Power data transmission method and system

Abstract

The application discloses a kind of electric power data transmission method and system, it is related to data transmission technical field, the present application is based on the basis of existing rough classification to the power data to be transmitted, further scientific screening based on data driving is executed to it, by the analysis to the various indexes of real-time power data including real-time, importance and urgency, including the intervention of optimization weight, to filter out the power data in real-time power data with optimization score lower than threshold value, but in order to still ensure the integrity of data, it is not completely eliminated, but completely classified in non real-time power data, by the whole process of screening, further obtain more scientific and accurate classification optimization real-time power data and non real-time power data, on the basis of further classified power data setting priority and executing transmission, can effectively solve the problem of data transmission delay, so as to effectively reduce the influence caused to the response speed of system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data transmission, and particularly relates to a power data transmission method and system. BACKGROUND

[0002] The power data transmission method generally refers to a technology of transmitting data by using existing power lines, which is called power line communication; the accurate transmission of power data can effectively ensure the accuracy and reliability of data in the transmission process, and in order to ensure the accurate transmission of power data, the existing technology usually realizes the above purpose by a series of technical means, wherein the existing power data accurate transmission implementation mainly includes the following aspects:

[0003] Modulation and demodulation technology: advanced modulation and demodulation technologies are adopted, such as orthogonal frequency division multiplexing, quadrature amplitude modulation, etc. These technologies can effectively improve the robustness and bandwidth utilization of data transmission. Orthogonal frequency division multiplexing distributes data on multiple subcarriers, reduces the influence of multipath effect, and improves the stability of transmission. Efficient channel coding technologies are used, such as low-density parity-check codes, Turbo codes, etc. These coding technologies can correct errors and reduce error rates during transmission, and improve the integrity of data. In the power line environment, there are a large amount of electromagnetic interference and noise, so noise suppression technologies such as adaptive filter, frequency domain equalization, etc. are needed to reduce the influence of noise on data transmission. In order to ensure the accurate transmission of data, accurate time synchronization and frequency synchronization need to be realized. Time synchronization technology can calibrate the clock of the receiving end by sending a synchronization signal, and frequency synchronization technology can maintain the stability of transmission by frequency offset estimation and compensation. At the high-layer protocol level, the transmission protocol is optimized, such as using automatic repeat request mechanism to ensure reliable transmission of data packets, and in addition, the data slicing method is used to further improve the accuracy of data transmission.

[0004] Although the existing power data accurate transmission technology has made certain progress, it still has the following defects in actual application:

[0005] In some application scenarios, such as real-time control and monitoring, high-load and complex network topology application scenarios, the delay requirement of data transmission is very high, especially when a large amount of data is processed, delay problems are prone to occur. If only simple data classification is used and the data transmission priority is set according to the classification result, it is obviously difficult to effectively solve the problem of data transmission delay, which still easily affects the response speed of the system, and further easily leads to the decline of system performance, poor user experience, and even in some key applications such as real-time control of smart grid, video transmission of telemedicine, etc., leading to serious safety risks and economic losses.

[0006] Therefore, the prior art urgently needs a technical scheme of a power data transmission method and system. SUMMARY

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

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

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

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

[0011] Step S3a, performing real-time analysis on each power data in the real-time type 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 the real-time index of each power data according to the generation time and the expected arrival time of each power data;

[0015] Wherein, the calculation formula of the real-time index of each power data is:

[0016]

[0017] Wherein, R i represents the real-time index of the i-th power data in the real-time type power data; T expected，i represents the expected arrival time of the i-th power data in the real-time type power data; T generated，i represents the generation time of the i-th power data in the real-time type power data; and ∈ represents a constant.

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

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

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

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

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

[0023] Step S3c1, obtaining an emergency degree of each power data;

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

[0025] Step S3c3, converting the emergency level into a numerical value to obtain an emergency index of 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 emergency 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 value of the real-time index of each power data and the importance index of each power data;

[0029] Step S3d3, obtaining a second ratio value of the emergency index of each power data and the importance index of each power data;

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

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

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

[0033] Wherein, the calculation formula of the optimized 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] wherein, S i represents the optimization score of the i-th power data in the real-time type power data; R i represents the real-time index of the i-th power data in the real-time type power data; I i represents the importance index of the i-th power data in the real-time type power data; E i represents the urgency index of the i-th power data in the real-time type power data; W init，i represents the initial weight of the i-th power data in the real-time type power data; W first，i represents the first weight of the i-th power data in the real-time type power data; W opt，i represents the optimization weight of the i-th power data in the real-time type power data; a, b, g, d, z, h represent preset coefficients;

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

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

[0038] Step S3f2, until each power data in the real-time type power data is judged, then the real-time type power data after being judged is defined as the optimized real-time type power data, and the non-real-time type power data is defined as the optimized non-real-time type power data;

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

[0040] Step S5, performing power data transmission according to the transmission priorities.

