Power data transmission method and system

Abstract

The invention discloses an electric power data transmission method and system, and relates to the technical field of data transmission. On the basis of carrying out rough classification on existing electric power data to be transmitted, further scientific screening based on data driving is carried out on the electric power data; various indexes of real-time electric power data including real-time performance, importance and emergency degree are analyzed, including intervention of optimization weights, so that electric power data with optimization scores lower than a threshold value in the real-time electric power data are screened out, but in order to still ensure the integrity of the data, the electric power data are not completely eliminated, and the data are not completely eliminated. According to the method, real-time electric power data and non-real-time electric power data are completely classified into the non-real-time electric power data, the optimized real-time electric power data and the non-real-time electric power data which are more scientifically and accurately classified are further obtained through the whole screening process, priorities are set for the further classified electric power data on the basis, transmission is executed, the problem of data transmission delay can be effectively solved, and the data transmission efficiency is improved. Therefore, the influence on the response speed of the system can be effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a method and system for power data transmission. Background Art

[0002] The power data transmission method generally refers to the technology of transmitting data by using the existing power lines, which is called power line communication. The accurate transmission of power data can effectively ensure the accuracy and reliability of data during the transmission process. In order to ensure the accurate transmission of power data, the following series of technical means are often used to achieve the above purpose. The existing methods for implementing accurate power data transmission mainly include the following aspects:

[0003] Modulation and demodulation technology: using advanced modulation and demodulation technologies, such as orthogonal frequency division multiplexing and orthogonal amplitude modulation, these technologies can effectively improve the robustness and bandwidth utilization of data transmission. Orthogonal frequency division multiplexing reduces the impact of multipath effects and improves the stability of transmission by distributing data on multiple subcarriers; using efficient channel coding technologies, such as low-density parity check codes and turbo codes, these coding technologies can correct errors during transmission, reduce bit error rates, and improve data integrity; there is a lot of electromagnetic interference and noise in the power line environment, so it is necessary to use noise suppression technologies, such as adaptive filters and frequency domain equalization, to reduce the impact of noise on data transmission; in order to ensure accurate data transmission, it is necessary to achieve accurate time synchronization and frequency synchronization. Time synchronization technology can calibrate the clock of the receiving end by sending synchronization signals, and frequency synchronization technology maintains the stability of transmission by frequency deviation estimation and compensation; at the high-level protocol level, by optimizing the transmission protocol, such as using the automatic retransmission request mechanism, the reliable transmission of data packets is ensured. In addition, the accuracy of data transmission is further improved by data slicing.

[0004] Although the existing power data precision transmission technology has made some progress, it still faces the following defects in practical applications:

[0005] In some application scenarios, such as real-time control and monitoring, high load and complex network topology application scenarios, the delay requirements for data transmission are very high, especially when processing large amounts of data, delay problems are prone to occur. If only simple data classification is used and the data transmission priority is set according to the classification results, it is obviously difficult to effectively solve the problem of data transmission delay, which can still easily affect the response speed of the system, and then easily lead to system performance degradation and poor user experience. In some key applications such as real-time control of smart grids and video transmission of telemedicine, it may even lead to serious security risks and economic losses.

[0006] Therefore, the prior art urgently needs a technical solution for a power data transmission method and system. Summary of the invention

[0007] In order to solve the above technical problems, the present invention provides a method for power data transmission, which specifically comprises the following steps:

[0008] Step S1, obtaining the power data to be transmitted by the current node;

[0009] Step S2: dividing the power data to be transmitted into real-time power data and non-real-time power data according to the real-time characteristics of data transmission;

[0010] Step S3: further analyzing the real-time power data to obtain optimized real-time power data and optimized non-real-time power data;

[0011] Step S3a, performing real-time analysis on each power data in the real-time power data to obtain a real-time index of each power data;

[0012] Step S3a1, obtaining the generation time of each power data;

[0013] Step S3a2, obtaining the expected arrival time of each power data;

