Method and device for allocating charging stations, computing equipment and readable storage medium

Abstract

This invention discloses a method, apparatus, computing device, and readable storage medium for allocating charging and battery swapping stations, relating to the field of computers. The method for allocating charging and battery swapping stations includes: obtaining basic parameters; obtaining the comprehensive utility of each candidate station in the area to be allocated based on social network analysis; and constructing a charging and battery swapping station allocation model based on the obtained comprehensive utility of each candidate station. This model includes an objective function and constraints, where the objective function is where P represents a metric for charging and battery swapping station allocation, and P... i x represents the overall utility of candidate station i. i x can be either 0 or 1. i Setting x to 1 indicates that a charging / swapping station is established at candidate station i, and x i Setting the value to 0 indicates that no charging / swapping station will be established at candidate station i, and m represents the number of candidate stations in the area to be allocated. The basic parameters are input into the model, and the model is solved with the objective of minimizing the metric for charging / swapping station allocation. The resulting solution outputs the allocation scheme for charging / swapping stations in the area to be allocated. This invention can achieve a more balanced distribution of charging / swapping stations.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of computers, and in particular to a charging station distribution method and device, a computing device and a readable storage medium. BACKGROUND

[0002] Environmental pollution and energy crisis caused by environmental destruction and resource depletion have become a serious problem for the sustainable development of the world.

[0003] Among them, the widespread use of electric vehicles is crucial to the sustainable development of cities, which can promote the low-carbon transformation of urban transportation systems. However, the development of electric vehicles is constrained by their service facilities. For example, in recent years, the lack of charging station layout has seriously hindered the development of electric vehicles in cities and the promotion of decarbonization of urban transportation.

[0004] Therefore, there is an urgent need for a charging station distribution method to solve the above problems. SUMMARY

[0005] Therefore, the present application provides a charging station distribution method, device, computing device and readable storage medium to try to solve or at least alleviate the above problems.

[0006] According to one aspect of the present application, a charging station distribution method is provided, comprising: obtaining basic parameters; obtaining the comprehensive utility of each candidate station in the region to be distributed based on social network analysis; constructing a charging station distribution model based on the obtained comprehensive utility of each candidate station, the model including an objective function and a constraint condition, the objective function being wherein P represents a metric index of charging station distribution, P i represents the comprehensive utility of candidate station i, x i takes the value of 0 or 1, x i takes 1 to indicate that a charging station is established at candidate station i, x i takes 0 to indicate that no charging station is established at candidate station i, and m represents the number of candidate stations in the region to be distributed; inputting the basic parameters into the model to establish the sum of the reciprocals of the comprehensive utility of each candidate station of the charging station as the target, solving the model, and outputting the distribution scheme of the charging station in the region to be distributed.

[0007] Optionally, in the charging station distribution method according to the present application, the comprehensive utility of each candidate station in the region to be distributed is obtained based on social network analysis, comprising: obtaining the point centrality, proximity centrality and interval centrality of each candidate station; normalizing the point centrality, proximity centrality and interval centrality of each candidate station; for each candidate station, obtaining the average value of the normalized point centrality, proximity centrality and interval centrality of the candidate station, and taking it as the comprehensive utility of the candidate station.

[0008] Optionally, in the distribution method of charging and swapping stations according to the present application, in the step of obtaining the point centrality, the proximity centrality and the interval centrality of each candidate station:

[0009] The point centrality is obtained by the following formula:

[0010]

[0011] The proximity centrality is obtained by the following formula:

[0012]

[0013] The interval centrality is obtained by the following formula:

[0014]

[0015] wherein C D (i) represents the point centrality of the candidate station i, a ij takes the value of 1 or 0, a ij takes 1 to represent that the candidate station i and the candidate station j are directly connected by a road, a ij takes 0 to represent that the candidate station i and the candidate station j are not directly connected by a road, C c (i) represents the proximity centrality of the candidate station i, d(i,j) represents the distance between the candidate station i and the candidate station j, C B (i) represents the interval centrality of the candidate station i, g jk represents the number of shortest paths connecting the two candidate stations j and k, g jk (i) represents the number of paths containing the candidate station i in the shortest paths connecting the two candidate stations j and k.

[0016] Optionally, in the distribution method of charging and swapping stations according to the present application, the constraint conditions include the constraint of the candidate station establishing charging and swapping stations, the constraint of the number of electric vehicles served by the candidate station, the constraint of the demand point being covered by the candidate station, and the constraint of the total number of charging and swapping stations to be established.

[0017] Optionally, in the distribution method of charging and swapping stations according to the present application, the constraint of the candidate station establishing charging and swapping stations includes:

[0018]

[0019] x i ≥x iu

[0020] wherein x iu takes the value of 0 or 1, x iu takes 0 to represent that the demand point u is not covered by the candidate station i, x iu1 indicates that the demand point u is covered by the candidate station i, and n indicates the number of demand points in the region to be allocated.

