Fault diagnosis method and device for power distribution network

Abstract

The invention relates to a fault diagnosis method and device for a power distribution network. The method comprises the following steps: acquiring electrical data obtained by electrical data monitoring of each monitoring terminal in a power distribution network; determining whether the distribution network has a fault according to the electrical data; if yes, the distribution line between the first monitoring terminal and the second monitoring terminal is determined as a fault section, and the first monitoring terminal and the second monitoring terminal are adjacent and opposite in polarity; acquiring a first moment when the traveling wave current reaches the first monitoring terminal and a second moment when the traveling wave current reaches the second monitoring terminal; acquiring the traveling wave velocity of the traveling wave current and a sag effect coefficient between the first monitoring terminal and the second monitoring terminal; and obtaining the length of the distribution line between the fault point location and the first monitoring terminal or the second monitoring terminal according to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient and the length of the distribution line between the first monitoring terminal and the second monitoring terminal. The method can improve the fault positioning precision of the power distribution network.

Description

Technical Field

[0001] This application relates to the technical field of power system operation and maintenance, and particularly to a fault diagnosis method and device for a distribution network. Background Art

[0002] At present, with the continuous development of the smart grid, the stable operation of the distribution network is of great significance for ensuring reliable power supply. As a key link directly facing users, the accuracy and efficiency of fault location in the distribution network are directly related to the power supply quality and the user's power consumption experience.

[0003] Currently, the fault location in the distribution network is mainly achieved through feeder automation, covering two modes: centralized and local. The centralized working mode is that the distribution automation master station aggregates the fault alarm information sent by the terminals in the area, and then analyzes and judges the fault type and fault section based on the collected fault alarm information. The local mode relies on the local logic function between the terminals to judge the fault section. However, the actual power grid lines have an extremely complex topological structure. On the one hand, operations such as loop closing and switch disconnectors are extremely frequent, which makes the connection state of the lines constantly changing; on the other hand, the number of actual operating lines often changes, and the capacitive current sizes are different. The intertwining of these complex factors brings many uncertainties to fault line selection, resulting in the current fault location technology can only achieve an accuracy of kilometer level. Even after successfully determining the fault section, there are still a large number of fault inspection tasks, and the workload of traditional fault inspection has not been reduced from the root cause. Summary of the Invention

[0004] Based on this, the embodiments of this application provide a fault diagnosis method and device for a distribution network, which are used to improve the fault location accuracy of the distribution network.

[0005] In the first aspect, this application provides a fault diagnosis method for a distribution network, including:

[0006] Obtain the electrical data monitored by each monitoring terminal in the distribution network;

[0007] Determine whether there is a fault in the distribution network according to the electrical data;

[0008] If so, determine the distribution line between the first monitoring terminal and the second monitoring terminal as the fault interval, where the first monitoring terminal and the second monitoring terminal are adjacent monitoring terminals in the distribution network and the polarities of the traveling wave currents they monitor are opposite;

[0009] Obtain the first time when the traveling wave current reaches the first monitoring terminal and the second time when the traveling wave current reaches the second monitoring terminal;

[0010] Obtain the traveling wave velocity of the traveling wave current and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal;

[0011] According to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal, obtain the length of the power distribution line between the fault point and the first monitoring terminal or the second monitoring terminal.

[0012] As an optional implementation manner of an embodiment of the present application, the electrical data includes: zero-sequence voltage; the determining whether the power distribution network has a fault according to the electrical data includes:

[0013] Obtain the number of voltage overlimit points of the zero-sequence voltage waveform. The zero-sequence voltage waveform is a voltage waveform formed by the zero-sequence voltage collected within a first duration, and the number of voltage overlimit points is the number of zero-sequence voltage sampling points greater than the threshold voltage in the zero-sequence voltage waveform;

[0014] If the number of voltage overlimit points is less than or equal to a first threshold number, determine that the power distribution network has no fault;

[0015] If the number of voltage overlimit points is greater than the first threshold number, perform band-pass filtering on the zero-sequence voltage waveform, determine the moment corresponding to the maximum amplitude point of the voltage waveform after band-pass filtering as the fault occurrence moment, and determine whether there is a traveling wave current within a second duration before the fault occurrence moment;

[0016] If there is no traveling wave current, determine that the power distribution network has no fault;

[0017] If there is a traveling wave current, determine that the power distribution network has a fault.

