Power feature generation method and device of energy storage system, computer equipment, readable storage medium and program product

Abstract

The invention relates to a power feature generation method and device of an energy storage system, computer equipment, a readable storage medium and a program product, and is applied to the technical field of data processing, and the method comprises the following steps: obtaining energy storage power information of the energy storage system, and evaluating a configuration response demand type corresponding to the energy storage system according to the energy storage power information; selecting multiple pieces of target energy storage power sub-information from the energy storage power information; according to the configuration response demand type, recursive processing is performed on a unit energy storage characteristic matrix corresponding to the energy storage system to obtain an energy storage characteristic matrix corresponding to the energy storage system, the unit energy storage characteristic matrix comprises a unit characteristic value and a zero value, the unit characteristic value represents a charging and discharging state corresponding to an energy storage device in the energy storage system, and the zero value represents a charging and discharging state corresponding to the energy storage device in the energy storage system; the zero value represents a stagnation state corresponding to an energy storage device in the energy storage system; and generating power characteristics of the energy storage system according to the energy storage characteristic matrix and the multiple pieces of target energy storage power sub-information. By adopting the method, the power characteristic generation accuracy of the energy storage system can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for generating power characteristics of an energy storage system. Background Art

[0002] With the widespread adoption of energy storage systems, the demand for their control is increasing. By generating the power signature of an energy storage system, we can distinguish the sources of power fluctuations in different frequency bands or time periods. For example, short-term fluctuations may be caused by load changes, while long-term fluctuations may be related to the charging and discharging process of the energy storage device or the external grid status. This helps to better understand the operating characteristics of energy storage systems under different circumstances. The power signature of an energy storage system can help analyze the power requirements of the energy storage system at different time scales, thereby formulating more precise energy management strategies.

[0003] Currently, when a preset transformation method (for example, Fourier transform) is usually used to generate the power characteristics of an energy storage system, due to the limitations of its transformation characteristics, the generated power characteristics may be unable to represent the stagnant state of the energy storage system, resulting in low accuracy in the generation of the power characteristics of the energy storage system. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for generating power characteristics of an energy storage system, which can improve the accuracy of power characteristics generation of the energy storage system, in order to address the above technical problems.

[0005] In a first aspect, the present application provides a method for generating a power signature of an energy storage system, comprising:

[0006] Obtaining energy storage power information of the energy storage system, and evaluating the configuration response requirement type corresponding to the energy storage system based on the energy storage power information;

[0007] Selecting a plurality of target energy storage power sub-information from the energy storage power information;

[0008] recursively processing a unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response requirement type to obtain an energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to represent a charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to represent a stagnant state corresponding to the energy storage device in the energy storage system;

[0009] The power characteristics of the energy storage system are generated according to the energy storage characteristic matrix and the plurality of target energy storage power sub-information.

[0010] In a second aspect, the present application further provides a power signature generating device for an energy storage system, comprising:

[0011] An evaluation module is used to obtain energy storage power information of the energy storage system and evaluate the configuration response requirement type corresponding to the energy storage system based on the energy storage power information;

[0012] A selection module, configured to select a plurality of target energy storage power sub-information from the energy storage power information;

[0013] a recursive module, configured to recursively process a unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response requirement type to obtain an energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to characterize the charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to characterize the stagnant state corresponding to the energy storage device in the energy storage system;

[0014] A generating module is used to generate the power characteristics of the energy storage system according to the energy storage characteristic matrix and the multiple target energy storage power sub-information.

[0015] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0016] Obtaining energy storage power information of the energy storage system, and evaluating the configuration response requirement type corresponding to the energy storage system based on the energy storage power information;

[0017] Selecting a plurality of target energy storage power sub-information from the energy storage power information;

[0018] recursively processing a unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response requirement type to obtain an energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to represent a charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to represent a stagnant state corresponding to the energy storage device in the energy storage system;

[0019] The power characteristics of the energy storage system are generated according to the energy storage characteristic matrix and the plurality of target energy storage power sub-information.

[0020] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0021] Obtaining energy storage power information of the energy storage system, and evaluating the configuration response requirement type corresponding to the energy storage system based on the energy storage power information;

[0022] Selecting a plurality of target energy storage power sub-information from the energy storage power information;

[0023] recursively processing a unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response requirement type to obtain an energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to represent a charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to represent a stagnant state corresponding to the energy storage device in the energy storage system;

[0024] The power characteristics of the energy storage system are generated according to the energy storage characteristic matrix and the plurality of target energy storage power sub-information.

[0025] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0026] Obtaining energy storage power information of the energy storage system, and evaluating the configuration response requirement type corresponding to the energy storage system based on the energy storage power information;

[0027] Selecting a plurality of target energy storage power sub-information from the energy storage power information;

[0028] recursively processing a unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response requirement type to obtain an energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to represent a charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to represent a stagnant state corresponding to the energy storage device in the energy storage system;

[0029] The power characteristics of the energy storage system are generated according to the energy storage characteristic matrix and the plurality of target energy storage power sub-information.

[0030] The above-mentioned power characteristic generation method, device, computer equipment, computer-readable storage medium and computer program product of the energy storage system obtain the energy storage power information of the energy storage system and evaluate the configuration response requirement type corresponding to the energy storage system based on the energy storage power information; select multiple target energy storage power sub-information from the energy storage power information; recursively process the unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response requirement type to obtain the energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes unit eigenvalues ​​and zero values, the unit eigenvalues ​​are used to characterize the charge and discharge states corresponding to the energy storage devices in the energy storage system, and the zero values ​​are used to characterize the stagnation states corresponding to the energy storage devices in the energy storage system; based on the energy storage characteristic matrix and the multiple target energy storage power sub-information, the power characteristics of the energy storage system are generated.