[0014] Step S3a3, obtaining a real-time index of each power data according to the generation time and expected arrival time of each power data;

[0015] The calculation formula for obtaining the real-time index of each power data is:

[0016]

[0017] Among them, R i represents the real-time index of the ith power data in the real-time power data; T expected，i represents the expected arrival time of the ith power data in the real-time power data; T generated，i represents the generation time of the i-th power data in the real-time power data; ∈ represents a constant;

[0018] Step S3b, performing importance analysis on each power data in the real-time power data to obtain an importance index of each power data;

[0019] Step S3b1, obtaining application scenarios of each power data;

[0020] Step S3b2: Determine the importance of each power data according to the application scenario;

[0021] Step S3b3, converting the importance into a numerical value to obtain an importance index of each power data;

[0022] Step S3c, performing urgency analysis on each power data in the real-time power data to obtain an urgency index of each power data;

[0023] Step S3c1, obtaining the urgency of each power data;

[0024] Step S3c2: determining the emergency level of each power data according to the emergency level;

[0025] Step S3c3, converting the emergency level into a numerical value to obtain an emergency index for each power data;

[0026] Step S3d, obtaining an initial weight and a first weight of each power data according to the real-time index, the importance index and the urgency index of each power data, and obtaining an optimized weight of each power data according to the initial weight and the first weight;

[0027] Step S3d1: assigning an initial weight to each power data according to the importance index, and the initial weight is proportional to the importance index;

[0028] Step S3d2, obtaining a first ratio of the real-time index of each power data to the importance index of each power data;

[0029] Step S3d3, obtaining a second ratio of the urgency index of each power data to the importance index of each power data;

[0030] Step S3d4, obtaining a first weight for each power data according to the first ratio and the second ratio;

[0031] Step S3d5, obtaining the optimized weight of each power data according to the initial weight and the first weight;

[0032] Step S3e, obtaining an optimization score for each power data according to the real-time index, importance index, urgency index, initial weight, first weight, and optimization weight of each power data;

[0033] The calculation formula for obtaining the optimization score of each power data is:

[0034] S i =α·R i +β·I i +γ·E i +δ·W init，i +ζ·W first，i +η·W opt，i ;

[0035] Among them, S i represents the optimization score of the ith power data in the real-time power data; R i Represents the real-time index of the i-th power data in the real-time power data; I i represents the importance index of the ith power data in the real-time power data; E i represents the urgency index of the i-th power data in the real-time power data; W init，i represents the initial weight of the i-th power data in the real-time power data; W first，i represents the first weight of the i-th power data in the real-time power data; W opt，i represents the optimization weight of the i-th power data in the real-time power data; α, β, γ, δ, ζ, η represent preset coefficients;

[0036] Step S3f, setting a threshold for the optimization score, and determining the optimization score of each power data according to the threshold, and obtaining optimized real-time power data and optimized non-real-time power data respectively;

[0037] Step S3f1: If the optimization score of the current power data is greater than or equal to the threshold, it is retained and still classified as real-time power data; if it is less than the threshold, it is removed from the real-time power data and classified as non-real-time power data;

[0038] Step S3f2, until all power data in the real-time power data are determined, then the real-time power data after determination is defined as optimized real-time power data, and the non-real-time power data is defined as optimized non-real-time power data;

[0039] Step S4, setting a transmission priority for the optimized real-time power data and the optimized non-real-time power data, wherein the transmission priority of the optimized real-time power data is greater than the transmission priority of the optimized non-real-time power data;

[0040] Step S5: Execute power data transmission according to the transmission priority.

