CN118449805A - Intelligent gateway based on multi-protocol conversion and implementation method thereof - Google Patents
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Abstract
The invention relates to the technical field of power networks, in particular to an intelligent gateway based on multi-protocol conversion and an implementation method thereof. The invention discloses an intelligent gateway based on multi-protocol conversion, which comprises 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 gateway realizes seamless integration of data exchange among devices by solving the problems of incompatibility of protocols among devices, untimely data acquisition, low communication efficiency, insufficient safety and the like, improves manageability and stability of a system, and reduces operation and maintenance cost and risk.
Description
Technical Field
The invention relates to the technical field of power networks, in particular to an intelligent gateway based on multi-protocol conversion and an implementation method thereof.
Background
With the rapid development of smart power grids and internet of things, the requirements of a power system on the real-time performance and the accuracy of data are higher and higher. In the power system, various power equipment such as a transformer substation, a wind driven generator, a solar photovoltaic system and the like need to exchange data with a monitoring system through a communication protocol. However, these devices often employ different communication protocols, such as IEC 104, IEC61850, modbus, DLT645, etc., which results in complexity of data integration and communication.
Existing power communication solutions typically employ a single or limited communication protocol, which makes it difficult to meet diverse communication requirements. In addition, as the scale of power systems increases, the number of devices increases, and conventional polling scheduling methods face challenges in terms of data acquisition efficiency, system response time, and network load management. Under high load conditions, conventional polling scheduling may cause data acquisition delays, affecting the real-time and reliability of the system.
In order to solve these problems, there is a need for an intelligent gateway capable of supporting multi-protocol conversion, which not only needs to implement conversion between different power communication protocols, but also needs to have efficient data acquisition, intelligent scheduling and security management capabilities. In addition, with the improvement of automation and intelligence level of the power system, higher requirements are also put on the data processing capability, user interaction interface and system reliability of the gateway.
The invention is based on the technical background, and aims to improve the communication efficiency, the data processing capacity and the system stability of a power system through an intelligent gateway integrating multi-protocol conversion, intelligent scheduling, safe communication, high-efficiency data processing and a user-friendly interface. By introducing an advanced DACSA algorithm and a real-time data analysis technology, the intelligent gateway can dynamically adjust a polling strategy, optimize communication efficiency and response time, and simultaneously has self-learning capability so as to adapt to the continuously-changing power system requirements.
Disclosure of Invention
The present invention has been made in view of the problems occurring in the prior art.
Therefore, the technical problems to be solved by the invention are as follows: how to meet the multi-protocol conversion requirement of the power system and how to improve the operation efficiency of the gateway of the power system.
In order to solve the technical problems, the invention provides the following technical scheme: an intelligent gateway based on multi-protocol conversion comprises 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.
As a preferable scheme of the intelligent gateway based on multi-protocol conversion, the invention comprises the following steps: the multi-protocol conversion module is used for realizing conversion among different power communication protocols, and the power communication protocols comprise IEC 104, IEC61850, modbus, DLT645 and MQTT so as to support diversified communication requirements;
the data acquisition module is used for collecting data from power equipment in the power system;
the polling scheduling module is used for reading data or sending commands to the connected devices according to a preset sequence and a preset time interval, so that all the devices can be accessed regularly;
The network communication module is used for being responsible for the communication between the intelligent gateway and an external network;
the security management module is used for monitoring all data transmission and equipment access activities, implementing user authentication, data encryption and access control strategies and preventing unauthorized access;
the device management module is used for monitoring and managing all devices connected to the gateway and automatically searching, configuring, detecting and maintaining the power device;
the data processing module is used for preprocessing and analyzing the acquired data, including data cleaning, format conversion, data compression and storage, and supporting a complex data processing algorithm;
the user interface module is used for providing an operation interface, so that a user monitors and manages the running state of the gateway and supports a Web interface, mobile application and command line interface;
the redundancy and backup module is used for realizing redundancy backup of data and service, improving the reliability of the system and rapidly recovering the operation of the system when faults occur;
the intelligent scheduling module is used for dynamically adjusting the polling strategy by utilizing DACSA algorithm and real-time data analysis, optimizing the communication efficiency and response time, and has self-learning capability.
