Mobile energy storage configuration method and system for distribution network supply assurance

Abstract

The present invention provides a mobile energy storage configuration method and system for ensuring power supply in a distribution network. The method includes: obtaining the equivalent road section distance that a mobile energy storage device i needs to traverse, and calculating the travel time based on the equivalent road section distance; obtaining the power outage risk value of each node per unit time, constructing a first objective function based on the power outage risk value and the travel time, and constructing a maximum travel time constraint; solving the first objective function, and obtaining the number of energy storage device sites and the location of each site based on the solution result; constructing an energy storage sizing model for the energy storage device at each site, the energy storage sizing model including a second objective function with the goal of minimizing the total cost of the mobile energy storage device, and constraints on the second objective function. The embodiments of the present invention can solve the problems of low resource allocation efficiency and difficulty in quickly responding to faults and minimizing power outage losses in traditional technologies.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage configuration, and in particular to a mobile energy storage configuration method and system for ensuring power supply in a distribution network. Background Art

[0002] In the event of power emergencies, such as natural disasters or equipment failures, rapid response is key to ensuring power supply. Therefore, the speed at which mobile energy storage devices can move within a specific area and the time limits for doing so become particularly important to ensure they can reach the fault site in the shortest possible time.

[0003] The current distribution network faces significant shortcomings in responding to sudden power outages. Traditional emergency material management strategies rely heavily on fixed warehouses, resulting in redundant emergency power configurations and low daily utilization. Furthermore, the site selection and scheduling of existing mobile energy storage devices lack systematic optimization, failing to comprehensively consider the differences in power outage risks and user satisfaction requirements at different load nodes. These issues stem from the fact that emergency response mechanisms focus on handling major incidents while neglecting flexible, everyday applications. Existing models fail to effectively integrate the scheduling time of mobile energy storage devices with load demands, and lack a hierarchical management strategy for safety, economy, and quality loads. This results in inefficient resource allocation and makes it difficult to quickly respond to failures and minimize power outage losses. Summary of the Invention

[0004] The purpose of the present invention is to provide a mobile energy storage configuration method and system for ensuring power supply in distribution networks, aiming to solve the problems of low resource allocation efficiency in traditional technologies, difficulty in quickly responding to faults and minimizing power outage losses.

[0005] In a first aspect, the present invention provides a method for configuring mobile energy storage for ensuring power supply to a distribution network, the method comprising:

[0006] Obtain the equivalent road section distance that the mobile energy storage device i needs to travel from its initial position to the load node k of the distribution network in the transportation network, and calculate the travel time based on the equivalent road section distance;

[0007] Obtaining a power outage risk value per unit time for each node, constructing a first objective function according to the power outage risk value and the movement time, and constructing a maximum movement time constraint condition;

[0008] Solving the first objective function and obtaining the number of selected sites for energy storage devices and the location of each selected site based on the solution;

[0009] An energy storage sizing model for energy storage equipment is constructed at each selected site. The energy storage sizing model includes a second objective function aimed at minimizing the total cost of mobile energy storage equipment, and constraints on the second objective function. The constraints include mobile energy storage equipment constraints, mobile energy storage guaranteed power constraints, node power balance constraints, load power constraints, self-contained power supply constraints, and satisfaction constraints.

[0010] Furthermore, the step of obtaining the equivalent road section distance that the mobile energy storage device i needs to travel from the initial position to the load node k of the distribution network in the transportation network, and calculating the travel time based on the equivalent road section distance includes:

[0011] The moving time is calculated according to the following formula:

[0012] ;

[0013] in, Indicates that the mobile energy storage vehicle i moves from the initial position The time required to deploy to node j; Indicates that the mobile energy storage device i moves from its initial position in the transportation network The equivalent distance of the road section required to reach node k; represents the actual travel speed of the mobile energy storage device i during the travel period;

[0014] The distance of the road section is calculated according to the following formula:

[0015] ;

[0016] in, The mobile energy storage device i moves from its initial position in the traffic network The shortest distance to node k;

[0017] The actual speed is calculated according to the following formula:

[0018] ;

[0019] in, is the vehicle speed under ideal conditions with zero traffic flow; c represents the congestion level of the traffic network under disaster scenarios.

[0020] Furthermore, the step of obtaining the power outage risk value of each node per unit time includes:

[0021] The power outage risk value is calculated according to the following formula:

[0022] ;

[0023] in, represents the power outage risk value of node j during a power outage; represents the power outage loss value of node j during power outage; represents the power outage probability of node j under an emergency event;

[0024] The power outage loss value is calculated according to the following formula:

[0025] ;

[0026] in, is the loss value of node j per unit power shortage per unit time, is the power demand value of the load system at node j during a power outage, It is the power that the load system of node j can provide by its own power supply during a power outage.

