CVT internal capacitance state comprehensive evaluation method and system based on temperature compensation

Abstract

The invention discloses a CVT internal capacitance state comprehensive evaluation method and system based on temperature compensation, and belongs to the field of capacitor voltage transformer optimization compensation, and the method comprises the following steps: S1, detecting the primary voltage amplitude and phase angle of a capacitor transformer, and obtaining the performance parameters of the capacitor transformer; s2, acquiring environment temperature information; s3, determining a mathematical relationship between the environment temperature and the performance parameters of the capacitance transformer, and calculating a temperature compensation coefficient according to the mathematical relationship and the environment temperature value; s4, compensating a primary voltage amplitude and a phase angle by using a temperature compensation coefficient; and S5, analyzing the compensated voltage amplitude and phase angle data to obtain an analysis result, and evaluating whether the internal capacitance state of the capacitance transformer is normal or not according to the analysis result. By accurately detecting the primary voltage amplitude and the phase angle of the capacitance transformer and combining environment temperature information, the method can calculate an accurate temperature compensation coefficient, so that the influence of temperature change on the performance of the CVT is effectively corrected.

Description

Technical Field

[0001] The present invention relates to the technical field of capacitive voltage transformers, and more specifically, to a comprehensive evaluation method and system for the internal capacitance state of a CVT based on temperature compensation. Background Art

[0002] A capacitive voltage transformer (CVT for short) is an important measuring device in the power system. Its main function is to convert the voltage signal of a high-voltage line into a measurable or controllable signal within a low-voltage range, so as to be used in the fields of power system measurement, metering, protection, and control, etc. The working principle of a capacitive voltage transformer is based on the change of capacitance. It is composed of two layers of metal foil and insulating materials. When a high-voltage signal acts on the capacitor, the electric field of the capacitor will change, resulting in a change in the capacitance value. By measuring the change in the capacitance value to reflect the magnitude of the voltage, and then converting it into a corresponding low-voltage signal for output. A capacitive voltage transformer has high precision and stability, and can provide accurate measurement results within a wide voltage range. It has low load impact and small phase difference, and will not have an obvious impact on the operation of the power system. In addition, it has a small volume and weight, which is convenient for installation and maintenance. Most importantly, a capacitive voltage transformer does not require an external power supply and can work independently, greatly improving its reliability and safety.

[0003] The publication number is CN114966515A, and the name is a method for preparing a self-powered capacitive voltage transformer and its error compensation, including a capacitive voltage divider, a medium-voltage transformer, a voltage amplifier, a voltage transformer, an energy-taking capacitor, a voltage-limiting circuit, and a DC / DC power module. The high voltage connected to the primary terminal of the capacitive voltage transformer is divided by the capacitive voltage divider into a low voltage as an input signal and sent to the input terminal of the voltage amplifier. The voltage amplifier amplifies the low-voltage signal and then sends it to the primary winding of the medium-voltage transformer. The voltage transformer collects the voltage of the secondary winding of the medium-voltage transformer as a feedback signal and inputs it to the voltage amplifier. The energy-taking capacitor, the voltage-limiting circuit, and the DC / DC power module step down and rectify the high voltage and generate positive and negative power supplies through voltage-limiting protection to supply power to the voltage amplifier. The capacitive voltage transformer proposed by the present invention realizes automatic compensation for the load error caused by connecting a load in series to the secondary terminal, ensuring the linearity and accuracy of the capacitive voltage transformer.

[0004] The publication number is CN118112301A, and the name is a capacitive voltage transformer and an on-line monitoring method for its operating state, belonging to the technical field of capacitive voltage transformer fault monitoring. It includes a high-voltage terminal H, a capacitive voltage divider, and a low-voltage terminal N of the capacitive voltage divider. The high-voltage terminal H, the capacitive voltage divider, and the low-voltage terminal N of the capacitive voltage divider are connected in series in turn. The capacitive voltage divider includes a series-connected high-voltage capacitor C1 and a medium-voltage capacitor C2. An electromagnetic unit is connected between the high-voltage capacitor C1 and the medium-voltage capacitor C2. The end of the electromagnetic unit is connected with a low-voltage terminal XL. Both the low-voltage terminal N of the capacitive voltage divider and the low-voltage terminal XL are grounded, and the low-voltage terminal N of the capacitive voltage divider is connected to the low-voltage terminal XL. A first current acquisition device is connected in series between the medium-voltage capacitor C2 and the low-voltage terminal N of the capacitive voltage divider, and a second current acquisition device is connected in series between the electromagnetic unit and the low-voltage terminal XL.

