An auxiliary management method, device and equipment of a charging pile and a medium

Abstract

The application relates to the financial technology field and provides an auxiliary management method for charging piles, which comprises the following steps: acquiring initial charging pile set data; performing average processing on the charging pile data of site data to generate intermediate charging pile data; collecting the intermediate charging pile data to generate intermediate charging pile set data; acquiring initial flow set data; acquiring daily charging income data of the site data according to the transaction date data in the flow data, acquiring average flow data in the site data according to the daily charging income data; collecting the average flow data to obtain intermediate flow set data; and sorting the intermediate charging pile set data according to the intermediate flow set data to generate site recommendation data. The auxiliary management method for charging piles can help relevant enterprises to manage charging piles and improve the income.

Description

Technical Field

[0001] This invention relates to the field of financial technology, and in particular to an auxiliary management method, device, equipment and medium for charging piles. Background Technology

[0002] With the booming development of the new energy vehicle industry, more and more financial institutions are participating in businesses involving charging pile assets, such as financial leasing and bank loans. The operating revenue of charging pile assets directly affects the repayment ability of related companies and the safety of financial institutions' investments. Currently, related companies mainly use on-site inspections, fund account supervision, and operational data collection for asset management of charging pile businesses. On-site inspections rely on manual data collection, fund account supervision involves monitoring bank transaction data, and operational data collection involves monitoring the operation of charging pile assets. These three methods can only monitor transaction data and cannot effectively improve the profitability of companies with low charging utilization rates and low charging revenue. Summary of the Invention

[0003] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide an auxiliary management method, device, equipment and medium for charging piles, which can help relevant enterprises manage charging piles and improve revenue.

[0004] In a first aspect, the present invention provides an auxiliary management method for charging piles, comprising:

[0005] Acquire initial charging pile set data, which includes multiple location data, each location data includes multiple charging pile data, and the charging pile data includes charging power data, charging duration data, and charging time data.

[0006] The average data of multiple charging piles in the aforementioned location data is processed to generate intermediate charging pile data.

[0007] The data from multiple intermediate charging piles are aggregated to generate an intermediate charging pile set data.

[0008] Obtain initial transaction data, which includes multiple transaction data sets. Each charging pile data set corresponds to one transaction data set, and the transaction data set includes transaction date data and charging revenue data.

[0009] Based on the transaction date data in the transaction data, obtain the daily charging revenue data of the venue data, and based on the daily charging revenue data, obtain the average transaction data within the venue data, wherein the daily charging revenue data is the charging revenue data of all charging piles within the venue data on a single day;

[0010] The average flow data from multiple sources are aggregated to obtain intermediate flow set data;

[0011] The intermediate charging pile data is sorted based on the intermediate flow data to generate location recommendation data.

[0012] Secondly, the present invention provides an auxiliary management device for charging piles, comprising:

[0013] The charging pile set acquisition module is used to acquire initial charging pile set data, which includes multiple location data, multiple charging pile data, and charging pile data including charging power data, charging duration data, and charging time data.

[0014] The first processing module is used to average the multiple charging pile data of the location data to generate intermediate charging pile data.

[0015] The first aggregation module is used to aggregate the data of multiple intermediate charging piles to generate intermediate charging pile set data.

[0016] The transaction data acquisition module is used to acquire initial transaction data, which includes multiple transaction data. Each charging pile data corresponds to one transaction data. The transaction data includes transaction date data and charging revenue data.

[0017] The second processing module is used to obtain the daily charging revenue data of the venue data based on the transaction date data in the transaction data, and to obtain the average transaction data in the venue data based on the daily charging revenue data, wherein the daily charging revenue data is the charging revenue data of all charging piles in the venue data on a single day.

[0018] The second aggregation module is used to aggregate multiple average flow data to obtain intermediate flow set data; and

[0019] The sorting module is used to sort the intermediate charging pile set data according to the intermediate flow set data and generate location recommendation data.

[0020] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-mentioned auxiliary management method for charging piles.

