High power charging configuration method and device

Abstract

The present invention provides a high-power charging configuration method and device, the method comprising: determining the configurable high-power charging capacity of the distribution area according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; obtaining the predicted value of the number of electric vehicles in the distribution area after a preset time; obtaining the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging; determining the high-power charging demand capacity of the distribution area according to the above-mentioned predicted value, probability and average power; determining the actual high-power charging capacity of the distribution area according to the above-mentioned high-power charging capacity and high-power charging demand capacity; determining the high-power charging wiring scheme in the distribution area according to the above-mentioned actual high-power charging capacity, the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line. The present invention can meet the high-power charging demand of electric vehicles in the distribution area at a low cost.

Description

Technical Field

[0001] The present invention relates to the field of charging technology, and in particular to a high-power charging configuration method and a high-power charging configuration device. Background Art

[0002] With the popularity of electric vehicles, the demand for charging piles in residential areas is growing, but the current construction of residential areas does not take into account the load demand of charging piles or only considers the demand for low-power AC charging piles. Currently, most charging piles in residential areas can only meet the needs of users to fully charge their electric vehicles after get off work and before work the next day, and it is difficult to effectively meet the needs of users for fast charging.

[0003] There are two main reasons for this problem. First, the current community capacity is insufficient. If capacity expansion is used to meet the needs of high-power fast charging, it will require high-cost primary equipment investment including transformers, power lines, and distribution cabinets. Second, the current community distribution network does not have a single outgoing line that is sufficient to support high-power charging needs. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems in the above-mentioned technology to a certain extent. To this end, one purpose of the present invention is to propose a high-power charging configuration method, which can aggregate the surplus capacity of each outgoing line of the distribution network in the distribution area, so as to meet the high-power charging needs of electric vehicles in the distribution area, and only needs to connect the cables to achieve the aggregation of each outgoing line, with low investment cost, simple operation, cost saving, and strong applicability.

[0005] The second objective of the present invention is to provide a high-power charging configuration device.

[0006] To achieve the above-mentioned purpose, a first aspect of the present invention proposes a high-power charging configuration method, comprising the following steps: determining the configurable high-power charging capacity of the distribution area according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; obtaining a predicted value of the number of electric vehicles in the distribution area after a preset time; obtaining the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging; determining the high-power charging demand capacity of the distribution area according to the predicted value of the number of electric vehicles in the distribution area after the preset time, the probability of the user using high-power charging and the average power of the electric vehicle when high-power charging; determining the actual high-power charging capacity of the distribution area according to the configurable high-power charging capacity of the distribution area and the high-power charging demand capacity of the distribution area; determining the high-power charging wiring scheme in the distribution area according to the actual high-power charging capacity of the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line.

[0007] According to the high-power charging configuration method of the embodiment of the present invention, the configurable high-power charging capacity of the distribution area is determined according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, the predicted value of the number of electric vehicles in the distribution area after a preset time is obtained, the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging are obtained, the high-power charging demand capacity of the distribution area is determined according to the predicted value of the number of electric vehicles in the distribution area after a preset time, the probability of users using high-power charging and the average power of the electric vehicle when high-power charging is performed, the actual high-power charging capacity of the distribution area is determined according to the configurable high-power charging capacity of the distribution area and the high-power charging demand capacity of the distribution area, and the high-power charging wiring scheme in the distribution area is determined according to the actual high-power charging capacity of the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line. As a result, the surplus capacity of each outgoing line of the distribution network in the distribution area can be aggregated to meet the high-power charging demand of the electric vehicles in the distribution area, and the aggregation of each outgoing line only needs to be achieved through the connection of cables, which has low investment cost, simple operation, cost saving and strong applicability.

[0008] In addition, the high-power charging configuration method proposed in the above embodiment of the present invention may also have the following additional technical features:

[0009] According to one embodiment of the present invention, the high-power charging capacity that can be configured in the distribution area is determined based on the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, specifically including: calculating the surplus capacity of each outgoing line based on the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; determining the number of available outgoing lines based on the surplus capacity of each outgoing line and the power of a single charging module; calculating the high-power charging capacity that can be configured in the distribution area based on the number of available outgoing lines and the power of a single charging module.

