Power distribution network high-resistance fault detection and line selection method

Abstract

The invention relates to a high-resistance fault detection and line selection method for a power distribution network. The method comprises the steps of generating an original waveform from zero-sequence voltage recording data; performing morphological filtering processing on the original waveform, calculating a curve abrupt change area by adopting a sliding window mode, setting an early warning self-adaptive threshold value, and judging the running state of the power distribution network; carrying out fault detection by adopting a high-resistance grounding fault identification method; analyzing the flow direction after the fault based on the phase distribution, and judging whether the fault point is located at the upstream or downstream of the power distribution terminal, thereby completing the fault line selection. Performing data preprocessing on each waveform, calculating a zero-sequence voltage curve abrupt change area by adopting a sliding window mode, and judging whether the distribution network is in a normal operation state or not by combining a set early warning self-adaptive threshold value; distinguishing capacitor switching interference and a high-resistance grounding fault through a high-resistance grounding fault identification method based on signal difference; the power flow direction after the fault is analyzed based on phase distribution, the threshold setting trouble of a traditional line selection method is avoided, and thus fault line selection is completed.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a method for detecting high-resistance faults in a distribution network and selecting a line. Background Art

[0002] High-resistance grounding faults (>2kΩ) account for about 5% to 10% of medium-voltage distribution network faults, and often occur when overhead lines are broken or dropped and come into contact with non-metallic conductors such as concrete, trees, and lawns. Usually, the surface of the grounding medium is not smooth. When the conductor forms an electrical connection with the grounding medium and causes a grounding fault, it will be accompanied by nonlinear air arc breakdown or solid medium breakdown, which can easily cause fires, electric shocks, and other serious accidents. The characteristics of high-resistance grounding faults are weak, and traditional protection devices or fuses are difficult to detect and cut off the faulty line in time. Usually, grounding line selection devices, fault indicators, etc. are used to detect and alarm faults, and then manual treatment is sent.

[0003] The arc fault at the grounding point will cause signal distortion, thereby generating harmonics, transient oscillations, etc., which can be used as an important fault feature for high-resistance grounding fault detection. However, since the high-resistance grounding fault feature is weak, it is easy to be confused with normal grid disturbance signals such as capacitor switching, which may cause false alarms for fault detection, and its detection reliability cannot be guaranteed. In addition, since the electrical quantity characteristics show volatility after a high-resistance grounding fault occurs, it is difficult to set a suitable electrical quantity threshold to ensure detection sensitivity. There is still a lot of work to be done in the detection and line selection of high-resistance faults in distribution networks. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method for detecting high-resistance faults in a distribution network and selecting a line, so as to overcome the deficiencies in the above-mentioned prior art.

[0005] The technical solution of the present invention to solve the above technical problem is as follows: A method for detecting high-resistance faults in a distribution network and selecting a line, comprising the following steps:

[0006] Step S01: Obtain zero-sequence voltage recording data and phase voltage and current recording data monitored by the distribution terminal, and generate the original waveform u from the zero-sequence voltage recording data 0 (t); for the original waveform u 0 (t) Perform morphological filtering, use a sliding window method to calculate the curve mutation area S(t), set the early warning adaptive threshold K, and determine whether the distribution network is in normal operation or abnormal operation;

[0007] Step S02: After the early warning is started, if the distribution network is in an abnormal operating state, a high-resistance grounding fault identification method based on signal difference is used for fault detection to determine whether the abnormal operating state is a switching disturbance or a high-resistance grounding fault;

[0008] Step S03: When the abnormal operating state is a high-resistance ground fault, the power flow direction after the fault is analyzed based on the phase distribution, and it is determined whether the fault point is located upstream or downstream of the power distribution terminal, thereby completing the fault line selection.

