CN106841915B - Power transmission line fault positioning method based on compressed sensing - Google Patents
Power transmission line fault positioning method based on compressed sensing Download PDFInfo
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- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/085—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution lines, e.g. overhead
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Abstract
The invention discloses a power transmission line fault positioning method based on Compressed Sensing, which is characterized in that Compressed Sensing (CS) is applied to fault positioning aiming at the problems of low precision and the like of the existing power transmission line fault signal processing method. Constructing an over-complete dictionary; extracting fault signal data, and preprocessing by utilizing a wavelet modulus maximum method and combining FIR filtering; providing a Fast-DOMP algorithm to analyze the frequency domain signal of the fault traveling wave; based on the information, a multi-time natural frequency value of the traveling wave is estimated by utilizing compressed sensing, and a power transmission line fault positioning method is provided for analyzing different fault conditions of the power transmission line. The method is scientific and reasonable, and has the advantages of high positioning precision, high popularization and application value, good effect and the like.
Description
Technical Field
The invention relates to the technical field of power transmission, in particular to a power transmission line fault positioning method based on compressed sensing.
Background
The power industry is the basic power for national economic development, and reliable power supply is also the prerequisite guarantee for the stable development of the modern society. The transmission line fault is the link with the most faults in the power system. After the line is in fault, if the position of the fault point can be found out timely, accurately and reliably, the method plays a great role in the economic operation of the whole country and the safety and stability of the whole power system. Therefore, the research on the fault location of the transmission line is always a hotspot in the power industry, and particularly, the research on a quick and accurate fault location method is of great significance. For this reason, many fault location methods have been proposed, which can be classified into an impedance method, a fault analysis method, a time-domain traveling wave method, and a natural frequency component method according to the principle of calculating the fault distance. The positioning accuracy of the impedance method and the fault analysis method is greatly influenced by factors such as transition resistance, system parameters and the like, and the time-domain traveling wave method which is widely researched at present is less influenced by the factors. However, the method is difficult to accurately identify the wave head, the traveling wave speed is influenced by the frequency in the transmission of the lossy transmission line, the corresponding traveling wave speed is difficult to accurately calculate, and the fault positioning precision is influenced, and the natural frequency component method is basically not interfered by the problems.
At present, most of the methods for extracting natural frequency values include Fourier Transform (FT), Wavelet Transform (WT), Matching Pursuit (MP), and the like. The Fourier transform has a large error in extracting the natural frequency value under the condition that the processing main natural frequency value is low and the wavelet transform is high. The MP algorithm uses an inner product to represent the similarity between atoms and a signal to be processed, but the method cannot effectively distinguish two atoms in a dictionary with high correlation between atoms, so that the selection of the optimal matching atoms is influenced. In addition, the method only depends on extracting a single main natural frequency value when determining the natural frequency value, but the value is greatly influenced by factors such as noise, discontinuous lines, harmonic interference and the like, so that the positioning effect is influenced.
The invention patent with the patent application number of 201310616675.4 is to finish the positioning of faults by combining a Gabor dictionary and an MP algorithm, and neither the dictionary nor a reconstruction algorithm is optimally designed for the characteristics of traveling wave fault signals. In order to better improve the analysis and identification capability of the signals, the dictionary must be highly redundant, so that the decomposition result achieves higher sparsity.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide the power transmission line fault positioning method based on the compressed sensing, which is scientific, reasonable, strong in applicability and good in effect. According to the method, an over-complete dictionary is constructed and completed according to the analysis and processing of actual data, and a Fast-DOMP algorithm is provided to analyze frequency domain signals of fault traveling waves; on the basis, multiple natural frequency values of the traveling wave are estimated by utilizing compressed sensing, so that a power transmission line fault positioning method based on compressed sensing is provided, the universality analysis is carried out on different fault conditions of the power transmission line, and the fault positioning accuracy is improved.
