Electric power Internet of Things safety protection technology based on electric red Internet of Things operating system

Abstract

The invention relates to the technical field of electric power systems, Internet of Things and computing, in particular to an electric power Internet of Things safety protection technology based on an electric Hongyu Internet of Things operating system. According to the invention, an efficient, intelligent and safe power Internet of Things data processing flow is constructed by integrating advanced technical means of the Internet of Things, big data, cloud computing, edge computing, artificial intelligence and the like, so that the security of the power Internet of Things is comprehensively improved. As the core of the technology, the electric Hongyu Internet of Things operating system not only provides strong data processing and communication capabilities, but also has abundant safety functions and mechanisms, and can realize comprehensive safety protection of the electric power Internet of Things. The invention aims to solve the security challenge faced by the power internet of things, and provides powerful guarantee for stable operation and power supply security of a power system by introducing an advanced technical means and an innovative security protection strategy.

Description

Technical Field

[0001] The present invention proposes a power Internet of Things security protection technology based on the Dianhong IoT operating system. This technology integrates advanced technologies such as the Internet of Things, big data, cloud computing, edge computing and artificial intelligence to build an efficient, intelligent and secure power Internet of Things data processing process, aiming to comprehensively improve the security of the power Internet of Things. Background Art

[0002] With the rapid development and widespread application of Internet of Things technology, the power Internet of Things, as an important part of the smart grid, is gradually becoming a key means to realize the intelligence, automation and digitization of the power system. The power Internet of Things integrates sensors, smart devices, communication networks and data processing technologies to achieve real-time monitoring, control and optimization of various links such as power production, transmission, distribution and consumption.

[0003] However, the rapid development of the power Internet of Things has also brought many security challenges. Due to the large number of IoT devices, their wide distribution, and the frequent presence of security vulnerabilities and weaknesses, the power Internet of Things is extremely vulnerable to malicious attacks and illegal intrusions. These attacks may not only lead to data leakage, equipment damage and system paralysis, but may also have a serious impact on the stable operation of the power system and the security of power supply.

[0004] In order to cope with these security challenges, the existing security protection technology of the power Internet of Things mainly relies on traditional network security measures, such as firewalls, intrusion detection systems, data encryption, etc. However, these measures often seem to be powerless in the face of new network attacks and complex security threats. Therefore, a more comprehensive, intelligent and efficient security protection technology is needed to cope with the security challenges faced by the power Internet of Things. Summary of the invention

[0005] In the corresponding context, the present invention proposes a power Internet of Things security protection technology based on the Dianhong IoT operating system. This technology integrates advanced technologies such as the Internet of Things, big data, cloud computing, edge computing, and artificial intelligence to build an efficient, intelligent, and secure data processing process for the power Internet of Things, aiming to comprehensively improve the security of the power Internet of Things. As the core of this technology, the Dianhong IoT operating system not only provides powerful data processing and communication capabilities, but also has rich security functions and mechanisms, which can achieve comprehensive security protection for the power Internet of Things.

[0006] In summary, the invention aims to solve the security challenges faced by the power Internet of Things, and to provide strong guarantees for the stable operation of the power system and the security of power supply by introducing advanced technical means and innovative security protection strategies.

[0007] A power Internet of Things security protection technology based on the Dianhong IoT operating system, including:

[0008] 1. Data collection and preprocessing:

[0009] Collection methods: Use IoT sensors, smart meters and other equipment to collect various data in the power IoT in real time, including but not limited to current, voltage, power factor, temperature, humidity, etc.

[0010] Preprocessing strategy: With the support of the Dianhong IoT operating system, the collected raw data is cleaned, denoised, formatted and other preprocessing operations are performed to ensure the accuracy and completeness of the data.

[0011] 2. Data encryption and transmission:

[0012] Encryption technology: Use advanced encryption algorithms, such as AES, RSA, etc., to encrypt pre-processed data to ensure the security of data during transmission.

[0013] Transmission protocol: Use IoT communication protocols such as MQTT and CoAP to achieve efficient and reliable data transmission between IoT devices, edge nodes and cloud platforms.

[0014] 3. Edge computing and intelligent analysis:

[0015] Edge computing: Deploy edge computing devices at the edge nodes of the power Internet of Things, use edge computing technology to realize real-time processing and analysis of data, reduce the burden on the cloud platform, and improve the real-time and accuracy of data processing.

