Intelligent battery management method and system based on cloud-edge collaboration

Abstract

The present invention provides an intelligent battery management method and system based on cloud-edge collaboration, which belongs to the field of battery management technology, and specifically includes: based on the usage cycle data of the energy storage battery in the energy storage system, determining the deviation of the charging and discharging power of the energy storage battery and other energy storage batteries in different usage cycle times, and using the deviation to determine the problem battery in the energy storage battery, removing the problem battery as a reliable battery, and determining that the operating reliability of the energy storage system meets the requirements based on the capacity of the reliable battery and the energy storage adjustment demand in different historical energy storage adjustment times, and using the real-time energy storage adjustment data and the battery capacity change data of the reliable battery to determine whether to connect to the cloud to control the energy storage battery of the energy storage system, thereby improving the service life of the battery.

Description

Technical Field

[0001] The present invention belongs to the field of battery management technology, and in particular relates to an intelligent battery management method and system based on cloud-edge collaboration. Background Art

[0002] Energy storage systems are often composed of multiple groups of energy storage batteries. As the number of cycles of energy storage batteries increases, various types of battery failure problems will inevitably occur. This means that if the energy storage batteries cannot be managed, the service life of the energy storage batteries and the operational reliability of the energy storage system will inevitably be affected to a certain extent.

[0003] In order to achieve battery management of energy storage systems, the invention patent application CN202410584963.4 "A battery management method and system based on edge computing of big data" realizes rapid and accurate mining of energy storage battery big data value information, overcomes the bottleneck problems of many energy storage batteries, large data volume and limited edge computing capabilities, and effectively improves execution efficiency and real-time performance. However, there are the following technical problems:

[0004] Due to the differences in regulation requirements for different energy storage systems, when different energy storage systems face energy storage regulation instructions, there are differences in the number of energy storage batteries in the energy storage systems that respond to regulation requirements. This leads to differences in the difficulty of battery management for different energy storage systems. Therefore, if differentiated management strategies cannot be generated based on the difficulty of battery management, the reliability of battery management cannot be guaranteed.

[0005] In response to the above technical problems, the specific present invention utilizes cloud-edge collaboration to manage the energy storage batteries of the energy storage system and improve the service life of the energy storage batteries. Specifically, the present application provides an intelligent battery management method and system based on cloud-edge collaboration. Summary of the invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, an intelligent battery management method based on cloud-edge collaboration is provided.

[0008] An intelligent battery management method based on cloud-edge collaboration, specifically comprising:

[0009] Based on the usage data of the energy storage system, determine the usage data of the energy storage battery of the energy storage system in different historical energy storage adjustment times, and when it is determined that the battery management difficulty of the energy storage system meets the requirements according to the usage data of the energy storage battery in different historical energy storage adjustment times, proceed to the next step;

[0010] Based on the usage cycle data of the energy storage battery in the energy storage system, determine the deviation of the charge and discharge power of the energy storage battery and other energy storage batteries in different usage cycles, and use the deviation to determine the problematic battery in the energy storage battery;

[0011] The problematic battery is removed as a reliable battery, and when it is determined that the operating reliability of the energy storage system meets the requirements based on the capacity of the reliable battery and the energy storage regulation needs in different historical energy storage adjustment times, real-time energy storage regulation data and change data on the battery capacity of the reliable battery are used to determine whether to connect to the cloud to control the energy storage battery of the energy storage system.

[0012] The beneficial effects of the present invention are:

[0013] Based on the capacity of the reliably used battery and the energy storage regulation needs in different historical energy storage regulation times, it is determined whether the operating reliability of the energy storage system meets the requirements, thereby realizing the evaluation of the regulation matching situation in different historical energy storage regulation times from the perspective of the capacity of the reliably used battery in the historical energy storage regulation times, thereby realizing a reliable evaluation of the operating reliability of the energy storage system and laying the foundation for determining the differentiated control processing methods of the energy storage battery.

[0014] Real-time energy storage regulation data and the change data of the battery capacity of the reliable battery are used to determine whether to connect to the cloud for control processing of the energy storage battery of the energy storage system. This takes into account both the needs of real-time regulation and the regulation data of the battery capacity of the reliable battery. It realizes the determination of the control processing method in different energy storage regulation processes from the perspective of real-time energy storage regulation data, thereby ensuring the efficiency and reliability of the control management of the energy storage battery.