As a preferable scheme of the intelligent gateway based on multi-protocol conversion, the invention comprises the following steps: the multi-protocol conversion module transmits data of different protocols to the data acquisition module to perform unified format conversion;
the data acquisition module is connected with the polling scheduling module, and transmits acquired data to the polling scheduling module for timing access scheduling
The polling scheduling module is connected with the intelligent scheduling module, and transmits a basic access strategy to the intelligent scheduling module for dynamic optimization;
The data acquisition module is connected with the network communication module, and the data acquisition module transmits the processed data to the network communication module for safe transmission;
the network communication module is connected with the security management module, and transmits the transmitted data to the security management module for security encryption and authentication;
The device management module is connected with the data acquisition module and transmits device state information to the data acquisition module for data updating and device monitoring;
The data processing module is connected with the user interface module, and transmits the analyzed and processed data to the user interface module for information display and user interaction;
And the redundancy and backup module transmits the backup data to all modules for fault recovery and data protection.
As a preferable scheme of the intelligent gateway based on multi-protocol conversion, the invention comprises the following steps: the working steps of the polling scheduling module include,
The polling scheduling module is initialized when the system is started, and a device list and a polling strategy are loaded;
setting a time interval and an order of polling, which are configured based on importance of the device and a frequency of data update;
At the beginning of each polling period, the module checks the device list to confirm the status and availability of all devices;
for offline or malfunctioning devices, the module will attempt to reconnect or flag as maintenance status;
the module sends a data request to each device according to a set sequence;
After the equipment responds to the data request, the polling scheduling module receives the returned data;
the polling scheduling module is combined with the intelligent scheduling module, and the polling strategy is adjusted according to the real-time data and DACSA algorithm;
the polling scheduling module updates the state information of the equipment, including the last time of successful communication and the collected data;
All polling activities and results are recorded in the system log;
As a preferable scheme of the intelligent gateway based on multi-protocol conversion, the invention comprises the following steps: the intelligent regulation module comprises the working steps of,
The intelligent adjustment module collects real-time data and historical data, and analyzes the communication mode and the data generation frequency of the equipment;
analyzing response time and network conditions of the device;
Evaluating device behavior and network conditions over a short period of time using a DACSA algorithm that runs based on the power device;
According to the results of the data analysis and the prediction model, a polling strategy is formulated;
the polling strategy comprises the steps of setting the priority, time interval and sequence of polling;
As a preferable scheme of the intelligent gateway based on multi-protocol conversion, the invention comprises the following steps: the DACSA algorithm includes: data acquisition and analysis, D t＝{d1,d2,...,dn } wherein each D i contains information such as equipment state, data update frequency and the like, and h= { H 1,h2,...,hm } wherein each H i contains historical communication mode and fault record information;
Calculating a statistical index Stat d＝fstat(Dt, H of the communication mode and response time for each device d);
for each device d, calculating a behavior prediction P (d, t) =f pred(Statd,Cd using a prediction function f pred;
Calculating a network condition prediction N (d, t) =f net(Dt, H) using a prediction function f net;
If the data has time dependency, predicting the equipment behavior by using a time sequence analysis method.
If the influence of equipment configuration needs to be considered, a machine learning regression model is used;
For each device d, calculating a polling policy S (d, t) =f strat(P(d,t),N(d,t),Cd) using a policy function f strat;
Calculating a data transmission optimization suggestion T (d, T) =f opt (N (d, T)) using an optimization function f opt;
For each device D, the polling strategy S (D, T) and the data transmission optimization proposal T (D, T) are dynamically adjusted according to the real-time data D t and the system load L t.
Wherein D t is a real-time data set collected at time T, H is a historical data set, C d is configuration information of device D, L t is a system load at time T, P (D, T) is a behavior prediction of device D at time T, N (D, T) is a prediction of network condition at time T, S (D, T) is a polling policy of device D at time T, T (D, T) is a data transmission optimization suggestion, f stat(Dt, H) is a statistical analysis function for analyzing device communication mode and response time, f pred(Statd,Cd) is a prediction function for predicting device behavior f net(Dt based on statistical indicators and device configuration, H) is a network prediction function for predicting network conditions, f strat(P(d,t),N(d,t),Cd) is a policy function for making a polling policy, f opt (N (D, T)) is an optimization function for providing a data transmission optimization suggestion.