[0041] A power data transmission system for performing the power data transmission method as described above, comprising the following modules:

[0042] A data acquisition module for acquiring power data to be transmitted by a current node;

[0043] A data classification module connected with the data acquisition module, for classifying the power data to be transmitted into real-time type power data and non-real-time type power data according to the real-time characteristics of data transmission;

[0044] Classification optimization module: connected with the data classification module, used for performing further analysis on the real-time power data, and obtaining optimized real-time power data and optimized non-real-time power data respectively;

[0045] Priority setting module: connected with the classification optimization module, used for setting transmission priorities 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 higher than that of the optimized non-real-time power data;

[0046] Transmission execution module: connected with the priority setting module, used for performing power data transmission according to the transmission priorities.

[0047] The embodiment of the present application has the following technical effects:

[0048] The present application performs further scientific screening based on data driving on the basis of the existing rough classification of the power data to be transmitted. In the further screening process, the real-time power data is analyzed in terms of indicators including real-time performance, importance and emergency level, and the intervention of optimization weight is involved to screen out the power data in the real-time power data whose optimization score is lower than the threshold. However, in order to still ensure the integrity of the data, the power data is not completely excluded, but is completely classified into non-real-time power data. Through the whole screening process, the optimized real-time power data and non-real-time power data classified more scientifically and accurately are further obtained. On this basis, the further classified power data is set with priorities 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 the system performance, and avoiding the occurrence of serious safety risks and economic losses. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the specific embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0050] Figure 1 is a flowchart of a power data transmission method provided by an embodiment of the present application;

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

[0052] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be clearly and completely described below. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work belong to the scope of protection of the present application.

[0053] Embodiment one: as shown, the present application provides a power data transmission method, comprising the following steps: Figure 1

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

[0055] Obtaining 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, etc. communication technology; 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 for further processing and transmission; extracting the power data to be transmitted from the stored data, which can be achieved by querying the database or directly reading the data from the buffer; packaging the extracted data into a data packet format suitable for transmission, so as to be transmitted through the power line; wherein the obtained power data includes but is not limited to:

[0056] Electric energy data: records the user's electricity consumption, such as hourly electricity consumption, daily cumulative electricity consumption, etc.; voltage data: records the voltage value at the user side, such as voltage readings per minute; current data: records the current value at the user side, such as current readings per minute; power factor: records the power factor of the user, which is used to evaluate the power quality; temperature data: records the temperature of key devices such as transformers and cables, such as temperature readings per minute; humidity data: records the ambient humidity, such as humidity readings per hour; vibration data: records the vibration of devices such as generators and transformers, such as vibration readings per minute; switch status: records the status of switch devices such as circuit breakers and relays, such as on or off; fault alarm: records fault alarm information in the system, such as overload, short circuit, etc.; device health status: records the health status of key devices, such as remaining service life, maintenance recommendations, etc.; weather data: records meteorological data such as wind speed, rainfall, and light intensity, which is used to predict power demand and optimize power generation plan; air quality data: records air quality data such as PM2.5 and PM10, which is used for environmental monitoring and health management.​

[0057] Step S2, the power data to be transmitted is divided into real-time type power data and non-real-time type power data according to the real-time characteristic of data transmission;

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

[0059] According to the above classification basis, the specific data of real-time type power data and non-real-time type power data are as follows:

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

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

[0062] Energy data: updated every hour, used to record the power consumption of users for subsequent electricity bill settlement and power 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 for power demand prediction and generation plan optimization.

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

[0065] Device health status: updated daily, used to record the health status of key devices such as remaining service life and maintenance recommendations for device maintenance and management.

[0066] Step S3, performing further analysis on the real-time type power data to obtain optimized real-time type power data and optimized non-real-time type power data respectively;

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

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

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

[0070] The generation time refers to a specific time point at which the power data is collected or generated, which is usually the time at which the data collection device such as a smart meter, a sensor, etc. records data; and the expected arrival time refers to a time at which the power data is expected to arrive at the receiving end, which is usually determined according to the real-time requirement of the system and the network transmission delay.

