Charging system and energy storage device control method and apparatus

Abstract

This invention discloses a charging system and a control method and apparatus for energy storage devices. This invention periodically acquires the charging power of the charging device at an energy storage charging station, as well as user information and battery information of the device being charged. Based on the charging information, it determines the estimated power demand for the current cycle, predicts the estimated power demand for the next cycle based on the current cycle's charging power and user information, and then determines a target discharge power limit based on the current cycle's estimated power demand, the next cycle's estimated power demand, and the rated discharge power of the energy storage device. Based on this target discharge power limit, it controls the discharge of the energy storage device in the next cycle, thereby ensuring that the discharge power of the energy storage device does not exceed the actual needs of the charging device, preventing backflow from the source. The technical solution of this invention can be implemented with software modifications on the server side, resulting in low cost and ensuring the safety of the charging station and the power grid.

Description

Technical Field

[0001] This invention relates to the field of energy storage and charging technology, specifically to a charging system and a control method and apparatus for energy storage devices. Background Technology

[0002] Energy storage charging stations are gradually expanding their application scale. For these stations, the electrical energy for the load can come from either the power grid or the energy storage device. Since the energy storage device is actually connected to the grid to supply power to the charging unit or load, it is directly or indirectly connected to the grid. In this scenario, backflow can occur, meaning the electrical energy released by the energy storage device can be fed back to the grid through the circuit, posing a significant threat to the stability and security of the power grid.

[0003] To prevent backflow, existing technologies often rely on installing physical anti-backflow devices between the energy storage equipment at charging stations and the power grid. These devices collect relevant data to regulate the energy storage equipment and prevent backflow. Alternatively, the energy storage converter can be modified to have data acquisition and calculation capabilities, enabling real-time power monitoring of both the grid-connected and energy storage sides to achieve backflow prevention. Both solutions require additional site equipment installation and place certain demands on the hardware's computing power. Furthermore, tailored solutions are needed for different construction scenarios, resulting in high costs. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a charging system and a method and apparatus for controlling energy storage devices, which aim to improve the safety of energy storage charging stations by using servers to predict charging trends at a lower cost without requiring large-scale modifications to hardware devices.

[0005] In a first aspect, a method for controlling an energy storage device is provided, the energy storage device being configured to be connected to a power grid in a grid-connected manner to supply power to at least one charging device, wherein the method includes:

[0006] Obtain the charging power of each charging device in the current cycle, as well as the user information currently being charged and the battery information of the device being charged;

[0007] A first estimate of the total power demand in the current cycle is determined based on the charging power;

[0008] For each charging device, the predicted value of the second charging power for the next cycle is determined based on the charging power of the current cycle, the charging device information, the user information, and the battery information.

[0009] A second estimate of the total power demand for the next cycle is determined based on the predicted charging power of each charging device for the next cycle.

[0010] Based on the first estimated value, the second estimated value, and the rated discharge power of the energy storage device, determine the upper limit of the target discharge power for the next cycle;

[0011] The target discharge power limit is sent to the energy storage device to control the output power limit of the energy storage device.

[0012] In a second aspect, a control device for an energy storage device is provided, the energy storage device being configured to supply power to at least one charging device, the energy storage device also being connected to a power grid, wherein the energy storage device discharge power control device includes:

[0013] The information acquisition unit is used to acquire the charging power of each charging device in the current cycle, as well as the user information currently being charged and the battery information of the device being charged.

[0014] The first estimation unit is used to determine a first estimated value of the total power demand in the current cycle based on the charging power.

[0015] The prediction unit is used to determine the predicted value of the second charging power for the next cycle for each charging device based on the charging power of the current cycle, the charging device information, the user information, and the battery information.

[0016] The second estimation unit is used to determine a second estimated value of the total demand power for the next cycle based on the predicted value of the charging power of each charging device for the next cycle.

[0017] The upper limit determination unit is used to determine the target discharge power upper limit for the next cycle based on the first estimated value, the second estimated value, and the rated discharge power of the energy storage device.

[0018] The control unit is used to send the target discharge power limit to the energy storage device in order to control the output power limit of the energy storage device.

[0019] Thirdly, an electronic device is provided, the controller including a memory and a processor, the memory for storing one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method as described in the first aspect.

[0020] Fourthly, a computer-readable storage medium is provided that stores computer program instructions thereon, which, when executed by a processor, implement the method described in the first aspect.

