A Lightning Interference Identification Method for Flexible DC Transmission Lines Based on Voltage Traveling Wave Distribution Characteristics

Abstract

This invention discloses a method for identifying lightning interference in flexible DC transmission lines based on voltage traveling wave distribution characteristics. The method includes the following steps: Step 1, obtaining the line-mode voltage fault component and the line-mode current fault component, and then calculating the line-mode voltage reverse traveling wave accordingly; Step 2, performing minimum-maximum normalization on the line-mode voltage reverse traveling wave from the start-up time to 1.5 ms after start-up; Step 3, based on the waveform distribution of the line-mode voltage reverse traveling wave time-domain curve obtained in Step 2, extracting the number of sampling points Q1 located in (0.1,1) and the number of sampling points Q2 located in [0,0.1), and calculating the ratio λ between the two; Step 4, determining whether lightning interference has occurred based on the ratio λ of the number of sampling points. This method enables accurate identification of lightning interference.

Description

Technical Field

[0001] This invention belongs to the field of power system technology and relates to a method for identifying lightning interference in flexible DC transmission lines based on voltage traveling wave distribution characteristics. Background Technology

[0002] Flexible DC transmission technology has important applications in power systems, but it faces significant safety challenges when subjected to lightning strikes. Lightning strikes can not only cause transient overvoltages but also lead to malfunctions in protection systems, resulting in more serious faults or power outages. Existing lightning strike identification methods are mostly based on current traveling waves and waveform analysis, but they have significant shortcomings in accuracy and real-time performance. Especially under complex operating conditions, they are prone to misjudging or missing lightning strikes, thus failing to effectively prevent protection malfunctions.

[0003] While traditional traveling wave methods can capture transient signals induced by lightning strikes, the similarity between lightning strikes and other current fluctuation events makes accurate differentiation difficult in practical operations, easily leading to malfunctions. Waveform analysis methods struggle with complex interference, such as multiple lightning strikes or high-noise environments, exhibiting poor signal resolution, especially under low signal-to-noise ratio conditions where recognition performance significantly deteriorates. While time-frequency domain processing methods can obtain richer signal spectral information, their high computational complexity makes real-time application in practical engineering difficult. Summary of the Invention

[0004] The purpose of this invention is to provide a method for identifying lightning interference in flexible DC transmission lines based on voltage traveling wave distribution characteristics. This method utilizes the fact that when a ground fault or lightning fault occurs, the line-mode voltage reverse traveling wave will not drop to near 0, and when lightning interference occurs, the line-mode voltage reverse traveling wave will attenuate to 0. Even if subsequent wavefront superposition occurs, there is still a significant attenuation characteristic, thus achieving accurate identification of lightning interference.

[0005] The technical solution adopted in this invention is a method for identifying lightning interference in flexible DC transmission lines based on voltage traveling wave distribution characteristics, which specifically includes the following steps:

[0006] Step 1: Calculate the line-mode voltage fault component Δu1(k) and the line-mode current fault component Δi1(k), and finally calculate the line-mode voltage reverse traveling wave u based on these components. b (k);

[0007] Step 2: Take the line-mode voltage inverse traveling wave from the start time to 1.5ms after start-up and perform minimum-maximum normalization;

[0008] Step 3: Based on the waveform distribution of the line-mode voltage inverse traveling wave time domain curve obtained in Step 2, extract the number of sampling points Q1 located in (0.1,1) and the number of sampling points Q2 located in [0,0.1), and calculate the ratio λ between the two.

[0009] Step 4: Based on the ratio λ of the number of sampling distribution points calculated in Step 3, determine whether lightning interference has occurred.