The technical scheme adopted for realizing the aim of the invention is as follows: a transmission line fault positioning method based on compressed sensing is characterized by comprising the following steps:
1) and (3) according to the analysis and processing of actual data, constructing and finishing an over-complete dictionary:
①, analyzing the frequency domain signals of the traveling waves by selecting different fault types and different fault distances;
②, carrying out segmentation processing on the frequency domain signal of the traveling wave, firstly extracting the first 6 wave crests for analysis, and then fitting each section of wave crest through a Gaussian function to obtain an atomic window function for constructing the dictionary, wherein the atomic window function is as follows:
wherein gamma is gγIndex of (a)1,b1,c1,…a3,b3,c3The parameter values are weighted average values after being analyzed by a plurality of groups of data because the variation fluctuation of the parameters b and c is small;
③, analyzing the parameters of the atomic window function, and finally constructing an overcomplete dictionary through scale and translation modulation:
D＝{D1,D2,...,Dm} (2)
wherein D has dimension NXNa，D1And DmThe values of (A) are:
in the formula D1Is directed to the 1 st parameter gamma1(a1,a2,a3) Each column of atoms, DmIs directed to the m-th set of parameters gammam(a1,a2,a3) Each column of atoms, and wherein
And
the values of (A) are:
2) extracting fault signal data, and preprocessing by using wavelet mode maximum and combining FIR filtering:
① extracting fault data, transforming into traveling wave signals through phase mode, obtaining corresponding mode components by Clarke transformation, wherein the Clarke transformation matrix is:
②, adopting wavelet modulus maximum method to detect mutation points, effectively analyzing mutation signals, then combining FIR high pass filter to filter low frequency interference components to complete pretreatment, reducing the influence of low frequency interference components on identifying natural frequency values;
3) and (3) providing a Fast-DOMP algorithm to analyze the frequency domain signals of the fault traveling waves:
① on the basis of orthogonal matching pursuit, the optimal atom is found in the dictionary by introducing the Dice coefficient atom matching criterion, and two similar atoms can be effectively distinguished, wherein the Dice coefficient is:
② Signal index γ a is obtained by fast Fourier transform preprocessing1,a2,a3Prior information of the dictionary is used for restraining the search range of m groups of parameters in the overcomplete dictionary;
③, selecting the atom which is most matched with the residual signal from the dictionary according to the index gamma, and adding the atom into the support set omega:
④ approximate the original signal using the existing atoms in the support set Ω:
⑤ update the residual signal:
repeating the previous two steps until a stop iteration condition is met;
⑥ solving the approximate value of the sparse coefficient u from y to phi Du
Reflecting the main natural frequency information of the traveling wave signal;
4) and (3) carrying out compressed sensing to estimate multiple natural frequency values of the traveling wave, and carrying out accurate fault location:
①, on the basis of the compressive sensing theory, estimating multiple natural frequency values of the traveling wave by using a new dictionary and algorithm;
② locating the fault position by using the multiple natural frequency value of the fault travelling wave and combining the following formula:
where L is the distance to failure, θmkIs a bus EmAngle of reflection of end travelling wave, vm1For the travelling-wave mode wave velocity, f, at the corresponding frequencykThe frequency value is k times of main natural frequency values of the m-end traveling wave, and sigma is the residual quantity;
③ are used for universal analysis of different fault situations of the power transmission line.
The invention provides a power transmission line fault positioning method based on compressed sensing, which starts from the optimization design of an over-complete dictionary and the improvement of a reconstruction algorithm, utilizes the frequency domain signal characteristics of a traveling wave fault signal to construct the over-complete dictionary, and identifies a traveling wave natural frequency value through an improved Fast-DOMP algorithm; finally, accurate fault location is realized by combining a fault location algorithm of multiple natural frequencies, the effectiveness of the method provided by the invention is proved through simulation results, the resolution is high, the stability is good, and the requirement of a power system on fault location can be better met. Compared with the prior art, the invention has the further effects that:
1) by designing a new over-complete dictionary, the sparsity and pertinence of the dictionary are higher, a Fast-DOMP algorithm is provided to process fault frequency domain signals, and the accuracy and speed of the algorithm are effectively improved;
2) different fault conditions of the power transmission line are analyzed, compressed sensing is applied to fault positioning, and the method is combined with a mode of multiple traveling wave natural frequencies, so that the problems of low accuracy and the like of the existing power transmission line fault signal processing method are effectively solved, and the requirements of a power system on the accuracy and the stability of the same fault positioning can be met;
3) the method is scientific and reasonable, has strong applicability, high popularization and application value and good effect.
Drawings
FIG. 1 is a schematic flow chart of a compressed sensing-based transmission line fault location method of the invention;
FIG. 2 is a schematic diagram of a frequency domain signal analysis of a 100Km traveling wave;
FIG. 3 is a schematic diagram of a 50Km traveling wave frequency domain signal analysis;
FIG. 4 is a schematic diagram of atomic parameter variation analysis;
FIG. 5 is a schematic illustration of atomic translation;
FIG. 6 is a schematic diagram of a power transmission line simulation model;
FIG. 7 is a schematic diagram of a three-phase voltage waveform;
FIG. 8 is a schematic diagram of a three-phase current waveform;
FIG. 9 is a schematic representation of a traveling wave signal;
FIG. 10 is a schematic diagram of a residual signal waveform;
fig. 11 is a schematic diagram of a traveling wave frequency domain signal reconstruction waveform.
Detailed Description
The following detailed description of embodiments of the present invention will be made with reference to the accompanying drawings and examples.