[0021] Optionally, in the allocation method of the charging and swapping station according to the present application, the constraint of the number of electric vehicles served by the candidate station comprises:

[0022]

[0023] wherein D u indicates the number of electric vehicles in the demand point u, D i indicates the number of electric vehicles served by the candidate station i.

[0024] Optionally, in the allocation method of the charging and swapping station according to the present application, the constraint of the demand point covered by the candidate station comprises:

[0025]

[0026]

[0027] x iu ≤c iu

[0028] wherein c iu indicates the coverage coefficient of the candidate station i covering the demand point u, l iu indicates the Manhattan distance between the candidate station i and the demand point u, R2 indicates the maximum service radius of the candidate station, and q u q takes a value of 0 or 1, q u q takes 0, indicating that the demand point u is an invalid demand point, q u q takes 1, indicating that the demand point u is a valid demand point.

[0029] Optionally, in the allocation method of the charging and swapping station according to the present application, the constraint of the total number of charging and swapping stations comprises:

[0030]

[0031] wherein N indicates the minimum number of charging and swapping stations to be established in the region to be allocated.

[0032] According to another aspect of the present application, there is provided an allocation device of a charging and swapping station, comprising: a parameter acquisition module adapted to acquire basic parameters; a utility acquisition module adapted to acquire the comprehensive utility of each candidate station in the region to be allocated based on a social network analysis method; and a model construction module adapted to construct a charging and swapping station allocation model based on the obtained comprehensive utility of each candidate station, the model comprising an objective function and constraint conditions, the objective function being wherein P indicates a measurement index of the charging and swapping station allocation, P i indicates the comprehensive utility of the candidate station i, x ix takes the value 0 or 1. i Setting x to 1 indicates that a charging / swapping station is established at candidate station i, and x i Setting it to 0 indicates that no charging / swapping station will be established at candidate station i, and m represents the number of candidate stations in the area to be allocated. The model solving module is suitable for inputting basic parameters into the model, with the goal of minimizing the sum of the reciprocals of the comprehensive utility of each candidate station that establishes a charging / swapping station, solving the model, and outputting the allocation scheme of charging / swapping stations in the area to be allocated.

[0033] According to another aspect of the present invention, a computing device is provided, comprising: at least one processor; and a memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, the program instructions including instructions for performing the allocation method of the charging / swapping station according to the present invention.

[0034] According to another aspect of the present invention, a readable storage medium storing program instructions is provided, which, when read and executed by a computing device, causes the computing device to perform the allocation method of the charging / swapping station according to the present invention.

[0035] In summary, this invention provides a method for allocating charging and battery swapping stations based on social network analysis. This method enables a more balanced distribution of charging and battery swapping stations, thereby better meeting the charging and battery swapping needs of electric vehicle users and promoting the development of electric vehicles in cities and the decarbonization of urban transportation. Furthermore, this invention helps to achieve load balancing of charging and battery swapping stations and optimize energy utilization. Attached Figure Description

[0036] To achieve the foregoing and related objectives, certain illustrative aspects are described herein in conjunction with the following description and accompanying drawings. These aspects indicate various ways in which the principles disclosed herein may be practiced, and all aspects and their equivalents are intended to fall within the scope of the claimed subject matter. The foregoing and other objectives, features, and advantages of this disclosure will become more apparent from the following detailed description, taken in conjunction with the accompanying drawings. Throughout this disclosure, the same reference numerals generally refer to the same parts or elements.

[0037] Figure 1 A structural block diagram of a computing device 100 according to an embodiment of the present invention is shown;

[0038] Figure 2 A flowchart of a charging / swapping station allocation method 200 according to an embodiment of the present invention is shown;

[0039] Figure 3 A structural diagram of a distribution device 300 for a charging / swapping station according to an embodiment of the present invention is shown. Detailed Implementation

[0040] Exemplary embodiments of the present disclosure will be described below in greater detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure can be embodied in various forms without being limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be thorough and complete, and will fully convey the scope of the present disclosure to those skilled in the art.

[0041] In recent years, the layout of electric vehicle service facilities, especially charging and battery swapping stations, hinders the development of electric vehicles in cities and the promotion of decarbonization of urban transportation. Based on this, the present application provides a charging and battery swapping station distribution method. The charging and battery swapping station distribution method of the present application can be executed in a computing device.

[0042] Figure 1 A block diagram showing the physical components (i.e., hardware) of the computing device 100 is shown. In a basic configuration, the computing device 100 includes at least one processing unit 102 and a system memory 104. According to one aspect, depending on the configuration and type of computing device, the processing unit 102 can be implemented as a processor. The system memory 104 includes, but is not limited to, volatile (e.g., random access memory (RAM)), non-volatile (e.g., read-only memory (ROM)), flash memory, or any combination thereof. According to one aspect, the system memory 104 includes an operating system 105 and program modules 106, which include a charging and battery swapping station distribution apparatus 300 configured to perform the charging and battery swapping station distribution method 200 of the present application.

