Intelligent power grid communication protocol optimal configuration method, system, device and medium

Abstract

The invention provides an intelligent power grid communication protocol optimal configuration method, system and device and a medium, and belongs to the technical field of intelligent power grid communication. The method comprises the following steps: collecting communication data of each node in the smart power grid; processing and analyzing the communication data by using a data analysis technology, extracting characteristics of communication requirements, and generating a data analysis result; setting basic parameters of a communication protocol according to a data analysis result; basic parameters of the communication protocol are dynamically adjusted based on an intelligent optimization algorithm, and optimal communication protocol configuration is determined; and the optimal communication protocol configuration is deployed to the corresponding node of the smart power grid, and the optimization effect is evaluated by monitoring the communication performance of each node in real time. Through data driving and intelligent optimization technologies, dynamic adjustment and optimization of communication protocol parameters are realized, and the communication efficiency and stability of an intelligent power grid are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of smart grid communication technology, and more specifically to a smart grid communication protocol optimization configuration method, system, device and medium. Background Art

[0002] As an important part of the modern power system, the stability and efficiency of the communication network of the smart grid have an important impact on the overall operation of the power grid. As the basis of information transmission in the smart grid communication network, the rationality of its configuration is directly related to the communication quality and operation efficiency of the power grid.

[0003] In the prior art, the communication protocol configuration of smart grids is often based on fixed parameter settings and lacks the ability to dynamically adjust according to the actual operation of the grid. This fixed configuration method is often difficult to meet the communication needs of the grid when the grid load changes greatly and the communication demand fluctuates frequently, resulting in communication delays and increased packet loss rates, which in turn affects the stable operation of the grid.

[0004] Traditional communication protocol configuration methods usually rely on manual experience to set parameters, lacking scientific data analysis and optimization methods. This method is not only inefficient, but also difficult to ensure the accuracy and optimality of parameter settings.

[0005] Traditional communication protocol configuration methods cannot be dynamically adjusted according to the actual operation of the power grid, which makes it difficult to meet the communication needs of the power grid when the power grid load changes greatly and the communication demand fluctuates frequently. Moreover, traditional configuration methods rely on manual experience to set parameters and lack scientific data analysis and optimization methods, which makes it difficult to ensure the accuracy and optimality of parameter settings. In addition, due to unreasonable configuration methods, the communication quality and efficiency of smart grids are limited, and communication delays and packet loss rates increase, which seriously affects the stable operation of the power grid. Summary of the invention

[0006] In view of the above problems, the purpose of the present invention is to provide a smart grid communication protocol optimization configuration method, system, device and medium, which realizes dynamic adjustment and optimization of communication protocol parameters through data-driven and intelligent optimization technology, and significantly improves the communication efficiency and stability of the smart grid.

[0007] To achieve the above object, the present invention is implemented through the following technical solutions: a method for optimizing configuration of smart grid communication protocols, comprising: Collecting communication data of each node in the smart grid; the communication data includes: communication flow, communication delay and communication packet loss rate; Use data analysis technology to process and analyze communication data, extract the characteristics of communication needs, and generate data analysis results; According to the data analysis results, the basic parameters of the communication protocol are set; the basic parameters include communication rate, data packet size and retransmission mechanism; Dynamically adjust the basic parameters of the communication protocol based on intelligent optimization algorithms to determine the optimal communication protocol configuration; The optimal communication protocol configuration is deployed to the corresponding nodes of the smart grid, and the optimization effect is evaluated by monitoring the communication performance of each node in real time.

[0008] Further, the collecting of communication data of each node in the smart grid includes: By connecting the network interface cards of each node in the smart grid and utilizing the statistical function of the network interface cards, the communication flow, communication delay and communication packet loss rate are obtained.

[0009] Further, the collecting of communication data of each node in the smart grid includes: Identify the communication protocols of each node in the smart grid; Determining whether the communication protocol supports a performance data collection function; If supported, the communication data of each node in the smart grid is collected through the communication protocol.

