Equipment point location data management method and system in energy storage system

Abstract

The invention relates to an equipment point location data management method and system, and the method comprises the steps: writing data into one of N caches with different importance levels through a comparison result obtained through the sequential comparison of a difference value between data collection time and current system time and N-1 aging node values, and enabling the smaller the difference value, the higher the priority of the cache with the higher writing importance level, and the higher the priority of the cache with the higher writing importance level. Therefore, the data can be cached and stored in a layered manner according to the data acquisition time. Once new data is written into the cache, the service scene unit is notified, and all service scenes related to the data can be found. When the newly written data meets all the use constraint conditions of at least one service scene, the newly written data is applied to perform service calculation on the service scenes meeting all the use constraint conditions to drive the service scene data to be updated, so that data with different timeliness can be acquired and applied according to different service scenes; the timeliness is high, and point location data aggregation can be realized according to different service scenes.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage system data management, and in particular to a method and system for managing equipment point data in an energy storage system. Background Art

[0002] The energy storage system needs to collect point data from BMS, PCS, fire protection, air conditioning, cameras and other equipment. The point data of each device will be stored in different database tables. The energy storage system updates the latest collected point data to the real-time table or cache as real-time data, and also stores the data in the historical database table as historical data. When the relevant point data is used in the business scenario, the point data will be queried from the corresponding database table, and then directly displayed or processed and calculated according to the scenario requirements. Real-time data is generally used for business scenarios that display the latest dynamic data, such as dynamic data on the large screen of the configuration diagram. Historical data is generally used for data statistics, such as the display of line charts by year, month and day.

[0003] However, the traditional equipment point data management method lacks timeliness and personalized push for different business scenarios due to the mechanism of point data push. First, the point data required by the business scenario is passively obtained from the cache or library table, and the point data is not actively pushed to the relevant business scenario when it changes in real time. Second, the point data push method is to set a fixed timeliness threshold, and there is no personalized timeliness push plan for different business scenarios, and it is impossible to obtain data with different timeliness according to specific business scenarios. Summary of the invention

[0004] Based on this, it is necessary to provide a method and system for managing device point data in an energy storage system to address the problems of lack of timeliness and personalized push for different business scenarios due to the mechanism of point data push in traditional energy storage systems.

[0005] On the one hand, the present application provides a method for managing device point data in an energy storage system, the method for managing device point data in the energy storage system comprising: Determine whether a piece of device point data is received; If a piece of equipment point data is received, the equipment point data is obtained, and the equipment point information attached to the equipment point data is simultaneously obtained; Read the data collection time in the device point information; Obtain the difference between the data collection time and the current system time, and write the device point data into one of N caches of different importance levels according to the comparison result of the difference between the data collection time and the current system time and N-1 time-effect node values ​​in sequence; the smaller the difference between the data collection time and the current system time, the higher the priority of writing into the cache with a higher importance level; N is a positive integer; As time goes by, the control device point data flows from the cache with a higher importance level to the cache with a lower importance level; Determine whether there is at least one cache into which new device point data is written; If there is at least one cache into which new device point data is written, the business scenario rule table is retrieved; Select a newly written device point data; Determine whether the newly written equipment point data meets all usage constraints of at least one business scenario in the business scenario rule table; If the newly written device point data meets all usage constraints of at least one business scenario in the business scenario rule table, the newly written device point data is applied to perform business calculations in the business scenario that meets all usage constraints; If the newly written equipment point data does not meet all the usage constraints of at least one business scenario in the business scenario rule table, an alarm message is issued; Return to the selection of a newly written device point data until all the newly written device point data are processed.

[0006] On the other hand, the present application also provides an equipment point data management system, including: A management unit, used to execute the device point data management method in the energy storage system mentioned above; A storage unit, connected to the management unit, including a plurality of caches of different importance levels; The business scenario unit is connected to the management unit.

[0007] The present application relates to a method and system for managing device point data. The data collection time of the received device point data is read by a management unit. The device point data is written into one of N caches of different importance levels through the comparison result of the difference between the data collection time and the current system time and N-1 time node values ​​in sequence. The smaller the difference, the higher the priority of writing into the cache with a higher importance level. In this way, the device point data can be cached and stored in layers according to the early or late data collection time. Once the cache writes new data, the business scenario unit is notified to find all business scenarios related to the device point data. When the newly written device point data meets all the usage constraints of at least one business scenario in the business scenario rule table, the newly written device point data is applied to perform business calculations on the business scenarios that meet all the usage constraints to drive the business scenario data update. In this way, it is possible to obtain and apply data of different timeliness according to different business scenarios. Not only is the timeliness strong, but also point data aggregation can be achieved according to different business scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 This is a flowchart of steps S100 to S200 in a method for managing device point data in an energy storage system provided in one embodiment of the present application.

[0009] Figure 2 This is a flowchart of S200 to S370 in a method for managing device point data in an energy storage system provided in one embodiment of the present application.

