Charging station network distribution method, device and electronic equipment

Abstract

The present application discloses a distribution network method, device and electronic equipment for a charging station. The method comprises: obtaining historical charging data corresponding to the vehicle used by the target object, wherein the historical charging data at least includes the original power distribution strategy of the charging station; determining the spatial domain viscosity coefficient and the temporal domain viscosity coefficient based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent the relationship between the location of the vehicle used by the target object and the selection of the charging station, and the temporal domain viscosity coefficient is used to represent the relationship between the charging time of the vehicle used by the target object and the selection of the charging station; determining the charging load safety domain of the charging station based on the spatial domain viscosity coefficient and the temporal domain viscosity coefficient; adjusting the original power distribution strategy based on the charging load safety domain to obtain the target power distribution strategy of the charging station. The present application solves the technical problem that the site selection problem of charging piles in the related art mostly considers the charging electricity price and the travel distance required for charging, but often ignores the impact of the user's charging habits on charging behavior.

Description

Technical Field

[0001] The present application relates to the field of electric power, and more specifically, to a method, device, and electronic equipment for distributing a network of a charging station. Background Art

[0002] Amidst the booming new energy vehicle industry, the rational location and layout of charging piles (or charging stations), as critical infrastructure supporting the widespread adoption of electric vehicles, are crucial. Currently, planning for charging pile locations generally focuses on analyzing the economics of charging electricity prices and the minimum distance between charging stations and users' daily commutes, aiming to reduce charging costs and improve convenience. However, this process often fails to fully consider the profound impact of user charging habits on charging behavior. User charging habits, including preferred charging time, frequency, and battery anxiety, are directly linked to the actual efficiency and satisfaction of charging piles. Ignoring these factors can lead to a disconnect between charging pile layout and actual demand, resulting in wasted resources and inconvenience for users.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] The embodiments of the present application provide a network distribution method, device, and electronic equipment for a charging station, so as to at least solve the technical problem that the site selection of charging piles in the related art mainly considers the charging electricity price and the travel distance required for charging, but often ignores the impact of user charging habits on charging behavior.

[0005] According to one aspect of an embodiment of the present application, a network distribution method for a charging station is provided, comprising: obtaining historical charging data corresponding to a vehicle used by a target object, wherein the historical charging data includes at least an original power distribution strategy of the charging station; determining a spatial domain viscosity coefficient and a temporal domain viscosity coefficient based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent the relationship between the location of the vehicle used by the target object and the selection of the charging station, and the temporal domain viscosity coefficient is used to represent the relationship between the charging time of the vehicle used by the target object and the selection of the charging station; determining a charging load safety domain of the charging station based on the spatial domain viscosity coefficient and the temporal domain viscosity coefficient; and adjusting the original power distribution strategy based on the charging load safety domain to obtain a target power distribution strategy for the charging station.

[0006] Optionally, determining the spatial domain viscosity coefficient based on historical charging data includes: obtaining the first duration of the first vehicle from the starting point to the end point of each charging station in the historical charging data to obtain a first duration sequence, wherein the first duration sequence is determined by the first duration, the first vehicle is a vehicle used by any target object, and the positions of the starting point and the end point are different; determining the first minimum duration and the first maximum duration from the first duration sequence; determining the first total number of times the first vehicle is charged from the starting point to the end point from the historical charging data, determining the second total number of times the first vehicle is charged from the starting point, and determining the total number of times the first vehicle is charged in the historical charging data; determining the spatial domain viscosity coefficient corresponding to the first vehicle based on the first duration, the first minimum duration, the first maximum duration, the first total number, the second total number and the total number of charging times.

[0007] Optionally, obtaining the first duration of the first vehicle from the starting point to the end point of each charging station in the historical charging data includes: obtaining a road network topology map corresponding to all nodes, wherein the nodes in the road network topology map include at least the starting point where the first vehicle is located and the end point where each charging station is located, and the road network topology map is used to represent the connection relationship between the nodes; determining the intermediate nodes passed from the starting point to the end point in sequence from the road network topology map, and determining the average travel time between each two nodes in the order of the starting point, the intermediate nodes and the end point; determining the first duration based on the average travel time between each two nodes among the starting point, the intermediate nodes and the end point.

[0008] Optionally, the average travel time between each two nodes is determined in turn, including: obtaining the first travel time of all vehicles passing through the road section where the first node and the second node are located, and determining the total number of vehicles passing through the road section where the first node and the second node are located, wherein the first node and the second node are any two directly connected nodes among the starting point, the intermediate node and the end point; based on the first travel time and the total number of vehicles, determine the average travel time between the first node and the second node.

[0009] Optionally, determining the time-domain viscosity coefficient based on historical charging data includes: determining the charging time corresponding to the first vehicle at each charging moment from the historical charging data, wherein the first vehicle is a vehicle used by any target object; determining a first variance of the charging time corresponding to the first vehicle, and determining a second variance of the charging moment corresponding to the first vehicle; determining a first maximum variance from a first variance set, and determining a second maximum variance from a second variance set, wherein the first variance set is determined by the first variance of the charging time corresponding to all vehicles, and the second variance set is determined by the second variance of the charging moment corresponding to all vehicles; determining the time-domain viscosity coefficient corresponding to the first vehicle based on the first maximum variance, the second maximum variance, the first variance, and the second variance.