[0018] As an optional implementation manner of an embodiment of the present application, the electrical data further includes: power frequency voltage; when it is determined that the power distribution network has a fault, the method further includes:

[0019] Obtain the first voltage, the second voltage, the third voltage, the fourth voltage, the fifth voltage, and the sixth voltage. The first voltage, the second voltage, and the third voltage are the effective voltages of the first phase, the second phase, and the third phase of the power distribution network from the starting moment of the zero-sequence voltage waveform to the fault occurrence moment, respectively. The fourth voltage, the fifth voltage, and the sixth voltage are the effective voltages of the first phase, the second phase, and the third phase of the power distribution network from the fault occurrence moment to the ending moment of the zero-sequence voltage waveform, respectively.

[0020] Determine whether the voltage of the first phase satisfies the decreasing characteristic or the increasing characteristic according to whether the ratio of the first voltage to the fourth voltage belongs to a preset range;

[0021] Determine whether the voltage of the second phase satisfies the decreasing characteristic or the increasing characteristic according to whether the ratio of the second voltage to the fifth voltage belongs to the preset range;

[0022] Determine whether the voltage of the third phase satisfies the decreasing characteristic or the increasing characteristic according to whether the ratio of the third voltage to the sixth voltage belongs to the preset range;

[0023] If any one of the first phase, the second phase, and the third phase satisfies the voltage decreasing characteristic, and the other two phases satisfy the voltage increasing characteristic, determine that the fault of the distribution network is a single-phase grounding fault.

[0024] As an optional implementation manner of the embodiment of the present application, the electrical data further includes: power frequency current; when it is determined that there is a fault in the distribution network, the method further includes:

[0025] Obtain the number of current over-limit points of the power frequency current waveforms of the first phase, the second phase, and the third phase of the distribution network. The power frequency current waveform is a current waveform formed by the power frequency current collected within the first time period, and the number of current over-limit points is the number of power frequency current sampling points greater than the threshold current in the power frequency current waveform;

[0026] If the number of current over-limit points of the power frequency current waveforms of two of the first phase, the second phase, and the third phase is greater than the second threshold number and the polarities of the power frequency currents are opposite, determine that the fault of the distribution network is a two-phase short-circuit fault;

[0027] If the number of current over-limit points of the power frequency current waveforms of the first phase, the second phase, and the third phase are all greater than the second threshold number, determine that the fault of the distribution network is a three-phase short-circuit fault.

[0028] As an optional implementation manner of the embodiment of the present application, the obtaining the first moment when the traveling wave current reaches the first monitoring terminal and the second moment when the traveling wave current reaches the second monitoring terminal includes:

[0029] Perform continuous variational mode decomposition on the traveling wave current monitored by the first monitoring terminal or the second monitoring terminal to obtain the intrinsic mode function IMF components of each center frequency;

[0030] Obtain the kurtosis value of the IMF component with the highest center frequency;

[0031] Determine the moment corresponding to the sampling point with the largest amplitude in the kurtosis values as the first moment or the second moment.

[0032] As an optional implementation manner of an embodiment of the present application, obtaining the traveling wave velocity of the traveling wave current and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal includes:

[0033] Obtaining the length of the power distribution line between the first monitoring terminal and the second monitoring terminal;

[0034] Based on the first moment, the second moment, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal, obtaining the traveling wave velocity and the sag effect coefficient by the alternating direction multiplier method.

