile energy storage vehicles in multiple regions is complex and has many variables, making it difficult to directly model and solve it using traditional methods. Summary of the invention

[0004] The purpose of the present invention is to provide a method, system, device and medium for dynamic scheduling of mobile energy storage vehicles for multi-regional electricity consumption in view of the above-mentioned problems existing in the prior art.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows:

[0006] In a first aspect, the present invention proposes a dynamic dispatching method for a mobile energy storage vehicle for multi-regional electricity consumption, comprising:

[0007] S1. Construct a dynamic dispatch optimization model for mobile energy storage vehicles with the goal of minimizing the total overload cost and total transportation cost in each region;

[0008] S2. Solve the dynamic dispatch optimization model of mobile energy storage vehicles to obtain the optimal dispatch plan of mobile energy storage vehicles among various regions;

[0009] S3. Dynamic scheduling is performed based on the optimal scheduling plan of mobile energy storage vehicles among various regions.

[0010] In S1, the objective function of the dynamic dispatch optimization model of the mobile energy storage vehicle includes:

[0011]

[0012] M V-i,t =V i-t

[0013] V i-t =(P S-i-t ,P E-i-t ,T S-i-t ,T L-i-t ,E V-i-t ,B V-i-t )

[0014] In the above formula, m, n, and l are the number of mobile energy storage vehicles, the number of areas that need power supply, and the number of time periods, respectively. A-j When the power provided to the jth region exceeds the maximum power that can be provided under normal circumstances, the additional overload fee per kilowatt-hour is generated, E O-j-t The power provided by the jth region in period t exceeds the maximum power that can be provided under normal circumstances. T is the cost of each mobile energy storage vehicle transporting for one period of time, T S-i-t is the transport state variable of the i-th mobile energy storage vehicle in period t, M V is the m×l dimensional matrix for mobile energy storage vehicle scheduling, M V-i,t M V The elements in V i-t is the state vector of the i-th mobile energy storage vehicle at time t, P S-i-t is the departure area of ​​the i-th mobile energy storage vehicle in the t-period, P E-i-t is the area that the i-th mobile energy storage vehicle plans to reach during the t-period trip, T L-i-t is the transport status label of the i-th mobile energy storage vehicle in period t, E V-i-t is the total amount of discharge of the i-th mobile energy storage vehicle in period t, B V-i-t is the battery capacity of the i-th mobile energy storage vehicle after charging and discharging in period t.

[0015] The constraints of the dynamic dispatch optimization model of the mobile energy storage vehicle include:

[0016] E O-j-t =max{E A-j-t -E S-j-t -E A-max-j ,0}

[0017]

[0018] B V-i-t =B V-i-(t-1) -E V-i-t

[0019] -E V-max ≤E V-i-t ≤E V-max

[0020] 0≤B V-i-t ≤BV-max

[0021] In the above formula, E A-j-t is the power required by the jth area in period t, E S-j-t is the amount of electricity provided by the mobile energy storage vehicle in the jth area during period t, E A-max-j is the maximum amount of electricity that the jth region can normally provide in a period of time, M T-PS-i-(t-1),PE-i-(t-1) is the number of time periods required for the i-th mobile energy storage vehicle to travel from the departure area to the planned arrival area in time period t-1, E V-max B is the amount of electricity that the mobile energy storage vehicle charges and discharges at maximum power in a period of time. V-max It is the maximum battery capacity of the mobile energy storage vehicle.

[0022] The S2 solves the dynamic scheduling optimization model of the mobile energy storage vehicle by traversing the feasible set.

[0023] In a second aspect, the present invention proposes a dynamic dispatching system for mobile energy storage vehicles for multi-regional electricity consumption, including an optimization model building module, an optimization model solving and dispatching module;

[0024] The optimization model building module is used to build a dynamic scheduling optimization model for mobile energy storage vehicles with the goal of minimizing the total overload cost and total transportation cost in each area;

[0025] The optimization model solving and scheduling module is used to solve the dynamic scheduling optimization model of the mobile energy storage vehicle, obtain the optimal scheduling plan of the mobile energy storage vehicle between various regions, and perform dynamic scheduling based on the optimal scheduling plan of the mobile energy storage vehicle between various regions.