[0010] Optionally, the charging load safety domain of the charging station is determined based on the spatial domain viscosity coefficient and the time domain viscosity coefficient, including: when the spatial domain viscosity coefficient of the first vehicle is less than or equal to the first value, and the time domain viscosity coefficient of the first vehicle is less than or equal to the second value, determining that the charging behavior of the first vehicle belongs to the first type, and the first vehicle is a vehicle used by any target object; when the spatial domain viscosity coefficient of the first vehicle is less than or equal to the first value, and the time domain viscosity coefficient of the first vehicle is greater than the second value, determining that the charging behavior of the first vehicle belongs to the second type; when the spatial domain viscosity coefficient of the first vehicle is greater than the first value, and the time domain viscosity coefficient of the first vehicle is less than or equal to the second value. When the viscosity coefficient of the first vehicle in the spatial domain is greater than the first value and the viscosity coefficient of the first vehicle in the time domain is greater than the second value, the charging behavior of the first vehicle is determined to be of the fourth type; a first charging load corresponding to the first type, a second charging load corresponding to the second type, a third charging load corresponding to the third type and a fourth charging load corresponding to the fourth type are obtained from the historical charging data; a total charging load is determined based on the first charging load, the second charging load, the third charging load and the fourth charging load; a charging load safety domain is determined based on the total charging load and the charging deviation.

[0011] Optionally, the original power distribution strategy is adjusted according to the charging load safety domain to obtain the target power distribution strategy of the charging station, including: obtaining the original charge capacity from the original power distribution strategy of the target charging station, wherein the target charging station is any charging station used by the target object; comparing the original charge capacity and the charging load safety domain to obtain a comparison result; when the comparison result indicates that the difference between the maximum value of the charging load safety domain and the original charge capacity is greater than a preset threshold, the original power distribution strategy of the target charging station is adjusted by increasing the original charge capacity or increasing the number of cables of the target charging station to obtain the corresponding target power distribution strategy of the target charging station.

[0012] According to another aspect of an embodiment of the present application, a network distribution device for a charging station is also provided, including: an acquisition module for acquiring historical charging data corresponding to a vehicle used by a target object, wherein the historical charging data includes at least the original power distribution strategy of the charging station; a first determination module for determining a spatial domain viscosity coefficient and a time domain viscosity coefficient based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent the relationship between the location of the vehicle used by the target object and the selection of the charging station, and the time domain viscosity coefficient is used to represent the relationship between the charging time of the vehicle used by the target object and the selection of the charging station; a second determination module for determining a charging load safety domain of the charging station based on the spatial domain viscosity coefficient and the time domain viscosity coefficient; an adjustment module for adjusting the original power distribution strategy based on the charging load safety domain to obtain a target power distribution strategy of the charging station.

[0013] According to another aspect of the embodiment of the present application, an electronic device is also provided, including: a memory for storing program instructions; a processor, connected to the memory, for executing program instructions to implement the following functions: obtaining historical charging data corresponding to a vehicle used by a target object, wherein the historical charging data includes at least the original power distribution strategy of the charging station; determining a spatial domain viscosity coefficient and a time domain viscosity coefficient based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent the relationship between the location of the vehicle used by the target object and the selection of the charging station, and the time domain viscosity coefficient is used to represent the relationship between the charging time of the vehicle used by the target object and the selection of the charging station; determining a charging load safety domain of the charging station based on the spatial domain viscosity coefficient and the time domain viscosity coefficient; adjusting the original power distribution strategy based on the charging load safety domain to obtain a target power distribution strategy of the charging station.

[0014] According to another aspect of the embodiments of the present application, a computer program product is provided, including computer instructions, which implement the above-mentioned charging station network distribution method when executed by a processor.

[0015] In an embodiment of the present application, historical charging data corresponding to the vehicle used by the target object is obtained, wherein the historical charging data at least includes the original power distribution strategy of the charging station; the spatial domain viscosity coefficient and the time domain viscosity coefficient are determined based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent the relationship between the location of the vehicle used by the target object and the charging station selection, and the time domain viscosity coefficient is used to represent the relationship between the charging time of the vehicle used by the target object and the charging station selection; the charging load safety domain of the charging station is determined based on the spatial domain viscosity coefficient and the time domain viscosity coefficient; the original power distribution strategy is adjusted based on the charging load safety domain to obtain the target power distribution strategy of the charging station, thereby achieving the purpose of optimizing the power distribution strategy of the charging station, thereby achieving the technical effect of improving the operating efficiency of the charging station, and further solving the technical problem in the related technology that the site selection problem of charging piles mostly considers the charging electricity price and the travel distance required for charging, but often ignores the impact of user charging habits on charging behavior. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 This is a hardware structure block diagram of a computer terminal for implementing a network distribution method for a charging station according to an embodiment of the present application;

[0018] Figure 2 is a flow chart of a network distribution method for a charging station according to an embodiment of the present application;

[0019] Figure 3is a road network topology diagram according to an embodiment of the present application;

[0020] Figure 4 This is a structural diagram of a distribution network device for a charging station according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. 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 a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] The network distribution method embodiment of the charging station provided in the embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal for implementing a charging station distribution method is shown. Figure 1 As shown, the computer terminal 10 may include one or more processors (illustrated as 102a, 102b, ..., 102n in the figure) (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission module 106 for communication functions via a wired and / or wireless network connection. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, and a BUS bus. Those skilled in the art will understand that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1More or fewer components than shown, or with Figure 1 Different configurations shown.

[0024] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry." The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be fully or partially integrated into any of the other components of the computer terminal 10. As discussed in the embodiments of the present application, the data processing circuitry functions as a processor control (e.g., the selection of a variable resistor terminal path connected to an interface).

[0025] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the network distribution method of the charging station in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, implementing the network distribution method of the charging station mentioned above. The memory 104 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely located relative to the processor, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0026] The transmission module 106 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of the computer terminal 10. In one embodiment, the transmission module 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission module 106 may be a radio frequency (RF) module, which is configured to communicate with the Internet wirelessly.

[0027] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 .

[0028] It should be noted that, in some optional embodiments, the above Figure 1 The computer terminal shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of hardware elements and software elements. Figure 1This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the computer terminal described above.

