An intelligent gateway based on multi-protocol conversion and its implementation method

Abstract

The present invention relates to the field of power network technology, and in particular to an intelligent gateway based on multi-protocol conversion and an implementation method thereof. The present invention discloses an intelligent gateway based on multi-protocol conversion, including a multi-protocol conversion module, a data acquisition module, a polling scheduling module, a network communication module, a security management module, a device management module, a data processing module, a user interface module, a redundancy and backup module, and an intelligent scheduling module. The present invention solves the problems of protocol incompatibility between devices, untimely data acquisition, low communication efficiency, and insufficient security. The gateway realizes seamless integration of data exchange between devices, improves the manageability and stability of the system, and reduces operation and maintenance costs and risks.

Description

Technical Field

[0001] The present invention relates to the technical field of power network, and in particular to an intelligent gateway based on multi-protocol conversion and an implementation method thereof. Background Art

[0002] With the rapid development of smart grid and Internet of Things technology, the power system has higher and higher requirements for the real-time and accuracy of data. In the power system, various power equipment such as substations, wind turbines, solar photovoltaic systems, etc., need to exchange data with the monitoring system through communication protocols. However, these devices often use different communication protocols, such as IEC 104, IEC61850, Modbus, DLT645, etc., which leads to the complexity of data integration and communication.

[0003] Existing power communication solutions usually adopt a single or limited communication protocol, which is difficult to meet diverse communication needs. In addition, with the expansion of the scale of power systems and the increase in the number of devices, traditional polling scheduling methods face challenges in data collection efficiency, system response time and network load management. Under high load conditions, traditional polling scheduling may cause data collection delays, affecting the real-time performance and reliability of the system.

[0004] In order to solve these problems, an intelligent gateway that can support multi-protocol conversion is needed. It not only needs to realize the conversion between different power communication protocols, but also needs to have efficient data collection, intelligent scheduling and safety management capabilities. In addition, with the improvement of the automation and intelligence level of the power system, higher requirements are also placed on the data processing capabilities, user interaction interface and system reliability of the gateway.

[0005] The present invention is proposed based on such a technical background, and aims to improve the communication efficiency, data processing capability and system stability of the power system through an intelligent gateway that integrates multi-protocol conversion, intelligent scheduling, secure communication, efficient data processing and user-friendly interface. By introducing advanced DACSA algorithm and real-time data analysis technology, the intelligent gateway of the present invention can dynamically adjust the polling strategy, optimize communication efficiency and response time, and has self-learning ability to adapt to the ever-changing power system needs. Summary of the invention

[0006] In view of the problems existing in the prior art, the present invention is proposed.

[0007] Therefore, the technical problem to be solved by the present invention is: how to meet the multi-protocol conversion requirements of the power system and how to improve the operating efficiency of the power system gateway.

[0008] To solve the above technical problems, the present invention provides the following technical solutions: an intelligent gateway based on multi-protocol conversion, comprising a multi-protocol conversion module, a data acquisition module, a polling scheduling module, a network communication module, a security management module, a device management module, a data processing module, a user interface module, a redundancy and backup module, and an intelligent scheduling module.

[0009] As a preferred solution of the intelligent gateway based on multi-protocol conversion described in the present invention, wherein: the multi-protocol conversion module is used to realize the conversion between different power communication protocols, and the power communication protocols include IEC 104, IEC61850, Modbus, DLT645, MQTT, so as to support diversified communication requirements;

[0010] The data acquisition module is used to collect data from power equipment in the power system;

[0011] The polling scheduling module is used to read data or send commands to connected devices in a predetermined order and time interval to ensure that all devices can be accessed regularly;

[0012] The network communication module is responsible for the communication between the intelligent gateway and the external network;

[0013] The security management module is used to monitor all data transmission and device access activities, implement user authentication, data encryption and access control policies, and prevent unauthorized access;

[0014] The device management module is used to monitor and manage all devices connected to the gateway, and automatically search, configure, detect faults and maintain power equipment;

[0015] The data processing module is used to pre-process and analyze the collected data, including data cleaning, format conversion, data compression and storage, and supports complex data processing algorithms;

[0016] The user interface module is used to provide an operation interface, allowing users to monitor and manage the operation status of the gateway, and supports Web interface, mobile application and command line interface;

[0017] The redundancy and backup module is used to implement redundant backup of data and services, improve system reliability, and quickly restore system operation in the event of a failure;

[0018] The intelligent scheduling module is used to utilize the DACSA algorithm and real-time data analysis to dynamically adjust the polling strategy, optimize communication efficiency and response time, and has self-learning capabilities.

