Power distribution network overhead fault detection method, device and equipment and storage medium

Abstract

The invention provides a power distribution network overhead fault detection method, device and equipment and a storage medium method, and the method comprises the steps: collecting current signals of N points in at least one complete cycle of a sampling circuit, and extracting a fundamental current and a second harmonic in the current signals; calculating the ratio of the second harmonic to the fundamental current; setting a fault current threshold value of the fundamental wave current, and when the fundamental wave current is greater than the fault current threshold value, performing judgment: if the ratio is greater than a preset excitation surge current judgment threshold value, judging that the excitation surge current is the excitation surge current; and if the ratio is not greater than the preset excitation inrush current judgment threshold, judging that the current is a fault current. According to the application, the current signal in the sampling circuit is collected, whether the current is the excitation surge current or the fault current is accurately judged according to the magnitude of the fundamental wave current and the comparison result of the ratio and the preset threshold value, the detection precision is high, and the power distribution network fault detection requirements under different conditions can be met.

Description

Technical Field

[0001] The present application relates to the field of power grid fault detection, and in particular to a method, device, equipment and storage medium for detecting overhead faults in a distribution network. Background Art

[0002] In the power system, the distribution network is a key link in the distribution of electric energy, and its stable operation is crucial to ensuring the quality and reliability of power supply. However, the overhead lines of the distribution network are exposed to the natural environment and are susceptible to various factors such as bad weather, tree growth, external force damage, etc., resulting in frequent faults. Traditional fault detection methods often rely on manual inspections or simple current and voltage threshold judgments. The methods are not only inefficient, but also difficult to accurately distinguish different types of fault currents, such as fault current and excitation inrush current, which makes it difficult to locate and repair faults. Summary of the invention

[0003] The purpose of this application is to overcome the defects existing in the above-mentioned prior art and to provide a distribution network overhead fault detection method, device, equipment and storage medium.

[0004] The present application provides a method for detecting overhead faults in a distribution network, comprising:

[0005] Collecting current signals at N points in at least one complete cycle of the sampling circuit, and extracting fundamental current and second harmonics from the current signals;

[0006] Calculating a ratio of the second harmonic to the fundamental current;

[0007] A fault current threshold of the fundamental current is set. When the fundamental current is greater than the fault current threshold, it is judged as follows: if the ratio is greater than a preset excitation inrush current judgment threshold, it is judged as an excitation inrush current; if the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current.

[0008] Optionally, collecting current signals at N points in at least one complete cycle of the sampling circuit includes:

[0009] A digital short-circuit current sensor is installed on the single-phase cable to collect the current signal.

[0010] Optionally, the digital short-circuit current sensor is divided into two coils, which are used for CPU wake-up and measurement respectively.

[0011] Optionally, extracting the fundamental current and the second harmonic in the current signal includes: performing discrete Fourier transform or radix-2 fast Fourier transform on the sampling circuit signal.

[0012] Optionally, calculating the ratio of the second harmonic to the fundamental current includes:

[0013] The ratio is obtained by comparing the amplitude of the second harmonic with the amplitude of the fundamental current.

[0014] Optionally, the acquisition of the N points is completed through an ADC pin, and the sampling value of each point constitutes a time domain signal.

[0015] Optionally, extracting the fundamental current and the second harmonic in the current signal includes:

[0016] The discrete signal including harmonics and fundamental waves in the current signal is transformed into the frequency domain to extract the fundamental current and the second harmonic.

[0017] The present application also provides a distribution network overhead fault detection device, comprising:

[0018] An acquisition module, used to acquire current signals of N points in at least one complete cycle of the sampling circuit, and extract fundamental current and second harmonics from the current signal;

[0019] A ratio module, used for calculating the ratio of the second harmonic to the fundamental current;

[0020] A judgment module is used to set a fault current threshold of the fundamental current. When the fundamental current is greater than the fault current threshold, it is judged that: if the ratio is greater than a preset excitation inrush current judgment threshold, it is judged as an excitation inrush current; if the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current.

[0021] Optionally, collecting current signals at N points in at least one complete cycle of the sampling circuit includes:

[0022] A digital short-circuit current sensor is installed on the single-phase cable to collect the current signal.

[0023] Optionally, the digital short-circuit current sensor is divided into two coils, which are used for CPU wake-up and measurement respectively.

[0024] Optionally, the sampling module extracts the fundamental current and the second harmonic in the current signal, including: performing discrete Fourier transform or radix-2 fast Fourier transform on the sampling circuit signal.

[0025] Optionally, the ratio module calculates the ratio of the second harmonic to the fundamental current, including:

[0026] The ratio is obtained by comparing the amplitude of the second harmonic with the amplitude of the fundamental current.

