Fault positioning method and system for low-frequency transmission line of flexible frequency division power transmission system

Abstract

The invention discloses a fault positioning method and system for a low-frequency transmission line of a flexible frequency-division power transmission system, and relates to the field of fault positioning of the flexible frequency-division power transmission system. According to the method, ICEEMDAN after SCSSA parameter optimization is utilized to decompose 1-mode voltage components of voltage traveling wave signals, subjected to phase-mode transformation, on the two sides of a line, and IMF spectrum components are obtained. And selecting the highest-frequency IMF component, enhancing the wave head mutation characteristic by adopting NTEO, realizing accurate calibration of the moment when the traveling wave arrives at the traveling wave head and arrives at the measurement position, and calculating the distance from the fault point to the installation position of the traveling wave positioning device by combining the time when the forward traveling wave and the reverse traveling wave arrive at the measurement device for the first time and the traveling wave speed. The method fills the blank of fault positioning of the low-frequency transmission line of the flexible frequency division power transmission system, is not influenced by fault distance, fault type, system noise and the like, realizes relatively accurate positioning of the fault position of the low-frequency transmission line of the flexible frequency division power transmission system, and has good engineering value.

Description

Technical Field

[0001] This invention relates to the field of fault location technology for flexible frequency division transmission systems, and in particular to a method and system for fault location of low-frequency outgoing lines in flexible frequency division transmission systems. Background Technology

[0002] Modular multilevel matrix converter (M 3 C) The flexible frequency-division transmission system, with its core component, provides a high-performance and relatively economical new technical solution for transmitting electricity from large-scale offshore wind farms. Demonstration projects have already been implemented in Hangzhou and Taizhou, Zhejiang Province. The low-frequency transmission line, as the sole channel for transmitting electricity from offshore wind farms, plays a crucial role in the normal operation of the flexible frequency-division transmission system. However, the working environment of submarine transmission cables is complex and harsh, susceptible to maritime activities, tides, and geological movements, which can easily lead to grounding or phase-to-phase short-circuit accidents. After the relay protection device isolates the fault, fault clearing and repair work requires locating the fault point. However, submarine transmission cables are located on the seabed, making fault location difficult to pinpoint, which significantly impacts maintenance personnel's inspections. Currently, there is no specific fault location method for low-frequency transmission lines in flexible frequency-division transmission systems in the academic and engineering communities. Summary of the Invention

[0003] The purpose of this invention is to overcome the difficulty in locating faults in low-frequency transmission lines of existing flexible frequency division transmission systems. This invention provides a method and system for locating faults in low-frequency transmission lines of flexible frequency division transmission systems. It utilizes an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm, optimized with parameters of the sine-cosine and Cauchy mutation sparrow search algorithm (SCSSA), to decompose the mode-1 voltage components of the voltage traveling wave signals on both sides of the line after phase-mode transformation, obtaining their intrinsic mode functions (IMFs). The highest frequency IMF component is selected, and a novel Teager Energy Operator (NTEO) is used to enhance the wavefront abrupt change characteristics, achieving accurate calibration of the arrival time of the traveling wave wavefront at the measurement point. Finally, the distance from the fault point to the measurement device is calculated by combining the first arrival times of the forward and reverse traveling waves and the traveling wave velocity. This method fills the gap in fault location of low-frequency outgoing lines in flexible frequency division transmission systems. It is unaffected by fault distance, fault type, and system noise, and can achieve relatively accurate location of faults in low-frequency outgoing lines of flexible frequency division transmission systems, thus having good engineering value.

[0004] This invention is achieved through the following technical solution:

[0005] A method for locating faults in low-frequency outgoing lines of a flexible frequency-division transmission system includes the following steps:

[0006] S1, respectively in M 3 The low-frequency isolation star-shaped side and the offshore wind farm step-up star-shaped side of C are equipped with the same type of voltage transformer, current transformer and traveling wave positioning device. Each set of voltage transformer and current transformer independently measures the three-phase voltage on its side.

