Data processing system and method based on 5G communication intelligent gateway

Abstract

The invention belongs to the technical field of electric power. The invention provides a data processing system and method based on a 5G communication intelligent gateway. The system comprises a data processing module, a 5G communication module, a wired communication module and a storage module, the 5G communication module comprises two communication frequency bands, and an electric power communication protocol library is stored in the storage module; wherein the processing module is used for deciding whether to perform 5G communication connection with a power dispatching system based on the power communication protocol library, and deciding to obtain a communication strategy with the power dispatching system based on the real-time operation data, transmitted by the wired communication module, of the power equipment; the 5G communication module is used for being in communication connection with the power dispatching system, and the wired communication module is used for being in communication connection with the power devices. According to the invention, the processing of the real-time operation data of the power equipment in the 5G communication intelligent gateway is realized, so that the uploading strategy of the real-time operation data is optimized.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a data processing system and method based on a 5G communication intelligent gateway. Background Art

[0002] The power system needs to conduct unified command and dispatch for power generation, transmission, transformation, distribution and consumption to ensure the safe, economical, reliable and efficient operation of the power system. Power dispatching requires the communication gateway to transmit the real-time operation data of each power device to the dispatching system. The dispatching system analyzes the real-time operation data of each power device to obtain the corresponding dispatching instructions, and transmits the dispatching instructions to the corresponding power device through the communication gateway.

[0003] Traditional communication gateways have poor communication capabilities and are unable to cope with the up and down transmission of massive dispatching data in today's increasingly complex power grid systems, especially when uploading real-time operating data of power equipment. Due to the larger amount of data, the upload rate is low, resulting in the dispatching system's dispatching decisions not being accurate and timely. There are already some 5G-based communication gateways, but these generally have many obvious shortcomings in data processing, resulting in a large room for improvement in the upload strategy of real-time operating data of power equipment, which cannot meet the expected goals of the power dispatching system. The following technical solution of the present invention is intended to improve the above-mentioned technical problems. Summary of the invention

[0004] In this regard, the present invention provides a data processing method, system, electronic device, computer storage medium and computer program product based on a 5G communication intelligent gateway to solve the above-mentioned technical problems.

[0005] The present invention provides a data processing system based on a 5G communication intelligent gateway, the system comprising a data processing module, a 5G communication module, a wired communication module, and a storage module, the 5G communication module comprising two communication frequency bands, and the storage module storing a power communication protocol library; wherein, The processing module is used to decide whether to establish a 5G communication connection with the power dispatching system based on the power communication protocol library, and to decide on a communication strategy with the power dispatching system based on the real-time operation data of each of the power devices transmitted by the wired communication module; The 5G communication module is used to establish a communication connection with the electric power dispatching system, and the wired communication module is used to establish a communication connection with each of the electric power equipment.

[0006] The present invention also provides a data processing method based on a 5G communication intelligent gateway. The method is based on the aforementioned system and comprises the following steps: The processing module receives the real-time operation data of each power device transmitted through the wired communication module; The processing module dispatches the identification module to identify the special identification of each of the real-time operation data, and classifies the real-time operation data with the special identification into the first type; wherein each of the special identifications is stored in the special identification library of the storage module; The processing module further dispatches the identification prediction module to perform in-depth analysis and prediction processing on the real-time operation data without special identification, obtain corresponding data urgency, and classify the real-time operation data without special identification into the first type or the second type according to the data urgency; The real-time operation data of the first type is transmitted to the electric power dispatching system through the millimeter wave frequency band, and the real-time operation data of the second type is transmitted to the electric power dispatching system through the Sub-6 GHz frequency band.

[0007] In some embodiments, the processing module dispatches the identification module to perform special identification on each of the real-time operation data, and classifies the real-time operation data with special identification into a first type, including: The processing module obtains the data header information of the real-time operation data during the transmission process, and extracts the identification of the data header information; If several identifiers are extracted, each identifier is matched and calculated with each special identifier in the special identifier library. If any identifier matches successfully, the real-time operation data is judged as having a special identifier, otherwise the real-time operation data is judged as not having a special identifier.