[0021] This invention, through its embodiments, periodically acquires charging power, user information, and battery information of the charging devices at an energy storage charging station on the server side. Based on the charging information, it determines the estimated power demand for the current cycle, predicts the estimated power demand for the next cycle based on the current cycle's charging power and user information, and then determines the target discharge power ceiling based on the current cycle's estimated power demand, the next cycle's estimated power demand, and the rated discharge power of the energy storage device. Finally, based on the target discharge power ceiling, it controls the discharge of the energy storage device in the next cycle, thereby ensuring that the discharge power of the energy storage device does not exceed actual needs and preventing backflow from the source. The technical solution of this invention can be implemented with software modifications on the server side, is low-cost, and ensures the safety of the charging station. Attached Figure Description

[0022] The above and other objects, features and advantages of the present invention will become clearer from the following description of embodiments of the invention with reference to the accompanying drawings, in which:

[0023] Figure 1 This is a schematic diagram of a charging system according to an embodiment of the present invention;

[0024] Figure 2 This is a flowchart of an energy storage device control method according to an embodiment of the present invention;

[0025] Figure 3 This is a data flow diagram of the energy storage device control method according to an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of the energy storage device control device according to an embodiment of the present invention;

[0027] Figure 5 This is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0028] The present application is described below based on embodiments, but it is not limited to these embodiments. In the detailed description of the present application below, certain specific details are described in detail. Those skilled in the art can fully understand the present application without these details. To avoid obscuring the substance of the present application, well-known methods, processes, flows, elements, and circuits are not described in detail.

[0029] Furthermore, those skilled in the art should understand that the accompanying drawings provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0030] Unless the context explicitly requires it, words such as "including" or "contains" throughout the application should be interpreted as including rather than exclusive or exhaustive; that is, meaning "including but not limited to".

[0031] In the description of this application, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0032] The solutions described in this specification and embodiments, if involving the processing of personal information, will be processed only under the premise of having a legal basis (such as obtaining the consent of the personal information subject, or being necessary for the performance of a contract), and will only be processed within the scope stipulated or agreed upon. A user's refusal to process personal information beyond what is necessary for basic functions will not affect the user's use of basic functions.

[0033] Figure 1 This is a schematic diagram of a charging system according to an embodiment of the present invention. The charging system can constitute the main body of an energy storage charging station, or it can be a part of an energy storage charging station. Figure 1 As shown, the charging system of this embodiment includes an energy storage device 1, at least one charging device 2, and a server 3. The energy storage device 1 includes at least one battery 11 and a power conversion system 12 (PCS). The power conversion system 12 is connected to the power grid 5 and the charging device 2.

[0034] Battery 11 can be a battery with high energy density, such as a lithium-ion battery.

[0035] The power conversion system 12 is the core component of the energy storage charging station, used to achieve DC-AC conversion, DC-DC conversion, or AC-DC conversion. The power conversion system 12 can not only convert DC power stored in the battery into AC power suitable for AC loads or DC power suitable for DC loads, but also convert AC power from the grid 5 into DC power suitable for battery charging. Simultaneously, the power conversion system 12 supports switching between grid-connected and off-grid modes for the energy storage device, enabling connected charging devices (e.g., charging piles) to obtain power from the battery 11 of the energy storage device 1 or the grid 5 for charging. The structure of the power conversion system 12 mainly includes a power electronic converter, a controller, sensors, and interface modules. The power electronic converter is responsible for bidirectional conversion between DC and AC power, as well as conversion between DC and DC power. For example, inverter and rectification technologies can be used to complete the DC-AC or DC-DC conversion process. The controller precisely regulates the operating state of the power electronic converter through a preset control algorithm to ensure the stability of output parameters such as voltage and current. Sensors are used to monitor internal and external environmental parameters, such as temperature, current, and voltage, providing control data for the controller. The interface module is used to communicate with external devices, including data exchange with the power grid, battery management system (BMS), user interface and other control systems, to ensure that the components work together.

[0036] When operating in grid-connected mode, since the power conversion system 12 is connected to the power grid 5, if the power extracted by the power conversion system 12 from the battery 11 is higher than the total demand of the charging device 2, current may flow to the power grid through the grid connection node of the power conversion system 12 and the power grid 5, thereby threatening the stable operation of the power grid 5.