[0010] Figure 3 A schematic diagram of the structural framework of a device point data management system in an energy storage system provided in one embodiment of the present application.

[0011] Figure 4 A schematic diagram of the structural framework of a device point data management system in an energy storage system provided in yet another embodiment of the present application. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solution and advantages of this application more clear, the following is a further detailed description of this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain this application and are not used to limit this application.

[0013] The present application provides a method for managing device point data in an energy storage system. It should be noted that the method for managing device point data in an energy storage system provided by the present application is applicable to the management of point data of any type of device in the energy storage system.

[0014] In addition, the device point data management method in the energy storage system provided by the present application does not limit its execution subject. Optionally, the execution subject of the device point data management method in the energy storage system provided by the present application can be a device point data management system. Specifically, the execution subject of the device point data management method in the energy storage system provided by the present application can be a management unit in the device point data management system.

[0015] like Figure 1 and Figure 2 As shown, in one embodiment of the present application, the device point data management method includes: S110, determining whether a piece of equipment point data is received.

[0016] S120: If a piece of equipment point data is received, the equipment point data is acquired, and equipment point information attached to the equipment point data is synchronously acquired.

[0017] S130, reading the data collection time in the device point information.

[0018] S140, obtaining the difference between the data collection time and the current system time, and writing the device point data into one of N caches of different importance levels according to the comparison result of the difference between the data collection time and the current system time and N-1 time-effect node values ​​in sequence. The smaller the difference between the data collection time and the current system time, the higher the priority of writing into the cache of higher importance level. N is a positive integer.

[0019] S200: As time goes by, the control device point data flows from a cache with a higher importance level to a cache with a lower importance level.

[0020] S310, determining whether there is at least one cache into which new device point data is written.

[0021] S320: If there is at least one cache into which new device point data is written, the business scenario rule table is retrieved.

[0022] S330, selecting a newly written device point data.

[0023] S340, determining whether the newly written equipment point data satisfies all usage constraints of at least one business scenario in the business scenario rule table.

[0024] S350: If the newly written device point data satisfies all usage constraints of at least one business scenario in the business scenario rule table, the newly written device point data is applied to perform business calculations in the business scenario that satisfies all usage constraints.

[0025] S360: If the newly written device point data does not satisfy all usage constraints of at least one business scenario in the business scenario rule table, an alarm message is issued.

[0026] S370, returning to S330, that is, returning to the selection of a newly written device point data, until all the newly written device point data are processed.

[0027] Specifically, the equipment point data management system is connected in communication with the data acquisition device (not shown in the figure) provided on each device. After the data acquisition device acquires the point data of the equipment, it will be sent to the equipment point data management system for processing. The equipment point data management system first executes S100, that is, it determines whether the equipment point data is received normally. The equipment point data management system can also be connected in communication with a host computer (not shown in the figure). If it cannot be received, the possible reason is that the equipment point data management system and the data acquisition device do not communicate well, or there may be an abnormality in the data. At this time, an alarm message is sent to the host computer.

[0028] The equipment may include BMS (battery management system, BMS, battery management system) equipment, PCS (Power Conversion System, PCS, energy storage inverter system) equipment, fire fighting equipment, air conditioning equipment, camera equipment, DIDO equipment, temperature equipment, adaptability equipment, etc.

[0029] The point data of PCS equipment may include current, voltage, power, cumulative charge amount, cumulative discharge amount, etc.

[0030] The point data of the energy storage unit (such as the battery stack, RACK) can include SOC. The point data of the M meter device (METER) can include the accumulated charge amount and the accumulated discharge amount.

[0031] Optionally, S110 determines whether a piece of equipment point data is received, including: S111, receiving a piece of equipment point data sent by a data acquisition device.

[0032] S112, filtering the equipment point data to determine whether the equipment point data has passed the filtering process.

[0033] S113: If the device point data passes the filtering process, it is confirmed that the device point data has been received.

[0034] S114, if the device point data fails to pass the filtering process, it is not considered that the device point data is received, and the device point data that fails to pass the filtering process is deleted.

[0035] Among them, the filtering process of the equipment point data in S112 can be specifically performed through the filtering rule table. The filtering rule table is shown in Table 1. For example, the filtering threshold in the power point of PCS1 in Table 1 is set to "X>1000 ||X<-1000", where X in the expression represents the currently collected equipment point data. If the data meets the filtering processing conditions, it will be filtered, that is, deleted. Then only the data within -1000 to 1000 will be retained. This can prevent a sudden curve from appearing on a line chart. This filtered data will be saved as abnormal data and an alarm message will be generated, which can be used for fault analysis.

