Electric vehicle charging station planning method and device

Abstract

The present invention relates to a method and device for planning electric vehicle charging stations, comprising: determining the positions of charging stations within a planning area according to the coordinates of parking positions within the planning area; determining the number of charging connectors of the charging stations within the planning area according to the distances between the positions of the charging stations within the planning area and the parking positions within the planning area; using the positions of the charging stations within the planning area and the number of charging connectors of each charging station as a planning scheme, and using the planning scheme to plan electric vehicle charging stations in the planning area; the present invention determines the positions of the charging stations by the parking positions within the planning area, and determines the number of charging connectors by the distances between the positions of the charging stations and the parking positions, thereby obtaining a charging station planning scheme, thereby solving the problem of waste of resources and funds caused by unreasonable charging station planning.

Description

Technical Field

[0001] The present invention relates to the field of energy internet, and in particular to a method and device for planning electric vehicle charging stations. Background Art

[0002] Electric vehicles are a green, environmentally friendly, and convenient means of transportation. Their advantages lie in their energy-saving and environmentally friendly nature. The widespread promotion and use of electric vehicles in my country will help address issues such as energy shortages and environmental pollution. Electric vehicle charging stations can provide the security and momentum needed for the rapid and large-scale development of electric vehicles.

[0003] The development of electric vehicle charging stations has a significant impact on both the power grid and electric vehicle users. Existing research on charging station location selection fails to consider the distance between the parking location and the charging station, nor the number of electric vehicles parked at the location. In reality, charging station location planning can have a significant impact on electric vehicle users. Properly planned charging station locations can save users unnecessary costs. Furthermore, since charging station owners bear the costs of land and equipment, charging station planning also has a profound impact on them. Inappropriate charging station location planning can lead to a waste of resources and funds. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the purpose of the present invention is to provide a method and device for planning electric vehicle charging stations. By comprehensively considering the distance between the parking location of the electric vehicle and the charging station and the number of electric vehicles at the parking location, a charging station planning scheme is obtained, which solves the problem of waste of resources and funds caused by unreasonable charging station planning.

[0005] The purpose of the present invention is achieved by adopting the following technical solutions:

[0006] The present invention provides a method for planning electric vehicle charging stations, wherein the method comprises:

[0007] Determine the location of charging stations within the planned area based on the coordinates of parking locations within the planned area;

[0008] Determine the number of charging connectors at the charging stations within the planned area based on the distance between the charging station locations and the parking locations within the planned area;

[0009] The locations of the charging stations in the planning area and the number of charging connectors at each charging station are used as a planning scheme, and the electric vehicle charging stations are planned in the planning area using the planning scheme.

[0010] Preferably, determining the location of the charging station within the planned area according to the coordinates of the parking location within the planned area includes:

[0011] Substituting the coordinates of the parking locations within the planned area into a pre-established distance objective function, and solving the pre-established distance objective function using a genetic algorithm to obtain the locations of the charging stations within the planned area;

[0012] Among them, the parking locations in the planned area include residential building locations, parking lot locations, office building locations and commercial venue locations.

[0013] Furthermore, the pre-established distance objective function is determined as follows:

[0014]

[0015] Where L is the sum of the distances between the parking spaces in the planning area and the nearest charging station in the planning area, N is the number of parking spaces in the planning area, C is the number of charging stations in the planning area, i∈[1,N],j∈[1,C], α ij is the distance judgment result value between the parking position in the planning area and the charging station in the planning area. If the distance between the i-th parking position in the planning area and the j-th charging station in the planning area is less than the distance between the i-th parking position in the planning area and other charging stations in the planning area, then α ij =1, otherwise α ij =0,(x i ,y i ) is the coordinate of the i-th parking position in the planning area, (x j ,y j ) is the coordinate of the jth charging station in the planning area.

