Fault identification method for long-distance direct-current transmission line

Abstract

The invention discloses a long-distance direct-current transmission line fault identification method. The method comprises the following steps: acquiring positive and negative pole line voltages, performing Karen Bell transformation on the two pole line voltages to obtain line modulus voltages, performing difference on the modulus voltages to obtain a first-order difference, constructing a first-order difference quadratic sum, and introducing a db4 wavelet first scale filter high-frequency detail coefficient h; and carrying out convolution on the first-order difference quadratic sum and the first-order difference quadratic sum, selecting a high-frequency detail coefficient h, constructing an internal and external fault discriminant and an internal and external fault criterion, and carrying out other steps to recognize the fault of the long-distance direct-current transmission line. The blocking effect of smoothing reactors on the two sides of the power transmission line of the double-end flexible direct-current power transmission system on the high-frequency component in the fault electrical quantity is utilized, so that the high-frequency quantity comparison is more obvious when faults occur inside and outside the area, and the protection accuracy is improved.

Description

Technical Field

[0001] The invention belongs to the electrical field, and in particular relates to a long-distance direct current transmission line fault identification method based on the sum of squares of first-order differences of pole line voltages and their high-frequency characteristics. Background Art

[0002] Traditional overcurrent protection and undervoltage protection have poor selectivity in DC power grids, and distance protection is difficult to accurately measure distance in a few milliseconds and cannot meet the speed requirements of DC power grids. New protection methods need to be introduced to meet the needs. Conventional DC protection uses traveling wave protection as the main protection, and the flexible DC transmission system draws on the protection of conventional DC systems and also adopts traveling wave protection. However, its essence is sudden change protection, so in order to ensure selectivity, the setting value is usually set higher. Therefore, when the end of the line or high-resistance fault occurs, there is a possibility of refusal to operate due to insufficient sensitivity, and it is easily affected by transition resistance and noise. Many literatures have proposed to construct DC protection using traveling wave change rate, amplitude, line zero mode component, etc., but most schemes still have problems such as being easily affected by noise and difficult to identify high-resistance faults.

[0003] After a fault occurs, the fault location needs to be identified quickly and accurately. If the fault location cannot be identified in time, it may cause the recurrence of transient faults or evolve into more serious permanent faults, seriously affecting the normal work progress and causing economic losses. Therefore, it is hoped that there is a fault detection method that can realize the fault section identification to solve the problem of line protection after a fault occurs in the transmission line of the double-terminal flexible DC transmission system. Summary of the invention

[0004] The purpose of the present invention is to provide a long-distance DC transmission line fault identification method based on the sum of squares of the first-order differences of the pole line voltage and its high-frequency characteristics, using the high-frequency components of the voltage to make in-and-out zone judgments to solve transmission line faults in DC transmission systems.

[0005] To achieve the above technical problems, the technical solution of the present invention is:

[0006] A line fault identification method based on the sum of squares of first-order differences of pole line voltages and their high-frequency characteristics comprises the following steps:

[0007] Step 1: Select the fault time window and use the monitoring device DTU (Data Transfer Unit, wireless terminal equipment) to sample. After the fault occurs, use the monitoring device to collect the positive pole line voltage u1(k) and the negative pole line voltage u2(k), where: k is the kth sampling time after the fault start time, and voltage sampling is performed once at each sampling time;

[0008] Step 2 Perform Karenberg transformation on the positive pole line voltage u1(k) and the negative pole line voltage u2(k) to obtain the line modulus voltage um1 (k);

[0009] Step 3: Line modulus voltage u m1 (k) Take the difference and get the first-order difference du m1 (k) = u m1 (k)-u m1 (k-1); where k has the same meaning as in Step 1 (the following repeated parts will not be repeated);

[0010] Step 4 Construct the first-order difference sum of squares It is assumed that the square of the first-order difference of every five pole line voltages is summed up once; where: is the sum of squares of the first-order differences of the pole-line voltages obtained from the kth to k-5th voltage sampling points after the fault occurs, where k′=k-4, k≥5; when k′=1, the expansion is:

[0011]

[0012] Step 5: Determine the high-frequency detail coefficient h of the db4 wavelet first scale filter based on the fault time window set to 1ms and the DTU sampling rate of the monitoring device to 10kHz;

[0013] Step6: Convolve with h: Where: N is 5; D u (n) is the convolution result; n is the number of parameters in the detail coefficient h;

[0014] Step 7: Construct the internal and external fault discrimination formula: And round it to get In the formula: Combined with the fault quantity time window and sampling rate, N1 is set to 6; For the 6 convolution results D u (n) The result of taking the average; For The result of rounding;

[0015] Step 8: If the fault judgment criteria inside and outside the construction area are: If the fault is within the zone, the protection will be activated; This is an out-of-zone fault.

