A charging pile power distribution method and device, a charging pile, and a medium

Abstract

This application relates to the field of charging piles, and discloses a method, apparatus, charging pile, and medium for allocating charging pile power. The method includes: when the current charging pile is connected to the charging gun, obtaining the user category corresponding to the current charging pile; if the user category is a regular user, generating a target parameter x corresponding to the current charging pile. ij The process involves: defining an objective function; identifying conflicting constraints between at least two constraints based on the objective parameters; adjusting at least one constraint to eliminate conflicting constraints between the two constraints; finding the optimal solution to the objective function when there are no conflicting constraints, and using this optimal solution as the target power allocation for the current charging station; and allocating the target power to the current charging station. This application, when dealing with large-scale charging stations, uses flexible constraint configuration to accurately calculate the maximum power required for the current charging station without generating conflicting constraints.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of charging piles, in particular to a charging pile power distribution method and device, a charging pile and a medium. BACKGROUND

[0002] Global fuel consumption and environmental pollution, these two big problems promote the rapid development of new energy automobile industry, with the popularity of electric vehicles, charging piles as the energy supply station of electric vehicles, gradually become one of the commonly used devices of human.

[0003] However, when a large number of charging pile interfaces are used at the same time, the whole power grid layer reasonably restricts the distribution of charging power, which is of great significance to ensure the charging efficiency, stability and safety of the charging vehicle and the whole power grid layer. In the peak and valley stage of the use of charging piles, if the charging power is not limited, it will cause the main power grid or charging pile circuit to burn out; on the contrary, in the trough stage of the use of charging piles, the conservative charging power distribution will seriously affect the charging efficiency of the vehicle. Therefore, how to intelligently and real-time distribute the power of the charging pile is one of the core problems in the development stage of electric vehicles. SUMMARY

[0004] The purpose of the embodiment of the present application is to provide a charging pile power distribution method, device, charging pile and medium, which can flexibly configure constraint conditions, and accurately calculate the maximum power required by the current charging pile when there is no conflict constraint condition.

[0005] To solve the above technical problems, the embodiment of the present application adopts the following technical scheme:

[0006] In the first aspect, the embodiment of the present application provides a charging pile power distribution method, which comprises:

[0007] When the current charging pile is connected with the charging gun, the user category corresponding to the current charging pile is obtained;

[0008] If the user category is a normal user, the target parameter x ij and the objective function corresponding to the current charging pile are generated; wherein the target parameter x ij represents the distribution power parameter corresponding to the jth charging pile of the ith cluster of the current charging pile, and i and j are positive integers; the objective function is used to represent the function of the maximum distribution power that can be distributed when the current charging pile is the jth charging pile of the ith cluster;

[0009] Based on the target parameter, it is determined that there is a conflict constraint condition between at least two constraint conditions; wherein the constraint condition is configured based on the multiple charging pile configuration levels where the current charging pile is located;

[0010] Adjust at least one of the constraints so that there are no conflicting constraints between the at least two of the constraints;

[0011] When there are no conflicting constraints between at least two of the constraints, the optimal solution of the objective function is obtained and used as the target power allocation for the current charging pile.

[0012] The target power allocation is assigned to the current charging station.

[0013] For ordinary users, when allocating target power to the current charging pile, corresponding target parameters and objective functions are generated. If conflicting constraints exist, adjustments are made to ensure that the target parameters meet the constraints. When no conflicting constraints are generated, the optimal solution of the objective function is obtained, thereby accurately calculating the maximum power that the current charging pile needs to be allocated.

[0014] In some embodiments, the charging pile configuration layers are the power grid layer, the cluster layer, and the charging pile layer; the power grid layer includes at least one cluster layer, and each cluster layer includes at least one charging pile layer.

[0015] Since the configuration of charging piles includes various situations related to the scale of charging stations, it is possible to calculate the target power allocation of the current charging piles in a timely manner under a large number of constraints, thereby improving the stability of the power system, the charging experience of car owners, and the profitability of charging pile owners.

[0016] In some embodiments, determining that there are conflicting constraints between at least two constraints based on the target parameter includes:

[0017] Based on the power grid level, the cluster level, and the charging pile level, it is determined in sequence whether the target parameter satisfies the first constraint condition.

[0018] If the first constraint condition is met, then based on the first relationship between the power grid level and the cluster level, and the second relationship between the cluster level and the charging pile level, it is determined whether the target parameter meets the second constraint condition.

[0019] If the second constraint is not met, then it is determined that there is a conflicting constraint between at least two of the constraints.

[0020] By analyzing multiple charging pile configuration layers and the relationships between these layers, the system can determine whether the target parameters meet the constraints, intelligently identify conflicting constraints, and facilitate adjustments to the constraints.

[0021] In some embodiments, the first constraint includes the total grid power limit at the grid level, different power limits at the cluster level, and different power limits at the charging pile level.

[0022] The second constraint includes the power ratio between different cluster layers and the power ratio between different charging pile layers.

[0023] The first and second constraints limit the maximum power that the current charging pile can be allocated from both the hard conditions at each level and the software aspect of the power ratio between charging piles, fully considering the constraint configuration at multiple levels.

