Charging pile charging control method and device, storage medium and equipment

Abstract

The application discloses a charging pile charging control method and device, a storage medium and equipment. The method comprises the following steps: obtaining historical charging data of a target charging pile, and obtaining charging and discharging information of an energy storage device of the target charging pile; determining a typical load curve based on the historical charging data; determining configuration information of the energy storage device based on the charging and discharging information and the typical load curve; and determining charging and discharging arrangement of the target charging pile based on the configuration information and the typical load curve. The application solves the technical problem of high operating cost of charging piles.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and more specifically, to a charging control method, device, storage medium, and equipment for charging piles. Background Technology

[0002] In existing technologies, all buses are charged only during off-peak hours. When optimizing the orderly charging schedule of electric buses, the charging load of electric buses can be approximated as constant power charging. The remaining battery power of each bus is related to the driver's driving style, weather temperature, bus route (road conditions), whether it is a weekday or holiday, passenger volume, etc. Since the operation of the same electric bus is similar every day, the remaining battery power of the same electric bus is approximately the same every day. Historical data is used to approximate the remaining battery power of each electric bus on that day.

[0003] However, in reality, the charging time of buses is not affected by the peak and off-peak electricity pricing policy. Everything is based on ensuring public transportation services. Electric buses charge high electricity costs and have high operating costs during peak hours. In fact, the starting time of electric bus charging is random, and the accuracy of the model needs to be improved.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a charging control method, device, storage medium, and equipment for charging piles, in order to at least solve the technical problem of high operating costs of charging piles.

[0006] According to one aspect of the present invention, a charging control method for a charging pile is provided, comprising: acquiring historical charging data of a target charging pile, and acquiring charging and discharging information of an energy storage device of the target charging pile; determining a typical load curve based on the historical charging data; determining configuration information of the energy storage device based on the charging and discharging information and the typical load curve; and determining a charging and discharging arrangement for the target charging pile based on the configuration information and the typical load curve.

[0007] Optionally, the above-mentioned acquisition of historical charging data of the target charging pile includes: acquiring the historical charging period and historical charging amount of the target charging pile; and performing calculations on the historical charging period and historical charging amount to obtain the historical load curve.

[0008] Optionally, determining the typical load curve based on the historical charging data includes: classifying the historical load curves to obtain multiple daily charging load curves; and calculating the multiple daily charging load curves to determine multiple typical load curves, wherein each typical load curve corresponds to a daily charging load curve.

[0009] Optionally, obtaining the charging and discharging information of the energy storage device of the aforementioned charging pile includes: obtaining the historical discharge period and historical discharge amount of the energy storage device.

[0010] Optionally, determining the configuration information of the energy storage device based on the charging and discharging information and the typical load curve includes: calculating and processing the charging and discharging cost information and the charging and discharging time information to determine the capacity information and power information of the energy storage device calculated based on the historical discharge period, the historical discharge amount and the typical load curve; and determining the configuration information of the energy storage device based on the capacity information and the power information.

[0011] According to another aspect of the present invention, a charging pile charging control device is also provided, comprising: an acquisition module, configured to acquire historical charging data of a target charging pile and acquire charging and discharging information of an energy storage device of the target charging pile; a first determination module, configured to determine a typical load curve based on the historical charging data; a second determination module, configured to determine configuration information of the energy storage device based on the charging and discharging information and the typical load curve; and a third determination module, configured to determine the charging and discharging arrangement of the target charging pile based on the configuration information and the typical load curve.

[0012] According to another aspect of the present invention, a non-volatile storage medium is also provided, wherein the non-volatile storage medium stores a plurality of instructions, the instructions being adapted to be loaded by a processor and executed any one of the above-described charging pile charging control methods.

[0013] According to another aspect of the present invention, a processor is also provided, which is used to run a program, wherein the program is configured to execute any of the above-described charging pile charging control methods during runtime.

[0014] According to another aspect of the present invention, an electronic device is also provided, including a memory and a processor, characterized in that the memory stores a computer program, and the processor is configured to run the computer program to execute any one of the above-described charging pile charging control methods.

