Electric vehicle real-time electricity price calculation method and system considering charging pile utilization rate

Abstract

The invention relates to the technical field of power demand response, and provides an electric vehicle real-time electricity price calculation method and system considering a charging pile utilization rate, and the method comprises the following steps: building a user charging intention model through considering the charging intention of a charging station charging price and a date attribute for an electric vehicle user; based on the utilization rate and the congestion degree of the charging station, determining a charging pile utilization rate correction coefficient; constructing a target function by maximizing the comprehensive benefit of the charging station operator; according to the user charging intention model, the expected charging user number at any moment is determined, the real-time electricity price at the corresponding moment is adjusted according to the charging pile utilization rate correction coefficient, and an electric vehicle real-time charging electricity price planning result is obtained by solving the target function. Compared with a traditional method, the method optimizes the electricity price composition structure of the charging station, improves the operation income of the charging station, effectively alleviates the problem of insufficient utilization rate of the charging pile, optimizes the power resource configuration, and has a wide application prospect.

Description

Technical Field

[0001] The present invention relates to the technical field of power demand response, and more specifically, to a method and system for calculating the real-time electricity price of an electric vehicle taking into account the utilization rate of a charging pile. Background Art

[0002] In recent years, with the increasing global attention to environmental protection and sustainable development, new energy vehicles, especially electric vehicles, have grown rapidly. Large-scale disorderly charging will increase the burden on the distribution network, resulting in increased transmission losses and heavy overloads, which is not conducive to the safe and economic operation of the power grid. Charging infrastructure provides charging and replacement services for electric vehicles. It usually uses time-of-use electricity prices to guide electric vehicle users to charge during non-peak hours with lower electricity prices according to the load of the power grid, thereby ensuring the charging needs of users while reducing the pressure on the power grid during peak hours, achieving a balance between power supply and demand and stable power grid operation.

[0003] However, at present, charging infrastructure still has problems such as unreasonable structure, unbalanced services, irregular operations, and poor dispatch optimization. At the same time, there is a contradiction between low utilization rate and congestion of electric vehicle charging piles. Some electric vehicle charging operators are in a loss-making situation, which has dampened the enthusiasm of charging infrastructure builders. Therefore, when setting charging electricity prices to dispatch users, it is necessary to consider not only the fluctuation of new energy on the power generation side, but also the economic situation of power transmission of the distribution network on the power consumption side to ensure the economic benefits of electric vehicle charging operators. Summary of the invention

[0004] In order to overcome the defects of the existing charging infrastructure, such as unreasonable structure and unbalanced services, the present invention provides a method and system for calculating the real-time electricity price of electric vehicles taking into account the utilization rate of charging piles.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A method for calculating the real-time electricity price of an electric vehicle taking into account the utilization rate of a charging pile comprises the following steps:

[0007] Considering the charging price and date attributes of charging stations on the charging willingness of electric vehicle users, a user charging intention model is constructed;

[0008] Determine the charging pile utilization correction factor based on the utilization and congestion of the charging station;

[0009] The objective function is constructed by maximizing the comprehensive benefits of charging station operators;

[0010] The expected number of charging users at any time is determined according to the user charging intention model, and the real-time electricity price at the corresponding time is adjusted according to the charging pile utilization correction coefficient, and the real-time electricity price planning result of the electric vehicle is obtained by solving the objective function.

[0011] Furthermore, the present invention also proposes a real-time electricity price calculation system for electric vehicles that takes into account the utilization rate of charging piles, and applies the real-time electricity price calculation method for electric vehicles that takes into account the utilization rate of charging piles described in the present invention. The system includes:

[0012] The charging intention update module is used to update the user charging intention model based on the charging price and date attributes of the charging station to determine the charging intention of the electric vehicle user;

[0013] A charging pile utilization correction module, used to determine a charging pile utilization correction coefficient based on the utilization and congestion of the charging station;

[0014] The real-time electricity price calculation module is used to determine the expected number of charging users at any time according to the user charging intention model, and adjust the real-time electricity price at the corresponding time according to the charging pile utilization correction coefficient, and obtain the real-time electricity price planning result of the electric vehicle by solving the objective function of maximizing the comprehensive benefits of the charging station operator.