[0008] In some embodiments, the processing module further dispatches the identification prediction module to perform in-depth analysis and prediction processing on the real-time operation data without special identification to obtain the corresponding data urgency, including: Decomposing the real-time operation data without any special identification into a data header part and a data payload part; The first prediction model of the identification prediction module performs in-depth analysis and prediction on the data header portion to obtain a first data urgency; The second prediction model of the identification prediction module performs in-depth analysis and prediction on the data load portion to obtain a second data urgency; The data urgency is obtained by performing weighted calculation according to the first data urgency, the second data urgency and corresponding weighted weights.

[0009] In some embodiments, performing weighted calculation according to the first data urgency, the second data urgency and corresponding weights to obtain the data urgency includes: Performing weighted calculation according to the first data urgency, the second data urgency and corresponding weighted weights to obtain an initial data urgency; Use the fine-tuned GPT model to perform semantic analysis on the real-time operation data and related information of the power dispatching system, evaluate the data urgency probability of the real-time operation data, and convert the correction coefficient according to the data urgency probability; The target data urgency is obtained by multiplying the initial data urgency by the correction factor.

[0010] In some embodiments, the correction coefficient is calculated based on the data urgency probability, including: ; In the formula, is the correction factor, is the data urgency probability, is the weighted weight of the urgency of the first data, is the weighted weight of the urgency of the second data; , is the corresponding conversion factor, is a constant.

[0011] In some embodiments, classifying the real-time operation data without a special identifier into the first type or the second type according to the data urgency includes: If the data urgency is higher than the urgency threshold, the real-time operation data is classified as the first type; if the data urgency is not higher than the urgency threshold, the real-time operation data is classified as the second type.

[0012] The present invention also discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement any of the above methods.

[0013] The present invention also discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement any of the above methods.

[0014] The present invention also discloses a computer program product, characterized in that: the computer program includes a number of computer codes, and when the computer codes are executed by a processor, any of the above methods is implemented.

[0015] The above-mentioned data processing system of the present invention can enable the 5G communication intelligent gateway to more intelligently determine the communication strategy with the power dispatching system, so that the power dispatching system can obtain the real-time operation data of the power equipment more timely, and then make more reasonable and timely dispatching plans, thereby improving the operation safety and efficiency of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a structural diagram of a data processing system based on a 5G communication intelligent gateway disclosed in an embodiment of the present invention; Figure 2 is a schematic diagram of the structure of the identification prediction module disclosed in the embodiment of the present invention; Figure 3 It is a flow chart of a data processing method based on a 5G communication intelligent gateway disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0019] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0020] like Figure 1 As shown, an embodiment of the present invention discloses a data processing system based on a 5G communication intelligent gateway, the system includes a data processing module, a 5G communication module, a wired communication module, and a storage module, the 5G communication module includes two communication frequency bands, and the storage module stores a power communication protocol library; wherein, The processing module is used to decide whether to establish a 5G communication connection with the power dispatching system based on the power communication protocol library, and to decide on a communication strategy with the power dispatching system based on the real-time operation data of each of the power devices transmitted by the wired communication module; The 5G communication module is used to establish a communication connection with the electric power dispatching system, and the wired communication module is used to establish a communication connection with each of the electric power equipment.

