Method and apparatus for determining construction location of charging station

Abstract

This application relates to a method and apparatus for determining the construction location of a charging station. The method includes: acquiring first charging demand data for each candidate construction location of a charging station within a target power supply area, considering their respective charging service coverage areas; performing density clustering on all candidate construction locations to obtain at least one demand hot zone, and determining the corresponding hot zone weight based on the first charging demand data of the candidate locations within each hot zone; when the shortest path length between any two candidate construction locations is not greater than a first length threshold, acquiring the number of first charging piles and the number of users that a single pile can serve, and calculating a collaborative gain value based on the second unmet charging demand data within the intersection of their coverage areas, which characterizes the additional charging demand that can be met by the two locations; finally, determining a target location combination based on the hot zone weight and the collaborative gain value, and planning charging stations within the power supply area accordingly. This method can accurately meet the charging demand of a power supply area.

Description

Technical Field

[0001] This application relates to the field of charging station layout technology, and in particular to a method and apparatus for determining the construction location of a charging station. Background Technology

[0002] With the acceleration of urbanization and the booming development of the sharing economy, the popularity of new energy bicycles in high-density residential areas such as urban villages has increased significantly. However, due to their complex geographical environment, limited power capacity, and uneven distribution of charging demand, urban village power supply areas face challenges in the site selection and scale configuration of new energy bicycle charging stations.

[0003] In existing technologies, the location of charging stations is usually based on a simple distance coverage model or a fixed scale allocation, which cannot accurately meet the charging needs within the power supply area. Summary of the Invention

[0004] Therefore, it is necessary to provide a method and apparatus for determining the construction location of charging stations that can accurately meet the charging needs within the power supply area, in order to address the aforementioned technical problems.

[0005] Firstly, this application provides a method for determining the construction location of a charging station, the method comprising:

[0006] For any candidate construction location of a charging station in the target power supply area, obtain the first charging demand data of the charging service coverage area of ​​the candidate construction location;

[0007] Density clustering is performed on all candidate construction locations in the power supply area to obtain at least one demand hot zone; for all charging service coverage areas of all candidate construction locations in any demand hot zone, the hot zone weight of the demand hot zone is obtained based on the first charging demand data of all the charging service coverage areas.

[0008] If the length of the shortest path between any two candidate construction locations is not greater than a first length threshold, obtain the first number of charging piles to be planned at the two candidate construction locations and the number of users that can be served by any one charging pile. For the intersection between the charging service coverage of the two candidate construction locations, obtain the second charging demand data that is not satisfied by the planned charging piles in the intersection.

[0009] Based on the first number of charging piles, the number of users that can be served, and the second charging demand data, a collaborative gain value is obtained between the two candidate construction locations; wherein, the collaborative gain value is used to characterize that when there is an intersection between the charging service coverage areas of the two candidate construction locations, the two candidate construction locations meet additional charging demand;

[0010] Based on the heat zone weight and the cooperative gain value, a target location combination formed by multiple candidate construction locations is determined, and a charging station is planned in the power supply area based on the target location combination.

[0011] In one embodiment, obtaining the first charging demand data of the charging service coverage area of ​​the candidate construction location includes:

[0012] Any candidate construction location is determined as the first location, and any other candidate construction location other than the first location is determined as the second location. For the shortest path between the first location and the second location, if the length of the shortest path is not greater than a second length threshold, the second location is determined as the serviceable location of the first location.

[0013] Obtain the third charging demand data of the first location and the fourth charging demand data of any available location of the first location, and determine the sum of the third charging demand data and all the fourth charging demand data as the first charging demand data of the charging service coverage area of ​​the first location.

[0014] In one embodiment, obtaining the hot zone weight of the demand hot zone based on the first charging demand data of all the charging service coverage areas includes:

[0015] The sum of the first charging demand data of all the charging service coverage areas is determined as the fifth charging demand data of the demand hot zone, and the maximum charging demand data among the fifth charging demand data of all demand hot zones is obtained.

[0016] The first ratio between the fifth charging demand data of the demand hot zone and the maximum charging demand data is determined as the hot zone weight of the demand hot zone.

[0017] In one embodiment, determining the target location combination formed by multiple candidate construction locations based on the hot zone weight and the cooperative gain value includes:

[0018] All demand hot zones are sorted in descending order of their hot zone weights, and the first demand hot zone in the sorting results is determined as the first demand hot zone.

[0019] Based on the fifth charging demand data of the first demand hot zone, at least one candidate construction location in the first demand hot zone is determined as the initial location, and the number of second charging piles to be planned at at least one of the initial locations is obtained.

[0020] If the number of the second charging piles is less than the number threshold, for the remaining demand hot areas in the sorting result other than the first demand hot area, the first demand hot area in the remaining demand hot areas is determined as the new first demand hot area according to the sorting result, and the first difference between the number threshold and the number of the second charging piles is determined as the new number threshold.

[0021] Return the fifth charging demand data based on the first demand hot zone, determine at least one candidate construction location in the first demand hot zone as the initial location, and continue to execute until the number of second charging piles to be planned at the initial location is not less than the number threshold.

[0022] Based on all determined initial positions and the said cooperative gain value, a target position combination formed by multiple candidate construction positions is determined.

[0023] In one embodiment, determining the target location combination formed by multiple candidate construction locations based on all determined initial locations and the cooperative gain value includes:

[0024] All combinations of the initial positions are determined as the first initial position combination, and for the first initial position combination, the number of second charging piles of the planned charging piles at at least one initial position is adjusted to obtain at least one second initial position combination.

[0025] Determine at least one third initial location combination; wherein any third initial location combination is formed by at least one candidate construction location combination randomly selected from all the demand hot zones;

[0026] For any one of the first initial position combination, the second initial position combination, and the third initial position combination, if the length of the shortest path between any two candidate construction locations in the initial position combination is less than a third length threshold, and the two candidate construction locations are located in the same demand hot zone, the initial position combination is deleted.

[0027] If the collaborative gain value between any two candidate construction locations in the initial location combination is less than the gain value threshold, the initial location combination is deleted.

[0028] All remaining initial position combinations that have not been deleted are determined as the first intermediate position combination, and the target position combination is determined based on the first intermediate position combination.

[0029] In one embodiment, determining the target position combination based on the first intermediate position combination includes:

[0030] Based on any candidate construction location in any first intermediate location combination and the number of third charging piles of the planned charging piles at the candidate construction location, obtain the fitness value of the first intermediate location combination.

[0031] Sort all first intermediate position combinations in descending order of fitness value, and determine the first preset number of first intermediate position combinations in the sorting result as second intermediate position combinations.