[0027] Furthermore, the step of constructing a first objective function according to the power outage risk value and the movement time, and constructing a maximum movement time constraint condition includes:

[0028] The first objective function is constructed according to the following formula:

[0029] ;

[0030] in, represents the initial node position of mobile energy storage vehicle i, and n represents the total number of n load nodes in the distribution network system;

[0031] The maximum movement time constraint is constructed according to the following formula:

[0032] ;

[0033] in, Indicates the maximum time allowed for a mobile energy storage vehicle to be deployed to the target node.

[0034] Furthermore, the step of solving the first objective function and obtaining the number of selected sites for energy storage devices and the position of each selected site according to the solution includes:

[0035] Generate a node traffic network diagram to be planned based on geographic traffic data information and distribution network node information, wherein the node traffic network includes the travel time between any two nodes;

[0036] Construct the node matrix S with the total number of nodes as the number of rows and columns, , , ; represents the travel time between the xth node and the yth node, N represents the total number of nodes, and if the xth node is not connected to the yth node, fill in inf in the node matrix;

[0037] Solve the shortest route between any two nodes according to the node matrix, and predict the minimum number of site selection points P based on the shortest route;

[0038] Determine whether the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold;

[0039] If the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold, then at least one site selection point set is obtained based on the minimum number of site selection points;

[0040] Sorting the at least one set of site selection points according to the power outage risk value, and selecting the target set of site selection points with the lowest total power outage risk value according to the sorting result;

[0041] If the travel time between any two nodes in the number of site selection points is greater than the preset maximum time threshold, then , and re-judge whether the travel time between any two nodes after the number of site selection points is updated is less than or equal to the preset maximum time threshold, until the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold.

[0042] Furthermore, the step of constructing an energy storage capacity determination model for the energy storage device at each selected site, wherein the energy storage capacity determination model includes a second objective function with the goal of minimizing the total cost of the mobile energy storage device and constraints on the second objective function, includes:

[0043] The second objective function is constructed according to the following formula:

[0044] ;

[0045] in, represents the total mobile energy storage vehicle construction cost; represents the construction cost of a single mobile energy storage vehicle of type h; H represents the number of types of mobile energy storage vehicles; represents the number of mobile energy storage devices of type h;

[0046] The power constraint for mobile energy storage supply is constructed according to the following formula:

[0047] ;

[0048] Where H represents the total number of mobile energy storage vehicles; Indicates the type of mobile energy storage vehicle, h can be a positive integer from 1 to H, represents the power supply that the mobile energy storage device at load node j can provide for the safety load layer, represents the power supply that the mobile energy storage device at load node j can provide to the economic load layer, It represents the power supply that the mobile energy storage device of load node j can provide to the quality load layer;

[0049] The node power balance constraint is constructed according to the following formula:

[0050] ;

[0051] in, represents the safety load layer load power of node j, represents the economic load layer load power of node j, represents the high-quality load layer load power of node j, represents the total load power of node j, represents the power that the self-contained power supply of the load system at node j can provide during a power outage;

[0052] The load power constraint is constructed according to the following formula:

[0053] ;

[0054] The self-provided power supply power constraint is constructed according to the following formula:

[0055] ;

[0056] in, It represents the power that the self-contained power supply of load node j can provide to the safety load layer during a power outage. It represents the power that the self-contained power supply of load node j can provide to the economic load layer during a power outage. It represents the power that the self-contained power supply of load node j can provide to the quality load layer during a power outage. The sum of the self-supplied power of different load layers of node j does not exceed the maximum self-supplied power that node j can provide;

[0057] The satisfaction constraint is constructed according to the following formula:

[0058] ;

[0059] Among them, Y is the user's overall satisfaction; is the weight of safety load layer satisfaction; is the weight of the economic load layer satisfaction; is the weight of the satisfaction of the high-quality load layer; Satisfaction level for safety load layer; is the economic load layer satisfaction; For quality load layer satisfaction.

[0060] Furthermore, the safety load layer satisfaction is calculated according to the following formula:

[0061] ;

[0062] in, It represents the guaranteed supply demand level of the load power of the safety load layer of load node j, represents the power supply that the mobile energy storage device at load node j can provide for the safety load layer, It represents the power that the self-contained power supply of load node j can provide to the safety load layer during a power outage;

[0063] The economic load layer satisfaction is calculated according to the following formula:

[0064] ;

[0065] in, It represents the supply demand level of the load power of the economic load layer of load node j, represents the power supply that the mobile energy storage device at load node j can provide to the economic load layer, It represents the power that the self-contained power supply of load node j can provide to the economic load layer during a power outage;

[0066] The quality load layer satisfaction is calculated according to the following formula:

[0067] ;

[0068] in, It represents the supply demand level of the load power of the quality load layer of load node j, It represents the power supply that the mobile energy storage device of load node j can provide to the quality load layer, It represents the power that the self-contained power supply of load node j can provide to the quality load layer during a power outage.

