Mobile energy storage vehicle optimal scheduling method and system for emergency power shortage area

Abstract

The invention belongs to the technical field of power systems, and particularly relates to a mobile energy storage vehicle optimal scheduling method and system for emergency power shortage areas, and the method comprises the steps: building a mobile energy storage vehicle distribution scheduling model with the goal of minimizing the total economic loss of all emergency power shortage areas and the mobile energy storage vehicle scheduling cost; the economic loss of the emergency power shortage area comprises the economic loss generated before all the distributed mobile energy storage vehicles arrive and the economic loss generated from the period after all the distributed mobile energy storage vehicles arrive to the end of power shortage, and the scheduling cost of the mobile energy storage vehicles comprises the discharging cost of the mobile energy storage vehicles, the transportation cost of the mobile energy storage vehicles and the discharging cost of the mobile energy storage vehicles. And solving the mobile energy storage vehicle distribution scheduling model to obtain an optimal distribution scheduling scheme of the mobile energy storage vehicle. According to the method, the mobile energy storage vehicle is dispatched at the minimum cost to deal with the regional emergency power shortage, the anti-risk capability of a city for the regional emergency power shortage is improved, the cost is comprehensively considered, and practical application is facilitated.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power systems, and in particular relates to a method, system, device and medium for optimizing the dispatching of mobile energy storage vehicles in emergency power shortage areas. Background Art

[0002] The electric vehicle V2G (Vehicle to Grid) technology refers to the technology of electric vehicles supplying electricity to the power grid. Its core idea is to use the energy of a large number of electric vehicles as a buffer between the power grid and renewable energy. By applying V2G technology, the problems of low power grid efficiency and fluctuations in renewable energy can be alleviated to a great extent. A large number of mobile energy storage vehicles in urban areas can not only alleviate the power consumption pressure in different areas of the power grid in daily life, but also serve as an emergency power supply for a certain period of time through the unified joint dispatch of sufficient mobile energy storage vehicles when emergency power shortages occur in some areas, playing a role in helping urban areas cope with emergency power shortages. However, the model construction of the unified centralized dispatching problem of a large number of mobile energy storage vehicles is difficult, involves many variables, and has a complex solution process. At present, there is little research on the centralized dispatching of mobile energy storage vehicles in response to emergency power shortages. It is urgent to propose an optimized dispatching method for mobile energy storage vehicles for regional emergency power shortages to improve the city's ability to resist risks in response to regional emergency power shortages.

[0003] The invention patent with application number 202311370371.4 provides a method and system for restoring power grid load after wildfire considering support from mobile power sources. Based on the power outage plan, an objective function is formed with the goal of minimizing the power outage cost, the power generation cost of the mobile power vehicle, and the operating cost of the mobile energy storage vehicle. The emergency resources such as the power generation cost of the mobile power vehicle and the scheduling strategy of the mobile energy storage vehicle are solved to minimize the impact of wildfires on the power grid. However, the impact of the arrival of batches of mobile energy storage vehicles is not taken into account when calculating the economic losses caused by the power outage, which is not suitable for practical applications. In addition, the discharge cost is not taken into account when calculating the cost of the mobile power vehicle, and the cost calculation of the mobile power vehicle is not comprehensive. Summary of the invention

[0004] The purpose of the present invention is to address the above-mentioned problems existing in the prior art and to provide a method, system, device and medium for optimizing the scheduling of mobile energy storage vehicles for emergency power shortages in areas with emergency power shortages, which can dispatch mobile energy storage vehicles at the lowest cost while comprehensively considering the cost and ensuring the low complexity of model calculation, and is conducive to practical application.

[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 method for optimizing the scheduling of mobile energy storage vehicles in an emergency power shortage area, and the method for optimizing the scheduling of mobile energy storage vehicles comprises:

[0007] S1. A mobile energy storage vehicle allocation and dispatching model is constructed with the goal of minimizing the total economic losses of all emergency power shortage areas and the dispatching costs of mobile energy storage vehicles. The economic losses of the emergency power shortage areas include the economic losses incurred before all the allocated mobile energy storage vehicles arrive, and the economic losses incurred after all the allocated mobile energy storage vehicles arrive until the end of the power shortage. The dispatching costs of mobile energy storage vehicles include the discharge costs of mobile energy storage vehicles and the transportation costs of mobile energy storage vehicles.

[0008] S2. Solve the above mobile energy storage vehicle allocation and scheduling model to obtain the optimal allocation and scheduling plan for the mobile energy storage vehicle.