As a preferable scheme of the intelligent gateway based on multi-protocol conversion, the invention comprises the following steps: the statistical analysis functions f stat(Dt, H) are input as real-time data D t＝{d1,d2,...,dn and historical data h= { H 1,h2,...,hm };
processing to calculate statistical indexes of communication modes and response time of each device d;
The output is a statistical index Stat d＝{μd,σd,Fd;
Fd＝Histogram(Dt)
Wherein F stat(Dt, H) is a statistical analysis function for analyzing real-time data and historical data, calculating statistical indexes of communication mode and response time of the device, D t is a real-time data set including data samples of a plurality of devices, H is a historical data set including information such as historical communication mode and fault record of the device, D i is a single data sample in the real-time data set, representing a state of one device at a certain time point, stat d is statistical index output for device D, μ d is average response time or data update frequency of device D, σ d is standard deviation of response time or data update frequency of device D, for measuring discrete degree of data, F d is communication mode of device D, for displaying data distribution condition, n is number of data samples of device D in the real-time data set, Is the sum of all data samples in the real-time dataset for device d.
As a preferable scheme of the intelligent gateway based on multi-protocol conversion, the invention comprises the following steps: the intelligent regulation module further comprises the working steps of,
Monitoring the equipment state and the network communication condition in real time, and dynamically adjusting a polling strategy according to the change;
for devices with frequent data update or high priority, the polling interval is reduced;
Optimizing data transmission path and method, reducing network congestion and improving data transmission efficiency;
And when the network condition is poor, the size and the frequency of the data transmission are adjusted.
As a preferable scheme of the intelligent gateway based on multi-protocol conversion, the invention comprises the following steps: the intelligent adjustment module is not started under the conventional scheduling condition, and the gateway accesses the equipment according to a preset sequence and time intervals by using a basic polling scheduling strategy under the conventional scheduling condition;
when the gateway load exceeds a preset threshold value, the system automatically switches to an intelligent scheduling mode;
when the gateway load returns to the normal range, the intelligent scheduling module will reevaluate whether the intelligent scheduling needs to be continuously used;
and if the system is stable, the intelligent scheduling module switches the scheduling mode back to the basic polling scheduling.
Another object of the present invention is to provide a method for implementing an intelligent gateway based on multi-protocol conversion, which implements conversion between different power communication protocols through a multi-protocol conversion module, so as to solve the problem of incompatibility of protocols between devices.
As a preferable scheme of the intelligent gateway implementation method based on multi-protocol conversion, the invention comprises the following steps: the steps are as follows,
After the gateway is started, the intelligent gateway performs self-checking, including hardware state checking and software module loading;
The security management module is initialized, and encryption parameters and an access control list are set;
the device management module searches for and identifies the power devices connected to the gateway;
for newly discovered equipment, the equipment management module registers information of the newly discovered equipment into a system and configures communication parameters;
the data acquisition module periodically acquires data from each power device according to the instruction of the polling scheduling module;
The multi-protocol conversion module receives the data collected by the data collection module and performs protocol conversion according to the requirements of a target system;
for data needing long-term storage, the data processing module compresses the data and stores the compressed data;
the intelligent scheduling module analyzes the real-time data and the historical data and predicts the communication requirement of the equipment;
According to the prediction result, the intelligent scheduling module dynamically adjusts a polling strategy to optimize the data acquisition efficiency;
the network communication module sends the processed data to a central monitoring system or other external systems through a safe channel;
the security management module monitors the data transmission process and prevents data leakage and unauthorized access;
The redundancy and backup module periodically backs up the key data and the system configuration;
When a fault occurs, the gateway quickly recovers from the backup, reducing system downtime.
The invention has the beneficial effects that: the functions of multi-protocol conversion, data acquisition, intelligent scheduling, safety management and the like are realized, and the overall efficiency and safety of the power and industrial communication system are improved. By solving the problems of incompatibility of protocols between devices, untimely data acquisition, low communication efficiency, insufficient safety and the like, the gateway realizes seamless integration of data exchange between devices, improves manageability and stability of a system, and reduces operation and maintenance cost and risk.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
Fig. 1 is a block diagram of an intelligent gateway based on multi-protocol conversion according to an embodiment of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Example 1
Referring to fig. 1, a first embodiment of the present invention provides an intelligent gateway based on multi-protocol conversion, which includes 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.