[0016] Intelligent analysis: Use artificial intelligence technologies such as machine learning and deep learning to conduct intelligent analysis on the data processed by edge computing devices, identify potential safety hazards and failure modes, and provide support for subsequent decision-making.

[0017] 4. Data aggregation and storage:

[0018] Data aggregation: Aggregate the data processed by edge nodes to the cloud platform to form a unified data warehouse.

[0019] Data storage: Use distributed storage technologies, such as cloud storage and Hadoop, to achieve efficient and reliable data storage while ensuring data security and privacy.

[0020] 5. Safety monitoring and early warning:

[0021] Security monitoring: Through the security monitoring module of the Dianhong IoT operating system, security events and abnormal situations in the power Internet of Things are monitored in real time, including data leakage, equipment failure, malicious attacks, etc.

[0022] Early warning mechanism: Based on the results of security monitoring, the early warning mechanism is triggered to promptly notify relevant personnel to handle the situation and prevent the security incident from further expanding and spreading.

[0023] 6. Data visualization and decision support:

[0024] Data visualization: Using data visualization technology, the data in the power Internet of Things can be displayed in the form of charts, reports, etc., to help relevant personnel intuitively understand the system status and operation status.

[0025] Decision support: Based on the results of data visualization, provide decision support to relevant personnel, including suggestions on equipment maintenance, troubleshooting, safety protection, etc.

[0026] The present invention integrates advanced technologies such as the Internet of Things, big data, cloud computing, edge computing, and artificial intelligence to build an efficient, intelligent, and secure data processing process for the power Internet of Things. This process not only improves the real-time and accuracy of data processing, but also achieves comprehensive security protection for the power Internet of Things, effectively preventing the occurrence of security incidents such as data leakage, equipment failure, and malicious attacks. At the same time, data visualization technology provides intuitive decision-making support for relevant personnel, which helps to optimize the operation and management of the power Internet of Things.

[0027] The power Internet of Things security protection technology based on the Dianhong IoT operating system proposed in this invention has broad application prospects and huge market potential. Through the implementation of this technology, the security, reliability and intelligence level of the power Internet of Things can be significantly improved, providing a strong guarantee for the stable operation and sustainable development of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application, 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 some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0029] Figure 1 An overall step block diagram provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0031] See also Figure 1As shown, the best embodiment of the present invention is further described;

[0032] The present invention proposes a power Internet of Things security protection technology based on the Dianhong IoT operating system. This technology integrates advanced technologies such as the Internet of Things, big data, cloud computing, edge computing, and artificial intelligence to build an efficient, intelligent, and secure data processing process for the power Internet of Things, aiming to comprehensively improve the security of the power Internet of Things. As the core of this technology, the Dianhong IoT operating system not only provides powerful data processing and communication capabilities, but also has a wealth of security functions and mechanisms, which can achieve comprehensive security protection for the power Internet of Things.

[0033] The present invention is described in detail below based on embodiments:

[0034] 1. Data collection and preprocessing:

[0035] Data collection:

[0036] In the power Internet of Things, data collection is the cornerstone of the entire system. Using advanced equipment such as IoT sensors and smart meters, real-time collection of various key parameters in the power system can be achieved. These parameters include but are not limited to electrical parameters such as current, voltage, power factor, and environmental parameters such as temperature and humidity.

[0037] Current and voltage acquisition: Through high-precision current transformers and voltage transformers, the current and voltage changes in the power lines are monitored in real time, providing basic data support for the stable operation of the power system.

[0038] Power factor collection: Power factor is an indicator that measures the ratio of active power to apparent power in a power system. By collecting this data, the energy efficiency level of the power system can be evaluated and corresponding optimization adjustments can be made.

[0039] Temperature and humidity collection: Deploy temperature and humidity sensors around power equipment to monitor the equipment operating environment in real time, and promptly detect and address potential safety hazards such as overheating and humidity.

[0040] Preprocessing strategy:

[0041] With the support of Hongwulian operating system, a series of preprocessing operations are performed on the collected raw data to ensure the accuracy and completeness of the data.

[0042] Data cleaning: Remove invalid data such as outliers and duplicate values ​​during the collection process to improve data quality.