[0035] In a second aspect, an embodiment of the present application provides a fault diagnosis device for a power distribution network, including:

[0036] An acquisition module, configured to acquire electrical data obtained by each monitoring terminal in the power distribution network through electrical data monitoring;

[0037] A fault diagnosis module, configured to determine whether there is a fault in the power distribution network according to the electrical data;

[0038] An interval determination module, configured to, when there is a fault in the power distribution network, determine the power distribution line between the first monitoring terminal and the second monitoring terminal as a fault interval, where the first monitoring terminal and the second monitoring terminal are adjacent monitoring terminals in the power distribution network and the polarities of the traveling wave currents they monitor are opposite;

[0039] A fault location module, configured to obtain the first moment when the traveling wave current reaches the first monitoring terminal and the second moment when the traveling wave current reaches the second monitoring terminal; obtain the traveling wave velocity of the traveling wave current and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal, and obtain the length of the power distribution line between the fault location and the first monitoring terminal or the second monitoring terminal according to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal.

[0040] As an alternative implementation manner of an embodiment of the present application, the electrical data includes: zero-sequence voltage; the fault diagnosis module is specifically configured to obtain the number of voltage over-limit points of the zero-sequence voltage waveform; if the number of voltage over-limit points is less than or equal to the first threshold number, it is determined that there is no fault in the distribution network; if the number of voltage over-limit points is greater than the first threshold number, band-pass filtering processing is performed on the zero-sequence voltage waveform, and the moment corresponding to the amplitude maximum point of the voltage waveform after the band-pass filtering processing is determined as the fault occurrence moment, and it is determined whether there is a traveling wave current within a second duration before the fault occurrence moment; if there is no traveling wave current, it is determined that there is no fault in the distribution network; if there is a traveling wave current, it is determined that there is a fault in the distribution network;

[0041] Wherein, the zero-sequence voltage waveform is a voltage waveform formed by the zero-sequence voltage collected within a first duration, and the number of voltage over-limit points is the number of zero-sequence voltage sampling points greater than the threshold voltage in the zero-sequence voltage waveform.

[0042] As an alternative implementation manner of an embodiment of the present application, the electrical data further includes: power frequency voltage; the fault diagnosis module is further configured to, when it is determined that there is a fault in the distribution network, obtain the first voltage, the second voltage, the third voltage, the fourth voltage, the fifth voltage, and the sixth voltage; determine whether the voltage of the first phase satisfies a decreasing characteristic or an increasing characteristic according to whether the ratio of the first voltage to the fourth voltage belongs to a preset range; determine whether the voltage of the second phase satisfies a decreasing characteristic or an increasing characteristic according to whether the ratio of the second voltage to the fifth voltage belongs to the preset range; determine whether the voltage of the third phase satisfies a decreasing characteristic or an increasing characteristic according to whether the ratio of the third voltage to the sixth voltage belongs to the preset range; if any one of the first phase, the second phase, and the third phase satisfies the voltage decreasing characteristic, and the other two phases satisfy the voltage increasing characteristic, it is determined that the fault of the distribution network is a single-phase grounding fault;

[0043] Wherein, the first voltage, the second voltage, and the third voltage are respectively the effective voltages of the first phase, the second phase, and the third phase of the distribution network from the starting moment of the zero-sequence voltage waveform to the fault occurrence moment, and the fourth voltage, the fifth voltage, and the sixth voltage are respectively the effective voltages of the first phase, the second phase, and the third phase of the distribution network from the fault occurrence moment to the termination moment of the zero-sequence voltage waveform.

[0044] As an alternative implementation manner of the embodiment of the present application, the electrical data further includes: power frequency current; the fault diagnosis module is further configured to, when it is determined that there is a fault in the distribution network, obtain the number of current over-limit points of the power frequency current waveforms of the first phase, the second phase, and the third phase of the distribution network; if the number of current over-limit points of the power frequency current waveforms of two phases among the first phase, the second phase, and the third phase is greater than the second threshold number and the polarities of the power frequency currents are opposite, it is determined that the fault of the distribution network is a two-phase short-circuit fault; if the number of current over-limit points of the power frequency current waveforms of the first phase, the second phase, and the third phase are all greater than the second threshold number, it is determined that the fault of the distribution network is a three-phase short-circuit fault;

[0045] Wherein, the power frequency current waveform is a current waveform formed by the power frequency current collected within the first time period, and the number of current over-limit points is the number of power frequency current sampling points greater than the threshold current in the power frequency current waveform.

