A method and system for fault location of medium voltage distribution network based on traveling wave waveform restoration

Abstract

The application discloses a kind of medium voltage distribution network fault ranging method and system based on travelling wave waveform reduction, it is related to distribution network ranging technical field, the method includes according to the entry capacitor of the collected to be detected distribution network line, line impedance and travelling wave transmission delay, total transmission function reflecting the multi-stage distribution of travelling wave signal is established;In total transmission function, introduce the frequency domain compensation mechanism of being set, obtain target inverse filter compensation function;The target inverse filter compensation function is converted into discrete problem, and regularization correction and parameter optimization are carried out in turn;Solve the regularization equation obtained after optimization, according to the original travelling wave signal waveform that result is reduced out;According to original travelling wave signal waveform, high-precision fault ranging to the line of to-be-tested distribution network is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution network ranging, in particular to a medium-voltage distribution network fault ranging method and system based on traveling wave waveform restoration. BACKGROUND

[0002] With the development of society, as the key link of the end of the power grid, the safe and stable operation ability of 10kV medium-voltage distribution network is facing new challenges. The traditional distribution network operation and maintenance mode has been difficult to meet the modern power supply reliability demand. Under this background, the fault ranging technology based on double-end traveling wave positioning principle is gradually becoming the core technical support for the intelligentization and stability upgrading of 10kV distribution network.

[0003] Due to the complex network structure of 10kV medium-voltage distribution system, multi-T connection, mixed frame and radial network, the traveling wave refraction and reflection path is complex and the interference is serious. For the network structure of multi-T connection and mixed frame, the fault traveling wave signal often appears the case of slowing down of the rising speed of the traveling wave signal after multiple distribution transformers. And due to the structural limitation of the traditional ranging algorithm, it is difficult to cope with the complex network structure and complex path, thereby causing the delay deviation in the fault detection of the traveling wave signal head position, so that the accuracy of the detection result is poor, and the stable operation of the distribution network is affected.

[0004] Therefore, how to effectively range the traveling wave of the medium-voltage distribution network and reduce the fault positioning error has become a technical problem to be solved by those skilled in the art. SUMMARY

[0005] The present application provides a medium-voltage distribution network fault ranging method and system based on traveling wave waveform restoration, which solves how to compensate the frequency domain of the traveling wave transmission process through the inverse filter compensation mechanism and improves the accuracy of fault ranging.

[0006] In order to solve the above technical problems, the present application embodiment provides a medium-voltage distribution network fault ranging method based on traveling wave waveform restoration, comprising:

[0007] According to the collected inlet capacitance, line impedance and traveling wave transmission time delay of the to-be-detected distribution network line, a total transmission function reflecting the multi-stage distribution transformer of the traveling wave signal is established;

[0008] A set frequency domain compensation mechanism is introduced into the total transmission function to obtain a target inverse filter compensation function;

[0009] The target inverse filter compensation function is converted into a discrete problem, and regularization correction and parameter optimization are sequentially performed;

[0010] The regularization equation obtained after optimization is solved, and the original traveling wave signal waveform is restored according to the solving result;

[0011] According to the original traveling wave signal waveform, fault distance measurement is performed on the power distribution network line to be detected.

[0012] Further, the process of establishing the transfer function comprises:

[0013] According to the entry capacitance, the line impedance and the traveling wave transmission time delay, a single-stage transformer transfer function is established, and according to the single-stage transformer transfer function, the total transfer function of multi-stage connection is determined.

[0014] Further, the introduction of the set frequency domain compensation mechanism in the total transfer function to obtain a target inverse filter compensation function comprises:

[0015] The total transfer function is subjected to amplitude compensation and phase delay correction to obtain the target inverse filter compensation function.

[0016] Further, the target inverse filter compensation function is converted into a discrete problem, and regularization correction and parameter optimization are sequentially performed, comprising:

[0017] Real-time observation signals corresponding to the traveling wave signals are obtained, and according to the observation signals and the target inverse filter compensation function, a discretization matrix equation is established;

[0018] The discretization matrix equation is subjected to regularization correction to obtain a corresponding regularization target function;

[0019] The regularization parameter in the regularization target function is dynamically optimized to determine the optimal parameter.