[0015] In this embodiment of the invention, by acquiring historical charging data of the target charging pile and charging / discharging information of the energy storage device of the target charging pile; based on the historical charging data, a typical load curve is determined; based on the charging / discharging information and the typical load curve, the configuration information of the energy storage device is determined; based on the configuration information and the typical load curve, the charging / discharging arrangement of the target charging pile is determined. This achieves the goal of meeting the charging demand of electric buses during peak electricity price periods by establishing a minute-level charging control strategy and utilizing the energy storage device, thereby achieving the technical effect of accurately reducing the electricity cost of charging pile operation and solving the technical problem of high charging pile operation costs. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0017] Figure 1 This is a flowchart of a charging pile charging control method according to an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram of the structure of a charging pile charging control device according to an embodiment of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] Example 1

[0022] According to an embodiment of the present invention, an embodiment of a charging pile charging control method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0023] In existing technologies, the remaining battery power of each bus is related to factors such as driver style, weather temperature, bus route (road conditions), weekday or holiday, and passenger volume. Since the operation of the same electric bus is similar every day, the remaining battery power of the same electric bus is approximately the same every day. Historical data is usually used to approximate the remaining battery power of each electric bus on that day. Therefore, the charging time of buses is not affected by peak and off-peak electricity pricing policies, and everything is based on ensuring public transportation service. Electricity costs are high for charging electric buses during peak hours, resulting in high operating costs. Furthermore, all buses only charge during off-peak hours. When optimizing the orderly charging schedule of electric buses, the charging load of electric buses can be approximated as constant power charging. However, the actual starting time of electric bus charging is random. Existing technologies usually use 15-minute time scales, and the accuracy of the model needs to be improved.

[0024] Figure 1 This is a flowchart of a charging pile charging control method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0025] Step S102: Obtain historical charging data of the target charging pile and charging and discharging information of the energy storage device of the target charging pile.

[0026] Step S104: Based on the above historical charging data, determine the typical load curve;

[0027] Step S106: Based on the above charging and discharging information and the above typical load curve, determine the configuration information of the above energy storage device;

[0028] Step S108: Based on the above configuration information and the above typical load curve, determine the charging and discharging arrangement of the above target charging pile.

[0029] In this embodiment of the invention, the charging control method for charging piles provided in steps S102 to S108 is executed by a charging pile charging control system. The system acquires historical charging data of the target charging pile and charging and discharging information of the energy storage device of the target charging pile. Based on the historical charging data, a typical load curve is determined. Based on the charging and discharging information and the typical load curve, the configuration information of the energy storage device is determined. Based on the configuration information and the typical load curve, the charging and discharging arrangement of the target charging pile is determined.

[0030] As an optional implementation, the historical charging load curve of the charging pile is obtained based on the historical charging time periods and the amount of electricity charged each time. A clustering algorithm is then used to obtain the typical charging load curve of the charging pile. Based on the peak-valley electricity price distribution, the charging and discharging time periods of the energy storage device are arranged as follows: charging during valley hours, charging and discharging during normal hours, and discharging during peak hours. Based on the typical load curve of the charging pile, the required discharge power and discharge time for each peak, normal, and valley period are obtained. For 12 typical daily load curves, the capacity and power configuration of the energy storage device are calculated respectively. The charging and discharging time period arrangement of the energy storage device is determined as follows: charging during valley hours, charging and discharging during normal hours, and discharging during peak hours (the period participating in grid peak shaving is the normal period). The charging and discharging arrangement of the charging pile containing the energy storage device is determined with the objective function of maximizing overall revenue.

[0031] This invention, through its embodiments, determines the energy storage capacity and power of charging piles based on historical charging data, and establishes a minute-level optimized scheduling model for charging piles including energy storage devices. The energy storage devices can be used to charge during off-peak hours and discharge during peak hours, achieving peak-shifting and valley-filling of the electric load characteristics of electric bus charging piles, thus saving on electricity costs for charging pile operation. Compared to a 15-minute timescale scheduling model, this model is more accurate, has better optimization scheduling effects, and more precisely achieves peak-shifting and valley-filling, saving on electricity costs for charging pile operation.

[0032] In one optional embodiment, the above-mentioned acquisition of historical charging data of charging piles includes: acquiring the historical charging period and historical charging amount of the target charging pile; and performing calculation processing on the historical charging period and historical charging amount to obtain a historical load curve.

[0033] As an optional embodiment, the historical charging load curve of the charging pile is obtained based on the historical charging period and the amount of electricity charged each time.