[0029] In the above-mentioned operating environment, an embodiment of the present application provides an embodiment of a network distribution method for a charging station. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0030] Figure 2 is a flow chart of a charging station network distribution method according to an embodiment of the present application, such as Figure 2 As shown, the method includes the following steps:

[0031] Step S202 : Acquire historical charging data corresponding to the vehicle used by the target object, wherein the historical charging data at least includes the original power distribution strategy of the charging station.

[0032] In step S202, the historical charging data, in addition to the charging station's original power distribution strategy, should also include: the user's (i.e., the target object) charging interval, the user's location before charging, traffic conditions before charging, charging duration, and the location of the charging station. It should be noted that the user's charging interval and location before charging can be understood as the charging interval of the user's vehicle (e.g., electric vehicle) and the location of the user's vehicle before charging.

[0033] In step S204, a spatial domain viscosity coefficient and a temporal domain viscosity coefficient are determined based on the historical charging data. The spatial domain viscosity coefficient is used to represent the relationship between the location of the target object's vehicle and the selected charging station, and the temporal domain viscosity coefficient is used to represent the relationship between the charging time of the target object's vehicle and the selected charging station.

[0034] In step S204 above, the spatial and temporal stickiness coefficients are two important indicators derived from analyzing historical charging data. They reveal the behavior patterns and preferences of electric vehicle users when selecting charging stations, respectively, from the spatial and temporal dimensions. The spatial stickiness coefficient can reflect a user's propensity to select a charging station in a specific geographic location. For example, the probability distribution of a user's choice of charging station in different areas can be calculated based on the user's GPS data or vehicle driving trajectory, combined with charging records. For example, if a user frequently selects a nearby charging station in a commercial area, but is more likely to choose a home charger or a nearby public charging station in a residential area, then the user can be considered to have a higher spatial stickiness coefficient in the commercial area. The temporal stickiness coefficient reflects the user's considerations and preferences regarding charging time when selecting a charging station within different time periods. For example, the difference in charging time at different charging stations within the same time period can be compared to determine the user's sensitivity to charging time when selecting a charging station.

[0035] Step S206 : determining the charging load safety region of the charging station based on the spatial domain viscosity coefficient and the temporal domain viscosity coefficient.

[0036] In step S206, the spatial viscosity coefficient is used to determine the distribution of charging loads at charging stations in different geographic locations. For example, in high-viscosity areas, the charging load may be high due to users frequently selecting nearby charging stations. In contrast, in low-viscosity areas, charging demand may be more dispersed or insufficient. During peak hours, the temporal viscosity coefficient indicates that users tend to choose fast-charging stations with high charging speeds, causing the charging load at these stations to increase dramatically. During off-peak hours, the charging load is relatively low. By comprehensively considering the spatial and temporal viscosity coefficients, the total charging load required by users is determined, and thus the charging load safety zone of the charging station is determined.

[0037] Step S208: Adjust the original power distribution strategy according to the charging load safety domain to obtain the target power distribution strategy of the charging station.

[0038] In step S208 above, the charging load safety domain refers to the maximum range of charging loads that can be sustained while ensuring the safe operation of the charging station. This range is based on an analysis of historical charging data, taking into account factors such as the spatial viscosity coefficient (the relationship between geographic location and charging station selection) and the temporal viscosity coefficient (the relationship between charging duration and charging station selection), as well as the grid's carrying capacity, equipment reliability, and emergency response capabilities. After determining the charging load safety domain, a comprehensive assessment of the current original power distribution strategy is required. For example, an assessment is needed to determine whether the existing power distribution system can meet the maximum load requirements within the charging load safety domain. If the original power distribution system cannot meet the requirements within the charging load safety domain, expansion or upgrades are necessary. For example, increasing transformer capacity, replacing high-efficiency distribution equipment, optimizing cable layout, etc., will determine the target power distribution strategy for the charging station.

[0039] Through steps S202 to S208 above, the goal of optimizing the charging station's power distribution strategy is achieved, thereby achieving the technical effect of improving the charging station's operational efficiency. This further addresses the technical issue in related technologies where charging pile site selection primarily considers charging electricity prices and required travel distances, but often overlooks the impact of user charging habits on charging behavior. This is explained in detail below.

[0040] In step S204 of the above-mentioned charging station distribution method, the spatial domain viscosity coefficient is determined based on the historical charging data, including: obtaining the first duration of the first vehicle from the starting point to the end point where each charging station is located in the historical charging data to obtain a first duration sequence, wherein the first duration sequence is determined by the first duration, the first vehicle is a vehicle used by any target object, and the positions of the starting point and the end point are different; determining a first minimum duration and a first maximum duration from the first duration sequence; determining a first total number of times the first vehicle is charged from the starting point to the end point from the historical charging data, determining a second total number of times the first vehicle is charged starting from the starting point, and determining the total number of times the first vehicle is charged in the historical charging data; and determining the spatial domain viscosity coefficient corresponding to the first vehicle based on the first duration, the first minimum duration, the first maximum duration, the first total number, the second total number, and the total number of charging times.

[0041] In this embodiment of the present application, historical charging data includes information such as the starting point location of each charge, the location of the selected charging station (or destination), charging duration, and charge amount. For any target vehicle (herein referred to as the first vehicle), the driving time from the vehicle's starting point to each destination at each charging station is extracted from the historical charging data to form a first duration sequence. Each element in this sequence (i.e., the first duration) represents the driving time from the starting point to a specific charging station. In the first duration sequence, the shortest driving time is found as the first minimum duration, which represents the fastest achievable time from the starting point to a specific charging station. Similarly, the longest driving time is found as the first maximum duration, which represents the longest or most time-consuming route from the starting point to a specific charging station. The total number of times the first vehicle charged from the starting point to the destination (i.e., the charging station actually selected for charging) is counted, i.e., the first total number. The first total number reflects the actual frequency of charging behavior between the starting point and the specific charging station. The total number of times the first vehicle charged from the starting point is counted, i.e., the second total number. The total number of charging times of the first vehicle in the historical charging data is counted, for example, including charging behaviors from all possible starting points, to obtain the total number of charging times. The spatial domain viscosity coefficient corresponding to the first vehicle is determined based on the first duration, the first minimum duration, the first maximum duration, the first total number of times, the second total number of times, and the total number of charging times.

