Standard current transformer self-calibration platform and whole-process encryption supervision metering system

Abstract

The invention discloses a standard current transformer self-calibration platform and a whole-process encryption supervision metering system, and relates to the technical field of power equipment calibration and data safety monitoring, and the standard current transformer self-calibration platform comprises a data collection unit which collects the real-time current data of a standard current transformer and a calibrated current transformer through a current sensor, meanwhile, system operation environment parameters are collected; and the self-calibration operation module is used for calculating an error value of the calibrated current transformer by applying a preset self-calibration algorithm based on the acquired data of the standard current transformer and the calibrated current transformer, and generating a calibration compensation instruction according to the error value. Through a self-calibration algorithm and data collected in real time, error calculation and calibration compensation of the calibrated current transformer can be automatically completed, frequent manual field operation is not needed, calibration efficiency is greatly improved, manpower and time cost is reduced, and the method is suitable for calibration requirements of the current transformer in a large-scale power system.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment calibration and data security monitoring, and specifically relates to a self-calibration platform for standard current transformers and a whole-process encrypted supervision metering system. Background Art

[0002] In the power system, as a high-precision current measurement and calibration reference device, the accuracy of the standard current transformer plays a crucial role in power metering, relay protection, and the stable operation of the power system. However, the traditional calibration work of standard current transformers often faces many challenges.

[0003] On the one hand, conventional calibration requires professional personnel to carry calibration equipment to the site, and the operation process is cumbersome and time-consuming. It is difficult to calibrate a large number of widely distributed current transformers in a timely and efficient manner, especially in some areas with harsh environments and inconvenient transportation, where it is more difficult to carry out calibration work.

[0004] On the other hand, with the development of the digitalization and intelligentization of the power system, the requirements for the security of calibration data and the strictness of metering supervision are increasing day by day. The traditional calibration process lacks effective data encryption measures, making the data at risk of being stolen and tampered with during transmission and storage, and it is difficult to meet the high requirements for data security in modern power systems. At the same time, most of the existing metering supervision means rely on manual regular inspections, and it is impossible to realize the whole-process real-time supervision of the calibration process and the operation status of the current transformer, and it is difficult to quickly discover potential error problems and equipment failure hidden dangers, which may lead to inaccurate power metering and even affect the reliable operation of the power system. Summary of the Invention

[0005] To solve the above technical problems, a self-calibration platform for standard current transformers and a whole-process encrypted supervision metering system are provided, and this technical solution solves the above problems.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A self-calibration platform for standard current transformers and a whole-process encrypted supervision metering system, including:

[0008] A data acquisition unit: through a current sensor, collect the real-time current data of the standard current transformer and the current transformer to be calibrated, and at the same time collect the system operation environment parameters;

[0009] A self-calibration operation module: based on the data of the standard current transformer and the current transformer to be calibrated collected, use a preset self-calibration algorithm to calculate the error value of the current transformer to be calibrated, and generate a calibration compensation instruction according to the error value;

[0010] Encryption communication module: Adopt a specific encryption algorithm to encrypt the data transmitted between units within the system and the data communicated with the outside;

[0011] Supervision and metrology module: Continuously monitor the operating status of the system, including the working status of equipment and the accuracy of calibration data, judge the calibration results according to metrology standards, and generate a supervision and metrology report;

[0012] Control and storage unit: Receive data from each unit and store it, build a user operation interface for users to set system parameters and start the calibration process remotely or locally.

