Rural tidal load conservation and supply optimization method, device, equipment and medium

Abstract

The invention discloses a rural tidal load supply guarantee optimization method, device, equipment and medium, and relates to the technical field of smart power grids, and the technical scheme is characterized in that the method comprises the steps: obtaining the data of at least one emergency equipment for rural tidal load supply guarantee in the operation process; wherein the emergency equipment comprises mobile energy storage equipment and mobile diesel power generation equipment; inputting the data into a pre-constructed double-layer optimization model, and iteratively solving the double-layer optimization model to obtain an optimization scheme of the operation of the emergency equipment in rural tidal load conservation and supply; wherein the double-layer optimization model comprises a first model and a second model, the first model aims at minimizing the total operation cost of the emergency equipment and the loss of the power transmission line, the second model aims at minimizing the influence of the operation of the emergency equipment on the environment, and the first model is used for optimizing the total capacity of the emergency equipment; the second model is used for optimizing the power supply position, the driving path and the capacity of each emergency device; the optimization scheme refers to the capacity configuration, the power supply position and the driving path of the emergency equipment.

Description

Technical Field

[0001] The present invention relates to the field of smart grid technology, and more specifically, to a rural tidal load supply optimization method, device, equipment and medium. Background Art

[0002] With the increase in renewable energy penetration and the popularization of distributed energy systems, there is a growing demand for flexibility in power systems, especially when responding to emergencies or seasonal load changes.

[0003] The emergency equipment response methods provided by relevant technologies usually rely on fixed-capacity backup power supplies, which may lead to over-allocation or under-allocation of emergency equipment resources. In addition, although emergency resources such as mobile energy storage equipment and mobile diesel generators provide more flexible options, their operation may bring certain environmental impacts, including greenhouse gas emissions, energy consumption, and noise pollution. Summary of the invention

[0004] The purpose of the present invention is to provide a rural tidal load supply optimization method, device, equipment and medium. The present invention solves the problem that the current emergency equipment response mode cannot effectively cope with the power supply efficiency and environmental impact caused by the rural tidal load supply process.

[0005] A first aspect of the present invention provides a rural tidal load supply optimization method, the method comprising:

[0006] Obtaining data during the operation of at least one emergency device for rural tidal load protection; wherein the emergency device is a mobile energy storage device and a mobile diesel generator;

[0007] The data are input into a pre-constructed two-layer optimization model, and the two-layer optimization model is iteratively solved to obtain an optimization scheme for the operation of emergency equipment in rural tidal load supply. The two-layer optimization model includes a first model whose goal is to minimize the total operating cost of emergency equipment and the loss of transmission lines, and a second model whose goal is to minimize the environmental impact of the operation of emergency equipment. The first model is used to optimize the total capacity of emergency equipment, and the second model is used to optimize the power supply location, driving path and capacity size of each emergency equipment. The optimization scheme refers to the capacity configuration, power supply location and driving path of the emergency equipment supply.

[0008] In one implementation, the expression for minimizing the total cost of emergency equipment operation and transmission line loss is:

[0009]

[0010] ;in, are the use costs of mobile energy storage equipment and mobile diesel generator equipment at time t respectively; N is the number of mobile energy storage equipment; M is the number of mobile diesel generator equipment; are the unit power supply costs of the i-th mobile energy storage device and the j-th mobile diesel generator at time t, respectively; are the power supply power of the i-th mobile energy storage device at time t and the power supply power of the j-th mobile diesel generator at time t; C tran is the transportation cost; E is the route set; l mn is the line loss coefficient from node m to node n; y mn is a binary variable, y mn =1 means the line is enabled, y mn =0 means the line is disabled.

[0011] In one implementation, the first model satisfies the following constraints: load balance constraint, charging and discharging constraint and charge state constraint of the mobile energy storage device, and capacity constraint of the mobile diesel generator device.

[0012] In one implementation, the expression for minimizing the environmental impact of emergency equipment operation is: minZ=w1Υ+w2Ω; where Υ is the noise generated by the emergency equipment; Ω is the total carbon emissions; w1 is the weight coefficient of the noise, and w2 is the weight coefficient of the total carbon emissions; is the noise level of the i-th mobile energy storage device at time t; are the noise level and emission of the j-th mobile diesel generator set at time t, respectively.

[0013] In one implementation, the second model satisfies the following constraints: power balance constraint, emergency equipment spatial scheduling path constraint, access location constraint, and carbon emission and noise constraint of mobile diesel generator equipment.