[0021] The present invention constructs a data processing system based on a 5G communication intelligent gateway, which includes the above-mentioned data processing module, 5G communication module, wired communication module, and storage module. The 5G communication module is used to transmit data with a remote power dispatching system through 5G communication technology, and the wired communication module is used to transmit data with various power equipment on the field. In addition, the storage module also stores a power communication protocol library, which includes various protocols that can be supported by the 5G communication intelligent gateway, such as MODBUS RTU / TCP master and slave, CDT master and slave, IEC101 master and slave, IEC103 serial / network master, IEC104 master and slave, IEC61850 server and client, electric meter DL645-1997, DL645-2007, DLT698.45 protocol, Nanzhi Ethernet 103 master and slave, Nanrui Ethernet / serial 103, Jinzhi Ethernet 103, Xuji serial 103, Ethernet 103, 104, Tianzheng Mingri Ethernet 103, Sifang Protection CSC2000 Client, server, PLC protocols of Siemens / Schneider / Panasonic / Mitsubishi / Omron / GE / AB / Delta / Yahong / Xinjie, etc., universal acquisition protocol, State Grid Cloud (photovoltaic poverty alleviation power station), Ethernet to serial transparent transmission, Langxin / Xinyao photovoltaic platform, Chint Zhongzi photovoltaic platform, Alibaba Cloud IoT / Tuya Smart / China Unicom / Amazon / Genyun 3.0 / Genyun 4.0 / Sany Heavy Industry / Chint IoT / Dianxiang / Instruction Set / Guangyuan / Dingkong / Sanshui Smart / Jinghe / Fangzhu, etc. IoT, MQTT platforms, various inverters for new energy, weather station protocols, etc. The 5G communication intelligent gateway of the present invention runs the LPC data acquisition core software platform (referred to as LPC software). When the gateway device is started, the LPC software reads the configured project and dynamically loads the power communication protocol library required according to the configured project. When developing a new communication protocol or expanding an existing communication protocol, it does not affect the stability of other communication protocols of the original system.

[0022] In addition, the processing module analyzes whether the connected power dispatching system belongs to the above-mentioned power communication protocol library. If it does, it is connected through 5G communication. At the same time, it also makes decisions based on the real-time operation data of each power equipment transmitted by the wired communication module to derive the communication strategy with the power dispatching system.

[0023] The above-mentioned data processing system of the present invention can enable the 5G communication intelligent gateway to more intelligently determine the communication strategy with the power dispatching system, so that the power dispatching system can obtain the real-time operation data of the power equipment more timely, and then make more reasonable and timely dispatching plans, thereby improving the operation safety and efficiency of the power system.

[0024] Among them, the power equipment can be a photovoltaic inverter, a grid-connected cabinet, etc., and the wired communication module supports WLAN network, power carrier network or 485 wired network, etc.

[0025] like Figure 3 As shown, the embodiment of the present invention further discloses a data processing method based on a 5G communication intelligent gateway. The method is based on the aforementioned system and comprises the following steps: The processing module receives the real-time operation data of each power device transmitted through the wired communication module; The processing module dispatches the identification module to identify the special identification of each of the real-time operation data, and classifies the real-time operation data with the special identification into the first type; wherein each of the special identifications is stored in the special identification library of the storage module; The processing module further dispatches the identification prediction module to perform in-depth analysis and prediction processing on the real-time operation data without special identification, obtain corresponding data urgency, and classify the real-time operation data without special identification into the first type or the second type according to the data urgency; The real-time operation data of the first type is transmitted to the electric power dispatching system through the millimeter wave frequency band, and the real-time operation data of the second type is transmitted to the electric power dispatching system through the Sub-6 GHz frequency band.

[0026] In this embodiment, the 5G communication module of the present invention supports two 5G communication frequency bands, namely the Sub-6 GHz frequency band (FR1 frequency band) and the millimeter wave frequency band (FR2 frequency band).

[0027] Among them, the Sub-6 GHz band is the low frequency band of the 5G network, with a frequency range from 450MHz to 6GHz. This band is characterized by strong signal penetration and is suitable for providing wide coverage and indoor coverage. Some common FR1 bands include: n77 (3300-3800MHz), n78 (3300-3800MHz), n79 (4400-5000MHz), n41 (2500-2690MHz, also known as TD-LTEB5).

[0028] The millimeter wave band is a high frequency band for 5G networks, with frequencies ranging from 24.25 GHz to 52.6 GHz. The millimeter wave band provides extremely high data transmission rates, but the signal coverage is small and is easily affected by physical obstacles. Some common FR2 bands include: n257 (24.25-27.5GHz), n258 (24.25-29.5GHz), n260 (37-40GHz), n261 (27.5-28.35GHz).