[0024] In some embodiments, adjusting at least one of the constraints includes:

[0025] Based on the priority of each second constraint, delete the second constraints with lower priority until there are no conflicting constraints between the first constraint and the second constraint.

[0026] When a conflict occurs, constraints with lower priority can be deleted based on the pre-determined priority of each constraint, thereby updating the constraint configuration.

[0027] In some embodiments, adjusting at least one of the constraints includes:

[0028] If a deletion instruction is received for the second constraint, the second constraint is deleted until there are no conflicting constraints between the first constraint and the second constraint.

[0029] When conflict conditions occur, the constraints that need to be deleted can be manually selected, enabling flexible configuration of constraints.

[0030] In some embodiments, after determining the user category corresponding to the charging pile, the method further includes:

[0031] If the user category is a VIP user, then the maximum charging power of the current charging pile is assigned to the charging pile.

[0032] If the user category is a time-limited user, then a fixed power is assigned to the current charging station.

[0033] Different charging power is configured for different types of users to meet the diverse charging power allocation needs of users.

[0034] Secondly, embodiments of this application also provide a power distribution device for a charging pile, the device comprising:

[0035] The user category acquisition module is used to acquire the user category corresponding to the current charging pile when the current charging pile is connected to the charging gun.

[0036] The target generation module is used to generate target parameters x corresponding to the current charging pile if the user category is a regular user. ij and the objective function; wherein the objective parameter x ij The parameter represents the allocated power parameter corresponding to the j-th charging pile in the i-th cluster, where i and j are both positive integers; the objective function is a function used to characterize the maximum allocated power that can be allocated when the current charging pile is the j-th charging pile in the i-th cluster.

[0037] A conflict determination module is used to determine, based on the target parameters, that there are conflicting constraints between at least two constraints; wherein the constraints are configured based on the configuration layers of multiple charging piles where the current charging pile is located.

[0038] An adjustment module is used to adjust at least one of the constraints so that there are no conflicting constraints between the at least two constraints.

[0039] The calculation module is used to solve the optimal solution of the objective function when there are no conflicting constraints between the at least two of the constraints, and use it as the target power allocation of the current charging pile;

[0040] The allocation module is used to allocate the target power to the current charging pile.

[0041] Thirdly, this application also provides a charging pile, the charging pile comprising:

[0042] At least one processor, and

[0043] A memory communicatively connected to the processor, the memory storing instructions executable by the at least one processor to enable the at least one processor to perform the method as described in the first aspect.

[0044] Fourthly, this application also provides a non-volatile computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-executable instructions, which, when executed by a charging pile, cause the charging pile to perform the method described in any of the first aspects.

[0045] The beneficial effects of this application's embodiments are as follows: Unlike existing technologies, the charging pile power allocation method, device, charging pile, and medium provided in this application's embodiments, when a user starts charging an electric vehicle using a charging pile, the current charging pile is connected to the charging gun. First, the user category corresponding to the current charging pile is obtained; different user categories can adopt different power allocation methods. When the user category is a regular user, a target parameter xij and an objective function corresponding to the current charging pile are generated; wherein, the target parameter xij represents the allocated power corresponding to the j-th charging pile in the i-th cluster, where i and j are both positive integers. Next, based on the target parameter, conflicting constraints are intelligently identified; furthermore, at least one constraint can be adjusted to achieve flexible configuration of the constraints until no conflicting constraints exist, and the optimal solution of the objective function is solved as the target allocated power for the current charging pile, achieving rapid iteration to find the global optimal solution under a large number of constraints. Furthermore, when the charging station scale is large, different power allocation methods corresponding to different user categories are implemented, improving the stability of the power system, the charging experience for vehicle owners, and the profitability of charging pile station owners. Attached Figure Description

[0046] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0047] Figure 1 This is a schematic diagram of the charging pile power distribution system of this application;

[0048] Figure 2 This is a flowchart illustrating one embodiment of the charging pile power allocation method of this application;

[0049] Figure 3 This is a schematic diagram of the structure of one embodiment of the charging pile power distribution device of this application;

[0050] Figure 4 This is a schematic diagram of the hardware structure of the controller in one embodiment of the charging pile of this application. Detailed Implementation

[0051] The present application will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present application, but do not limit the present application in any way. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application. These all fall within the protection scope of the present application.

[0052] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0053] It should be noted that, unless there is a conflict, the various features in the embodiments of this application can be combined with each other, all of which are within the protection scope of this application. Furthermore, although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than the module division in the device or the order in the flowchart. In addition, the terms "first," "second," and "third" used herein do not limit the data or execution order, but only distinguish identical or similar items with essentially the same function and effect.

[0054] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The term "and / or" as used in this specification includes any and all combinations of one or more of the associated listed items.

[0055] Furthermore, the technical features involved in the various embodiments of this application described below can be combined with each other as long as they do not conflict with each other.

[0056] In some implementations, the power allocation of charging piles is mainly based on rule-based methods and / or state-based strategies. For example, the allocation rules of the rule-based method are: weighted average, average allocation, and first-come, first-served. The allocation method of the state-based strategy method is to set the corresponding power range according to the monitored current, voltage, temperature of the charging pile or the charging demand of the vehicle battery.

