CN114547190A - Data processing method and device, storage medium and electronic equipment - Google Patents
Data processing method and device, storage medium and electronic equipment Download PDFInfo
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- CN114547190A CN114547190A CN202210076325.2A CN202210076325A CN114547190A CN 114547190 A CN114547190 A CN 114547190A CN 202210076325 A CN202210076325 A CN 202210076325A CN 114547190 A CN114547190 A CN 114547190A
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention discloses a data processing method, a device, a storage medium and electronic equipment, which are applied to edge side equipment, wherein the edge side equipment is pre-integrated with a plurality of algorithms for calculating performance data of a data source connected with the edge side equipment, and the method comprises the following steps: acquiring running state data of a data source connected with edge side equipment; performing structured storage on the running state data; and acquiring the running state data of the data source from the structured storage result, and calculating the running state data of the data source by using a pre-integrated algorithm to obtain the performance data of the data source. According to the method, various algorithms are integrated in the edge side equipment in advance to calculate the data of the data source, so that the influence of network interference on data transmission is overcome, the time delay is reduced, and the real-time performance of monitoring is improved.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data processing method and apparatus, a storage medium, and an electronic device.
Background
Large-scale battery energy storage power stations are generally formed by collecting a plurality of battery energy storage units, and each battery energy storage unit comprises a plurality of battery cells. In order to ensure the consistency of high-precision and high-speed output of the power station and the energy state of the battery and reduce the probability of occurrence of battery safety accidents, state data such as voltage, current and temperature of each battery cell need to be collected and analyzed in real time. In the prior art, a centralized calculation and control strategy is usually adopted, however, the centralized processing mode is limited by a network environment to cause huge pressure on a central server, and meanwhile, factors such as the network environment and data IO cause that the real-time performance and accuracy of data calculation cannot meet the requirements of real-time monitoring and accurate control on the battery cell.
Disclosure of Invention
In view of this, embodiments of the present invention provide a battery data processing method, an apparatus, a storage medium, and an electronic device, so as to solve the technical problem in the prior art that the real-time performance of battery data calculation cannot meet the requirements of real-time monitoring and accurate control of a battery cell.
The technical scheme provided by the invention is as follows:
a first aspect of an embodiment of the present invention provides a data processing method, which is applied to an edge device, where the edge device integrates multiple algorithms in advance for calculating performance data of a data source connected to the edge device, and the data processing method includes: acquiring running state data of a data source connected with edge side equipment; performing structured storage on the running state data; and acquiring the running state data of the data source from the structured storage result, and calculating the running state data of the data source by using a pre-integrated algorithm to obtain the performance data of the data source.
Optionally, the structured storage of the operating state data includes: storing the running state data in a pre-established cache region according to a preset structured type and a timestamp of the running state data; and synchronizing the cached results into the secondary storage device.
Optionally, obtaining the operation state data of the data source from the structured storage result and calculating the operation state data of the data source by using a pre-integrated algorithm to obtain the performance data of the data source, includes: acquiring running state data of a data source from a cache region according to a preset time window; additionally storing the operating state data acquired in each preset time window to the tail of a target data table; and carrying out micro batch processing on the operation state data acquired in each preset time window to obtain a micro batch processing result of the data source performance data, and additionally storing the micro batch processing result at the tail of the target result table.
Optionally, the micro-batch processing of the operation state data acquired in each preset time window to obtain a micro-batch processing result of the data source performance data includes: and transmitting the running state data acquired by each preset time window to a process of a pre-integrated algorithm according to a process communication mode for analysis and calculation to obtain a micro batch processing result of the data source performance data.
Optionally, after performing micro batch processing on the operation state data acquired in each preset time window to obtain a micro batch processing result of the data source performance data, the method further includes: and preprocessing the data of the target result table according to the received data use requirement and then sending the preprocessed data to a data use end.
Optionally, the data source connected to the edge side device includes: a plurality of energy storage units in an energy storage power station.
