Power grid electric energy quality monitoring system

Abstract

The invention discloses a power grid electric energy quality monitoring system, which relates to the field of electric energy quality monitoring, and is characterized in that a data acquisition module is arranged in the power grid electric energy quality monitoring system, a data transmission module is mounted on the outer side of the data acquisition module, and a data storage module is arranged behind the data transmission module; a data processing and analysis module is arranged on the outer side of the data storage module, a fault diagnosis and early warning module is arranged below the data processing and analysis module, and a display and visualization module is installed on the outer side of the fault diagnosis and early warning module. According to the power grid electric energy quality monitoring system, through widely distributed monitoring instruments and sensors, key parameters of a power grid are collected in real time, all nodes of the power grid are covered, data comprehensiveness and no monitoring blind area are ensured, and the real-time performance of data transmission is ensured by adopting multiple communication technologies and an automatic retry mechanism; in combination with a real-time analysis algorithm, power grid abnormity is rapidly identified, and fault response time is shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of power quality monitoring, and particularly to a power grid power quality monitoring system. Background Art

[0002] The power grid power quality monitoring system is an intelligent monitoring platform integrating data acquisition, transmission, storage, analysis, and management, aiming to monitor the operation status of the power grid in real time, ensure power quality, prevent power failures, and improve the stability and reliability of the power grid operation. The system realizes comprehensive monitoring and analysis of key parameters such as voltage, current, frequency, and harmonics through high-precision sensors, advanced algorithms, and visualization technologies, providing decision-making support and fault warning services for power companies.

[0003] In the prior art, when the power grid is in use, the internal data lines are prone to failures, which is not conducive to subsequent inspection and retrieval by staff, and subsequent maintenance is rather cumbersome.

[0004] To overcome the above deficiencies, a Chinese patent of the prior art (application number: 201210000714.3) discloses an intelligent power grid power quality monitoring system, including a main station of the power quality monitoring system, power quality monitoring terminals, and other power information systems. The main station of the power quality monitoring system, power quality monitoring terminals, and other power information systems are connected to the power communication network through a local area network. The power quality monitoring terminals are installed at the access points of various loads and power sources in the intelligent power grid. By setting power quality monitoring terminals at key nodes of the intelligent power grid, the power quality of the entire intelligent power grid can be monitored and analyzed in real time, laying a foundation for effectively analyzing the power quality and having important significance in reducing the cost investment of power quality monitoring equipment and improving the economic benefits of the power system.

[0005] To overcome the above deficiencies, a Chinese patent of the prior art (application number: 201811520426.4) discloses an intelligent power grid power quality monitoring system, including a voltage detection module, a current detection module, a frequency detection module, a signal processing unit, and a main control CPU. The voltage detection module, current detection module, and frequency detection module respectively collect current signals, voltage signals, and frequency signals on the power grid line and transmit them to the signal processing unit. The signal processing unit processes the input signals and outputs them to the main control CPU. The intelligent power grid power quality monitoring system of the present invention can monitor the voltage, current, and frequency on the AC power transmission line of the intelligent power grid in real time, visually display the data through a display, and automatically start the warning module to transmit an alarm signal when an abnormal situation occurs. It is powered by an independent power supply and does not depend on the power grid line to be detected, thus avoiding the impact of changes in the power grid line on the system.

[0006] Although the prior art can overcome the above-mentioned deficiencies, there are still other problems in its operation, such as: the data collected by the power grid power quality monitoring system is stored in the cloud. When transmitting data, if the network is poor, it is easy to cause data loss. When the lost data needs to be monitored and compared later, it will affect the accuracy of the data. Summary of the Invention

