Charging station site selection method, device, computer equipment and readable storage medium

Abstract

The charging station site selection method, device, computer equipment and readable storage medium provided by the present invention include: dividing the target study area into multiple grids, and selecting multiple points of interest outside the coverage of the built charging stations and / or recommended charging station sites in all grids according to the preset site selection strategy; then selecting some points of interest from the multiple points of interest as target points of interest to perform position disturbance operations and determine new points of interest corresponding to the target points of interest; when the evaluation function values ​​corresponding to all points of interest after the position disturbance operation are greater than the evaluation function values ​​corresponding to all points of interest before the position disturbance operation, all points of interest after the position disturbance operation are used as charging station site selection locations. The present invention can avoid the problem of uneven distribution caused by the overly dense locations of charging stations. At the same time, the present invention can also ensure that the site selection results are still energy-efficient under various complex constraints, thereby improving the rationality of the location of the charging station site.

Description

Technical Field

[0001] The present invention relates to the technical field of charging station planning, and in particular to a charging station site selection method, device, computer equipment and readable storage medium. Background Art

[0002] As the world's attention to environmental protection and sustainable development continues to deepen, the popularity of electric vehicles has increased rapidly, and their number has shown exponential growth in recent years. This trend has put forward huge demands on charging infrastructure. The construction of charging stations must not only consider current needs, but also effectively predict and plan future needs.

[0003] In the existing technology, the site selection of charging stations often only considers a single factor, ignoring the interaction and influence between multiple sites. This method may not only lead to irrational site selection decisions, but also fail to guarantee the efficient performance of site selection solutions when faced with diverse and complex constraints.

[0004] Therefore, how to provide a charging station site selection method that can comprehensively consider multiple factors and optimize the interaction between sites, so as to significantly improve the efficiency and rationality of site selection, is a technical problem that needs to be solved. Summary of the invention

[0005] In view of this, one of the purposes of the present invention is to provide a charging station site selection method, device, computer equipment and readable storage medium, which not only considers the location of a single site in the site selection process, but also evaluates the interaction between multiple sites, optimizes the site selection results through dynamic position adjustment and energy efficiency evaluation, ensures that the site selection results are still highly efficient under various complex constraints, and improves the rationality of the charging station site selection. The technical solution provided by the present invention can be implemented as follows:

[0006] In a first aspect, the present invention provides a charging station site selection method, the method comprising: dividing a target study area into multiple grids; wherein, there are built charging stations and / or recommended charging station sites in the target study area; in all the grids, selecting multiple points of interest according to a preset site selection strategy; wherein each of the points of interest is outside the coverage of the built charging stations and / or the recommended charging station sites; among the multiple points of interest, selecting some points of interest as target points of interest for position disturbance operation, and determining new points of interest corresponding to the target points of interest; wherein the position disturbance operation is to replace the grid where the target point of interest is located or to replace the target point of interest with another point of interest in the same site selection priority as the target point of interest; when the evaluation function values ​​corresponding to all points of interest after the position disturbance operation are greater than the evaluation function values ​​corresponding to all points of interest before the position disturbance operation, all the points of interest after the position disturbance operation are used as charging station site selection locations.

[0007] In a second aspect, the present invention provides a charging station site selection device, comprising: a division module, used to divide a target study area into multiple grids; there are built charging stations or recommended charging station sites in the target study area; a site selection module, used to select multiple points of interest in all the grids according to a preset site selection strategy; wherein each of the points of interest is outside the coverage of the built charging station or the recommended charging station site selection; an optimization module, used to select some points of interest from the multiple points of interest as target points of interest for position disturbance operation and determine new points of interest corresponding to the target points of interest; wherein the position disturbance operation is to replace the grid where the target point of interest is located or to replace the target point of interest with another point of interest in the same site selection priority as the target point of interest; the optimization module is also used to use all the points of interest after the position disturbance operation as charging station site selection locations when the evaluation values ​​corresponding to all the points of interest after the position disturbance operation are greater than the evaluation values ​​corresponding to all the points of interest before the position disturbance operation.

[0008] In a third aspect, the present invention provides a computer device, comprising a processor and a memory, wherein the memory stores a computer program executable by the processor, and the processor can execute the computer program to implement the charging station site selection method described in the first aspect.

[0009] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the charging station site selection method as described in the first aspect above.

[0010] The charging station site selection method, device, computer equipment and readable storage medium provided by the embodiment of the present invention adopt the method of dividing the target research area into multiple grids, and select multiple points of interest in all grids according to the preset site selection strategy, and each point of interest is outside the coverage of the built charging station and / or the recommended charging station site selection; after selecting multiple points of interest, select some points of interest as target points of interest to perform position disturbance operation and determine new points of interest corresponding to the target points of interest, when the evaluation function values ​​corresponding to all points of interest after the position disturbance operation are greater than the evaluation function values ​​corresponding to all points of interest before the position disturbance operation, all points of interest after the position disturbance operation are used as charging station site selection positions. Compared with the method in the prior art that ignores the interaction between multiple sites, the present invention only selects points outside the coverage of the built charging station and / or the recommended charging station site selection in the first site selection, which can avoid the problem of uneven distribution caused by too dense charging station locations. At the same time, the present invention also optimizes the site selection result based on the first site selection result through dynamic position adjustment and energy efficiency evaluation, ensuring that the site selection result still has high energy efficiency under various complex constraints, thereby improving the rationality of the site selection of the charging station.