[0034] As an optional implementation, the historical charging period t can be obtained based on the charging data information of the charging pile. use And the amount of electricity Q per charge use The load P of buses using charging stations during that period can be calculated. L-tuse For P L-tuse =Q use / t use .

[0035] In one optional embodiment, determining the typical load curve based on the historical charging data includes: classifying the historical load curves to obtain multiple daily charging load curves; and performing calculations on the multiple daily charging load curves to determine multiple typical load curves, wherein each typical load curve corresponds to a daily charging load curve.

[0036] As an optional implementation, historical charging load is calculated based on annual charging data to obtain the historical annual charging load curve. The year is divided into four typical scenarios: spring, summer, autumn, and winter. Each typical scenario is further divided into three operating conditions: weekdays, rest days, and holidays. The annual charging load curve is then categorized into 12 types of daily charging load curves. A typical daily load curve is extracted for each type of daily charging load curve. By calculating the average charging load for each minute, the typical daily load curve for that type is obtained.

[0037] In one optional embodiment, obtaining the charging and discharging information of the energy storage device of the charging pile includes: obtaining the historical discharge period and historical discharge amount of the energy storage device.

[0038] As an optional implementation, based on the peak-valley electricity price distribution, the charging and discharging periods of the energy storage device are arranged as follows: charging during valley hours, charging and discharging during normal hours, and discharging during peak hours. Based on the typical load curve of the charging pile, the required discharge power and discharge time for each peak, valley, and normal period are obtained. The capacity and power configuration of the energy storage device are calculated for 12 typical daily load curves.

[0039] As an optional embodiment, the capacity of the energy storage device is selected as follows: Starting from the end of the last peak period of the day, the capacity is calculated recursively and cumulatively. Peak period discharge is taken as a positive number, while valley and flat period charging is taken as a negative number. If the cumulative amount is less than zero, it is set to zero. This calculation is completed at the start of the i-th peak period of the day. The resulting cumulative amount is the minimum energy requirement Q that the energy storage device can meet the discharge demand of peak period i and all subsequent peak periods. fi The capacity C of the energy storage device es It should be greater than or equal to the minimum capacity requirement Q for each peak period. fi .

[0040] As an optional embodiment, the power selection of the energy storage device is as follows: during charging, it operates at the rated power P. n During charging and discharging, the charging load P of the electric bus is used as a guide. L Discharge. The calculation starts from the beginning of the day and proceeds cumulatively until the start of the i-th peak period. The charging amount during valley and flat periods is taken as positive, and the discharging amount during peak periods is taken as negative. The start time of the i-th peak period is t. fi-s Charge Q t-fis The minimum electricity demand Q during peak period i should be greater than or equal to that during peak period i. fi The rated power of the energy storage device should be greater than or equal to the maximum discharge power demand P during peak period i. Li-max .

[0041] As an optional embodiment, among the 12 sets of energy storage devices, the largest capacity and power are selected as the power capacity configuration of the charging pile.

[0042] In one optional embodiment, determining the configuration information of the energy storage device based on the charging and discharging information and the typical load curve includes: calculating and processing the charging and discharging cost information and the charging and discharging time information to determine the capacity information and power information of the energy storage device calculated based on the historical discharge period, the historical discharge amount and the typical load curve; and determining the configuration information of the energy storage device based on the capacity information and the power information.

[0043] As an optional embodiment, the energy storage device's charging and discharging periods are arranged as follows: charging during off-peak hours, charging and discharging during normal hours, and discharging during peak hours. The period participating in S2G ​​(grid peak shaving) is the normal hour period. The energy storage device starts at time t of the i-th peak hour. fi-s Charge Q t-fis The minimum electricity demand Q during peak period i should be greater than or equal to that during peak period i. fi .

[0044] It's important to note that S2G stands for "Substation to Grid," meaning the interface between a substation and the power grid. It refers to the connection point between a substation and the power grid within a power grid system, used to transmit electrical energy generated by the substation to the grid, and vice versa. Grid S2G is a crucial component of the power system, enabling the transmission, distribution, and exchange of electricity.

[0045] As an optional embodiment, with the objective function of maximizing the savings in electricity costs and minimizing the number of energy storage charge-discharge cycles, and with constraints such as meeting the charging demand of electric buses during peak electricity price periods, and the charging and discharging power and energy limits of the energy storage device, a particle swarm optimization algorithm is used to find the optimal solution for the charging and discharging arrangement of charging piles containing energy storage devices.