A second aspect of the embodiments of the present invention provides a data processing apparatus, which is applied to an edge-side device, where the edge-side device integrates multiple algorithms in advance for calculating performance data of a data source connected to the edge-side device, and the data processing apparatus includes: the acquisition module is used for acquiring the running state data of a data source connected with the edge side equipment; the storage module is used for carrying out structured storage on the running state data; and the calculation module is used for acquiring the running state data of the data source from the structured storage result and calculating the running state data of the data source by utilizing a pre-integrated algorithm to obtain the performance data of the data source.
Optionally, the storage module comprises: the first storage module is used for storing the running state data in a pre-established cache region according to a preset structured type and a timestamp of the running state data; and the second storage module is used for synchronizing the cache result to the secondary storage device.
A third aspect of the embodiments of the present invention provides a computer-readable storage medium, where computer instructions are stored, and the computer instructions are configured to cause a computer to execute a data processing method according to any one of the first aspect and the first aspect of the embodiments of the present invention.
A fourth aspect of an embodiment of the present invention provides an electronic device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the data processing method according to any one of the first aspect and the first aspect of the embodiments of the present invention.
The technical scheme provided by the invention has the following effects:
the data processing method provided by the embodiment of the invention is applied to edge side equipment, wherein the edge side equipment is pre-integrated with a plurality of algorithms for calculating performance data of a data source connected with the edge side equipment, and the method comprises the following steps: acquiring running state data of a data source connected with edge side equipment; performing structured storage on the running state data; and acquiring the running state data of the data source from the structured storage result, and calculating the running state data of the data source by using a pre-integrated algorithm to obtain the performance data of the data source. According to the method, various algorithms are integrated in the edge side equipment in advance to calculate the data of the data source, so that the influence of network interference on data transmission is overcome, the time delay is reduced, and the real-time performance of monitoring is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow diagram of a data processing method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of data processing provided in accordance with an embodiment of the present invention;
FIG. 3 is a flow chart of a data processing method provided according to an embodiment of the invention;
FIG. 4 is a block diagram of a data processing apparatus according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a computer-readable storage medium provided according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides a data processing method, which is applied to edge side equipment, wherein the edge side equipment is pre-integrated with a plurality of algorithms for calculating performance data of a data source connected with the edge side equipment. Specifically, when the data source connected to the edge-side device is an energy storage power station battery, core algorithms such as battery SOC, SOH, and equalization algorithm may be integrated in the edge-side device in advance. The pre-integration of the corresponding algorithm includes defining the execution rule of the algorithm and inputting and outputting data. As shown in fig. 1, the method comprises the steps of:
step S101: and acquiring the running state data of the data source connected with the edge side equipment. Specifically, firstly, the edge device obtains the running state data of a data source connected with the edge device and defines parameters such as a source, a name, a field type and the like of the running state data.
In an embodiment, when the data source connected to the edge-side device is an energy storage power station battery, the operation state data includes key input indexes such as voltage, current, and temperature.
Step S102: and carrying out structured storage on the running state data. Specifically, after the operation state data of the data source is acquired, the operation state data is stored as the structured MAP, that is, the structured storage is performed.
Step S103: and acquiring the running state data of the data source from the structured storage result, and calculating the running state data of the data source by using a pre-integrated algorithm to obtain the performance data of the data source. Specifically, after the operating state data is structurally stored, the corresponding operating state data is acquired in the structural storage structure, and the acquired operating state data of the data source is analyzed and calculated by using an algorithm pre-integrated in the edge side device, so that the performance data of the data source can be obtained, that is, the real-time monitoring of the operating state data of the data source is completed.
The data processing method provided by the embodiment of the invention is applied to edge side equipment, wherein the edge side equipment is pre-integrated with a plurality of algorithms for calculating performance data of a data source connected with the edge side equipment, and the method comprises the following steps: acquiring running state data of a data source connected with edge side equipment; performing structured storage on the running state data; and acquiring the running state data of the data source from the structured storage result, and calculating the running state data of the data source by using a pre-integrated algorithm to obtain the performance data of the data source. According to the method, various algorithms are integrated in the edge side equipment in advance to calculate the data of the data source, so that the influence of network interference on data transmission is overcome, the time delay is reduced, and the real-time performance of monitoring is improved.