[0026] The objective function of the mobile energy storage vehicle dynamic scheduling optimization model includes:

[0027]

[0028] M V-i,t =V i-t

[0029] V i-t =(P S-i-t ,P E-i-t ,T S-i-t ,T L-i-t ,E V-i-t ,B V-i-t )

[0030] In the above formula, m, n, and l are the number of mobile energy storage vehicles, the number of areas that need power supply, and the number of time periods, respectively. A-j When the power provided to the jth region exceeds the maximum power that can be provided under normal circumstances, the additional overload fee per kilowatt-hour is generated, E O-j-tThe power provided by the jth region in period t exceeds the maximum power that can be provided under normal circumstances. T is the cost of each mobile energy storage vehicle transporting for one period of time, T S-i-t is the transport state variable of the i-th mobile energy storage vehicle in period t, M V is the m×l dimensional matrix for mobile energy storage vehicle scheduling, M V-i,t M V The elements in V i-t is the state vector of the i-th mobile energy storage vehicle at time t, P S-i-t is the departure area of ​​the i-th mobile energy storage vehicle in the t-period, P E-i-t is the area that the i-th mobile energy storage vehicle plans to reach during the t-period trip, T L-i-t is the transport status label of the i-th mobile energy storage vehicle in period t, E V-i-t is the total amount of discharge of the i-th mobile energy storage vehicle in period t, B V-i-t is the battery capacity of the i-th mobile energy storage vehicle after charging and discharging in period t.

[0031] The constraints of the dynamic dispatch optimization model of the mobile energy storage vehicle include:

[0032] E O-j-t =max{E A-j-t -E S-j-t -E A-max-j ,0}

[0033]

[0034] B V-i-t =B V-i-(t-1) -E V-i-t

[0035] -E V-max ≤E V-i-t ≤E V-max

[0036] 0≤B V-i-t ≤B V-max

[0037] In the above formula, E A-j-t is the power required by the jth area in period t, E S-j-t is the amount of electricity provided by the mobile energy storage vehicle in the jth area during period t, E A-max-j is the maximum amount of electricity that the jth region can normally provide in a period of time, is the number of time periods required for the i-th mobile energy storage vehicle to travel from the departure area to the planned arrival area in time period t-1, E V-max B is the amount of electricity that the mobile energy storage vehicle charges and discharges at maximum power in a period of time. V-maxIt is the maximum battery capacity of the mobile energy storage vehicle.

[0038] The optimization model solving and scheduling module solves the dynamic scheduling optimization model of the mobile energy storage vehicle by traversing feasible sets.

[0039] In a third aspect, the present invention provides a mobile energy storage vehicle dynamic scheduling device for multi-regional electricity consumption, including a memory and a processor;

[0040] The memory is used to store computer program code and transmit the computer program code to the processor;

[0041] The processor is used to execute the aforementioned method according to the instructions in the computer program code.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the aforementioned method when executed by a processor.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The present invention proposes a method for dynamic scheduling of mobile energy storage vehicles for multi-regional electricity consumption. First, a dynamic scheduling optimization model for mobile energy storage vehicles is constructed with the goal of minimizing the total overload cost and total transportation cost of each region, and then the dynamic scheduling optimization model of the mobile energy storage vehicle is solved to obtain the optimal scheduling scheme of the mobile energy storage vehicle between each region. Finally, dynamic scheduling is performed based on the optimal scheduling scheme of the mobile energy storage vehicle between each region. On the one hand, this method selects key indicators of the electricity consumption area to model the optimization model, and the obtained dynamic scheduling scheme can balance the power supply pressure of multiple regions as much as possible and improve the stability of the power system; on the other hand, by discretizing continuous time variables by dividing them into time periods, and constructing a vector reflecting the state of each mobile energy storage vehicle in each time period, the scheduling of vehicles over time can be represented by a finite-dimensional matrix, thereby significantly reducing the complexity of the model. Since the feasible set of the problem under this model is a finite set, the optimal solution can be obtained by traversing the feasible set. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of the method described in Example 1.

[0046] Figure 2 This is a structural diagram of the system described in Example 2.

[0047] Figure 3 This is a structural diagram of the device described in Example 3. DETAILED DESCRIPTION

[0048] The present invention is further described in detail below in conjunction with specific implementations and drawings.

