Single-end distance measurement method and device based on multi-algorithm fusion analysis

Abstract

The invention provides a single-end distance measurement method and device based on multi-algorithm fusion analysis. The distance measurement method comprises the following steps: obtaining distance measurement voltage and current after converting steady-state data of voltage and current before and after a fault point; dividing the ranging algorithm into two branch structures, namely a transition resistance-free branch structure and a transition resistance branch structure, and adaptively selecting the required branch structure to perform multi-algorithm ranging calculation according to a judgment result of whether the transition resistance exists or not; calculating a mean value of the algorithm ranging results of the two branch structures, and removing abnormal results according to the mean value to obtain residual algorithm ranging results; and constructing a fusion weighting function, recalculating a mean square error of a residual algorithm ranging result, constructing a ranging algorithm weighted value according to the mean square error, combining the algorithm weighted value with the residual algorithm ranging result, and calculating to obtain a final unique ranging value. According to the invention, the branch structure of the algorithm can be directly selected in a self-adaptive manner when the grounding fault occurs through and not through the transition resistor, and the flexibility of distance measurement is improved.

Description

Technical Field

[0001] The invention relates to a fault distance measurement method for an electric power system, and in particular to a distance measurement method for multi-algorithm fusion analysis. Background Art

[0002] Due to the complexity and diversity of the power system structure, when a fault occurs, it is necessary to quickly and accurately locate the fault point and eliminate the fault in time, so as to shorten the repair time of the faulty line and improve the stability of the system.

[0003] At present, the fault distance measurement / location function of most transmission lines is integrated into the fault recorder. The power grid has certain requirements for the accuracy of the single-ended fault distance measurement algorithm of the fault recorder. In the application of power system engineering in my country, common single-ended fault distance measurement algorithms include impedance method, complex equation solution method, differential equation solution method, etc. These algorithms only need to use the electrical quantity on one side of the line, the acquisition signal is easy to obtain, and the method is simple and easy to implement.

[0004] In the current use of single-ended fault location algorithms, some operating devices perform poorly in harsh environments due to two reasons: One is that the transition resistance is not zero, and the influence of the transition resistance cannot be overcome. The line action is more complicated, and the fault distance measurement result often has too large an error. The other is the uncertainty of the results measured by a single ranging algorithm. After the ranging is completed, it is impossible to judge the validity of the ranging results. Some researchers introduce two ranging algorithms in the ranging process. First, one ranging algorithm is used for predictive ranging, and then the second ranging algorithm is used for precise ranging. The two ranging results are compared and one of them is taken as the final result, but this comparison is often accidental.

[0005] Regarding the first aspect of the problem, in the prior art, a master's thesis from Xihua University (Li Shuangxiu, Electrical Engineering, October 2020) disclosed a study on a method for calculating the fault distance of a distribution network based on single-ended impedance measurement. It mentioned that the existence of transition resistance has a certain impact on the accuracy of fault location, and corresponding measures are adopted to reduce the impact of transition resistance.

[0006] Regarding the second aspect of the problem, another invention patent with publication number CN105823964A provides a comprehensive fault location method for transmission lines for smart substations. When a transmission line fails, the method selects the method with the highest ranging accuracy among the existing single-ended power frequency ranging methods to provide accurate fault location information. The existing power frequency ranging methods currently have different sources of system errors, and the ranging accuracy will be affected by the combined influence of parameters such as power supply, opposite system impedance and transition resistance. Under different fault conditions, the ranging accuracy of each method will have different performances and give different ranging results. The invention first obtains a large number of training samples when a transmission line fails, applies rough set theory to simplify the attributes of the training samples, finds the intrinsic relationship between ranging accuracy and fault conditions, deletes parameters with smaller influencing factors, and speeds up the solution process. When a system fails, the KNN algorithm is applied to find the method with the most accurate ranging results among multiple power frequency ranging methods to improve the ranging accuracy. Another article published by Shu Hongchun, Si Dajun, Chen Xueyun et al. in Power System Technology (2004 (07), P49-52+57) provides a transmission line fault location system based on multiple algorithms. In order to improve the accuracy of the results, multiple fault location methods are used to calculate the fault location for each fault data, and finally one or several reference fault points are given. The reference points are referenced but there is no cross calculation. In practical applications, multiple reference fault points need to be checked one by one.

