Current-driven dielectric loss and electric energy quality joint detection system

Abstract

The invention discloses a current-driven dielectric loss and electric energy quality joint detection system, which relates to the technical field of electric power systems and comprises a voltage and current acquisition module, a harmonic analysis module, a voltage and current detection module, a voltage and current detection module, a voltage and current detection module, a voltage and current detection module and a voltage and current detection module, and the voltage and current detection module is used for real-time acquisition of voltage and current signals from a to-be-detected circuit and extraction of time domain and frequency domain characteristics. The harmonic analysis module is used for carrying out harmonic analysis on a nonlinear load based on extracted voltage and current signal characteristics and identifying various harmonic components, the electric energy quality evaluation module is used for constructing an electric energy quality evaluation model according to a harmonic analysis result and quantifying an energy efficiency index of the nonlinear load, and the report generation module is used for generating a report. The analysis module outputs a final analysis report according to the power quality evaluation result; according to the current-driven dielectric loss and electric energy quality joint detection system, full-process automation from data acquisition to harmonic analysis, problem evaluation to optimization suggestion generation can be realized, and the precision, efficiency and stability of monitoring and optimization of an electric power system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and particularly to a current-driven combined detection system for dielectric loss and power quality. Background Art

[0002] With the increasing dependence of modern society on electric energy, various electrical devices, especially non-linear loads (such as household appliances, industrial equipment, computer systems, etc.), play an important role in daily life and production. However, non-linear loads usually generate a large amount of harmonics during operation, which not only has an adverse impact on the operation of the power system, but also may lead to power quality problems, thus affecting the normal operation of power equipment and energy utilization efficiency. Therefore, how to accurately monitor and evaluate the energy efficiency and power quality of non-linear loads has become an important problem to be solved urgently in the power system.

[0003] Currently, traditional power quality detection methods mainly rely on single power monitoring technologies, such as the measurement of voltage, current, and power factor. These methods usually can only provide limited power quality information, and there are certain limitations in the extraction and analysis of characteristics such as the true energy consumption level and harmonic components under non-linear loads. In addition, most of the existing monitoring systems cannot analyze the load characteristics in real time and dynamically, and also lack sufficient intelligent identification and classification capabilities, and cannot make accurate judgments in a short time. Therefore, the existing power quality detection and energy efficiency evaluation methods have many deficiencies in practical applications and cannot meet the requirements of efficient, intelligent, and accurate monitoring. To solve the above problems, in recent years, many scholars and engineers have proposed various power quality monitoring technologies, including methods based on digital signal processing and machine learning, but these methods still face problems such as poor real-time performance and poor adaptability. In addition, although there are some current-driven detection systems that can provide certain non-linear load analysis, they lack an effective intelligent identification and classification mechanism, resulting in these systems being unable to achieve the expected performance when dealing with complex load types. Summary of the Invention

[0004] The purpose of the present invention is to provide a current-driven combined detection system for dielectric loss and power quality to solve the problems in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A current-driven combined detection system for dielectric loss and power quality, the system includes: A voltage and current acquisition module, which is used to collect voltage and current signals from the circuit to be measured in real time and extract the time-domain and frequency-domain characteristics thereof; A harmonic analysis module connected to the voltage and current acquisition module, which is used to perform harmonic analysis of non-linear loads based on the extracted voltage and current signal characteristics, identify various harmonic components, including converting the actual harmonic intensity into the perceived impact intensity on the power system, and quantifying the degree of influence of the power system on harmonics. The specific formula is: A = m × log(B); Among them, A represents the perceived impact intensity of a certain harmonic on the power system, m represents the perceived sensitivity coefficient of the harmonic intensity, B represents the actual intensity of the collected harmonic component, and log represents the logarithmic operation; Using the perceived impact intensity of harmonics on the power system as the classification basis, classify the harmonics, analyze the harmonic influence range, and output the harmonic perception result; A power quality assessment module connected to the harmonic analysis module, which is used to construct a power quality assessment model based on the harmonic analysis results, and quantify the energy efficiency index of non-linear loads, including defining the influence degree of different power quality problems according to the harmonic analysis results, and calculating the weight of each problem. The specific formula is: ; Among them, D i represents the i-th power quality problem, E i represents the actual influence degree of the i-th power quality problem on the system operation, n represents the total number of power quality problems, and i represents the number of the power quality problem; Sort according to the weight, quantify the energy efficiency index of the non-linear load, and evaluate the power quality problems in descending order of weight; A report generation module connected to the power quality assessment module, which is used to output a final analysis report according to the power quality assessment result.