As an optional implementation manner of the embodiment of the present invention, the performing structured storage on the operation state data includes: storing the running state data in a pre-established cache region according to a preset structured type and a timestamp of the running state data; and synchronizing the cached results into the secondary storage device. Specifically, after the edge side device acquires the running state data of the data source connected to the edge side device, firstly, a KV cache is created in the memory, then, the running state data is stored in the KV cache as a continuously-increasing structured MAP (which may be an infinitely-increasing log-type data structure) with a timestamp of the running state data as a key, and a cache result is synchronized into the secondary storage device at the same time, which is convenient for state recovery when the subsequent data source is abnormal.
As an optional implementation manner of the embodiment of the present invention, step S103 includes: acquiring running state data of a data source from a cache region according to a preset time window; additionally storing the operating state data acquired in each preset time window to the tail of a target data table; and carrying out micro batch processing on the operation state data acquired in each preset time window to obtain a micro batch processing result of the data source performance data, and additionally storing the micro batch processing result at the tail of the target result table. Specifically, after the running state data is structurally stored, firstly, the running state data of the data source is acquired in the structural storage result according to a preset time window, then the running state data acquired in each time window is taken as a line of the structural storage result and is additionally input to the tail of the structural storage result, and meanwhile, the running state data acquired in each time window is subjected to micro batch processing to obtain a micro batch processing result of the corresponding data source performance data and the result is additionally stored in the structural storage result. Wherein the structured storage result is the target result table.
In one embodiment, a rolling time window is used, 10s is set as a time window, from 0, every 10s is a time window, the running state data with the time stamp between 0 and 10s is subjected to micro batch processing and divided into an effective data set (table), and the corresponding running state data and the corresponding micro batch processing result are added to the target result table according to the sequence of the time stamps. Similarly, the operating state data within each 10s is subjected to micro batch processing and divided into different effective data sets (tables), and the corresponding operating state data and the corresponding micro batch processing result are added to the target result table according to the sequence of the timestamps, as shown in fig. 2, TIME WINDOW represents a TIME WINDOW, and KV STORE represents a KV cache.
As an optional implementation manner of the embodiment of the present invention, the obtaining a micro batch processing result of the data source performance data by performing micro batch processing on the operation state data obtained in each preset time window includes: and transmitting the running state data acquired by each preset time window to a process of a pre-integrated algorithm according to a process communication mode for analysis and calculation to obtain a micro batch processing result of the data source performance data. Specifically, the running state data acquired in each preset time window is sent to a pre-integrated algorithm for analysis and calculation through an inter-process communication (IPC) mode.
In one embodiment, when the data source connected with the edge side device is an energy storage power station battery, the pre-integrated algorithm includes core algorithms such as battery SOC, SOH and equalization algorithm, the running state data acquired in every 10s is sent to the pre-integrated SOC/SOH through an inter-process communication (IPC) mode for calculation, and the specific calculation method is a general SOC/SOH calculation method including ampere-hour integration, open-circuit voltage and kalman filtering.
As an optional implementation manner in the embodiment of the present invention, after the micro batch processing is performed on the operation state data acquired in each preset time window to obtain a micro batch processing result of the data source performance data, the method further includes: and preprocessing the data of the target result table according to the received data use requirement and then sending the preprocessed data to a data use end. Specifically, the data in the target result table is converted into different forms according to the received use requirement, for example, the data is saved in a database and forwarded to a centralized control system.
In one embodiment, the data in the target result table is persisted as needed and forwarded to the centralized control platform or to the message queue.
As an optional implementation manner of the embodiment of the present invention, the data source connected to the edge side device includes: a plurality of energy storage units in an energy storage power station. Specifically, the energy storage power station is generally formed by collecting a plurality of battery energy storage units, and each battery energy storage unit includes a plurality of battery cells.