[0020] Further, the regularization parameter in the regularization target function is dynamically optimized to determine the optimal parameter, comprising:

[0021] The L-curve criterion is used to calculate the norm of the regularization target function corresponding to different regularization parameters;

[0022] According to the norm, a corresponding L-curve is generated, and the optimal parameter corresponding to the inflection point of the L-curve is determined.

[0023] Further, the regularization equation obtained after optimization is solved, and the original traveling wave signal waveform is restored according to the solution result, comprising:

[0024] The optimal parameter is input into the regularization target function to obtain the regularization equation;

[0025] The preconditioned conjugate gradient method is used to solve the regularization equation, and the optimal vector estimation of the original traveling wave signal is output;

[0026] According to the optimal vector estimation, the original traveling wave signal waveform is restored.

[0027] Further, the fault distance measurement on the to-be-detected power distribution network line according to the original traveling wave signal waveform comprises:

[0028] Under the original traveling wave signal waveform, wave head detection is performed by using a preset fault distance measurement algorithm to determine a fault positioning result of the to-be-detected power distribution network line.

[0029] Another embodiment of the present application provides a medium-voltage distribution network fault distance measurement system based on traveling wave waveform restoration, comprising:

[0030] A transfer function design module is configured to establish a total transfer function reflecting multi-stage distribution transformers of a traveling wave signal according to an entry capacitance, a line impedance and a traveling wave transmission time delay of the to-be-detected power distribution network line.

[0031] An ideal frequency domain compensation module is configured to introduce a set frequency domain compensation mechanism into the total transfer function to obtain a target inverse filter compensation function.

[0032] A discrete and correction module is configured to convert the target inverse filter compensation function into a discrete problem and sequentially perform regularization correction and parameter optimization.

[0033] A waveform restoration module is configured to solve the regularized equation obtained after optimization and restore the original traveling wave signal waveform according to a solution result.

[0034] A fault distance measurement module is configured to perform fault distance measurement on the to-be-detected power distribution network line according to the original traveling wave signal waveform.

[0035] Still another embodiment of the present application provides a computer device comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the medium-voltage distribution network fault distance measurement method based on traveling wave waveform restoration as described above when executing the computer program.

[0036] Still another embodiment of the present application provides a computer readable storage medium storing a computer program, wherein a device where the computer readable storage medium is located implements the medium-voltage distribution network fault distance measurement method based on traveling wave waveform restoration as described above when executing the computer program.

[0037] Compared with the prior art, the embodiment of the present application has at least one of the following advantages:

[0038] The application accurately reveals the traveling wave propagation law and distortion mechanism by establishing the s-domain transfer function of the multi-stage distribution transformer; the ideal inverse filter compensation mechanism is adopted to compensate the transfer function in the frequency domain, which can eliminate the linear distortion of the traveling wave signal after passing through N-stage distribution transformers, improve the response speed of the traveling wave signal, further convert the compensated function into a discrete deconvolution form and introduce a regularization mechanism to solve the ill-conditioned problem of inverse filtering; finally, the target solution is output to realize the waveform detail reconstruction, so as to accurately find the wave head position, solve the problem that the fault traveling wave signal in the 10kV distribution network often slows down after passing through multiple distribution transformers, and improve the fault distance measurement accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 is a medium voltage distribution network fault distance measurement method flowchart based on traveling wave waveform restoration in one of the embodiments of the application;

[0040] Figure 2 is a medium voltage distribution network fault distance measurement structure diagram based on traveling wave waveform restoration in one of the embodiments of the application;

[0041] Figure 3 is a structure block diagram of a preferred embodiment of a computer device provided by the application. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. The purpose of providing these embodiments is to make the disclosure of the application more thorough and comprehensive. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0043] In the description of the present application, the terms "first", "second", "third" and the like are only used for description purpose, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second", "third" and the like can explicitly or implicitly include one or more features. In the description of the present application, unless otherwise specified, the meaning of "multiple" is two or more.