[0007] S2. After the fault occurs, M 3 The low-frequency side of C and the traveling wave locating device on the offshore wind farm side independently collect the x-phase voltage after the fault on their respective sides and form a voltage sequence. and Where x is one of the three phases, For M 3 The sequence of n voltage sample values ​​after a low-frequency x-phase fault on the C side; This is a sequence of n voltage sampling values ​​after an x-phase fault on the offshore wind farm side; , Sampling frequency, Sampling duration;

[0008] S3, combined with M 3 The low-frequency side of C has the same sampling frequency as before the fault on the offshore wind farm side. With sampling duration The obtained voltage sample value sequence and M 3 C. Fault voltage components on the low-frequency side and offshore wind farm side and ;

[0009] S4. Fault voltage components on the low-frequency side and the offshore wind farm side. and Phase-mode transformation is performed to obtain the first-mode component of the fault voltage. and And use it as the detection object of the traveling wave head;

[0010] S5. Set the relevant parameters for the SCSSA and ICEEMDAN algorithms and initialize the algorithms;

[0011] S6, Convert the fault voltage to a modulo-1 component and The input is fed into the SCSSA-ICEEMDAN algorithm, and after optimization, the optimal values ​​of the added white noise amplitude Nstd and the number of times white noise is added NR are obtained. and Output fault voltage 1-modulus component and IMF spectral components;

[0012] S7. Calculate the first-order component of the fault voltage using the NTEO algorithm. , The Teager energy value of the IMF spectral components enhances the wavefront abrupt change characteristics of both forward and reverse traveling waves;

[0013] S8. Accurately calibrate the arrival times of the traveling wave fronts at the locations of the traveling wave positioning devices on the low-frequency side and the offshore wind farm side to obtain the first arrival times of the forward and reverse traveling waves at M. 3 Time of traveling wave positioning devices on the low-frequency side and offshore wind farm side and And the fault location is calculated.

[0014] M in S1 3The low-frequency side employs a fault current-limiting strategy for fault ride-through, and traveling wave positioning devices installed at both ends of the low-frequency transmission line communicate via a communication channel. The M3C is a power electronic converter, and in the event of a fault, a fault ride-through strategy is needed for current limiting to ensure the safety of the power electronic devices and to prevent the converter from disconnecting from the grid.

[0015] M in S3 3 C. Fault voltage components on the low-frequency side and offshore wind farm side and The calculation methods are shown in equations (1) and (2):

[0016] (1)

[0017] (2)

[0018] Where x can be A, B, or C, representing phase A, phase B, and phase C respectively.

[0019] The S4 fault voltage 1-modulus component and The calculation methods are shown in equations (3) and (4):

[0020] (3)

[0021] (4)

[0022] in, , and M respectively 3 C. Low-frequency side fault voltage 1-mode, 2-mode and 0-mode component sequences; , and These are the 1-mode, 2-mode, and 0-mode component sequences of the fault voltage on the offshore wind farm side.

[0023] S5 includes: setting the population size N of the SCSSA algorithm and the maximum number of iterations. Discoverer ratio Follower ratio Warning threshold The safety threshold ST parameter; sets the value range of two parameters of the ICEEMDAN algorithm, namely Nstd and NR.

[0024] Step S6 includes: using the ICEEMDAN decomposition optimized by SCSSA. and The calculation method is as follows:

[0025] To the original signal sequence Adding k-th order Gaussian white noise yields a new signal sequence. :

[0026] (5)

[0027] in This indicates that an EMD decomposition is performed. This represents the adaptive white noise signal added in the k-th decomposition. This represents the signal-to-noise ratio of the initial added noise;

[0028] The k signals obtained in the previous step EMD decomposition was performed to obtain the first-order modal components. :

[0029] (6)

[0030] in For a first-order residual, , A custom operator is used to calculate the average value.