[0042] The following is an explanation of the process of determining the spatial domain viscosity coefficient using a specific formula:

[0043] Use Dijkstra's method to sort the time (i.e., the first duration) of the i-th vehicle (i.e., the first vehicle) from the current position p (i.e., the starting point) to each charging station. The durations are ranked from short to long: D i,p,1 、D i,p,2 ,……,D i,p,c , where c is the total number of charging stations.

[0044]

[0045] Among them, y i,1 is the spatial domain viscosity coefficient of user i (i.e., the electric vehicle used by the user), or the spatial domain viscosity coefficient corresponding to the first vehicle, p is the starting point of vehicle charging, q is the charging end point (i.e., the location of the charging station), and m is the total number of nodes in the study area D. p,q The total number of times the i-th vehicle goes from node p to node q to charge, that is, the first total number mentioned above, O p is the total number of times the i-th vehicle starts charging from node p, that is, the second total number mentioned above, and O is the total number of times the i-th vehicle is charged in the historical records, that is, the total number of times charged above. represents the first time duration for the i-th vehicle to travel from node p to node q to charge, Indicates the first minimum duration mentioned above, Indicates the first maximum duration mentioned above.

[0046] In the above steps, obtaining the first duration of the first vehicle from the starting point to the end point of each charging station in the historical charging data includes: obtaining a road network topology map corresponding to all nodes, wherein the nodes in the road network topology map include at least the starting point where the first vehicle is located and the end point where each charging station is located, and the road network topology map is used to represent the connection relationship between the nodes; determining the intermediate nodes passed from the starting point to the end point in sequence from the road network topology map, and determining the average travel time between each two nodes in the order of the starting point, the intermediate nodes and the end point; determining the first duration based on the average travel time between each two nodes among the starting point, the intermediate nodes and the end point.

[0047] In the above steps, the average travel time between each two nodes is determined in turn, including: obtaining the first travel time of all vehicles passing through the road section where the first node and the second node are located, and determining the total number of vehicles passing through the road section where the first node and the second node are located, wherein the first node and the second node are any two directly connected nodes among the starting point, the intermediate node and the end point; based on the first travel time and the total number of vehicles, the average travel time between the first node and the second node is determined.

[0048] In the embodiment of the present application, the process of obtaining the first duration is explained through the following example.

[0049] Figure 3 is a road network topology diagram according to an embodiment of the present application, Figure 3 The algorithm contains four nodes, with node 1 as the starting point for the first vehicle and nodes 2-4 as the end points for the charging stations. If the duration from node 1 to node 2 needs to be determined, the intermediate nodes include nodes 4 and 3, resulting in three corresponding paths: Path 1: Node 1 → Node 2; Path 2: Node 1 → Node 4 → Node 2; Path 3: Node 1 → Node 4 → Node 3 → Node 2. After determining the average travel time of adjacent nodes in each path, the average travel time is added together to obtain the first travel time. In an optional embodiment, the average travel time of adjacent nodes in each path can also be added together to obtain the average travel time.

[0050] Figure 3 The Dijkstra matrix corresponding to the road network topology is as follows:

[0051]

[0052] Where D is the improved Dijkstra matrix, It represents the average travel time of the road section from node i to node j, which can be used Indicates that k represents the road section from node i to node j. It can be calculated by the following formula:

[0053]

[0054] Where n is the total number of electric vehicles on the kth road section, that is, the total number of vehicles mentioned above, t k,i is the average travel time of the i-th vehicle on the k-th road section, that is, the first travel time mentioned above, Represents the sum of the first travel time of all vehicles.

[0055] In step S204 of the network distribution method for the above-mentioned charging station, a time-domain viscosity coefficient is determined based on historical charging data, including: determining the charging time corresponding to the first vehicle at each charging moment from the historical charging data, wherein the first vehicle is a vehicle used by any target object; determining a first variance of the charging time corresponding to the first vehicle, and determining a second variance of the charging moment corresponding to the first vehicle; determining a first maximum variance from a first variance set, and determining a second maximum variance from a second variance set, wherein the first variance set is determined by the first variance of the charging time corresponding to all vehicles, and the second variance set is determined by the second variance of the charging moment corresponding to all vehicles; determining the time-domain viscosity coefficient corresponding to the first vehicle based on the first maximum variance, the second maximum variance, the first variance, and the second variance.

[0056] In the embodiment of the present application, the charging time can be represented by T, the charging time can be represented by a, and the time domain viscosity coefficient is determined by the following formula:

[0057]

[0058] in, represents the time domain viscosity coefficient of user i (or the electric vehicle used by the user), represents the first variance corresponding to the first vehicle i, represents the second variance corresponding to the first vehicle i, represents the first largest variance mentioned above, represents the second largest variance mentioned above.

