High-resistance grounding fault detection method based on zero-sequence current integral characteristic

Abstract

The invention discloses a high-resistance grounding fault detection method based on zero-sequence current integral characteristics, and relates to the field of 10kV power distribution network high-resistance grounding fault detection, and the method comprises the steps: carrying out the low-pass filtering of a collected zero-sequence current original signal, and obtaining a zero-sequence current low-frequency signal; performing segmentation processing on the obtained zero-sequence current low-frequency signal, performing integration on each segment, fitting a sin function according to an integral curve, and calculating a distortion area; calculating a historical distortion area sequence, and establishing an adaptive threshold to judge whether a fault or disturbance occurs; establishing a distortion area positive and negative identifier, an area distortion degree identifier and a distortion area continuous number identifier, and judging whether a continuous section is a fault feature period or not; setting a time window to judge whether the occurrence frequency of the fault feature period is out of limit; according to the invention, whether a fault or disturbance occurs is determined according to the relationship between the distortion area of the current section and the adaptive threshold, and then a high-resistance grounding fault and a non-high-resistance grounding fault or system disturbance are distinguished through the fault characteristic period identifier. And finally, judging whether the high-resistance grounding fault occurs or not according to whether the occurrence frequency of the fault characteristic period in the specified time window is out of limit or not. According to the method, the reliability and the sensitivity of high-resistance grounding fault detection can be effectively improved.

Description

Technical Field

[0001] The invention relates to the technical field of high-resistance grounding fault detection in a 10kV distribution network, in particular to a high-resistance grounding fault detection method based on zero-sequence current integral characteristics. Background Art

[0002] High-resistance grounding fault is one of the most common single-phase grounding faults in 10kV distribution networks. It often occurs when trees grow in contact with overhead lines or when wires break and touch non-metallic conductors such as cement ground and grass. Electrical connection is easily formed between the rough surface of the wire and the grounding medium, which will be accompanied by nonlinear air arc breakdown. The long-term existence of arcs may cause forest fires, personal electric shock and other serious accidents. The characteristics of high-resistance grounding faults are weak, and traditional protection devices are difficult to detect and remove faults in time. The existing detection method is based on the arc angle, and calculates the characteristic quantities such as the concavity, slope, and distortion time of the zero-sequence current to quantify the nonlinear distortion characteristics caused by the arc. It has high sensitivity, but the fault detection method is easily affected by system disturbances. At the same time, the fault state may be repeated between fault and non-fault, and the reliability of the detection method is difficult to guarantee. Summary of the invention

[0003] In order to solve the problems existing in the prior art, the purpose of the present invention is to provide a high-resistance grounding fault detection method based on the zero-sequence current integral characteristic. The present invention can reliably determine whether a high-resistance grounding fault occurs, while eliminating the influence of system disturbances, so as to achieve the purpose of quickly and effectively detecting faults. Moreover, the present invention uses digital as the output quantity, which is more conducive to on-site operation and maintenance personnel to make a judgment on whether a fault occurs.

[0004] To achieve the above object, the technical solution adopted by the present invention is: a high-resistance grounding fault detection method based on zero-sequence current integral characteristics, comprising the following steps:

[0005] Step 1: low-pass filter the original waveform of the collected zero-sequence current data using Fourier transform filtering method to obtain the filtered current after filtering out background noise and high-frequency signals;

[0006] Step 2, segment the filtered current, integrate the zero-sequence current waveform in each segment, fit the sin function according to the integral curve, and calculate the distortion area according to the fitting curve and the integral curve;

[0007] Step 3: Calculate the adaptive threshold value based on the historical distortion area data, compare it with the distortion area of ​​the current section, and judge whether a fault or disturbance occurs based on the result. If it is judged that a fault or disturbance occurs, proceed to step 4; otherwise, return to step 1, judge it as normal operation and the area is included in the historical distortion area data;

[0008] Step 4, calculate the fault characteristic quantity, and judge whether the continuous section satisfies the three identifications at the same time according to the positive and negative identification of the distortion area, the identification of the area distortion degree, and the identification of the continuous number of the distortion area. If the continuous section satisfies the three identifications at the same time, the current continuous section is judged to be a fault characteristic cycle, otherwise, return to step 1 and judge it as a non-high-resistance grounding fault;

[0009] Step 5: If the number of fault characteristic cycles within five power frequency cycles or nine consecutive sections is ≥5, it is determined that a high-resistance grounding fault has occurred, otherwise return to step 1 to monitor system operation.