[0009] The beneficial effects of the present invention are as follows: the present invention configures fault recording terminals at key nodes of distribution lines to measure the power frequency and zero-sequence voltage and current data of each node, firstly proposes an early warning start mechanism, performs data preprocessing on each waveform through morphological filtering, and calculates the zero-sequence voltage curve mutation area S(t) by a sliding window method, and combines the set early warning adaptive threshold K to further determine whether the distribution network is in a normal operating state; secondly, the present invention distinguishes capacitor switching interference and high-resistance grounding fault through a high-resistance grounding fault identification method based on signal differential; finally, based on the fault flow distribution characteristics, the present invention analyzes the flow direction after the fault based on phase distribution, thereby avoiding the threshold setting problem of traditional line selection methods, thereby completing fault line selection.

[0010] Based on the above technical solution, the present invention can also be improved as follows.

[0011] Further, step S01 specifically includes the following steps:

[0012] Step S11: Obtain the zero-sequence voltage recording data and phase voltage and current recording data monitored by the distribution terminal, and generate the original waveform u from the zero-sequence voltage recording data 0 (t);

[0013] Step S12: The original waveform u 0y (t) Perform morphological filtering to obtain u 0 (t);

[0014] Step S13: Select a window pair u of a preset length 0 (t) Perform continuous scanning and calculate the waveform segment u in each window 0 The curve mutation area S of k(t) 1 (t), S 2 (t), according to S 1 (t) and S 2 (t) Calculate the curve mutation area S(t);

[0015] Step S14: judging whether the distribution line is operating normally according to the curve mutation area S(t) and the early warning adaptive threshold K.

[0016] Further, in step S13, the waveform segments u in each window 0 The curve mutation area S of k(t) 1 (t), S 2 The calculation formula of (t) is as follows:

[0017]

[0018] In the formula, t represents u 0k (t) The sampling point corresponds to the time, f S represents the sampling frequency, f S =8000, S 1 (t) represents u 0k (t) The curve mutation area in the first 1 / 4 cycle, S 2 (t) represents u 0k (t) The curve mutation area in the first 1 / 2 cycle;

[0019] The calculation formula of the curve mutation area S(t) is:

[0020] S(t)=max{4S 1 (t), 2S 2 (t)}.

[0021] Further, step S14 is specifically as follows:

[0022] Based on the historical curve area data, the early warning adaptive threshold K is designed according to the normal distribution probability to determine whether the curve mutation area S(t) exceeds the early warning adaptive threshold K. The calculation formula of the early warning adaptive threshold K is as follows:

[0023] K=μ+4σ,

[0024] In the formula, μ and σ represent the mean and variance of S(t) respectively;

[0025] If S(t)>K, it is considered that the distribution line has abnormal behavior of fault or disturbance; if S(t)≤K, it is considered that the distribution line is operating normally at this time, and the sudden change area S(t) of the curve is used as the historical curve area data for the calculation of the next warning adaptive threshold K.

[0026] Further, step S02 specifically includes the following steps:

[0027] Step S21: 0k (t) Perform five-point difference to obtain u′ 0k (t), its expression is:

[0028]

[0029] Step S22: quantify the oscillation degree of the waveform by performing zero crossing of the waveform after differentiation under a fixed window, u′ 0k (t n ), u′ 0k (r n+1) is the difference value of two adjacent sampling points of the waveform after differentiation under a certain window, n = 1, 2, ..., 159, starting from the first two points under the window, if u′ is satisfied 0k (t n )·u′ 0k (t n+1 )≤0, it is considered that there is one zero-crossing point in the window, and the calculation is continued until the 159th time, and the total number of zero-crossing points in the window is N;

[0030] Step S23: Count u′ under 20 consecutive sliding windows 0k The number of zero-crossing points of (t) is N. If each window satisfies N>10, it is considered that there is a capacitor switching disturbance in the distribution network, otherwise it is considered that there is a high-resistance grounding fault in the distribution network.