[0007] The purpose of the present invention is to provide a power grid power quality monitoring system to solve the problem that the data collected by the power grid power quality monitoring system is stored in the cloud. When transmitting data, if the network is poor, it is easy to cause data loss. When the lost data needs to be monitored and compared later, it will affect the accuracy of the data as mentioned in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions: A power grid power quality monitoring system, which includes a data acquisition module, a data transmission module, a data storage module, a data processing and analysis module, a fault diagnosis and warning module, a display and visualization module, a report generation and export module, a system management and maintenance module, and a data security and backup module; A data acquisition module is provided inside the power grid power quality monitoring system, a data transmission module is installed outside the data acquisition module, a data storage module is provided behind the data transmission module, and a data processing and analysis module is provided outside the data storage module. A fault diagnosis and warning module is provided below the data processing and analysis module, a display and visualization module is installed outside the fault diagnosis and warning module, a report generation and export module is provided outside the display and visualization module, and a system management and maintenance module is provided outside the report generation and export module. A data security and backup module is provided at the back end of the system management and maintenance module; The data acquisition module: Samples the power grid signal through the installed monitoring equipment, monitors various parameters of the power grid in real time and transmits them to the data storage module; The data transmission module: Adopts wireless communication, optical fiber transmission, and power line carrier communication technologies to ensure the stability and real-time nature of data transmission; The data storage module: Uses a database management system to classify and store data, adopts a big data storage architecture to ensure high concurrency, high availability, and high reliability, receives data in real time and stores it, and archives and backs up historical data at the same time to ensure that the data is not lost and is convenient for later query and analysis; The data processing and analysis module: Processes the data using data analysis algorithms, identifies and reports abnormal situations, monitors the power quality data in real time through preset analysis models and algorithms, and generates an analysis report indicating potential power quality problems; The fault diagnosis and warning module: Detects power quality problems according to the set alarm threshold and a machine learning-based prediction algorithm, and the system automatically triggers an alarm mechanism to notify relevant personnel to take emergency measures; The display and visualization module: Displays various power quality data, real-time trend charts, and alarm information of the power grid to users by developing a Web interface and a mobile App. Through the graphical interface, the change trends of various indicators of the power grid, such as voltage, frequency, and harmonic content, are displayed in real time. Users can perform interactive operations through the interface to view detailed information; The report generation and export module: Generates a power quality assessment report based on the historical data of the power grid operation. Users specify the time range and report format as needed, and the system automatically generates the report; The system management and maintenance module: Through the Web management platform and a dedicated client, system settings, device management, and log viewing are performed. The administrator configures system settings, monitors the operating status of devices, and manages user permissions through the background interface to ensure the efficient operation of the system;The data security and backup module: adopts the data encryption protocol SSL, regularly backs up data to the cloud platform and external storage devices, and through encryption and backup strategies, ensures that data will not be lost or leaked when the system faces external attacks and hardware failures.

[0009] Furthermore, the data acquisition module collects relevant data on power quality through monitoring instruments distributed at key nodes of the power grid. The monitoring instruments consist of measurement sensors for voltage, current, power factor, frequency, and harmonics. The instruments use high-precision sensors to monitor various parameters of the power grid in real time, convert analog signals into digital signals through the built-in sampling system, and the collected data is transmitted to the data transmission module. The monitoring instruments will collect power grid data at regular intervals according to the set sampling frequency.

[0010] Furthermore, the data transmission module transmits the power quality data collected at each monitoring point to the central processing unit through communication. It adopts wireless communication and ensures data security through encryption processing. When a transmission interruption occurs, the system adopts an automatic retry mechanism and switches to a backup channel to ensure the integrity of the data.

[0011] Furthermore, the data storage module receives and stores all power quality data from the data transmission module. The data storage is managed using a database management system. A relational database is selected and classified, archived, and optimized according to storage requirements. For large-scale data, a distributed database storage solution is adopted. Real-time data will be stored in memory and on the local hard disk, and historical data will be regularly archived, and a backup mechanism is used to ensure that the data will not be lost.

[0012] Furthermore, the data processing and analysis module performs real-time and offline analysis on the data. The analysis method is Fourier transform, which identifies problems such as frequency fluctuations, harmonic distortion, and transient events in the power grid. Through Fourier transform, the system extracts each harmonic component from the voltage signal and determines whether it exceeds the specified threshold. Real-time analysis targets the current power grid state, generates a monitoring report, provides real-time feedback on the power grid health, and the processing algorithm predicts and diagnoses faults based on rule settings.