[0016] Furthermore, the using of a genetic algorithm to solve the pre-established distance objective function to obtain the location of the charging station within the planning area includes:

[0017] S1. Initialize the chromosome population and the number of iterations n=0, wherein the individuals of the chromosome population are composed of binary codes of C groups of position coordinates randomly selected within the planning area;

[0018] S2. Obtaining the fitness values ​​of the individuals in the chromosome population, performing selection, crossover, and mutation on the chromosome population to generate the next generation chromosome population;

[0019] S3. Let n=n+1. If the number of iterations meets the maximum number of iterations, the decoded coordinates of the individual with the largest fitness value in the next generation chromosome population are used as the location of the charging station in the planned area. Otherwise, return to S1.

[0020] Furthermore, the fitness value F of the individuals in the chromosome population is determined according to the following fitness function:

[0021] F=1 / L

[0022] Where L is the sum of the distances between the parking locations within the planning area and the nearest charging station within the planning area.

[0023] Furthermore, the mutation probability p during the mutation process is determined as follows:

[0024]

[0025] Where n∈[1,n max ],n max is the maximum number of iterations.

[0026] Preferably, determining the number of charging connectors of the charging stations in the planned area according to the distances between the charging station locations in the planned area and the parking locations in the planned area includes:

[0027] If the distance between the jth charging station and the ith parking space in the planning area is less than the distance between other charging stations in the planning area and the ith parking space in the planning area, then the ith parking space in the planning area is the service object corresponding to the jth charging station in the planning area;

[0028] Determine the number of charging connectors at the jth charging station in the planning area as follows:

[0029]

[0030] Where, N j,h is the number of electric vehicles parked at the h hour by the service objects of the j-th charging station in the planning area, is the number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, m∈[1,M], M is the total number of service objects corresponding to the charging stations in the planning area, H is the preset period, h∈[1,H].

[0031] Furthermore, the number of electric vehicle parking spaces at the hth hour for the mth service object corresponding to the jth charging station in the planning area is determined as follows:

[0032]

[0033] Where, is the initial number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, is the percentage of the number of electric vehicles parked by the mth service object corresponding to the jth charging station in the planning area at the tth hour to the initial number of electric vehicles parked by the service object at the tth hour, The percentage of the number of electric vehicles parked by the mth service object corresponding to the jth charging station in the planning area at the tth hour to the initial number of electric vehicles parked by the service object at the tth hour, t∈[1,h].

[0034] The present invention also provides an electric vehicle charging station planning device, the improvement of which is that the device comprises:

[0035] A charging station location determination unit, configured to determine the location of a charging station within the planned area based on the coordinates of a parking location within the planned area;

[0036] a charging connector determination unit, configured to determine the number of charging connectors at the charging stations within the planned area based on the distances between the charging station locations within the planned area and the parking locations within the planned area;

[0037] The planning unit is configured to use the locations of the charging stations in the planning area and the number of charging connectors at each charging station as a planning scheme, and plan the electric vehicle charging stations in the planning area using the planning scheme.

[0038] Preferably, the charging station location determination unit is specifically configured to:

[0039] Substituting the coordinates of the parking locations within the planned area into a pre-established distance objective function, and solving the pre-established distance objective function using a genetic algorithm to obtain the locations of the charging stations within the planned area;

[0040] Wherein, the parking locations within the planning area include residential building locations, parking lot locations, office building locations and commercial premises locations;

[0041] The charging connector determination unit is specifically configured to:

[0042] If the distance between the jth charging station and the ith parking space in the planning area is less than the distance between other charging stations in the planning area and the ith parking space in the planning area, then the ith parking space in the planning area is the service object corresponding to the jth charging station in the planning area;

[0043] Determine the number of charging connectors at the jth charging station in the planning area as follows:

[0044]

[0045] Where, N j,h is the number of electric vehicles parked at the h hour by the service objects of the j-th charging station in the planning area, is the number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, m∈[1,M], M is the total number of service objects corresponding to the charging stations in the planning area, H is the preset period, h∈[1,H].

