Data management method and system of transportation junction energy management and control system

Abstract

The invention provides a transportation junction energy management and control system data management method and system, and the method comprises the steps: defining plant station division and equipment types, creating a new bitmap array and a mapping table, and carrying out the system initialization; existing equipment is inquired by inputting equipment meta-information, a new equipment serial number is generated according to the existing equipment, a start bit offset and an extended bitmap length are determined based on the new equipment serial number, mapping table equipment information of different statistical time periods is input into a mapping table, and equipment counting is updated; receiving real-time parameter data of the equipment, judging a parameter state according to a parameter verification rule, converting the equipment-parameter into an absolute bit index in the bitmap through a mapping function, and executing an atomic bitmap updating operation; and the regional health degree and the type health degree are determined through multi-dimensional statistics and aggregation statistics. According to the method, real-time sensing of the state of the distributed energy equipment, rapid positioning of abnormal data, multi-dimensional energy consumption statistics and intelligent regulation and control are realized, and dynamic addition and deletion of the equipment and efficient management of variable-length parameter data are supported.

Description

Technical Field

[0001] This application belongs to the field of interdisciplinary technology of intelligent transportation and energy management, and in particular relates to a data management method and system for energy control system of transportation hub. Background Technology

[0002] The current energy management system for transportation hubs faces three core challenges: (1) Strong equipment heterogeneity: The number and type of parameters reported by different equipment vary greatly (e.g., air conditioners have 5 parameters, while lighting has only 1), making it difficult to unify the modeling of the traditional "one record per device" model; (2) Frequent dynamic changes in equipment: Adding or replacing equipment causes the index to become invalid, and the static bitmap structure needs to be completely rearranged, which is inefficient; (3) Single statistical dimension: lacks the ability to aggregate multiple dimensions such as region, type, parameter, time, etc., and cannot support refined management and control.

[0003] Existing solutions mostly use relational databases or simple bitmaps, which have problems such as high storage overhead (TB level / day), high query latency (second level), and poor scalability. Summary of the Invention

[0004] In view of this, this application aims to propose a data management method and system for energy control systems in transportation hubs to solve at least one of the above-mentioned problems.

[0005] To achieve the above objectives, the technical solution of this application is implemented as follows: Firstly, this application provides a data management method for a transportation hub energy management system, including: Define the plant division and equipment type, create new bitmap arrays and mapping tables, and perform system initialization; The system queries existing devices by entering device metadata, generates new device serial numbers based on the queried existing devices, determines the starting bit offset and extended bitmap length based on the new device serial numbers, enters the mapping table device information for different statistical periods into the mapping table and updates the device count to complete device registration. The system receives real-time parameter data from the device, determines the parameter status according to preset parameter verification rules, converts the device-parameter into absolute bit indices in a bitmap using a mapping function, and performs atomic bitmap update operations; wherein, the atomic bitmap update includes abnormal bitmap status update and missing bitmap status update. The total number of abnormal parameters and the total number of missing parameters are statistically aggregated through multidimensional statistics. The health of the region is determined based on the abnormality rate formula, and the health of the type is determined based on the missing rate formula.

[0006] Secondly, based on the same inventive concept, this application also provides a data management system for a transportation hub energy management system, comprising: The system initialization module is configured to define the plant division and equipment type, create new bitmap arrays and mapping tables, and perform system initialization; The data mapping module is configured to query existing devices by inputting device metadata, generate new device serial numbers based on the queried existing devices, determine the starting bit offset and extended bitmap length based on the new device serial numbers, input the mapping table device information for different statistical periods into the mapping table and update the device count to complete device registration. The status update module is configured to receive real-time parameter data from the device, determine the parameter status according to preset parameter verification rules, convert the device-parameter into absolute bit indices in the bitmap through a mapping function, and perform atomic bitmap update operations; wherein, the atomic bitmap update includes abnormal bitmap status update and missing bitmap status update. The multidimensional statistical aggregation module is configured to use multidimensional statistical aggregation to count the total number of abnormal parameters and the total number of missing parameters, and to determine the regional health based on the abnormality rate formula and the type health based on the missing rate formula.