[0014] A second aspect of the present invention provides a rural tidal load supply optimization device, the device comprising:

[0015] A data acquisition module, used to acquire data during the operation of at least one emergency device for rural tidal load supply; wherein the emergency device is a mobile energy storage device and a mobile diesel generator;

[0016] A scheme optimization module is used to input the data into a pre-built two-layer optimization model, and iteratively solve the two-layer optimization model to obtain an optimization scheme for the operation of emergency equipment in rural tidal load supply; wherein the two-layer optimization model includes a first model with the goal of minimizing the total operating cost of emergency equipment and the loss of transmission lines, and a second model with the goal of minimizing the environmental impact of the operation of emergency equipment. The first model is used to optimize the total capacity of the emergency equipment, and the second model is used to optimize the power supply location, driving path and capacity size of each emergency equipment supply; the optimization scheme refers to the capacity configuration, power supply location and driving path of the emergency equipment supply.

[0017] In one implementation, the expression for minimizing the total cost of emergency equipment operation and transmission line loss is:

[0018]

[0019] ;in, are the use costs of mobile energy storage equipment and mobile diesel generator equipment at time t respectively; N is the number of mobile energy storage equipment; M is the number of mobile diesel generator equipment; are the unit power supply costs of the i-th mobile energy storage device and the j-th mobile diesel generator at time t, respectively; are the power supply power of the i-th mobile energy storage device at time t and the power supply power of the j-th mobile diesel generator at time t; C tran is the transportation cost; E is the route set; l mn is the line loss coefficient from node m to node n; y mn is a binary variable, y mn =1 means the line is enabled, y mn =0 means the line is disabled.

[0020] In one implementation, the expression for minimizing the environmental impact of emergency equipment operation is: minZ=w1Υ+w2Ω; where Υ is the noise generated by the emergency equipment; Ω is the total carbon emissions; w1 is the weight coefficient of the noise, and w2 is the weight coefficient of the total carbon emissions; is the noise level of the i-th mobile energy storage device at time t; are the noise level and emission of the j-th mobile diesel generator set at time t, respectively.

[0021] A third aspect of the present invention provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of a rural tidal load supply optimization method provided in the first aspect of the present invention are implemented.

[0022] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of a rural tidal load supply optimization method provided in the first aspect of the present invention are implemented.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] In a rural tidal load supply optimization method provided by the present invention, a two-layer optimization model including a first model and a second model is provided. By alternately iterating and solving the first model and the second model, in the optimization of the first model, according to the load demand prediction and the emergency resource configuration, the emergency resource capacity that meets the load demand and minimizes the cost is calculated, and the network reconstruction operation is adjusted to optimize the spatial scheduling path of the emergency resource to ensure adaptation to different emergency situations. In the lower layer optimization, based on the given emergency resource capacity, the power supply position, driving path and capacity size of the diesel generator and the mobile energy storage device are further optimized with the goal of minimizing noise and emissions; finally, the optimization result of the second model is fed back to the first model and re-evaluated as a new input, and so on, iterative optimization is performed until the two-layer model solutions converge, and the optimization performance can be evaluated by indicators such as load matching, power quality and environment. Therefore, it can be seen that the hierarchical optimization model provided by the present invention can not only realize the effective utilization of emergency equipment resources, but also ensure the service quality of rural tidal load supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0026] Figure 1 A schematic diagram of a flow chart of a rural tidal load supply optimization method provided by an embodiment of the present invention;

[0027] Figure 2 A principle block diagram of a rural tidal load supply optimization device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0029] It should be noted that the terms "include" or "may include" used in various embodiments of the present application indicate the presence of the function, operation or element applied for, and do not limit the addition of one or more functions, operations or elements. In addition, as used in various embodiments of the present application, the terms "include", "have" and their cognates are only intended to indicate specific features, numbers, steps, operations, elements, components or a combination of the foregoing items, and should not be understood as first excluding the presence of one or more other features, numbers, steps, operations, elements, components or a combination of the foregoing items or the possibility of adding one or more features, numbers, steps, operations, elements, components or a combination of the foregoing items.

[0030] In various embodiments of the present application, the expression "or" or "at least one of B or / and C" includes any combination or all combinations of the words listed at the same time. For example, the expression "B or C" or "at least one of B or / and C" may include B, may include C, or may include both B and C.