[0057] However, the rule-based and state-strategy-based allocation methods described above cannot achieve optimal universal allocation across various charging pile usage scenarios, thus affecting vehicle charging efficiency and the full utilization of electricity. In particular, when the scale of charging piles is large, different vehicles may have different power limitations. Under numerous constraints, the rule-based calculation method cannot find the optimal solution within a limited time, and it will seriously affect the stability of the power system, the charging experience for car owners, and the profitability of charging pile operators.

[0058] To address the aforementioned issues, this application proposes a method for allocating power to charging piles. This method is applied to charging pile power allocation systems.

[0059] like Figure 1 As shown,Figure 1 This is a schematic diagram of the charging pile power distribution system of this application. The distribution system includes at least one grid layer, within which at least one cluster layer is included, and within each cluster layer, at least one charging pile is included, indicating a relatively large scale of charging piles. The charging pile power distribution method and apparatus can be applied to charging piles, where each charging pile can be any charging pile in any cluster layer of the grid layer.

[0060] When a charging pile is connected to a charging gun, the charging pile can perform the power allocation method, and / or another charging pile not connected to a charging gun can perform the power allocation method. The charging piles can communicate with each other through a cloud server. After determining the target power allocation, the cloud server sends relevant instructions to the corresponding charging pile.

[0061] Please see Figure 2 The above is a flowchart illustrating an embodiment of the charging pile power allocation method applied in this application. The method can be executed by a controller in the charging pile and includes steps S201-S206.

[0062] S201: When the current charging pile is connected to the charging gun, obtain the user category corresponding to the current charging pile.

[0063] When a user needs to charge an electric vehicle using a charging gun, the user selects a charging station to connect the charging gun to, and this charging station becomes the current charging station.

[0064] At this time, the charging pile power distribution system detects that the current charging pile is connected to a charging gun and needs to charge the electric vehicle, thereby determining which charging pile is located in which cluster layer.

[0065] Users can be categorized based on their location, including regular users, VIP users, and time-limited users.

[0066] The general user group is relatively large, and the number of charging piles available for charging is usually large and widely distributed. For example, in a power grid layer, there are n clusters, and each cluster has m charging piles. Most of the charging piles are for general users, a small number are for VIP users, and similarly, a small number are for users with limited time access.

[0067] In some implementations, to allow different user groups to enjoy different power allocation methods, after obtaining the user category corresponding to the charging pile, the method further includes:

[0068] If the user category is a VIP user, then the maximum charging power of the current charging pile is assigned to the charging pile.

[0069] If the user category is a time-limited user, then a fixed power is assigned to the current charging station.

[0070] Specifically, if the user category is a VIP user, then the maximum charging power of the current charging pile is allocated to the charging pile; expressed by Formula 1:

[0071] x ij =pile_max_power[i,j] Formula 1;

[0072] Where, x ij This indicates that the current charging pile is the j-th charging pile in the i-th cluster, and pile_max_power[i,j] represents the maximum power of the j-th charging pile in the i-th cluster. When the user category is VIP user, Formula 1 holds true, so the maximum charging power can be allocated to the current charging pile xij, so that the current charging pile xij can charge the vehicle with the maximum charging power.

[0073] If the user category is a time-limited user, then a fixed power is allocated to the current charging station, expressed by Formula 2:

[0074] x ij =min(soe / t,pile_max_power[i,j]) Formula 2;

[0075] Where, x ij This indicates that the current charging station is the j-th charging station in the i-th cluster, soe represents the charging capacity that the electric vehicle needs to be fully charged, and t represents the time required for the electric vehicle to be fully charged.

[0076] Formula 2 is used to calculate the fixed charging power that the charging station can be allocated when the user category is a time-limited user.

[0077] By identifying user categories, different user groups can use different charging stations and thus receive different power allocations.

[0078] S202: If the user category is a regular user, then generate the target parameter x corresponding to the current charging pile. ij and the objective function; wherein the objective parameter x ij The function is used to represent the allocated power corresponding to the j-th charging pile in the i-th cluster, where i and j are both positive integers; the objective function is used to characterize the maximum allocated power that can be allocated when the current charging pile is the j-th charging pile in the i-th cluster.

[0079] Specifically, since the number of ordinary users is usually large, most charging stations are designated for their use. When the user category is ordinary user, the target parameter x corresponding to the current charging station is generated.ij and the objective function; wherein the objective parameter x ij This is used to represent the allocated power corresponding to the j-th charging pile in the i-th cluster, where i and j are both positive integers. Furthermore, the objective function is used to characterize the maximum allocated power that can be allocated when the current charging pile is the j-th charging pile in the i-th cluster.

[0080] Target parameter x ij It is generated based on the number of charging pile clusters (group_num) and the number of charging piles in each cluster (pile_num), where pile_num = [n1, n2, n3, n4, ..., ng]; the target parameter can be specifically represented as: x 11 x 12 x 13 x 1n1 ... x ij .