[0029] Based on the characteristics of the above two 5G communication frequency bands, the present invention is configured to analyze and process the real-time operation data of the power equipment transmitted by the wired communication module, and divide them into a first type and a second type, respectively. The first type corresponds to emergency transmission data, and the second type corresponds to non-urgent transmission data. For urgent transmission data, a millimeter wave frequency band with a higher transmission rate is used for transmission, while for non-urgent transmission data, a Sub-6 GHz frequency band with a lower transmission rate but a wider coverage range is used for transmission. Through the mutual cooperation of the two 5G communication frequency bands, the orderly and hierarchical data transmission between the 5G communication intelligent gateway and the power dispatching system is realized, which can improve the operating safety and efficiency of the power system.

[0030] Each electric power equipment can mark the real-time operation data generated by it with a special mark according to the preset rules. The special mark is used to indicate to the processing module that it belongs to urgent transmission data. The mark recognition module in the processing module identifies the special mark based on the special mark library in the storage module, thereby classifying the real-time operation data into the first type. In addition, since there may be delays in the update of the special mark library, some special marks are not synchronously updated to the special mark library, and the mark recognition module cannot recognize that they belong to urgent transmission data, or the electric power equipment does not mark any special mark for some real-time operation data, but the real-time operation data is objectively determined to be urgent transmission data for the electric power dispatching system. In view of this situation, the present invention further sets up a mark prediction module, which uses the mark prediction module to perform in-depth analysis and prediction processing on those real-time operation data without special marks, and obtain the corresponding data urgency. According to the data urgency, the real-time operation data without special marks can be divided into the first type or the second type.

[0031] Among them, taking photovoltaic inverters as an example, the urgently transmitted data is, for example, fault alarm information: any fault or abnormal state detected by the inverter, such as overheating, overload, insulation failure, etc., needs to be reported immediately for rapid response and maintenance. Protection action signal: data generated when the automatic protection mechanism of the inverter is triggered (such as rapid shutdown or power-limited operation). These data are critical to system safety. Real-time power output: real-time power output data of the inverter. For grid operators, understanding real-time power is crucial for grid stability and demand response. Key performance parameters: real-time data of key performance parameters such as efficiency, current, and voltage. These data are critical for monitoring system performance and optimizing operation. Predictive maintenance data: the usage status and expected life of certain key components of the inverter (such as fans and capacitors). These data help preventive maintenance and reduce unexpected downtime.

[0032] Examples of non-urgent data include historical performance data: historical operating data of the inverter, such as daily, monthly, and annual power generation statistics. These data are useful for analyzing long-term performance trends and making maintenance plans, but are not required to be transmitted in real time. Environmental monitoring data: Environmental data of the inverter's location, such as temperature, humidity, etc. These data are helpful for understanding the impact of the environment on system performance, but are not urgent data. System configuration information: Configuration settings of the inverter, such as operating mode, parameter settings, etc. This information is useful for system management and maintenance personnel, but does not need to be updated in real time. Maintenance records: Maintenance and repair records of the inverter. These data help record the maintenance history of the equipment, but are not required to be transmitted in real time. Status log: The inverter's operation log records all operations and status changes of the equipment. These data are helpful for fault analysis and system monitoring, but are not urgent data.

[0033] In some embodiments, the processing module dispatches the identification module to perform special identification on each of the real-time operation data, and classifies the real-time operation data with special identification into a first type, including: The processing module obtains the data header information of the real-time operation data during the transmission process, and extracts the identification of the data header information; If several identifiers are extracted, each identifier is matched and calculated with each special identifier in the special identifier library. If any identifier matches successfully, the real-time operation data is judged as having a special identifier, otherwise the real-time operation data is judged as not having a special identifier.