[0010] According to one embodiment of the present invention, the predicted value of the number of electric vehicles in the distribution area after a preset time is obtained, specifically including: based on the historical annual number of fuel vehicles in the city, the historical annual number of electric vehicles in the city, GDP, and population development trends, a random forest algorithm is used to predict the development trend of the number of electric vehicles in the city in the next L years, and a predicted value of the number of electric vehicles in the city in the next L year is determined, wherein L is a positive integer; based on the historical annual number of fuel vehicles in the city, the historical annual and predicted annual number of electric vehicles in the city, and the historical annual number of fuel vehicles in the distribution area, a regression analysis is used to predict the development trend of the number of electric vehicles in the distribution area in the next L years, and a predicted value of the number of electric vehicles in the distribution area in the next L year is determined.

[0011] According to one embodiment of the present invention, the probability of a single user using high-power charging and the average power of an electric vehicle when performing high-power charging are obtained, specifically including: statistically analyzing the charging time distribution of multiple users, the charging power distribution of vehicle models, and the ratio of high-power charging to conventional charging in the power distribution area, and determining the probability of a single user using high-power charging and the average power of an electric vehicle when performing high-power charging by using the Monte Carlo method.

[0012] To achieve the above-mentioned purpose, the second embodiment of the present invention proposes a high-power charging configuration device, including: a first determination module, the first determination module is used to determine the configurable high-power charging capacity of the distribution area according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; a first acquisition module, the first acquisition module is used to obtain the predicted value of the number of electric vehicles in the distribution area after a preset time; a second acquisition module, the second acquisition module is used to obtain the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging is performed; the second determination module, the second determination module is used to determine the configurable high-power charging capacity of the distribution area according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; a third determination module, the third determination module is used to determine the high-power charging demand capacity of the distribution area according to the configurable high-power charging capacity of the distribution area and the high-power charging demand capacity of the distribution area; a fourth determination module, the fourth determination module is used to determine the high-power charging wiring scheme in the distribution area according to the actual high-power charging capacity of the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line.

[0013] According to the high-power charging configuration device of the embodiment of the present invention, the high-power charging capacity that can be configured in the distribution area is determined by the first determination module according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, the predicted value of the number of electric vehicles in the distribution area after a preset time is obtained by the first acquisition module, the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging are obtained by the second acquisition module, and the high-power charging demand capacity of the distribution area is determined by the second determination module according to the predicted value of the number of electric vehicles in the distribution area after a preset time, the probability of users using high-power charging and the average power of the electric vehicle when high-power charging is performed. The actual high-power charging capacity of the distribution area is determined by the third determination module according to the configurable high-power charging capacity of the distribution area and the high-power charging demand capacity of the distribution area. The high-power charging wiring scheme in the distribution area is determined by the fourth determination module according to the actual high-power charging capacity of the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line. As a result, the surplus capacity of each outgoing line of the distribution network in the distribution area can be aggregated to meet the high-power charging needs of electric vehicles in the distribution area, and the aggregation of each outgoing line only needs to be achieved through the connection of cables, which has low investment cost, simple operation, cost saving and strong applicability.

[0014] In addition, the high-power charging configuration device proposed in the above embodiment of the present invention may also have the following additional technical features:

[0015] According to one embodiment of the present invention, the first determination module is specifically used to calculate the surplus capacity of each outgoing line according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, and determine the number of available outgoing lines according to the surplus capacity of each outgoing line and the power of a single charging module, and calculate the configurable high-power charging capacity of the distribution area according to the number of available outgoing lines and the power of a single charging module.

[0016] According to one embodiment of the present invention, the first acquisition module is specifically used to predict the development trend of the city's electric vehicle stock in the next L years based on the city's historical annual stock of fuel vehicles, the city's historical annual stock of electric vehicles, GDP, and population development trends, using a random forest algorithm, and determine the predicted value of the city's electric vehicle stock in the next L year; and to predict the development trend of the electric vehicle stock in the distribution area in the next L years based on the city's historical annual stock of fuel vehicles, the city's historical annual and predicted annual stock of electric vehicles, and the historical annual stock of fuel vehicles in the distribution area, using regression analysis, and determine the predicted value of the electric vehicle stock in the distribution area in the next L year, wherein L is a positive integer.