[0043] According to one aspect, the operating system 105 is suitable for controlling the operation of the computing device 100, for example. Moreover, examples are practiced in conjunction with a graphics library, other operating systems, or any other application program, and are not limited to any particular application or system. In Figure 1 This basic configuration is illustrated in FIG. 1 by those components within the dashed line 108. According to one aspect, the computing device 100 has additional features or functionality. For example, according to one aspect, the computing device 100 includes additional data storage devices (removable and / or non-removable) such as, for example, magnetic disks, optical disks, or tape. Such additional storage is illustrated in FIG. 1 by the removable storage 109 and the non-removable storage 110. Figure 1 According to one aspect, the removable storage 109 and the non-removable storage 110 are examples of storage media. According to one aspect, the removable storage 109 and the non-removable storage 110 include, but are not limited to, volatile (e.g., random access memory (RAM)), non-volatile (e.g., read-only memory (ROM)), flash memory, or any combination thereof. According to one aspect, the computing device 100 includes a storage controller 111, which represents a component that is configured to facilitate the transfer of data between the system memory 104 and the removable storage 109 and the non-removable storage 110.

[0044] As stated above, according to one aspect, a program module is stored in system memory 104. According to one aspect, the program module may include one or more applications. The present invention does not limit the type of application; for example, applications may include: email and contact applications, word processing applications, spreadsheet applications, database applications, slideshow applications, drawing or computer-aided applications, web browser applications, etc.

[0045] According to one aspect, examples can be practiced on circuits including discrete electronic components, packaged or integrated electronic chips containing logic gates, circuits utilizing microprocessors, or on a single chip containing electronic components or a microprocessor. For example, it can be practiced via wherein... Figure 1 Each or many of the components shown can be implemented as an example by integrating a System-on-a-Chip (SOC) on a single integrated circuit. According to one aspect, such an SOC device may include one or more processing units, graphics units, communication units, system virtualization units, and various application functions, all integrated (or “burned in”) as a single integrated circuit onto a chip substrate. When operating via the SOC, the functions described herein can be operated via dedicated logic integrated on a single integrated circuit (chip) with other components of the computing device 100. Embodiments of the invention can also be implemented using other techniques capable of performing logical operations (e.g., AND, OR, and NOT), including but not limited to mechanical, optical, fluid, and quantum technologies. Additionally, embodiments of the invention can be implemented within a general-purpose computer or in any other circuit or system.

[0046] According to one aspect, computing device 100 may also have one or more input devices 112, such as a keyboard, mouse, pen, voice input device, touch input device, etc. It may also include output devices 114, such as a display, speaker, printer, etc. The foregoing devices are examples and other devices may also be used. Computing device 100 may include one or more communication connections 116 that allow communication with other computing devices 118. Examples of suitable communication connections 116 include, but are not limited to: RF transmitter, receiver and / or transceiver circuitry; Universal Serial Bus (USB), parallel and / or serial ports.

[0047] The term computer readable media as used herein includes computer storage media. Computer storage media can include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, or program modules. The system memory 104, the removable storage 109, and the non-removable storage 110 are all computer storage media examples (i.e., memory storage.) Computer storage media can include Random Access Memory (RAM), Read-Only Memory (ROM), Electronically Erasable Programmable Read-Only Memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other article of manufacture which can be used to store information and which can be accessed by the computing device 100. According to an aspect, any such computer storage media can be part of the computing device 100. Computer storage media does not include a carrier wave or other propagated data signal.

[0048] According to an aspect, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. According to an aspect, the term "modulated data signal" describes a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.

[0049] Figure 2 A method for allocating a charging station is shown, method 200 is suitable for execution in a computing device (e.g. Figure 1 The computing device 100 is shown. As Figure 2 The method 200 begins at 210.

[0050] In 210, the basic parameters are acquired. The basic parameters are input data of the charging station allocation model. Specifically, in some embodiments, the basic parameters can include one or more of the following: a minimum number of charging stations to be established in the region to be allocated, a number of candidate stations in the region to be allocated, a number of demand points in the region to be allocated, a total area of the region to be allocated, an average coverage area of the candidate stations, a total number of electric vehicles in the region to be allocated, a distribution coefficient of electric vehicles at each demand point (or a distribution coefficient of electric vehicles in each sub-region of the region to be allocated), an average distance between all adjacent candidate stations in the region to be allocated, a maximum service radius of the candidate stations (i.e., a maximum service distance of the candidate stations), a number of electric vehicles that can be served by the candidate stations (i.e., a maximum number of electric vehicles that can be served by one candidate station), and a charging probability. It should be noted that the specific values of the maximum service radius of the candidate stations, the number of electric vehicles that can be served by the candidate stations, and the charging probability can be set according to actual needs, and the present application does not limit them.