[0032] For any two combinations of second intermediate positions, one of the combinations of second intermediate positions is determined as the first position combination, and the other combination of second intermediate positions is determined as the second position combination;

[0033] At least one first candidate construction location is selected from the first location combination, and at least one second candidate construction location is selected from the second location combination, and the location combination formed by at least one first candidate construction location and at least one second candidate construction location is determined as a third intermediate location combination;

[0034] At least one third candidate construction location is selected from the first location combination, and at least one fourth candidate construction location is selected from the second location combination. The number of charging piles to be planned at the third candidate construction location is determined as the new number of charging piles to be planned at the fourth candidate construction location, and the number of charging piles to be planned at the fourth candidate construction location is determined as the new number of charging piles to be planned at the third candidate construction location; wherein, the number of third candidate construction locations is the same as the number of fourth candidate construction locations.

[0035] The first and second position combinations after adjusting the number of charging piles are determined as the fourth intermediate position combination, and the third and fourth intermediate position combinations are determined as the fifth intermediate position combination. The target position combination is determined based on the fifth intermediate position combination.

[0036] In one embodiment, determining the target position combination based on the fifth intermediate position combination includes:

[0037] Make the first adjustment to at least one candidate construction position in any fifth intermediate position combination;

[0038] Obtain the center point location of the center point of any demand hot zone, and obtain the distance between the candidate construction location after the first adjustment and the center point location;

[0039] According to the preset adjustment probability, based on the center point position with the smallest corresponding distance and the candidate construction position after the first adjustment, the candidate construction position after the first adjustment is adjusted a second time, and the fifth intermediate position combination after the second adjustment of the candidate construction position is determined as the sixth intermediate position combination;

[0040] The number of charging piles to be planned at at least one candidate construction location in any sixth intermediate location combination is adjusted, and the sixth intermediate location combination with the adjusted number of charging piles is determined as the seventh intermediate location combination.

[0041] The target position combination is determined based on the seventh intermediate position combination.

[0042] In one embodiment, determining the target position combination based on the seventh intermediate position combination includes:

[0043] Obtain the sixth charging demand data that can be met by the planned charging piles at all candidate construction locations in any seventh intermediate location combination, and the seventh charging demand data required within the charging service coverage area of ​​all the candidate construction locations, and obtain the second ratio between the sixth charging demand data and the seventh charging demand data.

[0044] For any candidate construction location in the seventh intermediate location combination, obtain the eighth charging demand data that the planned charging piles at the candidate construction location can meet, and the ninth charging demand data required within the charging service coverage area of ​​the candidate construction location.

[0045] Obtain the second difference between the eighth charging demand data and the ninth charging demand data, and determine the first demand matching degree of the candidate construction location based on the third ratio between the second difference and the ninth charging demand data;

[0046] Based on the first demand matching degree, obtain the second demand matching degree corresponding to the seventh intermediate position combination;

[0047] The second ratio and the second demand matching degree are weighted and summed, and based on the result of the weighted summation, the corresponding target location combination of the power supply area is determined from the seventh intermediate location combination.

[0048] In one embodiment, the method further includes:

[0049] The geographic topology data of the power supply area is obtained, and an undirected graph corresponding to the power supply area is constructed based on the geographic topology data; wherein, the nodes in the undirected graph represent candidate construction locations of charging stations, and the edges in the undirected graph represent paths between different candidate construction locations;

[0050] Input the undirected graph into the Floyd shortest path model and output the length of the shortest path between any two candidate construction locations.

[0051] Secondly, this application also provides a device for determining the construction location of a charging station, the device comprising:

[0052] The first acquisition module is used to acquire the first charging demand data of the charging service coverage area of ​​any candidate construction location of a charging station in the target power supply area.

[0053] The clustering module is used to perform density clustering on all candidate construction locations in the power supply area to obtain at least one demand hot zone; for all charging service coverage areas of all candidate construction locations in any demand hot zone, the hot zone weight of the demand hot zone is obtained based on the first charging demand data of all the charging service coverage areas.

[0054] The second acquisition module is used to acquire the number of first charging piles to be planned at the two candidate construction locations and the number of users that can be served by any one charging pile, provided that the length of the shortest path between any two candidate construction locations is not greater than the first length threshold. It is also used to acquire second charging demand data that is not satisfied by the planned charging piles within the intersection of the charging service coverage areas of the two candidate construction locations.

[0055] The third acquisition module is used to acquire a collaborative gain value between two candidate construction locations based on the first number of charging piles, the number of users that can be served, and the second charging demand data; wherein, the collaborative gain value is used to characterize that when there is an intersection between the charging service coverage areas of the two candidate construction locations, the two candidate construction locations meet additional charging demand.

[0056] The determination module is used to determine a target location combination formed by multiple candidate construction locations based on the hot zone weight and the cooperative gain value, and to plan a charging station in the power supply area based on the target location combination.

[0057] The aforementioned method and apparatus for determining the construction location of charging stations involves: acquiring first charging demand data for the charging service coverage area of ​​any candidate construction location within a target power supply area; performing density clustering on all candidate construction locations within the power supply area to obtain at least one demand hotspot; acquiring the hotspot weight of the demand hotspot based on the first charging demand data for all charging service coverage areas of all candidate construction locations within any given demand hotspot; and, provided that the length of the shortest path between any two candidate construction locations is not greater than a first length threshold, acquiring the first number of charging piles to be planned at the two candidate construction locations. The system calculates the number of first charging piles, the number of users that can be served by any given charging pile, and obtains the second charging demand data that is not met by the planned charging piles within the intersection of the charging service coverage areas of two candidate construction locations. Based on the number of first charging piles, the number of users that can be served, and the second charging demand data, it obtains the collaborative gain value between the two candidate construction locations. The collaborative gain value is used to characterize the additional charging demand that the two candidate construction locations meet when there is an intersection between their charging service coverage areas. Based on the heat zone weight and the collaborative gain value, it determines the target location combination formed by multiple candidate construction locations and plans charging stations in the power supply area based on the target location combination. The method provided in this application obtains demand data of the charging service coverage area of ​​candidate construction sites and identifies demand hotspots based on density clustering. This allows for a precise grasp of the spatial distribution of charging demand, avoiding blind site selection and making the layout of charging stations more aligned with actual user needs. The method introduces a collaborative gain value to quantitatively evaluate the additional demand-satisfying capacity of two candidate construction sites due to overlapping service areas. This prioritizes site combinations that can complement each other and improve overall service efficiency, avoiding resource waste and insufficient coverage. Furthermore, the method determines the target location combination based on hotspot weights and collaborative gains, ensuring priority coverage of high-demand areas while improving overall service capabilities through site collaboration, achieving a balance between local priorities and overall efficiency. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 This is a flowchart illustrating a method for determining the construction location of a charging station in one embodiment;

[0060] Figure 2 This is a flowchart illustrating the first charging demand data acquisition step in one embodiment;

[0061] Figure 3 A structural block diagram of a charging station construction location determination device in one embodiment;

[0062] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0064] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0065] In one embodiment, such as Figure 1 As shown, a method for determining the construction location of a charging station is provided. This embodiment illustrates the application of this method to a terminal. It is understood that this method can also be applied to a server, and further to a system including both a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0066] S102. For any candidate construction location of a charging station in the target power supply area, obtain the first charging demand data of the charging service coverage area of ​​the candidate construction location.