[0036] Table 1 - Filtering rules table In one embodiment of the present application, a point template is set for each point of each device type. The point template defines and classifies the device point data by attaching a device point label to the device point data, so as to distinguish the device point data from each other. The device point label includes two pieces of information, device number information and point number information. The uniqueness of the device point data is determined by the device number + point number. For example, the power point of device PCS1 in Table 1 is defined as "PCS1.TAG000003", "PCS1" is the device number information, and "TAG000003" is the point number information. A point refers to a piece of data collected by the device, such as voltage and current corresponding to two different points respectively.

[0037] The meaning of S340 to S360 is that when a certain level of cache changes, the business scenario unit related to the corresponding level will be notified to drive the business scenario data update. By monitoring the changes in the point cache of Redis, the point cache change message will be published to the MQ queue. After the business scenario unit subscribes to the cache change message, it will update the data according to the scenario rule agreement. The scenario rules define the constraints of the cache level, point priority principle, scenario alarm threshold, whether the over-alarm threshold is available, and the business layer filtering threshold. Only data that meets all the constraints of a business scenario will participate in the business scenario calculation. Explain in conjunction with the constraints of the business scenario configured in Table 2: Table 2-Business scenario constraint definition table Cache level: refers to the point data changes that need to meet the cache level to trigger business scenario calculation. For example, "Level 1, Level 2" means that one of the conditions for triggering business scenario calculation is met when data is written or updated to the Level 1 cache or Level 2 cache.

[0038] Point priority principle: refers to which one should be used first when two different equipment points can participate in the scene business calculation. For example, "METER1.TAG00125 > PCS1.TAG000029" means that in the energy storage charging and discharging scenario, the point used to calculate the power consumption is calculated with the equipment point data of the meter device first. If the meter device is not installed, the equipment point data of the PCS device can be used instead.

[0039] Scenario alarm threshold and whether the over-alarm threshold is available: These two constraints act in combination. When the point data exceeds the scenario alarm threshold and "Whether the over-alarm threshold is available" is set to "Yes", the point data also meets one of the conditions for triggering the business scenario. As long as the scenario alarm threshold is exceeded, an alarm will be generated.

[0040] Secondary business layer filtering threshold: Those that meet the expression will be filtered out, indicating that the conditions for triggering the business scenario are not met. For example, "X>1000" means that when the point data is greater than 1000, the business scenario calculation cannot be triggered and an alarm will be generated. It can be understood that S111-S114 is the first filtering, and the filtering in Table 2 is the second filtering (referred to as secondary filtering).

[0041] Only when all conditions in the scenario rules are met at the same time can the business scenario calculation be triggered and the business scenario data be updated.

[0042] In this embodiment, the data collection time of the received device point data is read by the management unit, and the device point data is written into one of N caches of different importance levels through the comparison result of the difference between the data collection time and the current system time and the N-1 time node values ​​in sequence. The smaller the difference, the higher the priority of writing into the cache with a higher importance level, so that the device point data can be cached and stored in layers according to the early or late data collection time. Once the cache writes new data, the business scenario unit is notified to find all business scenarios related to the device point data. When the newly written device point data meets all the usage constraints of at least one business scenario in the business scenario rule table, the newly written device point data is applied to perform business calculations on the business scenarios that meet all the usage constraints to drive the business scenario data update, so that data with different timeliness can be obtained and applied according to different business scenarios. Not only is the timeliness strong, but also point data aggregation can be achieved according to different business scenarios.

[0043] In one embodiment of the present application, S140 includes obtaining the difference between the data collection time and the current system time, and writing the device point data into one of N caches of different importance levels according to the comparison result of the difference between the data collection time and the current system time and N-1 timeliness node values ​​in sequence, including: S141, determining whether the difference between the data collection time and the current system time is greater than 0.

[0044] S142: If the difference between the data collection time and the current system time is greater than 0, further determine whether the difference between the data collection time and the current system time is less than the first-level timeliness node value.

[0045] S143: If the difference between the data collection time and the current system time is less than the first-level timeliness node value, the device point data is written into the first-level cache.

[0046] S144, if the difference between the data collection time and the current system time is greater than or equal to the first-level timeliness node value, further determine whether the difference between the data collection time and the current system time is less than the second-level timeliness node value.

[0047] S145, if the difference between the data collection time and the current system time is less than the secondary timeliness node value, the device point data is written into the secondary cache.

[0048] S146: If the difference between the data collection time and the current system time is greater than or equal to the secondary timeliness node value, the device point data is written into the third-level cache.

[0049] Specifically, if the difference between the data collection time and the current system time is less than 0 or equal to 0, the collected device point data is considered to be abnormal data. The possible reason is that the current system time of the server is recorded incorrectly, or the collection program is wrong, and an alarm message is sent to the host computer.

[0050] Optionally, the primary timeliness node value and the secondary timeliness node value can be comprehensively determined based on different equipment types and different point types. That is to say, the primary timeliness node value and the secondary timeliness node value are determined based on two factors, one factor is the type of equipment, and the other factor is the type of point. This is because different points of different equipment have different timeliness requirements. Some equipment points have higher requirements for data timeliness, while some equipment points have lower requirements for data timeliness.

