Power distribution network cable insulation situation on-line monitoring platform based on equivalent electrical characteristics

Abstract

The invention belongs to the technical field of cable insulation monitoring, and provides a power distribution network cable insulation situation on-line monitoring platform based on equivalent electrical characteristics, which comprises a data acquisition module used for acquiring electrical parameters of cables in a power distribution network in real time; the database module is used for storing historical data, equivalent electrical characteristic model parameters of various insulation defects, insulation situation evaluation reports and correlation analysis results among electrical parameters; the signal processing module is used for combining the data output by the data acquisition module with a database and carrying out correlation analysis; the insulation situation judgment module is used for judging whether the cable has an insulation deterioration trend or not based on the output of the signal processing module in combination with a preset insulation state threshold value; and the alarm module is used for triggering an alarm signal when the insulation situation judgment module detects that the insulation degradation trend exceeds a preset threshold value. According to the scheme, the insulation state of the power cable in operation is evaluated more comprehensively, so that accurate early warning is achieved, and faults are effectively checked.

Description

Technical Field

[0001] The invention belongs to the technical field of cable insulation monitoring, and relates to an online monitoring platform for the insulation status of cables in a distribution network based on equivalent electrical characteristics. Background Art

[0002] In the power system, cables are important carriers for the transmission and distribution of electric energy, and their insulation status is directly related to the safe and stable operation of the power grid. However, due to factors such as manufacturing process, operating environment, and aging during long-term operation, cable insulation may gradually deteriorate, and even cause insulation breakdown and single-phase grounding faults. Traditional preventive testing methods require detection in a power outage state, and can only achieve centralized defect detection of the entire cable power supply network, and cannot accurately monitor a single cable. Therefore, there is an urgent need for a platform that can monitor the insulation status of cables in real time to improve the safety and reliability of the power grid. Summary of the invention

[0003] The present invention proposes an online monitoring platform for the insulation status of power cables in distribution networks based on equivalent electrical characteristics. The platform more comprehensively evaluates the insulation status of power cables in operation, thereby accurately warning and effectively troubleshooting faults.

[0004] The technical solution of the present invention is achieved in this way:

[0005] An online monitoring platform for cable insulation status in distribution network based on equivalent electrical characteristics, including:

[0006] The data acquisition module is used to collect the electrical parameters of the cables in the distribution network in real time, including current, voltage and insulation resistance, and input the collected data into the database;

[0007] Database module, used to store historical data, equivalent electrical characteristic model parameters of various insulation defects, insulation status assessment reports, and correlation analysis results between electrical parameters for subsequent analysis and optimization;

[0008] The signal processing module is used to combine the data output by the data acquisition module with the database to perform correlation analysis to identify the change trend of the cable insulation status;

[0009] The insulation status judgment module determines whether the cable has an insulation degradation trend based on the output of the signal processing module and the preset insulation status threshold, and generates an insulation status assessment report;

[0010] Alarm module: When the insulation situation judgment module detects that the insulation degradation trend exceeds the preset threshold, an alarm signal is triggered to alert the operation and maintenance personnel.

[0011] Preferably, the establishment of the equivalent parameter model of various types of insulation defects includes the following steps:

[0012] Data collection: Collect data on various types of insulation defects through experiments or field tests;

[0013] Feature extraction: Process the collected data to extract key features that can characterize different types of insulation defects;

[0014] Model building: Use machine learning or statistical modeling methods to build equivalent parameter models based on the extracted features;

[0015] Cross-validation of model validity;

[0016] Store the established model and its related parameters in the database;

[0017] Update the database regularly to add new defect types and models;

[0018] Continuously optimize the model based on feedback.

[0019] Preferably, the collected data include different types of defects such as partial discharge, aging, and cracks; the data for each defect include resistance, capacitance, and dielectric loss factor.

[0020] Preferably, the model building step uses a clustering algorithm to group similar defects into one category.

