High-precision traveling wave positioning method suitable for low sampling rate

Abstract

The invention relates to a low-sampling-rate traveling wave positioning method suitable for a power distribution line, and the method employs a plurality of traveling wave positioning devices near a fault point to collect traveling wave waveform data when a fault occurs in a power distribution network. The method comprises the following key steps: carrying out singular value removal and smoothing processing on collected traveling wave waveform data to reduce the influence of singular data; intercepting a rising edge waveform in each piece of waveform data, and screening waveform data with strong fault correlation and intact characteristic waveforms through correlation analysis; the equivalent arrival time of the screened waveform data is calculated through the interpolation expansion technology, so that the positioning error caused by the low sampling rate is reduced; and finally, realizing accurate positioning of a fault point by using a D-type traveling wave method based on a statistical time difference minimum value method of network topology. According to the method, through waveform preprocessing, correlation analysis, an interpolation expansion sampling technology and a statistical time difference minimum value method based on network topology, the influence of interference is effectively reduced, the influence of a low sampling rate is reduced, and the positioning precision is remarkably improved.

Description

Technical Field

[0001] The invention belongs to the technical field of power systems, and in particular relates to a high-precision traveling wave positioning method suitable for low sampling rates. Background Art

[0002] In the power system, fault detection and location of distribution lines are crucial to ensure the reliability of power supply and the stability of the system. As the scale of power systems continues to expand and the complexity increases, the demand for fault warning and precise positioning is growing. Traveling wave positioning technology has become an effective tool to address this challenge due to its high precision and rapid response. Traveling wave positioning technology performs fault diagnosis based on traveling wave theory. When a line fails, the fault point will excite a traveling wave signal that propagates to both sides. By measuring the time difference between the traveling wave reaching different ranging devices, the location of the fault point can be accurately calculated.

[0003] However, the key to traveling wave positioning technology lies in the calculation accuracy of the arrival time of the traveling wave head. Since the propagation speed of traveling waves is close to the speed of light, in order to improve the positioning accuracy, higher requirements are placed on the sampling rate. At present, the sampling rate of traveling wave positioning devices is usually above 1MHz or even 10MHz. Although this high sampling rate improves the resolution of the data, it also places higher requirements on the analysis, processing and storage of the data, and significantly increases the power consumption of the system.

[0004] The present invention aims to solve the data processing and power consumption problems caused by high sampling rate in the prior art, while maintaining the high precision and fast response characteristics of the traveling wave positioning technology. Summary of the invention

[0005] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art and propose a high-precision traveling wave positioning method suitable for low sampling rates. The present invention effectively removes waveform data that is not highly correlated with the fault, especially interference waveform data, through waveform preprocessing and correlation analysis, and significantly improves the positioning accuracy. In addition, by calculating the equivalent arrival time of the waveform, the positioning error problem caused by the large sampling interval at low sampling rates is solved, and the positioning accuracy is further improved. Furthermore, the statistical time difference minimum method is used to reduce the impact of random errors on positioning accuracy. Therefore, the method can achieve high-precision traveling wave positioning function at a relatively low sampling rate, reduce the cost, operating power consumption and design difficulty of the traveling wave positioning device, and has a high practical value.

[0006] The technical solution of the present application is as follows: A high-precision traveling wave positioning method suitable for low sampling rate, the method comprising the following steps:

[0007] Step 1: Each traveling wave positioning device collects the traveling wave data of each phase current in real time, and determines whether a fault occurs through the collected traveling waves; when a fault occurs, a traveling wave fault recording operation is performed;

[0008] Step 2: After the wave recording is completed, the recorded waveform data is pre-processed by removing singular values ​​and smoothing, and the pre-processed waveform data is sent to the traveling wave positioning master station through communication;

[0009] The steps to remove singular values ​​are:

[0010] (1) Smoothing the traveling wave waveform data X three times to obtain smoothed waveform data Y;

[0011] The 3rd smoothing method is:

[0012] (2) According to experience, the singular threshold th is set to 0.5A. When abs(y[i]-x[i])>th, it is determined to be a singular value point, and x[i] determined as a singular value is replaced by y[i];

[0013] (3) The data X finally obtained is used as the waveform data after removing the singular values.

[0014] The smoothing step is as follows: smoothing the waveform data after removing the singular values ​​for 5 times;

[0015]

[0016] Step 3: The traveling wave positioning master station selects the traveling wave waveform for ranging from the traveling wave waveforms sent by each traveling wave positioning device through correlation analysis;

[0017] The steps of correlation analysis are:

[0018] (1) Extract the rising edge waveform of each traveling wave waveform data. The extraction method is:

[0019] a. Calculate the maximum value maxA of the traveling wave waveform and the position of the maximum value,

[0020] b. Start from the maximum value and search forward to the first position posEnd where the amplitude is less than 0.9 times the maximum value.

