Charging pile configuration method and device and storage medium

Abstract

The invention discloses a charging pile configuration method and device and a storage medium, and belongs to the technical field of Internet of Vehicles. The method comprises the following steps: dividing a selected region range into a plurality of regions; obtaining the number of electric vehicles entering and the number of electric vehicles parking in each time period in each area based on the Internet of Vehicles data; aggregating and classifying the plurality of regions into corresponding region categories according to the time distribution characteristics of the Internet of Vehicles data of each region; obtaining a region category of a to-be-built region of the charging pile and a parking and charging related model corresponding to the region category; inputting the actual parking number of the electric vehicles in the parking peak period of the charging pile to-be-built area into the parking and charging related model to obtain the required total average charging power of the electric vehicles; the current charging pile rated total charging power of the charging pile to-be-built area is obtained based on the charging pile data; and obtaining the construction demand of the charging pile based on the current rated total charging power of the charging pile and the required total average charging power of the electric vehicle. And the charging pile plan configuration accuracy is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of vehicle networking technology, and in particular to a method, device and storage medium for configuring a charging pile. Background Art

[0002] As the number of electric vehicles increases, the demand for charging piles, the supporting facilities for electric vehicles, is also increasing. In the related art, the number of charging piles to be built is usually determined according to the size of the flow of people and vehicles in the area. In the related art, the collection of data on the flow of people and vehicles in an area is very general, which affects the accuracy and rationality of the configuration of charging piles. Therefore, how to ensure the rationality and accuracy of the configuration of charging piles in each area, while meeting the charging needs of local electric vehicles, and improving the utilization rate of charging piles, is a problem that needs to be solved. Summary of the invention

[0003] The embodiment of the present application provides a method, device and storage medium for configuring charging piles, which can be used to ensure the rationality of the configuration of charging piles in various areas. The technical solution is as follows: On the one hand, an embodiment of the present application provides a method for configuring a charging pile, the method comprising: Obtain Internet of Vehicles data and charging pile data within a selected period in a selected area; Dividing the selected area into a plurality of regions; Based on the Internet of Vehicles data, the number of electric vehicles entering and the number of electric vehicles parked in each area and each time period are obtained; Aggregating and classifying the multiple regions into corresponding region categories according to the time distribution characteristics of the Internet of Vehicles data of each region; Obtaining the regional category of the area where the charging pile is to be built and the parking charging related model corresponding to the regional category, wherein the input of the parking charging related model is the number of electric vehicles parked during the peak parking period in the area, and the output is the total average charging power of the electric vehicles during the peak parking period; Inputting the actual number of electric vehicles parked during the peak parking period in the area where the charging piles are to be built into the parking charging related model to obtain the required total average power of electric vehicle charging; Acquire the current rated total charging power of the charging piles in the area where the charging piles are to be built based on the charging pile data; The charging pile construction requirement is obtained based on the current rated total charging power of the charging pile and the required total average power for charging electric vehicles. The charging pile construction requirement indicates whether new charging piles need to be built and / or the number of new charging piles that need to be built.

[0004] On the other hand, a device for configuring a charging pile is provided, the device comprising: The first acquisition module is used to acquire the Internet of Vehicles data and charging pile data within a selected period range within a selected area; A division module, used for dividing the selected area into a plurality of areas; A second acquisition module is used to acquire the number of electric vehicles entering and the number of electric vehicles parked in each area and each time period based on the Internet of Vehicles data; A classification module, configured to aggregate and classify the plurality of regions into corresponding region categories according to the time distribution characteristics of the Internet of Vehicles data of each region; A third acquisition module is used to obtain the regional category of the area where the charging pile is to be built and the parking charging related model corresponding to the regional category, the input of the parking charging related model is the number of electric vehicles parked during the regional parking peak period, and the output is the total average charging power of the electric vehicles during the parking peak period; An input module, used for inputting the actual number of electric vehicles parked during the peak parking period in the area where the charging pile is to be built into the parking charging related model to obtain the required total average power of electric vehicle charging; A fourth acquisition module, configured to acquire the current rated total charging power of the charging piles in the area where the charging piles are to be built based on the charging pile data; The demand module is used to obtain the charging pile construction demand based on the current rated total charging power of the charging pile and the required total average power of electric vehicle charging. The charging pile construction demand indicates whether new charging piles need to be built and / or the number of new charging piles that need to be built.

[0005] On the other hand, a computer program product is also provided, which includes computer instructions, and when the computer instructions are executed by a processor, the steps of any of the above-mentioned methods for configuring a charging pile are implemented.

[0006] On the other hand, a non-temporary computer-readable storage medium is also provided, characterized in that a computer program is stored in the computer-readable storage medium, and the computer program is loaded and executed by a processor to implement any of the above-mentioned methods for configuring a charging pile.