[0081] The objective function subject is expressed by the following formula 3:

[0082] subject = min(-x11-x12……-xij) Formula 3;

[0083] The objective function is to maximize the power allocation of all charging stations while satisfying all constraints. Therefore, the overall objective is to maximize the total power allocation, which is equivalent to minimizing the inverse.

[0084] S203: Based on the target parameters, determine that there are conflicting constraints between at least two constraints; wherein the constraints are configured based on the configuration layers of multiple charging piles where the current charging pile is located.

[0085] To enable intelligent configuration of constraints, the constraints are divided into constraint layers: the power grid layer, the cluster layer, and the charging pile layer. The power grid layer includes at least one cluster layer, and each cluster layer includes at least one charging pile layer. That is, a power grid layer includes multiple charging pile clusters, and each charging pile cluster includes multiple charging piles. This application's embodiment uses a single power grid layer as an example.

[0086] In some implementations, determining that there are conflicting constraints between at least two constraints based on the target parameter may include:

[0087] Based on the power grid level, the cluster level, and the charging pile level, it is determined in sequence whether the target parameter satisfies the first constraint condition.

[0088] If the first constraint condition is met, then based on the first relationship between the power grid level and the cluster level, and the second relationship between the cluster level and the charging pile level, it is determined whether the target parameter meets the second constraint condition.

[0089] If the second constraint is not met, then it is determined that there is a conflicting constraint between at least two of the constraints.

[0090] Specifically, the first step is to determine whether the target parameter xij satisfies the first constraint condition. The first constraint condition is a hard indicator in charging power allocation. Therefore, the first constraint condition includes the total grid power limit at the grid level, the power limits at different cluster levels, and the power limits at different charging pile levels. Specifically, the first constraint condition is: the sum of the power of all charging piles does not exceed the total power at the grid level; the sum of the power of charging piles in each cluster level does not exceed the maximum total power of the first cluster level where the current charging pile is located; and the power of the current charging pile is between the maximum and minimum power of the first cluster level.

[0091] The sum of the power of all charging piles shall not exceed the total power of the power grid layer, as expressed by Formula 3, which is as follows:

[0092] Sum(x11,x12,x13,……,xij)≤max_power (Formula 3);

[0093] Where Sum represents the total, and max_power represents the maximum total power of the power grid layer.

[0094] The sum of the power of the charging piles in each cluster layer shall not exceed the maximum total power of the corresponding cluster layer, as expressed by Formula 4, which is as follows:

[0095]

[0096] Where group_num represents the number of charging pile clusters, and group_max_powers represents the maximum total power of each cluster.

[0097] The power of the current charging pile is between the maximum and minimum power of the cluster layer to which the current charging pile belongs, as expressed by Formula 5, which is as follows:

[0098] pile_min_power[i,j]≤xij≤pile_max_power[i,j] Formula 5;

[0099] Where pile_min_power represents the minimum power of each charging pile in the cluster, and pile_max_power represents the maximum power of each charging pile in the cluster.

[0100] If the target parameter x ij If the above first constraints are met, then based on the first relationship between the power grid level and the cluster level, and the second relationship between the cluster level and the charging pile level, it is determined whether the target parameter satisfies the second constraint. Conversely, if the first constraint is not met, it indicates that the target parameter x... ij If the hard parameters for charging power allocation are not met, the target parameter x is regenerated. ij .

[0101] The second constraint is a soft indicator in charging power allocation, including the power ratio between different cluster levels and the power ratio between different charging pile levels. The second constraint includes a first ratio equal to a second ratio and a third ratio equal to a fourth ratio.

[0102] Wherein, the first ratio is equal to the ratio of the sum of the power of n1 charging piles in the i-th cluster to the sum of the power of n2 charging piles in the k-th cluster; n1 is less than j, and n2 is less than j;

[0103] The second ratio is equal to the ratio between the total power ratio between the i-th cluster and the total power ratio between the k-th cluster;

[0104] The third ratio is equal to the ratio between the power of the i-th charging pile in the i-th cluster and the power of the j-th charging pile;

[0105] The fourth ratio is equal to the ratio between the power ratio of the i-th charging pile in the i-th cluster and the power ratio between the j-th charging pile.

[0106] Furthermore, the sum of the power of n1 charging piles in the i-th cluster is the sum of the power of the first charging pile to the n1-th charging pile in the i-th cluster, and the sum of the power of n2 charging piles in the k-th cluster is the sum of the power of the first charging pile to the n2-th charging pile in the k-th cluster, where n1 is less than j and n2 is less than j; the second ratio is equal to the ratio between the total power ratio between the i-th cluster and the total power ratio between the k-th cluster, that is, the first equals the second ratio can be expressed by Formula 6, as follows:

[0107]

[0108] Wherein, group_power_p represents the total power ratio between clusters, Sum(xi1,xi2,……,xin1) represents the sum of power of n1 charging piles in the i-th cluster; Sum(xk1,xk2,……,xkn2) represents the sum of power of n2 charging piles in the k-th cluster; group_power_p[i] represents the total power ratio between clusters in the i-th cluster, and group_power_p[k] represents the total power ratio between clusters in the k-th cluster.