[0069] In a second aspect, the present invention provides a mobile energy storage configuration system for ensuring power supply to a distribution network, the system comprising:

[0070] A travel time calculation module is used to obtain the equivalent road section distance that the mobile energy storage device i needs to travel from its initial position in the transportation network to the load node k of the distribution network, and calculate the travel time based on the equivalent road section distance;

[0071] a first objective function construction module, configured to obtain a power outage risk value per unit time for each node, to construct a first objective function according to the power outage risk value and the movement time, and to construct a maximum movement time constraint;

[0072] A solution module, configured to solve the first objective function and obtain the number of selected sites for energy storage devices and the location of each selected site according to the solution result;

[0073] An energy storage sizing model construction module is used to construct an energy storage sizing model for energy storage equipment at each selected site. The energy storage sizing model includes a second objective function with the goal of minimizing the total cost of mobile energy storage equipment, and constraints on the second objective function. The constraints include mobile energy storage equipment constraints, mobile energy storage guaranteed power constraints, node power balance constraints, load power constraints, self-contained power supply constraints, and satisfaction constraints.

[0074] In a third aspect, the present invention provides a storage medium storing one or more programs, which, when executed by a processor, implement the above-mentioned mobile energy storage configuration method for ensuring power supply to a distribution network.

[0075] In a fourth aspect, the present invention provides an electronic device, comprising a memory and a processor, wherein:

[0076] The memory is used to store computer programs;

[0077] When the processor is used to execute the computer program stored in the memory, it implements the above-mentioned mobile energy storage configuration method for power distribution network supply guarantee.

[0078] Compared with the existing technology, the embodiment of the present invention systematically solves the defects of the existing technology by optimizing the site selection and sizing of mobile energy storage equipment in steps. First, a mathematical model is established based on the power outage risk value and user satisfaction to prioritize the scheduling of high-risk load nodes, and the Floyd algorithm is used to solve the optimized path planning to shorten the arrival time of the energy storage vehicle. Secondly, through the layered load (safety, economy, quality) satisfaction constraints, the mobile energy storage power is accurately matched with user needs, and the energy storage model and quantity are selected based on the cost optimization principle. This method not only improves the daily utilization efficiency of emergency resources, but also significantly enhances the response speed and supply guarantee capability of the distribution network in emergencies, effectively shortening the duration of power outages and reducing economic losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 This is a flow chart of a method for configuring mobile energy storage for ensuring power supply in a distribution network, as proposed in one embodiment of the present invention;

[0080] Figure 2 A node traffic network diagram according to an example of an embodiment of the present invention;

[0081] Figure 3 is a schematic diagram of a node matrix according to an embodiment of the present invention;

[0082] Figure 4 This is a structural diagram of a mobile energy storage configuration system for ensuring power supply to a distribution network, proposed in one embodiment of the present invention.

[0083] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0084] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Unless otherwise defined, the technical terms or scientific terms used herein should be the common meanings understood by people with ordinary skills in the field to which the invention belongs. The words "including" and similar words used in this article mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects.

[0085] like Figure 1 As shown, an embodiment of the present invention provides a mobile energy storage configuration method for ensuring power supply to a distribution network, the method comprising steps S101 to S104, wherein:

[0086] Step S101: obtaining the equivalent road distance that the mobile energy storage device i needs to travel from its initial position to the load node k of the distribution network in the transportation network, and calculating the travel time based on the equivalent road distance;

[0087] First, it should be pointed out that in the site selection model for mobile energy storage equipment in the distribution network area, one point considered in this step is the time constraints on the operation and scheduling of mobile energy storage vehicles. Therefore, it is necessary to establish a time consumption model for mobile energy storage vehicles:

[0088]

[0089] in, Indicates that the mobile energy storage vehicle i moves from the initial position The time required to deploy to node j; Indicates that the mobile energy storage device i moves from its initial position in the transportation network The equivalent distance of the road section required to reach node k; represents the actual travel speed of the mobile energy storage device i during the travel period; and and There is a functional relationship, and the traffic integration coefficient is used to reflect the spatial scheduling relationship between the actual speed of mobile energy storage and the equivalent travel distance.

[0090] The distance of the road section is calculated according to the following formula:

[0091] ;

[0092] in, The mobile energy storage device i moves from its initial position in the traffic network The shortest distance to node k;

[0093] The actual speed is calculated according to the following formula:

[0094] ;

[0095] in, is the vehicle speed under ideal conditions with zero traffic flow; c represents the congestion level of the traffic network under disaster scenarios, which is related to the degree of disaster impact and traffic flow, and can be estimated based on the damage to the traffic network after the disaster.