[0021] c. Continue searching forward to the first position posStart where the amplitude is less than 0.1 times the maximum value.

[0022] d. Intercept the middle data x[posStart:posEnd] of the traveling wave waveform as the rising edge waveform;

[0023] (2) For all the rising edge waveforms captured, calculate the cosine similarity between them as the waveform correlation value

[0024] (3) Set the correlation empirical threshold to 0.8. For the i-th rising edge waveform, count the number of waveforms N[i] whose correlation with other waveforms is higher than the threshold.

[0025] (4) Find the rising edge waveform with the largest N value, and the traveling wave waveform with a correlation higher than the threshold among all traveling wave waveforms as the final traveling wave waveform for positioning.

[0026] Step 4: Use the equivalent time method to calculate the waveform equivalent arrival time of each traveling wave waveform, and use the statistical time difference minimum method to locate the fault.

[0027] The steps to calculate the equivalent moment are:

[0028] (1) Further process the traveling wave waveform, remove the points that are not monotonically changing, and restore the points that are monotonically changing by interpolation; search from the first point backward, remove all points that satisfy x[i+1]<x[i], and replace the removed points with the points obtained by linear interpolation of x[i-1] and x[i];

[0029] (2) The time scale of each point in the traveling wave waveform is t[i], and the amplitude is x[i].

[0030] (3) Use the traveling wave waveform to linearly interpolate the time of each point of the equivalent waveform; let the amplitude array of the equivalent waveform be z[M], and the time scale array be tz[M], where M is the size of the equivalent waveform and can be set to 9 according to experience. The value of the amplitude array is Using the amplitude array x of the traveling wave as the input array and the time-scale array t as the output array, the time-scale array tz[M] of the equivalent waveform is interpolated according to the target array z[M].

[0031] (4) Calculate the mean value td of the equivalent waveform time-scale array tz[M], which is the equivalent arrival time of the waveform.

[0032] The steps of the statistical time difference minimum method are:

[0033] (1) Record the installation position A[K] of the device that selects the upgoing wave waveform, where K is the number of devices, and record the calculated equivalent waveform equivalent arrival time array as td[K],

[0034] (2) Enumerate the distribution circuits associated with each device,

[0035] (3) Enumerate each location on the distribution line according to the location interval. The location interval can be set to 10 meters according to the empirical threshold;

[0036] (4) For each location, assume it is a fault location, and calculate the time tA[K] it takes for the fault to occur at that location and for the traveling wave to propagate to each device based on the traveling wave velocity.

[0037] (5) According to the distribution network topology, the equivalent arrival time difference td_differ[P] and propagation time difference tA_differ[P] of the equivalent waveforms of adjacent devices are calculated, where P is the number of groups of adjacent devices.

[0038] (6) Calculate the minimum statistical time difference dt = Σ(td_differ[i]-tA_differ[i]) 2 ,

[0039] (7) Among all the calculated statistical time differences, the position corresponding to the minimum dt value is selected as the fault location.

[0040] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, a low sampling rate traveling wave positioning method applicable to distribution lines is implemented.

[0041] Compared with the prior art, the present invention has the following significant advantages:

[0042] 1. Data preprocessing: By removing singular values ​​and smoothing the traveling wave waveform data, the present invention not only significantly reduces the impact of external interference, but also improves the effectiveness of subsequent correlation analysis. This preprocessing step ensures the quality of the data and the accuracy of the analysis.

[0043] 2. Correlation analysis: The present invention effectively eliminates the adverse effects of singular traveling wave waveforms on fault location caused by various reasons by performing comprehensive positioning through the traveling wave waveform array screened out through correlation analysis. This step significantly improves the accuracy and stability of positioning.

[0044] 3. Low sampling rate requirement: The present invention uses the equivalent waveform equivalent arrival time method to calculate the arrival time difference between traveling waves. This method reduces the sampling rate requirement while ensuring the positioning basis. Compared with traditional algorithms, the present invention only requires a sampling rate of 200kHz or above to achieve high-precision positioning, while traditional algorithms usually require a sampling rate of at least 1MHz or even 10MHz.

[0045] 4. Statistical time difference method: The final fault location is obtained by using the statistical time difference method. The present invention reduces the influence of random errors of some traveling wave positioning devices on the positioning results and further improves the positioning accuracy.

[0046] In summary, the present invention ensures from multiple aspects that high-precision positioning results can be obtained at low sampling rates, effectively reduces the cost and design difficulty of the traveling wave positioning device, and improves the economy and practicality of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0049] The following descriptions of the embodiments refer to the accompanying drawings to illustrate specific embodiments in which the present invention may be implemented.