[0010] The invention is further characterized by:

[0011] The specific process of step 1 is as follows:

[0012] Step 1.1: After the protection starting element is activated, the time range from the activation moment to 1.5ms after activation is set as the protection time window. Within this window, the positive voltage u at the installation location of the protection device is read. p (k) Negative electrode voltage u n (k), positive current i p (k), negative electrode current i n (k) Compare these data with the average positive voltage u within 10ms before protection activation. p0 Average negative electrode voltage u n0 Average positive current i p0 Average negative current i n0 Subtract to calculate the positive voltage fault component Δu p (k) Negative electrode voltage fault component Δu n (k), Positive current fault component Δi p (k) and the negative electrode current fault component Δi n (k), the calculation formula is shown in equation (1):

[0013]

[0014] Step 1.2: Calculate the line-mode voltage fault component Δu1(k) and the line-mode current fault component Δi1(k) within the time window. The calculation formula is shown in equation (2):

[0015]

[0016] Step 1.3: Calculate the line-mode voltage inverse traveling wave u within the time window. b (k), the calculation formula is shown in equation (3):

[0017]

[0018] In the formula, Z c1 The impedance of the line mode wave is given.

[0019] The specific process of step 2 is as follows:

[0020] Step 2.1, for the line-mode voltage inverse traveling wave data u within the time window b (k) By comparing using formula (4), when the sampled voltage amplitude is greater than twice the system rated voltage, the voltage value at that sampling point is recorded as twice the system rated voltage, as shown in formula (4) below:

[0021] u b (k)≥2U N (4)

[0022] In the formula: k is the time sequence number, 0≤k≤N-1; N is the number of sampling points from the start-up time of the faulty component to 1.5ms after start-up; U N This is the system's rated voltage;

[0023] Step 2.2, according to the following formula (5), the line-mode voltage reverse traveling wave u1.5ms after the faulty component starts is calculated. b (k) Normalized voltage u bMN (k):

[0024]

[0025] In the formula: min(u b (k) is the minimum value within the time window; max(u) is the minimum value within the time window. b (k) is the maximum value within the time window.

[0026] The specific process of step 4 is as follows:

[0027] If λ>λ set If λ < λ, then a fault is determined to have occurred; if λ < λ set If so, it is determined to be lightning interference, λ set This is the threshold value.

[0028] The beneficial effects of this invention are that it identifies lightning interference based on the distribution characteristics of the line-mode voltage inverse traveling wave. This method normalizes the line-mode voltage inverse traveling wave, reducing the impact of transition resistance on the identification method. Simultaneously, the method of extracting distribution characteristics makes the identification rapid and possesses strong anti-noise interference capabilities, effectively identifying lightning interference even with 0Ω and 500Ω transition resistances and 10dB noise interference. Furthermore, because its lightning identification principle based on the inverse traveling wave can be used in both bounded and unbounded flexible DC power grids. Attached Figure Description

[0029] Figure 1 This is a flowchart of the lightning interference identification method for flexible DC transmission lines based on voltage traveling wave distribution characteristics according to the present invention;

[0030] Figure 2This is a simulation model diagram of a true bipolar MMC flexible DC transmission system at both ends;

[0031] Figure 3(a) shows the simulation verification stage, where the lightning interference identification method for flexible DC transmission lines based on voltage traveling wave distribution characteristics of this invention is used to normalize and display the waveform distribution of the line-mode voltage reverse traveling wave with a transition resistance of 500Ω at an in-zone grounding fault at 250km in a bipolar flexible DC system.

[0032] Figure 3(b) shows the distribution of the normalized waveform of the line-mode voltage reverse traveling wave at a ground fault within the area at 250km of the bipolar flexible DC system with a transition resistance of 500Ω in various amplitude ranges.

[0033] Figure 4 This is a simulation model diagram of a four-terminal MMC flexible DC transmission network;

[0034] Figure 5(a) shows the simulation verification stage, where the line mode voltage reverse traveling wave of the flexible DC transmission line lightning interference identification method based on voltage traveling wave distribution characteristics of the present invention is used to normalize the lightning interference back-traveling wave in the 100km area of ​​the four-terminal flexible DC power grid and the waveform distribution diagram.

[0035] Figure 5(b) shows the number of distribution points of the normalized waveform of the line-mode voltage reverse traveling wave for lightning interference detection within a 100km radius of the four-terminal flexible DC power grid in various amplitude ranges.

[0036] Figure 6 This is a simulation model diagram of a four-terminal "mesh-type" MMC flexible DC transmission network;

[0037] Figure 7(a) shows the simulation verification stage, where the line mode voltage reverse traveling wave of the flexible DC transmission line lightning interference identification method based on voltage traveling wave distribution characteristics of the present invention is used to normalize the lightning fault back wave of the four-terminal "mesh" flexible DC system at 100km and the waveform distribution diagram.