[0037] Server 3 communicates with energy storage device 1 and charging device 2 via network 4. Network 4 can be a remote communication network, such as a mobile communication network or fiber optic network, or a combination thereof, or a local area network, such as a wireless or wired LAN. In some implementations, server 3 can communicate with energy storage device 1 and charging device 2 separately via independent communication connections. In other implementations, since power conversion system 12 is connected to at least one corresponding charging device 2 and can communicate with the connected charging device 2, server 3 can also communicate indirectly with the charging device 2 by communicating with the power conversion system 12 of energy storage device 1 via the network. Through different methods, server 3 can obtain information such as charging power, user information of the user currently using charging device 2, and battery information of the device being charged from energy storage device 1 and charging device 2. Based on this information, server 3 can determine a first estimate of the total power demand of the energy storage device in the current cycle, and predict a second estimate of the total power demand of the energy storage device in the next cycle. Then, based on the first and second estimates and the rated discharge power of the energy storage device, it determines the target discharge power ceiling for the next cycle and sends the target discharge power ceiling to the power conversion system 12 of energy storage device 1 to control the output power ceiling. This ensures that the output power of energy storage device 1 will not exceed the power demand of all connected charging devices, thereby effectively preventing reverse current and ensuring grid safety. The power conversion system 12 can control the output power according to the target discharge power ceiling by controlling parameters such as output current and output voltage during the power conversion process.

[0038] In this embodiment, server 3 should be understood as a device that provides data processing, database, and communication facilities. For example, server 3 may refer to a single physical server with associated communication, data storage, and database facilities, or it may refer to a networked or aggregated collection of processors, associated networks, and storage devices, operating software and one or more database systems and application software that support the services provided by the server. Server 3 may be a monolithic server or a distributed server spanning multiple computers or computer data centers. Server 3 may be various types of cloud servers. In some embodiments, each server 3 may include hardware, software, or embedded logic components or combinations of two or more such components for performing suitable functions supported or implemented by the server.

[0039] Figure 2 This is a flowchart of an energy storage device control method according to an embodiment of the present invention. Figure 2 As shown, the energy storage device control method of this embodiment is applied to Figure 1 The server in the aforementioned charging system. The control method includes:

[0040] Step S100: Obtain the charging power of each charging device in the current cycle, as well as the user information currently being charged and the battery information of the device being charged.

[0041] Step S200: Determine a first estimate of the total power demand in the current cycle based on the charging power.

[0042] Step S300: For each charging device, determine the predicted value of the charging power in the next cycle based on the charging power of the current cycle, the charging device information, the user information, and the battery information.

[0043] Step S400: Determine a second estimate of the total power demand for the next cycle based on the predicted charging power of each charging device for the next cycle.

[0044] Step S500: Determine the upper limit of the target discharge power for the next cycle based on the first estimated value, the second estimated value, and the rated discharge power of the energy storage device.

[0045] Step S600: Send the target discharge power limit to the energy storage device to control the output power limit of the energy storage device.

[0046] This invention, through a server-side approach, periodically acquires the charging power of the charging devices at an energy storage charging station, along with user information and battery information of the devices being charged. Based on this charging information, it determines an estimated power demand for the current cycle. Then, based on the current cycle's charging power and user information, it predicts an estimated power demand for the next cycle. Finally, it determines a target discharge power ceiling based on the current and next cycle's estimated power demand and the energy storage device's rated discharge power. Finally, based on this target discharge power ceiling, it controls the energy storage device's discharge in the next cycle, ensuring that the energy storage device's discharge power does not exceed actual needs and preventing backflow from the source. This invention's technical solution involves software modifications on the server side, achieving low cost and ensuring the safety of the charging station.

[0047] The following provides further explanation of the different implementation methods for each step.

[0048] In step S100, in this embodiment, user information may include the user account and the model of the device being charged. Since the charging device obtains relevant information about the device being charged, such as its model and battery capacity, through the charging interface after connecting to it, this information can be stored as user information on the server. When a user uses the charging device again, they typically need to log in to their user account through a client program on their terminal or the charging device to settle subsequent payments. Therefore, the server can obtain the currently logged-in user information for each used charging device. The charging power of the charging device in the current cycle can be actively reported by the charging device through a communication connection, or detected by the energy storage device through a power conversion system and reported to the server, or periodically requested by the server from the charging device. For unused charging devices, it is still necessary to obtain their consumed power; however, since they do not output a significant amount of energy, and the user information and battery information obtained can be empty, the potential power of these charging devices will not be predicted in the subsequent prediction stage. Even if unused charging devices are used later, the power demand for energy storage devices will increase, ensuring that the target power limit determined in the current cycle will not exceed the demand.