[0051] Optionally, the primary aging node value and the secondary aging node value may be set according to a fixed multiple of the acquisition frequency of the corresponding equipment type and point type.

[0052] Optionally, the primary timeliness node value is set to twice the time period consumed by collecting data once at the collection frequency of the point data of the corresponding device type and point type, and the secondary timeliness node value is set to six times the time period consumed by collecting data once at the collection frequency of the point data of the corresponding device type and point type. For example, if the collection frequency of the accumulated charge of the PCS1 device is 30 seconds / time, then the primary timeliness node value can be set to 60 seconds, and the secondary timeliness node value can be set to 180 seconds.

[0053] Optionally, when executing S142 to determine whether the difference between the data collection time and the current system time is less than the first-level aging node value, and when executing S144 to determine whether the difference between the data collection time and the current system time is less than the second-level aging node value, the equipment aging node value definition table stored locally in the equipment point data management system can be called to obtain the first-level aging node value and the second-level aging node value of different points of different equipment. The equipment aging node value definition table is shown in Table 3.

[0054] Table 3- Equipment aging node value definition table Taking the cumulative charging capacity of the PCS1 device as an example, if the data collection time of a piece of cumulative charging capacity data of a PCS1 device is 09:05:05 on March 14, 2025, and the current system time is 09:05:35 on March 14, 2025, the difference between the data collection time and the current system time is 30 seconds. From Table 3, it is known that the first-level timeliness node value is 60 seconds and the second-level timeliness node value is 180 seconds. It can be seen that 0-60 seconds will be written into the first-level cache, 60-180 seconds will be written into the second-level cache, and more than 180 seconds will be written into the third-level cache. Then 30 seconds falls within the range of 0-60 seconds, so the cumulative charging capacity data of the PCS1 device is written into the first-level cache.

[0055] When executing S142 to write the device point data into the first-level cache, S145S to write the device point data into the second-level cache, and S146 to write the device point data into the third-level cache, the write action is to write when there is no data corresponding to the device point tag in the cache, or to overwrite (i.e., update) when there is data corresponding to the device point tag in the cache. Overwriting (i.e., updating) when there is data corresponding to the device point tag in the cache means that when there is data corresponding to the device point tag in the same cache, only the device point data with the latest data collection is retained. For example, when writing a PSC1.TAG000001 data with a data collection time of 09:05:05 on March 14, 2025 into the first-level cache, it is found that there is another PSC1.TAG000001 data with a data collection time of 09:04:05 on March 14, 2025 in the first-level cache. Then, the PSC1.TAG000001 data with a data collection time of 09:05:05 on March 14, 2025 is retained, and the PSC1.TAG000001 data with a data collection time of 09:04:05 on March 14, 2025 is deleted. This is "overwrite".

[0056] That is, each cache of different importance levels can store at most one piece of data of the same device point tag. For example, the first-level cache can have a piece of PSC1.TAG000001 data with a data collection time of 09:04:05 on March 14, 2025. At the same time, the second-level cache can have a piece of PSC1.TAG000001 data with a data collection time of 09:06:05 on March 14, 2025. The third-level cache can have a piece of PSC1.TAG000001 data with a data collection time of 09:08:05 on March 14, 2025. However, each cache cannot have two pieces of PSC1.TAG000001 data at the same time.

[0057] While writing to the cache, the storage structure table can also be updated. The storage structure table is stored locally in the equipment point data management system. The storage structure table is shown in Table 4.

[0058] Table 4 - Storage structure table In this embodiment, the data of equipment points are managed in layers according to timeliness. The point data cache is divided into three caches with different importance levels: level one cache, level two cache and level three cache through two levels of timeliness. After the equipment point data is collected, it will be stored in the cache of the corresponding level according to timeliness. This makes it convenient for each subsequent equipment point data to flow between caches of different importance levels according to data timeliness rules.

[0059] In one embodiment of the present application, after determining whether there is at least one cache into which new device point data is written, the method further includes: S381, if there is at least one cache into which new device location data is written, an expiration time tag matching the importance level of the cache is generated, so that the expiration time of the device location data is different for different importance levels of the cache.

[0060] S382, determining whether the cache to which the newly written device point data belongs is the cache with the lowest importance level.

[0061] S383: If the cache to which the newly written device point data belongs is not the cache with the lowest importance level, an expiration time tag is added to the newly written device point data.

[0062] Specifically, the expiration time tag and the timeliness node value can define the point data expiration time TX of a device point data. Since the data point data is stored in caches of different importance levels, the point data expiration time TX of the data point data in different caches is also different.