[0010] As a further improvement of the present invention, the step 1 is specifically as follows:

[0011] The Fourier transform filtering method is used for low-pass filtering to retain the harmonic components that cause nonlinear distortion as much as possible, and a zero-sequence current filtering signal within 0Hz-500Hz is obtained;

[0012] As a further improvement of the present invention, the step 2 is specifically as follows:

[0013] The filter current is divided into waveforms of each segment with only the positive half cycle, that is, the absolute value of the filter current is obtained. The calculation formula is as follows:

[0014] I abs (t)=|I(t)

[0015] Where I(t) is the filter current, I abs (t) is the absolute value of the filter current;

[0016] For each segment I abs (t) is integrated to obtain the integral curve changing with time. The calculation formula is as follows:

[0017]

[0018] In the formula, I n (t) is the integral function, t is the t-th sampling point in the current segment, i is the sampling point, and Δt is the time step;

[0019] The starting point coordinates (t0, I0) of the integral curve are used as the starting point (-π / 2, -1) coordinates of the sin function, and the end point (t1, I1) corresponds to the sin function (π / 2, 1) coordinates for sin function fitting. The calculation formula for the fitting sin function is as follows:

[0020]

[0021] Where f(t) is the fitted sin function, ω is the angular frequency of the sin function, and f s is the sampling rate;

[0022] The calculation formula of the distortion area S is as follows:

[0023]

[0024] Where N is the number of sampling data points in the segment [t0, t1];

[0025] As a further improvement of the present invention, the step 3 is specifically as follows:

[0026] Calculate the ten distortion area sequences A before the xth segment of data, as follows:

[0027] A={|S(t0-T n )|,|S(t0-2T n )|...|S(t0-10T n )|}

[0028] Where, T n is the calculation step size and T n =T / 2, S(t0-kT n ) is the distortion area of ​​the xkth segment of data, k∈[1,10], k is a positive integer;

[0029] Assume that sequence A follows normal distribution X~N(μ,σ 2 ), then the probability density function P(S(r)) is calculated as follows:

[0030]

[0031] Where S(r) is the distortion area of ​​the rth segment, r∈[x-1,x-10], r is a positive integer, μ is the mean, and σ is the standard deviation;

[0032] The larger S(r) is, the smaller the probability of the event represented by the area. The high-resistance grounding fault in the distribution network is regarded as a low-probability event. The adaptive threshold Det of the x-th segment distortion area is set based on the probability density function of the historical area data sequence A. The adaptive threshold Det calculation formula is as follows:

[0033] Det=μ+4σ

[0034] As a further improvement of the present invention, the fault or disturbance detection criterion is specifically as follows:

[0035] If the distortion area S of the xth segment is greater than Det, it is judged as a fault or disturbance; if S≤Det, it is judged as normal operation;

[0036] As a further improvement of the present invention, the step 4 is specifically as follows:

[0037] Calculate the fault characteristic quantity:

[0038] Distortion area positive and negative mark P m :

[0039] If the distortion area S>0, then mark the positive and negative signs of the distortion area P m =1; if the distortion area S≤0, then mark the positive and negative signs of the distortion area P m =0;

[0040] Area distortion degree indicator P n , the calculation formula of area distortion degree Ds is as follows:

[0041]

[0042] If the area distortion degree Ds>α, then mark the area distortion degree indicator P n =1; if the area distortion degree Ds≤α, then mark the area distortion degree mark P n =0; where α is the threshold value, α is 1% to 3%;

