Energy storage device state monitoring method, device, apparatus, medium and program product

Abstract

The present application relates to the field of electronic technology, discloses energy storage device state monitoring method, device, equipment, medium and program product, the method provided by the present application, through the multiple power grid parameters that influence the operation state of energy storage device in the energy storage process of energy storage device and the category of each power grid parameter, the energy storage device parameters corresponding to different power grid parameters are calculated, the energy storage device parameters corresponding to different power grid parameters are fused, the target energy storage device parameter is obtained, the operation state of energy storage device is determined based on the target energy storage parameter and the actual collected energy storage device parameter, instead of determining the operation state of energy storage device based on fixed threshold, improve the accuracy of energy storage device operation state determination result, in addition, potential failure of energy storage device can be found in advance, more processing time is provided for staff, and the problem size and solution can be quickly judged according to the degree of change of energy storage device, especially battery parameter.

Description

Technical Field

[0001] This invention relates to the field of electronic technology, and more specifically to methods, devices, equipment, media, and program products for monitoring the status of energy storage devices. Background Technology

[0002] Energy storage systems are playing an increasingly important role in the current energy industry, providing more efficient, reliable, and sustainable solutions for energy systems. The photovoltaic-storage-charging integrated solution combines photovoltaic power generation, energy storage, and charging technologies to provide a renewable energy-driven solution for charging electric vehicles. By integrating photovoltaic cells and energy storage systems into charging stations, solar energy can be stored during the day and used for charging electric vehicles at night. This comprehensive solution promotes the use of clean energy and reduces dependence on the traditional power grid.

[0003] With the rapid development of energy storage devices, their safety has become a key concern. In related technologies, the battery management system (BMS) of energy storage systems typically provides alarms at the cabinet level for high / low temperature and temperature difference of battery cells, high / low voltage and differential voltage of individual cells, high / low system voltage, excessive charging / discharging current, low SOC, abnormal equalization, and internal, cumulative, and differential voltage alarms. These alarm methods are primarily based on fixed thresholds for key measurements. However, energy storage devices are susceptible to numerous influencing factors, and even for the same battery, its operating condition varies under different influencing factors. If alarms are based solely on fixed thresholds without considering the factors affecting battery operation, the accuracy of fault diagnosis for energy storage devices will be low. Summary of the Invention

[0004] In view of this, the present invention provides a method, apparatus, device, medium and program product for monitoring the status of energy storage equipment, in order to solve the problem of low fault diagnosis accuracy in related technologies that use fixed thresholds to monitor the operating status of energy storage equipment.

[0005] In a first aspect, the present invention provides a method for monitoring the status of an energy storage device. The method includes: acquiring multiple grid parameters of the photovoltaic power grid system in which the energy storage device is located during energy storage and the actual collected parameters of the energy storage device; determining the category of the corresponding grid parameter based on the variation pattern of each grid parameter; calculating the corresponding energy storage device parameters based on each grid parameter and the corresponding grid parameter category; fusing the energy storage device parameters corresponding to each grid parameter to obtain the fused target energy storage device parameters; and determining the operating status of the energy storage device based on the target energy storage device parameters and the actual collected parameters of the energy storage device.

[0006] The energy storage device status monitoring method provided by this invention classifies multiple grid parameters of the photovoltaic power grid system in which the energy storage device operates during energy storage. Based on each grid parameter and its classification results, the corresponding energy storage device parameters are calculated. These grid parameters are then fused to obtain the fused target energy storage device parameters. The operating status of the energy storage device is determined based on these target parameters and the actually collected energy storage device parameters. This method calculates the energy storage device parameters corresponding to different grid parameters by considering the multiple grid parameters affecting the operating status of the energy storage device during energy storage and their categories. The parameters corresponding to these different grid parameters are then fused to obtain the target energy storage device parameters. The operating status of the energy storage device is determined based on these target parameters and the actually collected parameters, rather than on fixed thresholds. This improves the accuracy of the energy storage device operating status assessment. Furthermore, it can detect potential faults in the energy storage device in advance, providing more time for staff to handle them. It can also quickly determine the magnitude of the problem and the appropriate solution based on the degree of change in energy storage device parameters, especially battery parameters.