[0011] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0013] Figure 1 A schematic flow chart of a charging station site selection method provided in an embodiment of the present invention;

[0014] Figure 2 A schematic flow chart of step S102 provided in an embodiment of the present invention;

[0015] Figure 3 A schematic diagram of site selection results of a charging station site selection method provided by an embodiment of the present invention;

[0016] Figure 4 A functional module diagram of a charging station site selection device provided by an embodiment of the present invention;

[0017] Figure 5 A structural block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0019] Considering that the existing charging station site selection technology has the defects of unreasonable site selection or low performance, an embodiment of the present invention provides a charging station site selection method, which is described below through an embodiment.

[0020] See also Figure 1 , Figure 1The present invention provides a schematic flow chart of a charging station site selection method provided in an embodiment of the present invention. The execution subject of the method may be a computer device with specific data analysis and processing capabilities. The method may include the following steps:

[0021] S101. Divide the target study area into multiple grids; wherein there are built charging stations or recommended charging station sites in the target study area.

[0022] S102. In all grids, multiple points of interest are selected according to a preset site selection strategy; wherein each point of interest is outside the coverage of an existing charging station or a recommended charging station site selection;

[0023] S103, selecting some of the multiple points of interest as target points of interest for position disturbance operation, and determining new points of interest corresponding to the target points of interest; wherein the position disturbance operation is to replace the grid where the target point of interest is located or to replace the target point of interest with another point of interest in the same location priority as the target point of interest;

[0024] S104. When the evaluation function values ​​corresponding to all the points of interest after the position disturbance operation are greater than the evaluation function values ​​corresponding to all the points of interest before the position disturbance operation, all the points of interest after the position disturbance operation are used as charging station site selection locations.

[0025] The scheme of step S101 to step S104 provided in the embodiment of the present invention has the following advantages: First, the embodiment of the present invention subdivides the target study area into multiple grids, and carefully selects multiple points of interest in all grids according to the preset site selection strategy to ensure that each point of interest is located outside the coverage of the existing charging station or the recommended charging station site selection. After preliminarily screening out multiple points of interest, some points of interest are further screened out as target points of interest, and the positions are disturbed to determine the new positions of the points of interest. If the evaluation function values ​​corresponding to all points of interest are higher than those before the position disturbance after the position disturbance, then these points of interest after the disturbance will be determined as the site selection of the charging station. Compared with the method of ignoring the interaction between sites in the prior art, the present invention excludes the areas overlapping with the existing charging stations or recommended sites in the preliminary site selection stage, effectively avoiding the over-concentration of the distribution of charging stations, thereby ensuring the balanced allocation of resources. In addition, the present invention optimizes the preliminary site selection results through dynamic adjustment of the location and energy efficiency evaluation, ensuring that the site selection plan can still maintain high efficiency while meeting various complex constraints, thereby significantly improving the rationality and practicality of the charging station site selection.

[0026] The following will be combined with the attached drawings Figure 1 The implementation methods of each step in the process are clearly and detailedly introduced.

[0027] In step S101, the embodiment of the present invention allows the user to flexibly set the scope of the target research area according to actual needs, which is not limited here. The target research area can be a city, a village or any other geographical area of ​​interest to the user.

[0028] In one embodiment of the present invention, the map of the target research area can be divided into Geohash7 grids using Geohash technology. For example, assuming that the longitude and latitude range of a certain city is from 120 degrees east longitude to 121 degrees east longitude, and from 30 degrees north latitude to 31 degrees north latitude. Use the Geohash algorithm to divide this range into 27 / 2 × 27 / 2 = 128 × 128 Geohash7 grids.

[0029] It is understood that there may be existing charging stations, recommended charging station sites, or both within the target study area. "Recommended charging station sites" refer to sites where specific locations have been selected and recommended, but charging stations have not yet been actually built at these locations.

[0030] Taking into account the potential impact of the siting of existing charging stations and / or recommended charging stations on the siting of new charging stations, in order to prevent charging stations from being too dense and causing uneven resource allocation, in one embodiment of the present invention, the coverage range of existing and / or recommended charging stations can be determined first, which can be used as a constraint range for the subsequent selection of points of interest to ensure that the selected points of interest are reasonable.

[0031] The following first introduces the implementation method of determining the above coverage range in the embodiment of the present invention. For the convenience of distinction, in the embodiment of the present invention, the coverage range determined when the area where the built charging station and / or the recommended charging station is located is divided into the city center is represented by radius R1, and the coverage range determined when the area is divided into the rural area is represented by R2. Then the radius R1 and the radius R2 can be determined by:

[0032] Step a1: Determine the reachable circle of the built charging stations and / or recommended charging station locations within a preset time range.

[0033] Step a2: For each reach circle range, calculate the average distance from the center to each coordinate point, take the average of all average values ​​as the area radius, and determine the coverage range.

[0034] In step a1, the preset time range can be flexibly defined according to actual needs and is not limited here. The arrival circle is defined by a series of coordinate points, which form a closed shape, representing all areas that can be reached within the preset time range starting from the station.

[0035] For example, the preset time range is set to 10 minutes. In this case, the range that the user can reach within 10 minutes from the built charging station or the recommended charging station site constitutes the "arrival circle" in the embodiment of the present invention.

[0036] In an optional embodiment, factors such as road networks, traffic speeds, and traffic signals may be considered, and traffic models and map data may be used to estimate the maximum range that a user can reach within a preset time frame from each charging station.

