Power communication system optimization method based on big data analysis

Abstract

The invention discloses an electric power communication system optimization method based on big data analysis, and the method comprises the steps: collecting operation data of an electric power communication system, carrying out the format conversion, and carrying out the fusion; identifying system operation characteristics based on the fused data, and evaluating the system to obtain an evaluation result; and carrying out optimization scheduling on the network resources according to the system operation characteristics and the evaluation result. According to the method, comprehensive optimization, including real-time data processing, operation feature recognition, intelligent resource scheduling and dynamic path optimization, of the electric power communication system is achieved by integrating the big data analysis technology, the operation efficiency, stability, safety and reliability of the system are remarkably improved, and efficient data support and decision basis are provided for intelligent power grid management.

Description

Technical Field

[0001] The present invention relates to the field of power communication technology, and more specifically to a power communication system optimization method based on big data analysis. Background Art

[0002] With the development of smart grids, power communication systems have become a key component supporting the operation of power systems. At the same time, science and technology are constantly advancing, and the introduction of big data technology has provided new possibilities for optimizing power communication systems. Big data analysis can process massive, high-speed, and diverse data. Through algorithms such as deep learning and machine learning, it can achieve real-time monitoring of the operating status of power communication systems, fault prediction, and resource scheduling optimization, thereby improving the overall performance and stability of the system.

[0003] However, the traditional power communication system optimization methods still have the following shortcomings:

[0004] Poor data integration capabilities: Traditional power communication systems often lack effective data integration methods, making it difficult to uniformly manage and analyze data from various devices and network layers in the system. This limits the system's comprehensive understanding of the overall operating status and makes it difficult to achieve cross-platform and cross-system data sharing and collaborative optimization.

[0005] Low real-time data processing capability: In traditional methods, data processing often relies on post-analysis and lacks real-time performance. This results in the system being unable to quickly respond to changes in operation and unable to detect potential faults or performance bottlenecks in a timely manner, thus affecting the real-time control and scheduling of the power communication system.

[0006] Poor data security: Traditional power communication systems have loopholes in data protection and lack effective encryption and access control mechanisms. As cyber attacks become increasingly sophisticated, the risk of data leakage and illegal intrusion into the system continues to increase, posing a threat to the safe operation of the power system.

[0007] Therefore, how to overcome the above problems and optimize the power communication system is an urgent problem to be solved by those skilled in the art. Summary of the invention

[0008] In view of this, in order to at least partially solve the above technical problems, the present invention provides a power communication system optimization method based on big data analysis.

[0009] In order to achieve the above object, the present invention adopts the following technical solution:

[0010] On the one hand, the present application discloses a method for optimizing a power communication system based on big data analysis, comprising:

[0011] Collect the operation data of the power communication system and integrate it after format conversion;

[0012] Identify system operation characteristics based on fused data, and evaluate the system to obtain evaluation results;

[0013] Optimize and schedule network resources based on system operation characteristics and evaluation results.

[0014] Preferably, the operating data includes operating temperature, operating current, voltage, communication signal strength, network delay and bandwidth usage.

[0015] As a preferred method, the collected operation data is processed in real time through the data processing framework Apache Kafka, the ETL tool is used to convert the data into a unified format, and then the data is integrated using the following function:

[0016]

[0017] In the formula, R i Represents the result value of the fusion function, represents the data to be fused in the power communication system, ω represents the conversion factor value of the fusion function, i represents the data order, μ represents the conversion frequency of different data sources, Represents the fusion function coefficient.

[0018] Preferably, identifying the operation characteristics based on the fusion data includes:

[0019] Summarize the data characteristics of the power communication system through the mean, median and standard deviation of the data;

[0020] The trend analysis is performed using a line graph to obtain the operating characteristics of the power communication system data, including the average operating temperature of the system, the median of voltage fluctuations, and the stability of signal strength.

[0021] Preferably, the system is evaluated using an evaluation function to obtain an evaluation result; the expression of the evaluation function is:

[0022]

[0023] Where P represents the evaluation function, κ represents the power factor of the power communication system, and t n represents the operation time of the power communication system, β n represents the power supply of the electric communication system, n represents the order of function evaluation data, and S represents the prediction factor of the evaluation function.