[0043] Distortion area continuous number mark N p :

[0044] Calculate the positive and negative marks of the distortion area and the degree of area distortion of the x+1 segment data. If the data of segments x and x+1 satisfy P m =P n = 1, then the continuous number of distortion areas is marked N p =1; otherwise, mark the continuous number of distortion areas N p =0;

[0045] As a further improvement of the present invention, the fault characteristic period detection criterion is specifically as follows:

[0046] If the data of the continuous segments (segments x and x+1) satisfy the following formula:

[0047]

[0048] The continuous section is determined to be a fault characteristic period, and the fault characteristic period identifier F is marked. T =1;

[0049] As a further improvement of the present invention, the step 5 is specifically as follows:

[0050] If the number of fault characteristic cycles in five power frequency cycles or nine consecutive sections is ≥5, the fault characteristic cycle identification F is output. T =1 for more than 5 times, it is determined that a high-resistance grounding fault has occurred.

[0051] The beneficial effects of the present invention are:

[0052] This paper considers that high-resistance grounding fault is one of the most common single-phase grounding faults in 10kV distribution network. High-resistance grounding fault will be accompanied by nonlinear air arc breakdown. The long-term existence of arc may cause forest fires, biological electric shock and other malicious events, thereby causing major economic losses and casualties. The characteristics of high-resistance grounding fault are weak, and the traditional detection method has low sensitivity and is easily affected by system disturbances. If the occurrence of the fault can be detected in time, and the influence of system disturbances can be effectively eliminated to avoid misjudgment, the stability of safe operation of the system will be significantly improved. The high-resistance grounding fault detection method proposed in the present invention is to separate the zero-sequence current low-frequency signal in the original signal, segment the signal, obtain the distortion area according to the integral and fitting curve, and then establish the adaptive threshold of the current section through the historical distortion area data to reliably judge whether the fault or disturbance occurs. Then calculate the fault characteristic quantity, distinguish non-high-resistance grounding faults and disturbances such as system capacitance, load switching, and transformer excitation inrush current according to the positive and negative marks of the distortion area, the mark of the degree of area distortion, and the continuous number mark of the distortion area, and judge it as a fault characteristic cycle. Finally, the occurrence of a high-resistance grounding fault is determined based on the number of fault characteristic cycles occurring within the specified time window, thereby improving the sensitivity and reliability of high-resistance grounding fault detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a flow chart of an embodiment of the present invention;

[0054] Figure 2 is a schematic diagram of the distortion area S in an embodiment of the present invention;

[0055] Figure 3 is a probability density distribution diagram of the historical distortion area sequence A in an embodiment of the present invention;

[0056] Figure 4 Graph showing changes in adaptive threshold and distortion area in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0058] Example

[0059] Figure 1 As shown, a high-resistance grounding fault detection method based on zero-sequence current integral characteristics includes the following steps:

[0060] Step 1: low-pass filter the original waveform of the collected zero-sequence current data using Fourier transform filtering method to obtain the filtered current after filtering out background noise and high-frequency signals;

[0061] Step 2: Process the filtered current in sections, integrate the zero-sequence current waveform in each section, fit the sin function according to the integral curve, and calculate the distortion area according to the fitting curve and the integral curve, such as Figure 2 As shown, the details are as follows:

[0062] The filter current is divided into waveforms of each segment with only the positive half cycle, that is, the absolute value of the filter current is obtained. The calculation formula is as follows:

[0063] I abs (t)=|I(t)

[0064] Where I(t) is the filter current, I abs (t) is the absolute value of the filter current;

[0065] For each segment I abs (t) is integrated to obtain the integral curve changing with time. The calculation formula is as follows:

[0066]

[0067] In the formula, I n (t) is the integral function, t is the t-th sampling point in the current segment, i is the sampling point, and Δt is the time step;

[0068] The starting point coordinates (t0, I0) of the integral curve are used as the starting point (-π / 2, -1) coordinates of the sin function, and the end point (t1, I1) corresponds to the sin function (π / 2, 1) coordinates for sin function fitting. The calculation formula for the fitting sin function is as follows:

[0069]

[0070] Where f(t) is the fitted sin function, ω is the angular frequency of the sin function, and f s is the sampling rate;

[0071] The calculation formula of the distortion area S is as follows:

[0072]

[0073] Where N is the number of sampling data points in the segment [t0, t1];

[0074] Step 3: Calculate the adaptive threshold value based on the historical distortion area data, compare it with the distortion area of ​​the current section, and determine whether a fault or disturbance occurs based on the result. If it is determined that a fault or disturbance occurs, proceed to step 4. Otherwise, return to step 1 and determine that it is normal operation and the area is included in the historical distortion area data. The details are as follows:

[0075] Calculate the ten distortion area sequences A before the xth segment of data, as follows:

[0076] A={|S(t0-T n )|,|S(t0-2T n )|...|S(t0-10T n )|}

[0077] Where, T n is the calculation step size and T n =T / 2, S(t0-kT n ) is the distortion area of ​​the xkth segment of data, k∈[1,10], k is a positive integer;

[0078] Assume that sequence A follows normal distribution X~N(μ,σ 2 ), then the probability density function P(S(r)) is calculated as follows:

[0079]

[0080] Where S(r) is the distortion area of ​​the rth segment, r∈[x-1,x-10], r is a positive integer, μ is the mean, and σ is the standard deviation;

[0081] The larger S(r) is, the smaller the probability of the event represented by the area. The high-resistance grounding fault in the distribution network is regarded as a low-probability event. Based on the probability density function of the historical area data sequence A, the adaptive threshold Det of the x-th segment distortion area is set. The probability density distribution diagram of sequence A is shown in Figure 3 As shown, the calculation formula of the adaptive threshold Det is as follows:

[0082] Det=μ+4σ

[0083] The adaptive threshold and distortion area change process are as follows: Figure 4 As shown in the figure, if the distortion area S(t) of the tth segment is greater than Det, it is judged as a fault or disturbance; if S(t)≤Det, it is judged as normal operation;

[0084] Step 4, calculate the fault characteristic quantity: positive and negative mark of distortion area, mark of area distortion degree, mark of continuous number of distortion area, and judge whether the continuous section satisfies the three marks at the same time. If the continuous section satisfies the three marks at the same time, judge the current continuous section as the fault characteristic cycle, otherwise return to step 1 and judge it as non-high-resistance grounding fault; the details are as follows:

[0085] Distortion area positive and negative mark P m :

[0086] If the distortion area S>0, then mark the positive and negative signs of the distortion area P m=1; if the distortion area S≤0, then mark the positive and negative signs of the distortion area P m =0;

[0087] Area distortion degree indicator P n , the calculation formula of area distortion degree Ds is as follows:

[0088]

[0089] If the area distortion degree Ds>α, then mark the area distortion degree indicator P n =1; if the area distortion degree Ds≤α, then mark the area distortion degree mark P n =0; where α is the threshold value, α is 1% to 3%;

[0090] Distortion area continuous number mark N p :

[0091] Calculate the positive and negative marks of the distortion area and the degree of area distortion of the x+1 segment data. If the data of segments x and x+1 satisfy P m =P n = 1, then the continuous number of distortion areas is marked N p =1; otherwise, mark the continuous number of distortion areas N p =0;

[0092] If the data of the continuous segments (segments x and x+1) satisfy the following formula:

[0093]

[0094] The continuous section is determined to be a fault characteristic period, and the fault characteristic period identifier F is marked. T =1;

[0095] Step 5: If the number of fault characteristic cycles in five power frequency cycles or nine consecutive sections is ≥5, it is determined that a high-resistance grounding fault has occurred. Otherwise, return to step 1 and monitor the operation of the system, as follows:

[0096] If the number of fault characteristic cycles in five power frequency cycles or nine consecutive sections is ≥5, the fault characteristic cycle identification F is output. T =1 for more than 5 times, it is determined that a high-resistance grounding fault has occurred.