[0049] Embodiment 1:

[0050] Consider that there are several electricity consumption areas, and the electricity demand in each area varies over time. At the same time, there are multiple mobile energy storage vehicles that can travel back and forth between these areas to realize the transmission of part of the electricity. In order to make the load of each area in each time period as much as possible in a relatively healthy state, when the electricity demand in a certain area is large during a certain period of time, a mobile energy storage vehicle is required to discharge here to share part of the power supply pressure in this area; and when the electricity demand in a certain area is small at this time, the mobile energy storage vehicle can be charged at a certain power without causing excessive load here, so as to achieve that the load in multiple areas is in a relatively healthy state in each time period. For the above scenario, that is, the dynamic scheduling problem of mobile energy storage vehicles for multi-regional electricity consumption, a reasonable scheduling method is designed, such as Figure 1 As shown, the specific implementation steps are as follows:

[0051] 2. According to the actual situation of the power consumption area and the mobile energy storage vehicle, determine the number of mobile energy storage vehicles m and the number of areas that need power supply n. Consider the dynamic scheduling problem of mobile energy storage vehicles within a long period of time T, divide the long period of time T into l time periods, and introduce the n×n dimensional time matrix M required for the mobile energy storage vehicle to travel back and forth between various areas. T , whose element M T-i,j represents the number of time periods required to travel from the i-th area to the j-th area. It is easy to know that

[0052] For the i-th mobile energy storage vehicle, in order to reflect its state in period t, a vector V is introduced i-t =(P S-i-t ,P E-i-t ,T S-i-t ,T L-i-t ,E V-i-t ,B V-i-t ), where P S-i-t is the departure area of ​​the i-th mobile energy storage vehicle in the t-period, P E-i-t is the area that the i-th mobile energy storage vehicle plans to reach during the t-period. If P S-i-t =P E-i-t , it means that the i-th mobile energy storage vehicle has been in this area during the t period, so it can be charged and discharged. On the contrary, if P S-i-t ≠P E-i-t , it means that during this period, the vehicle is on its way from the departure area to the planned arrival area and cannot be charged or discharged; T S-i-t is the transport state variable of the i-th mobile energy storage vehicle in period t. If P S-i-t ≠P E-i-t , then the i-th mobile energy storage vehicle is in the transportation state during the t period, TS-i-t =1, otherwise, if P S-i-t =P E-i-t , then T S-i-t =0; T L-i-t is the transport status label of the i-th mobile energy storage vehicle in period t. If P S-i-t ≠P E-i-t , then T L-i-t ≠0, indicating that the time period is the Tth time on the way from the departure area to the planned arrival area L-i-t time period, i.e. is the number of time periods required for the i-th mobile energy storage vehicle to travel from the departure area to the planned arrival area in time period t. Otherwise, T L-i-t = 0. For example, if one hour is divided into one period, and it takes 2 hours to go from area A to area B, if vehicle i charges in area A for the first hour, then P in the first hour is S-i-1 and P E-i-1 are all in area A; if the vehicle goes from area A to area B in the 2nd and 3rd hours, then P in these two hours S-i-t All are A areas, P E-i-t Both are in area B, because the starting point and destination of this journey (from area A to area B) are the same, and the difference between the state vectors of the two is only the transportation state label T L-i-t They are 1 and 2 respectively, indicating that the current time period is the first and second time period of this journey (from area A to area B). V-i-t is the total amount of energy discharged by the i-th mobile energy storage vehicle in period t, and the discharge time E V-i-t Is positive, when charging E V-i-t When it is negative and cannot or does not need to be charged or discharged, E V-i-t Zero; B V-i-t is the battery capacity of the i-th mobile energy storage vehicle after charging and discharging in period t, and the initial state vector V of the mobile energy storage vehicle i-0 =(P S-i-0 ,P E-i-0 ,T S-i-0 ,T L-i-0 ,E V-i-0 ,B V-i-0 ), then B V-i-t =B V-i-(t-1) -E V-i-t , if P S-i-(t-1) =P E-i-(t-1) , then P S-i-t =P E-i-(t-1) , if P S-i-(t-1) ≠P E-i-(t-1) ,and Then P S-i-t =P S-i-(t-1) , P E-i-t =P E-i-(t-1) , TL-i-t =T L-i-(t-1) +1, if P S-i-(t-1) ≠P E-i-(t-1) ,and Then P S-i-t =P E-i-(t-1) Therefore, the update rule of the mobile energy storage vehicle state is:

[0053]

[0054] B V-i-t =B V-i-(t-1) -E V-i-t ;

[0055] The amount of electricity E charged and discharged by the mobile energy storage vehicle at maximum power in a period of time V-max , with -E V-max ≤E V-i-t ≤E V-max ;Introduce the maximum battery capacity B of the mobile energy storage vehicle V-max , then 0≤B V-i-t ≤B V-max .

