Electric energy quality monitoring method and device based on intelligent flexible regulation and control terminal

Abstract

The invention provides an electric energy quality monitoring method and device based on an intelligent flexible regulation and control terminal, and belongs to the technical field of electric power system control. The method comprises the following steps: controlling an intelligent flexible regulation and control terminal to execute a meter reading task, and reading real-time electric energy quality data of each measurement point in a power grid system based on a meter reading task ID; extracting synchronous voltage signals from the acquired voltage signals by adopting a maximum similarity algorithm, and multiplying the synchronous voltage signals to extract a signal envelope line; a MATLAB tool is adopted to conduct simulation analysis on the signal envelope containing the voltage fluctuation and flicker signals, S transformation is utilized to process the flicker signals, a high-frequency characteristic curve of the flicker signals is analyzed so as to obtain the occurrence time and the end time of the flicker signals, and an S transformation result is generated; and calculating the amplitude of the flicker signal based on the occurrence time, the ending time and the S transformation result of the flicker signal. The electric energy quality problem can be efficiently and accurately monitored, and the operation reliability and stability of an electric power system are improved.

Description

Technical Field

[0001] This application belongs to the technical field of power system control, and particularly relates to a method and device for power quality monitoring based on an intelligent flexible control terminal. Background Art

[0002] With the development of social economy and the progress of technology, the power system has become increasingly complex, and the requirements for power quality have also become higher and higher. Power quality is not only related to the safe and stable operation of the power system, but also directly affects the working efficiency and lifespan of various electrical equipment.

[0003] Traditional power quality monitoring methods mainly rely on fixedly installed monitoring devices. These devices usually can only provide data at limited monitoring points and lack flexibility and real-time performance. In addition, traditional data analysis methods often require complex filtering processing, and it is difficult to accurately identify and quantify fast-changing transient events (such as voltage flicker).

[0004] In recent years, with the development of smart grid technology, intelligent flexible control terminals, as a new type of intelligent device, have been widely used in power systems. Such terminals can not only be flexibly deployed at different measurement points to achieve real-time monitoring of the power quality of the power grid, but also can perform remote meter reading tasks to collect more comprehensive and detailed power quality data.

[0005] However, even with the support of intelligent flexible control terminals, how to quickly and accurately extract useful power quality indicators from a large amount of real-time data, especially how to effectively process non-steady signals such as voltage flicker, remains a challenge. Summary of the Invention

[0006] To solve at least one aspect of the technical problems in the background art, this application provides a method for power quality monitoring based on an intelligent flexible control terminal, which can achieve efficient and accurate monitoring of power quality problems and improve the operation reliability and stability of the power system.

[0007] The second aspect of this application provides a device for power quality monitoring based on an intelligent flexible control terminal.

[0008] The technical solution adopted by this application is as follows:

[0009] The first aspect of the embodiments of this application provides a method for power quality monitoring based on an intelligent flexible control terminal, including:

[0010] Controlling the intelligent flexible control terminal to execute a meter reading task, and reading the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID, where the power quality data at least includes voltage;

[0011] The synchronous voltage signal is extracted from the collected voltage signals by using the maximum similarity algorithm, and the synchronous voltage signals are multiplied to extract the signal envelope;

[0012] The signal envelope containing voltage fluctuation and flicker signals is simulated and analyzed by using MATLAB tool, the flicker signals are processed by using S transform, and the high-frequency characteristic curve of the flicker signals is analyzed to obtain the occurrence time and end time of the flicker signals, and the S transform result is generated;

[0013] Based on the occurrence time, the end time and the S transform result of the flicker signals, the amplitude of the flicker signals is calculated.

[0014] According to the power quality monitoring method based on an intelligent flexible control terminal provided by the first aspect of the present application, first, control the intelligent flexible control terminal to execute a meter reading task, and read the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID. Among them, the power quality data at least includes voltage. In this step, by controlling the intelligent flexible control terminal to execute the meter reading task, the real-time power quality data can be flexibly and efficiently collected from multiple measurement points. This method not only improves the flexibility and real-time performance of data collection, but also ensures the integrity and accuracy of the data, providing a reliable basis for subsequent data analysis and power quality assessment; the second step is to extract the synchronous voltage signal from the collected voltage signal by using the maximum similarity algorithm, and multiply the synchronous voltage signals to extract the signal envelope. The maximum similarity algorithm can effectively extract the synchronous voltage signal from the complex voltage signal. By multiplying the synchronous voltage signals to extract the signal envelope, the change trend and characteristics of the voltage signal can be more clearly displayed. This step helps to remove noise and interference, improve the accuracy of signal processing, and provide high-quality data support for subsequent flicker signal analysis; then, use the MATLAB tool to perform simulation analysis on the signal envelope containing voltage fluctuation and flicker signals, process the flicker signal by using the S transform, and analyze the high-frequency characteristic curve of the flicker signal to obtain the occurrence time and end time of the flicker signal, and generate the S transform result. By using the MATLAB tool for simulation analysis and combining the S transform technology, the high-frequency characteristics of voltage fluctuation and flicker signals can be accurately identified and analyzed. The S transform can provide detailed information in the time-frequency domain, helping to determine the occurrence and end time of the flicker signal, so as to realize the precise positioning and quantification of flicker events. This process not only improves the accuracy of analysis, but also provides a scientific basis for subsequent fault diagnosis and preventive measures. Finally, based on the occurrence time, end time and S transform result of the flicker signal, calculate the amplitude of the flicker signal. Through the comprehensive analysis of the occurrence time, end time and S transform result of the flicker signal, the amplitude of the flicker signal can be accurately calculated. This step not only provides a quantitative evaluation index, but also helps technicians better understand the severity of flicker events, providing data support for formulating reasonable power quality improvement measures. In summary, the power quality monitoring method based on an intelligent flexible control terminal provided by the first aspect of the present application improves the flexibility, real-time performance and accuracy of data collection and processing, provides strong technical support for the efficient monitoring and management of power quality problems, and significantly improves the operation reliability and stability of the power system.