[0013] Preferably, the data acquisition unit determines the installation areas of the standard current transformer and the current transformer to be calibrated, constructs an equipment layout diagram covering the installation areas, divides several monitoring sub-areas on the layout diagram, sets monitoring points at key positions in each sub-area, arranges sensors at the monitoring points, and the data collected by the sensors includes the real-time current values of the standard current transformer and the current transformer to be calibrated, the surrounding electromagnetic interference intensity, and the environmental temperature and humidity data. Summarize these data to construct a comprehensive parameter set for the system operation. Obtain the real-time current data sequence {I1i} of the standard current transformer at a certain monitoring point from the sensor, where i = 1, 2,..., n, and n represents the number of data points. Calculate the average value of the real-time current of the standard current transformer. The specific calculation formula is as follows:

[0014]

[0015] Based on the obtained real-time current value I2 of the current transformer to be calibrated and the average value of the real-time current of the standard current transformer Assume the transformation ratio of the current transformer is k, and calculate the theoretical output current value of the current transformer to be calibrated. The specific calculation formula is as follows:

[0016]

[0017] Calculate the deviation rate between the actual output current and the theoretical output current of the current transformer to be calibrated. The calculation formula is as follows:

[0018]

[0019] Obtain the environmental temperature data sequence {Tj} from the sensor data, where j = 1, 2,..., m, and m represents the number of temperature data points. Calculate the average environmental temperature. The formula is as follows:

[0020]

[0021] Based on the calculation of the above various parameters, construct a comprehensive parameter reflecting the system operation status.

[0022] Preferably, the specific calculation formula of the comprehensive parameter is as follows:

[0023]

[0024] Among them, α, β, and γ respectively represent weights, E is the electromagnetic interference intensity value, and the comprehensive parameter P can comprehensively reflect the system operation state and the calibration state of the current transformer.

[0025] Preferably, the self - calibration operation module continuously monitors the standard current transformer and the current transformer to be calibrated based on the comprehensive parameters collected by the data acquisition unit, collects historical calibration data, cleans and pre - processes the data, divides the data into a training set, a validation set, and a test set, inputs the real - time collected current data into a pre - constructed self - calibration model for prediction, randomly initializes the parameters of the self - calibration model, and records the true error value marked as the first sample as e i , and the predicted error value of the model is denoted as The mean absolute error is used as the loss function, and its calculation formula is as follows:

[0026]

[0027] Among them, n represents the number of samples in the training set. Input the training set data into the self - calibration model for forward propagation. In the hidden layer of the model, the output of each neuron is:

[0028]

[0029] where w ij represents the weight connecting the i - th neuron in the input layer to the j - th neuron in the hidden layer, x i is the value of the i - th neuron in the input layer, b j represents the bias of the j - th neuron in the hidden layer, and f is the activation function;

[0030] Use backpropagation to calculate the gradients of the loss function with respect to each weight and bias. For the output layer, the gradients are calculated according to the derivatives of the loss function with respect to the output. The derivatives of the mean absolute error loss function with respect to the weights and biases of the output layer are respectively:

[0031]

[0032] Among them, l represents the neuron serial number in the output layer, sgn is the sign function. Use the optimization algorithm to update the weights and biases according to the calculated gradients. The specific calculation formulas for updating the weights and biases are as follows:

[0033]

[0034] Among them, \(t\) represents the number of iterations, and \(\eta\) represents the learning rate. Repeat the above steps of forward propagation, loss calculation, backpropagation, and parameter update until a predetermined number of training epochs is reached.

[0035] Preferably, according to the prediction result of the self-calibration model, a calibration compensation signal is generated. If the predicted error value indicates that the output current of the calibrated current transformer is too large, the output current is reduced by adjusting the calibration circuit parameters; if indicates that the output current of the calibrated current transformer is too small, the calibration circuit parameters are adjusted to increase the output current.

[0036] Preferably, the supervision and metering module compares and analyzes the calibration result generated by the self-calibration operation module with the metering standard, and simultaneously monitors the system operation status data. Let the current error control deviation be \(\Delta I\), the environmental parameter control deviation be \(\Delta E\), and the calibration time control deviation be \(\Delta t\). And set the weight of the current error control deviation to \(w_1\), the weight of the environmental parameter control deviation to \(w_2\), and the weight of the calibration time control deviation to \(w_3\), and satisfy \(w_1 + w_2 + w_3 = 1\).