[0056] For the jth area, the maximum amount of electricity that can be provided in a period of time under normal circumstances is introduced. A-max-j If the actual amount of electricity provided by the area exceeds the maximum amount of electricity that can be provided under normal circumstances, the additional overload fee per kilowatt-hour will be C A-j Considering that the power demand of each area varies at different times, the power E required by the jth area in time period t is introduced. A-j-t And the amount of electricity E provided by the mobile energy storage vehicle in this area during this period S-j-t , then:

[0057]

[0058] The area actually provides more power than the maximum power it can provide under normal circumstances. O-j-t have:

[0059] E O-j-t =max{E A-j-t -E S-j-t -E A-max-j ,0}

[0060] Introducing the m×l-dimensional matrix M for mobile energy storage vehicle scheduling V , whose element M V-i,t =V i-t , that is, the matrix M V Each element in is a 6-dimensional vector.

[0061] 2. Based on the above parameters, the following dynamic dispatch optimization model of mobile energy storage vehicle is constructed:

[0062]

[0063] M V-i,t =V i-t

[0064] V i-t =(P S-i-t ,P E-i-t ,T S-i-t ,T L-i-t ,E V-i-t ,B V-i-t )

[0065] E O-j-t =max{E A-j-t -E S-j-t -E A-max-j ,0}

[0066]

[0067] -E V-max ≤E V-i-t ≤E V-max

[0068] 0≤B V-i-t ≤B V-max

[0069] B V-i-t =B V-i-(t-1) -E V-i-t .

[0070] 3. Solve the dynamic scheduling optimization model of mobile energy storage vehicles by traversing the feasible set, and obtain the optimal scheduling plan for mobile energy storage vehicles among various regions.

[0071] 4. Dynamic scheduling is carried out based on the optimal scheduling plan of mobile energy storage vehicles among various regions.

[0072] Embodiment 2:

[0073] A dynamic dispatching system for mobile energy storage vehicles for multi-regional electricity consumption, such as Figure 2 As shown, it includes an optimization model building module, an optimization model solving and scheduling module.

[0074] The optimization model building module is used to build the following mobile energy storage vehicle dynamic scheduling optimization model with the goal of minimizing the total overload cost and total transportation cost in each area:

[0075]

[0076] M V-i,t =Vi-t

[0077] V i-t =(P S-i-t ,P E-i-t ,T S-i-t ,T L-i-t ,E V-i-t ,B V-i-t )

[0078] E O-j-t =max{E A-j-t -E S-j-t -E A-max-j ,0}

[0079]

[0080] -E V-max ≤E V-i-t ≤E V-max

[0081] 0≤B V-i-t ≤B V-max

[0082] B V-i-t =B V-i-(t-1) -E V-i-t

[0083] In the above formula, m, n, and l are the number of mobile energy storage vehicles, the number of areas that need power supply, and the number of time periods, respectively. A-j When the power provided to the jth region exceeds the maximum power that can be provided under normal circumstances, the additional overload fee per kilowatt-hour is generated, E O-j-t The power provided by the jth region in period t exceeds the maximum power that can be provided under normal circumstances. T is the cost of each mobile energy storage vehicle transporting for one period of time, T S-i-t is the transport state variable of the i-th mobile energy storage vehicle in period t, M V is the m×l dimensional matrix for mobile energy storage vehicle scheduling, M V-i,t M V The elements in V i-t is the state vector of the i-th mobile energy storage vehicle at time t, P S-i-t is the departure area of ​​the i-th mobile energy storage vehicle in the t-period, P E-i-t is the area that the i-th mobile energy storage vehicle plans to reach during the t-period trip, T L-i-t is the transport status label of the i-th mobile energy storage vehicle in period t, E V-i-t is the total amount of discharge of the i-th mobile energy storage vehicle in period t, B V-i-t is the battery capacity of the i-th mobile energy storage vehicle after charging and discharging in period t, E A-j-tis the power required by the jth area in period t, E S-j-t is the amount of electricity provided by the mobile energy storage vehicle in the jth area during period t, E A-max-j is the maximum amount of electricity that the jth region can normally provide in a period of time, is the number of time periods required for the i-th mobile energy storage vehicle to travel from the departure area to the planned arrival area in time period t-1, E V-max B is the amount of electricity that the mobile energy storage vehicle charges and discharges at maximum power in a period of time. V-max It is the maximum battery capacity of the mobile energy storage vehicle.

