Interphase fault identification method, system and device based on transient quantity of power transmission line

Abstract

The application discloses a kind of interphase fault identification method, system and equipment based on transmission line transient quantity, it is related to fault identification method field.The traditional power frequency quantity protection faces the problem of cannot correctly act;The present application comprises the following steps: by db10 wavelet to differential current wavelet packet 3 layer decomposition, obtain eight frequency bands;The sampling point data of each frequency band is respectively squared, to obtain each sampling point energy value under each frequency band;For each time, the sampling point energy value located in the data window of current time before is accumulated, as the energy value of this time, obtain eight energy sequences of corresponding frequency band;The energy value of last four energy sequences is multiplied, to obtain energy cumulative value;When energy cumulative value is greater than set value, then judge as internal fault.The technical scheme of the present application combines the information of the last four higher frequency energy sequences, increases the threshold value of distinguishing normal condition and fault condition, thereby improves the accuracy and reliability of fault identification.

Description

Technical Field

[0001] This invention relates to the field of fault identification methods, and more particularly to a method, system and equipment for phase-to-phase fault identification based on transient quantities of transmission lines. Background Technology

[0002] As the first line of defense for ensuring the safe operation of the power grid, relay protection currently relies mainly on power frequency electrical quantities to identify faults in practical engineering applications. However, with the widespread application of power electronic equipment, power system faults exhibit more complex fault characteristics and develop more rapidly. This reduces the speed and reliability of traditional power frequency quantity protection, leading to problems with its inability to operate correctly. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the objective of this invention is to provide a rapid phase-to-phase fault identification method based on transient quantities of transmission lines, so as to achieve rapid and reliable operation of line protection devices.

[0004] To achieve the above objectives, the first technical solution of the present invention is as follows:

[0005] A fast phase-to-phase fault identification method based on transient quantities of transmission lines includes the following steps:

[0006] Monitoring faults; when a fault occurs, the connection topology information of the line fault point is obtained, and the protection devices on both sides of the fault point are determined based on the connection topology information, and the phase current information of the installation location of the protection devices on both sides of the fault point is obtained.

[0007] The obtained phase current information is transformed into mode current information by phase-mode conversion.

[0008] Calculate the differential current based on the modal current information at the installation locations of the protection devices on both sides;

[0009] The differential current is decomposed into three layers of wavelet packets using the db10 wavelet, and then divided into eight frequency bands with progressively increasing frequencies.

[0010] The sampling data of each frequency band is squared to obtain the energy value of each sampling point in each frequency band;

[0011] For each time moment, the energy values ​​of the sampling points located in the data window preceding the current time moment are accumulated and used as the energy value at that time moment, resulting in eight energy sequences for the corresponding frequency band;

[0012] Multiply the energy values ​​of the last four energy sequences to obtain the cumulative energy value;

[0013] When the accumulated energy value exceeds the set value, it is determined to be a fault within the zone, and the protection device will activate; otherwise, the protection device will not activate.

[0014] This technical solution utilizes the fact that after a fault occurs within the zone, the fault current of this line will generate a high-frequency component, but the high-frequency component content of this line is relatively small when a fault occurs outside the zone. Furthermore, the high-frequency component of the fault current is not affected by the system operation mode, power frequency oscillation, etc., and is only related to the fault location. This constitutes transient quantity protection, which can identify phase-to-phase short-circuit faults (excluding single-phase ground faults) more quickly and accurately.

[0015] This technical solution, based on the transient quantities of transmission lines, can quickly acquire line connection topology information and phase current information at the installation location of protection devices after a fault occurs. It then performs differential current calculations and wavelet packet decomposition to achieve rapid fault identification and judgment. By decomposing the differential current wavelet packets and calculating energy, it extracts feature information from different frequency bands in the fault signal and determines the fault type and region based on the accumulated energy value, exhibiting high identification accuracy and efficiency. Furthermore, this technical solution only requires processing and calculating information from the protection devices on both sides of the fault point. Compared to other fault detection methods with complex data acquisition and processing requirements, it is lower in cost and easier to implement and promote. By multiplying the energy values ​​of the last four energy sequences to obtain the accumulated energy value, which effectively combines the information from the last four higher-frequency energy sequences, it increases the threshold for distinguishing between normal and fault conditions, thereby improving the accuracy and reliability of fault identification.