[0031] use Repeat the first two steps using the initial signal to calculate the nth-order modal components. :

[0032] (7)

[0033] in , The residual is of order n-1;

[0034] Repeat the above steps until all IMF components and residuals are obtained.

[0035] Step S7 includes: taking , The highest frequency component in the IMF spectral components and Then use the NTEO algorithm to calculate and The Teager energy value, where the NTEO algorithm calculates it as follows:

[0036] For a one-dimensional continuous time domain signal The TEO energy operator is defined as follows:

[0037] (8)

[0038] in , They are one-dimensional continuous time domain signals. The first and second derivatives for time t;

[0039] The TEO energy operator is defined as follows when the differential algorithm is used for approximation:

[0040] (9)

[0041] In the formula It is a discrete one-dimensional time-domain signal.

[0042] S8 includes: the moment when the Teager energy calculated by the NTEO algorithm in S7 reaches its maximum value is the moment when the forward and reverse traveling wave fronts arrive at the measurement points on both sides of the low-frequency transmission line in S8; the arrival times of the traveling wave fronts at the measurement points on both sides of the low-frequency transmission line are precisely calibrated to obtain the first arrival times of the forward and reverse traveling waves at M. 3 Time of traveling wave positioning devices on the low-frequency side and wind farm side and The location of the fault is shown in equation (10):

[0043] (10)

[0044] in This refers to the total length of the low-frequency transmission line; , From the fault point to M 3 Distance between the low-frequency side and the offshore wind farm side; This represents the propagation speed of the traveling wave.

[0045] A fault location system for low-frequency transmission lines in a flexible frequency-division transmission system includes:

[0046] Detection module: respectively in M 3 The low-frequency isolation star-shaped side and the offshore wind farm step-up star-shaped side of C are equipped with the same type of voltage transformer, current transformer and traveling wave positioning device. Each set of voltage transformer and current transformer independently measures the three-phase voltage and current on its side.

[0047] Voltage sampling value acquisition module: After a fault occurs, M 3 The low-frequency side of C and the traveling wave locating device on the offshore wind farm side independently collect the x-phase voltage after the fault on their respective sides and form a voltage sequence. and Where x is one of the three phases, For M 3 The sequence of n voltage sample values ​​after a low-frequency x-phase fault on the C side; This is a sequence of n voltage sampling values ​​after an x-phase fault on the offshore wind farm side; , Sampling frequency, Sampling duration; combined with M3 The low-frequency side of C has the same sampling frequency as before the fault on the offshore wind farm side. With sampling duration The obtained voltage sample value sequence and M 3 C. Fault voltage components on the low-frequency side and offshore wind farm side and ;

[0048] Fault voltage modulus component calculation module: calculates fault voltage components on the low-frequency side and the offshore wind farm side. and Phase-mode transformation is performed to obtain the first-mode component of the fault voltage. and And use it as the detection object of the traveling wave head;

[0049] Optimization module: Sets relevant parameters for the SCSSA and ICEEMDAN algorithms, initializes the algorithms, and modulates the fault voltage into one modulus component. and The input is fed into the SCSSA-ICEEMDAN algorithm, which uses SCSSA to optimize two parameters of ICEEMDAN: the amplitude of the added white noise (Nstd) and the number of times white noise is added (NR). The output is the optimal value of Nstd and NR obtained after optimization. and Using SCSSA-optimized ICEEMDAN to decompose M 3 C. Low-frequency side and wind farm side fault voltage 1-mode component and Output the and IMF spectral components;

[0050] Fault location calculation module: Calculates the modulo-1 component of the fault voltage using the NTEO algorithm. , The Teager energy value of the IMF spectral components is used to enhance the abrupt change characteristics of the wavefronts of forward and reverse traveling waves; the arrival times of the traveling wave wavefronts at the locations of the traveling wave positioning devices on the low-frequency side and the offshore wind farm side are precisely calibrated to obtain the first arrival times of the forward and reverse traveling waves at M. 3 Time of traveling wave positioning devices on the low-frequency side and offshore wind farm side and And the fault location is calculated.