[0084] The optimization model solving and scheduling module is used to solve the dynamic scheduling optimization model of the mobile energy storage vehicle by traversing the feasible set, obtain the optimal scheduling plan of the mobile energy storage vehicle between various regions, and perform dynamic scheduling based on the optimal scheduling plan of the mobile energy storage vehicle between various regions.

[0085] Embodiment 3:

[0086] A dynamic dispatching device for mobile energy storage vehicles for multi-regional electricity consumption, such as Figure 3 As shown, it includes a memory and a processor; the memory is used to store computer program code and transmit the computer program code to the processor;

[0087] The processor is configured to execute the method as described in Embodiment 1 according to the instructions in the computer program code.

[0088] Embodiment 4:

[0089] A computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the method described in Embodiment 1 when executed by a processor.

Claims

1. A dynamic dispatching method for mobile energy storage vehicles for multi-regional electricity consumption, characterized in that: The method comprises: S1. Construct a dynamic dispatch optimization model for mobile energy storage vehicles with the goal of minimizing the total overload cost and total transportation cost in each region; S2. Solve the dynamic dispatch optimization model of mobile energy storage vehicles to obtain the optimal dispatch plan of mobile energy storage vehicles among various regions; S3. Dynamic scheduling is performed based on the optimal scheduling plan of mobile energy storage vehicles among various regions.

2. A method for dynamic dispatching of mobile energy storage vehicles for multi-regional electricity consumption according to claim 1, characterized in that: In S1, the objective function of the dynamic dispatch optimization model of the mobile energy storage vehicle includes: M V-i,t =V i-t V i-t =(P S-i-t ,P E-i-t ,T S-i-t ,T L-i-t ,E V-i-t ,B V-i-t ) In the above formula, m, n, and l are the number of mobile energy storage vehicles, the number of areas that need power supply, and the number of time periods, respectively. A-j When the power provided to the jth region exceeds the maximum power that can be provided under normal circumstances, the additional overload fee per kilowatt-hour is generated, E O-j-t The power provided by the jth region in period t exceeds the maximum power that can be provided under normal circumstances. T is the cost of each mobile energy storage vehicle transporting for one period of time, T S-i-t is the transport state variable of the i-th mobile energy storage vehicle in period t, M V is the m×l dimensional matrix for mobile energy storage vehicle scheduling, M V-i,t M V The elements in V i-t is the state vector of the i-th mobile energy storage vehicle at time t, P S-i-t is the departure area of ​​the i-th mobile energy storage vehicle in the t-period, P E-i-t is the area that the i-th mobile energy storage vehicle plans to reach during the t-period trip, T L-i-t is the transport status label of the i-th mobile energy storage vehicle in period t, E V-i-t is the total amount of discharge of the i-th mobile energy storage vehicle in period t, B V-i-t is the battery capacity of the i-th mobile energy storage vehicle after charging and discharging in period t.

3. A method for dynamic dispatching of mobile energy storage vehicles for multi-regional electricity consumption according to claim 2, characterized in that: The constraints of the dynamic dispatch optimization model of the mobile energy storage vehicle include: AND O-j-t =max{E A-j-t -AND S-j-t -AND A-max-j ,0} B V-i-t =B V-i-(t-1) -E V-i-t -AND V-max ≤E V-i-t ≤E V-max 0≤B V-i-t ≤B V-max In the above formula, E A-j-t is the power required by the jth area in period t, E S-j-t is the amount of electricity provided by the mobile energy storage vehicle in the jth area during period t, E A-max-j is the maximum amount of electricity that the jth region can normally provide in a period of time, is the number of time periods required for the i-th mobile energy storage vehicle to travel from the departure area to the planned arrival area in time period t-1, E V-max B is the amount of electricity that the mobile energy storage vehicle charges and discharges at maximum power in a period of time. V-max It is the maximum battery capacity of the mobile energy storage vehicle.