[0034] In this embodiment, when the power equipment is transmitting data to the 5G communication intelligent gateway, the processing module immediately obtains the data header information of the real-time operation data, analyzes whether there is an identifier in the data header, and if there is (at least one), matches and calculates the identifier with each special identifier in the special identifier library. If one identifier matches successfully, the real-time operation data is judged to have a special identifier, otherwise the real-time operation data is judged to have no special identifier. With this arrangement, it is possible to determine which type of data it belongs to in a short time before or after the completion of the real-time operation data transmission, so that its 5G communication frequency band can be quickly determined for rapid transmission.

[0035] It should be noted that the header is the beginning of the data packet, which contains metadata for data transmission and processing. In the power system, the header can be used to mark the priority, type, source, destination and other information of the data, and the priority tag is the above-mentioned identifier.

[0036] In some embodiments, Figure 2As shown, the processing module also dispatches the identification prediction module to perform in-depth analysis and prediction processing on the real-time operation data without special identification, and obtains the corresponding data urgency, including: Decomposing the real-time operation data without any special identification into a data header part and a data payload part; The first prediction model of the identification prediction module performs in-depth analysis and prediction on the data header portion to obtain a first data urgency; The second prediction model of the identification prediction module performs in-depth analysis and prediction on the data load portion to obtain a second data urgency; The data urgency is obtained by performing weighted calculation according to the first data urgency, the second data urgency and corresponding weighted weights.

[0037] In this embodiment, the data packet corresponding to the real-time operation data transmitted by the power equipment to the 5G communication intelligent gateway includes a data header part and a data payload part.

[0038] The data header includes: priority tag (urgent data is usually marked as high priority), data type (used to indicate whether the data is telemetry data (such as voltage, current), telesignaling data (such as circuit breaker status), remote control command or other types of data), source identifier (identifies which device or part of the power system the data comes from), timestamp (records the time when the data is generated), sequence number (used to track the order of data packets, especially in the case of data fragmentation or multi-packet transmission), checksum / CRC: (used to detect whether errors occur during data transmission), destination address (specifies the recipient of the data, especially in distributed or networked control systems), security information (may include encryption and authentication information to ensure the security of data transmission).

[0039] The data payload is the main part of the above data packet, which contains the information that actually needs to be transmitted, such as the voltage, current, power, temperature, equipment status, etc. of the power equipment.

[0040] Since the data types of the data header part and the data payload part and the degree of direct correlation with the data urgency are different, the present invention sets two prediction models, namely the first prediction model and the second prediction model, in the identification prediction module. The first prediction model is used to perform in-depth analysis and prediction on the data header part to obtain the first data urgency, and the second prediction model is used to perform in-depth analysis and prediction on the data payload part to obtain the second data urgency, and then the first data urgency and the second data urgency are weighted and averaged to obtain the final data urgency.

[0041] Among them, the weighted weights of the first data urgency and the second data urgency are preset and can be pre-specified according to the type of power equipment to which the real-time operating data belongs, and the details are not repeated here.

[0042] It should be noted that the first prediction model and the second prediction model in the identification prediction module are preferably constructed through a convolutional network. Since it belongs to a mature existing technology, the present invention does not elaborate on the construction and training process of the model.

[0043] In some embodiments, performing weighted calculation according to the first data urgency, the second data urgency and corresponding weights to obtain the data urgency includes: Performing weighted calculation according to the first data urgency, the second data urgency and corresponding weighted weights to obtain an initial data urgency; Use the fine-tuned GPT model to perform semantic analysis on the real-time operation data and related information of the power dispatching system, evaluate the data urgency probability of the real-time operation data, and convert the correction coefficient according to the data urgency probability; The target data urgency is obtained by multiplying the initial data urgency by the correction factor.

[0044] At the same time, the present invention also fine-tunes the existing general large model GPT model (such as GPT-4) to make it a proprietary model. The fine-tuned GPT model is used to perform semantic analysis on the real-time operation data of the power equipment and the relevant information of the power dispatching system, and the data urgency probability of the real-time operation data is evaluated, and then the correction coefficient is converted according to the data urgency probability. Therefore, the correction coefficient is used to correct the initial data urgency obtained above to the target data urgency, which is used as the final data urgency.