[0051] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system.

[0052] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system.

[0053] The advantage of this invention is that after a fault occurs in the low-frequency transmission line, M... 3 The traveling wave locating devices on the low-frequency side and the offshore wind farm side respectively calculate the voltage fault component on their respective sides and perform phase-mode transformation on it. The first-order component is taken as the target for traveling wave front detection. Then, SCSSA is used to optimize two parameters of ICEEMDAN, namely the amplitude (Nstd) and frequency (NR) of the added white noise, to obtain the optimal tuning parameters. Using the ICEEMDAN optimized with the above SCSSA parameters, the first-order voltage component of the phase-mode transformed voltage traveling wave signal on both sides of the line is decomposed to obtain its IMF component. The highest frequency IMF component is selected, and NTEO is used to enhance the wavefront abrupt change characteristic to achieve accurate calibration of the arrival time of the traveling wave at the measurement point. Finally, the distance from the fault point to the installation location of the measurement device is calculated by combining the first arrival time of the forward and reverse traveling waves and the traveling wave velocity. This method is unaffected by fault distance, fault type, and system noise, and can achieve relatively accurate location of faults on low-frequency transmission lines of flexible frequency division transmission systems, demonstrating good engineering value. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of the flexible frequency division transmission system of the present invention;

[0055] Figure 2 This is a flowchart of a method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system.

[0056] Figure 3 Schematic diagram of traveling wave propagation of a fault on the low-frequency side of a flexible frequency-division transmission system. Detailed Implementation

[0057] The present invention will be further described in detail below with reference to the accompanying drawings and specific preferred embodiments.

[0058] In the description of this invention, it should be understood that the terms "left side," "right side," "upper part," "lower part," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. "First," "second," etc., do not indicate the importance of the components, and therefore should not be construed as a limitation of this invention. The specific dimensions used in this embodiment are only for illustrating the technical solution and do not limit the scope of protection of this invention.

[0059] Currently, there is no specific method for locating faults in low-frequency transmission lines of flexible frequency-division transmission systems in the academic and engineering communities. To address this problem, this invention proposes a method for locating faults in low-frequency transmission lines of flexible frequency-division transmission systems. A schematic diagram of a flexible frequency-division transmission system is shown below. Figure 1 As shown. In an offshore wind farm, the voltage is boosted by a low-frequency step-up transformer, then transmitted via a low-frequency transmission line to the low-frequency isolation transformer and M. 3 C connected, via M 3 After C-frequency conversion, it is connected to the mains power grid. Offshore wind farms, after a fault, undergo fault ride-through according to the technical requirements of the national standard GB / T 19963.1—2021 "Technical Specifications for Wind Farm Connection to Power Systems Part 1: Onshore Wind Power". 3 C. The low-frequency side adopts a fault current limiting strategy for fault ride-through. Traveling wave positioning devices are installed at both ends of the low-frequency transmission line and communicate through the communication channel.

[0060] A flowchart of a method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system is shown below. Figure 2 As shown, the specific steps are as follows:

[0061] S1, respectively in M 3 C. The low-frequency side is isolated by the star-shaped transformer, and the offshore wind farm side is equipped with voltage transformers and current transformers of the same type. Each set of voltage transformers and current transformers independently measures the three-phase voltage on its own side.

[0062] S2. After the fault occurs, M 3 The traveling wave locating devices on the low-frequency side and the offshore wind farm side independently collect the x-phase voltage after a fault on their respective sides and form a voltage sequence. and .

[0063] in For M 3 C. A sequence of n voltage sample values ​​after a low-frequency x-phase fault; This is a sequence of n voltage sampling values ​​after an x-phase fault on the offshore wind farm side; , Sampling frequency, The sampling duration is x; x can be A, B, or C.

