Flexible adjustment unit data transmission method for smart power grid

Abstract

The invention provides a flexible adjustment unit data transmission method for a smart power grid, and belongs to the technical field of power grid management. The flexible adjusting unit data transmission method for the smart power grid comprises the following steps: acquiring electric energy parameters of a special transformer user in real time, wherein the electric energy parameters comprise split-phase voltage, current, active power, a power factor and frequency; performing edge calculation processing on the electric energy parameters to formulate a load prediction strategy, a load identification strategy, an electric energy quality monitoring strategy and a flexible regulation and control strategy; and reporting the processed electric energy parameters to an interactive management master station in an encrypted communication mode. According to the flexible adjustment unit data transmission method for the smart power grid, the security of data transmission can be guaranteed, load fine management, power quality optimization and dynamic adjustment capability enhancement of the smart power grid are realized, and the stability of a power grid system is maintained.

Description

Technical Field

[0001] The present application belongs to the technical field of power grid management, and specifically relates to a flexible regulation unit data transmission method for smart grids. Background Art

[0002] Smart grid, also known as "Grid 2.0", is a modern power supply and management system based on an integrated, high-speed, two-way communication network, integrating advanced sensing and measurement technology, equipment technology, control methods, and decision support system technology. The design of smart grid aims to achieve multiple goals such as reliable, safe, economical, efficient, environmentally friendly and safe use of the power grid.

[0003] Flexible regulation unit data transmission is the core link of efficient energy management and dynamic control of smart grids. It is of great significance to improve grid stability, optimize energy distribution, promote the grid connection of renewable energy and improve user experience.

[0004] However, during the data transmission process, there is a risk of data being illegally intercepted and tampered with, which affects the security and integrity of data transmission and is not conducive to the refined management and dynamic control of smart grids. Summary of the invention

[0005] In order to solve at least one technical problem existing in the background technology, the present application provides a flexible regulation unit data transmission method for smart grids, which can ensure the security of data transmission, realize fine load management, power quality optimization and dynamic regulation capability enhancement of smart grids, and maintain the stability of the power grid system.

[0006] The technical solution adopted in this application is: The first aspect of the present application provides a smart grid-oriented flexible regulation unit data transmission method, including: Real-time collection of power parameters of dedicated transformer users, including phase voltage, current, active power, power factor and frequency; Performing edge computing processing on the electric energy parameters to formulate load forecasting strategies, load identification strategies, power quality monitoring strategies and flexible control strategies; The processed electric energy parameters are reported to the interactive management main station through encrypted communication.

[0007] According to the data transmission method of the flexible regulating unit for smart grid provided by the first embodiment of the present application, by collecting electric energy parameters in high frequency and in real time, it is possible to instantly gain insight into the operation status of the power grid, promptly discover and respond to abnormal situations in the power grid, and enhance the stability and reliability of the system. The integration of edge computing makes data processing closer to the data source, reduces data transmission delay, and improves processing efficiency. The formulation of load forecasting and identification strategies helps to reasonably arrange resources, optimize power grid load distribution, reduce power loss, and improve energy utilization efficiency. The power quality monitoring strategy can monitor the operation quality of the power grid in real time, promptly discover and correct problems such as voltage fluctuations and harmonic pollution, ensure power supply quality, and enhance the power consumption experience of end users. The flexible control strategy can dynamically adjust the operation status of the power grid based on the real-time data analysis results, better adapt to the volatility of renewable energy, promote the efficient access and utilization of clean energy, and support green and low-carbon transformation. The use of encrypted communication ensures the security of data during transmission, prevents data from being illegally intercepted or tampered with, and protects the user's privacy information, enhancing the user's trust in the smart grid. The efficient data reporting mechanism provides rich real-time data support for the interactive management master station, and provides a solid data foundation for the master station's intelligent decision-making, automated operation and maintenance, and long-term planning, promoting the development of the power grid in a smarter and more autonomous direction. In summary, the data transmission method for the flexible adjustment unit for smart grids provided in this application can ensure the security of data transmission, realize the fine load management, power quality optimization, and dynamic adjustment capability enhancement of smart grids, and maintain the stability of the power grid system.