[0016] After a fault occurs, the traveling wave originates from the fault point and propagates to both sides of the line. At the busbar, it is attenuated due to factors such as busbar-to-ground capacitance. The higher the frequency of the traveling wave, the more significant the attenuation at the line boundary (i.e., the busbar). Lower frequency traveling waves show little attenuation. Therefore, for faults outside the fault zone, most of the high-frequency components are attenuated at the busbar; for faults within the fault zone, more high-frequency components can be detected. Since the high-frequency component content differs significantly between faults inside and outside the fault zone, this technical solution uses only the high-frequency component for fault analysis, reducing computational load and, to some extent, avoiding the influence of low-frequency interference, thus improving the clarity and accuracy of fault characteristics.

[0017] While examining a single frequency band can distinguish between faults inside and outside the fault zone, it doesn't fully utilize information from other high-frequency bands. Since any single high-frequency band can differentiate faults inside and outside the fault zone, multiplying the data from four frequency bands amplifies this distinction, making the results more reliable and the data more fully utilized. Therefore, this technical solution uses the cumulative multiplication of four high-frequency bands for fault diagnosis. This solution effectively narrows down the possible location range of faults and improves the accuracy of fault diagnosis. Furthermore, this method has a certain degree of anti-interference capability because different frequency bands correspond to different fault types. Combining data from multiple frequency bands can supplement each other's information to a certain extent, avoiding the problem of missed detections and misjudgments caused by a single feature failing to fully represent the fault. This is mainly because in the high-frequency range, the noise generated by power system operation is relatively large. Using the energy value of each frequency band alone as a fault feature is subject to a lot of interference, making it difficult to accurately reflect the line status. Therefore, by multiplying the energy of the last four frequency bands, fault signals and noise signals can be better distinguished, improving the accuracy of fault identification; increasing the difference leads to more accurate fault identification.

[0018] As a preferred technical approach, the obtained phase current information is transformed into mode current information using a phase-mode transformation, and the formula used is:

[0019]

[0020] In the formula, This is the modulus current of the first relay protection device; For the first relay protection device terminal a

[0021] Phase-mode current; The phase b current at the terminal of the first relay protection device; The c-phase mode current at the terminal of the first relay protection device; This refers to the modulus current of the second relay protection device; The phase-mode current at the second relay protection device terminal; This refers to the phase b current at the second relay protection device terminal. This refers to the c-phase mode current at the second relay protection device terminal.

[0022] As a preferred technical approach: the differential current is calculated based on the modal current information at the installation locations of the protection devices on both sides, using the following formula:

[0023]

[0024] in, This is the differential current.

[0025] As a preferred technical means, the frequencies of the eight frequency bands are 0-12.5kHz, 12.5-25kHz, 25-37.5kHz, 37.5-50kHz, 50-62.5kHz, 62.5-75kHz, 75-87.5kHz, and 87.5-100kHz.

[0026] This technical solution selects a lower observation frequency band to weaken the transmission impact, and the sampling frequency can be selected twice that frequency, which can avoid aliasing during sampling.

[0027] As a preferred technical approach, a sampling frequency of 200kHz is selected, meaning there is a sampling point every 5μs. By accumulating over a time window, the difference in high-frequency signal energy between the inside and outside of the fault zone is amplified.

[0028] As a preferred technique, the length of the data window is the length of 400 sampling points, i.e., 2ms.

[0029] As a preferred technical means: the frequency bands corresponding to the last four energy sequences are: 50-62.5kHz, 62.5-75kHz, 75-87.5kHz, and 87.5-100kHz. As a preferred technical means: the set value is Ed.set, where Ed.set = 1 × 10 -6 .

[0030] The second objective of this invention is to provide a protection system based on differential current low-frequency band fault identification, so as to achieve rapid and reliable operation of the line protection device;

[0031] To achieve the above objectives, the second technical solution of the present invention is as follows:

[0032] A fast phase-to-phase fault identification system based on transient quantities of transmission lines, the system comprising:

[0033] Fault monitoring module: When a fault occurs, it is used to obtain the connection topology information of the line fault point, determine the protection devices on both sides of the fault point based on the connection topology information, and obtain the phase current information of the installation location of the protection devices on both sides of the fault point.