[0027] Optionally, the sampling module collects the N points through ADC pins, and the sampling value of each point constitutes a time domain signal.

[0028] Optionally, the sampling module extracts the fundamental current and the second harmonic in the current signal, including:

[0029] The discrete signal including harmonics and fundamental waves in the current signal is transformed into the frequency domain to extract the fundamental current and the second harmonic.

[0030] The present application also provides a distribution network overhead fault detection device, comprising:

[0031] Memory;

[0032] A processor is used to store a computer executable program of the above-mentioned distribution network overhead fault detection method, and executes: collecting current signals of N points in at least one complete cycle of a sampling circuit, extracting fundamental current and second harmonic in the current signal; calculating the ratio of the second harmonic to the fundamental current; setting a fault current threshold of the fundamental current, and when the fundamental current is greater than the fault current threshold, judging: if the ratio is greater than a preset excitation inrush current judgment threshold, it is judged as an excitation inrush current; if the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current.

[0033] The present application also provides a storage medium, comprising: storing a computer executable program, wherein the computer executable program is used to be called by a processor to execute the steps of the above-mentioned distribution network overhead fault detection method.

[0034] The beneficial effects of this application are:

[0035] The present application provides a method for detecting overhead faults in a distribution network, including: collecting current signals of N points in at least one complete cycle of a sampling circuit, extracting the fundamental current and the second harmonic in the current signal; calculating the ratio of the second harmonic to the fundamental current; setting the fault current threshold of the fundamental current, and when the fundamental current is greater than the fault current threshold, judging: if the ratio is greater than the preset excitation inrush current judgment threshold, it is judged as an excitation inrush current; if the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current. The present application collects the current signal in the sampling circuit and compares the magnitude of the fundamental current and the ratio with the preset threshold to accurately judge whether the current is an excitation inrush current or a fault current. It has high detection accuracy and can adapt to the distribution network fault detection requirements under different conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the overhead fault detection process of the distribution network in this application;

[0037] Figure 2 Schematic diagram of the core components of the overhead fault indicator for the distribution network in this application. DETAILED DESCRIPTION

[0038] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that various forms of implementing the present disclosure should not be limited by the embodiments set forth herein. On the contrary, the embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0039] Please refer to Figure 1 As shown, the present application provides a method for detecting overhead faults in a distribution network, comprising:

[0040] S101 , collecting current signals of N points in at least one complete cycle of a sampling circuit, and extracting fundamental current and second harmonics from the current signals.

[0041] Distribution network overhead fault indicator core components:

[0042] like Figure 2 As shown in the figure, precision transformer: used to measure current signals with high precision to ensure the accuracy of data. Transformer: further ensures the stability and reliability of current measurement. Professionally tuned PCB: built-in 16-bit differential ADC and low-power DSP processor (Core), responsible for signal acquisition, processing and calculation. 16bit differential ADC: provides high-precision analog-to-digital conversion to ensure the accuracy of signal acquisition. Low-power DSP processor: efficiently processes the collected signals and performs complex algorithm operations. Battery: provides a long-lasting and stable power supply for the entire system.

[0043] Pull open the sensor ring and install it on the monitored power line. Preferably, a special tool can be used to firmly install the sensor to the predetermined monitoring point to ensure that the sensor can stably and accurately collect current signals.

[0044] Start the sampling circuit and start collecting current signals. Sample a complete cycle to ensure the integrity and periodicity of the collected signal. Sample N points per cycle, and the value of N is determined according to actual needs and sampling frequency. The sampled value output by the ADC pin is a time domain signal, which contains real-time change information of the current signal.

[0045] The discrete signal with analytical value in the sampled value is subjected to discrete Fourier transform (DFT) to convert it from the time domain to the frequency domain. The number of input sampling points N determines the calculation scale of DFT. After the transformation, the spectrum output will contain complex results of N points. However, due to the symmetry of the spectrum, usually only N / 2+1 points contain useful information. The points represent the signal amplitude and phase at different frequencies.

[0046] The DFT operation is performed using a specific mathematical formula:

[0047]

[0048] The above formula can accurately convert the time domain signal into the frequency domain signal.

[0049] Where X(K) is the complex result of the Kth point in the discrete frequency domain, x(n) is the nth sample value in the discrete time domain signal, N is the number of input sampling points, k is an integer from 0 to N-1, representing different points in the frequency domain, j is the imaginary unit, and e is the number of samples. -jΠnt / n is a complex exponential function that is used to calculate the signal component at each frequency point.