[0024] Preferably, the optimized scheduling includes:

[0025] Dynamically optimize the data transmission path of the power communication system through Dijkstra shortest path;

[0026] And use UDP low-latency communication protocol to control signals in real time.

[0027] Preferably, the data transmission path of the power communication system is dynamically optimized by using the Dijkstra shortest path, and the steps include:

[0028] The power communication network structure is abstracted into a graph model, where nodes represent power equipment or exchange points, and edges represent connection links between equipment or exchange points;

[0029] Select a source node in the network as the starting point of the Dijkstra algorithm, initialize the shortest path distance from the source node to all other nodes to infinity, the distance from the source node to itself to 0, and mark all nodes as unvisited in the initial state;

[0030] Select a node with the currently known shortest path distance from the unvisited node set, traverse all neighbor nodes of the node, and calculate the path length from the source point through the current node to the neighbor node; if the path from the current node to the neighbor node is shorter, update the shortest path distance of the neighbor node and mark the current node as visited;

[0031] Starting from the target node, backtrack to the source node, and build the final shortest path along the updated shortest path.

[0032] Preferably, use intrusion detection systems and intrusion prevention systems to identify and block potential attacks and abnormal behaviors, and control access rights to network resources;

[0033] The intrusion detection system is also used to proactively block attacks, and the transmitted data is encrypted via the RSA encryption algorithm.

[0034] On the other hand, the present application discloses a power communication system optimization system based on big data analysis, comprising:

[0035] Data acquisition module, used to collect the operation data of the power communication system,

[0036] A fusion processing module is used to perform format conversion and fusion on the running data;

[0037] The data analysis module is used to identify the system operation characteristics based on the fused data, and to evaluate the system and obtain the evaluation results;

[0038] The system optimization module is used to optimize the scheduling of network resources according to system operation characteristics and evaluation results.

[0039] Preferably, it also includes a safety protection module and a system feedback module;

[0040] Security protection module, which is used to identify and prevent potential attacks and abnormal behaviors by using intrusion detection system and intrusion prevention system, and control the access rights of network resources;

[0041] The system feedback module is used to collect the operating status data of the power communication system after optimization in real time and provide feedback for subsequent optimization.

[0042] Through the above technical solutions, it can be known that the present invention discloses a method for optimizing a power communication system based on big data analysis. Compared with the prior art, the present invention provides a more comprehensive perspective for system optimization by integrating data from different data sources and different formats; the data is analyzed in real time through the Apache Spark framework algorithm and evaluation function, thereby improving the real-time processing capability of data; the operation characteristics of the power communication system are accurately identified through statistical analysis methods, providing key information for system evaluation; the application of the evaluation function realizes the prediction of power load and behavior patterns, and guides the optimal scheduling of network resources; the Dijkstra algorithm is further adopted to realize the dynamic optimization of the data transmission path and improve the communication efficiency. And the introduction of RSA encryption and intrusion detection system significantly improves the security of data transmission and prevents network attacks and data leakage.

[0043] The present invention realizes the comprehensive optimization of the power communication system by integrating big data analysis technology, including real-time data processing, operation feature identification, intelligent resource scheduling and dynamic path optimization, which significantly improves the operation efficiency, stability, security and reliability of the system, and provides efficient data support and decision-making basis for smart grid management.

[0044] Other advantages, objectives and features of the present invention will be described in part in the following description; and in part, will be apparent to those skilled in the art based on an examination of the following; or, may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] 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.

[0046] Figure 1 This is a flow chart of a method for optimizing a power communication system based on big data analysis according to the present invention;

[0047] Figure 2 This is a schematic diagram of the structure of the power communication system optimization system based on big data analysis of the present invention;

[0048] Figure 3 It is a structural schematic diagram of the fusion processing module of the present invention;

[0049] Figure 4 It is a structural schematic diagram of the data analysis module of the present invention;

[0050] Figure 5 It is a structural schematic diagram of the security protection module of the present invention. DETAILED DESCRIPTION

[0051] 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.

[0052] In order to address the deficiencies of the prior art, the present application provides a method and system for optimizing a power communication system based on big data analysis.