[0021] Preferably, the data acquisition module includes a current sensor, a voltage sensor and an insulation resistance sensor, which are respectively used to collect current, voltage and insulation resistance data of the cable line;

[0022] The data acquisition module acquires electrical parameters of the cable under different working conditions, including but not limited to data under conditions such as load fluctuation and temperature change.

[0023] Preferably, the correlation analysis in the signal processing module adopts a cross-correlation function or an autocorrelation function to evaluate the time correlation or waveform similarity between the electrical parameters of current, voltage and insulation resistance.

[0024] Preferably, the data acquisition module first performs data preprocessing, and the data preprocessing is used to obtain a fundamental signal from the collected signal through a conditioning circuit and an A / D conversion circuit, and then perform low-pass filtering through wavelet denoising, and perform Fourier transform to extract the fundamental frequency component therein.

[0025] Preferably, when judging the insulation status of the cable, the insulation status judgment module also takes into account the changing trend of the electrical parameter correlation over time, so as to more accurately evaluate the speed and degree of insulation degradation.

[0026] Preferably, the alarm module is configured to: when it is detected that the insulation degradation trend exceeds a preset threshold, an alarm is issued to the operation and maintenance personnel through sound and light alarms, SMS notifications or remote data transmission; at the same time, the alarm information is recorded, including the alarm time, alarm type and cable location, etc., for subsequent analysis and processing.

[0027] Preferably, the platform also includes:

[0028] User interface module, used to display insulation status assessment reports, alarm information and historical data of cable insulation status, which is convenient for operation and maintenance personnel to view and analyze;

[0029] The remote monitoring module is used to remotely access and control the online monitoring platform to improve operation and maintenance efficiency and flexibility.

[0030] The working principle and beneficial effects of the present invention are:

[0031] 1. The online monitoring platform for the insulation status of cables in the distribution network based on equivalent electrical characteristics provided by the present invention can monitor the insulation defects of the cable lines in real time and evaluate the insulation status of the cable lines.

[0032] 2. The online monitoring platform for the insulation status of the distribution network cable based on equivalent electrical characteristics provided by the present invention collects characteristic quantities under the insulation state of the cable during online monitoring, enters the collected data and actual operating parameters into the database, and performs correlation analysis to obtain the insulation state of the cable, and thereby decide whether to issue an early warning. Since there is a complete database, the collected relevant data can be entered regularly, and a time curve that is easy to read intuitively can be produced. By comparing and trending the collected relevant data with the time curve, the changes in the insulation state of the cable can be further predicted. Moreover, based on the correlation theory, by comprehensively analyzing the various insulation parameters in the operation of the power cable, the insulation state of the operating power cable can be more comprehensively evaluated, thereby accurately warning and effectively troubleshooting.

[0033] 3. The present invention monitors a variety of cable insulation conditions, builds a database of parameter changes during cable insulation degradation, builds equivalent parameter models for various insulation defects, and establishes different types of insulation defect models to quickly identify specific types of defects in the cable during actual operation. This helps to improve the accuracy and efficiency of fault diagnosis; by analyzing the changing trends of cable insulation parameters over time, potential degradation problems can be discovered earlier, so that measures can be taken in advance to avoid faults; by continuously monitoring the insulation status of the cable, its health status can be understood in real time, thereby improving the reliability and stability of the entire power system; based on a large amount of historical data and model analysis, more scientific and reasonable decisions can be made to improve the overall management level of the system.

[0034] 4. In the present invention, when detecting the signal, the correlation coefficient is selected to effectively avoid the defect of detecting the fault only by relying on the fault signal, which not only reflects the comprehensive phase relationship of the signal, but also better reflects the amplitude relationship of each frequency component in the signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0036] Figure 1 It is a schematic diagram of the structure of the online monitoring platform for the insulation status of cables in the distribution network of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] like Figure 1 As shown in the figure, the main process of the online monitoring platform for the insulation status of distribution network cables based on equivalent electrical characteristics includes: the sensor component collects current and voltage signals, and then the current signal is converted into an equivalent voltage value through the signal conditioning circuit, and then the continuous signal is converted into a digital signal through the data acquisition card. Finally, the LABVIEW software installed on the industrial computer reads the collected signal from the data acquisition card, and the data after wavelet denoising and fast Fourier transform is saved in the database. Then, the correlation analysis is performed on the sample data in the system to determine the change in the insulation performance of the cable and give the judgment result. According to the result, it is determined whether to issue an alarm. Finally, specific online information on the insulation status is provided for remote access.