[0063] In this embodiment, the reason for executing S382 is that the cache with the lowest importance level does not set the point data expiration time TX, so the device point data newly written into the cache with the lowest importance level does not need to be attached with an expiration time tag. Taking the first-level cache, the second-level cache, and the third-level cache as examples, the first-level cache has the highest importance level, the second-level cache has the second highest importance level, and the third-level cache has the lowest importance level. Therefore, the device point data newly written into the third-level cache does not have an expiration time tag attached, and the device point data newly written into the second-level cache and the first-level cache are attached with an expiration time tag.

[0064] In this embodiment, when a new device point data is written to any cache that is not the cache with the lowest importance level, an expiration time tag is added to the newly written device point data. The expiration time tag can be used to monitor the expiration status of the device point data, so that the device point data can be controlled to flow from a cache with a higher importance level to a cache with a lower importance level over time.

[0065] In one embodiment of the present application, the value of the expiration time tag is equal to the difference between the aging node value corresponding to the cache importance level and the data collection time of the newly written device point data.

[0066] Specifically, for example, when the first-level cached device point data is written or updated, the point data expiration time TX of the device point data will be set at the same time, TX = first-level aging node value - data collection time of the device point data, indicating that the device point data written or updated this time will be invalid after the TX time.

[0067] In this embodiment, by setting the value of the expiration time label equal to the difference between the aging node value corresponding to the cache importance level and the data collection time of the newly written device point data, the sum of the expiration time and the data collection time of the device point data is exactly the first-level aging node value, thereby ensuring that the device point data can flow naturally in caches of different importance levels.

[0068] In one embodiment of the present application, S200 includes: S210, each cache traverses all the device point data stored in itself, and determines whether there is at least one device point data failure based on the failure time tag of the device point data.

[0069] S220: If at least one device point data has a failure phenomenon, obtain all device point data that have a failure phenomenon.

[0070] S230, selecting a device point data that produces a failure phenomenon.

[0071] S240, determining whether the cache to which the device point data that has failed belongs is the cache with the lowest importance level.

[0072] S250, if the cache to which the equipment point data causing the failure phenomenon belongs is not the cache with the lowest importance level, the equipment point data causing the failure phenomenon will be deleted from the current cache, and the equipment point data causing the failure phenomenon will be transferred to the next level cache with a lower importance level, and return to S230 until all the equipment point data causing the failure phenomenon are processed, that is, one equipment point data causing the failure phenomenon is selected until all the equipment point data causing the failure phenomenon are processed.

[0073] Specifically, the significance of executing S240 is that if the cache to which the device point data with the failure phenomenon belongs is the cache with the lowest importance level, there is no need to transfer the data, and the data will always be retained in the cache with the lowest importance level. If the cache to which the device point data with the failure phenomenon belongs is not the cache with the lowest importance level, the data will be transferred.

[0074] S250 is a specific step of the flow. Optionally, the expiration time can be monitored through the redis function. The data flow of S250 is realized based on the SETEX command of Redis, for example: "SETEX LEVEL1.PCS1.TAG000001 5100.21,1728442665", which means writing the point "PCS1.TAG000001" data and the acquisition time into the first-level cache, and setting the device point data expiration time to 5 seconds. Redis will automatically clear the device point data in the first-level cache after 5 seconds. The energy storage system can obtain the device point data cleared by the first-level cache by listening to the cache expiration notification of Redis. Specifically, by inheriting the Key Expiration Event Message Listener class in the redis source code, the expiration notification and the expired device point data can be obtained.

[0075] In this embodiment, by judging whether a failure phenomenon occurs based on the expiration time label of the device point data, the device point data where the failure phenomenon occurs is deleted from the current cache, and the device point data where the failure phenomenon occurs is transferred to the next level of cache with a lower importance level, the natural flow of control device point data from a cache with a higher importance level to a cache with a lower importance level can be achieved.

[0076] In one embodiment of the present application, S250 includes, that is, deleting the device point data that generates the failure phenomenon in the current cache, transferring the device point data that generates the failure phenomenon to the next level of cache with a lower importance level, returning to selecting a device point data that generates the failure phenomenon until all the device point data that generates the failure phenomenon are processed, including: S251, obtaining the equipment point label of the equipment point data that caused the failure phenomenon.

[0077] S252, obtaining information on whether there is device location data with the same device location tag in a cache at a lower level of importance than the current cache.

[0078] S253, if the device point data with the same device point label does not exist in the cache with a lower importance level at the next level of the current cache, the device point data that causes the failure phenomenon is deleted from the current cache, and the device point data that causes the failure phenomenon is transferred to the cache with a lower importance level at the next level of the current cache, and returns to S230, that is, returns the selected device point data that causes the failure phenomenon.

[0079] S254a, if the device point data with the same device point tag exists in the cache of the next level with a lower importance level of the current cache, the data collection time of the device point data that causes the failure phenomenon in the current cache is obtained, and the data collection time is used as the first collection time.

[0080] S254b, obtaining the data collection time of the device point data with the same device point tag in the next-level cache with a lower importance level of the current cache, and using the data collection time as the second collection time.

