Residual current abrupt change detection method and device and storage medium

Abstract

The invention provides a residual current abrupt change detection method, which comprises the following steps of acquiring residual current, improving the accuracy of the residual current, processing the residual current by adopting a continuous moving variable quantity method, predicting future residual current, and calculating abrupt change leakage current through the predicted residual current. Through denoising technologies such as FFT and a filter, and an optimized abrupt change electric leakage detection algorithm, the detection speed and precision of residual current abrupt change are significantly improved. Only limited historical data needs to be stored, the occupation of storage capacity is reduced, the hardware cost is reduced, an exponential smoothing algorithm is introduced for prediction, the requirement for measuring and calculating the residual electric quantity at the follow-up moment is reduced, the measuring and calculating speed is further improved, and the method has certain perspectiveness.

Description

Technical Field

[0001] The present invention relates to the technical field of power system monitoring, and in particular to a residual current mutation detection method, device and storage medium. Background Art

[0002] In the power system, the monitoring of residual current (also called leakage current) is crucial to prevent electrical fires and ensure the safety of electricity use.

[0003] There are two traditional methods for measuring residual current. One is to measure the current of the neutral line and the live line separately, and obtain the residual current in the neutral line by online differential between the neutral line and the live line. The other is to directly measure the leakage current by developing a leakage current sensor. The specific contents of the two methods are as follows:

[0004] Solution 1: Measure the live and neutral current data of each household through the live and neutral wires respectively, collect 15 minutes of current data by communication and send it to the concentrator or master station system, and calculate the leakage current value of each user by differential method.

[0005] Solution 2: Add a leakage current monitoring terminal at the user's site, select a dedicated leakage current sensor (with high precision), connect the transformer in series with the live wire and the neutral wire, and the secondary output current is the leakage current. The monitoring terminal monitors the leakage current in real time. When the value is normal, the leakage current data will be sent in a 15-minute cycle. When the leakage current exceeds the limit, it will be triggered to be sent actively (the upper limit of the abnormal leakage current for general residents is greater than 30mA).

[0006] Although the calculation method of Solution 1 is more economical, there are some technical problems that affect the leakage current measurement accuracy in application; Solution 2 uses leakage current sensors and monitoring terminals to improve the leakage current monitoring accuracy, but requires the addition of additional monitoring terminals, and both solutions do not have the function of predicting residual current. The residual current must be determined based on the current measurement value, which is not forward-looking. Summary of the invention

[0007] The object of the present invention is to provide a residual current mutation detection method, device and storage medium to solve the problems raised in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solution: a residual current mutation detection method, characterized in that it comprises the following steps:

[0009] 1) Obtain the residual current and improve the accuracy of the residual current;

[0010] 2) Use the continuous moving variation method to process the residual current;

[0011] 3) Predict the future residual current and calculate the sudden leakage current based on the predicted residual current.

[0012] Preferably, the specific method for obtaining the residual current in step 1) is:

[0013] Through the embedded residual current transformer in the smart electricity meter, the current signal is converted into a small signal that can be used for electronic measurement. Then a dedicated electricity measurement chip is used to convert the converted current analog signal into a digital signal, and a digital integration operation is performed on it. The pulse signal is then output with a frequency proportional to the electric energy. The pulse signal is sent to the microcontroller unit, which analyzes the specific value of the sudden change current.

[0014] Preferably, the specific method for improving the accuracy of the residual current in step 1) is:

[0015] FFT (Fast Fourier Transform) is used to process small signals to reduce signal noise. The residual current true effective value algorithm based on FFT is adopted. The formula is:

[0016]

[0017] Among them, I RMS is the effective value of the residual current; K f is the form factor of the sine wave, is the average current, T is the period, and i is the current value at time t;

[0018] Through discretization processing, we can get:

[0019]

[0020] Preferably, the specific steps of the moving average method in step 2) are:

[0021] Compare the residual current at each moment with the residual current at the previous fixed time interval to calculate the sudden leakage current at that moment. The formula is as follows:

[0022] I Δt =I t -I m

[0023] Among them I Δt is the newly generated fault leakage current, I t is the residual current at time t, I m is the residual current at time m before time t.

[0024] Preferably, in step 3), the exponential averaging method is used to predict the future residual current.

[0025] Preferably, the specific steps of the exponential averaging method are:

[0026] 3.1) Choose a smoothing constant α to represent the weight of more recent data points;

[0027] 3.2) Take the first data point as the first smoothed data point;

[0028] 3.3) Starting from the second data point, use the exponential smoothing formula to calculate the smoothed data point: S(t) = α*X(t) + (1-α)*S(t-1), where X(t) is the current original data point and S(t-1) is the previous smoothed data point;

[0029] 3.4) Repeat step 3.3) to calculate the smoothed values ​​of the required data points.