[0059] In step S206 of the above-mentioned charging station distribution method, the charging load safety domain of the charging station is determined based on the spatial domain viscosity coefficient and the time domain viscosity coefficient, including: when the spatial domain viscosity coefficient of the first vehicle is less than or equal to the first value, and the time domain viscosity coefficient of the first vehicle is less than or equal to the second value, it is determined that the charging behavior of the first vehicle belongs to the first type, and the first vehicle is a vehicle used by any target object; when the spatial domain viscosity coefficient of the first vehicle is less than or equal to the first value, and the time domain viscosity coefficient of the first vehicle is greater than the second value, it is determined that the charging behavior of the first vehicle belongs to the second type; when the spatial domain viscosity coefficient of the first vehicle is greater than the first value, and the first vehicle When the time-domain viscosity coefficient is less than or equal to the second value, it is determined that the charging behavior of the first vehicle belongs to the third type; when the spatial-domain viscosity coefficient of the first vehicle is greater than the first value and the time-domain viscosity coefficient of the first vehicle is greater than the second value, it is determined that the charging behavior of the first vehicle belongs to the fourth type; a first charging load corresponding to the first type, a second charging load corresponding to the second type, a third charging load corresponding to the third type, and a fourth charging load corresponding to the fourth type are obtained from historical charging data; a total charging load is determined based on the first charging load, the second charging load, the third charging load, and the fourth charging load; a charging load safety domain is determined based on the total charging load and the charging deviation.

[0060] In the embodiment of the present application, users can be classified according to the ranges of the spatial domain viscosity coefficient and the temporal domain viscosity coefficient, as follows:

[0061]

[0062] Among them, L i is the charging load corresponding to the label of user i, L1 represents the charging load corresponding to users of the non-sticky spatial domain type and non-sticky time domain type (i.e., the first type mentioned above), i.e., the first charging load mentioned above; L2 represents the charging load corresponding to users of the non-sticky spatial domain type and sticky time domain type (i.e., the second type mentioned above), i.e., the second charging load mentioned above; L3 represents the charging load corresponding to users of the sticky spatial domain type and non-sticky time domain type (i.e., the third type mentioned above), i.e., the third charging load mentioned above; L4 represents the charging load corresponding to users of the sticky spatial domain type and sticky time domain type (i.e., the fourth type mentioned above).

[0063] The total charging load L is calculated using the following formula:

[0064]

[0065] in, The corresponding proportional weights for each type of user.

[0066] Charging load safety zone The corresponding calculation formula is as follows:

[0067]

[0068] in, The fluctuation range of the proportion of various types of users can be artificially adjusted according to security requirements. Set the value, such as 10%, etc.

[0069] In step S208 of the above-mentioned network distribution method for the charging station, the original power distribution strategy is adjusted according to the charging load safety domain to obtain the target power distribution strategy of the charging station, including: obtaining the original charge capacity from the original power distribution strategy of the target charging station, wherein the target charging station is any charging station used by the target object; comparing the original charge capacity and the charging load safety domain to obtain a comparison result; when the comparison result indicates that the difference between the maximum value of the charging load safety domain and the original charge capacity is greater than a preset threshold, adjusting the original power distribution strategy of the target charging station by increasing the original charge capacity or increasing the number of cables of the target charging station to obtain the corresponding target power distribution strategy of the target charging station.

[0070] In this embodiment of the present application, it is necessary to determine the original power distribution strategy of the target charging station (i.e., the charging station currently being used or planned to be used by the user), specifically its original charge capacity. The original charge capacity refers to the maximum charging power or amount of electricity that the charging station can simultaneously provide under the current power distribution strategy and is the basis for evaluating the charging station's load capacity. The original charge capacity is compared with the charging load safety domain. The charging load safety domain is determined based on factors such as the charging station's design parameters, equipment performance, grid connection conditions, and safety regulations. It represents the maximum range of charging loads that the charging station can handle while ensuring safety and efficiency. This comparison allows an assessment of whether the current power distribution strategy can meet potential future growth in charging demand while ensuring the safety of the charging process. If the comparison result shows that the difference between the maximum value of the charging load safety domain and the original charge capacity is greater than a preset threshold, it indicates that the original charge capacity under the current power distribution strategy is insufficient to meet potential future growth in charging demand or presents a safety hazard under current demand. In this case, the original power distribution strategy needs to be adjusted through one of the following methods: 1. Increasing the original charge capacity: For example, by upgrading charging equipment, increasing transformer capacity, or optimizing the power distribution strategy, the overall load capacity of the charging station can be improved. 2. Increase the number of cables in the target charging station: If physical conditions permit, increasing the number of cables within the charging station can expand the number of vehicles that can be charged simultaneously, thereby improving the charging station's service capacity. After these adjustments, the resulting target power distribution strategy should better meet charging needs and improve charging efficiency while ensuring charging safety.

[0071] Figure 4 This is a structural diagram of a network distribution device for a charging station according to an embodiment of the present application. Figure 4As shown, the device includes:

[0072] An acquisition module 40 is configured to acquire historical charging data corresponding to the vehicle used by the target object, wherein the historical charging data at least includes the original power distribution strategy of the charging station;

[0073] A first determining module 42 is configured to determine a spatial viscosity coefficient and a temporal viscosity coefficient based on historical charging data, wherein the spatial viscosity coefficient represents the relationship between the location of the target vehicle and the selected charging station, and the temporal viscosity coefficient represents the relationship between the charging duration of the target vehicle and the selected charging station;

[0074] A second determining module 44 is configured to determine a charging load safety region of the charging station based on the spatial domain viscosity coefficient and the temporal domain viscosity coefficient;

[0075] The adjustment module 46 is configured to adjust the original power distribution strategy according to the charging load safety domain to obtain a target power distribution strategy for the charging station.

[0076] Through the acquisition module 40, the first determination module 42, the second determination module 44 and the adjustment module 46 in the distribution network device of the above-mentioned charging station, the purpose of optimizing the power distribution strategy of the charging station is achieved, thereby realizing the technical effect of improving the operating efficiency of the charging station, and further solving the technical problem that the site selection of charging piles in the related art mostly considers the charging electricity price and the travel distance required for charging, but often ignores the impact of user charging habits on charging behavior.