[0064] S3, combined with M 3 The C-side sampling frequency is the same as the offshore wind farm side before the fault. With sampling duration The obtained voltage sample value sequence and M 3 C. Fault voltage components on the low-frequency side and offshore wind farm side and .

[0065] in

[0066] (1)

[0067] (2)

[0068] Where x can be A, B, or C, representing phase A, phase B, and phase C, respectively.

[0069] S4, to and Phase-mode transformation is performed to obtain the first-mode component of the fault voltage. and And it is used as the detection object of the traveling wave head, as shown in equations (1) and (2):

[0070] (3)

[0071] (4)

[0072] in, , and M respectively 3 C. Low-frequency side fault voltage 1-mode, 2-mode and 0-mode component sequences; , and These are the 1-mode, 2-mode, and 0-mode component sequences of the fault voltage on the offshore wind farm side.

[0073] S5. Set the population size N and the maximum number of iterations for the SCSSA algorithm. Discoverer ratio Follower ratio Warning threshold Set parameters such as the safety threshold ST; set the value range of two parameters of ICEEMDAN, namely Nstd and NR, and initialize the proposed algorithm.

[0074] S6, Convert the fault voltage to a modulo-1 component and The input is fed into the SCSSA-ICEEMDAN algorithm, which uses SCSSA to optimize two parameters of ICEEMDAN: the amplitude of the added white noise (Nstd) and the number of times white noise is added (NR). The output is the optimal value of Nstd and NR obtained after optimization. and Using SCSSA-optimized ICEEMDAN to decompose M 3 C. Low-frequency side and wind farm side fault voltage 1-mode component and Output the and IMF spectral components.

[0075] S7, Take and The highest frequency component of the IMF spectrum and Calculate using the NTEO algorithm and The Teager energy value enhances the abrupt change characteristics of the wavefronts of both forward and reverse traveling waves.

[0076] S8. Accurately calibrate the arrival time of the traveling wave wavefront at the traveling wave positioning devices on both sides of the low-frequency transmission line, and calculate using the NTEO algorithm. and The moment when the Teager energy reaches its maximum value is the moment when the wavefront of the forward and reverse traveling waves first reaches M. 3 Time of traveling wave positioning devices on the low-frequency side and wind farm side and The fault location is obtained as shown in equation (5):

[0077] (5)

[0078] in This refers to the total length of the outgoing transmission line; , From the fault point to M 3 C. Distance between the low-frequency side and the offshore wind farm side; This represents the propagation speed of the traveling wave.

[0079] The working principle of this invention is as follows:

[0080] Data Acquisition: Establishing a foundation for dual-end synchronous measurement via M 3 C. Install the same type of instrument transformer (S1) on the low-frequency side and the wind farm side respectively, and synchronously collect the three-phase voltage (core) and current (auxiliary) before and after the fault to obtain the raw measurement data at both ends, and provide "baseline data (before the fault)" and "fault data (after the fault)" for subsequent analysis.

[0081] Fault component separation: Eliminating steady-state interference. Using the "fault-before-fault voltage" calculation of S3, the voltage component caused only by the fault is separated out, eliminating steady-state signals such as fundamental voltage and background harmonics during normal operation, and highlighting the transient characteristics of the fault (such as traveling wave signal).

[0082] Signal preprocessing: Optimize traveling wave extraction conditions. Through phase mode transformation in S4, the three-phase fault voltage components are converted into 1-mode components to eliminate inter-phase coupling interference. Then, through the SCSSA-ICEEMDAN algorithm in S5-S6, the intelligent optimization (SCSSA) is used to adapt the signal decomposition (ICEEMDAN) parameters to decompose the 1-mode components into IMF spectral components, further refining the high-frequency transient signals related to the traveling wave.

