Data hierarchical compression storage method, energy storage management system, device and storage medium

Abstract

The application discloses a data hierarchical compression storage method and an energy storage management system, device and storage medium, and comprises the following steps: acquiring operation data of a cascaded energy storage system; classifying the operation data into first data, second data and third data according to the reading frequency and the importance of the data; compressing the second data by using a second lossless compression step to form second storage data, wherein the compression rate of the first lossless compression step is lower than that of the second lossless compression step; screening the third data by using a decision tree screening step to form third storage data, wherein the decision tree screening step is provided with a screening condition, part of the content in the third data is deleted based on the screening condition, and the remaining content in the third data forms the third storage data; and storing the first storage data, the second storage data and the third storage data in a local storage, so that the classified storage improves the flexibility of storage reading, reduces the storage load of the storage and improves the reliability of data storage.

Description

Technical Field

[0001] This invention relates to the field of power equipment data processing technology, and in particular to a data hierarchical compression and storage method, energy storage management system, device, and storage medium. Background Technology

[0002] With the development of energy technology, cascaded energy storage systems are being used more and more widely in power systems. A cascaded energy storage system typically consists of dozens or even hundreds of energy storage modules, generating a large amount of operational data during operation, including battery status data, charge and discharge records, voltage and current waveforms, environmental parameters, and operational logs. Efficient storage of this data is crucial for system monitoring, maintenance, and subsequent performance analysis.

[0003] However, traditional data storage methods suffer from the following drawbacks: they involve massive amounts of data, occupy a large amount of storage space, and are not conducive to fast retrieval. Full-data storage can easily lead to memory overload, resulting in the loss or damage of some important data. Summary of the Invention

[0004] This invention aims to solve at least one of the technical problems existing in the prior art. To this end, this invention proposes a data hierarchical compression storage method, energy storage management system, device, and storage medium, which classifies storage, improves the flexibility of storage and retrieval, reduces the storage load of the memory, and improves the reliability of data storage.

[0005] According to a first aspect of the present invention, a hierarchical data compression and storage method is applied to a cascaded energy storage system to store operational data generated by the cascaded energy storage system. The method includes: acquiring operational data from the cascaded energy storage system; classifying the operational data into first data, second data, and third data based on reading frequency and data importance, wherein the reading frequency of the first data and third data is higher than that of the second data, and the data importance of the first data and second data is higher than that of the third data; compressing the first data using a first lossless compression step to form first stored data; compressing the second data using a second lossless compression step to form second stored data, wherein the compression ratio of the first lossless compression step is lower than that of the second lossless compression step; filtering the third data using a decision tree filtering step to form third stored data, wherein the decision tree filtering step includes filtering conditions, and based on these conditions, partially deleting content from the third data and storing the remaining content in the third data to form third stored data; and storing the first stored data, second stored data, and third stored data in a local memory.

[0006] The data hierarchical compression and storage method according to embodiments of the present invention has at least the following beneficial effects:

[0007] This invention discloses a hierarchical data compression and storage method. It categorizes the operational data of a cascaded energy storage system into at least three classes: first data, second data, and third data, based on the frequency of access and the importance of the data. First data, with both high access frequency and high importance, is compressed using a first lossless compression step with a low compression ratio to ensure data integrity. While the compressed data size is larger due to the low compression ratio, decompression is faster during retrieval, allowing for quick access and utilization. Second data, with a lower access frequency but higher importance, is compressed using a second lossless compression step with a higher compression ratio to ensure data integrity. This higher compression ratio significantly reduces the data size and storage load. Third data, with a high access frequency but lower importance, may not be compressed. However, a decision tree filtering step is used to filter and delete some content from the third data, thus reducing its size. This rational processing and categorized storage of different data improves the flexibility of storage retrieval, reduces the storage load on the memory, and enhances the reliability of data storage.

[0008] According to some embodiments of the present invention, the first lossless compression step includes a differential pulse coding step and a Huffman coding step; the compression of the first data to form the first stored data in the first lossless compression step includes: processing the first data using the differential pulse coding step to form a residual value; and processing the residual value into encoded data using the Huffman coding step to form the first stored data, wherein the size of the residual value determines the length of the encoded data, with a larger residual value resulting in longer encoded data and a smaller residual value resulting in shorter encoded data.