[0019] As a preferred solution of the intelligent gateway based on multi-protocol conversion described in the present invention, wherein: the multi-protocol conversion module transmits data of different protocols to the data acquisition module for unified format conversion;

[0020] The data acquisition module is connected to the polling scheduling module, and the data acquisition module transmits the collected data to the polling scheduling module for scheduled access scheduling.

[0021] The polling scheduling module is connected to the intelligent scheduling module, and the polling scheduling module transmits the basic access strategy to the intelligent scheduling module for dynamic optimization processing;

[0022] The data acquisition module is connected to the network communication module, and the data acquisition module transmits the processed data to the network communication module for secure transmission;

[0023] The network communication module is connected to the security management module, and the network communication module transmits the transmitted data to the security management module for security encryption and authentication;

[0024] The device management module is connected to the data acquisition module, and the device management module transmits device status information to the data acquisition module to perform data update and device monitoring;

[0025] The data processing module is connected to the user interface module, and the data processing module transmits the analyzed and processed data to the user interface module for information display and user interaction;

[0026] The redundancy and backup modules transmit backup data to all modules for fault recovery and data protection.

[0027] As a preferred solution of the intelligent gateway based on multi-protocol conversion described in the present invention, the working steps of the polling scheduling module include:

[0028] The polling scheduling module is initialized when the system starts, loading the device list and polling strategy;

[0029] Set the polling interval and order, which are configured based on the importance of the device and the frequency of data updates;

[0030] At the beginning of each polling cycle, the module checks the device list to confirm the status and availability of all devices;

[0031] For offline or faulty devices, the module will try to reconnect or mark them as maintenance status;

[0032] The module sends data requests to each device in the set order;

[0033] After the device responds to the data request, the polling scheduling module receives the returned data;

[0034] Combined with the intelligent scheduling module, the polling scheduling module will adjust the polling strategy based on real-time data and the DACSA algorithm;

[0035] The polling scheduling module updates the device status information, including the time of the last successful communication and the collected data;

[0036] All polling activities and results are recorded in the system log;

[0037] As a preferred solution of the intelligent gateway based on multi-protocol conversion described in the present invention, the working steps of the intelligent adjustment module include:

[0038] The intelligent adjustment module collects real-time and historical data, analyzes the communication mode and data generation frequency of the equipment;

[0039] Analyze device response time and network status;

[0040] Use the DACSA algorithm based on power equipment operation to evaluate short-term equipment behavior and network conditions;

[0041] Develop polling strategies based on the results of data analysis and predictive models;

[0042] The polling strategy includes setting the priority, time interval and order of polling;

[0043] As a preferred solution of the intelligent gateway based on multi-protocol conversion described in the present invention, the DACSA algorithm includes: data collection and analysis, D t ={d1,d2,...,d n} where each d i Contains information such as device status and data update frequency, H = {h1,h2,...,h m} Each h i Contains historical communication mode and fault record information;

[0044] For each device d, calculate the statistical indicators Stat of communication mode and response time d =f stat (D t ,H);

[0045] For each device d, use the prediction function f pred Calculate the behavior prediction P(d,t)=f pred (Stat d ,C d );

[0046] Use the prediction function f net Calculate the network condition prediction N(d,t)=f net (D t,H);

[0047] If the data is time-dependent, use time series analysis methods to predict device behavior.

[0048] If the impact of device configuration needs to be considered, use a machine learning regression model;

[0049] For each device d, use the policy function f strat Calculate the polling strategy S(d,t)=f strat (P(d,t),N(d,t),C d );

[0050] Use the optimization function f opt Calculate the data transmission optimization suggestion T(d,t)=f opt (N(d,t));

[0051] For each device d, according to the real-time data D t and system load L t , dynamically adjust the polling strategy S(d,t) and data transmission optimization suggestion T(d,t).

[0052] Among them, D t is the real-time data set collected at time t, H is the historical data set, and C d is the configuration information of device d, L t is the system load at time t, P(d,t) is the predicted behavior of device d at time t, N(d,t) is the predicted network condition at time t, S(d,t) is the polling strategy of device d at time t, T(d,t) is the data transmission optimization suggestion, and f stat (D t ,H) is a statistical analysis function used to analyze the device communication mode and response time, f pred (Stat d ,C d ) is a prediction function used to predict device behavior based on statistical indicators and device configuration f net (D t ,H) is the network prediction function, used to predict network conditions, f strat (P(d,t),N(d,t),C d ) is a strategy function used to formulate polling strategy, f opt (N(d,t)) is an optimization function used to make suggestions for data transmission optimization.