[0015] According to an embodiment of the present application, the step of controlling the intelligent flexible control terminal to execute a meter reading task and reading the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID, where the power quality data at least includes voltage, specifically includes:

[0016] Define the meter reading frequency parameter, measurement point sequence, and meter reading data type of the meter reading task;

[0017] At a preset meter reading time point, control the intelligent flexible regulation terminal to send a meter reading request instruction to the target measurement point, and receive the corresponding power quality data returned by the target measurement point;

[0018] Associate the power quality data with the meter reading task ID to achieve traceability of the meter reading task for power quality data.

[0019] According to an embodiment of the present application, the method of extracting the synchronous voltage signal from the collected voltage signals by using the maximum similarity algorithm and multiplying the synchronous voltage signals to extract the signal envelope is specifically as follows:

[0020] Select one of the voltage signals as the reference signal;

[0021] Calculate the cross-correlation function R xy (τ) between the voltage signal and the reference signal to obtain the time delay τ corresponding to the maximum value. The formula for the cross-correlation function R xy (τ) is:

[0022]

[0023] where x(t) is the voltage signal, y(t) is the reference signal, N is the length of the signal, and τ is the time delay.

[0024] According to an embodiment of the present application, the method of extracting the synchronous voltage signal from the collected voltage signals by using the maximum similarity algorithm and multiplying the synchronous voltage signals to extract the signal envelope further includes:

[0025] Align the collected voltage signals according to the time delay τ to obtain the synchronous voltage signal x sync (t);

[0026] Based on the synchronous voltage signal x sync (t), generate a delayed version of the synchronous voltage signal x sync (t - τ). Multiply the synchronous voltage signal x sync (t) by the delayed version of the synchronous voltage signal x sync (t - τ) to obtain the product signal z(t) = x sync (t) · x sync (t - τ);

[0027] Smooth the product signal z(t) to generate the signal envelope E(t).

[0028] According to an embodiment of the present application, the high-frequency characteristic curve includes an instantaneous frequency curve and a power spectral density curve, and the S-transform result includes a time-frequency distribution diagram, an instantaneous frequency response diagram, a localization information diagram, and a multi-resolution analysis diagram.

[0029] According to an embodiment of the present application, calculating the amplitude of the flicker signal based on the occurrence time, the end time, and the S-transform result of the flicker signal specifically includes:

[0030] Extracting the flicker signal time period from the original voltage signal based on the occurrence time, the end time, and the S-transform result of the flicker signal;

[0031] Calculating the difference between the maximum value and the minimum value of the signal within the flicker signal time period to generate the amplitude of the flicker signal, or calculating the root mean square value of the signal within the flicker signal time period to generate the amplitude of the flicker signal, or extracting the envelope of the signal within the flicker signal time period and calculating the difference between the maximum value and the minimum value of the envelope to generate the amplitude of the flicker signal.

[0032] According to an embodiment of the present application, the power quality data further includes current, frequency, harmonics, power factor, and transients.

[0033] According to an embodiment of the present application, the method further includes:

[0034] Setting a flicker signal amplitude threshold and comparing the calculated flicker signal amplitude with the set flicker signal amplitude threshold;

[0035] If the calculated flicker signal amplitude exceeds the set flicker signal amplitude threshold, an alarm is triggered.

[0036] An embodiment of the second aspect of the present application provides a power quality monitoring device based on an intelligent flexible control terminal, including:

[0037] A power quality data reading module, adapted to control the intelligent flexible control terminal to execute a meter reading task and read the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID, where the power quality data includes at least voltage;

[0038] A first calculation module, adapted to extract a synchronous voltage signal from the collected voltage signal by using the maximum similarity algorithm and multiply the synchronous voltage signals to extract the signal envelope;

[0039] A second calculation module, adapted to perform simulation analysis on the signal envelope containing voltage fluctuation and flicker signals by using MATLAB tools, process the flicker signals by using the S transform, analyze the high-frequency characteristic curve of the flicker signals, so as to obtain the occurrence time and end time of the flicker signals, and generate an S transform result;

[0040] A third calculation module, adapted to calculate the amplitude of the flicker signals based on the occurrence time, the end time and the S transform result of the flicker signals.

[0041] An embodiment of the third aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the power quality monitoring method based on an intelligent flexible control terminal in any embodiment of the first aspect as described above. Description of the Drawings

[0042] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation of the present application. In the drawings:

[0043] Figure 1 It is a schematic flowchart of the power quality monitoring method based on an intelligent flexible control terminal provided by an embodiment of the present application;

[0044] Figure 2 It is a schematic structural diagram of the power quality monitoring device based on an intelligent flexible control terminal provided by an embodiment of the present application;

[0045] Figure 3 It is a schematic structural diagram of the electronic device provided by an embodiment of the present application.

[0046] Among them,

[0047] 110. Power quality data reading module; 120. First calculation module; 130. Second calculation module; 140. Third calculation module;

[0048] 810. Processor; 820. Communication interface; 830. Memory; 840. Communication bus. Detailed Embodiments

[0049] In order to more clearly illustrate the overall concept of the present application, the following will be described in detail by way of examples in conjunction with the drawings of the specification.

[0050] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, the present application may be implemented in other ways different from those described herein. Therefore, the scope of protection of the present application is not limited by the specific embodiments disclosed below. It should be noted that, without conflict, the embodiments of the present application and the features in each embodiment may be combined with each other.

[0051] In the present application, unless otherwise clearly defined and limited, the first feature being "on" or "under" the second feature may mean that the first and second features are in direct contact, or the first and second features are indirectly in contact through an intermediate medium. In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0052] As Figure 1 shown, an embodiment of the first aspect of the present application provides a power quality monitoring method based on an intelligent flexible control terminal, including:

[0053] Step 100, control the intelligent flexible control terminal to execute a meter reading task, and read the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID, where the power quality data at least includes voltage.