[0009] The objective function of the mobile energy storage vehicle allocation and scheduling model includes:

[0010]

[0011] In the above formula, M represents the time matrix used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation, M = D⊙T, D represents the m×n-dimensional mobile energy storage vehicle allocation matrix, and the element D in the mobile energy storage vehicle allocation matrix is ij ∈{0,1},D ij =0 means that the i-th mobile energy storage vehicle is not assigned to the j-th emergency power shortage area, D ij =1 indicates that the i-th mobile energy storage vehicle is assigned to the j-th emergency power shortage area; Ca-j indicates the economic loss caused by each kilowatt-hour of power shortage in the j-th emergency power shortage area; Pa-j indicates the discharge power required by the j-th emergency power shortage area; Ps-j indicates the power actually provided by the mobile energy storage vehicle to the j-th emergency power shortage area; ta-j indicates the time required for all mobile energy storage vehicles assigned to the j-th emergency power shortage area to arrive at the emergency power shortage area; Pt indicates the power required by the mobile energy storage vehicle during the transportation process; Cv indicates the cost required for a single mobile energy storage vehicle to release each kilowatt-hour of electricity; T indicates the m×n-dimensional time matrix required for each mobile energy storage vehicle to reach each emergency power shortage area, and the elements T in the time matrix ij represents the time required for the i-th mobile energy storage vehicle to travel from the current position to the j-th emergency power shortage area; ⊙ represents the matrix point multiplication symbol; m represents the total number of mobile energy storage vehicles; n represents the total number of emergency power shortage areas; t represents the duration of the emergency power shortage in the j-th emergency power shortage area.

[0012] The constraints of the mobile energy storage vehicle allocation and scheduling model include:

[0013]

[0014] In the above formula, Pv represents the maximum discharge power of the mobile energy storage vehicle; Mij represents the elements in the time matrix M used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation.

[0015] S2 includes: first constructing a quantity ≤ (n+1) m The solution set is formed by removing the solutions that do not meet the constraints in the solution set, thereby forming a feasible solution set, and traversing the feasible solution set to obtain the optimal solution.

[0016] In a second aspect, the present invention proposes a mobile energy storage vehicle optimization scheduling system for emergency power shortage areas, the mobile energy storage vehicle optimization scheduling system comprising:

[0017] A model building module is used to build a mobile energy storage vehicle allocation and scheduling model with the goal of minimizing the total economic losses of all emergency power shortage areas and the scheduling costs of mobile energy storage vehicles; the economic losses of the emergency power shortage areas include the economic losses incurred before all the allocated mobile energy storage vehicles arrive, and the economic losses incurred after all the allocated mobile energy storage vehicles arrive until the power shortage ends; the scheduling costs of mobile energy storage vehicles include the discharge costs of mobile energy storage vehicles and the transportation costs of mobile energy storage vehicles;

[0018] The calculation module is used to solve the mobile energy storage vehicle allocation and scheduling model and obtain the optimal allocation and scheduling plan for the mobile energy storage vehicle.

[0019] The objective function of the mobile energy storage vehicle allocation and scheduling model includes:

[0020]

[0021] In the above formula, M represents the time matrix used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation, M = D⊙T, D represents the m×n-dimensional mobile energy storage vehicle allocation matrix, and the element D in the mobile energy storage vehicle allocation matrix is ij ∈{0,1},D ij =0 means that the i-th mobile energy storage vehicle is not assigned to the j-th emergency power shortage area, D ij =1 indicates that the i-th mobile energy storage vehicle is assigned to the j-th emergency power shortage area; Ca-j indicates the economic loss caused by each kilowatt-hour of power shortage in the j-th emergency power shortage area; Pa-j indicates the discharge power required by the j-th emergency power shortage area; Ps-j indicates the power actually provided by the mobile energy storage vehicle to the j-th emergency power shortage area; ta-j indicates the time required for all mobile energy storage vehicles assigned to the j-th emergency power shortage area to arrive at the emergency power shortage area; Pt indicates the power required by the mobile energy storage vehicle during the transportation process; Cv indicates the cost required for a single mobile energy storage vehicle to release each kilowatt-hour of electricity; T indicates the m×n-dimensional time matrix required for each mobile energy storage vehicle to reach each emergency power shortage area, and the elements T in the time matrix ijrepresents the time required for the i-th mobile energy storage vehicle to travel from the current position to the j-th emergency power shortage area; ⊙ represents the matrix point multiplication symbol; m represents the total number of mobile energy storage vehicles; n represents the total number of emergency power shortage areas; t represents the duration of the emergency power shortage in the j-th emergency power shortage area.