[0041] A power data transmission system, which executes a power data transmission method as described above, comprises the following modules:

[0042] Data acquisition module: used to obtain the power data to be transmitted by the current node;

[0043] Data classification module: connected to the data acquisition module, used to classify the power data to be transmitted into real-time power data and non-real-time power data according to the real-time characteristics of data transmission;

[0044] Classification optimization module: connected to the data classification module, used to perform further analysis on the real-time power data to obtain optimized real-time power data and optimized non-real-time power data;

[0045] Priority setting module: connected to the classification optimization module, used to set the transmission priority of the optimized real-time power data and the optimized non-real-time power data, wherein the transmission priority of the optimized real-time power data is greater than the transmission priority of the optimized non-real-time power data;

[0046] Transmission execution module: connected to the priority setting module, used to execute power data transmission according to the transmission priority.

[0047] The embodiments of the present invention have the following technical effects:

[0048] The present invention performs further scientific screening based on data-driven on the basis of the existing rough classification of power data to be transmitted. In the further screening process, various indicators of real-time power data including real-time, importance and urgency are analyzed, including the intervention of optimization weights, so as to screen out power data with optimization scores lower than the threshold in the real-time power data. However, in order to ensure the integrity of the data, it is not completely eliminated, but thoroughly classified as non-real-time power data. Through the entire screening process, more scientifically and accurately classified optimized real-time power data and non-real-time power data are further obtained. On this basis, priority is set for the further classified power data and transmission is performed, which can effectively solve the problem of data transmission delay, thereby effectively reducing the impact on the response speed of the system, improving system performance, and avoiding serious safety risks and economic losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 is a flow chart of a power data transmission method provided by an embodiment of the present invention;

[0051] Figure 2 It is a framework diagram of a power data transmission system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0053] Embodiment 1: Figure 1 As shown, the present invention provides a method for transmitting power data, comprising the following steps:

[0054] Step S1, obtaining the power data to be transmitted by the current node;

[0055] Acquiring the power data to be transmitted by the current node usually involves the following steps: collecting real-time data of the power system through various sensors and monitoring devices installed in the power system, such as smart meters, voltage / current sensors, temperature sensors, etc.; aggregating the collected data to a central node or data concentrator, which can be achieved through wired or wireless means, such as using RS-485 interface, Ethernet, Wi-Fi, Zigbee and other communication technologies; preprocessing the aggregated data, including data cleaning, format conversion, timestamp synchronization, etc., to ensure the quality and consistency of the data; storing the preprocessed data in a temporary buffer or database, waiting for further processing and transmission; extracting the power data currently required to be transmitted from the stored data, which can be achieved by querying the database or reading the data directly from the buffer; encapsulating the extracted data into a data packet format suitable for transmission so that it can be transmitted through the power line; the power data obtained includes but is not limited to:

[0056] Electric energy data: record the user's electricity consumption, such as hourly electricity consumption, daily cumulative electricity consumption, etc.; voltage data: record the voltage value on the user side, such as voltage readings every minute; current data: record the current value on the user side, such as current readings every minute; power factor: record the user's power factor for evaluating power quality; temperature data: record the temperature of key equipment such as transformers and cables, such as temperature readings every minute; humidity data: record ambient humidity, such as humidity readings every hour; vibration data: record the vibration of equipment such as generators and transformers, such as vibration readings every minute; switch status: record the status of switch devices such as circuit breakers and relays, such as open or closed; fault alarm: record fault alarm information in the system, such as overload, short circuit, etc.; equipment health status: record the health status of key equipment, such as remaining service life, maintenance recommendations, etc.; weather data: record meteorological data such as wind speed, rainfall, and light intensity for predicting power demand and optimizing power generation plans; air quality data: record air quality data such as PM2.5 and PM10 for environmental monitoring and health management.

[0057] Step S2: dividing the power data to be transmitted into real-time power data and non-real-time power data according to the real-time characteristics of data transmission;

[0058] The power data to be transmitted is classified according to the real-time characteristics of data transmission. The specific classification basis is: in the smart grid system, different types of power data have different real-time transmission requirements. Real-time power data needs to be transmitted quickly in a short time to ensure the immediate response and control of the system; while non-real-time power data can tolerate a certain degree of delay and is usually used for analysis, reporting and long-term monitoring. The main basis for classification includes the purpose of the data, update frequency and sensitivity to delay.