[0007] In one optional implementation, the grid parameters are categorized into a first category of regularly changing grid parameters, a second category of irregularly changing grid parameters, and a third category of unchanging grid parameters. The step of calculating the corresponding energy storage device parameters based on each grid parameter and its corresponding category includes: calculating the corresponding first energy storage device parameters based on the changing patterns of each first category of grid parameters; calculating the corresponding second energy storage device parameters based on each second category of grid parameters and the probability matrix of different values ​​in the corresponding grid parameters; and calculating the corresponding third energy storage device parameters based on each third category of grid parameters and a pre-constructed first relationship model, wherein the first relationship model is used to characterize the correlation between unchanging grid parameters and energy storage device parameters.

[0008] In one optional implementation, the step of determining the operating status of the energy storage device based on the target energy storage device parameters and the actual collected energy storage device parameters includes: determining the difference between the target energy storage device parameters and the actual collected energy storage device parameters; if the difference between the target energy storage device parameters and the actual collected energy storage device parameters is greater than a preset threshold, determining that the energy storage device is operating abnormally.

[0009] In an optional implementation, the method further includes: if the energy storage device is malfunctioning, adjusting the device parameters of the energy storage device using the target energy storage device parameters to obtain the adjustment result.

[0010] In one optional implementation, the parameters of the corresponding first energy storage device are calculated based on the variation patterns of each first category of grid parameters, including: determining the variation sequence of each first category of grid parameters, the variation sequence being used to characterize the variation patterns of the corresponding grid parameters; and obtaining the parameters of the corresponding first energy storage device based on the variation sequences of each first category of grid parameters.

[0011] Secondly, the present invention provides an energy storage device status monitoring device, which includes: an acquisition module for acquiring multiple grid parameters of the photovoltaic grid system in which the energy storage device is located during energy storage and the actual collected energy storage device parameters; a first determination module for determining the category of the corresponding grid parameter based on the variation law of each grid parameter; a calculation module for calculating the corresponding energy storage device parameters based on each grid parameter and the corresponding grid parameter category; a second determination module for fusing the energy storage device parameters corresponding to each grid parameter to obtain the fused target energy storage device parameters; and a third determination module for determining the operating status of the energy storage device based on the target energy storage device parameters and the actual collected energy storage device parameters.

[0012] In one optional implementation, the grid parameters are categorized into a first category of regularly changing grid parameters, a second category of irregularly changing grid parameters, and a third category of unchanging grid parameters. The calculation module includes: a first calculation submodule for calculating the corresponding first energy storage device parameters based on the changing patterns of each first category of grid parameters; a second calculation submodule for calculating the corresponding second energy storage device parameters based on each second category of grid parameters and the probability matrix of different values ​​in the corresponding grid parameters; and a third calculation submodule for calculating the corresponding third energy storage device parameters based on each third category of grid parameters and a pre-built first relationship model, wherein the first relationship model is used to characterize the correlation between unchanging grid parameters and energy storage device parameters.

[0013] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the energy storage device status monitoring method of the first aspect or any corresponding embodiment described above.

[0014] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the energy storage device status monitoring method of the first aspect or any corresponding embodiment described above.

[0015] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the energy storage device status monitoring method described in the first aspect or any corresponding embodiment. Attached Figure Description

[0016] 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.

[0017] Figure 1 This is a flowchart illustrating the energy storage device status monitoring method according to an embodiment of the present invention;

[0018] Figure 2 This is a flowchart illustrating another energy storage device status monitoring method according to an embodiment of the present invention;

[0019] Figure 3 This is a structural block diagram of an energy storage device status monitoring device according to an embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. 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.