[0022] The constraints of the mobile energy storage vehicle allocation and scheduling model include:

[0023]

[0024]

[0025] In the above formula, Pv represents the maximum discharge power of the mobile energy storage vehicle; Mij represents the elements in the time matrix M used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation.

[0026] The calculation module is used to first construct the number of solutions ≤ (n+1) m The solution set is obtained by eliminating the solutions that do not meet the constraints in the solution set, and the feasible solution set is obtained by traversing the feasible solution set.

[0027] In a third aspect, the present invention proposes a mobile energy storage vehicle optimization scheduling device for emergency power shortage areas, the mobile energy storage vehicle optimization scheduling device comprising 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 used to execute the aforementioned mobile energy storage vehicle optimization scheduling method according to the instructions in the computer program code.

[0028] In a fourth aspect, the present invention proposes a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the aforementioned mobile energy storage vehicle optimization scheduling method is implemented.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The mobile energy storage vehicle optimization scheduling method for emergency power shortage areas described in the present invention is to minimize the total economic losses of all emergency power shortage areas and the scheduling cost of mobile energy storage vehicles as the goal to construct a mobile energy storage vehicle allocation and scheduling model. By solving the above mobile energy storage vehicle allocation and scheduling model, the optimal allocation and scheduling scheme of the mobile energy storage vehicle can be obtained, thereby realizing the response to regional emergency power shortages by scheduling mobile energy storage vehicles at the minimum cost, and improving the city's risk resistance to regional emergency power shortages; when designing the objective function of the mobile energy storage vehicle allocation and scheduling model, in terms of the economic losses in the emergency power shortage area, the economic losses generated before all the assigned mobile energy storage vehicles arrive and the economic losses generated after all the assigned mobile energy storage vehicles arrive to the end of the power shortage are considered. In terms of mobile energy storage vehicles, the discharge cost of mobile energy storage vehicles and the transportation cost of mobile energy storage vehicles are considered. While comprehensively considering the cost, the model calculation complexity is guaranteed to be low, which provides convenience for the optimization and scheduling of mobile energy storage vehicles. Therefore, the present invention realizes the response to regional emergency power shortages by scheduling mobile energy storage vehicles at the minimum cost, and while comprehensively considering the cost, the model calculation complexity is guaranteed to be low, which is conducive to practical application. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a flow chart of the mobile energy storage vehicle optimization scheduling method of the present invention.

[0032] Figure 2 It is a structural schematic diagram of the mobile energy storage vehicle optimization scheduling system of the present invention.

[0033] Figure 3 It is a structural schematic diagram of the mobile energy storage vehicle optimization scheduling device of the present invention. DETAILED DESCRIPTION

[0034] The present invention is further described in detail below in conjunction with specific implementations and drawings.

[0035] Embodiment 1:

[0036] See also Figure 1 The present invention takes into account the regional emergency power shortage situation and proposes an optimization scheduling method for mobile energy storage vehicles in emergency power shortage areas, thereby improving the city's risk resistance ability to cope with regional emergency power shortages.

[0037] S1. With the goal of minimizing the total economic losses of all emergency power shortage areas and the dispatching costs of mobile energy storage vehicles, a mobile energy storage vehicle allocation and dispatching model is constructed; the objective function of the mobile energy storage vehicle allocation and dispatching model includes:

[0038]

