Electric vehicle charging and discharging control method, device, equipment and storage medium

Abstract

The present application discloses an electric vehicle charging and discharging control method, device, equipment and storage medium, which relates to the field of electric vehicle charging and discharging technology, and can improve the flexibility of the power grid while meeting the charging needs of electric vehicles. The scheme includes: obtaining the reported information of electric vehicles in charging stations in each time period of the previous day, and the reported information includes: the time information of the electric vehicle connected to the power grid, the battery parameters of the power battery in the electric vehicle, and the battery charging information; according to the reported information and the preset constraints, determining the adjustable power range of each charging station in each time period of the previous day; according to the adjustable power range of each time period of the previous day and the preset power grid flexibility determination algorithm, determining the allocated power of each charging station in each time period of the day; according to the allocated power in each time period of the day, determining the allocated power of each electric vehicle in each charging station in each time period.

Description

Technical Field

[0001] The present application relates to the technical field of electric vehicle charging and discharging, and in particular to an electric vehicle charging and discharging control method, device, equipment and storage medium. Background Art

[0002] With the large-scale popularization of electric vehicles, the randomness and volatility of their charging demand have a significant impact on the load curve of the power grid. This impact not only increases the complexity and uncertainty of power grid operation, but also poses many challenges to the safe and stable operation of the power grid. As a new type of load, the uncertainty of electric vehicles' charging behavior in time and space makes the traditional power system face greater operating risks. In order to effectively respond to these challenges, the power system urgently needs to improve its flexibility to adapt to the variability of power demand. For example, the charging behavior of electric vehicles is often concentrated in specific time periods, generally at night and on weekends, which overlaps with the traditional peak hours of electricity consumption, resulting in a sudden increase in the load of the power grid. The layout of charging piles and the use habits of electric vehicles also bring about spatial imbalances, and the charging demand in some areas may be much higher than that in other areas. This uneven distribution of charging demand has brought greater pressure to the grid dispatching. Therefore, the power system needs to establish a more flexible dispatching mechanism to cope with sudden load changes.

[0003] As a mobile energy storage device, electric vehicles can not only support the safe and stable operation of the power grid, but also greatly increase the number of electric vehicles accepted by the power grid if their energy storage characteristics can be well utilized. As a mobile energy storage device, the energy storage characteristics of electric vehicles provide a new way of supporting the power grid. Through effective technical applications and control methods, electric vehicles can not only enhance the safety and stability of the power grid, but also promote greater acceptance of electric vehicles by the power grid and promote the development of sustainable energy. This will be a key step in achieving green transportation and smart grids, laying the foundation for future energy systems. Therefore, there is an urgent need for an electric vehicle charging and discharging control method to control the charging and discharging power of electric vehicles to improve the flexibility of the power grid. Summary of the invention

[0004] The present application provides an electric vehicle charging and discharging control method, device, equipment and storage medium, which can improve the flexibility of the power grid while meeting the charging needs of the electric vehicle.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect of an embodiment of the present application, a method for controlling charging and discharging of an electric vehicle is provided, the method comprising:

[0007] Acquire the reported information of electric vehicles in the charging station in each time period of the previous day, wherein the reported information includes: time information of the electric vehicle connecting to the power grid, battery parameters of the power battery in the electric vehicle, and battery charging information;

[0008] Determine the adjustable power range of each charging station in each time period of the previous day according to the reported information and preset constraints;

[0009] Determine the power allocation for each charging station in each time period of the day according to the adjustable power range for each time period of the previous day and a preset grid flexibility determination algorithm;

[0010] The allocated power for each electric vehicle in each charging station in each time period is determined according to the allocated power for each time period of the day.

[0011] As a possible implementation, determining the adjustable power range of each charging station in each time period of the previous day according to the reported information and preset constraints includes:

[0012] After determining that the reported information is within the corresponding constraint condition, the adjustable power range of each charging station in each time period of the previous day is determined according to the target reported information that meets the corresponding preset condition.

[0013] As a possible implementation manner, the constraint conditions include: battery charging and discharging constraint, battery safety constraint and vehicle owner driving demand constraint.