[0022] In related technologies, the battery management system (BMS) of energy storage systems typically performs alarms at the cabinet level for cell temperature (high / low temperature and temperature difference), cell voltage (high / low voltage and voltage difference), system high / low voltage, excessive charging / discharging current, low SOC, abnormal equalization, and internal, cumulative, and voltage difference alarms. These alarm methods are mainly based on fixed thresholds for key measurements. However, energy storage devices are susceptible to numerous influencing factors, and for the same battery, its operating condition varies under different influencing factors. If alarms are based on fixed thresholds without considering the factors affecting battery operation, the accuracy of fault diagnosis for energy storage devices will be low.

[0023] In view of this, the energy storage device status monitoring method provided in this application embodiment can be applied to a server to realize the detection of the energy storage device status. The method provided by the present invention calculates the energy storage device parameters corresponding to different grid parameters by using multiple grid parameters that affect the operating status of the energy storage device during the energy storage process and the category of each grid parameter. The energy storage device parameters corresponding to different grid parameters are fused to obtain the target energy storage device parameters. The operating status of the energy storage device is determined based on the target energy storage parameters and the actual collected energy storage device parameters, rather than based on a fixed threshold. This improves the accuracy of the energy storage device operating status judgment results. In addition, it can detect potential faults in the energy storage device in advance, providing more processing time for staff. It can also quickly determine the size of the problem and the solution based on the degree of change in energy storage device parameters, especially battery parameters.

[0024] According to an embodiment of the present invention, an embodiment of a method for monitoring the status of an energy storage device is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0025] This embodiment provides a method for monitoring the status of an energy storage device, which can be used in the aforementioned server. Figure 1 This is a flowchart of an energy storage device status monitoring method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0026] Step S101: Obtain multiple grid parameters of the photovoltaic grid system in which the energy storage device is located during the energy storage process, as well as the actual collected parameters of the energy storage device.

[0027] For example, during the energy storage process, the photovoltaic grid system connected to the energy storage device provides it with electrical energy. Therefore, the operating status of the photovoltaic grid system has some direct or indirect impact on the operating status of the energy storage device. In this embodiment, the energy storage device may include, but is not limited to, batteries. Grid parameters are parameters that affect energy storage efficiency or safety during grid transmission and storage. Grid parameters may include, but are not limited to, voltage and current during grid transmission, as well as current environmental factors such as temperature and humidity, and other factors such as battery capacity. The actually collected energy storage device parameters can be the currently collected actual energy storage device parameters. Energy storage device parameters may include, but are not limited to, the battery's state of charge, health status, energy storage efficiency, and capacity, among other key performance indicators. Energy storage device parameters can reflect the operating status of the energy storage device.

[0028] Step S102: Determine the category of the corresponding power grid parameter based on the variation pattern of each power grid parameter.

[0029] For example, different grid parameters exhibit different patterns of change. Classifying grid parameters based on these patterns facilitates the subsequent calculation of energy storage device parameters reflecting their operational status based on different categories of grid parameters. In this embodiment, the patterns of change for each grid parameter can be obtained through historical data analysis of the corresponding grid parameters.

[0030] Step S103: Calculate the corresponding energy storage device parameters based on each grid parameter and the corresponding grid parameter category.

[0031] For example, in the embodiments of this application, the input voltage, rated power, or charging and discharging process of the energy storage device are related to the input and output parameters of the power grid, ambient temperature, and other indicators. By establishing and identifying these relationships, the parameters of the energy storage device can be analyzed.

[0032] Step S104: Merge the energy storage device parameters corresponding to each grid parameter to obtain the merged target energy storage device parameters.

[0033] For example, in this application embodiment, the weight of the energy storage device parameters corresponding to each grid parameter can be determined based on the importance of different grid parameters, and the energy storage device parameters corresponding to each grid parameter can be fused based on different weights to obtain the fused target energy storage device parameters.

[0034] Step S105: Determine the operating status of the energy storage device based on the target energy storage device parameters and the actual collected energy storage device parameters.

[0035] For example, in the embodiments of this application, the operating status of the energy storage device can be determined based on the magnitude of the difference between the target energy storage device parameters and the actual collected energy storage device parameters.