[0067] Among them, the power supply area refers to a power supply area with a clear geographical boundary that is powered by a single distribution transformer or a single distribution circuit; the charging demand data refers to quantitative data used to characterize the amount of charging services required for a region or location.

[0068] S104. Perform density clustering on all candidate construction locations in the power supply area to obtain at least one demand hot zone; for all charging service coverage areas of all candidate construction locations in any demand hot zone, obtain the hot zone weight of the demand hot zone based on the first charging demand data of all charging service coverage areas.

[0069] Among them, the demand hot zone refers to the area where charging demand is highly concentrated and the candidate construction sites are densely distributed; the hot zone weight represents the charging demand potential of the corresponding demand hot zone.

[0070] Optionally, the purpose of density clustering is to identify high-demand hotspots based on charging demand at candidate construction locations; the DBSCAN clustering algorithm can be used to perform density clustering on all candidate construction locations in the power supply area, and the clustering radius can be, but is not limited to, [missing information]. The minimum group size can be, but is not limited to, 1. Among them, the DBSCAN clustering algorithm is an algorithm for spatial clustering based on data point density. This is a preset length threshold.

[0071] S106. If the length of the shortest path between any two candidate construction locations is not greater than the first length threshold, obtain the number of first charging piles to be planned at the two candidate construction locations and the number of users that can be served by any one charging pile. For the intersection of the charging service coverage of the two candidate construction locations, obtain the second charging demand data that is not satisfied by the planned charging piles within the intersection.

[0072] Optionally, for any two candidate construction positions i and j, if the following conditions are met... Then, obtain the number of the first charging piles and the number of users that any one charging pile can serve; where, Let be the length of the shortest path between candidate construction locations i and j.

[0073] S108. Based on the number of first charging piles, the number of users that can be served, and the second charging demand data, obtain the collaborative gain value between the two candidate construction locations; wherein, the collaborative gain value is used to characterize that when there is an intersection between the charging service coverage of the two candidate construction locations, the two candidate construction locations meet the additional charging demand.

[0074] Alternatively, the synergistic gain value can be calculated using the following formula:

[0075]

[0076] In the formula, The collaborative gain value between candidate construction positions i and j; and These represent the first number of charging piles to be planned at candidate construction locations i and j, respectively. The scale effect coefficient represents how many users a single charging station can serve. This represents the remaining unmet demand at location k, i.e., the second charging demand data within the intersection that has not been satisfied by the planned charging piles.

[0077] S110. Based on the heat zone weight and the collaborative gain value, determine the target location combination formed by multiple candidate construction locations, and plan charging stations in the power supply area based on the target location combination.

[0078] Optionally, charging stations can be planned in the power supply area based on the location coordinates of each candidate construction location in the target location combination and the number of charging piles to be planned.

[0079] In the above method for determining the construction location of charging stations, for any candidate construction location of a charging station in the target power supply area, the first charging demand data of the charging service coverage area of ​​the candidate construction location is obtained; density clustering is performed on all candidate construction locations in the power supply area to obtain at least one demand hot zone; for all charging service coverage areas of all candidate construction locations in any demand hot zone, the hot zone weight of the demand hot zone is obtained based on the first charging demand data of all charging service coverage areas; and if the length of the shortest path between any two candidate construction locations is not greater than a first length threshold, the first number of charging piles to be planned for the two candidate construction locations is obtained. The system calculates the number of users that can be served by any one charging pile, and obtains the second charging demand data that is not met by the planned charging piles within the intersection of the charging service coverage areas of two candidate construction locations. Based on the number of the first charging piles, the number of users that can be served, and the second charging demand data, it obtains the collaborative gain value between the two candidate construction locations. The collaborative gain value is used to characterize the additional charging demand that the two candidate construction locations meet when there is an intersection between their charging service coverage areas. Based on the heat zone weight and the collaborative gain value, it determines the target location combination formed by multiple candidate construction locations, and plans charging stations in the power supply area based on the target location combination. The method provided in this application obtains demand data of the charging service coverage area of ​​candidate construction sites and identifies demand hotspots based on density clustering. This allows for a precise grasp of the spatial distribution of charging demand, avoiding blind site selection and making the layout of charging stations more aligned with actual user needs. The method introduces a collaborative gain value to quantitatively evaluate the additional demand-satisfying capacity of two candidate construction sites due to overlapping service areas. This prioritizes site combinations that can complement each other and improve overall service efficiency, avoiding resource waste and insufficient coverage. Furthermore, the method determines the target location combination based on hotspot weights and collaborative gains, ensuring priority coverage of high-demand areas while improving overall service capabilities through site collaboration, achieving a balance between local priorities and overall efficiency.

[0080] In some embodiments, such as Figure 2 As shown, the first charging demand data for the charging service coverage area of ​​the candidate construction location is obtained, including:

[0081] S202. Determine any candidate construction location as the first location and any other candidate construction location besides the first location as the second location. For the shortest path between the first location and the second location, if the length of the shortest path is not greater than the second length threshold, determine the second location as the serviceable location of the first location.

[0082] S204. Obtain the third charging demand data of the first location and the fourth charging demand data of any available location of the first location, and determine the sum of the third charging demand data and all the fourth charging demand data as the first charging demand data of the charging service coverage area of ​​the first location.

[0083] Optionally, the set of service locations formed by all serviceable locations of the first location can be represented by the following formula:

[0084]

[0085] In the formula, Let i be the set of service locations, where i is the first location and j is the second location. Let be the length of the shortest path between the first and second positions. This is the second length threshold.

[0086] Optionally, the first position i and the second position j can be the same position.

[0087] Optionally, the first charging demand data can be represented by the following formula:

[0088]

[0089] In the formula, The first charging demand data for the charging service coverage area of ​​the first location i. Data on the fourth charging demand for available locations.

[0090] In this embodiment, by determining the serviceable location based on the shortest path length and summing the demand of the first location itself with the demand of surrounding serviceable locations to obtain the first charging demand data, the overall charging service demand of a single candidate construction location can be quantified more comprehensively and accurately. This provides a real and reliable data foundation for subsequent demand hotspot division and hotspot weight calculation, thereby improving the rationality of determining the construction location of charging stations.

[0091] In some embodiments, obtaining the hot zone weight of a demand hot zone based on the first charging demand data of all charging service coverage areas includes: determining the sum of the first charging demand data of all charging service coverage areas as the fifth charging demand data of the demand hot zone, and obtaining the maximum charging demand data among the fifth charging demand data of all demand hot zones; and determining the first ratio between the fifth charging demand data and the maximum charging demand data of the demand hot zone as the hot zone weight of the demand hot zone.