[0031] It should be understood that terms such as "first" and "second" are only used for descriptive purposes and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0032] Please refer to Figure 1 , Figure 1 A flow chart of a rural tidal load supply optimization method provided by an embodiment of the present invention is as follows: Figure 1 As shown, the method includes:

[0033] S101, obtaining data during the operation of at least one emergency device for rural tidal load protection; wherein the emergency device is a mobile energy storage device and a mobile diesel generator.

[0034] In this embodiment, data on the environmental impact of the operation of emergency resources (such as mobile energy storage equipment and mobile diesel generators) are collected, including emissions, energy consumption, and noise levels. Relevant data on the operation of emergency resources is acquired in real time through gas emission sensors, electric energy meters, noise meters, and other equipment. At the same time, historical data such as product specifications provided by manufacturers, records of previous projects, or existing databases need to be integrated. During the data cleaning and processing process, obviously erroneous or abnormal data should be eliminated and all data should be ensured to follow a unified standard and format.

[0035] Statistical analysis methods are used to evaluate the tolerance of different environments to noise and emissions, and provide a basis for the subsequent optimization of the site selection of emergency equipment. Statistical analysis methods include: correlation analysis, principal component analysis, cluster analysis, regression analysis, etc. Appropriate methods should be used for analysis based on specific data characteristics, and finally identify and integrate the key factors and patterns of environmental impacts, so as to adjust parameter settings in a targeted manner in actual operations, provide a basis for the subsequent optimization of the site selection of emergency equipment, and improve the operating efficiency of emergency equipment.

[0036] S102, input the data into a pre-constructed two-layer optimization model, iteratively solve the two-layer optimization model to obtain an optimization scheme for the operation of emergency equipment in rural tidal load supply; wherein the two-layer optimization model includes a first model with the goal of minimizing the total operating cost of emergency equipment and the transmission line loss and a second model with the goal of minimizing the environmental impact of the operation of emergency equipment, the first model is used to optimize the total capacity of the emergency equipment, and the second model is used to optimize the power supply location, driving path and capacity size of each emergency equipment supply; the optimization scheme refers to the capacity configuration, power supply location and driving path of the emergency equipment supply.

[0037] Specifically, the expression for minimizing the total cost of emergency equipment operation and transmission line loss is:

[0038]

[0039] ;in, are the use costs of mobile energy storage equipment and mobile diesel generator equipment at time t respectively; N is the number of mobile energy storage equipment; M is the number of mobile diesel generator equipment; are the unit power supply costs of the i-th mobile energy storage device and the j-th mobile diesel generator at time t, respectively; are the power supply power of the i-th mobile energy storage device at time t and the power supply power of the j-th mobile diesel generator at time t; C tran is the transportation cost; E is the route set; l mn is the line loss coefficient from node m to node n; y mn is a binary variable, y mn =1 means the line is enabled, y mn =0 means the line is disabled.

[0040] In one embodiment, the first model satisfies the following constraints: load balance constraint, charge and discharge constraint and charge state constraint of the mobile energy storage device, and capacity constraint of the mobile diesel generator device.

[0041] Specifically, the expression of the load balancing constraint is: Where: x i andj are binary variables, a value of 1 indicates that the emergency device is selected, and a value of 0 indicates that the emergency device is not selected; T is the time period; P t load Ensure the required quantity for the load;

[0042] The expressions of charging and discharging constraints and state of charge constraints of mobile energy storage equipment are as follows:

[0043] Where: is the discharge power of the i-th mobile energy storage device at time t, represents the charging power of the i-th mobile energy storage device at time t; is the charge state of the i-th mobile energy storage device at time t, is the charge state at the previous moment, Represents the charging efficiency of mobile energy storage equipment, It represents the discharge efficiency of mobile energy storage equipment; Δt is the time interval; They represent the charging and discharging decision variables of the mobile energy storage device, which are 0-1 binary variables; Indicates the upper limit of charging and discharging power of mobile energy storage equipment; Indicates the minimum value of the state of charge of the mobile energy storage device. Indicates the maximum value of the state of charge of the mobile energy storage device. By reasonably defining the state of charge range of the mobile energy storage device, the impact of excessive charging and discharging of the mobile energy storage device on the battery life can be avoided;

[0044] (3) Capacity constraints Where: Γ j is the capacity of the jth mobile diesel generator.