[0017] According to one embodiment of the present invention, the second acquisition module is specifically used to count the charging time distribution of multiple users, the charging power distribution of vehicle models, and the ratio of high-power charging to conventional charging in the distribution area, and determine the probability of a single user using high-power charging and the average power of electric vehicles during high-power charging through the Monte Carlo method. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flowchart of a high-power charging configuration method according to an embodiment of the present invention;

[0019] Figure 2 A flowchart of a method for calculating configurable high-power charging capacity in a power distribution area according to an embodiment of the present invention;

[0020] Figure 3 A schematic diagram of high-power charging wiring according to an embodiment of the present invention;

[0021] Figure 4 A schematic diagram of high-power charging wiring according to a specific embodiment of the present invention;

[0022] Figure 5 It is a block diagram of a high-power charging configuration device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Figure 1 This is a flow chart of a high-power charging configuration method according to an embodiment of the present invention.

[0025] like Figure 1 As shown, the high-power charging configuration method of the embodiment of the present invention includes the following steps:

[0026] S1, determine the configurable high-power charging capacity of the distribution area according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line.

[0027] Furthermore, if Figure 2 As shown, the above step S1 may include:

[0028] S101, calculating the surplus capacity of each outgoing line according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line.

[0029] Specifically, the surplus capacity of each outgoing line can be calculated by the following formula:

[0030]

[0031] Among them, P i is the surplus capacity of each outgoing line of the distribution network in the distribution area, P set i is the rated capacity of each outgoing line of the distribution network in the distribution area, P load i The maximum capacity of the load carried by each outgoing line of the distribution network in the distribution area, i = 1, 2...N, N is the total number of outgoing lines of the distribution network in the distribution area, and N is a positive integer.

[0032] Furthermore, the surplus capacity of the distribution lines at all levels in the distribution network within the distribution area can be obtained as:

[0033] {P i}, i=1,2…N.

[0034] S102: Determine the number of available outgoing lines according to the surplus capacity of each outgoing line and the power of a single charging module.

[0035] Specifically, if the surplus capacity P of the outgoing line j of the distribution network in the distribution area j ≥P m , then the outgoing line j can be determined as an available outgoing line, and the surplus capacity of the outgoing lines available in the distribution network in the distribution area can be obtained as:

[0036] {P j}, j = 1, 2…M

[0037] Where M is the number of outgoing lines available in the distribution network within the distribution area, M≤N, and M is a positive integer, p m The power of a single charging module.

[0038] Furthermore, the number of available charging modules can be obtained as:

[0039]

[0040] S103: Calculate the configurable high-power charging capacity of the power distribution area according to the number of available outgoing lines and the power of a single charging module.

[0041] Specifically, the high-power charging capacity that can be configured in the distribution area can be calculated by the following formula:

[0042]

[0043] Among them, P a Provides configurable high-power charging capacity for distribution areas.

[0044] S2, obtaining a predicted value of the number of electric vehicles in the distribution area after a preset time.

[0045] Specifically, the random forest algorithm can be used to predict the development trend of the city's electric vehicle population in the next L years based on the historical annual population of fuel vehicles in the city, the historical annual population of electric vehicles in the city, GDP, and population development trends, and determine the predicted value D of the city's electric vehicle population in the next L years. L , where L is a positive integer. Then, based on the historical annual number of fuel vehicles in the city, the historical and predicted annual number of electric vehicles in the city, and the historical annual number of fuel vehicles in the distribution area, regression analysis can be used to predict the development trend of the number of electric vehicles in the distribution area in the next L years, and determine the predicted value F of the number of electric vehicles in the distribution area in the next L years. L .

[0046] In a specific embodiment of the present invention, taking the prediction of the number of electric vehicles in the next five years as an example, the historical annual number of urban fuel vehicles, the historical annual number of urban electric vehicles, GDP, and population development trends can be input into the random forest algorithm as four feature numbers. Specifically, 800 groups of 1000 groups of historical data in the past 10 years from 100 cities can be selected using bootstrap sampling as training samples, and the remaining 200 groups can be used as test samples to obtain a random forest model. The random forest model can be used to predict the development trend of the number of urban electric vehicles in the next five years, and determine the predicted value D5 of the number of urban electric vehicles in the fifth year.