[0050] Example: Figure 1 A high-precision traveling wave positioning method suitable for low sampling rate is shown, comprising:

[0051] (1) Each traveling wave positioning device collects the traveling wave data of each phase current in real time, and determines whether a fault occurs based on the collected traveling waves; when a fault occurs, a traveling wave fault recording operation is performed;

[0052] (2) After the wave recording is completed, the recorded waveform data is pre-processed by removing singular values ​​and smoothing, and the pre-processed waveform data is sent to the traveling wave positioning master station through communication;

[0053] The steps to remove singular values ​​are:

[0054] a. Smooth the traveling wave data X three times to obtain the smoothed waveform data Y

[0055] The 3rd smoothing method is:

[0056] b. According to experience, the singular threshold th is set to 0.5A. When abs(y[i]-x[i])>th, it is determined to be a singular value point, and x[i] determined as a singular value is replaced by y[i]

[0057] c. The final data X is used as the waveform data after removing the singular value

[0058] The smoothing step is: smooth the waveform data after removing the singular values ​​5 times

[0059]

[0060] (3) The traveling wave positioning master station selects the traveling wave waveforms for ranging from the traveling wave waveforms sent by each traveling wave positioning device through correlation analysis;

[0061] The steps of correlation analysis are:

[0062] a. Cut out the rising edge waveform of each traveling wave waveform data. The cutting method is:

[0063] 1. Calculate the maximum value maxA of the traveling wave waveform and the position of the maximum value

[0064] 2. Start from the maximum value and search forward to the first position where the amplitude is less than 0.9 times the maximum value, posEnd

[0065] 3. Continue to search forward to the first position posStart where the amplitude is less than 0.1 times the maximum value

[0066] 4. Intercept the intermediate data x[posStart:posEnd] of the traveling wave waveform as the rising edge waveform

[0067] b. For all the rising edge waveforms captured, calculate the cosine similarity between them as the waveform correlation value

[0068] c. Set the correlation empirical threshold to 0.8. For the i-th rising edge waveform, count the number of waveforms N[i] whose correlation with other waveforms is higher than the threshold.

[0069] d. Find the rising edge waveform with the largest N value, and the traveling wave waveform with a correlation higher than the threshold among all traveling wave waveforms as the final traveling wave waveform for positioning.

[0070] (4) The equivalent arrival time of each traveling wave waveform is calculated using the equivalent time method, and the statistical time difference minimum method is used to locate the fault.

[0071] The steps to calculate the equivalent moment are:

[0072] a. Further process the traveling wave waveform, remove the points that are not monotonically changing, and use interpolation to restore the points that are monotonically changing

[0073] Search from the first point backwards, remove all points that satisfy x[i+1]<x[i], and replace the removed points with points obtained by linear interpolation of x[i-1] and x[i];

[0074] b. Let the time scale of each point of the traveling wave waveform be t[i], the amplitude be x[i], and use the traveling wave waveform to linearly interpolate the equivalent waveform

[0075] a point in time;

[0076] The amplitude array of the equivalent waveform is z[M], the time scale array is tz[M], M is the size of the equivalent waveform, which can be set to 9 according to experience. The value of the amplitude array is Using the amplitude array x of the traveling wave as the input array and the time-scale array t as the output array, the time-scale array tz[M] of the equivalent waveform is interpolated according to the target array z[M].

[0077] c. Calculate the mean value td of the equivalent waveform time-scale array tz[M], which is the equivalent arrival time of the waveform.

[0078] The steps of the statistical time difference minimum method are:

[0079] a. Record the installation position A[K] of the device that filters out the upgoing wave waveform, where K is the number of devices, and record the calculated equivalent waveform equivalent arrival time array as td[K]

[0080] b. Enumerate the distribution lines associated with each device, and enumerate each location on the distribution line according to the location interval. The location interval can be set to 10 meters according to the empirical threshold;

[0081] c. For each location, assume it is the fault location, and calculate the time tA[K] required for the fault to occur at that location and for the traveling wave to propagate to each device based on the traveling wave velocity.

[0082] d. According to the distribution network topology, calculate the equivalent waveform arrival time difference td_differ[P] and propagation time difference tA_differ[P] of adjacent devices, where P is the number of adjacent devices.

[0083] e. Calculate the minimum statistical time difference dt = Σ(td_differ[i]-tA_differ[i]) 2

[0084] f. Among all the calculated statistical time difference values, select the position corresponding to the minimum dt value as the fault location.

[0085] The technical means disclosed in the scheme of the present invention are not limited to the technical means disclosed in the above-mentioned implementation mode, but also include technical schemes composed of any combination of the above technical features.