[0009] According to some embodiments of the present invention, the second lossless compression step includes a Brotli compression step; compressing the second data using the second lossless compression step to form the second stored data includes: processing the second data using the Brotli compression step to form the second stored data.

[0010] According to some embodiments of the present invention, the cascaded energy storage system includes a cascaded energy storage module, an environmental parameter control module, a control module, and a manipulation module. The cascaded energy storage module includes multiple energy storage modules, each including a power conversion unit and an energy storage battery. The DC terminal of the power conversion unit is connected to the energy storage battery. The control module is connected to the controlled terminal of the power conversion unit, the manipulation module, and the environmental parameter control module, respectively. The first data includes one or more combinations of control command data for controlling the power conversion unit, battery electrical data of the energy storage battery, and system electrical data of the cascaded energy storage module, wherein the battery electrical data includes... The system electrical data includes one or more combinations of the energy storage battery's output voltage, output current, and energy storage capacity; the system electrical data includes one or more combinations of the DC-side output voltage, DC-side output current, AC-side output voltage, and AC-side output current of the cascaded energy storage module; the second data includes historical electrical data of the energy storage battery and environmental sensor data, wherein the historical electrical data of the energy storage battery includes one or more combinations of the energy storage battery's historical output voltage, historical output current, and historical energy storage capacity; the third data includes status log data of the cascaded energy storage module, status log data of the environmental parameter control module, and control data generated by the operation of the control module.

[0011] According to some embodiments of the present invention, the data hierarchical compression storage method further includes: obtaining the remaining capacity value of the local storage; when the remaining capacity value is lower than the capacity threshold, migrating at least a portion of the second storage data or the third storage data to the cloud storage.

[0012] According to some embodiments of the present invention, the data hierarchical compression storage method further includes: updating the reading time of the read content when the content of the second storage data and the third storage data is read; the migration of at least part of the second storage data or the third storage data to the cloud storage includes: sorting the content of the second storage data and the third storage data according to the reading time, and preferentially migrating the content of the second storage data or the third storage data with the earlier reading time to the cloud storage.

[0013] According to some embodiments of the present invention, the data hierarchical compression storage method further includes: obtaining a setting instruction; selecting, according to the setting instruction, to match the third storage data based on the time axis to form a third storage data paired with time; and storing the third storage data paired with time in a local memory.

[0014] According to a second aspect of the present invention, an energy storage management system is applied to a cascaded energy storage system. The energy storage management system includes a data acquisition module, a processing module, and a local storage device. The data acquisition module is used to connect to the cascaded energy storage system to acquire operating data of the energy storage management system. The processing module is connected to the data acquisition module and the local storage device to execute the data hierarchical compression storage method disclosed in any of the above embodiments.

[0015] The energy storage management system according to embodiments of the present invention has at least the following beneficial effects:

[0016] The energy storage management system of the present invention applies the data hierarchical compression storage method disclosed in any of the above embodiments to classify and store the operating data generated by the cascaded energy storage system, thereby improving the flexibility of storage and retrieval, reducing the storage load of the memory, and improving the reliability of data storage.

[0017] According to a third aspect of the present invention, the control device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the data hierarchical compression storage method disclosed in any of the above embodiments.

[0018] According to a fourth aspect of the present invention, a computer-readable storage medium stores a computer program, characterized in that, when the computer program is executed by a processor, it implements the data hierarchical compression storage method disclosed in any of the above embodiments.

[0019] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0020] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0021] Figure 1 This is a schematic diagram of the principle structure of one embodiment of the energy storage management system of the present invention;

[0022] Figure 2 This is a flowchart of one embodiment of the hierarchical data compression and storage method of the present invention;

[0023] Figure 3 This is a schematic diagram of the control device of the present invention in one embodiment.