[0109] The third ratio is equal to the ratio between the power of the i-th charging pile in the i-th cluster and the power of the j-th charging pile.

[0110] The fourth ratio is equal to the ratio between the power ratio of the i-th charging pile in the i-th cluster and the power ratio between the j-th charging pile. In other words, the fourth ratio is equal to the ratio between the power ratio of the i-th charging pile in the i-th cluster and the power ratio between the j-th charging pile in the i-th cluster.

[0111] The third ratio equals the fourth ratio, which can be expressed by Formula 7, as follows:

[0112] xii / xij=(pile_power_p[i,i] / pile_power_p[i,j]) Formula 7;

[0113] Where xii represents the power of the i-th charging pile in the i-th cluster, xij represents the power of the j-th charging pile in the i-th cluster; pile_power_p represents the power ratio between charging piles; pile_power_p[i,i] represents the power ratio between the i-th charging pile in the i-th cluster, and pile_power_p[i,j] represents the power ratio between the j-th charging pile in the i-th cluster.

[0114] If the target parameter satisfies the second constraint, it is determined that there are no conflicting constraints; otherwise, if the second constraint is not satisfied, it is determined that there are conflicting constraints between at least two of the constraints.

[0115] In some embodiments, input test cases for the deployment interface are used for illustration.

[0116] {

[0117] "Total power max_power": 1500,

[0118] "Group power limit":[600,800,800],

[0119] "Pile power limitation":

[0120] {1:{1:(5,200),2:(5,100),3:(5,150),4:(5,200)},2:{1:(5,200),2:(5,200),3:(5,150),4:(5,200)},3:{1:(5,100),2:(5,200),3:(5,100),4:(5,200),5:(5,200),6:(5,150)}},

[0121] "VIP User":["1_1","2_2","3_3","3_5"],

[0122] "Fixed power":{"3_1":80,"1_3":100,"2_4":150,"2_1":100,},

[0123] "Group power ratio":{"1:3":"1:2"},

[0124] "Pile power ratio":{1:{'1:2':'1:2'},2:{'1:2':'2:3'},3:{'1:2':'2:3','4:5':'1:2'}}},

[0125] "del_type":"0"

[0126] }

[0127] Among them, the total power max_power represents the grid-level limit of no more than 1500kW; the group power limit represents the limit at different cluster levels as [600, 800, 800], indicating that there are 3 groups, and the maximum power of each cluster does not exceed 600kW, 800kW, and 800kW respectively; the power limit at different charging pile levels is pile power limit 1:{1:(5,200)}, which means that the power of the first pile in group 1 is greater than 5kW and less than 200kW; VIP user 1_1 represents the first pile in group 1, which is used by VIP users and needs to operate at full power; fixed power limit 3_1 represents the fixed power of 80kW specified for the first pile in group 3, which is used by users with limited time; the group power ratio represents the ratio that the total power allocated to the group must meet, which are 1:3 and 1:2 respectively; the pile power ratio represents which piles in each group need to meet a certain ratio.

[0128] The above-mentioned relationship input program automatically defines parameters and generates the constraints shown in Table 1 below:

[0129]

[0130] Table 1

[0131] By inputting the above constraints into the program and running it, it can be determined whether there are conflicting constraints between at least two constraints. If there are conflicting constraints, further adjustments are needed until there are no conflicting constraints, and then the optimal solution of the objective function can be calculated.

[0132] S204: Adjust at least one of the constraints such that there are no conflicting constraints between the at least two constraints.

[0133] Specifically, the first constraint is a rigid indicator related to the power allocation of charging piles, such as the total grid power limit at the grid level, the power limits at different cluster levels, and the power limits at different charging pile levels. These are conditions that must be met. Therefore, the conflict usually arises from the second constraint. For example, formula 6 might be satisfied, but formula 7 might not. In this case, to make the power allocation more reasonable, the second constraint needs to be adjusted.

[0134] In some implementations, adjusting at least one of the constraints may include:

[0135] Based on the priority of each second constraint, delete the second constraints with lower priority until there are no conflicting constraints between the first constraint and the second constraint.

[0136] Specifically, if the user selects the method of automatically handling conflicting conditions, the priority ranking of each second constraint is obtained. Based on the priority of each second constraint, it can be sorted from low to high priority. For example, the priority of formula 6 is higher than that of formula 7. The second constraint with lower priority (formula 7) is deleted until there is no conflicting constraint between the first constraint and the second constraint, thus reducing the complexity of the problem constraints.

[0137] In some embodiments, adjusting at least one of the constraints may further include:

[0138] If a deletion instruction is received for the second constraint, the second constraint is deleted until there are no conflicting constraints between the first constraint and the second constraint.

[0139] Specifically, if the user chooses the interactive method to handle conflicting conditions, a pop-up window will display various second constraints. The user can select some second constraints to delete according to their own needs. At this time, the controller will receive a deletion instruction for the second constraint, and then the controller will delete the second constraint until there are no conflicting constraints between the first constraint and the second constraint.