[0005] However, the influence of temperature change on the performance of CVT (capacitive voltage transformer) is significant. The working principle of CVT depends on the capacitance value of the capacitor, and the capacitance value of the capacitor will change with the change of temperature. This change will affect the measurement accuracy and stability of CVT. The change of temperature will affect the dielectric loss of the capacitor. The increase of dielectric loss may lead to measurement errors. The increase of temperature may increase the leakage current inside CVT, which will affect the accuracy of the measurement result. The change of temperature may affect the response time of CVT, resulting in a slower response speed when the voltage changes.

[0006] Therefore, how to provide a comprehensive evaluation method and system for the internal capacitance state of CVT based on temperature compensation is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0007] In view of this, the present invention provides a comprehensive evaluation method and system for the internal capacitance state of CVT based on temperature compensation, aiming to solve the technical problem of the influence of temperature change on the performance of CVT (capacitive voltage transformer).

[0008] To achieve the above object, the present invention adopts the following technical solutions:

[0009] A comprehensive evaluation method for the internal capacitance state of CVT based on temperature compensation includes the following steps:

[0010] S1. Detect the primary voltage amplitude and phase angle of the capacitance transformer to obtain the performance parameters of the capacitance transformer;

[0011] S2. Obtain the ambient temperature information;

[0012] S3. Determine the mathematical relationship between the ambient temperature and the performance parameters of the capacitance transformer, and calculate the temperature compensation coefficient according to the mathematical relationship and the ambient temperature value;

[0013] S4. Compensate the primary voltage amplitude and phase angle using the temperature compensation coefficient;

[0014] S5. Analyze the compensated voltage amplitude and phase angle data to obtain an analysis result, and based on the analysis result, evaluate whether the internal capacitance state of the capacitive voltage transformer is normal.

[0015] Further, the evaluation method further includes:

[0016] S6. Collect historical operation data of the capacitive voltage transformer;

[0017] S7. Statistically analyze the performance parameters of the capacitive voltage transformer at different ambient temperatures, and identify the correlation between the performance parameters and the ambient temperature;

[0018] S8. Establish a prediction model between the performance parameters and the ambient temperature, and based on the prediction model and the ambient temperature information, predict the comprehensive state of the capacitive voltage transformer.

[0019] Further, the specific content of S1 is as follows:

[0020] Prepare voltage measurement equipment, including a digital multimeter, an oscilloscope, or a dedicated voltage tester;

[0021] Calibrate the measurement equipment so that the measurement range and accuracy of the voltage measurement equipment meet the measurement requirements of the primary side voltage of the capacitive voltage transformer;

[0022] According to the safety operation procedures, connect the probe or test lead of the measurement equipment to the primary side terminal of the capacitive voltage transformer, ensuring a firm and good contact;

[0023] Turn on the voltage measurement equipment for measurement, and record the voltage amplitude and phase angle data of the primary side of the capacitive voltage transformer;

[0024] Conduct a preliminary verification on the recorded voltage amplitude and phase angle data to check for any abnormal readings or errors.

[0025] Further, the specific content of S2 is as follows:

[0026] Place the temperature sensor at a position where it can accurately reflect the ambient temperature of the capacitive voltage transformer, ensuring that the sensor is not affected by direct radiant heat, air flow, or other factors that may affect the readings. Read and record the ambient temperature data displayed by the temperature sensor, and conduct a preliminary verification on the recorded temperature data to check for any abnormal readings or errors.

[0027] Further, the specific content of S3 is as follows:

[0028] Collect and analyze the performance parameter data of the capacitive voltage transformer at different ambient temperatures to determine the impact of temperature changes on the performance of the transformer, and construct a training set and a validation set based on the performance parameter data.

[0029] Construct a performance parameter model that describes the relationship between the ambient temperature and the performance parameters of the instrument transformer, and train the performance parameter model with a training set and verify the performance parameter model based on a validation set;

[0030] Input the ambient temperature value into the trained performance parameter model, calculate the corresponding temperature compensation coefficient according to the input ambient temperature value, and verify the calculated temperature compensation coefficient.