[0034] Phase-mode conversion module: Connected to the fault monitoring module, it is used to perform phase-mode conversion on the obtained phase current information to obtain mode current information;

[0035] Differential current calculation module: connected to the phase mode conversion module, used to calculate the differential current based on the mode current information at the installation points of the protection devices on both sides;

[0036] Differential current decomposition module: connected to the differential current calculation module, used to perform wavelet packet 3-level decomposition on the differential current using db10 wavelet, dividing it into eight frequency bands with progressively increasing frequencies;

[0037] Energy value calculation module: connected to the differential current decomposition module, used to square the sampling point data of each frequency band to obtain the energy value of each sampling point in each frequency band;

[0038] Energy sequence energy value calculation module: connected to the energy value calculation module, used for energy sequence energy value calculation. For each time moment, the energy values ​​of the sampling points located in the previous data window of the current time moment are accumulated and used as the energy value of that time moment, to obtain the energy values ​​of the eight energy sequences of the corresponding frequency band;

[0039] Energy accumulation value calculation module: Connected to the energy sequence energy value calculation module, it is used to multiply the energy values ​​of the last four energy sequences to obtain the energy accumulation value;

[0040] Fault identification module: Connected to the energy accumulation value calculation module, it is used to determine whether the energy accumulation value is greater than the set value. When the energy accumulation value is greater than the set value, it is determined to be a fault within the zone, and the protection device will operate; otherwise, the protection will not operate.

[0041] This system employs wavelet analysis and other techniques to process and decompose differential current, enabling more accurate extraction of feature information from fault signals. High-precision fault identification is achieved through energy calculation and cumulative value judgment. It can rapidly obtain fault information and perform diagnosis after a fault occurs, thus enabling fast and timely operation of protection devices and minimizing losses caused by faults. Based on traditional transmission line transient quantity detection technology, this system incorporates multi-level and multi-angle analysis and calculation methods, effectively avoiding interference and misjudgment. It can perform online monitoring and detection of transmission lines around the clock, automatically detecting and diagnosing fault signals caused by short-term changes and long-term drift. Without compromising signal processing accuracy, it achieves high data processing efficiency and fast computing speed through efficient algorithms and calculation modes, making it suitable for various large-scale datasets and real-time data stream analysis.

[0042] By performing multi-dimensional and multi-faceted time-domain and frequency-domain analysis on fault signals, effective feature information is extracted while noise and interference signals are filtered out. Phase-mode transformation converts the three-phase AC signal into positive-sequence, negative-sequence, and zero-sequence components, enabling more accurate detection of fault type and location. Wavelet analysis is used to decompose and reconstruct the fault signal, obtaining information on its high and low frequency components, as well as the time-domain and frequency-domain relationships between various frequency bands. The energy value of each frequency band at each moment is calculated, and the magnitude of the energy value is related to the nature and location of the fault. The energy is calculated using the decomposed multi-level wavelet coefficients, thereby improving the accuracy of fault detection. These analytical and computational methods are complementary and synergistic, enabling faster and more accurate diagnosis of fault location and type through comprehensive judgment of information from different aspects. These methods work together to form a complete and efficient fault identification system, providing fault diagnosis methods from multiple perspectives and with diverse approaches to adapt to complex power system environments and operating conditions.

[0043] The third objective of this invention is to provide a device that achieves rapid and reliable operation of the line protection device.

[0044] To achieve the above objectives, the third technical solution of the present invention is as follows:

[0045] A device includes one or more processors and one or more memories, wherein the one or more memories store at least one piece of program code, which, when executed by the one or more processors, implements the above-described method for rapid phase-to-phase fault identification based on transient quantities of transmission lines.

[0046] Beneficial effects: This technical solution enables rapid identification of phase-to-phase short-circuit faults, unaffected by system operating mode and power frequency oscillations, and has no dead zones within the protection zone, unaffected by fault location, thus improving protection reliability.