[0036] The energy storage device status monitoring method provided in this embodiment calculates the corresponding energy storage device parameters for different grid parameters by using multiple grid parameters that affect the operating status of the energy storage device during the energy storage process and the category of each grid parameter. The energy storage device parameters corresponding to different grid parameters are then fused to obtain the target energy storage device parameters. The operating status of the energy storage device is determined based on the target energy storage parameters and the actual collected energy storage device parameters, rather than based on a fixed threshold. This improves the accuracy of the energy storage device operating status judgment results. In addition, it can detect potential faults in the energy storage device in advance, providing more time for staff to handle them. It can also quickly determine the size of the problem and the solution based on the degree of change in energy storage device parameters, especially battery parameters.

[0037] This embodiment provides a method for monitoring the status of an energy storage device, which can be used in the aforementioned server. Figure 2 This is a flowchart of an energy storage device status monitoring method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0038] Step S201: Obtain multiple grid parameters of the photovoltaic power grid system in which the energy storage device operates during energy storage, as well as the actual collected parameters of the energy storage device. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0039] Step S202: Determine the category of the corresponding power grid parameter based on the variation pattern of each power grid parameter. For details, please refer to [link to relevant documentation]. Figure 1 Step S102 of the illustrated embodiment will not be described again here.

[0040] Step S203: Calculate the corresponding energy storage device parameters based on each grid parameter and the corresponding grid parameter category.

[0041] Specifically, the categories of power grid parameters include a first category of regularly changing parameters, a second category of irregularly changing parameters, and a third category of unchanging parameters. In this embodiment, for each parameter, all historical data can be analyzed to obtain the changing pattern of the parameter; subsequently, the parameter is classified according to different patterns. The changing patterns are divided into three cases: regularly changing, irregularly changing, and unchanging. Parameters with regularly changing patterns can be roughly derived and calculated through certain relationships, and under normal circumstances, they are within a predictable range; parameters with irregularly changing patterns are usually irregular, and within a certain range, each value may appear with a certain probability; parameters that do not change are usually constant, or have only minor changes that do not affect the normal operation of the motor. For example, in the current environment, temperature typically follows a certain pattern of change, such as rising continuously from a low of 0 degrees Celsius to 25 degrees Celsius and then continuously falling back to 5 degrees Celsius. Therefore, temperature falls under the category of regularly changing parameters. Humidity, on the other hand, can fluctuate significantly depending on weather conditions, such as changing from 20% to 80% due to rain. Therefore, humidity falls under the category of irregularly changing parameters. Furthermore, if the battery is not replaced within a certain period, the battery's storage capacity will not change significantly. Therefore, the same battery falls under the category of unchanging parameters in grid energy storage. It is worth noting that some parameters belong to different parameter categories depending on the application. For example, if the grid equipment or energy storage device in the photovoltaic system needs to operate stably, the input voltage will be set to a fixed value. In this case, voltage falls under the category of unchanging parameters. If the battery needs to operate under different loads or conditions, different voltage values ​​will be input to calculate and analyze the state of the energy storage device (battery). In this case, voltage falls under the category of regularly changing parameters. Historical data for power grid parameters refers to the relevant parameters such as power grid transmission and storage during the energy storage process over a period of time, such as 1-5 hours, 5-10 hours, 10-20 hours, 1-2 days, 1-2 weeks, etc. The data is set according to the actual situation to ensure that there is enough historical data for analysis, so as to achieve the purpose of classifying power grid parameters.

[0042] Step S203 above includes:

[0043] Step S2031: Calculate the corresponding parameters of the first energy storage device based on the variation patterns of each first category of grid parameters.

[0044] In some optional implementations, step S2021 above includes:

[0045] Step a1: Determine the change sequence of each first category of power grid parameter. The change sequence is used to characterize the change pattern of the corresponding power grid parameter.

[0046] Step a2: Obtain the corresponding parameters of the first energy storage device based on the change sequence of each first category of grid parameters.

[0047] For example, in the embodiments of this application, for the regular changing parameters, the corresponding energy storage device parameters are obtained through a certain regular transformation sequence S.