[0096] Step S102: Obtaining a power outage risk value per unit time for each node, constructing a first objective function based on the power outage risk value and the movement time, and constructing a maximum movement time constraint;

[0097] It should be pointed out that in the mobile energy storage equipment site selection model, in addition to the time constraints on the operation and scheduling of mobile energy storage vehicles, the power outage risk value also needs to be considered. For identified key power users, relevant regulations must be followed, self-contained emergency power supplies must be deployed, and their safety management measures must be strengthened. Therefore, when these load nodes in the distribution network fail, they will quickly activate their own emergency power supplies as a substitute. At the same time, grid operators will also race against time to start redundant lines in order to restore power supply to some areas. These operations are efficient and fast, and can bring power supply to some power outage areas in a very short time. In this scenario, the actual power shortage at the load point is the difference between the power that its system can provide and the power or capacity of its self-contained emergency power supply. Such a configuration and management strategy is intended to ensure that when the power supply of a certain line is interrupted, the critical load can continue to obtain the necessary power support, and help to gradually repair the affected power supply network until the normal power supply is fully restored. Based on this, for the calculation of the value of power outage losses, it is necessary to take into account the power supply provided by the self-contained power supply of important nodes, and define is the loss value of node j per unit power shortage per unit time, and then the power outage risk value is calculated according to the following formula:

[0098] ;

[0099] in, represents the power outage risk value of node j during a power outage; represents the power outage loss value of node j during power outage; represents the power outage probability of node j under an emergency event, such as a natural disaster.

[0100] More specifically, the power outage loss value is calculated according to the following formula:

[0101] ;

[0102] in, is the loss value of node j per unit power shortage per unit time, is the power demand value of the load system at node j during a power outage, It is the power that the load system of node j can provide by its own power supply during a power outage.

[0103] In addition, the above steps comprehensively consider the deployment time of mobile energy storage vehicles and the power outage risk values ​​of each load node in the distribution network. In order to ensure that the mobile energy storage equipment can reach the load nodes with the highest power outage risk values ​​in the shortest time, thereby minimizing power outage losses, on the premise of meeting time requirements, locations close to these high-risk load nodes are preferentially selected as the initial deployment points of the mobile energy storage equipment. Based on this logic, this step establishes the core goal of optimizing the site selection of mobile energy storage equipment, namely, minimizing the product of the power outage risk value and the deployment time of the mobile energy storage vehicle, thereby improving the emergency response capability and supply efficiency of the distribution network.

[0104] Specifically, in some embodiments, the first objective function is constructed according to the following formula:

[0105] ;

[0106] in, represents the initial node position of mobile energy storage vehicle i, and n represents the total number of n load nodes in the distribution network system;

[0107] The maximum movement time constraint is constructed according to the following formula:

[0108] ;

[0109] in, Indicates the maximum time allowed for a mobile energy storage vehicle to be deployed to the target node.

[0110] Step S103: solving the first objective function, and obtaining the number of selected sites for energy storage devices and the location of each selected site according to the solution result;

[0111] It's important to note that this step employs an innovative matrix iteration approach to systematically explore the shortest path between any two points in a transportation network or similar complex structure. This approach not only enhances the comprehensiveness of the solution, ensuring accurate coverage of the shortest path for all nodes in the network, but also enhances the algorithm's deep analytical capabilities through an iterative process, demonstrating its flexibility and superior design.

[0112] Specifically, if Figure 2 and Figure 3 As shown in the figure, firstly, a node traffic network diagram to be planned is generated based on geographic traffic data information and distribution network node information. The node traffic network includes the travel time between any two nodes, where A, B, C, D, E, F, and G in the example represent nodes, and the numbers between the nodes represent the travel time between the two nodes. Then, a node matrix S is constructed with the total number of nodes as the number of rows and columns. , , ; Represents the travel time between the xth node and the yth node, N represents the total number of nodes, if the xth node is not connected to the yth node, fill in inf in the node matrix; solve the shortest route between any two nodes according to the node matrix, and predict the minimum number of site selection points P based on the shortest route; determine whether the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold; if the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold, obtain at least one site selection point set based on the minimum number of site selection points; sort the at least one site selection point set according to the power outage risk value, and screen out the target site selection point set with the lowest total power outage risk value according to the sorting result; if the travel time between any two nodes in the number of site selection points is greater than the preset maximum time threshold, let , and re-judge whether the travel time between any two nodes after the number of site selection points is updated is less than or equal to the preset maximum time threshold, until the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold.

[0113] It should also be noted that each node included in the site selection point set corresponds to a power outage risk value, and the total power outage risk value is obtained by adding up the power outage risk values ​​of all nodes in the same site selection point set.

[0114] Step S104: Construct an energy storage sizing model for the energy storage equipment at each selected site. The energy storage sizing model includes a second objective function with the goal of minimizing the total cost of the mobile energy storage equipment, and constraints on the second objective function. The constraints include mobile energy storage equipment constraints, mobile energy storage guaranteed power constraints, node power balance constraints, load power constraints, self-contained power supply constraints, and satisfaction constraints.

[0115] It should be noted that in the distribution network, different types of loads with greatly different characteristics exist at the same node. This step divides them into a safety load layer, an economic load layer, and a quality load layer. In order to maximize the use value of mobile energy storage equipment, it is necessary to scientifically and rationally configure the capacity and location of mobile energy storage equipment according to the load characteristics of each node. By accurately matching the capacity of mobile energy storage equipment with the needs of critical loads, these devices can be utilized more effectively, improving the supply guarantee capacity of the distribution network and ensuring the stable operation of the power grid. Therefore, optimizing the configuration strategy of mobile energy storage equipment and improving its utilization efficiency in the distribution network are the key to enhancing the distribution network's ability to respond to emergencies.