[0047] When a phase-to-phase short-circuit fault occurs, the signals on the line are often interfered with or masked, affecting fault detection and diagnosis. This technical solution employs multiple signal analysis methods, comprehensively considering various characteristic information, effectively avoiding interference from system operating modes and power frequency oscillations on fault detection. By using signal data from multiple test points, coupled with continuous monitoring and online processing of the data, the detection range can be guaranteed to cover the entire power system area, thereby eliminating dead zone effects, reducing false positive rates, and improving fault diagnosis accuracy. Multiple fault type and fault location detection methods are employed, some of which can achieve functions such as area protection that traditional single-point and distance protection cannot, without requiring precise fault location information, avoiding problems such as fault judgment errors and delayed processing due to insufficient accuracy. Therefore, this technical solution has higher protection reliability and good applicability. Attached Figure Description

[0048] Figure 1 This is a diagram of a line fault.

[0049] Figure 2 This is a schematic diagram of the faults in each frequency band within the area.

[0050] Figure 3 This is a schematic diagram of each frequency band for faults outside the zone.

[0051] Figure 4 This is a flowchart of the present invention.

[0052] Figure 5 This is a diagram showing the results of using this method to determine faults inside and outside the fault zone according to the present invention. Detailed Implementation

[0053] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings.

[0054] like Figure 4 As shown, the present invention includes the following steps:

[0055] S1: Fault monitoring; When a fault occurs, obtain the connection topology information of the line fault point, and determine the protection devices on both sides of the fault point based on the connection topology information, and obtain the phase current information at the installation location of the protection devices on both sides of the fault point.

[0056] S2: Perform phase-mode transformation on the obtained phase current information to obtain mode current information; calculate the differential current based on the mode current information at the installation locations of the protection devices on both sides;

[0057] S3: The differential current is decomposed into three layers of wavelet packets using the db10 wavelet, and then divided into eight frequency bands with progressively increasing frequencies. The sampling point data of each frequency band is squared to obtain the energy value of each sampling point in each frequency band. For each time moment, the energy values ​​of the sampling points located in the previous data window are accumulated to obtain the energy value of that time moment, thus obtaining the eight energy sequences of the corresponding frequency band, Ed1, Ed2, ... Ed8.

[0058] S4: Multiply the energy values ​​Ed5-Ed8 of the last four energy sequences to obtain the cumulative energy value, i.e., Ed = Ed5 × Ed6 × Ed7 × Ed8;

[0059] S5: Determine if the accumulated energy value is greater than the set value, Ed>Ed se t; When the accumulated energy value is greater than the set value, proceed to step S6; otherwise, proceed to step S7.

[0060] S6: The fault is determined to be within the zone, and the protection device activates.

[0061] S7: If the fault is determined to be outside the zone or due to system oscillation, the protection device will not operate.

[0062] The following will provide further explanation with specific examples.

[0063] like Figure 1 The diagram shown is a schematic of a line fault in this specific example.

[0064] When a fault occurs at a certain point in the system, this technical solution will quickly determine whether it is an intra-zone fault based on the fault information identified by the relay protection at both ends of the line, providing a basis for rapid fault isolation.

[0065] Assuming a fault occurs at point f1 on a certain line, the phase mode of the three-phase current at protection points M and N is transformed, i.e.

[0066]

[0067] The differential current is formed by utilizing the modulus current at the two protective mounting points, i.e.

[0068]

[0069] Wavelet functions need to have good frequency domain characteristics to reduce spectral leakage and aliasing. The dbN series wavelets meet this requirement due to their wide applicability. As N increases, the time domain support becomes longer, and the temporal locality deteriorates. Studies have shown that when the value of N increases to 10, the frequency division capability is similar to that of db10. Therefore, this method uses the db10 wavelet to process the signal.

[0070] By using the db10 wavelet to perform three-level wavelet packet decomposition and reconstruction on the differential current, the original current waveform can be decomposed into eight frequency bands. Let d1, d2, ..., d8 be the eight frequency bands obtained, with the corresponding frequencies increasing sequentially.