[0007] Thirdly, based on the same inventive concept, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in the first aspect.

[0008] Fourthly, based on the same inventive concept, this application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions for causing the computer to perform the method as described in the first aspect.

[0009] Compared with existing technologies, the data management method and system for energy management systems in transportation hubs described in this application have the following advantages: The data management method for a transportation hub energy management system described in this application adopts a five-in-one architecture of "type partitioning + parameter granularity + dynamic block allocation + logical deletion + bitmap re-indexing". It can be applied to large transportation hubs (such as high-speed rail stations, airport terminals, subway transfer centers, etc.) to realize real-time perception of the status of distributed energy equipment, rapid location of abnormal data, multi-dimensional energy consumption statistics and intelligent control. It is particularly suitable for high-concurrency, low-latency, and memory-friendly status monitoring scenarios of massive heterogeneous equipment (electricity meters, water meters, air conditioners, lighting, charging piles, etc.) and supports efficient management of dynamic addition and deletion of equipment and variable-length parameter data. Attached Figure Description

[0010] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating a data management method for a transportation hub energy management system as described in an embodiment of this application. Figure 2 This is a flowchart illustrating the system initialization process described in an embodiment of this application. Figure 3 This is a flowchart illustrating the device registration process described in an embodiment of this application; Figure 4 This is a flowchart illustrating the data acquisition and status update process described in the embodiments of this application. Figure 5 This is a flowchart illustrating the information interaction between the mapping table and the bitmap array as described in the embodiments of this application. Figure 6 This is a flowchart illustrating the multidimensional statistical aggregation process described in the embodiments of this application; Figure 7 This is a schematic diagram of the data management system structure of a transportation hub energy management system according to an embodiment of this application; Figure 8 This is a schematic diagram of the hardware structure of the electronic device described in an embodiment of this application. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0012] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0013] The embodiments of this application are described in detail below with reference to the accompanying drawings.

[0014] Please see Figure 1 As shown in the figure, this embodiment provides a data management method for a transportation hub energy management system, which specifically includes the following steps: Step S101: Define the plant division and equipment type, create a new bitmap array and mapping table, and perform system initialization.

[0015] Specifically, in this embodiment, such as Figure 2 As shown, the definition of the plant and station division is based on the actual physical structure and energy management needs of the transportation hub, dividing the entire hub into... A logical factory station, denoted as , , ..., For example, high-speed rail stations can be divided into "West Area Waiting Hall," "West Area Waiting Hall," "Platform 1," "Platform 2," and "Commercial Area," etc. Each station represents an independent energy management and statistics unit, facilitating regional-level energy efficiency analysis and fault location.

[0016] The equipment type is defined based on the equipment's functional characteristics and energy form, and is predefined. Device type, denoted as , , ..., For example, there are "lighting," "air conditioning," "elevators," "charging stations," and "water pumps." Each equipment type is associated with a specific set of monitoring parameters. For instance, air conditioning equipment typically monitors multiple parameters such as "current," "voltage," "power," "set temperature," and "return air temperature," while lighting equipment may only monitor two parameters: "on / off status" and "power." This classification method provides a clear logical framework for subsequent parameter-level refined management. Lighting system (usually includes 1-2 parameters: on / off status, power); Central air conditioning (including 5-8 parameters: supply air temperature, return air temperature, compressor current, cooling power, operating mode, etc.); Elevator (typically 5-8 parameters: voltage, current, power, electrical quantity, start / stop status, etc.); ... Charging station (typically has 5-8 parameters: voltage, current, power, charging capacity, charging status, charging / discharging time, etc.); This "plant × type" two-dimensional model supports flexible aggregation and statistics by region and equipment category, which is a prerequisite for realizing multidimensional analysis.