[0051] Next, in step 220, the comprehensive utility of each candidate station in the region to be allocated is acquired based on social network analysis. The candidate station is each node of a road network (hereinafter referred to as a road network for convenience) in the region to be allocated. Specifically, the road network is composed of nodes and connecting lines, the nodes are intersections of roads, and the connecting lines represent roads.

[0052] In addition, social network analysis (SNA) can analyze social networks from multiple different perspectives, including centrality analysis, cohesive subgroup analysis, core-periphery structure analysis, and structural equivalence analysis. In this embodiment, centrality analysis is used. Specifically, it can be analyzed from the following three aspects: first, the core role of a node in the network, referred to as point degree centrality; second, the ability of a node to establish connections with other nodes, referred to as closeness centrality; and third, the control ability of a node over other nodes, referred to as betweenness centrality.

[0053] Based on this, according to an embodiment of the present application, the comprehensive utility of each candidate station in the region to be allocated can be acquired based on social network analysis in the following manner.

[0054] First, the point degree centrality, closeness centrality, and betweenness centrality of each candidate station are acquired.

[0055] Wherein, before acquiring the point degree centrality of each candidate station, an adjacency matrix A(G) of the road network G in the region to be allocated can be established first. ij} where a ij takes the value of 1 or 0, and a ij takes the value of 1, indicating that there is a direct connection between node i and node j (or a ijSetting a value of 1 indicates that candidate station i and candidate station j are directly connected by a road. ij Setting it to 0 indicates that there is no direct road connection between node i and node j (or, in other words, a). ij (A value of 0 indicates that there is no direct road connection between candidate station i and candidate station j), V is the set of nodes, and E is the set of edges (i.e., roads). Table 1 below shows the adjacency matrix of the road network established when the number of nodes in the region to be assigned is m.

[0056]

[0057] Table 1

[0058] To clarify, road network G is an undirected road network, meaning that in this embodiment, the direction and flow characteristics of the areas to be allocated are ignored when determining road network G. Additionally, when i and j are the same, a... ij The value is 0.

[0059] After establishing the adjacency matrix A(G), we can know the values ​​of each a. ij The value of . Thus, the degree centrality of each candidate station can be obtained using the following formula:

[0060]

[0061] Among them, C D (i) represents the degree centrality of candidate station i, and m represents the number of candidate stations in the region to be assigned.

[0062] Regarding proximity centrality and spacing centrality, according to an embodiment of the present invention, they can be obtained respectively in the following ways. Specifically:

[0063] The proximity centrality of each candidate station is obtained using the following formula:

[0064]

[0065] The interval centrality of each candidate station is obtained using the following formula:

[0066]

[0067] Among them, C c (i) represents the proximity centrality of candidate station i, d(i,j) represents the distance between candidate station i and candidate station j (which can be obtained from the coordinates of candidate stations i and j), C B (i) represents the interval centrality of candidate station i, g jk G represents the number of shortest paths connecting candidate stations j and k (i.e., the number of shortest paths among all paths connecting candidate stations j and k). jk (i) represents the number of paths that contain candidate station i in the shortest path connecting two candidate stations j and k.

[0068] At this point, the point centrality, the proximity centrality and the interval centrality of each candidate station are obtained. Then, the point centrality, the proximity centrality and the interval centrality of each candidate station are normalized. Specifically:

[0069] The point centrality of each candidate station is normalized by the following formula:

[0070]

[0071] The proximity centrality of each candidate station is normalized by the following formula:

[0072]

[0073] The interval centrality of each candidate station is normalized by the following formula:

[0074]

[0075] Wherein, P Di , P Ci and P Bi respectively represent the normalized point centrality, the normalized proximity centrality and the normalized interval centrality of the candidate station i.

[0076] Finally, for each candidate station, the average value of the normalized point centrality, the normalized proximity centrality and the normalized interval centrality of the candidate station is obtained, and is taken as the comprehensive utility of the candidate station. That is, the average value of the normalized point centrality, the normalized proximity centrality and the normalized interval centrality of each candidate station is taken as the comprehensive utility of the candidate station, which is specifically as follows.

[0077]

[0078] Wherein, P i represents the comprehensive utility of the candidate station i. The larger Pi is, the more important the core, the relevance and the control force of the candidate station i in the road network are

[0079] At this point, the comprehensive utility of each candidate station is obtained. In some embodiments, the comprehensive utility set S = {P i i = 1, 2, 3, …, m} can be used to represent the comprehensive utility of each candidate station, of course, this is only an example, and the present application is not limited thereto.

[0080] After obtaining the comprehensive utility of each candidate station, proceed to 230, and build a charging and swapping station allocation model based on the obtained comprehensive utility of each candidate station. It is noted that in the present embodiment, the following assumptions are made when building the charging and swapping station allocation model: the building distribution and population density in the road network are not considered; the region to be allocated is divided into rectangular grids of the same size; the construction cost of each candidate station is the same; and the power supply of each candidate station is stable.