[0043] De-noising: Use filtering algorithms to denoise the collected data to reduce noise interference and improve data accuracy.

[0044] Data formatting: Convert the collected data into a unified format to facilitate subsequent data processing and analysis.

[0045] Taking smart substations as an example, IoT sensors and smart meters are deployed to monitor the operating status and electrical parameters of each device in the substation in real time. After preprocessing, the collected data can be displayed in real time in the substation monitoring system for operation and maintenance personnel to view and analyze. At the same time, these data can also serve as the basis for intelligent analysis and decision support, helping operation and maintenance personnel to promptly discover and deal with potential safety hazards and faults.

[0046] Effects and beneficial effects:

[0047] Improve data quality: Through pre-processing operations such as data cleaning, denoising and formatting, the quality of collected data can be significantly improved, providing a reliable foundation for subsequent data processing and analysis.

[0048] Real-time monitoring and early warning: Real-time collection and processing of various data in the power Internet of Things can promptly discover and warn of potential safety hazards and faults, and improve the stability and safety of the power system.

[0049] Optimize operation and maintenance management: Based on the collected data, operation and maintenance personnel can more accurately grasp the operating status of the power system, optimize operation and maintenance strategies, and reduce operation and maintenance costs.

[0050] Support intelligent decision-making: Preprocessed data can serve as the basis for intelligent analysis and decision support, helping relevant personnel make more scientific and reasonable decisions and improving the overall efficiency of the power system.

[0051] 2. Data encryption and transmission:

[0052] Data encryption technology:

[0053] In the power Internet of Things, data encryption is an important means to ensure data security. Using advanced encryption algorithms, such as AES (Advanced Encryption Standard) and RSA (asymmetric encryption algorithm), the pre-processed data can be encrypted to ensure the confidentiality, integrity and authenticity of the data during transmission.

[0054] AES encryption: AES is a symmetric encryption algorithm, which means that the same key is used for encryption and decryption. The AES algorithm provides three encryption strengths: 128-bit, 192-bit, and 256-bit. You can choose the appropriate encryption strength based on the actual needs of the power Internet of Things. AES encryption is fast and is suitable for power Internet of Things data with high real-time requirements.

[0055] RSA encryption: RSA is an asymmetric encryption algorithm that uses a public key for encryption and a private key for decryption. The RSA algorithm can ensure the confidentiality and integrity of data during data transmission, while providing a digital signature function to ensure the authenticity of the data. RSA encryption is strong but relatively slow, and is suitable for scenarios with extremely high security requirements and small data volumes.

[0056] Transport Protocol:

[0057] In order to achieve efficient and reliable data transmission between IoT devices, edge nodes and cloud platforms, the power IoT adopts IoT communication protocols such as MQTT (Message Queue Telemetry Transport) and CoAP (Constrained Application Protocol).

[0058] MQTT protocol: MQTT is a lightweight, publish / subscribe-based message transmission protocol suitable for communication between devices and cloud platforms in the IoT environment. The MQTT protocol supports communication over low-bandwidth, unreliable networks, can reduce data transmission latency and power consumption, and improve data transmission reliability. In the power IoT, the MQTT protocol can be used to achieve real-time upload of device data and remote monitoring of the cloud platform.

[0059] CoAP protocol: CoAP is a network application protocol designed for the Internet of Things, supporting RESTful architecture and simple resource operations. The CoAP protocol can realize communication between devices in a restricted network environment, such as low-power wide area network (LPWAN). In the power Internet of Things, the CoAP protocol can be used to realize resource discovery and interaction between devices, such as data sharing and remote configuration between smart meters.

[0060] In the power Internet of Things, data encryption and transmission technology can be applied to the following scenarios:

[0061] Smart meter data transmission: Smart meters upload the collected current, voltage, power factor and other data to the cloud platform through the MQTT protocol. During the data transmission process, the AES encryption algorithm is used to encrypt the data to ensure the security of the data during transmission.

[0062] Remote monitoring of equipment: The cloud platform sends remote monitoring instructions to the edge node through the MQTT protocol. The edge node collects equipment data according to the instructions and uploads it to the cloud platform. During the data transmission process, the RSA encryption algorithm is used to encrypt the instructions and data to ensure the confidentiality and integrity of data transmission.