[0006] Preferably, the voltage and current acquisition module collects voltage and current signals from the circuit under test in real time, and extracts their time-domain and frequency-domain characteristics, including: Collect voltage and current signals from the circuit under test in real time, define the sampling sensitivity and signal intensity, preset an acquisition accuracy threshold, and calculate the signal acquisition completion degree. The specific formula is: ; Among them, α represents the signal acquisition completion degree, b represents the acquisition sensitivity coefficient, and G represents the signal intensity collected from the circuit under test; Judge whether the preset acquisition accuracy threshold is reached. If it exceeds the threshold, end the current acquisition process. If not, dynamically adjust the acquisition sensitivity coefficient to optimize the acquisition process.

[0007] Preferably, the report generation module outputs a final analysis report according to the power quality assessment result, including modeling the weight distribution of the power quality assessment module, and calculating the complexity degree of the optimization suggestions proposed for the power quality problems. The specific formula is: ; Among them, g represents the complexity degree of the optimization suggestions proposed for power quality problems, z represents the influence of the optimization suggestions on power quality improvement, x represents the number of optimization suggestions proposed, and cosh represents the hyperbolic cosine function; Generate a comprehensive report.

[0008] Preferably, the report generation module outputs a final analysis report according to the power quality assessment results. The generated comprehensive report includes a power quality problem weight distribution diagram, a power quality assessment result analysis diagram, and an optimization suggestion complexity priority diagram.

[0009] Preferably, the voltage and current acquisition module includes a signal filter for filtering out noise signals and a signal amplifier for amplifying the acquired signals.

[0010] Preferably, the harmonic analysis module further includes a harmonic classification unit for identifying specific harmonic frequencies and classifying them.

[0011] Preferably, the report generation module includes a data visualization unit for generating a power quality problem weight distribution diagram, a harmonic impact assessment diagram, and an optimization suggestion priority chart.

[0012] Preferably, the voltage and current acquisition module uses a high-speed sampling chip to improve the capture ability of rapidly changing signals.

[0013] Preferably, the voltage and current acquisition module is connected to an external data storage unit to record and store the signal data collected in real time.

[0014] Preferably, the comprehensive report in the final analysis report output by the report generation module according to the power quality assessment results supports an export function to generate an electronic report file in a standard format, which is convenient for users to archive and share.

[0015] As can be seen from the above technical solutions, the present invention has the following beneficial effects: The current-driven joint detection system for dielectric loss and power quality collects voltage and current signals from the circuit under test in real time through the voltage and current acquisition module, and extracts the time-domain and frequency-domain characteristics thereof. The harmonic analysis module performs harmonic analysis of nonlinear loads based on the extracted voltage and current signal characteristics to identify various harmonic components. The power quality evaluation module constructs a power quality evaluation model according to the harmonic analysis results to quantify the energy efficiency index of the nonlinear load. The report generation module is used to output the final analysis report according to the power quality evaluation results, realizing the collection of real-time voltage and current signals of the nonlinear load. Combined with the harmonic analysis module, it can accurately extract the time-domain and frequency-domain characteristics of the load, effectively solving the problem that the traditional method cannot analyze the load characteristics in real time and dynamically. It can perform refined analysis on the harmonics generated by the nonlinear load, identify various harmonic components and quantify their impact on the power system, significantly improving the accuracy of harmonic component extraction and evaluation. It can intelligently classify the characteristics of nonlinear loads, dynamically update the power quality evaluation model, overcoming the problem of lack of intelligent identification mechanism in the traditional method, realizing accurate classification and evaluation of complex load types. It can efficiently quantify the impact degree of power quality problems, generate targeted optimization suggestions according to the priority ranking, shortening the response time of power quality evaluation and optimization. It can adapt to the operating conditions of different nonlinear loads and power systems, effectively solving the problem of poor adaptability in the prior art, providing intuitive optimization guidance for users, improving the energy utilization efficiency and stability of the power system. It can realize the full-process automation from data collection to harmonic analysis, problem evaluation to optimization suggestion generation, improving the accuracy, efficiency and stability of power system monitoring and optimization, and significantly improving the impact of power quality problems on equipment operation. Description of the Drawings

[0016] Figure 1 It is a schematic diagram of the connection of the system modules of the present invention. Detailed Embodiments