[0038] Figure 7(b) shows the number of distribution points of the normalized waveform of the line mode voltage reverse traveling wave for lightning fault bypass detection at 100km in the four-terminal "mesh-type" flexible DC system in various amplitude ranges. Detailed Implementation

[0039] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0040] This invention provides a method for identifying lightning interference in flexible DC transmission lines based on voltage traveling wave distribution characteristics, specifically including the following steps:

[0041] Step 1: After the protection starting element starts, set the time from the start time to 1.5ms after start as the protection time window. Within this time window, read the voltage and current data. Calculate the positive voltage fault component Δu. p(k), Positive current fault component Δi p (k) Negative electrode voltage fault component Δu n (k) and the negative electrode current fault component Δi n (k), and then calculate the line-mode voltage fault component Δu1(k) and the line-mode current fault component Δi1(k) based on these components. Finally, calculate the line-mode voltage reverse traveling wave u based on this. b (k);

[0042] The specific process of step 1 is as follows:

[0043] Step 1.1: After the protection starting element is activated, the time range from the activation moment to 1.5ms after activation is set as the protection time window. Within this window, the positive voltage u at the installation location of the protection device is read. p (k) Negative electrode voltage u n (k), positive current i p (k), negative electrode current i n (k) Compare these data with the average positive voltage u within 10ms before protection activation. p0 Average negative electrode voltage u n0 Average positive current i p0 Average negative current i n0 Subtract to calculate the positive voltage fault component Δu p (k) Negative electrode voltage fault component Δu n (k), Positive current fault component Δi p (k) and the negative electrode current fault component Δi n (k), the calculation formula is shown in equation (1):

[0044]

[0045] Step 1.2: Calculate the line-mode voltage fault component Δu1(k) and the line-mode current fault component Δi1(k) within the time window. The calculation formula is shown in equation (2):

[0046]

[0047] Step 1.3: Calculate the line-mode voltage inverse traveling wave u within the time window. b (k), the calculation formula is shown in equation (3):

[0048]

[0049] In the formula, Z c1 The impedance of the line mode wave is given.

[0050] Step 2: Take the line-mode voltage inverse traveling wave from the start time to 1.5ms after start-up and perform minimum-maximum normalization to obtain the corresponding normalized line-mode voltage inverse traveling wave time-domain curve.

[0051] Step 2.1, for the line-mode voltage inverse traveling wave data u within the time window b (k) By comparing with formula (4), when the sampled voltage amplitude is greater than twice the system rated voltage, the voltage value of the sampling point is recorded as twice the system rated voltage.

[0052] u b (k)≥2U N (4)

[0053] In the formula: k is the time sequence number, 0≤k≤N-1; N is the number of sampling points from the start-up time of the faulty component to 1.5ms after start-up; U N This is the system's rated voltage.

[0054] Step 2.2, according to the following formula (5), the line-mode voltage reverse traveling wave u1.5ms after the faulty component starts is calculated. b (k) Normalized voltage u bMN (k).

[0055]

[0056] In the formula: k is the time sequence number, 0≤k≤N-1; N is the number of sampling points from the start-up time of the faulty component to 1.5ms after start-up; min(u b (k) is the minimum value within the time window; max(u) is the minimum value within the time window. b (k) is the maximum value within the time window.

[0057] Step 3: Determine the waveform distribution of the time-domain curve of the line-mode voltage inverse traveling wave obtained in Step 2; extract the number of sampling points Q1 located in (0.1,1) and the number of sampling points Q2 located in [0,0.1), and calculate the ratio λ between the two.

[0058] Step 3.1, using the normalized voltage u obtained in step 2 bMN (k) Plot the time-domain distribution of the line-mode voltage reverse traveling wave: when u bMN If (k)>0.1, then the sampled line-mode voltage is located in (0.1,1]. The number of sampled points located in (0.1,1) within the time window is denoted as Q1. When u bMN If (k)≤0.1, then the sampled line-mode voltage is distributed in [0,0.1]. The number of sampled points located in [0,0.1] within the time window is denoted as Q2.