[0050] Furthermore, the signal data converted into the frequency domain is subjected to a radix-2 fast Fourier transform (FFT).

[0051] In digital signal processing, when a continuous-time signal is sampled, the sampling frequency Fs determines the frequency range of the signal that can be accurately represented.

[0052] Assuming the signal frequency is F and the number of sampling points is N, the sampled signal is a sequence of N discrete points. After FFT transformation, a result sequence of N complex numbers is obtained. Each point in this complex number sequence corresponds to a specific frequency point. These frequency points are evenly distributed, starting from 0Hz (DC component) and ending at the sampling frequency Fs.

[0053] Due to the symmetry of the FFT result, this application only processes the first N / 2+1 points, because the subsequent points are just the conjugate symmetry of the previous points.

[0054] Except for the first point representing the DC component, for each complex point in the FFT result, its modulus represents the signal amplitude characteristics at that frequency point. This modulus is a measure of the size of the component of the original signal at that frequency. Assuming that the peak value of the original signal is A, the modulus of each non-DC component point in the FFT result will be N / 2 times A. This is because the FFT algorithm will expand the signal during the calculation process, resulting in changes in amplitude. The first point, the DC component, has a modulus value that is N times the size of the DC signal.

[0055] In addition to the modulus value, each point in the FFT result also has a phase value, which represents the phase characteristics of the signal at that frequency. The phase value is relative to a reference point (usually the starting point of the signal), and it describes the waveform shape of the signal at that frequency. For a complex number a+bi, its phase can be calculated using the inverse tangent function atan2(b,a).

[0056] Based on the modulus and phase information in the FFT result, the signal expression corresponding to each frequency point can be calculated. For the nth point (n≠1, and n≤N / 2), the corresponding signal expression is:

[0057] An / (N / 2)cos(2piFnt+Pn)

[0058] Where An is the modulus value of the point, Fn is the frequency corresponding to the point (Fn = n*Fs / N), Pn is the phase value of the point, and t is the time variable. This expression describes the waveform shape and amplitude of the signal at this frequency.

[0059] In the implementation of the fault indicator of the distribution network ring main cabinet, in order to avoid false alarms and improve measurement accuracy, a complete cycle data is used to calculate the fundamental current. A complete cycle data is collected through ADC, for example, including 256 measurement points.

[0060] The DSP library function is used to shift the collected data. The expression is as follows:

[0061] input[i]=((s16_ADC_Value[i]<<16

[0062] s16_ADC_Value[i]: indicates the i-th real value collected by ADC, and the data type is a 16-bit integer. <<16: indicates shifting the value of s16_ADC_Value[i] left by 16 bits. input[i]: indicates the i-th complex data after processing, and the data type is a 32-bit integer.

[0063] In this 32-bit integer, the upper 16 bits are the real part and the lower 16 bits are the imaginary part.

[0064] In this application, the algorithm is to convert the real input variable into a complex form (imaginary part is 0), write the processed variable array and sampling points into the DSP library function, and use the first bit of the function output data to extract the fundamental component and the 21st bit to extract the second harmonic component.

[0065] Call the rms function in the DSP library to calculate the effective value of the fundamental component.

[0066] In the above signal transformation and calculation process, the influence of the DC component has been implicitly considered. The first point in the FFT result represents the DC component, and its modulus value reflects the amplitude of the DC component.

[0067] In order to obtain the true fundamental current data and second harmonic data, the influence of the DC component needs to be eliminated, which can be achieved by ignoring the first point in the calculation process or making appropriate compensation.

[0068] The rms function, or root mean square function, is a standard method for calculating the effective value of a signal. In a parallel circuit, the relationship between voltage and current can be described by Ohm's law. That is, voltage equals current multiplied by resistance (V=IR). In the application, it is assumed that a known resistance R is connected in parallel to the transformer, so the current can be calculated from the voltage and resistance.

[0069] Based on the above principle, the formula for calculating the effective value of the current fundamental wave is derived:

[0070] Current fundamental effective value = (voltage fundamental effective value / resistance R connected in parallel to the transformer) * transformation ratio. Finally, the real fundamental current data and second harmonic data are output for subsequent analysis and judgment.

[0071] S102: Calculate the ratio of the second harmonic current to the fundamental current.

[0072] In the previous step, the fundamental current and second harmonic current data have been extracted from the sampling circuit. These data are usually expressed in complex form and contain amplitude and phase information.

[0073] Dividing the amplitude of the second harmonic current by the amplitude of the fundamental current gives the ratio of the second harmonic to the fundamental current. This ratio is a real number that indicates the magnitude of the second harmonic relative to the fundamental current.

