Method and system for checking secondary circuit before operation of extra-high voltage transformer substation

Abstract

The invention belongs to the technical field of electric power signal detection, and particularly relates to a secondary circuit verification method and system before an extra-high voltage transformer substation is put into operation, and the method comprises the steps: constructing three groups of unrelated orthogonal fingerprint sequences, converting the orthogonal fingerprint sequences into voltage signals, and injecting the voltage signals into a three-phase sleeve at the primary side of the extra-high voltage transformer; collecting a current signal at a sampling rate higher than the frequency of the injection signal at a secondary loop side, and obtaining a real-time receiving sequence; calculating a sliding cross-correlation function between the real-time receiving sequence and a pre-stored fingerprint sequence by using a sliding window algorithm, extracting peak intensity and background noise statistical characteristics, and constructing a connection confidence index; and comparing the connection confidence coefficient index with a preset judgment threshold value to judge the wiring topology state of the secondary circuit. According to the invention, through orthogonal fingerprint coding and relevancy discrimination, the problems that phases of same-frequency signals cannot be distinguished and misjudgment is caused by long cable crosstalk are solved, and accurate verification of a secondary circuit is realized.

Description

Technical Field

[0001] This invention relates to the field of power signal detection technology. More specifically, this invention relates to a method and system for verifying the secondary circuits of an ultra-high voltage substation before commissioning. Background Technology

[0002] As the core hub of the power grid, the correctness of the secondary circuit wiring in ultra-high voltage (UHV) substations directly determines whether relay protection devices can accurately diagnose faults and execute actions. During the commissioning phase after project completion, it is essential to rigorously verify the circuit integrity between the primary equipment (current transformer) and the secondary equipment (protection and control cabinets). Currently, the industry commonly uses the load injection verification method, which involves injecting a small current (typically 5% to 10% of the rated current) into the primary side of the transformer or gas-insulated metal-enclosed switchgear bushing using a specialized testing device. The induced current is then measured on the secondary side to verify the circuit.

[0003] Currently, existing technologies typically use a single-frequency sine wave as the injection source, such as the 50Hz power frequency or a specific heterogeneous signal. Verification personnel mainly rely on handheld phase voltammeters to measure the amplitude and phase of the current on the secondary side, and judge whether the wiring is correct based on whether there is a current reading and the approximate range of the phase angle.

[0004] However, in the extremely complex electromagnetic environment of UHV substations, on the one hand, because the frequencies of the three-phase injected signals are often the same, when phase-to-phase misconnection or winding misconnection occurs, the secondary side can still detect current with normal amplitude, which can easily lead to the verification personnel misjudging that the wiring is correct, thus creating hidden dangers of protection devices malfunctioning or refusing to operate; on the other hand, the cables in the secondary cable trenches of UHV substations are laid long and densely, and long-distance parallel wiring will cause significant inter-line capacitive coupling effect, i.e., crosstalk. When the injected signal is weak, even circuits without actual physical connection may induce false voltage signals, making it difficult for verification personnel to distinguish whether it is a real physical connection or a false crosstalk signal, which seriously affects the efficiency and safety of the commissioning work. Summary of the Invention

[0005] To address the technical problems in the prior art, such as the inability to identify misconnections due to the use of a single frequency signal injection and the misjudgment of circuit continuity due to poor resistance to cable crosstalk, the present invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides a method for verifying the secondary circuit before commissioning of an ultra-high voltage substation, comprising: constructing three sets of mutually uncorrelated orthogonal fingerprint sequences, converting them into voltage signals and injecting them into the three-phase bushings on the primary side of the ultra-high voltage transformer; acquiring current signals on the secondary circuit side at a sampling rate higher than the frequency of the injected signals to obtain a real-time received sequence; calculating the sliding cross-correlation function between the real-time received sequence and the pre-stored orthogonal fingerprint sequences using a sliding window algorithm, extracting the peak intensity and background noise statistical characteristics in the sliding cross-correlation function curve, constructing a connection confidence index based on the peak intensity and background noise statistical characteristics; comparing the calculated connection confidence index with a preset judgment threshold, and determining the wiring topology status of the secondary circuit based on the comparison result.

[0007] This invention introduces orthogonal fingerprint coding technology to distinguish the characteristics of three-phase signals at the source. Even in the case of mixed or misconnected signals, it can accurately identify the source of the signal through cross-correlation analysis, effectively solving the problem of phase confusion caused by signals of the same frequency.