[0037] Preferably, the specific calculation formula of the deviation index is as follows:

[0038]

[0039] Among them, \(I\) 允许偏差 , \(E\) 允许偏差 , \(t\) 允许偏差 respectively represent the allowable deviation ranges of the set current error, environmental parameters, and calibration time. Based on the calculation of the deviation, it is judged whether the calibration result and the system operation status meet the expectations. When \(D\leq D\) 阈值 , it indicates that the overall operation situation meets the expectations. When \(D > D\) 阈值时 , it indicates that there are deviations in the overall operation. When deviations are detected, the parameters of the self-calibration model or the system operation parameters are optimized and adjusted.

[0040] Preferably, the control and storage unit receives the feedback data of each unit and stores it, provides a remote monitoring interface. Users can view the status, operation parameters, calibration results, and supervision and metering reports of the standard current transformer and the calibrated current transformer in real time. Users can remotely send control commands, including starting the self-calibration process, modifying calibration parameters, and adjusting the system operation mode. The control commands are transmitted to the corresponding execution units of the system through the encrypted communication module, and the execution units execute the corresponding operations issued by the control commands.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows: By virtue of the preset self-calibration algorithm and the real-time collected data, the error calculation and calibration compensation of the current transformer to be calibrated can be automatically completed without frequent on-site manual operations, greatly improving the calibration efficiency. It can calibrate a large number of current transformers in a short time, reducing the labor and time costs, and is particularly suitable for the calibration requirements of current transformers in large-scale power systems. In terms of data security guarantee, the system adopts an advanced encryption algorithm to encrypt the data transmitted between various units within the system and the data communicated with the outside, effectively preventing the data from being stolen or tampered with during the transmission and storage processes, ensuring the security and integrity of the calibration data and the system operation data, and laying a data security foundation for the accuracy and reliability of power metering. At the same time, the supervision and metering module can continuously monitor the operation status of the system, covering the equipment working status, the accuracy of calibration data, etc., and judge the calibration result according to the metering standard. By real-time collecting and analyzing various operation parameters, potential problems such as the error abnormality of the current transformer and equipment failures can be detected in time, realizing the whole-process real-time supervision of the calibration process and the operation status of the current transformer, which helps to quickly take measures for adjustment and repair, ensure the accuracy of power metering, and improve the stability and reliability of the power system operation. Brief Description of the Drawings

[0042] Figure 1 It is the system flow chart of the present invention. Detailed Embodiments

[0043] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variants.

[0044] Referring to Figure 1 as shown, the standard current transformer self-calibration platform and the whole-process encrypted supervision and metering system include:

[0045] Data acquisition unit: Through the current sensor, it acquires the real-time current data of the standard current transformer and the current transformer to be calibrated, and at the same time acquires the system operation environment parameters;

[0046] Self-calibration operation module: Based on the data of the standard current transformer and the current transformer to be calibrated collected, it uses the preset self-calibration algorithm to calculate the error value of the current transformer to be calibrated, and generates a calibration compensation instruction according to the error value;

[0047] Encryption communication module: Adopts a specific encryption algorithm to encrypt the data transmitted between various units within the system and the data communicated with the outside;

[0048] Supervision and metering module: Continuously monitors the operation status of the system, including the equipment working status, the accuracy of calibration data, judges the calibration result according to the metering standard, and generates a supervision and metering report;

[0049] Control and storage unit: Receives data from each unit and stores it, and builds a user operation interface for the user to set system parameters and start the calibration process remotely or locally.