[0077] In the first determination module in the distribution network device of the above-mentioned charging station, the first determination module is also used to obtain the first duration of the first vehicle from the starting point to the end point of each charging station in the historical charging data to obtain a first duration sequence, wherein the first duration sequence is determined by the first duration, the first vehicle is a vehicle used by any target object, and the positions of the starting point and the end point are different; determine the first minimum duration and the first maximum duration from the first duration sequence; determine the first total number of times the first vehicle is charged from the starting point to the end point from the historical charging data, determine the second total number of times the first vehicle is charged from the starting point, and determine the total number of times the first vehicle is charged in the historical charging data; determine the spatial domain viscosity coefficient corresponding to the first vehicle based on the first duration, the first minimum duration, the first maximum duration, the first total number, the second total number and the total number of charging times.

[0078] In the first determination module in the distribution network device of the above-mentioned charging station, the first determination module is also used to obtain a road network topology map corresponding to all nodes, wherein the nodes in the road network topology map include at least the starting point where the first vehicle is located and the end point where each charging station is located, and the road network topology map is used to represent the connection relationship between the nodes; the intermediate nodes passed from the starting point to the end point are determined in sequence from the road network topology map, and the average travel time between each two nodes is determined in sequence in the order of the starting point, the intermediate nodes and the end point; the first time is determined based on the average travel time between each two nodes among the starting point, the intermediate nodes and the end point.

[0079] In the first determination module in the distribution network device of the above-mentioned charging station, the first determination module is also used to obtain the first travel time of all vehicles passing through the road section where the first node and the second node are located, and to determine the total number of vehicles passing through the road section where the first node and the second node are located, wherein the first node and the second node are any two nodes with a directly connected relationship among the starting point, the intermediate node and the end point; based on the first travel time and the total number of vehicles, the average travel time between the first node and the second node is determined.

[0080] In the first determination module in the distribution network device of the above-mentioned charging station, the first determination module is also used to determine the charging time corresponding to the first vehicle at each charging moment from historical charging data, wherein the first vehicle is a vehicle used by any target object; determine the first variance of the charging time corresponding to the first vehicle, and determine the second variance of the charging moment corresponding to the first vehicle; determine the first maximum variance from the first variance set, and determine the second maximum variance from the second variance set, wherein the first variance set is determined by the first variance of the charging time corresponding to all vehicles, and the second variance set is determined by the second variance of the charging moment corresponding to all vehicles; determine the time domain viscosity coefficient corresponding to the first vehicle based on the first maximum variance, the second maximum variance, the first variance, and the second variance.

[0081] In the second determination module in the distribution network device of the above-mentioned charging station, the second determination module is also used to determine that the charging behavior of the first vehicle belongs to the first type when the spatial domain viscosity coefficient of the first vehicle is less than or equal to the first value, and the time domain viscosity coefficient of the first vehicle is less than or equal to the second value, and the first vehicle is a vehicle used by any target object; when the spatial domain viscosity coefficient of the first vehicle is less than or equal to the first value, and the time domain viscosity coefficient of the first vehicle is greater than the second value, determine that the charging behavior of the first vehicle belongs to the second type; when the spatial domain viscosity coefficient of the first vehicle is greater than the first value, and the time domain viscosity coefficient of the first vehicle is less than or equal to the second value. When the first value is greater than the first value and the time domain viscosity coefficient of the first vehicle is greater than the second value, the charging behavior of the first vehicle is determined to be of the third type; when the spatial domain viscosity coefficient of the first vehicle is greater than the first value and the time domain viscosity coefficient of the first vehicle is greater than the second value, the charging behavior of the first vehicle is determined to be of the fourth type; the first charging load corresponding to the first type, the second charging load corresponding to the second type, the third charging load corresponding to the third type and the fourth charging load corresponding to the fourth type are obtained from the historical charging data; the total charging load is determined based on the first charging load, the second charging load, the third charging load and the fourth charging load; the charging load safety domain is determined based on the total charging load and the charging deviation.

[0082] In the adjustment module in the distribution network device of the above-mentioned charging station, the adjustment module is also used to obtain the original charge capacity from the original power distribution strategy of the target charging station, wherein the target charging station is any charging station used by the target object; compare the original charge capacity and the charging load safety domain to obtain a comparison result; when the comparison result indicates that the difference between the maximum value of the charging load safety domain and the original charge capacity is greater than a preset threshold, adjust the original power distribution strategy of the target charging station by increasing the original charge capacity or increasing the number of cables of the target charging station to obtain the corresponding target power distribution strategy of the target charging station.

[0083] It should be noted that Figure 4 The distribution network device of the charging station shown is used to perform Figure 2 The network distribution method of the charging station shown in the figure, therefore the relevant explanations in the above-mentioned network distribution method of the charging station are also applicable to the network distribution device of the charging station, and will not be repeated here.

[0084] An embodiment of the present application also provides an electronic device, including: a memory for storing program instructions; a processor, connected to the memory, for executing program instructions to implement the following functions: obtaining historical charging data corresponding to a vehicle used by a target object, wherein the historical charging data at least includes an original power distribution strategy of the charging station; determining a spatial domain viscosity coefficient and a time domain viscosity coefficient based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent the relationship between the location of the vehicle used by the target object and the selection of the charging station, and the time domain viscosity coefficient is used to represent the relationship between the charging time of the vehicle used by the target object and the selection of the charging station; determining a charging load safety domain of the charging station based on the spatial domain viscosity coefficient and the time domain viscosity coefficient; adjusting the original power distribution strategy based on the charging load safety domain to obtain a target power distribution strategy of the charging station.

[0085] It should be noted that the above electronic equipment is used to perform Figure 2 The network configuration method of the charging station shown in the figure, therefore the relevant explanations in the above-mentioned network configuration method of the charging station are also applicable to the electronic device and will not be repeated here.