[0044] In the description of the present application, it should be noted that, unless otherwise defined, all technical and scientific terms used in the application have the same meaning as understood by those skilled in the art. The terms used in the specification of the application are only for the purpose of describing the specific embodiments, and are not intended to limit the application. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0045] An embodiment of the present application provides a medium-voltage distribution network fault location method based on traveling wave waveform restoration. Specifically, please refer to Figure 1 , Figure 1 A medium-voltage distribution network fault location method based on traveling wave waveform restoration in an embodiment of the present application is shown in the flowchart, including the following steps:

[0046] S1, according to the collected entry capacitance of the to-be-detected distribution network line, line impedance and traveling wave transmission time delay, a total transmission function reflecting the multi-stage distribution transformer of the traveling wave signal is established.

[0047] The transmission function designed in this embodiment can quantify the distortion mechanism of the fault traveling wave signal in the line after transmission through the multi-stage distribution transformer. Specifically, a single-stage distribution transformer transmission function can be established according to parameters such as entry capacitance, line impedance and traveling wave transmission time delay, and the total transmission function of multi-stage connection can be determined according to the single-stage distribution transformer transmission function.

[0048] For example, in a 10kV distribution network line, this embodiment takes the distribution transformer entry capacitance (1000 pF) and line impedance (typical value 50Ω) as an example to construct a single-stage distribution transformer transmission model. The single-stage distribution transformer transmission model can be represented by the following frequency domain transmission function .

[0049]

[0050] The total transmission function after connection is represented as follows: .

[0051]

[0052] In the formula, R represents the equivalent characteristic impedance of the high-voltage side line of the distribution transformer, which is mainly determined by the line resistance and inductance characteristics; C represents the equivalent entry capacitance of the distribution transformer high-voltage side to the ground; s represents a complex frequency variable, and t represents the time delay of the signal through the single-stage distribution transformer transmission; represents the kth stage time delay of the traveling wave propagation (typical value 50 ns / stage); n represents the number of stages of the distribution transformer, n=(1…k…n).

[0053] From the above formula, the attenuation characteristics and time delay generated when the traveling wave passes through the line can be determined. It can be understood that the complex frequency variable s= in this embodiment is a Laplace complex frequency variable. In the formula, σ is the attenuation coefficient, and ω is the angular frequency.

[0054] S2, introduce the set frequency domain compensation mechanism in the total transmission function to obtain the target inverse filter compensation function.

[0055] Because distortion can cause consequences in fault location such as wavefront detection errors, arrival time deviations, and reflected wave identification failures, this embodiment introduces an ideal inverse filter compensator, i.e., a frequency domain compensation mechanism, to eliminate the linear distortion of the high-frequency traveling wave signal after passing through the N-stage transformer. This compensates the amplitude and corrects the phase delay of the total transfer function, resulting in a target inverse filter compensation function that eliminates linear distortion.

[0056] Specifically, the ideal target inverse filter compensation function after the above frequency domain compensation Represented as:

[0057]

[0058] In this embodiment, it can be It is called an ideal inverse filter.

[0059] In the formula, for The phase response; and The total transfer function of a multi-stage distribution transformer system, which includes amplitude attenuation and phase delay, can be expressed in frequency domain as follows:

[0060]

[0061] In the formula, the first term represents the frequency domain response, and the second term represents the phase frequency response.

[0062] In frequency domain compensation, the complete form of the target inverse filter compensation function can be expressed as:

[0063]

[0064] In the formula, the first term is the amplitude plus the nonlinear phase compensation term, and the second term is the linear phase compensation term. It is used to compensate for the phase lag caused by the system time delay τ. For frequency.

[0065] Based on the above formulas, it can be understood that the compensation mechanism in this embodiment is divided into amplitude compensation, nonlinear phase compensation, and linear phase compensation. Amplitude compensation amplifies high-frequency components and restores waveform steepness; nonlinear phase compensation eliminates… The phase curvature caused by the phase compensation corrects the waveform shape; while linear phase compensation can cancel out the time delay and avoid the time-domain ringing effect caused by discontinuous phase compensation, ensuring the accuracy of the arrival time of the traveling wave.