[0008] According to one embodiment of the present application, the method further includes: Freezing and storing the electric energy parameters at the minute level; Record abnormal event information, including overvoltage, overcurrent, power reverse, power failure and control loop abnormality.

[0009] According to an embodiment of the present application, the minute-level freezing and storage of the electric energy parameters is specifically as follows: Define the freeze period; integrating the electric energy parameters acquired during the freezing period into a data frame; The data frame is stored according to a preset format.

[0010] According to an embodiment of the present application, the real-time collection of power parameters of dedicated transformer users is specifically: Real-time monitoring of three-phase current value or unidirectional current value through current transformer, real-time monitoring of three-phase voltage value or unidirectional voltage value through voltage transformer; Based on the voltage and current values, the active power, reactive power and power factor are calculated in real time through the internal calculation module.

[0011] According to an embodiment of the present application, the edge computing processing of the electric energy parameters is performed to formulate a load forecasting strategy, a load identification strategy, a power quality monitoring strategy and a flexible control strategy, specifically: De-noising, missing value filling and standardization processing are performed on the electric energy parameters; Obtain historical data, extract time series features, and establish a strategy prediction model; Performing spectrum analysis and pattern recognition on the current value and the voltage value to extract a characteristic vector of the user load; Using a clustering algorithm or a neural network to classify the feature vectors, and determine a user load classification result; Based on the user load classification result, the load forecasting strategy, the load identification strategy, the power quality monitoring strategy and the flexible control strategy are generated.

[0012] According to an embodiment of the present application, the processed electric energy parameters are reported to the interactive management main station by means of encrypted communication, specifically: Organizing the electric energy parameters into a data packet according to a preset format, wherein the data packet includes a data header, a data body and a check code; Determine the encryption algorithm and key; The data packet is encrypted using the encryption algorithm and the key, and the data packet is converted into ciphertext.

[0013] According to an embodiment of the present application, reporting the processed electric energy parameters to the interactive management master station by encrypted communication also includes: Establishing an encrypted communication channel, and reporting the encrypted data packet to the interactive management main station through the encrypted communication channel; During the reporting process, the data transmission status is monitored.

[0014] According to one embodiment of the present application, the method further includes: In the edge computing process, abnormal data in the electric energy parameters are monitored in real time; Analyzing the abnormal data using an anomaly detection algorithm; Flag anomalous data points and generate alert instructions.

[0015] A second aspect of the present application provides a flexible regulation unit data transmission device for a smart grid, including: The parameter acquisition module is suitable for real-time acquisition of power parameters of dedicated transformer users, including phase voltage, current, active power, power factor and frequency; A computing and processing module, adapted to perform edge computing processing on the electric energy parameters to formulate load forecasting strategies, load identification strategies, power quality monitoring strategies and flexible control strategies; The reporting module is suitable for reporting the processed electric energy parameters to the interactive management main station through encrypted communication.

[0016] An embodiment of the third aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the flexible regulation unit data transmission method for a smart grid as described in any embodiment of the first aspect as described above is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 A schematic diagram of a flow chart of a data transmission method of a flexible regulation unit for a smart grid provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a flexible regulation unit data transmission device for smart grid provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0018] in, 110, parameter collection module; 120, calculation and processing module; 130, reporting module; 810, processor; 820, communication interface; 830, memory; 840, communication bus. DETAILED DESCRIPTION

[0019] In order to more clearly illustrate the overall concept of the present application, a detailed description is given below in an illustrative manner in conjunction with the accompanying drawings.

[0020] In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present application is not limited by the specific embodiments disclosed below. It should be noted that the embodiments of the present application and the features in each embodiment may be combined with each other without conflict.

[0021] In addition, in the description of the present application, it should be understood that the orientations or positional relationships indicated by the terms "top", "bottom", "inside", "outside", "axial", "radial", "circumferential", etc. are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0022] In this application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like 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, an electrical connection, or a communication; it can be a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0023] In the present application, unless otherwise clearly specified and limited, a first feature "above" or "below" a second feature may be that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in an appropriate manner in any one or more embodiments or examples.