[0037] For ease of understanding, let's take an example: assuming that several charging pile stations have been built in the target study area, we can first collect the geographic location data of all the built charging pile stations, which include the precise latitude and longitude coordinates of each station. Then estimate the area that users can cover within 10 minutes from each charging pile station and draw a closed polygon. The boundary of this polygon is defined by the following coordinate points: (30.7000, 120.5000), (30.7050, 120.5100), (30.7100, 120.5050), (30.7150, 120.4950), (30.7000, 120.4900). Then we can first determine the geometric center (X, Y) of this polygon, and then continue to calculate the distance between (X, Y) and these four coordinate points and find the average.

[0038] Through the above-mentioned embodiments, the coverage range R1 of the charging station in the city center and the coverage range R2 of the charging station in the rural area can be determined. It can be understood that due to factors such as the population, vehicle density, vehicle flow, terrain, and network distribution in the city center and the rural area, the coverage range of the charging station in the city center is relatively small, while in rural areas, due to the vast land and sparse population, the service range of each charging station will be much larger, so R1 is smaller than R2.

[0039] On the basis of determining the charging station coverage range R1 of the urban center and the charging station coverage range R2 of the rural area in the target study area, the embodiment of the present invention can also first determine the energy efficiency value of each grid. This energy efficiency value is one of the key indicators for evaluating whether the potential site is highly efficient in the subsequent charging station site selection and optimization process. This will be elaborated and explained in more detail in the subsequent embodiments.

[0040] The following describes an implementation method for determining the energy efficiency value of a grid in an embodiment of the present invention, which may include the following steps:

[0041] Step b1: Acquire multi-source data corresponding to grids within the coverage area of ​​built charging stations and / or recommended charging station sites.

[0042] In one embodiment of the present invention, with the help of an advanced spatial big data interface, only the grid identifier needs to be input to obtain the charging pile planning and operation information within the grid as well as data including key indicators such as population, vehicles, transportation network and environmental formats.

[0043] Therefore, the multi-source data in the embodiment of the present invention mainly includes the following:

[0044] Charging station data: covers detailed data such as station name, district, construction location, precise longitude and latitude coordinates, number of AC and DC charging piles and their power.

[0045] Population data: including working population, resident population, tourist population, visiting population, resident population and resident population among online ride-hailing drivers and their number of stays.

[0046] Vehicle data: including the residence, workplace, number of stays of new energy vehicle owners, and the frequency of stays for commuting, travel and operating vehicles.

[0047] Environmental business data: statistics on parking lots, residential communities, office buildings, scenic spots (including 4A and 5A scenic spots and others), gas stations, charging stations, schools, shopping centers, hotels / inns / guest houses, and various types of accommodation services (such as guest houses, hotels, inns, guest houses, homestays) and parks / squares.

[0048] In an embodiment of the present invention, the energy efficiency value, as a key indicator for measuring the performance of a charging station, can be quantitatively expressed through parameters such as charging efficiency, but is not limited to it. In the model training stage, considering that the grid area corresponding to the multi-source data is located within the coverage of the built charging stations or the recommended charging station sites, the embodiment of the present invention can use the energy efficiency values ​​of these charging stations as a standard to mark the multi-source data of each grid as a training sample. In this way, the goal of model learning is to minimize the deviation between the predicted energy efficiency value and the actual marked value. After multiple trainings, the model will be able to accurately predict the corresponding energy efficiency value based on the multi-source data of the input grid, thereby providing a scientific basis for the site selection and optimization of charging stations.

[0049] Step b2: Use the multi-source data corresponding to all grids to train the initial machine learning model to obtain a performance evaluation model.

[0050] In one embodiment of the present invention, the machine learning models used include, but are not limited to, random forest, Light Gradient Boosting Machine (Light GBM), Multilayer Perceptron (MLP), etc. The selection of these models is entirely based on the specific needs of the user to ensure flexibility and adaptability, and therefore, no specific limitation is made here.

[0051] It is worth noting that in one embodiment of the present invention, the method for training the performance evaluation model can draw on existing model training technology, and the sample data required in the training process comes from the multi-source data collected in the aforementioned step b1. In view of the fact that these methods and data acquisition have been described in detail in the prior art, the embodiment of the present invention will not elaborate on this.

[0052] Step b3: For each grid, the multi-source data corresponding to the grid is input into the performance evaluation model for processing to obtain the energy efficiency value of each grid.

[0053] Through the above steps b1 to b3, the embodiment of the present invention can quickly and accurately evaluate the energy efficiency value of each grid, which provides a basis for subsequent site selection within the grid and evaluation of whether the site selection is reasonable.

[0054] In one embodiment of the present invention, an efficiency evaluation model may be trained separately for each zoning type. This method can ensure that the energy efficiency value of each grid is more in line with the characteristics of the area to which it belongs, thereby improving the rationality and accuracy of the evaluation results.

[0055] Therefore, in step b1, based on the previously determined coverage ranges R1 and R2 of the urban center and rural area, the grids falling within the ranges R1 and R2 can be identified and counted respectively. Then, the multi-source data collected by the grids within the range of R1 can be used to train the model, thereby obtaining a performance evaluation model specifically for the urban center. Similarly, the data of the grids within the range of R2 can be used to train another model to obtain a performance evaluation model suitable for rural areas.