[0015] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0016] The present invention aims to maximize the comprehensive benefits of charging station operators. The number of charging users at different times and different charging prices is determined according to the user charging intention model. After the data correction of the correction coefficient is coordinated, the optimal real-time charging price planning result of electric vehicles is obtained by solving the objective function. While satisfying the charging needs of users and improving the utilization rate of charging piles, the comprehensive benefits of charging station operators are maximized.

[0017] Compared with the traditional method, the present invention optimizes the electricity price composition structure of the charging station, improves the operating income of the charging station, effectively alleviates the problem of insufficient utilization of charging piles, optimizes the allocation of power resources, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a flowchart of a method for calculating the real-time electricity price of an electric vehicle according to an embodiment of the present invention.

[0019] Figure 2 The figure is a structural diagram of a real-time electricity price calculation system for electric vehicles according to one embodiment of the present invention. DETAILED DESCRIPTION

[0020] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0021] The terms used in the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The singular forms "a", "the" and "the" used in the present invention and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0022] It should be understood that although the terms first, second, third, etc. may be used in the present invention to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present invention, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0023] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] Example 1

[0025] This embodiment proposes a method for calculating the real-time electricity price of electric vehicles taking into account the utilization rate of charging piles. Figure 1 , which is a flow chart of the method for calculating the real-time electricity price of electric vehicles taking into account the utilization rate of charging piles in this embodiment.

[0026] The method for calculating the real-time electricity price of electric vehicles taking into account the utilization rate of charging piles proposed in this embodiment includes the following steps:

[0027] S1. Considering the charging price and date attributes of the charging station on the charging willingness of electric vehicle users, a user charging intention model is constructed;

[0028] S2. Determine the charging pile utilization correction factor based on the utilization rate and congestion of the charging station;

[0029] S3, constructing the objective function to maximize the comprehensive benefits of charging station operators;

[0030] S4. Determine the expected number of charging users at any time according to the user charging intention model, and adjust the real-time electricity price at the corresponding time according to the charging pile utilization correction coefficient, and obtain the real-time electricity price planning result of the electric vehicle by solving the objective function.

[0031] This embodiment collects historical operation data of charging stations, adopts a time-sharing step-by-step charging control strategy, and formulates real-time electricity prices for electric vehicles at charging stations, thereby providing a theoretical basis and practical guidance for time-sharing charging control of electric vehicles.

[0032] Specifically, this embodiment takes into account the different charging prices and date attributes of each user, and constructs a user charging intention model by fitting historical data; this embodiment also takes into account the utilization and congestion of charging stations, and constructs a correction coefficient for the utilization of charging stations; further, this embodiment takes maximizing the comprehensive benefits of charging station operators as the goal, determines the number of charging users at different times and different charging prices according to the user charging intention model, and after the data is corrected with the correction coefficient, the optimal real-time charging electricity price planning result for electric vehicles is obtained by solving the objective function.

[0033] During the specific implementation process, a historical data set is constructed by collecting the historical operation data of charging stations and the unit electricity purchase cost of charging stations.

[0034] Among them, the historical operation data of charging stations include the charging price of charging stations, the number of electric vehicles at charging stations, the battery capacity of electric vehicles at charging stations, the charging power of electric vehicles at charging stations, the maximum number of electric vehicles allowed to be accommodated at charging stations, and the waiting time of electric vehicles at charging stations.

[0035] In an optional embodiment, the step of constructing a user charging intention model includes the following steps:

[0036] S1.1. Collect historical operation data of charging stations, including the real-time charging price, number of charging users and / or waiting time of electric vehicles at charging stations at each sampling time within at least one week;

[0037] S1.2. Fit the historical operation data of the charging station based on the sampling time and the corresponding charging price to build a user charging intention model; the expression is:

[0038]

[0039] Among them, c i，j represents the user's intended charging price at the jth moment on the i-th day, represents the charging user at the jth moment on the i-th day; α i，j , β i，j , γ i，j is the model parameter.