[0014] As a possible implementation, determining the power allocation for each charging station in each time period of the day according to the adjustable power range in each time period of the previous day and a preset grid flexibility determination algorithm includes:

[0015] Input the adjustable power range for each time period of the previous day into a preset grid flexibility determination algorithm to obtain the ideal allocated power for each charging station for each time period of the day;

[0016] The power allocation for each time period of the day for each charging station is determined according to the ideal allocated power for each time period and a preset first objective function.

[0017] As a possible implementation, determining the power distribution for each charging station in each time period of the day according to the ideal power distribution for each time period and a preset first objective function includes:

[0018] Inputting the ideal allocated power for each time period into a preset first objective function to obtain the allocated power for each time period of each charging station on that day;

[0019] The first objective function is:

[0020]

[0021] Where t is the first time period, T is the number of time periods in a day, For the ideal power allocation of the i-th charging station in the t-th time period of the day, is the allocated power of the i-th charging station in the t-th time period of the day.

[0022] As a possible implementation, the grid flexibility determination algorithm includes:

[0023] Grid margin judgment function, grid load peak-to-valley difference judgment function, grid total network loss judgment function and voltage deviation judgment function.

[0024] As a possible implementation, the step of determining the allocated power for each electric vehicle in each charging station in each time period according to the allocated power for each time period of the day includes:

[0025] Inputting the power allocated to each charging station in each time period of the day into a preset second objective function to obtain the power allocated to each electric vehicle in the charging station in each time period;

[0026] Among them, the second objective function is:

[0027]

[0028] in, For a charging station The allocated power of an electric vehicle in the tth time period, is the number of electric vehicles in a charging station.

[0029] In a second aspect of the present application, a charge and discharge control device for an electric vehicle is provided, the device comprising:

[0030] An acquisition module is used to acquire the reported information of electric vehicles in the charging station in each time period of the previous day, wherein the reported information includes: time information of the electric vehicle connecting to the power grid, battery parameters of the power battery in the electric vehicle, and battery charging information;

[0031] A first determination module, configured to determine the adjustable power range of each charging station in each time period of the previous day according to the reported information and preset constraints;

[0032] A second determination module is used to determine the power allocation of each charging station in each time period of the day according to the adjustable power range in each time period of the previous day and a preset grid flexibility determination algorithm;

[0033] The third determination module is used to determine the allocated power of each electric vehicle in each charging station in each time period according to the allocated power in each time period of the day.

[0034] In a third aspect of an embodiment of the present application, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the electric vehicle charging and discharging control method in the first aspect of the embodiment of the present application is implemented.

[0035] In a fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the electric vehicle charging and discharging control method in the first aspect of the embodiments of the present application is implemented.

[0036] The beneficial effects brought by the technical solution provided by the embodiment of the present application include at least:

[0037] The electric vehicle charging and discharging control method provided in the embodiment of the present application obtains the reported information of the electric vehicles in the charging stations in each time period of the previous day, and the reported information includes: the time information of the electric vehicle connected to the power grid, the battery parameters of the power battery in the electric vehicle, and the battery charging information; according to the reported information and the preset constraints, the adjustable power range of each charging station in each time period of the previous day is determined; according to the adjustable power range of each time period of the previous day and the preset power grid flexibility determination algorithm, the allocated power of each charging station in each time period of the current day is determined; according to the allocated power in each time period of the current day, the allocated power of each electric vehicle in each charging station in each time period is determined, so that the charging and discharging of the electric vehicles can be orderly controlled, the various indicators of the power grid can be improved, and the flexibility of the power grid can be further enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A flow chart of a method for controlling charging and discharging of an electric vehicle provided in an embodiment of the present application;

[0039] Figure 2 A schematic diagram of a charging station connected to a power grid provided in an embodiment of the present application;

[0040] Figure 3 A load curve diagram of a power grid under three control scenarios provided in an embodiment of the present application;

[0041] Figure 4 A structural diagram of an electric vehicle charging and discharging control device provided in an embodiment of the present application;

[0042] Figure 5 A schematic diagram of the internal structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, "plurality" means two or more.

[0045] Additionally, the use of “based on” or “according to” is meant to be open and inclusive, as a process, step, calculation, or other action “based on” or “according to” one or more conditions or values ​​may, in practice, be based on additional conditions or beyond values.