[0007] The technical solution provided by this application brings at least the following beneficial effects: This application classifies regions according to the time distribution characteristics of Internet of Vehicles data, and selects corresponding parking charging related models according to the regional categories of the areas where charging piles are to be built, obtains relevant data from the Internet of Vehicles data and charging pile data of the areas where charging piles are to be built, and calculates the gap between the existing charging pile resources and the demand for charging piles in the area, thereby obtaining the charging pile construction demand in the area to guide the construction of charging piles. This application improves the accuracy of the plan for configuring charging piles, making the investment and construction of charging piles more in line with the actual needs of different regions, thereby ensuring the utilization rate of charging piles while meeting the charging needs of local electric vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 It is a schematic diagram of an implementation environment provided by an embodiment of the present application; Figure 2 It is a flow chart of a method for configuring a charging pile provided in an embodiment of the present application; Figure 3 An electric vehicle entry quantity curve and an electric vehicle parking quantity curve provided in an embodiment of the present application; Figure 4 It is a flowchart of configuring a charging pile provided in an embodiment of the present application; Figure 5 It is a structural schematic diagram of a device for configuring a charging pile provided in an embodiment of the present application. DETAILED DESCRIPTION

[0010] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0011] This application embodiment provides a method for configuring a charging pile, please refer to Figure 1 , which shows a schematic diagram of the implementation environment of the method provided in the embodiment of the present application. The implementation environment may include: a computer 11 of the operator's server, an ECU (Electronic Control Unit) 12, a BMS (Battery Management System) 13, a navigation system 14, a display screen 15 and an Internet of Things device 16.

[0012] Optionally, the computer 11 of the operator's server obtains the power-on and power-off status of the electric vehicle through the ECU 12, obtains the electric vehicle's location information through the navigation system 14, and reads the charging pile data through the Internet of Things device 16, so as to perform data analysis on the areas where charging piles have been built, and formulate a charging pile construction plan for the areas where charging piles are to be built.

[0013] In a possible implementation, the operator's server computer 11 obtains the electric vehicle SOC (State of Charge) through the BMS 13. When the electric vehicle SOC is less than the power threshold, the location information of the nearest unused charging pile is pushed to the electric vehicle, and the location information of the nearest charging pile is displayed through the electric vehicle's display screen 15. The operator's server computer 11, ECU 12, BMS 13, navigation system 14, display screen 15 and IoT device 16 establish a communication connection through a wired or wireless network.

[0014] Based on the above Figure 1 In the implementation environment shown, the present application embodiment provides a method for configuring a charging pile as shown in FIG. Figure 2 As shown, taking the method applied to a computer such as a server of an operator as an example, the method includes steps 201 to 208.

[0015] In step 201, the computer obtains Internet of Vehicles data and charging pile data within a selected period range within a selected area range.

[0016] In one possible implementation, the selected area range may be at least one of a city, a district, a town, or other areas not divided according to administrative regions. The selected period range may be set as required. For example, the selected period range may be set to 3 months. Optionally, the Internet of Vehicles data includes, but is not limited to: the power-on and power-off status of the electric vehicle, the SOC of the electric vehicle, and the location information of the electric vehicle. The charging pile data includes, but is not limited to: the type of charging pile, the charge amount of the charging pile, the rated charging power of the charging pile, and the location information of the charging pile. Among them, different types of charging piles correspond to different charging powers.

[0017] Exemplarily, after determining the selected area range and the selected cycle range, the Internet of Vehicles data within the selected cycle range is obtained within the selected area range, including: obtaining the power-on and power-off status of the electric vehicle through the ECU of the electric vehicle, obtaining the SOC of the electric vehicle through the BMS, and obtaining the location information of the electric vehicle through the navigation system installed on the electric vehicle. In a possible implementation, within the selected area range, the charging pile data within the selected cycle range is obtained, including: obtaining the type of charging pile, the charging amount of the charging pile, the rated charging power of the charging pile, the charging status of the charging pile, and the location information of the charging pile through the Internet of Things device installed on the charging pile. Among them, the Internet of Things device is installed on the charging pile to collect the data of the charging pile. Optionally, the Internet of Things device can be a wireless sensor.

[0018] In one possible implementation, the SOC of the electric vehicle is compared with a power threshold. When the SOC of the electric vehicle is less than the power threshold, the charging pile that is not in a charging state and is closest to the electric vehicle is determined based on the location information of the charging pile, the location information of the electric vehicle, and the charging state of the charging pile. The location information of the charging pile that is not in a charging state and is closest to the electric vehicle is pushed to the electric vehicle to prompt the driver of the nearest charging pile, so that the driver can charge the electric vehicle nearby. Optionally, the method of pushing the location information of the unused charging pile closest to the electric vehicle to the electric vehicle includes, but is not limited to: displaying the location information of the nearest charging pile on the display screen of the electric vehicle.

[0019] In step 202, the computer divides the selected area into a plurality of regions.

[0020] In one possible implementation, the selected area is divided into multiple areas, including: obtaining parking location information and corresponding time information of electric vehicles from Internet of Vehicles data; determining the location of parking lots and the parking quantity and time period distribution corresponding to each parking lot based on the parking location information and corresponding time information of electric vehicles; dividing parking lots with similar parking quantity and time period distribution and adjacent locations into a parking lot group; dividing the selected area into multiple areas in a manner where one area includes one parking lot group.