[0083] Wavefront Enhancement and Detection: Accurate time calibration utilizes the NTEO algorithm in S7 to calculate the Teager energy value of the highest frequency IMF component, amplifying the abrupt change characteristics of the traveling wave front (the energy peak corresponds to the wavefront arrival time), solving the problem of wavefront identification under weak signal and noise interference, and finally calibrating the arrival time of the double-ended wavefront in S8.

[0084] Location Calculation: Based on the traveling wave propagation characteristics and according to the traveling wave location formula (Equation 5) of S8, combined with the total line length (L), traveling wave propagation speed (v), and the time difference of arrival of the wavefronts at both ends, the distance from the fault point to M is calculated. 3 The distance from side C or the wind farm side is used to locate the fault.

[0085] This invention eliminates steady-state interference by using a "pre-fault voltage reference" and then performs three levels of anti-interference processing: phase mode transformation (S4), SCSSA-ICEEMDAN decomposition (S6), and NTEO energy enhancement (S7). This effectively suppresses noise caused by M3C frequency conversion and wind power fluctuations in flexible frequency division systems. Even in scenarios with high-resistance grounding and weak traveling wave signals, it can still stably extract wavefronts.

[0086] Fault rate limiting strategies and location processes work together to avoid M 3 C. Signal interruption caused by fault exit, ensuring data acquisition integrity.

[0087] High positioning accuracy relies on the fusion and optimization of multiple algorithms.

[0088] Breaking through the limitations of traditional traveling wave positioning that relies on "parameters depending on experience": Using SCSSA to intelligently optimize the Nstd and NR parameters of ICEEMDAN, ensuring signal decomposition accuracy and providing high-quality data for wavefront detection;

[0089] The NTEO algorithm normalizes the energy amplification wavefront features, making it easier to accurately calibrate the wavefront timing compared to the traditional TEO algorithm, thus reducing the impact of time errors on the positioning results (the smaller the time error, the smaller the position error).

[0090] Adaptable to the characteristics of flexible frequency division systems, highly practical.

[0091] For flexible frequency division transmission, "low-frequency transmission, M" 3Given the topological characteristic of "C as the core", the measurement point (S1) is directly selected at M. 3 C. The low-frequency side and the step-up transformer side of the wind farm are close to the key nodes of the system, and the collected signals can directly reflect the line fault status.

[0092] Dual-end independent data acquisition + communication collaboration eliminates the need to rely on a single measurement point, reducing the risk of positioning failure due to equipment malfunction. At the same time, cross-verification of data from both ends can further improve the reliability of the results.

[0093] This invention discloses a method for fault location in low-frequency outgoing lines of flexible frequency division transmission systems, relating to the field of fault location in flexible frequency division transmission systems. This invention utilizes ICEEMDAN, optimized with SCSSA parameters, to decompose the mode-1 voltage component of the voltage traveling wave signal on both sides of the line after phase-mode transformation, obtaining its IMF component. The highest frequency IMF component is selected, and NTEO is used to enhance the wavefront change feature, achieving precise calibration of the arrival time of the traveling wave wavefront at the measurement point. Finally, the distance from the fault point to the measurement device is calculated by combining the first arrival times of the forward and reverse traveling waves and the traveling wave velocity. This method fills the gap in fault location for low-frequency outgoing lines of flexible frequency division transmission systems, is unaffected by fault distance, fault type, and system noise, and can achieve relatively accurate fault location for low-frequency outgoing lines of flexible frequency division transmission systems, possessing significant engineering value.

[0094] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various equivalent transformations can be made to the technical solutions of the present invention, and these equivalent transformations all fall within the protection scope of the present invention.