[0066] S3. Transform the target inverse filter compensation function into a discrete problem, and perform regularization correction and parameter optimization in sequence.

[0067] Although the ideal inverse filter designed in step S2 Theoretically perfect, but engineering implementation faces multiple obstacles such as noise amplification, i.e. in this embodiment, the ideal inverse filter is not feasible in a discrete system due to noise and matrix ill-conditioning, therefore, this embodiment discretizes the target inverse filter compensation function, thereby exposing the ill-conditioning problem of the computable ideal filter compensation.

[0068] Specifically, this embodiment acquires an observation signal corresponding to the traveling wave signal in real time, and establishes a discretized matrix equation according to the observation signal and the target inverse filter compensation function.

[0069] For example, if the original traveling wave signal is The observation signal after multi-stage transformer transmission is represented as:

[0070]

[0071] wherein, is the multi-stage transformer equivalent impulse response (including the effect of capacitive load); is the measurement noise (mainly including high-frequency components); and

[0072] In combination with the above actually acquired observation equation, the ideal inverse filter needs to be matched to the actual sampling system. It can be understood that, since the actually acquired traveling wave signal is discrete sampling data (such as 10 ns interval corresponding to 100 MHz sampling rate), the continuous-time system model, i.e. the ideal inverse filter, must be converted into a discrete form to match the actual measurement data. Then the above observation signal is discretized to obtain a matrix equation represented as:

[0073]

[0074] In the formula, is a Toeplitz structure transmission matrix; Both are discretized signal vectors.

[0075] It should be understood that the above discretization process converts the ideal compensation theory into a computable discrete convolution model.

[0076] Further, since the above discretization exposes an ill-conditioning problem, this embodiment triggers a regularization mechanism to regularize and correct the discretized matrix equation.

[0077] During the correction, a regularization objective function corresponding to the discretized matrix equation is constructed and represented as follows:

[0078]

[0079] In the formula, the first term is a data fidelity term, which ensures the consistency of the restored signal and the observed signal; the second term is a regularization term, which is used to suppress noise amplification; L is a second-order difference matrix, which is used to force signal smoothness; and λ is a regularization parameter, which is used to balance the weights of the two terms.

[0080] The target function can solve the following problems: 1. In a multi-level variable cascade environment, the higher the condition number of the transmission matrix H, the greater the high-frequency noise, and the more severe the oscillation of the solution; 2. After introducing phase compensation, the time-domain solution appears pre-ringing.

[0081] The target function can solve the following problems: 1. In a multi-level variable cascade environment, the higher the condition number of the transmission matrix H, the greater the high-frequency noise, and the more severe the oscillation of the solution; 2. After introducing phase compensation, the time-domain solution appears pre-ringing.

[0082] In practical applications, there is a dilemma between over-smoothing the signal and losing details and amplifying noise caused by an excessively large regularization parameter λ. Based on this, the L-curve criterion is used to dynamically optimize the regularization parameter in the regularization target function to determine the optimal parameter.

[0083] Specifically, first, the L-curve criterion is used to calculate the norm of the regularization target function under different regularization parameters. For example, the residual norm under different λ is calculated as follows: And the solution norm is: In the formula, is the solution vector.

[0084] Next, the L-curve corresponding to the norm is generated, and the value corresponding to the inflection point in the L-curve is determined as the value of the optimal parameter λ.

[0085] S4, solve the regularization equation obtained after optimization, and restore the original traveling wave signal waveform according to the solution result.

[0086] The core task of this step is to efficiently solve the equation obtained after optimization of the regularization parameter, and the output result is the restored original traveling wave signal waveform.

[0087] Specifically, first, the optimal parameter λ is input into the regularization target function to obtain the target regularization equation, which is represented as follows:

[0088]

[0089] The preconditioned conjugate gradient method (PCG) is used to solve the above regularization equation, and the optimal vector estimate of the original traveling wave signal is output. Specifically, the output optimal vector is the discrete estimate value of the original traveling wave signal x(t), i.e. the restored waveform sampling sequence, and the original traveling wave signal waveform is restored.

