A method for constructing a support capability evaluation model of an energy storage system and a power energy storage system

Abstract

The application discloses a kind of energy storage system support capacity evaluation model construction method and electric power energy storage system, method includes: obtaining the running data of target historical time length of energy storage system under different operating conditions, the running data is used to determine the operating power of energy storage system;According to the running data, determine the safe operation boundary of energy storage system under different operating conditions;According to the safe operation boundary, determine the available support capacity corresponding to different operating data under corresponding operating state;According to the running data under different operating conditions and corresponding available support capacity, train energy storage system support capacity evaluation model, until the prediction accuracy of energy storage system support capacity evaluation model meets prediction requirement, wherein energy storage system support capacity evaluation model adopts compression model algorithm for model optimization in training process, optimize energy storage system support capacity evaluation model using compression model algorithm, improve the efficiency of real-time evaluation of large-scale energy storage system support capacity.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage support, in particular to an energy storage system support capacity evaluation model construction method and a power energy storage system. BACKGROUND

[0002] Power energy storage has the characteristics of rapid power regulation, and large-scale power energy storage can provide active, reactive or emergency recovery of many types of system support, effectively suppress system volatility, and is an important regulation resource of flexible system encouraged to develop under the background of current "double high" new power system. In the prior art, the support capacity of power energy storage to the system mainly has three technical routes, such as starting from the grid side or the power supply side, mainly through grid side operation scheduling, energy storage station level coordinated control or energy storage support new energy smoothing processing and other technologies to study the support capacity of the power energy storage system.

[0003] However, the prior art needs to calculate the real-time support capacity of the power energy storage system based on a large amount of operation data of energy storage system units, energy storage power station cluster systems and the like in different states, resulting in a huge amount of calculation and affecting the calculation speed. Therefore, it is urgent to propose an energy storage system support capacity evaluation model construction method, which uses the energy storage system support capacity evaluation model to calculate the real-time support capacity of the energy storage system, so as to improve the accuracy and efficiency of real-time evaluation of the support capacity of large-scale energy storage systems and improve the timeliness of operation decision-making for the energy storage system. SUMMARY

[0004] Therefore, the technical problem to be solved by the present application is to overcome the defects of large calculation amount and slow calculation speed of the real-time support capacity of the existing energy storage system, so as to provide an energy storage system support capacity evaluation model construction method and a power energy storage system.

[0005] According to a first aspect, an energy storage system support capacity evaluation model construction method is disclosed, the method comprising: obtaining operation data of an energy storage system corresponding to a target historical time length in different operating states, the operation data being used to determine the operating power of the energy storage system; determining the safe operating boundary of the energy storage system in different operating states according to the operation data; determining the available support capacity corresponding to different operation data in the corresponding operating state according to the safe operating boundary; training an energy storage system support capacity evaluation model according to the operation data in different operating states and the corresponding available support capacity until the prediction accuracy of the energy storage system support capacity evaluation model meets the prediction requirement, wherein the energy storage system support capacity evaluation model adopts a compression model algorithm for model optimization in the training process.

[0006] Optionally, the energy storage system comprises multiple energy storage units; the method further includes: acquiring operational data of the target historical duration corresponding to the energy storage units under different operating states; determining the safe operating boundaries of the energy storage units under different operating states based on the operational data; and determining the safe operating boundaries of the corresponding energy storage system under different operating states based on the safe operating boundaries of the multiple energy storage units under different operating states.

[0007] Optionally, determining the safe operating boundary of the energy storage system under different operating states based on the operating data includes: performing data filtering processing on the obtained operating data of the energy storage system under different states for a target historical duration based on preset safe operating conditions; and determining the safe operating boundary of the energy storage system under different operating states based on the operating data after data filtering processing.

[0008] Optionally, the method further includes: acquiring the operating temperature of the energy storage system corresponding to different operating data; the step of performing data filtering processing on the acquired operating data of the energy storage system under different states for a target historical duration based on preset safe operating conditions includes: based on the operating temperature of the energy storage system corresponding to different operating data, performing data filtering processing on the acquired operating data of the energy storage system under different states for a target historical duration according to preset safe operating temperature requirements, to obtain operating data that meets the safe operating conditions and is used to determine the operating power of the energy storage system.