[0024] like Figure 1 As shown, the first embodiment of the present application provides a flexible regulation unit data transmission method for a smart grid, including: Step 100: Collect the power parameters of the dedicated transformer user in real time, including phase voltage, current, active power, power factor and frequency.

[0025] Step 200: Perform edge computing on the electric energy parameters to formulate load forecasting strategy, load identification strategy, power quality monitoring strategy and flexible control strategy.

[0026] Step 300: Report the processed power parameters to the interactive management main station through encrypted communication.

[0027] In step 100, the power grid is usually a three-phase AC system, and the phase voltage refers to the voltage between each phase line and the neutral line (or ground line). Real-time monitoring of the voltage of each phase helps to evaluate the stability and power quality of the power grid and promptly discover problems such as voltage imbalance. Current is a physical quantity that measures the intensity of the flow of electric energy. Real-time monitoring of current can help understand the real-time changes in user loads, which is crucial for power distribution and fault diagnosis. Similarly, the current is also divided into three-phase currents, corresponding to the three phases of the power grid. Active power is the power that actually does work, which is directly related to the conversion and actual consumption of electric energy and is the main basis for calculating electricity charges. Real-time monitoring of active power is crucial for load management, electricity charge calculation and power balance analysis. Power factor reflects the efficiency of electric energy use and is the ratio of active power to apparent power. A high power factor indicates high efficiency in electric energy use, and vice versa. Real-time monitoring of power factor is critical to improving power quality and improving system efficiency. In an AC system, frequency is a physical quantity that measures the number of times the direction of the current changes per second. The standard frequency in my country is 50Hz. Frequency stability is crucial to the normal operation of power grid equipment. Real-time frequency monitoring helps maintain the frequency stability and synchronous operation of the power grid.

[0028] Real-time collection of these power parameters can provide an accurate and real-time data foundation for subsequent edge computing processing, load forecasting, power quality monitoring, flexible control strategy formulation, and rapid response to abnormal events.

[0029] In step 200, edge computing is used to perform time series analysis and seasonal pattern recognition on power parameters, and combined with external factors (such as weather forecasts, holidays, etc.), the load change trend of the power grid in the future is predicted. This helps to allocate resources in advance and ensure the stability and efficiency of power supply.

[0030] The load identification strategy uses waveform analysis, spectrum analysis and pattern recognition technology of current and voltage to identify different types of load characteristics from real-time data, such as distinguishing industrial loads, residential loads, etc., to provide a basis for refined management and demand-side response.

[0031] The power quality monitoring strategy is to monitor power quality parameters such as voltage fluctuations, frequency deviations, and harmonic content in real time. Edge computing can quickly identify power quality degradation and promptly initiate preset compensation measures or alarm mechanisms to ensure the power quality of the power grid.

[0032] Flexible control strategy means that based on the above analysis results, edge computing can dynamically adjust the operating parameters of the power grid, such as adjusting the output of distributed energy, the charging and discharging strategies of energy storage equipment, and the load adjustment of users participating in demand response, so as to achieve supply and demand balance of the power grid, optimize the efficiency of electricity use, and promote the efficient consumption of renewable energy.

[0033] The advantage of edge computing is that it can process data at close range, reduce data transmission delays, improve response speed, and reduce the pressure on cloud computing.

[0034] In step 300, in order to protect the data from being intercepted or tampered by unauthorized third parties during transmission, encryption technology is used to encrypt the data. This usually involves the use of encryption algorithms such as AES (Advanced Encryption Standard), RSA, TLS (Transport Layer Security Protocol), etc. The data will be converted into ciphertext before sending, and only the recipient with the correct key can decrypt and restore the data, ensuring the security of the data.

[0035] The interactive management master station is the central control unit of the smart grid, responsible for receiving and processing data reported by each edge computing unit, and conducting comprehensive analysis and decision-making. These processed power parameters include load forecast results, load identification information, power quality reports, and control strategy recommendations, which are key inputs for the master station to conduct grid dispatching, optimized operation, fault handling, and strategy formulation.

[0036] Before data transmission, the system will establish a secure communication channel, which involves the SSL / TLS handshake protocol to verify the identities of both parties in communication and ensure the security of data on the transmission channel. Encrypted communication is not limited to the data itself, but also includes the identity verification of both parties in communication and the integrity verification of data transmission.