[0007] In summary, although a variety of distance measurement methods and transition resistances are mentioned in the prior art, the various distance measurement methods in the prior art cannot be adaptively selected according to specific circumstances, and either all distance measurement methods are selected or some distance measurement methods are fixedly selected; and although the transition resistance can be eliminated through the data method in the derivation process of calculating the fault distance, its existence in practice will directly affect the fault electrical quantity measured at the single end, thereby affecting the calculation result. On the other hand, after the various existing distance measurement algorithms obtain the distance measurement results, they must be manually checked one by one in actual applications, and it is impossible to automatically eliminate abnormal results or select better results for priority processing, which increases the time and difficulty of fault handling. Summary of the invention

[0008] A brief summary of embodiments of the present invention is provided below to provide a basic understanding of certain aspects of the present invention. It should be understood that the following summary is not an exhaustive summary of the present invention. It is not intended to identify key or important parts of the present invention, nor is it intended to limit the scope of the present invention. Its purpose is merely to provide certain concepts in a simplified form as a prelude to a more detailed description discussed later.

[0009] The purpose of the present invention is to address the defects and shortcomings of the prior art by adopting the following ideas: First, in the data preprocessing stage, appropriate steady-state data are selected before and after the fault, and the tripping information is introduced to further extract the steady-state data. On this basis, the data is represented by phasor to make the distance measurement calculation reliable and convenient. Secondly, in the process of distance measurement using multiple algorithms, each algorithm judges and considers whether there is a transition resistor. Starting from the algorithm itself, according to whether there is a transition resistor, the corresponding branch structure is adaptively selected for distance measurement calculation, thereby improving the accuracy of the algorithm distance measurement; Finally, a single-ended fault ranging algorithm with multi-algorithm fusion analysis is provided. According to the cross-validation of the calculation results of multiple algorithms, the algorithm results that are not suitable for the current data are gradually and adaptively eliminated. Then, in view of the uncertainty of the existing single ranging algorithm results, the remaining algorithm results are used to construct a fusion function, and the results of multiple ranging algorithms are weighted and fused after removing the abnormalities to obtain the final result.

[0010] Specifically, according to one aspect of the present application, a single-end ranging method based on multi-algorithm fusion analysis is provided, including: Step 1: For the collected voltage and current, obtain the steady-state data of voltage and current before and after the fault point, and convert them to obtain the voltage and current input for distance measurement calculation; Step 2: Divide the distance measurement algorithm into two branch structures, a branch structure without transition resistance and a branch structure with transition resistance, and adaptively select the required branch structure to perform multi-algorithm distance measurement calculation according to the judgment result of whether the transition resistance exists; Both the branch structure without transition resistance and the branch structure with transition resistance contain all ranging algorithms, and all ranging algorithms include impedance method, complex equation solution method, differential equation solution method and voltage method; In the branch structure without transition resistance, the algorithm itself is used to directly perform distance calculation; In the transition resistance branch structure, the influence of the transition resistance is considered, and the influence of the transition resistance is eliminated before direct distance measurement; Both branch structures obtain ranging results corresponding to the ranging algorithm; Step 3: Calculate the mean of the distance measurement results of each algorithm of the branch structure without transition resistance and the branch structure with transition resistance in step 2, compare each algorithm distance measurement result with the mean, record the result whose comparison result exceeds the threshold range as an abnormal result, and eliminate the abnormal result to obtain the remaining algorithm distance measurement results; Construct the fusion weighting function P(len i ), recalculate the mean square error of the remaining algorithm ranging results, construct the ranging algorithm weighted value according to the mean square error, combine the algorithm weighted value with the remaining algorithm ranging results, and calculate the final unique ranging value.

[0011] As an implementation scheme, the step 1 specifically includes: For the collected voltage and current, the steady-state data of voltage and current before and after the fault point are obtained to increase the ranging stability; If the fault recorder collects the trip point, it is determined whether the end of the voltage and current steady-state data after the fault is within the trip point. If it is within the trip point, the next step of calculation is directly performed. If it is outside the trip point, the voltage and current steady-state data after the fault adopts a section of data between the starting point of the steady-state data and the trip point. The acquired voltage and current steady-state data are subjected to Fourier transformation, the sinusoidal wave phasor corresponding to the fundamental wave is calculated, and a primary value conversion is performed (represented by complex numbers, and the electrical quantity group after representation is multiplied by the transformation ratio to be converted into a primary value) to obtain the ranging voltage and current as the input for subsequent ranging.