[0092] Optionally, the heat zone weights of the demand heat zones can be represented by the following formula:

[0093]

[0094] In the formula, For the kth demand hot zone Hot zone weight, The maximum charging demand data is the fifth charging demand data among all demand hot zones.

[0095] In this embodiment, the total demand of the hot zone (the fifth charging demand data) is obtained by summing the demand data of all candidate construction locations within the hot zone. This total demand is then compared with the maximum demand among all hot zones to objectively and quantitatively reflect the demand intensity and importance of each hot zone within the entire power supply area. The hot zone weight, as a standardized dimensionless indicator, provides a clear and comparable basis for decision-making regarding the priority of deploying charging stations and configuring the number of charging piles in high-weight hot zones, which helps to improve the rationality and pertinence of the planning scheme. Based on the hot zone weight, the site layout and scale configuration can prioritize the allocation of limited charging facility resources to the areas with the most concentrated demand, thereby improving resource utilization efficiency and avoiding resource waste or insufficient coverage.

[0096] In some embodiments, determining a target location combination formed by multiple candidate construction locations based on hot zone weights and synergistic gain values ​​includes: sorting all demand hot zones in descending order of hot zone weights, and determining the first demand hot zone in the sorting result as the first demand hot zone; based on the fifth charging demand data of the first demand hot zone, determining at least one candidate construction location in the first demand hot zone as an initial location, and obtaining the number of second charging piles to be planned at at least one initial location; if the number of second charging piles is less than a quantity threshold, for the remaining demand hot zones other than the first demand hot zone in the sorting result, determining the first demand hot zone in the remaining demand hot zones as a new first demand hot zone according to the sorting result, and determining the first difference between the quantity threshold and the number of second charging piles as a new quantity threshold; returning to the step of determining at least one candidate construction location in the first demand hot zone as an initial location based on the fifth charging demand data of the first demand hot zone, and continuing to execute until the number of second charging piles to be planned at the initial location is not less than the quantity threshold; and determining a target location combination formed by multiple candidate construction locations based on all determined initial locations and synergistic gain values.

[0097] Optionally, after sorting all demand hot zones in descending order of their hot zone weights, starting from the demand hot zone with the highest hot zone weight, candidate construction locations are selected as initial locations in each demand hot zone. After selecting an initial location in each demand hot zone, it is determined whether the number of second charging piles to be planned in all the initial locations selected so far is less than a quantity threshold. If it is less, a new candidate construction location is selected as the initial location in the next demand hot zone according to the sorting result. If it is not less, the initial location selection process is stopped.

[0098] In this embodiment, by selecting the initial position according to the heat zone weight from large to small and combining it with synergistic gain optimization, high-demand areas can be prioritized for coverage, the construction scale can be accurately controlled, and the overall service efficiency can be improved, making the planning scheme more reasonable and feasible.

[0099] In some embodiments, based on all determined initial locations and cooperative gain values, determining a target location combination formed by multiple candidate construction locations includes: determining all combinations formed by initial locations as a first initial location combination, and adjusting the number of second charging piles for at least one initial location to be planned for the first initial location combination to obtain at least one second initial location combination; determining at least one third initial location combination; wherein any third initial location combination is formed by at least one candidate construction location combination randomly selected from all demand hot zones; for any initial location combination among the first, second, and third initial location combinations, deleting the initial location combination if the length of the shortest path between any two candidate construction locations in the initial location combination is less than a third length threshold and the two candidate construction locations are located in the same demand hot zone; deleting the initial location combination if the cooperative gain value between any two candidate construction locations in the initial location combination is less than a gain value threshold; determining all remaining initial location combinations that have not been deleted as a first intermediate location combination, and determining the target location combination based on the first intermediate location combination.

[0100] Optionally, after determining the first initial location combination, the number of second charging piles to be planned at at least one initial location can be adjusted to achieve a small random perturbation of the first initial location combination, so as to generate multiple different second initial location combinations and avoid a single initial population; the location coordinates of the candidate construction locations and the number of charging piles to be planned in the third initial location combination are both random.

[0101] Optionally, to reduce invalid or inefficient solution spaces, a collaborative gain matrix is ​​used to assist pruning. Specifically, if the collaborative gain value between any two candidate construction positions i and j in the initial position combination is... If the gain value is less than the threshold, the initial location combination is discarded to avoid wasting resources and overlapping coverage between sites.

[0102] Optionally, if any two candidate construction locations i and j in the initial location combination are located in the same demand hot zone, and the length of the shortest path between candidate construction locations i and j satisfies the following distance constraint, then the initial location combination is eliminated; wherein, the distance constraint is as follows:

[0103]

[0104] In the formula, This is the distance adjustment factor. and These represent the first number of charging piles to be planned at candidate construction locations i and j, respectively.

[0105] Optionally, if any two candidate construction locations i and j in the initial location combination are located in the same demand hot zone, and the fifth charging demand data of that demand hot zone is greater than a threshold... If the shortest path length between candidate construction locations i and j satisfies the following distance constraint, then the initial location combination is eliminated; where, The scale effect coefficient represents how many users a charging station can serve, and the distance constraint is shown in the following formula:

[0106]

[0107] In this embodiment, by generating, adjusting and filtering multiple initial location combinations, and combining the shortest path, hot zone, and cooperative gain threshold triple constraints for filtering, unreasonable and inefficient site combinations can be eliminated, ensuring the quality of the initial population for subsequent optimization and improving the rationality and reliability of the planning results.

[0108] In some embodiments, determining the target location combination based on the first intermediate location combination includes: obtaining a fitness value for the first intermediate location combination based on any candidate construction location in any first intermediate location combination and the number of third charging piles of the planned charging piles at the candidate construction locations; sorting all first intermediate location combinations in descending order of fitness value, and determining the top preset number of first intermediate location combinations in the sorting result as second intermediate location combinations; for any two second intermediate location combinations, determining one of the second intermediate location combinations as the first location combination, and determining the remaining second intermediate location combination as the second location combination; selecting at least one first candidate construction location from the first location combination and at least one second candidate construction location from the second location combination, and combining the at least one first candidate construction location with at least one second candidate construction location. The location combination formed by the second candidate construction locations is determined as the third intermediate location combination; at least one third candidate construction location is selected from the first location combination, and at least one fourth candidate construction location is selected from the second location combination. The number of charging piles to be planned at the third candidate construction location is determined as the new number of charging piles to be planned at the fourth candidate construction location, and the number of charging piles to be planned at the fourth candidate construction location is determined as the new number of charging piles to be planned at the third candidate construction location. The number of third candidate construction locations is the same as the number of fourth candidate construction locations. The first location combination and the second location combination after adjusting the number of charging piles are determined as the fourth intermediate location combination, and the third intermediate location combination and the fourth intermediate location combination are determined as the fifth intermediate location combination. The target location combination is determined based on the fifth intermediate location combination.