[0140] For example, Table 2 represents the user's choice of interaction handling conflict conditions:

[0141]

[0142] Table 2

[0143] As can be seen in Table 2, after deleting the second constraint conditions, namely pile power ratio constraint 1_1 / 2 and pile power ratio constraint 2_1 / 2, there are no more conflicting conditions.

[0144] Users can choose an interactive processing method to delete a specified second constraint, reconfigure the constraints, and find the optimal solution for the objective function without generating conflicting constraints.

[0145] S205: When there are no conflicting constraints between the at least two of the constraints, solve the optimal solution of the objective function and use it as the target power allocation for the current charging pile.

[0146] If there are no constraints in Table 1 that would cause a conflict, the objective function is to allocate as much power as possible to all piles while satisfying all constraints. Therefore, the overall objective is to maximize the total power allocation, which is equivalent to minimizing the inverse. Referring to Equation 3, we can obtain:

[0147] Subject=min(-x1_2-x1_4-x2_3-x3_2-x3_4-x3_6-x3_1-x1_3-x2_4-x2_1-x1_1-x2_2-x3_3-x3_5).

[0148] Then, the optimal solution to the objective function is found using a breadth-first search branch and bound algorithm. The branch and bound algorithm is an exact algorithm for solving integer linear programming problems. It uses a search tree to represent the solution space of the problem. By relaxing integer constraints, the original integer linear programming problem is continuously decomposed into linear programming problems. In solving the linear programming problems, the upper and lower bounds of the original problem are continuously tracked, thus solving the integer linear problem. Specifically, the steps S21-S24 are as follows:

[0149] S21. The original integer linear programming problem is A, and the corresponding linear programming problem is B;

[0150] S22. Solve problem B:

[0151] If B has no feasible solution, then A also has no feasible solution, so stop the calculation;

[0152] If B has an optimal solution that satisfies the integer condition, then this optimal solution is the optimal solution for A, and the calculation stops.

[0153] If B has an optimal solution but does not meet the integer condition, denote its objective function as Z*, which serves as the lower bound of the optimal solution;

[0154] S23. Find an integer feasible solution to problem A, and use its objective function value as the upper bound of the optimal solution;

[0155] S24. Perform iterations, where step S24 includes steps S41-S44:

[0156] S41, Branch: In the optimal solution of B, select any variable xj that does not meet the integer condition, and its value is bj. Construct two constraints: xj<=[bj] and xj>=[bj]+1, forming two subproblems B1 and B2 and solving the linear problem.

[0157] S42. Bounding: For each subsequent problem, indicate the result of its solution, compare it with other problems, and take the linear optimal objective function value as the new lower bound. In each branch that meets the integer condition, take the integer linear optimal objective function value as the new upper bound.

[0158] S43. Pruning: Remove branches whose objective function values ​​are not within the upper or lower bounds.

[0159] S44. Repeat S41-S43 until the optimal solution is obtained.

[0160] The algorithm's solution results are shown in Table 3 below:

[0161] Pile Allocate power Group Group total power Total power x1_1 100 1 303 1500 x1_2 98 1 303 1500 x1_3 100 1 303 1500 x1_4 5 1 303 1500 x2_1 100 2 591 1500 x2_2 200 2 591 1500 x2_3 141 2 591 1500 x2_4 150 2 591 1500 x3_1 80 3 606 1500 x3_2 120 3 606 1500 x3_3 100 3 606 1500 x3_4 100 3 606 1500 x3_5 200 3 606 1500 x3_6 6 3 606 1500

[0162] Table 3

[0163] As shown in Table 3, the optimal solution of the objective function is obtained by the breadth-first search branch and bound algorithm, which serves as the target power allocation for the current charging pile.

[0164] S206: Assign the target power to the current charging pile.

[0165] After determining the target power allocation for the current charging station, the controller allocates the target power to the current charging station and charges the vehicle through the connected charging gun.

[0166] In an embodiment of this application, when a user begins charging an electric vehicle using a charging pile, the current charging pile is connected to the charging gun. First, the user category corresponding to the current charging pile is obtained; different user categories can adopt different power allocation methods. When the user category is a regular user, a target parameter xij and an objective function corresponding to the current charging pile are generated; wherein, the target parameter xij represents the allocated power corresponding to the j-th charging pile in the i-th cluster, where i and j are both positive integers. Next, based on the target parameter, conflicting constraints are intelligently identified; furthermore, at least one constraint can be adjusted to achieve flexible configuration of the constraints until no conflicting constraints exist, and the optimal solution of the objective function is solved as the target allocated power for the current charging pile, enabling rapid iteration to find the global optimal solution under numerous constraints. Furthermore, when the charging station scale is large, different power allocation methods corresponding to different user categories can be implemented, improving the stability of the power system, the charging experience for vehicle owners, and the profitability of charging station owners.

[0167] This application also provides a charging pile power distribution device, please refer to... Figure 3 This illustration shows the structure of a charging pile power distribution device 300 provided in an embodiment of this application. The charging pile power distribution device 300 includes:

[0168] The user category acquisition module 301 is used to acquire the user category corresponding to the current charging pile when the current charging pile is connected to the charging gun.