[0015] A further technical solution is that the usage data of the energy storage system includes historical energy storage adjustment times of the energy storage system and energy storage adjustment data in different historical energy storage adjustment times.

[0016] A further technical solution is that the usage data of the energy storage battery includes the usage count of the energy storage battery in different historical energy storage adjustment times.

[0017] A further technical solution is to determine whether the battery management difficulty of the energy storage system meets the requirements, including:

[0018] Determine the usage quantity of the energy storage batteries in different historical energy storage adjustment times based on the usage data of the energy storage batteries in different historical energy storage adjustment times;

[0019] Determine the complex adjustment times in the historical energy storage adjustment times by using the usage number of the energy storage battery;

[0020] Whether the battery management difficulty of the energy storage system meets the requirement is determined according to the number of complex adjustments.

[0021] A further technical solution is that the complex adjustment times are the historical energy storage adjustment times when the usage number of the energy storage battery is greater than the preset usage number.

[0022] A further technical solution is that when the number of complex adjustments of the energy storage system is greater than a preset number threshold, it is determined that the battery management difficulty of the energy storage system does not meet the requirements.

[0023] A further technical solution is that, when the battery management difficulty of the energy storage system does not meet the requirements, the energy storage battery of the energy storage system is controlled and processed by accessing the cloud in all energy storage adjustment times.

[0024] A further technical solution is to determine whether the battery management difficulty of the energy storage system meets the requirements, including:

[0025] Determine the usage quantity of the energy storage batteries in different historical energy storage adjustment times based on the usage data of the energy storage batteries in different historical energy storage adjustment times;

[0026] Determine the average value of the usage quantity of the energy storage battery at different historical energy storage adjustment times by using the usage quantity of the energy storage battery, and use it as the average usage quantity;

[0027] Determine whether the battery management difficulty of the energy storage system meets the requirement according to the average usage quantity.

[0028] A further technical solution is to determine whether to access the cloud to control the energy storage battery of the energy storage system, specifically including:

[0029] Based on the real-time energy storage regulation data, determine the regulation power of the energy storage system at different times, and use the regulation power to determine the average regulation power

[0030] Determining the remaining battery capacity of the reliable battery according to the change data of the battery capacity of the reliable battery, and determining the remaining regulation time of the reliable battery in combination with the average regulation power;

[0031] Based on the remaining adjustment time, it is determined whether to access the cloud to perform control processing of the energy storage battery of the energy storage system.

[0032] A further technical solution is to determine whether to access the cloud to control the energy storage battery of the energy storage system based on the remaining adjustment time, which specifically includes:

[0033] When the remaining adjustment time is greater than the preset adjustment time, it is determined not to connect to the cloud to perform control processing of the energy storage battery of the energy storage system.

[0034] In a second aspect, the present invention provides a computer system comprising: a memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned intelligent battery management method based on cloud-edge collaboration when running the computer program.

[0035] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0036] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0038] Figure 1 It is a flow chart of an intelligent battery management method based on cloud-edge collaboration;

[0039] Figure 2 It is a flow chart to determine whether the battery management difficulty of the energy storage system meets the requirements;

[0040] Figure 3 is a flow chart of a method for determining a problematic battery in an energy storage battery;

[0041] Figure 4 It is a flow chart to determine whether the operational reliability of the energy storage system meets the requirements;

[0042] Figure 5 It is a framework diagram of a computer system. DETAILED DESCRIPTION

[0043] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0044] Due to the differences in regulation requirements for different energy storage systems, when different energy storage systems face energy storage regulation instructions, there are differences in the number of energy storage batteries in the energy storage system that respond to regulation requirements. This leads to differences in the difficulty of battery management for different energy storage systems. Therefore, it is necessary to determine whether to use a cloud server to manage the battery based on the difficulty of battery management to ensure the reliability of battery management.

[0045] Determine whether the battery management difficulty of the energy storage system meets the requirements: determine by using the historical energy storage adjustment times when the number of energy storage batteries in use is greater than the preset number threshold. When the number of energy storage batteries in use is greater than the historical energy storage adjustment times above the preset number threshold, and is greater than 100 times, it is determined that the battery management difficulty of the energy storage system does not meet the requirements.

[0046] When the battery management difficulty of the energy storage system does not meet the requirements, the cloud server is used to manage the battery for different energy storage adjustment times.