[0046] Compared with the closest prior art, the present invention has the following beneficial effects:

[0047] The present invention provides a method and device for planning electric vehicle charging stations, which determine the positions of charging stations in a planning area according to the coordinates of parking positions in the planning area; determine the number of charging connectors of the charging stations in the planning area according to the distances between the positions of charging stations in the planning area and parking positions in the planning area; use the positions of charging stations in the planning area and the number of charging connectors of each charging station as a planning scheme, and use the planning scheme to plan electric vehicle charging stations in the planning area; the present invention determines the positions of charging stations by using the parking positions in the planning area, and determines the number of charging connectors by the distances between the positions of charging stations and parking positions, thereby obtaining a charging station planning scheme, thereby solving the problem of waste of resources and funds caused by unreasonable charging station planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a flow chart of the electric vehicle planning method of the present invention;

[0049] Figure 2 It is a structural schematic diagram of the electric vehicle planning device of the present invention. DETAILED DESCRIPTION

[0050] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only 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 efforts shall fall within the scope of protection of the present invention.

[0052] The present invention provides a method for planning electric vehicle charging stations. Figure 1 As shown, the method includes:

[0053] Determine the location of charging stations within the planned area based on the coordinates of parking locations within the planned area;

[0054] Determine the number of charging connectors at the charging stations within the planned area based on the distance between the charging station locations and the parking locations within the planned area;

[0055] The locations of the charging stations in the planning area and the number of charging connectors at each charging station are used as a planning scheme, and the electric vehicle charging stations are planned in the planning area using the planning scheme.

[0056] In an embodiment of the present invention, the above method of determining the location of a charging station within the planned area based on the coordinates of the parking location within the planned area includes:

[0057] Substituting the coordinates of the parking locations within the planned area into a pre-established distance objective function, and solving the pre-established distance objective function using a genetic algorithm to obtain the locations of the charging stations within the planned area;

[0058] Among them, the parking locations in the planned area include residential building locations, parking lot locations, office building locations and commercial venue locations.

[0059] The pre-established distance objective function mentioned above:

[0060]

[0061] Where L is the sum of the distances between the parking spaces in the planning area and the nearest charging station in the planning area, N is the number of parking spaces in the planning area, C is the number of charging stations in the planning area, i∈[1,N],j∈[1,C], α ij is the distance judgment result value between the parking position in the planning area and the charging station in the planning area. If the distance between the i-th parking position in the planning area and the j-th charging station in the planning area is less than the distance between the i-th parking position in the planning area and other charging stations in the planning area, then α ij =1, otherwise α ij =0,(x i ,yi) is the coordinate of the i-th parking position in the planning area, (x j ,y j ) is the coordinate of the jth charging station in the planning area.

[0062] The above-mentioned use of the genetic algorithm to solve the pre-established distance objective function to obtain the location of the charging station in the planning area includes:

[0063] S1. Initialize the chromosome population and the number of iterations n = 0, where the individuals of the chromosome population are composed of binary codes of C sets of position coordinates randomly selected from the planning area, where C is the number of charging stations in the planning area;

[0064] S2. Obtaining the fitness values ​​of the individuals in the chromosome population, performing selection, crossover, and mutation on the chromosome population to generate the next generation chromosome population;

[0065] S3. Let n=n+1. If the number of iterations meets the maximum number of iterations, the decoded coordinates of the individual with the largest fitness value in the next generation chromosome population are used as the location of the charging station in the planned area. Otherwise, return to S1.

[0066] The fitness value F of the individuals in the chromosome population is determined according to the following fitness function:

[0067] F=1 / L

[0068] Where L is the sum of the distances between the parking locations within the planning area and the nearest charging station within the planning area.

[0069] The above-mentioned crossover process includes: when the length of the individual chromosome decreases after the crossover, 0 is added to the end of the chromosome, and the number of 0s added is the amount by which the length of the individual chromosome decreases; when the length of the individual chromosome increases after the crossover, 0 is deleted at the front end of the crossover position, and the number of 0s deleted is the amount by which the length of the individual chromosome increases.

[0070] The mutation probability p in the above mutation process is:

[0071]

[0072] Where n∈[1,n max ],n max is the maximum number of iterations.