[0040] Exemplarily, the model parameter α of the user charging intention model is i，j , β i，j , γ i，j Adjust settings according to actual application scenarios.

[0041] Among them, i∈[1,7] is the number of Sundays in the weekly time series. In particular, in the case of national statutory holidays, it can be optionally set to i∈[1,6].

[0042] In an optional embodiment, determining the charging pile utilization correction coefficient based on the utilization and congestion of the charging station includes the following steps:

[0043] S2.1. Collect historical operation data of charging stations, including the number of charging piles in operation, the number of charging users, the maximum number of electric vehicles allowed to be accommodated at the charging station, the average queuing time of electric vehicles at the charging station, and / or the average charging time of electric vehicles at the charging station at each sampling time within at least one week in history;

[0044] S2.2. Calculate the charging station utilization rate μus at the jth moment of the i-th day of the charging station e , i, j; its expression is:

[0045]

[0046] Among them, m i，j is the number of charging users at the charging station at the jth moment on the i-th day; n i，j is the number of charging piles with normal operation capacity at the charging station at the jth moment on the i-th day;

[0047] S2.3. Calculate the congestion degree μ of the charging station at the jth time on the i-th day queue，i，j ; Its expression is:

[0048]

[0049] in, represents the average waiting time of electric vehicles at charging stations, represents the average charging time of electric vehicles at the charging station; n p Indicates the maximum number of electric vehicles that a charging station is allowed to accommodate;

[0050] S2.4, according to the charging station utilization rate μ at any time use，i，j and charging station congestion μ queue，i，j , calculate the normalized coefficient β of charging station utilization use and the normalized coefficient of charging station congestion β queue , and further determine the charging pile utilization correction factor A i，j ; Its expression is:

[0051]

[0052] Among them, μ queue，max and μ queue，min They represent the maximum and minimum values ​​of the charging station congestion respectively; μ use，max and μ use，min Indicates the maximum and minimum values ​​of charging station utilization.

[0053] In an optional embodiment, in step S3, the objective function aims to maximize the comprehensive benefits of the charging station operator and determines the real-time electricity price of the charging station at each time of the day; the expression of the comprehensive benefits R of the charging station operator is:

[0054]

[0055] Among them, C i，j represents the real-time electricity price of the charging station at the jth moment on the i-th day, c i，j，base represents the unit electricity purchase cost of the charging station at the jth moment on the i-th day, P c，i，j represents the total charging power of the charging station at the jth moment on the i-th day, and ΔT is the preset electricity price update time interval.

[0056] Further, in an optional embodiment, obtaining the real-time electricity price planning result of the electric vehicle by solving the objective function comprises the following steps:

[0057] S4.1. Determine the user's intended charging price c at each moment according to the user's charging intention model i，j 、Number of charging users m i，j , and the corresponding charging power of the charging electric vehicle;

[0058] S4.2, based on the charging pile utilization correction coefficient, the user's intended charging price c at the corresponding time i , j is adjusted, and the total charging power of the charging station is determined according to the number of charging users at the corresponding moment and the charging power of the corresponding charging electric vehicles; its expression is:

[0059] C i，j =A i，j ·c i，j

[0060]

[0061]

[0062] in, represents the charging price c in the user charging intention model i，j The corresponding number of users who intend to charge; A i，jis the charging pile utilization correction factor; m i，j is the number of charging users at the charging station at the jth moment on the i-th day; n i，j is the number of charging piles with normal operation capacity at the charging station at the jth moment on the i-th day; p c，i，j，k represents the charging power of the electric vehicle of user k at the jth moment on the i-th day;

[0063] S4.3. Input the adjusted user intended charging price and the total charging power of the charging station into the objective function and solve it to obtain the real-time electricity price of the charging station at various times of the day.