[0090] S5, according to the original traveling wave signal waveform, the fault location of the power distribution network line to be detected is performed.

[0091] Specifically, the embodiment utilizes a preset fault ranging algorithm to perform wave head detection under the restored original traveling wave signal waveform, so as to determine the fault positioning result of the power distribution network line to be detected.

[0092] Exemplarily, the time when the initial wave head of the fault reaches the substations A and B can be determined by using the double-end traveling wave ranging method, and the fault positioning is realized.

[0093] Finally, taking the 10kV overhead line as an example, the detection results before and after the waveform restoration are further compared and analyzed by using the double-end ranging algorithm, and the table shown below is referred to:

[0094]

[0095] It can be seen that the embodiment realizes a substantial reduction in error and time delay through waveform restoration and high-precision wave head detection.

[0096] In summary, the embodiment of the present application proposes a waveform restoration and fault ranging method for the problem of slow rising edge of the fault traveling wave of the 10kV power distribution network after transmission through multiple distribution transformers: a multi-stage distribution transformer frequency domain transfer function is constructed to quantify the signal transmission distortion mechanism; then an ideal inverse filter decoupled in amplitude and phase is designed, including dynamic amplitude compensation, linear phase correction and nonlinear phase compensation; then a discrete equation is established to expose the ill-condition and trigger the regularization architecture, and the regularization parameter is optimized adaptively in combination with the L-curve criterion, and the restored signal is solved in real time through the PCG algorithm, and finally the wave head time is detected based on the restored waveform, and high-precision fault ranging is realized.

[0097] An embodiment of the present application provides a medium-voltage distribution network fault ranging system based on traveling wave waveform restoration, and specifically, please refer to Figure 2 , Figure 2 The figure shows the structure of the medium-voltage distribution network fault ranging system based on traveling wave waveform restoration in one embodiment of the present application, which comprises:

[0098] The transfer function design module M1 is used to establish a total transfer function reflecting the multi-stage distribution transformer of the traveling wave signal according to the collected entry capacitance, line impedance and traveling wave transmission time delay of the power distribution network line to be detected;

[0099] The ideal frequency domain compensation module M2 is used to introduce a set frequency domain compensation mechanism in the total transfer function to obtain a target inverse filter compensation function;

[0100] The discrete and correction module M3 is used to convert the target inverse filter compensation function into a discrete problem, and sequentially perform regularization correction and parameter optimization;

[0101] a waveform restoration module M4 configured to solve the regularization equation obtained after the optimization, and restore the original traveling wave signal waveform according to a solution of the regularization equation;

[0102] a fault location module M5 configured to perform fault location on the power distribution network line to be detected according to the original traveling wave signal waveform.

[0103] As shown in Figure 3 The present application also provides a computer device, Figure 3 A preferred embodiment of the computer device provided by the present application is shown in a structure block diagram, which comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the method as described above when executing the computer program.

[0104] Preferably, the computer program can be divided into one or more modules / units (such as computer program 1, computer program 2, …), which are stored in the memory and executed by the processor to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the computer device.

[0105] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), ready programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or the processor can also be any conventional processor. The processor is the control center of the terminal device, and connects various parts of the terminal device through various interfaces and lines.

[0106] The memory mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system, application programs required by at least one function, etc., and the data storage area can store relevant data, etc. In addition, the memory can be a high-speed random access memory, and can also be a non-volatile memory such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., or the memory can also be other volatile solid-state storage devices.

[0107] It should be noted that the terminal device described above can include, but is not limited to, a processor and a memory, and those skilled in the art can understand that Figure 3 The structural block diagram is only an example of the terminal device and does not constitute a limitation on the terminal device, and can include more or fewer components than those shown in the figure, or combine certain components, or different components. Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiment methods. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0108] Correspondingly, the embodiment of the present application provides a computer readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer readable storage medium is located is controlled to execute the steps in the above-mentioned embodiment methods, such as Figure 1 The steps S1-S5 described in the embodiment of the present application.

[0109] The technical features and technical effects of the medium-voltage distribution network fault location system based on the traveling wave waveform restoration provided by the embodiment of the present application are the same as those of the medium-voltage distribution network fault location method based on the traveling wave waveform restoration provided by the embodiment of the present application, and will not be repeated here.