[0012] As an implementation scheme, the method for determining whether a transition resistance exists in step 2 specifically includes: calculating the actual impedance of the line based on the ranging voltage and current obtained in step 1, and calculating its phase angle using the real and imaginary parts of the impedance; and simultaneously obtaining the theoretical impedance of the line and its phase angle based on known line parameters, comparing the two, and determining whether a transition resistance exists.

[0013] According to another aspect of the present application, a single-ended distance measurement device based on multi-algorithm fusion analysis is provided, comprising: The ranging data acquisition module is used to obtain the voltage and current steady-state data before and after the fault point for the collected voltage and current, and obtain the ranging voltage and current after conversion; The impedance calculation and adaptive selection branch structure module is used to divide the distance measurement algorithm into two branch structures, a branch structure without transition resistance and a branch structure with transition resistance, and adaptively select the required branch structure for multi-algorithm distance measurement calculation according to the judgment result of whether the transition resistance exists; A multi-algorithm distance measurement module is used for distance measurement calculation of a branch structure without transition resistance and a branch structure with transition resistance. Both the branch structure without transition resistance and the branch structure with transition resistance contain all distance measurement algorithms, and all distance measurement algorithms include impedance method, complex equation solution method, differential equation solution method and voltage method. In the branch structure without transition resistance, the algorithm itself is used to directly perform distance measurement calculation. In the branch structure with transition resistance, the influence of transition resistance is considered, and distance measurement is performed after the transition resistance is eliminated. Both branch structures obtain distance measurement results corresponding to the distance measurement algorithm. The multi-algorithm ranging result fusion module is used to calculate the mean of the ranging results of each algorithm of the transition resistance branch structure and the transition resistance branch structure, compare each algorithm ranging result with the mean, record the result exceeding the threshold range as an abnormal result, and eliminate the abnormal result to obtain the remaining algorithm ranging results; construct a fusion weighted function P(len i), recalculate the mean square error of the remaining algorithm ranging results, construct the ranging algorithm weighted value according to the mean square error, combine the algorithm weighted value with the remaining algorithm ranging results, and calculate the final unique ranging value.

[0014] Through the above scheme, the present application can not only directly and adaptively select the branch structure of the algorithm when the grounding fault occurs with or without transition resistance, thereby improving the flexibility of ranging; at the same time, multiple algorithms are introduced for different branch structures to avoid the instability of the results caused by one algorithm, and the ranging results under multiple algorithms are intuitively obtained. In addition, the abnormal ranging results are eliminated, the results of multiple algorithms are cross-validated, the algorithm results that are not suitable for the current data are adaptively eliminated, and the remaining other ranging result constructors are integrated to improve the reliability and accuracy of the ranging results, greatly shorten the fault line repair time, and reduce the risks and losses caused by line failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention may be better understood by referring to the following description given in conjunction with the accompanying drawings, wherein the same or similar reference numerals are used throughout the drawings to represent the same or similar components. The accompanying drawings, together with the following detailed description, are included in and form a part of this specification and are used to further illustrate the preferred embodiments of the present invention and to explain the principles and advantages of the present invention. In the drawings: Figure 1 It is a schematic diagram of a single-ended distance measurement device based on multi-algorithm fusion analysis; Figure 2 It is a flow chart of a single-end ranging method based on multi-algorithm fusion analysis; Figure 3 This is a schematic diagram of multiple algorithm ranging modules in a single-ended ranging method based on multi-algorithm fusion analysis. DETAILED DESCRIPTION

[0016] Embodiments of the present invention will be described below with reference to the accompanying drawings. Elements and features described in one drawing or one embodiment of the present invention may be combined with elements and features shown in one or more other drawings or embodiments. It should be noted that for the purpose of clarity, the representation and description of components and processes that are not related to the present invention and are known to those of ordinary skill in the art are omitted in the drawings and descriptions.