[0010] Furthermore, the communication data is processed and analyzed using data analysis technology to extract the characteristics of the communication demand and generate data analysis results, including: Clean, convert and normalize communication data; Based on the communication data, construct the characteristics of communication demand, which include the communication flow rate during peak hours, the average delay rate and the flow fluctuation rate; Perform dimensionality reduction on the characteristics of communication requirements; Based on the communication data, the characteristics of the communication demand are counted according to the timestamp; Use preset algorithm methods to analyze how the characteristics of communication needs change over time and generate data analysis results.

[0011] Further, the basic parameters of the communication protocol are set according to the data analysis results, including: If the data analysis results include that the communication flow during the peak period exceeds the flow threshold, the communication rate in the corresponding communication protocol is set to the theoretical maximum value during the peak period, and the size of the data packet is reduced; If the average delay rate or traffic fluctuation rate in the data analysis results exceeds the corresponding warning value, a retransmission strategy is configured for the corresponding communication protocol to improve the data response speed.

[0012] Further, dynamically adjusting basic parameters of the communication protocol based on the intelligent optimization algorithm to determine the optimal communication protocol configuration includes: Minimizing network latency and maximizing data transmission efficiency are set as optimization goals; Use QR codes to represent basic parameters and optimization goals of communication protocols; Based on the basic parameters of the communication protocol, the population is initialized and N groups of parameter configurations are generated; Define a fitness function to evaluate the performance of each set of parameter configurations; Genetic algorithms are used to iterate and optimize parameter configurations, and the optimal parameter configuration is determined as the optimal communication protocol configuration.

[0013] Furthermore, the optimal communication protocol configuration is deployed to the corresponding nodes of the smart grid, and the communication performance of each node is monitored in real time to evaluate the optimization effect, including: Convert the optimal communication protocol configuration into corresponding configuration parameters and instructions, and deploy the optimal communication protocol configuration to the corresponding nodes of the smart grid through remote configuration; collecting communication data of the corresponding node; Based on the collected communication data, calculate the average communication traffic, the average communication delay and the average communication packet loss rate; The communication traffic mean, communication delay mean and communication packet loss rate mean are compared with the corresponding mean thresholds, and an evaluation result is generated based on the comparison results.

[0014] Correspondingly, the present invention also discloses a smart grid communication protocol optimization configuration system, comprising: A data collection module configured to collect communication data of each node in the smart grid; the communication data includes: communication flow, communication delay and communication packet loss rate; An analysis module configured to process and analyze the communication data using data analysis technology, extract characteristics of the communication demand, and generate data analysis results; A parameter setting module, configured to set basic parameters of the communication protocol according to the data analysis results; the basic parameters include communication rate, data packet size and retransmission mechanism; A parameter adjustment module, configured to dynamically adjust basic parameters of the communication protocol based on an intelligent optimization algorithm to determine an optimal communication protocol configuration; The deployment verification module is configured to deploy the optimal communication protocol configuration to the corresponding nodes of the smart grid, and evaluate the optimization effect by monitoring the communication performance of each node in real time.

[0015] Accordingly, the present invention discloses a smart grid communication protocol optimization configuration device, comprising: A memory, used for storing a smart grid communication protocol optimization configuration program; A processor is used to implement the steps of the smart grid communication protocol optimization configuration method as described in any one of the above items when executing the smart grid communication protocol optimization configuration program.

[0016] Accordingly, the present invention discloses a readable storage medium, on which a smart grid communication protocol optimization configuration program is stored. When the smart grid communication protocol optimization configuration program is executed by a processor, the steps of the smart grid communication protocol optimization configuration method as described in any of the above items are implemented.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention discloses a method, system, device and medium for optimizing the configuration of smart grid communication protocols, which realizes automatic adjustment and optimization of communication protocol parameters by real-time monitoring of communication data of smart grid nodes, combined with data analysis technology and intelligent optimization algorithms. This overall strategy significantly improves the adaptability and flexibility of smart grid communication networks, and effectively responds to the challenges of large changes in grid load and frequent fluctuations in communication demand. At the same time, the method also reduces the need for manual intervention and improves the automation and intelligence level of the configuration process.