[0013] Furthermore, the fault diagnosis and warning module performs real-time monitoring on the power quality data according to pre-set thresholds. When a certain power quality index reaches the preset threshold, the fault diagnosis module will trigger an alarm. The alarm mechanism is divided into different levels according to the severity. In addition, the system also uses historical data and algorithms for trend analysis to predict possible power quality problems and issue early warnings to help power companies take preventive measures and reduce the likelihood of faults.

[0014] Furthermore, the display and visualization module displays the power quality parameters of the power grid in the form of charts through a real-time graphical interface, facilitating users to intuitively view the operating status of the power grid. All monitoring data and warning information will be displayed in real time. Users can select to view data for a specific time period according to their needs. The real-time refresh mechanism of the charts ensures the timeliness and accuracy of the data, and generates trend analysis charts to provide decision-making reports.

[0015] Furthermore, the report generation and export module automatically generates reports based on the operating data and analysis results of the power grid. The generated reports are automatically generated regularly. The report generation and export module automatically customizes the specific format and content of the report according to the time interval and report content set by the user.

[0016] Furthermore, the system management and maintenance module configures and maintains the entire power grid monitoring system through a dedicated management platform. The administrator performs initial configuration, modification operations, and daily maintenance on the system. The system management and maintenance module is responsible for user management, assigning different permissions to ensure that different users can access specific data. The administrator views the operating logs and health status of the system to ensure the stable operation of the system.

[0017] Furthermore, the data security and backup module ensures the security and integrity of data during storage and transmission. When transmitting data, an encryption protocol is used to encrypt the data to prevent data from being stolen and tampered with. The backup strategy regularly backs up the data to local storage devices and cloud storage systems to ensure that data can be quickly restored in case of system failures. Data access permission control prevents unauthorized users from accessing sensitive data, ensuring the privacy and security of the data. The validity of the backed-up data is regularly detected to ensure successful restoration of the data during recovery.

[0018] Compared with the prior art, the beneficial effects of the present invention are: 1. Through widely distributed monitoring instruments and sensors, key parameters of the power grid are collected in real time, covering all nodes of the power grid, ensuring the comprehensiveness of data and no blind spots in monitoring. A variety of communication technologies and automatic retry mechanisms are used to ensure the real-time nature of data transmission; combined with real-time analysis algorithms, power grid anomalies are quickly identified, shortening the fault response time; Furthermore, the data transmission module supports standby channel switching and encrypted transmission. The data storage module uses a distributed database and regular archiving and backup to ensure data integrity and high availability. Through SSL encryption, access permission control, and cloud plus local dual backup strategies, data leakage, tampering, or loss are prevented, and risks of network attacks and hardware failures are addressed; Furthermore, based on preset thresholds and machine learning algorithms, fault grading alarms are realized to assist in quickly locating problems. Through historical data trend analysis, potential power quality problems are predicted, and preventive measures are taken in advance to reduce the fault occurrence rate.

[0019] 2. Support the export of reports with custom time ranges and formats, reduce manual operations, improve the management efficiency of power companies, display data charts in real time on the Web and mobile devices, support user interaction operations, and enhance the intuitiveness of decision-making and the user experience; Furthermore, each module operates independently and collaborates with each other, facilitating function expansion or technology upgrade. The system management module is used to implement user permission allocation, device status monitoring, and log analysis, reduce the complexity of operation and maintenance, ensure the long-term stable operation of the system, and the automated monitoring reduces the need for manual inspections; preventive maintenance extends the service life of equipment, avoids power outage losses caused by major failures, optimizes grid operation parameters through accurate analysis and early warning, reduces problems such as harmonic pollution and voltage fluctuations, and ensures the safety of user electricity consumption and service quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the overall process of the present invention.