[0050] Specifically, the data acquisition unit determines the installation areas of the standard current transformer and the current transformer to be calibrated, constructs a layout diagram of the equipment covering the installation areas, divides several monitoring sub-areas on the layout diagram, sets monitoring points at key positions in each sub-area, arranges sensors at the monitoring points, and the data collected by the sensors includes the real-time current values of the standard current transformer and the current transformer to be calibrated, the surrounding electromagnetic interference intensity, and the environmental temperature and humidity data. These data are summarized to construct a comprehensive parameter set for the system operation. Obtain the real-time current data sequence {I1i} of the standard current transformer at a certain monitoring point from the sensor, where i = 1, 2,..., n, and n represents the number of data points. Calculate the average value of the real-time current of the standard current transformer. The specific calculation formula is as follows:

[0051]

[0052] Based on the obtained real-time current value I2 of the current transformer to be calibrated and the average value of the real-time current of the standard current transformer Assume that the transformation ratio of the current transformer is k, and calculate the theoretical output current value of the current transformer to be calibrated. The specific calculation formula is as follows:

[0053]

[0054] Calculate the deviation rate between the actual output current and the theoretical output current of the current transformer to be calibrated. The calculation formula is as follows:

[0055]

[0056] Obtain the environmental temperature data sequence {Tj} from the sensor data, where j = 1, 2,..., m, and m represents the number of temperature data points. Calculate the average environmental temperature. The formula is as follows:

[0057]

[0058] Based on the calculation of the above various parameters, construct a comprehensive parameter reflecting the system operation state.

[0059] Specifically, the self - calibration operation module continuously monitors the standard current transformer and the current transformer to be calibrated based on the comprehensive parameters collected by the data acquisition unit, collects historical calibration data, cleans and pre - processes the data, divides the data into training set, validation set and test set, inputs the real - time collected current data into the pre - constructed self - calibration model for prediction, randomly initializes the parameters of the self - calibration model, and records the true error value marked as the first sample as e i , and the predicted error value of the model is denoted as The mean absolute error is used as the loss function, and its calculation formula is as follows:

[0060]

[0061] Where n represents the number of samples in the training set. Input the training set data into the self - calibration model for forward propagation. In the hidden layer of the model, the output of each neuron is:

[0062]

[0063] Where w ij represents the weight connecting the i - th neuron in the input layer to the j - th neuron in the hidden layer, x i is the value of the i - th neuron in the input layer, b j represents the bias of the j - th neuron in the hidden layer, and f is the activation function;

[0064] Use backpropagation to calculate the gradients of the loss function with respect to each weight and bias. For the output layer, the gradients are calculated according to the derivative of the loss function with respect to the output. The derivatives of the mean absolute error loss function with respect to the weights and biases in the output layer are respectively:

[0065]

[0066] Where l represents the neuron number in the output layer, sgn is the sign function. Use the optimization algorithm to update the weights and biases according to the calculated gradients. The specific calculation formulas for updating the weights and biases are as follows:

[0067]

[0068] Where t represents the number of iterations, η represents the learning rate. Repeat the above steps of forward propagation, calculating the loss, backpropagation and parameter update until the predetermined number of training epochs is reached.

[0069] Specifically, the encryption communication module uses a specific encryption algorithm to encrypt the data transmitted between units within the system and the data communicated with the outside. The control and storage unit receives the feedback data from each unit and stores it, providing a remote monitoring interface. Users can view the status, operating parameters, calibration results, and supervision measurement reports of the standard current transformer and the current transformer to be calibrated in real time. Users can remotely send control commands, including starting the self-calibration process, modifying calibration parameters, and adjusting the system operation mode. The control commands are transmitted to the corresponding execution units of the system through the encryption communication module, and the execution units execute the corresponding operations issued by the control commands.

