High-speed safe and reliable network communication method in transformer substation

Abstract

The invention discloses a high-speed, safe and reliable network communication method in a transformer substation, which relates to the technical field of network communication, and comprises the following steps of: calculating a network congestion coefficient of a network node by monitoring the throughput, time delay and bandwidth utilization rate of each network node in the transformer substation in real time, and marking a congestion node; the method comprises the following steps: acquiring a queue length of a congestion node, calculating a real-time queue increment, combining a corresponding network congestion coefficient, determining a data discarding probability, calculating a data discarding frequency of each sensor, and discarding a data packet, which needs to be communicated, of each sensor by a network node according to the data discarding frequency of each sensor. And network congestion can be effectively relieved. In a network peak period, reasonable distribution of network resources can be ensured by discarding a part of non-critical or retransmittable data packets, and network paralysis is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of network communication, and in particular to a high-speed, safe and reliable network communication method in a substation. Background Art

[0002] With the rapid development and intelligent trend of power systems, substations, as key nodes for power transmission and distribution, have increasingly higher performance requirements for their internal communication networks. Traditional wired communication networks can no longer meet the needs of real-time monitoring and fault diagnosis of substations. Therefore, exploring new communication network architectures and studying corresponding key technologies to improve network performance and security have become important directions for the current development of substation technology. In the substation on-site communication network architecture, the research on high-speed network communication methods is crucial. High-speed network communication methods aim to increase data transmission rates, reduce latency, and improve network stability and reliability to meet high real-time requirements such as real-time monitoring and fault diagnosis of substations.

[0003] In the Chinese invention application with application publication number CN110493180A, a real-time analysis method for substation network communication traffic is disclosed. In order to ensure the safe, stable and reliable operation of complex power systems, establish a digital power system and an information-based power enterprise that promotes production automation and management modernization through informatization, the following scheme is proposed, including the following steps: analyzing and summarizing typical network traffic collection and analysis technologies, analyzing the practicality of substation protocols from the perspective of technical advantages and disadvantages; proposing a substation network intrusion detection and early warning model based on the analysis results in step 1; taking traffic anomalies as the entry point. The present invention proposes a substation network traffic intrusion detection and early warning model, realizes dynamic judgment of traffic anomalies, and proposes a dynamic abnormal traffic judgment mechanism based on historical data characteristics, which improves its adaptability and accuracy.

[0004] In the Chinese invention application with application publication number CN115499343A, a delay analysis method, system, device and storage medium based on effective contention flow are disclosed, including abstracting a new generation substation network communication system into an information flow fluid model; judging whether the business flow message and the target business flow message flowing through the same port are effective contention flows based on the determined busy period of each business flow message on each port on its path and the preset basic judgment rules of effective contention flow, and forming an effective contention flow set of the target business flow message on the port; considering the serialization effect, eliminating the effective contention flows that are repeatedly counted on two adjacent ports on the path with serialization, and obtaining the effective contention flow set of the port group; combining the effective contention flow set of the port group with conventional network calculation, and calculating the delay upper bound of the new generation network communication system.

[0005] In the above invention applications, invention CN110493180A proposed a substation network traffic intrusion detection and early warning model, which realized the dynamic judgment of traffic anomalies. However, the model can only issue an early warning signal when a traffic anomaly is detected, and cannot automatically take further analysis and processing. This means that after receiving the early warning, the operation and maintenance personnel still need to intervene manually to further judge and process the abnormal traffic. Invention CN115499343A combines the effective competitive flow set of the port group with conventional network calculations to calculate the upper bound of the delay of the new generation network communication system. Although the impact of serialization is taken into account, no specific solution is given, and manual intervention is still required to further judge and process the abnormal traffic.

[0006] To this end, the present invention provides a high-speed, safe and reliable network communication method in a substation. Summary of the invention

[0007] 1. Technical issues to be resolved In view of the shortcomings of the prior art, the present invention provides a high-speed, safe and reliable network communication method in a substation. The present invention monitors the throughput of each network node in the substation in real time. , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes , mark the congested node; get the queue length of the congested node , calculate the real-time queue growth , combined with its corresponding network congestion coefficient Jyc , determine the probability of data discard Dg , calculate the data discard frequency of each sensor , network nodes discard the data based on the frequency of each sensor By discarding the data packets that each sensor needs to communicate, network congestion can be effectively alleviated. During network peak hours, by discarding some non-critical or retransmittable data packets, reasonable allocation of network resources can be ensured to avoid network paralysis, thereby solving the technical problems recorded in the background technology.