[0046] The present application embodiment provides a method for controlling charging and discharging of an electric vehicle, such as Figure 1 As shown, the method comprises the following steps:

[0047] Step 101: Acquire the reported information of the electric vehicles in the charging station in each time period of the previous day, wherein the reported information includes: the time information of the electric vehicle connecting to the power grid, the battery parameters of the power battery in the electric vehicle, and the battery charging information.

[0048] Among them, a day can be divided into multiple time periods. The time information of electric vehicles connected to the grid includes: the time when the electric vehicle is connected to the grid and the time when the electric vehicle is disconnected from the grid. Battery parameters include: the total capacity of the power battery of the electric vehicle, the maximum charging power and the maximum discharging power, etc. Battery charging information includes: battery SOC change, battery charging and discharging power, battery charging and discharging status, etc.

[0049] In addition, the electric vehicle charging pile in the present application can be a V2G charging pile, which can interact with the electric vehicle for charging and discharging.

[0050] Step 102: Determine the adjustable power range of each charging station in each time period of the previous day according to the reported information and preset constraints.

[0051] Optionally, the process of step 102 may be: after determining that the reported information is within the corresponding constraint condition, determining the adjustable power range of each charging station in each time period of the previous day according to the target reported information that meets the corresponding preset condition.

[0052] Among them, the constraints include: battery charging and discharging constraints, battery safety constraints and owner's driving demand constraints.

[0053] Specifically, the battery charging and discharging constraints are:

[0054]

[0055] In the formula, for The first charging station The SOC value of an electric vehicle at time t+1, for The first charging station The SOC value of an electric vehicle at time t, Indicated in The first charging station The battery capacity of an electric vehicle; For the The charging and discharging power of an electric vehicle, Indicates the charging and discharging efficiency of the electric vehicle; Indicates a time period.

[0056] Battery safety constraints:

[0057]

[0058] In the formula, and They represent the lower and upper limits of the SOC of electric vehicles respectively.

[0059] Driving demand constraints of car owners:

[0060]

[0061] In the formula, Indicates electric vehicle charging station Middle The expected state of charge of an electric vehicle when it leaves the vehicle. Indicates electric vehicle charging station Middle The actual state of charge of an electric vehicle when it leaves the vehicle.

[0062] Step 103: Determine the power allocation for each charging station in each time period of the day according to the adjustable power range in each time period of the previous day and a preset grid flexibility determination algorithm.

[0063] Optionally, the process of step 103 may be:

[0064] Input the adjustable power range for each time period of the previous day into a preset grid flexibility determination algorithm to obtain the ideal allocated power for each charging station for each time period of the day;

[0065] The ideal allocated power for each time period is input into a preset first objective function to obtain the allocated power for each time period of each charging station on that day.

[0066] Among them, the grid flexibility judgment algorithm includes: grid margin judgment function, grid load peak-to-valley difference judgment function, grid total network loss judgment function and voltage deviation judgment function.

[0067] The grid margin judgment function is:

[0068]

[0069] in, is the grid line margin index, For power grid lines The current value on line The maximum current value allowed on the grid is Lines.

[0070] The peak-to-valley difference judgment function of the power grid load is:

[0071]

[0072] in, is the peak-to-valley difference of the power grid load, is the maximum load of the day, This is the minimum load for the day.

[0073] The total grid loss judgment function is:

[0074]

[0075] is the total grid loss, For line on loss.

[0076] The voltage deviation judgment function is:

[0077]

[0078] in, is the rated voltage of the node, for The actual voltage at the node, Indicates the deviation between the rated voltage of the node and the actual voltage after regulation. The network involved has a total of nodes.

[0079]

[0080] in, is the flexible operation index of the power grid. is the weight coefficient, are the values ​​of each judgment function.

[0081] It should be noted that the electric vehicles in each charging station will affect the current, voltage and power of each node in the power grid after they are connected to the corresponding node in the power grid. Therefore, the current, voltage and power in the above power grid flexibility determination algorithm are determined after the adjustable power range of each charging station in each time period of the day before charging and discharging is connected to the power grid. According to the flexible operation index of the power grid, the ideal distribution power of each charging station in each time period of the day can be determined.