[0047] Then, the historical annual number of fuel vehicles in the city, the historical annual and predicted annual number of electric vehicles in the city, and the historical annual number of fuel vehicles in the distribution area can be input into the regression algorithm as regression analysis parameters. Specifically, the annual number of fuel vehicles in the city in the past 10 years, the annual and predicted annual number of electric vehicles in the city, and the annual number of fuel vehicles in the distribution area can be used as independent variables for regression analysis, and the number of electric vehicles in the distribution area can be used as the dependent variable. Nonlinear regression is used to obtain the relationship between the dependent variable and the independent variable, predict the development trend of the number of electric vehicles in the distribution area in the next five years, and determine the predicted value F5 of the number of electric vehicles in the distribution area in the next 5 years.

[0048] It should be noted that in the above embodiment, the historical annual number of urban fuel vehicles includes the current number of urban fuel vehicles, and the historical annual number of urban electric vehicles includes the current number of urban electric vehicles.

[0049] S3, obtains the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging is performed.

[0050] Furthermore, the charging time distribution of multiple users, the charging power distribution of vehicle models, and the ratio of high-power charging to conventional charging in the distribution area can be counted, and the probability P of a single user using high-power charging can be determined by the Monte Carlo method. 快 The average power P when charging an electric vehicle at high power EV .

[0051] S4, determining the high-power charging demand capacity of the distribution area according to the predicted value of the number of electric vehicles in the distribution area after a preset time, the probability of users using high-power charging, and the average power of electric vehicles when performing high-power charging.

[0052] Specifically, the high-power charging demand capacity of the distribution area can be calculated by the following formula:

[0053] P r =F N *P 快 *P EV

[0054] Among them, P r Provides capacity for high-power charging needs in distribution areas.

[0055] S5: determining the actual high-power charging capacity of the distribution area according to the configurable high-power charging capacity of the distribution area and the high-power charging demand capacity of the distribution area.

[0056] Specifically, the actual high-power charging capacity of the distribution area is:

[0057] min{P a ,P r}.

[0058] S6, determining a high-power charging wiring scheme in the distribution area according to the actual high-power charging capacity in the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area, and the maximum capacity of the load carried by each outgoing line.

[0059] In one embodiment of the present invention, Figure 3 As shown, the outgoing line P1 of the distribution network in the distribution area can be connected to the charging module P 1-1 , P 1-2 ,…,P 1-C1 , and so on, the outgoing line P of the distribution network in the distribution area can be M Connect to charging module P M-1 , P M-2 , ..., P M-CM .

[0060] The following will be combined Figure 4 The specific high-power charging wiring schematic diagram shown further illustrates a high-power charging wiring solution according to an embodiment of the present invention.

[0061] In a specific embodiment of the present invention, Figure 4 As shown in the figure, the power distribution area is a certain community, and the power distribution in the community is divided into primary distribution and secondary distribution. Figure 4 In the two-level distribution network of a community shown in the figure, the surplus capacity of each outgoing line of the primary distribution network of the community is first counted, such as the surplus capacity of the outgoing lines CB1-1, CB1-2, and CB1-3 in the primary distribution network, and the surplus capacity of each outgoing line of the secondary distribution network is counted at the same time, such as the surplus capacity of the outgoing lines CB1-1-1, CB1-1-2, and CB1-1-3 in the secondary distribution network.

[0062] Furthermore, it is necessary to determine whether the surplus capacity of each outgoing line of the two-level distribution network of the community is greater than or equal to the power of a single charging module. Among them, the above-mentioned single charging module adopts the most commonly used charging module with a power of 15kW. If the surplus capacity of the outgoing line CB1-1-3 is P 1-1-3 =30kW, the surplus capacity of the outgoing line CB1-N-1 is P 1-N-1 =30kW, the surplus capacity of the outgoing line CB1-N-1 is P 1-N-2 =30kW, then the high-power charging capacity that can be configured in this community is P 1-1-3 +P 1-N-1 +P 1-N-2 =90kW.

[0063] In a specific embodiment of the present invention, Figure 4 The high-power charging pile shown needs to be configured with 6 charging modules a1, a2, a3, a4, a5, and a6 with the above-mentioned power of 15kW each. Among them, the charging modules a1 and a2 can be connected to the outgoing line CB1-1-3 and powered by the outgoing line CB1-1-3, the charging modules a3 and a4 can be connected to the outgoing line CB1-N-1 and powered by the outgoing line CB1-N-1, and the charging modules a5 and a6 can be connected to the outgoing line CB1-N-2 and powered by the outgoing line CB1-N-2.