[0008] (II) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: A high-speed, safe and reliable network communication method in a substation, comprising the following steps: Real-time monitoring of the throughput of each network node in the substation , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes , mark the congested nodes; Get the queue length of the congested node , calculate the real-time queue growth , combined with its corresponding network congestion coefficient Jyc , determine the probability of data discard Dg ; Get the average packet size of each communicating sensor , Communication frequency , historical average data and the most recent successful transfer data , calculate the data discard frequency of each sensor , network nodes discard the data based on the frequency of each sensor Each sensor needs to discard the data packets for communication.

[0009] Furthermore, network monitoring tools such as network analyzers and traffic monitoring software are used to monitor the throughput of each network node in the substation in real time. , Delay and bandwidth utilization .

[0010] Network monitoring tools are software or hardware systems used to monitor and manage network activities, including network traffic monitoring tools, network security monitoring tools, and network device monitoring tools. NetworkMiner is a graphical network traffic analysis tool that can extract files from network traffic and display related metadata such as file name, file type, etc. It also provides protocol analysis functions such as DNS, HTTP, and FTP. Zabbix is ​​an enterprise-level open source network monitoring solution that supports monitoring of various network devices, servers, and virtual machines. It provides a distributed monitoring architecture, advanced alarm and notification functions, and powerful data collection and analysis capabilities. Security Onion is a software suite for network security monitoring and intrusion detection based on the Ubuntu operating system and open source tools. It can monitor network traffic and logs in real time, analyze and detect threat behaviors.

[0011] In network communications, bandwidth refers to the maximum rate at which a network can transmit data, while bandwidth utilization reflects the actual use of network bandwidth. If bandwidth utilization is too high, it means that the network is heavily loaded, and problems such as congestion and delay may occur, affecting network performance and service quality. On the contrary, if bandwidth utilization is too low, it may mean that network resources are not fully utilized and there is waste.

[0012] Furthermore, the throughput of each network node is obtained , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes :

[0013] in, i Indicates the sequential numbering of each network node in the substation. i =1, 2, …, a , Indicates i The maximum throughput of network nodes, Indicates i The standard delay of a network node is taken as the average of the historical delays of the network node.

[0014] Furthermore, the network congestion coefficient of the network node is obtained. , when the network congestion coefficient Exceed , then the network node is marked as a congested node; is the network congestion coefficient of all network nodes The mean of is the network congestion coefficient of all network nodes The standard deviation of .

[0015] Furthermore, network monitoring tools are used to periodically obtain the queue length of congested nodes. , calculate the real-time queue growth :

[0016] in, j Indicates the detection time sequence number of the queue length. j =1, 2, …, x .

[0017] Furthermore, get the queue length of the congested node , real-time queue growth and its corresponding network congestion coefficient Jyc , determine the probability of data discard Dg :

[0018] in, is the maximum capacity of the queue of the node, The reference queue growth is used to normalize the real-time queue growth. It is twice the average of the node's historical real-time queue growth.

[0019] Furthermore, we use network monitoring tools to capture data packets passing through network nodes, analyze sensor devices that communicate through the node, record them as communication sensors, and count the average data packet capacity of each communication sensor. , Communication frequency and retrieve the historical average data of each communication sensor from the substation data storage terminal and the most recent successful transfer data .

[0020] Furthermore, the average data packet capacity of each communication sensor is obtained , Communication frequency , historical average data and the most recent successful transfer data , calculate the discard weight of each communicating sensor :

[0021] in, k Indicates the sequential number of each communicating sensor, k =1, 2, …, y .

[0022] Furthermore, the probability of data discarding is obtained Dg, The drop weight of each communicating sensor and communication frequency , calculate the data discard frequency of each sensor :

[0023] Network nodes discard data based on the frequency of each sensor Each sensor needs to discard the data packets for communication.

[0024] (III) Beneficial effects The present invention provides a high-speed, safe and reliable network communication method in a substation, which has the following beneficial effects: 1. Real-time monitoring of the throughput of each network node in the substation , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes ,Marking congested nodes can timely discover bottlenecks and congestion in the network. According to the location and congestion degree of the congested nodes, the network configuration can be optimized, such as adjusting the routing strategy, increasing bandwidth resources, etc., to improve the transmission efficiency and stability of the network, and avoid further deterioration

[0025] 2. Get the queue length of the congested node , calculate the real-time queue growth , combined with its corresponding network congestion coefficient Jyc , determine the probability of data discard Dg, dynamically adjusting the data discard probability Dg according to the real-time queue growth and network congestion coefficient Jyc, can more effectively alleviate network congestion, improve network transmission efficiency, give priority to the transmission of key data when the network is congested, and reduce the risk of important data loss.