[0109] Among them, the fitness value is a quantitative index obtained based on the comprehensive fitness function. It is used to characterize the quality of the location combination of candidate construction sites. The larger the fitness value, the wider the coverage of the corresponding location combination, the more reasonable the resource allocation, and the better the overall planning effect.

[0110] Alternatively, if a genetic algorithm is used to optimize the combination of the second middle positions, a two-point crossover method can be used to process the combination of the second middle positions into a third middle position combination, or an ordered crossover method can be used to process the combination of the second middle positions into a fourth middle position combination.

[0111] In this embodiment, by selecting the best solution based on fitness value and optimizing the combination of best locations by cross-referencing and exchanging the number of charging piles, better planning combinations can be continuously generated through iteration, thereby improving the overall planning effect and ensuring the rationality, efficiency and optimality of the final target location combination.

[0112] In some embodiments, determining the target location combination based on the fifth intermediate location combination includes: making a first adjustment to at least one candidate construction location in any fifth intermediate location combination; obtaining the center point location of the center point of any demand hot zone, and obtaining the distance between the candidate construction location after the first adjustment and the center point location; making a second adjustment to the candidate construction location after the first adjustment based on the center point location with the smallest corresponding distance and the candidate construction location after the first adjustment according to a preset adjustment probability, and determining the fifth intermediate location combination after the second adjustment of the candidate construction location as the sixth intermediate location combination; adjusting the number of charging piles of the planned charging piles at at least one candidate construction location in any sixth intermediate location combination, and determining the sixth intermediate location combination after adjusting the number of charging piles as the seventh intermediate location combination; and determining the target location combination based on the seventh intermediate location combination.

[0113] Optionally, in the process of optimizing the combination of positions using a genetic algorithm, the first adjustment of at least one candidate construction position is equivalent to genetic mutation of the candidate construction position; after the first adjustment, a hot zone gravity mechanism can be introduced to activate the probability (preset adjustment probability). This mechanism determines whether to redirect candidate construction locations, adjusted in the first round, to their nearest hotspot center to enhance coverage in high-demand areas. This helps strengthen the coverage density of individuals within the population in high-demand areas, improving service quality while avoiding ineffective location drift caused by mutations. It can be, but is not limited to, 0.3. Specifically, the distance between the candidate construction location after the first adjustment and the center point of any demand hot zone is calculated. After a preset adjustment probability indicates that the candidate construction location after the first adjustment needs to be adjusted a second time, based on the center point with the smallest corresponding distance to the candidate construction location after the first adjustment, and the candidate construction location after the first adjustment, the new location of the candidate construction location after the second adjustment is determined, and the candidate construction location after the first adjustment is adjusted to this new location. If the new location after the second adjustment is close to the center point with the smallest corresponding distance, the number of charging piles of the planned charging station at the candidate construction location after the first adjustment will also be fine-tuned according to the hot zone weight of the demand hot zone where the center point with the smallest corresponding distance is located. The new location after the second adjustment is shown in the following formula:

[0114]

[0115] In the formula, This is the new position after the second adjustment. These are the candidate construction locations after the first adjustment. In order to align with the first adjusted candidate construction locations The location of the center point of the demand hot zone with the smallest corresponding distance between them. The range of values ​​is The coefficient.

[0116] Optionally, when adjusting the number of charging piles to be planned at candidate construction locations in the sixth intermediate location combination, the adjusted number of charging piles to be planned... The quantity must not exceed the threshold. This ensures a smooth transition in scale and avoids excessive fluctuations.

[0117] Optionally, genetic operations such as selection, crossover, and mutation can be performed iteratively to continuously update the population and optimize site selection and scale configuration.

[0118] In this embodiment, by adjusting the candidate construction locations twice and optimizing the number of charging piles, the sites can be made closer to the center of the demand hotspot, further improving the coverage of charging services and resource utilization, making the final planning scheme more in line with actual charging needs and more practical.

[0119] In some embodiments, determining a target location combination based on a seventh intermediate location combination includes: obtaining sixth charging demand data that can be met by planned charging piles at all candidate construction locations in any seventh intermediate location combination, and seventh charging demand data required within the charging service coverage area of ​​all candidate construction locations, and obtaining a second ratio between the sixth charging demand data and the seventh charging demand data; for any candidate construction location in the seventh intermediate location combination, obtaining eighth charging demand data that can be met by planned charging piles at the candidate construction location, and ninth charging demand data required within the charging service coverage area of ​​the candidate construction location; obtaining a second difference between the eighth charging demand data and the ninth charging demand data, and determining a first demand matching degree for the candidate construction location based on a third ratio between the second difference and the ninth charging demand data; obtaining a second demand matching degree for the corresponding seventh intermediate location combination based on the first demand matching degree; performing a weighted summation of the second ratio and the second demand matching degree, and determining a target location combination for the power supply area from the seventh intermediate location combination based on the weighted summation result.

[0120] Optionally, but not limited to, the absolute value of the third ratio can be determined as the first demand matching degree of the candidate construction location; the corresponding second demand matching degree of the seventh intermediate location combination can be calculated as follows:

[0121]

[0122] Optionally, For the second requirement matching degree, Let N be the first requirement matching degree, and N be the number of candidate construction locations in the seventh middle position combination.

[0123] Optionally, the process of weighted summation of the second ratio and the second demand matching degree is shown in the following formula:

[0124]

[0125] In the formula, and All are weighting parameters, with CD being the second ratio.

[0126] Optionally, the seventh middle position combination with the largest result of the corresponding weighted summation is determined as the target position combination.

[0127] Optionally, it is possible to Optimize the solution across multiple scenarios within the range of demand disturbances to improve its robustness; design a flexible range for scale. This enhances the flexibility of the solution; it accelerates fitness calculation by adopting parallel computing architectures (such as OpenMP); among which, OpenMP is an API for shared memory parallel programming, which can realize code parallelization to improve computational efficiency.

[0128] In this embodiment, by quantifying the overall demand matching (second ratio) and the demand matching of individual candidate locations (first demand matching degree), and combining the weighted summation to comprehensively evaluate the seventh intermediate location combination, it can not only ensure the balance between the overall charging demand of the power supply area and the supply of charging piles, but also take into account the supply and demand adaptability of individual sites, eliminate schemes with supply and demand imbalance, improve the rationality and accuracy of the target location combination, and ensure that the planning scheme fits the actual charging demand.

[0129] In some embodiments, the method further includes: acquiring geographic topology data of the power supply area, and constructing an undirected graph corresponding to the power supply area based on the geographic topology data; wherein, nodes in the undirected graph represent candidate construction locations of charging stations, and edges in the undirected graph represent paths between different candidate construction locations; inputting the undirected graph into a Floyd shortest path model, and outputting the length of the shortest path between any two candidate construction locations.