[0047] Problem batteries in energy storage batteries: Energy storage batteries whose charge and discharge power deviates from that of other energy storage batteries and whose number of usage cycles accounts for more than 0.3 are considered problem batteries.

[0048] Operational reliability of energy storage system: The operational reliability coefficient is determined based on the proportion of historical energy storage regulation times in which the capacity of the reliably used battery can meet the energy storage regulation needs. Energy storage systems with an operational reliability coefficient less than 0.3 are regarded as energy storage systems whose operational reliability does not meet the requirements.

[0049] Determine whether to access the cloud to control the energy storage system's energy storage batteries: Based on real-time energy storage regulation data, determine the regulation power of the energy storage system at different times, use the regulation power to determine the average regulation power, and determine the remaining battery capacity of the reliable battery based on the change data of the battery capacity of the reliable battery. In combination with the average regulation power, determine the remaining regulation time of the reliable battery, and based on the remaining regulation time, determine whether to access the cloud to control the energy storage system's energy storage batteries.

[0050] Embodiment 1 To solve the above problem, according to one aspect of the present invention, Figure 1 As shown, a first aspect is provided. The present invention provides an intelligent battery management method based on cloud-edge collaboration, which specifically includes:

[0051] Based on the usage data of the energy storage system, determine the usage data of the energy storage battery of the energy storage system in different historical energy storage adjustment times, and when it is determined that the battery management difficulty of the energy storage system meets the requirements according to the usage data of the energy storage battery in different historical energy storage adjustment times, proceed to the next step;

[0052] Furthermore, the usage data of the energy storage system includes historical energy storage adjustment times of the energy storage system and energy storage adjustment data in different historical energy storage adjustment times.

[0053] Optionally, the usage data of the energy storage battery includes the usage count of the energy storage battery in different historical energy storage adjustment times.

[0054] It should be noted that if Figure 2 As shown in the figure, it is determined that the battery management difficulty of the energy storage system meets the requirements, including:

[0055] Determine the usage quantity of the energy storage batteries in different historical energy storage adjustment times based on the usage data of the energy storage batteries in different historical energy storage adjustment times;

[0056] Determine the complex adjustment times in the historical energy storage adjustment times by using the usage number of the energy storage battery;

[0057] Whether the battery management difficulty of the energy storage system meets the requirement is determined according to the number of complex adjustments.

[0058] It should be noted that the complex adjustment times are the historical energy storage adjustment times when the usage number of the energy storage battery is greater than the preset usage number.

[0059] Furthermore, when the number of complex adjustments of the energy storage system is greater than a preset number threshold, it is determined that the battery management difficulty of the energy storage system does not meet the requirements.

[0060] It is understandable that when the battery management difficulty of the energy storage system does not meet the requirements, the energy storage battery of the energy storage system is controlled and processed by accessing the cloud in all energy storage adjustment times.

[0061] Specifically, determine whether the battery management difficulty of the energy storage system meets the requirements, including:

[0062] Determine the usage quantity of the energy storage batteries in different historical energy storage adjustment times based on the usage data of the energy storage batteries in different historical energy storage adjustment times;

[0063] Determine the average value of the usage quantity of the energy storage battery at different historical energy storage adjustment times by using the usage quantity of the energy storage battery, and use it as the average usage quantity;

[0064] Determine whether the battery management difficulty of the energy storage system meets the requirement according to the average usage quantity.

[0065] Optionally, determining whether the battery management difficulty of the energy storage system meets the requirements includes:

[0066] S11 determines the usage quantity of the energy storage batteries in different historical energy storage adjustment times based on the usage data of the energy storage batteries in different historical energy storage adjustment times, and determines the weight coefficients of different historical energy storage adjustment times based on the accumulated usage time of different historical energy storage adjustment times;

[0067] S12 determines the usage duration corresponding to the usage quantity of the energy storage batteries in different historical energy storage adjustment times according to the usage data of the energy storage batteries in different historical energy storage adjustment times, and determines the energy storage adjustment complexity coefficient of different historical energy storage adjustment times according to the usage duration corresponding to the usage quantity of the energy storage batteries in different historical energy storage adjustment times;

[0068] S13 determines the adjustment difficulty coefficient of the energy storage system according to the weight coefficients of different historical energy storage adjustment times and the energy storage adjustment complexity coefficient, and determines whether the battery management difficulty of the energy storage system meets the requirements based on the adjustment difficulty coefficient.