[0031] Further, the specific content of S4 is as follows:

[0032] Extract the original measurement data of the primary voltage amplitude and phase angle of the capacitive instrument transformer from the voltage measurement device, obtain the temperature compensation coefficient calculated according to the ambient temperature information, and confirm that the compensation coefficient is for the current measurement environment and device characteristics;

[0033] According to the characteristics of the capacitive instrument transformer and the influence of temperature on the voltage amplitude, construct a mathematical model to describe the relationship, and use the determined compensation model to apply the temperature compensation coefficient to the original voltage amplitude data;

[0034] Specifically, the compensation model is specifically as follows:

[0035] V 补偿 =V 原始 ×(1 + α·ΔT)

[0036] In the formula, V 原始 is the original voltage amplitude, α is the temperature coefficient of the voltage amplitude, and ΔT is the temperature change;

[0037] According to the characteristics of the capacitive instrument transformer and the influence of temperature on the voltage phase angle, construct a mathematical model to describe the relationship, and use the determined compensation model to apply the temperature compensation coefficient to the original phase angle data;

[0038] Specifically, the compensation model is specifically as follows:

[0039] θ 补偿 =θ 原始 ×(1 + β·ΔT)

[0040] In the formula, θ 原始 is the original voltage phase angle, β is the temperature coefficient of the voltage phase angle, and ΔT is the temperature change.

[0041] Further, the specific content of S5 is as follows:

[0042] Obtain the compensated voltage amplitude and phase angle data, analyze the compensated data, observe the variation trends of the voltage amplitude and phase angle over time, compare the compensated data with the preset normal operation thresholds to determine whether it is within the normal range, evaluate the state of the internal capacitance of the capacitive voltage transformer according to the variations of the voltage amplitude and phase angle, identify any abnormal voltage or phase changes, conduct further diagnostic tests, including dielectric loss tests or capacitance value measurements, record the results of all diagnostic tests, evaluate whether the capacitive voltage transformer needs maintenance or replacement based on data analysis and diagnostic test results, and formulate a maintenance plan, including a maintenance schedule and required resources.

[0043] Further, the S7 specifically is:

[0044] Extract the required historical operation data from a database or data storage system, including but not limited to voltage amplitude, phase angle, and ambient temperature. Check whether the extracted data is complete to ensure that there are no missing key measurement values. Preprocess the collected data, including data cleaning to remove outliers and noise, formatting, and standardization. Conduct a statistical analysis of the performance parameters at different ambient temperatures to identify the relationship between the performance parameters and the ambient temperature. Use regression analysis to identify the variation trends of the performance parameters over time and the relationship between the trends and the changes in ambient temperature. Conduct a correlation analysis to determine the strength of the correlation between the performance parameters and the ambient temperature;

[0045] Further, the S8 specifically is:

[0046] Determine the key parameters according to the influencing parameters of the capacitive voltage transformer error model, including the interphase leakage current of the capacitive voltage transformer and the secondary load of the current transformer. Construct a capacitive voltage transformer error model that includes the ratio error and phase error as outputs and the leakage current and secondary load as inputs;

[0047] Use an autoregressive radial basis function neural network to optimize the clustering of the RBF network through the ant colony algorithm to determine the center and radius of the basis function of the network. Adopt the particle swarm algorithm to dynamically update the weights of the output layer of the RBF to obtain the optimal weight parameters;

[0048] Input the capacitive voltage transformer error data before the current moment and the capacitive voltage transformer environmental parameter data at the current moment into the capacitive voltage transformer error model. Use the trained RBF neural network model to predict the error of the capacitive voltage transformer at the current moment according to the input data. Preprocess the historical capacitive voltage transformer error data input into the RBF neural network, output the predicted error value, and obtain the warning of the metering error exceeding the limit and the deterioration trend information of the capacitive voltage transformer.

[0049] A comprehensive evaluation system for the internal capacitance state of a CVT based on temperature compensation, comprising:

[0050] A voltage amplitude detection unit for detecting the primary voltage amplitude of a capacitive voltage transformer.

[0051] A voltage phase angle detection unit for detecting the primary voltage phase angle of a capacitive voltage transformer.

[0052] A temperature information acquisition unit for acquiring ambient temperature information.

[0053] A temperature compensation calculation unit for calculating a temperature compensation coefficient based on ambient temperature information, including a mathematical relationship determination unit and a coefficient calculation unit; the mathematical relationship determination unit for determining the mathematical relationship between ambient temperature and the performance parameters of the capacitive voltage transformer; the coefficient calculation unit for calculating the temperature compensation coefficient according to the mathematical relationship and the ambient temperature value.

[0054] A voltage compensation unit for compensating the primary voltage amplitude and phase angle by applying the temperature compensation coefficient, including an amplitude adjustment unit and a phase angle adjustment unit; the amplitude adjustment unit for adjusting the primary voltage amplitude according to the temperature compensation coefficient; the phase angle adjustment unit for adjusting the primary voltage phase angle according to the temperature compensation coefficient.