[0009] According to a second aspect, embodiments of the present invention also disclose a method for evaluating the support capability of an energy storage system. The method includes: acquiring the current operating status and operating data of the energy storage system; inputting the acquired operating status and operating data of the energy storage system into an energy storage system support capability evaluation model to determine the support capability of the energy storage system. The energy storage system support capability evaluation model is constructed by the energy storage system support capability evaluation model construction method as described in the first aspect or any optional embodiment of the first aspect.

[0010] According to a third aspect, embodiments of the present invention also disclose a power energy storage system, the system comprising: an energy storage cluster, the energy storage cluster including at least one energy storage system; an energy storage operation control center, communicatively connected to the energy storage cluster and a dispatch center respectively; and a support capability prediction platform, connected to the energy storage cluster and the energy storage operation control center respectively, wherein the support capability prediction platform integrates an energy storage system support capability assessment model, used to predict the support capability of the energy storage cluster, and sends the support capability of the energy storage cluster to the energy storage operation control center, so that the energy storage operation control center sends the received support capability of the energy storage cluster to the dispatch center, so that the dispatch center performs energy storage dispatch planning, wherein the energy storage system support capability assessment model is constructed by the energy storage system support capability assessment model construction method described in the first aspect or any optional embodiment of the first aspect;

[0011] According to a fourth aspect, embodiments of the present invention also disclose an apparatus for constructing a support capability assessment model for an energy storage system. The apparatus includes: a data acquisition module for acquiring operational data of a target historical duration corresponding to different operating states of the energy storage system, the operational data being used to determine the operating power of the energy storage system; an operational boundary determination module for determining the safe operating boundary of the energy storage system under different operating states based on the operational data; a support capability determination module for determining the available support capability corresponding to different operational data under the corresponding operating states based on the safe operating boundary; and a model construction module for training an energy storage system support capability assessment model based on the operational data under different operating states and the corresponding available support capability, until the prediction accuracy of the energy storage system support capability assessment model meets the prediction requirements, wherein the energy storage system support capability assessment model is optimized using a compressed model algorithm during the training process.

[0012] According to the fifth aspect, the present invention also discloses an energy storage system support capability assessment device, comprising: a data acquisition module for acquiring the current operating status and operating data of the energy storage system; and a support capability determination module for inputting the acquired operating status and operating data of the energy storage system into an energy storage system support capability assessment model to determine the support capability of the energy storage system, wherein the energy storage system support capability assessment model is constructed by the energy storage system support capability assessment model construction method described in the first aspect or any optional embodiment of the first aspect.

[0013] According to a sixth aspect, embodiments of the present invention also disclose an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the steps of the energy storage system support capability assessment model construction method as described in the first aspect or any optional embodiment of the first aspect, or the steps of the energy storage system support capability assessment method as described in the second aspect.

[0014] According to the seventh aspect, embodiments of the present invention also disclose a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the energy storage system support capability assessment model construction method as described in the first aspect or any optional embodiment of the first aspect, or the steps of the energy storage system support capability assessment method as described in the second aspect.

[0015] The technical solution of this invention has the following advantages:

[0016] The present invention provides a method for constructing an energy storage system support capability assessment model. This method involves acquiring historical operational data of the energy storage system under different operating conditions for a target duration, determining the safe operating boundaries of the energy storage system under different operating conditions based on the operational data, determining the available support capabilities corresponding to different operational data under the corresponding operating conditions based on the safe operating boundaries, and training the energy storage system support capability assessment model based on the operational data and corresponding available support capabilities under different operating conditions until the prediction accuracy of the energy storage system support capability assessment model meets the prediction requirements. During the training process, the energy storage system support capability assessment model is optimized using a compressed model algorithm. Optimizing the energy storage system support capability assessment model using the compressed model algorithm can improve the accuracy and efficiency of real-time assessment of the support capability of large-scale energy storage systems. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a specific example of the method for constructing an energy storage system support capability assessment model in an embodiment of the present invention;

[0019] Figure 2 This is a flowchart illustrating a specific example of the energy storage system support capability assessment method in an embodiment of the present invention;

[0020] Figure 3 This is a specific example diagram of a power energy storage system in an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of a specific example of a device for constructing an energy storage system support capability assessment model in an embodiment of the present invention.