[0056] Under this strategy, for any grid, we can first determine whether it belongs to the city center or the rural area. If it belongs to the city center, the energy efficiency value of the grid is calculated using the energy evaluation model of the city center; if not, the energy efficiency value is determined using the energy evaluation model of the rural area. This method can ensure that the energy efficiency evaluation of each grid more accurately reflects the characteristics of the actual area where it is located.

[0057] After knowing the coverage ranges R1 and R2 of the city center and rural areas and performing energy efficiency evaluation on each grid, step S102 may be executed to achieve preliminary charging station site selection. Step S102 will be described in detail below with reference to the accompanying drawings.

[0058] See also Figure 2 , Figure 2 The schematic flow chart of step S102 provided in the embodiment of the present invention may include the following steps:

[0059] S102-1: Select the grid with the highest energy efficiency value as the first site selection area, and select a point of interest from different types of points of interest in order of site selection priority from high to low;

[0060] It is understandable that the energy efficiency value of each grid has been evaluated through the performance evaluation model in the previous text, so all grids can be sorted according to the energy efficiency value, and the sorting method can be from high to low or from low to high, which is not limited here. In the embodiment of the present invention, the grid with the highest efficiency is preferentially selected as the preferred site selection area for the charging station.

[0061] In one embodiment of the present invention, the site selection is selected from various points of interest in the site selection area. These points of interest may include, but are not limited to, a variety of places including shopping malls, parking lots, gas stations, scenic spots, accommodation services, park squares, buildings, residential areas, etc. In order to ensure that the selected charging station location is not only convenient for users but also attractive, before the site selection process is started, corresponding site selection priorities can be assigned to these different categories of points of interest. Subsequently, based on this priority, the most suitable points of interest are evaluated and selected in order from high to low to ensure the scientific nature of the site selection decision and user satisfaction.

[0062] For example, continuing with the various points of interest listed above, the following site selection priorities can be set: 1 shopping mall, 2 parking lot, 3 gas station, 4 scenic spot, 5 accommodation service, 6 park square, 7 building, 8 residential area, where the smaller the number, the higher the priority. According to this priority order, when selecting a site, the shopping mall is considered first, then the parking lot, and so on.

[0063] It should be understood that the above-mentioned points of interest and their location priorities are only for illustrative purposes and do not limit the scope of the points of interest or the order of location priorities in the embodiments of the present invention. In practical applications, users can flexibly set the points of interest and their priorities according to their own location requirements. The embodiments of the present invention do not limit this.

[0064] In the process of setting the site selection priority, the embodiment of the present invention can set a site selection priority for each point of interest, or set the same site selection priority for different types of points of interest. For example, the site selection priority 1 includes shopping malls and parking lots, the site selection priority 2 includes gas stations and scenic spots, the site selection priority 3 includes accommodation services and park squares, and the site selection priority 4 includes buildings and residential areas.

[0065] In the case where there are multiple candidate points of interest under the same site selection priority, the embodiment of the present invention can randomly select one when selecting a site, or set the site selection order again. For example: the points of interest with a site selection priority of 1 include a shopping mall and a parking lot, then when selecting a site, one can be randomly selected as the site selection location, or the site selection order of the shopping mall and the parking lot can be set to the shopping mall first and then the parking lot.

[0066] The purpose of the above strategy is to ensure the rationality of the location of the selected POI. This can be understood as follows: if a selected POI is located within the coverage of an existing charging station or a recommended charging station (whether it is an urban radius R1 or a rural radius R2), it means that the POI is not reasonable. In this case, you can turn to the next candidate POI in the same location priority sequence, and so on, until a suitable location is found.

[0067] For example, if a shopping mall and a parking lot are both listed as candidate points of interest with a site selection priority of 1, and the preferred shopping mall needs to be abandoned because it is located within the R1 or R2 range, the next candidate point of interest in the site selection priority sequence can be postponed to the parking lot. Once the parking lot is confirmed to be not within the coverage of any existing charging station, it can be determined as a preliminary site selection result. If the parking lot also does not meet the conditions, continue to evaluate subsequent points of interest in order of priority until a qualified site selection is found. This method ensures the rationality of the site selection process and the quality of the initial site selection results.

[0068] S102-2: If the site selection stop condition is not triggered, select the next grid with the highest energy efficiency value, and repeat the step of selecting a point of interest from different types of points of interest in order of site selection priority from high to low until the site selection stop condition is triggered;

[0069] In the embodiment of the present invention, the site selection stop condition is that the currently selected points of interest cannot cover the target study area or the predetermined number of charging stations is not reached. In other words, if it is found that the currently selected points of interest cannot achieve full coverage of the target study area or the set number of charging stations is not reached, the next highest efficiency grid will be selected until the coverage requirement is met or the number of charging stations is reached.

[0070] Through the above implementation, the embodiment of the present invention can quickly screen out a batch of initial site selection locations, and these site selection locations are not within the coverage of the built charging stations and / or recommended charging station sites, effectively avoiding the problem of excessive concentration of charging station locations and uneven resource allocation.

[0071] In one embodiment of the present invention, after the first preliminary site selection is completed in step S102, the total number (S1) of these points of interest and their total energy efficiency value (P1) can also be calculated. Specifically, the total energy efficiency value can be calculated based on the energy efficiency value of the grid where each selected point of interest is located. The total number (S1) and the total energy efficiency value (P1) will provide a basis for subsequent location evaluation.