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

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

[0073]

[0074] Wherein, R i represents the real-time index of the i-th power data in the real-time type power data; T expected，i represents the expected arrival time of the i-th power data in the real-time type power data; T generated，i represents the generation time of the i-th power data in the real-time type power data; and ∈ represents a constant.

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

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

[0077] For real-time power data, such as voltage, current, power factor, temperature, vibration, switch status and fault alarm, etc., which are usually used for real-time monitoring, control and protection systems. Non-real-time power data: such data are usually used for analysis, reporting and long-term monitoring, such as power energy, humidity, weather data, air quality data and equipment health status, etc. Specifically, voltage data: application scenario is real-time monitoring. Current data: application scenario is real-time monitoring. Power factor: application scenario is real-time monitoring. Temperature data: application scenario is real-time monitoring. Vibration data: application scenario is real-time monitoring. Switch status: application scenario is real-time monitoring. Fault alarm: application scenario is real-time monitoring. Power energy data: application scenario is electricity settlement. Humidity data: application scenario is environmental monitoring. Weather data: application scenario is environmental monitoring. Air quality data: application scenario is environmental monitoring. Equipment health status: application scenario is equipment maintenance.

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

[0079] The importance refers to the criticality and influence 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, analyze the performance and influence of each power data in actual application. Then perform importance classification, high importance refers to data that is crucial to system stability and safety, such as voltage, current, power factor, temperature, vibration, switch status and fault alarm; medium importance refers to data that has some influence on system operation but is not crucial, such as humidity, weather data, air quality data; low importance refers to data that is mainly used for analysis and reporting, such as power energy, equipment health status. Then determine the importance level of power data in each application scenario, for example, voltage data in real-time monitoring application scenario is high importance, power energy data in electricity settlement application scenario is low importance.

[0080] Step S3b3, converting the importance into a numerical value to obtain the 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 range of 0.8 to 1.0; medium importance: assign a numerical value range of 0.5 to 0.7; low importance: assign a numerical value range of 0.1 to 0.4;

[0082] According to the importance ranking, a specific importance index is assigned to each 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 emergency degree analysis on each power data in the real-time type power data to obtain an emergency index of each power data;

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

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

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

[0087] It is worth noting that the same as the obtaining method of the importance index, the same as the obtaining method of the importance index, both of which adopt the historical data analysis method to determine the importance degree or the emergency degree, and both of which adopt the grading method and convert the level into a numerical value for subsequent calculation and processing; but the difference is that steps S3c1 to S3c3 are more inclined to the analysis of the emergency degree, while steps S3b1 to S3b3 are more inclined to the analysis of the importance degree, and although both of them adopt numerical ranges to represent the importance degree or the emergency degree, the specific numerical range and allocation are 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 emergency 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 emergency index of each power data to the importance index of each power data;

[0092] Step S3d4, obtaining a first weight of 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, the first weight;

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

[0095] The calculation formula of the optimized score of each power data is as follows:

[0096] S i = a · R i + b · I i + g · E i + d · W init，i + z · W first，i + h · W opt，i ;

[0097] Wherein, S i represents the optimized score of the i-th 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 i-th power data in the real-time power data; E i represents the emergency 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 optimized weight of the i-th power data in the real-time power data; a, b, g, d, z, and h represent preset coefficients.

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

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

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

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

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

[0103] Example 2: Figure 2 As shown, the present invention also proposes a power data transmission system that executes the power data transmission method described above, comprising the following modules:

[0104] Data acquisition module: used to acquire the power data to be transmitted at 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 real-time power data to obtain optimized real-time power data and optimized non-real-time power data respectively;

[0107] Priority setting module: connected to the classification optimization module, used to set transmission priorities for optimizing real-time power data and optimizing non-real-time power data, wherein the transmission priority of optimizing real-time power data is greater than the transmission priority of optimizing 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 terminology used in this invention is for describing specific embodiments only and is not intended to limit the scope of this application. As shown in this specification, unless the context clearly indicates otherwise, words such as "a," "an," "an," and / or "the" do not specifically refer to the singular and may include the plural. The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element.

[0110] It should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like, indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are used only to facilitate the description of the present application and simplify the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. Unless otherwise specifically defined and limited, the terms "mount", "connect", "connect" and the like should be broadly understood, for example, can be fixedly connected, can also be detachably connected, or integrally connected; can be mechanically connected, can also be electrically connected; can be directly connected, can also be indirectly connected through an intermediate medium; can be internal communication of two elements. For those of ordinary skill in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0111] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present application.