[0071] To minimize the impact of line transmission and highlight the role of line boundaries, the observation frequency band was selected to be below 100kHz, hence the sampling frequency was chosen to be 200kHz. Therefore, the resulting eight frequency bands, from low to high, are 0-12.5kHz, 12.5-25kHz, 25-37.5kHz, 37.5-50kHz, 50-62.5kHz, 62.5-75kHz, 75-87.5kHz, and 87.5-100kHz (i.e., the frequencies corresponding to bands d1, d2, ..., d8).

[0072] Will After decomposing and reconstructing the data into eight frequency bands, the energy value of each frequency band is calculated by squaring the sampled data of each frequency band.

[0073] After a phase-to-phase short-circuit fault occurs on the line, high-frequency components (50-100kHz) can be detected in the modal current. The content of these high-frequency components is mainly affected by the bus-to-ground capacitance. After being projected and reflected by the bus, the high-frequency component content of this line is higher, while the high-frequency component content of lines outside the area is lower. According to the simulation results, there is a difference of two orders of magnitude.

[0074] like Figure 2 , Figure 3 The above figures, from top to bottom, show the time-domain waveforms and energy diagrams of the d1-d8 frequency bands, respectively, for faults within and outside the zone.

[0075] Therefore, the difference in the high-frequency content between faults inside and outside the fault zone can be used to distinguish between faults inside and outside the zone.

[0076] For a sampling frequency of 200kHz, a sampling point is taken every 5μs, and the data window length is set to the length of 400 sampling points, i.e., 2ms. For each frequency band, the total energy within the data window is calculated, resulting in the sequence Ed1, Ed2, ..., Ed8. By accumulating the data within the time window, the difference in high-frequency energy between faults inside and outside the fault zone can be amplified. Depending on the actual situation, the length of the time window can also be changed; here, 2ms is used as an example.

[0077] Since the energy levels in the d5-d8 frequency bands (50-62.5kHz, 62.5-75kHz, 75-87.5kHz, 87.5-100kHz) are significantly different when there is a fault inside or outside the zone, Ed5, Ed6, Ed7, and Ed8 can be multiplied together to distinguish between faults inside and outside the zone.

[0078] like Figure 5The Ed result is obtained from simulations of faults inside and outside the zone. Let Ed.set = 1 × 10 -6 Obviously, there is a significant difference between faults inside and outside the zone. The protection operates reliably and can quickly identify faults after they occur (the fault occurs at t=4000, and every 4000 data points on the horizontal axis corresponds to one cycle, or 20ms).

[0079] Correspondingly, a fast phase-to-phase fault identification system based on transmission line transients includes:

[0080] Fault monitoring module: When a fault occurs, it is used to obtain the connection topology information of the line fault point, determine the protection devices on both sides of the fault point based on the connection topology information, and obtain the phase current information of the installation location of the protection devices on both sides of the fault point.

[0081] Phase-mode conversion module: Connected to the fault monitoring module, it is used to perform phase-mode conversion on the obtained phase current information to obtain mode current information;

[0082] Differential current calculation module: connected to the phase mode conversion module, used to calculate the differential current based on the mode current information at the installation points of the protection devices on both sides;

[0083] Differential current decomposition module: connected to the differential current calculation module, used to perform wavelet packet 3-level decomposition on the differential current using db10 wavelet, dividing it into eight frequency bands with progressively increasing frequencies;

[0084] Energy value calculation module: connected to the differential current decomposition module, used to square the sampling point data of each frequency band to obtain the energy value of each sampling point in each frequency band;

[0085] Energy sequence energy value calculation module: connected to the energy value calculation module, used for energy sequence energy value calculation. For each time moment, the energy values ​​of the sampling points located in the previous data window of the current time moment are accumulated and used as the energy value of that time moment, to obtain the energy values ​​of the eight energy sequences of the corresponding frequency band;

[0086] Energy accumulation value calculation module: Connected to the energy sequence energy value calculation module, it is used to multiply the energy values ​​of the last four energy sequences to obtain the energy accumulation value;

[0087] Fault identification module: Connected to the energy accumulation value calculation module, it is used to determine whether the energy accumulation value is greater than the set value. When the energy accumulation value is greater than the set value, it is determined to be a fault within the zone, and the protection device will operate; otherwise, the protection will not operate.