Further, the multi-protocol conversion module is used for realizing conversion between different power communication protocols, wherein the power communication protocols comprise IEC 104, IEC61850, modbus, DLT645 and MQTT so as to support diversified communication requirements;
the data acquisition module is used for collecting data from power equipment in the power system;
the polling scheduling module is used for reading data or sending commands to the connected devices according to a preset sequence and a preset time interval, so that all the devices can be accessed regularly;
The network communication module is used for being responsible for the communication between the intelligent gateway and an external network;
the security management module is used for monitoring all data transmission and equipment access activities, implementing user authentication, data encryption and access control strategies and preventing unauthorized access;
the device management module is used for monitoring and managing all devices connected to the gateway and automatically searching, configuring, detecting and maintaining the power device;
the data processing module is used for preprocessing and analyzing the acquired data, including data cleaning, format conversion, data compression and storage, and supporting a complex data processing algorithm;
The user interface module is used for providing an operation interface, so that a user can monitor and manage the running state of the gateway and support a Web interface, a mobile application and a command line interface;
the redundancy and backup module is used for realizing redundancy backup of data and service, improving the reliability of the system and rapidly recovering the operation of the system when faults occur;
the intelligent scheduling module is used for dynamically adjusting the polling strategy by utilizing DACSA algorithm and real-time data analysis, optimizing the communication efficiency and response time, and has self-learning capability.
Furthermore, the multi-protocol conversion module transmits data of different protocols to the data acquisition module for uniform format conversion;
the data acquisition module is connected with the polling scheduling module, and transmits acquired data to the polling scheduling module for timing access scheduling
The polling scheduling module is connected with the intelligent scheduling module, and transmits a basic access strategy to the intelligent scheduling module for dynamic optimization;
The data acquisition module is connected with the network communication module, and the data acquisition module transmits the processed data to the network communication module for safe transmission;
the network communication module is connected with the security management module, and transmits the transmitted data to the security management module for security encryption and authentication;
The device management module is connected with the data acquisition module and transmits device state information to the data acquisition module for data updating and device monitoring;
The data processing module is connected with the user interface module, and transmits the analyzed and processed data to the user interface module for information display and user interaction;
And the redundancy and backup module transmits the backup data to all modules for fault recovery and data protection.
Further, the working steps of the polling scheduling module comprise,
The polling scheduling module is initialized when the system is started, and a device list and a polling strategy are loaded;
setting a time interval and order of polling, which may be configured based on the importance of the device and the frequency of data updates;
At the beginning of each polling period, the module checks the device list to confirm the status and availability of all devices;
for offline or malfunctioning devices, the module will attempt to reconnect or flag as maintenance status;
the module sends a data request to each device according to a set sequence;
After the equipment responds to the data request, the polling scheduling module receives the returned data;
the polling scheduling module is combined with the intelligent scheduling module, and the polling strategy is adjusted according to the real-time data and DACSA algorithm;
the polling scheduling module updates the state information of the equipment, including the last time of successful communication and the collected data;
All polling activities and results are recorded in the system log;
further, the intelligent regulation module comprises the working steps of,
The intelligent adjustment module collects real-time data and historical data, and analyzes the communication mode and the data generation frequency of the equipment;
analyzing response time and network conditions of the device;
Predicting device behavior and network conditions within a short period of time using a power device operation DACSA algorithm;
According to the results of the data analysis and the prediction model, a polling strategy is formulated;
the polling strategy comprises the steps of setting the priority, time interval and sequence of polling;
Still further, the DACSA algorithm includes: data acquisition and analysis, D t＝{d1,d2,...,dn } wherein each D i contains information such as equipment state, data update frequency and the like, and h= { H 1,h2,...,hm } wherein each H i contains historical communication mode and fault record information;
Calculating a statistical index Stat d＝fstat(Dt, H of the communication mode and response time for each device d);
for each device d, calculating a behavior prediction P (d, t) =f pred(Statd,Cd using a prediction function f pred;
Calculating a network condition prediction N (d, t) =f net(Dt, H) using a prediction function f net;
If the data has time dependency, predicting the equipment behavior by using a time sequence analysis method.
If the influence of equipment configuration needs to be considered, a machine learning regression model is used;
For each device d, calculating a polling policy S (d, t) =f strat(P(d,t),N(d,t),Cd) using a policy function f strat;
Calculating a data transmission optimization suggestion T (d, T) =f opt (N (d, T)) using an optimization function f opt;
For each device D, the polling strategy S (D, T) and the data transmission optimization proposal T (D, T) are dynamically adjusted according to the real-time data D t and the system load L t.