[0053] Embodiment 1:

[0054] This method is Figure 1 , including the following steps:

[0055] S1. Collect the operation data of the power communication system, convert the format and merge it; the operation data includes operation temperature, operation current, voltage, communication signal strength, network delay and broadband usage;

[0056] Furthermore, in this embodiment, the collected operation data is processed in real time by the data processing framework Apache Kafka, the ETL tool is used to convert the data into a unified format, and then the data is merged using the following function:

[0057]

[0058] In the formula, R i Represents the result value of the fusion function, represents the data to be fused in the power communication system, ω represents the conversion factor value of the fusion function, i represents the data order, μ represents the conversion frequency of different data sources, Represents the fusion function coefficient.

[0059] The fusion function is based on the data to be fused by the power communication system Fusion function conversion factor value ω, conversion frequency μ of different data sources and fusion function coefficient Generate fusion function formulas to fuse data from different data sources and in different formats.

[0060] S2, identifying system operation characteristics based on fused data, and evaluating the system to obtain evaluation results;

[0061] Among them, identifying operation characteristics based on fusion data; including:

[0062] Summarize the data characteristics of the power communication system through the mean, median and standard deviation of the data;

[0063] The trend analysis is performed using a line graph to obtain the operating characteristics of the power communication system data, including the average operating temperature of the system, the median of voltage fluctuations, and the stability of signal strength.

[0064] The system is evaluated using an evaluation function to obtain an evaluation result; the expression of the evaluation function is:

[0065]

[0066] Where P represents the evaluation function, κ represents the power factor of the power communication system, and t n represents the operation time of the power communication system, β n represents the power supply of the electric communication system, n represents the order of function evaluation data, and S represents the prediction factor of the evaluation function.

[0067] The evaluation function of the present invention is based on the power factor κ of the power communication system and the operating time t of the power communication system. n 、Power supply power of power communication system β n The evaluation function formula is obtained by combining the evaluation function prediction factor S to predict the system power load and behavior pattern.

[0068] S3. Optimize and schedule network resources according to system operation characteristics and evaluation results. In this embodiment, the optimization and scheduling includes:

[0069] Dynamically optimize the data transmission path of the power communication system through the Dijkstra shortest path; dynamically optimize the data transmission path by calculating the shortest path between any two points in the network, reduce data transmission delay, and improve communication efficiency;

[0070] And the UDP low-latency communication protocol is used to control the real-time signal, providing low-latency data transmission to ensure the immediacy and accuracy of the control commands of the power communication system, and achieve efficient data transmission efficiency to achieve efficient transmission efficiency.

[0071] In an exemplary embodiment, the data transmission path of the power communication system is dynamically optimized by using the Dijkstra shortest path, and the steps include:

[0072] The power communication network structure is abstracted into a graph model, where nodes represent power equipment or exchange points, and edges represent connection links between equipment or exchange points;

[0073] Select a source node in the network as the starting point of the Dijkstra algorithm, initialize the shortest path distance from the source node to all other nodes to infinity, the distance from the source node to itself to 0, and mark all nodes as unvisited in the initial state;

[0074] Select a node with the currently known shortest path distance from the unvisited node set, traverse all neighbor nodes of the node, and calculate the path length from the source point through the current node to the neighbor node; if the path from the current node to the neighbor node is shorter, update the shortest path distance of the neighbor node and mark the current node as visited;

[0075] Starting from the target node, backtrack to the source node, and build the final shortest path along the updated shortest path.

[0076] When the link delay in the power communication system changes or the network status changes due to equipment failure, the Dijkstra algorithm is rerun to dynamically update the shortest path to adapt to the real-time changes in the network and ensure continuous optimization of the data transmission path.

[0077] Through the above steps, the Dijkstra shortest path algorithm can effectively find the shortest transmission path from the source point to any target point in the power communication network, and can automatically adjust according to the real-time changes in network conditions to ensure the efficiency of data transmission. In summary, the application of the Dijkstra shortest path algorithm in the optimization of the power communication system not only improves the efficiency and reliability of data transmission, but also realizes the efficient and stable operation of the power communication network through intelligent scheduling of network resources and optimization of data transmission paths, which is of great significance to improving the overall performance of the system.