[0021] Figure 2 It is a schematic diagram of the data flow process of the present invention.

[0022] Figure 3 It is a schematic diagram of the control flow process of the present invention.

[0023] Figure 4 It is a schematic diagram of the safety closed-loop process of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] Embodiment 1: As Figures 1 - 4The described technical solution, a power grid power quality monitoring system, discloses for solving what problems: The system includes a data acquisition module, a data transmission module, a data storage module, a data processing and analysis module, a fault diagnosis and early warning module, a display and visualization module, a report generation and export module, a system management and maintenance module, and a data security and backup module; Inside the power grid power quality monitoring system, a data acquisition module is provided, and a data transmission module is installed outside the data acquisition module, and a data storage module is provided behind the data transmission module, and a data processing and analysis module is provided outside the data storage module, a fault diagnosis and early warning module is provided below the data processing and analysis module, and a display and visualization module is installed outside the fault diagnosis and early warning module, and a report generation and export module is provided outside the display and visualization module, and a system management and maintenance module is provided outside the report generation and export module, and a data security and backup module is provided at the back end of the system management and maintenance module; Data acquisition module: Samples the power grid signal through the installed monitoring equipment, monitors various parameters of the power grid in real time and transmits them to the data storage module; Data transmission module: Adopts wireless communication, optical fiber transmission, and power line carrier communication technologies to ensure the stability and real-time of data transmission; Data storage module: Uses a database management system to classify and store data, adopts a big data storage architecture to ensure high concurrency, high availability, and high reliability, receives data in real time and stores it, and archives and backs up historical data at the same time to ensure that the data is not lost and is convenient for later query and analysis; Data processing and analysis module: Processes data using data analysis algorithms, identifies and reports abnormal situations, monitors power quality data in real time through preset analysis models and algorithms, and generates an analysis report indicating potential power quality problems; Fault diagnosis and early warning module: Detects power quality problems according to the set alarm threshold and a machine learning-based prediction algorithm, and the system automatically triggers an alarm mechanism to notify relevant personnel to take emergency measures; Display and visualization module: Displays various power quality data, real-time trend charts, and alarm information of the power grid to users by developing a Web interface and a mobile App. Through the graphical interface, the change trends of various indicators of the power grid, such as voltage, frequency, and harmonic content, are displayed in real time. Users can perform interactive operations through the interface to view detailed information; Report generation and export module: Generates a power quality assessment report based on the historical data of the power grid operation. Users specify the time range and report format as needed, and the system automatically generates the report; System management and maintenance module: Through the Web management platform and a dedicated client, system settings, device management, and log viewing are carried out. The administrator configures system settings, monitors the operating status of devices, and manages user permissions through the background interface to ensure the efficient operation of the system;Data Security and Backup Module: Adopt the data encryption protocol SSL, regularly back up data to the cloud platform and external storage devices, and through encryption and backup strategies, ensure that data will not be lost or leaked when the system faces external attacks and hardware failures.