[0054] Step 200, extract a synchronous voltage signal from the collected voltage signals by using the maximum similarity algorithm, and multiply the synchronous voltage signals to extract the signal envelope.

[0055] Step 300, perform simulation analysis on the signal envelope containing voltage fluctuation and flicker signals by using MATLAB tools, process the flicker signals by using the S transform, analyze the high-frequency characteristic curve of the flicker signals to obtain the occurrence time and end time of the flicker signals, and generate the S transform result.

[0056] Step 400, calculate the amplitude of the flicker signal based on the occurrence time, end time, and S transform result of the flicker signal.

[0057] In step 100, the intelligent flexible control terminal is a highly integrated intelligent device that can collect various power quality data in the power grid system in real time. These data include, but are not limited to, voltage, current, power factor, harmonic content, etc. The terminal supports remote task management and scheduling. It can control the terminal to execute specific meter reading tasks by sending a specific task ID. The task ID can contain parameters such as task type, timestamp, data collection frequency, etc., to ensure the precise execution of the task.

[0058] In addition, the terminal has a powerful communication function and can transmit data to the central management system through wired or wireless means (such as Ethernet, Wi-Fi, 4G / 5G, etc.) to ensure the real-time and reliability of the data.

[0059] The central management system issues meter reading tasks to the intelligent flexible control terminal according to the preset monitoring plan or sudden demand. The specific requirements of the task are included in the task ID, such as collection time, data type, sampling frequency, etc. After receiving the task ID, the terminal parses the task instruction and starts the corresponding data collection program. The terminal will collect power quality data in real time from each measurement point according to the task requirements. The collected data will be uploaded to the central management system in real time for further analysis and processing. During the data upload process, the terminal will also perform data verification and compression to ensure the integrity and transmission efficiency of the data.

[0060] Among them, voltage is one of the most basic and important parameters in power quality monitoring. By collecting voltage data in real time, problems such as voltage deviation, voltage fluctuation and flicker can be detected in a timely manner.

[0061] In addition to voltage data, the terminal can also collect other power quality parameters such as current, power factor, harmonic content, etc., providing more comprehensive data support.

[0062] To sum up, in step 100, the intelligent flexible control terminal can flexibly adjust the data collection time and frequency according to the task ID to ensure the real-time and accuracy of the data. This flexibility enables power quality monitoring to better adapt to different scenarios and requirements. The terminal has a powerful data verification and compression function, which can ensure the integrity and transmission efficiency of the data during the data upload process. This helps to reduce data loss and errors and improve the reliability of the overall monitoring system. Through task management and scheduling using the task ID, the central management system can conveniently control the meter reading tasks of multiple terminals, realizing centralized management and distributed execution. This method not only improves work efficiency but also reduces errors caused by human intervention. The terminal can collect various types of power quality data, not limited to voltage, but also including current, power factor, harmonic content, etc. These diverse data provide rich information support for subsequent power quality analysis and fault diagnosis.

[0063] In step 200, the maximum similarity algorithm is a technique used in signal processing, mainly for extracting specific sub-signals from complex signals. This algorithm finds the most matching part by comparing the similarity between the signal to be processed and known reference signals, thus extracting the required signal. In power quality monitoring, the maximum similarity algorithm can be used to extract synchronous voltage signals from the collected voltage signals. The synchronous voltage signal refers to the voltage signal synchronized with the power grid fundamental frequency (usually 50Hz or 60Hz), which is an important basis for evaluating power quality.

[0064] Extracting synchronous voltage signals:

[0065] First, a reference signal synchronized with the power grid fundamental frequency needs to be generated. This reference signal can be a sine wave with the same frequency as the power grid fundamental frequency. Then, the collected voltage signal is compared point by point with the reference signal to calculate their similarity. Commonly used similarity calculation methods include correlation coefficient, cross-correlation function, etc. The part with the highest similarity is selected as the synchronous voltage signal. This method can effectively remove noise and interference and retain the main signal components.

[0066] Extracting the signal envelope:

[0067] First, multiply the extracted synchronous voltage signal by its own delayed version. The delayed version refers to the signal obtained by shifting the original signal backward by a certain time interval.

[0068] The result of the multiplication reflects the amplitude change of the signal. By filtering out the high-frequency components through a low-pass filter, the signal envelope can be obtained. The envelope can visually display the amplitude change trend of the signal, which helps to further analyze phenomena such as voltage fluctuations and flicker.

[0069] The maximum similarity algorithm can accurately extract synchronous voltage signals from complex voltage signals, effectively removing noise and interference. Compared with traditional filtering methods, this method can more accurately retain the main features of the signal and improve the accuracy of signal processing. After extracting the synchronous voltage signal, through signal multiplication and envelope detection, a clear signal envelope can be obtained. The envelope can visually display the amplitude change trend of the voltage signal, which helps to further analyze phenomena such as voltage fluctuations and flicker. This is of great significance for power quality assessment and fault diagnosis. Compared with traditional multi-step filtering and processing methods, the method of combining the maximum similarity algorithm with signal multiplication and envelope detection simplifies the data processing flow. This method not only improves the processing efficiency but also reduces the consumption of computing resources and is suitable for large-scale data processing scenarios. Synchronous voltage signals and signal envelopes are important parameters for evaluating power quality. Through these parameters, power quality problems such as voltage fluctuations and flicker can be more accurately identified and quantified. This provides reliable data support for subsequent power quality analysis and improvement measures.

[0070] In summary, step 200 realizes the precise processing and analysis of voltage signals through the maximum similarity algorithm and the signal envelope extraction technology, significantly improving the accuracy and reliability of power quality monitoring.

[0071] In step 300, MATLAB is a powerful numerical calculation and simulation software widely used in fields such as signal processing, control system design, and image processing. In power quality monitoring, MATLAB can be used to simulate and analyze the collected signal envelopes to verify the effectiveness of signal processing algorithms.