[0063] Effects and beneficial effects:

[0064] The application of data encryption and transmission technology in the power Internet of Things has the following functions and beneficial effects:

[0065] Ensure data security: Use advanced encryption algorithms and IoT communication protocols to ensure the confidentiality, integrity and authenticity of data during transmission, and prevent data leakage and malicious attacks.

[0066] Improve data transmission efficiency: Use lightweight IoT communication protocols to reduce data transmission latency and power consumption, and improve data transmission reliability and real-time performance.

[0067] Support remote monitoring and intelligent analysis: Realize remote uploading of equipment data and remote monitoring of the cloud platform, providing a reliable data source for intelligent analysis and decision support.

[0068] To sum up, data encryption and transmission technology is an indispensable part of the power Internet of Things. It plays an important role and has beneficial effects in ensuring data security, improving data transmission efficiency, and supporting remote monitoring and intelligent analysis.

[0069] Edge computing and intelligent analysis:

[0070] Edge computing:

[0071] In the power Internet of Things, edge computing technology plays a vital role. Since the power Internet of Things involves a large number of sensors and smart meters, these devices will generate massive amounts of data in real time. If all data is directly transmitted to the cloud platform for processing, it will not only increase the processing pressure of the cloud platform, but may also cause data transmission delays, affecting the real-time nature of data processing.

[0072] Therefore, deploying edge computing devices at the edge nodes of the power Internet of Things (such as substations, distribution rooms, etc.) can realize real-time processing and analysis of data. These edge computing devices have powerful computing capabilities and can quickly process and analyze data from sensors and smart meters, extract key information, and filter out irrelevant or redundant data. In this way, only data that has been preliminarily processed will be transmitted to the cloud platform, which greatly reduces the burden on the cloud platform and improves the efficiency of data processing.

[0073] Smart Analysis:

[0074] Based on edge computing, artificial intelligence technologies such as machine learning and deep learning can be used to perform intelligent analysis on processed data. These technologies can identify potential patterns and regularities in data, thereby discovering potential safety hazards and failure modes.

[0075] Taking the power Internet of Things as an example, intelligent analysis can be applied to the following aspects:

[0076] Fault prediction: By analyzing historical data and real-time monitoring data, intelligent analysis can predict the failure probability and failure time of power equipment and provide early warning for equipment maintenance.

[0077] Energy consumption optimization: By analyzing power consumption data, intelligent analysis can identify equipment or time periods with abnormal energy consumption, make energy-saving suggestions, and optimize energy use.

[0078] Security monitoring: Intelligent analysis can monitor security events and abnormal situations in the power Internet of Things in real time, such as data leakage, equipment failure, malicious attacks, etc., and trigger early warning mechanisms in a timely manner.

[0079] Effects and beneficial effects:

[0080] 1. Improve real-time performance: Edge computing technology can realize real-time processing and analysis of data, greatly shortening the time of data processing and improving the real-time performance of data processing.

[0081] 2. Reduce the burden on the cloud platform: Through the initial processing of edge computing devices, only critical data will be transmitted to the cloud platform, thereby reducing the processing pressure on the cloud platform.

[0082] 3. Improve accuracy: Intelligent analysis technology can identify potential patterns and regularities in data, improving the accuracy and reliability of data analysis.

[0083] 4. Optimize decision-making: Based on the results of intelligent analysis, relevant personnel can understand the status and operation of the power Internet of Things more accurately, and thus make more scientific decisions.

[0084] 5. Improve security: Intelligent analysis technology can monitor security events and abnormal situations in the power Internet of Things in real time, and trigger early warning mechanisms in a timely manner, thereby improving the security of the system.

[0085] In summary, the application of edge computing and intelligent analysis technology in the power Internet of Things can not only improve the real-time and accuracy of data processing, but also reduce the burden on the cloud platform, optimize the decision-making process, and improve the security of the system. The application of these technologies and methods is of great significance to promoting the development of the power Internet of Things.

[0086] 4. Data aggregation and storage:

[0087] Data Aggregation:

[0088] In the power Internet of Things, data aggregation is a key step, which involves integrating and summarizing data from different edge nodes. These edge nodes may include various IoT sensors, smart meters, environmental monitoring equipment, etc., which generate a wide variety of data in different formats. The main task of data aggregation is to uniformly process these data according to certain rules and formats for subsequent data storage and analysis.