[0017] A new bitmap array is created for each data collection period, and all data in the bitmap values ​​is initialized. After the bitmap statistics are completed and the statistical information is saved, the previously created bitmap array is destroyed. For each pair (... , The system initializes three independent bitmaps, each with a bit as the smallest storage unit, significantly reducing memory overhead (1 bit / test point). The bitmap includes: Abnormal state bitmap A n，m Each bit corresponds to a specific monitoring parameter; a value of 1 indicates that the parameter is currently in an abnormal state (such as exceeding limits, logical conflicts, etc.); missing state bitmap M n，m A value of 1 indicates that the parameter was not reported due to communication interruption, device offline, or other reasons, and is in a missing state; delete flag bitmap R n，m Used to mark whether a device has been logically deleted, to avoid physical deletion causing index reordering.

[0018] Initially, all bitmaps have a length L. n，m =0, adopting an "on-demand allocation" strategy—that is, dynamically expanding the bitmap length when the device is registered. This design avoids the problem of pre-allocating a large amount of memory for unused devices in traditional solutions, and is especially suitable for scenarios where the number of devices is uncertain or gradually added.

[0019] A new mapping table is created for each data statistics period, and all data in the mapping table is initialized. The global device registry is a "bridge" connecting "device metadata" and "bitmap location". By storing key device attributes, it enables fast mapping between devices and bitmap indexes, avoiding location confusion during subsequent data updates.

[0020] The mapping table is essentially a structured data table. It is initially empty, and a new record is added for each registered device. It is used to store the device's "identity information" and "location information" to ensure that the system can quickly find the storage location of its parameters in the bitmap through the device ID.

[0021] Key fields: The table structure includes the following core fields to ensure complete information and easy querying: Device ID: A unique identifier (e.g., "..."). - "-001" indicates Factory Station Type 1 equipment); Plant / station number : Associated logical factory station (e.g., 1 corresponds to ); Equipment type number : Associated device type (e.g., 2 corresponds to) ); Equipment serial number The equipment belongs to ( , The unique serial number in the combination (e.g., the first air conditioner) ); Number of parameters P: The number of parameters that the device needs to monitor (e.g., P=4 for air conditioners); Starting offset: The starting position of the first parameter of the device in the bitmap.

[0022] System initialization is the foundational step in building the entire bitmap mapping architecture. It aims to provide structured support for subsequent dynamic device registration, parameter-level state mapping, and efficient statistics. This step achieves logical decoupling and resource isolation through a two-dimensional partitioning strategy of "plant-equipment type," balancing management granularity and computational efficiency.

[0023] Step S102: Query existing devices by entering device metadata, generate new device serial numbers based on the queried existing devices, determine the starting bit offset and extended bitmap length based on the new device serial numbers, enter the mapping table device information for different statistical periods into the mapping table and update the device count to complete device registration.

[0024] Specifically, in this embodiment, such as Figure 3 As shown, device metadata serves as the "identity credential" for registration and must comprehensively cover three dimensions: "space ownership," "function type," and "monitoring requirements" to ensure the accuracy of subsequent bitmap allocation and parameter management.

[0025] Plant / Station Number Clearly define the logical station where the equipment is installed, on a terminal-by-terminal basis, and ensure that it matches the station number assigned in step S101. For example, if the equipment is installed in the waiting hall of a high-speed rail station (… , ), then enter If installed in the platform area ( , ), then enter This number directly determines the subsequent association of the device ( , If the bitmap combination is entered incorrectly, the parameter status will be stored in the wrong bitmap, affecting the statistical results.

[0026] Equipment type number : Clearly define the type of equipment, which must match the predefined equipment type number in step 1. For example, adding a central air conditioner ( , ), then enter Add a new electricity meter ( , ), then enter This number determines the device's parameter monitoring template (e.g., ...). Corresponding to 4 parameters (Corresponding to 3 parameters), ensuring that the number of parameters matches the type.