[0026] The data acquisition module collects relevant data on power quality through monitoring instruments distributed at key nodes of the power grid. The monitoring instruments consist of sensors for measuring voltage, current, power factor, frequency, and harmonics. The instruments use high-precision sensors to monitor various parameters of the power grid in real time, convert analog signals into digital signals through the built-in sampling system, and the collected data is transmitted to the data transmission module. The monitoring instruments collect power grid data at regular intervals according to the set sampling frequency. The data transmission module transmits the power quality data collected at each monitoring point to the central processing unit through communication methods. The wireless communication method is adopted, and data security is ensured through encryption processing. When a transmission interruption occurs, the system adopts an automatic retry mechanism and switches to a backup channel to ensure the integrity of the data. The data storage module receives and stores all power quality data from the data transmission module. The data storage is managed using a database management system. A relational database is selected and classified, archived, and optimized according to storage requirements. For large-scale data, a distributed database storage solution is adopted. Real-time data is stored in memory and on the local hard disk, and historical data is regularly archived, and a backup mechanism is used to ensure that the data is not lost. The data processing and analysis module performs real-time and offline analysis on the data. The analysis method is Fourier transform to identify problems such as frequency fluctuations, harmonic distortion, and transient events in the power grid. Through Fourier transform, the system extracts each harmonic component from the voltage signal and determines whether it exceeds the specified threshold. The real-time analysis is for the current power grid state, generates a monitoring report, and provides real-time feedback on the power grid health. The processing algorithm predicts and diagnoses faults based on rule settings. The fault diagnosis and warning module monitors the power quality data in real time according to pre-set thresholds. When a certain power quality index reaches the preset threshold, the fault diagnosis module triggers an alarm. The alarm mechanism is divided into different levels according to the severity. In addition, the system also uses historical data and algorithms for trend analysis to predict possible power quality problems and issue early warnings in advance to help power companies take preventive measures and reduce the likelihood of faults. The display and visualization module displays the power quality parameters of the power grid in the form of charts through a real-time graphical interface, facilitating users to intuitively view the operation state of the power grid. All monitoring data and warning information are displayed in real time. Users can select to view data for a specific time period according to their needs. The real-time refresh mechanism of the charts ensures the timeliness and accuracy of the data, generates trend analysis charts to provide decision-making reports. The report generation and export module automatically generates reports based on the operation data and analysis results of the power grid. The generated reports are automatically generated regularly. The report generation and export module automatically customizes the specific format and content of the report according to the time interval and report content set by the user. The system management and maintenance module configures and maintains the entire power grid monitoring system through a dedicated management platform. The administrator performs initial configuration, modification operations, and daily maintenance on the system. The system management and maintenance module is responsible for user management, assigning different permissions to ensure that different users can access specific data.Administrators view the system's operation logs and health status to ensure the stable operation of the system. The data security and backup module ensures the security and integrity of data during storage and transmission. When transmitting data, an encryption protocol is used to encrypt the data to prevent data from being stolen or tampered with. The backup strategy regularly backs up data to local storage devices and cloud storage systems to ensure that data can be quickly restored in case of system failures. Data access permission control prevents unauthorized users from accessing sensitive data, protecting the privacy and security of data. The validity of the backed-up data is regularly detected to ensure that the data can be successfully restored during recovery.,

[0027] Monitoring instruments are deployed at key nodes of the power grid (such as substations, distribution lines, and user access points), integrating high-precision voltage, current, and harmonic sensors to collect power grid parameters (voltage, frequency, power factor, harmonic distortion rate, etc.) in real time. The sensors convert analog signals into digital signals and generate time-series data packets at a preset sampling frequency (such as 1000 times per second). After attaching timestamps and location tags, the data is sent to the central server through the data transmission module. The data transmission module uses wireless communication (such as 4G / 5G) and fiber-optic dual channels for transmission. If the main channel is interrupted, it automatically switches to the backup channel; the data is transmitted after being encrypted by SSL to prevent eavesdropping or tampering; After receiving the data, the data storage module first stores it in an in-memory database (such as Redis), which supports high-concurrency reading and writing to ensure low latency for real-time analysis. The real-time data is regularly transferred to a relational database (such as MySQL) for structured storage. The historical data is compressed and archived in a distributed database (such as Hadoop HDFS) or cloud storage to support long-term queries. It is incrementally backed up to the local hard drive and the cloud every day to prevent data loss. Outliers (such as invalid data caused by sensor noise and communication packet loss) are automatically removed before storage to ensure data quality. Spectrum analysis is performed on the voltage / current waveforms to extract fundamental and harmonic components (such as 2 - 50th harmonics), calculate the total harmonic distortion rate (THD), and compare it with preset thresholds (such as voltage deviation ±10%, frequency deviation ±0.5Hz). If the limit is exceeded, it is marked as abnormal. Machine learning models (such as LSTM neural networks) are used to analyze historical data to predict future power quality trends (such as the probability of voltage sags). Waveform feature matching is performed on transient events (such as voltage surges and short-term interruptions) to locate the fault source (such as lightning strikes and equipment short circuits). The system combines a knowledge base (such as power grid topology and equipment parameters) to recommend the cause of the fault (such as harmonic over-standard caused by capacitor bank failure), shortening the troubleshooting time. A heat map of the power quality of the entire network (color-coded abnormal areas), real-time waveform diagrams, and key indicator dashboards are displayed through the Web interface. Operation and maintenance personnel receive alarm notifications through the App, view the fault location and recommended measures, and users can customize data views (such as the voltage fluctuation curve of a certain substation in the past 1 hour), support zooming and comparison (such as comparing harmonic contents at the same time period on different dates), and generate interactive trend analysis diagrams.