[0064] Compared with the traditional method, this embodiment optimizes the electricity price composition structure of the charging station, improves the operating income of the charging station, effectively alleviates the problem of insufficient utilization of charging piles, optimizes the allocation of power resources, and has broad application prospects.

[0065] Example 2

[0066] This embodiment applies the electric vehicle real-time electricity price calculation method considering the charging pile utilization rate proposed in Example 1, and proposes an electric vehicle real-time electricity price calculation system considering the charging pile utilization rate. Figure 2 , which is an architecture diagram of the electric vehicle real-time electricity price calculation system taking into account the charging pile utilization rate of this embodiment.

[0067] The electric vehicle real-time electricity price calculation system considering the utilization rate of charging piles proposed in this embodiment includes:

[0068] The charging intention update module is used to update the user charging intention model based on the charging price and date attributes of the charging station to determine the charging intention of the electric vehicle user;

[0069] A charging pile utilization correction module, used to determine a charging pile utilization correction coefficient based on the utilization and congestion of the charging station;

[0070] The real-time electricity price calculation module is used to determine the expected number of charging users at any time according to the user charging intention model, and adjust the real-time electricity price at the corresponding time according to the charging pile utilization correction coefficient, and obtain the real-time electricity price planning result of the electric vehicle by solving the objective function of maximizing the comprehensive benefits of the charging station operator.

[0071] In an optional embodiment, the charging intention update module performs the following steps:

[0072] Collect historical operation data of charging stations, including real-time charging prices, number of charging users and / or waiting time of electric vehicles at charging stations at each sampling time within at least one week;

[0073] The historical operation data of the charging station is fitted based on the sampling time and the corresponding charging price to construct a user charging intention model; its expression is:

[0074]

[0075] Among them, c i，j represents the user's intended charging price at the jth moment on the i-th day, represents the charging user at the jth moment on the i-th day; α i，j , β i，j , γ i，j is the model parameter.

[0076] In an optional embodiment, the charging pile utilization correction module performs the following steps:

[0077] Collect historical operation data of charging stations, including the number of working charging piles at the charging station, the number of charging users, the maximum number of electric vehicles allowed to be accommodated at the charging station, the average queuing time of electric vehicles at the charging station, and / or the average charging time of electric vehicles at the charging station at each sampling time within at least one week in history;

[0078] Calculate the charging station utilization μ at the jth time on the i-th day of the charging station use，i，j ; Its expression is:

[0079]

[0080] Among them, m i，j is the number of charging users at the charging station at the jth moment on the i-th day; n i，j is the number of charging piles with normal operation capacity at the charging station at the jth moment on the i-th day;

[0081] Calculate the congestion degree μ of the charging station at the jth time on the i-th day queue，i，j ; Its expression is:

[0082]

[0083] in, represents the average waiting time of electric vehicles at charging stations, represents the average charging time of electric vehicles at the charging station; n p Indicates the maximum number of electric vehicles that a charging station is allowed to accommodate;

[0084] According to the charging station utilization μ at any time use，i，j and charging station congestion μ queue，i，j , calculate the normalized coefficient β of charging station utilization use and the normalized coefficient of charging station congestion β queue , and further determine the charging pile utilization correction factor A i，j ; Its expression is:

[0085]

[0086] Among them, μ queue，max and μ queue，min They represent the maximum and minimum values ​​of the charging station congestion respectively; μ use，max and μ use，min Indicates the maximum and minimum values ​​of charging station utilization.

[0087] In an optional embodiment, the objective function aims to maximize the comprehensive benefits of the charging station operator and determines the real-time electricity price of the charging station at various times of the day; the expression of the comprehensive benefits R of the charging station operator is:

[0088]

[0089] Among them, C i，j represents the real-time electricity price of the charging station at the jth moment on the i-th day, c i，j，base represents the unit electricity purchase cost of the charging station at the jth moment on the i-th day, P c，i，j represents the total charging power of the charging station at the jth moment on the i-th day, and ΔT is the preset electricity price update time interval.