[0045] Specifically, the expression for minimizing the environmental impact of emergency equipment operation is: minZ=w1Υ+w2Ω; where Υ is the noise generated by the emergency equipment; Ω is the total carbon emissions; w1 is the weight coefficient of the noise, and w2 is the weight coefficient of the total carbon emissions; is the noise level of the i-th mobile energy storage device at time t; are the noise level and emission of the j-th mobile diesel generator set at time t, respectively.

[0046] In one embodiment, the second model satisfies the following constraints: power balance constraint, emergency equipment spatial scheduling path constraint, access location constraint, and carbon emission and noise constraint of mobile diesel generator equipment.

[0047] Specifically, the expression of the power balance constraint is:

[0048] The spatial scheduling path constraint of emergency equipment means that each emergency equipment can only move once in the same time period. It is necessary to ensure that the selection state of the emergency equipment matches the actual movement behavior, while considering the movement cost and time limit of the emergency equipment;

[0049] Where: I is the set of all mobile energy storage devices; Θ is the set of mobile diesel generators; K and Ψ are the sets of all possible starting points and destinations, respectively; w i,t,kh 、w j,t,kh are binary variables. A value of 1 indicates that resource i or j moves from position k to position h at time t, and vice versa. kh is the moving distance of the emergency resource from location k to location h; t kh is the moving time of emergency resources from location k to location h; D max and T max They are the maximum allowed moving distance and maximum moving time respectively;

[0050] The expression of the access location constraint is: Where: Π is the set of nodes that can access emergency resources; the above formula limits each emergency resource to only one node.

[0051] The expression of emission and noise constraints of mobile diesel generator equipment is: Where: e j (t) and n j (t) are the emission and noise level of the jth mobile diesel generator at time t; max and Ω max These are the maximum permitted emissions and noise levels, respectively.

[0052] In this embodiment, the test is carried out in a simulation environment, and the double-layer optimization model is solved in an alternating iterative manner to obtain the emergency resource capacity configuration, driving path and power supply location, etc. that can cope with the rural tidal load demand, so as to ensure the load demand and power supply quality. The iterative solution process is as follows: create a power grid topology diagram containing all possible access points Π, including substations, distribution lines, user nodes, etc., simulate the load changes in different time periods based on historical data or prediction models, especially tidal load characteristics such as morning and evening peak hours, initialize the relevant parameters of mobile energy storage equipment, mobile diesel generator equipment and other equipment and system parameters, and randomly assign the location and capacity of mobile energy storage equipment and mobile diesel generator equipment as the initial solution of the model; secondly, the double-layer optimization model is solved in an alternating iterative manner. In the first model optimization, according to the load demand forecast and emergency resource configuration, the load demand is calculated to meet the load demand. The emergency resource capacity that meets the load demand and minimizes the cost, and at the same time adjusts the network reconstruction operation to optimize the spatial scheduling path of the emergency resources to ensure adaptation to different emergency situations. In the lower-level optimization, based on the given emergency resource capacity, with the goal of minimizing noise and emissions, the power supply location, driving path and capacity of the diesel generator and mobile energy storage equipment are further optimized; finally, the optimization results of the second model are fed back to the first model and re-evaluated as a new input, and so on, iterative optimization is performed until the two-layer model solutions converge. At the same time, the optimization performance can be evaluated by indicators such as load matching, power quality and environment. Therefore, it can be seen that the hierarchical optimization model provided by the present invention can not only realize the effective utilization of emergency equipment resources, but also ensure the service quality of rural tidal load supply.

[0053] Please refer to Figure 2 , Figure 2 A principle block diagram of a rural tidal load supply optimization device provided by an embodiment of the present invention, such as Figure 2 As shown, the device comprises:

[0054] The data acquisition module 210 is used to acquire data during the operation of at least one emergency device for rural tidal load supply; wherein the emergency device is a mobile energy storage device and a mobile diesel generator;

[0055] The scheme optimization module 220 is used to input the data into a pre-built two-layer optimization model, and iteratively solve the two-layer optimization model to obtain an optimization scheme for the operation of emergency equipment in rural tidal load supply; wherein the two-layer optimization model includes a first model with the goal of minimizing the total operating cost of emergency equipment and the loss of transmission lines and a second model with the goal of minimizing the environmental impact of the operation of emergency equipment. The first model is used to optimize the total capacity of the emergency equipment, and the second model is used to optimize the power supply location, driving path and capacity size of each emergency equipment supply; the optimization scheme refers to the capacity configuration, power supply location and driving path of the emergency equipment supply.