[0130] The Floyd shortest path model is a dynamic programming algorithm model used to find the shortest path between any two nodes in a graph. It can obtain the shortest path between all pairs of nodes in the graph by iteratively updating the path length between nodes.

[0131] In this embodiment, by constructing an undirected graph and adopting the Floyd shortest path model, the shortest path length between any two candidate construction locations within the power supply area can be calculated accurately and efficiently. This provides an accurate and reliable path basis for subsequent distance judgment between stations, cooperative gain calculation, and location combination optimization, thereby improving the rationality and accuracy of determining the construction location of charging stations.

[0132] In one exemplary embodiment, another method for determining the construction location of a charging station is provided, including the following:

[0133] (1) The locations of potential sites within urban village areas are abstracted as nodes in the graph, and the spatial relationships and distance matrices between nodes are obtained. The Floyd algorithm is used to calculate the shortest path between any two points in the entire graph, realizing global service reachability modeling. It supports a scale of over 500 nodes and is suitable for practical application scenarios in high-density areas.

[0134] (2) Based on historical charging behavior, building distribution, and demand point density, service set and node demand potential indicators are defined. Using the density-based clustering algorithm (DBSCAN), hotspot areas are automatically extracted based on the service influence radius, significantly improving the spatial resolution of demand identification. Hotspot weights are constructed through weighted statistics to provide a quantitative priority basis for subsequent site selection.

[0135] (3) For station pairs in the same hot zone or adjacent areas, analyze the intersection of their service ranges, evaluate the collaborative gain of the remaining unmet needs in the intersection area, and construct a service collaboration network between the node pairs. Use sparse matrices to efficiently store the gain values, improve computational performance, and avoid redundant calculations.

[0136] (4) A chromosome encoding method including "site location + construction scale" is adopted, and novel genetic operators such as heat zone-aware hierarchical initialization strategy, scale-aware dynamic pruning mechanism, pruning operator based on cooperative gain, heat zone gravity mutation mechanism and scale stability crossover operator are introduced for the first time in the charging facility planning problem. This design takes into account both the spatial rationality of the solution and the convergence efficiency, and has good engineering practicality.

[0137] (5) Construct a multi-dimensional fitness function for service coverage and scale-demand matching, and systematically evaluate the service effectiveness and resource utilization efficiency of the solution. The fitness function fully considers the rationality of the total coverage demand and scale configuration to avoid resource waste and demand mismatch.

[0138] (6) Considering the daily fluctuations and behavioral uncertainties of the charging load of new energy vehicles, this invention introduces a multi-scenario simulation mechanism within a ±5% disturbance range and allows the scale configuration value of each site to be adjusted within a preset elastic range to improve the adaptability of the scheme to future changes in operating conditions.

[0139] (7) To address the problem of high computational complexity of fitness function, an OpenMP parallel evaluation structure is constructed to support efficient processing of parallel scoring and evolution of multiple individuals under large-scale node sets, significantly improving the scalability of the algorithm in engineering-level deployment environments.

[0140] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0141] Based on the same inventive concept, this application also provides a charging station construction location determination device for implementing the charging station construction location determination method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more charging station construction location determination device embodiments provided below can be found in the limitations of the charging station construction location determination method described above, and will not be repeated here.

[0142] In one exemplary embodiment, such as Figure 3 As shown, a charging station construction location determination device 300 is provided, comprising: a first acquisition module 301, a clustering module 302, a second acquisition module 303, a third acquisition module 304, and a determination module 305, wherein:

[0143] The first acquisition module 301 is used to acquire the first charging demand data of the charging service coverage area of ​​any candidate construction location of a charging station in the target power supply area.

[0144] Clustering module 302 is used to perform density clustering on all candidate construction locations in the power supply area to obtain at least one demand hot zone; for all charging service coverage areas of all candidate construction locations in any demand hot zone, the hot zone weight of the demand hot zone is obtained based on the first charging demand data of all the charging service coverage areas.

[0145] The second acquisition module 303 is used to acquire the number of first charging piles to be planned at the two candidate construction locations and the number of users that can be served by any one charging pile, provided that the length of the shortest path between any two candidate construction locations is not greater than a first length threshold. It is also used to acquire second charging demand data that is not satisfied by the planned charging piles within the intersection of the charging service coverage areas of the two candidate construction locations.

[0146] The third acquisition module 304 is used to acquire a collaborative gain value between two candidate construction locations based on the first number of charging piles, the number of users that can be served, and the second charging demand data; wherein, the collaborative gain value is used to characterize that when there is an intersection between the charging service coverage areas of the two candidate construction locations, the two candidate construction locations meet additional charging demand.

[0147] The determination module 305 is used to determine a target location combination formed by multiple candidate construction locations based on the hot zone weight and the cooperative gain value, and to plan a charging station in the power supply area based on the target location combination.

[0148] In some embodiments, the first acquisition module 301 is further configured to determine any candidate construction location as a first location and any other candidate construction location besides the first location as a second location, and, for the shortest path between the first location and the second location, determine the second location as a serviceable location of the first location if the length of the shortest path is not greater than a second length threshold; acquire third charging demand data of the first location and fourth charging demand data of any serviceable location of the first location, and determine the sum of the third charging demand data and all fourth charging demand data as the first charging demand data of the charging service coverage area of ​​the first location.

[0149] In some embodiments, the clustering module 302 is further configured to determine the sum of the first charging demand data of all the charging service coverage areas as the fifth charging demand data of the demand hot zone, and obtain the maximum charging demand data among the fifth charging demand data of all demand hot zones; and determine the first ratio between the fifth charging demand data of the demand hot zone and the maximum charging demand data as the hot zone weight of the demand hot zone.

[0150] In some embodiments, the determining module 305 is further configured to: sort all demand hot zones in descending order of hot zone weight, and determine the first demand hot zone in the sorting result as the first demand hot zone; based on the fifth charging demand data of the first demand hot zone, determine at least one candidate construction location in the first demand hot zone as the initial location, and obtain the number of second charging piles to be planned at at least one of the initial locations; if the number of second charging piles is less than a quantity threshold, for the remaining demand hot zones in the sorting result other than the first demand hot zone, determine the first demand hot zone in the remaining demand hot zones as the new first demand hot zone according to the sorting result, and determine the first difference between the quantity threshold and the number of second charging piles as the new quantity threshold; return to the step of determining at least one candidate construction location in the first demand hot zone as the initial location based on the fifth charging demand data of the first demand hot zone, and continue to execute until the number of second charging piles to be planned at the initial location is not less than the quantity threshold; and determine a target location combination formed by multiple candidate construction locations based on all determined initial locations and the cooperative gain value.