[0059] Step 3.2, calculate the ratio λ between Q1 and Q2 according to the following formula (6).

[0060]

[0061] Step 4, if λ>λ set If λ < λ, then a fault is determined to have occurred; if λ < λ set If so, it is judged to be lightning interference.

[0062] The specific process of step 4 is as follows:

[0063] Step 4.1, if λ>λ set If λ < λ, then a fault is determined to have occurred; if λ < λ set If the value is such that the signal is detected by lightning, then it is determined to be lightning interference. The obtained ratio λ is then compared with the threshold value λ. set In contrast, as shown in Equation (5), the relationship between λ and the threshold value is used as the criterion for identifying lightning disturbance.

[0064]

[0065] Step 4.2: Based on the difference in voltage reverse traveling wave waveforms during faults and lightning interference, and the simulation test results, select the threshold value λ. set =5.

[0066] As attached Figure 2 The figure shows a simulation model of a double-ended flexible DC transmission system. In the figure, the current-limiting reactor L = 0.2H, MMC1 and MMC2 are modular converters, P1 and P2 are line boundary protection measurement points, and f1 is the location of the disturbance. This system has a rated voltage of ±500kV, a rated transmission capacity of 3000MVA, and a total transmission line length of 500km. An overhead line frequency-varying parameter model is used, and its line surge impedances are Z... c0 =320Ω, Z c1 =260Ω. During system simulation, the sampling frequency was 100kHz, and a 1.2 / 50μs standard lightning current model was used to simulate a lightning strike. The entire text uses Line 1, measuring point P1 as an example; the fault distance is the distance from the fault location to measuring point P1, as shown in the attached figure. Figure 1 The identification process identifies lightning interference.

[0067] Example 1

[0068] As shown in Figure 3(a), in the case of Figure 2In the dual-ended flexible DC transmission system shown, when a positive ground fault with a transition resistance of 500Ω occurs 250km from the protection measuring point P1, the simulated value of the line-mode voltage reverse traveling wave measured at the protection measuring point is obtained. After the protection element is activated, the line-mode voltage reverse traveling wave data from 150 sampling points after activation are read and normalized. The λ value is calculated, and the fault is determined, triggering the protection action. As shown in Figure 3(b), the distribution of the number of points of the normalized line-mode voltage reverse traveling wave in various amplitude ranges proves the feasibility of the protection scheme.

[0069] As attached Figure 4 The figure shows a simulation model of a four-terminal MMC flexible DC transmission network. In the figure, the current-limiting reactor L = 0.2H, MMC1, MMC2, MMC3, and MMC4 are modular converters, P1 and P2 are line boundary protection measurement points, f1 is the location of the disturbance, the rated voltage between MMC1 and MMC2 is ±500kV, the rated transmission capacity is 3000MVA, the total length of the transmission line is 207.9km, and an overhead line frequency-varying parameter model is used. The line surge impedances are Z... c0 =310Ω, Z c1 =250Ω. During system simulation, the sampling frequency was 100kHz, and a 1.2 / 50μs standard lightning current model was used to simulate lightning strikes. The four-terminal flexible DC power grid structure is highly symmetrical. The entire text takes Line 1, measurement point P1 as an example. The fault distance is the distance from the fault location to measurement point P1, as shown in the attached figure. Figure 1 The identification process identifies lightning interference.

[0070] Example 2

[0071] As shown in Figure 5(a), in the case of Figure 4 In the four-terminal MMC flexible DC transmission network shown, when a lightning strike interference occurs 100km from the protection installation point, the simulated value of the line-mode voltage reverse traveling wave measured at the protection measuring point is presented. After the protection element is activated, the line-mode voltage reverse traveling wave data from 150 sampling points after activation are read and normalized. The λ value is calculated, and it is determined to be lightning interference, so the protection returns. As shown in Figure 5(b), the distribution of the number of points of the normalized line-mode voltage reverse traveling wave in various amplitude ranges proves the feasibility of the protection scheme.