[0053] As a preferred solution of the intelligent gateway based on multi-protocol conversion described in the present invention, wherein: the statistical analysis function f stat (D t ,H) Input is real-time data D t={d1,d2,...,d n} and historical data H = {h1,h2,...,h m};

[0054] The processing is to calculate the statistical indicators of the communication mode and response time of each device d;

[0055] Output is statistical indicator Stat d ={μ d ,σ d ,F d};

[0056]

[0057]

[0058] F d =Histogram(D t )

[0059] Among them, f stat (D t ,H) is a statistical analysis function used to analyze real-time data and historical data, and calculate the statistical indicators of the communication mode and response time of the device. t is a real-time data set, which contains data samples of multiple devices. H is a historical data set, which contains information such as the historical communication mode and fault records of the devices. i A single data sample in a real-time data set represents the state of a device at a certain point in time. d is the statistical indicator output for device d, μ d is the average response time or data update frequency of device d, σ d is the standard deviation of the response time or data update frequency of device d, which is used to measure the discreteness of the data. d is the communication mode of device d, which is used to show the data distribution. n is the number of data samples of device d in the real-time data set. is the sum of all data samples of device d in the real-time dataset.

[0060] As a preferred solution of the intelligent gateway based on multi-protocol conversion described in the present invention, the working steps of the intelligent adjustment module also include:

[0061] Monitor device status and network communication in real time, and dynamically adjust polling strategies based on changes;

[0062] For devices with frequent data updates or high priority, reduce the polling interval;

[0063] Optimize data transmission paths and methods, reduce network congestion and improve data transmission efficiency;

[0064] Adjust the size and frequency of data transfers when network conditions are poor.

[0065] As a preferred solution of the intelligent gateway based on multi-protocol conversion described in the present invention, wherein: the intelligent adjustment module will not be started under normal scheduling conditions, and under normal scheduling conditions, the gateway uses a basic polling scheduling strategy to access the device in a preset order and time interval;

[0066] When the gateway load exceeds the preset threshold, the system automatically switches to intelligent scheduling mode;

[0067] When the gateway load returns to the normal range, the smart scheduling module will re-evaluate whether it is necessary to continue using smart scheduling;

[0068] If the system is stable, the intelligent scheduling module will switch the scheduling mode back to basic polling scheduling.

[0069] Another object of the present invention is to provide a method for realizing an intelligent gateway based on multi-protocol conversion, which realizes conversion between different power communication protocols through a multi-protocol conversion module, thereby solving the problem of protocol incompatibility between devices.

[0070] As a preferred solution of the intelligent gateway implementation method based on multi-protocol conversion described in the present invention, the steps are as follows:

[0071] After the gateway is started, the smart gateway performs self-test, including hardware status check and software module loading;

[0072] Initialize the security management module, set encryption parameters and access control lists;

[0073] The device management module searches for and identifies the power devices connected to the gateway;

[0074] For newly discovered devices, the device management module registers their information into the system and configures communication parameters;

[0075] The data acquisition module collects data from each power device regularly according to the instructions of the polling scheduling module;

[0076] The multi-protocol conversion module receives the data collected by the data acquisition module and performs protocol conversion according to the requirements of the target system;

[0077] For data that needs to be stored for a long time, the data processing module compresses it and stores it;

[0078] The intelligent scheduling module analyzes real-time and historical data to predict the communication needs of equipment;

[0079] According to the prediction results, the intelligent scheduling module dynamically adjusts the polling strategy to optimize the efficiency of data collection;

[0080] The network communication module sends the processed data to the central monitoring system or other external systems through a secure channel;

[0081] The security management module monitors the data transmission process to prevent data leakage and unauthorized access;

[0082] Redundancy and backup modules regularly back up key data and system configurations;

[0083] In the event of a failure, the gateway quickly recovers from the backup, reducing system downtime.