[0069] Based on the usage cycle data of the energy storage battery in the energy storage system, determine the deviation of the charge and discharge power of the energy storage battery and other energy storage batteries in different usage cycles, and use the deviation to determine the problematic battery in the energy storage battery;

[0070] Furthermore, the usage cycle data includes the usage cycle number of the energy storage battery in the energy storage system and the charge and discharge power at different usage cycle numbers.

[0071] Specifically, the deviation of the charge and discharge power is determined according to the deviation of the charge and discharge power of the energy storage battery in the energy storage system at different usage cycles and the charge and discharge power of other energy storage batteries.

[0072] Specific examples, such as Figure 3 As shown, the method for determining the problematic battery in the energy storage battery is:

[0073] Based on the charge and discharge powers of different energy storage batteries in different use cycle numbers, the charge and discharge reference powers of the energy storage batteries in different use cycle numbers are determined;

[0074] Determine the deviation usage cycle number in the usage cycle number according to the deviation between the charge and discharge reference power of the energy storage battery in different usage cycle numbers and the charge and discharge power of the energy storage battery;

[0075] A problematic battery in the energy storage battery is determined based on the deviation using a cycle count.

[0076] Optionally, the charge and discharge reference power is an average value of the charge and discharge power corresponding to the charge and discharge power interval with the largest number of energy storage batteries in the number of usage cycles.

[0077] It can be understood that when the deviation between the charge and discharge reference power of the energy storage battery in the use cycle number and the charge and discharge power of the energy storage battery is greater than a preset power deviation, the use cycle number is determined to be the deviation use cycle number.

[0078] Furthermore, when the deviation usage cycle number of the energy storage battery is greater than a preset cycle number threshold, the energy storage battery is determined to be a problematic battery.

[0079] Optionally, the method for determining the problematic battery in the energy storage battery is:

[0080] Based on the charge and discharge powers of different energy storage batteries in different use cycles, determine the deviation between the charge and discharge powers of energy storage batteries in different use cycles and other energy storage batteries;

[0081] Determine the deviation energy storage battery in different usage cycle numbers according to the deviation amount of the charge and discharge power from other energy storage batteries, and determine the deviation usage cycle number in the usage cycle number by using the number of the deviation energy storage battery;

[0082] A problematic battery in the energy storage battery is determined based on the deviation using a cycle count.

[0083] Optionally, the method for determining the problematic battery in the energy storage battery is:

[0084] S21 determines the charge and discharge power intervals corresponding to different energy storage batteries in different use cycle numbers based on the charge and discharge powers of different energy storage batteries in different use cycle numbers, and determines the credibility coefficients of different charge and discharge power intervals by using the number of energy storage batteries in the charge and discharge power intervals;

[0085] S22 determines the credible power interval according to the credible coefficients of different charge and discharge power intervals, determines the charge and discharge reference power of different use cycles according to the average values ​​of the charge and discharge power intervals of different credible power intervals, and determines the deviation between the charge and discharge reference power of the energy storage battery in different use cycles and the charge and discharge power of the energy storage battery;

[0086] Optionally, the above step S22 includes the following contents:

[0087] S221 determines a credible power interval according to the credible coefficients of different charge and discharge power intervals, determines the charge and discharge reference power of different use cycles according to the average values ​​of the charge and discharge power intervals of different credible power intervals, and determines the deviation between the charge and discharge reference power of the energy storage battery in different use cycles and the charge and discharge power of the energy storage battery;

[0088] S222: when the deviations between the charge and discharge reference power of the energy storage battery and the charge and discharge power of the energy storage battery in different use cycle times are all within the preset deviation range, it is determined that the energy storage battery is not a problematic battery; when there is a use cycle time in which the deviation between the charge and discharge reference power of the energy storage battery and the charge and discharge power of the energy storage battery is not within the preset deviation range, the process proceeds to step S223;

[0089] S223 takes the number of use cycles whose deviation is not within the preset deviation interval as the number of deviation use cycles. When the number of deviation use cycles is greater than the preset deviation number, it is determined that the energy storage battery is a problematic battery. When the number of deviation use cycles is not greater than the preset deviation number and is within the preset deviation number interval, the process proceeds to step S224. When the number of deviation use cycles is not within the preset deviation number interval, the process proceeds to step S23.