[0116] Furthermore, it should be noted that the core objective of dividing distribution network loads into safety, quality, and economic load layers is to achieve coordinated optimization of grid operational efficiency, reliability, and economy through hierarchical management. The safety load layer focuses on basic power supply assurance in extreme scenarios, prioritizing the power supply of critical loads in special scenarios such as hospitals and emergency facilities to avoid major risks caused by power outages. The quality load layer addresses the stringent power quality requirements of some high-end industries, ensuring voltage and frequency stability through customized services and reducing harmonic interference, thereby supporting the development of high-end industries and reducing equipment losses. The economic load layer effectively regulates interruptible or flexible loads, utilizing time-of-use pricing and demand response mechanisms to guide users to stagger their electricity consumption, smoothing out peak and valley load differences, reducing power supply costs, and enhancing the ability to absorb new energy. This layered model breaks the "one-size-fits-all" management limitations of traditional power grids through differentiated services, which not only enhances the system's resilience to risks, but also optimizes resource allocation with the help of price signals. It reflects the transformation of the power system from "single supply guarantee" to refined services with multiple objectives coordinated under the "safety-quality-economy" model. Especially in the context of a high proportion of new energy access, it can more flexibly coordinate resources on both the supply and demand sides and effectively achieve a balance between social and economic benefits.

[0117] In the power industry, customer satisfaction, as a core indicator for measuring a company's service quality, is of paramount importance. This metric is not only directly linked to the market competitiveness of power companies but also serves as the cornerstone for building and maintaining customer loyalty. A comprehensive assessment of customer satisfaction requires comprehensive consideration of multiple dimensions, such as service quality, perceived value, and customer trust and loyalty. From a technical perspective, the continuity and stability of power supply are crucial technical safeguards for improving customer satisfaction. In this context, mobile energy storage devices play a crucial role. By clarifying the installation capacity and location of mobile energy storage devices, their application value within the distribution network can be maximized.

[0118] Specifically, when the power grid is operating normally, mobile energy storage devices can actively participate in peak load regulation, frequency regulation, and power quality control, effectively ensuring the stable operation of the distribution network and improving overall power supply quality. In the event of a grid failure, these devices can quickly serve as emergency power sources, providing power to the affected area, significantly shortening the outage duration and reducing outage losses. Furthermore, deploying mobile energy storage devices in the distribution system not only improves system stability and reliability, but also enhances its resilience and adaptability. This enables the distribution system to respond quickly and effectively to various emergencies, thereby ensuring the continuity and stability of power supply and further improving customer satisfaction. In summary, mobile energy storage devices play a vital role in improving customer satisfaction and enhancing the stability and reliability of the distribution system. In the future, with the continuous advancement of technology and the deepening of its application, its value in the power industry will be further demonstrated.

[0119] By constraining user satisfaction, the minimum power value of the mobile energy storage device that needs to be provided is obtained, and then the mobile energy storage device is selected based on the types of mobile energy storage vehicles that can be provided and considering cost issues.

[0120] For example, for a certain distribution network, there are n load nodes that need to be guaranteed to be supplied in a specified power supply area. The letter j represents any node among them, and j can be a positive integer from 1 to n. When a fault occurs, the power department needs to dispatch mobile energy storage equipment to meet the power quality requirements of each load node and the satisfaction of power users as much as possible. When the load power supply of node j is insufficient due to a fault, the required power can be defined separately. Define the safe load layer load power of node j as , the economic load layer load power of node j is , the high-quality load layer load power of node j is .

[0121] The safety load layer satisfaction is then calculated according to the following formula:

[0122] ;

[0123] in, It represents the guaranteed supply demand level of the load power of the safety load layer of load node j, represents the power supply that the mobile energy storage device at load node j can provide for the safety load layer, It represents the power that the self-contained power supply of load node j can provide to the safety load layer during a power outage;

[0124] The economic load layer satisfaction is calculated according to the following formula:

[0125] ;

[0126] in, It represents the supply demand level of the load power of the economic load layer of load node j, represents the power supply that the mobile energy storage device at load node j can provide to the economic load layer, It represents the power that the self-contained power supply of load node j can provide to the economic load layer during a power outage;

[0127] The quality load layer satisfaction is calculated according to the following formula:

[0128] ;

[0129] in, It represents the supply demand level of the load power of the quality load layer of load node j, It represents the power supply that the mobile energy storage device of load node j can provide to the quality load layer, It represents the power that the self-contained power supply of load node j can provide to the quality load layer during a power outage.

[0130] Furthermore, in some embodiments, the second objective function is constructed according to the following formula:

[0131] ;

[0132] in, represents the total mobile energy storage vehicle construction cost; represents the construction cost of a single mobile energy storage vehicle of type h; H represents the number of types of mobile energy storage vehicles; represents the number of mobile energy storage devices of type h.