[0064] According to the high-power charging configuration method proposed in the embodiment of the present invention, the configurable high-power charging capacity of the distribution area is determined according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, the predicted value of the number of electric vehicles in the distribution area after a preset time is obtained, the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging are obtained, the high-power charging demand capacity of the distribution area is determined according to the predicted value of the number of electric vehicles in the distribution area after a preset time, the probability of users using high-power charging and the average power of the electric vehicle when high-power charging is performed, the actual high-power charging capacity of the distribution area is determined according to the configurable high-power charging capacity of the distribution area and the high-power charging demand capacity of the distribution area, and the high-power charging wiring scheme in the distribution area is determined according to the actual high-power charging capacity of the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line. Therefore, the surplus capacity of each outgoing line of the distribution network in the distribution area can be aggregated to meet the high-power charging demand of the electric vehicles in the distribution area, and the aggregation of each outgoing line only needs to be achieved through the connection of cables, which has low investment cost, simple operation, cost saving and strong applicability.

[0065] Corresponding to the high-power charging configuration method proposed in the above embodiment, the present invention also proposes a high-power charging configuration device.

[0066] like Figure 5 As shown, the high-power charging configuration device according to the embodiment of the present invention includes: a first determination module 10, a first acquisition module 20, a second acquisition module 30, a second determination module 40, a third determination module 50 and a fourth determination module 60. Among them, the first determination module 10 is used to determine the configurable high-power charging capacity of the distribution area according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; the first acquisition module 20 is used to obtain the predicted value of the number of electric vehicles in the distribution area after a preset time; the second acquisition module 30 is used to obtain the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging is performed; the second determination module 40 is used to determine the high-power charging demand capacity of the distribution area according to the predicted value of the number of electric vehicles in the distribution area after a preset time, the probability of users using high-power charging and the average power of the electric vehicle when high-power charging is performed; the third determination module 50 is used to determine the actual high-power charging capacity of the distribution area according to the configurable high-power charging capacity of the distribution area and the high-power charging demand capacity of the distribution area; the fourth determination module 50 is used to determine the high-power charging wiring plan in the distribution area according to the actual high-power charging capacity of the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line.

[0067] In one embodiment of the present invention, the first determination module 10 is specifically used to calculate the surplus capacity of each outgoing line according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, and to determine the number of available outgoing lines according to the surplus capacity of each outgoing line and the power of a single charging module, and to calculate the configurable high-power charging capacity of the distribution area according to the number of available outgoing lines and the power of a single charging module.

[0068] In a specific embodiment of the present invention, the first determining module 10 can calculate the surplus capacity of each outgoing line by the following formula:

[0069]

[0070] Among them, P i is the surplus capacity of each outgoing line of the distribution network in the distribution area, P set i is the rated capacity of each outgoing line of the distribution network in the distribution area, P load i The maximum capacity of the load carried by each outgoing line of the distribution network within the distribution area, i = 1, 2...N, N is the total number of distribution outgoing lines.

[0071] Furthermore, the first determination module 10 can obtain the surplus capacity of the distribution lines at all levels of the distribution network in the distribution area:

[0072] {P i}, i=1,2…N.

[0073] In a specific embodiment of the present invention, if the surplus capacity P of the outgoing line j of the distribution network in the distribution area j ≥P m , then the outgoing line j can be determined as an available outgoing line, and thus the first determination module 10 can obtain the surplus capacity of the outgoing lines available to the distribution network in the distribution area as:

[0074] {P j}, j = 1, 2…M

[0075] Where M is the number of outgoing lines available in the distribution network within the distribution area, M≤N, and M is a positive integer, P m The power of a single charging module.

[0076] Further, the first determining module 10 may obtain the number of available modules as:

[0077]

[0078] In a specific embodiment of the present invention, in combination with the number of available outgoing lines and the power of a single charging module obtained in the above embodiment, the first determination module 10 can calculate the configurable high-power charging capacity of the power distribution area through the following formula:

[0079]

[0080] Among them, P a Provides configurable high-power charging capacity for distribution areas.