[0031] In this way, first, multiple target energy storage power sub-information is selected from the energy storage power information of the energy storage system, and based on the configuration response demand type, the unit energy storage feature matrix is ​​recursively processed to obtain an energy storage feature matrix that is compatible with the configuration response demand corresponding to the energy storage system, and the unit energy storage feature matrix is ​​composed of a unit matrix. The unit matrix itself means that all elements on the main diagonal are unit eigenvalues, and the remaining elements are zero values. Therefore, the energy storage feature matrix can characterize the stagnation state and charge and discharge state corresponding to the energy storage system. Based on the energy storage feature matrix and multiple target energy storage power sub-information, the generated power characteristics of the energy storage system can not only characterize the stagnation state corresponding to the energy storage system, but also characterize the specific power value under the charge and discharge state, thereby improving the accuracy of the power feature generation of the energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0033] Figure 1 A diagram illustrating an application environment of a method for generating power characteristics of an energy storage system according to an embodiment;

[0034] Figure 2 1 is a flow chart of a method for generating power characteristics of an energy storage system in one embodiment;

[0035] Figure 3 A schematic diagram of a power linear graph generated in one embodiment;

[0036] Figure 4A flowchart illustrating the steps of recursively processing the unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response demand type in one embodiment to obtain the energy storage characteristic matrix corresponding to the energy storage system;

[0037] Figure 5 1. A flowchart of steps for generating power characteristics of the energy storage system according to the energy storage characteristic matrix and the plurality of target energy storage power sub-information in one embodiment;

[0038] Figure 6 is a structural block diagram of a power signature generating device for an energy storage system in one embodiment;

[0039] Figure 7 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0041] It should be noted that the information (for example, energy storage power information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the acquisition, transmission, storage, use and processing of relevant data are in compliance with the relevant provisions of national laws and regulations. The content pushed to the user (for example, configuration response demand type, target energy storage power sub-information, energy storage feature matrix and power characteristics, etc.) can be rejected by the user or can be conveniently rejected by the user. In the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0042] It's understandable that the power signature of an energy storage system is intended to better schedule the system's charging, discharging, and stagnation times, optimizing the system's economic benefits and operational efficiency. Generating the system's power signature can proactively identify potential instability factors, such as excessive instantaneous power fluctuations or sustained power fluctuations, enabling the implementation of necessary control measures and enhancing the system's control stability. Generating the system's power signature helps analyze the system's charging and discharging patterns, thereby inferring its future performance and lifespan. Because prolonged and frequent deep charging and discharging can cause damage to the energy storage system, generating the system's power signature allows for earlier assessment of its health, thereby extending its service life. Furthermore, analyzing the system's power signature can identify anomalies during operation. For example, abnormal power fluctuations in a specific frequency band may indicate a component failure or maintenance requirements. The above analysis demonstrates that generating the system's power signature is closely linked to the system's normal operation, lifespan reduction, and control stability. Therefore, a method for accurately generating the system's power signature is urgently needed.

[0043] The power characteristics generation method of the energy storage system provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. The energy storage system 102 and the terminal 104 communicate with the server 106 through the network respectively. The data storage system can store data that the server 106 needs to process. The data storage system can be integrated on the server 106, or placed on the cloud or other network servers. The server 106 receives the energy storage power information of the energy storage system 102 sent by the energy storage system 102, and selects multiple target energy storage power sub-information from the energy storage power information; based on the multiple target energy storage power sub-information, the configuration response requirement type corresponding to the energy storage system 102 is evaluated; according to the configuration response requirement type, the unit energy storage characteristic matrix corresponding to the energy storage system 102 is recursively processed to obtain the energy storage characteristic matrix corresponding to the energy storage system 102, wherein the unit energy storage characteristic matrix includes unit eigenvalues ​​and zero values, the unit eigenvalues ​​are used to characterize the charge and discharge state corresponding to the energy storage device in the energy storage system 102, and the zero value is used to characterize the stagnation state corresponding to the energy storage device in the energy storage system 102; based on the energy storage characteristic matrix and the multiple target energy storage power sub-information, the power characteristics of the energy storage system 102 are generated. Server 106 can push at least one of the following: the configuration response demand type, target energy storage power sub-information, energy storage feature matrix, and power feature to terminal 104. Terminal 104 can include, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart car devices, and projectors. Portable wearable devices can include smart watches, smart bracelets, and head-mounted devices. Head-mounted devices can include virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, and the like. Server 106 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server providing cloud computing services.

[0044] In an exemplary embodiment, Figure 2 As shown, a method for generating power characteristics of an energy storage system is provided, and the method is applied to Figure 1 The server 106 in FIG. 1 is used as an example to illustrate the process, including the following steps 202 to 208. In which:

[0045] Step 202: Obtain energy storage power information of the energy storage system, and evaluate the configuration response requirement type corresponding to the energy storage system based on the energy storage power information.