[0048] For example, if the grid load where the energy storage device is located remains unchanged, the change in the battery's state of charge (SOC) is related to the change in the grid current (A). When calculating the SOC, the grid current change sequence S(1,2,3,5,7,10,15,10,7,5,3,2,1) can be used. Therefore, the range of the motor torque T is between Amax = 15A and Amin = 1A.

[0049] The sequence S is obtained based on historical data of regularly changing motor drive parameters. It is usually S(B1 / B, B2 / B, B3 / B..., B, B10, B11...), where B is the current parameter value and B1, B2, B3... are the historical data. Therefore, the sequence S reflects the changing pattern of the parameters.

[0050] Step S2032: Calculate the corresponding second energy storage device parameters based on each second category of grid parameters and the probability matrix of different values ​​in the corresponding grid parameters.

[0051] For example, in this embodiment of the application, for irregularly changing parameters, the probability matrix P and the corresponding conversion formula Qp = M * Qx * P are used, where Qp is the predicted or required energy storage device parameter, Ex is the grid parameter at the current or previous moment, and M is the conversion coefficient for the calculated parameter. P is the probability matrix, such as... Among them, P 00 P 01 P 11 ...to obtain the probability of different values, this is obtained by statistically analyzing a large amount of historical data of irregular parameters.

[0052] Therefore, the energy storage device parameter Qp is obtained through the probability and coefficient relationship of the corresponding grid parameters under certain conditions.

[0053] Step S2033: Calculate the corresponding third energy storage device parameters based on the grid parameters of each third category and the pre-built first relationship model. The first relationship model is used to characterize the correlation between the unchanging grid parameters and the energy storage device parameters.

[0054] For example, in this embodiment of the application, for parameters that do not change (fixed values), the corresponding energy storage device parameters are obtained through the actually determined conversion factor M.

[0055] For example, for a certain time range, that is, a period when the battery capacity usually does not decay, the corresponding output power Ft of the power grid per unit time, the battery capacity Q = MFt, and M is the conversion factor for calculating the capacity.

[0056] Step S204: Merge the energy storage device parameters corresponding to each grid parameter to obtain the merged target energy storage device parameters.

[0057] For example, in this embodiment of the application, an energy storage device parameter fusion model is constructed based on the relationship between grid parameters and energy storage device parameters and the classification of grid parameters. This model is used for determining and monitoring the parameters of the target energy storage device. The device parameter fusion model can be expressed as follows:

[0058] Qp = a*M*Qx + b*Qp(S) + c*M*Qx(P)

[0059] Where Qp represents the energy storage device parameters, Qx represents the grid parameters, M represents the conversion factor, Qp(S) represents the energy storage device parameters calculated based on the sequence S, Qx(P) represents the grid parameters calculated based on the probability matrix P, and a, b, and c are model factors, all values ​​between 0 and 1. If a is 0, it means there is no fixed value when calculating the energy storage device parameter E; if b is 0, it means there is no regular parameter value when calculating the energy storage device parameter E; and if c is 0, it means there is no irregularly changing grid parameter value when calculating the energy storage device parameter E.

[0060] Therefore, the energy storage device parameter Qp may be calculated using a single category of parameters, such as Qp = a*k*Qpx, or the energy storage efficiency may be calculated using fixed input voltage and current values ​​as well as other grid parameters. Alternatively, the energy storage parameter may be calculated using multiple categories of parameters, such as Qp = a*M*Qx + b*Qp(S) or Qp = a*M*Qx + b*Qp(S) + c*M*Qx(P), or the energy storage efficiency may be calculated through comprehensive analysis of input voltage, input current, and ambient temperature.

[0061] Step S205: Determine the operating status of the energy storage device based on the target energy storage device parameters and the actual collected energy storage device parameters.

[0062] In this embodiment, the constructed energy storage device parameter fusion model is used to determine and monitor the parameters of the energy storage device, thereby obtaining highly accurate parameters of the energy storage device during operation and improving the operational safety of the energy storage device.