[0084] The beneficial effects of the present invention are as follows: it realizes the functions of multi-protocol conversion, data collection, intelligent scheduling and security management, and improves the overall efficiency and security of power and industrial communication systems. By solving the problems of protocol incompatibility between devices, untimely data collection, low communication efficiency and insufficient security, the gateway realizes seamless integration of data exchange between devices, improves the manageability and stability of the system, and reduces operation and maintenance costs and risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0086] Figure 1 A structural diagram of an intelligent gateway based on multi-protocol conversion provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0087] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0088] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0089] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0090] Example 1

[0091] Reference Figure 1 , which is the first embodiment of the present invention, provides an intelligent gateway based on multi-protocol conversion, including a multi-protocol conversion module, a data acquisition module, a polling scheduling module, a network communication module, a security management module, a device management module, a data processing module, a user interface module, a redundancy and backup module, and an intelligent scheduling module.

[0092] Furthermore, the multi-protocol conversion module is used to realize conversion between different power communication protocols, and the power communication protocols include IEC 104, IEC61850, Modbus, DLT645, and MQTT to support diverse communication requirements;

[0093] The data acquisition module is used to collect data from power equipment in the power system;

[0094] The polling scheduling module is used to read data or send commands to connected devices in a predetermined order and time interval to ensure that all devices can be accessed regularly;

[0095] The network communication module is responsible for the communication between the intelligent gateway and the external network;

[0096] The security management module is used to monitor all data transmission and device access activities, implement user authentication, data encryption and access control policies, and prevent unauthorized access;

[0097] The device management module is used to monitor and manage all devices connected to the gateway, and automatically search, configure, detect faults and maintain power equipment;

[0098] The data processing module is used to pre-process and analyze the collected data, including data cleaning, format conversion, data compression and storage, and supports complex data processing algorithms;

[0099] The user interface module is used to provide an operation interface so that users can monitor and manage the operation status of the gateway, and supports Web interface, mobile application and command line interface;

[0100] The redundancy and backup module is used to implement redundant backup of data and services, improve system reliability, and quickly restore system operation in the event of a failure;

[0101] The intelligent scheduling module is used to utilize the DACSA algorithm and real-time data analysis to dynamically adjust the polling strategy, optimize communication efficiency and response time, and has self-learning capabilities.

[0102] Furthermore, the multi-protocol conversion module transmits data of different protocols to the data acquisition module for unified format conversion;

[0103] The data acquisition module is connected to the polling scheduling module, and the data acquisition module transmits the collected data to the polling scheduling module for scheduled access scheduling.

[0104] The polling scheduling module is connected to the intelligent scheduling module, and the polling scheduling module transmits the basic access strategy to the intelligent scheduling module for dynamic optimization processing;

[0105] The data acquisition module is connected to the network communication module, and the data acquisition module transmits the processed data to the network communication module for secure transmission;

[0106] The network communication module is connected to the security management module, and the network communication module transmits the transmitted data to the security management module for security encryption and authentication;

[0107] The device management module is connected to the data acquisition module, and the device management module transmits device status information to the data acquisition module to perform data update and device monitoring;

[0108] The data processing module is connected to the user interface module, and the data processing module transmits the analyzed and processed data to the user interface module for information display and user interaction;

[0109] The redundancy and backup modules transmit backup data to all modules for fault recovery and data protection.

[0110] Furthermore, the working steps of the polling scheduling module include:

[0111] The polling scheduling module is initialized when the system starts, loading the device list and polling strategy;

[0112] Set the polling interval and order, which can be configured based on the importance of the device and the frequency of data updates;

[0113] At the beginning of each polling cycle, the module checks the device list to confirm the status and availability of all devices;

[0114] For offline or faulty devices, the module will try to reconnect or mark them as maintenance status;

[0115] The module sends data requests to each device in the set order;

[0116] After the device responds to the data request, the polling scheduling module receives the returned data;

[0117] Combined with the intelligent scheduling module, the polling scheduling module will adjust the polling strategy based on real-time data and the DACSA algorithm;

[0118] The polling scheduling module updates the device status information, including the time of the last successful communication and the collected data;

[0119] All polling activities and results are recorded in the system log;

[0120] Furthermore, the working steps of the intelligent adjustment module include:

[0121] The intelligent adjustment module collects real-time and historical data, analyzes the communication mode and data generation frequency of the equipment;

[0122] Analyze device response time and network status;

[0123] Using power equipment to run the DACSA algorithm to predict short-term equipment behavior and network conditions;

[0124] Develop polling strategies based on the results of data analysis and predictive models;

[0125] The polling strategy includes setting the priority, time interval and order of polling;

[0126] Furthermore, the DACSA algorithm includes: data collection and analysis, D t ={d1,d2,...,d n} where each d i Contains information such as device status and data update frequency, H = {h1,h2,...,h m} Each h i Contains historical communication mode and fault record information;

[0127] For each device d, calculate the statistical indicators Stat of communication mode and response time d =f stat (D t ,H);

[0128] For each device d, use the prediction function f pred Calculate the behavior prediction P(d,t)=f pred (Stat d ,C d );

[0129] Use the prediction function fnet Calculate the network condition prediction N(d,t)=f net (D t ,H);

[0130] If the data is time-dependent, use time series analysis methods to predict device behavior.