[0097] In this embodiment, the collected original zero-sequence current signal is first low-pass filtered to obtain a zero-sequence current low-frequency signal within 0Hz-500Hz. Then, the zero-sequence current low-frequency signal is processed in sections, the waveform of each section is integrated, the sin function is fitted according to the integral curve, and then the distortion area is calculated according to the integral curve and the fitting curve. Then, the adaptive threshold is calculated by establishing a historical distortion area data sequence to determine whether a fault or disturbance occurs in the current section. Then, according to the non-high-resistance grounding fault characteristics such as non-high-resistance grounding faults and system disturbances such as capacitor switching, compliance switching, transformer excitation inrush current, etc., the distortion area positive and negative marks, area distortion degree marks, and distortion area continuous number marks are respectively established to determine whether the continuous section is a fault characteristic cycle. Finally, by setting a time window, the reliability and sensitivity of high-resistance grounding fault detection are improved by judging whether a high-resistance grounding fault occurs according to the number of fault characteristic cycles that occur within the specified time window.

[0098] This embodiment has the following advantages: low-pass filtering of the original zero-sequence current signal can effectively filter out background noise, while better retaining the harmonic signal that causes nonlinear distortion. Segmented processing of the zero-sequence current signal can improve the efficiency of subsequent processing, integrate the waveform of each segment, fit the sin function according to the integral curve, and then quantify the nonlinear characteristics caused by the arc according to the distortion area calculated by the integral curve and the fitting curve. The adaptive threshold calculated according to the historical distortion area data takes into account the reliability and sensitivity of fault detection. Calculating the positive and negative identification of the distortion area, the area distortion degree mark and the continuous number mark of the distortion area can reliably distinguish between non-high-resistance grounding faults and system disturbances. Setting a time window to determine whether the number of fault characteristic cycles exceeds the limit prevents the fault state from fluctuating between fault and non-fault or the arc from repeatedly extinguishing and reigniting in an unstable manner, prevents missed judgment, and improves the reliability and sensitivity of high-resistance grounding fault detection.

[0099] The above-mentioned embodiments only express the specific implementation of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A high-resistance grounding fault detection method based on zero-sequence current integral characteristics, characterized in that: The steps include: Step 1: low-pass filter the original waveform of the collected zero-sequence current data using Fourier transform filtering method to obtain the filtered current after filtering out background noise and high-frequency signals; Step 2, segment the filtered current, integrate the zero-sequence current waveform in each segment, fit the sin function according to the integral curve, and calculate the distortion area according to the fitting curve and the integral curve; Step 3: Calculate the adaptive threshold value based on the historical distortion area data, compare it with the distortion area of ​​the current section, and judge whether a fault or disturbance occurs based on the result. If it is judged that a fault or disturbance occurs, proceed to step 4; otherwise, return to step 1, judge it as normal operation and the area is included in the historical distortion area data; Step 4, calculate the fault characteristic quantity, and judge whether the continuous section satisfies the three identifications at the same time according to the positive and negative identification of the distortion area, the identification of the area distortion degree, and the identification of the continuous number of the distortion area. If the continuous section satisfies the three identifications at the same time, the current continuous section is judged to be a fault characteristic cycle, otherwise, return to step 1 and judge it as a non-high-resistance grounding fault; Step 5: If the number of fault characteristic cycles within five power frequency cycles or nine consecutive sections is ≥5, it is determined that a high-resistance grounding fault has occurred, otherwise return to step 1 to monitor system operation.

2. The high-resistance grounding fault detection method based on zero-sequence current integral characteristics according to claim 1 is characterized in that: The step 1 is specifically as follows: The Fourier transform filtering method is used for low-pass filtering to retain the harmonic components that cause nonlinear distortion as much as possible, and a zero-sequence current filtering signal within 0Hz-500Hz is obtained;.