[0082] The first objective function is:

[0083]

[0084] Where t is the first time period, T is the number of time periods in a day, For the ideal power allocation of the i-th charging station in the t-th time period of the day, is the allocated power of the i-th charging station in the t-th time period of the day.

[0085] The ideal allocated power for each time period is input into the preset first objective function, so as to obtain the allocated power for each time period of each charging station on the day.

[0086] Step 104: Determine the allocated power for each electric vehicle in each charging station in each time period according to the allocated power for each time period of the day.

[0087] Optionally, the power allocated to each charging station in each time period of the day is input into a preset second objective function to obtain the power allocated to each electric vehicle in the charging station in each time period;

[0088] Among them, the second objective function is:

[0089]

[0090] in, For a charging station The allocated power of an electric vehicle in the tth time period, is the number of electric vehicles in a charging station.

[0091] The electric vehicle charging and discharging control method provided in the embodiment of the present application constructs a two-layer electric vehicle dispatching architecture. The upper layer is issued by the power grid dispatching center to issue dispatching instructions and realize the instruction distribution to each charging station. The lower layer is respectively responded to the upper layer control instructions by each electric vehicle charging station, and the instructions received by each charging station are distributed to the electric vehicles in each charging station. On the basis of ensuring the safe operation of the power grid, the line margin, load peak-valley difference, network loss, and voltage deviation are selected as the key indicators of the flexibility of the power network. The power dispatcher issues relevant control instructions and uses them as the objective function of the upper layer control model to construct the charging and discharging control optimization model of each charging station. While ensuring that the daily driving needs of electric vehicle users are met, the actual dispatching results of each electric vehicle charging station and the instruction difference assigned to each charging station are used as the objective function of the lower layer model, that is, the control response of each electric vehicle in the station can maximize the satisfaction of the control instructions assigned by the station, thereby constructing the charging and discharging control optimization model of each electric vehicle in the lower layer. The two-layer model is optimized and solved. After the upper layer is solved, the dispatching instructions are distributed to each electric vehicle charging station, and then each electric vehicle charging station solves the charging plan of its internal vehicles to maximize the satisfaction of the target. The strategy of the present invention can effectively improve various flexibility indicators of the power grid when a large number of electric vehicles are connected, thereby improving the flexibility of the power grid while meeting the charging needs of electric vehicles.

[0092] For example, a schematic diagram of a charging station connected to a power grid in an embodiment of the present application is as follows: Figure 2 As shown, the power grid can be connected to three charging stations, each of which is configured to connect to 100 electric vehicles. Figure 3 The load curves of the power grid under three control scenarios. The control targets are disordered charging, peak-valley difference optimization, and the control strategy proposed in this paper. Although the control result on the load curve is not as good as the peak-valley difference optimization, it greatly increases the flexibility of the power grid and can maintain the safe and stable operation of the power grid.

[0093] The present application embodiment provides a charge and discharge control device for an electric vehicle, such as Figure 4 As shown, the device comprises:

[0094] The acquisition module 11 is used to acquire the reported information of the electric vehicles in the charging station in each time period of the previous day, wherein the reported information includes: the time information of the electric vehicle connecting to the power grid, the battery parameters of the power battery in the electric vehicle, and the battery charging information;

[0095] A first determination module 12, configured to determine the adjustable power range of each charging station in each time period of the previous day according to the reported information and preset constraints;

[0096] The second determination module 13 is used to determine the power allocation of each charging station in each time period of the day according to the adjustable power range in each time period of the previous day and a preset grid flexibility determination algorithm;

[0097] The third determining module 14 is used to determine the allocated power of each electric vehicle in each charging station in each time period according to the allocated power in each time period of the day.

[0098] In one embodiment, the first determining module 12 is specifically configured to:

[0099] After determining that the reported information is within the corresponding constraint condition, the adjustable power range of each charging station in each time period of the previous day is determined according to the target reported information that meets the corresponding preset condition.

[0100] In one embodiment, the constraints include: battery charging and discharging constraints, battery safety constraints and vehicle owner driving demand constraints.