[0022] Figure 5 This is a schematic diagram of a specific example of an energy storage system support capability assessment device in an embodiment of the present invention.

[0023] Figure 6 This is a specific example diagram of an electronic device in an embodiment of the present invention. Detailed Implementation

[0024] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can also refer to the internal connection of two components; and they can refer to a wireless connection or a wired connection. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0027] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0028] This invention discloses a method for constructing an assessment model for the support capacity of an energy storage system, such as...Figure 1 As shown, the method includes the following steps:

[0029] Step 101: Obtain the target historical duration of operating data for the energy storage system under different operating states. The operating data is used to determine the operating power of the energy storage system. For example, in this application, different operating states include at least the charging, discharging, or static states of the energy storage system. Obtain historical operating data for a time period corresponding to different states of the energy storage system. The historical operating data includes current and voltage used to determine the operating power of the energy storage system. It may also include the charging and discharging conditions and duration, cycle number, and internal resistance value of the energy storage battery in the energy storage system, which are used to estimate the health status and performance status of the energy storage battery, such as estimating the SOH value of the energy storage battery.

[0030] Step 102: Determine the safe operating boundary of the energy storage system under different operating states based on the operating data. For example, in this embodiment, the safe operating boundary of the energy storage system can be represented in the form of [min(I,U,T), max(I,U,T)]. The safe operating boundary of the energy storage system can be determined by selecting the limit charge and discharge current, voltage, and temperature range that ensures the energy storage system is in normal operating state, etc., of the operating data of the energy storage system under any safe operating state. This is just an example. The safe operating boundary model includes, but is not limited to, current, voltage, and temperature.

[0031] Step 103: Based on the safe operation boundary, determine the available support capacity corresponding to different operating data under the corresponding operating state;

[0032] For example, in this application embodiment, the energy storage system has a power conversion function, and its support for the power grid can refer to the power balance support under steady state and the safety and stability support under transient state, including but not limited to the energy storage system performing frequency regulation, peak shaving, or voltage regulation on the power grid. The maximum available support capacity of the energy storage system can be calculated by the following formula:

[0033] Maximum available support capacity = Real-time active power of energy storage system - Active power of energy storage system under maximum safe operating boundary;

[0034] Maximum available support capacity = Real-time reactive power of energy storage system - Reactive power of energy storage system under maximum safe operating boundary;

[0035] Based on any operating data under any operating state, the real-time active or reactive power of the corresponding energy storage system can be obtained. Then, based on the above formula, the active or reactive power under the maximum safe operating boundary of the energy storage system is subtracted. By repeating the calculation for different operating data, the maximum available support capacity corresponding to different operating data under different operating states can be obtained. The calculation method of support capacity is only an example.

[0036] Step 104: Train the energy storage system support capability assessment model based on the operating data and corresponding support capabilities under different operating conditions until the prediction accuracy of the energy storage system support capability assessment model meets the prediction requirements. The energy storage system support capability assessment model is optimized by using a compressed model algorithm during the training process.

[0037] For example, this application embodiment employs a compression model algorithm to optimize the energy storage system support capability assessment model. For instance, the SparseGPT intelligent compression model algorithm can be used to optimize the energy storage system support capability assessment model. This involves sorting the magnitudes of the output and intermediate layer weights in the energy storage system support capability assessment model, pruning connections below a preset threshold, and updating the weights to obtain the pruned network. The SparseGPT algorithm can prune the energy storage system support capability assessment model to 50% sparsity in a single step without any retraining, reducing the model's accuracy loss. This is merely an example. Operating data under different operating conditions and the corresponding support capabilities are input into the energy storage system support capability assessment model for training until the assessment accuracy of the energy storage system support capability assessment model meets the requirements.