[0039] In the above formula, the first term represents the economic loss incurred by the jth emergency power shortage area before all the assigned mobile energy storage vehicles arrive; the second term represents the economic loss incurred by the jth emergency power shortage area after all the assigned mobile energy storage vehicles arrive until the power shortage ends; the third term represents the discharge cost of the mobile energy storage vehicle assigned to the jth emergency power shortage area; the fourth term represents the transportation cost of the mobile energy storage vehicle assigned to the jth emergency power shortage area; M represents the time matrix used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation, M = D⊙T, D represents the m×n-dimensional mobile energy storage vehicle allocation matrix, and the element D in the mobile energy storage vehicle allocation matrix is ij ∈{0,1},D ij =0 means that the i-th mobile energy storage vehicle is not assigned to the j-th emergency power shortage area, D ij =1 indicates that the i-th mobile energy storage vehicle is assigned to the j-th emergency power shortage area; Ca-j indicates the economic loss caused by each kilowatt-hour of power shortage in the j-th emergency power shortage area; Pa-j indicates the discharge power required by the j-th emergency power shortage area; Ps-j indicates the power actually provided by the mobile energy storage vehicle to the j-th emergency power shortage area; ta-j indicates the time required for all mobile energy storage vehicles assigned to the j-th emergency power shortage area to arrive at the emergency power shortage area; Pt indicates the power required by the mobile energy storage vehicle during the transportation process; Cv indicates the cost required for a single mobile energy storage vehicle to release each kilowatt-hour of electricity; T indicates the m×n-dimensional time matrix required for each mobile energy storage vehicle to reach each emergency power shortage area, and the elements T in the time matrix ij represents the time required for the i-th mobile energy storage vehicle to travel from the current position to the j-th emergency power shortage area; ⊙ represents the matrix point multiplication symbol; m represents the total number of mobile energy storage vehicles; n represents the total number of emergency power shortage areas; t represents the duration of the emergency power shortage in the j-th emergency power shortage area. If t is less than the dischargeable time of the mobile energy storage vehicle, that is, the power of the mobile energy storage vehicle has not been completely used up when the emergency power shortage ends;

[0040] In order to reduce the amount of calculation, the above objective function is simplified. The simplified objective function is as follows:

[0041]

[0042] Considering that a mobile energy storage vehicle can only be assigned to provide power to one emergency power shortage area at most, the following constraints are set:

[0043]

[0044] In order to prevent the maximum discharge power allowed by the mobile energy storage vehicle from being exceeded, it is necessary to wait until all the allocated mobile energy storage vehicles have arrived at the emergency power shortage area, that is, the total power of the mobile energy storage vehicles is greater than the discharge power required by the emergency power shortage area, and then start discharging at the same time. The time required for all mobile energy storage vehicles allocated to the jth emergency power shortage area to arrive at the area should meet the following constraints:

[0045]

[0046] Considering that the total amount of mobile energy storage vehicles is sufficient, the actual power provided by the mobile energy storage vehicles should be equal to the discharge power required to be provided in the emergency power shortage area, so the following constraints are set:

[0047]

[0048] Considering that the discharge power actually provided to the jth emergency power shortage area should be less than or equal to the sum of the maximum discharge powers of all mobile energy storage vehicles that actually arrive there, the following constraints are set:

[0049]

[0050] In the above formula, Pv represents the maximum discharge power of the mobile energy storage vehicle; Mij represents the elements in the time matrix M used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation;

[0051] S2. Solve the above mobile energy storage vehicle allocation and scheduling model to obtain the optimal allocation and scheduling plan for mobile energy storage vehicles. The specific solution steps are as follows: first construct a number ≤ (n+1) m The solution set is formed by removing the solutions that do not meet the constraints in the solution set, thereby forming a feasible solution set, and traversing the feasible solution set to obtain the optimal solution.

[0052] Embodiment 2:

[0053] See also Figure 2 , a mobile energy storage vehicle optimization scheduling system for emergency power shortage areas, the mobile energy storage vehicle optimization scheduling system includes a model building module and a calculation module; the model building module is used to build a mobile energy storage vehicle allocation scheduling model with the goal of minimizing the total economic losses of all emergency power shortage areas and the mobile energy storage vehicle scheduling costs; the economic losses of the emergency power shortage areas include the economic losses generated before all the allocated mobile energy storage vehicles arrive, and the economic losses generated after all the allocated mobile energy storage vehicles arrive until the power shortage ends, and the mobile energy storage vehicle scheduling costs include the mobile energy storage vehicle discharge cost and the mobile energy storage vehicle transportation cost; the objective function of the mobile energy storage vehicle allocation scheduling model includes:

[0054]