[0037] In this way, the smart grid can not only efficiently use edge computing to process real-time data, but also centrally manage the status information of all subsystems while ensuring information security, providing a solid guarantee for the efficient operation, flexible regulation and rapid response to faults of the smart grid.

[0038] According to the data transmission method of the flexible regulating unit for smart grid provided by the first embodiment of the present application, by collecting electric energy parameters in high frequency and in real time, it is possible to instantly gain insight into the operation status of the power grid, promptly discover and respond to abnormal situations in the power grid, and enhance the stability and reliability of the system. The integration of edge computing makes data processing closer to the data source, reduces data transmission delay, and improves processing efficiency. The formulation of load forecasting and identification strategies helps to reasonably arrange resources, optimize power grid load distribution, reduce power loss, and improve energy utilization efficiency. The power quality monitoring strategy can monitor the operation quality of the power grid in real time, promptly discover and correct problems such as voltage fluctuations and harmonic pollution, ensure power supply quality, and enhance the power consumption experience of end users. The flexible control strategy can dynamically adjust the operation status of the power grid based on the real-time data analysis results, better adapt to the volatility of renewable energy, promote the efficient access and utilization of clean energy, and support green and low-carbon transformation. The use of encrypted communication ensures the security of data during transmission, prevents data from being illegally intercepted or tampered with, and protects the user's privacy information, enhancing the user's trust in the smart grid. The efficient data reporting mechanism provides rich real-time data support for the interactive management master station, and provides a solid data foundation for the master station's intelligent decision-making, automated operation and maintenance, and long-term planning, promoting the development of the power grid in a smarter and more autonomous direction. In summary, the data transmission method for the flexible adjustment unit for smart grids provided in this application can ensure the security of data transmission, realize the fine load management, power quality optimization, and dynamic adjustment capability enhancement of smart grids, and maintain the stability of the power grid system.

[0039] In some embodiments of the present application, the method further comprises: Freeze and store electric energy parameters at the minute level; Record abnormal event information, including overvoltage, overcurrent, power reverse, power failure and control circuit abnormality.

[0040] The process of minute-level freezing and storage means that every minute, the system will "freeze" and store the current state of the power parameters. These frozen data include the instantaneous values ​​of key parameters such as phase voltage, current, active power, power factor and frequency. This minute-level data recording method helps to build a detailed time series of power usage, providing detailed historical data support for subsequent load analysis, power quality assessment, trend prediction and fault tracing. By defining a fixed freezing period (such as every minute), the system can effectively manage storage resources while ensuring the continuity and integrity of the data.

[0041] In the step of recording abnormal event information, the system not only continuously monitors the power parameters, but also automatically identifies and records any abnormal events that deviate from the normal operating range. These abnormal events include but are not limited to overvoltage (voltage exceeds the safety threshold), overcurrent (current exceeds the rated value), power reversal (current or power flow does not meet expectations), power failure (power interruption), and control loop abnormalities (errors or failures in the monitoring and control system). Recording this abnormal information is crucial for timely detection of potential problems in the power grid, prevention of accidents, rapid response, and taking corrective measures. Through the systematic abnormal event log, operation and maintenance personnel can quickly locate the source of the problem and take targeted measures to effectively improve the stability and safety of the power grid.

[0042] In some embodiments of the present application, the electric energy parameters are frozen and stored at the minute level, specifically: Define the freeze period; integrating the electric energy parameters acquired during the freezing period into a data frame; The data frame is stored in a preset format.

[0043] Set a fixed time interval, usually every minute, as a data freezing and storage operation cycle. At the end of this cycle, the system will capture and record the current state of the power parameters, such as voltage, current, power, etc. The minute-level cycle selection is intended to provide data points with sufficient frequency to accurately reflect the real-time changes in power grid operation without excessively increasing the burden of data storage and processing. At the end of each freezing cycle, the system will integrate the power parameter values ​​continuously monitored during the cycle into a data set, which is called a "data frame". The data frame contains instantaneous readings of all key power parameters during the cycle, such as phase voltage, current, active power, power factor, and frequency. The purpose of integrating data frames is to facilitate management and storage, so that the data exists in a structured form, which is easy to analyze and query later. Finally, the system will store the data frame in a hard disk, database, or cloud storage service in a pre-defined format, such as CSV, JSON, or other specific database formats. The preset storage format ensures data consistency and compatibility, and facilitates data exchange and sharing between different systems and tools. In addition, reasonable data organization and compression strategies are also important considerations in this link to optimize the use of storage space and speed up data retrieval.