[0063] Specifically, step S205 includes:

[0064] Step S2051: Determine the difference between the target energy storage device parameters and the actual collected energy storage device parameters.

[0065] For example, in this embodiment of the application, the parameters of the energy storage device during the current operation are collected in real time and compared with the parameters of the energy storage device obtained by using the energy storage device parameter fusion model to determine the difference between the two.

[0066] Step S2052: If the difference between the target energy storage device parameters and the actual collected energy storage device parameters is greater than a preset threshold, it is determined that the energy storage device is in abnormal operation.

[0067] For example, in this embodiment of the application, if the difference is within the threshold range, the current energy storage device parameters are determined to be the required high-accuracy energy storage device parameters, and the device operates normally; otherwise, the device operates abnormally.

[0068] In some alternative implementations, if the energy storage device malfunctions, the device parameters of the energy storage device are adjusted using the target energy storage device parameters to obtain the adjustment result.

[0069] For example, in this embodiment of the application, if the difference exceeds the threshold range, the energy storage device parameters obtained by using the energy storage device parameter fusion model are adjusted to obtain highly accurate energy storage device parameters.

[0070] This embodiment also provides an energy storage device status monitoring device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0071] This embodiment provides a status monitoring device for energy storage equipment, such as... Figure 3 As shown, it includes:

[0072] The acquisition module 301 is used to acquire multiple grid parameters of the photovoltaic grid system in which the energy storage device is located during the energy storage process, as well as the actual collected parameters of the energy storage device.

[0073] The first determining module 302 is used to determine the category of the corresponding power grid parameter based on the changing pattern of each power grid parameter;

[0074] Calculation module 303 is used to calculate the corresponding energy storage device parameters based on each power grid parameter and the corresponding power grid parameter category;

[0075] The second determining module 304 is used to fuse the energy storage device parameters corresponding to each grid parameter to obtain the fused target energy storage device parameters.

[0076] The third determining module 305 is used to determine the operating status of the energy storage device based on the target energy storage device parameters and the actual collected energy storage device parameters.

[0077] In some optional implementations, the categories of power grid parameters include a first category of regularly changing power grid parameters, a second category of irregularly changing power grid parameters, and a third category of unchanged power grid parameters. The calculation module 303 includes:

[0078] The first calculation submodule is used to calculate the corresponding parameters of the first energy storage device based on the changing patterns of each first category of power grid parameters.

[0079] The second calculation submodule is used to calculate the corresponding second energy storage device parameters based on each second category of grid parameters and the probability matrix of different values ​​in the corresponding grid parameters.

[0080] The third calculation submodule is used to calculate the corresponding third energy storage device parameters based on the grid parameters of each third category and the pre-built first relational model. The first relational model is used to characterize the correlation between the unchanging grid parameters and the energy storage device parameters.

[0081] In some alternative implementations, the third determining module 305 includes:

[0082] The first determining submodule is used to determine the difference between the target energy storage device parameters and the actual collected energy storage device parameters;

[0083] The second determination submodule is used to determine that the energy storage device is malfunctioning if the difference between the target energy storage device parameters and the actual collected energy storage device parameters is greater than a preset threshold.

[0084] In some alternative embodiments, the device may include:

[0085] The adjustment module is used to adjust the equipment parameters of the energy storage device based on the target energy storage device parameters if the device operates abnormally, and obtain the adjustment result.

[0086] In some alternative implementations, the first computation submodule includes:

[0087] The first determining unit is used to determine the change sequence of each first category of power grid parameter, and the change sequence is used to characterize the change pattern of the corresponding power grid parameter.

[0088] The second determining unit obtains the corresponding first energy storage device parameters based on the change sequence of each first category of grid parameters.

[0089] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0090] In this embodiment, the energy storage device status monitoring device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0091] This invention also provides a computer device having the above-described features. Figure 3 The energy storage device shown is a status monitoring device.

[0092] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 4 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 4 Take a processor 10 as an example.

[0093] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0094] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0095] The memory 20 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 based on the use of the computer device. Furthermore, the memory 20 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 alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0096] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0097] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0098] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0099] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0100] 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 scope defined by the appended claims.