[0070] Specifically, the supervision measurement module compares and analyzes the calibration results generated by the self-calibration operation module with the measurement standard, and simultaneously monitors the system operation status data. Let the current error control deviation be ΔI, the environmental parameter control deviation be ΔE, and the calibration time control deviation be Δt. And set the weight of the current error control deviation to w1, the weight of the environmental parameter control deviation to w2, and the weight of the calibration time control deviation to w3, and satisfy w1 + w2 + w3 = 1;

[0071] The specific calculation formula of the deviation index is as follows:

[0072]

[0073] Among them, I 允许偏差 , E 允许偏差 , t 允许偏差 respectively represent the allowable deviation ranges of the set current error, environmental parameters, and calibration time. Based on the calculation of the deviation, it is judged whether the calibration result and the system operation status meet the expectations. When D ≤ D 阈值 , it means that the overall operation situation meets the expectations. When D > D 阈值时 , it means that there are deviations in the overall operation. When deviations are detected, the self-calibration model parameters or system operation parameters are optimized and adjusted.

[0074] Specifically, the control and storage unit receives the feedback data from each unit and stores it, providing a remote monitoring interface. Users can view the status, operating parameters, calibration results, and supervision measurement reports of the standard current transformer and the current transformer to be calibrated in real time. Users can remotely send control commands, including starting the self-calibration process, modifying calibration parameters, and adjusting the system operation mode. The control commands are transmitted to the corresponding execution units of the system through the encryption communication module, and the execution units execute the corresponding operations issued by the control commands.

[0075] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements fall within the scope of the present invention claimed.

Claims

1. Standard current transformer self-calibration platform and whole-process encrypted supervision metering system, characterized in that Including: Data acquisition unit: Through current sensors, it acquires the real-time current data of the standard current transformer and the current transformer to be calibrated, and simultaneously acquires the system operation environment parameters; Self-calibration operation module: Based on the data of the standard current transformer and the current transformer to be calibrated collected, it uses a preset self-calibration algorithm to calculate the error value of the current transformer to be calibrated, and generates a calibration compensation instruction according to the error value; Encryption communication module: Adopts a specific encryption algorithm to encrypt the data transmitted between units within the system and the data communicated with the outside; Supervision and metrology module: Continuously monitors the operation status of the system, including the equipment working status and the accuracy of calibration data, determines the calibration result according to the metrology standard, and generates a supervision and metrology report; Control and storage unit: Receives the data from each unit and stores it, builds a user operation interface for users to set parameters for the system and start the calibration process remotely or locally.

2. The self-calibration platform for standard current transformers and the whole-process encrypted supervision metering system according to claim 1, characterized in that Determine the installation areas of the standard current transformer and the current transformer to be calibrated, construct an equipment layout diagram covering the installation areas, divide several monitoring sub-areas on the layout diagram, set monitoring points at key positions in each sub-area, arrange sensors at the monitoring points, and the data collected by the sensors includes the real-time current values of the standard current transformer and the current transformer to be calibrated, the surrounding electromagnetic interference intensity, and the environmental temperature and humidity data. Summarize these data to construct a comprehensive parameter set for the system operation. Obtain the real-time current data sequence {I1i} of the standard current transformer at a certain monitoring point from the sensor, where i = 1, 2,..., n, and n represents the number of data points. Calculate the average value of the real-time current of the standard current transformer, and its specific calculation formula is as follows: Based on the acquired real-time current value I2 of the calibrated current transformer and the real-time current average value of the standard current transformer Assume that the current transformer ratio is k, and calculate the theoretical output current value of the calibrated current transformer. The specific calculation formula is as follows: Calculate the deviation rate between the actual output current and the theoretical output current of the current transformer to be calibrated, and the calculation formula is as follows: Obtain the environmental temperature data sequence {Tj} from the sensor data, where j = 1, 2,..., m, and m represents the number of temperature data points. Calculate the average environmental temperature, and the formula is as follows: Based on the calculation of the above various parameters, construct a comprehensive parameter reflecting the system operation status.

3. The standard current transformer self-calibration platform and the whole-process encrypted supervision metering system according to claim 1, characterized in that, The specific calculation formula of the comprehensive parameter is as follows: Among them, α, β, and γ respectively represent weights, E is the electromagnetic interference intensity value, and the comprehensive parameter P can comprehensively reflect the system operation status and the calibration status of the current transformer.