[0028] The monitoring point sensor detected that the harmonic content exceeded the limit 5 times (threshold 8%, measured 12%). The data was encrypted and transmitted to the central server. The storage module marked it as abnormal. The analysis module triggered a secondary alarm. The diagnosis module suggested "check the load of the inverters in the park". The operation and maintenance personnel received the alarm through the App, retrieved the historical harmonic curve of this node to confirm the fault. The system automatically generated a treatment suggestion report and synchronized it to the management department. After processing, the harmonic data returned to normal. The system recorded the event in the knowledge base and optimized the future warning model.

[0029] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A power grid power quality monitoring system, characterized in that: The system includes a data acquisition module, a data transmission module, a data storage module, a data processing and analysis module, a fault diagnosis and early warning module, a display and visualization module, a report generation and export module, a system management and maintenance module, and a data security and backup module; Inside the power grid power quality monitoring system, there is a data acquisition module, and a data transmission module is installed outside the data acquisition module. And a data storage module is arranged behind the data transmission module. Moreover, a data processing and analysis module is arranged outside the data storage module. The fault diagnosis and early warning module is arranged below the data processing and analysis module. And a display and visualization module is installed outside the fault diagnosis and early warning module. And a report generation and export module is arranged outside the display and visualization module. Moreover, a system management and maintenance module is arranged outside the report generation and export module. The data security and backup module is arranged at the back end of the system management and maintenance module; The data acquisition module: Samples the power grid signals through the installed monitoring devices, and monitors various parameters of the power grid in real time and transmits them to the data storage module; The data transmission module: Adopts wireless communication, optical fiber transmission, and power line carrier communication technologies to ensure the stability and real-time nature of data transmission; The data storage module: Uses a database management system to classify and store data, adopts a big data storage architecture to ensure high concurrency, high availability, and high reliability, receives data in real time and stores it, and at the same time archives and backs up historical data to ensure that the data is not lost and is convenient for later query and analysis; The data processing and analysis module: Processes the data using data analysis algorithms, identifies and reports abnormal situations, and through preset analysis models and algorithms, monitors the power quality data in real time and generates an analysis report, indicating potential power quality problems; The fault diagnosis and early warning module: Detects power quality problems according to the set alarm threshold and a prediction algorithm based on machine learning. The system automatically triggers an alarm mechanism to notify relevant personnel to take emergency measures; The display and visualization module: Through developing a Web interface and a mobile App, displays various power quality data, real-time trend charts, and alarm information of the power grid to users. Through the graphical interface, it displays the change trends of various indicators of the power grid in real time, such as voltage, frequency, and harmonic content. Users can perform interactive operations through the interface to view detailed information; The report generation and export module: Generates a power quality assessment report according to the historical data of the power grid operation. Users specify the time range and report format as needed, and the system automatically generates the report; The system management and maintenance module: Through a Web management platform and a dedicated client, performs system settings, device management, and log viewing. The administrator configures system settings, monitors the operating status of devices, and manages user permissions through the background interface to ensure the efficient operation of the system; The data security and backup module: Adopts the data encryption protocol SSL, regularly backs up data to a cloud platform and external storage devices. Through encryption and backup strategies, it ensures that the data will not be lost or leaked when the system faces external attacks and hardware failures.