[0055] In the above formula, M represents the time matrix used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation, M = D⊙T, D represents the m×n-dimensional mobile energy storage vehicle allocation matrix, and the element D in the mobile energy storage vehicle allocation matrix is ij ∈{0,1},D ij =0 means that the i-th mobile energy storage vehicle is not assigned to the j-th emergency power shortage area, D ij =1 indicates that the i-th mobile energy storage vehicle is assigned to the j-th emergency power shortage area; Ca-j indicates the economic loss caused by each kilowatt-hour of power shortage in the j-th emergency power shortage area; Pa-j indicates the discharge power required by the j-th emergency power shortage area; Ps-j indicates the power actually provided by the mobile energy storage vehicle to the j-th emergency power shortage area; ta-j indicates the time required for all mobile energy storage vehicles assigned to the j-th emergency power shortage area to arrive at the emergency power shortage area; Pt indicates the power required by the mobile energy storage vehicle during the transportation process; Cv indicates the cost required for a single mobile energy storage vehicle to release each kilowatt-hour of electricity; T indicates the m×n-dimensional time matrix required for each mobile energy storage vehicle to reach each emergency power shortage area, and the elements T in the time matrix ij represents the time required for the i-th mobile energy storage vehicle to travel from the current position to the j-th emergency power shortage area; ⊙ represents the matrix point multiplication symbol; m represents the total number of mobile energy storage vehicles; n represents the total number of emergency power shortage areas; t represents the duration of the emergency power shortage in the j-th emergency power shortage area;

[0056] The constraints of the mobile energy storage vehicle allocation and scheduling model include:

[0057]

[0058] In the above formula, Pv represents the maximum discharge power of the mobile energy storage vehicle; Mij represents the elements in the time matrix M used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation;

[0059] The calculation module is used to solve the mobile energy storage vehicle allocation and scheduling model, obtain the optimal allocation and scheduling plan for the mobile energy storage vehicle, and allocate and schedule the mobile energy storage vehicle based on the optimal allocation and scheduling plan; the solution steps are specifically as follows: first construct the number of solutions ≤ (n+1) m The solution set is obtained by eliminating the solutions that do not meet the constraints in the solution set, and the feasible solution set is obtained by traversing the feasible solution set.

[0060] Embodiment 3:

[0061] See also Figure 3, a mobile energy storage vehicle optimization scheduling device for emergency power shortage areas, including 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 used to execute the mobile energy storage vehicle optimization scheduling method described in Example 1 according to the instructions in the computer program code.

[0062] Embodiment 4:

[0063] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the mobile energy storage vehicle optimization scheduling method described in Example 1.

[0064] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0065] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0066] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0067] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing the dispatching of mobile energy storage vehicles in emergency power shortage areas, characterized by: The mobile energy storage vehicle optimization scheduling method comprises: S1. A mobile energy storage vehicle allocation and dispatching model is constructed with the goal of minimizing the total economic losses of all emergency power shortage areas and the dispatching costs of mobile energy storage vehicles. The economic losses of the emergency power shortage areas include the economic losses incurred before all the allocated mobile energy storage vehicles arrive, and the economic losses incurred after all the allocated mobile energy storage vehicles arrive until the end of the power shortage. The dispatching costs of mobile energy storage vehicles include the discharge costs of mobile energy storage vehicles and the transportation costs of mobile energy storage vehicles. S2. Solve the above mobile energy storage vehicle allocation and scheduling model to obtain the optimal allocation and scheduling plan for the mobile energy storage vehicle.

2. The method for optimizing the dispatching of mobile energy storage vehicles for emergency power shortage areas according to claim 1, characterized in that: The objective function of the mobile energy storage vehicle allocation and scheduling model includes: In the above formula, M represents the time matrix used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation, M = D⊙T, D represents the m×n-dimensional mobile energy storage vehicle allocation matrix, and the element D in the mobile energy storage vehicle allocation matrix is ij ∈{0,1},D ij =0 means that the i-th mobile energy storage vehicle is not assigned to the j-th emergency power shortage area, D ij =1 indicates that the i-th mobile energy storage vehicle is assigned to the j-th emergency power shortage area; Ca-j indicates the economic loss caused by each kilowatt-hour of power shortage in the j-th emergency power shortage area; Pa-j indicates the discharge power required by the j-th emergency power shortage area; Ps-j indicates the power actually provided by the mobile energy storage vehicle to the j-th emergency power shortage area; ta-j indicates the time required for all mobile energy storage vehicles assigned to the j-th emergency power shortage area to arrive at the emergency power shortage area; Pt indicates the power required by the mobile energy storage vehicle during the transportation process; Cv indicates the cost required for a single mobile energy storage vehicle to release each kilowatt-hour of electricity; T indicates the m×n-dimensional time matrix required for each mobile energy storage vehicle to reach each emergency power shortage area, and the elements T in the time matrix ij represents the time required for the i-th mobile energy storage vehicle to travel from the current position to the j-th emergency power shortage area; ⊙ represents the matrix point multiplication symbol; m represents the total number of mobile energy storage vehicles; n represents the total number of emergency power shortage areas; t represents the duration of the emergency power shortage in the j-th emergency power shortage area.