[0081] Further, in some embodiments, the built charging and swapping station allocation model can include an objective function and constraint conditions. Specifically, the objective function is

[0082]

[0083] where P represents a metric index of charging and swapping station allocation, P i represents the comprehensive utility of candidate station i, x i takes a value of 0 or 1, x i takes 1 to indicate that a charging and swapping station is established at candidate station i, x i takes 0 to indicate that no charging and swapping station is established at candidate station i.

[0084] The constraint conditions corresponding to the objective function include: a constraint of candidate station establishing a charging and swapping station, a constraint of the number of electric vehicles served by a candidate station, a constraint of demand points being covered by a candidate station, and a constraint of the total number of charging and swapping stations established.

[0085] Further, the constraint of candidate station establishing a charging and swapping station is a prerequisite for candidate station to establish a charging and swapping station; the constraint of the number of electric vehicles served by a candidate station is to limit the maximum number of electric vehicles that can be served by a candidate station, that is, the service capacity of each candidate station has an upper limit, and the number of electric vehicles that can be served by each candidate station cannot exceed a preset value; the constraint of demand points being covered by a candidate station is to limit how many candidate stations cover each valid demand point, specifically, in some embodiments, each valid demand point can be covered by at least one candidate station, so as to ensure that all valid demand points in the region to be allocated are covered; and the constraint of the total number of charging and swapping stations established is to limit the total number of charging and swapping stations established in the region to be allocated, specifically, in some embodiments, in order to ensure that the number of charging and swapping stations in the region to be allocated is not less than the minimum value under objective conditions, the total number of charging and swapping stations established can be set to be not less than a certain value. Each constraint condition will be described in detail below.

[0086] The constraint of candidate station establishing a charging and swapping station includes:

[0087]

[0088] x i ≥x iu (10)

[0089] wherein x iu is 0 or 1, x iu 0 means that the demand point u is not covered by the candidate station i, x iu 1 means that the demand point u is covered by the candidate station i, and n represents the number of demand points in the region to be allocated.

[0090] As to the demand points, according to one embodiment of the present application, they can be constructed by a grid method. Specifically, the region to be allocated is divided into a plurality of grids by the grid method, and then each grid is taken as a demand point, and the coordinates (i.e. the position) of the center point of each grid are taken as the coordinates of the demand point. Wherein the coordinates of the demand point can be calculated by the following formula:

[0091]

[0092] wherein Loc u represents the coordinates of the demand point u, E u and N u represent the longitude and latitude of the demand point u respectively, E min represents the minimum longitude in the region to be allocated, E max represents the maximum longitude in the region to be allocated, N min represents the minimum latitude in the region to be allocated, N max represents the maximum latitude in the region to be allocated, L represents the number of grids divided in the longitude and latitude directions (i.e. the region to be allocated is divided into L grids in the longitude and latitude directions), g represents the grid ordinal number of the demand point u in the longitude direction from the minimum longitude side (i.e. the demand point u belongs to the gth grid in the longitude direction from the minimum longitude side), and f represents the grid ordinal number of the demand point u in the latitude direction from the minimum latitude side (i.e. the demand point u belongs to the fth grid in the latitude direction from the minimum latitude side).

[0093] It should be noted that the above-mentioned division of the region to be allocated into the same number of grids in the longitude and latitude directions is only an example, and the region to be allocated can also be divided into different numbers of grids in the longitude and latitude directions, which is not limited by the present application. Wherein the number n of demand points in the region to be allocated is the product of the number of grids divided in the longitude direction and the number of grids divided in the latitude direction, for example, when the region to be allocated is divided into L grids in the longitude and latitude directions, the number n of demand points in the region to be allocated is L*L.

[0094] The constraints of the number of electric vehicles served by the candidate station include:

[0095]

[0096] wherein D u represents the number of electric vehicles in the demand point u, Di This represents the number of electric vehicles that candidate station i can serve.

[0097] Regarding the number of electric vehicles D in demand point u. u (i.e., the number of electric vehicles distributed in the grid where demand point u is located), according to an embodiment of the present invention, can be obtained by the following formula:

[0098]

[0099] Among them, Q t α represents the total number of electric vehicles in the area to be assigned. u β represents the distribution coefficient of electric vehicles at demand point u (related to the population density of the area where demand point u is located), β represents the charging probability, and n n This indicates the number of valid demand points.

[0100] In some embodiments, the number of valid demand points n n It can be obtained using the following formula:

[0101]

[0102] Where, q u The value q can be either 0 or 1. u Setting 1 indicates that demand point u is a valid demand point, and q u Setting it to 0 indicates that demand point u is an invalid demand point.

[0103] Regarding q u Then it can be obtained using the following formula:

[0104]

[0105] Among them, Z target Z represents the region to be allocated. inner This indicates scenic spots, lakes, and other areas where there is no need for charging or battery swapping. "Other" indicates Z. target Remove Z inner The region. That is, when Loc u Located in Z target And located in Z inner At that time, q u Take 0, while when Loc u Located in Z target And not located in Z inner At that time, q u Take 1.