[0089] Specifically, the data aggregation process includes the following steps:

[0090] 1. Data reception: Receive data from each edge node to ensure data integrity and accuracy.

[0091] 2. Data parsing: Parse the received data, extract useful information, and convert it into a unified format.

[0092] 3. Data verification: Verify the parsed data to check its integrity and consistency to ensure its reliability.

[0093] 4. Data integration: Integrate the verified data to form a unified data set, providing a basis for subsequent storage and analysis.

[0094] In the power Internet of Things, data aggregation has a wide range of application scenarios. For example, in smart grids, real-time data from different substations, transmission lines, and distribution equipment need to be aggregated to monitor and analyze the operation status of the power grid in real time.

[0095] Data Storage:

[0096] Data storage is another important part of the power Internet of Things. Since the amount of data generated by the power Internet of Things is huge and needs to be stored for a long time and accessed efficiently, it is crucial to choose the right storage technology.

[0097] In terms of data storage, the power Internet of Things usually adopts distributed storage technologies, such as cloud storage, Hadoop, etc. These technologies are efficient, reliable, and scalable, and can meet the data storage needs of the power Internet of Things.

[0098] Specifically, the data storage process includes the following steps:

[0099] 1. Data partitioning: The aggregated data is partitioned according to certain rules to improve the efficiency of data access.

[0100] 2. Data encoding: Encode the partitioned data to reduce the size and complexity of the data during storage and transmission.

[0101] 3. Data storage: Store the encoded data in a distributed storage system to ensure data security and reliability.

[0102] 4. Data backup: Back up stored data regularly to prevent data loss or damage.

[0103] In the power Internet of Things, data storage has a wide range of application scenarios. For example, in smart meter management, the real-time power consumption, voltage, current and other data of each meter need to be stored in the cloud storage system so that the operating status of the meter can be monitored and analyzed in real time.

[0104] Data aggregation and storage play a vital role in the power Internet of Things, which is specifically reflected in the following aspects:

[0105] 1. Improve data utilization: Through data aggregation, data from different edge nodes can be integrated and summarized to form a unified data set, thereby improving data utilization and value.

[0106] 2. Optimize data storage costs: Distributed storage technology can dynamically adjust storage resources according to the size and access requirements of data, thereby optimizing storage costs.

[0107] 3. Improve data access efficiency: Through technical means such as data partitioning and encoding, the efficiency of data access can be improved and the delay of data processing can be reduced.

[0108] 4. Ensure data security and privacy: During the data storage process, the use of encryption, backup and other technical means can ensure data security and privacy and prevent data leakage and damage.

[0109] In summary, data aggregation and storage play an important role and have beneficial effects in the power Internet of Things, and are an indispensable part of building an efficient, reliable and secure power Internet of Things system.

[0110] 5. Safety monitoring and early warning:

[0111] Safety monitoring:

[0112] In the power Internet of Things, security monitoring is an important part of ensuring the stable operation of the system and data security. Through the security monitoring module of the Dianhong IoT operating system, the following aspects can be monitored in real time:

[0113] 1. Data leakage monitoring: Using data encryption technology and access control mechanisms, the data flow and access within the system are monitored, and once abnormal data transmission or access behavior is found, an alarm is triggered immediately. For example, when an unauthorized external device is detected trying to access sensitive data in the power Internet of Things, the system will immediately record and report this behavior.

[0114] 2. Equipment failure monitoring: By analyzing the equipment operating status data (such as current, voltage, temperature, etc.), the health status of the equipment is monitored in real time. Once the equipment data exceeds the preset safety range or shows an abnormal pattern, the system will issue a fault warning so that maintenance measures can be taken in time to prevent equipment failure from causing larger system problems.

[0115] 3. Malicious attack monitoring: Using advanced network security technologies, such as intrusion detection system (IDS) and intrusion prevention system (IPS), real-time monitoring of network traffic and abnormal behavior, identification and defense against potential malicious attacks. For example, when a DDoS attack or SQL injection attack is detected, the system will immediately activate the defense mechanism to block the attack source and protect the system security.