[0133] Furthermore, in some embodiments, regarding mobile energy storage device constraints, mobile energy storage vehicles are used. Due to cost considerations, the types and quantities of energy storage devices that power supply units can deploy are limited. Based on the aforementioned load node power requirements, a reasonable configuration solution is selected while minimizing costs.

[0134] Regarding the power constraint for mobile energy storage, after the mobile energy storage device is dispatched to load node j during a fault, the maximum power that the mobile energy storage device can provide should be no less than the maximum power required by the load side. That is, the power constraint for mobile energy storage is constructed according to the following formula:

[0135] ;

[0136] Where H represents the total number of mobile energy storage vehicles; Indicates the type of mobile energy storage vehicle, h can be a positive integer from 1 to H.

[0137] The node power balance constraint is constructed according to the following formula:

[0138] ;

[0139] in, represents the total load power of node j, It represents the power that the load system of node j can provide when the power is cut off.

[0140] Regarding the load power constraint, it is assumed that after the mobile energy storage device is dispatched, at node j, the power of different load layers that it can restore does not exceed the total power required by the load layer. That is, the load power constraint is constructed according to the following formula:

[0141] ;

[0142] Regarding the self-provided power supply power constraint, it is set that the sum of the self-provided power supply power of different load layers of node j does not exceed the maximum self-provided power supply power that node j can provide, that is, the self-provided power supply power constraint is constructed according to the following formula:

[0143] ;

[0144] in, It represents the power that the self-contained power supply of load node j can provide to the safety load layer during a power outage. It represents the power that the self-contained power supply of load node j can provide to the economic load layer during a power outage. It represents the power that the self-contained power supply of load node j can provide to the quality load layer during a power outage. It means that the total self-supplied power of different load layers of node j does not exceed the maximum self-supplied power that node j can provide.

[0145] Regarding the satisfaction constraint, when a distribution network failure occurs, the satisfaction needs to meet certain requirements. Considering the importance of different types of load layers, the weighted value is used for summation:

[0146] .

[0147] In summary, this step establishes a sizing model for mobile energy storage equipment. First, after load stratification, a corresponding satisfaction model is established. By constraining the satisfaction level, the minimum mobile energy storage equipment power required in the event of a fault is obtained. Further considering the cost issue, the optimal mobile energy storage vehicle configuration method is given, completing the sizing analysis of the mobile energy storage equipment.

[0148] In summary, according to the above-mentioned mobile energy storage configuration method for distribution network supply guarantee, the site selection problem of mobile energy storage equipment in the distribution network and the selection problem of mobile energy storage vehicles are divided into two parts and discussed in sequence, step by step. When constructing the mobile energy storage device configuration model, the time it takes for the energy storage vehicle to arrive at the node in the power outage area and the load demand that needs to be met are comprehensively considered. The first task is to select the best parking location for the energy storage vehicle to ensure that in the event of a power outage due to a load node failure, the mobile energy storage vehicle can respond quickly and quickly reach the power outage area, thereby shortening the power outage duration and ensuring the stability of the power supply. Then, by constraining user satisfaction, the minimum power value of the mobile energy storage device that needs to be provided is obtained, and then the configuration of the mobile energy storage vehicle is selected based on the types that the known mobile energy storage vehicles can provide and considering the cost issue. This method not only improves the daily utilization efficiency of emergency resources, but also significantly enhances the response speed and supply guarantee capability of the distribution network in emergencies, effectively shortening the power outage duration and reducing economic losses.

[0149] like Figure 4 As shown, an embodiment of the present invention further provides a mobile energy storage configuration system for ensuring power supply to a distribution network, the system comprising:

[0150] The travel time calculation module 10 is used to obtain the equivalent section distance that the mobile energy storage device i needs to travel from its initial position in the transportation network to the load node k of the distribution network, and calculate the travel time based on the equivalent section distance;

[0151] A first objective function construction module 20 is configured to obtain a power outage risk value per unit time for each node, construct a first objective function based on the power outage risk value and the movement time, and construct a maximum movement time constraint condition;

[0152] A solution module 30 is configured to solve the first objective function and obtain the number of selected sites for energy storage devices and the location of each selected site based on the solution result;

[0153] The energy storage sizing model construction module 40 is used to construct an energy storage sizing model for the energy storage equipment at each selected site. The energy storage sizing model includes a second objective function with the goal of minimizing the total cost of the mobile energy storage equipment, and constraints on the second objective function. The constraints include mobile energy storage equipment constraints, mobile energy storage guaranteed power constraints, node power balance constraints, load power constraints, self-contained power supply constraints, and satisfaction constraints.

[0154] On the other hand, the present invention further proposes a storage medium having one or more programs stored thereon, which, when executed by a processor, implements the above-mentioned mobile energy storage configuration method for ensuring power supply to a distribution network.