[0024] Figure label:

[0025] Cascaded energy storage system 100; Cascaded energy storage module 110; Environmental parameter control module 120; Control module 130; Operation module 140; Acquisition module 200; Processing module 300; Local memory 410; Cloud memory 420; Processor 610; Memory 620; Input / output interface 630; Communication interface 640; Bus 650. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0027] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0028] In the description of this invention, "several" means one or more, "multiple" means two or more, "greater than", "less than", "exceeding" are understood to exclude the number itself, and "above", "below", "within" are understood to include the number itself.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0030] like Figure 1 , 2 As shown, the data hierarchical compression storage method according to the first aspect of the present invention is applied to a cascaded energy storage system 100 to store the operational data generated by the cascaded energy storage system 100.

[0031] The cascaded energy storage system 100 typically includes a cascaded energy storage module 110, an environmental parameter control module 120, a control module 130, and a control module 140. The cascaded energy storage module 110 includes multiple energy storage modules, each of which includes a power conversion unit and an energy storage battery. The DC terminal of the power conversion unit is connected to the energy storage battery. The control module 130 is connected to the controlled terminal of the power conversion unit, the control module 140, and the environmental parameter control module 120, respectively.

[0032] The cascaded energy storage module 110 may include cascaded bridge arms connected to a three-phase power grid. Each cascaded bridge arm is composed of multiple energy storage modules connected in series at their AC terminals. Each power conversion unit may include multiple semiconductor switching transistors forming an H-bridge conversion circuit. The AC terminal of the H-bridge conversion circuit serves as the AC terminal of the energy storage module, while a bypass switch is connected in parallel at the AC terminal of the energy storage module. The H-bridge conversion circuit serves as the DC terminal of the power conversion unit, and the DC terminal of the power conversion unit is connected to the energy storage battery. The switching transistors may be MOSFETs or IGBTs. The controlled terminal of the switching transistors serves as the controlled terminal of the power conversion unit. The on / off status of components such as the bypass switch can generate status log data.

[0033] The environmental parameter control module 120 includes temperature sensors, humidity sensors, temperature control devices, humidity control devices, and fault alarm devices within the equipment. The temperature sensor detects the ambient temperature and generates temperature sensing data, while the humidity sensor detects the ambient humidity and generates humidity sensing data. The temperature control device may include a water-cooled radiator, an air conditioner, etc., which can regulate the temperature of the internal environment of the equipment and generate status log data. The humidity control device may include a humidifier, a dryer, etc., which can regulate the humidity of the internal environment of the equipment and generate status log data. The fault alarm device can output alarm signals to the monitoring platform wirelessly or via wired means and generate status log data.

[0034] The control module 140 may include a keyboard, mouse, operation buttons, etc., and the control module 130 may include a CPU processor and its auxiliary circuits. Operators can input control data into the control module 140, and the control module 130 generates control commands based on the control data to control the switching operation of the switching transistors of each power conversion unit. Specifically, the control command data may be PWM signals.

[0035] like Figure 2 As shown, the data hierarchical compression storage method includes:

[0036] S510: Obtain operational data from the cascaded energy storage system;

[0037] S520. The running data is classified into first data, second data and third data according to the reading frequency and the importance of the data. The reading frequency of first data and third data is higher than that of second data, and the importance of first data and second data is higher than that of third data.

[0038] S530: Compress the first data using the first lossless compression step to form the first stored data;

[0039] S540. The second data is compressed using a second lossless compression step to form second stored data, wherein the compression ratio of the first lossless compression step is lower than that of the second lossless compression step.

[0040] S550. The third data is filtered using a decision tree filtering step to form the third stored data. The decision tree filtering step is configured with filtering conditions. Based on the filtering conditions, some content in the third data is deleted and the remaining content in the third data forms the third stored data.

[0041] S560, Store the first storage data, the second storage data, and the third storage data in the local memory.

[0042] In some embodiments of the present invention, the first data includes one or more combinations of control command data for controlling the power conversion unit, battery electrical data of the energy storage battery, and system electrical data of the cascaded energy storage module. The battery electrical data includes one or more combinations of the output voltage, output current, and energy storage capacity of the energy storage battery, and the system electrical data includes one or more combinations of the DC-side output voltage, DC-side output current, AC-side output voltage, and AC-side output current of the cascaded energy storage module.