[0090] S224 calculates the average value of the deviation amounts of different deviation usage cycle numbers with the deviation amounts of different deviation usage cycle numbers. When the average value of the deviation amounts of different deviation usage cycle numbers is greater than the preset deviation threshold, it is determined that the energy storage battery is a problem battery. When the average value of the deviation amounts of different deviation usage cycle numbers is not greater than the preset deviation threshold, proceed to step S23.

[0091] S23 determines the usage deviation coefficient of the energy storage battery based on the deviation amount of the charge and discharge power at different usage cycle times and the credibility coefficient, and uses the usage deviation coefficient to determine whether the energy storage battery is a problematic battery.

[0092] Optionally, the above step S23 includes the following contents:

[0093] S231 determines the sum of the credibility coefficients of different deviation use cycle times based on the credibility coefficients of different deviation use cycle times. When the sum of the credibility coefficients of different deviation use cycle times is greater than the preset credibility coefficient threshold, the energy storage battery is determined to be a problematic battery. When the sum of the credibility coefficients of different deviation use cycle times is not greater than the preset credibility coefficient threshold, the process proceeds to step S232.

[0094] S232 determines the cycle deviation coefficients of different use cycle times according to the deviation amount of the charge and discharge power of different use cycle times and the credibility coefficient. When there is no use cycle time with a cycle deviation coefficient greater than a preset cycle deviation coefficient threshold, it is determined that the energy storage battery is not a problem battery. When there is a use cycle time with a cycle deviation coefficient greater than the preset cycle deviation coefficient threshold, the process proceeds to step S233.

[0095] S233: When the number of cycles used when the cycle deviation coefficient is greater than the preset cycle deviation coefficient threshold is not within the preset cycle number interval, it is determined that the energy storage battery is a problematic battery; when the number of cycles used when the cycle deviation coefficient is greater than the preset cycle deviation coefficient threshold is within the preset cycle number interval, the process proceeds to step S234;

[0096] S234 determines the usage deviation coefficient of the energy storage battery based on the deviation amount of the charge and discharge power at different usage cycle times and the credibility coefficient, and uses the usage deviation coefficient to determine whether the energy storage battery is a problematic battery.

[0097] The problematic battery is removed as a reliable battery, and when it is determined that the operating reliability of the energy storage system meets the requirements based on the capacity of the reliable battery and the energy storage regulation needs in different historical energy storage adjustment times, real-time energy storage regulation data and change data on the battery capacity of the reliable battery are used to determine whether to connect to the cloud to control the energy storage battery of the energy storage system.

[0098] Furthermore, the energy storage regulation requirement includes the energy storage regulation amount and the energy storage regulation duration.

[0099] Specifically, Figure 4 As shown, determining that the operational reliability of the energy storage system meets the requirements specifically includes:

[0100] Determine energy storage adjustment amounts for different historical energy storage adjustment times based on energy storage adjustment requirements in different historical energy storage adjustment times;

[0101] Determining the capacity deviation adjustment number in the historical energy storage adjustment number according to the energy storage adjustment amounts of different historical energy storage adjustment numbers and the capacity of the reliable battery;

[0102] Based on the capacity deviation adjustment times, it is determined whether the operation reliability of the energy storage system meets the requirements.

[0103] Further, when the capacity deviation adjustment times are greater than a preset deviation adjustment times threshold, it is determined that the operation reliability of the energy storage system does not meet the requirements.

[0104] It should also be noted that the capacity deviation adjustment times are the historical energy storage adjustment times in which the deviation between the energy storage adjustment amount and the capacity of the reliable battery is not within a preset capacity deviation range.

[0105] Optionally, determining whether the operational reliability of the energy storage system meets the requirements specifically includes:

[0106] Determine the energy storage adjustment amounts of different historical energy storage adjustment times based on the energy storage adjustment requirements in different historical energy storage adjustment times, and when it is determined that there is no capacity deviation adjustment number in the historical energy storage adjustment times based on the energy storage adjustment amounts of different historical energy storage adjustment times and the capacity of the reliable battery, it is determined that the operation reliability of the energy storage system meets the requirements;

[0107] When there is a capacity deviation adjustment number, when the capacity deviation adjustment number is greater than a preset deviation adjustment number threshold:

[0108] Determining that the operational reliability of the energy storage system does not meet the requirements;

[0109] When the capacity deviation adjustment times are not greater than the preset deviation adjustment times threshold:

[0110] Determine the sum of the deviation amounts of different capacity deviation adjustment times by using the energy storage adjustment amounts of different capacity deviation adjustment times and the deviation amount of the capacity of the reliable battery; when the sum of the deviation amounts of different capacity deviation adjustment times does not meet the requirement, determine that the operation reliability of the energy storage system does not meet the requirement;

[0111] When the sum of the deviations of different capacity deviation adjustment times meets the requirements:

[0112] Determining different adjustment time weight coefficients of different capacity deviation adjustment times according to the adjustment time of different capacity deviation adjustment times, and when the sum of the adjustment time weight coefficients of different capacity deviation adjustment times does not meet the requirements, it is determined that the operation reliability of the energy storage system does not meet the requirements;

[0113] When the sum of the adjustment time weight coefficients of different capacity deviation adjustment times meets the requirements:

[0114] Based on the adjustment time weight coefficients and deviations of different capacity deviation adjustment times, the correction deviations of different capacity deviation adjustment times are determined. When the average values ​​of the correction deviations of different capacity deviation adjustment times are within the preset correction deviation range:

[0115] When the capacity deviation adjustment times are within a preset deviation adjustment times interval, it is determined that the operation reliability of the energy storage system meets the requirements;

[0116] When the average value of the corrected deviations of different capacity deviation adjustment times is not within the preset corrected deviation range or the capacity deviation adjustment times is not within the preset deviation adjustment times interval:

[0117] The operation reliability coefficient is determined based on the correction deviation amount of different capacity deviation adjustment times, and the operation reliability coefficient is used to determine whether the operation reliability of the energy storage system meets the requirements.

[0118] Furthermore, it is determined whether to access the cloud to control the energy storage battery of the energy storage system, including:

[0119] Based on the real-time energy storage regulation data, determine the regulation power of the energy storage system at different times, and use the regulation power to determine the average regulation power

[0120] Determining the remaining battery capacity of the reliable battery according to the change data of the battery capacity of the reliable battery, and determining the remaining regulation time of the reliable battery in combination with the average regulation power;

[0121] Based on the remaining adjustment time, it is determined whether to access the cloud to perform control processing of the energy storage battery of the energy storage system.

[0122] Specifically, determining whether to access the cloud to perform control processing of the energy storage battery of the energy storage system based on the remaining adjustment time specifically includes:

[0123] When the remaining adjustment time is greater than the preset adjustment time, it is determined not to connect to the cloud to perform control processing of the energy storage battery of the energy storage system.

[0124] Embodiment 2 In the second aspect, as Figure 5 As shown, the present invention provides a computer system, comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned intelligent battery management method based on cloud-edge collaboration when running the computer program.

[0125] Optionally, the above step S11 includes the following contents:

[0126] S111 determines the usage number of energy storage batteries in different historical energy storage adjustment times based on the usage data of energy storage batteries in different historical energy storage adjustment times. When the usage numbers of energy storage batteries in different historical energy storage adjustment times are all less than the preset usage numbers, it is determined that the battery management difficulty of the energy storage system meets the requirements. When there is a historical energy storage adjustment number in which the usage number of energy storage batteries is not less than the preset usage number, the process proceeds to step S112.

[0127] S112: the number of historical energy storage adjustments when the number of energy storage batteries used is not less than the preset number of uses is taken as the number of complex adjustments. When the number of complex adjustments is greater than the preset number threshold, it is determined that the battery management difficulty of the energy storage system does not meet the requirements. When the number of complex adjustments is not greater than the preset number threshold, the process proceeds to step S113.

[0128] S113 determines the weight coefficients of different historical energy storage adjustment times based on the cumulative usage time of different historical energy storage adjustment times. When the sum of the weight coefficients of the complex adjustment times does not meet the requirements, it is determined that the battery management difficulty of the energy storage system does not meet the requirements. When the sum of the weight coefficients of the complex adjustment times meets the requirements, proceed to step S12.