[0046] As an alternative implementation manner of the embodiment of the present application, the fault location module is specifically configured to perform continuous variational mode decomposition on the traveling wave current monitored by the first monitoring terminal or the second monitoring terminal to obtain IMF components of each center frequency; obtain the kurtosis value of the IMF component with the highest center frequency; determine the moment corresponding to the sampling point with the largest amplitude in the kurtosis values as the first moment or the second moment.

[0047] As an alternative implementation manner of the embodiment of the present application, the fault location module specifically obtains the length of the power distribution line between the first monitoring terminal and the second monitoring terminal; based on the first moment, the second moment, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal, the traveling wave velocity and the sag effect coefficient are obtained by the alternating direction multiplier method.

[0048] In a third aspect, an embodiment of the present application provides a computer device, including: a memory and a processor, where the memory is used to store a computer program, and the processor is configured to, when executing the computer program, enable the computer device to implement the fault diagnosis method of the distribution network according to any one of the first aspects.

[0049] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a computing device, the computing device is enabled to implement the fault diagnosis method of the distribution network according to any one of the first aspects.

[0050] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when running on a computer, enables the computer to implement the fault diagnosis method of the distribution network according to any one of the first aspects.

[0051] After obtaining the electrical data monitored by each monitoring terminal in the distribution network, the fault diagnosis method of the above distribution network first determines whether there is a fault in the distribution network according to the electrical data. When it is determined that there is a fault in the distribution network, the power distribution line between the first monitoring terminal and the second monitoring terminal that are adjacent in the distribution network and have opposite polarities of the monitored traveling wave currents is determined as the fault interval. Then, the first time when the traveling wave current reaches the first monitoring terminal, the second time when the traveling wave current reaches the second monitoring terminal, the wave velocity of the traveling wave current, and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal are obtained. Finally, according to the first time, the second time, the wave velocity of the traveling wave current, the sag effect coefficient, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal, the length of the power distribution line between the fault point and the first monitoring terminal or the second monitoring terminal is obtained. Since the fault diagnosis method of the above distribution network further obtains the length of the power distribution line between the fault point and the first monitoring terminal or the second monitoring terminal according to the first time, the second time, the wave velocity of the traveling wave current, the sag effect coefficient, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal after determining the fault interval, compared with the current fault location technology that can only achieve a precision of kilometers, the fault diagnosis method of the above distribution network can improve the fault location accuracy of the distribution network. Description of the Drawings

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0053] Figure 1 It is a flowchart of the steps of the fault diagnosis method of the distribution network in an embodiment;

[0054] Figure 2 It is a flowchart of the steps of the fault diagnosis method of the distribution network in another embodiment;

[0055] Figure 3 It is a flowchart of the steps of the fault diagnosis method of the distribution network in another embodiment;

[0056] Figure 4 It is a schematic diagram of the fault interval in another embodiment;

[0057] Figure 5Schematic diagram of a traveling wave current and the waveforms of its IMF components;

[0058] Figure 6 Schematic diagram of the kurtosis value of the IMF components in an embodiment;

[0059] Figure 7 Schematic diagram of the structure of a fault diagnosis device for a distribution network in an embodiment;

[0060] Figure 8 Schematic diagram of the structure of a computer device in an embodiment. Detailed implementation manners

[0061] In order to make the objectives, technical solutions and advantages of this application clearer, the following further elaborates on this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0062] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific manner. In addition, in the description of the embodiments of this application, unless otherwise specified, "a plurality of" means two or more.

[0063] The embodiments of this application provide a fault diagnosis method for a distribution network. The execution subject of this fault diagnosis method for a distribution network can be distribution network operation and maintenance devices such as servers and service terminals. Referring to Figure 1 as shown, this fault diagnosis method for a distribution network includes the following steps:

[0064] S11. Obtain the electrical data monitored by each monitoring terminal in the distribution network.