[0027] Number of parameters Based on the monitoring requirements of the device type, enter the number of parameters that need to be collected in real time for that device. Strict adherence to the predefined type parameter standards in step S101 is required to avoid management confusion caused by inconsistent parameter numbers. For example: New lighting equipment ( , If two parameters need to be monitored according to the predefined parameters, then... ; New elevator equipment ( , If three parameters need to be monitored according to the predefined parameters, then... .

[0028] The new equipment serial number is the equipment's (in its) ( , The "exclusive number" in the combination follows the "continuous increment" principle to ensure that the serial number of each device is unique, providing a basis for subsequent calculation of the starting position offset and device positioning.

[0029] Existing device count query: The system automatically queries the current ( Factory Station - The total number of registered devices under the (type) combination is denoted as D. n，m The query needs to be based on the global device registry, filtered by "n=target plant number" and " The result is obtained by querying the number of records with the target type number. For example, querying " - "The number of registered devices in the combination. If there are 3 records for this combination in the registry, then D1,2=3."

[0030] New device serial number generation: New device serial number =D n，m +1 means incrementing the number based on the existing number of devices. For example: D 1，2 =3, then the serial number of the newly registered air conditioning equipment =3+1=4, becoming the 4th air conditioner in this combination. The uniqueness of the serial number ensures that when deleting devices or rebuilding the bitmap, the parameter range corresponding to the device can be accurately located, avoiding data confusion caused by duplicate serial numbers.

[0031] (3) Calculate the starting position offset The starting bit offset is the core of achieving "parameter-level precise positioning." By calculating the absolute position of the first parameter of a new device in the bitmap, it ensures that each parameter can be uniquely identified, providing a "precise address" for subsequent data updates and queries. The formula for calculating the absolute bit index is as follows: ; In the formula, Representation type At the factory station The current starting offset (i.e., the total number of existing parameters); Indicates the first in this type Number of parameters for each device; This represents the total number of parameters for all existing devices; This represents the absolute bit index of the first parameter of the new device in the global bitmap.

[0032] For example: Suppose " - "The combination already has 3 air conditioners, each with 4 parameters (P1,2,1=4, P1,2,2=4, P1,2,3=4), so the total number of parameters is 4+4+4=12. The newly registered 4th air conditioner ( , The starting bit offset is 12, meaning that the first parameter of the device corresponds to the 12th bit of the bitmap, the second parameter corresponds to the 13th bit, the third parameter corresponds to the 14th bit, and the fourth parameter corresponds to the 15th bit, thus achieving a one-to-one binding between the parameters and the bitmap positions.

[0033] In this embodiment, bitmap length extension is to "free up storage space" for new device parameters, ensuring that the bitmap can accommodate the new parameters while avoiding waste caused by excessive memory allocation.

[0034] ; In the formula, Indicates the total length of the current bitmap (unit: bits); Indicates the number of parameters for the new equipment; This indicates the new length after expansion.

[0035] The system calls the underlying memory management interface (such as realloc or the resize method of the bitmap library), appending to the end. Each bit is initialized to 0 (indicating an initial state of "normal and present"). This operation has a time complexity of O(1) (only modifying length metadata), and the actual memory allocation can be delayed until the first write.

[0036] In this embodiment, the mapping table is the key to bitmap retrieval. Since device changes occur frequently in the system, the system devices are checked for changes at the beginning of the statistical period. If there are changes, a new mapping table is created. During the statistical period, the newly created mapping table is used as the standard to store statistical data. After the statistical task of the mapping table in the previous statistical period is completed, the statistical data is saved to the database, and the historical mapping table will be deleted subsequently.

[0037] The process for registering devices to the mapping table is as follows: Map device information from different statistical time periods is... Entering the mapping table and updating the statistical data is the "final step" to complete the registration, ensuring that the subsequent system can quickly associate the device ID with the location on the map and achieve full lifecycle management of the data.