[0072] First, import the signal envelope data collected from the intelligent flexible control terminal into MATLAB. Then, perform necessary preprocessing such as denoising and normalization to ensure the quality and consistency of the data.

[0073] The S-transform is a time-frequency analysis method that combines the advantages of the short-time Fourier transform (STFT) and wavelet transform. By adjusting the window function and frequency resolution, it can provide detailed signal feature information in the time-frequency domain. In power quality monitoring, the S-transform is particularly suitable for processing non-steady signals such as voltage fluctuations and flicker. Through the S-transform, the signal can be decomposed into different frequency components and the changes of these components can be shown on the time-frequency plane.

[0074] Processing of flicker signals:

[0075] First, input the preprocessed signal envelope into the S-transform algorithm to generate a time-frequency diagram. The time-frequency diagram shows the frequency distribution of the signal at different time points and can help identify the characteristics of flicker signals.

[0076] Then, by analyzing the high-frequency components in the time-frequency diagram, the high-frequency characteristic curve of the flicker signal can be extracted. The high-frequency characteristic curve reflects the rapid change characteristics of the flicker signal and is the key to identifying flicker events.

[0077] Finally, in the time-frequency diagram, flicker signals usually show an increase in high-frequency components within a certain time period. By setting a threshold, the occurrence time and end time of flicker signals can be automatically detected.

[0078] During the process of generating the S-transform results, the S-transform results can be displayed in the form of a time-frequency diagram for intuitive observation of the time-frequency characteristics of the signal. The S-transform results can also be exported as data files for further analysis and recording.

[0079] The S-transform can provide detailed time-frequency information to help accurately identify voltage fluctuations and flicker signals. Compared with traditional Fourier transform and wavelet transform, the S-transform has higher resolution and sensitivity in processing non-stationary signals and can capture the characteristics of flicker events more accurately. By analyzing the high-frequency characteristic curve of the flicker signal, the causes and impacts of flicker events can be understood more deeply. This provides a scientific basis for fault diagnosis and the formulation of preventive measures, helping to improve the operational reliability and safety of the power system. The MATLAB tool provides rich signal processing functions and visualization tools, making the data processing and analysis process more convenient and efficient. Users can achieve complex data processing tasks through simple script writing, reducing the tediousness and errors of manual operations. The time-frequency diagram generated by the S-transform not only shows the frequency distribution of the signal but also provides information on temporal variations. This detailed information in the time-frequency domain helps to comprehensively evaluate power quality and detect potential problems and anomalies. In MATLAB, an automated signal processing and analysis process can be achieved through programming. For example, by setting thresholds to automatically detect the occurrence time and end time of the flicker signal, generating reports and alarms, and improving the intelligence level of the monitoring system.

[0080] In summary, step 300 realizes the accurate analysis and processing of voltage fluctuations and flicker signals through the MATLAB tool and S-transform technology, significantly improving the accuracy and reliability of power quality monitoring and providing strong technical support for the optimized operation of the power system.

[0081] In step 400, in the previous step, the occurrence time and end time of the flicker signal have been determined through the S-transform. These two time points define the time range of the flicker event and are the basis for calculating the amplitude of the flicker signal. The S-transform result provides detailed information of the flicker signal in the time-frequency domain, including the intensity and variation trend of different frequency components. This information is very useful for further analyzing the characteristics of the flicker signal.

[0082] In the time-frequency diagram generated by the S-transform, the flicker signal usually shows a significant increase in high-frequency components within a certain time period. The intensity of the flicker signal can be characterized by calculating the average amplitude or peak amplitude of the high-frequency components within this time period.

[0083] Another method is to calculate the amplitude of the flicker signal using the maximum and minimum values of the signal envelope during the flicker event. The maximum and minimum values of the envelope reflect the maximum variation range of the signal amplitude and can be directly used to calculate the amplitude.

[0084] The overall energy of the flicker signal can also be evaluated by calculating the integral value of the signal envelope during the flicker event, and then the amplitude can be calculated.

[0085] Based on the occurrence time and end time of the flicker signal and the S-transform result, the amplitude of the flicker signal can be accurately calculated. This provides a quantitative index for evaluating the severity of flicker events, helping to better understand the impact of power quality problems. Calculating the amplitude of the flicker signal helps identify the specific causes of flicker events, such as equipment failures, external interferences, etc. Accurate amplitude information provides a scientific basis for fault diagnosis and the formulation of preventive measures, contributing to improving the operational reliability and stability of the power system. The calculation results of the flicker signal amplitude can be used to optimize the power quality management strategy. For example, the operating parameters of the power system can be adjusted according to the amplitude size, and appropriate compensation measures can be taken to reduce the occurrence frequency and intensity of flicker events.

[0086] The automatic calculation of the flicker signal amplitude can also be achieved through programming. Set a threshold in the monitoring system, and when the amplitude exceeds the set value, an alarm is automatically triggered. This helps to promptly detect and handle power quality problems and improve the intelligence level of the monitoring system.

[0087] In summary, step 400 calculates the amplitude of the flicker signal based on the occurrence time, end time, and S-transform result of the flicker signal, achieving the precise evaluation and management of flicker events, and significantly improving the accuracy and reliability of power quality monitoring.