4. The standard current transformer self-calibration platform and the whole-process encrypted supervision metering system according to claim 1, characterized in that The self-calibration operation module continuously monitors the standard current transformer and the current transformer to be calibrated based on the comprehensive parameters collected by the data acquisition unit, collects historical calibration data, cleans and preprocesses the data, divides the data into a training set, a validation set, and a test set, inputs the real-time collected current data into a pre-constructed self-calibration model for prediction, randomly initializes the parameters of the self-calibration model, and records the true error value marked as the first sample as e i , and the predicted error value of the model is denoted as The mean absolute error is used as the loss function, and its calculation formula is as follows: Among them, n represents the number of samples in the training set. Input the training set data into the self-calibration model for forward propagation. In the hidden layer of the model, the output of each neuron is: where, w ij represents the weight connecting the i-th neuron in the input layer to the j-th neuron in the hidden layer, x i is the value of the i-th neuron in the input layer, b j represents the bias of the j-th neuron in the hidden layer, and f is the activation function; Use backpropagation to calculate the gradients of each weight and bias for the loss function. For the output layer, the gradient is calculated according to the derivative of the loss function with respect to the output. The derivatives of the mean absolute error loss function with respect to the output layer weights and biases are respectively: Among them, l represents the neuron serial number of the output layer, sgn is the sign function. Use the optimization algorithm to update the weights and biases according to the calculated gradients. The specific calculation formulas for updating the weights and biases are as follows: Among them, t represents the number of iterations, η represents the learning rate. Repeat the above steps of forward propagation, loss calculation, backpropagation, and parameter update until the predetermined number of training epochs is reached.

5. The standard current transformer self-calibration platform and the whole-process encrypted supervision metering system according to claim 1, characterized in that According to the prediction result of the self-calibration model, a calibration compensation signal is generated. If the predicted error value indicates that the output current of the current transformer to be calibrated is too large, the output current is reduced by adjusting the calibration circuit parameters; if indicates that the output current of the current transformer to be calibrated is too small, the calibration circuit parameters are adjusted to increase the output current.

6. The self-calibration platform for standard current transformers and the whole-process encrypted supervision and metering system according to claim 1, characterized in that, The supervision and metering module compares and analyzes the calibration results generated by the self-calibration operation module with the metering standard, and simultaneously monitors the system operation status data. Let the current error control deviation be ΔI, the environmental parameter control deviation be ΔE, and the calibration time control deviation be Δt. Also, set the weight of the current error control deviation as w1, the weight of the environmental parameter control deviation as w2, and the weight of the calibration time control deviation as w3, and satisfy w1 + w2 + w3 = 1.

7. The standard current transformer self-calibration platform and the whole-process encrypted supervision metering system according to claim 1, characterized in that, The specific calculation formula of the deviation index is as follows: Among them, I 允许偏差 , E 允许偏差 , t 允许偏差 respectively represent the set current error, environmental parameters, and allowable deviation range of the calibration time. Based on the calculation of the deviation, it is judged whether the calibration result and the system operating state meet the expectations. When D ≤ D 阈值 , it means that the overall operation meets the expectations. When D > D 阈值时 , it means that there is a deviation in the overall operation. When a deviation is detected, the self-calibration model parameters or system operation parameters are optimized and adjusted.

8. The standard current transformer self-calibration platform and the whole-process encrypted supervision metering system according to claim 1, characterized in that The control and storage unit receives the feedback data of each unit and stores it, provides a remote monitoring interface. Users can view the status, operation parameters, calibration results, and supervision and metering reports of the standard current transformer and the current transformer to be calibrated in real time. Users can remotely send control commands, including starting the self-calibration process, modifying calibration parameters, and adjusting the system operation mode. The control commands are transmitted to the corresponding execution unit of the system through the encrypted communication module, and the execution unit executes the corresponding operations issued by the control commands.

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