[0169] The target generation module 302 is used to generate target parameters x corresponding to the current charging pile if the user category is a regular user. ij and the objective function; wherein the objective parameter x ij The parameter represents the allocated power parameter corresponding to the j-th charging pile in the i-th cluster, where i and j are both positive integers; the objective function is a function used to characterize the maximum allocated power that can be allocated when the current charging pile is the j-th charging pile in the i-th cluster.

[0170] The conflict determination module 303 is used to determine, based on the target parameters, that there are conflicting constraints between at least two constraints; wherein the constraints are configured based on the configuration layers of multiple charging piles where the current charging pile is located.

[0171] The adjustment module 304 is used to adjust at least one of the constraints so that there are no conflicting constraints between the at least two constraints.

[0172] The calculation module 305 is used to solve the optimal solution of the objective function when there is no conflicting constraint between the at least two of the constraints, and use it as the target power allocation of the current charging pile;

[0173] The first power allocation module 306 is used to allocate the target power to the current charging pile.

[0174] In an embodiment of this application, when a user begins charging an electric vehicle using a charging pile, the current charging pile is connected to the charging gun. First, the user category corresponding to the current charging pile is obtained; different user categories can employ different power allocation methods. When the user category is a regular user, the target parameter x corresponding to the current charging pile is generated. ij and the objective function; wherein the objective parameter x ij This is used to represent the allocated power of the j-th charging pile in the i-th cluster, where i and j are both positive integers. Next, based on the target parameters, conflicting constraints are intelligently identified; furthermore, at least one constraint can be adjusted to achieve flexible configuration of constraints until no conflicting constraints exist. The optimal solution of the objective function is then solved, serving as the target allocated power for the current charging pile, enabling rapid iteration to find the global optimal solution under numerous constraints. Furthermore, when the charging station scale is large, different power allocation methods can be implemented for different user categories, improving the stability of the power system, the charging experience for vehicle owners, and the profitability for charging station owners.

[0175] In some embodiments, the charging pile configuration layers are the power grid layer, the cluster layer, and the charging pile layer; the power grid layer includes at least one cluster layer, and each cluster layer includes at least one charging pile layer.

[0176] In some embodiments, the conflict determination module 303 is further configured to:

[0177] Based on the power grid level, the cluster level, and the charging pile level, it is determined in sequence whether the target parameter satisfies the first constraint condition.

[0178] If the first constraint condition is met, then based on the first relationship between the power grid level and the cluster level, and the second relationship between the cluster level and the charging pile level, it is determined whether the target parameter meets the second constraint condition.

[0179] If the second constraint is not met, then it is determined that there is a conflicting constraint between at least two of the constraints.

[0180] In some embodiments, the first constraint includes the total grid power limit at the grid level, different power limits at the cluster level, and different power limits at the charging pile level.

[0181] The second constraint includes the power ratio between different cluster layers and the power ratio between different charging pile layers.

[0182] In some embodiments, the adjustment module 304 is further configured to:

[0183] Based on the priority of each second constraint, delete the second constraints with lower priority until there are no conflicting constraints between the first constraint and the second constraint.

[0184] In some embodiments, the adjustment module 304 is further configured to:

[0185] If a deletion instruction is received for the second constraint, the second constraint is deleted until there are no conflicting constraints between the first constraint and the second constraint.

[0186] In some embodiments, the charging pile power distribution device 300 further includes a second power distribution module 307 and a third power distribution module 308;

[0187] The second power allocation module 307 is used to allocate the maximum charging power of the charging pile to the current charging pile if the user category is a VIP user.

[0188] The third power allocation module 308 is used to allocate a fixed power to the current charging pile if the user category is a time-limited user.

[0189] It should be noted that the above-described apparatus can execute the method provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the apparatus embodiments can be found in the method provided in the embodiments of this application.

[0190] Figure 4 A schematic diagram of the hardware structure of controller 11 in one embodiment of a charging pile is shown below. Figure 4 As shown, the controller 11 includes:

[0191] One or more processors 111 and memory 112. Figure 4 The example uses a processor 111 and a memory 112.

[0192] Processor 111 and memory 112 can be connected via a bus or other means. Figure 4 Taking the example of a connection between China and Israel via a bus.

[0193] The memory 112, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the charging pile power allocation method in the embodiments of this application (e.g., attached...). Figure 3 The components shown are: user category acquisition module 301, target generation module 302, conflict determination module 303, adjustment module 304, calculation module 305, first power allocation module 306, second power allocation module 307, and third power allocation module 308. The processor 111 executes various functional applications and data processing of the controller 11 by running non-volatile software programs, instructions, and modules stored in the memory 112, thereby implementing the charging pile power allocation method of the above-described embodiment.

[0194] The memory 112 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the charging pile power distribution device, etc. Furthermore, the memory 112 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 112 may optionally include memory remotely located relative to the processor 111, and these remote memories can be connected to the charging pile via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0195] The one or more modules are stored in the memory 112. When executed by the one or more processors 111, they execute the charging pile power allocation method in any of the above method embodiments, for example, executing the above-described method. Figure 2 Method steps S201 to S206; implementation Figure 3 The functions of modules 301-308 in the document.