[0017] See also Figure 1 The embodiment of the present invention provides a single-ended ranging device based on multi-algorithm fusion analysis, which includes four modules: 1. ranging data acquisition module, 2. impedance calculation and adaptive selection branch structure module, 3. multiple algorithm ranging module, 4. multi-algorithm ranging result fusion module.

[0018] Among them, the distance measurement data acquisition module: for collecting voltage and current, take the steady-state data before and after the fault point to increase the stability of the distance measurement. At the same time, if the fault recorder collects the trip point, it is determined whether the end of the steady-state data after the fault is within the trip point. If it is within the trip point, it will directly proceed to the next step of calculation. If it is outside the trip point, the steady-state data after the fault is a section of data between the starting point of the steady-state data and the trip point. Perform Fourier transform on the acquired voltage and current, calculate the sinusoidal wave phasor corresponding to the fundamental wave, and express it with a complex number. The electrical quantity group after the expression is multiplied by the transformation ratio to convert it into a primary value as the input for subsequent distance measurement.

[0019] Impedance calculation and adaptive selection of branch structure module: Calculate the actual line impedance based on the input voltage and current, and use the real and imaginary parts of the impedance to calculate its phase angle; at the same time, obtain the theoretical impedance phase angle of the line based on the known line parameters, and compare the two to determine whether there is a transition resistance. Divide the multi-algorithm ranging into two branch structures, a branch structure without transition resistance and a branch structure with transition resistance. According to the transition resistance judgment result, the required branch structure is adaptively selected for multi-algorithm ranging calculation.

[0020] Multiple algorithm ranging module: Both branch structures contain all ranging algorithms, including impedance method, complex equation solution method, differential equation solution method and voltage method. In the branch structure without transition resistance, the algorithm itself is used to directly perform ranging calculations. In the branch structure with transition resistance, when the transition resistance affects the ranging algorithm result, the ranging algorithm considers the influence of the transition resistance; when the ranging algorithm itself can eliminate the influence of the transition resistance, the transition resistance is eliminated to directly measure the distance. Multiple ranging algorithms are optimized, and both branch structures obtain ranging results corresponding to the ranging algorithms.

[0021] Multi-algorithm ranging result fusion module: Calculate the mean of multi-algorithm ranging results, compare each ranging result with the mean, and remove abnormal results. Construct fusion weighted function P(len i ), the mean square error of the remaining ranging results is recalculated, and the ranging algorithm weighted value is constructed according to the mean square error. The algorithm weighted value is combined with the algorithm ranging result to jointly calculate the final unique ranging value.

[0022] See also Figure 2 and Figure 3 The embodiment of the present invention further provides a single-end ranging method based on multi-algorithm fusion analysis, which includes: Step 1: Get the ranging voltage and current: Step 11, according to the known fault point flt_point measured by the fault recorder, take one cycle cyc before and after the fault point as the starting point of the steady-state data nmlpos_start=flt_point–cyc, fltpos_start=flt_point+cyc; starting from the starting point, take one cycle forward and backward respectively as the steady-state data of voltage and current, and the end point is expressed as nmlpos=nmlpos_start–cyc, fltpos=fltpos_start+cyc; Step 12, measure the trip point trp_point according to the fault recorder, if fltpos>trp_point, then fltpos=trp_point; otherwise, fltpos remains unchanged; Step 13, the input voltage before the fault is expressed as NmlUα_raw= nmlposUα-nmlpos_startUα, and the input voltage after the fault is expressed as FltUα_raw= fltposUα-fltpos_startUα. Similarly, the input current before the fault is expressed as NmlIα_raw and FltIα_raw (α represents any one of the three phases A, B, and C); Among them, nmlpos_startUα: the starting point of the steady-state data of the voltage signal before the fault point; nmlposUα: the end point of the voltage steady-state data of one cycle before the fault point, starting from the starting point; fltpos_startUα: starting point of steady-state data of voltage signal after fault point; fltposUα: the end point of the next cycle of voltage steady-state data starting from the starting point after the fault point; Step 14: The input voltage and current data before and after the fault are expressed in phasor form and converted into primary values ​​NmlUα, FltUα, NmlIα, and FltIα.