Wherein D t is a real-time data set collected at time T, H is a historical data set, C d is configuration information of device D, L t is a system load at time T, P (D, T) is a behavior prediction of device D at time T, N (D, T) is a prediction of network condition at time T, S (D, T) is a polling policy of device D at time T, T (D, T) is a data transmission optimization suggestion, f stat(Dt, H) is a statistical analysis function for analyzing device communication mode and response time, f pred(Statd,Cd) is a prediction function for predicting device behavior f net(Dt based on statistical indicators and device configuration, H) is a network prediction function for predicting network conditions, f strat(P(d,t),N(d,t),Cd) is a policy function for making a polling policy, f opt (N (D, T)) is an optimization function for providing a data transmission optimization suggestion.
Further, the statistical analysis function f stat(Dt, H) is input as real-time data D t＝{d1,d2,...,dn and historical data h= { H 1,h2,...,hm };
processing to calculate statistical indexes of communication modes and response time of each device d;
The output is a statistical index Stat d＝{μd,σd,Fd;
Fd＝Histogram(Dt)
The predictive function f pred(Statd,Cd) is
Inputs are a statistical index Stat d and a device configuration C d.
The process is to predict device behavior using time series analysis or machine learning regression models.
The output is the device behavior prediction P (d, t).
If the time series analysis is used as P (d, t) =arima (Stat d,Cd)
If the machine learning regression model is used, P (d, t) = Regressor (Stat d,Cd)
Network prediction function f net(Dt, H) is
The inputs are real-time data D t and history data H.
The process is to predict network conditions using a neural network or deep learning model.
The output is the network condition prediction N (d, t).
N(d,t)＝NeuralNetwork(Dt,H)
Policy function f strat(P(d,t),N(d,t),Cd) is
Inputs are device behavior prediction P (d, t), network condition prediction N (d, t) and device configuration C d.
The process formulates a polling strategy using a multi-objective optimization and decision tree.
The output is the polling strategy S (d, T) = { T d,Priod }.
S(d,t)＝MultiObjectiveOptimization(P(d,t),N(d,t),Cd)
The optimization function f opt (N (d, t)) is
The inputs are network condition predictions N (d, t).
The process proposes data transmission optimization suggestions for using heuristic algorithms or linear programming.
Output is data transmission optimization suggestion T (d, T) = { Path d,Methodd,Freqd }.
It should be noted that the DACSA algorithm of the present invention may be adjusted and optimized according to the actual application scenario and data characteristics. In some embodiments, it may be desirable to continuously adjust parameters of the model based on real-time data and system feedback.
Further, the working steps of the intelligent adjusting module further comprise,
Monitoring the equipment state and the network communication condition in real time, and dynamically adjusting a polling strategy according to the change;
for devices with frequent data update or high priority, the polling interval is reduced;
Optimizing data transmission path and method, reducing network congestion and improving data transmission efficiency;
And when the network condition is poor, the size and the frequency of the data transmission are adjusted.
Furthermore, the intelligent adjustment module is not started under the conventional scheduling condition, and the gateway accesses the equipment according to a preset sequence and time intervals by using a basic polling scheduling strategy under the conventional scheduling condition;
when the gateway load exceeds a preset threshold value, the system automatically switches to an intelligent scheduling mode;
when the gateway load returns to the normal range, the intelligent scheduling module will reevaluate whether the intelligent scheduling needs to be continuously used;
it should be noted that in some embodiments the calculation of the threshold may be performed as follows:
and (3) data collection: the above-mentioned data of the system resource usage, network communication index, device status information, etc. are collected.
Data analysis: the historical performance data is processed by using a statistical analysis method, and the normal range and peak value of the system load are identified.
Model training: the data are trained using a machine learning algorithm to build a model that predicts the system load.
Threshold setting: an initial threshold is set based on model predictions and traffic demands. In some embodiments, the threshold is set at a time when the system resource usage reaches 85% to ensure that the system has sufficient margin to handle bursty load increases.
Testing and adjusting: the effect of the threshold is tested in actual operation and is appropriately adjusted according to the system performance. If the system is found to be still able to operate steadily when the threshold is reached, it may be considered to lower the threshold to further increase efficiency; conversely, if the system is not behaving stably, the threshold needs to be increased.
Dynamic optimization: the threshold should be dynamically adjustable to automatically adjust the threshold to accommodate changing load conditions based on real-time performance data of the system and external conditions.
The setting of the threshold is an iterative process, and needs to be continuously monitored, evaluated and adjusted, so that the system can meet the service requirement and simultaneously can cope with sudden high-load conditions.
And if the system is stable, the intelligent scheduling module switches the scheduling mode back to the basic polling scheduling.