[0046] The energy storage system in step 202 includes at least one energy storage device. The energy storage power information is used to characterize the operating power status of the energy storage system at multiple times (the time herein can be a time point or a time period, without limitation). The energy storage power information can include multiple energy storage power sub-information, each of which includes a specific operating power value of the energy storage system at a specific time. The operating power value can be one of a first-class characteristic value, a second-class characteristic value, and a zero value. For example, energy storage power sub-information a is (t1, p1). The energy storage power information can also include an energy storage system power curve. The energy storage system power curve characterizes the correspondence between time and the operating power value of the energy storage system. For example, with time as the horizontal axis and the operating power value of the energy storage system as the vertical axis, a curve drawn from multiple coordinate points (coordinate points consisting of multiple times and corresponding operating power values) serves as the power curve of the energy storage system.

[0047] Among them, when the first type of eigenvalue is positive, the second type of eigenvalue is negative; when the first type of eigenvalue is negative, the second type of eigenvalue is positive.

[0048] Exemplarily, obtaining energy storage power information of the energy storage system includes: sending an energy storage power query request to the energy storage system, and obtaining energy storage power information of the energy storage system sent by the energy storage system after receiving the energy storage power query request.

[0049] Exemplarily, based on the energy storage power information, evaluating the configuration response requirement type corresponding to the energy storage system includes: evaluating the configuration response requirement type corresponding to the energy storage system based on at least one of the power configuration times corresponding to multiple energy storage power sub-information and the power change information between the multiple energy storage power sub-information.

[0050] As one embodiment, the configuration response requirement type corresponding to the energy storage system is evaluated based on the energy storage power information, including: obtaining the power configuration time corresponding to multiple energy storage power sub-information; if the power configuration time is not within the preset peak time interval, then evaluating the configuration response requirement type corresponding to the energy storage system based on the power change information of the energy storage power information.

[0051] The preset peak time interval is the time interval of the peak power consumption corresponding to the power grid system corresponding to the energy storage system.

[0052] Furthermore, based on the power change information of the energy storage power information, the configuration response demand type corresponding to the energy storage system is evaluated, including: the power change information between multiple energy storage power sub-information includes the power change amount and power change duration between multiple energy storage power sub-information; based on the power change amount and power change duration between multiple energy storage power sub-information, the configuration response demand type corresponding to the energy storage system is evaluated, wherein, the greater the power change amount between multiple energy storage power sub-information, the faster the response demand speed represented by the evaluated configuration response demand type; the shorter the power change duration between multiple energy storage power sub-information, the faster the response demand speed represented by the evaluated configuration response demand type.

[0053] As an embodiment, the configuration response demand type corresponding to the energy storage system is evaluated based on the power change amount and power change duration between multiple energy storage power sub-information, including: fusing the power change amount between multiple energy storage power sub-information with the ratio between the corresponding power change durations to obtain the fused power change rate corresponding to the multiple energy storage power sub-information; and evaluating the configuration response demand type corresponding to the energy storage system based on the fused power change rate corresponding to the multiple energy storage power sub-information, wherein the larger the fused power change rate corresponding to the multiple energy storage power sub-information, the faster the response demand speed represented by the evaluated configuration response demand type.

[0054] In this way, considering that the faster the power changes between multiple energy storage power sub-information, the greater the power change amount, it means that there is a power mutation condition between multiple energy storage power sub-information. At this time, the configuration response demand type that represents a faster response speed is evaluated for the target energy storage power sub-information to ensure that the power characteristics finally generated based on the configuration response demand type can configure fast-response power.

[0055] As an embodiment, the configuration response demand type corresponding to the energy storage system is evaluated based on the fused power change rate corresponding to multiple energy storage power sub-information, including: if the fused power change rate corresponding to the multiple energy storage power sub-information is greater than a preset change rate threshold, then the first response demand type is determined as the configuration response demand type corresponding to the energy storage system; if the fused power change rate corresponding to the multiple energy storage power sub-information is not greater than the preset change rate threshold, then the second response demand type is determined as the configuration response demand type corresponding to the energy storage system, wherein the response demand speed represented by the first response demand type is faster than the response demand speed represented by the second response demand type.

[0056] Optionally, the above method also includes: if the power configuration times corresponding to multiple energy storage power sub-information are not within the preset peak time interval, then determining that the power configuration time is not within the preset peak time interval; if there is at least one target energy storage sub-power corresponding to a power configuration time within the preset peak time interval, then determining that the power configuration time is within the preset peak time interval.

[0057] As another embodiment, the configuration response requirement type corresponding to the energy storage system is evaluated based on the energy storage power information, including: if the power configuration time is within a preset peak time interval, the third response requirement type is determined as the configuration response requirement type corresponding to the energy storage system.

[0058] Among them, the response demand speed represented by the third response demand type is faster than the response demand speed represented by the second response demand type.

[0059] In this way, considering that the power configuration time is within the preset peak time interval, it means that multiple target energy storage power sub-information is used for the peak power consumption configuration of the power grid system. Therefore, it is necessary to set a configuration response demand type that represents a higher response demand speed for multiple target energy storage power sub-information, so that the energy storage system can cooperate with the power grid system in a timely manner and ensure the power supply demand during the peak power consumption period.

[0060] Step 204 : Select multiple target energy storage power sub-information from the energy storage power information.

[0061] Exemplarily, step 204 includes: obtaining an information selection quantity, and selecting a plurality of target energy storage power sub-information from the energy storage power information according to the information selection quantity.

[0062] Further, as an embodiment, obtaining the number of information selections includes: obtaining the number of information selections set by the user.