[0072] After a batch of initial site selection locations are determined through the above implementation process, in order to ensure that the selected charging station locations have the highest energy efficiency, step S103 provided in the embodiment of the present invention may be continued to be performed.

[0073] In step S103, the embodiment of the present invention can dynamically adjust and optimize some of the selected multiple points of interest as target points of interest, that is, the "position disturbance operation" proposed in the embodiment of the present invention, to ensure that the site selection result is still highly efficient under various complex constraints.

[0074] The number of target interest points can be flexibly set by the user, and can be one or more, which is not limited here. For example, after the first site selection, 10 interest points are obtained, and one target interest point is selected for position disturbance, and the remaining 9 are not disturbed.

[0075] For the selected target interest points, in one embodiment of the present invention, there are two types of location disturbance operations that can be performed: one is to replace the target interest point with another interest point in the same location priority as the target interest point; the other is to replace the grid where the target interest point is located.

[0076] In the first position disturbance operation, a point of interest can be selected in the same location priority as the target point of interest according to the location priority set in the previous location selection process, which is temporarily called the new point of interest after the location disturbance of the target point of interest.

[0077] For example, the points of interest with a location priority of 1 include shopping malls and parking lots. Assuming that the shopping mall is selected in the order of priority, then when performing location perturbation, the shopping mall can be substituted for the parking lot in the same location priority.

[0078] In this location perturbation operation, the location of the POI changes, but the grid does not change, and the total number of POIs may also change because there may be no alternative POIs in the same site selection priority or the selected POIs cannot meet the constraints outside the coverage of the built charging stations and / or recommended charging station sites.

[0079] In the second position perturbation operation, the new interest point after the position perturbation of the target interest point can be determined as follows:

[0080] Step c1: within the neighborhood of the grid where the target interest point is located, determine a target grid whose energy efficiency value is greater than the energy efficiency value of the grid where the target interest point is located;

[0081] Step c2: In the target grid, a step of selecting a plurality of points of interest according to a preset site selection strategy is performed to determine a new point of interest in the target grid.

[0082] This can be understood as follows: first, in the neighborhood of the grid where the target point of interest is located, that is, near the grid, find a grid with an energy efficiency value higher than that of this grid as the target grid, and then return to execute step S102, that is, in this target grid, select an interest point from different types of interest points in order of site selection priority from high to low.

[0083] In this location perturbation operation, both the location and grid of the POI are changed, and the total number of POIs may also change because there may not be a target grid with high energy efficiency value nearby or the POIs within the target grid do not meet the constraint of being outside the coverage of the built charging stations and / or recommended charging station locations.

[0084] Regardless of whether the first or second position perturbation operation is adopted, after determining the new interest points corresponding to the target interest points, the total number of interest points (S2) can be calculated again based on these new interest points and the remaining interest points that have not been positionally perturbed, and combined with the energy efficiency values ​​of the grids where these new interest points are located, their total energy efficiency values ​​(P2) can be calculated again. The total number (S1) and total energy efficiency value (P1) before the position perturbation operation and the total number (S2) and total energy efficiency value (P2) after the position perturbation operation can be used for position evaluation.

[0085] Therefore, in an embodiment of the present invention, a method for performing location assessment is provided, as shown in the following steps:

[0086] Step d1: before performing the location disturbance, the total number of site selections is counted and the total energy efficiency value of the site selection is calculated based on the energy efficiency value of the grid where each point of interest is located;

[0087] Step d2: after performing the position disturbance operation, the total number of new sites is calculated based on the new points of interest and the total energy efficiency value of the new sites is calculated based on the energy efficiency value of the grid where the new points of interest are located;

[0088] In an embodiment of the present invention, the points of interest that have not participated in the position disturbance and the new points of interest are combined together to obtain the total number of new site selections, and the energy efficiency values ​​of the grids where the points of interest that have not participated in the position disturbance and the new points of interest are located are summarized to obtain the total energy efficiency value of the new site selection.

[0089] For example, after the first site selection, 10 points of interest are obtained, and one target point of interest is selected for position disturbance to obtain a new point of interest. The remaining 9 points of interest do not participate in the position disturbance. When calculating the number of new sites, the total number of these 9 points of interest and new points of interest is counted as the total number of new sites, and the energy efficiency values ​​of the grids where these 9 points of interest and the new points of interest are located are added together to obtain the total energy efficiency value of the new site.

[0090] Step d3: Calculate the evaluation function value using the total number of site selections and the total energy efficiency value of site selections as well as the total number of new site selections and the total energy efficiency value of site selections.

[0091] In one embodiment of the present invention, the expression of the evaluation function is: , where S1 and P1 are the total number of locations and the total energy efficiency value of the locations of interest points before the position disturbance operation, respectively; S2 and P2 are the total number of new locations and the total energy efficiency value of new locations after the position disturbance operation, respectively. For the convenience of distinction and description, the evaluation function value calculated before the position disturbance operation is called the current solution, and the evaluation function value calculated after the position disturbance operation is called the new solution.

[0092] After determining the evaluation function value after the position disturbance operation, the size of the new solution and the current solution can be compared, so as to evaluate the points of interest before the position disturbance operation and the points of interest after the position disturbance operation in terms of comprehensive evaluation of quantity and effectiveness.