Claims

1. A method for fault location of low frequency sending out line of flexible frequency power transmission system, characterized in that: Includes the following steps: S1, respectively in M 3 The low-frequency side isolation star type side and the offshore wind farm side step-up star type side are installed with the same type of voltage transformers, current transformers and traveling wave positioning devices, and each set of voltage transformers and current transformers independently measures the three-phase voltage on the side. S2, after the fault occurs, M 3 The low-frequency side of C and the traveling wave positioning device on the offshore wind farm side independently collect the x-phase voltage after the fault on the side and form a voltage sequence and Wherein, x is one of the three phases, M 3 The n voltage sampling value sequence after the x-phase fault on the low-frequency side of C; The n voltage sampling value sequence after the x-phase fault on the offshore wind farm side; , The sampling frequency is f, The sampling time is T. S3, combined M 3 C low frequency side with the same sampling frequency as before the offshore wind farm side fault with the sampling time the resulting voltage sample value sequence and , resulting in M 3 C low frequency side with the same sampling frequency as before the offshore wind farm side fault and ; S4, to the low frequency side and the offshore wind farm side fault voltage component and Phase-mode transformation is performed to obtain the fault voltage 1-mode component and and take it as the detection object of the wave head S5. Set the relevant parameters for the SCSSA-ICEEMDAN algorithm and initialize the algorithm; S6, the fault voltage 1 modulus component and Input into the SCSSA-ICEEMDAN algorithm, using SCSSA to optimize the two parameters of ICEEMDAN, namely the amplitude Nstd of the added white noise and the number NR of the added white noise, output the optimal value of Nstd and NR obtained by optimization and , using the SCSSA-optimized ICEEMDAN to decompose M 3 C low-frequency side and wind farm side fault voltage 1 modulus component and , output the IMF frequency spectrum component of the and ; S7, calculating the fault voltage 1 modulus component by using NTEO algorithm , Teager energy value of IMF frequency component, enhancing the mutation characteristics of forward and reverse traveling wave wave front; S8, accurately calibrate the time when the wave head arrives at the installation place of the traveling wave positioning device on the low frequency side and the offshore wind farm side, obtain the first arrival time of the forward and reverse traveling waves at M 3 C low frequency side and offshore wind farm time of the traveling wave positioning device and , and calculate the fault location.

2. The method of claim 1, wherein the method further comprises: The M in S1 3 C low frequency side with fault current limiting strategy for fault ride through, low frequency sending line installed respectively traveling wave positioning device communication channel for communication.

3. The method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system according to claim 1, characterized in that: M in S3 3 C low frequency side and offshore wind farm side fault voltage component and The calculation method is shown in formula (1) and formula (2): (1) (2) Where x can be A, B, or C, representing phase A, phase B, and phase C respectively.

4. The method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system according to claim 1, characterized in that: The S4 fault voltage 1 mode component And The calculation method is shown in equation (3) and equation (4): (3) (4) wherein , and are the M 3 C low frequency side fault voltage 1st mode, 2nd mode and 0th mode component sequences; , and are the offshore wind farm side fault voltage 1st mode, 2nd mode and 0th mode component sequences.

5. The method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system according to claim 1, characterized in that: The S5 comprises: setting population size N of SCSSA algorithm, maximum iteration number , proportion of discoverer , proportion of follower , alert threshold , security threshold ST parameter; setting the value range of two parameters of ICEEMDAN algorithm, namely Nstd and NR.

6. The method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system according to claim 1, characterized in that, The step S6 comprises: using the ICEEMDAN decomposition optimized by SCSSA and The calculation method is: To the original signal sequence Add k times Gaussian white noise to obtain a new signal sequence : (5) wherein denotes performing an EMD decomposition, denotes the adaptive white noise signal added in the kth decomposition, denotes the signal-to-noise ratio of the initial added noise; The k signals obtained in the previous step are combined to obtain a signal EMD decomposition is performed to obtain a first order modal component : (6) wherein is a first order residual, , a custom operator for averaging values; With The first two steps are repeated as initial signal to calculate the n order modal component : (7) in , The residual is of order n-1; Repeat the above steps until all IMF components and residuals are obtained.