[0063] As another embodiment, obtaining the number of selected information includes: obtaining operating characteristics of the energy storage system, and determining the number of selected information according to the operating characteristics.

[0064] In this way, it can be ensured that the time distribution corresponding to the power characteristics of the generated energy storage system meets user expectations.

[0065] As one embodiment, determining the number of information to be selected based on operating characteristics includes: extracting periodic change features in the operating characteristics, and determining the number of information to be selected based on the periodic change features, wherein the more frequent the periodic changes represented by the periodic change features, the greater the number of information to be selected.

[0066] In this way, considering that the energy storage power information of the energy storage system is essentially the charging and discharging conditions of the energy storage system, the energy storage power change of the energy storage system is a time-series change. Therefore, by analyzing the periodic change characteristics in the operating characteristics of the energy storage system, it is possible to ensure that the power characteristics of the constructed energy storage system can represent the frequency change conditions of the periodic energy storage system.

[0067] As another embodiment, determining the number of selected information based on the operating characteristics includes: extracting power distribution features from the operating characteristics, and determining the number of selected information based on the power distribution features.

[0068] In this way, the amount of information to be selected is determined based on the power distribution characteristics, thereby ensuring that the power characteristics of the constructed energy storage system can characterize the frequency change status of the complete energy storage system as much as possible.

[0069] As another embodiment, obtaining the number of information selections includes: determining the number of information selections based on a selected preset feature generation method. Specifically, the preset feature generation method includes but is not limited to a Hadamard-Walsh transform method, a wavelet transform method, and a bridge function transform method, which are not limited here.

[0070] In this way, it can be ensured that the multiple target energy storage power sub-information obtained by selecting the information selection quantity is compatible with the preset feature generation method, thereby avoiding the need to fill zero values ​​or remove part of the target energy storage power sub-information to ensure the normal subsequent power feature generation process.

[0071] Furthermore, according to the selected preset feature generation method, the number of information selections is determined, including: obtaining the matrix order (obtained by the configuration response requirement type detection), and multiplying the matrix order and the number corresponding to the preset feature generation method to determine the number of information selections. For example, if the matrix order is b, then the number of information selections c=b*2 a .

[0072] In step 206, the unit energy storage characteristic matrix corresponding to the energy storage system is recursively processed according to the configuration response requirement type to obtain the energy storage characteristic matrix corresponding to the energy storage system. The unit energy storage characteristic matrix includes a unit eigenvalue and a zero value. The unit eigenvalue is used to represent the charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to represent the stagnant state corresponding to the energy storage device in the energy storage system.

[0073] As an embodiment, step 206 includes: obtaining a unit energy storage characteristic matrix according to the configuration response requirement type; and recursively processing the unit energy storage characteristic matrix according to the configuration response requirement type to obtain an energy storage characteristic matrix corresponding to the energy storage system.

[0074] Step 208 : Generate a power characteristic of the energy storage system based on the energy storage characteristic matrix and the multiple target energy storage power sub-information.

[0075] The power feature in step 208 is used to characterize the operating power status of each energy storage device at each time. The power feature may include the operating power value of each energy storage device (corresponding to each type of energy storage device or each energy storage device mentioned above) at each time. The operating power value may be one of a first-type characteristic value, a second-type characteristic value, and a zero value. The power feature may also include multiple target power linear graphs, each of which corresponds to an energy storage device. Each power linear graph represents the correspondence between time and the operating power value of the corresponding energy storage device. For example, with time as the horizontal axis and the characteristic value of the corresponding energy storage device as the vertical axis, a line drawn by multiple coordinate points (coordinate points consisting of multiple times and corresponding operating power values) is used as a power linear graph. The power linear graph may be a broken line graph or a curve graph, which is not limited here.

[0076] Exemplarily, step 208 includes: fusing the energy storage characteristic matrix and a plurality of target energy storage power sub-information to obtain an energy storage power characteristic matrix, and generating a power characteristic of the energy storage system according to the energy storage power characteristic matrix.

[0077] Furthermore, as an embodiment, generating the power characteristics of the energy storage system according to the energy storage power characteristic matrix includes: determining each eigenvalue (including the above-mentioned power eigenvalue and zero value) in the energy storage power characteristic matrix as the operating power value of each energy storage device at each time.

[0078] As another embodiment, generating the power characteristics of the energy storage system according to the energy storage power characteristic matrix includes: generating each power linear graph according to each eigenvalue in the energy storage power characteristic matrix, wherein each point in each power linear graph corresponds to each eigenvalue of each row in the energy storage power characteristic matrix.

[0079] Optionally, the distribution of the energy storage power characteristic matrix is ​​as follows: , and the time interval corresponding to multiple energy storage power sub-information is 1 / 9, and the range is 0-1, for example, then the generated power linear graph can refer to Figure 3 .

[0080] Optionally, after step 208, the method further includes: controlling the energy storage system according to the power characteristics of the energy storage system.

[0081] Furthermore, the energy storage system is controlled according to the power characteristics of the energy storage system. Specifically, each energy storage device in the energy storage system is controlled according to the charge and discharge power distribution of each energy storage device represented by the power characteristics of the energy storage system.