[0093] In step S104, the embodiment of the present invention provides an evaluation method:

[0094] When the evaluation function values ​​corresponding to all points of interest after the position disturbance operation are greater than the evaluation function values ​​corresponding to all points of interest before the position disturbance operation, all points of interest after the position disturbance operation are used as the location selection positions of the charging station.

[0095] That is to say, if the new solution is greater than or equal to the current solution, that is, the points of interest before the location perturbation operation are better than the points of interest after the location perturbation operation in terms of comprehensive evaluation of quantity and effectiveness, then the points of interest that did not participate in the location perturbation and the new points of interest obtained after the location perturbation can be used as the final charging station location.

[0096] It is understandable that if the new solution is smaller than the current solution, that is, the points of interest before the location perturbation operation are inferior to the points of interest after the location perturbation operation in terms of the comprehensive evaluation of quantity and efficiency, the embodiment of the present invention also has a certain probability of accepting the new solution to prevent the algorithm from converging to the local optimal solution too early. Therefore, after step S104, the following steps may also be performed until the optimal location selection result is determined:

[0097] Step e1: Determine whether to accept the new point of interest based on the acceptance probability;

[0098] In one embodiment of the present invention, the acceptance probability can be customized by the user to a specific value or a customized calculation method, which is not limited by the present invention.

[0099] In the embodiment of the present invention, a random number between 0 and 1 can be generated, and then the random number and the acceptance probability are compared. If the random number is less than or equal to the acceptance probability, the new solution, that is, the new interest point, is accepted. If the random number is less than or equal to the acceptance probability, then the position perturbation is performed again based on all the currently obtained interest points.

[0100] Step e2: If yes, the new POI and the POI not involved in the position disturbance operation are used as the charging station site selection locations;

[0101] Step e3: If not, reduce the acceptance probability;

[0102] Step e4: Based on the new points of interest and the points of interest that have not participated in the position disturbance operation, return to execute step S103.

[0103] The above implementation is iterated until a preset number of iterations is reached or the new solution is greater than or equal to the current solution, and all the points of interest obtained at this time are used as the final charging station site selection location.

[0104] Based on the above implementation methods, the final site selection result of the embodiment of the present invention is as follows: Figure 3 As shown, Figure 3 The schematic diagram of the site selection results of the charging station site selection method provided in the embodiment of the present invention shows that the embodiment of the present invention can ensure that the site selection location avoids the built charging stations and / or the recommended charging station sites, effectively preventing the uneven distribution problem caused by the excessive concentration of charging stations. At the same time, the embodiment of the present invention not only fully considers the optimal location of a single site when selecting a site, but also considers the interaction between multiple sites. On the basis of the preliminary site selection, further optimization is carried out through measures such as dynamic adjustment of the location and energy efficiency evaluation, ensuring that the selected location can still maintain high energy efficiency in the face of various complex conditions, significantly improving the rationality of the charging station site selection.

[0105] Based on Figure 1With the same inventive concept, the present invention also provides a charging station site selection device. Figure 4 , Figure 4 The functional module diagram of the charging station site selection device provided by the embodiment of the present invention. The charging station site selection device 40 may include: a division module 401 , a site selection module 402 and an optimization module 403 .

[0106] A division module is used to divide the target study area into multiple grids; there are charging stations that have been built or recommended charging station sites in the target study area;

[0107] A site selection module 401 is used to select a plurality of points of interest in all grids according to a preset site selection strategy; wherein each point of interest is outside the coverage of the built charging station or the recommended charging station site selection;

[0108] The optimization module 402 is used to select some of the interest points from the multiple interest points as target interest points to perform a position disturbance operation and determine a new interest point corresponding to the target interest point; wherein the position disturbance operation is to replace the grid where the target interest point is located or to replace the target interest point with another interest point in the same location priority as the target interest point;

[0109] The optimization module 403 is also used to use all the points of interest after the position disturbance operation as the location selection positions of the charging station when the evaluation values ​​corresponding to all the points of interest after the position disturbance operation are greater than the evaluation values ​​corresponding to all the points of interest before the position disturbance operation.

[0110] It is understandable that the partitioning module 401, the site selection module 402 and the optimization module 403 can be executed in a coordinated manner. Figure 1 Each step in the process is performed to achieve the corresponding technical effect.

[0111] In an optional embodiment, the site selection module 402 is configured to select a grid with the highest energy efficiency value as the first site selection area, and select a point of interest from different types of points of interest in descending order of site selection priority; if the site selection stop condition is not triggered, select the next grid with the highest energy efficiency value, and repeat the step of selecting a point of interest from different types of points of interest in descending order of site selection priority until the site selection stop condition is triggered; wherein the site selection stop condition is that the currently selected points of interest cannot cover the target research area or the predetermined number of charging stations is not reached.

[0112] In an optional embodiment, the charging station site selection device 40 may include a determination module for determining the coverage of built charging stations and / or recommended charging station sites; obtaining multi-source data corresponding to grids within the coverage area; using the multi-source data corresponding to all grids to train an initial machine learning model to obtain an efficiency evaluation model; for each grid, inputting the multi-source data corresponding to the grid into the efficiency evaluation model for processing to obtain the energy efficiency value of each grid.

[0113] In an optional embodiment, the determination module is also used to determine the arrival circle range of the built charging stations and / or recommended charging station sites within a preset time range; wherein the arrival circle range is a closed polygon formed by connecting multiple coordinate points; for each arrival circle range, the average value of the distance from the center to each coordinate point is calculated, and the average value of all average values ​​is taken as the area radius to determine the coverage range.