[0151] In some embodiments, the determining module 305 is further configured to: determine all combinations of the initial locations as a first initial location combination; adjust the number of second charging piles for at least one initial location for the first initial location combination to obtain at least one second initial location combination; determine at least one third initial location combination; wherein any third initial location combination is formed by at least one candidate construction location combination randomly selected from all the demand hot zones; for any initial location combination among the first, second, and third initial location combinations, if the length of the shortest path between any two candidate construction locations in the initial location combination is less than a third length threshold and the two candidate construction locations are located in the same demand hot zone, delete the initial location combination; if the cooperative gain value between any two candidate construction locations in the initial location combination is less than a gain value threshold, delete the initial location combination; determine all remaining initial location combinations that have not been deleted as a first intermediate location combination, and determine the target location combination based on the first intermediate location combination.

[0152] In some embodiments, the determining module 305 is further configured to: obtain a fitness value for the first intermediate location combination based on any candidate construction location in any first intermediate location combination and the number of third charging piles of the planned charging piles at the candidate construction location; sort all first intermediate location combinations in descending order of the fitness values, and determine the first preset number of first intermediate location combinations in the sorting result as second intermediate location combinations; for any two second intermediate location combinations, determine one of the second intermediate location combinations as a first location combination, and determine the remaining second intermediate location combination as a second location combination; select at least one first candidate construction location from the first location combination and at least one second candidate construction location from the second location combination, and combine the at least one first candidate construction location and at least one second candidate construction location into a single location combination. The first location combination is determined as the third intermediate location combination; at least one third candidate construction location is selected from the first location combination, and at least one fourth candidate construction location is selected from the second location combination. The number of charging piles to be planned at the third candidate construction location is determined as the new number of charging piles to be planned at the fourth candidate construction location, and the number of charging piles to be planned at the fourth candidate construction location is determined as the new number of charging piles to be planned at the third candidate construction location. The number of third candidate construction locations is the same as the number of fourth candidate construction locations. The first location combination and the second location combination after adjusting the number of charging piles are determined as the fourth intermediate location combination. The third intermediate location combination and the fourth intermediate location combination are determined as the fifth intermediate location combination. The target location combination is determined based on the fifth intermediate location combination.

[0153] In some embodiments, the determining module 305 is further configured to: perform a first adjustment on at least one candidate construction location in any fifth intermediate location combination; obtain the center point location of the center point of any demand hot zone, and obtain the distance between the first adjusted candidate construction location and the center point location; perform a second adjustment on the first adjusted candidate construction location based on the center point location with the smallest corresponding distance and the first adjusted candidate construction location according to a preset adjustment probability, and determine the fifth intermediate location combination after the second adjustment of the candidate construction location as the sixth intermediate location combination; adjust the number of charging piles to be planned at at least one candidate construction location in any sixth intermediate location combination, and determine the sixth intermediate location combination after the number of charging piles is adjusted as the seventh intermediate location combination; and determine the target location combination based on the seventh intermediate location combination.

[0154] In some embodiments, the determining module 305 is further configured to: acquire sixth charging demand data that can be met by planned charging piles at all candidate construction locations in any seventh intermediate location combination, and seventh charging demand data required within the charging service coverage area of ​​all candidate construction locations; acquire a second ratio between the sixth charging demand data and the seventh charging demand data; for any candidate construction location in the seventh intermediate location combination, acquire eighth charging demand data that can be met by planned charging piles at the candidate construction location, and ninth charging demand data required within the charging service coverage area of ​​the candidate construction location; acquire a second difference between the eighth charging demand data and the ninth charging demand data, and determine a first demand matching degree for the candidate construction location based on a third ratio between the second difference and the ninth charging demand data; acquire a second demand matching degree corresponding to the seventh intermediate location combination based on the first demand matching degree; perform a weighted summation of the second ratio and the second demand matching degree, and determine the corresponding target location combination of the power supply area from the seventh intermediate location combination based on the weighted summation result.

[0155] In some embodiments, the charging station construction location determination device 300 is specifically used to acquire the geographical topology data of the power supply area, and construct a corresponding undirected graph of the power supply area based on the geographical topology data; wherein, the nodes in the undirected graph represent candidate construction locations of the charging station, and the edges in the undirected graph represent paths between different candidate construction locations; the undirected graph is input into the Floyd shortest path model, and the length of the shortest path between any two candidate construction locations is output.

[0156] The various modules in the aforementioned charging station location determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0157] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for determining the construction location of a charging station.

[0158] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0159] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0160] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0161] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0162] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining the construction location of a charging station, characterized in that, The method includes: For any candidate construction location of a charging station in the target power supply area, obtain the first charging demand data of the charging service coverage area of ​​the candidate construction location; Density clustering is performed on all candidate construction locations in the power supply area to obtain at least one demand hot zone; for all charging service coverage areas of all candidate construction locations in any demand hot zone, the hot zone weight of the demand hot zone is obtained based on the first charging demand data of all the charging service coverage areas. If the length of the shortest path between any two candidate construction locations is not greater than a first length threshold, obtain the first number of charging piles to be planned at the two candidate construction locations and the number of users that can be served by any one charging pile. Then, for the intersection between the charging service coverage areas of the two candidate construction locations, obtain the second charging demand data that is not satisfied by the planned charging piles in the intersection. Based on the first number of charging piles, the number of users that can be served, and the second charging demand data, a collaborative gain value is obtained between the two candidate construction locations; wherein, the collaborative gain value is used to characterize that when there is an intersection between the charging service coverage areas of the two candidate construction locations, the two candidate construction locations meet additional charging demand; Based on the heat zone weight and the cooperative gain value, a target location combination formed by multiple candidate construction locations is determined, and the construction location of the charging station is determined in the power supply area based on the target location combination.

2. The method according to claim 1, characterized in that, The step of obtaining the first charging demand data for the charging service coverage area of ​​the candidate construction location includes: Any candidate construction location is determined as the first location, and any other candidate construction location other than the first location is determined as the second location. For the shortest path between the first location and the second location, if the length of the shortest path is not greater than a second length threshold, the second location is determined as the serviceable location of the first location. Obtain the third charging demand data of the first location and the fourth charging demand data of any available location of the first location, and determine the sum of the third charging demand data and all the fourth charging demand data as the first charging demand data of the charging service coverage area of ​​the first location.

3. The method according to claim 1, characterized in that, The step of obtaining the hot zone weight of the demand hot zone based on the first charging demand data of all the charging service coverage areas includes: The sum of the first charging demand data of all the charging service coverage areas is determined as the fifth charging demand data of the demand hot zone, and the maximum charging demand data among the fifth charging demand data of all demand hot zones is obtained. The first ratio between the fifth charging demand data of the demand hot zone and the maximum charging demand data is determined as the hot zone weight of the demand hot zone.