[0081] S254c, determining whether the first collection time is later than the second collection time.

[0082] S254d, if the first acquisition time is later than the second acquisition time, the device point data causing the failure phenomenon is deleted from the current cache, and the device point data causing the failure phenomenon is transferred to the next level of cache with a lower importance level of the current cache, and returns to S230, that is, returns the selected device point data causing the failure phenomenon.

[0083] S254e, if the first acquisition time is earlier than the second acquisition time, the device point data causing the failure phenomenon is deleted from the current cache, and the process returns to S230, that is, the process of selecting a device point data causing the failure phenomenon is returned.

[0084] Specifically, the device point data with the same device point tag in S252 refers to two different device point data of the same point of the same type of device appearing simultaneously in different caches, and both of the two data have the same device point tag.

[0085] If the device point data with the same device point tag does not exist in the cache of the next level with a lower importance level, the device point data causing the failure phenomenon is directly transferred to the cache of the next level with a lower importance level of the current cache.

[0086] If the device point data with the same device point tag exists in the cache of the next level with a lower importance level, the collection time of both is required, and the one with a later collection time is retained and migrated to the cache of the next level with a lower importance level.

[0087] In this embodiment, when the invalid data is transferred to the next level cache with a higher importance, when there is a data conflict with the same device point label, the data with a later collection time is retained, so that even if the device point data is invalid, it can be ensured that the data retained in each cache is the best quality data.

[0088] In one embodiment of the present application, after S240, that is, after determining whether the cache to which the device point data generating the failure phenomenon belongs is the cache with the lowest importance level, the following step is further included: S261: If the cache to which the device point data causing the failure phenomenon belongs is the cache with the lowest importance level, determine whether there is other device point data with the same device point tag in the current cache except the device point data causing the failure phenomenon.

[0089] S262, if there are other device point data with the same device point label in the current cache except for the device point data that has failed, the device point data with the latest data collection time under the device point label will be retained, and the remaining device point data except for the device point data with the latest data collection time under the device point label will be deleted.

[0090] Specifically, data in the cache with the lowest importance level will never become invalid and will always be retained.

[0091] Optionally, the invalid data retained in the cache with the lowest importance level may be marked as offline data, and displayed in red or other colors different from the data in other caches during data analysis.

[0092] In this embodiment, by setting the data in the cache with the lowest importance level to never become invalid, the integrity of the data in the cache is guaranteed. Without losing any data, it can be ensured that the cache with a higher importance level will not retain invalid data, making it more lightweight.

[0093] In one embodiment of the present application, it also includes: S410: Send a request to the cache for retrieving data.

[0094] S420: Select a device point tag.

[0095] S430, taking the current system time as the current snapshot time, obtaining the device point data of the device point tag in the cache that is closest to the current system time and storing it in the troubleshooting database as the snapshot data of the current snapshot time.

[0096] S440, returning to S420 until all device point tags are processed, that is, returning to the step of selecting a device point tag until all device point tags are processed.

[0097] S450, after a preset time period, returning to the step of sending a request to the cache to retrieve data.

[0098] Specifically, when troubleshooting, the system needs to restore the historical data of all equipment points for a period of time before and after a certain fault time point to facilitate problem analysis and location. Since the acquisition time of each device in the energy storage system is not fixed, it is necessary to cache all point data at a certain moment through the device point cache to form a point data snapshot at this time point for subsequent troubleshooting.

[0099] The preset time period is set to set the snapshot frequency, reduce computing pressure, and troubleshoot database storage pressure.

[0100] In this embodiment, by taking the current system time as the current snapshot moment, obtaining the device point data of the device point tag in the cache that is closest to the current system time and storing it in the troubleshooting database as the snapshot data of the current snapshot moment, all device point data at the current snapshot moment can be retained to facilitate subsequent troubleshooting.

[0101] In one embodiment of the present application, S430 includes, that is, taking the current system time as the current snapshot time, obtaining the device point data of the device point tag in the cache closest to the current system time as the snapshot data of the current snapshot time and storing it in the investigation database, including: S431, traverse multiple caches of different importance levels, and obtain the device point data of the device point tag closest to the current system time in each cache of the importance level. S432, determine whether the obtained device point data is obtained from the cache of the lowest importance level.

[0102] S433: If the acquired device point data is acquired from the cache with the lowest importance level, an offline data tag is added to the acquired device point data.

[0103] S434: If the acquired device point data is not acquired from the cache with the lowest importance level, an online data tag is added to the acquired device point data.

[0104] S435, storing the device point data with the online data tag and / or the offline data tag as the snapshot data at the current snapshot time in the troubleshooting database.

[0105] Specifically, while the equipment point data is stored in the cache, a snapshot of the equipment point data is also taken and stored in the troubleshooting database.