[0018] The present invention can optimize the allocation and use of communication resources according to actual communication needs by dynamically adjusting communication protocol parameters. During peak hours, by increasing the communication rate and reducing the size of data packets, communication delays and congestion can be effectively reduced, and communication efficiency can be improved. During off-peak hours, by reducing the communication rate and increasing the size of data packets, communication resources and energy consumption can be balanced, achieving more efficient communication.

[0019] The present invention can timely discover and solve potential communication problems by real-time monitoring and analyzing the communication performance of nodes. When communication delay or packet loss rate increases, the data response speed and transmission success rate can be improved by adjusting parameters such as the retransmission mechanism, thereby enhancing the stability of the communication network. In addition, the present invention can also continuously optimize the communication protocol parameters according to the actual operation of the power grid, further improving the reliability and stability of the communication network.

[0020] The present invention dynamically adjusts the communication protocol parameters through an intelligent optimization algorithm, and can achieve optimal utilization of communication resources. When the communication demand is low, the communication rate and the data packet size can be appropriately reduced to reduce energy consumption and reduce costs. When the communication demand is high, the communication demand of the power grid can be met by increasing the communication rate and increasing the data packet size, thereby maximizing the utilization of communication resources.

[0021] The present invention reduces the need for manual intervention through an automated and intelligent configuration process, making the operation more convenient and efficient. At the same time, the present invention also has good scalability and can adapt to smart grid communication networks of different scales and complexities. With the continuous development and upgrading of smart grids, the present invention can also be continuously optimized and improved to meet more complex and diverse communication needs.

[0022] It can be seen that compared with the prior art, the present invention has outstanding substantive features and significant progress, and the beneficial effects of its implementation are also obvious. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0024] Figure 1 is a method flow chart of a specific embodiment of the present invention; Figure 2 It is a system structure diagram of a specific implementation mode of the present invention.

[0025] In the figure, 1. Data collection module; 2. Analysis module; 3. Parameter setting module; 4. Parameter adjustment module; 5. Deployment verification module. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0027] See also Figure 1 As shown, this embodiment provides a smart grid communication protocol optimization configuration method, including the following steps: S1: Collecting communication data of each node in the smart grid; the communication data includes: communication flow, communication delay and communication packet loss rate.

[0028] In a specific implementation, a network interface card (NIC) can be used to collect communication data. By using the statistical function of the network interface card, data related to network traffic, delay, and error packets (packet loss) can be collected directly from the hardware level. Specifically, by connecting the network interface cards of each node in the smart grid, the statistical function of the network interface card is used to obtain communication traffic, communication delay, and communication packet loss rate.

[0029] In a specific implementation, it is also possible to first identify whether the communication protocol supports the data collection function. If it does, the communication protocol is directly used to collect the communication data of each node in the smart grid. In actual use, if the node adopts the following communication protocols, the performance data can be collected using its built-in functions: SNMP (Simple Network Management Protocol): Collects performance data from network devices (such as routers and switches) through the SNMP protocol, including but not limited to traffic, latency, and packet loss rate.

[0030] NetFlow / IPFIX: Use traffic monitoring protocols such as NetFlow or IPFIX to collect detailed traffic statistics from network devices to help analyze the distribution and flow of communication traffic.

[0031] MODBUS / TCP or DLMS / COSEM: Industrial communication protocols such as MODBUS / TCP or DLMS / COSEM are used in smart meters and remote terminal units (RTUs) to collect power data and indirectly reflect the communication status.

[0032] S2: Use data analysis technology to process and analyze communication data, extract the characteristics of communication needs, and generate data analysis results.

[0033] In a specific implementation manner, the specific process is as follows: 1. Clean, convert, and normalize communication data. Delete invalid records, such as those with missing time and flow information; handle outliers, such as data points with abnormally high flow, which may be due to false alarms or special events. Convert timestamps to a more analytically meaningful format, such as splitting data by hour or day. Normalize flow data to make it comparable between regions of different sizes.