[0021] Exemplarily, the parking location information and corresponding time information of the electric vehicle are obtained from the Internet of Vehicles data, including: determining whether the electric vehicle is in a parking state by the power-on and power-off states of the electric vehicle, and if the electric vehicle is in a parking state, recording the time information when the electric vehicle enters and exits the parking state. And the location information of the electric vehicle in the parking state is determined in combination with the location information of the electric vehicle, that is, the location information of the parking of the electric vehicle. After determining the location information and corresponding time information of the parking of the electric vehicle, the location of the parking lot and the corresponding parking quantity time period distribution of each parking lot are determined based on the location information and corresponding time information of the parking of the electric vehicle, including: treating the area where the number of parked electric vehicles exceeds the preset number as a parking lot, and treating the location of the area as the location of the parking lot. Then, based on the time information of the electric vehicles in the area entering and exiting the parking state in each time period, the corresponding parking quantity time period distribution of the parking lot is determined. Optionally, the preset number can be set based on experience.

[0022] In a possible implementation, after determining the location of the parking lot and the parking quantity and time period distribution corresponding to each parking lot, the parking lots with similar parking quantity and time period distribution and adjacent locations are divided into a parking lot group, including: generating a normal distribution map corresponding to the parking time period of each parking lot based on the parking quantity and time period distribution corresponding to each parking lot, and determining the parking lots with similar parking quantity and time period distribution according to the normal distribution map. Then, the parking lots with similar parking quantity and time period distribution are determined in combination with the location of the parking lot, and the parking lots with similar parking quantity and time period distribution and adjacent locations are regarded as a parking lot group. The selected area is divided according to the parking lot group to obtain multiple regions. For example, there is no restriction on the method of regional division and the number of regions, and they are set based on experience while ensuring that one area includes one parking lot group.

[0023] Exemplarily, determining parking lots with similar parking quantity and time period distribution according to the normal distribution graph includes: taking parking lots whose normal distribution graph similarity corresponding to parking time periods is greater than a preset percentage as parking lots with similar parking quantity and time period distribution, wherein the preset percentage can be set based on experience.

[0024] In addition, a parking lot may be directly regarded as a parking lot group, so in some implementation modes, a parking lot may also be regarded as an area.

[0025] In step 203, the computer obtains the number of electric vehicles entering and the number of electric vehicles parked in each area and each time period based on the Internet of Vehicles data.

[0026] Optionally, after completing the area division, the number of electric vehicles entering and the number of electric vehicles parked in each area in each time period are obtained based on the Internet of Vehicles data, including: determining the number of electric vehicles entering each area in each time period according to the location information of the electric vehicles; determining the number of electric vehicles parked in each area in each time period according to the parking location information of the electric vehicles and the corresponding time information.

[0027] Exemplarily, determining the number of electric vehicles entering each area in each time period based on the location information of the electric vehicles includes: within a certain time period, counting the electric vehicles whose location information switches from outside a certain area to within a certain area, and using the counting result as the number of electric vehicles entering a certain area in a certain time period. The number of electric vehicles entering each area in each time period is counted in the same way.

[0028] By counting the number of electric vehicles entering and parking in each area at each time period, it is easier to determine whether new charging piles need to be built and the number of new charging piles to be built.

[0029] It should be noted that in this application, a time period can refer to a certain time zone in a day, and in statistics based on a time period, the data representing the statistical results generally refers to the average value of the same time period of several days, so that the statistical results are more accurate and representative. Some of the days can be the result of selection, for example, some obviously abnormal days can be excluded, and working days and holidays can be distinguished for statistics. At the same time, when calculating, working days or holidays can be selected for statistics according to the regional category to adapt to the characteristics of the regional category.

[0030] In step 204 , the computer aggregates and classifies the multiple regions into corresponding regional categories according to the time distribution characteristics of the Internet of Vehicles data of each region.

[0031] Optionally, after obtaining the number of electric vehicles entering and the number of electric vehicles parked in each area in each time period, multiple areas are aggregated and classified into corresponding area categories according to the time distribution characteristics of the Internet of Vehicles data of each area, including: drawing the electric vehicle entry number curve and the electric vehicle parking number curve for each area with time as the horizontal axis and number as the vertical axis; and classifying areas with a high overlap of the area entry peak period of the electric vehicle entry number curve and / or the area parking peak period of the electric vehicle parking number curve into the same area category. The standard for a high overlap can be predetermined based on experience, or templates for each area category can be established in advance. Each area is considered to belong to the area category based on which template has a higher overlap of the entry and / or parking peak period. Thus, multiple areas classified into the same area category have a higher overlap of the entry and / or parking peak period than areas classified into other categories.

[0032] In a possible implementation, taking the data of any area as an example, the electric vehicle entry quantity curve and the electric vehicle parking quantity curve are as follows: Figure 3 As shown, the horizontal axis is time and the vertical axis is the number of vehicles.