[0055] The above technical solution has at least the following technical effects:

[0056] By accurately detecting the primary voltage amplitude and phase angle of the capacitive voltage transformer and combining the ambient temperature information, this method can calculate an accurate temperature compensation coefficient, thereby effectively correcting the influence of temperature change on the performance of the CVT. Secondly, by analyzing the compensated data, this system can more accurately evaluate the internal capacitance state of the CVT, detect abnormalities in a timely manner, prevent potential failures, and improve the stability and reliability of the power system. In addition, this method also includes the collection and analysis of historical operation data, which can establish a prediction model between performance parameters and ambient temperature, improve the accuracy of CVT performance evaluation, and reduce errors caused by temperature change. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0058] Figure 1 It is a schematic flow chart of a method for comprehensively evaluating the internal capacitance state of a CVT based on temperature compensation according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0059] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all 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.

[0060] See the appendix Figure 1 , the embodiments of the present invention disclose a comprehensive evaluation method and system for the internal capacitance state of a CVT based on temperature compensation, including Embodiment 1:

[0061] Select equipment suitable for measuring the primary side voltage of the capacitive voltage transformer, such as a digital multimeter, an oscilloscope, or a dedicated voltage tester.

[0062] Ensure that these devices have sufficient measurement ranges and accuracies to adapt to the possible voltage amplitudes on the primary side of the capacitive voltage transformer.

[0063] Calibrate the selected voltage measurement device to ensure the accuracy of the measurement results.

[0064] The calibration process may include using a standard with a known voltage to adjust the device to eliminate systematic errors.

[0065] Connect the probe or test lead of the measurement device to the primary side terminal of the capacitive voltage transformer according to the safety operating procedures.

[0066] Ensure that the connection is firm and the contact is good to avoid measurement errors caused by poor contact.

[0067] Turn on the voltage measurement device and start measuring the voltage amplitude and phase angle on the primary side of the capacitive voltage transformer.

[0068] Ensure that the measurement is carried out under interference-free conditions to obtain accurate data.

[0069] Record the measured voltage amplitude and phase angle data.

[0070] Use a data recording form or an electronic device to store the measurement results for subsequent analysis.

[0071] Conduct a preliminary verification on the recorded voltage amplitude and phase angle data.

[0072] Check whether there are abnormal readings or errors in the data, such as values outside the expected range or obvious measurement errors.

[0073] If necessary, repeat the measurement to confirm the accuracy of the data.

[0074] Organize the verified data into a format that is easy to analyze.

[0075] Label each measurement point with corresponding information such as timestamps and device numbers for easy tracking and analysis.

[0076] Report the organized data to the team or system responsible for analysis.

[0077] Ensure the security and integrity of the data during transmission to prevent the data from being tampered with or lost during transmission.

[0078] Select a suitable temperature sensor, such as a thermocouple, thermistor, or digital temperature sensor, according to the installation environment of the capacitance potential transformer and the measurement accuracy requirements.

[0079] Calibrate the temperature sensor before use to ensure the accuracy of its measurement results.

[0080] Use a standard temperature source for calibration and adjust the sensor reading to match the temperature of the standard source.

[0081] Place the temperature sensor at a location that can accurately reflect the ambient temperature of the capacitance potential transformer.

[0082] Ensure that the sensor is not affected by direct radiant heat, air currents, or other factors that may affect the reading.

[0083] Connect the temperature sensor to the data acquisition system or reading device. Ensure the connection is correct for accurate reading of temperature data.

[0084] Start the data acquisition system to monitor the ambient temperature in real-time. Set the data acquisition frequency as needed, such as recording temperature data once per second or per minute.

[0085] Record the ambient temperature data obtained from the temperature sensor. Use a data recording form or electronic device to store the measurement results for subsequent analysis.

[0086] Conduct a preliminary verification of the recorded ambient temperature data. Check if there are any abnormal readings or errors in the data, such as values outside the expected range or obvious measurement errors.

[0087] Organize the verified ambient temperature data into a format that is easy to analyze. Label each temperature reading with corresponding information such as timestamps and sensor location for easy tracking and analysis.

[0088] Report the organized ambient temperature data to the team or system responsible for analysis. Ensure the security and integrity of the data during transmission to prevent the data from being tampered with or lost during transmission.

[0089] Collect and analyze the performance parameter data of the capacitance potential transformer at different ambient temperatures to determine the impact of temperature changes on the performance of the transformer.