[0074] According to the obtained ratio, the harmonic pollution degree of the power system is evaluated. If the ratio is high, it means that there are more second harmonic components in the system.

[0075] S103, setting a fault current threshold of the fundamental current, and when the fundamental current is greater than the fault current threshold, judging: if the ratio is greater than a preset excitation inrush current judgment threshold, judging it as an excitation inrush current; if the ratio is not greater than the preset excitation inrush current judgment threshold, judging it as a fault current.

[0076] The present application uses a polymorphic method to accurately distinguish various types of surge currents on the line, including load surge current, non-fault phase reclosing surge current, excitation surge current caused by instantaneous load mutation, excitation surge current caused by artificial switching of large loads, and no-load closing excitation surge current.

[0077] Subsequent judgments are made based on the real fundamental current data. The second harmonic braking algorithm is used to identify the inrush current type based on characteristic parameters such as the ratio of fundamental current to harmonic current. At the same time, combined with the actual situation and operating experience of the power system, the polymorphic judgment technology is used to more accurately classify and identify the inrush current type.

[0078] Furthermore, according to the inrush current characteristics caused by load transient mutation, manual switching of large loads, and other phase line faults on the same bus, it is determined whether the effective value of the current is less than the fault current.

[0079] If the effective value of the current is less than the fault current, further judgment is made based on the proportion of the second harmonic:

[0080] The ratio is compared with a preset magnetizing inrush current judgment threshold.

[0081] Assuming that the judgment threshold of the excitation inrush current is 15%, determine whether the proportion of the second harmonic is greater than 15%. If the proportion of the second harmonic is greater than 15%, it is judged as an excitation inrush current and no alarm is triggered. If the proportion of the second harmonic is less than 15% and the effective value of the fundamental current is greater than the alarm setting value, it is judged as a fault current and the alarm is triggered.

[0082] After the alarm is activated, an alarm signal is output and the sensor lights up the fault indicator light at a certain frequency.

[0083] Furthermore, the staff receives the fault indication signal from the sensor. According to the fault indication signal and the actual situation of the power system, the fault location is quickly and accurately located. The fault location is inspected and maintained to eliminate the fault. After the fault is eliminated, the power supply of the power grid is restored to ensure the normal operation of the power system.

[0084] The present application also provides a distribution network overhead fault detection device, comprising:

[0085] An acquisition module, used to acquire current signals of N points in at least one complete cycle of the sampling circuit, and extract fundamental current and second harmonics from the current signal;

[0086] A ratio module, used for calculating the ratio of the second harmonic to the fundamental current;

[0087] A judgment module is used to set a fault current threshold of the fundamental current. When the fundamental current is greater than the fault current threshold, it is judged that: if the ratio is greater than a preset excitation inrush current judgment threshold, it is judged as an excitation inrush current; if the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current.

[0088] Furthermore, collecting current signals at N points in at least one complete cycle of the sampling circuit includes:

[0089] A digital short-circuit current sensor is installed on the single-phase cable to collect the current signal.

[0090] Furthermore, the digital short-circuit current sensor is divided into two coils, which are used for CPU wake-up and measurement respectively.

[0091] Furthermore, the sampling module extracts the fundamental current and the second harmonic in the current signal, including: performing discrete Fourier transform or radix-2 fast Fourier transform on the sampling circuit signal.

[0092] Further, the ratio module calculates the ratio of the second harmonic to the fundamental current, including:

[0093] The ratio is obtained by comparing the amplitude of the second harmonic with the amplitude of the fundamental current.

[0094] Furthermore, the sampling module collects the N points through ADC pins, and the sampling value of each point constitutes a time domain signal.

[0095] Furthermore, the sampling module extracts the fundamental current and the second harmonic in the current signal, including:

[0096] The discrete signal including harmonics and fundamental waves in the current signal is transformed into the frequency domain to extract the fundamental current and the second harmonic.

[0097] The present application also provides a distribution network overhead fault detection device, comprising:

[0098] Memory;

[0099] A processor is used to store a computer executable program of the above-mentioned distribution network overhead fault detection method, and executes: collecting current signals of N points in at least one complete cycle of a sampling circuit, extracting fundamental current and second harmonic in the current signal; calculating the ratio of the second harmonic to the fundamental current; setting a fault current threshold of the fundamental current, and when the fundamental current is greater than the fault current threshold, judging: if the ratio is greater than a preset excitation inrush current judgment threshold, it is judged as an excitation inrush current; if the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current.

[0100] The present application also provides a storage medium, comprising: storing a computer executable program, wherein the computer executable program is used to be called by a processor to execute the steps of the above-mentioned distribution network overhead fault detection method.