[0021] Fourthly, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the steps of the above-mentioned auxiliary management method for charging piles.

[0022] As described above, the present invention provides an auxiliary management method, device, equipment and medium for charging piles, which can sort the average daily revenue of different locations according to different dates and generate location recommendation data. At this time, relevant enterprises can manage charging piles according to the location recommendation data and improve revenue. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 The diagram shown illustrates an application environment of an auxiliary management method for charging piles according to an embodiment of the present invention.

[0025] Figure 2 The diagram shown is a flowchart illustrating an auxiliary management method for charging piles according to an embodiment of the present invention.

[0026] Figure 3 yes Figure 2 A schematic diagram of a specific implementation method for step S20.

[0027] Figure 4 yes Figure 2 A schematic diagram of a specific implementation of step S70.

[0028] Figure 5 This is a schematic diagram of the auxiliary management device for a charging pile in one embodiment of the present invention.

[0029] Figure 6 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention.

[0030] Figure 7 This is another structural schematic diagram of a computer device according to one embodiment of the present invention.

[0031] Component designation explanation:

[0032] 10. Charging pile acquisition module; 20. First processing module; 30. First aggregation module; 40. Flow acquisition module; 50. Second processing module; 60. Second aggregation module; 70. Sorting module; 80. Push module. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] The auxiliary management method for charging piles provided in this embodiment of the invention can be applied to, for example... Figure 1 In this application environment, the client can communicate with the server via a network. The server can obtain initial charging pile set data from the client and process it to obtain intermediate charging pile set data and intermediate flow set data, which correspond to each other. The intermediate charging pile set data includes multiple intermediate charging pile data, including average single-gun charging utilization rate data, average daily charging volume per single gun data, charging pile online rate data, and charging station online rate data. The intermediate flow set data includes multiple average flow data. Then, the data for different locations can be sorted according to the average flow data, and location recommendation data can be generated so that relevant enterprises can refer to the pricing of charging piles based on the location recommendation data. The client can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a dedicated server or a server cluster consisting of multiple servers. The invention will be described in detail below through specific embodiments.

[0035] Please see Figure 2 As shown, Figure 2 A flowchart illustrating an auxiliary management method for charging piles provided in an embodiment of the present invention is shown. The processing method may include the following steps:

[0036] S10. Obtain initial charging pile set data. The initial charging pile set data includes multiple location data, the location data includes multiple charging pile data, and the charging pile data includes charging pile location data, charging power data, charging duration data, and charging time data.

[0037] In one embodiment of the present invention, the initial charging pile data set may include multiple location data, which can represent the location information of charging stations in different areas. Each location data set may include multiple charging pile data, which can be related data of a specific charging pile. The charging pile data may include charging pile location data, charging power data, charging duration data, and charging time data. Specifically, the charging pile location data can be the location of the charging pile, which can be obtained by installing a location sensor on the charging pile. The charging power data can be the amount of electricity consumed by the charging pile, which can be collected by installing a corresponding sensor on the charging meter of the charging pile. The charging duration data can be the duration consumed during charging, which can be collected by installing a corresponding sensor on the charging meter. The charging time data can be the time point when the charging pile starts charging and the time point when charging stops, which can be collected by installing a corresponding sensor on the charging meter. After obtaining the location data, charging power data, charging duration data, and charging time data for each charging pile, the data from multiple charging piles can be aggregated to obtain the corresponding data for all charging piles within a given location, i.e., location data. After obtaining data from multiple locations, the data from these locations can be aggregated to obtain an initial set of charging pile data. The client can then send this initial set of charging pile data to the server, which can then process it accordingly.

[0038] S20. Average the data of multiple charging piles at the same location to generate intermediate charging pile data.

[0039] Please see Figure 3 As shown, in one embodiment of the present invention, when step S20 is executed, the sub-steps of step S20 may include:

[0040] S21. Average the data of multiple charging piles in the location data to obtain the average single-gun charging utilization rate data, the average daily charging volume of a single gun data, and the charging pile online rate data.