[0034] 2. Based on the communication data, construct the characteristics of communication demand, which include communication traffic during peak hours, average delay rate, and traffic fluctuation rate. Before construction, first select the features that have the greatest impact on communication demand based on business understanding, such as traffic during peak hours, average delay in a specific time period, etc. Then create new features to reveal hidden relationships, such as traffic fluctuation rate, packet loss rate change trend, etc.

[0035] 3. Reduce the dimension of the features of communication requirements. If the number of features is large, PCA (principal component analysis) and other methods can be used to reduce the dimension, reduce the computational complexity and retain the main information.

[0036] 3. Based on the communication data, the characteristics of communication demand are counted according to the timestamp. In addition, the daily, weekly, and monthly average flow, maximum flow, minimum flow, etc. can be calculated according to the timestamp to understand the basic trend.

[0037] 4. Use the preset algorithm method to analyze the change pattern of communication demand characteristics over time and generate data analysis results. Specifically, use ARIMA or seasonal decomposition time series (STL) method to analyze the change pattern of traffic over time and identify seasonal, trend and cyclical patterns.

[0038] S3: According to the data analysis results, the basic parameters of the communication protocol are set; the basic parameters include communication rate, data packet size and retransmission mechanism.

[0039] In a specific implementation, if the data analysis results include that the communication traffic during peak hours exceeds the traffic threshold, the communication rate in the corresponding communication protocol is set to the theoretical maximum value during the peak hours, and the size of the data packet is reduced; if the average delay rate or traffic fluctuation rate in the data analysis results exceeds the corresponding warning value, a retransmission strategy is configured for the corresponding communication protocol to improve the data response speed.

[0040] For example, if data analysis shows that traffic increases significantly during peak hours in the morning and evening, especially in high-load areas, then the communication rate should be appropriately increased to quickly transmit data and reduce congestion if network capacity permits. During off-peak hours, the rate can be appropriately reduced to save energy. In this case, the communication rate needs to be adjusted dynamically. For example, during peak hours in the morning and evening, the transmission rate of the wireless network is set to the highest level, such as the theoretical maximum speed of the 5G network (such as several Gbps), and during off-peak hours, it is reduced to a medium level (such as hundreds of Mbps) to ensure efficient use of resources.

[0041] At the same time, the packet size directly affects the efficiency and stability of the network. Larger packets can reduce header overhead and improve transmission efficiency, but may lead to higher packet loss rates, especially when the network is congested. On the contrary, smaller packets can improve transmission reliability, but increase control overhead. Therefore, during peak traffic periods, a medium to small packet size (for example, 1000-1500 bytes) is used to reduce packet loss and retransmission and ensure timely data transmission. During non-peak periods, the packet size can be appropriately increased (for example, more than 1500 bytes) to improve transmission efficiency.

[0042] In addition, in high-load areas and peak hours, the packet loss rate may increase, so more effective retransmission strategies are needed.

[0043] Specifically, the following three retransmission strategies can be used: Fast retransmit: When continuous packet loss is detected, fast retransmit is triggered immediately to reduce waiting time. It is suitable for peak hours.

[0044] Adaptive retransmission timer: Dynamically adjust the retransmission timeout (RTT, Round-TripTime) according to the current network conditions. During peak hours, the retransmission timeout is reduced to speed up the response; during non-peak hours, it can be appropriately extended to reduce unnecessary retransmissions.

[0045] Selective Acknowledgment (SACK): Enabling the SACK function allows the receiver to inform the sender which data packets have been received and which are lost, so that only the lost data packets can be retransmitted to improve efficiency.

[0046] S4: Dynamically adjust the basic parameters of the communication protocol based on the intelligent optimization algorithm to determine the optimal communication protocol configuration.

[0047] In a specific implementation, in order to better illustrate the dynamic adjustment process, the basic parameters of the communication protocol are defined as follows: Communication rate (R): The unit is bits per second (bps), which indicates the amount of data transmitted per second.

[0048] Data packet size (S): The unit is Byte, which indicates the size of the data packet transmitted each time.

[0049] Retransmission mechanism (M): used to handle packet loss or errors. It can be a fixed number of retransmissions or dynamic retransmissions based on a certain strategy.