Example 2
For one embodiment of the present invention, a method for implementing an intelligent gateway based on multi-protocol conversion is provided, including the following steps,
After the gateway is started, the intelligent gateway performs self-checking, including hardware state checking and software module loading;
The security management module is initialized, and encryption parameters and an access control list are set;
the device management module searches for and identifies the power devices connected to the gateway;
for newly discovered equipment, the equipment management module registers information of the newly discovered equipment into a system and configures communication parameters;
the data acquisition module periodically acquires data from each power device according to the instruction of the polling scheduling module;
The multi-protocol conversion module receives the data collected by the data collection module and performs protocol conversion according to the requirements of a target system;
for data needing long-term storage, the data processing module compresses the data and stores the compressed data;
the intelligent scheduling module analyzes the real-time data and the historical data and predicts the communication requirement of the equipment;
According to the prediction result, the intelligent scheduling module dynamically adjusts a polling strategy to optimize the data acquisition efficiency;
the network communication module sends the processed data to a central monitoring system or other external systems through a safe channel;
the security management module monitors the data transmission process and prevents data leakage and unauthorized access;
The redundancy and backup module periodically backs up the key data and the system configuration;
When a fault occurs, the gateway quickly recovers from the backup, reducing system downtime.
Example 3
The third embodiment of the invention provides an intelligent gateway based on multi-protocol conversion.
In order to verify the invention, the traditional gateway is used for comprehensively analyzing a plurality of aspects such as communication efficiency, data transmission delay, system stability and the like through a simulation experiment;
1. Communication efficiency comparison
TABLE 1
| Context | Number of traditional gateway communications | Intelligent gateway communication times |
| Scenario 1 | 1000 | 800 |
| Scenario 2 | 1200 | 900 |
| Scenario 3 | 1500 | 1000 |
As can be seen from table 1, under different circumstances, the intelligent gateway of the present invention reduces the communication times by dynamically adjusting the polling policy, thereby improving the communication efficiency, and the intelligent gateway of the present invention can optimize the polling policy according to the real-time data and DACSA algorithm, so that the efficiency of each communication is higher, and the unnecessary communication times are reduced.
2. Data transmission delay comparison results are shown in the following table:
TABLE 2
| Context | Traditional gateway delay (ms) | Intelligent gateway delay (ms) |
| Scenario 1 | 50 | 30 |
| Scenario 2 | 60 | 35 |
| Scenario 3 | 55 | 32 |
As can be seen from table 2, the intelligent gateway of the present invention has a lower data transmission delay than the conventional gateway under different circumstances. The intelligent gateway can dynamically adjust the polling strategy according to the real-time data and the historical data, so that the response speed of data transmission is faster, and the delay time of the data transmission is reduced.
3. System stability comparison
As can be seen from table 3, the conventional gateway and the intelligent gateway of the present invention are compared in terms of system stability, and under different circumstances, the number of failures of the system is recorded, and the results are shown in the following table:
TABLE 3 Table 3
| Context | Number of traditional gateway failures | Intelligent gateway failure times |
| Scenario 1 | 3 | 1 |
| Scenario 2 | 4 | 2 |
| Scenario 3 | 2 | 0 |
Compared with the traditional gateway, the intelligent gateway has higher system stability. The intelligent gateway of the invention adjusts the polling strategy and the recovery system in time through the intelligent scheduling and backup module, reduces the occurrence times of the faults of the system and improves the reliability of the system.
In summary, the intelligent gateway based on multi-protocol conversion and the method thereof have obvious advantages in improving the reliability and efficiency of the system compared with the traditional gateway. The dynamic adjustment of the polling strategy, the intelligent scheduling and backup module and other characteristics can effectively improve the stability and the communication efficiency of the system, and bring important technical progress to the field of power communication.
Example 4
A fourth embodiment of the present invention, which is different from the first three embodiments, is:
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a read-only memory (ROM, readOnlyMemory), a random access memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CDROM, optical storage, etc.) having computer-usable program code embodied therein. The scheme in the embodiment of the application can be realized by adopting various computer languages, such as object-oriented programming language Java, an transliteration script language JavaScript and the like.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. An intelligent gateway based on multi-protocol conversion is characterized in that: the system comprises 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.