Claims

1. A method of power data transmission, characterized by, The method comprises the following steps: Step S1, obtaining power data to be transmitted by a current node; Step S2, dividing the power data to be transmitted into real-time power data and non-real-time power data according to 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 transmission priorities 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 higher than that of the optimized non-real-time power data; Step S5, performing power data transmission according to the transmission priorities; The further analysis of the real-time power data to obtain the optimized real-time power data and the optimized non-real-time power data comprises: 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 emergency analysis on each power data in the real-time power data to obtain an emergency 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 emergency 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 optimized score of each power data according to the real-time index, the importance index, the emergency index, the initial weight, the first weight and the optimized weight of each power data; Step S3f, setting a threshold for the optimized score, and determining the optimized score of each power data according to the threshold to obtain the optimized real-time power data and the optimized non-real-time power data.

2. The power data transmission method of claim 1, wherein, The real-time analysis on each power data in the real-time power data to obtain the real-time index of each power data comprises: Step S3a1, obtaining a generation time of each power data; Step S3a2, obtaining an expected arrival time of each power data; Step S3a3, obtaining the real-time index of each power data according to the generation time and the expected arrival time of each power data; wherein a calculation formula for obtaining the real-time index of each power data is: wherein, Ri represents the real-time index of the i-th power data in the real-time type power data; T expected，i represents the expected arrival time of the i-th power data in the real-time type power data; T generated，i represents the generation time of the i-th power data in the real-time type power data; ∈ represents a constant.

3. The power data transmission method of claim 1, wherein, The importance analysis on each power data in the real-time power data to obtain the importance index of each power data comprises: Step S3b1, obtaining an application scenario of each power data; Step S3b2, determining an importance degree of each power data according to the application scenario; Step S3b3, converting the importance degree into a numerical value to obtain the importance index of each power data.

4. The method of claim 1, wherein, The emergency analysis on each power data in the real-time power data to obtain the emergency index of each power data comprises: Step S3c1, obtaining an emergency degree of each power data; Step S3c2, determining an emergency level of each power data according to the emergency degree. Step S3c3, converting the emergency level into a numerical value to obtain an emergency index of each power data.

5. The power data transmission method of claim 1, wherein, The initial weight and the first weight of each power data are obtained according to the real-time index, the importance index and the emergency index of each power data, and the optimized weight of each power data is obtained according to the initial weight and the first weight, which 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 emergency index of each power data to the importance index of each power data; Step S3d4, obtaining the first weight of each power data according to the first ratio and the second ratio; Step S3d5, obtaining the optimized weight of each power data according to the initial weight and the first weight.

6. The power data transmission method of claim 1, wherein, The calculation formula of the optimized score of each power data is: S i = a · R i + b · I i + g · E i + d · W init，i + z · W first，i + h · W opt，i ; wherein S i represents an optimization score of the i-th power data in the real-time type power data; R i represents a real-time index of the i-th power data in the real-time type power data; I i represents an importance index of the i-th power data in the real-time type power data; E i represents an urgency index of the i-th power data in the real-time type power data; W init，i represents an initial weight of the i-th power data in the real-time type power data; W first，i represents a first weight of the i-th power data in the real-time type power data; W opt，i represents an optimization weight of the i-th power data in the real-time type power data; α, β, γ, δ, ζ, η represent preset coefficients.

7. The power data transmission method of claim 1, wherein, The threshold value is set for the optimized score, and the optimized score of each power data is judged according to the threshold value to obtain the optimized real-time power data and the optimized non-real-time power data, which includes: Step S3f1, if the optimized score of the current power data is greater than or equal to the threshold value, the current power data is retained and still classified as real-time power data, and if the optimized score is less than the threshold value, the current power data 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 judged, the real-time power data after judgment is defined as the optimized real-time power data, and the non-real-time power data is defined as the optimized non-real-time power data.

8. A power data transmission system for carrying out a power data transmission method according to any one of claims 1 to 7, characterized by The system includes: A data acquisition module for acquiring power data to be transmitted by a current node; A data classification module connected with the data acquisition module, for classifying 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; A classification optimization module connected with the data classification module, for performing further analysis on the real-time power data to obtain the optimized real-time power data and the optimized non-real-time power data; A priority setting module connected with the classification optimization module, for setting transmission priorities for the optimized real-time power data and the optimized non-real-time power data, and the transmission priority of the optimized real-time power data is greater than that of the optimized non-real-time power data; A transmission execution module connected with the priority setting module, for performing power data transmission according to the transmission priorities.

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