[0131] If the impact of device configuration needs to be considered, use a machine learning regression model;

[0132] For each device d, use the policy function f strat Calculate the polling strategy S(d,t)=f strat (P(d,t),N(d,t),C d );

[0133] Use the optimization function f opt Calculate the data transmission optimization suggestion T(d,t)=f opt (N(d,t));

[0134] For each device d, according to the real-time data D t and system load L t , dynamically adjust the polling strategy S(d,t) and data transmission optimization suggestion T(d,t).

[0135] Among them, D t is the real-time data set collected at time t, H is the historical data set, and C d is the configuration information of device d, L t is the system load at time t, P(d,t) is the predicted behavior of device d at time t, N(d,t) is the predicted network condition at time t, S(d,t) is the polling strategy of device d at time t, T(d,t) is the data transmission optimization suggestion, and f stat (D t ,H) is a statistical analysis function used to analyze the device communication mode and response time, f pred (Stat d ,C d ) is a prediction function used to predict device behavior based on statistical indicators and device configuration f net (D t ,H) is the network prediction function, used to predict network conditions, f strat (P(d,t),N(d,t),C d ) is a strategy function used to formulate polling strategy, f opt (N(d,t)) is an optimization function used to make suggestions for data transmission optimization.

[0136] Furthermore, the statistical analysis function f stat (D t,H) Input is real-time data D t ={d1,d2,...,d n} and historical data H = {h1,h2,...,h m};

[0137] The processing is to calculate the statistical indicators of the communication mode and response time of each device d;

[0138] Output is statistical indicator Stat d ={μ d ,σ d ,F d};

[0139]

[0140]

[0141] F d =Histogram(D t )

[0142] Prediction function f pred (Stat d ,C d )for

[0143] Input is the statistical indicator Stat d and device configuration C d .

[0144] Processing is to use time series analysis or machine learning regression models to predict device behavior.

[0145] The output is the device behavior prediction P(d,t).

[0146] If the time series analysis is P(d,t)=ARIMA(Stat d ,C d )

[0147] If the machine learning regression model is P(d,t)=Regressor(Stat d ,C d )

[0148] Network prediction function f net (D t ,H) is

[0149] Input is real-time data D t and historical data H.

[0150] Processing involves using neural networks or deep learning models to predict network conditions.

[0151] The output is the network-conditioned prediction N(d,t).

[0152] N(d,t)=NeuralNetwork(D t ,H)

[0153] Policy function f strat (P(d,t),N(d,t),C d )for

[0154] The input is the device behavior prediction P(d,t), the network condition prediction N(d,t) and the device configuration C d .

[0155] The process is to develop polling strategies using multi-objective optimization and decision trees.

[0156] The output is the polling strategy S(d,t)={T d ,Prio d}.

[0157] S(d,t)=MultiObjectiveOptimization(P(d,t),N(d,t),C d )

[0158] Optimize function f opt (N(d,t)) is

[0159] The input is the network conditional prediction N(d,t).

[0160] The process uses heuristic algorithms or linear programming to make recommendations for optimizing data transmission.

[0161] The output is the data transmission optimization suggestion T(d,t)={Path d ,Method d ,Freq d}.

[0162] It should be noted that the DACSA algorithm of the present invention can be adjusted and optimized according to actual application scenarios and data characteristics. In some embodiments, it is necessary to continuously adjust the parameters of the model according to real-time data and system feedback.

[0163] Furthermore, the working steps of the intelligent adjustment module also include:

[0164] Monitor device status and network communication in real time, and dynamically adjust polling strategies based on changes;

[0165] For devices with frequent data updates or high priority, reduce the polling interval;

[0166] Optimize data transmission paths and methods, reduce network congestion and improve data transmission efficiency;

[0167] Adjust the size and frequency of data transfers when network conditions are poor.