[0090] In an optional embodiment, the real-time electricity price calculation module performs the following steps:

[0091] Determine the user's intended charging price c at each moment according to the user's charging intention model i，j 、Number of charging users m i，j , and the corresponding charging power of the charging electric vehicle;

[0092] The user's intended charging price c at the corresponding moment is calculated based on the charging pile utilization correction coefficient. i，j Adjustments are made, and the total charging power of the charging station is determined according to the number of charging users at the corresponding moment and the charging power of the corresponding electric vehicles; its expression is:

[0093] C i，j =A i，j ·c i，j

[0094]

[0095] in, represents the charging price c in the user charging intention model i，j The corresponding number of users who intend to charge; A i，j is the charging pile utilization correction factor; m i，j is the number of charging users at the charging station at the jth moment on the i-th day; n i，jis the number of charging piles with normal operation capacity at the charging station at the jth moment on the i-th day; p c，i，j，k represents the charging power of the electric vehicle of user k at the jth moment on the i-th day;

[0096] The adjusted user intended charging price and the total charging power of the charging station are input into the objective function and solved to obtain the real-time electricity price of the charging station at various times of the day.

[0097] It can be understood that the system of this embodiment corresponds to the method of the above-mentioned embodiment 1, and the options in the above-mentioned embodiment 1 are also applicable to this embodiment, so they will not be described repeatedly here.

[0098] Example 3

[0099] This embodiment proposes a computer device, including a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes all or part of the steps of the method for calculating the real-time electricity price of an electric vehicle proposed in Example 1.

[0100] Example 4

[0101] This embodiment proposes a storage medium on which computer-readable instructions are stored, wherein the computer-readable instructions, when executed by a processor, implement all or part of the steps of the method for calculating the real-time electricity price of an electric vehicle proposed in Embodiment 1.

[0102] Exemplarily, the storage medium includes, but is not limited to, a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0103] Exemplarily, the instructions, programs, code sets or instruction sets may be implemented using conventional programming languages.

[0104] Exemplarily, the processor includes but is not limited to a smart phone, a personal computer, a server, a network device, etc., and is used to execute all or part of the steps of the method for calculating the real-time electricity price of an electric vehicle described in Example 1.

[0105] Each embodiment of the present invention is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device embodiment described above is merely exemplary, in which the modules described as separate components may or may not be physically separated, and the functions of each module can be implemented in the same or one or more software and / or hardware when implementing the scheme of the present invention. It is also possible to select some or all of the modules according to actual needs to achieve the purpose of the scheme of this embodiment.

[0106] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A method for calculating the real-time electricity price of electric vehicles taking into account the utilization rate of charging piles, characterized in that: The following steps are involved: Considering the charging price and date attributes of charging stations on the charging willingness of electric vehicle users, a user charging intention model is constructed; Determine the charging pile utilization correction factor based on the utilization and congestion of the charging station; The objective function is constructed by maximizing the comprehensive benefits of charging station operators; The expected number of charging users at any time is determined according to the user charging intention model, and the real-time electricity price at the corresponding time is adjusted according to the charging pile utilization correction coefficient, and the real-time charging electricity price planning result of the electric vehicle is obtained by solving the objective function.

2. The method for calculating the real-time electricity price of an electric vehicle according to claim 1, characterized in that: The step of constructing a user charging intention model comprises the following steps: Collect historical operation data of charging stations, including real-time charging prices, number of charging users and / or waiting time of electric vehicles at charging stations at each sampling time within at least one week; The historical operation data of the charging station is fitted based on the sampling time and the corresponding charging price to construct a user charging intention model; its expression is: Among them, c i,j represents the user's intended charging price at the jth moment on the i-th day, represents the charging user at the jth moment on the i-th day; α i,j , β i,j , γ i,j is the model parameter.