[0045] Among them, the real-time operation data of various power equipment and the related information of the paired power dispatching system are collected in advance, and the related information includes but is not limited to the dispatching function type (load forecasting, power generation dispatching, fault detection and location, safety analysis, emergency handling, load control, power quality monitoring, etc.) and dispatching level (regional level, central level) of the power dispatching system, and the probability label about the probability of data urgency is configured for this set of data, thereby forming a fine-tuning training data [real-time operation data, related information of the paired power dispatching system, probability label]. The general large model is fine-tuned using a set of the above-mentioned fine-tuning training data to obtain the above-mentioned proprietary model.

[0046] In some embodiments, the step of converting the correction coefficient according to the data urgency probability includes: ; In the formula, is the correction factor, is the data urgency probability, is the weighted weight of the urgency of the first data, is the weighted weight of the urgency of the second data; , is the corresponding conversion factor, is a constant.

[0047] In this embodiment, the above conversion formula provided by the present invention includes two parts: Part of it is to directly convert the data urgency probability predicted by the GPT model into the corresponding correction coefficient, and Part of it is to consider the distance between the weighted weights of the first data urgency and the second data urgency.

[0048] Specifically, since the data urgency probability predicted by the GPT model is based on the entire real-time operation data, and the first data urgency and the second data urgency are predicted based on the data header part and the data payload part of the real-time operation data, respectively. Therefore, when the weighted weights of the first data urgency and the second data urgency are closer, it means that the correlation between the data header part and the data payload part of the real-time operation data of this type of power equipment based on empirical values ​​and the data urgency of the real-time operation data is roughly the same; conversely, it means that the correlation between the data header part and the data payload part of the real-time operation data of this type of power equipment based on empirical values ​​and the data urgency of the real-time operation data is quite different. Therefore, the present invention is set in Parts and correction factors It is a positive correlation, that is, the greater the difference between the weighted weights of the two, the lower the credibility of the initial data urgency (taking the data urgency probability obtained by the GPT model based on the analysis of complete real-time operation data as a reference benchmark), and a larger correction coefficient is used to correct it; conversely, the higher the credibility of the initial data urgency, the smaller the correction coefficient is used to correct it.

[0049] It should be noted that the correction coefficient in the present invention basically corrects the urgency of the initial data to be larger (the correction coefficient is greater than 1), so as to avoid delays in uploading certain real-time operating data that do not have special identification but are actually urgent data to the power dispatching system.

[0050] In some embodiments, classifying the real-time operation data without a special identifier into the first type or the second type according to the data urgency includes: If the data urgency is higher than the urgency threshold, the real-time operation data is classified as the first type; if the data urgency is not higher than the urgency threshold, the real-time operation data is classified as the second type.

[0051] In this embodiment, by comparing the data urgency determined above with a preset urgency threshold, the real-time operation data can be classified into the first type or the second type.

[0052] An embodiment of the present invention further discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in the above embodiment.

[0053] An embodiment of the present invention further discloses a computer storage medium, wherein the computer storage medium stores a computer program, and the computer program is executed by a processor to implement the method described in the above embodiment.

[0054] The embodiment of the present invention further discloses a computer program product, characterized in that: the computer program includes a number of computer codes, and when the computer codes are executed by a processor, any of the above methods is implemented.

[0055] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0056] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0057] The above-mentioned 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 invention patent. 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 patent of the present application shall be subject to the attached claims.

Claims

1. A data processing system based on a 5G communication intelligent gateway, characterized in that: The system includes a data processing module, a 5G communication module, a wired communication module, and a storage module. The 5G communication module includes two communication frequency bands. The storage module stores a power communication protocol library. The processing module is used to decide whether to establish a 5G communication connection with the power dispatching system based on the power communication protocol library, and to decide on a communication strategy with the power dispatching system based on the real-time operation data of each of the power devices transmitted by the wired communication module; The 5G communication module is used to establish a communication connection with the electric power dispatching system, and the wired communication module is used to establish a communication connection with each of the electric power equipment.

