A double-end traveling wave distance measurement method based on traveling wave body energy positioning

Abstract

The application discloses a double-end traveling wave distance measurement method based on wave body energy positioning. The method comprises the following steps: collecting fault current traveling waves at both ends of a line, and obtaining line mode components through Clarke transformation; selecting target IMF components through VMD decomposition; generating an energy accumulation curve by performing sliding window integration on the square of the components; taking the inflection point (energy maximum point) of the curve as the traveling wave arrival time; and substituting the traveling wave arrival time into a double-end distance measurement formula to calculate the fault distance. The application uses the overall energy characteristics of the traveling wave to replace the traditional wave head calibration, significantly improves the precision, robustness and application range of the distribution network fault positioning, and effectively overcomes the influence of noise interference and signal distortion.

Description

Technical Field

[0001] This invention relates to the field of power system relay protection and fault diagnosis technology, specifically a two-end traveling wave ranging method based on traveling wave energy positioning for fault location in distribution networks. This method is particularly suitable for solving the problem of low positioning accuracy caused by the weak wavefront characteristics of traditional traveling wave methods. By utilizing the overall energy information of the traveling wave signal, it improves the robustness and accuracy of fault location. Background Technology

[0002] As a critical link in the power system directly facing users, the safe and stable operation of the distribution network is of paramount importance. Quickly and accurately locating faults in the distribution network is a core guarantee for shortening power outage time and improving power supply reliability. Traditional methods for fault location in distribution networks mainly include impedance methods and traveling wave methods. Among them, the traveling wave method has been widely used in transmission systems due to its advantage of being unaffected by system parameters, load changes, and line asymmetry. However, in the distribution network environment, due to the complex line structure and numerous branches, and the susceptibility of the traveling wave signal to noise interference and signal distortion during propagation, traditional traveling wave location methods often rely on accurately calibrating the arrival time of the traveling wave front. In reality, the characteristics of the traveling wave front are often quite weak, making accurate identification difficult in complex electromagnetic environments, resulting in large location errors and limiting its engineering application effectiveness.

[0003] To address the aforementioned issues, existing technologies have proposed various improvement schemes, such as wavefront calibration methods based on Hilbert-Huang transform (HHT), complementary set empirical mode decomposition (CEEMD) combined with energy operator (TEO), and wavelet transform. While these methods have improved the accuracy of wavefront identification to some extent, their core ideas still focus on the extraction and enhancement of wavefront features, failing to fundamentally eliminate the dependence on weak wavefront signals. Therefore, in scenarios with strong noise or severe signal distortion, their robustness and accuracy still cannot meet engineering requirements. Summary of the Invention

[0004] The core innovation of this invention lies in proposing a novel method for calibrating the arrival time of traveling waves—the Wave Energy Calculator (WEC). This method breaks through the limitations of traditional approaches, expanding the analytical perspective from the "wavehead" of the traveling wave signal to the "wave body," that is, focusing on the overall energy change characteristics during the propagation of the traveling wave signal.

[0005] The basic principle is that when a fault occurs, the traveling wave signal excited at the fault point gradually accumulates energy as it propagates to the measurement end. By appropriately processing the traveling wave signal (such as squaring it to enhance amplitude characteristics and eliminate polarity effects), and then using a sliding window integration method to calculate its energy accumulation curve, this curve will exhibit a significant step change when the traveling wave signal completely passes through the measurement point, i.e., it reaches its maximum accumulated energy. This invention defines the moment when this accumulated energy reaches its maximum value (i.e., the inflection point of the energy accumulation curve) as the moment when the traveling wave arrives at the measurement end. Compared to relying on weak and volatile wavefront characteristics, the overall energy characteristics of the traveling wave signal have stronger stability and anti-interference capabilities. Therefore, the arrival time calibrated based on the wave volume energy positioning method can effectively overcome the influence of noise and signal distortion, significantly improving the accuracy and robustness of dual-end traveling wave ranging.

[0006] Fault information collection. When a fault occurs in the middle of a power distribution line, the generated traveling current signal is transmitted to both ends of the line. Traveling wave recording devices installed at both ends record the current traveling wave waveform of the signal, which serves as the collected fault signal information and provides data for subsequent fault location.

[0007] The core of this invention is a two-end traveling wave ranging method based on wave body energy positioning, and its specific implementation steps are as follows:

[0008] Current sensors are installed at both ends of the power distribution line (end A and end B) to synchronously collect the current traveling wave signal after a fault occurs. For example... Figure 1 The information collection model shown is shown.

[0009] The acquired three-phase current traveling wave signal was subjected to Clarke transform to achieve phase mode decoupling and extract the line mode component (or α-mode component) with stable propagation characteristics and less susceptibility to interference. The line mode component was chosen because it has relatively small attenuation during transmission and is easy to measure.

[0010] 2. Signal decomposition and noise reduction:

[0011] Variational Mode Decomposition (VMD) is performed on the line-mode component signals extracted from both ends. VMD is an adaptive signal decomposition method that can decompose complex non-stationary signals into several intrinsic mode functions (IMFs) with specific center frequencies.

[0012] Among the multiple IMF components obtained from the decomposition, the component that best reflects the overall characteristics of the fault current traveling wave signal (usually the high-frequency part, which contains the main energy information of the traveling wave) is selected. The introduction of VMD helps to remove low-frequency interference and noise in the signal, improving the accuracy of subsequent energy calculations.