[0081] In one embodiment of the present invention, the first acquisition module 20 can specifically use the random forest algorithm to predict the development trend of the number of urban electric vehicles in the next L years based on the historical annual number of urban fuel vehicles, the historical annual number of urban electric vehicles, GDP, and population development trends, and determine the predicted value D of the number of urban electric vehicles in the next L years. L Based on the historical annual number of urban fuel vehicles, the historical and predicted annual number of urban electric vehicles, and the historical annual number of fuel vehicles in the distribution area, regression analysis is used to predict the development trend of the number of electric vehicles in the distribution area in the next L years, and the predicted value F of the number of electric vehicles in the distribution area in the next L years is determined. L , where L is a positive integer.

[0082] In a specific embodiment of the present invention, taking the prediction of the number of electric vehicles in the next five years as an example, the first acquisition module 20 can input the historical annual number of urban fuel vehicles, the historical annual number of urban electric vehicles, GDP, and population development trends as four feature numbers into the random forest algorithm. Specifically, 800 groups of 1000 groups of historical data in the past 10 years from 100 cities can be extracted using bootstrap sampling as training samples, and the remaining 200 groups can be used as test samples to obtain a random forest model. Among them, in the random forest model, the depth of the tree is 3, with a total of 100 trees, and each tree uses a classification regression tree model. The development trend of the number of urban electric vehicles in the next five years is predicted by the random forest model, and the predicted value D5 of the number of urban electric vehicles in the fifth year in the future is determined.

[0083] Furthermore, the first acquisition module 20 can input the historical annual number of fuel vehicles in the city, the historical annual and predicted annual number of electric vehicles in the city, and the historical annual number of fuel vehicles in the distribution area as regression analysis parameters into the regression analysis algorithm. Specifically, the annual number of fuel vehicles in the city in the past 10 years, the annual and predicted annual number of electric vehicles in the city, and the annual number of fuel vehicles in the distribution area can be used as independent variables for regression analysis, and the number of electric vehicles in the distribution area can be used as the dependent variable. Nonlinear regression is used to derive the relationship between the dependent variable and the independent variable, predict the development trend of the number of electric vehicles in the distribution area in the next five years, and determine the predicted value F5 of the number of electric vehicles in the distribution area in the fifth year in the future.

[0084] It should be noted that in the above embodiment, the historical annual number of urban fuel vehicles includes the current number of urban fuel vehicles, and the historical annual number of urban electric vehicles includes the current number of urban electric vehicles.

[0085] In one embodiment of the present invention, the second acquisition module 30 can be specifically used to count the charging time distribution of multiple users, the charging power distribution of vehicle models, and the ratio of high-power charging to conventional charging in the power distribution area, and determine the probability P of a single user using high-power charging by Monte Carlo method. 快 The average power P when charging an electric vehicle at high power EV .

[0086] In one embodiment of the present invention, the second determination module 40 may specifically calculate the high-power charging demand capacity of the power distribution area by the following formula:

[0087] P r =F N *P 快 *P EV

[0088] Among them, P r Provides capacity for high-power charging needs in distribution areas.

[0089] In one embodiment of the present invention, the actual high-power charging capacity of the power distribution area that can be determined by the third determination module 50 is:

[0090] min{P a ,P r}.

[0091] In one embodiment of the present invention, the fourth determining module 60 can be specifically used to determine Figure 3 According to the wiring scheme determined by the fourth determination module 60, the outgoing line P1 of the distribution network in the distribution area can be connected to the charging module P 1-1 , P 1-2 ,…,P 1-C1 , and so on, the outgoing line P of the distribution network in the distribution area M Connect to the charging module P M-1 , P M-2 , ..., P M- CM.

[0092] The following will be combined Figure 4 The specific high-power charging wiring schematic diagram shown further illustrates a high-power charging wiring solution according to an embodiment of the present invention.