[0088] This system employs wavelet analysis and other techniques to process and decompose differential current, enabling more accurate extraction of feature information from fault signals. High-precision fault identification is achieved through energy calculation and cumulative value judgment. It can rapidly obtain fault information and perform diagnosis after a fault occurs, thus enabling fast and timely operation of protection devices and minimizing losses caused by faults. Based on traditional transmission line transient quantity detection technology, this system incorporates multi-level and multi-angle analysis and calculation methods, effectively avoiding interference and misjudgment. It can perform online monitoring and detection of transmission lines around the clock, automatically detecting and diagnosing fault signals caused by short-term changes and long-term drift. Without compromising signal processing accuracy, it achieves high data processing efficiency and fast computing speed through efficient algorithms and calculation modes, making it suitable for various large-scale datasets and real-time data stream analysis.

[0089] By performing multi-dimensional and multi-faceted time-domain and frequency-domain analysis on fault signals, effective feature information is extracted while noise and interference signals are filtered out. Phase-mode transformation converts the three-phase AC signal into positive-sequence, negative-sequence, and zero-sequence components, enabling more accurate detection of fault type and location. Wavelet analysis is used to decompose and reconstruct the fault signal, obtaining information on its high and low frequency components, as well as the time-domain and frequency-domain relationships between various frequency bands. The energy value of each frequency band at each moment is calculated, and the magnitude of the energy value is related to the nature and location of the fault. The energy is calculated using the decomposed multi-level wavelet coefficients, thereby improving the accuracy of fault detection. These analytical and computational methods are complementary and synergistic, enabling faster and more accurate diagnosis of fault location and type through comprehensive judgment of information from different aspects. These methods work together to form a complete and efficient fault identification system, providing fault diagnosis methods from multiple perspectives and with diverse approaches to adapt to complex power system environments and operating conditions.

[0090] One corresponding device includes one or more processors and one or more memories, wherein the one or more memories store at least one piece of program code, and when the program code is executed by the one or more processors, it implements the above-described method for rapid phase-to-phase fault identification based on transient quantities of transmission lines.

[0091] The functions that can be achieved by a fast phase-to-phase fault identification method based on transmission line transients can be performed by a device, which includes one or more processors and one or more memories. The one or more memories store at least one piece of program code, which is loaded and executed by the one or more processors to implement the wireless signal processing method.

[0092] The processor fetches instructions from memory one by one, analyzes the instructions, and then performs the corresponding operations according to the instructions, generating a series of control commands to enable the various parts of the computer to act automatically, continuously, and in a coordinated manner, forming an organic whole. This enables the input of programs and data, as well as the calculation and output of results. The arithmetic or logical operations generated in this process are all performed by the arithmetic unit. The memory includes a read-only memory (ROM), which is used to store computer programs. The memory is protected by an external protection device.

[0093] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0094] Those skilled in the art will understand that the above description of the device is merely an example and does not constitute a limitation on the device. It may include more or fewer components than described above, or a combination of certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0095] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the terminal device, connecting various parts of the user terminal via various interfaces and lines.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for rapid phase-to-phase fault identification based on transient quantities of transmission lines, characterized in that... Includes the following steps: Monitoring faults; When a fault occurs, the connection topology information of the line fault point is obtained, and the protection devices on both sides of the fault point are determined based on the connection topology information, so as to obtain the phase current information at the installation location of the protection devices on both sides of the fault point. The obtained phase current information is transformed into mode current information by phase-mode conversion. Calculate the differential current based on the modal current information at the installation locations of the protection devices on both sides; The differential current is decomposed into three layers of wavelet packets using the db10 wavelet, and then divided into eight frequency bands with progressively increasing frequencies. The sampling data of each frequency band is squared to obtain the energy value of each sampling point in each frequency band; For each time moment, the energy values ​​of the sampling points located in the data window preceding the current time moment are accumulated and used as the energy value at that time moment, resulting in eight energy sequences for the corresponding frequency band; Multiply the energy values ​​of the last four energy sequences to obtain the cumulative energy value; When the accumulated energy value exceeds the set value, it is determined to be a fault within the zone, and the protection device will activate; otherwise, the protection device will not activate.