[0008] Preferably, the construction of three sets of uncorrelated orthogonal fingerprint sequences includes: generating three reference sequences using a maximum length sequence generator; and modulating the reference sequences onto a non-power frequency carrier frequency using binary phase shift keying to obtain three-phase orthogonal fingerprint sequences.

[0009] By using binary phase shift keying to modulate the reference sequence onto a non-power frequency carrier frequency, interference from power frequency and its harmonics can be effectively avoided. At the same time, combined with the autocorrelation characteristics of the maximum length sequence, the sensitivity of signal recognition is improved.

[0010] Preferably, the sliding cross-correlation function satisfies the following relationship: ;in, To receive the signal and the A-phase fingerprint during the sliding delay The cross-correlation value at the location, The length of the integration window and The length of the orthogonal fingerprint sequence is greater than or equal to that of the fingerprint sequence. This is the discrete sequence of real-time secondary current acquired. For the pre-stored standard A-phase fingerprint sequence, For sequence indexes.

[0011] By using the sliding cross-correlation function as a matched filter, weak fingerprint feature signals can be extracted from a strong noise background, achieving highly sensitive signal detection.

[0012] Preferably, the value of the integration window length covers at least one complete orthogonal fingerprint sequence period.

[0013] Preferably, the extraction of peak intensity and background noise statistical features from the sliding cross-correlation function curve includes: searching for the maximum absolute value in the sliding cross-correlation function curve as the peak intensity; removing the data in the region where the peak intensity is located, and calculating the arithmetic mean and standard deviation of the remaining region data as the mean and standard deviation of the background noise, respectively.

[0014] By analyzing the noise floor characteristics of the statistical cross-correlation curve, a data foundation is provided for distinguishing between real signals and random crosstalk.

[0015] Preferably, the step of removing data from the region where the peak intensity is located includes: obtaining the total length of the data in the sliding cross-correlation function curve and setting a scaling factor for the removal window; locating the time index of the peak intensity in the sliding cross-correlation function curve, and determining the start and end points of the removal window based on the scaling factor and using the time index as the center; removing the data segment in the sliding cross-correlation function curve located between the start and end points, and retaining the remaining data in the sliding cross-correlation function curve as background noise analysis samples.

[0016] Preferably, the connection confidence index satisfies the following relationship: ;in, To connect the confidence index, The maximum peak intensity in the sliding cross-correlation function curve. The mean of the background noise. The standard deviation of background noise. Based on the stability constant, It is the natural logarithm function.

[0017] By constructing a connection confidence index and introducing a noise penalty mechanism, the index will be significantly reduced when there is strong random crosstalk causing large fluctuations in the noise floor, thereby effectively eliminating false conduction signals.

[0018] Preferably, the step of comparing the calculated connection confidence index with a preset judgment threshold and determining the wiring topology of the secondary circuit based on the comparison result includes: calculating the connection confidence index of the received signal for the three-phase orthogonal fingerprint sequence respectively; if the connection confidence index for a certain phase fingerprint sequence is greater than the judgment threshold, and the connection confidence index for the other two phase fingerprint sequences is much less than the judgment threshold, then the phase wiring is determined to be correct; if the connection confidence index for the other phase fingerprint sequences measured at a certain phase terminal is greater than the judgment threshold, then it is determined to be a phase misconnection.

[0019] Preferably, the step of determining the wiring topology of the secondary circuit based on the comparison results further includes: if all calculated connection confidence indices are less than the determination threshold, then the circuit is determined to be unconnected or only has crosstalk signals.

[0020] Secondly, the present invention provides a secondary circuit verification system for UHV substations before commissioning, comprising a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the aforementioned method for verifying secondary circuits before commissioning UHV substations is implemented.

[0021] By adopting the above technical solution, a computer program is generated for the above-mentioned method of verifying the secondary circuit before the commissioning of an ultra-high voltage substation, and stored in a memory so that it can be loaded and executed by a processor. Terminal equipment can then be made based on the memory and processor for convenient use.

[0022] This invention achieves effective fingerprint-level identification of secondary loop topology through orthogonal fingerprint coding injection and correlation discrimination. It breaks through the bottleneck of traditional sine wave injection method in distinguishing the source of signals of the same frequency by using orthogonal coding technology. Even if complex phase-to-phase short circuits or cross-connections occur, the error type can be accurately reported by the unique attribution of the correlation peak.