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the 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 of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] As Figure 1 shown, the present invention provides a technical solution: a current-driven joint detection system for dielectric loss and power quality, the system includes: A voltage and current acquisition module for collecting voltage and current signals from the circuit under test in real time and extracting the time-domain and frequency-domain characteristics thereof; A harmonic analysis module connected to the voltage and current acquisition module is used to perform harmonic analysis of nonlinear loads based on the extracted voltage and current signal characteristics, identify various harmonic components, including converting the actual harmonic intensity into the perceived impact intensity on the power system and quantifying the degree of influence of the power system on harmonics. The specific formula is: A = m × log(B); Among them, A represents the perceived impact intensity of a certain harmonic on the power system, m represents the perceived sensitivity coefficient of the harmonic intensity, B represents the actual intensity of the collected harmonic component, and log represents the logarithmic operation; Taking the perceived impact intensity of harmonics on the power system as the classification basis, classify the harmonics, analyze the harmonic influence range, and output the harmonic perception result; A power quality assessment module connected to the harmonic analysis module is used to construct a power quality assessment model according to the harmonic analysis results and quantify the energy efficiency indicators of nonlinear loads, including defining the influence degree of different power quality problems according to the harmonic analysis results and calculating the weight of each problem. The specific formula is: ; Among them, D i represents the i-th power quality problem, E i represents the actual impact degree of the i-th power quality problem on the system operation, n represents the total number of power quality problems, and i represents the number of the power quality problem; Sort according to the weight, quantify the energy efficiency indicators of the nonlinear load, and evaluate the power quality problems in descending order of weight; A report generation module connected to the power quality assessment module is used to output a final analysis report according to the power quality assessment results.

[0019] This system collects voltage and current signals in the circuit under test in real time through the voltage and current acquisition module, and extracts time-domain and frequency-domain features of the collected signals to ensure the integrity and accuracy of signal data. The extracted signal features are transmitted to the harmonic analysis module. Using the harmonic analysis technology of nonlinear loads, various harmonic components in the signal are identified, and the actual harmonic intensity is calculated. In order to quantify the impact of these harmonics on the power system, a calculation model for perceiving the impact intensity is adopted. Combining the perception sensitivity coefficient and the actual intensity, the perception impact value of each harmonic is determined. Subsequently, the harmonic analysis module uses the calculated perception impact intensity as the classification basis to classify and grade the harmonics, and outputs the harmonic impact analysis results. The power quality assessment module constructs a comprehensive power quality assessment model based on the harmonic analysis results, quantifies and calculates the weights of different power quality problems, clarifies the actual impact degree and ranking of each problem through a mathematical model, and finally outputs an analysis report through the report generation module, providing users with comprehensive power quality assessment and optimization suggestions. Through the efficient cooperation and data sharing among modules, the system realizes the comprehensive, accurate and efficient detection of the impact of nonlinear loads in the circuit, providing data support for the operation optimization of the power system. The present invention realizes the full-process automatic analysis from voltage and current signal acquisition to the generation of power quality assessment reports by introducing modular design, greatly improving the efficiency of detection and analysis. The harmonic analysis technology of nonlinear loads enables the system to accurately identify various harmonic components, and through the quantization model of perception impact intensity, effectively presents the impact degree of harmonics on the power system, improving the analytical ability of nonlinear interference. The power quality assessment module adopts a scientific weight calculation method to establish a quantitative evaluation system for various power quality problems, making the evaluation results more intuitive, objective and easy to understand. The report generation module not only supports the output form with pictures and texts, but also can be customized according to user needs, significantly improving the practicality of the results and the user experience. Generally speaking, the present invention not only improves the accuracy and efficiency of power quality detection, but also reduces the complexity of manual analysis, provides strong support for the stable operation and energy-saving optimization of the power system, and can be extended to the monitoring and evaluation of smart grids and distributed energy systems, having important engineering value and economic benefits.

[0020] Regarding dielectric loss, in the power system, it generally refers to the energy loss caused by polarization, conduction or other energy conversion mechanisms of dielectrics under the action of an alternating electric field. This loss is manifested as the conversion of electrical energy into heat energy and is one of the important parameters for evaluating the performance of insulating materials in the power system.

[0021] Relationship between the voltage and current acquisition module and dielectric loss: This module collects voltage and current signals in real time and extracts time-domain and frequency-domain features. In the time domain, dielectric loss is manifested as an increase in the phase lag between voltage and current. In the frequency domain, dielectric loss causes attenuation of high-frequency components or an increase in energy loss at specific frequency points. By collecting and extracting the features of voltage and current signals, the system can capture signal distortion, attenuation, or phase changes caused by dielectric loss. This provides data support for subsequent harmonic analysis and loss assessment.

[0022] Based on the extracted features of voltage and current signals, the harmonic analysis module identifies various harmonic components. The impact of dielectric loss on high-frequency harmonics is relatively significant. As the frequency increases, the dielectric loss factor usually rises, which means that the energy of high-frequency harmonic components is more easily dissipated. By precisely analyzing the harmonic components, the dielectric loss characteristics can be indirectly identified. Harmonic analysis can quantify the impact of loss on the power distribution. For example, detecting abnormal losses of specific frequency harmonics can be attributed to changes in the characteristics of the relevant dielectric (such as aging or defects).