2. The method for rapid phase-to-phase fault identification based on transient quantities of transmission lines according to claim 1, characterized in that: The obtained phase current information is transformed into mode current information by phase-mode transformation, using the following formula: In the formula, This is the modulus current of the first relay protection device; The phase-mode current at the terminal of the first relay protection device; The phase b current at the terminal of the first relay protection device; The c-phase mode current at the terminal of the first relay protection device; This refers to the modulus current of the second relay protection device; The phase-mode current at the second relay protection device terminal; This refers to the phase b current at the second relay protection device terminal. This refers to the c-phase mode current at the second relay protection device terminal.

3. The method for rapid phase-to-phase fault identification based on transient quantities of transmission lines according to claim 2, characterized in that: The differential current is calculated based on the modal current information at the installation locations of the protection devices on both sides. The formula used is: ； in, This is the differential current.

4. The method for rapid phase-to-phase fault identification based on transient quantities of transmission lines according to claim 3, characterized in that: The eight frequency bands are 0-12.5kHz, 12.5-25kHz, 25-37.5kHz, 37.5-50kHz, 50-62.5kHz, 62.5-75kHz, 75-87.5kHz, and 87.5-100kHz.

5. The method for rapid phase-to-phase fault identification based on transient quantities of transmission lines according to claim 4, characterized in that: The sampling frequency is selected as 200kHz, that is, there is a sampling point every 5μs. By accumulating the time window, the difference in high-frequency signal energy between the inside and outside of the fault area is amplified.

6. The method for rapid phase-to-phase fault identification based on transient quantities of transmission lines according to claim 5, characterized in that: The data window is 400 sampling points long, or 2ms.

7. The method for rapid phase-to-phase fault identification based on transient quantities of transmission lines according to claim 6, characterized in that: The frequency bands corresponding to the last four energy sequences are: 50-62.5kHz, 62.5-75kHz, 75-87.5kHz, and 87.5-100kHz.

8. The method for rapid phase-to-phase fault identification based on transient quantities of transmission lines according to claim 7, characterized in that: The value is set to Ed.set, where Ed.set = .

9. A fast phase-to-phase fault identification system based on transient quantities of transmission lines, characterized in that, The system includes: Fault monitoring module: When a fault occurs, it is used to obtain the connection topology information of the line fault point, determine the protection devices on both sides of the fault point based on the connection topology information, and obtain the phase current information of the installation location of the protection devices on both sides of the fault point. Phase-mode conversion module: Connected to the fault monitoring module, it is used to perform phase-mode conversion on the obtained phase current information to obtain mode current information; Differential current calculation module: connected to the phase mode conversion module, used to calculate the differential current based on the mode current information at the installation points of the protection devices on both sides; Differential current decomposition module: connected to the differential current calculation module, used to perform wavelet packet 3-level decomposition on the differential current using db10 wavelet, dividing it into eight frequency bands with progressively increasing frequencies; Energy value calculation module: connected to the differential current decomposition module, used to square the sampling point data of each frequency band to obtain the energy value of each sampling point in each frequency band; Energy sequence energy value calculation module: connected to the energy value calculation module, used for energy sequence energy value calculation. For each time moment, the energy values ​​of the sampling points located in the previous data window of the current time moment are accumulated and used as the energy value of that time moment, to obtain the energy values ​​of the eight energy sequences of the corresponding frequency band; Energy accumulation value calculation module: Connected to the energy sequence energy value calculation module, it is used to multiply the energy values ​​of the last four energy sequences to obtain the energy accumulation value; Fault identification module: Connected to the energy accumulation value calculation module, it is used to determine whether the energy accumulation value is greater than the set value. When the energy accumulation value is greater than the set value, it is determined to be a fault within the zone, and the protection device will operate; otherwise, the protection will not operate.

10. A device, characterized in that: The device includes one or more processors and one or more memories, wherein at least one piece of program code is stored in the one or more memories, and when the program code is executed by the one or more processors, it implements a fast phase-to-phase fault identification method based on transient quantities of transmission lines as described in any one of claims 1-8.

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