[0039] The platform specifically includes:

[0040] The data acquisition module is used to collect the electrical parameters of the cables in the distribution network in real time, including current, voltage and insulation resistance, through current sensors, voltage sensors and insulation resistance sensors, and input the collected data into the database; collect the electrical parameters of the cables under different working conditions, including but not limited to data under conditions such as load fluctuations and temperature changes; firstly, data preprocessing is performed, and the data preprocessing is used to obtain the fundamental wave signal through the conditioning circuit and the A / D conversion circuit of the collected signal, and then low-pass filtering is performed through wavelet denoising, and Fourier transform is performed to extract the fundamental frequency component therein;

[0041] A database module is used to store historical data, equivalent electrical characteristic model parameters of various insulation defects, insulation status assessment reports, and correlation analysis results between electrical parameters for subsequent analysis and optimization; the database module also includes: a simulated distribution network topology database, which is used to store the topology structure and cable parameter information of the distribution network; a fault type and line reference database, which is used to store historical fault cases and cable insulation fault types to assist the insulation status judgment module in fault location and cause analysis;

[0042] The signal processing module combines the pre-processed data with the database to perform correlation analysis to identify the changing trend of the cable insulation state; the correlation analysis uses a cross-correlation function or an autocorrelation function to evaluate the time correlation or waveform similarity between the electrical parameters of current, voltage and insulation resistance; the correlation analysis includes two aspects: cross-correlation and autocorrelation. The autocorrelation function does not involve information about the phase, but only reflects the state of its own common components in the entire time period; the cross-correlation function can not only restore the complete information, but also fully reflect the common frequency components in the two signals; when the waveforms of the two signals are close, a resonance phenomenon will be formed, which will greatly expand the signal; when the waveforms of the two signals differ greatly, the signals will cancel each other out and the signals will be reduced. However, it is not simple and intuitive to measure the correlation between the two signals with absolute values. After the correlation function is normalized, the obtained correlation coefficient reflects this similarity more intuitively. The larger the correlation coefficient ρ, the closer the waveforms of the two signals are. When ρ=-1, the waveforms of the two signals are completely opposite, and the signal is the weakest; when ρ=1, the waveforms of the two signals are completely consistent, and the signal is the strongest. When detecting the signal, the selection of the correlation coefficient effectively avoids the defect of relying solely on the fault signal to detect the fault. It not only reflects the comprehensive phase relationship of the signal, but also better reflects the amplitude relationship of each frequency component in the signal; the correlation between the changing characteristic quantity signal and the corresponding multiple fault specimens in the database is calculated, and the correlation coefficient distribution function diagram of the fault location and fault type is made. Based on this, the location of the insulation defect and the type of degradation are obtained. That is, only the largest correlation coefficient value in the two-dimensional coordinates needs to be identified to determine the actual location of the cable insulation defect and the degree of aging;

[0043] The insulation state judgment module, based on the output of the signal processing module, combines the preset insulation state threshold and the change trend of the electrical parameter correlation over time, judges whether the cable has an insulation degradation trend, and generates an insulation state assessment report; the insulation state judgment module includes: a threshold setting unit, which is used to set the insulation state threshold according to the type of cable, working environment and historical data; a state assessment unit, which is used to compare the real-time insulation state with the preset threshold to assess whether the insulation state of the cable is within a safe range; wherein, the insulation state threshold is set to 1, and the relative degradation degree reflects the degree of degradation of the current monitoring equipment. The data range is between 0-1, 0.5-0.55, indicating that the insulation state is normal, 0.55-0.65, the insulation state begins to deteriorate, early aging, 0.65-1, the insulation state is severely deteriorated, the end of aging, and needs to be powered off for maintenance; for the kth grounding wire current signal, its relative degradation degree d(t) can be expressed as:

[0044]

[0045] Among them, ΔI k =10 3 (I (n+1) -I (n) ), is the difference between two consecutive ground wire current sampling times; ΔI k (0) ΔI is the small difference in grounding current caused by the natural imbalance of the distribution network during normal operation; k max The maximum operating threshold reached when severe insulation cracking or even breakdown occurs;

[0046] The alarm module triggers an alarm signal when the insulation situation judgment module detects that the insulation degradation trend exceeds a preset threshold value, and sends an alarm to the operation and maintenance personnel; the alarm signal includes an audible and visual alarm, a text message notification, or a remote data transmission method; and the alarm information is recorded at the same time, including the alarm time, alarm type, and cable location, etc., for subsequent analysis and processing;

[0047] User interface module, used to display insulation status assessment reports, alarm information and historical data of cable insulation status, which is convenient for operation and maintenance personnel to view and analyze;

[0048] The remote monitoring module is used to remotely access and control the online monitoring platform to improve operation and maintenance efficiency and flexibility.

[0049] The establishment of the equivalent parameter model of various insulation defects includes the following steps:

[0050] Data collection: Through experiments or field tests, data on various types of insulation defects are collected; the collected data include different types of defects such as partial discharge, aging, and cracks; the data for each defect includes resistance, capacitance, and dielectric loss factor;

[0051] Feature extraction: Process the collected data to extract key features that can characterize different types of insulation defects;

[0052] Model building: Use clustering algorithms to group similar defects into one category, and build an equivalent parameter model based on the extracted features;

[0053] Cross-validation of model validity;

[0054] Store the established model and its related parameters in the database;

[0055] Update the database regularly to add new defect types and models;

[0056] Optimize the model continuously based on feedback: Use the calculated correlation coefficient to analyze the new sampled data, and further update the sampled data based on the analysis results. When the correlation between the new sampled data and the sampled data exceeds a certain range, it is considered that the insulation of the line has suddenly deteriorated into a fault or that the sampled data has errors, and the data is further analyzed. When the correlation between the new sampled data and the sampled data is within a certain range, it is considered that the insulation of the line is changing slowly, and the new data is added to the sampled data. As the sampled data continues to increase, the correlation between the data can be changed, so that the insulation changes of the system can be sensitively and accurately reflected.

[0057] The A / D conversion module chip uses the AD8138 chip, and the analog signal at the output of the signal conditioning circuit is a differential input signal, so that the conversion process is not affected by external factors;

[0058] The acquisition equipment processor uses the EP1C12240C8 FPGA chip, whose functions mainly include parameter setting, data storage and logic control;

[0059] The current sensor used in the present invention is Shuxin Electric BLMZC-10 type, and the measurement accuracy reaches 0.1 level.

[0060] The degradation of cable insulation does not occur instantaneously, but is a long process with different degradation cycles due to different working environments. In the process of cable insulation degradation, it is usually accompanied by a decrease in insulation resistance and an increase in equivalent distributed capacitance. By analyzing the changing rules of distributed capacitance and insulation resistance formed by electrical tree aging, it can be found that: in the middle and late stages of cable insulation degradation, the equivalent resistance gradually decreases; in the early stages of degradation, the distributed capacitance fluctuates and continues to increase. By analyzing the changes in the grounding current between the cable metal shielding layer and the cable core, it can be noticed that there is a certain correspondence between the waveform changes of the grounding wire current and the parameter changes of the distributed capacitance and the equivalent resistance. Therefore, the degradation type of cable insulation can be identified by the changes in the grounding wire current. Therefore, the present invention monitors a variety of cable insulation conditions, builds a database of parameter changes during cable insulation degradation, and builds equivalent parameter models for various types of insulation defects.