[0031] Further, step S03 specifically includes the following steps:

[0032] Step S31: Obtain the power frequency phase voltage recording data monitored by the power distribution terminal and generate the original waveform u a (t),u b (t),u c (t), and align the three-phase waveforms through the Beidou / GPS time scale, and then perform denoising;

[0033] Step S32: judging the fault phase according to the characteristics that the neutral point is offset toward the grounded phase and the waveform of the grounded phase decreases while the waveforms of the other two phases increase;

[0034] Step S33: After the fault phase is confirmed, the power frequency current recording data of the fault phase monitored by the power distribution terminal is obtained to generate the original waveform i fy (t), and denoise to obtain i f (t), and then the fault phase voltage u is converted into f (t), fault phase current i f (t) waveform alignment;

[0035] Step S34: Obtain the fault phase voltage u f (t), fault phase current i f (t) Time domain waveform data, analyze the waveform data, and find out the fault phase voltage u f (t), fault phase current i f The zero crossing point of (t) satisfies:

[0036] u f (t u )=0,

[0037] i f (t i )=0,

[0038] In the formula, t u ,t i They are respectively the fault phase voltage u f (t), fault phase current i f The zero-crossing moment of (t);

[0039] Calculate the time difference between the voltage and current zero crossings Δt = t i -t u ; If Δt>0, the fault point is located upstream of the distribution terminal; if Δt<0, the fault point is located downstream of the distribution terminal.

[0040] Further, the morphological filtering process in step S12 specifically includes:

[0041] Dilation operation: Compare each point in the signal with the neighborhood value corresponding to the structural element, and select the maximum value in the neighborhood to replace the value of the current point. The calculation method of the dilation operation is as follows:

[0042]

[0043] f(x) represents the original signal; B is the structural element, which is a centrally symmetric digital sequence; f dilated is the new signal obtained after the expansion operation; x′∈B represents the relative position of each structural element B;

[0044] Corrosion operation: Each point in the signal is compared with the neighborhood corresponding to the structural element, and the minimum value in the neighborhood is taken to replace the value of the current point. The calculation method of the corrosion operation is as follows:

[0045]

[0046] f(x) represents the original signal; B′ is the structural element, which is a centrally symmetric digital sequence; f eroded is the new signal obtained after the corrosion operation; x′∈B′ represents the relative position of the structural element B′;

[0047] Open operation: first perform the corrosion operation, then the expansion operation;

[0048] Closing operation: first perform the dilation operation, then the erosion operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a structural framework diagram of the present invention; DETAILED DESCRIPTION

[0050] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0051] like Figure 1As shown, in embodiment 1, a method for detecting high-resistance faults in a distribution network and selecting a line comprises the following steps:

[0052] Step S01: Early warning start: Obtain zero-sequence voltage recording data and phase voltage and current recording data monitored by the distribution terminal, and generate the original waveform u from the zero-sequence voltage recording data 0 (t); for the original waveform u 0 (t) Perform morphological filtering, use a sliding window method to calculate the curve mutation area S(t), set the early warning adaptive threshold K, and determine whether the distribution network is in normal operation or abnormal operation;

[0053] Step S02: Fault detection: After the early warning is started, if the distribution network is in an abnormal operating state, a high-resistance grounding fault identification method based on signal difference is used for fault detection to determine whether the abnormal operating state is a switching disturbance or a high-resistance grounding fault;

[0054] Step S03: Fault line selection: When the abnormal operating state is a high-resistance ground fault, by analyzing the flow direction after the fault, the threshold setting problem is avoided, and it is determined whether the fault point is located upstream or downstream of the distribution terminal, thereby completing the fault line selection.

[0055] The present invention configures fault recording terminals at key nodes of distribution lines to measure the power frequency and zero-sequence voltage and current data of each node. Firstly, an early warning start mechanism is proposed, data preprocessing is performed on each waveform through morphological filtering, and the zero-sequence voltage curve mutation area S(t) is calculated by a sliding window method. Combined with the set early warning adaptive threshold K, it is further determined whether the distribution network is in a normal operating state; secondly, the present invention distinguishes between capacitor switching interference and high-resistance grounding fault through a high-resistance grounding fault identification method based on signal differential; finally, based on the fault flow distribution characteristics, the present invention analyzes the flow direction after the fault based on phase distribution, avoids the threshold setting problem of traditional line selection methods, and completes the fault line selection.