[0041] In one embodiment of the present invention, since the same location data can include multiple charging pile data, and each charging pile data can include charging pile location data, charging power data, charging duration data, and charging time data, all charging pile data within the same location data can be aggregated, and average single-gun charging utilization rate data, average daily charging power per single gun data, charging pile online rate data, and charging station online rate data can be calculated. The average single-gun charging utilization rate data can be the charging utilization rate of each charging pile, and can be expressed as a / (b 24) 'a' can represent the sum of charging times for all charging stations in hours, and 'b' can represent the number of charging stations. Average daily charging capacity per charging station can be expressed as c / b, where c represents the sum of electricity consumed by all charging stations, and 'b' can represent the number of charging stations. Charging station online rate can be expressed as d / b, where 'd' represents the number of online charging stations, and 'b' can represent the number of charging stations. This is because some charging stations are online, while others may be offline due to various malfunctions. Charging station online rate can be expressed as e / f, where e represents the number of online charging stations, and 'f' can represent the number of charging stations. This is because some charging stations are online, while others may be offline due to various malfunctions.

[0042] S22. Determine whether the average single-gun charging utilization rate data is less than the preset charging utilization rate threshold. If it is less than the charging utilization rate threshold, generate the first type of alarm information and summarize the average single-gun charging utilization rate data and the first type of alarm information. If it is not less than the charging utilization rate threshold, summarize the average single-gun charging utilization rate data. The first type of alarm information indicates that the average single-gun charging utilization rate data of the location data is too low.

[0043] In one embodiment of the present invention, after generating average single-gun charging utilization rate data, this data can be compared with a preset charging utilization rate threshold to determine whether the average single-gun charging utilization rate of the location is normal. When the average single-gun charging utilization rate data is less than the preset threshold, a first type of alarm message can be generated, indicating that the average single-gun charging utilization rate of the location is too low, meaning that the location may be experiencing low user usage of charging stations due to high pricing or poor location. At this time, the average single-gun charging utilization rate data and the first type of alarm message can be summarized. The charging utilization rate threshold can be manually set by staff according to actual needs, or it can be generated by processing historical data. When the average single-gun charging utilization rate data is not less than the threshold, it indicates that the average single-gun charging utilization rate of the location is normal, meaning that there are many users at the location, and the average single-gun charging utilization rate data can be summarized.

[0044] S23. Determine whether the average daily charging amount per charging station is less than the preset charging amount threshold. If it is less than the charging amount threshold, generate a second type of alarm information. Summarize the average daily charging amount per charging station and the second type of alarm information. The second type of alarm information indicates that the average daily charging amount per charging station of the charging pile is too low. If it is not less than the charging amount threshold, summarize the average daily charging amount per charging station.

[0045] In one embodiment of the present invention, after generating the average daily charging volume data per charging station, this data can be compared with a preset charging volume threshold to determine whether the average daily charging volume data for that location is normal. When the average daily charging volume data per charging station is less than the preset charging volume threshold, a second type of alarm message can be generated, indicating that the average daily charging volume data per charging station for that location is too low, meaning that the location may be experiencing low user usage of charging stations due to reasons such as high pricing or poor location. At this time, the average daily charging volume data per charging station and the second type of alarm message can be summarized. The charging volume threshold can be manually set by staff according to actual needs, or it can be generated based on historical data. When the average daily charging volume data per charging station is not less than the charging volume threshold, it indicates that the average daily charging volume data per charging station for that location is normal, meaning that there are many users at that location, and at this time, the average daily charging volume data per charging station can be summarized.

[0046] S24. Determine whether the charging pile online rate data is less than the preset charging pile online rate threshold. If it is less than the charging pile online rate threshold, generate a third type of alarm information and summarize the charging pile online rate data and the third type of alarm information. The third type of alarm information indicates that the charging pile online rate data is too low. If it is not less than the charging pile online rate threshold, summarize the charging pile online rate data.