4. The method according to claim 3, characterized in that, The determination of a target location combination formed by multiple candidate construction locations based on the hot zone weight and the collaborative gain value includes: All demand hot zones are sorted in descending order of their hot zone weights, and the first demand hot zone in the sorting results is determined as the first demand hot zone. Based on the fifth charging demand data of the first demand hot zone, at least one candidate construction location in the first demand hot zone is determined as the initial location, and the number of second charging piles to be planned at at least one of the initial locations is obtained. If the number of the second charging piles is less than the number threshold, for the remaining demand hot areas in the sorting result other than the first demand hot area, the first demand hot area in the remaining demand hot areas is determined as the new first demand hot area according to the sorting result, and the first difference between the number threshold and the number of the second charging piles is determined as the new number threshold. Return the fifth charging demand data based on the first demand hot zone, determine at least one candidate construction location in the first demand hot zone as the initial location, and continue to execute until the number of second charging piles to be planned at the initial location is not less than the number threshold. Based on all determined initial positions and the said cooperative gain value, a target position combination formed by multiple candidate construction positions is determined.

5. The method according to claim 4, characterized in that, The determination of a target location combination formed by multiple candidate construction locations based on all determined initial locations and the cooperative gain value includes: All combinations of the initial positions are determined as the first initial position combination, and for the first initial position combination, the number of second charging piles of the planned charging piles at at least one initial position is adjusted to obtain at least one second initial position combination. Determine at least one third initial location combination; wherein any third initial location combination is formed by at least one candidate construction location combination randomly selected from all the demand hot zones; For any one of the first initial position combination, the second initial position combination, and the third initial position combination, if the length of the shortest path between any two candidate construction locations in the initial position combination is less than a third length threshold, and the two candidate construction locations are located in the same demand hot zone, the initial position combination is deleted. If the collaborative gain value between any two candidate construction locations in the initial location combination is less than the gain value threshold, the initial location combination is deleted. All remaining initial position combinations that have not been deleted are determined as the first intermediate position combination, and the target position combination is determined based on the first intermediate position combination.

6. The method according to claim 5, characterized in that, Determining the target position combination based on the first intermediate position combination includes: Based on any candidate construction location in any first intermediate location combination and the number of third charging piles of the planned charging piles at the candidate construction location, obtain the fitness value of the first intermediate location combination. Sort all first intermediate position combinations according to the fitness values ​​from largest to smallest, and determine the first preset number of first intermediate position combinations in the sorting results as second intermediate position combinations; For any two combinations of second intermediate positions, one of the combinations of second intermediate positions is determined as the first position combination, and the other combination of second intermediate positions is determined as the second position combination; At least one first candidate construction location is selected from the first location combination, and at least one second candidate construction location is selected from the second location combination, and the location combination formed by at least one first candidate construction location and at least one second candidate construction location is determined as a third intermediate location combination; At least one third candidate construction location is selected from the first location combination, and at least one fourth candidate construction location is selected from the second location combination. The number of charging piles to be planned at the third candidate construction location is determined as the new number of charging piles to be planned at the fourth candidate construction location, and the number of charging piles to be planned at the fourth candidate construction location is determined as the new number of charging piles to be planned at the third candidate construction location; wherein, the number of third candidate construction locations is the same as the number of fourth candidate construction locations. The first and second position combinations after adjusting the number of charging piles are determined as the fourth intermediate position combination, and the third and fourth intermediate position combinations are determined as the fifth intermediate position combination. The target position combination is determined based on the fifth intermediate position combination.

7. The method according to claim 6, characterized in that, Determining the target position combination based on the fifth intermediate position combination includes: Make the first adjustment to at least one candidate construction position in any fifth intermediate position combination; Obtain the center point location of the center point of any demand hot zone, and obtain the distance between the candidate construction location after the first adjustment and the center point location; According to the preset adjustment probability, based on the center point position with the smallest corresponding distance and the candidate construction position after the first adjustment, the candidate construction position after the first adjustment is adjusted a second time, and the fifth intermediate position combination after the second adjustment of the candidate construction position is determined as the sixth intermediate position combination; The number of charging piles to be planned at at least one candidate construction location in any sixth intermediate location combination is adjusted, and the sixth intermediate location combination with the adjusted number of charging piles is determined as the seventh intermediate location combination. The target position combination is determined based on the seventh intermediate position combination.

8. The method according to claim 7, characterized in that, Determining the target position combination based on the seventh intermediate position combination includes: Obtain the sixth charging demand data that can be met by the planned charging piles at all candidate construction locations in any seventh intermediate location combination, and the seventh charging demand data required within the charging service coverage area of ​​all the candidate construction locations, and obtain the second ratio between the sixth charging demand data and the seventh charging demand data. For any candidate construction location in the seventh intermediate location combination, obtain the eighth charging demand data that the planned charging piles at the candidate construction location can meet, and the ninth charging demand data required within the charging service coverage area of ​​the candidate construction location. Obtain the second difference between the eighth charging demand data and the ninth charging demand data, and determine the first demand matching degree of the candidate construction location based on the third ratio between the second difference and the ninth charging demand data; Based on the first demand matching degree, obtain the second demand matching degree corresponding to the seventh intermediate position combination; The second ratio and the second demand matching degree are weighted and summed, and based on the result of the weighted summation, the corresponding target location combination of the power supply area is determined from the seventh intermediate location combination.

9. The method according to claim 1, characterized in that, The method further includes: The geographic topology data of the power supply area is obtained, and an undirected graph corresponding to the power supply area is constructed based on the geographic topology data; wherein, the nodes in the undirected graph represent candidate construction locations of charging stations, and the edges in the undirected graph represent paths between different candidate construction locations; Input the undirected graph into the Floyd shortest path model and output the length of the shortest path between any two candidate construction locations.

10. A device for determining the construction location of a charging station, characterized in that, The device includes: The first acquisition module is used to acquire the first charging demand data of the charging service coverage area of ​​any candidate construction location of a charging station in the target power supply area. The clustering module is used to perform density clustering on all candidate construction locations in the power supply area to obtain at least one demand hot zone; for all charging service coverage areas of all candidate construction locations in any demand hot zone, the hot zone weight of the demand hot zone is obtained based on the first charging demand data of all the charging service coverage areas. The second acquisition module is used to acquire the number of first charging piles to be planned at the two candidate construction locations and the number of users that can be served by any one charging pile, provided that the length of the shortest path between any two candidate construction locations is not greater than a first length threshold. It is also used to acquire second charging demand data that is not satisfied by the planned charging piles within the intersection of the charging service coverage of the two candidate construction locations. The third acquisition module is used to acquire a collaborative gain value between two candidate construction locations based on the first number of charging piles, the number of users that can be served, and the second charging demand data; wherein, the collaborative gain value is used to characterize that when there is an intersection between the charging service coverage areas of the two candidate construction locations, the two candidate construction locations meet additional charging demand. The determination module is used to determine a target location combination formed by multiple candidate construction locations based on the hot zone weight and the cooperative gain value, and to plan a charging station in the power supply area based on the target location combination.

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