[0049] In this embodiment, the period is a pre-set fixed time period. Different time periods can be set according to different control strategies; for example, the period can be 1 second, 5 seconds, 30 seconds, or 1 minute. The setting of the period is related to the device hardware response speed, performance, and the protection response speed desired by the designer.

[0050] For step S200, the calculation of the first estimate of the total power demand for the current cycle can be simply achieved by summing the charging power of each charging device for the current cycle.

[0051] In another implementation, a more precise estimation method can be used. Specifically, a first estimate of the total power demand is determined by summing the charging power of all charging devices connected to the energy storage device in the current cycle and then comparing it with the detected fixed load power demand. The fixed load power demand can include the power consumed by the charging devices when not in use, as well as the relatively stable power demand of other loads connected to the energy storage device.

[0052] Specifically, the first estimated value P can be calculated using the following formula. s (t i ):

[0053]

[0054] Among them, P n, n∈(1,2,…N) is the charging power of the nth charging device in the current cycle, N is the number of charging devices connected to the energy storage device, n≤N.

[0055] α is a predetermined empirical amplification factor, which is set slightly greater than 1 to accurately account for some line or loss calculations. P other The power required for the fixed load is given. It should be understood that the empirical amplification factor can be set experimentally. For example, the power can be calculated from parameters reported by the charging device, or the reported power value can be obtained, and then the actual power can be measured using a high-precision power meter. The empirical amplification factor is then set based on the reported or calculated power value and the measured actual power.

[0056] After determining a first estimate of the total power demand for the current period, the method of this embodiment determines a predicted value (i.e., a second estimate) of the total power demand for the next period in steps S300 and S400.

[0057] Specifically, in step S300, the charging power for the next cycle is predicted. Various methods can be used to predict the charging power. For example, linear regression can be used, with the regression curve of the entire energy storage device or a single charging unit obtained in advance based on historical data. The charging power or sum of charging power for the next cycle is predicted based on the charging power or the sum of charging power for the current cycle. Alternatively, a power prediction model trained based on historical data can be used to predict the vehicle's charging power or the sum of charging power. The specific steps include:

[0058] Step S310: Determine the target charging device.

[0059] Different charging devices may have different rated power outputs. Furthermore, due to varying losses within the charging devices, different models can be trained for different charging devices or different models. It should be understood that all charging devices from the same manufacturer can also share the same power prediction model.

[0060] Step S320: Determine the power prediction model corresponding to the target charging device. The power prediction model is pre-trained based on historical charging data.

[0061] Specifically, the power prediction model can be trained and determined based on historical charging data. For example, charging power, user information, battery information, and other information from each cycle during historical charging processes can be collected. This data is used as input to a sample, and the charging power of the next cycle is used as the output. The power prediction model is then trained based on this sample data.

[0062] In one implementation, user information may include user account, the model of the charging device used by the user in the past, etc.

[0063] Specifically, the power prediction model can be trained individually for each charging device, or it can be trained based on historical data from a specific model of charging device. The model can employ, for example, LSTM, or a modified large language model.

[0064] It should be understood that in some implementations, historical charging data can also be used as part of the user information and as input to one dimension of the power prediction model.

[0065] Specifically, if the user information indicates that the user account has historical charging data stored on the server, then the historical charging data of the user account will be used as the historical charging data. If the user information indicates that the user account is a newly registered account, or an account that has not been used for a long time, and there is no historical charging data on the server, then the historical charging data corresponding to other user accounts that have used the same model of the charged device can be obtained as the historical charging data.

[0066] Step S340: Using the charging power of the current cycle, the charging device information of the target charging device, the user information, and the battery information as inputs, the predicted value of the charging power of the target charging device in the next cycle is determined by the power prediction model.

[0067] In this embodiment, the user information includes the user account, the model of the device being charged, and the aforementioned historical charging data, and the battery information is the current battery capacity of the device being charged.

[0068] Incorporating the charging power of the current cycle into the input of the power prediction model can help in subsequent judgments of changes in charging power.