[0168] Furthermore, the intelligent adjustment module will not be activated under normal scheduling conditions, in which case the gateway uses a basic polling scheduling strategy to access the devices in a preset order and time interval;

[0169] When the gateway load exceeds the preset threshold, the system automatically switches to intelligent scheduling mode;

[0170] When the gateway load returns to the normal range, the smart scheduling module will re-evaluate whether it is necessary to continue using smart scheduling;

[0171] It should be noted that, in some embodiments, the threshold value may be calculated according to the following steps:

[0172] Data collection: Collect the system resource usage, network communication indicators, device status information and other data mentioned above.

[0173] Data analysis: Use statistical analysis methods to process historical performance data and identify normal ranges and peak values ​​of system load.

[0174] Model training: Use machine learning algorithms to train data and build a model that can predict system load.

[0175] Threshold setting: Based on model prediction and business needs, an initial threshold is set. In some embodiments, the threshold is set when the system resource utilization reaches 85%, ensuring that the system has enough margin to handle sudden load increases.

[0176] Test and adjust: Test the effect of the threshold in actual operation and make appropriate adjustments based on system performance. If you find that the system can still run stably when reaching the threshold, you can consider lowering the threshold to further improve efficiency; conversely, if the system performance is unstable, you need to increase the threshold.

[0177] Dynamic optimization: The threshold should be dynamically adjustable, automatically adjusting the threshold based on the system's real-time performance data and external conditions to adapt to changing load conditions.

[0178] Threshold setting is an iterative process that requires continuous monitoring, evaluation, and adjustment to ensure that the system can meet business needs while also being able to cope with sudden high load situations.

[0179] If the system is stable, the intelligent scheduling module will switch the scheduling mode back to basic polling scheduling.

[0180] Example 2

[0181] In one embodiment of the present invention, a method for implementing an intelligent gateway based on multi-protocol conversion is provided, comprising the following steps:

[0182] After the gateway is started, the smart gateway performs self-test, including hardware status check and software module loading;

[0183] Initialize the security management module, set encryption parameters and access control lists;

[0184] The device management module searches for and identifies the power devices connected to the gateway;

[0185] For newly discovered devices, the device management module registers their information into the system and configures communication parameters;

[0186] The data acquisition module collects data from each power device regularly according to the instructions of the polling scheduling module;

[0187] The multi-protocol conversion module receives the data collected by the data acquisition module and performs protocol conversion according to the requirements of the target system;

[0188] For data that needs to be stored for a long time, the data processing module compresses it and stores it;

[0189] The intelligent scheduling module analyzes real-time and historical data to predict the communication needs of equipment;

[0190] According to the prediction results, the intelligent scheduling module dynamically adjusts the polling strategy to optimize the efficiency of data collection;

[0191] The network communication module sends the processed data to the central monitoring system or other external systems through a secure channel;

[0192] The security management module monitors the data transmission process to prevent data leakage and unauthorized access;

[0193] Redundancy and backup modules regularly back up key data and system configurations;

[0194] In the event of a failure, the gateway quickly recovers from the backup, reducing system downtime.

[0195] Example 3

[0196] The third embodiment of the present invention provides an intelligent gateway based on multi-protocol conversion.

[0197] To verify the present invention, a simulation experiment is conducted to comprehensively analyze the present invention with a traditional gateway from multiple aspects such as communication efficiency, data transmission delay, and system stability;

[0198] 1. Comparison of communication efficiency

[0199] Table 1

[0200] scene Traditional gateway communication times Smart gateway communication times Scenario 1 1000 800 Scenario 2 1200 900 Scenario 3 1500 1000

[0201] It can be seen from Table 1 that in different scenarios, the intelligent gateway of the present invention reduces the number of communications by dynamically adjusting the polling strategy, thereby improving the communication efficiency. The intelligent gateway of the present invention can optimize the polling strategy according to real-time data and the DACSA algorithm, so that each communication is more efficient and the number of unnecessary communications is reduced.

[0202] 2. Data transmission delay comparison, the results are shown in the following table:

[0203] Table 2

[0204] scene Traditional gateway latency (ms) Smart Gateway Delay (ms) Scenario 1 50 30 Scenario 2 60 35 Scenario 3 55 32

[0205] It can be seen from Table 2 that in different scenarios, the intelligent gateway of the present invention has lower data transmission delay than the traditional gateway. The intelligent gateway of the present invention can dynamically adjust the polling strategy according to real-time data and historical data, so that the response speed of data transmission is faster, thereby reducing the delay time of data transmission.