Claims

1. A method for detecting overhead faults in a distribution network, characterized in that: include: Collecting current signals at N points in at least one complete cycle of the sampling circuit, and extracting fundamental current and second harmonics from the current signals; Calculating a ratio of the second harmonic to the fundamental current; Setting a fault current threshold of the fundamental current, and when the fundamental current is greater than the fault current threshold, judging: if the ratio is greater than a preset excitation inrush current judgment threshold, judging it as an excitation inrush current; If the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current.

2. A method for detecting overhead faults in a distribution network according to claim 1, characterized in that: Collecting current signals at N points in at least one complete cycle of the sampling circuit includes: A digital short-circuit current sensor is installed on the single-phase cable to collect the current signal.

3. A method for detecting overhead faults in a distribution network according to claim 2, characterized in that: The digital short-circuit current sensor is divided into two coils, which are used for CPU wake-up and measurement respectively.

4. A method for detecting overhead faults in a distribution network according to claim 1, characterized in that: Extracting the fundamental current and the second harmonic in the current signal includes: performing discrete Fourier transform or radix-2 fast Fourier transform on the sampling circuit signal.

5. The method for detecting overhead faults in a power distribution network according to claim 1, characterized in that: Calculating the ratio of the second harmonic to the fundamental current includes: The ratio is obtained by comparing the amplitude of the second harmonic with the amplitude of the fundamental current.

6. The method for detecting overhead faults in a power distribution network according to claim 1, characterized in that: The acquisition of the N points is completed through the ADC pins, and the sampling value of each point constitutes a time domain signal.

7. The method for detecting overhead faults in a power distribution network according to claim 1, characterized in that: Extracting the fundamental current and the second harmonic in the current signal includes: The discrete signal including harmonics and fundamental waves in the current signal is transformed into the frequency domain to extract the fundamental current and the second harmonic.

8. A distribution network overhead fault detection device, characterized in that: include: An acquisition module, used to acquire current signals of N points in at least one complete cycle of the sampling circuit, and extract fundamental current and second harmonics from the current signal; A ratio module, used for calculating the ratio of the second harmonic to the fundamental current; A judgment module, used for setting a fault current threshold of the fundamental current, and when the fundamental current is greater than the fault current threshold, judging: if the ratio is greater than a preset excitation inrush current judgment threshold, then judging it as an excitation inrush current; If the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current.

9. A distribution network overhead fault detection device according to claim 8, characterized in that: Collecting current signals at N points in at least one complete cycle of the sampling circuit includes: A digital short-circuit current sensor is installed on the single-phase cable to collect the current signal.

10. A distribution network overhead fault detection device according to claim 9, characterized in that: The digital short-circuit current sensor is divided into two coils, which are used for CPU wake-up and measurement respectively.

11. A distribution network overhead fault detection device according to claim 8, characterized in that: The sampling module extracts the fundamental current and the second harmonic in the current signal, including: performing discrete Fourier transform or radix-2 fast Fourier transform on the sampling circuit signal.

12. The overhead fault detection device for distribution network according to claim 8, characterized in that: The ratio module calculates the ratio of the second harmonic to the fundamental current, including: The ratio is obtained by comparing the amplitude of the second harmonic with the amplitude of the fundamental current.

13. The overhead fault detection device for power distribution network according to claim 8, characterized in that: The sampling module collects the N points through ADC pins, and the sampling value of each point constitutes a time domain signal.

14. The overhead fault detection device for power distribution network according to claim 8, characterized in that: The sampling module extracts the fundamental current and the second harmonic in the current signal, including: The discrete signal including harmonics and fundamental waves in the current signal is transformed into the frequency domain to extract the fundamental current and the second harmonic.

15. A distribution network overhead fault detection device, characterized in that: include: Memory; A processor, for storing a computer executable program of a method for detecting overhead faults in a distribution network as claimed in any one of claims 1 to 7, and executing: collecting current signals of N points in at least one complete cycle of a sampling circuit, extracting a fundamental current and a second harmonic from the current signal; calculating a ratio of the second harmonic to the fundamental current; Setting a fault current threshold of the fundamental current, and when the fundamental current is greater than the fault current threshold, judging: if the ratio is greater than a preset excitation inrush current judgment threshold, judging it as an excitation inrush current; If the ratio is not greater than the preset excitation inrush current judgment threshold, it is judged as a fault current.

16. A storage medium, characterized in that: include: A computer executable program is stored, and the computer executable program is used to be called by a processor to execute the steps of a distribution network overhead fault detection method as described in any one of claims 1 to 7.

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