[0106] The constraints that the demand points are covered by the candidate sites include:

[0107]

[0108]

[0109] x iu ≤c iu (18)

[0110] wherein c iu denotes the coverage coefficient of the candidate station i covering the demand point u, R2denotes the maximum service radius of the candidate station, l iu denotes the Manhattan distance between the candidate station i and the demand point u.

[0111] It can be seen that when the Manhattan distance l iu between the candidate station i and the demand point u does not exceed the maximum service distance R2of the candidate station, c iu takes the value of 1, indicating that the demand point u can be covered by the candidate station i, otherwise c iu takes the value of 0, indicating that the demand point u cannot be covered by the candidate station i.

[0112] Regarding l iu , according to one embodiment of the present application, it can be obtained by the following formula:

[0113] l iu = a|E i -E u |+ b|N i -N u | (19)

[0114] wherein E i and N i denote the longitude and latitude of the candidate station i, E u and N u denote the longitude and latitude of the demand point u, a denotes the longitude coefficient (100km / 1°), and b denotes the latitude coefficient (111km / 1°).

[0115] The constraint of establishing the total number of charging and battery swapping stations includes:

[0116]

[0117] wherein N denotes the minimum number of charging and battery swapping stations to be established.

[0118] Regarding N, according to one embodiment of the present application, it can be obtained by the following formula:

[0119]

[0120] wherein Z s,target denotes the total area of the region to be allocated, and Z s,sever denotes the average coverage area of the candidate station, i.e., the area that can be covered by one candidate station.

[0121] Further, Zs,sever It can be obtained using the following formula:

[0122] Z s,sever =πR1 2 (twenty two)

[0123] In the formula, R1 represents the average distance between all adjacent candidate stations in the area to be assigned, that is, the average distance between all pairs of adjacent candidate stations.

[0124] At this point, the allocation model for charging and battery swapping stations has been constructed, and the basic parameters of the model have been obtained. Then, step 240, inputting the basic parameters into the model, and solving the model with the objective of minimizing the sum of the reciprocals of the comprehensive utility of each candidate charging and battery swapping station, outputting the allocation scheme of charging and battery swapping stations in the area to be allocated. The higher the comprehensive utility of any candidate station, the more important that candidate station is, and the smaller its reciprocal value. Therefore, in this embodiment, the objective function is to minimize the metric P for charging and battery swapping station allocation.

[0125] As mentioned above, x i Setting x to 1 indicates that a charging / swapping station is established at candidate station i, and x i Setting it to 0 indicates that no charging / swapping station will be established at candidate station i. Therefore, based on the output x... i This allows us to determine which candidate stations in the area to be allocated should be used to establish charging and battery swapping stations, thus enabling the allocation scheme for these stations within the area. It should be noted that charging and battery swapping stations refer to charging stations (CS) and battery swapping stations (BSS). In other words, this invention can be used for the layout of both charging stations and battery swapping stations for electric vehicles.

[0126] In addition, the present invention also provides a distribution device for a charging and battery swapping station. Figure 3 A structural block diagram of a distribution device 300 for a charging / swapping station according to an embodiment of the present invention is shown, suitable for residing in a computing device 100. For example... Figure 3 As shown, the device 300 includes a parameter acquisition module 310, a utility acquisition module 320, a model construction module 330, and a model solving module 340.

[0127] The parameter acquisition module 310 is suitable for acquiring basic parameters.

[0128] The utility acquisition module 320 is suitable for acquiring the comprehensive utility of each candidate station in the area to be assigned based on social network analysis.

[0129] Model building module 330 is suitable for constructing a charging and battery swapping station allocation model based on the comprehensive utility of each candidate station. This model includes an objective function and constraints. The objective function is...

[0130]

[0131] wherein P represents a metric index assigned by the charging station, P i represents the comprehensive utility of the candidate station i, x i takes the value of 0 or 1, x i takes the value of 1, indicating that the charging station is established at the candidate station i, x i takes the value of 0, indicating that the charging station is not established at the candidate station i, and m represents the number of candidate stations in the region to be allocated.

[0132] The model solving module 340 is adapted to input the basic parameters into the model, to establish the sum of the reciprocals of the comprehensive utilities of each candidate station of the charging station as the target, to solve the model, and to output the allocation scheme of the charging station in the region to be allocated.

[0133] The allocation device 300 of the charging station according to the present application has specific details which have been disclosed in detail in the description based on Figure 1 and Figure 2 , and will not be described here again.

[0134] In summary, the present application provides a method for allocating charging stations based on social network analysis, which can make the distribution of charging stations more balanced, thereby better meeting the charging needs of electric vehicle users, and being conducive to the development of electric vehicles in cities and the promotion of carbon-free urban transportation. Moreover, the present application helps to achieve load balancing of charging stations and optimize energy utilization.

[0135] A8. The method of A4, wherein the constraint of establishing the total number of charging stations comprises:

[0136]

[0137] wherein N represents the minimum number of charging stations to be established in the region to be allocated.