[0050] First, minimizing network delay and maximizing data transmission efficiency are set as optimization goals, where the parameter ranges include: R ∈ [1000, 5000] bps, S ∈ [50, 500]Byte, M ∈ [1, 5].

[0051] Then, binary coding is used to represent R, S and M. For example, R is represented by a 5-bit binary number (which can represent the range 0-31, mapped to 1000-5000), and the same is true for S and M.

[0052] At this point, based on the basic parameters of the communication protocol, the population is initialized and N groups of parameter configurations are randomly generated.

[0053] Define a fitness function to evaluate the performance of each set of parameter configurations. Specifically, define a fitness function F to evaluate the performance of each individual (parameter configuration). For example, F = α / D + β*E, where α and β are weight factors, and D and E are communication delay and data transmission efficiency, respectively. The communication delay D can be obtained through simulation or actual testing, and the data transmission efficiency E can be calculated based on the ratio of the amount of successfully transmitted data to the total amount of data transmitted.

[0054] Finally, the genetic algorithm (GA) is used to iterate and optimize the parameter configuration to determine the optimal parameter configuration as the optimal communication protocol configuration. The implementation process is as follows: a. Decode each individual in the population and obtain the corresponding parameter configuration (R, S, M).

[0055] b. Use simulation or actual testing to evaluate the performance of each parameter configuration and calculate the fitness value F.

[0056] c. Perform selection, crossover and mutation operations on the population according to the fitness value to generate a new population.

[0057] d. Repeat the above steps until the termination condition is met (such as reaching the maximum number of iterations or the fitness value converges).

[0058] S5: Deploy the optimal communication protocol configuration to the corresponding nodes of the smart grid, and evaluate the optimization effect by monitoring the communication performance of each node in real time.

[0059] In a specific implementation, the optimal communication protocol configuration is converted into corresponding configuration parameters and instructions, and the optimal communication protocol configuration is deployed to the corresponding nodes of the smart grid through remote configuration.

[0060] Then, the communication data of the corresponding node is collected. The data collection method may adopt the method provided in step S1. The following method may also be adopted: Establish a monitoring system: Utilize the sensor modules and data processing modules in the smart grid monitoring solution to establish a real-time monitoring system covering smart grid nodes.

[0061] Data collection and analysis: The communication data of the nodes, such as communication rate, data packet transmission success rate, delay, etc., are collected in real time through sensors and sent to the central control center for analysis and processing.

[0062] After data collection is completed, the average communication traffic, average communication delay, and average communication packet loss rate are calculated based on the collected communication data.

[0063] Finally, the communication traffic mean, communication delay mean and communication packet loss rate mean are compared with the corresponding mean thresholds, and the evaluation results are generated according to the comparison results. If the corresponding mean exceeds the threshold, it can be determined that the communication data is abnormal. Once the communication data is abnormal, it means that the optimization effect is not good. Then return to step S1 to re-optimize the configuration.

[0064] See also Figure 2 As shown, the present invention also discloses a smart grid communication protocol optimization configuration system, including: a data collection module 1, an analysis module 2, a parameter setting module 3, a parameter adjustment module 4 and a deployment verification module 5.

[0065] The data collection module 1 is configured to collect the communication data of each node in the smart grid; the communication data includes: communication flow, communication delay and communication packet loss rate.

[0066] The analysis module 2 is configured to process and analyze the communication data using data analysis technology, extract the characteristics of the communication demand, and generate data analysis results.

[0067] The parameter setting module 3 is configured to set basic parameters of the communication protocol according to the data analysis results; the basic parameters include communication rate, data packet size and retransmission mechanism.

[0068] The parameter adjustment module 4 is configured to dynamically adjust the basic parameters of the communication protocol based on an intelligent optimization algorithm to determine the optimal communication protocol configuration.

[0069] The deployment verification module 5 is configured to deploy the optimal communication protocol configuration to the corresponding nodes of the smart grid, and evaluate the optimization effect by monitoring the communication performance of each node in real time.