3. The high-resistance grounding fault detection method based on zero-sequence current integral characteristics according to claim 1 is characterized in that: The step 2 is specifically as follows: The filter current is divided into waveforms of each segment with only the positive half cycle, that is, the absolute value of the filter current is obtained. The calculation formula is as follows: I abs (t)=|I(t)| Where I(t) is the filter current, I abs (t) is the absolute value of the filter current; For each segment I abs (t) is integrated to obtain the integral curve changing with time. The calculation formula is as follows: In the formula, I n (t) is the integral function, t is the t-th sampling point in the current segment, i is the sampling point, and Δt is the time step; The starting point coordinates (t0, I0) of the integral curve are used as the starting point (-π / 2, -1) coordinates of the sin function, and the end point (t1, I1) corresponds to the sin function (π / 2, 1) coordinates for sin function fitting. The calculation formula for the fitting sin function is as follows: Where f(t) is the fitted sin function, ω is the angular frequency of the sin function, and f s is the sampling rate; The calculation formula of the distortion area S is as follows: Where N is the number of sampling data points in the segment [t0, t1].

4. The high-resistance grounding fault detection method based on zero-sequence current integral characteristics according to claim 1 is characterized in that: The step 3 is as follows: Calculate the ten distortion area sequences A before the xth segment of data, as follows: A={|S(t0-T n )|,|S(t0-2T n )|...|S(t0-10T n )|} Where, T n is the calculation step size and T n =T / 2, S(t0-kT n ) is the distortion area of ​​the xkth segment of data, k∈[1,10], k is a positive integer; Assume that sequence A follows normal distribution X~N(μ,σ 2 ), then the probability density function P(S(r)) is calculated as follows: Where S(r) is the distortion area of ​​the rth segment, r∈[x-1,x-10], r is a positive integer, μ is the mean, and σ is the standard deviation; The larger S(r) is, the smaller the probability of the event represented by the area. The high-resistance grounding fault in the distribution network is regarded as a low-probability event. The adaptive threshold Det of the x-th segment distortion area is set based on the probability density function of the historical area data sequence A. The adaptive threshold Det calculation formula is as follows: Det=μ+4σ.

5. The high-resistance grounding fault detection method based on zero-sequence current integral characteristics according to claim 4 is characterized in that: The specific fault or disturbance detection criteria are as follows: If the distortion area S of the xth segment is greater than Det, it is judged as a fault or disturbance; if S≤Det, it is judged as normal operation.

6. The high-resistance grounding fault detection method based on zero-sequence current integral characteristics according to claim 1 is characterized in that: The step 4 is specifically as follows: Calculate the fault characteristic quantity: Distortion area positive and negative mark P m : If the distortion area S>0, then mark the positive and negative signs of the distortion area P m =1; if the distortion area S≤0, then mark the positive and negative signs of the distortion area P m =0; Area distortion degree indicator P n , the calculation formula of area distortion degree Ds is as follows: If the area distortion degree Ds>α, then mark the area distortion degree indicator P n =1; if the area distortion degree Ds≤α, then mark the area distortion degree mark P n =0; where α is the threshold value, α is 1%; Distortion area continuous number mark N p : Calculate the positive and negative marks of the distortion area and the degree of area distortion of the x+1 segment data. If the data of segments x and x+1 satisfy P m =P n = 1, then the continuous number of distortion areas is marked N p =1; otherwise, mark the continuous number of distortion areas N p =0;.

7. The high-resistance grounding fault detection method based on zero-sequence current integral characteristics according to claim 5 is characterized in that: The fault characteristic period detection criteria are as follows: If the data of the continuous segments (segments x and x+1) satisfy the following formula: The continuous section is determined to be a fault characteristic period, and the fault characteristic period identifier F is marked. T =1;.

8. The high-resistance grounding fault detection method based on zero-sequence current integral characteristics according to claim 1, characterized in that: The step 5 is specifically as follows: If the number of fault characteristic cycles in five power frequency cycles or nine consecutive sections is ≥5, the fault characteristic cycle identification F is output. T =1 for more than 5 times, it is determined that a high-resistance grounding fault has occurred.

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