In one example, as shown in fig. 3, when the data source connected to the edge device is a battery, the operation state data of the battery is monitored in real time. Specifically, the method includes the steps of firstly obtaining running state data of a data source of a battery, defining a data stream formed by the data source and storing the data stream in a cache, then processing the running state data through a time window and a pre-integrated algorithm rule to obtain a structured data table (namely an effective data set), then obtaining a corresponding result table (namely a target result table) through micro batch processing, and finally processing the result table according to use requirements, wherein the method includes the following steps: persistent storage processing, sending to a message queue (message middleware), sending to the centralized control platform through a rest/rpc interface.
An embodiment of the present invention further provides a data processing apparatus, as shown in fig. 4, the apparatus includes:
an obtaining module 401, configured to obtain running state data of a data source connected to an edge side device; for details, refer to the related description of step S101 in the above method embodiment.
A storage module 402, configured to perform structured storage on the operation state data; for details, refer to the related description of step S102 in the above method embodiment.
A calculating module 403, configured to obtain operation state data of the data source from the structured storage result, and calculate the operation state data of the data source by using a pre-integrated algorithm to obtain performance data of the data source; for details, refer to the related description of step S103 in the above method embodiment.
The data processing device provided by the embodiment of the invention is applied to the edge side equipment, wherein the edge side equipment is pre-integrated with a plurality of algorithms for calculating the performance data of the data source connected with the edge side equipment, and acquires the running state data of the data source connected with the edge side equipment; performing structured storage on the running state data; and acquiring the running state data of the data source from the structured storage result, and calculating the running state data of the data source by using a pre-integrated algorithm to obtain the performance data of the data source. The device integrates various algorithms in advance in the edge side equipment to calculate the data of the data source, overcomes the influence of network interference on data transmission, reduces the time delay and improves the real-time performance of monitoring.
As an optional implementation manner of the embodiment of the present invention, the storage module includes: the first storage module is used for storing the running state data in a pre-established cache region according to a preset structured type and a timestamp of the running state data; and the second storage module is used for synchronizing the cache result to the secondary storage device.
As an optional implementation manner of the embodiment of the present invention, the apparatus further includes: the first acquisition module is used for acquiring the running state data of the data source from the cache region according to a preset time window; the third storage module is used for additionally storing the running state data acquired in each preset time window to the tail of the target data table; and the processing module is used for carrying out micro batch processing on the running state data acquired in each preset time window to obtain a micro batch processing result of the data source performance data and additionally storing the micro batch processing result at the tail of the target result table.
As an optional implementation manner of the embodiment of the present invention, the apparatus further includes: and the analysis and calculation module is used for transmitting the running state data acquired by each preset time window to a process of a pre-integrated algorithm according to a process communication mode to perform analysis and calculation to obtain a micro batch processing result of the data source performance data.
As an optional implementation manner of the embodiment of the present invention, the apparatus further includes: and the sending module is used for preprocessing the data of the target result table according to the received data use requirement and then sending the preprocessed data to a data use end.
As an optional implementation manner of the embodiment of the present invention, the data source connected to the edge side device includes: a plurality of energy storage units in an energy storage power station.
For a functional description of the data processing apparatus provided in the embodiment of the present invention, reference is made in detail to the description of the data processing method in the above embodiment.
An embodiment of the present invention further provides a storage medium, as shown in fig. 5, on which a computer program 601 is stored, where the instructions, when executed by a processor, implement the steps of the data processing method in the foregoing embodiments. The storage medium is also stored with audio and video stream data, characteristic frame data, interactive request signaling, encrypted data, preset data size and the like. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
An embodiment of the present invention further provides an electronic device, as shown in fig. 6, the electronic device may include a processor 51 and a memory 52, where the processor 51 and the memory 52 may be connected by a bus or in another manner, and fig. 6 takes the connection by the bus as an example.
The processor 51 may be a Central Processing Unit (CPU). The Processor 51 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof.
The memory 52, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as the corresponding program instructions/modules in the embodiments of the present invention. The processor 51 executes various functional applications and data processing of the processor by executing non-transitory software programs, instructions and modules stored in the memory 52, that is, implements the data processing method in the above method embodiment.