[0086] An embodiment of the present application further provides a non-volatile storage medium, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned charging station network distribution method by running the computer program.

[0087] An embodiment of the present application further provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the charging station network distribution method in each embodiment of the present application.

[0088] The embodiments of the present application further provide a computer program, which, when executed by a processor, implements the steps of the charging station network distribution method in each embodiment of the present application.

[0089] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0090] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0092] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0093] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0094] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program code.

[0095] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A charging station network distribution method, characterized in that: include: Obtaining historical charging data corresponding to the vehicle used by the target object, wherein the historical charging data at least includes the original power distribution strategy of the charging station; Determining a spatial domain viscosity coefficient and a temporal domain viscosity coefficient based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent the relationship between the location of the vehicle used by the target object and the selection of the charging station, and the temporal domain viscosity coefficient is used to represent the relationship between the charging duration of the vehicle used by the target object and the selection of the charging station; determining a charging load safety region of the charging station according to the spatial domain viscosity coefficient and the time domain viscosity coefficient; Adjusting the original power distribution strategy according to the charging load safety domain to obtain a target power distribution strategy for the charging station; Adjusting the original power distribution strategy according to the charging load safety domain to obtain a target power distribution strategy for the charging station includes: obtaining an original charge capacity from the original power distribution strategy of a target charging station, wherein the target charging station is any charging station used by the target object; comparing the original charge capacity with the charging load safety domain to obtain a comparison result; and when the comparison result indicates that the difference between the maximum value of the charging load safety domain and the original charge capacity is greater than a preset threshold, adjusting the original power distribution strategy of the target charging station by increasing the original charge capacity or increasing the number of cables of the target charging station to obtain a corresponding target power distribution strategy for the target charging station; Determining a spatial domain viscosity coefficient based on the historical charging data includes: obtaining a first duration of a first vehicle from a starting point to an end point at each charging station in the historical charging data to obtain a first duration sequence, wherein the first duration sequence is determined by the first duration, the first vehicle is a vehicle used by any target object, and the positions of the starting point and the end point are different; determining a first minimum duration and a first maximum duration from the first duration sequence; determining a first total number of times the first vehicle is charged from the starting point to the end point from the historical charging data, determining a second total number of times the first vehicle is charged starting from the starting point, and determining a total number of times the first vehicle is charged in the historical charging data; determining a spatial domain viscosity coefficient corresponding to the first vehicle based on the first duration, the first minimum duration, the first maximum duration, the first total number of times, the second total number of times, and the total number of times charged; Determining a time-domain viscosity coefficient based on the historical charging data includes: determining a charging time corresponding to a first vehicle at each charging moment from the historical charging data, wherein the first vehicle is a vehicle used by any target object; determining a first variance of the charging time corresponding to the first vehicle, and determining a second variance of the charging moment corresponding to the first vehicle; determining a first maximum variance from a first variance set, and determining a second maximum variance from a second variance set, wherein the first variance set is determined by the first variance of the charging time corresponding to all vehicles, and the second variance set is determined by the second variance of the charging moment corresponding to all vehicles; determining a time-domain viscosity coefficient corresponding to the first vehicle based on the first maximum variance, the second maximum variance, the first variance, and the second variance.

2. The method according to claim 1, characterized in that Obtaining a first duration of time for a first vehicle in the historical charging data to travel from a starting point to a destination at each charging station includes: Obtaining a road network topology graph corresponding to all nodes, wherein the nodes in the road network topology graph include at least a starting point where the first vehicle is located and an end point where each charging station is located, and the road network topology graph is used to represent a connection relationship between each node; Determining, in sequence, the intermediate nodes passed through by the starting point to the end point from the road network topology diagram, and determining, in sequence, the average travel time between each two nodes in the order of the starting point, the intermediate nodes, and the end point; The first duration is determined according to an average travel time between every two nodes among the starting point, the intermediate nodes and the end point.

3. The method according to claim 2, characterized in that Determine the average travel time between each two nodes in turn, including: Obtaining a first travel time of all vehicles passing through a road section where a first node and a second node are located, and determining a total number of vehicles passing through the road section where the first node and the second node are located, wherein the first node and the second node are any two directly connected nodes among the starting point, the intermediate node, and the end point; An average travel time between the first node and the second node is determined based on the first travel time and the total number of vehicles.

4. The method according to claim 1, wherein Determining the charging load safety region of the charging station according to the spatial domain viscosity coefficient and the time domain viscosity coefficient includes: When the spatial domain viscosity coefficient of the first vehicle is less than or equal to a first value, and the time domain viscosity coefficient of the first vehicle is less than or equal to a second value, determining that the charging behavior of the first vehicle belongs to the first type, and the first vehicle is a vehicle used by any target object; When the spatial domain viscosity coefficient of the first vehicle is less than or equal to the first value, and the time domain viscosity coefficient of the first vehicle is greater than the second value, determining that the charging behavior of the first vehicle belongs to the second type; When the spatial domain viscosity coefficient of the first vehicle is greater than the first value and the time domain viscosity coefficient of the first vehicle is less than or equal to the second value, determining that the charging behavior of the first vehicle belongs to the third type; When the spatial domain viscosity coefficient of the first vehicle is greater than the first value and the temporal domain viscosity coefficient of the first vehicle is greater than the second value, determining that the charging behavior of the first vehicle belongs to the fourth type; Obtaining, from the historical charging data, a first charging load corresponding to the first type, a second charging load corresponding to the second type, a third charging load corresponding to the third type, and a fourth charging load corresponding to the fourth type; determining a total charging load based on the first charging load, the second charging load, the third charging load, and the fourth charging load; The charging load safety region is determined according to the total charging load and the charging deviation.