[0072] As attached Figure 6 The figure shows a simulation model of a four-terminal "mesh-type" MMC flexible DC transmission network. In the figure, the current-limiting reactor L = 0.2H, MMC1, MMC2, MMC3, and MMC4 are modular converters, P1 and P2 are line boundary protection measurement points, f1 is the location of the disturbance, the rated voltage between MMC1 and MMC2 is ±500kV, the rated transmission capacity is 3000MVA, the total length of the transmission line is 207.9km, and an overhead line frequency-varying parameter model is used. The line surge impedances are Z... c0 =310Ω, Zc1 =250Ω. During system simulation, the sampling frequency was 100kHz, and a 1.2 / 50μs standard lightning current model was used to simulate lightning strikes. The four-terminal "mesh-type" flexible DC power grid structure is highly symmetrical. Taking Line 1 and P1 as an example, the fault distance is the distance from the fault location to the measuring point P1, as shown in the attached figure. Figure 1 The identification process identifies lightning strike faults.

[0073] Example 3

[0074] As shown in Figure 7(a), in the case of Figure 6 In the four-terminal "mesh-type" MMC flexible DC transmission network shown, when a lightning strike fault occurs 100km from the protection installation point, the simulated value of the line-mode voltage reverse traveling wave measured at the protection measuring point is presented. After the protection element is activated, the line-mode voltage reverse traveling wave data from 150 sampling points after activation are read and normalized. The λ value is calculated, and the fault is determined, triggering the protection operation. As shown in Figure 5(b), the distribution of the number of points of the normalized line-mode voltage reverse traveling wave in various amplitude ranges proves the feasibility of the protection scheme.

[0075] To comprehensively verify the impact of fault distance, lightning strike type, transition resistance magnitude, and system type on the discrimination results, lightning strike faults, lightning interference, and grounding faults with transition resistances of 0Ω and 500Ω were respectively set up in a two-terminal flexible DC system, a four-terminal flexible DC power grid, and a four-terminal "mesh-type" flexible DC power grid. The impact of 10dB noise was also considered, and the lightning interference identification method was verified based on the simulation results.

[0076] Table 1 provides simulation data for different fault distances on bipolar flexible DC transmission lines. All grounding faults are metallic grounding faults, and both lightning strikes and lightning interference are considered side-strikes. Data within the time window shows that λ is less than 5 when lightning interference occurs, and greater than 5 when both lightning strikes and grounding faults occur. Lightning interference can be identified at all fault distances.

[0077] Table 1 Simulation verification results for different fault distances

[0078]

[0079]

[0080] Table 2 provides simulation data for ground faults with different transition resistances on bipolar flexible DC transmission lines. Data within the time window shows that λ is greater than 5 when a ground fault occurs. Faults with different transition resistances can be accurately identified.

[0081] Table 2 Simulation verification results for different transition resistances

[0082]

[0083] Table 3 provides simulation data for lightning strikes and backflashovers on bipolar flexible DC transmission lines. Data within the time window shows that λ is less than 5 when lightning interference occurs, and greater than 5 when lightning faults and grounding faults occur. Both lightning strikes and backflashovers can be accurately identified.

[0084] Table 3 Simulation verification results for different lightning strike types

[0085]

[0086]

[0087] Table 4 provides simulation data for faults occurring on bipolar flexible DC transmission lines with 10dB noise interference. Data within the time window shows that λ is less than 5 when lightning interference occurs, and greater than 5 when both lightning and grounding faults occur. The protection criterion can identify lightning interference under 10dB noise interference.

[0088] Table 4 Simulation verification results under the influence of 10dB noise interference

[0089]

[0090] Table 5 shows the simulation data for faults occurring in three different flexible DC power grids. From the data within the time window, it can be seen that λ is less than 5 when lightning interference occurs; and greater than 5 when both lightning and grounding faults occur. The protection criterion can identify lightning interference in all different flexible DC power grids.

[0091] Table 5 shows the simulation results of faults occurring in three different flexible DC power grids.