[0065] In some embodiments, the monitoring terminals in the distribution network can be configured based on the following principles:

[0066] ①. At least two monitoring terminals should be installed in the distribution network. Since the double-end traveling wave positioning principle is adopted in the embodiments of this application for fault location, at least two monitoring terminals should be installed in the distribution network;

[0067] ②. Add 1 monitoring terminal for every length of the main line exceeding a preset length (for example: 3 km, 5 km, etc.), configure 1 monitoring terminal at the head of a branch where the length of the distribution line does not exceed the threshold length, and regard a branch where the length of the distribution line exceeds the threshold length as the main line;

[0068] ③. For every number of branches exceeding a preset quantity (e.g., 3), a monitoring terminal should be installed. Since branches can cause traveling wave attenuation, for every number of branches exceeding the preset quantity, a monitoring terminal should be installed to avoid missing the monitoring of traveling waves caused by traveling wave attenuation.

[0069] In the embodiments of the present application, the installation direction of each monitoring terminal in the distribution network is from the smaller number side to the larger number side (power supply direction).

[0070] In some embodiments, the electrical data obtained by the monitoring terminal for electrical data monitoring may include: power frequency signal and / or traveling wave current; the power frequency signal may include at least one of zero-sequence voltage, power frequency voltage, and power frequency current.

[0071] Exemplarily, the sampling rate of the power frequency signal (zero-sequence voltage, power frequency voltage, power frequency current) can be 12.8 kHz, and the sampling rate of the traveling wave signal can be 2 MHz.

[0072] S12. Determine whether there is a fault in the distribution network according to the electrical data.

[0073] Since the electrical data of the distribution network will change regularly within a normal range during the normal operation of the distribution network, it is possible to determine whether there is a fault in the distribution network based on methods such as threshold comparison, the change trend of electrical quantities, and extraction of fault characteristic quantities.

[0074] In the above step S12, if it is determined that there is no fault in the distribution network, return to step S11 to re-obtain the electrical data obtained by the electrical data monitoring of each monitoring terminal in the distribution network. If it is determined that there is a fault in the distribution network, execute the following step S13:

[0075] S13. Determine the power distribution line between the first monitoring terminal and the second monitoring terminal as the fault section.

[0076] Wherein, the first monitoring terminal and the second monitoring terminal are adjacent monitoring terminals in the distribution network and the polarities of the monitored traveling wave currents are opposite.

[0077] In the distribution network, when a fault (such as a short-circuit fault) occurs or a switch operation is performed, the original stable state will be broken, thus generating a traveling wave current. The fault instantaneously introduces a voltage or current mutation source at the fault point, which will excite traveling wave currents propagating towards both ends of the line, and the traveling wave currents monitored by the monitoring terminals at both ends will show an anti-correlation relationship in polarity. Therefore, in the embodiments of the present application, the power distribution line between the first monitoring terminal and the second monitoring terminal that are adjacent in the distribution network and have opposite polarities of the monitored traveling wave currents can be determined as the fault section.

[0078] S14. Obtain the first moment when the traveling wave current arrives at the first monitoring terminal and the second moment when the traveling wave current arrives at the second monitoring terminal.

[0079] In some embodiments, the time of each monitoring terminal can be synchronized by a satellite positioning system, and the time when the traveling wave current is monitored by the first monitoring terminal and the second monitoring terminal is determined as the first moment and the second moment respectively.

[0080] S15. Obtain the traveling wave velocity of the traveling wave current and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal.

[0081] The traveling wave velocity in the embodiments of the present application refers to the propagation velocity of the traveling wave current in the distribution line.

[0082] In an overhead transmission line, the conductor will sag naturally between two adjacent towers due to its own weight and the combined effects of factors such as tension, temperature, and wind force. This phenomenon is called the sag effect. The sag effect will directly affect the length of the distribution line, and thus affect the accuracy of fault location. Therefore, the above embodiments will obtain the sag effect coefficient between the first monitoring terminal and the second monitoring terminal, and consider the sag effect coefficient for fault location to improve the accuracy of fault location.

[0083] S16. According to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the distribution line between the first monitoring terminal and the second monitoring terminal, obtain the length of the distribution line between the fault location and the first monitoring terminal or the second monitoring terminal.