2. The power grid power quality monitoring system according to claim 1, characterized in that: The data acquisition module collects relevant data on power quality through monitoring instruments distributed at key nodes of the power grid. The monitoring instruments consist of measurement sensors for voltage, current, power factor, frequency, and harmonics. The instruments use high-precision sensors to monitor various parameters of the power grid in real time, convert analog signals into digital signals through the built-in sampling system, and the collected data is transmitted to the data transmission module. The monitoring instruments collect power grid data at regular intervals according to the set sampling frequency.

3. The power grid power quality monitoring system according to claim 1, wherein: The data transmission module transmits the power quality data collected at each monitoring point to the central processing unit through communication means. It uses wireless communication and ensures data security through encryption processing. When a transmission interruption occurs, the system adopts an automatic retry mechanism and switches to a backup channel to ensure the integrity of the data.

4. A power grid power quality monitoring system according to claim 1, characterized in that: The data storage module receives and stores all power quality data from the data transmission module. Data storage is managed using a database management system. A relational database is selected and classified, archived, and optimized according to storage requirements. For large-scale data, a distributed database storage solution is adopted. Real-time data is stored in memory and on the local hard disk, and historical data is regularly archived. A backup mechanism is used to ensure that the data is not lost.

5. The power grid power quality monitoring system according to claim 1, characterized in that: The data processing and analysis module performs real-time and offline analysis on the data. The analysis method is Fourier transform, which is used to identify problems such as frequency fluctuations, harmonic distortion, and transient events in the power grid. Through Fourier transform, the system extracts each harmonic component from the voltage signal and determines whether it exceeds the specified threshold. Real-time analysis is carried out for the current power grid state to generate a monitoring report and provide real-time feedback on the health of the power grid. The processing algorithm predicts and diagnoses faults based on rule settings.

6. The power grid power quality monitoring system according to claim 1, characterized in that: The fault diagnosis and warning module monitors the power quality data in real time according to pre-set thresholds. When a certain power quality index reaches the preset threshold, the fault diagnosis module triggers an alarm. The alarm mechanism is divided into different levels according to the severity. In addition, the system also uses historical data and algorithms for trend analysis to predict possible power quality problems and issue early warnings to help power companies take preventive measures and reduce the likelihood of faults.

7. A power grid power quality monitoring system according to claim 1, characterized in that: The display and visualization module displays the power quality parameters of the power grid in the form of charts through a real-time graphical interface, facilitating users to intuitively view the operating state of the power grid. All monitoring data and warning information are displayed in real time. Users can select to view data for a specific time period according to their needs. The real-time refresh mechanism of the charts ensures the timeliness and accuracy of the data and generates trend analysis charts to provide decision-making reports.

8. A power grid power quality monitoring system according to claim 1, characterized in that: The report generation and export module automatically generates reports based on the operating data and analysis results of the power grid. The generated reports are automatically generated regularly. The report generation and export module automatically customizes the specific format and content of the report according to the time interval and report content set by the user.

9. The power grid power quality monitoring system according to claim 1, characterized in that: The system management and maintenance module configures and maintains the entire power grid monitoring system through a dedicated management platform. The administrator performs initial configuration, modification operations, and daily maintenance on the system. The system management and maintenance module is responsible for user management, allocating different permissions to ensure that different users can access specific data. The administrator views the operation logs and health status of the system to ensure the stable operation of the system.

10. The power grid power quality monitoring system according to claim 1, wherein: The data security and backup module ensures the security and integrity of data during storage and transmission. When transmitting data, an encryption protocol is used to encrypt the data to prevent data from being stolen and tampered with. The backup strategy regularly backs up data to local storage devices and cloud storage systems to ensure that data can be quickly restored in case of system failures. Data access permission control prevents unauthorized users from accessing sensitive data, protecting the privacy and security of data. The validity of the backed-up data is regularly detected to ensure that the data can be successfully restored during recovery.

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