[0033] Optionally, after the electric vehicle entry number curve and the electric vehicle parking number curve are drawn in each area in the same way, the regional parking peak period of the electric vehicle entry number curve and the regional parking peak period of the electric vehicle parking number curve are determined according to the curves. Then, areas with a high overlap of the regional entry peak period of the electric vehicle entry number curve and / or the regional parking peak period of the electric vehicle parking number curve are classified into the same area class.

[0034] Exemplarily, a period of time before and after the peak position of the electric vehicle parking quantity curve and the electric vehicle entry quantity curve can be used as the parking peak period. Optionally, the area category can include at least one of an office building, a hospital, a school, a shopping mall, a residential area, and a scenic park.

[0035] Different regional categories correspond to different Internet of Vehicles data, charging pile data and charging needs. Therefore, each region is aggregated and classified based on the time distribution characteristics of the number of electric vehicles entering and the number of electric vehicles parking, and the regional category corresponding to each region is determined. This makes it easier to set appropriate charging pile configuration plans for each region, improve the accuracy of charging pile configuration, and ensure the utilization rate and revenue of charging piles while meeting charging needs.

[0036] Exemplarily, after completing the regional aggregation classification of each area, the areas with good charging pile data under each regional category are determined based on the charging pile data corresponding to the areas included in each regional category. The areas with good charging pile data refer to areas where the charging pile utilization rate during the peak parking period in the area is within a set range; based on the Internet of Vehicles data and charging pile data in areas with good charging pile data, a parking charging related model is formed.

[0037] In a possible implementation, based on the charging pile data corresponding to the areas included in each area category, the areas with good charging pile data under each area category are determined, including: calculating the charging pile utilization rate of the areas included in each area category during the peak parking period of the area, if the charging pile utilization rate of any area during the peak parking period of the area is within a set range, indicating that the area is an area with good charging pile data. The set range can be determined based on experience, and good charging pile data means that the charging pile utilization rate is neither too high nor too low. Too high means that the charging pile resources are insufficient and cannot meet the charging needs of electric vehicles well, and too low means that the charging pile resources are excessive and the interests of the charging pile operators are damaged.

[0038] Optionally, taking the area of ​​the shopping mall category as an example, the utilization rate of charging piles in any area under the shopping mall category during the regional parking peak period is calculated, including: calculating the sum of the charging amounts of the charging piles in any area under the shopping mall category during the regional parking peak period, dividing the sum of the charging amounts by the length of the regional parking peak period to obtain the total average charging power of electric vehicles during the parking peak period; and then dividing the total average charging power of electric vehicles by the rated total charging power of the charging piles. Among them, the rated total charging power of the charging piles is equal to the first calculation result of adding the rated charging powers of all charging piles in the area. The utilization rate of charging piles in the areas included in each regional category during the regional parking peak period is calculated in the same way.

[0039] Exemplarily, after determining the areas with good charging pile data in each regional category, a parking charging related model is formed based on the Internet of Vehicles data and charging pile data in the areas with good charging pile data, wherein the input of the parking charging related model is the number of electric vehicles parked during the peak parking period in the area, and the output is the total average charging power of electric vehicles during the peak parking period.

[0040] In one possible implementation, a parking and charging related model is formed based on the Internet of Vehicles data and charging pile data in areas with good charging pile data, including: for each area with good charging pile data under the same area type, the number of electric vehicles parked during peak parking hours is obtained, and the total average charging power of electric vehicles during peak parking hours is obtained based on the charging pile data; and a parking and charging related model is formed based on the correspondence between the number of electric vehicles parked and the total average charging power of electric vehicles in all areas under the same area type.

[0041] Optionally, taking the area of ​​the shopping mall category as an example, the number of electric vehicle parking during the peak parking period is obtained based on the Internet of Vehicles data, including: according to the number of electric vehicle parking in each area during each period, the number of electric vehicle parking during the peak parking period in each area with good charging pile data under the shopping mall category is calculated. The number of electric vehicle parking during the peak parking period in each area with good charging pile data under each area type is calculated in the same way.

[0042] Exemplarily, after determining the number of electric vehicle parking lots and the total average charging power of electric vehicles during peak parking periods in each area with good charging pile data under each area type, a parking charging related model is formed according to the corresponding relationship between the number of electric vehicle parking lots and the total average charging power of electric vehicles in all areas under the same area type, including: dividing a plurality of quantity intervals according to the number of electric vehicle parking lots, and fitting a relationship between the number of electric vehicle parking lots and the total average charging power of electric vehicles in each quantity interval.

[0043] In a possible implementation, there is no restriction on the divided quantity intervals, which can be set based on experience. After completing the division of the number of electric vehicle parking, a relationship between the number of electric vehicle parking and the total average power of electric vehicle charging is fitted in each quantity interval, including: using the number of electric vehicle parking as the X-axis coordinate, and constructing a coordinate system with the total average power of electric vehicle charging as the Y-axis coordinate, determining the data points corresponding to the number of electric vehicle parking and the corresponding total average power of electric vehicle charging in each quantity interval, and the coordinate positions corresponding to the data points. Then, a relationship is fitted based on the coordinate positions corresponding to each data point, where the relationship can be a linear relationship or a quadratic relationship.