[0084] Exemplarily, according to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the distribution line between the first monitoring terminal and the second monitoring terminal, obtaining the length of the distribution line between the fault location and the first monitoring terminal or the second monitoring terminal includes calculating the length of the distribution line between the fault location and the first monitoring terminal or the second monitoring terminal according to the following formula:

[0085]

[0086] Wherein, is the sag effect coefficient; is the length of the distribution line between the first monitoring terminal and the second monitoring terminal; is the traveling wave velocity; when is the first moment, is the second moment, is the length of the distribution line between the fault location and the first monitoring terminal; when For the second moment, When it is the first moment, is the length of the power distribution line between the fault point and the second monitoring terminal.

[0087] After the above fault diagnosis method of the power distribution network obtains the electrical data monitored by each monitoring terminal in the power distribution network, first, it determines whether there is a fault in the power distribution network according to the electrical data. And when it is determined that there is a fault in the power distribution network, the power distribution line between the first monitoring terminal and the second monitoring terminal that are adjacent in the power distribution network and the polarities of the monitored traveling wave currents are opposite is determined as the fault section. Then, it obtains the first moment when the traveling wave current reaches the first monitoring terminal, the second moment when the traveling wave current reaches the second monitoring terminal, the traveling wave velocity of the traveling wave current, and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal. Finally, according to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal, it obtains the length of the power distribution line between the fault point and the first monitoring terminal or the second monitoring terminal. Since the above fault diagnosis method of the power distribution network further obtains the length of the power distribution line between the fault point and the first monitoring terminal or the second monitoring terminal according to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal after determining the fault section, compared with the current fault location technology that can only achieve a precision of kilometer level, the above fault diagnosis method of the power distribution network can improve the fault location accuracy of the power distribution network.

[0088] Refer to Figure 2 As shown, in some embodiments, the implementation manner of determining whether there is a fault in the power distribution network according to the electrical data may include the following steps S201 to S207:

[0089] S201. Obtain the number of voltage overlimit points of the zero-sequence voltage waveform.

[0090] Among them, the zero-sequence voltage waveform is a voltage waveform formed by the zero-sequence voltage collected within the first duration, and the number of voltage overlimit points is the number of zero-sequence voltage sampling points greater than the threshold voltage in the zero-sequence voltage waveform.

[0091] The zero-sequence voltage refers to the vector sum of the three-phase voltages in a three-phase power system. Since the magnitudes of the three-phase voltages are equal and the phases are 120° out of phase with each other, the vector sum of the three-phase voltages (zero-sequence voltage) is zero under normal circumstances. However, when an asymmetric fault occurs in the system or there are certain special operating conditions, the symmetry of the three-phase voltages will be destroyed, and at this time, the vector sum of the three-phase voltages (zero-sequence voltage) will not be zero.

[0092] In some embodiments, the first duration may be 12 power frequency cycles.

[0093] In some embodiments, the threshold voltage may be set according to the power frequency voltage. For example, the threshold voltage may be 0.3% of the power frequency voltage. For example, when the supply voltage is 100,000 volts, the power frequency voltage of each phase is 100,000 / ≈57,735 volts, and then the threshold voltage can be calculated as 57,735 * 0.3% = 173.2 volts.

[0094] S202. Determine whether the number of voltage over - limit points is greater than the first threshold quantity.

[0095] In some embodiments, the first threshold quantity can be determined according to the sampling frequency of the power frequency signal, the first duration, and a preset proportionality coefficient. For example, the sampling frequency of the power frequency signal is 12.8 kHz, the first duration is 12 power frequency cycles, and the preset proportionality coefficient is 10%. Then the first threshold quantity can be 12800×0.24×10%≈307.

[0096] In the above step S202, if the number of voltage over - limit points is less than or equal to the first threshold quantity, then execute the following step S203:

[0097] S203. Determine that there is no fault in the distribution network.

[0098] In the above step S202, if the number of voltage over - limit points is greater than the first threshold quantity, then execute the following step S204:

[0099] S204. Perform band - pass filtering on the zero - sequence voltage waveform.