[0093] In a specific embodiment of the present invention, Figure 4As shown in the figure, the power distribution area is a certain community, and the power distribution in the community is divided into primary distribution and secondary distribution. Figure 4 In the two-level distribution network of a community shown in the figure, the surplus capacity of each outgoing line of the primary distribution network of the community is first counted, such as the surplus capacity of the outgoing lines CB1-1, CB1-2, and CB1-3 in the primary distribution network, and the surplus capacity of each outgoing line of the secondary distribution network is counted at the same time, such as the surplus capacity of the outgoing lines CB1-1-1, CB1-1-2, and CB1-1-3 in the secondary distribution network.

[0094] Furthermore, it is necessary to determine whether the surplus capacity of each outgoing line of the two-level distribution network of the community is greater than or equal to the power of a single charging module. Among them, the above-mentioned single charging module adopts the most commonly used charging module with a power of 15KW. If the surplus capacity of the outgoing line CB1-1-3 is P 1-1-3 =30kW, the surplus capacity of the outgoing line CB1-N-1 is P 1-N-1 =30kW, the surplus capacity of the outgoing line CB1-N-1 is P 1-N-2 =30kW, then the high-power charging capacity that can be configured in this community is P 1-1-3 +P 1-N-1 +P 1-N-2 =90kW.

[0095] In a specific embodiment of the present invention, Figure 4 The high-power charging pile shown needs to be configured with 6 charging modules a1, a2, a3, a4, a5, and a6 with the above-mentioned power of 15kW each. Among them, the charging modules a1 and a2 can be connected to the outgoing line CB1-1-3 and powered by the outgoing line CB1-1-3, the charging modules a3 and a4 can be connected to the outgoing line CB1-N-1 and powered by the outgoing line CB1-N-1, and the charging modules a5 and a6 can be connected to the outgoing line CB1-N-2 and powered by the outgoing line CB1-N-2.

[0096] According to the high-power charging configuration method proposed in an embodiment of the present invention, the configurable high-power charging capacity of the distribution area is determined by a first determination module according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, the predicted value of the number of electric vehicles in the distribution area after a preset time is obtained by a first acquisition module, the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging are obtained by a second acquisition module, and the high-power charging capacity of the distribution area is determined by a second determination module according to the predicted value of the number of electric vehicles in the distribution area after a preset time, the probability of the user using high-power charging and the average power of the electric vehicle when high-power charging is performed. The power demand capacity is determined by the third determination module according to the configurable high-power charging capacity of the distribution area and the high-power charging demand capacity of the distribution area. The high-power charging wiring scheme in the distribution area is determined by the fourth determination module according to the actual high-power charging capacity of the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line. As a result, the surplus capacity of each outgoing line of the distribution network in the distribution area can be aggregated to meet the high-power charging demand in the area, and the surplus capacity of each outgoing line only needs to be aggregated through cables, which has low investment cost, simple operation, cost saving and strong applicability.

[0097] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0098] In the present invention, unless otherwise clearly specified and limited, the terms "connected", "connection" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0099] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0100] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A high-power charging configuration method, characterized in that: The following steps are involved: Determine the configurable high-power charging capacity of the distribution area according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; Obtain a predicted value of the number of electric vehicles in the power distribution area after a preset time; Obtain the probability of a single user using high-power charging and the average power of electric vehicles when using high-power charging; Determine the high-power charging demand capacity of the power distribution area according to the predicted value of the number of electric vehicles in the power distribution area after the preset time, the probability of the user using high-power charging, and the average power of the electric vehicle when high-power charging is performed; Determine the actual high-power charging capacity of the power distribution area according to the configurable high-power charging capacity of the power distribution area and the high-power charging demand capacity of the power distribution area; Determine the high-power charging wiring scheme in the distribution area according to the actual high-power charging capacity in the distribution area, the rated capacity of each outgoing line of the distribution network in the distribution area, and the maximum capacity of the load carried by each outgoing line, The high-power charging capacity that can be configured in the distribution area is determined according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, specifically including: calculating the surplus capacity of each outgoing line according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; determining the number of available outgoing lines according to the surplus capacity of each outgoing line and the power of a single charging module; calculating the high-power charging capacity that can be configured in the distribution area according to the number of available outgoing lines and the power of a single charging module. The high-power charging capacity that can be configured in the distribution area is calculated by the following formula: Among them, P a is the high-power charging capacity that can be configured in the distribution area, M is the number of outgoing lines available in the distribution network in the distribution area, and P m is the power of a single charging module, C j is the number of charging modules available for line j, and the number of available charging modules C j for: Among them, P j is the spare capacity of outgoing line j.