[0044] In some embodiments of the present application, the power parameters of the dedicated transformer user are collected in real time, specifically: Real-time monitoring of three-phase current value or unidirectional current value through current transformer, real-time monitoring of three-phase voltage value or unidirectional voltage value through voltage transformer; Based on the voltage and current values, the active power, reactive power and power factor are calculated in real time through the internal calculation module.

[0045] Current transformers are used to measure the current in a circuit. In a three-phase system, there are usually three current transformers to monitor the three phases, while for a single-phase system, only one is needed. Current transformers work on the principle of magnetic coupling, and can safely and accurately measure current values ​​even under high current conditions without directly connecting to the circuit, ensuring the safety of the measurement.

[0046] The function of a voltage transformer is to convert the voltage of a high or medium voltage level to a low voltage (such as 100V or less) so that it can be safely measured and monitored. Similarly, for a three-phase system, three voltage transformers are required to monitor the three-phase voltage; in a single-phase system, only one is required. Voltage transformers are also based on the principle of electromagnetic induction to provide accurate voltage readings for the system.

[0047] Active power refers to the power actually doing work, which is the product of voltage, current and the cosine of the power factor angle. It reflects the actual consumed electrical energy and is an important basis for billing.

[0048] Reactive power is related to the energy exchange between electric and magnetic fields, reflecting the ability of inductor and capacitor components in the circuit to store and release energy, and has an important impact on the power quality of the power grid.

[0049] The power factor is an indicator that measures the ratio of active power to apparent power in a circuit, reflecting the utilization rate of power supply energy. A high power factor means high efficiency in the use of electrical energy, and is an important parameter for evaluating the efficiency of electrical equipment and systems.

[0050] Through this series of real-time monitoring and calculation, the smart grid can grasp the power usage of dedicated transformer users in real time, and provide necessary data support for load management, power quality optimization, fault warning and power cost calculation.

[0051] In some embodiments of the present application, edge computing is performed on power parameters to formulate load forecasting strategies, load identification strategies, power quality monitoring strategies and flexible control strategies, specifically: De-noising, missing value filling and standardization of electric energy parameters; Obtain historical data, extract time series features, and establish a strategy prediction model; Perform spectrum analysis and pattern recognition on current and voltage values ​​to extract the characteristic vector of user load; Use clustering algorithms or neural networks to classify feature vectors and determine user load classification results; Based on the user load classification results, load forecasting strategy, load identification strategy, power quality monitoring strategy and flexible control strategy are generated.

[0052] Since the actual collected data contains noise caused by measurement errors or external interference, denoising is necessary to ensure the accuracy of subsequent analysis. Missing value filling is to fill in the missing data caused by various reasons with appropriate methods (such as interpolation, prediction filling based on historical data, etc.) to ensure data continuity and integrity. There may be differences in dimensions and scales between different parameters. Through standardization (such as z-score standardization), all parameters are unified to the same scale for easy comparison and model training.

[0053] When acquiring historical data, collect the power parameters in the past time period as the basis for model training. Furthermore, extract features such as mean, variance, autocorrelation coefficient, etc. that reflect the load change trend, periodicity, seasonality, etc. from the historical data. Use the extracted features to establish models, such as time series prediction models such as ARIMA and LSTM, for load forecasting. By performing spectrum analysis such as Fourier transform on current and voltage signals, identifying different frequency components, it is helpful to understand the load characteristics, such as harmonic content, fluctuation characteristics, etc. According to the spectrum analysis results, identify specific load patterns or abnormal behaviors, and extract feature vectors that reflect the user load characteristics. Take the above-obtained feature vectors as input, and classify user loads through methods such as K-means clustering, hierarchical clustering or deep learning neural networks to identify different types of power consumption behaviors or load types. According to the classification of user loads, customized load forecasting strategies (predicting future load changes), load identification strategies (clarifying the specific composition and characteristics of various types of loads), power quality monitoring strategies (preventing and solving power quality problems) and flexible control strategies (dynamically adjusting power supply strategies to adapt to load changes and improve grid efficiency and reliability) are generated.