[0047] In one embodiment of the present invention, after generating charging pile online rate data, the charging pile online rate data can be compared with a preset charging pile online rate threshold to determine whether the charging pile online rate data for that location is normal. When the charging pile online rate data is less than the preset charging pile online rate threshold, a third type of alarm information can be generated, indicating that the charging pile online rate data for that location is too low, meaning that the location may have low user usage of the charging piles due to reasons such as high pricing or poor location. At this time, the charging pile online rate data and the third type of alarm information can be summarized. The charging pile online rate threshold can be manually set by staff according to actual needs, or it can be generated by processing historical data. When the charging pile online rate data is not less than the charging pile online rate threshold, it indicates that the charging pile online rate data for that location is normal, meaning that there are many users for that location, and at this time, the charging pile online rate data can be summarized.

[0048] In one embodiment of the present invention, the average single-gun charging utilization rate data, the average daily charging volume data per single gun, and the charging pile online rate data can be judged sequentially, or they can be judged sequentially, or they can be judged sequentially, along with the charging pile online rate data, the average daily charging volume data per single gun, and the average single-gun charging utilization rate data. The order in which these data are judged is not limited, as long as all three data points are judged.

[0049] S25. Summarize the average single-gun charging utilization rate data, the average daily charging volume per single gun data, and the charging pile online rate data to generate intermediate charging pile data.

[0050] In one embodiment of the present invention, after judging the average single-gun charging utilization rate data, the average daily charging volume data per single gun, the charging pile online rate data, and the charging station online rate data, the average single-gun charging utilization rate data, the average daily charging volume data per single gun, the charging pile online rate data, and the charging station online rate data can be summarized to generate intermediate charging pile data. If there are first-type, second-type, and third-type alarm information, the corresponding alarm information is also summarized into the intermediate charging pile data. The first-type alarm information can be associated with the average single-gun charging utilization rate data. The second-type alarm information can be associated with the average daily charging volume data per single gun. The third-type alarm information can be associated with the charging pile online rate data.

[0051] S30. Summarize the intermediate charging pile data from different locations to generate intermediate charging pile set data.

[0052] In one embodiment of the present invention, after averaging multiple charging pile data within a certain location data set, corresponding intermediate charging pile data can be generated. The intermediate charging pile data can correspond to a single location data set. After processing the location data set, the same processing can be performed on other location data sets to generate different intermediate charging pile data sets. These other location data sets may be operated by other related enterprises; therefore, location data from all related enterprises within the same city can be obtained through banks, etc. At this point, each location data set can generate one intermediate charging pile data set. Subsequently, the intermediate charging pile data sets from different location data sets can be aggregated to generate an intermediate charging pile set data set, which includes multiple intermediate charging pile data sets. Further processing of the intermediate charging pile set data set can yield the city's average single-gun charging utilization rate data, average daily charging volume per single gun data, and charging pile online rate data.

[0053] S40. Obtain initial transaction data. The initial transaction data includes multiple transaction data, which include transaction date data, charging revenue data, payer account data, payee account data, summary data, and usage data. Each charging pile data corresponds to one transaction data.

[0054] In one embodiment of the present invention, the initial transaction data set may include transaction data from multiple locations, each location may include multiple charging piles, and each charging pile may have one transaction data set. The transaction data for charging piles can be obtained through banks, etc. The transaction data may include transaction date data, charging revenue data, payer account data, payee account data, summary data, and usage data. The transaction date data may be the transaction time recorded when the charging pile is used. The charging revenue data may be the daily revenue of the charging pile or the daily revenue of the charging location. The payer account data may be the user's payment account data, such as Alipay, WeChat Pay, or UnionPay, which generates a payment account data set upon payment. The payee account data may be the receiving account data of the relevant enterprise, which may be received through Alipay, WeChat Pay, or UnionPay, generating a receiving account data set upon receiving payment. The summary data may be a summary description of the order. The usage data may be the purpose of charging, such as charging new energy vehicles or electric vehicles.

[0055] S50. Based on the transaction date data, obtain the charging revenue data for the same location. The daily charging revenue data includes the number of daily transactions, the amount of a single transaction, the total amount of transactions on the day, and settlement characteristic data. Based on the daily charging revenue data, obtain the average transaction data within the same location.