[0078] In order to further optimize the above technical solution, this application uses an intrusion detection system and an intrusion prevention system to identify and prevent potential attacks and abnormal behaviors, and control access rights to network resources to ensure that only authorized users and devices can access;

[0079] The intrusion detection system and the intrusion prevention system monitor network traffic in real time, identify and prevent potential network attacks and abnormal behaviors, so as to detect abnormalities in power system data. On this basis, the intrusion prevention system actively prevents attacks, protects the system from threats, and implements strict access control policies to ensure that only authorized users and devices can access network resources;

[0080] At the same time, the transmitted data is encrypted using the RSA encryption algorithm to protect the confidentiality of the data. Even if the data is intercepted during transmission, it cannot be parsed due to encryption.

[0081] The use of the RSA encryption algorithm provides an additional layer of security for data transmission, so that data can remain secure even on public networks. The intrusion detection and prevention system and access control strategy prevent illegal intrusions and malicious attacks from the source, ensuring the stable operation and data security of the power communication system. The detailed application steps of the RSA encryption algorithm in the power communication system are: key generation, selecting two large prime numbers m and n, and calculating their product X = m*n, and then calculating the Euler function Represents the output value of the Euler function, and selects an integer κ that satisfies And e and Mutually prime, calculate the output function formula The public key is (e, X) and the private key is (q, X); then, the data sender in the power communication system obtains the public key (e, X) of the data receiver, uses the public key e and the modulus X to encrypt the data, and converts the plaintext data p into the ciphertext c. The encryption formula is: c = p^e (mod X); data transmission: the ciphertext c is securely transmitted through the power communication network, and even if the data is intercepted during the transmission process, it cannot be decrypted; data decryption: the data receiver uses the private key q and the modulus X to decrypt the ciphertext c to obtain the original plaintext data p. The decryption formula is: p≡c^q (mod X). Through the above steps, the RSA encryption algorithm realizes the secure encryption of data transmission in the power communication system, protects the confidentiality of the data, and enhances the security protection capability of the power communication network.

[0082] Embodiment 2:

[0083] This embodiment discloses a power communication system optimization system based on big data analysis, such as Figure 2 include:

[0084] 1) Data acquisition module, used to collect the operation data of the power communication system,

[0085] In one embodiment, the invention comprises:

[0086] Deploy temperature sensors, current and voltage sensors, signal strength detectors and network performance monitors in the power system, and monitor the operating temperature of power equipment through the temperature sensors to prevent overheating;

[0087] The current and voltage data are collected by the current and voltage sensors to monitor the power quality;

[0088] The current and voltage data are collected by the current and voltage sensors to monitor the power quality;

[0089] Measuring the communication signal strength by the signal strength detector to ensure the communication quality;

[0090] Monitor network latency, bandwidth usage, and more with the network performance monitor

[0091] Furthermore, in order to ensure data transmission efficiency, the system operation data is obtained through the API interface and Modbus network protocol, and the network delay and bandwidth usage are monitored to ensure data transmission efficiency, thereby realizing data communication between industrial equipment and obtaining real-time operation data of the equipment;

[0092] Further, optionally, the data is cleaned and screened; that is, data cleaning removes duplicate data and processes missing values ​​to ensure the integrity and accuracy of the data; data screening is based on predefined rules to screen out key data directly related to the performance of the power communication system to ensure the quality and accuracy of the data. The API interface allows interaction between different software systems. Finally, the preprocessed data is stored in the MySQL database to provide data support for data analysis and system optimization. The MySQL database is used to provide structured data storage and support efficient data query and management.

[0093] Through the above steps, the data acquisition module ensures the real-time monitoring, high-quality collection and effective management of the power communication system operation data, providing a solid data foundation for subsequent system analysis, optimization and fault prediction. Through the data acquisition module, the power communication system can achieve comprehensive monitoring and efficient management of operation data, and provide accurate data support for system status analysis, fault prediction and optimization decision-making. The use of the API interface and Modbus protocol ensures the flexibility of data collection and seamless communication between devices, while the MySQL database provides a stable data storage solution. The entire process ensures the real-time, accuracy and availability of data.

[0094] 2) Fusion processing module, used to convert the format of the operation data and then fuse it;

[0095] The fusion processing module integrates big data analysis technology and power communication system. In one embodiment, the fusion processing module, such as Figure 3 , including real-time processing unit, conversion unit and fusion unit, thus jointly building an efficient, flexible and intelligent data processing system.