[0059] Based on the above classification criteria, the following are the specific data of real-time power data and non-real-time power data:

[0060] The specific data of real-time power data include: Voltage data: updated once a minute, used to monitor the real-time voltage status of the power grid to ensure voltage stability. Current data: updated once a minute, used to monitor the real-time current status of the power grid to prevent overload. Power factor: updated once a minute, used to monitor the real-time power factor of the power grid and optimize the power quality. Temperature data: updated once a minute, used to monitor the real-time temperature of key equipment such as transformers and cables to prevent overheating. Vibration data: updated once a minute, used to monitor the real-time vibration of equipment such as generators and transformers to prevent mechanical failures. Switch status: event-triggered update, used to monitor the status of switch devices such as circuit breakers and relays in real time to ensure the normal operation of the system. Fault alarm: event-triggered update, used to monitor fault alarm information in the system in real time, such as overload, short circuit, etc., and take timely measures.

[0061] The specific data of non-real-time power data include:

[0062] Electricity data: updated every hour, used to record the user's electricity consumption for subsequent electricity bill settlement and electricity consumption analysis. Humidity data: updated every hour, used to monitor environmental humidity for environmental monitoring and health management.

[0063] Weather data: Updated every hour, used to record meteorological data such as wind speed, rainfall, and light intensity, to provide power demand forecasts and optimize power generation plans.

[0064] Air quality data: updated every hour, used to record PM2.5, PM10 and other air quality data for environmental monitoring and health management.

[0065] Equipment health status: Updated daily to record the health status of key equipment, such as remaining service life, maintenance recommendations, etc., for equipment maintenance and management.

[0066] Step S3, further analyzing the real-time power data to obtain optimized real-time power data and optimized non-real-time power data;

[0067] Step S3a, performing real-time analysis on each power data in the real-time power data to obtain a real-time index of each power data;

[0068] Step S3a1, obtaining the generation time of each power data;

[0069] Step S3a2, obtaining the expected arrival time of each power data;

[0070] The generation time refers to the specific time point when the power data is collected or generated. This time point is usually the time when data acquisition devices such as smart meters and sensors record data. The expected arrival time refers to the time when the power data is expected to arrive at the receiving end. This time point is usually determined based on the real-time requirements of the system and network transmission delays.

[0071] Step S3a3, obtaining a real-time index of each power data according to the generation time and expected arrival time of each power data;

[0072] The calculation formula for obtaining the real-time index of each power data is:

[0073]

[0074] Among them, R i represents the real-time index of the ith power data in the real-time power data; T expected，i represents the expected arrival time of the ith power data in the real-time power data; T generated，i represents the generation time of the i-th power data in the real-time power data; ∈ represents a constant;

[0075] Step S3b, performing importance analysis on each power data in the real-time power data to obtain an importance index of each power data;

[0076] Step S3b1, obtaining application scenarios of each power data;

[0077] Real-time power data is usually used for real-time monitoring, control and protection of the system, such as voltage, current, power factor, temperature, vibration, switch status and fault alarm data; non-real-time power data: this type of data is usually used for analysis, reporting and long-term monitoring, such as electric energy, humidity, weather data, air quality data and equipment health status data; specifically, voltage data: the application scenario is real-time monitoring. Current data: the application scenario is real-time monitoring. Power factor: the application scenario is real-time monitoring. Temperature data: the application scenario is real-time monitoring. Vibration data: the application scenario is real-time monitoring. Switch status: the application scenario is real-time monitoring. Fault alarm: the application scenario is real-time monitoring. Electric energy data: the application scenario is electricity bill settlement. Humidity data: the application scenario is environmental monitoring. Weather data: the application scenario is environmental monitoring. Air quality data: the application scenario is environmental monitoring. Equipment health status: the application scenario is equipment maintenance.