[0116] Early warning mechanism:

[0117] Based on the results of security monitoring, the early warning mechanism triggers the following actions:

[0118] 1. Real-time notification: When a security incident or abnormal situation is detected, the system will immediately notify relevant personnel through SMS, email, APP push, etc. The notification content should include information such as the type of incident, time of occurrence, location, and possible degree of harm, so that relevant personnel can respond quickly.

[0119] 2. Emergency response: Depending on the severity of the warning information, the system will initiate the corresponding emergency response plan. For example, in the case of a data leak, the system will immediately cut off the source of the leak and initiate the data recovery procedure; in the case of an equipment failure, the system will instruct relevant personnel to go to the site for repair or equipment replacement.

[0120] 3. Event recording and analysis: The system will record every security event and early warning process in detail, including the time, location, cause, and processing results of the event. This information can be used for subsequent security event analysis and improvement work to improve the overall security level of the system.

[0121] In the power Internet of Things, the security monitoring and early warning mechanism can be applied to multiple scenarios. For example, in a smart grid, when the current data of a substation fluctuates abnormally, the system can monitor this change in real time and issue an early warning immediately. Through data analysis, the system can determine whether the current abnormality is caused by equipment failure or malicious attack. If it is an equipment failure, the system will instruct maintenance personnel to go to the site for repair; if it is a malicious attack, the system will activate the defense mechanism to protect the safety of the power grid.

[0122] Effects and beneficial effects:

[0123] 1. Improve system security: Through real-time monitoring and early warning mechanisms, potential security threats can be discovered and dealt with in a timely manner, reducing the risk of system attacks.

[0124] 2. Ensure data integrity: Data encryption and access control mechanisms can ensure the confidentiality and integrity of data and prevent data leakage and tampering.

[0125] 3. Improve emergency response capabilities: Through early warning mechanisms and emergency response plans, you can respond quickly when a security incident occurs and reduce losses.

[0126] 4. Optimize operation and maintenance management: The security monitoring and early warning mechanism can provide rich operation and maintenance data and analysis results, helping operation and maintenance personnel to better understand the system status and optimize the operation and maintenance strategy.

[0127] To sum up, the security monitoring and early warning mechanism plays a vital role in the power Internet of Things and is an important guarantee to ensure the stable operation of the system and data security.

[0128] 6. Data visualization and decision support:

[0129] Data Visualization:

[0130] In the power Internet of Things, data visualization is the process of transforming complex power data into intuitive and easy-to-understand graphics or images. This involves the following key aspects:

[0131] 1. Real-time data display: Through dashboards, line graphs, bar graphs, etc., key power parameters such as current, voltage, and power factor are displayed in real time, allowing operation and maintenance personnel to quickly understand the operating status of the power system.

[0132] 2. Historical data backtracking: Provides data backtracking function on the timeline, allowing operation and maintenance personnel to view changes in power data over a period of time, which helps analyze system trends and potential problems.

[0133] 3. Highlight abnormal data: Highlight abnormal data points or data points that exceed the threshold through color changes, flashing, etc., to remind operation and maintenance personnel to pay attention and take corresponding treatment measures.

[0134] 4. Multi-dimensional data analysis: Supports filtering and analyzing data by multiple dimensions such as time, location, and equipment type, helping operation and maintenance personnel to have a deeper understanding of the operating status of the power system.

[0135] Decision support:

[0136] Based on the results of data visualization, the decision support system provides the following support for the operation, maintenance and management of the power Internet of Things:

[0137] 1. Equipment maintenance suggestions: By analyzing the equipment's operating data and historical fault records, the system provides maintenance personnel with equipment maintenance priority suggestions to ensure that key equipment is maintained in a timely manner and reduce downtime.

[0138] 2. Troubleshooting guidance: When a system failure occurs, use data visualization tools to quickly locate the fault point and provide possible causes and solutions to improve troubleshooting efficiency.

[0139] 3. Security protection strategy: Based on the data from the security monitoring module, analyze potential security threats and vulnerabilities, and provide security protection strategy recommendations to operation and maintenance personnel, such as strengthening data encryption, updating security patches, etc.

[0140] 4. Energy management optimization: By analyzing power consumption data, identifying the source of energy waste, and providing optimization suggestions for energy management, such as adjusting power consumption plans, optimizing equipment configuration, etc., to reduce energy consumption and costs.