[0090] Construct a training set and a validation set based on the performance parameter data. Construct a performance parameter model that describes the relationship between the environmental temperature and the performance parameters of the instrument transformer, train the performance parameter model using the training set, and validate the performance parameter model based on the validation set. Input the environmental temperature value into the trained performance parameter model, calculate the corresponding temperature compensation coefficient according to the input environmental temperature value, and verify the calculated temperature compensation coefficient.

[0091] Collect the performance parameter data of the capacitive instrument transformer at different environmental temperatures, including voltage amplitude, phase angle, etc. Remove outliers and noise to ensure the accuracy and reliability of the data. Convert the data into a unified format and perform standardization processing for analysis.

[0092] Determine which performance parameters have a significant correlation with the environmental temperature, and these parameters will be used as the input features of the model. It may be necessary to transform the original data or derive new features to better capture the relationship between the performance parameters and the environmental temperature.

[0093] According to the characteristics of the data and the requirements of the problem, select a suitable model type, such as linear regression, polynomial regression, neural network, or other machine learning models. Divide the collected data into a training set and a validation set, usually in a certain proportion, such as 70% training set and 30% validation set.

[0094] Use the training set data to train the selected model, and adjust the model parameters to minimize the prediction error. According to the performance of the model, adjust the hyperparameters of the model to optimize the prediction ability of the model.

[0095] Use the validation set data to evaluate the prediction performance of the model to ensure that the model is not overfitting. Use appropriate evaluation metrics (such as mean squared error MSE, mean absolute error MAE, coefficient of determination R 2 etc.) to evaluate the accuracy of the model.

[0096] According to the validation results, it may be necessary to return and adjust the model structure or parameters to improve the prediction performance of the model. Use techniques such as cross-validation to further verify the stability and generalization ability of the model.

[0097] Deploy the trained model to the actual application to calculate the temperature compensation coefficient in real-time or regularly. Continuously monitor the prediction performance of the model to ensure its accuracy in the actual application. According to the new data and feedback, update the model regularly to adapt to environmental changes.

[0098] Extract the original measurement data of the primary voltage amplitude and phase angle of the capacitive voltage transformer from the voltage measurement device. Obtain the temperature compensation coefficient calculated based on the ambient temperature information, and confirm that the compensation coefficient is for the current measurement environment and device characteristics. According to the characteristics of the capacitive voltage transformer and the influence of temperature on the voltage amplitude, construct a mathematical model to describe the relationship, and use the determined compensation model to apply the temperature compensation coefficient to the original voltage amplitude data. Similarly, apply the temperature compensation coefficient to the original phase angle data.

[0099] Obtain the compensated voltage amplitude and phase angle data. Analyze the compensated data and observe the variation trends of the voltage amplitude and phase angle over time. Compare the compensated data with the preset normal operation thresholds to determine whether it is within the normal range. Based on the variations of the voltage amplitude and phase angle, evaluate the state of the internal capacitance of the capacitive voltage transformer and identify any abnormal voltage or phase changes. Conduct further diagnostic tests, including dielectric loss tests or capacitance value measurements, and record the results of all diagnostic tests. Based on the data analysis and diagnostic test results, evaluate whether the capacitive voltage transformer needs maintenance or replacement, and formulate a maintenance plan, including the maintenance schedule and required resources.

[0100] Example 2:

[0101] Detect the performance parameters of the capacitive voltage transformer

[0102] First, we use a series of voltage measurement devices, including digital multimeters, oscilloscopes, or dedicated voltage testers, to detect the primary voltage amplitude and phase angle of the CVT. These devices must be calibrated to ensure that their measurement ranges and accuracies meet the measurement requirements of the CVT primary side voltage. In accordance with the safety operating procedures, we connect the probes or test leads of the measurement device to the primary side terminals of the CVT and ensure that the connections are firm and in good contact. Subsequently, we turn on the voltage measurement device for measurement and record the voltage amplitude and phase angle data of the CVT primary side. Conduct a preliminary verification of these data to check for any abnormal readings or errors to ensure the accuracy of the data.

[0103] Obtain the ambient temperature information

[0104] Next, we place the temperature sensor at a location that can accurately reflect the ambient temperature of the CVT. Ensure that the sensor is not affected by direct radiant heat, air currents, or other factors that may affect the readings. We read and record the ambient temperature data displayed by the temperature sensor and conduct a preliminary verification of it to check for any abnormal readings or errors.

[0105] Calculate the temperature compensation coefficient

[0106] We collect and analyze the performance parameter data of the CVT at different ambient temperatures to determine the impact of temperature changes on the performance of the instrument transformer. Based on the performance parameter data, we construct a training set and a validation set, and build a model that describes the relationship between the ambient temperature and the performance parameters of the instrument transformer. The model is trained using the training set and validated based on the validation set. The ambient temperature value is input into the trained model to calculate the corresponding temperature compensation coefficient, and it is verified.