[0155] On the other hand, the present invention also proposes an electronic device, including a memory and a processor, wherein the memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to implement the above-mentioned mobile energy storage configuration method for distribution network supply guarantee.

[0156] Those skilled in the art will appreciate that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device), or in conjunction with such instruction execution system, apparatus, or device. For purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system, apparatus, or device, or in conjunction with such instruction execution system, apparatus, or device.

[0157] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0158] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the aforementioned embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one or a combination of the following technologies known in the art may be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0159] While the embodiments of the present invention have been described in detail above, it will be apparent to those skilled in the art that various modifications and variations of these embodiments are possible. However, it should be understood that such modifications and variations are within the scope and spirit of the present invention as set forth in the claims. Furthermore, the invention described herein is susceptible to other embodiments and may be practiced or implemented in a variety of ways.

Claims

1. A mobile energy storage configuration method for ensuring power supply in a distribution network, characterized in that: The method comprises: Obtain the equivalent road section distance that the mobile energy storage device i needs to travel from its initial position in the transportation network to the load node j in the distribution network, and calculate the travel time based on the equivalent road section distance; Obtaining a power outage risk value per unit time for each node, constructing a first objective function according to the power outage risk value and the movement time, and constructing a maximum movement time constraint condition; The power outage risk value is calculated according to the following formula: ； in, represents the power outage risk value of node j during a power outage; represents the power outage loss value of node j during power outage; represents the power outage probability of node j under an emergency event; The power outage loss value is calculated according to the following formula: ； in, is the loss value of node j per unit power shortage per unit time, is the power demand value of the load system at node j during a power outage, is the power that the self-contained power supply of the load system at node j can provide during a power outage; The first objective function is constructed according to the following formula: ； in, represents the initial node position of mobile energy storage vehicle i, and n represents the total number of n load nodes in the distribution network system; The maximum movement time constraint is constructed according to the following formula: ； in, Indicates the maximum time allowed for the mobile energy storage vehicle to be deployed to the target node; Solving the first objective function and obtaining the number of selected sites for energy storage devices and the location of each selected site based on the solution; Constructing an energy storage sizing model for the energy storage device at each selected site, the energy storage sizing model including a second objective function with the goal of minimizing the total cost of the mobile energy storage device, and constraints on the second objective function, the constraints including mobile energy storage device constraints, mobile energy storage guaranteed power constraints, node power balance constraints, load power constraints, self-contained power supply power constraints, and satisfaction constraints; Regarding the constraints on mobile energy storage equipment, the mobile energy storage equipment used is a mobile energy storage vehicle.

2. The mobile energy storage configuration method for ensuring power supply to a distribution network according to claim 1 is characterized in that: The step of obtaining the equivalent road section distance that the mobile energy storage device i needs to travel from the initial position to the load node k of the distribution network in the transportation network, and calculating the moving time based on the equivalent road section distance includes: The moving time is calculated according to the following formula: ； in, Indicates that the mobile energy storage vehicle i moves from the initial position The time required to deploy to node j; Represents the movement of mobile energy storage vehicle i from its initial position in the traffic network The equivalent distance of the road section required to reach node j; represents the actual speed of mobile energy storage vehicle i during the passage period; The distance of the road section is calculated according to the following formula: ； in, The mobile energy storage vehicle i moves from its initial position in the traffic network The shortest distance to node j; The actual speed is calculated according to the following formula: ； in, is the vehicle speed under ideal conditions with zero traffic flow; c represents the congestion level of the traffic network under disaster scenarios.

3. The mobile energy storage configuration method for ensuring power supply to a distribution network according to claim 2 is characterized in that: The step of solving the first objective function and obtaining the number of selected sites for energy storage devices and the position of each selected site according to the solution comprises: Generate a node traffic network diagram to be planned based on geographic traffic data information and distribution network node information, wherein the node traffic network includes the travel time between any two nodes; Construct the node matrix S with the total number of nodes as the number of rows and columns, , , ; represents the travel time between the xth node and the yth node, N represents the total number of nodes, and if the xth node is not connected to the yth node, fill in inf in the node matrix; Solve the shortest route between any two nodes according to the node matrix, and predict the minimum number of site selection points P based on the shortest route; Determine whether the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold; If the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold, then at least one site selection point set is obtained based on the minimum number of site selection points; Sorting the at least one set of site selection points according to the power outage risk value, and selecting the target set of site selection points with the lowest total power outage risk value according to the sorting result; If the travel time between any two nodes in the number of site selection points is greater than the preset maximum time threshold, then , and re-judge whether the travel time between any two nodes after the number of site selection points is updated is less than or equal to the preset maximum time threshold, until the travel time between any two nodes in the number of site selection points is less than or equal to the preset maximum time threshold.