[0056] In a rural tidal load supply optimization device provided by the present invention, a two-layer optimization model including a first model and a second model is provided. By alternately iterating and solving the first model and the second model, in the optimization of the first model, according to the load demand prediction and the emergency resource configuration, the emergency resource capacity that meets the load demand and minimizes the cost is calculated, and the network reconstruction operation is adjusted to optimize the spatial scheduling path of the emergency resource to ensure adaptation to different emergency situations. In the lower layer optimization, based on the given emergency resource capacity, the power supply position, driving path and capacity size of the diesel generator and the mobile energy storage device are further optimized with the goal of minimizing noise and emissions; finally, the optimization result of the second model is fed back to the first model and re-evaluated as a new input, and so on, iterative optimization is performed until the two-layer model solutions converge, and the optimization performance can be evaluated by indicators such as load matching, power quality and environment. Therefore, it can be seen that the hierarchical optimization model provided by the present invention can not only realize the effective utilization of emergency equipment resources, but also ensure the service quality of rural tidal load supply.

[0057] In some embodiments, the expression for minimizing the total cost of emergency equipment operation and transmission line loss is:

[0058]

[0059] ;in, are the use costs of mobile energy storage equipment and mobile diesel generator equipment at time t respectively; N is the number of mobile energy storage equipment; M is the number of mobile diesel generator equipment; are the unit power supply costs of the i-th mobile energy storage device and the j-th mobile diesel generator at time t, respectively; are the power supply power of the i-th mobile energy storage device at time t and the power supply power of the j-th mobile diesel generator at time t; C tran is the transportation cost; E is the route set; l mn is the line loss coefficient from node m to node n; y mn is a binary variable, y mn =1 means the line is enabled, y mn =0 means the line is disabled.

[0060] In some embodiments, the expression for minimizing the environmental impact of emergency equipment operation is: minZ=w1Υ+w2Ω; wherein Υ is the noise generated by the emergency equipment; Ω is the total carbon emissions; w1 is the weight coefficient of the noise, and w2 is the weight coefficient of the total carbon emissions; is the noise level of the i-th mobile energy storage device at time t; are the noise level and emission of the j-th mobile diesel generator set at time t, respectively.

[0061] The embodiment of the present application also provides an electronic device. The electronic device includes a processor, a memory, a communication interface, and at least one communication bus for connecting the processor, the memory, and the communication interface. The memory includes but is not limited to a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (PROM), or a portable CD-ROM, and the memory is used for related instructions and data.

[0062] The communication interface is used to receive and send data. The processor may be one or more CPUs. When the processor is a CPU, the CPU may be a single-core CPU or a multi-core CPU. The processor in the electronic device is used to read one or more programs stored in the memory and perform the following operations: obtaining data during the operation of at least one emergency device for rural tidal load guarantee; wherein the emergency device is a mobile energy storage device and a mobile diesel generator; inputting the data into a pre-constructed two-layer optimization model, iteratively solving the two-layer optimization model to obtain an optimization scheme for the operation of the emergency equipment in the rural tidal load guarantee; wherein the two-layer optimization model includes a first model with the goal of minimizing the total operating cost of the emergency equipment and the transmission line loss and a second model with the goal of minimizing the environmental impact of the operation of the emergency equipment. The first model is used to optimize the total capacity of the emergency equipment, and the second model is used to optimize the power supply location, driving path and capacity size of each emergency equipment guarantee; the optimization scheme refers to the capacity configuration, power supply location and driving path of the emergency equipment guarantee.

[0063] It should be noted that the specific implementation of each operation can be the corresponding description of the method embodiment described above, and the electronic device can be used to execute a rural tidal load supply optimization method of the above method embodiment of the present application, which will not be described in detail here.

[0064] In the embodiments of the present disclosure, a computer-readable storage medium is also provided, and the computer-readable storage medium is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both built-in storage media in a computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of a rural tidal load supply optimization method in the above embodiment. Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take 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 specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A rural tidal load supply optimization method, characterized in that the method include: Obtaining data during the operation of at least one emergency device for rural tidal load protection; wherein the emergency device is a mobile energy storage device and a mobile diesel generator; The data are input into a pre-constructed two-layer optimization model, and the two-layer optimization model is iteratively solved to obtain an optimization scheme for the operation of emergency equipment in rural tidal load supply. The two-layer optimization model includes a first model whose goal is to minimize the total operating cost of emergency equipment and the loss of transmission lines, and a second model whose goal is to minimize the environmental impact of the operation of emergency equipment. The first model is used to optimize the total capacity of emergency equipment, and the second model is used to optimize the power supply location, driving path and capacity size of each emergency equipment. The optimization scheme refers to the capacity configuration, power supply location and driving path of the emergency equipment supply.