[0023] Step 2: Impedance calculation and adaptive selection of branch structure construction: Step 21, calculate the actual line impedance according to the input voltage and current, that is, Z=FltUβ / FltIβ (β represents the fault phase among the three phases A, B, and C); Step 22: Calculate the phase angle corresponding to the actual line impedance ; Step 23, according to the known line parameters resistance R and reactance X, calculate the theoretical line impedance Zline=R+jX; similarly calculate the corresponding phase angle φZline; Step 24: Compare the actual line impedance phase angle with the theoretical phase angle. If φZ<φZline*0.9, it means there is a transition resistance. R f; Otherwise, there is no transition resistance; Step 25, after determining whether there is a transition resistance or not, adaptively select the corresponding branch structure for distance measurement. Each distance measurement branch structure includes four distance measurement algorithms: impedance method, complex equation solution method, differential equation solution method and voltage method.

[0024] Step 3: Distance measurement calculation using multiple algorithms: Step 31: When there is no transition resistance R f The following algorithms are used for calculation: (1) Impedance method The actual measurement impedance is calculated based on the ranging voltage and current as Z=FltUβ / FltIβ (β represents the fault phase among the three phases A, B, and C); At the same time, the theoretical impedance is calculated based on the known line parameters as Zline=R+jX (R is the line unit resistance, X is the line unit reactance); Let Z = Zline * len 1 , calculate len 1 =Z / Zline; (2) Method for solving complex equations According to the electrical equation for distance measurement , multiply both ends by I g The complex conjugate of : ; in, is the current distribution coefficient at the measuring end; Take the imaginary part of both ends of the above formula and sort it out to get: ; (3) Differential equation solution method According to the line, the differential equation can be written in the time domain: ; Wherein, Yline is the theoretical line admittance, Yline = G+jB, where G is the line conductance parameter G, and B is the line susceptance parameter B; Solving the above differential equation, we can get the distance len from the measurement point to the fault point: 3 ; (4) Voltage method The initial voltage component and initial current component can be calculated by using the voltage and current before and after the fault: ; ; According to the transmission line equation, the initial voltage at each point on the line and the measurement point is calculated to obtain the initial voltage phase sequence after the fault. The voltage phase sequence before the fault is calculated separately. n and the initial voltage phase sequence after the fault φ m , let Δφ be the voltage phase difference coefficient, when Δφ is the minimum value, the corresponding distance is recorded as the distance measurement result len 4 : ; ; cosh represents the hyperbolic cosine function, and the specific function is: ; sinh represents the hyperbolic sine function, the specific function is: ; Z c Represents the line characteristic impedance, which is calculated as follows: , z and y represent the line impedance and admittance per unit length in the line parameters respectively; represents the line propagation coefficient, which is calculated as follows: ; t Indicates the voltage phase sequence before and after the fault , The number of mid-phases; j Indicates the voltage phase sequence from the first to the second before and after the fault. t Any sequence number between j The value range is 1~ t ; is the jth phase in the voltage phase sequence before the fault, is the jth phase in the initial voltage phase sequence after the fault; Step 32: When there is transition resistance R f The following method is used for calculation: (1) Impedance method When transition resistance exists, the actual measured impedance can be expressed as: ; in, I f The fault component current is the fault point current I g Assuming that the current distribution coefficient has an argument of zero, and setting the real and imaginary parts on both sides of the above equation equal, we can derive: ; Where, tanφZline=X / R is the line impedance angle, Re[Z] and Im[Z] represent the real and imaginary parts of the measured impedance respectively, and a=Re[I g / FltIβ],b=Im[I g / FltIβ].

[0025] (2) Method for solving complex equations As with the complex equation method in the branch structure without transition resistance, the transition resistance term is eliminated in the actual distance measurement calculation process of the complex equation method, so the same algorithm is used in the branch structure with transition resistance.

[0026] (3) Differential equation solution method According to the circuit, the differential equation can be written in the time domain ; In order to eliminate the influence of transition resistance, when FltIβ=0, we can get ; Among them, FltUβ, and Indicates the voltage value and current derivative value measured at the moment when FltIβ crosses zero.