3. The method for calculating the real-time electricity price of an electric vehicle according to claim 1, characterized in that: Determining the charging pile utilization correction coefficient based on the utilization rate and congestion of the charging station includes the following steps: Collect historical operation data of charging stations, including the number of working charging piles at the charging station, the number of charging users, the maximum number of electric vehicles allowed to be accommodated at the charging station, the average queuing time of electric vehicles at the charging station, and / or the average charging time of electric vehicles at the charging station at each sampling time within at least one week in history; Calculate the charging station utilization μ at the jth time on the i-th day of the charging station use,i,j ; Its expression is: Among them, m i,j is the number of charging users at the charging station at the jth moment on the i-th day; n i,j is the number of charging piles with normal operation capacity at the charging station at the jth moment on the i-th day; Calculate the congestion degree μ of the charging station at the jth time on the i-th day queue,i,j ; Its expression is: in, represents the average waiting time of electric vehicles at charging stations, represents the average charging time of electric vehicles at the charging station; n p Indicates the maximum number of electric vehicles that a charging station is allowed to accommodate; According to the charging station utilization μ at any time use,i,j and charging station congestion μ queue,i,j , calculate the normalized coefficient β of charging station utilization use and the normalized coefficient of charging station congestion β queue , and further determine the charging pile utilization correction factor A i,j ; Its expression is: Among them, μ queue,max and μ queue,min They represent the maximum and minimum values ​​of the charging station congestion respectively; μ use,max and μ use,min Indicates the maximum and minimum values ​​of charging station utilization.

4. The method for calculating the real-time electricity price of an electric vehicle according to any one of claims 1 to 3, characterized in that: The objective function aims to maximize the comprehensive benefits of the charging station operator and determines the real-time electricity price of the charging station at each time of the day; the expression of the comprehensive benefits R of the charging station operator is: Among them, C i,j represents the real-time electricity price of the charging station at the jth moment on the i-th day, c i,j,base represents the unit electricity purchase cost of the charging station at the jth moment on the i-th day, P c,i,j represents the total charging power of the charging station at the jth moment on the i-th day, and ΔT is the preset electricity price update time interval.

5. The method for calculating the real-time electricity price of electric vehicles according to claim 4, characterized in that: The method of obtaining the real-time electricity price planning result of the electric vehicle by solving the objective function comprises the following steps: Determine the user's intended charging price c at each moment according to the user's charging intention model i,j 、Number of charging users m i,j , and the corresponding charging power of the charging electric vehicle; The user's intended charging price c at the corresponding moment is calculated based on the charging pile utilization correction coefficient. i,j Adjustments are made, and the total charging power of the charging station is determined according to the number of charging users at the corresponding moment and the charging power of the corresponding electric vehicles; its expression is: C i,j =A i,j ·c i,j in, represents the charging price c in the user charging intention model i,j The corresponding number of users who intend to charge; A i,j is the charging pile utilization correction factor; m i,j is the number of charging users at the charging station at the jth moment on the i-th day; n i,j is the number of charging piles with normal operation capacity at the charging station at the jth moment on the i-th day; p c,i,j,k represents the charging power of the electric vehicle of user k at the jth moment on the i-th day; The adjusted user intended charging price and the total charging power of the charging station are input into the objective function and solved to obtain the real-time electricity price of the charging station at various times of the day.

6. A real-time electricity price calculation system for electric vehicles taking into account the utilization rate of charging piles, applying the real-time electricity price calculation method for electric vehicles according to any one of claims 1 to 5, characterized in that: include: The charging intention update module is used to update the user charging intention model based on the charging price and date attributes of the charging station to determine the charging intention of the electric vehicle user; A charging pile utilization correction module, used to determine a charging pile utilization correction coefficient based on the utilization and congestion of the charging station; The real-time electricity price calculation module is used to determine the expected number of charging users at any time according to the user charging intention model, and adjust the real-time electricity price at the corresponding time according to the charging pile utilization correction coefficient, and obtain the real-time electricity price planning result of the electric vehicle by solving the objective function of maximizing the comprehensive benefits of the charging station operator.