[0069] Incorporating historical charging data into the input of the power prediction model can help reflect the specific attributes of the device being charged. Since different models of the device being charged use different battery models, their attributes will vary to some extent. By incorporating historical charging data from the user or similar devices, it is helpful to judge the changes in subsequent charging power.

[0070] Similarly, there are differences between charging devices. Therefore, the introduction of charging device information can help reflect the special attributes of the charging device and facilitate the power prediction model to predict the subsequent changes in the charging power of the charging device.

[0071] Among these, battery information can be battery capacity information, also known as state of charge (SOC). Battery capacity information can indicate whether the battery is about to be fully charged, and whether the charging device will stop charging in the next cycle, thus affecting whether total demand will suddenly decrease in the next cycle.

[0072] Simultaneously, charging order information can be used as one of the inputs to the power prediction model. Currently, charging order information can include the maximum charging amount or the maximum state of charge. That is, the charging order information can specify whether to stop charging the device at a certain cost or to a certain percentage of charge. This information can also help determine whether the target charging device will stop charging in the next cycle, thereby reducing total demand.

[0073] After determining the predicted value of the charging power, a second estimate of the total power demand, i.e., the predicted value of the total power demand for the next cycle, can be determined in the same manner as in step S200.

[0074] Specifically, the second estimated value is calculated according to the following formula:

[0075]

[0076] Among them, P n (t i+1 ), n∈(1,2,…N) represents the next cycle (t) of the nth charging device. i+1 The predicted charging power of the energy storage device is given by N, where N is the number of charging devices connected to the energy storage device, n≤N; and α is the predetermined empirical amplification factor. other The power required by the fixed load.

[0077] Therefore, the target discharge power upper limit for the next cycle can be determined between the first estimated value, the second estimated value and the rated discharge power value of the energy storage device in step S500.

[0078] Different methods can be used to determine the upper limit of the target discharge power.

[0079] In one alternative implementation, the minimum value among the first estimated value, the second estimated value, and the rated discharge power value of the energy storage device can be directly taken as the target discharge power upper limit. Using this minimum value as the target discharge power upper limit ensures that the discharge power of the energy storage device in the next cycle will definitely be less than the total demand value, thereby effectively preventing backflow.

[0080] In another alternative implementation, a safety threshold, namely a power hysteresis value, can be added. A first difference between a first estimated value and a predetermined power hysteresis value can be calculated; a second difference between a second estimated value and the predetermined power hysteresis value can be calculated; then, the minimum value among the first difference, the second difference, and the rated discharge power of the energy storage device is determined as the target discharge power upper limit. Because the power hysteresis value is introduced, the final target discharge power upper limit will be further less than or equal to the first estimated value or the second estimated value minus the power hysteresis value. This further ensures that the discharge power of the energy storage device in the next cycle is definitely less than the total demand, thereby effectively preventing backflow.

[0081] Figure 3 This is a data flow diagram of the energy storage device control method according to an embodiment of the present invention. For example... Figure 3 As shown, in the process of the energy storage device control method, firstly, in the current cycle, the server 3 obtains the charging power 31 of the current cycle, the battery information 32 of the device being charged, and the user information 33 of the user currently charging from each charging device 2.

[0082] Then, based on the charging power 31 of the multiple charging devices 2 in the current cycle, a first estimate 34 of the total power demand in the current cycle can be obtained. If the charging device 2 is not used, its charging power 31 in the current cycle is 0.

[0083] In parallel, for each charging device 2, the charging power 31 of the current cycle, charging device information 35 (which can be obtained from the server's database), user information 33, and battery information 32 are input into the power prediction model 36 to obtain the predicted charging power 37 for each charging device 2 in the next cycle. It should be understood that if a charging device 2 is not used, its predicted charging power for the next cycle can be assumed to be zero, and there is no need to use the power prediction model to predict it again. It should also be understood that the user information 33 may include historical charging data, the signal of the device being charged, order information, etc.

[0084] Then, the predicted charging power values ​​37 for the next cycle of all charging devices are combined to determine a second estimate 38 of the total power demand for the next cycle.

[0085] Then, the target discharge power upper limit 30 is determined based on the smaller of the first estimated value 34, the second estimated value 38, and the predetermined rated discharge power 39 of the energy storage device. It should be understood that in some alternative implementations, a power hysteresis value may also be introduced, and the minimum value obtained by subtracting the power hysteresis value from the first estimated value 34 and the second estimated value 38 and then taking the minimum value with the predetermined rated discharge power 39 of the energy storage device can be used as the target discharge power upper limit 30.