[0054] In some embodiments of the present application, the processed power parameters are reported to the interactive management master station through encrypted communication, specifically: Organizing the electric energy parameters into a data packet according to a preset format, the data packet including a data header, a data body and a check code; Determine the encryption algorithm and key; Encrypt the data packet using the encryption algorithm and key, and convert the data packet into ciphertext.

[0055] First, the processed power parameters need to be organized in a predetermined format. This usually involves arranging the parameters in a certain order and adding necessary identifiers or metadata to form a structured data packet. The data packet usually contains three main parts: Data header: Contains metadata about the data packet, such as the type, length, source address, destination address, etc. of the data packet, to facilitate parsing and processing by the receiver.

[0056] Data body: the core content part, i.e. the pre-processed electric energy parameter information.

[0057] Checksum: To ensure that no errors occur during data transmission, a checksum (such as CRC checksum, MD5 digest, etc.) is usually calculated for the data packet and appended to the end of the data packet. The receiving end can use this to verify the integrity of the data.

[0058] Select the appropriate encryption algorithm based on security requirements and system configuration. Common encryption algorithms include AES (Advanced Encryption Standard), RSA, DES, etc. AES is often used for symmetric encryption of data, while RSA can be used for asymmetric encryption key exchange.

[0059] The key is the key in the encryption and decryption process and must be kept safe. For symmetric encryption algorithms, the sender and receiver need to share the same key; while asymmetric encryption involves the use of public and private keys. The generation, distribution and update of keys must follow strict security policies.

[0060] The entire data packet (including the data header, data body, and checksum) is encrypted using a certain encryption algorithm and key. The encryption process converts plaintext data into ciphertext that cannot be directly deciphered, protecting the data from illegal interception and deciphering.

[0061] After encryption is completed, the ciphertext data packet is uploaded to the interactive management main station through a secure channel. This channel is a dedicated network, HTTPS protocol or other secure communication protocol to ensure the security of the data transmission process.

[0062] Through such a process, even if the data is intercepted by a third party during transmission, due to the existence of encryption protection, the third party cannot directly read the original power parameter information, thereby effectively ensuring the privacy and security of the data.

[0063] In some embodiments of the present application, reporting the processed power parameters to the interactive management master station by encrypted communication also includes: Establish an encrypted communication channel and report the encrypted data packet to the interactive management main station through the encrypted communication channel; During the reporting process, the data transmission status is monitored.

[0064] Before the actual data is reported, the first task is to ensure the security of the communication link. This is usually achieved by establishing an encrypted communication channel, such as using the SSL / TLS protocol (commonly used for HTTPS communication) or more professional industrial-grade security protocols such as DTLS (TLS version for resource-constrained devices). This process involves server authentication and key exchange to ensure that the data is always encrypted during transmission, effectively preventing man-in-the-middle attacks and data eavesdropping. The establishment of an encrypted channel provides a secure "tunnel" for the reporting of power parameters, so that even if the data passes through multiple nodes during transmission in the network, its content cannot be easily interpreted.

[0065] During the reporting process, it is very important to monitor the data transmission status in real time, which involves tracking the sending of data packets, the transmission process, and the confirmation of reaching the interactive management master station. This step may include but is not limited to the following aspects: Packet confirmation: Confirm whether the packet has arrived successfully through the ACK mechanism of the TCP / IP protocol or the specific protocol of the application layer to ensure reliable data transmission.

[0066] Transmission rate and delay monitoring: Monitoring the actual rate and delay of data transmission helps to promptly detect network congestion or other problems that affect transmission efficiency.

[0067] Error detection and retransmission: When data transmission errors are detected or no confirmation is received due to timeout, the retransmission mechanism is automatically triggered to ensure the complete delivery of data.