5. A network distribution device for a charging station, characterized in that: include: An acquisition module, configured to acquire historical charging data corresponding to the vehicle used by the target object, wherein the historical charging data at least includes the original power distribution strategy of the charging station; a first determining module, configured to determine a spatial domain viscosity coefficient and a temporal domain viscosity coefficient based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent a relationship between a location of a vehicle used by the target subject and a selected charging station, and the temporal domain viscosity coefficient is used to represent a relationship between a charging duration of the vehicle used by the target subject and the selected charging station; a second determining module, configured to determine a charging load safety region of the charging station according to the spatial domain viscosity coefficient and the time domain viscosity coefficient; an adjustment module, configured to adjust the original power distribution strategy according to the charging load safety domain to obtain a target power distribution strategy for the charging station; Adjusting the original power distribution strategy according to the charging load safety domain to obtain a target power distribution strategy for the charging station includes: obtaining an original charge capacity from the original power distribution strategy of a target charging station, wherein the target charging station is any charging station used by the target object; comparing the original charge capacity with the charging load safety domain to obtain a comparison result; and when the comparison result indicates that the difference between the maximum value of the charging load safety domain and the original charge capacity is greater than a preset threshold, adjusting the original power distribution strategy of the target charging station by increasing the original charge capacity or increasing the number of cables of the target charging station to obtain a corresponding target power distribution strategy for the target charging station; The first determination module is further configured to obtain a first duration from the starting point to the end point of each charging station in the historical charging data for the first vehicle, and obtain a first duration sequence, wherein the first duration sequence is determined by the first duration, the first vehicle is a vehicle used by any target object, and the starting point and the end point are at different positions; determine a first minimum duration and a first maximum duration from the first duration sequence; determine a first total number of times the first vehicle is charged from the starting point to the end point from the historical charging data, determine a second total number of times the first vehicle is charged starting from the starting point, and determine the total number of times the first vehicle is charged in the historical charging data; determine a spatial domain viscosity coefficient corresponding to the first vehicle based on the first duration, the first minimum duration, the first maximum duration, the first total number of times, the second total number of times, and the total number of times charged; The first determination module is further used to determine the charging time corresponding to the first vehicle at each charging moment from the historical charging data, wherein the first vehicle is a vehicle used by any target object; determine a first variance of the charging time corresponding to the first vehicle, and determine a second variance of the charging moment corresponding to the first vehicle; determine a first maximum variance from a first variance set, and determine a second maximum variance from a second variance set, wherein the first variance set is determined by the first variance of the charging time corresponding to all vehicles, and the second variance set is determined by the second variance of the charging moment corresponding to all vehicles; determine the time domain viscosity coefficient corresponding to the first vehicle based on the first maximum variance, the second maximum variance, the first variance, and the second variance.

6. An electronic device, characterized in that: include: a memory for storing program instructions; A processor, connected to the memory, is used to execute program instructions that implement the following functions: obtaining historical charging data corresponding to the vehicle used by the target object, wherein the historical charging data at least includes the original power distribution strategy of the charging station; determining a spatial domain viscosity coefficient and a time domain viscosity coefficient based on the historical charging data, wherein the spatial domain viscosity coefficient is used to represent the relationship between the location of the vehicle used by the target object and the charging station selection, and the time domain viscosity coefficient is used to represent the relationship between the charging time of the vehicle used by the target object and the charging station selection; determining a charging load safety domain of the charging station based on the spatial domain viscosity coefficient and the time domain viscosity coefficient; and adjusting the charging load safety domain based on the charging load safety domain. The method comprises: adjusting the original power distribution strategy to obtain the target power distribution strategy of the charging station; adjusting the original power distribution strategy according to the charging load safety domain to obtain the target power distribution strategy of the charging station, including: obtaining the original charge capacity from the original power distribution strategy of the target charging station, wherein the target charging station is any charging station used by the target object; comparing the original charge capacity with the charging load safety domain to obtain a comparison result; when the comparison result indicates that the difference between the maximum value of the charging load safety domain and the original charge capacity is greater than a preset threshold, adjusting the original power distribution strategy of the target charging station by increasing the original charge capacity or increasing the number of cables of the target charging station. Adjustments are made to obtain the target power distribution strategy corresponding to the target charging station; a spatial domain viscosity coefficient is determined based on the historical charging data, including: obtaining a first time duration of the first vehicle from the starting point to the end point of each charging station in the historical charging data to obtain a first time duration sequence, wherein the first time duration sequence is determined by the first time duration, the first vehicle is a vehicle used by any target object, and the positions of the starting point and the end point are different; determining a first minimum time duration and a first maximum time duration from the first time duration sequence; determining a first total number of times the first vehicle is charged from the starting point to the end point from the historical charging data, and determining the first vehicle from the starting point to the end point to the end point. a second total number of times the first vehicle is charged from the starting point, and a total number of times the first vehicle is charged in the historical charging data; determining a spatial domain viscosity coefficient corresponding to the first vehicle based on the first duration, the first minimum duration, the first maximum duration, the first total number of times, the second total number of times, and the total number of times of charging; determining a temporal domain viscosity coefficient based on the historical charging data, including: determining a charging duration corresponding to each charging moment of the first vehicle from the historical charging data, wherein the first vehicle is a vehicle used by any target object; determining a first variance of the charging duration corresponding to the first vehicle, and determining a second variance of the charging moment corresponding to the first vehicle;Determining a first maximum variance from a first variance set and a second maximum variance from a second variance set, wherein the first variance set is determined by first variances of charging times corresponding to all vehicles, and the second variance set is determined by second variances of charging times corresponding to all vehicles; determining a time-domain viscosity coefficient corresponding to the first vehicle based on the first maximum variance, the second maximum variance, the first variance, and the second variance.

7. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the network distribution method for a charging station according to any one of claims 1 to 4 is implemented.

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