[0044] Optionally, common linear and quadratic relationships can be used for fitting based on experience. Taking any quantity interval as an example, the relationship selected based on experience can be used to determine the parameters of the relationship through certain data points, and then the accuracy of the relationship can be verified through the remaining data points. If the relationship is accurate, the relationship is determined to be the relationship between the number of electric vehicles parked and the total average power of electric vehicles charged corresponding to the quantity interval; if the relationship is inaccurate, change the type of relationship, and fit and verify the relationship in the same way. Use the same method to fit the relationship between the number of electric vehicles parked and the total average power of electric vehicles charged in each quantity interval to obtain the parking charging related model corresponding to the area type.

[0045] In step 205, the computer obtains the regional category of the area where the charging pile is to be built and the parking charging related model corresponding to the regional category. The input of the parking charging related model is the number of electric vehicles parked during the peak parking period in the area, and the output is the total average charging power of the electric vehicles during the peak parking period.

[0046] Exemplarily, after selecting an area for charging piles to be built, the computer collects vehicle networking data within the selected period range of the area for charging piles to be built; and based on the vehicle networking data within the selected period range of the area for charging piles to be built, calculates the number of electric vehicles entering and the number of electric vehicles parked in each time period of the area for charging piles to be built.

[0047] In one possible implementation, after the computer obtains the number of electric vehicles entering and the number of electric vehicles parked in the area where charging piles are to be built, it draws a curve of the number of electric vehicles entering and the number of electric vehicles parked in the area where charging piles are to be built, with time as the horizontal axis and the number as the vertical axis, to obtain the time distribution characteristics of the Internet of Vehicles data in the area where charging piles are to be built.

[0048] Exemplarily, the time distribution characteristics of the Internet of Vehicles data of the area where the charging pile is to be built are compared with the time distribution characteristics of the Internet of Vehicles data corresponding to each category; the category that is closest to the time distribution characteristics of the Internet of Vehicles data of the area where the charging pile is to be built is used as the regional category of the area where the charging pile is to be built, and the parking charging related model corresponding to the closest category is used as the parking charging related model corresponding to the regional category of the area where the charging pile is to be built, wherein the input of the parking charging related model is the number of electric vehicles parked during the peak parking period corresponding to the regional category of the area where the charging pile is to be built, and the output is the total average charging power of electric vehicles during the peak parking period corresponding to the regional category of the area where the charging pile is to be built. In addition, the regional category of the area where the charging pile is to be built can also be obtained based on its own label. For example, if the label is hospital, it means that the regional category of the area where the charging pile is to be built is hospital.

[0049] In step 206, the computer inputs the actual number of electric vehicles parked during the peak parking period in the area where the charging piles are to be built into the parking charging related model to obtain the required total average power for charging the electric vehicles.

[0050] Optionally, a period of time is selected before and after the peak position of the electric vehicle parking number curve in the area where the charging pile is to be built as the parking peak period, and optionally, the selection method of the parking peak period can be preset. Exemplarily, after determining the parking charging related model corresponding to the area where the charging pile is to be built, the actual number of electric vehicles parked during the parking peak period in the area where the charging pile is to be built is input into the parking charging related model, and the output result of the parking charging related model in the area where the charging pile is to be built is obtained, and the output result is used as the total average charging power of electric vehicles required in the area where the charging pile is to be built.

[0051] In step 207 , the computer obtains the current rated total charging power of the charging piles in the area where the charging piles are to be built based on the charging pile data.

[0052] In one possible implementation, after obtaining the total average charging power of electric vehicles required for the area where charging piles are to be built, the current rated total charging power of the charging piles in the area where charging piles are to be built is obtained based on the charging pile data, including: calculating a second calculation result of adding the rated powers of all charging piles in the area where charging piles are to be built, and using the second calculation result as the current rated total charging power of the charging piles in the area where charging piles are to be built.

[0053] In step 208, the charging pile construction requirement is obtained based on the current rated total charging power of the charging pile and the required total average power of the electric vehicle charging. The charging pile construction requirement indicates whether new charging piles need to be built and / or the number of new charging piles that need to be built.

[0054] Exemplarily, after determining the current rated total charging power of the charging pile and the required total average charging power of electric vehicles, the charging pile construction demand is obtained based on the current rated total charging power of the charging pile and the required total average charging power of electric vehicles, including: obtaining the required rated total charging power of the charging pile based on the required total average charging power of electric vehicles and the expected utilization rate; when the required rated total charging power of the charging pile is greater than the current rated total charging power of the charging pile, the charging pile construction demand is that new charging piles need to be built; and / or, subtracting the rated total charging power of the current charging pile from the required total average charging power of electric vehicles to obtain the rated total charging power of the charging piles to be built, and based on the rated total charging power of the charging piles to be built and the charging pile charging power of the selected charging piles, the number of new charging piles to be built is obtained.