[0038] Specifically, add a new record in the global device registry, filling in the complete device ID (e.g., "..."). - -004”), factory station number Equipment type number Equipment serial number Number of parameters The starting offset is 12. This information covers the device's "identity" and "location". During subsequent data collection, only the device ID needs to be entered to query the corresponding parameter starting position, enabling rapid updates of parameter status.

[0039] Will( , The number of existing devices D under the combination n，m Updated to D n，m +1 (i.e., updated from 3 to 4) provides accurate basic data for the next registration of the same type of device, ensuring the continuity of the serial number calculation and the start bit offset calculation.

[0040] In step S102, adding (registering) devices is the "entry point" for the system to adapt to the dynamic changes of transportation hub devices. Through standardized metadata entry, serial number calculation, bitmap expansion and mapping table update process, the system can quickly access heterogeneous devices, while ensuring the orderly storage of parameters in the bitmap, thus solving the problem of index failure and data chaos caused by adding devices in traditional solutions.

[0041] Step S103: Receive real-time parameter data from the device, determine the parameter status according to the preset parameter verification rules, convert the device-parameter into an absolute bit index in the bitmap through a mapping function, and perform an atomic bitmap update operation; wherein, the atomic bitmap update includes abnormal bitmap status update and missing bitmap status update.

[0042] Specifically, in this embodiment, such as Figure 4 and Figure 5 As shown, the system receives real-time parameter data from sensors or data acquisition terminals (such as smart meters and air conditioner controllers). Each data entry contains four core pieces of information: "Device ID," "Parameter Sequence Number," "Measured Parameter Value," and "Collection Timestamp." For example, " - The measured value of the "return air temperature" parameter of the "-004" air conditioner is 28℃, and the data collection time is 10:00:00.

[0043] Based on preset parameter verification rules (combining equipment physical characteristics and industry standards), the status of the parameter is determined. The parameter verification rules are set as follows: If the measured value of the parameter exceeds the normal range (e.g., the normal range of air conditioner return air temperature is 18-26℃, but the measured temperature is 28℃) or there is a logical contradiction (e.g., the meter current is -5A), it is judged as "abnormal state" and recorded as Status=1. If the measured data for this parameter is not received (e.g., sensor communication is interrupted, only the device ID and parameter serial number are received, but no measured value is received), it is determined to be a "missing status" and recorded as Status=2; If the measured value of the parameter is within the normal range and the data is complete (e.g., the air conditioner return air temperature is 24℃), it is determined to be in "normal state" and recorded as Status=0.

[0044] In this embodiment, the calculation of parameter bit indices is the core of achieving "precise positioning." A mapping function transforms the "device-parameter" into absolute bit indices in a bitmap, ensuring that each parameter can be uniquely identified and providing a "precise target address" for subsequent state updates. The mapping function is as follows: ; In the formula, Indicates the plant / station number; Indicates the device type number; Indicates the serial number of the device within the type; Indicates the parameter number (starting from 1); Indicates the offset of the type's starting bit; This indicates the total number of parameters for all devices preceding this device; This indicates the absolute bit index of the parameter in the bitmap.

[0045] The atomic update in this embodiment is crucial for ensuring data consistency in high-concurrency scenarios. By implementing an uninterrupted update operation, it avoids state chaos caused by multiple threads simultaneously modifying the same bit, thus guaranteeing the accuracy of parameter states. This includes both abnormal updates and missing updates, as detailed in the following formula: Abnormal update: ; Missing updates: ; In the formula, Indicates the abnormal bitmap number Bit; Indicates the missing bitmap. Bit; When the status is 1, the exception bitmap A[k] is set to 1; when the status is not 1, the exception bitmap A[k] is set to 0. At this point, the exception bitmap status update is complete.