[0056] Embodiment 2: This embodiment is a further improvement on the basis of embodiment 1, and its details are as follows:

[0057] Step S01 specifically includes the following steps:

[0058] When the distribution network is operating soundly, the zero-sequence voltage monitored by the terminal is close to 0. When there is a line fault or disturbance such as capacitor switching, the zero-sequence voltage will rise until the fault disturbance is eliminated. This feature can be used as the basis for starting the distribution network diagnosis and early warning.

[0059] Step S11: Obtain the zero-sequence voltage recording data (for early warning start and fault detection) and phase voltage and current recording data (for fault line selection) monitored by the distribution terminal, and generate the original waveform u from the zero-sequence voltage recording data0 (t);

[0060] Step S12: The original waveform u 0y (t) Perform morphological filtering to obtain u 0 (t); On the basis of retaining the key features of the original waveform, the waveform denoising, feature enhancement and smoothing effects are achieved.

[0061] Step S13: Select a window pair u of a preset length 0 (t) Perform continuous scanning and calculate the waveform segment u in each window 0k (t) The curve mutation area S 1 (t), S 2 (t), according to S 1 (t) and S 2 (t) Calculate the curve mutation area S(t); Under the condition of 8kHz sampling rate, select a window with a window length X=160 (indicating the number of sampling points in the window);

[0062] Step S14: judging whether the distribution line is operating normally according to the curve mutation area S(t) and the early warning adaptive threshold K.

[0063] Embodiment 3, this embodiment is a further improvement on the basis of embodiment 2, and its details are as follows:

[0064] The waveform segments u in each window in step S13 0k (t) The curve mutation area S 1 (t), S 2 The calculation formula of (t) is as follows:

[0065]

[0066] In the formula, t represents u 0k (t) The sampling point corresponds to the time, f S represents the sampling frequency, f S =8000, S 1 (t) represents u 0k (t) The curve mutation area in the first 1 / 4 cycle, S 2 (t) represents u 0k (t) The curve mutation area in the first 1 / 2 cycle;

[0067] In order to avoid accidental factors under the fault interference state causing the single curve mutation area to be close to 0, thereby causing fault omission, the calculation formula of the curve mutation area S(t) is:

[0068] S(t)=max{4S 1 (t), 2S 2 (t)}.

[0069] Embodiment 4: This embodiment is a further improvement on the basis of embodiment 3, and its details are as follows:

[0070] Step S14 is specifically as follows:

[0071] In order to avoid short-term threshold crossing caused by short-term irregular waveform distortion, the early warning adaptive threshold K is designed based on the historical curve area data and the normal distribution probability to determine whether the curve mutation area S(t) exceeds the early warning adaptive threshold K. The calculation formula of the early warning adaptive threshold K is as follows:

[0072] K=μ+4σ,

[0073] In the formula, μ and σ represent the mean and variance of S(t) respectively;

[0074] Observe the position of the curve mutation area S(t) at any time in the Gaussian distribution of the historical curve mutation area data. If S(t)>K, it is considered that there is an abnormal behavior of fault or disturbance in the distribution line; if S(t)≤K, it is considered that the distribution line is operating normally at this time, and the curve mutation area S(t) of this time is used as the historical curve area data for the calculation of the next warning adaptive threshold K.

[0075] Embodiment 5, this embodiment is a further improvement on the basis of embodiment 4, and its details are as follows:

[0076] Step S02 specifically includes the following steps:

[0077] Step S21: After the early warning start process is completed and the distribution line is considered to be in an abnormal operating state, in order to distinguish between high-resistance grounding faults and capacitor switching interference, u 0k (t) Perform five-point difference to obtain u′ 0k (t), its expression is:

[0078]