[0043] The second data includes historical electrical data of the energy storage battery and environmental sensing data, wherein the historical electrical data of the energy storage battery includes one or more combinations of historical output voltage, historical output current, and historical energy storage capacity of the energy storage battery;

[0044] The third data includes the status log data of the cascaded energy storage module, the status log data of the environmental parameter control module, and the control data generated by the operation of the control module.

[0045] In step S520, unique identifiers can be set for the first data, the second data, and the third data respectively, so that they can be stored in different steps after subsequent classification. For example, the running data can be classified according to type. The first data is set with a first identifier, the second data is set with a second identifier, and the third data is set with a third identifier. By identifying the identifiers, different data can be assigned to steps S530, S540, and S550 for processing.

[0046] This invention discloses a hierarchical data compression and storage method. It categorizes the operational data of a cascaded energy storage system into at least three classes: first data, second data, and third data, based on the frequency of access and the importance of the data. First data, with both high access frequency and high importance, is compressed using a first lossless compression step with a low compression ratio to ensure data integrity. While the compressed data size is larger due to the low compression ratio, decompression is faster during retrieval, allowing for quick access and utilization. Second data, with a lower access frequency but higher importance, is compressed using a second lossless compression step with a higher compression ratio to ensure data integrity. This higher compression ratio significantly reduces the data size and storage load. Third data, with a high access frequency but lower importance, may not be compressed. However, a decision tree filtering step is used to filter and delete some content from the third data, thus reducing its size. This rational processing and categorized storage of different data improves the flexibility of storage retrieval, reduces the storage load on the memory, and enhances the reliability of data storage.

[0047] In some embodiments of the present invention, the first lossless compression step includes a differential pulse coding step and a Huffman coding step;

[0048] The first lossless compression step of compressing the first data to form the first stored data includes:

[0049] The residual value is generated by processing the first data using a differential pulse coding step;

[0050] The residual values ​​are processed into encoded data using Huffman coding steps to form the first stored data. The size of the residual value determines the length of the encoded data; larger residual values ​​result in longer encoded data, while smaller residual values ​​result in shorter encoded data.

[0051] The first data is compressed using the Differential Pulse Code (DPCM) step. A prediction model is established for each type of data, and the predicted value corresponding to each first data is obtained through the calculation of the prediction model. The difference between the predicted value and the actual value is calculated to obtain the residual value. The residual value is saved, and the corresponding true value can be deduced by reverse parsing. At the same time, there is a considerable amount of repetitive content in the residual value. Therefore, the Huffman coding step (VLC) step can be used to perform secondary compression processing on the residual value to convert it into coded data. This method achieves lossless compression and fast decompression speed.

[0052] In some embodiments of the present invention, the second lossless compression step includes a Brotli compression step; compressing the second data using the second lossless compression step to form the second stored data includes:

[0053] The second data is processed using a Brotli compression step to form the second stored data.

[0054] The Brotli compression step establishes a compression model through a hybrid approach, including the LZ77 algorithm and Huffman coding. The LZ77 algorithm uses a sliding window-based dictionary matching to find repeating strings and represents them as distance-length pairs. Huffman coding entropy-encodes the dictionary matching results and dynamically adjusts the encoding strategy based on the symbol context through context modeling. It matches repeating sequences in dictionary redundancy using a sliding window and calculates redundancy. Context modeling optimizes the symbol probability distribution, supports multi-level compression quality, and has a built-in dictionary reuse mechanism to reduce the transmission of duplicate data and improve the data compression ratio. Furthermore, the Brotli compression step can balance compression ratio and decompression speed by adjusting the corresponding configuration parameters.

[0055] In the S550, staff can set various filtering conditions by inputting setting commands. For example, the filtering condition can be set to set a normal operating range, which will delete data content within the normal operating range and retain data content outside the normal operating range.

[0056] Specifically, staff can roughly control the data compression rate by setting parameters for the first lossless compression step, the second lossless compression step, and the decision tree screening step.

[0057] In some embodiments of the present invention, the data hierarchical compression storage method further includes:

[0058] Get settings instructions;

[0059] According to the setting instructions, the third storage data will be matched based on the time axis to form a third storage data that is paired with time.