2. The intelligent gateway based on multi-protocol conversion according to claim 1, wherein: the multi-protocol conversion module is used for realizing conversion among different power communication protocols, and the power communication protocols comprise IEC 104, IEC61850, modbus, DLT645 and MQTT so as to support diversified communication requirements;
the data acquisition module is used for collecting data from power equipment in the power system;
the polling scheduling module is used for reading data or sending commands to the connected devices according to a preset sequence and a preset time interval, so that all the devices can be accessed regularly;
The network communication module is used for being responsible for the communication between the intelligent gateway and an external network;
the security management module is used for monitoring all data transmission and equipment access activities, implementing user authentication, data encryption and access control strategies and preventing unauthorized access;
the device management module is used for monitoring and managing all devices connected to the gateway and automatically searching, configuring, detecting and maintaining the power device;
the data processing module is used for preprocessing and analyzing the acquired data, including data cleaning, format conversion, data compression and storage, and supporting a complex data processing algorithm;
the user interface module is used for providing an operation interface, so that a user monitors and manages the running state of the gateway and supports a Web interface, mobile application and command line interface;
the redundancy and backup module is used for realizing redundancy backup of data and service, improving the reliability of the system and rapidly recovering the operation of the system when faults occur;
the intelligent scheduling module is used for dynamically adjusting the polling strategy by utilizing DACSA algorithm and real-time data analysis, optimizing the communication efficiency and response time, and has self-learning capability.
3. The intelligent gateway based on multi-protocol conversion according to claim 2, wherein: the multi-protocol conversion module transmits data of different protocols to the data acquisition module to perform unified format conversion;
the data acquisition module is connected with the polling scheduling module, and transmits acquired data to the polling scheduling module for timing access scheduling
The polling scheduling module is connected with the intelligent scheduling module, and transmits a basic access strategy to the intelligent scheduling module for dynamic optimization;
The data acquisition module is connected with the network communication module, and the data acquisition module transmits the processed data to the network communication module for safe transmission;
the network communication module is connected with the security management module, and transmits the transmitted data to the security management module for security encryption and authentication;
The device management module is connected with the data acquisition module and transmits device state information to the data acquisition module for data updating and device monitoring;
The data processing module is connected with the user interface module, and transmits the analyzed and processed data to the user interface module for information display and user interaction;
And the redundancy and backup module transmits the backup data to all modules for fault recovery and data protection.
4. A multi-protocol conversion based intelligent gateway according to claim 3, wherein: the working steps of the polling scheduling module include,
The polling scheduling module is initialized when the system is started, and a device list and a polling strategy are loaded;
Setting a time interval and an order of polling, wherein the time interval and the order are configured based on importance of the device and frequency of data update;
At the beginning of each polling period, the module checks the device list to confirm the status and availability of all devices;
for offline or malfunctioning devices, the module will attempt to reconnect or flag as maintenance status;
the module sends a data request to each device according to a set sequence;
After the equipment responds to the data request, the polling scheduling module receives the returned data;
The polling scheduling module is combined with the intelligent scheduling module, and the polling strategy is adjusted according to the real-time data and DACSA algorithm;
the polling scheduling module updates the state information of the equipment, including the last time of successful communication and the collected data;
all polling activities and results are recorded in the system log.
5. The intelligent gateway based on multi-protocol conversion according to claim 4, wherein: the working steps of the intelligent scheduling module include,
The intelligent scheduling module collects real-time data and historical data, and analyzes the communication mode and the data generation frequency of the equipment;
analyzing response time and network conditions of the device;
Predicting device behavior and network conditions within a short period of time using a power device operation DACSA algorithm;
According to the results of the data analysis and the prediction model, a polling strategy is formulated;
The polling policy includes setting the priority, time interval, and order of polling.
6. The intelligent gateway based on multi-protocol conversion according to claim 5, wherein:
The DACSA algorithm includes: data acquisition and analysis, D t＝{d1,d2,...,dn } wherein each D i contains information such as equipment state, data update frequency and the like, and h= { H 1,h2,...,hm } wherein each H i contains historical communication mode and fault record information;
Calculating a statistical index Stat d＝fstat(Dt, H of the communication mode and response time for each device d);
for each device d, calculating a behavior prediction P (d, t) =f pred(Statd,Cd using a prediction function f pred;
Calculating a network condition prediction N (d, t) =f net(Dt, H) using a prediction function f net;
If the data has time dependency, predicting the equipment behavior by using a time sequence analysis method.