[0056] In one embodiment of the present invention, after obtaining the initial transaction data set, daily charging revenue data for the same location can be obtained based on the transaction date data. Daily charging revenue data can be obtained through transaction data, which represents the charging revenue of all charging piles within the location data on a given day. Daily charging revenue data may include daily transaction count data, single transaction amount data, total daily transaction amount data, and settlement characteristic data. Specifically, the daily transaction count data can represent the total number of times multiple charging piles within the same location data are used; that is, each completed transaction generates one transaction count. The single transaction amount data can represent the revenue generated by a single charging pile after completing a transaction. The total daily transaction amount data can represent the total revenue of all charging piles within the same location data within a single day. The settlement characteristic data can represent different settlement methods for the charging pile data of related enterprises, such as settlement by single transaction, settlement by day, or settlement by month. After obtaining the daily charging revenue data, the average revenue per unit area within the same location can be calculated, denoted as x / y. Here, x represents the total revenue for that location on that day, and y represents the number of charging stations within that location. This yields the average revenue per unit area for a single day. Subsequently, based on date data, the same processing can be applied to the same location data for different dates to obtain the daily average revenue per unit area for different dates.

[0057] S60. Summarize the average flow data from multiple locations to obtain intermediate flow set data.

[0058] In one embodiment of the present invention, after obtaining the average transaction volume data for a certain location on different dates, the same processing can be performed on other location data to obtain the daily average transaction volume data for different locations on different dates. For example, on January 1, 2022, average transaction volume data for different locations can be generated, and on January 2, 2022, average transaction volume data for another different location can be generated. Then, the average transaction volume data for different locations can be summarized according to date to obtain intermediate transaction volume set data.

[0059]

[0060] Table 1. Reference for the Optimal Pricing of DC Fast Charging Stations in City X

[0061] S70. Sort the intermediate charging pile data according to the intermediate flow data and generate location recommendation data.

[0062] Please see Figure 4 As shown, in one embodiment of the present invention, the sub-step of step S70 may include:

[0063] S71. Based on multiple average transaction data within a specific transaction date, sort the corresponding multiple location data to generate initial recommendation data;

[0064] S72. Based on the average transaction data of the remaining transaction dates, sort the corresponding multiple venue data to generate multiple intermediate recommendation data.

[0065] S73. Summarize the initial recommendation data and multiple recommendation data to generate location recommendation data.

[0066] In one embodiment of the present invention, different location data can be sorted based on intermediate transaction data to filter out locations with higher revenue. When sorting different location data, the average transaction data of multiple locations can be sorted in descending order according to different dates. For example, on January 1, 2022, there will be multiple location data, each with average transaction data, and the values ​​of these average transaction data will be different. The location data can then be sorted according to the value of the average transaction data. For other dates, the sorting can be performed sequentially using this method. After sorting is complete, a location recommendation dataset can be generated.

[0067] S80. Export the recommended venue data.

[0068] In one embodiment of the present invention, after generating location recommendation data, the data can be sent to a client and displayed to relevant enterprises. Upon receiving the location recommendation data, relevant enterprises can manage charging stations based on the top-ranked locations within the data, thereby increasing revenue.

[0069] As can be seen, in the above scheme, the average daily revenue of different locations can be sorted according to different dates, and location recommendation data can be generated. At this time, relevant enterprises can price the charging piles they manage based on the location recommendation data to improve the corresponding revenue.

[0070] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0071] Please see Figure 5As shown, the present invention also provides an auxiliary management device for charging piles, which corresponds one-to-one with the auxiliary management method for charging piles in the above embodiments. This processing device may include a charging pile set acquisition module 10, a first processing module 20, a first aggregation module 30, a flow set acquisition module 40, a second processing module 50, a second aggregation module 60, a sorting module 70, and a push module 80. Detailed descriptions of each functional module are as follows:

[0072] The charging pile set acquisition module 10 is used to acquire initial charging pile set data. The initial charging pile set data includes multiple location data, the location data includes multiple charging pile data, and the charging pile data includes charging pile location data, charging power data, charging duration data, and charging time data.