4. The mobile energy storage configuration method for ensuring power supply to a distribution network according to claim 3 is characterized in that: The step of constructing an energy storage capacity determination model for the energy storage device at each selected site, wherein the energy storage capacity determination model includes a second objective function with the goal of minimizing the total cost of the mobile energy storage device and constraints on the second objective function includes: The second objective function is constructed according to the following formula: ； in, represents the total mobile energy storage vehicle construction cost; represents the construction cost of a single mobile energy storage vehicle of type h; H represents the number of types of mobile energy storage vehicles; represents the number of mobile energy storage vehicles of type h; The power constraint for mobile energy storage supply is constructed according to the following formula: ； Where H represents the total number of mobile energy storage vehicles; Represents the power of the h-th type of mobile energy storage vehicle, where h can be a positive integer from 1 to H. represents the power supply that the mobile energy storage vehicle at load node j can provide for the safety load layer, represents the power supply that the mobile energy storage vehicle at load node j can provide to the economic load layer, It represents the power supply that the mobile energy storage vehicle at load node j can provide to the quality load layer; The node power balance constraint is constructed according to the following formula: ； in, represents the safety load layer load power of node j, represents the economic load layer load power of node j, represents the quality load layer load power of node j, represents the total load power of node j, represents the power that the self-contained power supply of the load system at node j can provide during a power outage; The load power constraint is constructed according to the following formula: ； The self-provided power supply power constraint is constructed according to the following formula: ； in, It represents the power that the self-contained power supply of load node j can provide to the safety load layer during a power outage. It represents the power that the self-contained power supply of load node j can provide to the economic load layer during a power outage. It represents the power that the self-contained power supply of load node j can provide to the quality load layer during a power outage. The sum of the self-supplied power of different load layers of node j does not exceed the maximum self-supplied power that node j can provide; The satisfaction constraint is constructed according to the following formula: ； Among them, Y is the user's overall satisfaction; is the weight of safety load layer satisfaction; is the weight of the economic load layer satisfaction; is the weight of the quality load layer satisfaction; Satisfaction level for safety load layer; is the economic load layer satisfaction; For quality load layer satisfaction.

5. The mobile energy storage configuration method for ensuring power supply to a distribution network according to claim 4 is characterized in that: The safety load layer satisfaction is calculated according to the following formula: ； in, It represents the guaranteed supply demand level of the load power of the safety load layer of load node j, It represents the power that the self-contained power supply of load node j can provide to the safety load layer during a power outage; The economic load layer satisfaction is calculated according to the following formula: ； in, It represents the supply demand level of the load power of the economic load layer of load node j, represents the power supply that the mobile energy storage vehicle at load node j can provide to the economic load layer, It represents the power that the self-contained power supply of load node j can provide to the economic load layer during a power outage; The quality load layer satisfaction is calculated according to the following formula: ； in, It represents the supply demand level of the load power of the quality load layer of load node j, It represents the power supply that the mobile energy storage vehicle at load node j can provide to the quality load layer, It represents the power that the self-contained power supply of load node j can provide to the quality load layer during a power outage.

6. A mobile energy storage configuration system for ensuring power supply to distribution networks, characterized in that: The system comprises: A travel time calculation module is used to obtain the equivalent road section distance that the mobile energy storage device i needs to travel from its initial position in the transportation network to the load node j in the distribution network, and calculate the travel time based on the equivalent road section distance; a first objective function construction module, configured to obtain a power outage risk value per unit time for each node, to construct a first objective function according to the power outage risk value and the movement time, and to construct a maximum movement time constraint; The power outage risk value is calculated according to the following formula: ； in, represents the power outage risk value of node j during a power outage; represents the power outage loss value of node j during power outage; represents the power outage probability of node j under an emergency event; The power outage loss value is calculated according to the following formula: ； in, is the loss value of node j per unit power shortage per unit time, is the power demand value of the load system at node j during a power outage, is the power that the self-contained power supply of the load system at node j can provide during a power outage; The first objective function is constructed according to the following formula: ； in, represents the initial node position of mobile energy storage vehicle i, and n represents the total number of n load nodes in the distribution network system; The maximum movement time constraint is constructed according to the following formula: ； in, Indicates the maximum time allowed for the mobile energy storage vehicle to be deployed to the target node; A solution module, configured to solve the first objective function and obtain the number of selected sites for energy storage devices and the location of each selected site according to the solution result; An energy storage sizing model construction module is used to construct an energy storage sizing model for the energy storage device at each selected site. The energy storage sizing model includes a second objective function with the goal of minimizing the total cost of the mobile energy storage device, and constraints on the second objective function, including constraints on the mobile energy storage device, constraints on the guaranteed power supply of the mobile energy storage, constraints on node power balance, constraints on load power, constraints on the power of the self-contained power supply, and constraints on satisfaction. Regarding the constraints on mobile energy storage equipment, the mobile energy storage equipment used is a mobile energy storage vehicle.

7. A storage medium, characterized in that: The storage medium stores one or more programs, which, when executed by the processor, implement the mobile energy storage configuration method for distribution network supply guarantee as described in any one of claims 1 to 5.

8. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute the computer program stored in the memory, it implements the mobile energy storage configuration method for distribution network supply guarantee as described in any one of claims 1 to 5.

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