[0060] The third storage data paired with time is stored in local memory.

[0061] Since the third-party data is mostly status log data and operation data, which has a time-related characteristic, in order to make it easier for staff to know exactly when the data was generated, staff can enter setting commands to choose whether to match the time axis on the third-party storage data, so that the content of the third-party storage data is matched with the time point on the time axis. In addition, staff can also set up functions such as timed storage through setting commands.

[0062] In some embodiments of the present invention, the compressed first data or second data is periodically decompressed and verified. If the data content is found to be damaged or lost, it can be repaired or the original data can be retrieved in a timely manner.

[0063] In some embodiments of the present invention, the data hierarchical compression storage method further includes:

[0064] Get the remaining capacity of local storage;

[0065] When the remaining capacity value is lower than the capacity threshold, at least part of the second or third storage data will be migrated to the cloud storage 420.

[0066] When the remaining capacity of local storage 410 is lower than the capacity threshold, it means that local storage 410 is about to be full. In order to ensure that important data has sufficient space for storage, before local storage 410 is full, the second data with low reading frequency or the third data with low data importance will be migrated to cloud storage 420. It can be understood that migration here refers to sending data to cloud storage 420. After cloud storage 420 has received the data and confirmed that the content is correct, local storage 410 will delete the data sent to free up more storage space to store new data.

[0067] In some embodiments of the present invention, the data hierarchical compression storage method further includes:

[0068] When the contents of the second and third stored data are read, update the read time of the read content;

[0069] The migration of at least a portion of the second or third storage data to the cloud storage includes:

[0070] The contents of the second and third storage data are sorted according to the read time, and the contents of the second or third storage data with the earlier read time are migrated to the cloud storage first.

[0071] In actual use, staff can operate through the operation module and view the content of various data in the display module. When viewing, the compressed first or second data needs to be decompressed, while the third data can be viewed directly. As long as the data is viewed and read, the control module will update the reading time corresponding to the data content. When it is necessary to migrate some of the second or third storage data, the reading time corresponding to the content in the second and third storage data is obtained, and the content that has not been read for a longer time (i.e., the reading time is earlier) is migrated to the cloud storage first.

[0072] According to a second aspect of the energy storage management system of the present invention, such as Figure 1As shown, the energy storage management system is applied to a cascaded energy storage system 100. The energy storage management system includes a data acquisition module 200, a processing module 300, and a local storage device 410. The data acquisition module 200 is used to connect to the cascaded energy storage system 100 to acquire the operating data of the energy storage management system. The processing module 300 is connected to the data acquisition module 200 and the local storage device 410 respectively to execute the data hierarchical compression storage method disclosed in any of the above embodiments.

[0073] The energy storage management system of the present invention applies the data hierarchical compression storage method disclosed in any of the above embodiments to classify and store the operating data generated by the cascaded energy storage system 100, thereby improving the flexibility of storage and retrieval, reducing the storage load of the memory, and improving the reliability of data storage.

[0074] According to a third aspect of the present invention, the control device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the data hierarchical compression storage method disclosed in any of the above embodiments.

[0075] The control device can be any intelligent terminal, including a central computer, a remote equipment terminal computer, or any other intelligent terminal.

[0076] like Figure 3 As shown, Figure 3 The hardware structure of a control device according to another embodiment is also illustrated. The control device includes:

[0077] The processor 610 can be implemented using a general-purpose central processing unit (CPU), a microprocessor 610, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0078] The memory 620 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 620 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 620 and is called and executed by the processor 610 using the data hierarchical compression storage method of the embodiments of this application.

[0079] The input / output interface 630 is used to realize information input and output;

[0080] The communication interface 640 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0081] The bus 650 transmits information between various components of the device (such as processor 610, memory 620, input / output interface 630 and communication interface 640), and can also be connected to the smart Internet of Things.

[0082] The processor 610, memory 620, input / output interface 630 and communication interface 640 are connected to each other within the device via bus 650.

[0083] According to a fourth aspect of the present invention, a computer-readable storage medium stores a computer program, characterized in that, when executed by a processor, the computer program implements the data hierarchical compression storage method disclosed in any of the above embodiments.