[0073] In an embodiment of the present invention, the method of determining the number of charging connectors of charging stations in the planned area based on the distance between the charging station locations and the parking locations in the planned area includes:

[0074] If the distance between the jth charging station and the ith parking space in the planning area is less than the distance between other charging stations in the planning area and the ith parking space in the planning area, then the ith parking space in the planning area is the service object corresponding to the jth charging station in the planning area;

[0075] Determine the number of charging connectors at the jth charging station in the planning area as follows:

[0076]

[0077] Where, N j,h is the number of electric vehicles parked at the h hour by the service objects of the j-th charging station in the planning area, is the number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, m∈[1,M], where M is the total number of service objects corresponding to the charging stations in the planning area, and H is the preset period, h∈[1,H]. In this embodiment of the present invention, H is set to 24 hours.

[0078] Furthermore, the number of electric vehicle parking spaces at the hth hour for the mth service object corresponding to the jth charging station in the planning area is determined as follows:

[0079]

[0080] Where, is the initial number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, is the percentage of the number of electric vehicles parked by the mth service object corresponding to the jth charging station in the planning area at the tth hour to the initial number of electric vehicles parked by the service object at the tth hour, The percentage of the number of electric vehicles parked by the mth service object corresponding to the jth charging station in the planning area at the tth hour to the initial number of electric vehicles parked by the service object at the tth hour, t∈[1,h].

[0081] Based on the same inventive concept, the present invention also provides an electric vehicle charging station planning device, such as Figure 2 As shown, the device includes:

[0082] A charging station location determination unit, configured to determine the location of a charging station within the planned area based on the coordinates of a parking location within the planned area;

[0083] a charging connector determination unit, configured to determine the number of charging connectors at the charging stations within the planned area based on the distances between the charging station locations within the planned area and the parking locations within the planned area;

[0084] The planning unit is configured to use the locations of the charging stations in the planning area and the number of charging connectors at each charging station as a planning scheme, and plan the electric vehicle charging stations in the planning area using the planning scheme.

[0085] Preferably, the charging station location determination unit is specifically configured to:

[0086] Substituting the coordinates of the parking locations within the planned area into a pre-established distance objective function, and solving the pre-established distance objective function using a genetic algorithm to obtain the locations of the charging stations within the planned area;

[0087] Wherein, the parking locations within the planning area include residential building locations, parking lot locations, office building locations and commercial premises locations;

[0088] The pre-established distance objective function mentioned above:

[0089]

[0090] Where L is the sum of the distances between the parking spaces in the planning area and the nearest charging station in the planning area, N is the number of parking spaces in the planning area, C is the number of charging stations in the planning area, i∈[1,N],j∈[1,C], α ij is the distance judgment result value between the parking position in the planning area and the charging station in the planning area. If the distance between the i-th parking position in the planning area and the j-th charging station in the planning area is less than the distance between the i-th parking position in the planning area and other charging stations in the planning area, then α ij =1, otherwise α ij =0,(x i ,y i ) is the coordinate of the i-th parking position in the planning area, (x j ,y j ) is the coordinate of the jth charging station in the planning area.

[0091] The above-mentioned use of the genetic algorithm to solve the pre-established distance objective function to obtain the location of the charging station in the planning area includes:

[0092] S1. Initialize the chromosome population and the number of iterations n=0, wherein the individuals of the chromosome population are composed of binary codes of C groups of position coordinates randomly selected within the planning area;

[0093] S2. Obtaining the fitness values ​​of the individuals in the chromosome population, performing selection, crossover, and mutation on the chromosome population to generate the next generation chromosome population;

[0094] S3. Let n=n+1. If the number of iterations meets the maximum number of iterations, the decoded coordinates of the individual with the largest fitness value in the next generation chromosome population are used as the location of the charging station in the planned area. Otherwise, return to S1.

[0095] The fitness function F of the above-mentioned individual fitness values ​​of the chromosome population is obtained:

[0096] F=1 / L

[0097] The above-mentioned crossover process includes: when the length of the individual chromosome decreases after the crossover, 0 is added to the end of the chromosome, and the number of 0s added is the amount by which the length of the individual chromosome decreases; when the length of the individual chromosome increases after the crossover, 0 is deleted at the front end of the crossover position, and the number of 0s deleted is the amount by which the length of the individual chromosome increases.