[0068] Security monitoring: Continuously monitor the communication link to check for any attempts to illegally intrude or interfere with communications, and ensure the effectiveness and security of the encrypted channel.

[0069] In summary, by establishing an encrypted communication channel and implementing real-time monitoring of data transmission status, not only the security protection of power parameter data is strengthened, but also the reliability and efficiency of data reporting are improved, ensuring that the interactive management master station can accurately receive the processed power parameter information, providing a solid foundation for subsequent analysis and management decisions.

[0070] In some embodiments of the present application, the method further comprises: In edge computing processing, abnormal data in power parameters are monitored in real time; Analyze abnormal data using anomaly detection algorithms; Flag anomalous data points and generate alert instructions.

[0071] Real-time monitoring of abnormal data in power parameters involves preliminary analysis immediately after data collection, with the goal of instantly identifying data points that deviate significantly from normal patterns. This can be achieved by setting threshold comparisons, statistical methods (such as standard deviation analysis), or learning models based on historical data. Real-time monitoring ensures a rapid response to any unusual data changes that may be caused by equipment failure, grid anomalies, or measurement errors.

[0072] Once the monitoring system identifies potential abnormal data, it will then use anomaly detection algorithms for further analysis. These algorithms include machine learning methods (such as cluster analysis, isolation forest, support vector machine) or statistical methods (such as Grubbs test, Z-score method). They can more accurately determine which data deviates from normal behavior patterns based on the inherent patterns and relationships in the data, rather than simply comparing with preset thresholds.

[0073] After the analysis is completed, the system will clearly mark the confirmed abnormal data points, which is crucial for subsequent fault diagnosis and rapid response. At the same time, the system will automatically generate an alarm instruction, which can be an email or SMS notification sent to the operation and maintenance personnel, or directly trigger the early warning process in the automated management system. The alarm instruction should contain sufficient information, such as the time period when the abnormality occurred, the specific abnormal parameter value and its possible impact range, so that the recipient can make a decision quickly and take corresponding measures.

[0074] like Figure 2 As shown, the second aspect of the present application provides a flexible regulation unit data transmission device for a smart grid, including: The parameter acquisition module 110 is suitable for real-time acquisition of power parameters of dedicated transformer users, wherein the power parameters include phase voltage, current, active power, power factor and frequency; A computing and processing module 120, adapted to perform edge computing processing on the electric energy parameters to formulate load forecasting strategies, load identification strategies, power quality monitoring strategies and flexible control strategies; The reporting module 130 is adapted to report the processed electric energy parameters to the interactive management main station through encrypted communication.

[0075] The flexible regulation unit data transmission device for smart grid provided in the second aspect embodiment of the present application can implement the flexible regulation unit data transmission method for smart grid in any embodiment of the first aspect above, and thus can achieve any technical effect in the above flexible regulation unit data transmission method for smart grid, which will not be repeated here.

[0076] An embodiment of a third aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the flexible regulation unit data transmission method for a smart grid in any embodiment of the first aspect described above is implemented.

[0077] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute the data transmission method for the flexible regulation unit for smart grid in any embodiment of the first aspect, the method comprising: Step 100: Collect the power parameters of the dedicated transformer user in real time, including phase voltage, current, active power, power factor and frequency.

[0078] Step 200: Perform edge computing on the electric energy parameters to formulate load forecasting strategy, load identification strategy, power quality monitoring strategy and flexible control strategy.

[0079] Step 300: Report the processed power parameters to the interactive management main station through encrypted communication.

[0080] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0081] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute the smart grid-oriented flexible regulation unit data transmission method provided by the above methods, the method comprising: Step 100: Collect the power parameters of the dedicated transformer user in real time, including phase voltage, current, active power, power factor and frequency.

[0082] Step 200: Perform edge computing on the electric energy parameters to formulate load forecasting strategy, load identification strategy, power quality monitoring strategy and flexible control strategy.

[0083] Step 300: Report the processed power parameters to the interactive management main station through encrypted communication.

[0084] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for transmitting data of a flexible regulating unit for a smart grid provided by the above methods is implemented, and the method comprises: Step 100: Collect the power parameters of the dedicated transformer user in real time, including phase voltage, current, active power, power factor and frequency.