[0082] In the above-mentioned method for generating power characteristics of the energy storage system, multiple target energy storage power sub-information is first selected from the energy storage power information of the energy storage system, and based on the configuration response requirement type, the unit energy storage characteristic matrix is ​​recursively processed to obtain an energy storage characteristic matrix that is compatible with the configuration response requirement corresponding to the energy storage system, and the unit energy storage characteristic matrix is ​​composed of a unit matrix. The unit matrix itself means that all elements on the main diagonal are unit eigenvalues, and the remaining elements are zero values. Therefore, the energy storage characteristic matrix can characterize the stagnation state and charge and discharge state corresponding to the energy storage system. Based on the energy storage characteristic matrix and multiple target energy storage power sub-information, the power characteristics of the generated energy storage system can not only characterize the stagnation state corresponding to the energy storage system, but also characterize the specific power value under the charge and discharge state, thereby improving the accuracy of the power characteristic generation of the energy storage system.

[0083] In an exemplary embodiment, Figure 4 As shown, a method for accurately constructing an energy storage characteristic matrix is ​​provided. According to the configuration response demand type, the unit energy storage characteristic matrix corresponding to the energy storage system is recursively processed to obtain the energy storage characteristic matrix corresponding to the energy storage system, including steps 302 to 306.

[0084] Step 302 : Detecting the unit matrix configuration information corresponding to the energy storage system according to the configuration response requirement type, wherein the unit matrix configuration information represents the matrix order and recursion times of the unit energy storage characteristic matrix.

[0085] As an embodiment, step 302 includes: detecting a matrix order corresponding to the energy storage system according to a response demand speed represented by the configured response demand type; and detecting a number of recursion times corresponding to the energy storage system according to the matrix order and the number of information selections of the target energy storage power sub-information.

[0086] The faster the response speed represented by the configured response demand type, the lower the matrix order. The lower the matrix order, the higher the number of recursive detections. The more target energy storage power sub-information selected, the higher the number of recursive detections.

[0087] Furthermore, the number of recursions corresponding to the energy storage system is detected based on the matrix order and the number of selected information of the target energy storage power sub-information, including: the logarithm obtained by processing the ratio between the number of selected information of the target energy storage power sub-information and the matrix order power of the matrix order 2 with base 2 as the recursion number.

[0088] Optionally, the logarithm of the ratio between the number of selected sub-information items of target energy storage power and the power of the matrix order of 2, with base 2, is determined as the number of recursions and can be expressed in the following formula:

[0089]

[0090] in, is the number of recursions, is the number of information selected, and b is the matrix order.

[0091] Step 304: Obtain a unit energy storage characteristic matrix corresponding to the energy storage system according to the matrix order.

[0092] The number of rows and columns of the unit energy storage characteristic matrix is ​​the same as the matrix order. The main diagonal of the unit energy storage characteristic matrix is ​​1, and the rest of the positions are 0.

[0093] For example, when the matrix order is 3, the unit energy storage characteristic matrix is ​​as follows: .

[0094] Step 306 : recursively process the unit energy storage characteristic matrix according to the number of recursions to obtain the energy storage characteristic matrix corresponding to the energy storage system.

[0095] Exemplarily, step 306 includes: recursively performing a recursive algorithm on the unit energy storage characteristic matrix according to the number of recursions to obtain an energy storage characteristic matrix corresponding to the energy storage system.

[0096] For example, when the number of recursions is 1, the energy storage characteristic matrix is , when the number of recursions is n, the energy storage characteristic matrix is .

[0097] In this embodiment, the matrix order and number of recursions corresponding to the energy storage system are detected based on the configuration response requirement type. The matrix order represents the complexity of the unit matrix, and the number of recursions represents the degree of matrix replication. Therefore, the energy storage characteristic matrix obtained by recursive processing based on the matrix order and the number of recursions has a corresponding matrix complexity that matches the configuration response requirement type corresponding to the energy storage system, thereby improving the accuracy of the processed energy storage characteristic matrix.

[0098] In an exemplary embodiment, Figure 5 As shown, a method for accurately generating power characteristics is provided, which generates the power characteristics of the energy storage system according to the energy storage characteristic matrix and multiple target energy storage power sub-information, including steps 402 to 406.

[0099] Step 402 : For each unit eigenvalue in the energy storage characteristic matrix, the target energy storage power sub-information that matches the unit eigenvalue in time sequence is fused with the unit eigenvalue to obtain a power eigenvalue.

[0100] The number of rows and columns of the energy storage characteristic matrix is ​​equal to the number of selected information of the target energy storage power sub-information.

[0101] Exemplarily, step 402 includes: for each unit eigenvalue in the energy storage characteristic matrix, determining the power eigenvalue corresponding to the unit eigenvalue by the ratio of the product of the unit eigenvalue and the target energy storage power sub-information corresponding to the time series matching of the column where the unit eigenvalue is located to half of the power of the recursive number of 2.

[0102] Optionally, the power eigenvalue corresponding to the unit eigenvalue is determined as the ratio of the product of the unit eigenvalue and the target energy storage power sub-information corresponding to the time series matching of the column where the unit eigenvalue is located, and half of the power of the recursive number of 2. The power eigenvalue can be expressed as:

[0103]

[0104] in, For the Rank The power eigenvalue corresponding to the unit eigenvalue of the column, For the Rank The unit eigenvalue of the column, For the The target energy storage power sub-information corresponding to the column, It is half of 2 raised to the power of the number of recursions.

[0105] Step 404 : updating the energy storage characteristic matrix according to the power eigenvalue corresponding to each unit eigenvalue in the energy storage characteristic matrix to obtain an energy storage power characteristic matrix.