[0114] In an optional implementation, the optimization module 403 is specifically used to determine a target grid whose energy efficiency value is greater than the energy efficiency value of the grid where the target point of interest is located within the neighborhood of the grid where the target point of interest is located; within the target grid, select an interest point from different types of interest points in order of site selection priority from high to low as a new interest point.

[0115] In an optional implementation, the method for calculating the evaluation function value is: before performing the position disturbance, counting the total number of site selections and calculating the total energy efficiency value of the site selection based on the energy efficiency value of the grid where each point of interest is located; after performing the position disturbance operation, calculating the total number of new site selections based on the new points of interest and calculating the total energy efficiency value of the new site selection based on the energy efficiency value of the grid where the new points of interest are located; and calculating the evaluation function value using the total number of site selections and the total energy efficiency value of the site selections as well as the total number of new site selections and the total energy efficiency value of the site selections.

[0116] In an optional embodiment, the optimization module 403 is also used to determine whether to accept new points of interest based on the acceptance probability when the evaluation function values ​​corresponding to all points of interest after the position disturbance operation are less than or equal to the evaluation function values ​​corresponding to all points of interest before the position disturbance operation; if so, the new points of interest and the points of interest that did not participate in the position disturbance operation are used as charging station site selection locations; if not, the acceptance probability is reduced; based on the new points of interest and the points of interest that did not participate in the position disturbance operation, return to the step of selecting some points of interest as target points of interest for the position disturbance operation, and then determining the new points of interest corresponding to the target points of interest.

[0117] It should be noted that the division of modules in the above embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional unit in each embodiment of the present application may be integrated into a processing unit, or may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0118] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable an electronic device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program executable code.

[0119] The embodiment of the present invention further provides a computer device 50, see Figure 5 , Figure 5 The computer device 50 provided in the embodiment of the present invention includes a memory 501, a processor 502 and a communication interface 503. The memory 501, the processor 502 and the communication interface 503 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0120] Optionally, the bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0121] In the embodiment of the present invention, the processor 502 may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiment of the present invention. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the embodiment of the present invention may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor. The software module may be located in the memory 501, and the processor 502 reads the program instructions in the memory 501 and completes the steps of the above method in combination with its hardware.

[0122] In the embodiment of the present invention, the memory 501 may be a non-volatile memory, such as a hard disk (HDD) or a solid-state drive (SSD), etc., or a volatile memory (Volatile Memory), such as RAM. The memory may also be any other medium that can be used to carry or store the desired program executable code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory in the embodiment of the present invention may also be a circuit or any other device that can realize a storage function, for storing instructions and / or data.

[0123] The memory 501 can be used to store software programs and modules, such as the instructions / modules of the charging station site selection device 40 provided in the embodiment of the present invention, which can be stored in the memory 501 in the form of software or firmware (Firmware) or in the operating system (OS) of the fixed computer device 500. The processor 502 executes various functional applications and data processing by executing the software programs and modules stored in the memory 501. The communication interface 503 can be used to communicate signaling or data with other node devices.

[0124] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0125] Understandably, Figure 5 The structure shown is for illustration only. The computer device 50 may also include Figure 5 More or fewer components as shown, or with Figure 5 Different configurations shown. Figure 5 The components shown may be implemented in hardware, software or a combination thereof.

[0126] The computer device 50 may also include a network device and / or a user device. The network device includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud consisting of a large number of hosts or network servers based on cloud computing.

[0127] Based on the above embodiments, the present application further provides a storage medium, in which a computer program is stored. When the computer program is executed by a computer, the computer executes the charging station site selection method provided in the above embodiments.

[0128] Based on the above embodiments, an embodiment of the present invention further provides a computer program. When the computer program is executed on a computer, the computer executes the charging station site selection method provided in the above embodiments.

[0129] Based on the above embodiments, an embodiment of the present invention further provides a chip, which is used to read a computer program stored in a memory and to execute the charging station site selection method provided in the above embodiments.

[0130] An embodiment of the present invention further provides a computer program product, comprising instructions, which, when executed on a computer, enables the computer to execute the charging station site selection method provided in the above embodiment.

[0131] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by instructions. These instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0132] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0134] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for selecting a charging station site, characterized in that: The method comprises: Divide the target study area into a plurality of grids; wherein there are built charging stations and / or recommended charging station sites in the target study area; In all the grids, multiple points of interest are selected according to a preset site selection strategy; wherein each of the points of interest is outside the coverage of the built charging station and / or the recommended charging station site selection; Among the plurality of interest points, some interest points are selected as target interest points for position disturbance operation, and then new interest points corresponding to the target interest points are determined; wherein the position disturbance operation is to replace the grid where the target interest point is located or to replace the target interest point with another interest point in the same location priority as the target interest point; When the evaluation function values ​​corresponding to all points of interest after the position disturbance operation are greater than the evaluation function values ​​corresponding to all points of interest before the position disturbance operation, all points of interest after the position disturbance operation are used as the location selection positions of the charging station; The calculation method of the evaluation function value is: before performing the position disturbance, the total number of site selections is counted and the total energy efficiency value of the site selection is calculated based on the energy efficiency value of the grid where each point of interest is located; after performing the position disturbance operation, the total number of new site selections is calculated based on the new point of interest and the total energy efficiency value of the new site selection is calculated based on the energy efficiency value of the grid where the new point of interest is located; the evaluation function value is calculated using the total number of site selections and the total energy efficiency value of the site selection and the total number of new site selections and the total energy efficiency value of the site selection; the expression of the evaluation function is: , where S1 and P1 are the total number of locations and the total energy efficiency value of the locations of interest before the location perturbation operation, respectively; S2 and P2 are the total number of new locations and the total energy efficiency value of the new locations after the location perturbation operation, respectively; where the energy efficiency value is predicted by the model based on the multi-source data of the input grid; the multi-source data includes charging station data, population data, vehicle data, and environmental business data.