The following description and the annexed drawings set forth in detail certain illustrative embodiments of the invention to enable those skilled in the art to practice the invention. Other embodiments may incorporate structural, logical, electrical, process, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. The scope of the embodiments of the invention encompasses the full ambit of the claims, as well as all available equivalents of the claims. These embodiments may be referred to, individually or collectively, by the term "invention" herein for convenience only and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed.
As shown in fig. 1, the invention provides a power transmission line fault location method based on compressed sensing, which combines the multiple natural frequency value fault location principle on the basis of the compressed sensing theory, and the fault location process effectively improves the accuracy and stability of power transmission line fault location, and comprises the following steps:
1) and (3) according to the analysis and processing of actual data, constructing and finishing an over-complete dictionary:
①, selecting frequency domain signals of the downlink waves of three different fault types (single-end grounding, two-end short circuit and three-end short circuit) and different fault distances for analysis, as shown in fig. 2 and 3;
②, performing segmentation processing on the frequency domain signal of the traveling wave, firstly extracting the first 6 wave crests for analysis, as shown in fig. 2 and fig. 3, and then fitting each section of wave crest through a gaussian function to obtain an atomic window function for constructing a dictionary, wherein the atomic window function is as follows:
wherein gamma is gγIndex of (a)1,b1,c1,…a3,b3,c3Is the ginseng thereinThe parameter values of b and c are subjected to multiple groups of data analysis and then weighted average values are obtained due to small fluctuation of parameter changes, and the parameter changes are shown as (a) and (b) in fig. 4;
③, analyzing the parameters of the atomic window function, and finally constructing an overcomplete dictionary through scale and translation modulation:
D＝{D1,D2,...,Dm} (2)
wherein D has dimension NXNaAtomic translation as shown in FIGS. 5 (a) and (b), D1And DmThe values of (A) are:
in the formula D1Is directed to the 1 st parameter gamma1(a1,a2,a3) Each column of atoms, DmIs directed to the m-th set of parameters gammam(a1,a2,a3) Each column of atoms, and wherein
And
the values of (A) are:
2) extracting fault signal data, and preprocessing by using wavelet mode maximum and combining FIR filtering:
① extracting fault data, converting into traveling wave signal by phase mode, the three-phase voltage current data is shown in fig. 7 and fig. 8, the traveling wave signal is shown in fig. 9, obtaining corresponding mode component by Clarke conversion, wherein the Clarke conversion matrix is:
②, adopting wavelet modulus maximum method to detect mutation points, effectively analyzing mutation signals, then combining FIR high pass filter to filter low frequency interference components to complete pretreatment, reducing the influence of low frequency interference components on identifying natural frequency values;
3) and (3) providing a Fast-DOMP algorithm to analyze the frequency domain signals of the fault traveling waves:
① on the basis of orthogonal matching pursuit, the optimal atom is found in the dictionary by introducing the Dice coefficient atom matching criterion, and two similar atoms can be effectively distinguished, wherein the Dice coefficient is:
② Signal index γ a is obtained by fast Fourier transform preprocessing1,a2,a3Prior information of the dictionary is used for restraining the search range of m groups of parameters in the overcomplete dictionary;
③, selecting the atom from the dictionary which matches best with the residual signal according to the index gamma, and adding the atom to the support set omega, wherein the residual signal is shown in FIG. 10:
④ approximate the original signal using the existing atoms in the support set Ω:
⑤ update the residual signal:
repeating the previous two steps until a stop iteration condition is met;
⑥ solving an approximation of u from y to Φ Du
Then the original signal
The reconstructed signal is shown in fig. 11;
4) and (3) carrying out compressed sensing to estimate multiple natural frequency values of the traveling wave, and carrying out accurate fault location:
①, on the basis of the compressive sensing theory, estimating multiple natural frequency values of the traveling wave by using a new dictionary and algorithm;
② locating the fault position by using the multiple natural frequency value of the fault travelling wave and combining the following formula:
where L is the distance to failure, θmkIs a bus EmAngle of reflection of end travelling wave, vm1For the travelling-wave mode wave velocity, f, at the corresponding frequencykThe frequency value is k times of main natural frequency values of the m-end traveling wave, and sigma is the residual quantity;
③ simulation and general analysis for different fault conditions are shown in tables 1 and 2 below.
TABLE 1 Fault location results for different fault types and different fault locations
TABLE 2 Fault location results for different ground resistances
Example material simulation:
the invention takes the power transmission lines with different fault types, different fault points, different fault grounding resistances and other fault conditions as an example to verify the fault positioning accuracy of the dictionary designed by the invention and the proposed Fast-DOMP algorithm, and refer to FIG. 6.
The simulation parameters are set as follows: the simulation time is 0.0-0.1s, a fixed step length 1e-6 and a resolving algorithm ode3 are adopted, the fault conversion time is [0.035,0.08], the Frequency is 50Hz, the effective values of line voltages are all 500KV, the sampling data format is set to be a matrix form, and the dictionary designed by the invention and the proposed Fast-DOMP algorithm are utilized to carry out waveform analysis on different fault conditions.