[0046] Optionally, the objective function can be calculated as: F = min{C} ecost +C fcost};

[0047] Among them, C ecost Electricity costs; C fcost It is the cost of lifespan loss caused by the charging and discharging cycles of energy storage.

[0048] Optionally, the electricity cost Cecost is calculated using the following formula: Cecost=∑(cecost-t×(PL-t+Pes-t));

[0049] Among them, c ecost-t P is the electricity price at time t; L-t P is the charging load of the bus at time t; es-t It is the charging load of the energy storage device at time t. It is taken as a positive number when the energy storage is charging and a negative number when the energy storage is discharging.

[0050] Optional, the lifetime cost C caused by energy storage charge-discharge cycles. fcost The calculation formula is as follows: C, calculated based on the number of charge-discharge cycles of the energy storage device and its purchase cost. fcost =C escost ×f day / f all

[0051] Among them, C escost It is the cost of purchasing energy storage; f day It is the number of charge-discharge cycles per day for energy storage; f all It refers to the number of times the energy can be charged and discharged.

[0052] Optional constraints include: 0 ≤ Q es-t ≤C es ;-P n ≤P es-t ≤P n Q t-fis ≥Q fi ;

[0053] Among them, Q es-t C is the amount of energy stored at time t; es It is the rated capacity of energy storage; P es-t P is the charging load of the energy storage device at time t, taking a positive value during energy charging and a negative value during energy discharging; n Q is the rated power of the energy storage; t-fis The start time of the i-th peak period is t. fi-s The charge of Q; fi The minimum power requirement that can meet the discharge demand of peak period i and all subsequent peak periods.

[0054] Optionally, the particle swarm optimization (PSO) algorithm can be used to solve the problem. The PSO algorithm mainly consists of two iterative formulas: a velocity update formula and a position update formula, as shown below. The new velocity vector is influenced by the old velocity vector, the global optimal position vector, and the individual optimal position vector. The new position vector is related to the new velocity vector. Therefore, through continuous iteration, the particle's position can be made to tend towards the global optimal position.

[0055] Optionally, the calculation method is as follows: V i，k =w×V i，k-1 +c1×r1×(X gbest -X i，k-1 )+c2×r2×(X pbest，i -X i，k-1 ); X i，k =X i，k-1 +V i，k ;

[0056] Among them, V i，k and X i，k These are the velocity and position vectors of the i-th particle in the k-th iteration; w is the inertia coefficient; X gbest It is the globally optimal position vector, that is, the position vector that minimizes the objective function in all iterations of all particles; X pbest，i is the individual optimal position vector of the i-th particle, that is, the position vector with the minimum objective function in each iteration of the i-th particle; c1 and c2 are learning factors; r1 and r2 are random numbers in [0,1].

[0057] Optionally, the position vector is a vector consisting of the charging load of the energy storage device at every moment of the day, which is a 1×1440 array; the velocity vector is a vector consisting of the change in the charging load of the energy storage device at every moment between two iterations, which is a 1×1440 array.

[0058] Optionally, a particle swarm optimization (PSO) algorithm can be used to optimize the charging and discharging arrangement of charging piles containing energy storage devices. The specific solution process is as follows: Initialize all parameters in the PSO algorithm, setting the position vector to zero and the velocity vector to initialization using random selection. Calculate the position vector after the first iteration and determine the globally optimal position vector and the individual optimal position vector. Perform iterative calculations based on the velocity update formula and the position update formula. Calculate the objective function value for each particle and update the optimal position vector and the individual optimal position vector. Determine if the maximum number of iterations has been reached. If not, return to continue iterative calculation; if so, output the current optimal position vector, i.e., the optimized charging and discharging arrangement of charging piles containing energy storage devices.

[0059] Through the embodiments of the present invention, the energy storage configuration capacity and power of charging piles are determined based on historical charging data. By utilizing the energy storage device, charging is performed during off-peak hours and discharging during peak hours, thus realizing peak-shifting and valley-filling of the electric load characteristics of electric bus charging piles and saving electricity costs for charging pile operation. Furthermore, the minute-level charging and discharging optimization scheduling model for charging piles with energy storage devices is more accurate and has a better optimization scheduling effect compared to the 15-minute time scale scheduling model, achieving peak-shifting and valley-filling more precisely and saving electricity costs for charging pile operation.