[0046] When the Status is 2, the abnormal bitmap M[k] is set to 1; when Status is not 2, the abnormal bitmap M[k] is set to 0. At this point, the missing bitmap status update is complete.

[0047] It should be noted that update operations must guarantee atomicity to prevent concurrent conflicts. Therefore, this embodiment adopts an atomicity guarantee mechanism, namely, a dual guarantee of "hardware-level atomic operation + software lock": Hardware level: Utilize the CPU's atomic instructions (such as the CAS instruction in the x86 architecture and the LDREX / STREX instruction in the ARM architecture) to ensure that the modification operation of a single bit is indivisible; Software level: For the same ( , The combination of bitmap updates and lightweight spinlocks avoids conflicts caused by multiple threads updating the same bitmap simultaneously, making it particularly suitable for scenarios where tens of thousands of devices in transportation hubs report data concurrently.

[0048] Step S104: The total number of abnormal parameters and the total number of missing parameters are statistically aggregated through multidimensional statistics, and the regional health is determined based on the abnormality rate formula, and the type health is determined based on the missing rate formula.

[0049] Specifically, in this embodiment, such as Figure 6 As shown, multidimensional statistical aggregation is the core component of the system to achieve "refined analysis and decision support". By performing mathematical operations directly based on bitmaps, it can achieve millisecond-level anomaly / missing data statistics, regional / type health analysis and trend prediction without traversing massive amounts of raw data, thus solving the problems of high statistical latency and single dimension in traditional solutions.

[0050] Specifically, query parameter status is the "basic unit" of statistical aggregation. By combining it with the deletion flag bitmap, the current valid status of a certain parameter can be quickly determined, ensuring that the statistical results do not include data from deleted devices.

[0051] Through the abnormal state bitmap A n，m The system queries the abnormal status of different parameters of different devices, calculates the total number of abnormal parameters under the combination of plant and type according to the formula for the total number of abnormalities, and calculates the regional health status through the formula for the plant abnormality rate. The statistical health status values ​​are then written into the database for future system queries.

[0052] The formula for the total number of anomalies is as follows: ; In the formula, Representation type At the factory station The total number of abnormal parameters in the data; Indicates an abnormal bitmap; Indicates the first The number of parameters for each device; Indicates the first The deletion flag of the device. The value is 1 if the device has not been deleted, and 0 otherwise, thus achieving automatic filtering. express( The total number of registered devices in the combination.

[0053] The formula for plant / station anomaly rate is as follows: ; In the formula, This represents the regional anomaly rate. The numerator represents the total number of all abnormal parameters of the plant, and the denominator represents the total number of all valid parameters of the plant.

[0054] Through the missing state bitmap M n，m Query the missing status of different parameters for different devices, calculate the total number of missing parameters under the combination of plant and type according to the formula for total missing number, and calculate the type health of the corresponding plant using the formula for type missing rate.

[0055] The formula for the total number of missing numbers is as follows: ; In the formula, This indicates the total number of missing parameters for the plant-type combination.

[0056] The formula for the type missing rate is as follows: ; In the formula, The numerator represents the total number of all abnormal parameters of the type, and the denominator represents the total number of valid parameters of the type.

[0057] In addition, in this embodiment, the primary prerequisite for switching the statistical period is that all data collection tasks in the current period have been completed. By quantifying the "number of completed data collection tasks" and the "number of unexecuted tasks", the statistical data is ensured to cover all device parameters throughout the entire period, thus avoiding statistical distortion due to the failure of some tasks to be executed.

[0058] Specifically, within the current statistical period, the data collection tasks that the system needs to execute are based on the smallest unit of "device-parameter," meaning that each monitoring parameter of each valid device corresponds to one independent data collection task. A single data collection task is denoted as... (Corresponding plant) ,type ,equipment ,parameter ).