[0078] Step S3b2: Determine the importance of each power data according to the application scenario;

[0079] Importance refers to the criticality and impact of power data in a specific application scenario. The specific steps to determine the importance of each power data are as follows: refer to historical data and event records to analyze the performance and impact of each power data in actual applications. Then the importance is graded. High importance refers to data that is critical to system stability and safety, such as voltage, current, power factor, temperature, vibration, switch status, and fault alarms; medium importance refers to data that has a certain impact on system operation but is not critical, such as humidity, weather data, and air quality data; low importance refers to data that is mainly used for analysis and reporting, such as electric energy and equipment health status. Then determine the importance level of the power data in each application scenario. For example, the voltage data in the real-time monitoring application scenario is of high importance, and the electric energy data in the electricity bill settlement application scenario is of low importance.

[0080] Step S3b3, converting the importance into a numerical value to obtain an importance index of each power data;

[0081] The importance index is a quantitative representation of the importance of power data. The specific steps to convert the importance into a numerical value are as follows: high importance: assign a numerical value ranging from 0.8 to 1.0; medium importance: assign a numerical value ranging from 0.5 to 0.7; low importance: assign a numerical value ranging from 0.1 to 0.4;

[0082] According to the importance level, a specific importance index is assigned to each type of power data. For example: High importance: the importance index of voltage data is 0.9, and the importance index of current data is 0.85; Medium importance: the importance index of humidity data is 0.6, and the importance index of weather data is 0.55; Low importance: the importance index of electric energy data is 0.3, and the importance index of equipment health status is 0.2.

[0083] Step S3c, performing urgency analysis on each power data in the real-time power data to obtain an urgency index of each power data;

[0084] Step S3c1, obtaining the urgency of each power data;

[0085] Step S3c2: determining the emergency level of each power data according to the emergency level;

[0086] Step S3c3, converting the emergency level into a numerical value to obtain an emergency index for each power data;

[0087] It is worth noting that the method of obtaining the urgency index and the method of obtaining the importance index are similar in that both use historical data analysis to determine the importance or urgency, and both use a grading method and convert the grades into numerical values ​​for subsequent calculation and processing; but the difference is that steps S3c1 to S3c3 are more inclined to urgency analysis, while steps S3b1 to S3b3 are more inclined to urgency analysis, and although both use numerical ranges to represent importance or urgency, the specific numerical ranges and distributions may be different to reflect the characteristics of different attributes.

[0088] Step S3d, obtaining an initial weight and a first weight of each power data according to the real-time index, the importance index and the urgency index of each power data, and obtaining an optimized weight of each power data according to the initial weight and the first weight;

[0089] Step S3d1: assigning an initial weight to each power data according to the importance index, and the initial weight is proportional to the importance index;

[0090] Step S3d2, obtaining a first ratio of the real-time index of each power data to the importance index of each power data;

[0091] Step S3d3, obtaining a second ratio of the urgency index of each power data to the importance index of each power data;

[0092] Step S3d4, obtaining a first weight for each power data according to the first ratio and the second ratio;

[0093] Step S3d5, obtaining the optimized weight of each power data according to the initial weight and the first weight;

[0094] Step S3e, obtaining an optimization score for each power data according to the real-time index, importance index, urgency index, initial weight, first weight, and optimization weight of each power data;

[0095] The calculation formula for obtaining the optimization score of each power data is:

[0096] S i =α·R i +β·I i +γ·E i +δ·W init，i +ζ·W first，i +η·W opt，i ;

[0097] Among them, S i represents the optimization score of the ith power data in the real-time power data; R i Represents the real-time index of the i-th power data in the real-time power data; I i represents the importance index of the ith power data in the real-time power data; E i represents the urgency index of the i-th power data in the real-time power data; W init，i represents the initial weight of the i-th power data in the real-time power data; W first，i represents the first weight of the i-th power data in the real-time power data; W opt，i represents the optimization weight of the i-th power data in the real-time power data; α, β, γ, δ, ζ, η represent preset coefficients;