[0138] The various techniques described herein can be implemented in connection with hardware or software or, where appropriate, with a combination of both. Thus, the methods and apparatus of the present application, or certain aspects or portions thereof, can take the form of program code (i.e., instructions) embodied in tangible media, such as removable hard disks, USB flash drives, floppy diskettes, CD-ROMs, or any other machine-readable storage medium wherein, when the program code is loaded into an apparatus, such as a computer, the apparatus becomes an implementation of the present application for practicing the aspects of the present application.

[0139] When the program code is executed on a programmable computer, the computing device generally includes a processor, a processor-readable storage medium (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. The memory is configured to store program code; the processor is configured to execute the allocation method of the charging / swapping station of the present invention according to instructions in the program code stored in the memory.

[0140] By way of example, and not limitation, readable media include readable storage media and communication media. Readable storage media stores information such as computer-readable instructions, data structures, program modules, or other data. Communication media generally embodies computer-readable instructions, data structures, program modules, or other data in the form of modulated data signals such as carrier waves or other transmission mechanisms, and includes any information delivery medium. Any combination of the above is also included within the scope of readable media.

[0141] In the specification provided herein, the algorithms and displays are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used with the examples of this invention. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0142] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0143] It should be understood that, in order to simplify this disclosure and aid in understanding one or more aspects of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the above description of exemplary embodiments of the invention. However, this method of disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim.

[0144] Those skilled in the art will understand that modules, units, or components of the devices disclosed in the examples herein can be arranged in the devices described in this embodiment, or alternatively, can be located in one or more devices different from the devices in this example. The modules in the foregoing examples can be combined into a single module or, in addition, can be divided into multiple sub-modules.

[0145] Those skilled in the art will appreciate that the modules in the apparatuses in the embodiments can be adapted and placed in one or more apparatuses other than the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and further can be split into multiple sub-modules or sub-units or sub-components. Any combination of all the features disclosed in the specification (including the accompanying claims, abstract and drawings), and any method or process or steps of an embodiment so disclosed, can be made unless it is explicitly stated otherwise. Each feature disclosed in the description (including the accompanying claims, abstract and drawings) can be replaced by alternative features serving the same, equivalent or similar purpose unless expressly stated otherwise.

[0146] Furthermore, those skilled in the art will appreciate that the features of the different embodiments can be combined with each other, as the combination of features is within the scope of the present application and forms a different embodiment.

[0147] Furthermore, some of the embodiments described herein are of a machine implemented method or process, accomplished within a processor-based system (e.g., a computer system), or by other means. Hence, the described machine implemented method or process is a means for accomplishing a function of the apparatus. Also, the described elements of the apparatus embodiments are exemplary means for accomplishing the functions performed by the elements for the purpose of the application.

[0148] As used herein, unless otherwise indicated, the use of the ordinal adjectives "first", "second", "third", etc., merely to distinguish different instances of an object to which the adjective refers, and are not intended to denote a chronological or spatial order of such instances.

[0149] While the application has been described in terms of several embodiments, those skilled in the art will appreciate that other embodiments can be practiced under the claims, as the above description is intended to be illustrative only and not restrictive. The specification and drawings are, accordingly, to be regarded simply as an illustration of the broadest scope of the application. Many modifications and variations of this application can be effected without departing from its spirit, and the scope of the forward disclosure is to be intended to be illustrative only and not restrictive. The scope of the application is indicated by the appended claims, and all changes which come within the meaning and range of equivalency of the claims are intended to be embraced therein.

Claims

1. A method for allocating charging and battery swapping stations, comprising: Get basic parameters; The comprehensive utility of each candidate station in the region to be assigned is obtained based on social network analysis, including: obtaining the degree centrality, proximity centrality and interval centrality of each candidate station, normalizing the degree centrality, proximity centrality and interval centrality of each candidate station, and for each candidate station, obtaining the average value of the normalized degree centrality, proximity centrality and interval centrality of the candidate station, and using it as the comprehensive utility of the candidate station. A charging / swapping station allocation model is constructed based on the comprehensive utility of each candidate station. The model includes an objective function and constraints. The objective function is... Where P represents the metric for the allocation of charging and battery swapping stations, P i x represents the overall utility of candidate station i. i x takes the value 0 or 1. i Setting x to 1 indicates that a charging / swapping station is established at candidate station i, and x i Setting it to 0 indicates that no charging / swapping station will be established at candidate station i, and m represents the number of candidate stations in the area to be allocated. The basic parameters are input into the model, and the model is solved with the goal of minimizing the sum of the reciprocals of the comprehensive utility of each candidate charging and battery swapping station. The allocation scheme of charging and battery swapping stations in the area to be allocated is then output. The constraints include the establishment of charging and battery swapping stations by candidate stations, the number of electric vehicles served by candidate stations, the coverage of demand points by candidate stations, and the total number of charging and battery swapping stations established. The constraints for establishing charging and battery swapping stations at the candidate stations include: x i ≥x iu Where, x iu x takes the value 0 or 1. iu Setting x to 0 indicates that the demand point u is not covered by the candidate station i. iu A value of 1 indicates that demand point u is covered by candidate station i, and n represents the number of demand points in the area to be allocated. The constraints on the number of electric vehicles served by the candidate stations include: Among them, D u D represents the number of electric vehicles at demand point u. i This indicates the number of electric vehicles that candidate station i can serve; The constraint that the demand points are covered by the candidate stations includes: x iu ≤c iu Among them, c iu l represents the coverage coefficient of candidate station i covering the coverage requirement point u. iu R² represents the Manhattan distance between candidate station i and demand point u, R² represents the maximum service radius of the candidate station, and q represents the maximum service radius of the candidate station. u The value q can be either 0 or 1. u Setting q to 0 indicates that demand point u is an invalid demand point. u Setting it to 1 indicates that demand point u is a valid demand point; The constraints on the total number of charging and battery swapping stations to be established include: Where N represents the minimum number of charging and battery swapping stations to be established in the area to be allocated.