[0106] In this embodiment, since there is only one piece of device point data under one device point tag in each cache, the device point data of the snapshot in each cache is unique. However, each cache in the caches of different importance levels may have device point data under the same device point tag, so it can be understood as unique within the cache, but not unique between caches. For example, in the architecture of the first-level cache, the second-level cache, and the third-level cache, the snapshot data at the current snapshot moment may be 1, 2, or 3 (one for each of the three caches), but not 4.

[0107] In this embodiment, the addition of an online data tag may indicate that the device location data is reliable, and the addition of an offline data tag may indicate that the device location data is unreliable.

[0108] It should be noted that all the warning messages and alarm information mentioned in this application can be displayed on the display interface or monitoring interface of the equipment point data management system, and can also be sent to the host computer to realize the reporting function.

[0109] The present application also provides an equipment point data management system.

[0110] For the sake of brevity, all units or devices mentioned in the present application are numbered in the embodiment of the equipment point data management system, and are not numbered in the embodiment of the aforementioned equipment point data management method.

[0111] like Figure 3 As shown, in one embodiment of the present application, the equipment point data management system includes a management unit 100, a storage unit 200 and a business scenario unit 300.

[0112] Specifically, the management unit 100 is used to execute the device point data management method in the energy storage system as mentioned in at least one of the aforementioned embodiments.

[0113] The storage unit 200 is connected to the management unit 100. The storage unit 200 includes a plurality of caches 210 of different importance levels. The business scenario unit 300 is connected to the management unit 100.

[0114] like Figure 4 As shown, in one embodiment of the present application, the storage unit 200 includes a level 1 cache 210, a level 2 cache 220 and a level 3 cache 230. The importance level of the level 1 cache 210> the importance level of the level 2 cache 220> the importance level of the level 3 cache 230.

[0115] The cache may be a part of the local storage unit 200, and the cache may be a redis cache, which is a third-party open source cache middleware. Its data is in the computer memory, and the program can read and write data from it very efficiently.

[0116] The technical features of the above-described embodiments may be arbitrarily combined, and the execution order of the method steps is not limited. To make the description concise, not all possible combinations of the technical features in the above-described 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.

[0117] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for managing equipment point data in an energy storage system, characterized in that: The method comprises: Determine whether a piece of device point data is received; If a piece of equipment point data is received, the equipment point data is obtained, and the equipment point information attached to the equipment point data is simultaneously obtained; Read the data collection time in the device point information; Obtain the difference between the data collection time and the current system time, and write the device point data into one of N caches of different importance levels according to the comparison result of the difference between the data collection time and the current system time and N-1 time-effect node values ​​in sequence; the smaller the difference between the data collection time and the current system time, the higher the priority of writing into the cache with a higher importance level; N is a positive integer; As time goes by, the control device point data flows from the cache with a higher importance level to the cache with a lower importance level; Determine whether there is at least one cache into which new device point data is written; If there is at least one cache into which new device point data is written, the business scenario rule table is retrieved; Select a newly written device point data; Determine whether the newly written equipment point data meets all usage constraints of at least one business scenario in the business scenario rule table; If the newly written device point data meets all usage constraints of at least one business scenario in the business scenario rule table, the newly written device point data is applied to perform business calculations in the business scenario that meets all usage constraints; If the newly written equipment point data does not meet all the usage constraints of at least one business scenario in the business scenario rule table, an alarm message is issued; Return to the selection of a newly written device point data until all the newly written device point data are processed.

2. The method for managing equipment point data in an energy storage system according to claim 1, characterized in that: The step of obtaining the difference between the data collection time and the current system time, and writing the device point data into one of N caches of different importance levels according to the comparison result of the difference between the data collection time and the current system time and N-1 time-effect node values ​​in sequence, comprises: Determine whether the difference between the data collection time and the current system time is greater than 0; If the difference between the data collection time and the current system time is greater than 0, then further determine whether the difference between the data collection time and the current system time is less than the first-level timeliness node value; If the difference between the data collection time and the current system time is less than the first-level time-effectiveness node value, the device point data is written into the first-level cache; If the difference between the data collection time and the current system time is greater than or equal to the first-level timeliness node value, then further determine whether the difference between the data collection time and the current system time is less than the second-level timeliness node value; If the difference between the data collection time and the current system time is less than the secondary timeliness node value, the device point data is written into the secondary cache; If the difference between the data collection time and the current system time is greater than or equal to the secondary timeliness node value, the device point data is written into the third-level cache.

3. The method for managing equipment point data in an energy storage system according to claim 1, characterized in that: After determining whether there is at least one cache into which new device point data is written, the method further includes: If there is at least one cache into which new device point data is written, an expiration time tag matching the importance level of the cache is generated, so that the expiration time of the device point data is different for different importance levels of the caches; Determine whether the cache to which the newly written device point data belongs is the cache with the lowest importance level; If the cache to which the newly written device point data belongs is not the cache with the lowest importance level, an expiration time tag is added to the newly written device point data.