[0088] According to the power quality monitoring method based on an intelligent flexible control terminal provided by the first aspect of the present application, first, the intelligent flexible control terminal is controlled to execute a meter reading task, and real-time power quality data of each measurement point in the power grid system is read based on the meter reading task ID. Among them, the power quality data at least includes voltage. In this step, by controlling the intelligent flexible control terminal to execute the meter reading task, power quality data can be flexibly and efficiently collected from multiple measurement points in real time. This method not only improves the flexibility and real-time performance of data collection, but also ensures the integrity and accuracy of the data, providing a reliable basis for subsequent data analysis and power quality assessment; The second step is to extract the synchronous voltage signal from the collected voltage signal using the maximum similarity algorithm, and multiply the synchronous voltage signals to extract the signal envelope. The maximum similarity algorithm can effectively extract the synchronous voltage signal from complex voltage signals. By multiplying the synchronous voltage signals to extract the signal envelope, the change trend and characteristics of the voltage signal can be more clearly displayed. This step helps to remove noise and interference, improve the accuracy of signal processing, and provide high-quality data support for subsequent flicker signal analysis; Then, the MATLAB tool is used to perform simulation analysis on the signal envelope containing voltage fluctuation and flicker signals, and the S transform is used to process the flicker signals to analyze the high-frequency characteristic curve of the flicker signals, so as to obtain the occurrence time and end time of the flicker signals and generate the S transform result. Using the MATLAB tool for simulation analysis and combining the S transform technology can accurately identify and analyze the high-frequency characteristics of voltage fluctuation and flicker signals. The S transform can provide detailed information in the time-frequency domain, helping to determine the occurrence and end time of the flicker signals, thereby realizing the precise positioning and quantification of flicker events. This process not only improves the accuracy of analysis, but also provides a scientific basis for subsequent fault diagnosis and preventive measures. Finally, based on the occurrence time, end time, and S transform result of the flicker signal, the amplitude of the flicker signal is calculated. Through comprehensive analysis of the occurrence time, end time, and S transform result of the flicker signal, the amplitude of the flicker signal can be accurately calculated. This step not only provides a quantitative evaluation index, but also helps technicians better understand the severity of flicker events, providing data support for formulating reasonable power quality improvement measures. In summary, the power quality monitoring method based on an intelligent flexible control terminal provided by the first aspect of the present application improves the flexibility, real-time performance, and accuracy of data collection and processing, provides strong technical support for the efficient monitoring and management of power quality problems, and significantly improves the operation reliability and stability of the power system.

[0089] In some embodiments of the present application, controlling the intelligent flexible control terminal to execute a meter reading task and reading real-time power quality data of each measurement point in the power grid system based on the meter reading task ID, where the power quality data at least includes voltage, specifically:

[0090] Define the meter reading frequency parameter, measurement point sequence, and meter reading data type for the meter reading task;

[0091] At the preset meter reading time point, control the intelligent flexible regulation terminal to send a meter reading request instruction to the target measurement point and receive the corresponding power quality data returned by the target measurement point;

[0092] Associate the power quality data with the meter reading task ID to achieve traceability of the meter reading task for the power quality data.

[0093] Specifically, the meter reading frequency parameter is to determine the execution frequency of the meter reading task, such as once per minute, per hour, or per day. The selection of the meter reading frequency should be determined according to actual needs and system performance. The measurement point sequence is a list of measurement points specified for meter reading, and each measurement point has a unique identifier. The measurement point sequence can be sorted according to geographical location, importance, or other criteria. The meter reading data type is to define the type of power quality data to be collected, including at least voltage, and can also include other parameters such as current, power factor, harmonic content, etc.

[0094] The specific execution steps for sending the meter reading request instruction are as follows:

[0095] Preset meter reading time point: According to the meter reading frequency parameter, preset the execution time point of the meter reading task in advance. These time points can be fixed or dynamically adjusted.

[0096] Control the intelligent flexible regulation terminal: At the preset meter reading time point, control the intelligent flexible regulation terminal to send a meter reading request instruction to the target measurement point. The meter reading request instruction contains information such as the task ID, measurement point identifier, and required data type.

[0097] Receive the power quality data:

[0098] Receive the returned data: After receiving the meter reading request instruction, the target measurement point collects the corresponding power quality data and returns it to the intelligent flexible regulation terminal.

[0099] Data verification: The terminal verifies the received data to ensure the integrity and accuracy of the data. If necessary, the request can be resent to obtain the correct data.

[0100] After the meter reading task is completed, associate the received power quality data with the meter reading task ID to ensure that each piece of data can be traced back to the specific meter reading task. The associated data can also be stored in the database for subsequent analysis and management. When storing the data, key information such as the meter reading time, measurement point identifier, and data type should be included.

[0101] By defining the meter reading frequency parameter, the execution frequency of the meter reading task can be flexibly adjusted according to actual needs to ensure the timeliness and effectiveness of data. Defining the measurement point sequence allows for the simultaneous management of data acquisition tasks for multiple measurement points, improving the efficiency and coverage of data acquisition. After receiving the data, perform verification to ensure the integrity and accuracy of the data. This helps reduce data errors and losses and improves the reliability of the overall monitoring system. Associate the power quality data with the meter reading task ID to ensure that each piece of data can be traced back to a specific meter reading task, facilitating data management and analysis.

[0102] In addition, by defining the parameters of the meter reading task, multiple meter reading tasks can be centrally managed to achieve automated scheduling and execution of tasks. This not only improves work efficiency but also reduces errors caused by human intervention. The meter reading frequency and measurement points can also be dynamically adjusted according to actual situations to flexibly respond to different monitoring requirements and emergencies.

[0103] In the embodiments of the present application, in addition to voltage data, other types of power quality data can also be collected to provide more comprehensive data support. These data help comprehensively evaluate the power quality and discover potential problems and abnormalities.

[0104] Store the associated data in a database for subsequent analysis and management. When storing the data, key information such as the meter reading time, measurement point identifier, and data type should be included to support the long-term monitoring of power quality and historical data analysis.

[0105] Furthermore, the automatic execution of the meter reading task can be achieved through programming. Set thresholds in the monitoring system, and when the power quality data exceeds the set range, an alarm is automatically triggered. This helps to promptly discover and handle power quality problems and improve the intelligence level of the monitoring system. The stored data can be used for further data analysis and modeling to help discover the long-term trends and periodic changes in power quality and provide a scientific basis for optimizing the operation of the power system.

[0106] In summary, by defining the parameters of the meter reading task, sending the meter reading request instruction, receiving the power quality data, and associating the data with the meter reading task ID, the efficient and accurate acquisition and management of power quality data can be realized, significantly improving the flexibility, timeliness, and reliability of power quality monitoring.