If the influence of equipment configuration needs to be considered, a machine learning regression model is used;
For each device d, calculating a polling policy S (d, t) =f strat(P(d,t),N(d,t),Cd) using a policy function f strat;
Calculating a data transmission optimization suggestion T (d, T) =f opt (N (d, T)) using an optimization function f opt;
dynamically adjusting a polling strategy S (D, T) and a data transmission optimization suggestion T (D, T) for each device D according to the real-time data D t and the system load L t;
Wherein D t is a real-time dataset collected at time T, H is a historical dataset, C d is configuration information of device D, L t is a system load at time T, P (D, T) is a behavior prediction at time T of device D, N (D, T) is a prediction at time T of network conditions, S (D, T) is a polling policy at time T of device D, T (D, T) is a data transmission optimization suggestion, f stat(Dt, H) is a statistical analysis function for analyzing device communication mode and response time, f pred(Statd,Cd) is a prediction function for predicting device behavior f net(Dt based on statistical indicators and device configuration, H) is a network prediction function for predicting network conditions, f strat(P(d,t),N(d,t),Cd) is a policy function for determining a polling policy, f opt (N (D, T)) is an optimization function for providing a data transmission optimization suggestion.
7. The intelligent gateway based on multi-protocol conversion according to claim 6, wherein: the statistical analysis functions f stat(Dt, H) are input as real-time data D t＝{d1,d2,...,dn and historical data h= { H 1,h2,...,hm };
processing to calculate statistical indexes of communication modes and response time of each device d;
The output is a statistical index Stat d＝{μd,σd,Fd;
Fd＝Histogram(Dt)
wherein F stat(Dt, H) is a statistical analysis function for analyzing real-time data and historical data, calculating statistical indexes of communication mode and response time of the device, D t is a real-time data set, including data samples of a plurality of devices, H is a historical data set, including information such as historical communication mode and fault record of the device, D i is a single data sample in the real-time data set, representing a state of a device at a certain time point, stat d is output of the statistical indexes of the device D, mu d is average response time or data update frequency of the device D, sigma d is standard deviation of the response time or data update frequency of the device D, for measuring discrete degree of data, F d is communication mode of the device D, for displaying data distribution condition, and n is number of data samples of the device D in the real-time data set. Is the sum of all data samples in the real-time dataset for device d.
8. The intelligent gateway based on multi-protocol conversion according to claim 7, wherein: the intelligent regulation module further comprises the working steps of,
Monitoring the equipment state and the network communication condition in real time, and dynamically adjusting a polling strategy according to the change;
for devices with frequent data update or high priority, the polling interval is reduced;
Optimizing data transmission path and method, reducing network congestion and improving data transmission efficiency;
And when the network condition is poor, the size and the frequency of the data transmission are adjusted.
9. The intelligent gateway based on multi-protocol conversion according to claim 8, wherein: the intelligent adjustment module is not started under the conventional scheduling condition, and the gateway accesses the equipment according to a preset sequence and time intervals by using a basic polling scheduling strategy under the conventional scheduling condition;
when the gateway load exceeds a preset threshold value, the system automatically switches to an intelligent scheduling mode;
when the gateway load returns to the normal range, the intelligent scheduling module will reevaluate whether the intelligent scheduling needs to be continuously used;
and if the system is stable, the intelligent scheduling module switches the scheduling mode back to the basic polling scheduling.
10. An implementation method of an intelligent gateway based on multi-protocol conversion, applied to the intelligent gateway based on multi-protocol conversion of any one of claims 1 to 9, is characterized in that:
after the gateway is started, the intelligent gateway performs self-checking, including hardware state checking and software module loading;
The security management module is initialized, and encryption parameters and an access control list are set;
the device management module searches for and identifies the power devices connected to the gateway;
for newly discovered equipment, the equipment management module registers information of the newly discovered equipment into a system and configures communication parameters;
the data acquisition module periodically acquires data from each power device according to the instruction of the polling scheduling module;
The multi-protocol conversion module receives the data collected by the data collection module and performs protocol conversion according to the requirements of a target system;
for data needing long-term storage, the data processing module compresses the data and stores the compressed data;
the intelligent scheduling module analyzes the real-time data and the historical data and predicts the communication requirement of the equipment;
According to the prediction result, the intelligent scheduling module dynamically adjusts a polling strategy to optimize the data acquisition efficiency;
the network communication module sends the processed data to a central monitoring system or other external systems through a safe channel;
the security management module monitors the data transmission process and prevents data leakage and unauthorized access;
The redundancy and backup module periodically backs up the key data and the system configuration;
When a fault occurs, the gateway quickly recovers from the backup, reducing system downtime.
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