7. The electric vehicle real-time electricity price calculation system according to claim 6, characterized in that: In the charging intention update module, the following steps are performed: Collect historical operation data of charging stations, including real-time charging prices, number of charging users and / or waiting time of electric vehicles at charging stations at each sampling time within at least one week; The historical operation data of the charging station is fitted based on the sampling time and the corresponding charging price to construct a user charging intention model; its expression is: Among them, c i,j represents the user's intended charging price at the jth moment on the i-th day, represents the charging user at the jth moment on the i-th day; α i,j , β i,j , γ i,j is the model parameter.

8. The electric vehicle real-time electricity price calculation system according to claim 6, characterized in that: In the charging pile utilization correction module, the following steps are performed: Collect historical operation data of charging stations, including the number of working charging piles at the charging station, the number of charging users, the maximum number of electric vehicles allowed to be accommodated at the charging station, the average queuing time of electric vehicles at the charging station, and / or the average charging time of electric vehicles at the charging station at each sampling time within at least one week in history; Calculate the charging station utilization μ at the jth time on the i-th day of the charging station use,i,j ; Its expression is: Among them, m i,j is the number of charging users at the charging station at the jth moment on the i-th day; n i,j is the number of charging piles with normal operation capacity at the charging station at the jth moment on the i-th day; Calculate the congestion degree μ of the charging station at the jth time on the i-th day queue,i,j ; Its expression is: in, represents the average waiting time of electric vehicles at charging stations, represents the average charging time of electric vehicles at the charging station; n p Indicates the maximum number of electric vehicles that a charging station is allowed to accommodate; According to the charging station utilization μ at any time use,i,j and charging station congestion μ queue,i,j , calculate the normalized coefficient β of charging station utilization use and the normalized coefficient of charging station congestion β queue , and further determine the charging pile utilization correction factor A i,j ; Its expression is: Among them, μ queue,max and μ queue,min They represent the maximum and minimum values ​​of the charging station congestion respectively; μ use,max and μ use,min Indicates the maximum and minimum values ​​of charging station utilization.

9. The electric vehicle real-time electricity price calculation system according to any one of claims 6 to 8, characterized in that: The objective function aims to maximize the comprehensive benefits of the charging station operator and determines the real-time electricity price of the charging station at each time of the day; the expression of the comprehensive benefits R of the charging station operator is: Among them, C i,j represents the real-time electricity price of the charging station at the jth moment on the i-th day, c i,j,base represents the unit electricity purchase cost of the charging station at the jth moment on the i-th day, P c,i,j represents the total charging power of the charging station at the jth moment on the i-th day, and ΔT is the preset electricity price update time interval.

10. The electric vehicle real-time electricity price calculation system according to claim 6, characterized in that: In the real-time electricity price calculation module, the following steps are performed: Determine the user's intended charging price c at each moment according to the user's charging intention model i,j 、Number of charging users m i,j , and the corresponding charging power of the charging electric vehicle; The user's intended charging price c at the corresponding moment is calculated based on the charging pile utilization correction coefficient. i,j Make adjustments and determine the total charging power of the charging station according to the number of charging users at the corresponding moment and the charging power of the corresponding electric vehicles; Its expression is: C i,j =A i,j ·c i,j in, represents the charging price c in the user charging intention model i,j The corresponding number of users who intend to charge; A i,j is the charging pile utilization correction factor; m i,j is the number of charging users at the charging station at the jth moment on the i-th day; n i,j is the number of charging piles with normal operation capacity at the charging station at the jth moment on the i-th day; p c,i,j,k represents the charging power of the electric vehicle of user k at the jth moment on the i-th day; The adjusted user intended charging price and the total charging power of the charging station are input into the objective function and solved to obtain the real-time electricity price of the charging station at various times of the day.

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