[0096] The real-time processing unit processes streaming data from the power communication system in real time through the data processing framework Apache Kafka. It can process high-throughput real-time data streams and process streaming data from the power communication system in real time, such as equipment status and performance indicators, to ensure the timeliness and continuity of data and provide real-time data support for the efficient operation of the power system.

[0097] The conversion unit uses ETL tools to convert data into a unified format, executes data extraction, conversion, and loading processes, converts data from different data sources into a unified format, and solves the problem of inconsistent data formats. This process not only improves data compatibility, but also prepares for subsequent data analysis and integration;

[0098] The fusion unit fuses data from different data sources and different formats through a fusion function to achieve data fusion, deeply integrates and analyzes data from different data sources and different formats, and converts data from different data sources into a unified format to solve the problem of inconsistent data formats, in preparation for data fusion. The fusion unit realizes data fusion, extracts deep features in the data, improves the integrity and consistency of the data, and provides support for subsequent analysis and decision-making.

[0099] The fusion processing module of the present invention, combined with the real-time processing unit, conversion unit and fusion unit, ensures the real-time, consistency and integrity of data in the power communication system, and provides a high-quality data foundation for system optimization and fault prediction. Through the real-time processing capability of Apache Kafka, the data conversion function of the ETL tool, and the data integration capability of the fusion function and machine learning algorithm, effective management and utilization of data are achieved.

[0100] 3) Data analysis module, used to identify system operation characteristics based on fused data, and evaluate the system to obtain evaluation results;

[0101] like Figure 3 This embodiment summarizes the data characteristics of the power communication system based on the data mean, median and standard deviation, and uses a line graph to perform trend analysis. Through these statistics, the characteristics of the power communication system data are summarized, including the average operating temperature of the equipment, the median of the voltage fluctuation, and the stability of the signal strength; thereby intuitively displaying the trend of data changes over time, and through trend analysis, identifying the changing trends of performance indicators in the power communication system, such as network delay, signal strength, etc., to provide a reference for prediction and optimization.

[0102] At the same time, the power system data is loaded through the Apache Spark framework algorithm, and the evaluation function is used to predict the system power load and behavior patterns, providing a basis for power scheduling and resource allocation.

[0103] The data analysis module in the present invention can deeply understand the inherent laws of the power communication system data and predict the future state of the system to assist decision makers in making more scientific management decisions; the use of Apache Spark to process large-scale data sets improves the efficiency and accuracy of data processing.

[0104] 4) System optimization module, used to optimize and dispatch network resources according to system operation characteristics and evaluation results. In the present invention, this module is used to dynamically adjust the resource allocation of the power communication system by monitoring and analyzing the key performance indicators of the system. The key indicators include bandwidth usage, delay, and packet loss rate to ensure efficient use of resources and load balancing, and dynamically adjust the resource allocation of the power communication system to ensure efficient use of network resources and load balancing, and improve the system response speed.

[0105] In this embodiment, the data transmission path of the power communication system is dynamically optimized through the Dijkstra shortest path, and the UDP low-latency communication protocol is used to control the signal in real time; the specific implementation method is consistent with the embodiment 1 and will not be repeated here.

[0106] In order to further optimize the above technical solution, it also includes a safety protection module and a system feedback module;

[0107] 5) Security protection module, such as Figure 5 , used to identify and block potential attacks and abnormal behaviors using intrusion detection systems and intrusion prevention systems, and control access rights to network resources to enhance data protection;

[0108] In the present invention, the security protection module can effectively improve the security of the power communication system, prevent data leakage and unauthorized access, and ensure the protection of network resources and the confidentiality of data.

[0109] 6) System feedback module, which is used to collect the operating status data of the power communication system after optimization in real time and provide feedback for subsequent optimization. Specifically, by collecting the operating status data of the power communication system after optimization in real time, including performance indicators, equipment status and network load, a detailed system status report is generated through the Tableau tool, including performance analysis, fault records and recommended measures, a real-time view of the system status and historical trend analysis are generated, and data is analyzed to identify system bottlenecks, abnormal conditions and equipment operating efficiency. Adjust system parameters according to feedback information to optimize network configuration and resource allocation. Through continuous monitoring, data analysis, report generation and parameter adjustment of the system feedback module, the power communication system can achieve adaptive optimization to ensure the efficiency and stability of system operation. The application of the Tableau tool not only improves the efficiency of data analysis, but also makes data visualization, which is convenient for intuitive understanding of the system status, provides data support for decision-making, and ensures the continuity and effectiveness of power communication system optimization.