7. The method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system according to claim 6, characterized in that: Step S7 includes: taking , The highest frequency component in the IMF spectral components and Then use the NTEO algorithm to calculate and The Teager energy value, where the NTEO algorithm calculates it as follows: For a one-dimensional continuous time domain signal The TEO energy operator is defined as follows: (8) in , They are one-dimensional continuous time domain signals. The first and second derivatives for time t; The TEO energy operator is defined as follows when the differential algorithm is used for approximation: (9) In the formula It is a discrete one-dimensional time-domain signal.

8. The method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system according to claim 1, characterized in that: S8 includes: the moment when the Teager energy calculated by the NTEO algorithm in S7 reaches its maximum value is the moment when the forward and reverse traveling wave fronts arrive at the measurement points on both sides of the low-frequency transmission line in S8; the arrival times of the traveling wave fronts at the measurement points on both sides of the low-frequency transmission line are precisely calibrated to obtain the first arrival times of the forward and reverse traveling waves at M. 3 Time of traveling wave positioning devices on the low-frequency side and wind farm side and The location of the fault is shown in equation (10): (10) in This refers to the total length of the low-frequency transmission line; , From the fault point to M 3 Distance between the low-frequency side and the offshore wind farm side; This represents the propagation speed of the traveling wave.

9. A fault location system for low-frequency transmission lines in a flexible frequency division transmission system, characterized in that: Including: Detection module: in M 3 The low-frequency side isolation star type side and the offshore wind farm side step-up star type side are installed with the same type of voltage transformers, current transformers and traveling wave positioning devices, and each set of voltage transformers and current transformers independently measures the three-phase voltage and current on the side. Voltage sampling value acquisition module: After a fault occurs, M 3 The low-frequency side of C and the traveling wave locating device on the offshore wind farm side independently collect the x-phase voltage after the fault on their respective sides and form a voltage sequence. and Where x is one of the three phases, For M 3 The sequence of n voltage sample values ​​after a low-frequency x-phase fault on the C side; This is a sequence of n voltage sampling values ​​after an x-phase fault on the offshore wind farm side; , Sampling frequency, Sampling duration; combined with M 3 The low-frequency side of C has the same sampling frequency as before the fault on the offshore wind farm side. With sampling duration The obtained voltage sample value sequence and M 3 C. Fault voltage components on the low-frequency side and offshore wind farm side and ; Fault voltage modulus component calculation module: calculates fault voltage components on the low-frequency side and the offshore wind farm side. and Phase-mode transformation is performed to obtain the first-mode component of the fault voltage. and And use it as the detection object of the traveling wave head; Optimization module: Sets relevant parameters for the SCSSA and ICEEMDAN algorithms, initializes the algorithms, and modulates the fault voltage into one modulus component. and The input is fed into the SCSSA-ICEEMDAN algorithm, which uses SCSSA to optimize two parameters of ICEEMDAN: the amplitude of the added white noise (Nstd) and the number of times white noise is added (NR). The output is the optimal value of Nstd and NR obtained after optimization. and Using SCSSA-optimized ICEEMDAN to decompose M 3 C. Low-frequency side and wind farm side fault voltage 1-mode component and Output the and IMF spectral components; Fault location calculation module: Calculates the modulo-1 component of the fault voltage using the NTEO algorithm. , The Teager energy value of the IMF spectral components is used to enhance the abrupt change characteristics of the wavefronts of forward and reverse traveling waves; the arrival times of the traveling wave wavefronts at the locations of the traveling wave positioning devices on the low-frequency side and the offshore wind farm side are precisely calibrated to obtain the first arrival times of the forward and reverse traveling waves at M. 3 Time of traveling wave positioning devices on the low-frequency side and offshore wind farm side and And the fault location is calculated.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system as described in any one of claims 1-7.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for locating faults in low-frequency transmission lines of a flexible frequency division transmission system as described in any one of claims 1-7.

Images