[0098] Step S3f, setting a threshold for the optimization score, and determining the optimization score of each power data according to the threshold, and obtaining optimized real-time power data and optimized non-real-time power data respectively;

[0099] Step S3f1: If the optimization score of the current power data is greater than or equal to the threshold, it is retained and still classified as real-time power data; if it is less than the threshold, it is removed from the real-time power data and classified as non-real-time power data;

[0100] Step S3f2, until all power data in the real-time power data are determined, then the real-time power data after determination is defined as optimized real-time power data, and the non-real-time power data is defined as optimized non-real-time power data;

[0101] Step S4, setting a transmission priority for the optimized real-time power data and the optimized non-real-time power data, wherein the transmission priority of the optimized real-time power data is greater than the transmission priority of the optimized non-real-time power data;

[0102] Step S5: Execute power data transmission according to the transmission priority.

[0103] Embodiment 2: Figure 2 As shown, the present invention also proposes a power data transmission system, which executes the power data transmission method as described above, and includes the following modules:

[0104] Data acquisition module: used to obtain the power data to be transmitted by the current node;

[0105] Data classification module: connected to the data acquisition module, used to classify the power data to be transmitted into real-time power data and non-real-time power data according to the real-time characteristics of data transmission;

[0106] Classification optimization module: connected to the data classification module, used to perform further analysis on the real-time power data to obtain optimized real-time power data and optimized non-real-time power data;

[0107] Priority setting module: connected to the classification optimization module, used to set the transmission priority of the optimized real-time power data and the optimized non-real-time power data, wherein the transmission priority of the optimized real-time power data is greater than the transmission priority of the optimized non-real-time power data;

[0108] Transmission execution module: connected to the priority setting module, used to execute power data transmission according to the transmission priority.

[0109] It should be noted that the terms used in the present invention are only for describing specific embodiments, rather than limiting the scope of the present application. As shown in the present specification, unless the context clearly indicates an exception, the words "one", "a", "a kind of" and / or "the" do not specifically refer to the singular, but may also include the plural. The terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method or device. In the absence of more restrictions, the elements defined by the sentence "include one..." do not exclude the presence of other identical elements in the process, method or device including the elements.

[0110] It should also be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", etc. should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for transmitting power data, characterized in that: The following steps are involved: Step S1, obtaining the power data to be transmitted by the current node; Step S2: dividing the power data to be transmitted into real-time power data and non-real-time power data according to the real-time characteristics of data transmission; Step S3: further analyzing the real-time power data to obtain optimized real-time power data and optimized non-real-time power data; Step S4, setting a transmission priority for the optimized real-time power data and the optimized non-real-time power data, wherein the transmission priority of the optimized real-time power data is greater than the transmission priority of the optimized non-real-time power data; Step S5: Execute power data transmission according to the transmission priority.

2. The power data transmission method according to claim 1, characterized in that: The further analysis of the real-time power data to obtain optimized real-time power data and optimized non-real-time power data respectively includes: Step S3a, performing real-time analysis on each power data in the real-time power data to obtain a real-time index of each power data; Step S3b, performing importance analysis on each power data in the real-time power data to obtain an importance index of each power data; Step S3c, performing urgency analysis on each power data in the real-time power data to obtain an urgency index of each power data; Step S3d, obtaining an initial weight and a first weight of each power data according to the real-time index, the importance index and the urgency index of each power data, and obtaining an optimized weight of each power data according to the initial weight and the first weight; Step S3e, obtaining an optimization score for each power data according to the real-time index, importance index, urgency index, initial weight, first weight, and optimization weight of each power data; Step S3f, setting a threshold for the optimization score, and determining the optimization score of each power data according to the threshold, to obtain optimized real-time power data and optimized non-real-time power data respectively.