[0206] 3. System stability comparison

[0207] As can be seen from Table 3, the traditional gateway and the intelligent gateway of the present invention are compared in terms of system stability. In different scenarios, the number of system failures is recorded and compared. The results are shown in the following table:

[0208] Table 3

[0209] scene Traditional gateway failure times Smart gateway failure times Scenario 1 3 1 Scenario 2 4 2 Scenario 3 2 0

[0210] Compared with the traditional gateway, the intelligent gateway of the present invention has higher system stability. The intelligent gateway of the present invention timely adjusts the polling strategy and restores the system through intelligent scheduling and backup modules, reduces the number of system failures, and improves the reliability of the system.

[0211] In summary, the intelligent gateway and its method based on multi-protocol conversion have obvious advantages over traditional gateways in improving system reliability and efficiency. Its features such as dynamic adjustment of polling strategy, intelligent scheduling and backup module can effectively improve the stability and communication efficiency of the system, bringing important technological progress to the field of power communication.

[0212] Example 4

[0213] The fourth embodiment of the present invention is different from the first three embodiments in that:

[0214] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, 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. The computer software product is stored in a storage medium, including several instructions for 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 methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0215] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0216] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CDROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0217] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0218] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0219] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0220] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0221] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. An intelligent gateway based on multi-protocol conversion, characterized in that: It includes multi-protocol conversion module, data acquisition module, polling scheduling module, network communication module, security management module, equipment management module, data processing module, user interface module, redundancy and backup module, and intelligent scheduling module; The working steps of the polling scheduling module include: the polling scheduling module is initialized when the system starts, and the device list and polling strategy are loaded; Setting the polling interval and order, which are configured based on the importance of the device and the frequency of data updates; At the beginning of each polling cycle, the module checks the device list to confirm the status and availability of all devices; For offline or faulty devices, the module will try to reconnect or mark them as maintenance status; The module sends data requests to each device in the set order; After the device responds to the data request, the polling scheduling module receives the returned data; Combined with the intelligent scheduling module, the polling scheduling module adjusts the polling strategy based on real-time data and the DACSA algorithm; The polling scheduling module updates the device status information, including the time of the last successful communication and the collected data; All polling activities and results are recorded in the system log; The working steps of the intelligent scheduling module include: the intelligent scheduling module collects real-time data and historical data, analyzes the communication mode and data generation frequency of the device; Analyze device response time and network status; Using power equipment to run the DACSA algorithm to predict short-term equipment behavior and network conditions; The DACSA algorithm includes: data collection and analysis, Each of these Including device status, data update frequency, Each of these Contains historical communication mode and fault record information; For each device d, calculate the statistics of communication pattern and response time ; For each device d, use the prediction function Computational behavior prediction ; Using the prediction function Compute network condition predictions ; If the data is time-dependent, use time series analysis methods to predict device behavior; If the impact of device configuration needs to be considered, use a machine learning regression model; For each device d, use the policy function Calculate polling strategy ; Using the optimization function Compute data transfer optimization recommendations ; For each device d, according to real-time data and system load , dynamically adjust the polling strategy and data transfer optimization suggestions ; in, is the real-time data set collected at time t, H is the historical data set, is the configuration information of device d, is the system load at time t, is the behavior prediction of device d at time t, is the prediction of network conditions at time t, is the polling strategy of device d at time t, Provides suggestions for data transfer optimization. It is a statistical analysis function used to analyze device communication patterns and response times. A prediction function used to predict device behavior based on statistical indicators and device configuration is a network prediction function used to predict network conditions. is a strategy function used to formulate polling strategies. It is an optimization function used to make suggestions for data transmission optimization; Develop polling strategies based on the results of data analysis and predictive models; The polling strategy includes setting the priority, time interval and order of polling.

2. The intelligent gateway based on multi-protocol conversion according to claim 1 is characterized in that: The multi-protocol conversion module is used to realize conversion between different power communication protocols, and the power communication protocols include IEC 104, IEC61850, Modbus, DLT645, and MQTT to support diverse communication requirements; The data acquisition module is used to collect data from power equipment in the power system; The polling scheduling module is used to read data or send commands to connected devices in a predetermined order and time interval to ensure that all devices can be accessed regularly; The network communication module is responsible for the communication between the intelligent gateway and the external network; The security management module is used to monitor all data transmission and device access activities, implement user authentication, data encryption and access control policies, and prevent unauthorized access; The device management module is used to monitor and manage all devices connected to the gateway, and automatically search, configure, detect faults and maintain power equipment; The data processing module is used to pre-process and analyze the collected data, including data cleaning, format conversion, data compression and storage, and supports complex data processing algorithms; The user interface module is used to provide an operation interface, allowing users to monitor and manage the operation status of the gateway, and supports Web interface, mobile application and command line interface; The redundancy and backup module is used to implement redundant backup of data and services, improve system reliability, and quickly restore system operation in the event of a failure; The intelligent scheduling module is used to utilize the DACSA algorithm and real-time data analysis to dynamically adjust the polling strategy, optimize communication efficiency and response time, and has self-learning capabilities.