[0106] Exemplarily, step 404 includes: replacing each unit eigenvalue in the energy storage characteristic matrix with a corresponding power eigenvalue to obtain an energy storage power characteristic matrix.

[0107] Step 406: extract the power characteristics of the energy storage system from the energy storage power characteristic matrix.

[0108] Optionally, the specific implementation of step 406 may refer to the specific implementation content of the above step 208, which will not be repeated here.

[0109] It is understandable that since the unit eigenvalue of each row in the energy storage characteristic matrix corresponds to an energy storage device in the energy storage system, there may be a situation where the number of rows and columns of the generated energy storage characteristic matrix does not match the number of energy storage devices in the energy storage system. Therefore, in order to facilitate subsequent energy storage device control, the energy storage characteristic matrix needs to be updated accordingly.

[0110] Optionally, before step 402, the method further includes: extracting an energy storage unit feature of each unit eigenvalue in the energy storage feature matrix, wherein the energy storage unit feature is used to characterize at least one of a stagnation state distribution condition and an energy storage state switching condition of each unit eigenvalue; selecting at least one unit eigenvalue set from the energy storage power feature matrix based on the energy storage unit feature of each unit eigenvalue in the energy storage feature matrix, wherein each unit eigenvalue set includes multiple unit eigenvalues; and merging the multiple unit eigenvalues ​​in each energy storage feature set in the energy storage power feature matrix.

[0111] Furthermore, as an embodiment, the energy storage unit feature of each unit eigenvalue in the energy storage feature matrix is ​​extracted, including: the energy storage unit feature includes stagnation state information; for each row of unit eigenvalues, the number of zero values ​​and the number of vectors in the unit eigenvalues ​​in the row are accumulated, and the ratio between the number of zero values ​​and the number of vectors is determined as the stagnation state information; or, the number of zero values ​​is determined as the stagnation state information.

[0112] As another embodiment, extracting the energy storage unit feature of each unit eigenvalue in the energy storage feature matrix includes: the energy storage unit feature includes the energy storage charge and discharge state switching frequency; for each row of unit eigenvalues, accumulating the number of charge and discharge switching in the unit eigenvalues ​​in the row; and extracting the energy storage charge and discharge state switching frequency of the unit eigenvalues ​​in the row based on the number of charge and discharge switching in the unit eigenvalues ​​in the row, wherein a greater number of charge and discharge switching in the unit eigenvalues ​​in the row increases the energy storage charge and discharge state switching frequency of the unit eigenvalues ​​in the row.

[0113] As another embodiment, extracting energy storage unit features of each unit eigenvalue in the energy storage feature matrix includes: the energy storage unit feature includes energy storage state switching similarities with energy storage unit features in other rows; for each row of energy storage unit features, determining overlapping features between the energy storage unit features in that row and the energy storage unit features in other rows; and determining energy storage state switching similarities between the energy storage unit features in that row and the energy storage unit features in other rows based on the number of overlapping features between the energy storage unit features in that row and the energy storage unit features in other rows, wherein a greater number of overlapping features between the energy storage unit features in that row and the energy storage unit features in other rows indicates a higher energy storage state switching similarity between the energy storage unit features in that row and the energy storage unit features in other rows.

[0114] Among them, the stagnation state information and the energy storage charge and discharge state switching frequency between the energy storage unit features in each row in the unit feature value set are the same, and the energy storage state switching similarity between the energy storage unit features in each row in the unit feature value set is greater than a preset similarity threshold. The preset similarity threshold can be set by the user as needed or can be an empirical value.

[0115] For example, the set of unit eigenvalues ​​in the energy storage feature matrix includes: the first row of energy storage unit features is (1, 0, 0, 1, 0, 0) and the second row of energy storage unit features is (0, 1, 0, 0, 1, 0). The feature obtained by merging the first row of energy storage unit features and the second row of energy storage unit features is (1, 1, 0, 1, 1, 0).

[0116] In this embodiment, the unit eigenvalues ​​in the energy storage characteristic matrix are temporally fused with the target energy storage power sub-information to obtain power eigenvalues, thereby updating the energy storage characteristic matrix. This allows the updated energy storage power characteristic matrix to characterize not only the operating state of the energy storage system (including the charging and discharging state and the stagnant state), but also the power status under each operating state. Therefore, the power features extracted based on the energy storage power characteristic matrix can characterize not only the operating state of the energy storage system, but also the power status under each operating state, thereby improving the accuracy of power feature generation.

[0117] As a detailed embodiment, energy storage power information of the energy storage system is obtained, and based on the energy storage power information, the configuration response demand type corresponding to the energy storage system is evaluated; the power configuration time corresponding to the energy storage power information is obtained; if the power configuration time is not within the preset peak time interval, the configuration response demand type corresponding to the energy storage system is evaluated based on the power change information of the energy storage power information; the matrix order corresponding to the energy storage system is detected based on the response demand speed represented by the configuration response demand type; the number of recursions corresponding to the energy storage system is detected based on the matrix order and the number of information selected from the target energy storage power sub-information; the unit energy storage characteristic matrix corresponding to the energy storage system is obtained based on the matrix order; the unit energy storage characteristic matrix is ​​recursively processed based on the number of recursions to obtain the energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to represent the charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to represent the stagnation state corresponding to the energy storage device in the energy storage system.