[0110] The above-mentioned embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it cannot be understood as a limitation on the scope of the patent of the present application. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of protection of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for fault location in medium-voltage distribution networks based on traveling wave waveform reconstruction, characterized in that, include: A single-stage distribution transformer transmission function is established based on the collected input capacitance, line impedance, and traveling wave propagation delay of the distribution network line to be tested. A total transmission function reflecting the traveling wave signal of the multi-stage distribution transformers in multiple cascades is established based on the single-stage distribution transformer transmission function. A predetermined frequency domain compensation mechanism is introduced into the total transfer function to perform amplitude compensation and phase delay correction on the total transfer function, thereby obtaining the target inverse filter compensation function; The target inverse filtering compensation function is transformed into a discrete problem, and regularization correction and parameter optimization are performed sequentially. Solve the optimized regularized equation and reconstruct the original traveling wave signal waveform based on the solution results; The fault location of the distribution network line to be detected is performed based on the original traveling wave signal waveform.

2. The method for fault location in medium-voltage distribution networks based on traveling wave waveform reconstruction as described in claim 1, characterized in that, The process of transforming the target inverse filtering compensation function into a discrete problem and then performing regularization correction and parameter optimization sequentially includes: The observation signal corresponding to the traveling wave signal is acquired in real time, and a discretized matrix equation is established based on the observation signal and the target inverse filtering compensation function; The discretized matrix equation is regularized to obtain the corresponding regularization objective function; The regularization parameters in the regularization objective function are dynamically optimized to determine the optimal parameters.

3. The method for fault location in medium-voltage distribution networks based on traveling wave waveform reconstruction as described in claim 2, characterized in that, The step of dynamically optimizing the regularization parameters in the regularization objective function to determine the optimal parameters includes: The norm of the regularization objective function under different regularization parameters is calculated using the L-curve criterion. Generate the corresponding L-curve based on the norm, and determine the optimal parameters corresponding to the inflection points in the L-curve.

4. The method for fault location in medium-voltage distribution networks based on traveling wave waveform reconstruction as described in claim 2, characterized in that, The regularized equation obtained after optimization is used to reconstruct the original traveling wave signal waveform based on the solution results, including: The optimal parameters are input into the regularization objective function to obtain the regularization equation; The regularization equation is solved using the preprocessing conjugate gradient method, and the optimal vector estimate of the original traveling wave signal is obtained as the output. The original traveling wave signal waveform is reconstructed based on the optimal vector estimation.

5. The method for fault location in medium-voltage distribution networks based on traveling wave waveform reconstruction as described in claim 1, characterized in that, The step of fault location based on the original traveling wave signal waveform for the distribution network line under test includes: Under the original traveling wave signal waveform, a preset fault location algorithm is used to perform wavefront detection to determine the fault location result of the distribution network line to be detected.

6. A medium-voltage distribution network fault location system based on traveling wave waveform reconstruction, characterized in that, include: The transmission function design module is used to establish a single-stage distribution transformer transmission function based on the collected input capacitance, line impedance, and traveling wave propagation delay of the distribution network line to be tested, and to establish a total transmission function of multi-stage distribution transformers reflecting the traveling wave signal based on the single-stage distribution transformer transmission function. An ideal frequency domain compensation module is used to introduce a set frequency domain compensation mechanism into the total transfer function to perform amplitude compensation and phase delay correction on the total transfer function, thereby obtaining the target inverse filter compensation function. The discrete and corrective module is used to transform the target inverse filter compensation function into a discrete problem, and then perform regularization correction and parameter optimization in sequence. The waveform restoration module is used to solve the optimized regularized equation and restore the original traveling wave signal waveform based on the solution result. The fault location module is used to locate faults in the distribution network line to be tested based on the original traveling wave signal waveform.

7. A computer device, characterized in that, The method includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the medium-voltage distribution network fault location method based on traveling wave waveform reconstruction as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the medium-voltage distribution network fault location method based on traveling wave waveform restoration as described in any one of claims 1 to 5.

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