3. The intelligent gateway based on multi-protocol conversion according to claim 2 is characterized in that: The multi-protocol conversion module transmits data of different protocols to the data acquisition module for unified format conversion; The data acquisition module is connected to the polling scheduling module, and the data acquisition module transmits the collected data to the polling scheduling module for scheduled access scheduling; The polling scheduling module is connected to the intelligent scheduling module, and the polling scheduling module transmits the basic access strategy to the intelligent scheduling module for dynamic optimization processing; The data acquisition module is connected to the network communication module, and the data acquisition module transmits the processed data to the network communication module for secure transmission; The network communication module is connected to the security management module, and the network communication module transmits the transmitted data to the security management module for security encryption and authentication; The device management module is connected to the data acquisition module, and the device management module transmits device status information to the data acquisition module to perform data update and device monitoring; The data processing module is connected to the user interface module, and the data processing module transmits the analyzed and processed data to the user interface module for information display and user interaction; The redundancy and backup modules transmit backup data to all modules for fault recovery and data protection.

4. The intelligent gateway based on multi-protocol conversion according to claim 3 is characterized in that: The statistical analysis function Input is real-time data and historical data ; The processing is to calculate the statistical indicators of the communication mode and response time of each device d; Output as statistical indicators ; in, It is a statistical analysis function used to analyze real-time data and historical data, and calculate the statistical indicators of the communication mode and response time of the device. is a real-time data set, which contains data samples of multiple devices. H is a historical data set, which contains the historical communication mode and fault records of the devices. A single data sample in a real-time data set represents the state of a device at a certain point in time. is the statistical indicator output for device d, is the average response time or data update frequency of device d, is the standard deviation of the response time or data update frequency of device d, which is used to measure the discreteness of the data. is the communication mode of device d, which is used to show the data distribution. n is the number of data samples of device d in the real-time data set. is the sum of all data samples of device d in the real-time dataset.

5. The intelligent gateway based on multi-protocol conversion according to claim 4 is characterized in that: The working steps of the intelligent adjustment module also include: Monitor device status and network communication in real time, and dynamically adjust polling strategies based on changes; For devices with frequent data updates or high priority, reduce the polling interval; Optimize data transmission paths and methods, reduce network congestion and improve data transmission efficiency; Adjust the size and frequency of data transfers when network conditions are poor.

6. The intelligent gateway based on multi-protocol conversion according to claim 5 is characterized in that: The intelligent adjustment module will not be started under normal scheduling conditions. Under normal scheduling conditions, the gateway uses a basic polling scheduling strategy to access the device in a preset order and time interval; When the gateway load exceeds the preset threshold, the system automatically switches to intelligent scheduling mode; When the gateway load returns to the normal range, the smart scheduling module will re-evaluate whether it is necessary to continue using smart scheduling; If the system is stable, the intelligent scheduling module will switch the scheduling mode back to basic polling scheduling.

7. A method for implementing a multi-protocol conversion-based intelligent gateway, applied to a multi-protocol conversion-based intelligent gateway according to any one of claims 1 to 6, characterized in that: After the gateway is started, the smart gateway performs self-test, including hardware status check and software module loading; Initialize the security management module, set encryption parameters and access control lists; The device management module searches for and identifies the power devices connected to the gateway; For newly discovered devices, the device management module registers their information into the system and configures communication parameters; The data acquisition module collects data from each power device regularly according to the instructions of the polling scheduling module; The multi-protocol conversion module receives the data collected by the data acquisition module and performs protocol conversion according to the requirements of the target system; For data that needs to be stored for a long time, the data processing module compresses it and stores it; The intelligent scheduling module analyzes real-time and historical data to predict the communication needs of equipment; According to the prediction results, the intelligent scheduling module dynamically adjusts the polling strategy to optimize the efficiency of data collection; The network communication module sends the processed data to the central monitoring system or other external systems through a secure channel; The security management module monitors the data transmission process to prevent data leakage and unauthorized access; Redundancy and backup modules regularly back up key data and system configurations; In the event of a failure, the gateway quickly recovers from the backup, reducing system downtime.

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