[0079] Step S22: In actual scenarios, capacitor switching transients have two obvious characteristics: ① There is a high-frequency arc in the air gap of the circuit breaker during switching, which aggravates the transient oscillation degree; ② The duration of the zero-sequence transient process is short, which depends on the asynchronous action time of the circuit breaker; The oscillation degree of the waveform is quantified by the zero crossing of the waveform after differential under a fixed window, u′ 0k (t n ), u′ 0k (t n+1 ) is the difference value of two adjacent sampling points of the waveform after differentiation under a certain window, n = 1, 2, ..., 159, starting from the first two points under the window, if u′ is satisfied 0k (tn)·u′ 0k (tn+1 )≤0, it is considered that there is one zero-crossing point in the window, and the calculation is continued until the 159th time, and the total number of zero-crossing points in the window is N;

[0080] Step S23: Count u′ under 20 consecutive sliding windows 0k The number of zero-crossing points of (t) is N. If each window satisfies N>10, it is considered that there is a capacitor switching disturbance in the distribution network, otherwise it is considered that there is a high-resistance grounding fault in the distribution network.

[0081] Embodiment 6: This embodiment is a further improvement on the basis of embodiment 5, and its details are as follows:

[0082] Step S03 specifically includes the following steps:

[0083] Step S31: Obtain the power frequency phase voltage recording data monitored by the power distribution terminal and generate the original waveform u a (t),u b (t),u c (t), and align the three-phase waveforms by Beidou / GPS time scale, and then perform denoising, the denoising process adopts the method in step S12;

[0084] Step S32: According to the characteristics that the neutral point is offset toward the grounded phase and the waveform of the grounded phase decreases while the waveforms of the other two phases increase, the fault phase is determined; when a high-resistance grounding fault exists in the distribution network, the distribution network will be in an unbalanced state. Assuming that the A phase is grounded, since the distribution network adopts an indirect grounding method, the line voltage will remain unchanged after the fault, and the neutral point will be offset toward the A phase, resulting in u a (t) decreases, u b (t),u c (t) Rising characteristics, based on which fault phase discrimination can be achieved;

[0085] Step S33: After the fault phase is confirmed, the power frequency current recording data of the fault phase monitored by the power distribution terminal is obtained to generate the original waveform i fy (t), and denoising is performed to obtain i f (t), and then the fault phase voltage u is converted into f (t), fault phase current i f (t) waveform alignment;

[0086] Step S34: When the distribution network fails, the reactive power of the fault phase will flow from the fault point to both sides of the conductor. At this time, the phase angle between the current and voltage is negative, and the current leads the voltage. Based on this characteristic, the fault phase voltage u is obtained. f (t), fault phase current i f (t) Time domain waveform data, analyze the waveform data, and find out the fault phase voltage uf (t), fault phase current i f The zero crossing point of (t) (i.e. the crossing point of the waveform from the positive half cycle to the negative half cycle) satisfies:

[0087] u f (t u )=0,

[0088] i f (t i )=0,

[0089] Where, t u ,t i They are respectively the fault phase voltage u f (t), fault phase current i f The zero-crossing moment of (t);

[0090] Calculate the time difference between the voltage and current zero crossings Δt = t i -t u , the time difference reflects the fault phase voltage u f (t), fault phase current i f (t); since the terminal installation direction is from the small side to the large side, if Δt>0, the current is ahead of the voltage, indicating that the reactive power flows through the distribution terminal in the forward direction, and the fault point is located upstream of the distribution terminal; if Δt<0, the voltage is ahead of the current, indicating that the reactive power flows through the distribution terminal in the reverse direction, and the fault point is located downstream of the distribution terminal.

[0091] When a high-resistance ground fault occurs in a distribution line, the fault point will inject reactive power into the substations at both ends at the same time. However, due to the weak characteristics of the high-resistance ground fault, the traditional line selection method based on transient reactive power thresholds often fails. Based on the characteristics of the power flow distribution during a fault, the present invention analyzes the power flow direction after the fault, avoids the trouble of threshold setting, and realizes fault line selection (the fault point is located upstream or downstream of the terminal).