[0073] The first processing module 20 is used to average the data of multiple charging piles in the same location to generate intermediate charging pile data.

[0074] The first aggregation module 30 is used to perform average processing on the data of other locations in sequence and generate multiple intermediate charging pile data. The intermediate charging pile data of different locations are aggregated to generate intermediate charging pile set data.

[0075] The transaction data acquisition module 40 is used to acquire initial transaction data, which includes multiple transaction data, including transaction date data, charging revenue data, payer account data, payee account data, summary data and usage data. Each charging pile data corresponds to one transaction data.

[0076] The second processing module 50 is used to obtain daily charging revenue data for the same location based on transaction date data. The daily charging revenue data includes daily transaction count data, single transaction amount data, total transaction amount data for the day, and settlement characteristic data. Based on the daily charging revenue data, the average transaction data within the same location is obtained.

[0077] The second aggregation module 60 is used to aggregate the average flow data of multiple locations to obtain intermediate flow set data;

[0078] The sorting module 70 is used to sort the intermediate charging pile set data according to the intermediate flow set data and generate location recommendation data;

[0079] The push module 80 is used to send venue recommendation data to the client.

[0080] In one embodiment of the present invention, the first processing module 20 is specifically used for:

[0081] Average data from multiple charging piles at the same location are processed to obtain average single-gun charging utilization rate, average daily charging volume per single gun, charging pile online rate, and charging station online rate.

[0082] Determine whether the average single-gun charging utilization rate data is less than a preset charging utilization rate threshold. If it is less than the charging utilization rate threshold, generate a first type of alarm information. Summarize the average single-gun charging utilization rate data and the first type of alarm information. The first type of alarm information indicates that the average single-gun charging utilization rate data of the location data is too low. If it is not less than the charging utilization rate threshold, summarize the average single-gun charging utilization rate data.

[0083] Determine whether the average daily charging amount per charging station is less than a preset charging amount threshold. If it is less than the charging amount threshold, generate a second type of alarm information. Summarize the average daily charging amount per charging station data and the second type of alarm information. The second type of alarm information indicates that the average daily charging amount per charging station data of the charging station is too low. If it is not less than the charging amount threshold, summarize the average daily charging amount per charging station data.

[0084] Determine whether the charging pile online rate data is less than a preset charging pile online rate threshold. If it is less than the charging pile online rate threshold, generate a third type of alarm information. Summarize the charging pile online rate data and the third type of alarm information. The third type of alarm information indicates that the charging pile online rate data is too low. If it is not less than the charging pile online rate threshold, summarize the charging pile online rate data.

[0085] In one embodiment of the present invention, the sorting module 70 is specifically used for:

[0086] Based on multiple average transaction data within a specific transaction date, sort the corresponding data from multiple locations to generate initial recommendation data;

[0087] Based on the average transaction data within the remaining transaction dates, the corresponding data from multiple locations are sorted to generate multiple intermediate recommendation data.

[0088] The initial recommendation data and multiple recommendation data are aggregated to generate location recommendation data.

[0089] This invention provides an auxiliary management device for charging piles, which can sort the average daily revenue of different locations according to different dates and generate location recommendation data. At this time, relevant enterprises can manage charging piles based on the location recommendation data to improve revenue.

[0090] Specific limitations regarding the auxiliary management device for charging piles can be found in the limitations of the auxiliary management method for charging piles mentioned above, and will not be repeated here. Each module in the aforementioned auxiliary management device for charging piles can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0091] Please see Figure 6 As shown, the present invention also provides a computer device, which can be a server. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a charging pile auxiliary management method on the server side.

[0092] Please see Figure 7 As shown, the present invention also provides another computer device, which can be a client. This computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. The processor of this computer device provides computing and control capabilities. The memory of this computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of this computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a charging pile auxiliary management method on the server side.