[0085] Step 200: Perform edge computing on the electric energy parameters to formulate load forecasting strategy, load identification strategy, power quality monitoring strategy and flexible control strategy.

[0086] Step 300: Report the processed power parameters to the interactive management main station through encrypted communication.

[0087] Anything not described in this application can be achieved by adopting or drawing on existing technologies.

[0088] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0089] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A flexible regulation unit data transmission method for smart grid, characterized in that: include: Real-time collection of power parameters of dedicated transformer users, including phase voltage, current, active power, power factor and frequency; Performing edge computing processing on the electric energy parameters to formulate load forecasting strategies, load identification strategies, power quality monitoring strategies and flexible control strategies; The processed electric energy parameters are reported to the interactive management main station through encrypted communication.

2. The method for transmitting data of a flexible regulating unit for a smart grid according to claim 1, characterized in that: The method also includes: Freezing and storing the electric energy parameters at the minute level; Record abnormal event information, including overvoltage, overcurrent, power reverse, power failure and control loop abnormality.

3. The method for transmitting data of a flexible regulating unit for smart grid according to claim 2, characterized in that: The minute-level freezing and storage of the electric energy parameters is specifically as follows: Define the freeze period; integrating the electric energy parameters acquired during the freezing period into a data frame; The data frame is stored according to a preset format.

4. The method for transmitting data of a flexible regulating unit for a smart grid according to claim 1, characterized in that: The real-time collection of power parameters of dedicated transformer users is specifically: Real-time monitoring of three-phase current value or unidirectional current value through current transformer, real-time monitoring of three-phase voltage value or unidirectional voltage value through voltage transformer; Based on the voltage and current values, the active power, reactive power and power factor are calculated in real time through the internal calculation module.

5. The method for transmitting data of a flexible regulating unit for smart grid according to claim 4, characterized in that: The edge computing process of the electric energy parameters is performed to formulate load forecasting strategy, load identification strategy, power quality monitoring strategy and flexible control strategy, specifically: De-noising, missing value filling and standardization processing are performed on the electric energy parameters; Obtain historical data, extract time series features, and establish a strategy prediction model; Performing spectrum analysis and pattern recognition on the current value and the voltage value to extract a characteristic vector of the user load; Using a clustering algorithm or a neural network to classify the feature vectors, and determine a user load classification result; Based on the user load classification result, the load forecasting strategy, the load identification strategy, the power quality monitoring strategy and the flexible control strategy are generated.

6. The method for transmitting data of a flexible regulating unit for smart grid according to claim 5, characterized in that: The processing of the electric energy parameters is reported to the interactive management main station by means of encrypted communication, specifically: Organizing the electric energy parameters into a data packet according to a preset format, wherein the data packet includes a data header, a data body and a check code; Determine the encryption algorithm and key; The data packet is encrypted using the encryption algorithm and the key, and the data packet is converted into ciphertext.

7. The method for transmitting data of a flexible regulating unit for smart grid according to claim 6, characterized in that: The step of reporting the processed electric energy parameters to the interactive management main station by means of encrypted communication also includes: Establishing an encrypted communication channel, and reporting the encrypted data packet to the interactive management main station through the encrypted communication channel; During the reporting process, the data transmission status is monitored.

8. The method for transmitting data of a flexible regulating unit for a smart grid according to any one of claims 1 to 7, characterized in that: The method also includes: In the edge computing process, abnormal data in the electric energy parameters are monitored in real time; Analyzing the abnormal data using an anomaly detection algorithm; Flag anomalous data points and generate alert instructions.

9. A flexible regulation unit data transmission device for smart grid, characterized in that: include: The parameter acquisition module is suitable for real-time acquisition of power parameters of dedicated transformer users, including phase voltage, current, active power, power factor and frequency; A computing and processing module, adapted to perform edge computing processing on the electric energy parameters to formulate load forecasting strategies, load identification strategies, power quality monitoring strategies and flexible control strategies; The reporting module is suitable for reporting the processed electric energy parameters to the interactive management main station through encrypted communication.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the flexible regulation unit data transmission method for smart grid as described in any one of claims 1 to 8 is implemented.

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