Claims

1. A low sampling rate traveling wave positioning method suitable for distribution lines, characterized in that: The method comprises the following steps: Step 1: Each traveling wave positioning device collects the traveling wave data of each phase current in real time, and determines whether a fault occurs through the collected traveling waves; when a fault occurs, the traveling wave fault recording operation is performed. Step 2: After the recording is completed, the recorded waveform data is pre-processed by removing singular values ​​and smoothing, and the pre-processed waveform data is sent to the traveling wave positioning master station through communication. Step 3: The traveling wave positioning master station selects the traveling wave waveforms for ranging from the traveling wave waveforms sent by each traveling wave positioning device through correlation analysis. Step 4: Use the equivalent time method to calculate the waveform equivalent arrival time of each traveling wave waveform, and use the statistical time difference minimum method to locate the fault.

2. A low sampling rate traveling wave positioning method suitable for distribution lines according to claim 1, characterized in that: In step 2, the singular value removal is as follows: (1) Smoothing the traveling wave waveform data X three times to obtain smoothed waveform data Y; The 3rd smoothing method is: Among them, x[i] is the i-th data point of the original waveform data, and y[i] is the i-th data point of the smoothed data. (2) Set the singular threshold th to 0.5A. When abs(y[i]-x[i])>th, x[i] is determined to be a singular value point, and x[i] determined to be a singular value is replaced by y[i]. (3) The data X finally obtained is used as the waveform data after removing the singular values.

3. A low sampling rate traveling wave positioning method suitable for distribution lines according to claim 1, characterized in that: In step 2, the smoothing step is to smooth the waveform data after removing the singular values ​​for 5 times, and the method is as follows: Where Z is the smoothed waveform data, which is used for subsequent further calculations.

4. The low sampling rate traveling wave positioning method applicable to distribution lines according to claim 1, characterized in that: In step 3, the correlation analysis steps are: (1) Cut out the rising edge waveform of each traveling wave waveform data, and the cutting method is: a. Calculate the maximum value maxA of the traveling wave waveform and the position of the maximum value, b. Start from the maximum value and search forward to the first position posEnd where the amplitude is less than 0.9 times the maximum value. c. Continue searching forward to the first position posStart where the amplitude is less than 0.1 times the maximum value. d. Intercept the middle data x[posStart:posEnd] of the traveling wave waveform as the rising edge waveform. (2) For all the rising edge waveforms captured, the cosine similarity between the two is calculated as the waveform correlation value. (3) Set the correlation empirical threshold to 0.

8. For the i-th rising edge waveform, count the number of waveforms N[i] whose correlation with other waveforms is higher than the threshold. (4) Find the rising edge waveform with the largest N value, and the traveling wave waveform with a correlation with the rising edge waveform higher than a threshold among all traveling wave waveforms as the traveling wave waveform for final positioning.

5. The low sampling rate traveling wave positioning method applicable to distribution lines according to claim 1, characterized in that: In step 4, the equivalent time calculation steps are: (1) Further process the traveling wave waveform, remove the points that are not monotonically changing, and use the interpolation method to restore the monotonically changing points; search from the first point backward, remove all points that satisfy x[i+1]<x[i], and replace the removed points with the points obtained by linear interpolation of x[i-1] and x[i], (2) The time scale of each point in the traveling wave waveform is t[i], and the amplitude is x[i]. (3) Use the traveling wave waveform to linearly interpolate the time of each point of the equivalent waveform. The amplitude array of the equivalent waveform is denoted as az[M], and the time scale array is tz[M]. M is the size of the equivalent waveform, which can be set to 9 according to experience. The value of the amplitude array is Using the amplitude array x of the traveling wave as the input array and the time-scale array t as the output array, the time-scale array tz[M] of the equivalent waveform is interpolated according to the target array az[M]. (4) Calculate the mean value td of the equivalent waveform time-scale array tz[M], which is the equivalent arrival time of the waveform.

6. The low sampling rate traveling wave positioning method applicable to distribution lines according to claim 1, characterized in that: In step 4, the steps of the statistical time difference minimum method are: (1) Record the installation position A[K] of the device that selects the upgoing wave waveform, where K is the number of devices, and record the calculated equivalent waveform equivalent arrival time array as td[K], (2) Enumerate the distribution circuits associated with each device, (3) Enumerate each location on the distribution line according to the location interval, and set the location interval to 10 meters according to the empirical threshold. (4) For each location, assume it is a fault location, and calculate the time tA[K] it takes for the fault to occur at that location and for the traveling wave to propagate to each device based on the traveling wave velocity. (5) According to the distribution network topology, the equivalent arrival time difference td_differ[P] and propagation time difference tA_differ[P] of the equivalent waveforms of adjacent devices are calculated, where P is the number of groups of adjacent devices. (6) Calculate the minimum statistical time difference dt = ∑ (td_differ[i] - tA_differ[i]) 2 , (7) Among all the calculated statistical time difference values, the position corresponding to the minimum dt value is selected as the fault location.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, a low sampling rate traveling wave positioning method suitable for distribution lines as described in any one of claims 1 to 6 is implemented.

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