[0016] Furthermore, the fault quantity time window in Step 1 is set to 1ms, and the sampling rate of the monitoring device DTU is 10kHz.

[0017] Furthermore, the high frequency detail coefficient h in Step 5 is -0.23, 0.72, -0.63, -0.03, 0.19, 0.03, -0.01.

[0018] Furthermore, the number n of parameters in the detail coefficient h in Step 6 is 7.

[0019] Furthermore, the fault criterion threshold value described in Step 8 Set to 50.

[0020] Beneficial effects of the present invention: In view of the fact that after a short-circuit fault occurs in the transmission line of a DC transmission system, the capacitors in the rectifier inverter discharge rapidly and the discharge amount is huge, which can cause serious consequences in a very short time. For example, the present invention utilizes the blocking effect of the smoothing reactors on both sides of the transmission line of the double-terminal flexible DC transmission system on the high-frequency components in the fault electrical quantity, making the high-frequency quantity comparison more obvious when there is a fault inside and outside the area, thereby improving the rapid response capability of the protection and the accuracy of fault identification. It is suitable for the transmission line fault protection of a long-distance DC transmission system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The topological structure diagram of the two-terminal flexible DC transmission system and possible fault areas.

[0022] Figure 2 The figure is a flow chart of a line fault identification method based on the sum of squares of the first-order differences of the pole line voltage and its high-frequency characteristics. DETAILED DESCRIPTION

[0023] The present invention will be further described below in conjunction with the accompanying drawings and specific examples. It will be appreciated by those skilled in the art that the following examples are only used to illustrate the present invention and should not be considered as limiting the scope of the present invention. In the examples, if no specific techniques or conditions are indicated, the techniques or conditions described in the literature in this area or the product specifications are used. If the manufacturer is not indicated for reagents or instruments used, they are all conventional products that can be purchased.

[0024] Example

[0025] like Figure 1 As shown, the double-terminal flexible power transmission system is composed of several traction lines, including 2 MMC sending ends and 2 MMC receiving ends; the double-terminal flexible direct current power transmission system transmission line fault identification method includes the following steps:

[0026] like Figure 2 As shown,

[0027] Step 1: Select the fault time window and use the monitoring device DTU to sample. After the fault occurs, the monitoring device DTU collects the positive and negative pole line voltages u1(k) and u2(k); where k is the kth sampling moment after the fault starts, and voltage sampling is performed once at each sampling moment;

[0028] Step 2: Perform Karenberg transformation on the positive pole line voltage u1(k) and the negative pole line voltage u2(k) to obtain the line modulus voltage um1 (k);

[0029] Specifically, the Karen Bell transformation is:

[0030]

[0031] Where u1(k) is substituted into u p , u2(k) is substituted into u n , we get u1, which is u m1 (k);

[0032] Step 3: u m1 (k) Take the difference and get the first-order difference du m1 (k) = u m1 (k)-u m1 (k-1);

[0033] Step 4: Construct the sum of squares of first-order differences:

[0034] ξ u1 (k) = ξ u1 (k-1)+[u1(k)-u1(k-1)] 2 (2)

[0035] It is assumed that the square of the first-order difference of every five pole line voltages is summed up once; where: is the sum of squares of the first-order differences of the pole-line voltages obtained from the kth to k-5th voltage sampling points after the fault occurs, where k′=k-4, k≥5; when k′=1, the expansion is:

[0036]

[0037] Step 5: According to the fault time window setting of 1ms and the sampling rate of the monitoring device DTU of 10kHz, determine the high-frequency detail coefficient h of the db4 wavelet first scale filter; the high-frequency detail coefficient h is: -0.23, 0.72, -0.63, -0.03, 0.19, 0.03, -0.01;