[0070] The specific implementation of the smart grid communication protocol optimization configuration system of this embodiment is basically the same as the specific implementation of the smart grid communication protocol optimization configuration method described above, and will not be repeated here.

[0071] The present invention also discloses a smart grid communication protocol optimization configuration device, comprising a processor and a memory; wherein, when the processor executes the smart grid communication protocol optimization configuration program stored in the memory, the steps of the smart grid communication protocol optimization configuration method as described in any one of the above items are implemented.

[0072] Furthermore, the smart grid communication protocol optimization configuration device in this embodiment may also include: The input interface is used to obtain the smart grid communication protocol optimization configuration program imported from the outside, and save the obtained smart grid communication protocol optimization configuration program to the memory, and can also be used to obtain various instructions and parameters transmitted by external terminal devices, and transmit them to the processor, so that the processor can use the above various instructions and parameters to carry out corresponding processing. In this embodiment, the input interface can specifically include but is not limited to a USB interface, a serial interface, a voice input interface, a fingerprint input interface, a hard disk reading interface, etc.

[0073] The output interface is used to output various data generated by the processor to the terminal device connected thereto, so that other terminal devices connected to the output interface can obtain various data generated by the processor. In this embodiment, the output interface may specifically include but is not limited to a USB interface, a serial interface, etc.

[0074] The communication unit is used to establish a remote communication connection between the smart grid communication protocol optimization configuration device and the external server so that the smart grid communication protocol optimization configuration device can mount the image file to the external server. In this embodiment, the communication unit may specifically include but is not limited to a remote communication unit based on wireless communication technology or wired communication technology.

[0075] The keyboard is used to obtain various parameter data or instructions input by the user by tapping the keycaps in real time.

[0076] The display is used to display the relevant information of the optimization configuration process of the smart grid communication protocol in real time.

[0077] The mouse can be used to assist users in inputting data and simplify user operations.

[0078] The present invention also discloses a readable storage medium, wherein the readable storage medium includes a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable hard disk, a CD-ROM or any other form of storage medium known in the technical field. The readable storage medium stores a smart grid communication protocol optimization configuration program, and when the smart grid communication protocol optimization configuration program is executed by a processor, the steps of the smart grid communication protocol optimization configuration method described in any one of the above items are implemented.

[0079] In summary, the present invention realizes dynamic adjustment and optimization of communication protocol parameters through data-driven and intelligent optimization technology, and significantly improves the communication efficiency and stability of the smart grid.

[0080] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. As for the method disclosed in the embodiment, since it corresponds to the system disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0081] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0082] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0083] 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.

[0084] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each module may exist physically separately, or two or more modules may be integrated into one unit.

[0085] Similarly, each processing unit in each embodiment of the present invention may be integrated into one functional module, or each processing unit may exist physically, or two or more processing units may be integrated into one functional module.

[0086] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0087] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0088] The above is a detailed introduction to the smart grid communication protocol optimization configuration method, system, device and readable storage medium provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. A smart grid communication protocol optimization configuration method, characterized in that: include: Collect communication data of each node in the smart grid; The communication data includes: communication flow, communication delay and communication packet loss rate; Use data analysis technology to process and analyze communication data, extract the characteristics of communication needs, and generate data analysis results; According to the data analysis results, the basic parameters of the communication protocol are set; the basic parameters include communication rate, data packet size and retransmission mechanism; Dynamically adjust the basic parameters of the communication protocol based on intelligent optimization algorithms to determine the optimal communication protocol configuration; The optimal communication protocol configuration is deployed to the corresponding nodes of the smart grid, and the optimization effect is evaluated by monitoring the communication performance of each node in real time.

2. The smart grid communication protocol optimization configuration method according to claim 1, characterized in that: The collecting of communication data of each node in the smart grid includes: By connecting the network interface cards of each node in the smart grid and utilizing the statistical function of the network interface cards, the communication flow, communication delay and communication packet loss rate are obtained.