3. The power data transmission method according to claim 2, characterized in that: The real-time analysis is performed on each power data in the real-time power data to obtain the real-time index of each power data, including: Step S3a1, obtaining the generation time of each power data; Step S3a2, obtaining the expected arrival time of each power data; Step S3a3, obtaining a real-time index of each power data according to the generation time and expected arrival time of each power data; The calculation formula for obtaining the real-time index of each power data is: Among them, R i represents the real-time index of the ith power data in the real-time power data; T expected，i represents the expected arrival time of the ith power data in the real-time power data; T generated，i represents the generation time of the i-th power data in the real-time power data; ∈ represents a constant.

4. The power data transmission method according to claim 2, characterized in that: The importance analysis is performed on each power data in the real-time power data to obtain the importance index of each power data, including: Step S3b1, obtaining application scenarios of each power data; Step S3b2: Determine the importance of each power data according to the application scenario; Step S3b3: convert the importance into a numerical value to obtain an importance index for each power data.

5. A method for transmitting power data according to claim 2, characterized in that: The step of performing an urgency analysis on each power data in the real-time power data to obtain an urgency index of each power data includes: Step S3c1, obtaining the urgency of each power data; Step S3c2: determining the emergency level of each power data according to the emergency level; Step S3c3: convert the emergency level into a numerical value to obtain an emergency index for each power data.

6. The power data transmission method according to claim 2, characterized in that: The method of obtaining an initial weight and a first weight of each power data according to the real-time index, the importance index and the urgency index of each power data, and obtaining an optimized weight of each power data according to the initial weight and the first weight includes: Step S3d1: assigning an initial weight to each power data according to the importance index, and the initial weight is proportional to the importance index; Step S3d2, obtaining a first ratio of the real-time index of each power data to the importance index of each power data; Step S3d3, obtaining a second ratio of the urgency index of each power data to the importance index of each power data; Step S3d4, obtaining a first weight for each power data according to the first ratio and the second ratio; Step S3d5: Obtain the optimized weight of each power data according to the initial weight and the first weight.

7. The power data transmission method according to claim 2, characterized in that: The calculation formula for obtaining the optimization score of each power data is: S i =α·R i +β·I i +γ·E i +δ·W init，i +ζ·W first，i +η·W opt，i ; Among them, S i represents the optimization score of the ith power data in the real-time power data; R i Represents the real-time index of the i-th power data in the real-time power data; I i represents the importance index of the ith power data in the real-time power data; E i represents the urgency index of the i-th power data in the real-time power data; W init，i represents the initial weight of the i-th power data in the real-time power data; W first，i represents the first weight of the i-th power data in the real-time power data; W opt，i represents the optimization weight of the i-th power data in the real-time power data; α, β, γ, δ, ζ, η represent preset coefficients.

8. The power data transmission method according to claim 2, characterized in that: The optimization score is set to a threshold, and the optimization score of each power data is determined according to the threshold, so as to obtain optimized real-time power data and optimized non-real-time power data, respectively, including: Step S3f1: If the optimization score of the current power data is greater than or equal to the threshold, it is retained and still classified as real-time power data; if it is less than the threshold, it is removed from the real-time power data and classified as non-real-time power data; Step S3f2, until each power data in the real-time power data is determined, the real-time power data after determination is defined as optimized real-time power data, and the non-real-time power data is defined as optimized non-real-time power data.

9. A power data transmission system, used to execute a power data transmission method according to any one of claims 1 to 8, characterized in that: The system comprises: Data acquisition module: used to obtain the power data to be transmitted by the current node; Data classification module: connected to the data acquisition module, used to classify the power data to be transmitted into real-time power data and non-real-time power data according to the real-time characteristics of data transmission; Classification optimization module: connected to the data classification module, used to perform further analysis on the real-time power data to obtain optimized real-time power data and optimized non-real-time power data; Priority setting module: connected to the classification optimization module, used to set the transmission priority of the optimized real-time power data and the optimized non-real-time power data, wherein the transmission priority of the optimized real-time power data is greater than the transmission priority of the optimized non-real-time power data; Transmission execution module: connected to the priority setting module, used to execute power data transmission according to the transmission priority.

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