[0023] Furthermore, by constructing a connection confidence index, combining signal strength with noise statistical distribution, it is possible to automatically filter out inductive crosstalk signals that do not have fingerprint characteristics and are accompanied by high-frequency random fluctuations, so that the verification work can still maintain extremely high accuracy in an environment without power and with strong interference. Attached Figure Description

[0024] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the invention are illustrated by way of example and not limitation, and like or corresponding reference numerals denote like or corresponding parts, wherein: Figure 1 This is a flowchart illustrating a secondary circuit verification method for an ultra-high voltage substation before commissioning, according to the present invention. Figure 2 It is a schematic diagram illustrating the comparison of signal characteristics under complex on-site working conditions; Figure 3 This is a schematic diagram illustrating fingerprint demodulation analysis based on the cross-correlation algorithm; Figure 4 This diagram schematically illustrates a comparison of the anti-crosstalk capabilities of the present invention and existing technologies. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0027] This invention discloses a method for verifying the secondary circuits of an ultra-high voltage substation before commissioning, referring to... Figure 1 This includes steps S1-S4: S1. Construct three sets of uncorrelated orthogonal fingerprint sequences, convert them into voltage signals, and inject them into the three-phase bushings on the primary side of the UHV transformer.

[0028] In an optional embodiment, to ensure that the three-phase signals A, B, and C do not interfere with each other logically, an excitation source with a unique identifier can be generated, and three sets of uncorrelated pseudo-random sequences can be generated using a digital signal processor or a field-programmable gate array.

[0029] In this optional embodiment, to ensure the orthogonality of the sequences, the baseband sampling length of the injected signal is set to... Construct orthogonal fingerprint sequences of phases A, B, and C. , , These sequences must satisfy the orthogonality constraint, meaning that their own autocorrelation function has a sharp peak at zero time delay, while the cross-correlation function between them approaches zero at any time delay.

[0030] Specifically, three reference sequences are generated using a 1023-bit m-sequence generator (the maximum length sequence generator), and then modulated onto a 200Hz carrier using binary phase shift keying (BPSK). The 200Hz carrier frequency was chosen to effectively avoid interference from the 50Hz power frequency and its harmonics.

[0031] Next, the generated three sets of digital sequences are converted into continuous voltage signals by a high-precision digital-to-analog converter, and then driven by a power amplifier, injected into phases A, B, and C of the primary side of the high-voltage bushing of the UHV transformer. At this point, the current flowing through the primary circuit is no longer an ordinary sine wave, but a fingerprint current carrying specific identification information.

[0032] In this way, by constructing and injecting orthogonal fingerprint sequences, each phase circuit can be given a unique electronic tag, thereby distinguishing signals of different phases at the source and avoiding the problem that traditional signals of the same frequency cannot distinguish their source.

[0033] S2. Acquire the current signal on the secondary circuit side at a sampling rate higher than the injected signal frequency to obtain the real-time received sequence.

[0034] In an optional embodiment, to extract weak fingerprint features from the high-noise, high-interference environment of the secondary side, a portable high-frequency acquisition unit can be used to read the secondary circuit current signal at the terminal block of the relay protection room cabinet. To ensure signal integrity and the accuracy of subsequent processing, the sampling frequency can be set to at least 10 times the injected carrier frequency, for example, 5kHz, to obtain the real-time received sequence. .

[0035] like Figure 2 As shown in the figure, the signal characteristics comparison diagram under complex on-site conditions is schematically illustrated. It can be seen that the sub-figure (a) shows the primary side injection fingerprint sequence, and the waveform is a standard positive and negative level encoding with clear BPSK modulation characteristics. The sub-figure (b) shows the secondary side field acquisition waveform. It can be seen that the originally clear injection signal is completely submerged in the large background noise and power frequency interference sine wave after being transmitted by UHV equipment and interfered with by the on-site environment. This comparison shows the reason why the existing technology that relies solely on amplitude detection fails.

[0036] In this way, high-frequency synchronous acquisition can completely record the mixed signals in the secondary circuit, providing the original data foundation for subsequent extraction of effective fingerprint features using digital signal processing technology.

[0037] S3. Calculate the sliding cross-correlation function between the real-time received sequence and the pre-stored orthogonal fingerprint sequence using the sliding window algorithm, extract the peak intensity and background noise statistical characteristics in the sliding cross-correlation function curve, and construct the connection confidence index based on the peak intensity and background noise statistical characteristics.