[0086] Finally, the target discharge power limit of 30 is sent to the energy storage device 1 via network 4 to control the output power of the energy storage device.

[0087] Figure 4 This is a schematic diagram of the energy storage device control device according to an embodiment of the present invention. Figure 4 As shown, the energy storage device control device in this embodiment includes an information acquisition unit 41, a first estimation unit 42, a prediction unit 43, a second estimation unit 44, an upper limit determination unit 45, and a control unit 46.

[0088] Information acquisition unit 41 is used to acquire the charging power of each charging device in the current cycle, as well as the user information and battery information of the device being charged. First estimation unit 42 is used to determine a first estimated value of the total power demand in the current cycle based on the charging power. Prediction unit 43 is used to determine a predicted value of the second charging power for the next cycle for each charging device, based on the charging power of the current cycle, the charging device information, the user information, and the battery information. Second estimation unit 44 is used to determine a second estimated value of the total power demand for the next cycle based on the predicted values ​​of the charging power for each charging device in the next cycle. Upper limit determination unit 45 is used to determine a target discharge power upper limit for the next cycle based on the first and second estimated values ​​and the rated discharge power of the energy storage device. Control unit 46 is used to send the target discharge power upper limit to the energy storage device to control the upper limit of the energy storage device's output power.

[0089] This invention, through a server-side approach, periodically acquires the charging power of the charging devices at an energy storage charging station, along with user information and battery information of the devices being charged. Based on this charging information, it determines an estimated power demand for the current cycle. Then, based on the current cycle's charging power and user information, it predicts an estimated power demand for the next cycle. Finally, it determines a target discharge power ceiling based on the current and next cycle's estimated power demand and the energy storage device's rated discharge power. Finally, based on this target discharge power ceiling, it controls the energy storage device's discharge in the next cycle, ensuring that the energy storage device's discharge power does not exceed actual needs and preventing backflow from the source. This invention's technical solution involves software modifications on the server side, achieving low cost and ensuring the safety of the charging station.

[0090] Figure 5 This is a schematic diagram of an electronic device according to an embodiment of the present invention. (For example...) Figure 5 As shown, the electronic device includes a general computer hardware structure, which includes at least a processor 51 and a memory 52, and is used to constitute a server in an embodiment of the present invention.

[0091] Processor 51 and memory 52 are connected via bus 53. Memory 52 is adapted to store instructions or programs executable by processor 51. Processor 51 may be a standalone microprocessor or a collection of one or more microprocessors. Thus, processor 51 executes the instructions stored in memory 52 to perform the method flow of the embodiments of the present invention as described above, thereby realizing data processing and control of other devices. Bus 53 connects the aforementioned components together and connects the aforementioned components to display controller 54, display device, and input / output (I / O) device 55. Input / output (I / O) device 55 may be a mouse, keyboard, modem, network interface, touch input device, motion-sensing input device, printer, and other devices known in the art. Typically, input / output device 55 is connected to the system via input / output (I / O) controller 56.

[0092] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus (devices), or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0093] This application is described with reference to flowchart illustrations of methods, apparatus (devices), and computer program products according to embodiments of this application. It should be understood that each step in the flowchart can be implemented by computer program instructions.

[0094] These computer program instructions may be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction means, the implementation process of which is described in the instruction means. Figure 1 The function specified in one or more processes.

[0095] These computer program instructions may also be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, produce instructions for implementing processes. Figure 1 A device for a function specified in one or more processes.

[0096] Another embodiment of the present invention relates to a non-volatile storage medium for storing a computer-readable program for use by a computer to execute some or all of the above-described method embodiments.

[0097] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program specifying the relevant hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0098] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method of controlling an energy storage device configured to be connected to a power grid to supply power to at least one charging device in a grid-connected manner, characterized in that, The method includes: Obtain the charging power of each charging device in the current cycle, as well as the user information currently being charged and the battery information of the device being charged; A first estimate of the total power demand in the current cycle is determined based on the charging power; For each charging device, the predicted value of the second charging power for the next cycle is determined based on the charging power of the current cycle, the charging device information, the user information, and the battery information. A second estimate of the total power demand for the next cycle is determined based on the predicted charging power of each charging device for the next cycle. Based on the first estimated value, the second estimated value, and the rated discharge power of the energy storage device, determine the upper limit of the target discharge power for the next cycle; The target discharge power limit is sent to the energy storage device to control the output power limit of the energy storage device.