4. A method for dynamic dispatching of mobile energy storage vehicles for multi-regional electricity consumption according to any one of claims 1-3, characterized in that: The S2 solves the dynamic scheduling optimization model of the mobile energy storage vehicle by traversing the feasible set.

5. A dynamic dispatching system for mobile energy storage vehicles for multi-regional electricity consumption, characterized in that: The system includes an optimization model building module, an optimization model solving and scheduling module; The optimization model building module is used to build a dynamic scheduling optimization model for mobile energy storage vehicles with the goal of minimizing the total overload cost and total transportation cost in each area; The optimization model solving and scheduling module is used to solve the dynamic scheduling optimization model of the mobile energy storage vehicle, obtain the optimal scheduling plan of the mobile energy storage vehicle between various regions, and perform dynamic scheduling based on the optimal scheduling plan of the mobile energy storage vehicle between various regions.

6. A dynamic dispatching system for mobile energy storage vehicles for multi-regional electricity consumption according to claim 5, characterized in that: The objective function of the mobile energy storage vehicle dynamic scheduling optimization model includes: M V-i,t =V i-t V i-t =(P S-i-t ,P E-i-t ,T S-i-t ,T L-i-t ,E V-i-t ,B V-i-t ) In the above formula, m, n, and l are the number of mobile energy storage vehicles, the number of areas that need power supply, and the number of time periods, respectively. A-j When the power provided to the jth region exceeds the maximum power that can be provided under normal circumstances, the additional overload fee per kilowatt-hour is generated, E O-j-t The power provided by the jth region in period t exceeds the maximum power that can be provided under normal circumstances. T is the cost of each mobile energy storage vehicle transporting for one period of time, T S-i-t is the transport state variable of the i-th mobile energy storage vehicle in period t, M V is the m×l dimensional matrix for mobile energy storage vehicle scheduling, M V-i,t M V The elements in V i-t is the state vector of the i-th mobile energy storage vehicle at time t, P S-i-t is the departure area of ​​the i-th mobile energy storage vehicle in the t-period, P E-i-t is the area that the i-th mobile energy storage vehicle plans to reach during the t-period trip, T L-i-t is the transport status label of the i-th mobile energy storage vehicle in period t, E V-i-t is the total amount of discharge of the i-th mobile energy storage vehicle in period t, B V-i-t is the battery capacity of the i-th mobile energy storage vehicle after charging and discharging in period t.

7. A dynamic dispatching system for mobile energy storage vehicles for multi-regional electricity consumption according to claim 6, characterized in that: The constraints of the dynamic dispatch optimization model of the mobile energy storage vehicle include: AND O-j-t =max{E A-j-t -AND S-j-t -AND A-max-j ,0} B V-i-t =B V-i-(t-1) -E V-i-t -AND V-max ≤E V-i-t ≤E V-max 0≤B V-i-t ≤B V-max In the above formula, E A-j-t is the power required by the jth area in period t, E S-j-t is the amount of electricity provided by the mobile energy storage vehicle in the jth area during period t, E A-max-j is the maximum amount of electricity that the jth region can normally provide in a period of time, is the number of time periods required for the i-th mobile energy storage vehicle to travel from the departure area to the planned arrival area in time period t-1, E V-max B is the amount of electricity that the mobile energy storage vehicle charges and discharges at maximum power in a period of time. V-max It is the maximum battery capacity of the mobile energy storage vehicle.

8. A dynamic dispatching system for mobile energy storage vehicles for multi-regional electricity consumption according to claims 5-7, characterized in that: The optimization model solving and scheduling module solves the dynamic scheduling optimization model of the mobile energy storage vehicle by traversing the feasible set.

9. A dynamic dispatching device for mobile energy storage vehicles for multi-regional electricity consumption, characterized in that: The device comprises a memory and a processor; The memory is used to store computer program code and transmit the computer program code to the processor; The processor is configured to execute the method according to any one of claims 1 to 4 according to instructions in the computer program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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