[0023] Relationship between the power quality assessment module and dielectric loss. This module constructs a power quality assessment model based on the results of harmonic analysis to quantify the energy efficiency indicators of nonlinear loads. The power loss caused by dielectric loss directly affects the key indicators of power quality, such as a decrease in power factor and an increase in total harmonic distortion rate. Through the power quality assessment model, the system can identify the impact of dielectric loss on the overall power efficiency and quantify the degree of this impact. The power quality assessment model may include parameters related to dielectric loss (such as dielectric loss factor, loss power ratio, etc.), and through model calculation, the comprehensive effect of the dielectric on power quality can be accurately evaluated.

[0024] Dielectric loss analysis in joint detection: The system realizes the full-process automation from data acquisition to harmonic analysis, power quality assessment, and then to the generation of optimization suggestions. The manifestations of dielectric loss include: In data acquisition, the signal characteristics of dielectric loss (phase lag, amplitude attenuation, etc.) are captured through real-time acquisition and feature extraction of voltage and current. In harmonic analysis, the impact of the dielectric on the energy distribution of high-frequency harmonics is revealed through frequency-domain analysis, and the loss characteristics of harmonic components are identified. In power quality assessment, the impact of loss on energy efficiency indicators is quantified to reflect the role of dielectric loss in the overall system performance. The manifestation of dielectric loss in the system focuses on the extraction and analysis of voltage and current signals. By identifying signal features (such as phase lag, frequency attenuation), combined with harmonic analysis and power quality assessment, the impact of dielectric loss can be quantified. This provides strong support for evaluating the dielectric state and optimizing the performance of the power system.

[0025] The voltage and current acquisition module collects voltage and current signals from the circuit under test in real time and extracts their time-domain and frequency-domain features, including: Collect voltage and current signals from the circuit under test in real time, define the sampling sensitivity and signal strength, preset a collection accuracy threshold, and calculate the signal collection completion degree. The specific formula is: ; Among them, α represents the signal collection completion degree, b represents the collection sensitivity coefficient, and G represents the signal strength collected from the circuit under test; Judge whether the preset collection accuracy threshold is reached. If the threshold is exceeded, end the current collection process. If not, dynamically adjust the collection sensitivity coefficient to optimize the collection process.

[0026] The voltage and current collection module of this system dynamically quantifies the collection accuracy and signal completion degree by using a mathematical model through real-time collection of voltage and current signals in the circuit. During the signal collection process, the system first defines the range of the sampling sensitivity coefficient and signal strength, and calculates the signal collection completion degree value. Through the formula , combined with the signal strength G collected in real time and the preset sensitivity coefficient b, dynamically judge whether the collected signal meets the preset accuracy threshold. If the completion degree α reaches or exceeds the threshold, the collection process ends; if not, adjust the collection sensitivity coefficient b to optimize the signal collection process to adapt to different circuit environments, ensuring that the collected signal accurately reflects the state of the circuit under test. Through this method, the system can achieve efficient and accurate signal collection, laying a foundation for subsequent time-domain and frequency-domain feature extraction. The voltage and current collection module described in the present invention realizes accurate collection and efficient analysis of signals by real-time collection and dynamic adjustment of the collection sensitivity. The setting and dynamic optimization mechanism of the collection accuracy threshold avoid resource waste or signal incompleteness problems caused by over-sampling or under-sampling, improving the adaptability and flexibility of the system. Quantifying the signal collection completion degree through a mathematical model further ensures the accuracy and consistency of the collection results. At the same time, the automatic optimization function during the collection process can adapt to a variety of complex circuit environments, enhancing the versatility and robustness of the system, and providing more reliable data support for harmonic analysis and power quality assessment. This system not only simplifies the operation process of signal collection but also reduces the error rate, providing important technical support for intelligent power quality detection and circuit monitoring.

[0027] The report generation module outputs a final analysis report according to the power quality assessment results, including modeling the weight distribution of the power quality assessment module and calculating the complexity degree of the optimization suggestions proposed for power quality problems. The specific formula is: ; Among them, g represents the complexity degree of the optimization suggestions proposed for power quality problems, z represents the influence of the optimization suggestions on power quality improvement, x represents the number of optimization suggestions proposed, and cosh represents the hyperbolic cosine function; Generate a comprehensive report.