[0107] In some embodiments of the present application, the maximum similarity algorithm is used to extract the synchronous voltage signal from the collected voltage signal, and the synchronous voltage signals are multiplied to extract the signal envelope. Specifically:

[0108] Select one of the voltage signals as the reference signal;

[0109] Calculate the cross-correlation function R between the voltage signal and the reference signalxy (τ) to obtain the time delay τ corresponding to the maximum value, and the cross-correlation function R xy (τ) formula is:

[0110]

[0111] where x(t) is the voltage signal, y(t) is the reference signal, N is the length of the signal, and τ is the time delay.

[0112] Specifically, select one of the collected voltage signals as the reference signal. Usually, select the voltage signal with better signal quality and less noise as the reference signal. If a suitable reference signal cannot be directly selected from the collected signals, a sine wave synchronized with the power grid fundamental frequency (50Hz or 60Hz) can be generated as the reference signal.

[0113] Through cross-correlation function calculation, the time delay between the voltage signal and the reference signal can be accurately found, thereby extracting the synchronous voltage signal. Compared with the traditional filtering method, this method can more accurately retain the main features of the signal and improve the accuracy of signal processing. The cross-correlation function can effectively remove noise and interference and retain the main signal components, making the extracted synchronous voltage signal purer. By multiplying the signals and low-pass filtering, a clear signal envelope can be obtained. The envelope can intuitively show the amplitude change trend of the voltage signal, which helps to further analyze phenomena such as voltage fluctuations and flickers. The signal envelope reflects the high-frequency characteristics of the signal and helps to identify and analyze the fast-changing characteristics of flicker events.

[0114] Both the cross-correlation function and low-pass filtering are mature signal processing technologies and can be efficiently implemented in tools such as MATLAB. This not only improves the processing efficiency but also reduces the consumption of computing resources. The entire process can be automated through programming, reducing manual intervention and improving the reliability and consistency of data processing.

[0115] In addition, the synchronous voltage signal and the signal envelope are important parameters for evaluating power quality. Through these parameters, power quality problems such as voltage fluctuations and flickers can be more accurately identified and quantified. The accurate signal characteristics provide a scientific basis for fault diagnosis and the formulation of preventive measures, which helps to improve the operation reliability and safety of the power system.

[0116] In some embodiments of the present application, the maximum similarity algorithm is used to extract the synchronous voltage signal from the collected voltage signals, and the synchronous voltage signals are multiplied to extract the signal envelope, and further includes:

[0117] Align the collected voltage signals according to the time delay τ to obtain the synchronous voltage signal x sync (t);

[0118] Based on the synchronous voltage signal x sync (t), generate a delayed version of the synchronous voltage signal x sync (t - τ), multiply the synchronous voltage signal x sync (t) by the delayed version of the synchronous voltage signal x sync (t - τ) to obtain the product signal z(t) = x sync (t) · x sync (t - τ);

[0119] Perform smoothing processing on the product signal z(t) to generate the signal envelope E(t).

[0120] Specifically, the signal envelope E(t) = LPF(z(t)), where LPF represents a low-pass filter. Through signal multiplication and low-pass filtering, a clear signal envelope can be obtained. The envelope can intuitively display the amplitude change trend of the voltage signal, which helps to further analyze phenomena such as voltage fluctuations and flicker. The signal envelope reflects the high-frequency characteristics of the signal and helps to identify and analyze the fast-changing characteristics of flicker events.

[0121] In some embodiments of the present application, the high-frequency characteristic curves include the instantaneous frequency curve and the power spectral density curve, and the S-transform results include the time-frequency distribution diagram, the instantaneous frequency response diagram, the localization information diagram, and the multi-resolution analysis diagram.

[0122] The instantaneous frequency curve describes the frequency change of the signal at a certain moment. For the voltage flicker signal, the instantaneous frequency curve can reflect the fast-changing characteristics of the flicker event. Through the time-frequency distribution diagram obtained by the S-transform, the frequency components at each moment can be extracted, and then the instantaneous frequency curve can be generated. The instantaneous frequency curve helps to identify the occurrence time and frequency change trend of the flicker event, providing important information for fault diagnosis and cause analysis.

[0123] The power spectral density (PSD) curve describes the power distribution of the signal at different frequencies. For the voltage flicker signal, the PSD curve can reflect the energy distribution of different frequency components. Through Fourier transform or S-transform, the power spectral density of the signal can be calculated. The advantage of the S-transform is that it can provide the power spectral density information in the time-frequency domain. The PSD curve helps to identify the main frequency components and their energy distribution of the flicker signal, providing an important basis for power quality assessment and fault location.

[0124] The time-frequency distribution diagram shows the frequency component distribution of the signal at different time points. Through the time-frequency distribution diagram generated by the S-transform, the time-frequency characteristics of the signal can be intuitively seen. The time-frequency distribution diagram helps to identify the occurrence time and frequency change trend of the flicker event, providing support for the real-time monitoring and analysis of power quality.

[0125] The instantaneous frequency response diagram shows the frequency response of the signal at each moment. The instantaneous frequency response diagram generated by the S-transform can be used to observe the instantaneous frequency variation of the signal in detail. The instantaneous frequency response diagram helps to identify the instantaneous frequency variation characteristics of flicker events and provides detailed information for fault diagnosis and cause analysis.

[0126] The localization information diagram shows the localization information of the signal in the time-frequency domain, that is, the intensity distribution of the signal at a certain time point and frequency point. The localization information diagram helps to identify the local characteristics of the signal. Especially in the case of multiple frequency components, it can clearly show the localization information of each frequency component.

[0127] The multi-resolution analysis diagram shows the time-frequency characteristics of the signal at different resolutions. The multi-resolution analysis diagram generated by the S-transform can be used to observe the variation of the signal at different scales. The multi-resolution analysis diagram helps to identify the multi-scale characteristics of the signal. Especially when analyzing complex signals, it can provide more comprehensive time-frequency information.