3. The method for optimizing the dispatching of mobile energy storage vehicles for emergency power shortage areas according to claim 2 is characterized in that: The constraints of the mobile energy storage vehicle allocation and scheduling model include: In the above formula, Pv represents the maximum discharge power of the mobile energy storage vehicle; Mij represents the elements in the time matrix M used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation.

4. The method for optimizing the dispatching of mobile energy storage vehicles for emergency power shortage areas according to claim 3 is characterized in that: S2 includes: first constructing a quantity ≤ (n+1) m The solution set is formed by removing the solutions that do not meet the constraints in the solution set, thereby forming a feasible solution set, and traversing the feasible solution set to obtain the optimal solution.

5. Optimized dispatching system for mobile energy storage vehicles in emergency power shortage areas, characterized by: The mobile energy storage vehicle optimization dispatching system comprises: A model building module is used to build a mobile energy storage vehicle allocation and scheduling model with the goal of minimizing the total economic losses of all emergency power shortage areas and the scheduling costs of mobile energy storage vehicles; the economic losses of the emergency power shortage areas include the economic losses incurred before all the allocated mobile energy storage vehicles arrive, and the economic losses incurred after all the allocated mobile energy storage vehicles arrive until the power shortage ends; the scheduling costs of mobile energy storage vehicles include the discharge costs of mobile energy storage vehicles and the transportation costs of mobile energy storage vehicles; The calculation module is used to solve the mobile energy storage vehicle allocation and scheduling model and obtain the optimal allocation and scheduling plan for the mobile energy storage vehicle.

6. The mobile energy storage vehicle optimization dispatching system for emergency power shortage areas according to claim 5 is characterized in that: The objective function of the mobile energy storage vehicle allocation and scheduling model includes: In the above formula, M represents the time matrix used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation, M = D⊙T, D represents the m×n-dimensional mobile energy storage vehicle allocation matrix, and the element D in the mobile energy storage vehicle allocation matrix is ij ∈{0,1},D ij =0 means that the i-th mobile energy storage vehicle is not assigned to the j-th emergency power shortage area, D ij =1 indicates that the i-th mobile energy storage vehicle is assigned to the j-th emergency power shortage area; Ca-j indicates the economic loss caused by each kilowatt-hour of power shortage in the j-th emergency power shortage area; Pa-j indicates the discharge power required by the j-th emergency power shortage area; Ps-j indicates the power actually provided by the mobile energy storage vehicle to the j-th emergency power shortage area; ta-j indicates the time required for all mobile energy storage vehicles assigned to the j-th emergency power shortage area to arrive at the emergency power shortage area; Pt indicates the power required by the mobile energy storage vehicle during the transportation process; Cv indicates the cost required for a single mobile energy storage vehicle to release each kilowatt-hour of electricity; T indicates the m×n-dimensional time matrix required for each mobile energy storage vehicle to reach each emergency power shortage area, and the elements T in the time matrix ij represents the time required for the i-th mobile energy storage vehicle to travel from the current position to the j-th emergency power shortage area; ⊙ represents the matrix point multiplication symbol; m represents the total number of mobile energy storage vehicles; n represents the total number of emergency power shortage areas; t represents the duration of the emergency power shortage in the j-th emergency power shortage area.

7. The mobile energy storage vehicle optimization dispatching system for emergency power shortage areas according to claim 6 is characterized by: The constraints of the mobile energy storage vehicle allocation and scheduling model include: In the above formula, Pv represents the maximum discharge power of the mobile energy storage vehicle; Mij represents the elements in the time matrix M used by each mobile energy storage vehicle to travel to each emergency power shortage area after allocation.

8. The mobile energy storage vehicle optimization dispatching system for emergency power shortage areas according to claim 7 is characterized by: The calculation module is used to first construct the number of solutions ≤ (n+1) m The solution set is obtained by eliminating the solutions that do not meet the constraints in the solution set, and the feasible solution set is obtained by traversing the feasible solution set.

9. Optimized dispatching equipment for mobile energy storage vehicles in emergency power shortage areas, characterized by: The mobile energy storage vehicle optimization and scheduling device includes 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 used to execute the mobile energy storage vehicle optimization and scheduling method as described in claims 1-4 according to the 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 the processor, the mobile energy storage vehicle optimization scheduling method as described in claims 1-4 is implemented.

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