[0027] (4) Method for solving quadratic equations It is known that when there is a transition resistance, the voltage and current equations are: ; ; ; k is the zero-sequence current compensation coefficient; FltIβ0 is the zero-sequence current; is the zero-sequence component of the short-circuit current at the fault point; Zline 0 Indicates the line parameter zero-sequence impedance; Indicates the line length; Z M0 It represents the system impedance of the zero sequence at the measuring end M; Z N0 represents the zero-sequence system impedance at the other end, which is represented by infinity here; Substituting the last two equations into the voltage equation, we get the quadratic complex equation: ; in, ; ; ; k represents the zero-sequence current compensation coefficient; Z N0 represents the zero-sequence system impedance at the other end, which is represented by infinity here; Zline 0 Indicates the line parameter zero-sequence impedance; l represents the line length; g 1m , g 1n , g 2m , g 2n , g 3m , g 3n Represents g 1 , g 2 , g 3 Data representation of the real and imaginary parts of formulas; The quadratic complex equation contains the unknown number len 4 , R f The complex expression of R f Get information about len 4 The quadratic equation of one variable can be solved to get the distance measurement result len 4 : .

[0028] Step 4: Fusion calculation of multi-algorithm ranging results: Step 41, calculate the average value of the four distance measurement results obtained in the multiple algorithm distance measurement modules len_avg = (len 1 +len 2 +len 3 +len 4 ) / 4; Step 42: Compare the distance measurement results of each algorithm with the average value. If |len i –len_avg|<0.25(i=1,2,3,4), the distance measurement result of the corresponding algorithm is retained; otherwise, the distance measurement result of the corresponding algorithm is removed from all distance measurement results; Step 43: The remaining algorithm distance measurement results recalculate the mean len_μ and standard deviation len_S to represent the average of the sum of squares of the deviations of the remaining distance measurement results from their mean. Assume that the impedance method distance measurement result len 1 is eliminated, then: ; ; Step 44: When len_S<ξ (ξ is a small constant), use the distance measurement result and the mean to construct the probability function P(len i), represents the probability of the distance measurement result of the ith algorithm. The farther it deviates from the mean, the smaller the function probability: ; At this time, the weighted fusion result of multiple algorithm ranging is calculated as follows: ; When len_S>ξ, remove the remaining distance measurement results |len i –len_μ|, and then continue to repeat the above steps 43 and 44 until the remaining two algorithm distance measurement results are obtained. Then, the fused distance measurement result len ​​is directly calculated based on the constructed probability function and weighted fusion method.

[0029] In the prior art, some algorithms can directly eliminate the influence of transition resistance, and the distance measurement is not affected by transition resistance; while some algorithms cannot directly eliminate transition resistance and can only remove the influence of transition resistance through calculation between transition resistance and transition resistance. R f It represents the transition resistance. It can be seen from the calculation formula that some of the distance measurement results are calculated without transition resistance, while others are calculated by substituting transition resistance.

[0030] In this application, in order to overcome the defects of the prior art, the applicant specially designed the formulas in the first module, the ranging data acquisition module, and the fourth module, the multi-algorithm ranging result fusion module.

[0031] After each algorithm in this application calculates the result, the final distance measurement result is not directly obtained based on the result. It compares the distance measurement results of multiple algorithms with each other and gradually and adaptively removes the algorithm results with abnormal results in several algorithms. The abnormal results removed are the algorithm results that are not suitable for the current distance measurement data, and the retained algorithm results are the algorithms that are suitable for the current data, and then the weighted fusion is performed to calculate the final result.

[0032] It should be emphasized that the term “include / comprises” when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0033] In addition, the method of the present invention is not limited to being executed in the time sequence described in the specification, and may also be executed in other time sequences, in parallel or independently. Therefore, the execution order of the method described in this specification does not limit the technical scope of the present invention.

[0034] Although the present invention has been disclosed above by describing specific embodiments of the present invention, it should be understood that all the above embodiments and examples are exemplary rather than restrictive. Those skilled in the art may design various modifications, improvements or equivalents of the present invention within the spirit and scope of the appended claims. These modifications, improvements or equivalents should also be considered to be included in the protection scope of the present invention.