[0055] Optionally, the expected utilization rate of the charging pile can be set and adjusted according to demand. After determining the expected utilization rate of the charging pile in the area where the charging pile is to be built, the required rated total charging power of the charging pile is obtained based on the required total average charging power of the electric vehicles and the expected utilization rate, including: calculating a third calculation result of dividing the required total average charging power of the electric vehicle by the expected utilization rate, and using the third calculation result as the rated total charging power of the charging pile required for the area where the charging pile is to be built.

[0056] In one possible implementation, after calculating the required total charging power of the charging piles in the area to be built, the required total charging power of the charging piles is compared with the current total charging power of the charging piles. When the required total charging power of the charging piles is greater than the current total charging power of the charging piles, the charging pile construction requirement is that new charging piles need to be built; when the required total charging power of the charging piles is greater than the current total charging power of the charging piles, the charging pile construction requirement is that no new charging piles need to be built.

[0057] Exemplarily, the fourth calculation result can also be obtained by subtracting the rated total charging power of the current charging pile from the required total average charging power of the electric vehicle, and the fourth calculation result is used as the rated total charging power of the charging pile to be built. Determine the charging power of the new charging pile used for construction this time. If the charging power of the new charging pile is of only one type, calculate the fifth calculation result of the rated total charging power of the charging pile to be built divided by the charging power of the charging pile, and use the fifth calculation result as the number of new charging piles to be built; if the charging power of the new charging pile is of multiple types, and multiple types correspond to multiple charging powers, determine the number ratio of new charging piles of various specifications based on experience, and finally make the total charging power of the new charging pile meet the rated total charging power of the charging pile to be built.

[0058] Combining the above methods, Figure 4The flowchart of a flow chart for configuring a charging pile provided in the embodiment of the present application is used as an example for illustration. Among them, the execution subject can be the operator's server. At the electric vehicle end, the Internet of Vehicles data is accessed, wherein the Internet of Vehicles data includes the power-on and power-off status of the electric vehicle, the SOC of the electric vehicle, and the location information of the electric vehicle. At the charging pile end, the Internet of Things data is accessed, wherein the Internet of Things data includes the type of charging pile, the rated charging power of the charging pile, the charging amount of the charging pile, and the location information of the charging pile. On the operator's server cloud, multiple areas are aggregated and classified into corresponding area categories. For example, office buildings, hospitals, schools, shopping malls, residential communities, and scenic parks. Then, on the operator's server cloud, based on the Internet of Vehicles data and the charging pile data, parking and charging related models are constructed, such as models of office building area types, hospital area types, and residential area types.

[0059] For new sites, that is, areas where charging piles are not built and are to be built, collect Internet of Vehicles data, calculate and process it, and input it into the parking charging related model corresponding to the area category to obtain the total average power required for electric vehicle charging in areas where charging piles are not built and are to be built. Then, according to the power of the charging piles used for construction, calculate the number of charging piles used for construction.

[0060] For old site areas, that is, areas where charging piles have been built and the number of charging piles is considered to be increased, the collected Internet of Vehicles data is input into the parking charging related model corresponding to the area category after calculation and processing, and the total average charging power of electric vehicles required in areas where charging piles have been built and the number of charging piles is considered to be increased is obtained. Collect IoT data, calculate the current rated total charging power of the charging pile based on the IoT data, compare the current rated total charging power of the charging pile with the required total average charging power of the electric vehicle, so as to determine whether it is necessary to increase the charging piles, and calculate the number of charging piles that need to be increased in combination with the power of the charging piles used for construction.

[0061] The embodiment of the present application classifies regions according to the time distribution characteristics of the Internet of Vehicles data, and selects the corresponding parking charging related model according to the regional category of the area where the charging pile is to be built, obtains relevant data from the Internet of Vehicles data and the charging pile data of the area where the charging pile is to be built, and calculates the gap between the existing charging pile resources and the charging pile demand in the area, thereby obtaining the charging pile construction demand in the area to guide the construction of charging piles. The present application improves the accuracy of the plan for configuring charging piles, so that the investment and construction of charging piles are more in line with the actual needs of different regions, thereby ensuring the utilization rate of charging piles while meeting the charging needs of local electric vehicles.

[0062] See also Figure 5 , an embodiment of the present application provides a device for configuring a charging pile, the device comprising: The first acquisition module 501 is used to acquire the Internet of Vehicles data and charging pile data within a selected period range within a selected area; A division module 502 is used to divide the selected area into multiple areas; The second acquisition module 503 is used to acquire the number of electric vehicles entering and the number of electric vehicles parked in each area and each time period based on the Internet of Vehicles data; A classification module 504, for aggregating and classifying multiple regions into corresponding regional categories according to the time distribution characteristics of the Internet of Vehicles data of each region; The third acquisition module 505 is used to obtain the regional category of the area where the charging pile is to be built and the parking charging related model corresponding to the regional category. The input of the parking charging related model is the number of electric vehicles parked during the peak parking period in the area, and the output is the total average charging power of the electric vehicles during the peak parking period; An input module 506 is used to input the actual number of electric vehicles parked during the peak parking period in the area where the charging pile is to be built into the parking charging related model to obtain the required total average power of electric vehicle charging; A fourth acquisition module 507 is used to acquire the current rated total charging power of the charging piles in the area where the charging piles are to be built based on the charging pile data; The demand module 508 is used to obtain the charging pile construction demand based on the current rated total charging power of the charging pile and the required total average power of the electric vehicle charging. The charging pile construction demand indicates whether new charging piles need to be built and / or the number of new charging piles that need to be built.