2. The method of claim 1, wherein, Determining the first estimate of the total power demand for the current cycle based on the charging power includes: A first estimate of the total power demand is determined by summing the current cycle charging power of all charging devices connected to the energy storage device and the detected fixed load demand power.

3. The method of claim 2, wherein, Determining a first estimate of the total power demand based on the sum of the current cycle charging power of all charging devices connected to the energy storage device, and the detected fixed load demand power, includes calculating the first estimate according to the following formula: Wherein, P n , n ∈ (1, 2, … N) is the charging power of the nth charging device in the current period, N is the number of charging devices connected to the energy storage device, n ≤ N; α is a predetermined empirical amplification factor; P other is the fixed load demand power.

4. The method of claim 1, wherein, The predicted value of the charging power for the next cycle is determined based on the charging power of the current cycle, the charging device information, the user information, and the battery information, including: Identify the target charging device; Determine the power prediction model corresponding to the target charging device, and the power prediction model is pre-trained based on historical charging data; Using the charging power of the current cycle, the charging device information of the target charging device, the user information, and the battery information as inputs, the predicted value of the charging power of the target charging device in the next cycle is determined by the power prediction model. The user information includes the user account and the model of the device being charged, and the battery information is the current battery capacity of the device being charged.

5. The method of claim 4, wherein, The user information also includes historical charging data; The method further includes: In response to the user account in the user information including historical charging data, the historical charging data of the user account is used as the historical charging data. If the user account in the user information does not have historical charging data, the historical charging data of other user accounts with the same model of the device being charged will be used as the historical charging data.

6. The method of claim 3, wherein, Determining a second estimated value of the total demand power for the next period in dependence on predicted values of the charging power of the respective charging devices for the next period comprises calculating said second estimated value P s (t i+1 ) according to the formula P(t) = P(t-1) + ∑(P(t-1) - P(t-1)) wherein P n (t i+1 ), n∈(1,2,…N) is the predicted value of the charging power of the nth charging device in the next period, N is the number of charging devices connected to the energy storage device, n≤N; a is a predetermined empirical amplification factor; P other is the fixed load demand power.

7. The method of claim 6, wherein, Based on the first estimated value, the second estimated value, and the rated discharge power of the energy storage device, the upper limit of the target discharge power for the next cycle is determined as follows: Calculate the first difference between the first estimated value and the predetermined power hysteresis value; Calculate the second difference between the second estimate and the predetermined power hysteresis value; The minimum value among the first difference, the second difference, and the rated discharge power of the energy storage device is determined as the upper limit of the target discharge power.

8. An energy storage device control device, the energy storage device being configured to power at least one charging device, the energy storage device further being connected to a power grid, characterized in that, The energy storage device discharge power control device includes: The information acquisition unit is used to acquire the charging power of each charging device in the current cycle, as well as the user information currently being charged and the battery information of the device being charged. The first estimation unit is used to determine a first estimated value of the total power demand in the current cycle based on the charging power. The prediction unit is used to determine the predicted value of the second charging power for the next cycle for each charging device based on the charging power of the current cycle, the charging device information, the user information, and the battery information. The second estimation unit is used to determine a second estimated value of the total demand power for the next cycle based on the predicted value of the charging power of each charging device for the next cycle. The upper limit determination unit is used to determine the target discharge power upper limit for the next cycle based on the first estimated value, the second estimated value, and the rated discharge power of the energy storage device. The control unit is used to send the target discharge power limit to the energy storage device in order to control the output power limit of the energy storage device.

9. A charging system, characterized by include: Energy storage devices are connected to the power grid; At least one charging device is connected to the energy storage device to obtain electrical energy from the energy storage device or the power grid for charging; A server, communicatively connected to the charging device and the energy storage device, is configured to perform the method as described in any one of claims 1-7.

10. An electronic device, comprising: The electronic device includes a memory and a processor, the memory being used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method as described in any one of claims 1-7.

11. A computer readable storage medium having stored thereon computer program instructions, wherein, When the computer program instructions are executed by the processor, they implement the method as described in any one of claims 1-7.

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