2. The high-power charging configuration method according to claim 1, characterized in that: Obtaining a predicted value of the number of electric vehicles in the power distribution area after a preset time, specifically including: According to the historical annual number of fuel vehicles in the city, the historical annual number of electric vehicles in the city, GDP, and population development trends, the random forest algorithm is used to predict the development trend of the number of electric vehicles in the city in the next L years, and the predicted value of the number of electric vehicles in the city in the next L years is determined, where L is a positive integer; Based on the historical annual number of fuel vehicles in the city, the historical and predicted annual number of electric vehicles in the city, and the historical annual number of fuel vehicles in the distribution area, regression analysis is used to predict the development trend of the number of electric vehicles in the distribution area in the next L years, and determine the predicted value of the number of electric vehicles in the distribution area in the next L years.

3. The high-power charging configuration method according to claim 2, characterized in that: Obtain the probability of a single user using high-power charging and the average power of electric vehicles when charging at high power, including: The charging time distribution of multiple users, the charging power distribution of vehicle models, and the ratio of high-power charging to conventional charging in the distribution area are counted, and the probability of a single user using high-power charging and the average power of electric vehicles during high-power charging are determined by the Monte Carlo method.

4. A high-power charging configuration device, characterized in that: include: A first determination module, the first determination module is used to determine the configurable high-power charging capacity of the distribution area according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line; A first acquisition module, the first acquisition module is used to obtain a predicted value of the number of electric vehicles in the power distribution area after a preset time; A second acquisition module, the second acquisition module is used to obtain the probability of a single user using high-power charging and the average power of the electric vehicle when high-power charging is performed; A second determination module, the second determination module is used to determine the high-power charging demand capacity of the distribution area according to the predicted value of the number of electric vehicles in the distribution area after the preset time, the probability of the user using high-power charging, and the average power of the electric vehicle when high-power charging is performed; A third determination module, the third determination module is used to determine the actual high-power charging capacity of the power distribution area according to the configurable high-power charging capacity of the power distribution area and the high-power charging demand capacity of the power distribution area; a fourth determination module, the fourth determination module being used to determine a high-power charging wiring scheme in the power distribution area according to an actual high-power charging capacity in the power distribution area, a rated capacity of each outgoing line of the power distribution network in the power distribution area, and a maximum capacity of a load carried by each outgoing line, The first determination module is specifically used to calculate the surplus capacity of each outgoing line according to the rated capacity of each outgoing line of the distribution network in the distribution area and the maximum capacity of the load carried by each outgoing line, and determine the number of available outgoing lines according to the surplus capacity of each outgoing line and the power of a single charging module, and calculate the configurable high-power charging capacity of the distribution area according to the number of available outgoing lines and the power of a single charging module. The first determination module calculates the configurable high-power charging capacity of the distribution area through the following formula: Among them, P a is the high-power charging capacity that can be configured in the distribution area, M is the number of outgoing lines available in the distribution network in the distribution area, and P m is the power of a single charging module, C j is the number of charging modules available for line j, and the number of available charging modules C j for: Among them, P j is the spare capacity of outgoing line j.

5. The high-power charging configuration device according to claim 4, characterized in that: The first acquisition module is specifically used to predict the development trend of the city's electric vehicle ownership in the next L years using a random forest algorithm based on the city's historical annual ownership of fuel vehicles, the city's historical annual ownership of electric vehicles, GDP, and population development trends, and determine the predicted value of the city's electric vehicle ownership in the next L year; and to predict the development trend of the electric vehicle ownership in the distribution area in the next L years using regression analysis based on the city's historical annual ownership of fuel vehicles, the city's historical annual and predicted annual ownership of electric vehicles, and the historical annual ownership of fuel vehicles in the distribution area, and determine the predicted value of the electric vehicle ownership in the distribution area in the next L year, wherein L is a positive integer.

6. The high-power charging configuration device according to claim 5, characterized in that: The second acquisition module is specifically used to count the charging time distribution of multiple users, the charging power distribution of vehicle models, and the ratio of high-power charging to conventional charging in the distribution area, and determine the probability of a single user using high-power charging and the average power of electric vehicles during high-power charging through the Monte Carlo method.

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