[0030] Preferably, the smoothing constant is calculated as follows: α=2 / (n+1), (0<α<1).

[0031] Preferably, the specific steps of calculating the sudden leakage current by predicting the residual current in step 3) are:

[0032] Detect the frequency k required for the sudden leakage current to reach the stable current state, then I k represents the residual current at the previous k moments, then

[0033] I Δt =I t -I K

[0034] The above exponential smoothing method is introduced to predict the residual current I at k moments after moment c based on moment c. c+k , update formula:

[0035] I Δt =I c+k -I c

[0036] A residual current mutation detection device, comprising:

[0037] Residual current measurement module: obtains residual current and improves the accuracy of residual current;

[0038] Residual current processing module: uses the continuous moving variation method to process the residual current;

[0039] Prediction processing module: predicts future residual current and calculates sudden leakage current based on the predicted residual current.

[0040] A storage medium stores a computer program, which implements a residual current mutation detection method when executed by a processor.

[0041] Compared with the prior art, the present invention has the following beneficial effects: 1. Through denoising techniques such as FFT and filters, and an optimized mutation leakage detection algorithm, the detection speed and accuracy of residual current mutations are significantly improved.

[0042] 2. Reduce storage capacity requirements: Only limited historical data needs to be stored, which reduces storage capacity and hardware costs.

[0043] 3. Improve calculation efficiency: The exponential smoothing algorithm is introduced for prediction, which reduces the need to calculate the remaining power at subsequent times, further improves the calculation rate, and has a certain degree of foresight. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flow chart of the present invention;

[0045] Figure 2 It is a flow chart of residual current sampling signal processing;

[0046] Figure 3 This is the module diagram of the residual current mutation detection device. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in 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.

[0048] Embodiment 1

[0049] See also Figure 1-Figure 2 As shown, the present invention provides a technical solution: a residual current mutation detection method, which converts the current signal into a small signal that can be used for electronic measurement by embedding a residual current transformer in an intelligent electric energy meter, and then uses a dedicated intelligent electric energy measurement chip to convert the converted current analog signal into a digital signal, and performs digital integration operation on it, and then outputs a pulse signal whose frequency is proportional to the electric energy, and the pulse signal is sent to a microcontroller unit, wherein the microcontroller unit is a single-chip microcomputer processing unit, so as to obtain a specific value of the mutation current;

[0050] In order to improve the accuracy of residual current detection, FFT (Fast Fourier Transform) is used to process small signals and reduce signal noise. The residual current true effective value algorithm based on FFT is adopted. The formula is:

[0051]

[0052] Among them, I RMS is the effective value of the residual current; Kf is the form factor of the sine wave, is the average current, T is the period, and i is the current value at time t;

[0053] Through discretization processing, we can get:

[0054]

[0055] The residual current is processed by the continuous moving variation method. Specifically, the residual current at each moment is compared with the residual current at the previous fixed time interval to calculate the sudden leakage current at that moment. The formula is as follows:

[0056] I Δt =I t -I m

[0057] Among them I Δt is the newly generated fault leakage current, I t is the residual current at time t, I m is the residual current at time m before time t;

[0058] The residual current at the future moment is calculated by the exponential smoothing method; the specific steps of the exponential smoothing method are:

[0059] 1) Choose a smoothing constant α to weight more recent data points

[0060] 2) Initially, take the first data point as the first smoothed data point;

[0061] 3) Starting from the second data point, use the exponential smoothing formula to calculate the smoothed data point: S(t) = α*X(t) + (1-α)*S(t-1), where X(t) is the current original data point and S(t-1) is the previous smoothed data point;

[0062] 4) Repeat the above steps to calculate the smoothed values ​​of all data points.

[0063] Since the time series of the sudden residual current (the sudden residual current that changes with time) is relatively stable, the n time series before the prediction period are used to determine the optimal value of the smoothing coefficient α.

[0064] The calculation formula of α is: α = 2 / (n+1), (0<α<1);

[0065] Detect the frequency k required for the sudden leakage current to reach the stable current state, then I k represents the residual current at the previous k moments, then

[0066] I Δt =I t-I K

[0067] The above exponential smoothing method is introduced to predict the residual current I at k moments after moment c based on moment c. c+k , update formula:

[0068] I Δt =I c+k -I c

[0069] It can be seen that the residual current at the next k moments is predicted based on the current moment, and the residual current at the future moment is used as the current mutation current in the mutation leakage current calculation formula to calculate the newly generated mutation current.

[0070] It should be noted that the specific predicted residual current at a certain moment is determined according to actual use. If the residual current at more future moments cannot be accurately predicted, the predicted moments can be reduced.

[0071] By adopting the continuous moving change method to process the residual current, there is no need to memorize all historical data, which reduces the storage capacity. The matching exponential smoothing method has a prediction function, which can estimate the newly generated fault leakage current without waiting for the arrival of subsequent moments, thereby improving the calculation rate of the remaining power.