[0093] In one embodiment of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it performs the following steps:

[0094] Acquire initial charging pile data, which includes data from multiple locations, data from multiple charging piles, and data from charging piles including charging pile location data, charging power data, charging duration data, and charging time data.

[0095] Average the data of multiple charging piles at the same location to generate intermediate charging pile data.

[0096] The data from the remaining locations are averaged sequentially to generate multiple intermediate charging pile data sets. The intermediate charging pile data from different locations are then aggregated to generate an intermediate charging pile set.

[0097] Obtain initial transaction data, which includes multiple transaction data sets. The transaction data sets include transaction date data, charging revenue data, payer account data, payee account data, summary data, and usage data. Each charging pile data set corresponds to one transaction data set.

[0098] Based on transaction date data, obtain daily charging revenue data for the same location. Daily charging revenue data includes daily transaction count data, single transaction amount data, total transaction amount data for the day, and settlement characteristic data. Based on daily charging revenue data, obtain average transaction data within the same location.

[0099] The average flow data from multiple locations is aggregated to obtain intermediate flow set data;

[0100] The intermediate charging pile data is sorted based on the intermediate flow data to generate location recommendation data;

[0101] Send the venue recommendation data to the client.

[0102] In one embodiment of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the following steps:

[0103] Acquire initial charging pile data, which includes data from multiple locations, data from multiple charging piles, and data from charging piles including charging pile location data, charging power data, charging duration data, and charging time data.

[0104] Average the data of multiple charging piles at the same location to generate intermediate charging pile data.

[0105] The data from the remaining locations are averaged sequentially to generate multiple intermediate charging pile data sets. The intermediate charging pile data from different locations are then aggregated to generate an intermediate charging pile set.

[0106] Obtain initial transaction data, which includes multiple transaction data sets. The transaction data sets include transaction date data, charging revenue data, payer account data, payee account data, summary data, and usage data. Each charging pile data set corresponds to one transaction data set.

[0107] Based on transaction date data, obtain daily charging revenue data for the same location. Daily charging revenue data includes daily transaction count data, single transaction amount data, total transaction amount data for the day, and settlement characteristic data. Based on daily charging revenue data, obtain average transaction data within the same location.

[0108] The average flow data from multiple locations is aggregated to obtain intermediate flow set data;

[0109] The intermediate charging pile data is sorted based on the intermediate flow data to generate location recommendation data;

[0110] Send the venue recommendation data to the client.

[0111] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0112] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0113] In the description of this specification, the references to terms such as "this embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0114] The embodiments of the present invention disclosed above are merely illustrative of the invention. The embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An auxiliary management method for charging piles, characterized in that, include: Acquire initial charging pile set data, which includes multiple location data, each location data includes multiple charging pile data, and the charging pile data includes charging power data, charging duration data, and charging time data. The average data of multiple charging piles in the aforementioned location data is processed to generate intermediate charging pile data. The data from multiple intermediate charging piles are aggregated to generate an intermediate charging pile set data. Obtain initial transaction data, which includes multiple transaction data sets. Each charging pile data set corresponds to one transaction data set, and the transaction data set includes transaction date data and charging revenue data. Based on the transaction date data in the transaction data, obtain the daily charging revenue data of the venue data, and based on the daily charging revenue data, obtain the average transaction data within the venue data, wherein the daily charging revenue data is the charging revenue data of all charging piles within the venue data on a single day; The average flow data from multiple sources are aggregated to obtain intermediate flow set data; The intermediate charging pile data is sorted based on the intermediate flow data to generate location recommendation data.

2. The auxiliary management method for charging piles according to claim 1, characterized in that, The step of averaging multiple charging pile data points from the location data to generate intermediate charging pile data includes: The average data of multiple charging piles in the location data is processed to obtain average single-gun charging utilization rate data, average single-gun daily charging volume data, and charging pile online rate data. The average single-gun charging utilization rate data represents the charging utilization rate of each charging pile data, the average single-gun daily charging volume data represents the daily power consumption of each charging pile data, and the charging pile online rate data represents the ratio of the normally operating charging pile data to all charging pile data. The average single-gun charging utilization rate data, the average daily charging volume per single gun data, and the charging pile online rate data are summarized to generate intermediate charging pile data.