[0028] The report generation module in this system is based on the output data of the power quality assessment module. Combining with the weight distribution model of power quality problems, it ranks and quantifies the importance of various problems. Through the mathematical formula , the number of optimization suggestions is associated with their actual influence, and the complexity of each optimization suggestion is quantified. The complexity value of the optimization suggestion not only reflects the difficulty of its implementation but also reflects its potential improvement effect on power quality problems. When generating the comprehensive report, the module presents the complexity of the optimization suggestions in the form of charts or data lists according to the weight distribution, helping users intuitively understand the priority of each optimization suggestion and its impact on the overall system performance. The finally generated report not only includes the weight analysis results of the problems but also provides detailed information and distribution of the optimization suggestions, providing a scientific and data-driven decision-making basis for the adjustment and optimization of the power system. The report generation module of the present invention significantly improves the comprehensiveness and scientificity of the analysis report by constructing the weight distribution of the power quality assessment model and the complexity modeling of the optimization suggestions. The quantification formula of the complexity of the optimization suggestions provides an objective decision-making basis for users, enabling them to quickly judge the priority and implementation difficulty of different optimization schemes, thereby more efficiently allocating resources and formulating improvement plans. The comprehensive analysis report provided by the report generation module not only shows the current situation and priority of power quality problems but also deeply analyzes the potential influence of the optimization suggestions, providing systematic guidance for users. In addition, the flexibility of the report generation module allows users to customize the report content according to specific needs, such as focusing on specific power quality problems or generating real-time dynamic reports, thus enhancing the practicality and user experience of the system.

[0029] The report generation module generates a comprehensive report including a power quality problem weight distribution diagram, a power quality evaluation result analysis diagram, and an optimization suggestion complexity priority diagram in the final analysis report output according to the power quality evaluation results. The report generation module of this system is based on the weight distribution and optimization suggestion complexity data output by the power quality evaluation module, and generates key charts in the comprehensive report through visualization processing technology. First, the power quality problem weight distribution diagram is generated according to the weight distribution results of the power quality problem, which intuitively displays the importance and relative weight of various problems, so that users can quickly identify the problem categories that need to be handled with priority. Secondly, combined with the analysis data of the evaluation module, the power quality evaluation result analysis diagram is generated to display the specific evaluation indicators of various problems, including the frequency of occurrence of problems, the degree of impact, and the historical change trend. Finally, the optimization suggestion complexity priority diagram is generated through the optimization suggestion complexity calculation formula. The diagram presents the complexity and priority ranking of all suggestions in the form of a histogram or radar chart to help users choose the most suitable optimization solution. The entire working principle is based on modular processing and data-driven visualization, which not only improves the professionalism and readability of the report, but also makes the power quality analysis results and optimization suggestions easier to understand and operate. The report generation module of the present invention generates a variety of intuitive chart display forms through comprehensive analysis results, so that users can quickly grasp the overall picture of power quality problems. The power quality problem weight distribution diagram highlights the importance of each problem in a simple and intuitive way, helping users to prioritize key problems; the power quality assessment result analysis diagram decomposes the data into easy-to-interpret indicators, which is convenient for users to conduct detailed analysis of the current status and trends of power quality; the optimization suggestion complexity priority diagram quantifies the difficulty and priority of the optimization suggestions, thereby improving the scientificity and efficiency of user decision-making. In addition, the comprehensive report displays data results in a graphic and textual manner, which not only enhances the professionalism and intuitiveness of the report, but also reduces the difficulty for non-technical users to understand the report content. It is suitable for a variety of scenarios, such as power system operation and maintenance, management decision-making, and energy-saving optimization design.

[0030] The voltage and current acquisition module includes a signal filter for filtering out noise signals and a signal amplifier for amplifying the acquired signals. By integrating the signal filter and the signal amplifier, the voltage and current acquisition module achieves the accuracy of signal processing and high-quality signal transmission. The signal filter is used for the preliminary processing of the acquired voltage and current signals to filter out high-frequency or low-frequency noise signals introduced during the acquisition process, thereby effectively improving the purity of the signals. The filter can adopt various design schemes. For example, a low-pass filter is used to suppress high-frequency noise, or a band-pass filter is used to extract signals in a specific frequency band. The signals processed by the filter are then transmitted to the signal amplifier for amplitude enhancement. The main function of the signal amplifier is to amplify the voltage and current signals to ensure that weak signals have sufficient dynamic range and signal-to-noise ratio in subsequent processing stages. The gain of the amplifier can be adjusted according to specific application requirements to adapt to different circuit environments and detection requirements. Through the synergistic effect of filtering and amplification, the voltage and current acquisition module can provide high-quality signal input for subsequent time-domain and frequency-domain feature extraction, ensuring the accuracy and reliability of the system's analysis results. The present invention significantly improves the accuracy and reliability of signal acquisition by adding a signal filter and a signal amplifier to the voltage and current acquisition module. The signal filter can effectively filter out noise interference during the acquisition process, ensure the purity of signal quality, and reduce the complexity of subsequent data processing. The gain adjustment function of the signal amplifier further ensures the dynamic range and signal-to-noise ratio of the signals, which is particularly suitable for weak signal detection scenarios. In addition, the modular design of filtering and amplification not only improves the adaptability of the acquisition module but also enhances the overall robustness of the system. Generally speaking, the present invention optimizes the signal acquisition process and quality, provides more reliable data support for subsequent analysis and evaluation, and reduces the error rate caused by noise or signal distortion, and is widely applicable to various application scenarios such as power systems, power quality monitoring, and signal processing.