[0196] The above-described product can perform the methods provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for performing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in the embodiments of this application.

[0197] This application provides a non-volatile computer-readable storage medium storing computer-executable instructions that are executed by one or more processors, for example... Figure 4 One of the processors 111 can enable the one or more processors to execute the charging pile power allocation method in any of the above method embodiments, for example, to execute the above-described method. Figure 2Method steps S201 to S206; implementation Figure 3 The functions of modules 301-308 in the document.

[0198] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. 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 network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0199] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software and a general-purpose hardware platform, or of course, using hardware. 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 program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0200] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; under the concept of the present invention, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the present invention as described above, which are not provided in detail for the sake of brevity; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for allocating power in a charging pile, characterized in that, The method includes: When the current charging pile is connected to the charging gun, obtain the user category corresponding to the current charging pile; If the user category is a regular user, then generate the target parameter x corresponding to the current charging pile. ij and the objective function; wherein the objective parameter x ij The parameter represents the allocated power parameter corresponding to the j-th charging pile in the i-th cluster, where i and j are both positive integers; the objective function is a function used to characterize the maximum allocated power that can be allocated when the current charging pile is the j-th charging pile in the i-th cluster. Based on the target parameters, it is determined that there are conflicting constraints between at least two constraints; wherein, the constraints are configured based on multiple charging pile configuration layers where the current charging pile is located, and the charging pile configuration layers are the power grid layer, the cluster layer, and the charging pile layer; the power grid layer includes at least one cluster layer, and each cluster layer includes at least one charging pile layer. Adjust at least one of the constraints so that there are no conflicting constraints between the at least two constraints, wherein the at least one constraint includes a second constraint, the second constraint including the power ratio between different cluster layers and the power ratio between different charging pile layers, and the adjustment of the at least one constraint includes deleting the second constraint with lower priority according to the priority of each second constraint. When there are no conflicting constraints between at least two of the constraints, the optimal solution of the objective function is obtained and used as the target power allocation for the current charging pile. The target power allocation is assigned to the current charging station.

2. The method according to claim 1, characterized in that, The determination of conflicting constraints between at least two constraints based on the target parameters includes: Based on the power grid level, the cluster level, and the charging pile level, it is determined in sequence whether the target parameter satisfies the first constraint condition. If the first constraint condition is met, then based on the first relationship between the power grid level and the cluster level, and the second relationship between the cluster level and the charging pile level, it is determined whether the target parameter meets the second constraint condition. If the second constraint is not met, then it is determined that there is a conflicting constraint between at least two of the constraints.

3. The method according to claim 2, characterized in that, The first constraint includes the total grid power limit at the grid level, different power limits at the cluster level, and different power limits at the charging pile level.

4. The method according to claim 2, characterized in that, The adjustment of at least one of the constraints includes: Based on the priority of each second constraint, delete the second constraints with lower priority until there are no conflicting constraints between the first constraint and the second constraint.

5. The method according to claim 2, characterized in that, The adjustment of at least one of the constraints includes: If a deletion instruction is received for the second constraint, the second constraint is deleted until there are no conflicting constraints between the first constraint and the second constraint.

6. The method according to any one of claims 1 to 5, characterized in that, After obtaining the user category corresponding to the charging pile, the method further includes: If the user category is a VIP user, then the maximum charging power of the current charging pile is assigned to the charging pile. If the user category is a time-limited user, then a fixed power is assigned to the current charging station.

7. A power distribution device for a charging pile, characterized in that, The device includes: The user category acquisition module is used to acquire the user category corresponding to the current charging pile when the current charging pile is connected to the charging gun. The target generation module is used to generate target parameters x corresponding to the current charging pile if the user category is a regular user. ij and the objective function; wherein the objective parameter x ij The parameter represents the allocated power parameter corresponding to the j-th charging pile in the i-th cluster, where i and j are both positive integers; the objective function is a function used to characterize the maximum allocated power that can be allocated when the current charging pile is the j-th charging pile in the i-th cluster. The conflict determination module is used to determine, based on the target parameters, that there are conflicting constraints between at least two constraints; wherein the constraints are configured based on multiple charging pile configuration layers where the current charging pile is located, and the charging pile configuration layers are the power grid layer, the cluster layer, and the charging pile layer; the power grid layer includes at least one cluster layer, and each cluster layer includes at least one charging pile layer. An adjustment module is used to adjust at least one of the constraints so that there are no conflicting constraints between the at least two constraints. The at least one constraint includes a second constraint, which includes the power ratio between different cluster layers and the power ratio between different charging pile layers. Adjusting the at least one constraint includes deleting the second constraint with lower priority according to the priority of each second constraint. The calculation module is used to solve the optimal solution of the objective function when there are no conflicting constraints between the at least two of the constraints, and use it as the target power allocation of the current charging pile; The first power allocation module is used to allocate the target power to the current charging pile.

8. A charging pile, characterized in that, The charging pile includes: At least one processor, and A memory communicatively connected to the processor, the memory storing instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1-6.

9. A non-volatile computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by the charging pile, cause the charging pile to perform the method as described in any one of claims 1-6.

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