[0098] The mutation probability p in the above mutation process is:

[0099]

[0100] Where n∈[1,n max ],n max is the maximum number of iterations.

[0101] The charging connector determination unit is specifically configured to:

[0102] If the distance between the jth charging station and the ith parking space in the planning area is less than the distance between other charging stations in the planning area and the ith parking space in the planning area, then the ith parking space in the planning area is the service object corresponding to the jth charging station in the planning area;

[0103] Determine the number of charging connectors at the jth charging station in the planning area as follows:

[0104]

[0105] Where, N j,h is the number of electric vehicles parked at the h hour by the service objects of the j-th charging station in the planning area, is the number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, m∈[1,M], M is the total number of service objects corresponding to the charging stations in the planning area, H is the preset period, h∈[1,H].

[0106] Furthermore, the number of electric vehicle parking spaces at the hth hour for the mth service object corresponding to the jth charging station in the planning area is determined as follows:

[0107]

[0108] Where, is the initial number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, is the percentage of the number of electric vehicles parked by the mth service object corresponding to the jth charging station in the planning area at the tth hour to the initial number of electric vehicles parked by the service object at the tth hour, The percentage of the number of electric vehicles parked by the mth service object corresponding to the jth charging station in the planning area at the tth hour to the initial number of electric vehicles parked by the service object at the tth hour, t∈[1,h].

[0109] In summary, the present invention provides a method and device for planning electric vehicle charging stations, which determine the locations of charging stations in a planning area according to the coordinates of parking positions in the planning area; determine the number of charging connectors of the charging stations in the planning area according to the distances between the locations of charging stations in the planning area and parking positions in the planning area; use the locations of charging stations in the planning area and the number of charging connectors of each charging station as a planning scheme, and use the planning scheme to plan electric vehicle charging stations in the planning area; the present invention determines the locations of charging stations by the parking positions in the planning area, and determines the number of charging connectors by the distances between the locations of charging stations and parking positions, thereby obtaining a charging station planning scheme, thereby solving the problem of waste of resources and funds caused by unreasonable charging station planning.

[0110] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0111] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0112] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for planning an electric vehicle charging station, characterized in that: The method comprises: Determine the location of charging stations within the planned area based on the coordinates of parking locations within the planned area; Determine the number of charging connectors at the charging stations within the planned area based on the distance between the charging station locations and the parking locations within the planned area; The locations of charging stations in the planning area and the number of charging connectors at each charging station are used as a planning scheme, and the planning scheme is used to plan electric vehicle charging stations in the planning area; Determining the location of the charging station within the planned area according to the coordinates of the parking location within the planned area includes: Substituting the coordinates of the parking locations within the planned area into a pre-established distance objective function, and solving the pre-established distance objective function using a genetic algorithm to obtain the locations of the charging stations within the planned area; Wherein, the parking locations within the planning area include residential building locations, parking lot locations, office building locations and commercial premises locations; The pre-established distance objective function is determined as follows: Where L is the sum of the distances between the parking spaces in the planning area and the nearest charging station in the planning area, N is the number of parking spaces in the planning area, C is the number of charging stations in the planning area, i∈[1,N],j∈[1,C], α ij is the distance judgment result value between the parking position in the planning area and the charging station in the planning area. If the distance between the i-th parking position in the planning area and the j-th charging station in the planning area is less than the distance between the i-th parking position in the planning area and other charging stations in the planning area, then α ij =1, otherwise α ij =0,(x i ,y i ) is the coordinate of the i-th parking position in the planning area, (x j ,y j ) are the coordinates of the jth charging station in the planning area; Determining the number of charging connectors for charging stations within the planned area based on the distances between charging station locations within the planned area and parking locations within the planned area includes: If the distance between the jth charging station in the planning area and the i-th parking space in the planning area is less than the distance between other charging stations in the planning area and the i-th parking space in the planning area, then the i-th parking space in the planning area is the service object corresponding to the jth charging station in the planning area.