[0038] In an optional embodiment, to determine whether the signal received on the secondary side originates from a specific primary phase, such as phase A, a sliding window algorithm can be used to calculate the received signal. With the pre-stored A-phase fingerprint The cross-correlation matching degree between them, the sliding cross-correlation function satisfies the following relationship:

[0039] in, To receive the signal and the A-phase fingerprint during the sliding delay The cross-correlation value at each point is used to characterize the degree of matching; The length of the integration window and The length of N should be greater than or equal to the length of the orthogonal fingerprint sequence; therefore, the value of N should cover at least one complete fingerprint sequence period. This is the discrete sequence of real-time secondary current acquired. For the pre-stored standard A-phase fingerprint sequence, is the sequence index; k is the sliding time offset used to search for the best alignment point in the time domain.

[0040] Specifically, the sliding cross-correlation function is essentially a matched filter. When the received signal contains the true A-phase fingerprint and is time-aligned, the product terms accumulate in the same direction, making... A significant positive peak appears; if the received signal is a B-phase signal or pure background noise, the positive and negative terms of the product cancel each other out, and the result approaches 0.

[0041] For example, let the integration window length be... The simplified sequence received at a certain moment for Pre-stored A-phase fingerprint sequence Also for Then the cross-correlation value is calculated as follows: If the received sequence is a B-phase orthogonal sequence, such as Then the cross-correlation value is: It approaches 0.

[0042] Furthermore, for cable crosstalk issues, a normalized confidence index can be constructed, and the authenticity of the connection can be determined by comparing the peak signal intensity with background noise fluctuations. Specifically, firstly, waveform statistical features are extracted, and then the cross-correlation curve is calculated. In the middle, perform a global search to find the maximum absolute value of the curve, denoted as . Next, the region containing the peak is removed, for example, a 5% window before and after the peak. The arithmetic mean and standard deviation of the remaining region, i.e., the noise base region, are calculated, and the confidence index is connected to satisfy the following relationship:

[0043] in, The connection confidence index is a dimensionless positive real number. The larger the value, the more reliable the current physical connection. The maximum peak intensity in the sliding cross-correlation function curve. This represents the average background noise, reflecting either background DC bias or constant interference. The standard deviation of background noise reflects the severity of fluctuations in environmental electromagnetic noise and crosstalk signals. It is the basic stability constant, and its function is to prevent the calculation overflow caused by the denominator being 0 in an extremely pure environment. For example, it can be taken as 0.001. It is the natural logarithm function.

[0044] like Figure 3As shown in the figure, the fingerprint demodulation analysis diagram based on the cross-correlation algorithm is illustrated. It can be seen that after the original chaotic signal is cross-correlation calculated, the uncorrelated background noise is effectively suppressed to the vicinity of the zero axis, and an extremely high and sharp asterisk mark appears at a specific time alignment point, which is the fingerprint matching feature peak.

[0045] In this way, by calculating the cross-correlation function and constructing the connection confidence index, the real physical connection signal can be separated from strong background noise and spurious crosstalk signals, thus achieving an accurate assessment of connection reliability.

[0046] S4. Compare the calculated connection confidence index with the preset judgment threshold, and determine the wiring topology status of the secondary circuit based on the comparison result.

[0047] In an optional embodiment, the system automatically traverses three sets of orthogonal fingerprint sequences, calculates the connection confidence index corresponding to each set, and pre-sets a judgment threshold. For example, the threshold for judgment is 10.

[0048] Furthermore, if measured and , All are much smaller than If the connection is correct, then the wiring of phase A is determined to be correct; if the connection is measured at the terminal of phase A... If all The values ​​are all less than ,even though There are some readings, but the large fluctuations in the background noise cause... If the value is low, it is determined to be either not connected or only crosstalk exists.

[0049] like Figure 4 The diagram illustrates a comparison of the anti-crosstalk capabilities of the present invention and existing technologies. It can be seen that in the last five crosstalk samples, the measured values ​​of the existing technology are still relatively high, making it easy to misjudge as a connection. In contrast, the fingerprint confidence index of the present invention exhibits a binary step characteristic, with an extremely high index in the real connection region and a rapid drop to zero in the crosstalk interference region.

[0050] In this way, by setting reasonable thresholds and combining them with logical judgments, it is possible to accurately identify various complex loop states such as correct wiring, incorrect wiring, and false crosstalk, effectively avoiding misjudgments and ensuring the accuracy of the verification results.

[0051] This invention also discloses a secondary circuit verification system for UHV substations before commissioning, comprising a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a secondary circuit verification method for UHV substations before commissioning according to the present invention.

[0052] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0053] In the description of this specification, "multiple" or "several" means at least two, such as two, three or more, unless otherwise expressly and specifically defined.

[0054] While this specification has shown and described numerous embodiments of the invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in the practice of this invention.