3. The smart grid communication protocol optimization configuration method according to claim 1, characterized in that: The collecting of communication data of each node in the smart grid includes: Identify the communication protocols of each node in the smart grid; Determining whether the communication protocol supports a performance data collection function; If supported, the communication data of each node in the smart grid is collected through the communication protocol.

4. The smart grid communication protocol optimization configuration method according to claim 1, characterized in that: The communication data is processed and analyzed by using data analysis technology to extract the characteristics of communication requirements and generate data analysis results, including: Clean, convert and normalize communication data; Based on the communication data, construct the characteristics of communication demand, which include the communication flow rate during peak hours, the average delay rate and the flow fluctuation rate; Perform dimensionality reduction on the characteristics of communication requirements; Based on the communication data, the characteristics of the communication demand are counted according to the timestamp; Use preset algorithm methods to analyze how the characteristics of communication needs change over time and generate data analysis results.

5. The smart grid communication protocol optimization configuration method according to claim 4, characterized in that: The basic parameters of the communication protocol are set according to the data analysis results, including: If the data analysis results include that the communication flow during the peak period exceeds the flow threshold, the communication rate in the corresponding communication protocol is set to the theoretical maximum value during the peak period, and the size of the data packet is reduced; If the average delay rate or traffic fluctuation rate in the data analysis results exceeds the corresponding warning value, a retransmission strategy is configured for the corresponding communication protocol to improve the data response speed.

6. The smart grid communication protocol optimization configuration method according to claim 5, characterized in that: The method of dynamically adjusting basic parameters of the communication protocol based on an intelligent optimization algorithm to determine the optimal communication protocol configuration includes: Minimizing network latency and maximizing data transmission efficiency are set as optimization goals; Use QR codes to represent basic parameters and optimization goals of communication protocols; Based on the basic parameters of the communication protocol, the population is initialized and N groups of parameter configurations are generated; Define a fitness function to evaluate the performance of each set of parameter configurations; Genetic algorithms are used to iterate and optimize parameter configurations, and the optimal parameter configuration is determined as the optimal communication protocol configuration.

7. The method for optimizing configuration of smart grid communication protocols according to claim 6, characterized in that: The optimal communication protocol configuration is deployed to the corresponding nodes of the smart grid, and the communication performance of each node is monitored in real time to evaluate the optimization effect, including: Convert the optimal communication protocol configuration into corresponding configuration parameters and instructions, and deploy the optimal communication protocol configuration to the corresponding nodes of the smart grid through remote configuration; collecting communication data of the corresponding node; Based on the collected communication data, calculate the average communication traffic, the average communication delay and the average communication packet loss rate; The communication traffic mean, communication delay mean and communication packet loss rate mean are compared with the corresponding mean thresholds, and an evaluation result is generated based on the comparison results.

8. A smart grid communication protocol optimization configuration system, characterized in that: include: A data collection module configured to collect communication data of each node in the smart grid; The communication data includes: communication flow, communication delay and communication packet loss rate; An analysis module configured to process and analyze the communication data using data analysis technology, extract characteristics of the communication demand, and generate data analysis results; A parameter setting module, configured to set basic parameters of the communication protocol according to the data analysis results; the basic parameters include communication rate, data packet size and retransmission mechanism; A parameter adjustment module, configured to dynamically adjust basic parameters of the communication protocol based on an intelligent optimization algorithm to determine an optimal communication protocol configuration; The deployment verification module is configured to deploy the optimal communication protocol configuration to the corresponding nodes of the smart grid, and evaluate the optimization effect by monitoring the communication performance of each node in real time.

9. A smart grid communication protocol optimization configuration device, characterized in that: include: A memory, used for storing a smart grid communication protocol optimization configuration program; A processor, configured to implement the steps of the smart grid communication protocol optimization configuration method as described in any one of claims 1 to 7 when executing the smart grid communication protocol optimization configuration program.

10. A readable storage medium, characterized in that: The readable storage medium stores a smart grid communication protocol optimization configuration program, and when the smart grid communication protocol optimization configuration program is executed by a processor, the steps of the smart grid communication protocol optimization configuration method according to any one of claims 1 to 7 are implemented.

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