[0013] 3. Wavebody Energy Location (WEC):

[0014] Signal squaring: Squaring the selected target IMF component, i.e. The purpose of this step is to enhance the amplitude characteristics of the traveling wave signal and eliminate the influence of signal polarity on energy calculation, so that the subsequent energy accumulation curve is clearer.

[0015] Sliding window integration: integration of the squared signal s ( t Perform sliding window integration to calculate its energy accumulation curve. E ( t The integral formula is:

[0016] in, T The length (time) of the sliding window determines the timescale of energy accumulation. In practical digital implementations, a discrete form is used:

[0017] in, N It corresponds to the window length. T The number of sampling points is the sampling interval. ( ).

[0018] Inflection point calibration: energy accumulation curve obtained through analysis and calculation E ( t )(or E ( n The inflection point is determined by calibrating the energy accumulation curve. This inflection point corresponds to the moment when the energy accumulation curve reaches its maximum value, i.e., the moment when the traveling wave signal energy has completely passed through the measurement point. This invention defines this moment as the moment when the traveling wave arrives at the measurement end. T A and T B ).

[0019] 4. Two-end distance measurement calculation:

[0020] Obtain the arrival times of the traveling waves at both ends of the line (end A and end B) as determined by the WEC method described above. T A and T B Time difference | T B - T A Substituting into the two-end traveling wave ranging formula:

[0021] in: DIt is the calculated distance from the fault point to end A of the line. v It is the propagation speed of the traveling wave in the power distribution line (which can be calculated or measured and calibrated through line parameters). L This is the total length of the line from end A to end B. (Calculation result) D This indicates the location of the fault.

[0022] This invention has significant advantages over existing technologies:

[0023] (1) High precision and strong robustness: By utilizing the overall energy characteristics (wave body) of the traveling wave signal rather than the weak wavefront characteristics for arrival time calibration, the influence of noise interference and signal distortion on positioning accuracy is effectively overcome. Simulation results show that the relative error of ranging can be controlled within 1.5% (e.g., error ≤ 150m for a 10km line).

[0024] (2) Wide applicability: This method is not sensitive to factors such as fault type (single-phase grounding, phase-to-phase short circuit, three-phase short circuit, etc.), fault initial phase angle, and grounding resistance. It can maintain stable high-precision positioning under various fault conditions.

[0025] (3) Reduced dependence on sampling accuracy: Compared with methods that rely on precise wavefront identification, WEC has relatively relaxed requirements on sampling frequency.

[0026] (4) Strong engineering practicality: The method has a clear principle, moderate calculation complexity, and is easy to implement in existing traveling wave fault recording devices or protection devices.

[0027] The effects of the invention (1) Under different grounding resistance conditions, assume that a single-phase ground fault occurs 3km away from the beginning of the line, with grounding resistances of 0Ω, 100Ω, 300Ω, 500Ω and 1000Ω respectively. The location results under different grounding resistances are shown in Table 1.

[0028] Table 1. Location results for different grounding resistances Grounding resistance / Ω <![CDATA[t a / (ms)]]> <![CDATA[t b / (ms)]]> Location results / km relative error / % 0 5.011 5.025 2.97042 0.2958 100 5.011 5.025 2.97042 0.2958 300 5.011 5.025 2.97042 0.2958 500 5.011 5.025 2.97042 0.2958 1000 5.011 5.025 2.97042 0.2958

[0029] The impact of fault location on location results. Assume single-phase ground faults with a grounding resistance of 100Ω occur at distances of 2km, 3km, 4km, and 5km from the beginning of the line. The location results for different fault locations are shown in Table 2.

[0030] Table 2. Location results of different fault locations Fault distance / km <![CDATA[t a / (ms)]]> <![CDATA[t b / (ms)]]> Location results / km relative error / % 2 5.008 5.028 2.1006 1.006 3 5.011 5.025 2.97042 0.2958 4 5.015 5.022 3.9852 0.148 5 5.018 5.019 4.85503 1.4497

[0031] Methods and processes, such as Figure 1 As shown.

[0032]

[0033] Figure 1 Flowchart of the calculation method.

Claims

1. A two-end traveling wave ranging method based on wavebody energy localization, characterized in that, Includes the following steps: Fault current traveling wave signals are collected at both ends of the power distribution line and obtained as line mode components by Clarke transformation. Variational mode decomposition (VMD) is performed on the linear mode components to obtain multiple intrinsic mode components (IMFs). The target IMF component that best reflects the overall characteristics of the fault traveling wave is selected. The target IMF component is then squared to obtain the amplitude enhancement signal. s (t); For the amplitude enhancement signal s (t) Perform sliding window integration to generate the energy accumulation curve. E (t); Calibrate the energy accumulation curve E The inflection point of (t) is the moment when the energy accumulation reaches its maximum value, which is also the moment when the traveling wave arrives at both ends of the path. T A and T B Time difference | T B - T A Substitute into the two-end traveling wave ranging formula Calculate the distance to the fault point D ;in, v For traveling wave speed, L This is the total length of the line.

2. The method according to claim 1, characterized in that, The discrete calculation formula for the sliding window integral is as follows: ,in N s(k) represents the number of sampling points within the window, and s(k) represents the discretized amplitude enhancement signal.

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