[0092]

[0093]

[0094] This invention normalizes the line-mode voltage reverse traveling wave and significantly reduces the possibility of false positives and false negatives by extracting its waveform distribution characteristics. Simultaneously, the voltage traveling wave analysis method has the advantages of low computational complexity and fast response speed, meeting the real-time and high-precision requirements of flexible DC transmission systems and avoiding protection malfunctions. The purpose of this invention is to provide a lightning interference identification method based on voltage traveling wave distribution characteristics. This method utilizes the fact that during ground faults and lightning faults, the line-mode voltage reverse traveling wave does not subsequently drop to near zero; during lightning interference, the line-mode voltage reverse traveling wave attenuates to zero, and even with subsequent wavefront superposition, significant attenuation characteristics remain. Therefore, normalizing the line-mode voltage reverse traveling wave reduces the impact of transition resistance on the identification method. Furthermore, the method of extracting distribution characteristics enables rapid identification and strong anti-noise interference capabilities. Moreover, since its lightning identification principle based on reverse traveling waves can be used in both bounded and unbounded flexible DC power grids.

Claims

1. A method for identifying lightning interference in flexible DC transmission lines based on voltage traveling wave distribution characteristics, characterized in that: Specifically, the steps include the following: Step 1: Calculate the line-mode voltage fault component. Linear current fault component Finally, the reverse traveling wave of the line-mode voltage was calculated based on this. ; Step 2: Take the line-mode voltage inverse traveling wave from the start time to 1.5 ms after start-up and perform minimum-maximum normalization; the specific process of step 2 is as follows: Step 2.1, for the line-mode voltage inverse traveling wave data within the time window By comparing using formula (4), when the sampled voltage amplitude is greater than twice the system rated voltage, the voltage value at that sampling point is recorded as twice the system rated voltage, as shown in formula (4) below: （4） In the formula: k For time sequence number, 0≤ k ≤ N -1; N This represents the number of sampling points from the moment the faulty component starts up to 1.5 ms after startup. U N This is the system's rated voltage; Step 2.2, according to the following formula (5), the reverse traveling wave of the line-mode voltage 1.5 ms after the faulty component is started. Normalized voltage : （5） In the formula: It is the minimum value within the time window; It is the maximum value within the time window. It is a line-mode voltage inverse traveling wave; Step 3: Based on the waveform distribution of the line-mode voltage inverse traveling wave time domain curve obtained in Step 2, extract the number of sampling points Q1 located in (0.1,1) and the number of sampling points Q2 located in [0,0.1), and calculate the ratio between the two. The specific process of step 3 is as follows: Step 3.1, using the normalized voltage obtained in Step 2. Plot the time-domain distribution of the inverse traveling wave of the line-mode voltage: When If the value is greater than 0.1, then the line-mode voltage of the sampling point is located in (0.1, 1]. The number of sampling points located in (0.1, 1) within the time window is denoted as... Q 1. will; when If the value is 0.1, then the sampled line-mode voltage is distributed in [0, 0.1]. The number of sampled points located in [0, 0.1] within the time window is denoted as . Q 2; Step 3.2, calculate according to the following formula (6). Q 1 With Q The ratio between 2 : （6） Step 4: Based on the ratio of sampling distribution points calculated in Step 3 To determine whether lightning interference has occurred; the specific process of step 4 is as follows: If > If set, it is determined that a fault has occurred; if < When set, it is determined to be lightning interference. `set` represents the threshold value.

2. The method for identifying lightning interference in flexible DC transmission lines based on voltage traveling wave distribution characteristics according to claim 1, characterized in that: The specific process of step 1 is as follows: Step 1.1: After the protection starting element is activated, a protection time window is set from the activation time to 1.5 ms after activation. Within this window, the positive voltage at the installation location of the protection device is read. Negative voltage Positive current Negative current These data were compared with the average positive voltage within 10 ms before protection activation. Average negative electrode voltage Average positive current Average negative current Subtract to calculate the positive voltage fault component. Negative voltage fault component Positive current fault component With negative current fault component The calculation formula is shown in equation (1): （1） Step 1.2: Calculate the line-mode voltage fault component within the time window. Linear current fault component The calculation formula is shown in equation (2): （2） Step 1.3: Calculate the line-mode voltage back-traveling wave within the time window. The calculation formula is shown in equation (3): （3） In the formula, The impedance of the line mode wave is given.

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