[0128] In summary, by generating high-frequency characteristic curves (instantaneous frequency curve and power spectral density curve) and S-transform results (time-frequency distribution diagram, instantaneous frequency response diagram, localization information diagram and multi-resolution analysis diagram), the accurate analysis and evaluation of voltage flicker signals can be realized, significantly improving the accuracy and reliability of power quality monitoring. This method provides strong technical support for the optimal operation and fault diagnosis of power systems.

[0129] In some embodiments of the present application, based on the occurrence time, end time of the flicker signal and the S-transform result, the amplitude of the flicker signal is calculated as follows:

[0130] Based on the occurrence time, end time of the flicker signal and the S-transform result, the flicker signal time period is extracted from the original voltage signal;

[0131] Calculate the difference between the maximum value and the minimum value of the signal within the flicker signal time period to generate the amplitude of the flicker signal, or calculate the root mean square value of the signal within the flicker signal time period to generate the amplitude of the flicker signal, or extract the envelope of the signal within the flicker signal time period and calculate the difference between the maximum value and the minimum value of the envelope to generate the amplitude of the flicker signal.

[0132] The amplitudes of the flicker signals can be calculated by three different methods, which can verify and complement each other to improve the accuracy of the calculation results. The difference between the maximum and minimum values, the root mean square value, and the difference between the maximum and minimum values of the envelope respectively evaluate the intensity of the flicker signal from different perspectives, providing a comprehensive basis for power quality assessment. By calculating the amplitude of the flicker signal, the severity of the flicker event can be accurately identified, providing important information for fault diagnosis and cause analysis. Accurate amplitude information provides a scientific basis for formulating fault diagnosis and preventive measures, helping to improve the operation reliability and safety of the power system.

[0133] Calculating the amplitudes of the flicker signals by different methods provides multi-dimensional information, which helps to comprehensively evaluate the power quality and discover potential problems and anomalies. The calculated amplitudes can generate detailed analysis reports, recording the time, amplitude, and other relevant information of the flicker events, providing support for long-term monitoring and historical data analysis of power quality.

[0134] In summary, by extracting the flicker signal time period from the original voltage signal based on the occurrence time, end time, and S-transform result of the flicker signal, and calculating the amplitude of the flicker signal, the accurate evaluation and management of the flicker event can be realized, significantly improving the accuracy and reliability of power quality monitoring. This method provides strong technical support for the optimal operation and fault diagnosis of the power system.

[0135] In some embodiments of the present application, the power quality data further includes current, frequency, harmonics, power factor, and transients. By expanding the monitoring scope of the power quality data to include not only voltage but also parameters such as current, frequency, harmonics, power factor, and transients, a comprehensive and accurate evaluation of the power quality can be achieved, significantly improving the operation reliability and safety of the power system. This method provides strong technical support for the optimal operation and fault diagnosis of the power system.

[0136] In some embodiments of the present application, the method further includes:

[0137] Setting a threshold for the amplitude of the flicker signal and comparing the calculated amplitude of the flicker signal with the set threshold for the amplitude of the flicker signal;

[0138] If the calculated amplitude of the flicker signal exceeds the set threshold for the amplitude of the flicker signal, an alarm is triggered.

[0139] According to the standards and actual requirements of the power system, set the threshold for the amplitude of the flicker signal. The setting of the threshold should consider the tolerance of the equipment and the standards of power quality. Store the set threshold for the amplitude of the flicker signal in the system configuration for subsequent comparison and alarm triggering.

[0140] By setting the flicker signal amplitude threshold and triggering an alarm, the timely detection and handling of power quality problems can be achieved, significantly improving the operation reliability and safety of the power system. This method provides strong technical support for the optimal operation and fault diagnosis of the power system.

[0141] As Figure 2 shown, an embodiment of the second aspect of the present application provides a power quality monitoring device based on an intelligent flexible control terminal, including:

[0142] A power quality data reading module 110, adapted to control the intelligent flexible control terminal to execute a meter reading task and read the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID, where the power quality data at least includes voltage;

[0143] A first calculation module 120, adapted to extract a synchronous voltage signal from the collected voltage signals using the maximum similarity algorithm and multiply the synchronous voltage signals to extract the signal envelope;

[0144] A second calculation module 130, adapted to perform simulation analysis on the signal envelope containing voltage fluctuation and flicker signals using MATLAB tools, process the flicker signals using the S transform, analyze the high-frequency characteristic curve of the flicker signals to obtain the occurrence time and end time of the flicker signals, and generate the S transform result;

[0145] A third calculation module 140, adapted to calculate the flicker signal amplitude based on the occurrence time, end time of the flicker signals and the S transform result.

[0146] The power quality monitoring device based on the intelligent flexible control terminal provided by the embodiment of the second aspect of the present application can implement the power quality monitoring method based on the intelligent flexible control terminal in any of the above-mentioned first aspect embodiments, and thus can achieve any of the technical effects in the above-mentioned power quality monitoring method based on the intelligent flexible control terminal, which will not be elaborated here.

[0147] As Figure 3 shown, an embodiment of the third aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the power quality monitoring method based on the intelligent flexible control terminal in any of the above-mentioned embodiments when executing the program.

[0148] Figure 3 Illustrates a schematic physical structure diagram of an electronic device, as Figure 3As shown in the figure, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840. Among them, the processor 810, the communication interface 820, and the memory 830 complete communication with each other through the communication bus 840. The processor 810 may call the logical instructions in the memory 830 to execute the power quality monitoring method based on the intelligent flexible control terminal in any of the above embodiments. The method may specifically include:

[0149] Step 100: Control the intelligent flexible control terminal to execute a meter reading task, and read the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID. Among them, the power quality data at least includes voltage.

[0150] Step 200: Extract the synchronous voltage signal from the collected voltage signals by using the maximum similarity algorithm, and multiply the synchronous voltage signals to extract the signal envelope.