[0107] Apply the temperature compensation coefficient

[0108] Extract the original measurement data of the primary voltage amplitude and phase angle of the CVT from the voltage measurement device, and obtain the temperature compensation coefficient calculated based on the ambient temperature information. We construct a mathematical model to describe the relationship according to the characteristics of the CVT and the influence of temperature on the voltage amplitude, and use the determined compensation model to apply the temperature compensation coefficient to the original voltage amplitude data. The specific compensation model is:

[0109] V 补偿 =V 原始 ×(1 + α·ΔT)

[0110] Where, V 原始 is the original voltage amplitude, α is the temperature coefficient of the voltage amplitude, and ΔT is the temperature change;

[0111] Similarly, we construct a mathematical model to describe the relationship according to the characteristics of the CVT and the influence of temperature on the voltage phase angle, and use the determined compensation model to apply the temperature compensation coefficient to the original phase angle data. The specific compensation model is:

[0112] The specific compensation model is:

[0113] θ 补偿 =θ 原始 ×(1 + β·ΔT)

[0114] Where, θ 原始 is the original voltage phase angle, β is the temperature coefficient of the voltage phase angle, and ΔT is the temperature change.

[0115] Analyze the compensated data

[0116] After obtaining the compensated voltage amplitude and phase angle data, we analyze this data to observe the variation trends of the voltage amplitude and phase angle over time. Compare the compensated data with the preset normal operation thresholds to determine whether it is within the normal range. Based on the variations of the voltage amplitude and phase angle, evaluate the state of the internal capacitors of the CVT, identify any abnormal voltage or phase changes, and conduct further diagnostic tests, including dielectric loss tests or capacitance value measurements. Record the results of all diagnostic tests, and based on the data analysis and diagnostic test results, evaluate whether the CVT requires maintenance or replacement, and formulate a maintenance plan, including a maintenance schedule and required resources.

[0117] Collect historical operation data

[0118] We extract the required historical operation data from the database or data storage system, including but not limited to voltage amplitude, phase angle, and ambient temperature. Check whether the extracted data is complete to ensure that no key measurement values are missing. Preprocess the collected data, including data cleaning to remove outliers and noise, formatting, and standardization. Conduct statistical analysis on the performance parameters at different ambient temperatures to identify the relationship between the performance parameters and the ambient temperature. Use regression analysis to identify the variation trends of the performance parameters over time, as well as the relationship between the trends and the changes in the ambient temperature, and conduct a correlation analysis to determine the correlation strength between the performance parameters and the ambient temperature.

[0119] Establish a prediction model

[0120] According to the influencing parameters of the capacitive voltage transformer error model, determine the key parameters, including the interphase leakage current of the capacitive voltage transformer and the secondary load of the current transformer. Construct a capacitive voltage transformer error model, which includes the ratio error and phase angle error as outputs, and the leakage current and secondary load as inputs. Use an autoregressive radial basis function neural network, and optimize the clustering of the RBF network through the ant colony algorithm to determine the center and radius of the basis function of the network. Adopt a particle swarm algorithm to dynamically update the weights of the output layer of the RBF to obtain the optimal weight parameters.

[0121] Input the capacitive voltage transformer error data before the current moment and the capacitive voltage transformer ambient parameter data at the current moment into the capacitive voltage transformer error model. Using the trained RBF neural network model, predict the error of the capacitive voltage transformer at the current moment according to the input data. Preprocess the historical capacitive voltage transformer error data input into the RBF neural network, output the predicted error value, and obtain the warning of the metering error exceeding the limit and the deterioration trend information of the capacitive voltage transformer.

[0122] The system of this embodiment includes the following units:

[0123] The voltage amplitude detection unit is used to detect the primary voltage amplitude of the CVT. The voltage phase angle detection unit is used to detect the primary voltage phase angle of the CVT. The temperature information acquisition unit is used to acquire the ambient temperature information. The temperature compensation calculation unit is used to calculate the temperature compensation coefficient according to the ambient temperature information, including a mathematical relationship determination unit and a coefficient calculation unit. The mathematical relationship determination unit is used to determine the mathematical relationship between the ambient temperature and the CVT performance parameters; the coefficient calculation unit is used to calculate the temperature compensation coefficient according to the mathematical relationship and the ambient temperature value. The voltage compensation unit is used to compensate the primary voltage amplitude and phase angle by applying the temperature compensation coefficient, including an amplitude adjustment unit and a phase angle adjustment unit. The amplitude adjustment unit is used to adjust the primary voltage amplitude according to the temperature compensation coefficient; the phase angle adjustment unit is used to adjust the primary voltage phase angle according to the temperature compensation coefficient.