[0061] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An online monitoring platform for cable insulation status in distribution network based on equivalent electrical characteristics, characterized in that: include: The data acquisition module is used to collect the electrical parameters of the cables in the distribution network in real time, including current, voltage and insulation resistance, and input the collected data into the database; Database module, used to store historical data, equivalent electrical characteristic model parameters of various insulation defects, insulation status assessment reports, and correlation analysis results between electrical parameters; The signal processing module is used to combine the data output by the data acquisition module with the database to perform correlation analysis to identify the change trend of the cable insulation status; The insulation status judgment module determines whether the cable has an insulation degradation trend based on the output of the signal processing module and the preset insulation status threshold, and generates an insulation status assessment report; Alarm module: When the insulation situation judgment module detects that the insulation degradation trend exceeds the preset threshold, an alarm signal is triggered to alert the operation and maintenance personnel.

2. The online monitoring platform for the insulation status of cables in the distribution network based on equivalent electrical characteristics according to claim 1 is characterized in that: The establishment of the equivalent parameter model of various insulation defects includes the following steps: Data collection: Collect data on various types of insulation defects through experiments or field tests; Feature extraction: Process the collected data to extract key features that can characterize different types of insulation defects; Model building: Use machine learning or statistical modeling methods to build equivalent parameter models based on the extracted features; Cross-validation of model validity; Store the established model and its related parameters in the database; Update the database regularly to add new defect types and models; Continuously optimize the model based on feedback.

3. The online monitoring platform for the insulation status of cables in the distribution network based on equivalent electrical characteristics according to claim 2 is characterized in that: The collected data include different types of defects such as partial discharge, aging, and cracks; the data for each defect includes resistance, capacitance, and dielectric loss factor.

4. The online monitoring platform for the insulation status of cables in the distribution network based on equivalent electrical characteristics according to claim 2 is characterized in that: The model building step uses a clustering algorithm to group similar defects into one category.

5. The online monitoring platform for the insulation status of cables in the distribution network based on equivalent electrical characteristics according to claim 1 is characterized in that: The data acquisition module includes a current sensor, a voltage sensor and an insulation resistance sensor, which are used to collect current, voltage and insulation resistance data of the cable line respectively; The data acquisition module acquires electrical parameters of the cable under different working conditions, including but not limited to data under conditions such as load fluctuation and temperature change.

6. The online monitoring platform for the insulation status of cables in the distribution network based on equivalent electrical characteristics according to claim 1 is characterized in that: The correlation analysis in the signal processing module uses a cross-correlation function or an autocorrelation function to evaluate the time correlation or waveform similarity between the electrical parameters of current, voltage and insulation resistance.

7. The online monitoring platform for cable insulation status of distribution network based on equivalent electrical characteristics according to claim 1 is characterized in that: The data acquisition module first performs data preprocessing, which is used to obtain a fundamental signal from the collected signal through a conditioning circuit and an A / D conversion circuit, and then performs low-pass filtering through wavelet denoising and Fourier transform to extract the fundamental frequency component.

8. The online monitoring platform for the insulation status of cables in the distribution network based on equivalent electrical characteristics according to claim 1 is characterized in that: When judging the insulation status of the cable, the insulation status judgment module also takes into account the changing trend of the electrical parameter correlation over time to more accurately evaluate the speed and degree of insulation degradation.

9. The online monitoring platform for cable insulation status of distribution network based on equivalent electrical characteristics according to claim 1 is characterized in that: The alarm module is configured to, when it is detected that the insulation degradation trend exceeds a preset threshold, send an alarm to the operation and maintenance personnel through sound and light alarms, SMS notifications or remote data transmission; and record the alarm information, including the alarm time, alarm type and cable location, etc., for subsequent analysis and processing.

10. The online monitoring platform for cable insulation status of distribution network based on equivalent electrical characteristics according to claim 1, characterized in that: The platform also includes: User interface module, used to display insulation status assessment reports, alarm information and historical data of cable insulation status, which is convenient for operation and maintenance personnel to view and analyze; The remote monitoring module is used to remotely access and control the online monitoring platform to improve operation and maintenance efficiency and flexibility.

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