[0038] The present invention provides a method for constructing an energy storage system support capability assessment model. This method involves acquiring historical operational data of the energy storage system under different operating conditions for a target duration, determining the safe operating boundaries of the energy storage system under different operating conditions based on the operational data, determining the available support capabilities corresponding to different operational data under the corresponding operating conditions based on the safe operating boundaries, and training the energy storage system support capability assessment model based on the operational data and corresponding available support capabilities under different operating conditions until the prediction accuracy of the energy storage system support capability assessment model meets the prediction requirements. During the training process, the energy storage system support capability assessment model is optimized using a compressed model algorithm. Optimizing the energy storage system support capability assessment model using the compressed model algorithm can improve the accuracy and efficiency of real-time assessment of the support capability of large-scale energy storage systems.

[0039] As an optional embodiment of the present invention, the energy storage system is composed of multiple energy storage units; the method further includes: acquiring operating data of the target historical duration corresponding to the energy storage units under different operating states; determining the safe operating boundary of the energy storage units under different operating states based on the operating data; and determining the safe operating boundary of the corresponding energy storage system under different operating states based on the safe operating boundaries of the multiple energy storage units under different operating states.

[0040] For example, in this embodiment of the application, the target historical duration of the operation data of the energy storage unit under different operating conditions is obtained. By obtaining the limit charge and discharge current, voltage, and temperature range that ensures the safe operation of the energy storage unit, the safe operating boundary of the corresponding energy storage unit is determined. Since the energy storage system is composed of multiple energy storage units, the safe operating boundary set of the energy storage system is obtained by statistically analyzing the safe operating boundaries of multiple energy storage units. When the energy storage system needs to support the power grid and ensure the stable operation of the power grid, a suitable energy storage unit is selected based on the safe operating boundary of each energy storage unit to support the power grid and ensure the stable operation of the power grid. Then, the maximum available support capacity of the energy storage system is calculated. For example, the safe operating boundary of the energy storage system under different operating conditions can be determined by taking the intersection of the safe operating boundaries of multiple energy storage units under different operating conditions.

[0041] As an optional embodiment of the present invention, determining the safe operating boundary of the energy storage system under different operating states based on the operating data includes: performing data filtering processing on the obtained operating data of the energy storage system under different states for a target historical duration based on preset safe operating conditions; and determining the safe operating boundary of the energy storage system under different operating states based on the operating data after data filtering processing.

[0042] For example, in the operation data of the energy storage system for the target historical period obtained in the embodiments of this application, there may be abnormal operation data due to the failure of the energy storage system, which will affect the calculation of the support capability of the energy storage system. Therefore, after obtaining the operation data, the operation data can be detected and filtered. For example, threshold ranges for parameters such as current and voltage can be set. When any operation data is not within the corresponding threshold range, it is removed. Finally, the operation data of the energy storage system under normal operation is obtained, and then the safe operation boundary of the energy storage system is determined. This is only an example.

[0043] As an optional embodiment of the present invention, the method further includes: acquiring the operating temperature of the energy storage system corresponding to different operating data; the step of performing data filtering processing on the acquired operating data of the energy storage system under different states for a target historical duration based on preset safe operating conditions includes: based on the operating temperature of the energy storage system corresponding to different operating data, performing data filtering processing on the acquired operating data of the energy storage system under different states for a target historical duration according to preset safe operating temperature requirements, to obtain operating data that meets the safe operating conditions and is used to determine the operating power of the energy storage system. For example, the operating data obtained in this application embodiment may also include the operating temperature of the energy storage system. Generally, when the energy storage system is running, the temperature of the energy storage system needs to be maintained within a preset target temperature range to reduce the energy loss of the energy storage system. If the operating temperature of the energy storage system is greater than the target temperature, it may affect the safe operation of the energy storage system and cause abnormalities in the operating data of the energy storage system. Therefore, after obtaining the operating data of the energy storage system, it is possible to detect whether the temperature data in the operating data is within the preset target temperature range. If not, it indicates that the energy storage system is in a fault state, and the corresponding operating data is removed. Finally, the operating data of the energy storage system under normal operating conditions is obtained for subsequent data calculation. This is only an example.