2. A rural tidal load supply optimization method according to claim 1, characterized in that: The expression for minimizing the total cost of emergency equipment operation and transmission line loss is: in, are the use costs of mobile energy storage equipment and mobile diesel generator equipment at time t respectively; N is the number of mobile energy storage equipment; M is the number of mobile diesel generator equipment; are the unit power supply costs of the i-th mobile energy storage device and the j-th mobile diesel generator at time t, respectively; are the power supply power of the i-th mobile energy storage device at time t and the power supply power of the j-th mobile diesel generator at time t; C tran is the transportation cost; E is the route set; l mn is the line loss coefficient from node m to node n; y mn is a binary variable, y mn =1 means the line is enabled, y mn =0 means the line is disabled.

3. A rural tidal load supply optimization method according to claim 2, characterized in that: The first model satisfies the following constraints: load balance constraint, charging and discharging constraint and charge state constraint of mobile energy storage equipment, and capacity constraint of mobile diesel generator equipment.

4. A rural tidal load supply optimization method according to claim 1, characterized in that: The expression for minimizing the environmental impact of emergency equipment operation is: minZ=w1Υ+w2Ω; where Υ is the noise generated by the emergency equipment; Ω is the total carbon emissions; w1 is the weight coefficient of the noise, and w2 is the weight coefficient of the total carbon emissions; is the noise level of the i-th mobile energy storage device at time t; are the noise level and emission of the j-th mobile diesel generator set at time t, respectively.

5. A rural tidal load supply optimization method according to claim 4, characterized in that: The second model satisfies the following constraints: power balance constraint, emergency equipment spatial scheduling path constraint, access location constraint, and carbon emission and noise constraint of mobile diesel generator equipment.

6. A rural tidal load supply optimization device, characterized in that: The device includes: A data acquisition module, used to acquire data during the operation of at least one emergency device for rural tidal load supply; wherein the emergency device is a mobile energy storage device and a mobile diesel generator; A scheme optimization module is used to input the data into a pre-built two-layer optimization model, and iteratively solve the two-layer optimization model to obtain an optimization scheme for the operation of emergency equipment in rural tidal load supply; wherein the two-layer optimization model includes a first model with the goal of minimizing the total operating cost of emergency equipment and the loss of transmission lines, and a second model with the goal of minimizing the environmental impact of the operation of emergency equipment. The first model is used to optimize the total capacity of the emergency equipment, and the second model is used to optimize the power supply location, driving path and capacity size of each emergency equipment supply; the optimization scheme refers to the capacity configuration, power supply location and driving path of the emergency equipment supply.

7. A rural tidal load supply optimization device according to claim 6, characterized in that: The expression for minimizing the total cost of emergency equipment operation and transmission line loss is: in, are the use costs of mobile energy storage equipment and mobile diesel generator equipment at time t respectively; N is the number of mobile energy storage equipment; M is the number of mobile diesel generator equipment; are the unit power supply costs of the i-th mobile energy storage device and the j-th mobile diesel generator at time t, respectively; are the power supply power of the i-th mobile energy storage device at time t and the power supply power of the j-th mobile diesel generator at time t; C tran is the transportation cost; E is the route set; l mn is the line loss coefficient from node m to node n; y mn is a binary variable, y mn =1 means the line is enabled, y mn =0 means the line is disabled.

8. A rural tidal load supply optimization device according to claim 6, characterized in that: The expression for minimizing the environmental impact of emergency equipment operation is: minZ=w1Υ+w2Ω; where Υ is the noise generated by the emergency equipment; Ω is the total carbon emissions; w1 is the weight coefficient of the noise, and w2 is the weight coefficient of the total carbon emissions; is the noise level of the i-th mobile energy storage device at time t; are the noise level and emission of the j-th mobile diesel generator set at time t, respectively.

9. An electronic device, characterized in that: The electronic device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of a rural tidal load supply optimization method as described in any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of a rural tidal load supply optimization method as described in any one of claims 1 to 5 are implemented.

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