Claims

1. A single-terminal ranging method based on multi-algorithm fusion analysis, characterized in that: include: Step 1: For the collected voltage and current, obtain the steady-state data of voltage and current before and after the fault point, and convert them to obtain the voltage and current input for distance measurement calculation; Step 2: Divide the distance measurement algorithm into two branch structures, a branch structure without transition resistance and a branch structure with transition resistance, and adaptively select the required branch structure to perform multi-algorithm distance measurement calculation according to the judgment result of whether the transition resistance exists; Both the branch structure without transition resistance and the branch structure with transition resistance contain all ranging algorithms, and all ranging algorithms include impedance method, complex equation solution method, differential equation solution method and voltage method; In the branch structure without transition resistance, the algorithm itself is used to directly perform distance calculation; In the transition resistance branch structure, the algorithm considers the influence of transition resistance, eliminates the influence of transition resistance and then directly measures the distance; Both branch structures obtain ranging results corresponding to the ranging algorithm; Step 3: Calculate the mean of the distance measurement results of each algorithm of the branch structure without transition resistance or the branch structure with transition resistance in step 2, compare each distance measurement result of the algorithm with the mean, record the result whose comparison result exceeds the threshold range as an abnormal result, and eliminate the abnormal result to obtain a valid distance measurement result value of the algorithm; Construct a fusion weighted function, recalculate the mean square error of the valid algorithm ranging result values, construct the ranging algorithm weighted value based on the mean square error, combine the algorithm weighted value with the remaining algorithm ranging results, and calculate the final unique ranging value.

2. The single-ended ranging method according to claim 1, characterized in that: The step 1 specifically includes: For the collected voltage and current, the steady-state data of voltage and current before and after the fault point are obtained to increase the ranging stability; If the fault recorder collects the trip point, it is determined whether the end of the voltage and current steady-state data after the fault is within the trip point. If it is within the trip point, the next step of calculation is directly performed. If it is outside the trip point, the voltage and current steady-state data after the fault adopts a section of data between the starting point of the steady-state data and the trip point. The acquired voltage and current steady-state data are Fourier transformed, the sinusoidal wave phasor corresponding to the fundamental wave is calculated, and a value conversion is performed to obtain the ranging voltage and current as the input for subsequent ranging.

3. The single-ended ranging method according to claim 1, characterized in that: The method for determining whether a transition resistance exists in step 2 specifically includes: calculating the actual impedance of the line according to the ranging voltage and current obtained in step 1, and calculating its phase angle using the real and imaginary parts of the impedance; and obtaining the theoretical impedance of the line and its phase angle according to known line parameters, comparing the two, and determining whether a transition resistance exists.

4. A single-ended distance measurement device based on multi-algorithm fusion analysis, characterized in that: include: The ranging data acquisition module is used to obtain the voltage and current steady-state data before and after the fault point for the collected voltage and current, and obtain the ranging voltage and current after conversion; The impedance calculation and adaptive selection branch structure module is used to divide the distance measurement algorithm into two branch structures, a branch structure without transition resistance and a branch structure with transition resistance, and adaptively select the required branch structure for multi-algorithm distance measurement calculation according to the judgment result of whether the transition resistance exists; A multi-algorithm distance measurement module is used for distance measurement calculation of a branch structure without transition resistance and a branch structure with transition resistance. Both the branch structure without transition resistance and the branch structure with transition resistance contain all distance measurement algorithms, and all distance measurement algorithms include impedance method, complex equation solution method, differential equation solution method and voltage method. In the branch structure without transition resistance, the algorithm itself is used to directly perform distance measurement calculation; in the branch structure with transition resistance, the algorithm considers the influence of transition resistance and eliminates the influence of transition resistance before distance measurement. Optimize multiple distance measurement algorithms, and both branch structures obtain distance measurement results corresponding to the distance measurement algorithms; The multi-algorithm ranging result fusion module is used to calculate the mean of the ranging results of each algorithm of the transition resistance branch structure and the transition resistance branch structure, compare each algorithm ranging result with the mean, record the result exceeding the threshold range as an abnormal result, and eliminate the abnormal result to obtain the remaining algorithm ranging results; construct a fusion weighted function, recalculate the mean square error of the remaining algorithm ranging results, construct the ranging algorithm weighted value according to the mean square error, combine the algorithm weighted value with the remaining algorithm ranging results after eliminating the abnormality, and calculate the final unique ranging value.

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