[0118] Furthermore, the energy storage unit feature of each unit eigenvalue in the energy storage feature matrix is ​​extracted, wherein the energy storage unit feature is used to characterize at least one of the stagnation state distribution status and the energy storage state switching status of each unit eigenvalue; according to the energy storage unit feature of each unit eigenvalue in the energy storage feature matrix, at least one unit eigenvalue set is selected from the energy storage power feature matrix, wherein each unit eigenvalue set includes multiple unit eigenvalues; the multiple unit eigenvalues ​​in each energy storage feature set in the energy storage power feature matrix are merged; for each unit eigenvalue in the energy storage feature matrix, the target energy storage power sub-information that matches the unit eigenvalue in time series is fused with the unit eigenvalue to obtain a power eigenvalue; according to the power eigenvalue corresponding to each unit eigenvalue in the energy storage feature matrix, the energy storage feature matrix is ​​updated to obtain an energy storage power feature matrix; and the power characteristics of the energy storage system are extracted from the energy storage power feature matrix.

[0119] In this way, first, multiple target energy storage power sub-information is selected from the energy storage power information of the energy storage system, and based on the configuration response demand type, the unit energy storage feature matrix is ​​recursively processed to obtain an energy storage feature matrix that is compatible with the configuration response demand corresponding to the energy storage system, and the unit energy storage feature matrix is ​​composed of a unit matrix. The unit matrix itself means that all elements on the main diagonal are unit eigenvalues, and the remaining elements are zero values. Therefore, the energy storage feature matrix can characterize the stagnation state and charge and discharge state corresponding to the energy storage system. Based on the energy storage feature matrix and multiple target energy storage power sub-information, the generated power characteristics of the energy storage system can not only characterize the stagnation state corresponding to the energy storage system, but also characterize the specific power value under the charge and discharge state, thereby improving the accuracy of the power feature generation of the energy storage system.

[0120] Furthermore, based on the configuration response demand type, the matrix order and number of recursions corresponding to the energy storage system are detected. The matrix order represents the complexity of the unit matrix, and the number of recursions represents the degree of matrix replication. Therefore, the energy storage characteristic matrix obtained by recursive processing based on the matrix order and the number of recursions has a corresponding matrix complexity and a matrix complexity that matches the configuration response demand type corresponding to the energy storage system, thereby improving the accuracy of the processed energy storage characteristic matrix. In addition, the unit eigenvalues ​​in the energy storage characteristic matrix are fused with the target energy storage power sub-information in a time series to obtain power eigenvalues, thereby realizing the update of the energy storage characteristic matrix, so that the updated energy storage power characteristic matrix can not only characterize the operating state of the energy storage system (including the charging and discharging state and the stagnant state), but also characterize the power status under each operating state. Therefore, the power characteristics extracted based on the energy storage power characteristic matrix can not only characterize the operating state of the energy storage system, but also characterize the power status under each operating state, thereby improving the accuracy of power feature generation.

[0121] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0122] Based on the same inventive concept, embodiments of the present application also provide a power signature generation device for an energy storage system for implementing the aforementioned method for generating a power signature for an energy storage system. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations in the embodiments of the power signature generation device for one or more energy storage systems provided below can be found in the limitations of the method for generating a power signature for an energy storage system described above and will not be further elaborated here.

[0123] In an exemplary embodiment, Figure 6 As shown, a power signature generation device 600 for an energy storage system is provided, comprising: a selection module 602, an evaluation module 604, a recursive module 606 and a generation module 608, wherein:

[0124] Evaluation module 602, configured to obtain energy storage power information of the energy storage system and evaluate the configuration response requirement type corresponding to the energy storage system based on the energy storage power information;

[0125] A selection module 604 is configured to select a plurality of target energy storage power sub-information from the energy storage power information;

[0126] a recursive module 606 for recursively processing the unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response demand type to obtain the energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to represent the charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to represent the stagnant state corresponding to the energy storage device in the energy storage system;

[0127] The generating module 608 is configured to generate a power characteristic of the energy storage system according to the energy storage characteristic matrix and a plurality of target energy storage power sub-information.

[0128] In one embodiment, the recursive module 606 is further configured to detect the unit matrix configuration information corresponding to the energy storage system according to the configuration response requirement type, wherein the unit matrix configuration information represents the matrix order and the number of recursions of the unit energy storage characteristic matrix; obtain the unit energy storage characteristic matrix corresponding to the energy storage system according to the matrix order; and recursively process the unit energy storage characteristic matrix according to the number of recursions to obtain the energy storage characteristic matrix corresponding to the energy storage system.

[0129] In one embodiment, the recursive module 606 is further configured to detect the matrix order corresponding to the energy storage system according to the response demand speed represented by the configured response demand type; and to detect the number of recursive operations corresponding to the energy storage system according to the number of information selected based on the matrix order and the target energy storage power sub-information.

[0130] In one embodiment, the generation module 608 is further configured to, for each unit eigenvalue in the energy storage characteristic matrix, fuse the target energy storage power sub-information that matches the unit eigenvalue in time sequence with the unit eigenvalue to obtain a power eigenvalue; update the energy storage characteristic matrix according to the power eigenvalue corresponding to each unit eigenvalue in the energy storage characteristic matrix to obtain an energy storage power characteristic matrix; and extract the power characteristics of the energy storage system from the energy storage power characteristic matrix.