[0060] Example 2

[0061] According to an embodiment of the present invention, an apparatus embodiment for implementing the above-described charging pile charging control method is also provided. Figure 2 This is a schematic diagram of the structure of a charging pile charging control device according to an embodiment of the present invention, as shown below. Figure 2 As shown, the above-mentioned device includes: an acquisition module 20, a first determination module 22, a second determination module 24, and a third determination module 26, wherein:

[0062] The acquisition module 20 is used to acquire historical charging data of the target charging pile and to acquire charging and discharging information of the energy storage device of the target charging pile.

[0063] The first determining module 22 is used to determine a typical load curve based on the aforementioned historical charging data;

[0064] The second determining module 24 is used to determine the configuration information of the energy storage device based on the above-mentioned charging and discharging information and the above-mentioned typical load curve.

[0065] The third determining module 26 is used to determine the charging and discharging arrangement of the target charging pile based on the above configuration information and the above typical load curve.

[0066] It should be noted that the above-mentioned acquisition module 20, first determination module 22, second determination module 24 and third determination module 26 correspond to steps S102 to S106 in embodiment 1. The three modules and the corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in embodiment 1 above.

[0067] It should be noted that the preferred implementation of this embodiment can be found in the relevant description in Embodiment 1, and will not be repeated here.

[0068] According to an embodiment of the present invention, an embodiment of a computer-readable storage medium is also provided. Optionally, in this embodiment, the computer-readable storage medium can be used to store the program code executed by the charging pile charging control method provided in Embodiment 1.

[0069] Optionally, in this embodiment, the computer-readable storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0070] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: acquiring historical charging data of the target charging pile and acquiring charging and discharging information of the energy storage device of the target charging pile; determining a typical load curve based on the historical charging data; determining configuration information of the energy storage device based on the charging and discharging information and the typical load curve; and determining the charging and discharging arrangement of the target charging pile based on the configuration information and the typical load curve.

[0071] Optionally, the aforementioned computer-readable storage medium is configured to store program code for performing the following steps: obtaining the historical charging period and historical charging amount of the target charging pile; performing calculations on the aforementioned historical charging period and historical charging amount to obtain a historical load curve.

[0072] Optionally, the aforementioned computer-readable storage medium is configured to store program code for performing the following steps: classifying the aforementioned historical load curves to obtain multiple daily charging load curves; calculating and processing the aforementioned multiple daily charging load curves to determine multiple aforementioned typical load curves, wherein each of the aforementioned typical load curves corresponds to a daily charging load curve.

[0073] Optionally, the aforementioned computer-readable storage medium is configured to store program code for performing the following steps: obtaining historical discharge periods and historical discharge amounts of the energy storage device.

[0074] Optionally, the aforementioned computer-readable storage medium is configured to store program code for performing the following steps: calculating and processing the aforementioned charge / discharge cost information and the aforementioned charge / discharge time information to determine the aforementioned capacity information and power information of the energy storage device based on the aforementioned historical discharge period, the aforementioned historical discharge amount, and the aforementioned typical load curve; and determining the aforementioned configuration information of the energy storage device based on the aforementioned capacity information and the aforementioned power information.

[0075] According to an embodiment of the present invention, an embodiment of a processor is also provided. Optionally, in this embodiment, the computer-readable storage medium described above can be used to store the program code executed by the charging pile charging control method provided in Embodiment 1 above.

[0076] This application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: acquiring historical charging data of a target charging pile and acquiring charging and discharging information of the energy storage device of the target charging pile; determining a typical load curve based on the historical charging data; determining configuration information of the energy storage device based on the charging and discharging information and the typical load curve; and determining the charging and discharging arrangement of the target charging pile based on the configuration information and the typical load curve.

[0077] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having the following method steps: acquiring historical charging data of a target charging pile, and acquiring charging and discharging information of the energy storage device of the target charging pile; determining a typical load curve based on the historical charging data; determining configuration information of the energy storage device based on the charging and discharging information and the typical load curve; and determining the charging and discharging arrangement of the target charging pile based on the configuration information and the typical load curve.