[0151] Step 300: Use the MATLAB tool to perform simulation analysis on the signal envelope containing voltage fluctuation and flicker signals, process the flicker signals by using the S transform, analyze the high-frequency characteristic curve of the flicker signals to obtain the occurrence time and end time of the flicker signals, and generate the S transform result.

[0152] Step 400: Calculate the amplitude of the flicker signal based on the occurrence time, end time, and S transform result of the flicker signal.

[0153] In addition, when the logical instructions in the above-mentioned memory 830 are implemented in the form of software function units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, may be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0154] What is not described in this application can be realized by adopting or referring to the existing technologies.

[0155] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

[0156] The above description is only for the embodiments of the present application and is not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A power quality monitoring method based on an intelligent flexible control terminal, characterized in that Including: Controlling the intelligent flexible regulation terminal to execute a meter reading task, and reading the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID, wherein the power quality data at least includes voltage; Extracting a synchronous voltage signal from the collected voltage signals by using the maximum similarity algorithm, and multiplying the synchronous voltage signals to extract a signal envelope; Performing a simulation analysis on the signal envelope containing voltage fluctuation and flicker signals by using MATLAB tools, processing the flicker signals by using the S transform, analyzing the high-frequency characteristic curve of the flicker signals to obtain the occurrence time and end time of the flicker signals, and generating an S transform result; Calculating the amplitude of the flicker signal based on the occurrence time, the end time and the S transform result of the flicker signal.

2. The power quality monitoring method based on an intelligent flexible control terminal according to claim 1, wherein The controlling the intelligent flexible regulation terminal to execute a meter reading task, and reading the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID, wherein the power quality data at least includes voltage, specifically: Defining the meter reading frequency parameter, the measurement point sequence and the meter reading data type of the meter reading task; At a preset meter reading time point, controlling the intelligent flexible regulation terminal to send a meter reading request instruction to a target measurement point, and receiving the corresponding power quality data returned by the target measurement point; Associating the power quality data with the meter reading task ID to realize the traceability of the meter reading task of the power quality data.

3. The power quality monitoring method based on an intelligent flexible control terminal according to claim 1, characterized in that The extracting a synchronous voltage signal from the collected voltage signals by using the maximum similarity algorithm, and multiplying the synchronous voltage signals to extract a signal envelope, specifically: Selecting one of the voltage signals as a reference signal; Calculate the cross-correlation function R between the voltage signal and the reference signal xy (τ) to obtain the time delay τ corresponding to the maximum value. The formula for the cross-correlation function R xy (τ) is as follows: Wherein, x(t) is the voltage signal, y(t) is the reference signal, N is the length of the signal, and τ is the time delay.

4. The power quality monitoring method based on an intelligent flexible control terminal according to claim 3, characterized in that The extracting a synchronous voltage signal from the collected voltage signals by using the maximum similarity algorithm, and multiplying the synchronous voltage signals to extract a signal envelope further includes: Align the collected voltage signal according to the time delay τ to obtain a synchronized voltage signal x sync (t); Based on the synchronous voltage signal x sync (t), generate a delayed version of the synchronous voltage signal x sync (t - τ), multiply the synchronous voltage signal x sync (t) by the delayed version of the synchronous voltage signal x sync (t - τ) to obtain a product signal z(t) = x sync (t) · x sync (t - τ); Performing smoothing processing on the product signal z(t) to generate a signal envelope E(t).

5. The power quality monitoring method based on an intelligent flexible control terminal according to any one of claims 1 to 4, characterized in that, The high-frequency characteristic curve includes an instantaneous frequency curve and a power spectral density curve, and the S transform result includes a time-frequency distribution diagram, an instantaneous frequency response diagram, a localization information diagram and a multi-resolution analysis diagram.

6. The power quality monitoring method based on an intelligent flexible control terminal according to claim 5, wherein, The calculating the amplitude of the flicker signal based on the occurrence time, the end time and the S transform result of the flicker signal, specifically: Extracting a flicker signal time period from the original voltage signal based on the occurrence time, the end time and the S transform result of the flicker signal; Calculating the difference between the maximum value and the minimum value of the signal within the flicker signal time period to generate the amplitude of the flicker signal, or calculating the root mean square value of the signal within the flicker signal time period to generate the amplitude of the flicker signal, or extracting the signal envelope within the flicker signal time period and calculating the difference between the maximum value and the minimum value of the envelope to generate the amplitude of the flicker signal.

7. The power quality monitoring method based on an intelligent flexible control terminal according to claim 1, wherein The power quality data further includes current, frequency, harmonic, power factor and transient.

8. The power quality monitoring method based on an intelligent flexible control terminal according to claim 1, wherein The method further includes: Set the flicker signal amplitude threshold and compare the calculated flicker signal amplitude with the set flicker signal amplitude threshold; If the calculated flicker signal amplitude exceeds the set flicker signal amplitude threshold, an alarm is triggered.

9. A power quality monitoring device based on an intelligent flexible control terminal, characterized in that, It includes: A power quality data reading module, suitable for controlling the intelligent flexible regulation terminal to execute the meter reading task and reading the real-time power quality data of each measurement point in the power grid system based on the meter reading task ID. Among them, the power quality data at least includes voltage; A first calculation module, suitable for extracting the synchronous voltage signal from the collected voltage signal by using the maximum similarity algorithm and multiplying the synchronous voltage signals to extract the signal envelope; A second calculation module, suitable for performing simulation analysis on the signal envelope containing voltage fluctuation and flicker signals by using MATLAB tools, processing the flicker signals by using the S transform, analyzing the high-frequency characteristic curve of the flicker signals to obtain the occurrence time and end time of the flicker signals, and generating the S transform result; A third calculation module, suitable for calculating the flicker signal amplitude based on the occurrence time, the end time and the S transform result of the flicker signal.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the power quality monitoring method based on the intelligent flexible regulation terminal as described in any one of claims 1 to 8.

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