2. The method as described in claim 1, wherein, In the steps of obtaining the point degree centrality, proximity centrality, and margin centrality of each candidate station: The degree and centrality of a point are obtained using the following formula: The proximity to centrality is obtained using the following formula: The interval centrality is obtained using the following formula: Among them, C D (i) represents the degree centrality of candidate station i, a ij The value is either 1 or 0, a ij A value of 1 indicates that candidate station i and candidate station j are directly connected by a road. ij Setting C to 0 indicates that there is no direct road connection between candidate station i and candidate station j. c (i) represents the proximity centrality of candidate station i, d(i,j) represents the distance between candidate station i and candidate station j, and C B (i) represents the interval centrality of candidate station i, g jk G represents the number of shortest paths connecting candidate stations j and k. jk (i) represents the number of paths that contain candidate station i in the shortest path connecting two candidate stations j and k.

3. A distribution device for a charging / swapping station, comprising: The parameter acquisition module is suitable for acquiring basic parameters. The utility acquisition module is suitable for acquiring the comprehensive utility of each candidate station in the area to be assigned based on social network analysis. It includes: acquiring the degree centrality, proximity centrality, and interval centrality of each candidate station, normalizing the degree centrality, proximity centrality, and interval centrality of each candidate station, and for each candidate station, acquiring the average value of the normalized degree centrality, proximity centrality, and interval centrality of the candidate station, and using it as the comprehensive utility of the candidate station. The model building module is suitable for constructing a charging and battery swapping station allocation model based on the comprehensive utility of each candidate station. The model includes an objective function and constraints. The objective function is... Where P represents the metric for the allocation of charging and battery swapping stations, P i x represents the overall utility of candidate station i. i x takes the value 0 or 1. i Setting x to 1 indicates that a charging / swapping station is established at candidate station i, and x i Setting it to 0 indicates that no charging / swapping station will be established at candidate station i, and m represents the number of candidate stations in the area to be allocated. The model solving module is adapted to input the basic parameters into the model, with the goal of minimizing the sum of the inverses of the comprehensive utility of each candidate charging and battery swapping station, to solve the model and output the allocation scheme of charging and battery swapping stations in the area to be allocated. The constraints include the establishment of charging and battery swapping stations by candidate stations, the number of electric vehicles served by candidate stations, the coverage of demand points by candidate stations, and the total number of charging and battery swapping stations established. The constraints for establishing charging and battery swapping stations at the candidate stations include: x i ≥x iu Where, x iu x takes the value 0 or 1. iu Setting x to 0 indicates that the demand point u is not covered by the candidate station i. iu A value of 1 indicates that demand point u is covered by candidate station i, and n represents the number of demand points in the area to be allocated. The constraints on the number of electric vehicles served by the candidate stations include: Among them, D u D represents the number of electric vehicles at demand point u. i This indicates the number of electric vehicles that candidate station i can serve; The constraint that the demand points are covered by the candidate stations includes: x iu ≤c iu Among them, c iu l represents the coverage coefficient of candidate station i covering the coverage requirement point u. iu R² represents the Manhattan distance between candidate station i and demand point u, R² represents the maximum service radius of the candidate station, and q represents the maximum service radius of the candidate station. u The value q can be either 0 or 1. u Setting q to 0 indicates that demand point u is an invalid demand point. u Setting it to 1 indicates that demand point u is a valid demand point; The constraints on the total number of charging and battery swapping stations to be established include: Where N represents the minimum number of charging and battery swapping stations to be established in the area to be allocated.

4. A computing device, comprising: At least one processor; as well as A memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, the program instructions including instructions for performing the method as claimed in claim 1 or 2.

5. A readable storage medium storing program instructions that, when read and executed by a computing device, cause the computing device to perform the method as described in claim 1 or 2.

Images