[0059] Total number of data collection tasks in the current period This is the sum of the number of parameters for all valid devices, ensuring that only the acquisition tasks corresponding to the valid parameters of valid devices are counted. The formula is as follows: ; The system maintains a "Data Acquisition Task Execution Status Table" in real time, recording each task. The execution result (success / failure), the number of tasks completed. This represents the number of tasks that were "executed successfully" in the status table (including cases where parameters were reported normally and cases where abnormal parameters were reported, but excluding cases where parameters were missing).

[0060] Number of unexecuted tasks If and only if When the current cycle collection task is completed, it is determined that the "data integrity prerequisite" for cycle switching is met.

[0061] If a data collection task cannot be executed due to reasons such as device offline or communication interruption, the system will mark it as "execution failed" and record it. At this point, a re-collection mechanism needs to be triggered (e.g., re-collecting every 5 seconds, with a maximum of 3 re-collections). If the re-collection is successful, the data will be updated. If the data collection fails, the parameters corresponding to the task will be marked as "missing" and recorded. (Considered as "complete missing state acquisition"), ultimately ensuring .

[0062] Once the relevant statistical tasks for the current period have been completed, the bitmap data and historical mapping table for the current period will be destroyed, and the relevant statistical objects for the current period will be cleared to reduce memory leaks and prepare for the statistical tasks of the next period.

[0063] The data management method for a transportation hub energy management system described in this embodiment adopts a five-in-one architecture of "type partitioning + parameter granularity + dynamic block allocation + logical deletion + bitmap re-indexing". It can be applied to large transportation hubs (such as high-speed rail stations, airport terminals, subway transfer centers, etc.) to realize real-time perception of the status of distributed energy equipment, rapid location of abnormal data, multi-dimensional energy consumption statistics and intelligent control. It is particularly suitable for high-concurrency, low-latency, and memory-friendly status monitoring scenarios of massive heterogeneous equipment (electricity meters, water meters, air conditioners, lighting, charging piles, etc.), and supports efficient management of dynamic addition and deletion of equipment and variable-length parameter data.

[0064] It should be noted that the above description describes some embodiments of this application. 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 a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0065] Based on the same inventive concept, and corresponding to the methods of any of the above embodiments, the embodiments of this application also provide a data management system for a transportation hub energy management system.

[0066] like Figure 7 As shown, the data management system for the transportation hub energy management system includes: System initialization module 11 is configured to define plant division and equipment type, create new bitmap arrays and mapping tables, and perform system initialization; The data mapping module 12 is configured to query existing devices by inputting device metadata, generate new device serial numbers based on the queried existing devices, determine the starting bit offset and extended bitmap length based on the new device serial numbers, input the mapping table device information for different statistical periods into the mapping table and update the device count to complete device registration. The status update module 13 is configured to receive real-time parameter data from the device, determine the parameter status according to the preset parameter verification rules, convert the device-parameter into an absolute bit index in the bitmap through a mapping function, and perform atomic bitmap update operations; wherein, atomic bitmap update includes abnormal bitmap status update and missing bitmap status update. The multidimensional statistical aggregation module 14 is configured to use multidimensional statistical aggregation to count the total number of abnormal parameters and the total number of missing parameters, and to determine the regional health based on the abnormality rate formula and the type health based on the missing rate formula.

[0067] For ease of description, the above system is described by dividing it into various modules based on their functions. Of course, in implementing the embodiments of this application, the functions of each module can be implemented in one or more software and / or hardware.

[0068] The system described in the above embodiments is used to implement the corresponding method in any of the foregoing embodiments and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0069] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, embodiments of this application also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the methods described in any of the above embodiments.

[0070] Figure 8 This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0071] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0072] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0073] The input / output interface 1030 is used to connect input / output modules to realize information input and output. The input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0074] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0075] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0076] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0077] The electronic devices described above are used to implement the corresponding methods in any of the foregoing embodiments and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0078] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to perform the methods described in any of the above embodiments.