[0129] Optionally, the above step S12 includes the following contents:

[0130] S121 determines the usage duration corresponding to the usage quantity of the energy storage batteries in different historical energy storage adjustment times according to the usage data of the energy storage batteries in different historical energy storage adjustment times, and determines the energy storage adjustment complexity coefficient of different historical energy storage adjustment times according to the usage duration corresponding to the usage quantity of the energy storage batteries in different historical energy storage adjustment times;

[0131] S122: When the energy storage adjustment complexity coefficient is greater than the historical energy storage adjustment times of the preset complexity coefficient, the process proceeds to step S123; when the energy storage adjustment complexity coefficients of different historical energy storage adjustment times are not greater than the preset complexity coefficient, it is determined that the battery management difficulty of the energy storage system meets the requirements;

[0132] S123 uses the historical energy storage adjustment times for which the energy storage adjustment complexity coefficient is greater than the preset complexity coefficient as the screening complex adjustment times. When the screening complex adjustment times are greater than the preset complex adjustment times threshold, it is determined that the battery management difficulty of the energy storage system does not meet the requirements. When the screening complex adjustment times are not greater than the preset complex adjustment times threshold, proceed to step S13.

[0133] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0134] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0135] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. An intelligent battery management method based on cloud-edge collaboration, characterized in that: Specifically include: Based on the usage data of the energy storage system, determine the usage data of the energy storage battery of the energy storage system in different historical energy storage adjustment times, and when it is determined that the battery management difficulty of the energy storage system meets the requirements according to the usage data of the energy storage battery in different historical energy storage adjustment times, proceed to the next step; Based on the usage cycle data of the energy storage battery in the energy storage system, determine the deviation of the charge and discharge power of the energy storage battery and other energy storage batteries in different usage cycles, and use the deviation to determine the problematic battery in the energy storage battery; Remove the problematic battery as a reliable battery, and determine whether to access the cloud to control the energy storage battery of the energy storage system by using the capacity of the reliable battery and the energy storage regulation requirements in different historical energy storage regulation times to determine whether the operation reliability of the energy storage system meets the requirements, using the real-time energy storage regulation data and the change data of the battery capacity of the reliable battery; Determine that the battery management difficulty of the energy storage system meets the requirements, including: Determine the usage quantity of the energy storage batteries in different historical energy storage adjustment times based on the usage data of the energy storage batteries in different historical energy storage adjustment times; Determine the complex adjustment times in the historical energy storage adjustment times by using the usage number of the energy storage battery; Determining whether the battery management difficulty of the energy storage system meets the requirements according to the number of complex adjustments; The complex adjustment times are the historical energy storage adjustment times when the usage of the energy storage battery is greater than the preset usage number; When the number of complex adjustments of the energy storage system is greater than a preset number threshold, it is determined that the battery management difficulty of the energy storage system does not meet the requirements.

2. The intelligent battery management method based on cloud-edge collaboration as claimed in claim 1, characterized in that: The usage data of the energy storage system includes the historical energy storage adjustment times of the energy storage system and the energy storage adjustment data in different historical energy storage adjustment times.

3. The intelligent battery management method based on cloud-edge collaboration as claimed in claim 1, characterized in that: The usage data of the energy storage battery includes the usage count of the energy storage battery in different historical energy storage adjustment times.

4. The intelligent battery management method based on cloud-edge collaboration as claimed in claim 1, characterized in that: When the battery management difficulty of the energy storage system does not meet the requirements, the energy storage battery of the energy storage system is controlled and processed by accessing the cloud in all energy storage adjustment times.

5. The intelligent battery management method based on cloud-edge collaboration as claimed in claim 1, characterized in that: The usage cycle data includes the usage cycle number of the energy storage battery in the energy storage system and the charge and discharge power at different usage cycle numbers.

6. The intelligent battery management method based on cloud-edge collaboration as claimed in claim 1, characterized in that: The deviation of the charge and discharge power is determined according to the deviation of the charge and discharge power of the energy storage battery in the energy storage system at different usage cycles and the charge and discharge power of other energy storage batteries.

7. The intelligent battery management method based on cloud-edge collaboration as claimed in claim 1, characterized in that: Determine whether to access the cloud to control the energy storage system's energy storage batteries, including: Based on the real-time energy storage regulation data, determine the regulation power of the energy storage system at different times, and use the regulation power to determine the average regulation power Determining the remaining battery capacity of the reliable battery according to the change data of the battery capacity of the reliable battery, and determining the remaining regulation time of the reliable battery in combination with the average regulation power; Based on the remaining adjustment time, it is determined whether to access the cloud to perform control processing of the energy storage battery of the energy storage system.

8. A computer system comprising: A memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, characterized in that when the processor runs the computer program, an intelligent battery management method based on cloud-edge collaboration as described in any one of claims 1-7 is executed.

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