[0124] Based on the CVT internal capacitance state comprehensive evaluation method and system with temperature compensation designed according to the present invention, by accurately detecting the primary voltage amplitude and phase angle of the capacitive voltage transformer and combining the ambient temperature information, this method can calculate an accurate temperature compensation coefficient, thereby effectively correcting the influence of temperature change on the performance of the CVT. Secondly, by analyzing the compensated data, this system can more accurately evaluate the internal capacitance state of the CVT, timely discover abnormalities, prevent potential failures, and improve the stability and reliability of the power system. In addition, this method also includes the collection and analysis of historical operation data, which can establish a prediction model between performance parameters and ambient temperature, improve the performance evaluation accuracy of the CVT, and reduce errors caused by temperature changes.

[0125] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the various embodiments, reference can be made to each other.

[0126] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation, characterized in that It includes the following steps: S1. Detect the primary voltage amplitude and phase angle of the capacitive voltage transformer to obtain the performance parameters of the capacitive voltage transformer; S2. Obtain the ambient temperature information; S3. Determine the mathematical relationship between the ambient temperature and the performance parameters of the capacitive voltage transformer, and calculate the temperature compensation coefficient according to the mathematical relationship and the ambient temperature value; S4. Apply the temperature compensation coefficient to compensate the primary voltage amplitude and phase angle; S5. Analyze the compensated voltage amplitude and phase angle data to obtain the analysis result, and evaluate whether the internal capacitance state of the capacitive voltage transformer is normal according to the analysis result.

2. The comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation according to claim 1, wherein, The evaluation method further includes: S6. Collect the historical operation data of the capacitive voltage transformer; S7. Statistically analyze the performance parameters of the capacitive voltage transformer at different ambient temperatures, and identify the correlation between the performance parameters and the ambient temperature; S8. Establish a prediction model between the performance parameters and the ambient temperature, and predict the comprehensive state of the capacitive voltage transformer based on the prediction model and the ambient temperature information.

3. A comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation according to claim 1, characterized in that, The specific content of S1 is as follows: Prepare voltage measurement equipment, including a digital multimeter, an oscilloscope or a dedicated voltage tester; Calibrate the measurement equipment so that the measurement range and accuracy of the voltage measurement equipment meet the measurement requirements of the primary side voltage of the capacitive voltage transformer; Connect the probe or test line of the measurement equipment to the primary side terminal of the capacitive voltage transformer according to the safety operation regulations, ensuring a firm and good contact; Turn on the voltage measurement equipment for measurement, and record the voltage amplitude and phase angle data of the primary side of the capacitive voltage transformer; Conduct a preliminary verification on the recorded voltage amplitude and phase angle data to check for abnormal readings or errors.

4. A comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation according to claim 1, characterized in that The specific content of S2 is as follows: Place the temperature sensor at a position that can accurately reflect the ambient temperature of the capacitive voltage transformer, ensuring that the sensor is not affected by direct radiant heat, air flow or other factors that may affect the reading. Read and record the ambient temperature data displayed by the temperature sensor, and conduct a preliminary verification on the recorded temperature data to check for abnormal readings or errors.

5. A comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation according to claim 1, characterized in that The specific content of S3 is as follows: Collect and analyze the performance parameter data of the capacitive voltage transformer at different ambient temperatures to determine the influence of temperature change on the performance of the transformer. Based on the performance parameter data, construct a training set and a validation set; Construct a performance parameter model describing the relationship between the ambient temperature and the performance parameters of the transformer, train the performance parameter model through the training set, and validate the performance parameter model based on the validation set; Input the ambient temperature value into the trained performance parameter model, calculate the corresponding temperature compensation coefficient according to the input ambient temperature value, and verify the calculated temperature compensation coefficient.