[0141] Taking the smart substation in the power Internet of Things as an example, data visualization and decision support systems can play the following roles:

[0142] Real-time monitoring: Through data visualization tools, operation and maintenance personnel can monitor the operating status of each device in the substation in real time, including key parameters such as current, voltage, and temperature, to ensure the safe and stable operation of the substation.

[0143] Fault warning: When equipment in the substation fails or is abnormal, the system can automatically trigger the early warning mechanism and display the fault location and possible causes through data visualization tools to guide operation and maintenance personnel to quickly troubleshoot and handle the fault.

[0144] Energy efficiency management: By analyzing the energy consumption data of the substation, the system can identify the source of energy waste, such as transformer overload, line loss, etc., and provide energy efficiency management optimization suggestions to operation and maintenance personnel to reduce the energy consumption and operating costs of the substation.

[0145] The application of data visualization and decision support in the power Internet of Things has the following functions and beneficial effects:

[0146] Improve operation and maintenance efficiency: Through real-time monitoring and fault warning functions, operation and maintenance personnel can quickly grasp the operating status and abnormal conditions of the power system, and improve operation and maintenance efficiency and quality.

[0147] Reduce operating costs: Through energy efficiency management optimization suggestions, reduce the energy consumption and operating costs of the power system and improve the economic benefits of the enterprise.

[0148] Enhanced security: Through security protection strategy recommendations and data encryption technology, the security capabilities of the power system are enhanced to prevent security incidents such as data leakage and malicious attacks.

[0149] Improve decision-making level: Provide data-based decision support for operation and maintenance personnel to help them formulate operation and maintenance plans, troubleshooting plans and safety protection strategies more scientifically, and improve the overall operation level of the power system.

[0150] The above are only preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for processing power Internet of Things data, characterized in that: It includes data collection and preprocessing steps, which use IoT sensors, smart meters and other equipment to collect current, voltage, power factor, temperature, humidity and other data in the power IoT in real time, and perform preprocessing operations such as cleaning, denoising and formatting on the collected raw data with the support of the Dianhong IoT operating system.

2. The method for processing data of the electric power Internet of Things according to claim 1, characterized in that: It also includes data encryption and transmission steps, which use encryption algorithms such as AES and RSA to encrypt the pre-processed data, and use IoT communication protocols such as MQTT and CoAP to achieve efficient and reliable transmission of data between IoT devices, edge nodes and cloud platforms.

3. The method for processing data of the electric power Internet of Things according to claim 2 is characterized in that: It also includes edge computing and intelligent analysis steps, which deploy edge computing devices at the edge nodes of the power Internet of Things, use edge computing technology to achieve real-time processing and analysis of data, and use artificial intelligence technologies such as machine learning and deep learning to perform intelligent analysis of data to identify potential safety hazards and failure modes.

4. The method for processing data of the electric power Internet of Things according to claim 3 is characterized in that: It also includes data aggregation and storage steps, which aggregate the data processed by the edge nodes to the cloud platform to form a unified data warehouse, and use distributed storage technology to achieve efficient and reliable storage of data.

5. The method for processing electric power Internet of Things data according to claim 4 is characterized in that: It also includes a security monitoring and early warning step, which monitors security events and abnormal situations in the power Internet of Things in real time through the security monitoring module of the Dianhong IoT operating system, triggers an early warning mechanism based on the monitoring results, and promptly notifies relevant personnel for processing.

6. A system for implementing the power Internet of Things data processing method according to any one of claims 1 to 5, characterized in that: It includes data acquisition module, preprocessing module, encryption module, transmission module, edge computing module, intelligent analysis module, data aggregation module, storage module, security monitoring module and early warning module.

7. The system according to claim 6, characterized in that The data acquisition module includes Internet of Things sensors and smart meters, which are used to collect various types of data in the power Internet of Things in real time.

8. The system according to claim 6, characterized in that The encryption module uses encryption algorithms such as AES and RSA to encrypt the pre-processed data.

9. The system according to claim 6, characterized in that The storage module utilizes distributed storage technologies, such as cloud storage, Hadoop, etc., to achieve efficient and reliable storage of data.

10. The system according to claim 6, characterized in that The security monitoring module triggers the early warning mechanism by monitoring the security events and abnormal situations in the power Internet of Things in real time, and promptly notifies relevant personnel to handle them.

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