The invention well improves the precision of power transmission line fault location by the designed dictionary and the proposed Fast-DOMP algorithm, and the fault location method for estimating the traveling wave natural frequency by compressed sensing has better transient signal processing capability, higher resolution, high location precision and good stability, and can better meet the requirement of a power system on fault location.
Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can make modifications and equivalents to the specific embodiments of the present invention without departing from the spirit and scope of the present invention, which falls within the scope of the appended claims.
Claims (1)
1. A transmission line fault positioning method based on compressed sensing is characterized by comprising the following steps:
1) and (3) according to the analysis and processing of actual data, constructing and finishing an over-complete dictionary:
①, analyzing the frequency domain signals of the traveling waves by selecting different fault types and different fault distances;
②, carrying out segmentation processing on the frequency domain signal of the traveling wave, firstly extracting the first 6 wave crests for analysis, and then fitting each section of wave crest through a Gaussian function to obtain an atomic window function for constructing the dictionary, wherein the atomic window function is as follows:
wherein gamma is gγIndex of (a)1,b1,c1,…a3,b3,c3The parameter values are weighted average values after being analyzed by a plurality of groups of data because the variation fluctuation of the parameters b and c is small;
③, analyzing the parameters of the atomic window function, and finally constructing an overcomplete dictionary through scale and translation modulation:
D＝{D1,D2,...,Dm} (2)
wherein D has dimension NXNa，D1And DmThe values of (A) are:
in the formula D1Is directed to the 1 st parameter gamma1(a1,a2,a3) Each column of atoms, DmIs directed to the m-th set of parameters gammam(a1,a2,a3) Each column of atoms, and wherein
And
the values of (A) are:
2) extracting fault signal data, and preprocessing by using wavelet mode maximum and combining FIR filtering:
① extracting fault data, transforming into traveling wave signals through phase mode, obtaining corresponding mode components by Clarke transformation, wherein the Clarke transformation matrix is:
②, adopting wavelet modulus maximum method to detect mutation points, effectively analyzing mutation signals, then combining FIR high pass filter to filter low frequency interference components to complete pretreatment, reducing the influence of low frequency interference components on identifying natural frequency values;
3) and (3) providing a Fast-DOMP algorithm to analyze the frequency domain signals of the fault traveling waves:
① on the basis of orthogonal matching pursuit, the optimal atom is found in the dictionary by introducing the Dice coefficient atom matching criterion, and two similar atoms can be effectively distinguished, wherein the Dice coefficient is:
② Signal index γ a is obtained by fast Fourier transform preprocessing1,a2,a3Prior information of the dictionary is used for restraining the search range of m groups of parameters in the overcomplete dictionary;
③, selecting the atom which is most matched with the residual signal from the dictionary according to the index gamma, and adding the atom into the support set omega:
④ approximate the original signal using the existing atoms in the support set Ω:
⑤ update the residual signal:
repeating the previous two steps until a stop iteration condition is met;
⑥ solving the approximate value of the sparse coefficient u from y to phi Du
Reflecting the main natural frequency information of the traveling wave signal;
4) and (3) carrying out compressed sensing to estimate multiple natural frequency values of the traveling wave, and carrying out accurate fault location:
①, on the basis of the compressive sensing theory, estimating multiple natural frequency values of the traveling wave by using a new dictionary and algorithm;
② locating the fault position by using the multiple natural frequency value of the fault travelling wave and combining the following formula:
where L is the distance to failure, θmkIs a bus EmAngle of reflection of end travelling wave, vm1For the travelling-wave mode wave velocity, f, at the corresponding frequencykThe frequency value is k times of main natural frequency values of the m-end traveling wave, and sigma is the residual quantity;
③ perform a universal analysis for different fault conditions.
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| CN110045226A (en) * | 2019-03-18 | 2019-07-23 | 昆明理工大学 | A kind of compressed sensing based electrical power distribution network fault location method |
| CN110221168B (en) * | 2019-05-15 | 2021-03-09 | 广西电网有限责任公司电力科学研究院 | Method for positioning leading harmonic source and tracking harmonic pollution propagation path |
| CN110553156B (en) * | 2019-08-30 | 2020-09-25 | 清华大学 | Pipeline ultrasonic guided wave compression sensing health monitoring method |
| CN112269099A (en) * | 2020-10-12 | 2021-01-26 | 广东电网有限责任公司广州供电局 | Voltage sag state estimation method and system based on compressed sensing theory |
| CN117909909B (en) * | 2024-03-19 | 2024-06-14 | 青岛鼎信通讯股份有限公司 | Arc grounding fault identification method for power distribution network |
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