Claims

1. A method for verifying the secondary circuits of an ultra-high voltage substation before commissioning, characterized in that, include: Three sets of uncorrelated orthogonal fingerprint sequences were constructed, converted into voltage signals, and injected into the three-phase bushings on the primary side of the UHV transformer, respectively. The current signal is acquired at a sampling rate higher than the injected signal frequency on the secondary circuit side to obtain the real-time received sequence; The sliding window algorithm is used to calculate the sliding cross-correlation function between the real-time received sequence and the pre-stored orthogonal fingerprint sequence. The peak intensity and background noise statistical features in the sliding cross-correlation function curve are extracted, and the connection confidence index is constructed based on the peak intensity and background noise statistical features. The calculated connection confidence index is compared with a preset judgment threshold, and the wiring topology of the secondary circuit is determined based on the comparison result.

2. The method for verifying the secondary circuit of an ultra-high voltage substation before commissioning, as described in claim 1, is characterized in that... The construction of three sets of mutually uncorrelated orthogonal fingerprint sequences includes: Three baseline sequences are generated using a maximum length sequence generator; The reference sequence is modulated onto a non-power frequency carrier frequency using binary phase shift keying to obtain a three-phase orthogonal fingerprint sequence.

3. The method for verifying the secondary circuit of an ultra-high voltage substation before commissioning, as described in claim 1, is characterized in that... The sliding cross-correlation function satisfies the following relationship: in, To receive the signal and the A-phase fingerprint during the sliding delay The cross-correlation value at the location, The length of the integration window and The length of the orthogonal fingerprint sequence is greater than or equal to that of the fingerprint sequence. This is the discrete sequence of real-time secondary current acquired. For the pre-stored standard A-phase fingerprint sequence, For sequence indexes.

4. The method for verifying the secondary circuit of an ultra-high voltage substation before commissioning, as described in claim 3, is characterized in that... The value of the integration window length covers at least one complete orthogonal fingerprint sequence cycle.

5. The method for verifying the secondary circuit of an ultra-high voltage substation before commissioning, as described in claim 3, is characterized in that... The extraction of peak intensity and background noise statistical features from the sliding cross-correlation function curve includes: The maximum absolute value in the sliding cross-correlation function curve is used as the peak intensity. Data in the region where the peak intensity is located is removed, and the arithmetic mean and standard deviation of the remaining data are calculated, which are used as the mean and standard deviation of the background noise, respectively.

6. The method for verifying the secondary circuit of an ultra-high voltage substation before commissioning, as described in claim 5, is characterized in that... The data removed from the region containing the peak intensity includes: Obtain the total length of the sliding cross-correlation function curve and set the scaling factor for the rejection window; Locate the time index of the peak intensity in the sliding cross-correlation function curve, and determine the start and end points of the elimination window based on the scaling factor, using the time index as the center. Remove the data segment between the starting point and the ending point in the sliding cross-correlation function curve, and retain the remaining data in the sliding cross-correlation function curve as background noise analysis samples.

7. The method for verifying the secondary circuit of an ultra-high voltage substation before commissioning, as described in claim 1, is characterized in that... The connection confidence index satisfies the following relationship: in, To connect the confidence index, The maximum peak intensity in the sliding cross-correlation function curve. The mean of the background noise. The standard deviation of background noise. Based on the stability constant, It is the natural logarithm function.

8. The method for verifying the secondary circuit of an ultra-high voltage substation before commissioning, as described in claim 1, is characterized in that... The step of comparing the calculated connection confidence index with a preset judgment threshold and determining the wiring topology of the secondary circuit based on the comparison result includes: Calculate the connection confidence index of the received signal for the three-phase orthogonal fingerprint sequence respectively; If the connection confidence index for a certain phase fingerprint sequence is greater than the judgment threshold, and the connection confidence index for the other two phase fingerprint sequences is much less than the judgment threshold, then the connection of that phase is determined to be correct. If the connection confidence index for fingerprint sequences of other phases measured at a certain phase terminal is greater than the judgment threshold, it is judged as a phase misconnection.

9. The method for verifying the secondary circuit of an ultra-high voltage substation before commissioning, as described in claim 1, is characterized in that... The step of determining the wiring topology of the secondary circuit based on the comparison results also includes: if all calculated connection confidence indices are less than the determination threshold, then the circuit is determined to be unconnected or only has crosstalk signals.

10. A secondary circuit verification system for ultra-high voltage substations before commissioning, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions, which, when executed by the processor, implement a secondary circuit verification method for an ultra-high voltage substation before commissioning, as described in any one of claims 1-9.

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