[0092] Embodiment 7: This embodiment is a further improvement based on any one of Embodiments 2 to 6, and its details are as follows:

[0093] The morphological filtering process in step S12 specifically includes:

[0094] Dilation operation: Compare each point in the signal with the neighborhood value corresponding to the structural element, and select the maximum value in the neighborhood to replace the value of the current point, thereby expanding the waveform value. It is usually used to expand the foreground area and enhance local features. The calculation method of the dilation operation is as follows:

[0095]

[0096] f(x) represents the original signal; B is the structural element, which is a centrally symmetric digital sequence; f dilated is the new signal obtained after the expansion operation; x′∈B represents the relative position of each structural element B;

[0097] Erosion operation: Each point in the signal is compared with the neighborhood corresponding to the structural element, and the minimum value in the neighborhood is taken to replace the value of the current point. The erosion operation is contraction compared to the dilation operation. The purpose is to reduce the size of the foreground area and remove details or noise. The calculation method of the erosion operation is as follows:

[0098]

[0099] f(x) represents the original signal; B′ is the structural element, which is a centrally symmetric digital sequence; f eroded is the new signal obtained after the corrosion operation; x′∈B′ represents the relative position of the structural element B′;

[0100] Opening operation: first perform corrosion operation, then dilation operation, which is used to remove small noise or irregular small fluctuations in the waveform and retain the large-scale waveform structure;

[0101] Closing operation: First perform the dilation operation, then the erosion operation, which is used to smooth out small depressions in the waveform and eliminate small fluctuations.

[0102] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for detecting high-resistance faults in a distribution network and selecting a line, characterized in that: The steps include: Step S01: Obtain zero-sequence voltage recording data and phase voltage and current recording data monitored by the distribution terminal, and generate the original waveform u0(t) from the zero-sequence voltage recording data; perform morphological filtering on the original waveform u0(t), calculate the curve mutation area S(t) by a sliding window method, set an early warning adaptive threshold K, and judge whether the distribution network is in a normal operating state or an abnormal operating state; Step S02: After the early warning is started, if the distribution network is in the abnormal operating state, a high-resistance grounding fault identification method based on signal difference is used to perform fault detection to determine whether the abnormal operating state is a switching disturbance or a high-resistance grounding fault; Step S03: When the abnormal operating state is the high-resistance grounding fault, the power flow direction after the fault is analyzed based on the phase distribution, and it is determined whether the fault point is located upstream or downstream of the power distribution terminal, thereby completing the fault line selection.

2. A method for detecting and selecting high-resistance faults in a distribution network according to claim 1, characterized in that: The step S01 specifically includes the following steps: Step S11: acquiring the zero-sequence voltage recording data and the phase voltage and current recording data monitored by the power distribution terminal, and generating the original waveform u0(t) from the zero-sequence voltage recording data; Step S12: The original waveform u 0y (t) performs morphological filtering to obtain u0(t); Step S13: Select a window of preset length to continuously scan u0(t) and calculate the waveform segment u in each window. 0k (t), the curve mutation area S1(t), S2(t), the curve mutation area S(t) is calculated according to S1(t) and S2(t); Step S14: judging whether the power distribution line is operating normally according to the curve mutation area S(t) and the early warning adaptive threshold K.

3. A method for detecting and selecting high-resistance faults in a distribution network according to claim 2, characterized in that: In step S13, the waveform segments u in each window 0k The calculation formulas for the curve mutation areas S1(t) and S2(t) are as follows: In the formula, t represents u 0k (t) The sampling point corresponds to the time, f S represents the sampling frequency, f S =8000, S1(t) represents u 0k (t) is the curve mutation area of ​​the first 1 / 4 period, S2(t) represents u 0k (t) The curve mutation area in the first 1 / 2 cycle; The calculation formula of the curve mutation area S(t) is: S(t)=max{4S1(t), 2S2(t)}.