Claims

1. A method for monitoring the condition of an energy storage device, characterized in that, The method includes: Acquire multiple grid parameters of the photovoltaic power grid system in which the energy storage device is located during the energy storage process, as well as the actual collected parameters of the energy storage device; The category of the corresponding power grid parameter is determined based on the variation pattern of each power grid parameter; Calculate the corresponding energy storage device parameters based on each power grid parameter and the corresponding power grid parameter category; The parameters of the energy storage devices corresponding to each power grid parameter are merged to obtain the merged target energy storage device parameters; The operating status of the energy storage device is determined based on the target energy storage device parameters and the actual collected energy storage device parameters. The categories of power grid parameters include a first category of regularly changing power grid parameters, a second category of irregularly changing power grid parameters, and a third category of unchanged power grid parameters. The step of calculating the corresponding energy storage device parameters based on each power grid parameter and its corresponding category includes: Calculate the parameters of the corresponding first energy storage device based on the variation patterns of each first category of power grid parameters; The parameters of the corresponding second energy storage device are calculated based on the probability matrix of each second category of grid parameters and the different values ​​of the corresponding grid parameters. The corresponding third energy storage device parameters are calculated based on the grid parameters of each third category and the pre-built first relational model. The first relational model is used to characterize the correlation between the unchanging grid parameters and the energy storage device parameters.

2. The method according to claim 1, characterized in that, The step of determining the operating status of the energy storage device based on the target energy storage device parameters and the actually collected energy storage device parameters includes: Determine the difference between the target energy storage device parameters and the actual collected energy storage device parameters; If the difference between the target energy storage device parameters and the actual collected energy storage device parameters is greater than a preset threshold, the operation of the energy storage device is determined to be abnormal.

3. The method according to claim 1 or 2, characterized in that, The method further includes: If the energy storage device malfunctions, the device parameters of the energy storage device are adjusted using the target energy storage device parameters to obtain the adjustment result.

4. The method according to claim 1, characterized in that, The calculation of the corresponding parameters of the first energy storage device based on the variation patterns of each first category of power grid parameters includes: Determine the change sequence of each first category of power grid parameter, the change sequence being used to characterize the change pattern of the corresponding power grid parameter; The parameters of the first energy storage device are obtained based on the change sequence of each of the first category of power grid parameters.

5. A condition monitoring device for energy storage equipment, characterized in that, The device includes: The acquisition module is used to acquire multiple grid parameters of the photovoltaic grid system in which the energy storage device is located during the energy storage process, as well as the actual collected parameters of the energy storage device. The first determining module is used to determine the category of the corresponding power grid parameter based on the variation pattern of each power grid parameter; The calculation module is used to calculate the parameters of the corresponding energy storage devices based on each grid parameter and the corresponding grid parameter category; The second determining module is used to fuse the energy storage device parameters corresponding to each grid parameter to obtain the fused target energy storage device parameters. The third determining module is used to determine the operating status of the energy storage device based on the target energy storage device parameters and the actually collected energy storage device parameters; The categories of power grid parameters include a first category of regularly changing power grid parameters, a second category of irregularly changing power grid parameters, and a third category of unchanged power grid parameters. The calculation module includes: The first calculation submodule is used to calculate the corresponding parameters of the first energy storage device based on the changing patterns of each first category of power grid parameters. The second calculation submodule is used to calculate the corresponding second energy storage device parameters based on each second category of grid parameters and the probability matrix of different values ​​in the corresponding grid parameters. The third calculation submodule is used to calculate the corresponding third energy storage device parameters based on the grid parameters of each third category and the pre-built first relationship model. The first relationship model is used to characterize the correlation between the unchanging grid parameters and the energy storage device parameters.

6. A computer device, characterized in that, include: The device includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the energy storage device status monitoring method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the energy storage device status monitoring method according to any one of claims 1 to 4.

8. A computer program product, characterized in that, It includes computer instructions for causing a computer to execute the energy storage device status monitoring method according to any one of claims 1 to 4.

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