[0031] The harmonic analysis module also includes a harmonic classification unit for identifying specific harmonic frequencies and classifying them. By adding the harmonic classification unit, the harmonic analysis module can further refine the analysis and processing of harmonic signals. First, based on the collected voltage and current signals, the harmonic classification unit analyzes the frequency-domain characteristics, identifies various harmonic components in the signal through spectral decomposition methods (such as the Fast Fourier Transform FFT or wavelet transform), and accurately locates specific harmonic frequencies. The classification unit classifies the identified harmonics according to the set harmonic frequency ranges (such as odd harmonics, even harmonics, or harmonics of a specific order), marks and stores different types of harmonic components separately. The classification results can also be further combined with harmonic intensity information to quantify the impact of each type of harmonic on the power system, providing a reference for subsequent power quality assessment and optimization schemes. In this way, the harmonic classification unit achieves precise classification and refined management of harmonics, providing an efficient solution to the harmonic problems caused by nonlinear loads. The harmonic classification unit of the present invention greatly improves the detection accuracy and refinement degree of the harmonic analysis module through the identification and classification of specific harmonic frequencies. The classification unit can not only quickly identify harmonic components of different frequencies but also classify and mark these harmonics according to categories, enabling users to more intuitively understand the distribution of harmonics and their impact on power quality. Compared with traditional harmonic analysis methods, the present invention significantly reduces the time for processing complex frequency signals and improves the classification efficiency and accuracy by introducing the classification unit. In addition, the classification results provide more detailed data support for subsequent power quality assessment, facilitating users to formulate targeted optimization measures according to the harmonic categories and intensities, thereby effectively reducing the impact of harmonics on the power system and enhancing the stability and operating efficiency of the system.

[0032] The report generation module includes a data visualization unit for generating a weight distribution map of power quality problems, a harmonic impact assessment map, and a priority chart of optimization suggestions. The data visualization unit in the report generation module uses graphical techniques to intuitively display complex power quality analysis data. First, based on the weight distribution results of the power quality assessment module, the data visualization unit generates a weight distribution map of power quality problems, presenting the relative importance and weight values of different problems in the form of a pie chart, bar chart, or heat map. Secondly, for the harmonic assessment data output by the harmonic analysis module, a harmonic impact assessment map is generated, showing the impact intensity of each harmonic component and its interference degree on the power system through a spectrogram or line chart to help users identify key harmonic problems. Finally, according to the calculation results of the complexity of optimization suggestions, a priority chart of optimization suggestions is generated, presenting the complexity and priority of optimization suggestions in the form of a histogram, radar chart, or priority ranking table to guide users' decisions in resource allocation and solution implementation. Through flexible chart design, combined with efficient data processing and dynamic update functions, the data visualization unit ensures that the analysis results are accurate and intuitive, providing users with a clear and comprehensive power quality analysis report. By integrating the data visualization unit into the report generation module, the present invention significantly improves the display effect of power quality analysis results and the user experience. The weight distribution map can intuitively reflect the importance of various power quality problems, providing a scientific decision-making basis for users; the harmonic impact assessment map clearly shows the interference degree of different harmonic components on the system, facilitating users to quickly locate and prioritize key harmonic problems; the priority chart of optimization suggestions clarifies the implementation order and difficulty of optimization solutions, helping users efficiently allocate resources and formulate reasonable optimization strategies. In addition, the data visualization unit supports flexible switching between various chart styles and content customization, meeting the personalized needs of different user groups, especially having extremely high application value in complex power system analysis and decision-making scenarios. Overall, the present invention not only improves the readability and practicality of the report but also provides users with a deeper insight into power quality problems and optimization guidance.