[0101] In one embodiment, the second determining module 13 is specifically configured to:

[0102] Input the adjustable power range for each time period of the previous day into a preset grid flexibility determination algorithm to obtain the ideal allocated power for each charging station for each time period of the day;

[0103] The power allocation for each time period of the day for each charging station is determined according to the ideal allocated power for each time period and a preset first objective function.

[0104] In one embodiment, the second determining module 13 is specifically configured to:

[0105] Inputting the ideal allocated power for each time period into a preset first objective function to obtain the allocated power for each time period of each charging station on that day;

[0106] The first objective function is:

[0107]

[0108] Where t is the first time period, T is the number of time periods in a day, For the ideal power allocation of the i-th charging station in the t-th time period of the day, is the allocated power of the i-th charging station in the t-th time period of the day.

[0109] In one embodiment, the grid flexibility determination algorithm includes:

[0110] Grid margin judgment function, grid load peak-to-valley difference judgment function, grid total network loss judgment function and voltage deviation judgment function.

[0111] In one embodiment, the third determining module 14 is specifically configured to:

[0112] Inputting the power allocated to each charging station in each time period of the day into a preset second objective function to obtain the power allocated to each electric vehicle in the charging station in each time period;

[0113] Among them, the second objective function is:

[0114]

[0115] in, For a charging station The allocated power of an electric vehicle in the tth time period, is the number of electric vehicles in a charging station.

[0116] The electric vehicle charging and discharging control device provided in this embodiment can execute the above-mentioned electric vehicle charging and discharging control method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here.

[0117] For the specific definition of the electric vehicle charging and discharging control device, please refer to the definition of the electric vehicle charging and discharging control method above, which will not be repeated here. Each module in the above-mentioned electric vehicle charging and discharging control device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor of the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0118] The executor of the electric vehicle charging and discharging control method provided in the embodiment of the present application may be an electronic device, which may be a computer device, a terminal device, a server or a server cluster, and the embodiment of the present application does not specifically limit this.

[0119] Figure 5 This is a schematic diagram of the internal structure of an electronic device provided in an embodiment of the present application. Figure 5 As shown, the electronic device includes a processor and a memory connected via a system bus. The processor is used to provide computing and control capabilities. The memory may include a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The computer program can be executed by the processor to implement the steps of the electric vehicle charging and discharging control method provided in the above embodiments. The internal memory provides a cache operating environment for the operating system and computer program in the non-volatile storage medium.

[0120] Those skilled in the art will understand that Figure 5The internal structure diagram of the electronic device shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0121] In another embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the electric vehicle charging and discharging control method in the embodiment of the present application are implemented.

[0122] In another embodiment of the present application, a computer program product is also provided. The computer program product includes computer instructions. When the computer instructions are executed on the electric vehicle charging and discharging control device, the electric vehicle charging and discharging control device executes each step of the electric vehicle charging and discharging control method in the method flow shown in the above method embodiment.