[0078] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0079] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0081] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0083] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0084] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A charging control method for a charging pile, characterized in that, include: Obtain historical charging data of the target charging pile, and obtain charging and discharging information of the energy storage device of the target charging pile; Based on the historical charging data, a typical load curve is determined. The typical load curve is based on four typical scenarios in spring, summer, autumn and winter, and each typical scenario is divided into three working conditions: weekdays, rest days and holidays to obtain multiple daily charging load curves. Based on the charging and discharging information and the typical load curve, the configuration information of the energy storage device is determined; Based on the configuration information and the typical load curve, the charging and discharging arrangement of the target charging pile is determined. The charging and discharging arrangement is calculated using a particle swarm optimization algorithm with the objective function of maximizing the saved electricity cost and minimizing the number of energy storage charging and discharging times, and with the constraints of meeting the charging demand during peak electricity price periods and the charging and discharging power and power limits of the energy storage device. The step of determining the configuration information of the energy storage device based on the charging and discharging information and the typical load curve includes: calculating the capacity and power information of the energy storage device based on historical discharge periods, historical discharge amounts, and the typical load curve; and determining the configuration information of the energy storage device based on the capacity and power information. The capacity information is calculated by recursively accumulating backwards from the end time of the last peak period in the typical load curve, with peak discharge amounts being positive and valley / normal charging amounts being negative, until the start time of the i-th peak period in a day. The accumulated amount is the minimum power requirement for the energy storage device to meet the discharge demand of peak period i and subsequent peak periods. The capacity information should be greater than or equal to the minimum capacity requirement of each peak period. The power information is calculated by accumulating backwards from the start time in the typical load curve until the start time of the i-th peak period, with valley / normal charging amounts being positive and peak discharge amounts being negative. The power information is greater than or equal to the maximum discharge power requirement of peak period i.

2. The method according to claim 1, characterized in that, The acquisition of historical charging data for the target charging pile includes: Obtain the historical charging time period and historical charging amount of the target charging pile; The historical charging periods and historical charging amounts are calculated and processed to obtain the historical load curve.

3. The method according to claim 2, characterized in that, The process of determining a typical load curve based on the historical charging data includes: The historical load curves are classified to obtain multiple daily charging load curves; The multiple daily charging load curves are calculated and processed to determine multiple typical load curves, wherein each typical load curve corresponds to a daily charging load curve.

4. The method according to claim 1, characterized in that, Obtaining the charging and discharging information of the energy storage device of the charging pile includes: Obtain the historical discharge periods and historical discharge amounts of the energy storage device.

5. A charging control device for a charging pile, characterized in that, include: The acquisition module is used to acquire historical charging data of the target charging pile and to acquire charging and discharging information of the energy storage device of the target charging pile. The first determining module is used to determine a typical load curve based on the historical charging data. The typical load curve is based on four typical scenarios in spring, summer, autumn and winter, and each typical scenario is divided into three working conditions: weekdays, rest days and holidays to obtain multiple daily charging load curves. The second determining module is used to determine the configuration information of the energy storage device based on the charging and discharging information and the typical load curve; The third determining module is used to determine the charging and discharging arrangement of the target charging pile based on the configuration information and the typical load curve. The charging and discharging arrangement is calculated using a particle swarm optimization algorithm with the objective function of maximizing the saved electricity cost and minimizing the number of energy storage charging and discharging times, and with the constraints of meeting the charging demand during peak electricity price periods and the charging and discharging power and power limits of the energy storage device. The second determining module is further configured to calculate the capacity and power information of the energy storage device based on historical discharge periods, historical discharge amounts, and the typical load curve; and to determine the configuration information of the energy storage device based on the capacity and power information. The capacity information is calculated by recursively accumulating backwards from the end time of the last peak period in the typical load curve, with peak discharge amounts being positive and valley / normal charging amounts being negative, until the start time of the i-th peak period in a day. The accumulated amount is the minimum power requirement for the energy storage device to meet the discharge demand of peak period i and subsequent peak periods. The capacity information should be greater than or equal to the minimum capacity requirement of each peak period. The power information is calculated by accumulating backwards from the start time in the typical load curve until the start time of the i-th peak period, with valley / normal charging amounts being positive and peak discharge amounts being negative. The power information is greater than or equal to the maximum discharge power requirement of peak period i.

6. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores multiple instructions, which are adapted to be loaded by a processor and executed by the charging pile charging control method according to any one of claims 1 to 4.

7. A processor, characterized in that, The processor is used to run a program, wherein the program is configured to execute the charging pile charging control method according to any one of claims 1 to 4 when running.

8. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to execute the charging pile charging control method according to any one of claims 1 to 4.

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