[0038] Step 6: Convert each u (k) is convolved with h, that is:

[0039]

[0040] Where: N is 5; D u (n) is the convolution result; n is the number of parameters in the detail coefficient h, n is 7;

[0041] Step 7: Construct the internal and external fault discrimination formula:

[0042]

[0043] And round it to get In the formula: Combined with the fault quantity time window and sampling rate, N1 is set to 6; For the 6 convolution results D u (n) The result of taking the average; For The result of rounding;

[0044] Step 8: Construct the fault judgment criteria inside and outside the area:

[0045] like If the fault is within the zone, the protection will be activated; This is an out-of-zone fault.

[0046] Fault judgment threshold Set to 50.

[0047] Application Example 1: When a ground fault occurs at each distance from the M end, under each transition resistance condition, obtain ξ according to the above steps u1 (k), specific Table 1:

[0048] Table 1

[0049]

[0050] Application Example 2: When an inter-pole fault occurs at each distance from the M end, ξ is obtained according to the above steps under various transition resistance conditions. u1 (k), as shown in Table 2:

[0051] Table 2

[0052]

[0053] Application Example 3: When a ground fault occurs outside the zone, the above steps are used to obtain ξ under various transition resistance conditions. u1 (k), as shown in Table 3:

[0054] Table 3

[0055]

[0056] Application Example 4: Application Examples 1, 2, and 3 are obtained according to the above steps. The details are shown in Table 4:

[0057] Table 4

[0058]

[0059] According to the results in the table of application examples 1-4, it can be seen that, with the smoothing reactor on the DC transmission line as the boundary, the present invention can accurately identify the faults inside and outside the zone of the DC transmission line.

[0060] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for identifying faults in a long-distance DC transmission line, characterized in that: The following steps are involved: Step 1: Select the fault time window and use the monitoring device DTU to sample. After the fault occurs, use the monitoring device to collect the positive pole line voltage u1(k) and the negative pole line voltage u2(k); where: k is the kth sampling time after the fault starts, and voltage sampling is performed once at each sampling time; Step 2: Perform Karenberg transformation on the positive pole line voltage u1(k) and the negative pole line voltage u2(k) to obtain the line modulus voltage u m1 (k); Step 3: Line modulus voltage u m1 (k) Take the difference and get the first-order difference du m1 (k) = u m1 (k)-u m1 (k-1); where k has the same meaning as in Step 1; Step 4 Construct the first-order difference sum of squares It is assumed that the square of the first-order difference of every five pole line voltages is summed up once; where: is the sum of squares of the first-order differences of the pole-line voltages obtained from the kth to k-5th voltage sampling points after the fault occurs, where k′=k-4, k≥5; when k′=1, the expansion is: Step 5: Determine the high-frequency detail coefficient h of the db4 wavelet first scale filter based on the fault time window set to 1ms and the DTU sampling rate of the monitoring device to 10kHz; Step6: Convolve with h: Where: N is 5; D u (n) is the convolution result; n is the number of parameters in the detail coefficient h; Step 7: Construct the internal and external fault discrimination formula: And round it to get In the formula: Combined with the fault quantity time window and sampling rate, N1 is set to 6; For the 6 convolution results D u (n) The result of taking the average; For The result of rounding; Step 8: If the fault judgment criteria inside and outside the construction area are: If the fault is within the zone, the protection will be activated; is an out-of-zone fault; where, is the fault judgment threshold.

2. The method for identifying long-distance DC transmission line faults according to claim 1, characterized in that: The fault time window described in Step 1 is set to 1ms, and the sampling rate of the monitoring device DTU is 10kHz.

3. The method for identifying a long-distance DC transmission line fault according to claim 1, characterized in that: The high-frequency detail coefficient h described in Step 5 is -0.23, 0.72, -0.63, -0.03, 0.19, 0.03, -0.

01.

4. The method for identifying long-distance DC transmission line faults according to claim 1, characterized in that: The number of parameters n in the detail coefficient h described in Step 6 is 7.

5. The method for identifying long-distance DC transmission line faults according to claim 1, characterized in that: The fault judgment threshold value described in Step 8 Set to 50.

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