4. The method for managing equipment point data in an energy storage system according to claim 3, characterized in that: The value of the expiration time tag is equal to the difference between the aging node value corresponding to the cache importance level and the data collection time of the newly written device point data.

5. The method for managing equipment point data in an energy storage system according to claim 4, characterized in that: The control device point data is transferred from a cache with a high importance level to a cache with a low importance level over time, including: Each cache traverses all the device point data stored in itself, and determines whether at least one device point data has failed based on the expiration time tag of the device point data; If at least one device point data has a failure phenomenon, then all device point data that have a failure phenomenon are obtained; Select a device point data that produces a failure phenomenon; Determine whether the cache to which the device point data that causes the failure phenomenon belongs is the cache with the lowest importance level; If the cache to which the equipment point data causing the failure phenomenon belongs is not the cache with the lowest importance level, the equipment point data causing the failure phenomenon will be deleted from the current cache, and the equipment point data causing the failure phenomenon will be transferred to the next level cache with a lower importance level, and the selected equipment point data causing the failure phenomenon will be returned until all the equipment point data causing the failure phenomenon have been processed.

6. The method for managing equipment point data in an energy storage system according to claim 5, characterized in that: The device point data that will cause the failure phenomenon is deleted from the current cache, and the device point data that will cause the failure phenomenon is transferred to the next level of cache with a lower importance level, and the device point data that will cause the failure phenomenon is selected is returned until all the device point data that will cause the failure phenomenon are processed, including: Obtain the device point label of the device point data that causes the failure phenomenon; Get whether there is device point data with the same device point tag in the next-level cache with a lower importance level than the current cache; If there is no device point data with the same device point label in the cache of the next level with a lower importance level of the current cache, the device point data that has caused the failure phenomenon is deleted from the current cache, and the device point data that has caused the failure phenomenon is transferred to the cache of the next level with a lower importance level of the current cache, and the device point data that has caused the failure phenomenon is selected and returned; If there is device point data with the same device point tag in a cache of a lower level of importance than the current cache, then the data collection time of the device point data that has failed in the current cache is obtained, and the data collection time is used as the first collection time; Obtain the data collection time of the device point data with the same device point tag in the next-level cache with a lower importance level than the current cache, and use the data collection time as the second collection time; Determining whether the first collection time is later than the second collection time; If the first acquisition time is later than the second acquisition time, the device point data that generates the failure phenomenon is deleted from the current cache, and the device point data that generates the failure phenomenon is transferred to a cache of a lower importance level of the next level of the current cache, and the device point data that generates the failure phenomenon is selected and returned; If the first acquisition time is earlier than the second acquisition time, the device point data that generates the failure phenomenon is deleted from the current cache, and the selected device point data that generates the failure phenomenon is returned.

7. The method for managing equipment point data in an energy storage system according to claim 6, characterized in that: After determining whether the cache to which the device point data that generates the failure phenomenon belongs is the cache with the lowest importance level, the method further includes: If the cache to which the device point data that has caused the failure phenomenon belongs is the cache with the lowest importance level, it is determined whether there is other device point data with the same device point tag in the current cache except for the device point data that has caused the failure phenomenon; If there are other device point data with the same device point tag in the current cache except the device point data that has failed, the device point data with the latest data collection time under the device point tag will be retained, and the remaining device point data except the device point data with the latest data collection time under the device point tag will be deleted.

8. The method for managing equipment point data in an energy storage system according to claim 7, characterized in that: Also includes: Send a request to the cache to retrieve data; Select a device point tag; The current system time is used as the current snapshot time, and the device point data of the device point tag in the cache that is closest to the current system time is obtained and stored as the snapshot data of the current snapshot time in the troubleshooting database; Return to the step of selecting a device point tag until all device point tags are processed; After a preset time period, the process returns to the step of sending a request to the cache to retrieve data.

9. The method for managing equipment point data in an energy storage system according to claim 8, characterized in that: The method of taking the current system time as the current snapshot moment, obtaining the device point data of the device point tag in the cache closest to the current system time and storing it in the troubleshooting database as the snapshot data of the current snapshot moment, includes: Traverse multiple caches of different importance levels, and obtain the device point data of the device point tag closest to the current system time in the cache of each importance level; Determine whether the acquired device point data is obtained from the cache with the lowest importance level; If the acquired device point data is acquired from the cache with the lowest importance level, an offline data tag is added to the acquired device point data; If the acquired device point data is not acquired from the cache with the lowest importance level, an online data tag is added to the acquired device point data; The device point data with online data tags and / or offline data tags attached thereto are stored in the troubleshooting database as snapshot data at the current snapshot moment.

10. A device point data management system, characterized in that: include: A management unit, configured to execute the device point data management method in the energy storage system according to any one of claims 1 to 9; A storage unit, connected to the management unit, including a plurality of caches of different importance levels; The business scenario unit is connected to the management unit.

Images