[0026] 3. Get the average packet capacity of each communication sensor , Communication frequency , historical average data and the most recent successful transfer data , calculate the data discard frequency of each sensor , network nodes discard the data based on the frequency of each sensor By discarding the data packets that each sensor needs to communicate, network congestion can be effectively alleviated. During network peak hours, by discarding some non-critical or retransmittable data packets, network resources can be reasonably allocated to avoid network paralysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 The present invention is a flowchart of a high-speed, safe and reliable network communication method in a substation. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] See also Figure 1 The present invention provides a high-speed, safe and reliable network communication method in a substation, comprising the following steps: Step 1: Real-time monitoring of the throughput of each network node in the substation , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes , mark the congested nodes.

[0030] The step 1 includes the following contents: Step 101: Use network monitoring tools, such as network analyzers, traffic monitoring software, etc., to monitor the throughput of each network node in the substation in real time. , Delay and bandwidth utilization .

[0031] In network communications, bandwidth refers to the maximum rate at which a network can transmit data, while bandwidth utilization reflects the actual use of network bandwidth. If bandwidth utilization is too high, it means that the network is heavily loaded, and problems such as congestion and delay may occur, affecting network performance and service quality. On the contrary, if bandwidth utilization is too low, it may mean that network resources are not fully utilized and there is waste.

[0032] Step 102: Obtain the throughput of each network node , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes :

[0033] in, i Indicates the sequential numbering of each network node in the substation. i =1, 2, …, a , Indicates i The maximum throughput of network nodes, Indicates i The standard delay of a network node is taken as the average of the historical delays of the network node.

[0034] Step 103: Obtain the network congestion coefficient of the network node , when the network congestion coefficient Exceed When , the network node is marked as a congested node. is the network congestion coefficient of all network nodes The mean of is the network congestion coefficient of all network nodes The standard deviation of .

[0035] When using, combine the contents in steps 101 to 103: Real-time monitoring of the throughput of each network node in the substation , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes ,Marking congested nodes can timely discover bottlenecks and congestion in the network. According to the location and congestion degree of the congested nodes, the network configuration can be optimized, such as adjusting the routing strategy, increasing bandwidth resources, etc., to improve the transmission efficiency and stability of the network, and avoid further deterioration

[0036] Step 2: Get the queue length of the congested node , calculate the real-time queue growth , combined with its corresponding network congestion coefficient Jyc , determine the probability of data discard Dg.

[0037] The step 2 includes the following contents: Step 201: Use network monitoring tools to periodically obtain the queue length of the congested node , calculate the real-time queue growth :

[0038] in, j Indicates the detection time sequence number of the queue length. j =1, 2, …, x .

[0039] Network monitoring tools are software or hardware systems used to monitor and manage network activities, including network traffic monitoring tools, network security monitoring tools, and network device monitoring tools. NetworkMiner is a graphical network traffic analysis tool that can extract files from network traffic and display related metadata such as file name, file type, etc. It also provides protocol analysis functions such as DNS, HTTP, and FTP. Zabbix is ​​an enterprise-level open source network monitoring solution that supports monitoring of various network devices, servers, and virtual machines. It provides a distributed monitoring architecture, advanced alarm and notification functions, and powerful data collection and analysis capabilities. Security Onion is a software suite for network security monitoring and intrusion detection based on the Ubuntu operating system and open source tools. It can monitor network traffic and logs in real time, analyze and detect threat behaviors.

[0040] Step 202: Obtain the queue length of the congested node , real-time queue growth and its corresponding network congestion coefficient Jyc , determine the probability of data discard Dg :

[0041] in, is the maximum capacity of the queue of the node, The reference queue growth is used to normalize the real-time queue growth. It is twice the average of the node's historical real-time queue growth.

[0042] When using, combine the contents in steps 201 and 202: Get the queue length of the congested node , calculate the real-time queue growth , combined with its corresponding network congestion coefficient Jyc, determine the probability of data discard Dg , dynamically adjusting the data discard probability Dg according to the real-time queue growth and network congestion coefficient Jyc, can more effectively alleviate network congestion, improve network transmission efficiency, give priority to the transmission of key data when the network is congested, and reduce the risk of important data loss.