[0044] This invention also discloses a method for evaluating the support capacity of an energy storage system, such as... Figure 2 As shown, the method includes:

[0045] Step 201: Obtain the current operating status and operating data of the energy storage system; for example, in this embodiment of the application, the current operating status and operating data of the energy storage system can be obtained in real time for subsequent data processing.

[0046] Step 202 involves inputting the acquired operating status and data of the energy storage system into the energy storage system support capability assessment model to determine the support capability of the energy storage system. This energy storage system support capability assessment model is constructed using the energy storage system support capability assessment model construction method described in the above embodiments. For example, in this application embodiment, the real-time acquired operating status and data are input into the energy storage system support capability assessment model, which can quickly match the corresponding operating status and determine the corresponding energy storage system support capability based on the acquired operating data.

[0047] The energy storage system support capability assessment method provided by this invention obtains the current operating status and operating data of the energy storage system, and inputs the obtained operating status and operating data of the energy storage system into the energy storage system support capability assessment model to determine the maximum available support capability of the energy storage system. This method can quickly achieve accurate implementation assessment and prediction of the energy storage system support capability, improve the timeliness of energy storage system operation decisions, and enable internal control operation planning and support capability reporting for energy storage participation in grid ancillary services under the constraints of meeting grid dispatch instructions and optimal economic efficiency.

[0048] This invention also discloses an energy storage system, such as... Figure 3 As shown, the system includes:

[0049] An energy storage cluster, the energy storage cluster comprising at least one energy storage system;

[0050] The energy storage operation control center is communicatively connected to both the energy storage cluster and the dispatch center.

[0051] A support capability prediction platform is connected to both the energy storage cluster and the energy storage operation control center. This platform integrates an energy storage system support capability assessment model to predict the support capability of the energy storage cluster and transmits this capability to the energy storage operation control center. The control center then forwards the received support capability data to the dispatch center, enabling the dispatch center to perform energy storage dispatch planning. The energy storage system support capability assessment model is constructed using the method described in the above embodiments. For detailed explanations, please refer to the above embodiments; further elaboration is omitted here.

[0052] This invention also discloses a device for constructing an assessment model for the support capacity of an energy storage system, such as... Figure 4 As shown, the device includes:

[0053] Data acquisition module 301 is used to acquire the target historical duration of the operation data of the energy storage system under different operating states, and the operation data is used to determine the operating power of the energy storage system;

[0054] The operation boundary determination module 302 is used to determine the safe operation boundary of the energy storage system under different operating states based on the operation data.

[0055] The support capability determination module 303 is used to determine the available support capability corresponding to different operating data under the corresponding operating state based on the safe operating boundary;

[0056] The model building module 304 is used to train the energy storage system support capability assessment model based on the operating data under different operating conditions and the corresponding available support capabilities until the prediction accuracy of the energy storage system support capability assessment model meets the prediction requirements. The energy storage system support capability assessment model is optimized by a compressed model algorithm during the training process.

[0057] The energy storage system support capability assessment model construction device provided by this invention acquires operational data of the energy storage system for a target historical duration under different operating states, determines the safe operating boundary of the energy storage system under different operating states based on the operational data, determines the support capability corresponding to different operational data under the corresponding operating states based on the safe operating boundary, and trains the energy storage system support capability assessment model based on the operational data and corresponding support capabilities under different operating states until the prediction accuracy of the energy storage system support capability assessment model meets the prediction requirements. During the training process, the energy storage system support capability assessment model is optimized using a compressed model algorithm. Optimizing the energy storage system support capability assessment model using the compressed model algorithm can improve the accuracy and efficiency of real-time assessment of the support capability of large-scale energy storage systems.

[0058] As an optional embodiment of the present invention, the energy storage system is composed of multiple energy storage units; the device further includes: a data acquisition submodule, used to acquire operating data of the target historical duration corresponding to the energy storage units under different operating states; a first operating boundary determination module, used to determine the safe operating boundary of the energy storage units under different operating states based on the operating data; and a second operating boundary determination module, used to determine the safe operating boundary of the corresponding energy storage system under different operating states based on the safe operating boundaries of the multiple energy storage units under different operating states.