[0063] In one possible implementation, the division module 502 is used to obtain the parking location information and corresponding time information of the electric vehicle from the Internet of Vehicles data; determine the location of the parking lot and the parking quantity and time period distribution corresponding to each parking lot based on the parking location information and corresponding time information of the electric vehicle; divide the parking lots with similar parking quantity and time period distribution and adjacent locations into a parking lot group; and divide the selected area into multiple areas in such a way that one area includes one parking lot group.

[0064] In one possible implementation, the classification module 504 is used to draw an electric vehicle entry number curve and an electric vehicle parking number curve for each area with time as the horizontal axis and quantity as the vertical axis; and classify areas with a high overlap of regional parking peak periods of the electric vehicle entry number curve and / or a high overlap of regional parking peak periods of the electric vehicle parking number curve into the same area category.

[0065] In one possible implementation, the classification module 504 is also used to determine the areas with good charging pile data under each area category based on the charging pile data corresponding to the areas included in each area category. The areas with good charging pile data refer to areas where the charging pile utilization rate during the peak parking period in the area is within a set range; based on the Internet of Vehicles data and charging pile data in the areas with good charging pile data, a parking charging related model is formed.

[0066] In one possible implementation, the classification module 504 is used to obtain the number of electric vehicles parked during peak parking periods based on the Internet of Vehicles data and the total average charging power of electric vehicles during peak parking periods based on the charging pile data for each area with good charging pile data under the same area type; and form a parking and charging related model based on the correspondence between the number of electric vehicles parked and the total average charging power of electric vehicles in all areas under the same area type.

[0067] In a possible implementation, the classification module 504 is used to divide the number of parked electric vehicles into multiple number intervals, and fit a relationship between the number of parked electric vehicles and the total average charging power of the electric vehicles in each number interval.

[0068] In one possible implementation, the demand module 508 is also used to obtain the required rated total charging power of the charging pile based on the required total average charging power of the electric vehicle and the expected utilization rate; when the required rated total charging power of the charging pile is greater than the rated total charging power of the current charging pile, the charging pile construction demand is that new charging piles need to be built; and / or, the rated total charging power of the charging pile to be built is obtained by subtracting the rated total charging power of the current charging pile from the required total average charging power of the electric vehicle, and the number of new charging piles to be built is obtained based on the rated total charging power of the charging pile to be built and the charging pile charging power of the selected charging pile.

[0069] This device classifies regions according to the time distribution characteristics of the Internet of Vehicles data, and selects the corresponding parking charging related model according to the regional category of the area where the charging pile is to be built, and obtains relevant data from the Internet of Vehicles data and charging pile data of the area where the charging pile is to be built. The gap between the existing charging pile resources and the charging pile demand in the area is calculated from these, so as to obtain the charging pile construction demand in the area to guide the construction of charging piles. This application improves the accuracy of the plan for configuring charging piles, so that the investment and construction of charging piles are more in line with the actual needs of different regions, thereby ensuring the utilization rate of charging piles while meeting the charging needs of local electric vehicles.

[0070] It should be noted that the device provided in the above embodiment only uses the division of the above functional modules as an example to implement its functions. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and their specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0071] In an exemplary embodiment, a non-temporary computer-readable storage medium is also provided, in which at least one computer program is stored. The at least one computer program is loaded and executed by a processor of a computer device so that the computer implements any of the above-mentioned methods for configuring a charging pile.

[0072] In one possible implementation, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0073] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs any of the above-mentioned methods for configuring a charging pile.

[0074] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions. For example, the Internet of Vehicles data and charging pile data involved in this application are all obtained with full authorization.

[0075] It should be understood that the "plurality" mentioned in this article refers to two or more. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0076] It should be noted that the terms "first", "second", etc. (if any) in the specification and claims of the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0077] The above description is only an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for configuring a charging pile, characterized in that: The method comprises: Obtain Internet of Vehicles data and charging pile data within a selected period in a selected area; Dividing the selected area into a plurality of regions; Based on the Internet of Vehicles data, the number of electric vehicles entering and the number of electric vehicles parked in each area and each time period are obtained; Aggregating and classifying the multiple regions into corresponding region categories according to the time distribution characteristics of the Internet of Vehicles data of each region; Obtaining the regional category of the area where the charging pile is to be built and the parking charging related model corresponding to the regional category, wherein the input of the parking charging related model is the number of electric vehicles parked during the peak parking period in the area, and the output is the total average charging power of the electric vehicles during the peak parking period; Inputting the actual number of electric vehicles parked during the peak parking period in the area where the charging piles are to be built into the parking charging related model to obtain the required total average power of electric vehicle charging; Acquire the current rated total charging power of the charging piles in the area where the charging piles are to be built based on the charging pile data; The charging pile construction requirement is obtained based on the current rated total charging power of the charging pile and the required total average power for charging electric vehicles. The charging pile construction requirement indicates whether new charging piles need to be built and / or the number of new charging piles that need to be built.