[0110] The present invention improves the operating efficiency, stability, safety and reliability of the power communication system as a whole, reduces operation and maintenance costs, and improves the management level of the smart grid.

[0111] 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. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0112] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing a power communication system based on big data analysis, characterized in that: include: Collect the operation data of the power communication system and integrate it after format conversion; Identify system operation characteristics based on fused data, and evaluate the system to obtain evaluation results; Optimize and schedule network resources based on system operation characteristics and evaluation results.

2. The method for optimizing a power communication system based on big data analysis according to claim 1, characterized in that: The operating data includes operating temperature, operating current, voltage, communication signal strength, network latency, and bandwidth usage.

3. The power communication system optimization method based on big data analysis according to claim 1 is characterized in that: The collected operation data is processed in real time through the data processing framework Apache Kafka, and the ETL tool is used to convert the data into a unified format. Then, the following functions are used to merge the data: In the formula, R i Represents the result value of the fusion function, represents the data to be fused in the power communication system, ω represents the conversion factor value of the fusion function, i represents the data order, μ represents the conversion frequency of different data sources, Represents the fusion function coefficient.

4. The method for optimizing a power communication system based on big data analysis according to claim 1, characterized in that: Identify operational characteristics based on fused data; including: Summarize the data characteristics of the power communication system through the mean, median and standard deviation of the data; The trend analysis is performed using a line graph to obtain the operating characteristics of the power communication system data, including the average operating temperature of the system, the median of voltage fluctuations, and the stability of signal strength.

5. The method for optimizing a power communication system based on big data analysis according to claim 1, characterized in that: The system is evaluated using an evaluation function to obtain an evaluation result; the expression of the evaluation function is: Where P represents the evaluation function, κ represents the power factor of the power communication system, and t n represents the operation time of the power communication system, β n represents the power supply of the electric communication system, n represents the order of function evaluation data, and S represents the prediction factor of the evaluation function.

6. The method for optimizing a power communication system based on big data analysis according to claim 1, characterized in that: Optimized scheduling includes: Dynamically optimize the data transmission path of the power communication system through Dijkstra shortest path; And use UDP low-latency communication protocol to control signals in real time.

7. The method for optimizing a power communication system based on big data analysis according to claim 6, characterized in that: The data transmission path of the power communication system is dynamically optimized by using the Dijkstra shortest path, and the steps include: The power communication network structure is abstracted into a graph model, where nodes represent power equipment or exchange points, and edges represent connection links between equipment or exchange points; Select a source node in the network as the starting point of the Dijkstra algorithm, initialize the shortest path distance from the source node to all other nodes to infinity, the distance from the source node to itself to 0, and mark all nodes as unvisited in the initial state; Select a node with the currently known shortest path distance from the unvisited node set, traverse all neighbor nodes of the node, and calculate the path length from the source point through the current node to the neighbor node; if the path from the current node to the neighbor node is shorter, update the shortest path distance of the neighbor node and mark the current node as visited; Starting from the target node, backtrack to the source node, and build the final shortest path along the updated shortest path.

8. The method for optimizing a power communication system based on big data analysis according to claim 1, characterized in that: Use intrusion detection systems and intrusion prevention systems to identify and block potential attacks and abnormal behaviors, and control access rights to network resources; The intrusion detection system is also used to proactively block attacks, and the transmitted data is encrypted via the RSA encryption algorithm.

9. A power communication system optimization system based on big data analysis, characterized in that: include: Data acquisition module, used to collect the operation data of the power communication system, A fusion processing module is used to perform format conversion and fusion on the running data; The data analysis module is used to identify the system operation characteristics based on the fused data, and to evaluate the system and obtain the evaluation results; The system optimization module is used to optimize the scheduling of network resources according to system operation characteristics and evaluation results.

10. The power communication system optimization system based on big data analysis according to claim 9, characterized in that: It also includes a safety protection module and a system feedback module; Security protection module, which is used to identify and prevent potential attacks and abnormal behaviors by using intrusion detection system and intrusion prevention system, and control the access rights of network resources; The system feedback module is used to collect the operating status data of the power communication system after optimization in real time and provide feedback for subsequent optimization.

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