6. The comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation according to claim 1, characterized in that The specific content of S4 is as follows: Extract the original measurement data of the primary voltage amplitude and phase angle of the capacitive voltage transformer from the voltage measurement equipment, obtain the temperature compensation coefficient calculated according to the ambient temperature information, and confirm that the compensation coefficient is for the current measurement environment and equipment characteristics; According to the characteristics of the capacitive voltage transformer and the influence of temperature on the voltage amplitude, construct a mathematical model to describe the relationship, and use the determined compensation model to apply the temperature compensation coefficient to the original voltage amplitude data; Specifically, the compensation model is specifically: V 补偿 = V 原始 × (1 + α·ΔT) Where, V 原始 is the original voltage amplitude, α is the temperature coefficient of the voltage amplitude, and ΔT is the temperature change; According to the characteristics of the capacitive voltage transformer and the influence of temperature on the voltage phase angle, a mathematical model is constructed to describe the relationship. Using a determined compensation model, the temperature compensation coefficient is applied to the original phase angle data; Specifically, the compensation model is specifically as follows: θ 补偿 = θ 原始 × (1 + β·ΔT) where θ 原始 is the original voltage phase angle, β is the temperature coefficient of the voltage phase angle, and ΔT is the temperature change.

7. A comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation according to claim 1, characterized in that, Specifically, S5 is as follows: Obtain the compensated voltage amplitude and phase angle data, analyze the compensated data, observe the variation trends of the voltage amplitude and phase angle over time, compare the compensated data with the preset normal operation thresholds to determine whether it is within the normal range, evaluate the state of the internal capacitance of the capacitive voltage transformer according to the variations of the voltage amplitude and phase angle, identify any abnormal voltage or phase changes, conduct further diagnostic tests, including dielectric loss tests or capacitance value measurements, record the results of all diagnostic tests, and based on the data analysis and diagnostic test results, evaluate whether the capacitive voltage transformer needs maintenance or replacement, and formulate a maintenance plan, including a maintenance schedule and the required resources.

8. A comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation according to claim 2, characterized in that Specifically, S7 is as follows: Extract the required historical operation data from a database or data storage system, including but not limited to voltage amplitude, phase angle, and ambient temperature. Check whether the extracted data is complete to ensure that there are no missing key measurement values. Preprocess the collected data, including data cleaning to remove outliers and noise, formatting, and standardization. Conduct a statistical analysis of the performance parameters at different ambient temperatures to identify the relationship between the performance parameters and the ambient temperature. Use regression analysis to identify the variation trend of the performance parameters over time and the relationship between the trend and the variation of the ambient temperature. Conduct a correlation analysis to determine the correlation strength between the performance parameters and the ambient temperature.

9. A comprehensive evaluation method for the internal capacitance state of a CVT based on temperature compensation according to claim 2, characterized in that Specifically, S8 is as follows: According to the influencing parameters of the capacitive voltage transformer error model, determine the key parameters, including the inter-phase leakage current of the capacitive voltage transformer and the secondary load of the current transformer. Construct a capacitive voltage transformer error model, which includes the ratio error and the angle error as outputs, and the leakage current and the secondary load as inputs; Use an autoregressive radial basis function neural network. Optimize the clustering of the RBF network through the ant colony algorithm to determine the center and radius of the basis function of the network. Dynamically update the weights of the output layer of the RBF using the particle swarm algorithm to obtain the optimal weight parameters; Input the capacitive voltage transformer error data before the current moment and the capacitive voltage transformer environmental parameter data at the current moment into the capacitive voltage transformer error model. Using the trained RBF neural network model, predict the error of the capacitive voltage transformer at the current moment according to the input data. Preprocess the capacitive voltage transformer error historical data input into the RBF neural network, output the predicted error value, and obtain the metering error overlimit warning and deterioration trend information of the capacitive voltage transformer.

10. A comprehensive evaluation system for the internal capacitance state of a CVT based on temperature compensation, applicable to any one of the comprehensive evaluation methods for the internal capacitance state of a CVT based on temperature compensation described in claims 1-9, characterized in that, Including: A voltage amplitude detection unit for detecting the primary voltage amplitude of the capacitive voltage transformer; A voltage phase angle detection unit for detecting the primary voltage phase angle of the capacitive voltage transformer; A temperature information acquisition unit for acquiring ambient temperature information; A temperature compensation calculation unit for calculating the temperature compensation coefficient according to the ambient temperature information, including a mathematical relationship determination unit and a coefficient calculation unit; A mathematical relationship determination unit for determining the mathematical relationship between the ambient temperature and the performance parameters of the capacitive voltage transformer; A coefficient calculation unit for calculating the temperature compensation coefficient according to the mathematical relationship and the ambient temperature value. A voltage compensation unit for compensating the amplitude and phase angle of the primary voltage by applying the temperature compensation coefficient, including an amplitude adjustment unit and a phase angle adjustment unit. The amplitude adjustment unit is used to adjust the amplitude of the primary voltage according to the temperature compensation coefficient; the phase angle adjustment unit is used to adjust the phase angle of the primary voltage according to the temperature compensation coefficient.

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