[0033] The voltage and current acquisition module uses a high-speed sampling chip to improve the ability to capture rapidly changing signals. By using a high-speed sampling chip, the voltage and current acquisition module can collect voltage and current signals at a higher sampling frequency, thus significantly improving the ability to capture rapidly changing signals. The high-speed sampling chip has the characteristics of high bandwidth, high precision, and low latency. During the signal acquisition process, it can collect continuous data points at extremely short time intervals to ensure accurate capture of the detailed changes in rapidly changing signals. The acquired high-speed signal data will be transmitted in real-time to the subsequent signal processing unit for further operations such as filtering, amplification, and feature extraction. Through the application of the high-speed sampling chip, the system can effectively meet the acquisition requirements of dynamic loads, transient fluctuations, and other high-frequency signals, providing more accurate and rich data support for the harmonic analysis and power quality assessment modules. This design is particularly suitable for complex power systems and non-linear load environments with significant high-frequency signal fluctuations. In this invention, by adopting a high-speed sampling chip in the voltage and current acquisition module, the frequency and precision of signal acquisition are greatly improved, especially having significant advantages in capturing rapidly changing dynamic signals. The high-speed sampling chip can maintain the integrity and continuity of data in a high-frequency signal environment, effectively avoiding signal distortion or information loss problems caused by insufficient sampling frequency. At the same time, the high dynamic response ability of this module provides higher-quality input data for the subsequent analysis module, thus improving the accuracy of harmonic analysis, harmonic classification, and power quality assessment. This design is not only applicable to general power quality monitoring scenarios but also shows important engineering value in special application environments that require high precision and high response speed, such as new energy systems, smart grids, or industrial automation.

[0034] The voltage and current acquisition module is connected to an external data storage unit to record and store the signal data collected in real time. During the process of real-time signal data acquisition, the voltage and current acquisition module transmits the data to the external data storage unit through a high-speed interface for recording and storage. The storage unit can be a hard disk drive, a solid-state drive, or other non-volatile storage devices, or it can also be a remote storage system based on cloud computing. The data collected in real time includes the time-domain and frequency-domain characteristics of voltage and current signals, which are used to support subsequent in-depth analysis and historical data backtracking. The design of the storage unit can receive the data transmitted by the acquisition module with high throughput and has a large-capacity storage function to ensure uninterrupted long-term recording. Through the stored signal data, users can reconstruct and re-analyze the historical sampling results to discover the long-term trends of power quality problems. In addition, the data storage unit supports automatic segmentation and indexing functions, which facilitate the quick retrieval of sampling data for a specific time period or a specific event, thus significantly improving the efficiency of data management and utilization. By connecting an external data storage unit in the voltage and current acquisition module, the present invention realizes the real-time recording and long-term storage functions of signal data, providing a reliable data foundation for the system. The real-time storage function ensures the integrity and availability of the collected signal data in subsequent analysis, avoiding the problem of affecting the analysis accuracy due to data loss. The large-capacity characteristic of the external storage unit meets the requirements of long-term monitoring and is particularly suitable for application scenarios that require long-term recording of power quality data. In addition, the stored data can support secondary analysis and trend research, providing users with more in-depth diagnostic capabilities, helping to discover potential power quality problems and formulate long-term optimization plans. Through the segmented storage and indexing functions, the system can quickly locate specific abnormal events or time periods, further enhancing the practicality of the system and the efficiency of data management. This design is particularly suitable for various application scenarios such as smart grids, power equipment monitoring, and industrial energy management.

[0035] The report generation module outputs a comprehensive report in the final analysis report according to the power quality assessment results. The comprehensive report supports the export function and generates an electronic report file in a standard format, which is convenient for users to archive and share. By comprehensively analyzing the power quality assessment results, the report generation module generates a complete comprehensive report and supports the export of electronic files in multiple standard formats. The implementation of the export function is based on the format conversion and file generation technologies embedded in the module. Users can choose to generate electronic report files in formats such as PDF, Word, Excel, and HTML. The generated report content includes a weight distribution map of power quality problems, a harmonic impact assessment map, a priority chart of optimization suggestions, and relevant text descriptions. When generating the file, the system automatically embeds dynamic data and chart content to ensure that the report is consistent with the real-time analysis results. In addition, the report generation module supports file encryption and signature functions, and users can choose to protect the content integrity and privacy of the report. Through the export function, users can archive the electronic report file for subsequent reference or for various purposes such as engineering reports, academic research, and equipment maintenance records. The supported formats are widely applicable to various office and analysis software, improving the sharing and use efficiency of the report. By integrating the electronic report export function into the report generation module, the present invention greatly improves the convenience of storing and sharing the comprehensive report. The electronic report file in a standard format enables users to easily view and edit the report content in various environments without additional software conversion operations. The PDF format is convenient for archiving and printing, the Word and Excel formats are suitable for further editing, and the HTML format can be used for web display or remote collaboration. The generation process of the electronic report is efficient and flexible, ensuring the content integrity and format consistency of the report. In addition, the support for encryption and signature functions further enhances the security of the report, especially suitable for scenarios with strict protection requirements for sensitive power quality data. Generally speaking, the export function of the present invention provides a convenient solution for the management and dissemination of power quality assessment results and is applicable to various application requirements of energy management, power system optimization, and industrial and commercial users.