2. The method for selecting a charging station site according to claim 1, characterized in that: In all the grids, multiple points of interest are selected according to a preset site selection strategy, including: Selecting a grid with the highest energy efficiency value as the first site selection area, and selecting one of the points of interest from different types of points of interest in descending order of the site selection priority; If the site selection stop condition is not triggered, selecting the next grid with the highest energy efficiency value, and repeating the step of selecting one of the points of interest from different types of points of interest in the order of the site selection priority from high to low until the site selection stop condition is triggered; The site selection stopping condition is that the currently selected points of interest cannot cover the target research area or the predetermined number of charging stations is not reached.

3. The charging station site selection method according to claim 1 or 2, characterized in that: Before the step of selecting a plurality of points of interest in all the grids according to a preset site selection strategy, the method further includes: Determining the coverage of the built charging stations and / or the recommended charging station sites; Acquire multi-source data corresponding to the grids within the coverage area; The initial machine learning model is trained using multi-source data corresponding to all grids to obtain an efficiency evaluation model; For each of the grids, the multi-source data corresponding to the grid is input into the performance evaluation model for processing to obtain the energy efficiency value of each of the grids.

4. The method for selecting a charging station site according to claim 3, characterized in that: Determining the coverage of the built charging station and / or the recommended charging station site selection includes: Determine the arrival circle range of the built charging station and / or the recommended charging station site within a preset time range; wherein the arrival circle range is a closed polygon formed by connecting multiple coordinate points; For each of the arrival circle ranges, the average value of the distance from the center to each of the coordinate points is calculated, and the average value of all the average values ​​is taken as the area radius to determine the coverage range.

5. The method for selecting a charging station site according to any one of claims 1, 2 and 4, characterized in that: When the position disturbance operation is to replace the grid where the target interest point is located, after selecting some interest points as the target interest points for the position disturbance operation, determining new interest points corresponding to the target interest points includes: In the neighborhood of the grid where the target point of interest is located, determining a target grid whose energy efficiency value is greater than the energy efficiency value of the grid where the target point of interest is located; In the target grid, an interest point is selected from different types of interest points in the order of the site selection priorities from high to low as the new interest point.

6. The method for selecting a charging station site according to any one of claims 1, 2 and 4, characterized in that: The method further comprises: When the evaluation function values ​​corresponding to all the interest points after the position disturbance operation are less than or equal to the evaluation function values ​​corresponding to all the interest points before the position disturbance operation, determining whether to accept the new interest point based on the acceptance probability; If yes, the new point of interest and the points of interest that have not participated in the position disturbance operation are used as the charging station site selection location; if no, the acceptance probability is reduced; Based on the new points of interest and the points of interest that have not participated in the position disturbance operation, return to the step of selecting some points of interest as target points of interest for the position disturbance operation, and then determining new points of interest corresponding to the target points of interest.

7. A charging station site selection device, characterized in that: include: A division module is used to divide the target research area into multiple grids; there are charging stations that have been built or recommended charging station sites in the target research area; A site selection module, configured to select a plurality of points of interest in all the grids according to a preset site selection strategy; wherein each of the points of interest is outside the coverage of the built charging station or the recommended charging station site selection; An optimization module, used to select some of the interest points from the plurality of interest points as target interest points for position disturbance operation and determine new interest points corresponding to the target interest points; wherein the position disturbance operation is to replace the grid where the target interest point is located or to replace the target interest point with another interest point in the same location priority as the target interest point; The optimization module is further configured to use all the points of interest after the position disturbance operation as the location selection positions of the charging station when the evaluation function values ​​corresponding to all the points of interest after the position disturbance operation are greater than the evaluation function values ​​corresponding to all the points of interest before the position disturbance operation; The calculation method of the evaluation function value is: before performing the position disturbance, the total number of site selections is counted and the total energy efficiency value of the site selection is calculated based on the energy efficiency value of the grid where each point of interest is located; after performing the position disturbance operation, the total number of new site selections is calculated based on the new point of interest and the total energy efficiency value of the new site selection is calculated based on the energy efficiency value of the grid where the new point of interest is located; the evaluation function value is calculated using the total number of site selections and the total energy efficiency value of the site selection and the total number of new site selections and the total energy efficiency value of the site selection; the expression of the evaluation function is: , where S1 and P1 are the total number of locations and the total energy efficiency value of the locations of interest before the location perturbation operation, respectively; S2 and P2 are the total number of new locations and the total energy efficiency value of the new locations after the location perturbation operation, respectively; where the energy efficiency value is predicted by the model based on the multi-source data of the input grid; the multi-source data includes charging station data, population data, vehicle data, and environmental business data.

8. A computer device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program executable by the processor, and the processor can execute the computer program to implement the charging station site selection method according to any one of claims 1 to 6.

9. A readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the charging station site selection method according to any one of claims 1 to 6 is implemented.

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