4. A method for detecting and selecting high-resistance faults in a distribution network according to claim 3, characterized in that: The step S14 is specifically as follows: Based on the historical curve area data, the early warning adaptive threshold K is designed according to the normal distribution probability to determine whether the curve mutation area S(t) exceeds the early warning adaptive threshold K. The calculation formula of the early warning adaptive threshold K is as follows: K=μ+4σ, In the formula, μ and σ represent the mean and variance of S(t) respectively; If S(t)>K, it is considered that there is abnormal behavior of fault or disturbance in the distribution line; if S(t)≤K, it is considered that the distribution line is operating normally at this time, and the sudden change area S(t) of the curve this time is used as the historical curve area data for the calculation of the next warning adaptive threshold K.

5. A method for detecting and selecting high-resistance faults in a distribution network according to claim 4, characterized in that: The step S02 specifically includes the following steps: Step S21: 0k (t) Perform five-point difference to obtain u′ 0k (t), its expression is: Step S22: quantify the oscillation degree of the waveform by performing zero crossing of the waveform after differentiation under a fixed window, u′ 0k (t n ), u′ 0k (t n+1 ) is the difference value of two adjacent sampling points of the waveform after differentiation under a certain window, n = 1, 2, ..., 159, starting from the first two points under the window, if u′ is satisfied 0k (t n )·u′ 0k (t n+1 )≤0, it is considered that there is one zero-crossing point in the window, and the calculation is continued until the 159th time, and the total number of zero-crossing points in the window is N; Step S23: Count u′ under 20 consecutive sliding windows 0k The number of zero-crossing points of (t) is N. If each window satisfies N>10, it is considered that there is a capacitor switching disturbance in the distribution network, otherwise it is considered that there is a high-resistance grounding fault in the distribution network.

6. A method for detecting and selecting high-resistance faults in a distribution network according to claim 5, characterized in that: The step S03 specifically includes the following steps: Step S31: Obtain the power frequency phase voltage recording data monitored by the power distribution terminal and generate the original waveform u a (t),u b (t),u c (t), and align the three-phase waveforms through the Beidou / GPS time scale, and then perform denoising; Step S32: judging the fault phase according to the characteristics that the neutral point is offset toward the grounded phase and the waveform of the grounded phase decreases while the waveforms of the other two phases increase; Step S33: After the fault phase is confirmed, the power frequency current recording data of the fault phase monitored by the power distribution terminal is obtained to generate the original waveform i fy (t), and denoise to obtain i f (t), and then the fault phase voltage u is converted into f (t), fault phase current i f (t) waveform alignment; Step S34: Obtain the fault phase voltage u f (t), fault phase current i f (t) Time domain waveform data, analyze the waveform data, and find out the fault phase voltage u f (t), fault phase current i f The zero crossing point of (t) satisfies: u f (t u )=0, i f (t i )=0, Where, t u ,t i They are respectively the fault phase voltage u f (t), fault phase current i f The zero-crossing moment of (t); Calculate the time difference between the voltage and current zero crossings Δt = t i -t u ; If Δt>0, the fault point is located upstream of the distribution terminal; if Δt<0, the fault point is located downstream of the distribution terminal.

7. A method for detecting high-resistance faults in a distribution network and selecting a line according to any one of claims 2 to 6, characterized in that: The morphological filtering process in step S12 specifically includes: Dilation operation: Compare each point in the signal with the neighborhood value corresponding to the structural element, and select the maximum value in the neighborhood to replace the value of the current point. The calculation method of the dilation operation is as follows: f(x) represents the original signal; B is the structural element, which is a centrally symmetric digital sequence; f dilated is the new signal obtained after the expansion operation; x′∈B represents the relative position of each structural element B; Corrosion operation: Each point in the signal is compared with the neighborhood corresponding to the structural element, and the minimum value in the neighborhood is taken to replace the value of the current point. The calculation method of the corrosion operation is as follows: f(x) represents the original signal; B′ is the structural element, which is a centrally symmetric digital sequence; f eroded is the new signal obtained after the corrosion operation; x′∈B′ represents the relative position of the structural element B′; Open operation: first perform the corrosion operation, then the expansion operation; Closing operation: first perform the dilation operation, then the erosion operation.

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