2. The method according to claim 1, characterized in that The selected area is divided into multiple areas, including: Acquire parking location information and corresponding time information of the electric vehicle from the Internet of Vehicles data; Determine the location of the parking lot and the parking quantity and time period distribution corresponding to each parking lot based on the parking location information and corresponding time information of the electric vehicle; The parking lots with similar parking quantity distribution in time periods and adjacent locations are divided into a parking lot group; The selected area range is divided into the plurality of areas in such a manner that one area includes one parking lot group.

3. The method according to claim 1, characterized in that The aggregating and classifying the multiple regions into corresponding region categories according to the time distribution characteristics of the Internet of Vehicles data of each region includes: With time as the horizontal axis and quantity as the vertical axis, a curve of the number of electric vehicles entering and a curve of the number of electric vehicles parking in each of the said areas are plotted; Areas with a high overlap of the regional entry peak hours of the electric vehicle entry quantity curve and / or a high overlap of the regional parking peak hours of the electric vehicle parking quantity curve are classified into the same area category.

4. The method according to claim 1, characterized in that After aggregating and classifying the multiple regions into corresponding region categories according to the time distribution characteristics of the Internet of Vehicles data of each region, the method further includes: Determine the area with good charging pile data under each area category based on the charging pile data corresponding to the area included in each area category, wherein the area with good charging pile data refers to the area where the charging pile utilization rate of the area during the peak parking period of the area is within a set range; The parking charging related model is formed based on the Internet of Vehicles data and charging pile data in the area with good charging pile data.

5. The method according to claim 4, characterized in that The forming of the parking charging related model based on the Internet of Vehicles data and the charging pile data in the area with good charging pile data includes: For each area with good charging pile data under the same area type, the number of electric vehicles parked during the peak parking period is obtained based on the Internet of Vehicles data, and the total average charging power of electric vehicles during the peak parking period is obtained based on the charging pile data; The parking and charging related model is formed according to the corresponding relationship between the number of electric vehicle parking and the total average power of electric vehicle charging in all areas under the same area type.

6. The method according to claim 5, characterized in that The forming of the parking charging related model according to the correspondence between the number of electric vehicle parking and the total average power of electric vehicle charging in all areas of the same area type includes: The number of parked electric vehicles is divided into a plurality of number intervals, and a relationship between the number of parked electric vehicles and the total average charging power of the electric vehicles is fitted in each number interval.

7. The method according to claim 1, characterized in that The charging pile construction requirement is obtained based on the current rated total charging power of the charging pile and the required total average power of the electric vehicle charging, and the charging pile construction requirement indicates whether new charging piles need to be built and / or the number of new charging piles that need to be built, including: Obtaining the required total rated charging power of the charging pile based on the required total average charging power of the electric vehicle and the expected utilization rate; When the required total rated charging power of the charging pile is greater than the current total rated charging power of the charging pile, the charging pile construction requirement is that a new charging pile needs to be built; and / or, The rated total charging power of the charging piles to be built is obtained by subtracting the current rated total charging power of the charging piles from the required total average charging power of the electric vehicles, and the number of new charging piles to be built is obtained based on the rated total charging power of the charging piles to be built and the charging power of the selected charging piles.

8. A device for configuring a charging pile, characterized in that: The device comprises: The first acquisition module is used to acquire the Internet of Vehicles data and charging pile data within a selected period range within a selected area; A division module, used for dividing the selected area into a plurality of areas; A second acquisition module is used to acquire the number of electric vehicles entering and the number of electric vehicles parked in each area and each time period based on the Internet of Vehicles data; A classification module, configured to aggregate and classify the plurality of regions into corresponding region categories according to the time distribution characteristics of the Internet of Vehicles data of each region; A third acquisition module is used to obtain the regional category of the area where the charging pile is to be built and the parking charging related model corresponding to the regional category, the input of the parking charging related model is the number of electric vehicles parked during the regional parking peak period, and the output is the total average charging power of the electric vehicles during the parking peak period; An input module, used for inputting the actual number of electric vehicles parked during the peak parking period in the area where the charging pile is to be built into the parking charging related model to obtain the required total average power of electric vehicle charging; A fourth acquisition module, configured to acquire the current rated total charging power of the charging piles in the area where the charging piles are to be built based on the charging pile data; The demand module is used to obtain the charging pile construction demand based on the current rated total charging power of the charging pile and the required total average power of electric vehicle charging. The charging pile construction demand indicates whether new charging piles need to be built and / or the number of new charging piles that need to be built.

9. A computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the method for configuring a charging pile as claimed in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is loaded and executed by a processor to implement the method for configuring a charging pile as described in any one of claims 1 to 7.

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