[0043] Step 3: Get the average packet capacity of each communication sensor , Communication frequency , historical average data and the most recent successful transfer data , calculate the data discard frequency of each sensor , network nodes discard the data based on the frequency of each sensor Each sensor needs to discard the data packets for communication.

[0044] The step three includes the following contents: Step 301: Use a network monitoring tool to capture data packets passing through a network node, analyze sensor devices that communicate through the node, record them as communication sensors, and count the average data packet capacity of each communication sensor. , Communication frequency and retrieve the historical average data of each communication sensor from the substation data storage terminal and the most recent successful transfer data .

[0045] Among them, the historical average data and the most recent successful transfer data Refers to the data itself transmitted by the sensor, including current, voltage, etc., which is determined by the sensor type.

[0046] Step 302: Obtain the average data packet capacity of each communication sensor , Communication frequency , historical average data and the most recent successful transfer data , calculate the discard weight of each communicating sensor :

[0047] in, k Indicates the sequential number of each communicating sensor, k =1, 2, …, y .

[0048] Step 303: Obtaining data discard probability Dg, The drop weight of each communicating sensor and communication frequency , calculate the data discard frequency of each sensor :

[0049] Network nodes discard data based on the frequency of each sensor Each sensor needs to discard the data packets for communication.

[0050] When using, combine the contents in steps 301 to 303: Get the average packet size of each communicating sensor , Communication frequency , historical average data and the most recent successful transfer data , calculate the data discard frequency of each sensor , network nodes discard the data based on the frequency of each sensor By discarding the data packets that each sensor needs to communicate, network congestion can be effectively alleviated. During network peak hours, by discarding some non-critical or retransmittable data packets, network resources can be reasonably allocated to avoid network paralysis.

[0051] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0052] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0053] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A high-speed, safe and reliable network communication method in a substation, characterized by: The steps include: Real-time monitoring of the throughput of each network node in the substation , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes , mark the congested nodes; Get the queue length of the congested node , calculate the real-time queue growth , combined with its corresponding network congestion coefficient Jb , determine the probability of data discard Dg ; Get the average packet size of each communicating sensor , Communication frequency , historical average data and the most recent successful transfer data , calculate the data discard frequency of each sensor , network nodes discard the data based on the frequency of each sensor Each sensor needs to discard the data packets for communication.

2. A high-speed, safe and reliable network communication method in a substation according to claim 1, characterized in that: Get the throughput of each network node , Delay and bandwidth utilization , calculate the network congestion coefficient of network nodes : in, i Indicates the sequential numbering of each network node in the substation. i =1, 2, …, a , Indicates i The maximum throughput of network nodes, Indicates i The standard delay of a network node is taken as the average of the historical delays of the network node.

3. A high-speed, safe and reliable network communication method in a substation according to claim 1, characterized in that: Get the network congestion coefficient of the network node , when the network congestion coefficient Exceed , then the network node is marked as a congested node; is the network congestion coefficient of all network nodes The mean of is the network congestion coefficient of all network nodes The standard deviation of .

4. A high-speed, safe and reliable network communication method in a substation according to claim 1, characterized in that: Use network monitoring tools to periodically obtain the queue length of congested nodes , calculate the real-time queue growth : in, j Indicates the detection time sequence number of the queue length. j =1, 2, …, x .

5. A high-speed, safe and reliable network communication method in a substation according to claim 1, characterized in that: Get the queue length of the congested node , real-time queue growth and its corresponding network congestion coefficient Jb , determine the probability of data discard Dg : in, is the maximum capacity of the queue of the node, The reference queue growth is used to normalize the real-time queue growth. It is twice the average of the node's historical real-time queue growth.

6. A high-speed, safe and reliable network communication method in a substation according to claim 1, characterized in that: Use network monitoring tools to capture data packets passing through network nodes, analyze sensor devices that communicate through the node, record them as communication sensors, and count the average data packet capacity of each communication sensor , Communication frequency and retrieve the historical average data of each communication sensor from the substation data storage terminal and the most recent successful transfer data . Get the average packet size of each communicating sensor , Communication frequency , historical average data and the most recent successful transfer data , calculate the discard weight of each communicating sensor : in, k Indicates the sequential number of each communicating sensor, k =1, 2, …, y . Get data discard probability Dg, The drop weight of each communicating sensor and communication frequency , calculate the data discard frequency of each sensor : Network nodes discard data based on the frequency of each sensor Each sensor needs to discard the data packets for communication.

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