[0079] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0080] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to perform the methods described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0081] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0082] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0083] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A data management method for a transportation hub energy management system, characterized in that, include: Define the plant division and equipment type, create new bitmap arrays and mapping tables, and perform system initialization; The system queries existing devices by entering device metadata, generates new device serial numbers based on the queried existing devices, determines the starting bit offset and extended bitmap length based on the new device serial numbers, enters the mapping table device information for different statistical periods into the mapping table and updates the device count to complete device registration. The system receives real-time parameter data from the device, determines the parameter status according to preset parameter verification rules, converts the device-parameter into absolute bit indices in a bitmap using a mapping function, and performs atomic bitmap update operations; wherein, the atomic bitmap update includes abnormal bitmap status update and missing bitmap status update. The total number of abnormal parameters and the total number of missing parameters are statistically aggregated through multidimensional statistics. The health of the region is determined based on the abnormality rate formula, and the health of the type is determined based on the missing rate formula.

2. The method according to claim 1, characterized in that: A new bitmap array and a mapping table are created for each data statistics period, and all data in the bitmap array and the mapping table are initialized respectively; wherein, the bitmap array includes an abnormal state bitmap, a missing state bitmap, and a deletion flag bitmap.

3. The method according to claim 1, characterized in that: The equipment metadata includes the plant number, type number, and number of parameters; The absolute position of the first parameter of the new device in the bitmap is calculated based on the starting bit offset, wherein the formula for calculating the absolute bit index is as follows: ； In the formula, Representation type At the factory station The current starting offset; Indicates the first in this type Number of parameters for each device; This represents the total number of parameters for all existing devices; This represents the absolute bit index of the first parameter of the new device in the global bitmap.

4. The method according to claim 1, characterized in that: Extract real-time parameter data fields, including device ID, parameter sequence number, measured parameter value, and collection timestamp. Determine the parameter status according to preset parameter verification rules, including abnormal status, missing status, and normal status.

5. The method according to claim 1, characterized in that: By combining the deletion flag bitmap and filtering deleted device data, the abnormal status can be queried through the abnormal status bitmap. The total number of abnormal parameters under the combination of plant and type is calculated according to the formula for the total number of abnormalities, and the regional health is obtained by calculating the plant abnormality rate formula.

6. The method according to claim 5, characterized in that, in, The formula for the total number of anomalies includes: ； In the formula, Representation type At the factory station The total number of abnormal parameters in the data. Indicates an abnormal bitmap. Indicates the first The number of parameters for each device. Indicates the first The deletion flag of the device. express ( The total number of registered devices in the combination.

7. The method according to claim 6, characterized in that, in, The formula for the plant / station anomaly rate includes: ； In the formula, This indicates the regional anomaly rate.

8. The method according to claim 5, characterized in that, Also includes: The missing status is queried by the missing status bitmap, the total number of missing parameters under the plant and type combination is calculated according to the total number of missing parameters formula, and the type health of the corresponding plant is calculated by the type missing rate formula.

9. A data management system for energy control and management in a transportation hub, characterized in that, include: The system initialization module is configured to define the plant division and equipment type, create new bitmap arrays and mapping tables, and perform system initialization; The data mapping module is configured to query existing devices by inputting device metadata, generate new device serial numbers based on the queried existing devices, determine the starting bit offset and extended bitmap length based on the new device serial numbers, input the mapping table device information for different statistical periods into the mapping table and update the device count to complete device registration. The status update module is configured to receive real-time parameter data from the device, determine the parameter status according to preset parameter verification rules, convert the device-parameter into absolute bit indices in the bitmap through a mapping function, and perform atomic bitmap update operations; wherein, the atomic bitmap update includes abnormal bitmap status update and missing bitmap status update. The multidimensional statistical aggregation module is configured to use multidimensional statistical aggregation to count the total number of abnormal parameters and the total number of missing parameters, and to determine the regional health based on the abnormality rate formula and the type health based on the missing rate formula.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as claimed in any one of claims 1-8.

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