[0059] As an optional embodiment of the present invention, the operation boundary determination module includes: a data processing submodule, used to perform data filtering processing on the acquired operation data of the energy storage system under different states for a target historical duration based on preset safe operation conditions; and an operation boundary determination submodule, used to determine the safe operation boundary of the energy storage system under different operating states based on the operation data after data filtering processing.

[0060] As an optional embodiment of the present invention, the device further includes: a temperature acquisition module, used to acquire the operating temperature of the energy storage system corresponding to different operating data; the data processing submodule includes: a data filtering submodule, used to perform data filtering processing on the acquired operating data of the energy storage system under different states for a target historical duration based on the operating temperature of the energy storage system corresponding to different operating data, according to the preset safe operating temperature requirements, to obtain operating data that meets the safe operating conditions and is used to determine the operating power of the energy storage system.

[0061] This invention also discloses an energy storage system support capability assessment device, such as... Figure 5 As shown, the device includes: a data acquisition module 501, used to acquire the current operating status and operating data of the energy storage system; and a support capability determination module 502, used to input the acquired operating status and operating data of the energy storage system into the energy storage system support capability assessment model to determine the available support capability of the energy storage system. The energy storage system support capability assessment model is constructed by the energy storage system support capability assessment model construction method described in the above embodiment.

[0062] The energy storage system support capability assessment device provided by this invention acquires the current operating status and operating data of the energy storage system, and inputs the acquired operating status and operating data into the energy storage system support capability assessment model to determine the available support capability of the energy storage system. This allows for rapid and accurate implementation assessment and prediction of the energy storage system support capability, improves the timeliness of energy storage system operation decisions, and enables internal control operation planning and support capability reporting for energy storage participation in grid ancillary services under the constraints of meeting grid dispatch instructions and optimal economic efficiency.

[0063] This invention also provides an electronic device, such as... Figure 6 As shown, the electronic device may include a processor 401 and a memory 402, wherein the processor 401 and the memory 402 may be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0064] Processor 401 may be a central processing unit (CPU). Processor 401 may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof.

[0065] The memory 402, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the energy storage system support capability calculation method in the embodiments of the present invention. The processor 401 executes various functional applications and data processing by running the non-transitory software programs, instructions, and modules stored in the memory 402, thereby implementing the energy storage system support capability assessment model construction method or the energy storage system support capability assessment method in the above method embodiments.

[0066] The memory 402 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor 401, etc. Furthermore, the memory 402 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 402 may optionally include memory remotely located relative to the processor 401, and these remote memories may be connected to the processor 401 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0067] The one or more modules are stored in the memory 402, and when executed by the processor 401, they perform actions such as... Figure 1 or Figure 2 The embodiment shown illustrates the construction of an energy storage system support capability assessment model or the method for assessing the support capability of an energy storage system.

[0068] For specific details regarding the aforementioned electronic devices, please refer to the relevant documentation. Figure 1 or Figure 2 The relevant descriptions and effects in the illustrated embodiments are for understanding purposes only and will not be repeated here.

[0069] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0070] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the defined scope.

Claims

1. A method for constructing an assessment model for the support capacity of an energy storage system, characterized in that, The method includes: Acquire operational data of the energy storage system for a target historical duration under different operating states, and the operational data is used to determine the operating power of the energy storage system; The safe operating boundaries of the energy storage system under different operating conditions are determined based on the aforementioned operating data; The step of determining the safe operating boundary of the energy storage system under different operating states based on the operating data includes: performing data filtering processing on the obtained operating data of the energy storage system under different states for a target historical duration based on preset safe operating conditions; and determining the safe operating boundary of the energy storage system under different operating states based on the operating data after data filtering processing. The method further includes: acquiring the operating temperature of the energy storage system corresponding to different operating data; the step of performing data filtering on the acquired operating data of the energy storage system under different states for a target historical duration based on preset safe operating conditions includes: based on the operating temperature of the energy storage system corresponding to different operating data, performing data filtering on the acquired operating data of the energy storage system under different states for a target historical duration according to preset safe operating temperature requirements, to obtain operating data that meets the safe operating conditions and is used to determine the operating power of the energy storage system; Based on the aforementioned safe operating boundary, determine the available support capabilities corresponding to different operating data under the corresponding operating state; The energy storage system support capability assessment model is trained based on the operating data under different operating conditions and the corresponding available support capabilities until the prediction accuracy of the energy storage system support capability assessment model meets the prediction requirements. The energy storage system support capability assessment model is optimized by a compressed model algorithm during the training process.