3. The auxiliary management method for charging piles according to claim 2, characterized in that, After the step of averaging the data from multiple charging piles at the location to obtain average single-gun charging utilization rate data, average daily charging volume per single gun data, and charging pile online rate data, the method further includes: Determine whether the average single-gun charging utilization rate data is less than a preset charging utilization rate threshold; If the average single-gun charging utilization rate is less than the charging utilization rate threshold, a first type of alarm information is generated. The average single-gun charging utilization rate data and the first type of alarm information are summarized. The first type of alarm information indicates that the average single-gun charging utilization rate data of the location data is too low. If the average single-gun charging utilization rate is not less than the charging utilization rate threshold, the average single-gun charging utilization rate data is summarized.

4. The auxiliary management method for charging piles according to claim 3, characterized in that, After the step of summarizing the average single-gun charging utilization rate data if it is not less than the charging utilization rate threshold, the method further includes: Determine whether the average daily charging amount per gun is less than a preset charging amount threshold. If the charging amount is less than the charging amount threshold, a second type of alarm information is generated. The average daily charging amount data per charging gun and the second type of alarm information are summarized. The second type of alarm information indicates that the average daily charging amount data per charging gun of the charging pile is too low. If the charging amount is not less than the charging amount threshold, the average daily charging amount data per gun is summarized.

5. The auxiliary management method for charging piles according to claim 4, characterized in that, After the step of summarizing the average daily charging amount data per gun if it is not less than the charging amount threshold, the method further includes: Determine whether the charging pile online rate data is less than a preset charging pile online rate threshold; If the online rate is less than the charging pile online rate threshold, a third type of alarm information is generated. The charging pile online rate data and the third type of alarm information are summarized. The third type of alarm information indicates that the charging pile online rate data is too low. If the online rate is not less than the charging pile online rate threshold, the charging pile online rate data is summarized.

6. The auxiliary management method for charging piles according to claim 1, characterized in that, The step of sorting the intermediate charging pile set data according to the intermediate flow set data to generate location recommendation data includes: Based on multiple average transaction data within a specific transaction date, sort the corresponding multiple intermediate charging pile sets to generate initial recommendation data; Based on the average transaction data within the remaining transaction date data, the corresponding intermediate charging pile sets are sorted to generate multiple intermediate recommendation data. The initial recommendation data and multiple intermediate recommendation data are aggregated to generate location recommendation data.

7. The auxiliary management method for charging piles according to claim 1, characterized in that, After the step of sorting different intermediate charging pile sets based on the intermediate flow set data to generate location recommendation data, the method further includes: exporting the location recommendation data.

8. An auxiliary management device for a charging pile, characterized in that, include: The charging pile set acquisition module is used to acquire initial charging pile set data, which includes multiple location data, multiple charging pile data, and charging pile data including charging power data, charging duration data, and charging time data. The first processing module is used to average the multiple charging pile data of the location data to generate intermediate charging pile data. The first aggregation module is used to aggregate the data of multiple intermediate charging piles to generate intermediate charging pile set data. The transaction data acquisition module is used to acquire initial transaction data, which includes multiple transaction data. Each charging pile data corresponds to one transaction data. The transaction data includes transaction date data and charging revenue data. The second processing module is used to obtain the daily charging revenue data of the venue data based on the transaction date data in the transaction data, and to obtain the average transaction data in the venue data based on the daily charging revenue data, wherein the daily charging revenue data is the charging revenue data of all charging piles in the venue data on a single day. The second aggregation module is used to aggregate multiple average flow data to obtain intermediate flow set data; and The sorting module is used to sort the intermediate charging pile set data according to the intermediate flow set data and generate location recommendation data.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the auxiliary management method for charging piles as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the auxiliary management method for the charging pile as described in any one of claims 1 to 7.

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