[0036] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art 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 current-driven dielectric loss and power quality joint detection system, characterized in that: The system comprises: The voltage and current acquisition module is used to collect voltage and current signals from the circuit to be tested in real time and extract time domain and frequency domain features; The harmonic analysis module connected to the voltage and current acquisition module is used to perform harmonic analysis of nonlinear loads based on the extracted voltage and current signal characteristics and identify various harmonic components; the intensity of the perceived impact of harmonics on the power system is used as the classification basis to classify harmonics, analyze the harmonic impact range, and output harmonic perception results; A power quality assessment module connected to the harmonic analysis module is used to construct a power quality assessment model based on the harmonic analysis results and quantify the energy efficiency index of the nonlinear load; Sort by weight, quantify the energy efficiency indicators of nonlinear loads and evaluate power quality issues from large to small weights; The report generation module connected to the power quality assessment module is used to output a final analysis report based on the power quality assessment results.

2. The current-driven dielectric loss and power quality joint detection system according to claim 1, characterized in that: The voltage and current acquisition module acquires voltage and current signals from the circuit to be tested in real time, and extracts time domain and frequency domain characteristics thereof, including: Collect voltage and current signals from the circuit to be tested in real time, define sampling sensitivity and signal strength, preset an acquisition accuracy threshold, and calculate the signal acquisition completion. The specific formula is: ; Among them, α is the signal acquisition completion, b is the acquisition sensitivity coefficient, and G is the signal strength collected from the circuit to be tested; Determine whether the preset acquisition accuracy threshold is reached. If it exceeds the threshold, end the current acquisition process. If it does not reach the threshold, dynamically adjust the acquisition sensitivity coefficient to optimize the acquisition process.

3. The current-driven dielectric loss and power quality joint detection system according to claim 1, characterized in that: Harmonic analysis of nonlinear loads is performed based on the extracted voltage and current signal features to identify various harmonic components, including: converting the actual harmonic intensity into the perceived impact intensity on the power system, and quantifying the impact of the power system on the harmonics. The specific formula is: A = m × log (B); Where A represents the perceived impact intensity of a certain harmonic on the power system, m represents the perceived sensitivity coefficient of the harmonic intensity, B represents the actual intensity of the collected harmonic component, and log represents logarithmic operation.

4. The current-driven dielectric loss and power quality joint detection system according to claim 1, characterized in that: According to the harmonic analysis results, a power quality assessment model is constructed to quantify the energy efficiency index of nonlinear loads, including: according to the harmonic analysis results, the impact degree of different power quality problems is defined, and the weight of each problem is calculated. The formula is: ； Among them, D i represents the ith power quality problem, E i It represents the actual impact of the ith power quality problem on the system operation, n represents the total number of power quality problems, and i represents the number of the power quality problem.

5. The current-driven dielectric loss and power quality joint detection system according to claim 1, characterized in that: The report generation module outputs the final analysis report according to the power quality assessment result, including modeling the weight distribution of the power quality assessment module and calculating the complexity of the optimization suggestions proposed for the power quality problem. The specific formula is: ; Wherein, g represents the complexity of the optimization suggestions proposed for power quality issues, z represents the influence of the optimization suggestions on power quality improvement, x represents the number of optimization suggestions proposed, and cosh represents the hyperbolic cosine function; Generate comprehensive reports.

6. A current-driven dielectric loss and power quality joint detection system according to claim 5, characterized in that: The report generation module generates a comprehensive report including a power quality problem weight distribution diagram, a power quality assessment result analysis diagram, and an optimization suggestion complexity priority diagram according to the final analysis report output by the power quality assessment result.

7. The current-driven dielectric loss and power quality joint detection system according to claim 1, characterized in that: The voltage and current acquisition module includes a signal filter for filtering out noise signals and a signal amplifier for amplifying the acquired signals; the report generation module includes a data visualization unit for generating a power quality problem weight distribution diagram, a harmonic impact assessment diagram and an optimization suggestion priority chart.

8. The current-driven dielectric loss and power quality joint detection system according to claim 1, characterized in that: The voltage and current acquisition module adopts a high-speed sampling chip to improve the ability to capture fast-changing signals.

9. The current-driven dielectric loss and power quality joint detection system according to claim 2, characterized in that: The voltage and current acquisition module is connected to an external data storage unit to record and store the signal data acquired in real time.

10. The current-driven dielectric loss and power quality joint detection system according to claim 3, characterized in that: The report generation module outputs the comprehensive report in the final analysis report according to the power quality assessment results, supports the export function, and generates an electronic report file in a standard format for easy archiving and sharing by users.

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