2. The method for constructing an energy storage system support capability assessment model according to claim 1, characterized in that, The energy storage system comprises multiple energy storage units; the method further includes: Acquire operational data of the energy storage unit for the target historical duration under different operating conditions; Based on the operational data, determine the safe operating boundaries of the energy storage unit under different operating conditions; The safe operating boundaries of the corresponding energy storage system under different operating conditions are determined based on the safe operating boundaries of multiple energy storage units under different operating conditions.

3. A method for assessing the support capacity of an energy storage system, characterized in that, include: Obtain the current operating status and operating data of the energy storage system; The acquired operating status and operating data of the energy storage system are input into the energy storage system support capability assessment model to determine the support capability of the energy storage system. The energy storage system support capability assessment model is constructed by the energy storage system support capability assessment model construction method according to any one of claims 1-2.

4. An electric energy storage system, characterized in that, The method includes: An energy storage cluster, the energy storage cluster comprising at least one energy storage system; The energy storage operation control center is communicatively connected to both the energy storage cluster and the dispatch center. A support capability prediction platform is connected to the energy storage cluster and the energy storage operation control center, respectively. The support capability prediction platform integrates an energy storage system support capability assessment model, which is used to predict the support capability of the energy storage cluster and send the support capability of the energy storage cluster to the energy storage operation control center. The energy storage operation control center then sends the received support capability of the energy storage cluster to the dispatch center, enabling the dispatch center to perform energy storage dispatch planning. The energy storage system support capability assessment model is constructed by the energy storage system support capability assessment model construction method according to any one of claims 1-2.

5. A device for constructing an assessment model for the support capacity of an energy storage system, characterized in that, The device includes: The data acquisition module is used to acquire the target historical duration of the operation data of the energy storage system under different operating states, and the operation data is used to determine the operating power of the energy storage system. The operation boundary determination module is used to determine the safe operation boundary of the energy storage system under different operating states based on the operation data. The operation boundary determination module includes: a data processing submodule, used to perform data filtering processing on the acquired operation data of the energy storage system under different states for a target historical duration based on preset safe operation conditions; and an operation boundary determination submodule, used to determine the safe operation boundary of the energy storage system under different operating states based on the operation data after data filtering processing. The device further includes: a temperature acquisition module, used to acquire the operating temperature of the energy storage system corresponding to different operating data; the data processing submodule includes: a data filtering submodule, used to filter the acquired operating data of the energy storage system under different states for a target historical duration according to the preset safe operating temperature requirements based on the operating temperature of the energy storage system corresponding to different operating data, so as to obtain operating data that meets the safe operating conditions and is used to determine the operating power of the energy storage system. The support capability determination module is used to determine the available support capability corresponding to different operating data under the corresponding operating state based on the safe operating boundary. The model building module is used to train the energy storage system support capability assessment model based on the operating data under different operating conditions and the corresponding available support capabilities, until the prediction accuracy of the energy storage system support capability assessment model meets the prediction requirements. The energy storage system support capability assessment model is optimized by a compressed model algorithm during the training process.

6. A device for evaluating the support capacity of an energy storage system, characterized in that, include: The data acquisition module is used to acquire the current operating status and operating data of the energy storage system; The support capability determination module is used to input the acquired operating status and operating data of the energy storage system into the energy storage system support capability assessment model to determine the support capability of the energy storage system. The energy storage system support capability assessment model is constructed by the energy storage system support capability assessment model construction method according to any one of claims 1-2.

7. An electronic device, characterized in that, include: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the steps of the energy storage system support capability assessment model construction method as described in any one of claims 1-2, or the steps of the energy storage system support capability assessment method as described in claim 3.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the energy storage system support capability assessment model construction method as described in any one of claims 1-2, or the steps of the energy storage system support capability assessment method as described in claim 3.

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