The memory 52 may include a storage program area and a storage data area, wherein the storage program area may store an operating device, an application program required for at least one function; the storage data area may store data created by the processor 51, and the like. Further, the memory 52 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 52 may optionally include memory located remotely from the processor 51, and these remote memories may be connected to the processor 51 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 52 and, when executed by the processor 51, perform the data processing method in the embodiment shown in fig. 1-3.
The details of the electronic device may be understood by referring to the corresponding descriptions and effects in the embodiments shown in fig. 1 to fig. 3, and are not described herein again.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (10)
1. A data processing method is applied to an edge side device, the edge side device integrates a plurality of algorithms for calculating performance data of a data source connected with the edge side device in advance, and the method comprises the following steps:
acquiring running state data of a data source connected with edge side equipment;
performing structured storage on the running state data;
and acquiring the running state data of the data source from the structured storage result, and calculating the running state data of the data source by using a pre-integrated algorithm to obtain the performance data of the data source.
2. The method of claim 1, wherein the structured storage of the operating state data comprises:
storing the running state data in a pre-established cache region according to a preset structured type and a timestamp of the running state data;
and synchronizing the cached results into the secondary storage device.
3. The method of claim 2, wherein obtaining the operating state data of the data source from the structured storage result and calculating the operating state data of the data source using a pre-integrated algorithm to obtain the performance data of the data source comprises:
acquiring running state data of a data source from a cache region according to a preset time window;
additionally storing the operating state data acquired in each preset time window to the tail of a target data table;
and carrying out micro batch processing on the operation state data acquired in each preset time window to obtain a micro batch processing result of the data source performance data, and additionally storing the micro batch processing result at the tail of the target result table.
4. The method according to claim 3, wherein the obtaining of the micro-batch processing result of the data-source performance data by micro-batch processing the operation state data acquired at each preset time window comprises:
and transmitting the running state data acquired by each preset time window to a process of a pre-integrated algorithm according to a process communication mode for analysis and calculation to obtain a micro batch processing result of the data source performance data.
5. The method according to claim 4, wherein after the micro-batch processing of the operation state data acquired in each preset time window is performed to obtain a micro-batch processing result of the data source performance data, the method further comprises:
and preprocessing the data of the target result table according to the received data use requirement and then sending the preprocessed data to a data use end.
6. The method of claim 1, wherein the data source connected to the edge side device comprises: a plurality of energy storage units in an energy storage power station.
7. A data processing apparatus, applied to an edge-side device, the edge-side device pre-integrating a plurality of algorithms for calculating performance data of a data source connected thereto, comprising:
the acquisition module is used for acquiring the running state data of a data source connected with the edge side equipment;
the storage module is used for carrying out structured storage on the running state data;
and the calculation module is used for acquiring the running state data of the data source from the structured storage result and calculating the running state data of the data source by utilizing a pre-integrated algorithm to obtain the performance data of the data source.
8. The apparatus of claim 7, wherein the storage module comprises:
the first storage module is used for storing the running state data in a pre-established cache region according to a preset structured type and a timestamp of the running state data;
and the second storage module is used for synchronizing the cache result to the secondary storage device.
9. A computer-readable storage medium storing computer instructions for causing a computer to perform the data processing method of any one of claims 1 to 6.
10. An electronic device, comprising: a memory and a processor, communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to perform the data processing method according to any one of claims 1 to 6.
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| CN202210076325.2A CN114547190A (en) | 2022-01-21 | 2022-01-21 | Data processing method and device, storage medium and electronic equipment |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116418124A (en) * | 2023-06-12 | 2023-07-11 | 广东采日能源科技有限公司 | Micro-grid control system and energy storage power station control system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116418124A (en) * | 2023-06-12 | 2023-07-11 | 广东采日能源科技有限公司 | Micro-grid control system and energy storage power station control system |
| CN116418124B (en) * | 2023-06-12 | 2023-10-13 | 广东采日能源科技有限公司 | Micro-grid control system and energy storage power station control system |
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Application publication date: 20220527 |