[0084] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor 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.

[0085] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0086] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0087] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0088] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0089] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0090] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

[0091] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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 specification.

[0092] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A data hierarchical compression and storage method, applied to cascaded energy storage systems for storing operational data generated by the cascaded energy storage systems, characterized in that... The hierarchical data compression and storage method includes: Acquire operational data from cascaded energy storage systems; The running data is classified into first data, second data, and third data according to the frequency of reading and the importance of the data. The reading frequency of first data and third data is higher than that of second data, and the importance of first data and second data is higher than that of third data. The first data is compressed using a first lossless compression step to form the first stored data; The second data is compressed using a second lossless compression step to form second stored data, wherein the compression ratio of the first lossless compression step is lower than that of the second lossless compression step; The decision tree filtering step is used to filter the third data to form the third stored data. The decision tree filtering step is set with filtering conditions. Based on the filtering conditions, some content in the third data is deleted and the remaining content in the third data forms the third stored data. The first storage data, the second storage data, and the third storage data are stored in the local memory; The cascaded energy storage system includes a cascaded energy storage module, an environmental parameter control module, a control module, and an operation module. The cascaded energy storage module includes multiple energy storage modules, each of which includes a power conversion unit and an energy storage battery. The DC terminal of the power conversion unit is connected to the energy storage battery. The control module is connected to the controlled terminal of the power conversion unit, the operation module, and the environmental parameter control module, respectively. The first data includes one or more combinations of control command data for power conversion unit control, battery electrical data of energy storage battery, and system electrical data of cascaded energy storage module. The battery electrical data includes one or more combinations of output voltage, output current, and energy storage capacity of energy storage battery. The system electrical data includes one or more combinations of DC-side output voltage, DC-side output current, AC-side output voltage, and AC-side output current of cascaded energy storage module. The second data includes historical electrical data of the energy storage battery and environmental sensing data, wherein the historical electrical data of the energy storage battery includes one or more combinations of historical output voltage, historical output current, and historical energy storage capacity of the energy storage battery; The third data includes the status log data of the cascaded energy storage module, the status log data of the environmental parameter control module, and the control data generated by the operation of the control module. The first lossless compression step includes a differential pulse coding step and a Huffman coding step; The first lossless compression step of compressing the first data to form the first stored data includes: The residual value is generated by processing the first data using a differential pulse coding step; The residual values ​​are processed into encoded data using Huffman coding steps to form the first stored data. The size of the residual value determines the length of the encoded data; larger residual values ​​result in longer encoded data, while smaller residual values ​​result in shorter encoded data. The second lossless compression step includes a Brotli compression step; The second data is compressed using a second lossless compression step to form the second stored data, which includes: The second data is processed using a Brotli compression step to form the second stored data.

2. The data hierarchical compression and storage method according to claim 1, characterized in that, Also includes: Get the remaining capacity of local storage; When the remaining capacity value is lower than the capacity threshold, at least part of the second or third storage data will be migrated to the cloud storage.

3. The data hierarchical compression and storage method according to claim 2, characterized in that, Also includes: When the contents of the second and third stored data are read, update the read time of the read content; The migration of at least a portion of the second or third storage data to the cloud storage includes: sorting the contents of the second and third storage data according to the reading time, and prioritizing the migration of the contents of the second or third storage data with the earlier reading time to the cloud storage.

4. The data hierarchical compression and storage method according to claim 1, characterized in that, Also includes: Get settings instructions; According to the setting instructions, the third storage data will be matched based on the time axis to form a third storage data that is paired with time. The third storage data paired with time is stored in local memory.

5. An energy storage management system, characterized in that, The method is applied to a cascaded energy storage system. The energy storage management system includes a data acquisition module, a processing module, and a local storage device. The data acquisition module is used to connect to the cascaded energy storage system to acquire the operating data of the energy storage management system. The processing module is connected to the data acquisition module and the local storage device to execute the data hierarchical compression storage method as described in any one of claims 1 to 4.

6. A control device, characterized in that, The control device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the data hierarchical compression storage method according to any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the data hierarchical compression storage method according to any one of claims 1 to 4.

Images