[0123] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using a software program, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer execution instruction is loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instruction can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instruction can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that can be accessed by the computer or a data storage device such as a server, data center, etc. that contains one or more servers that can be integrated with the medium. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0124] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for controlling charging and discharging of an electric vehicle, characterized in that: The method comprises: Construct a two-layer electric vehicle dispatching architecture. The upper layer is where the power grid dispatching center issues dispatching instructions and distributes the instructions to each charging station. The lower layer is where each electric vehicle charging station responds to the upper layer control instructions and distributes the instructions received by each charging station to the electric vehicles in each charging station. Acquire the reported information of electric vehicles in the charging station in each time period of the previous day, wherein the reported information includes: time information of the electric vehicle connecting to the power grid, battery parameters of the power battery in the electric vehicle, and battery charging information; Determine the adjustable power range of each charging station in each time period of the previous day according to the reported information and preset constraints; Determine the power allocation for each charging station in each time period of the day according to the adjustable power range for each time period of the previous day and a preset grid flexibility determination algorithm; Determine the allocated power for each electric vehicle in each charging station in each time period according to the allocated power for each time period of the day; The constraints include: battery charging and discharging constraints, battery safety constraints and vehicle owner driving demand constraints; The battery charge and discharge constraints are: In the formula, for The first charging station The SOC value of an electric vehicle at time t+1, for The first charging station The SOC value of an electric vehicle at time t, Indicated in The first charging station The battery capacity of an electric vehicle; For the The charging and discharging power of an electric vehicle, Indicates the charging and discharging efficiency of the electric vehicle; Indicates a time period; The battery safety constraints are: In the formula, and They represent the lower and upper limits of the SOC of electric vehicles respectively; The owner's driving demand constraints: In the formula, Indicates electric vehicle charging station Middle The expected state of charge of an electric vehicle when it leaves the vehicle. Indicates electric vehicle charging station Middle The actual state of charge of an electric vehicle when it leaves; The step of determining the power allocation for each charging station in each time period of the day according to the adjustable power range in each time period of the previous day and a preset grid flexibility determination algorithm includes: Input the adjustable power range for each time period of the previous day into a preset grid flexibility determination algorithm to obtain the ideal allocated power for each charging station for each time period of the day; Determine the power allocation for each charging station in each time period of the day according to the ideal power allocation for each time period and the preset first objective function; The grid flexibility determination algorithm comprises: Grid margin judgment function, grid load peak-to-valley difference judgment function, grid total network loss judgment function and voltage deviation judgment function; The grid margin judgment function is: in, is the grid line margin index, For power grid lines The current value on line The maximum current value allowed on the grid is lines; The power grid load peak-to-valley difference judgment function is: in, is the peak-to-valley difference of the power grid load, is the maximum load of the day, The minimum load of the day; The total network loss judgment function of the power grid is: is the total grid loss, For line loss on The voltage deviation judgment function is: in, is the rated voltage of the node, for The actual voltage at the node, Indicates the deviation between the rated voltage of the node and the actual voltage after regulation. The network involved has a total of nodes; in, is the flexible operation index of the power grid. is the weight coefficient, are the values ​​of each judgment function; The step of determining the allocated power of each electric vehicle in each charging station in each time period according to the allocated power in each time period of the day includes: Inputting the power allocated to each charging station in each time period of the day into a preset second objective function to obtain the power allocated to each electric vehicle in the charging station in each time period; Among them, the second objective function is: in, For a charging station The allocated power of an electric vehicle in the tth time period, is the number of electric vehicles in a charging station, is the allocated power of the i-th charging station in the t-th time period of the day, t is the first time period, and T is the number of time periods included in a day.

2. The method according to claim 1, characterized in that The step of determining the adjustable power range of each charging station in each time period of the previous day according to the reported information and the preset constraint conditions includes: After determining that the reported information is within the corresponding constraint condition, the adjustable power range of each charging station in each time period of the previous day is determined according to the target reported information that meets the corresponding preset condition.

3. The method according to claim 1, characterized in that The step of determining the power distribution for each time period of each charging station on the day according to the ideal power distribution for each time period and the preset first objective function includes: Inputting the ideal allocated power for each time period into a preset first objective function to obtain the allocated power for each time period of each charging station on that day; The first objective function is: Where t is the first time period, T is the number of time periods in a day, For the ideal power allocation of the i-th charging station in the t-th time period of the day, is the allocated power of the i-th charging station in the t-th time period of the day.

4. An electric vehicle charging and discharging control device, characterized in that: Used to execute the electric vehicle charging and discharging control method according to any one of claims 1 to 3, the device comprises: An acquisition module is used to acquire the reported information of electric vehicles in the charging station in each time period of the previous day, wherein the reported information includes: time information of the electric vehicle connecting to the power grid, battery parameters of the power battery in the electric vehicle, and battery charging information; A first determination module, configured to determine the adjustable power range of each charging station in each time period of the previous day according to the reported information and preset constraints; A second determination module is used to determine the power allocation of each charging station in each time period of the day according to the adjustable power range in each time period of the previous day and a preset grid flexibility determination algorithm; The third determination module is used to determine the allocated power of each electric vehicle in each charging station in each time period according to the allocated power in each time period of the day.

5. An electronic device, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the electric vehicle charging and discharging control method according to any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the electric vehicle charging and discharging control method according to any one of claims 1 to 3 is implemented.

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