2. The method according to claim 1, wherein Solving the pre-established distance objective function using a genetic algorithm to obtain the locations of charging stations within the planned area includes: S1. Initialize the chromosome population and the number of iterations n = 0, where the individuals of the chromosome population are composed of binary codes of C sets of position coordinates randomly selected from the planning area, where C is the number of charging stations in the planning area; S2. Obtaining the fitness values ​​of the individuals in the chromosome population, performing selection, crossover, and mutation on the chromosome population to generate the next generation chromosome population; S3. Let n=n+1. If the number of iterations meets the maximum number of iterations, the decoded coordinates of the individual with the largest fitness value in the next generation chromosome population are used as the location of the charging station in the planned area. Otherwise, return to S1.

3. The method according to claim 2, wherein The fitness value F of the individuals in the chromosome population is determined according to the following fitness function: F=1 / L Where L is the sum of the distances between the parking locations within the planning area and the nearest charging station within the planning area.

4. The method according to claim 3, wherein The mutation probability p during the mutation process is determined as follows: Where n∈[1,n max ],n max is the maximum number of iterations.

5. The method according to claim 1, wherein Determine the number of charging connectors at the jth charging station in the planning area as follows: Where, N j,h is the number of electric vehicles parked at the h hour by the service objects of the j-th charging station in the planning area, is the number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, m∈[1,M], M is the total number of service objects corresponding to the charging stations in the planning area, H is the preset period, h∈[1,H].

6. The method according to claim 5, wherein The number of electric vehicle parking spaces at the h hour for the mth service object corresponding to the jth charging station in the planning area is determined by the following formula: Where, is the initial number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, is the percentage of the number of electric vehicles parked by the mth service object corresponding to the jth charging station in the planning area at the tth hour to the initial number of electric vehicles parked by the service object at the tth hour, The percentage of the number of electric vehicles parked by the mth service object corresponding to the jth charging station in the planning area at the tth hour to the initial number of electric vehicles parked by the service object at the tth hour, t∈[1,h].

7. An electric vehicle charging station planning device, characterized in that: The device comprises: A charging station location determination unit, configured to determine the location of a charging station within the planned area based on the coordinates of a parking location within the planned area; a charging connector determination unit, configured to determine the number of charging connectors at the charging stations within the planned area based on the distances between the charging station locations within the planned area and the parking locations within the planned area; a planning unit, configured to use the locations of charging stations in the planning area and the number of charging connectors at each charging station as a planning scheme, and to plan electric vehicle charging stations in the planning area using the planning scheme; The pre-established distance objective function is determined as follows: Where L is the sum of the distances between the parking spaces in the planning area and the nearest charging station in the planning area, N is the number of parking spaces in the planning area, C is the number of charging stations in the planning area, i∈[1,N],j∈[1,C], α ij is the distance judgment result value between the parking position in the planning area and the charging station in the planning area. If the distance between the i-th parking position in the planning area and the j-th charging station in the planning area is less than the distance between the i-th parking position in the planning area and other charging stations in the planning area, then α ij =1, otherwise α ij =0,(x i ,y i ) is the coordinate of the i-th parking position in the planning area, (x j ,y j ) are the coordinates of the jth charging station in the planning area; The charging station location determination unit is specifically configured to: Substituting the coordinates of the parking locations within the planned area into a pre-established distance objective function, and solving the pre-established distance objective function using a genetic algorithm to obtain the locations of the charging stations within the planned area; Wherein, the parking locations within the planning area include residential building locations, parking lot locations, office building locations and commercial premises locations; The charging connector determination unit is specifically configured to: If the distance between the jth charging station in the planning area and the i-th parking space in the planning area is less than the distance between other charging stations in the planning area and the i-th parking space in the planning area, then the i-th parking space in the planning area is the service object corresponding to the jth charging station in the planning area.

8. The device according to claim 7, wherein Determine the number of charging connectors at the jth charging station in the planning area as follows: Where, N j,h is the number of electric vehicles parked at the h hour by the service objects of the j-th charging station in the planning area, is the number of electric vehicles parked at the mth service object corresponding to the jth charging station in the planning area at the hth hour, m∈[1,M], M is the total number of service objects corresponding to the charging stations in the planning area, H is the preset period, h∈[1,H].

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