[0072] Embodiment 2

[0073] In order to solve the problem that leakage will cause the leakage protector of the transformer in the substation to operate, the following method is used to realize relay tripping control:

[0074] The output signal of the residual current transformer is amplified, and the amplified signal is compared with the reference value of the comparator, and the residual current value is compared with the preset threshold value in real time. If the residual current value does not exceed the threshold value, the comparator outputs a non-interrupt signal, and the single-chip microcomputer does not disconnect the relay;

[0075] Once the residual current value exceeds the threshold, the comparator outputs a terminal signal to the microcontroller interrupt interface. After receiving the interrupt signal, the microcontroller responds and processes in real time, and controls the relay to disconnect the phase line. It can also control the relay to trip or not trip according to internal settings, and record the time when the current leakage current exceeds the limit, the residual current value and some related parameters at this moment. The recorded data can be read through the communication port or the time can be displayed on the display device or actively reported. Corresponding early warning operations can also be performed to indicate that leakage has occurred.

[0076] Embodiment 3

[0077] like Figure 3 As shown, a residual current mutation detection device includes

[0078] Residual current measurement module: obtains residual current and improves the accuracy of residual current;

[0079] Residual current processing module: uses the continuous moving variation method to process the residual current;

[0080] Prediction processing module: predicts future residual current and calculates sudden leakage current based on the predicted residual current.

[0081] Embodiment 4

[0082] A storage medium stores a computer program, which implements a residual current mutation detection method when executed by a processor.

[0083] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A residual current mutation detection method, characterized in that: The steps include: 1) Obtain the residual current and improve the accuracy of the residual current; 2) Use the continuous moving variation method to process the residual current; 3) Predict the future residual current and calculate the sudden leakage current based on the predicted residual current.

2. A residual current mutation detection method according to claim 1, characterized in that: The specific method for obtaining the residual current in step 1) is: Through the embedded residual current transformer in the smart electricity meter, the current signal is converted into a small signal that can be used for electronic measurement. Then a dedicated electricity measurement chip is used to convert the converted current analog signal into a digital signal, and a digital integration operation is performed on it. The pulse signal is then output with a frequency proportional to the electric energy. The pulse signal is sent to the microcontroller unit, which analyzes the specific value of the sudden change current.

3. A residual current mutation detection method according to claim 1, characterized in that: The specific method for improving the accuracy of residual current in step 1) is: FFT (Fast Fourier Transform) is used to process small signals to reduce signal noise. The residual current true effective value algorithm based on FFT is adopted. The formula is: Among them, I RMS is the effective value of the residual current; K f is the form factor of the sine wave, is the average current, T is the period, and i is the current value at time t; Through discretization processing, we can get:

4. A residual current mutation detection method according to claim 1, characterized in that: The specific steps of the moving average method in step 2) are: Compare the residual current at each moment with the residual current at the previous fixed time interval to calculate the sudden leakage current at that moment. The formula is as follows: I Δt =I t -I m Among them I Δt is the newly generated fault leakage current, I t is the residual current at time t, I m is the residual current at time m before time t.

5. A residual current mutation detection method according to claim 1, characterized in that: In step 3), the exponential averaging method is used to predict the future residual current.

6. A residual current mutation detection method according to claim 5, characterized in that: The specific steps of the exponential averaging method are: 3.1) Choose a smoothing constant α to represent the weight of more recent data points; 3.2) Take the first data point as the first smoothed data point; 3.3) Starting from the second data point, use the exponential smoothing formula to calculate the smoothed data point: S(t) = α*X(t) + (1-α)*S(t-1), where X(t) is the current original data point and S(t-1) is the previous smoothed data point; 3.4) Repeat step 3.3) to calculate the smoothed values ​​of the required data points.

7. A residual current mutation detection method according to claim 6, characterized in that: The calculation method of the smoothing constant is: α=2 / (n+1), (0<α<1).

8. A residual current mutation detection method according to claim 1, characterized in that: The specific steps of calculating the sudden leakage current by predicting the residual current in step 3) are: Detect the frequency k required for the sudden leakage current to reach the stable current state, then I k represents the residual current at the previous k moments, then I Δt =I t -I K The above exponential smoothing method is introduced to predict the residual current I at k moments after moment c based on moment c. c+k , update formula: I Δt =I c+k -I c 。 9. A residual current mutation detection device, characterized in that: include Residual current measurement module: obtains residual current and improves the accuracy of residual current; Residual current processing module: uses the continuous moving variation method to process the residual current; Prediction processing module: predicts future residual current and calculates sudden leakage current through the predicted residual current.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the residual current mutation detection method according to any one of claims 1 to 8 is implemented.

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