[0131] In one embodiment, before the target energy storage power sub-information that matches the unit eigenvalue in time sequence is fused with the unit eigenvalue to obtain the power eigenvalue, the above-mentioned device also includes: a merging module, which is used to extract the energy storage unit feature of each unit eigenvalue in the energy storage feature matrix, wherein the energy storage unit feature is used to characterize at least one of the stagnation state distribution status and the energy storage state switching status of each unit eigenvalue; based on the energy storage unit feature of each unit eigenvalue in the energy storage feature matrix, at least one unit eigenvalue set is selected from the energy storage power feature matrix, wherein each unit eigenvalue set includes multiple unit eigenvalues; and multiple unit eigenvalues ​​in each energy storage feature set in the energy storage power feature matrix are merged.

[0132] In one embodiment, the evaluation module 602 is further configured to obtain power configuration times corresponding to a plurality of energy storage power sub-information; if the power configuration time is not within a preset peak time interval, a plurality of target energy storage power sub-information is selected from the energy storage power information.

[0133] Each module in the power signature generation device for the energy storage system described above can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0134] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication, and the wireless communication can be achieved via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for generating power characteristics of an energy storage system. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0135] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0136] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0137] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0138] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0139] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0140] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0141] The above embodiments merely illustrate several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for generating power characteristics of an energy storage system, characterized in that: The method comprises: Obtaining energy storage power information of the energy storage system, and evaluating the configuration response requirement type corresponding to the energy storage system based on the energy storage power information; Selecting a plurality of target energy storage power sub-information from the energy storage power information; recursively processing a unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response requirement type to obtain an energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to represent a charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to represent a stagnant state corresponding to the energy storage device in the energy storage system; The power characteristics of the energy storage system are generated according to the energy storage characteristic matrix and the plurality of target energy storage power sub-information.

2. The method according to claim 1, characterized in that The recursive processing of the unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response demand type to obtain the energy storage characteristic matrix corresponding to the energy storage system includes: Detecting, according to the configuration response requirement type, unit matrix configuration information corresponding to the energy storage system, wherein the unit matrix configuration information represents the matrix order and the number of recursions of the unit energy storage characteristic matrix; Obtaining a unit energy storage characteristic matrix corresponding to the energy storage system according to the matrix order; According to the number of recursions, the unit energy storage characteristic matrix is ​​recursively processed to obtain an energy storage characteristic matrix corresponding to the energy storage system.

3. The method according to claim 2, characterized in that The detecting, according to the configuration response requirement type, the unit matrix configuration information corresponding to the energy storage system includes: detecting a matrix order corresponding to the energy storage system according to a response demand speed represented by the configuration response demand type; The number of recursive operations corresponding to the energy storage system is detected according to the matrix order and the number of selected sub-information of the target energy storage power.

4. The method according to claim 1, wherein Generating the power characteristics of the energy storage system according to the energy storage characteristic matrix and the plurality of target energy storage power sub-information includes: For each unit eigenvalue in the energy storage characteristic matrix, the target energy storage power sub-information that matches the unit eigenvalue in time sequence is fused with the unit eigenvalue to obtain a power eigenvalue; According to the power eigenvalue corresponding to each unit eigenvalue in the energy storage characteristic matrix, the energy storage characteristic matrix is ​​updated to obtain an energy storage power characteristic matrix; The power characteristics of the energy storage system are extracted from the energy storage power characteristic matrix.

5. The method according to claim 4, characterized in that Before fusing the target energy storage power sub-information that matches the unit characteristic value in time sequence with the unit characteristic value to obtain the power characteristic value, the method further includes: Extracting an energy storage unit feature of each unit eigenvalue in the energy storage feature matrix, wherein the energy storage unit feature is used to characterize at least one of a stagnation state distribution condition and an energy storage state switching condition of each unit eigenvalue; Selecting at least one unit eigenvalue set from the energy storage power characteristic matrix according to the energy storage unit characteristic of each unit eigenvalue in the energy storage characteristic matrix, wherein each unit eigenvalue set includes a plurality of unit eigenvalues; Multiple unit eigenvalues ​​in each energy storage feature set in the energy storage power feature matrix are merged.

6. The method according to any one of claims 1 to 5, characterized in that The step of evaluating the configuration response requirement type corresponding to the energy storage system according to the energy storage power information includes: Obtaining the power configuration time corresponding to the energy storage power information; If the power configuration time is not within the preset peak time interval, the configuration response requirement type corresponding to the energy storage system is evaluated according to the power change information of the energy storage power information.

7. A power characteristic generating device for an energy storage system, characterized in that: The device comprises: An evaluation module is used to obtain energy storage power information of the energy storage system and evaluate the configuration response requirement type corresponding to the energy storage system based on the energy storage power information; A selection module, configured to select a plurality of target energy storage power sub-information from the energy storage power information; a recursive module, configured to recursively process a unit energy storage characteristic matrix corresponding to the energy storage system according to the configuration response requirement type to obtain an energy storage characteristic matrix corresponding to the energy storage system, wherein the unit energy storage characteristic matrix includes a unit eigenvalue and a zero value, the unit eigenvalue is used to characterize the charge and discharge state corresponding to the energy storage device in the energy storage system, and the zero value is used to characterize the stagnant state corresponding to the energy storage device in the energy storage system; A generating module is used to generate the power characteristics of the energy storage system according to the energy storage characteristic matrix and the multiple target energy storage power sub-information.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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