2. A data processing method based on a 5G communication intelligent gateway, the method is based on the system according to claim 1, characterized in that: The method comprises the following steps: The processing module receives the real-time operation data of each power device transmitted through the wired communication module; The processing module dispatches the identification module to identify the special identification of each of the real-time operation data, and classifies the real-time operation data with the special identification into the first type; wherein each of the special identifications is stored in the special identification library of the storage module; The processing module also dispatches the identification prediction module to perform in-depth analysis and prediction processing on the real-time operation data without special identification, obtain corresponding data urgency, and classify the real-time operation data without special identification into the first type or the second type according to the data urgency; The real-time operation data of the first type is transmitted to the electric power dispatching system through the millimeter wave frequency band, and the real-time operation data of the second type is transmitted to the electric power dispatching system through the Sub-6 GHz frequency band.

3. According to claim 2, a data processing method based on a 5G communication intelligent gateway is characterized in that: The processing module dispatches the identification identification module to identify the special identification of each of the real-time operation data, and classifies the real-time operation data with the special identification into the first type, including: The processing module obtains the data header information of the real-time operation data during the transmission process, and extracts the identification of the data header information; If several identifiers are extracted, each identifier is matched and calculated with each special identifier in the special identifier library. If any identifier matches successfully, the real-time operation data is judged as having a special identifier, otherwise the real-time operation data is judged as not having a special identifier.

4. According to claim 3, a data processing method based on a 5G communication intelligent gateway is characterized in that: The processing module also dispatches the identification prediction module to perform in-depth analysis and prediction processing on the real-time operation data without special identification, and obtains the corresponding data urgency, including: Decomposing the real-time operation data without any special identification into a data header part and a data payload part; The first prediction model of the identification prediction module performs in-depth analysis and prediction on the data header portion to obtain a first data urgency; The second prediction model of the identification prediction module performs in-depth analysis and prediction on the data load portion to obtain a second data urgency; The data urgency is obtained by performing weighted calculation according to the first data urgency, the second data urgency and corresponding weighted weights.

5. A data processing method based on a 5G communication intelligent gateway according to claim 4, characterized in that: Performing weighted calculation according to the first data urgency, the second data urgency and corresponding weights to obtain the data urgency includes: Performing weighted calculation according to the first data urgency, the second data urgency and corresponding weighted weights to obtain an initial data urgency; Use the fine-tuned GPT model to perform semantic analysis on the real-time operation data and related information of the power dispatching system, evaluate the data urgency probability of the real-time operation data, and convert the correction coefficient according to the data urgency probability; The target data urgency is obtained by multiplying the initial data urgency by the correction factor.

6. A data processing method based on a 5G communication intelligent gateway according to claim 5, characterized in that: The correction factor is calculated based on the emergency probability of the data, including: ; In the formula, is the correction factor, is the data urgency probability, is the weighted weight of the urgency of the first data, is the weighted weight of the urgency of the second data; , is the corresponding conversion factor, is a constant.

7. A data processing method based on a 5G communication intelligent gateway according to claim 2, characterized in that: Classifying the real-time operation data without a special identifier into the first type or the second type according to the data urgency includes: If the data urgency is higher than the urgency threshold, the real-time operation data is classified as the first type; if the data urgency is not higher than the urgency threshold, the real-time operation data is classified as the second type.

8. An electronic device comprising: At least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method according to any one of claims 2 to 7.

9. A computer storage medium storing a computer program, characterized in that: The computer program is executed by a processor to implement the method according to any one of claims 2 to 7.

10. A computer program product, characterized in that: The computer program includes a number of computer codes, and when the computer codes are executed by a processor, the method according to any one of claims 2 to 7 is implemented.

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