[0100] In some embodiments, the filtering frequency band of the band - pass filtering is [100 Hz, 10000 Hz].

[0101] Performing band - pass filtering on the zero - sequence voltage waveform can avoid the influence of fault interference or crosstalk on the accuracy of fault monitoring.

[0102] S205. Determine the moment corresponding to the maximum amplitude point of the voltage waveform after band - pass filtering as the fault occurrence moment.

[0103] That is, find the maximum amplitude point of the voltage waveform after band - pass filtering, and determine the moment corresponding to this maximum amplitude point as the fault occurrence moment.

[0104] S206. Determine whether there is a traveling - wave current within the second duration before the fault occurrence moment.

[0105] In the above step S206, if there is no traveling wave current within the second time period before the fault occurrence time, return to the above step S203 to determine that there is no fault in the distribution network. If there is traveling wave current within the second time period before the fault occurrence time, then execute the following step S207:

[0106] S207. Determine that there is a fault in the distribution network.

[0107] Compared with the fault judgment based on a single index, the above embodiments can combine the zero-sequence voltage and the traveling wave current for fault judgment. Therefore, the above embodiments can more accurately judge whether there is a fault in the distribution network.

[0108] In some embodiments, the electrical data further includes: power frequency voltage. When it is determined that there is a fault in the distribution network, the fault diagnosis method of the distribution network determines whether the fault of the distribution network is a single-phase grounding fault based on the power frequency voltage. Specifically, the implementation manner of determining whether the fault of the distribution network is a single-phase grounding fault based on the power frequency voltage includes the following steps a to e:

[0109] Step a. Obtain the first voltage, the second voltage, the third voltage, the fourth voltage, the fifth voltage, and the sixth voltage.

[0110] Wherein, the first voltage, the second voltage, and the third voltage are the effective voltages of the first phase, the second phase, and the third phase of the distribution network respectively within the time period from the starting moment of the zero-sequence voltage waveform to the fault occurrence time, and the fourth voltage, the fifth voltage, and the sixth voltage are the effective voltages of the first phase, the second phase, and the third phase of the distribution network respectively within the time period from the fault occurrence time to the ending moment of the zero-sequence voltage waveform.

[0111] In some embodiments, the first voltage, the second voltage, and the third voltage can be obtained through the following formula:

[0112]

[0113] Wherein, represents the first phase, the second phase, and the third phase; is the number of power frequency voltage sampling points within the time period from the starting moment of the zero-sequence voltage waveform to the fault occurrence time; is the power frequency voltage at the kth sampling point, are the first voltage, the second voltage, and the third voltage.

[0114] In some embodiments, the fourth voltage, the fifth voltage, and the sixth voltage can be obtained through the following formula:

[0115]

[0116] Among them, represents the first phase, the second phase, and the third phase; is the total number of power frequency voltage sampling points within the time period corresponding to the zero-sequence voltage waveform, is the number of power frequency voltage sampling points from the starting moment of the zero-sequence voltage waveform to the moment of the fault occurrence; is the power frequency voltage of the k-th sampling point, are the fourth voltage, the fifth voltage, and the sixth voltage. Exemplarily, the sampling frequency of the power frequency signal is 12.8 kHz, and the first duration is 12 power frequency cycles, then = 12800×0.24 = 3072.

[0117] Step b: Determine whether the voltage of the first phase satisfies the falling characteristic or the rising characteristic according to whether the ratio of the first voltage to the fourth voltage belongs to a preset range.

[0118] Exemplarily, the preset range can be [0.9, 1.1]. That is, if ≥0.9 , it is determined that the falling characteristic is satisfied. If ≤1.1 , it is determined that the rising characteristic is satisfied. And if 0.9 ≤ ≤1.1 , it is determined that neither the falling characteristic nor the rising characteristic is satisfied.

[0119] Step c: Determine whether the voltage of the second phase satisfies the falling characteristic or the rising characteristic according to whether the ratio of the second voltage to the fifth voltage belongs to the preset range.

[0120] Step d: Determine whether the voltage of the third phase satisfies the falling characteristic or the rising characteristic according to whether the ratio of the third voltage to the sixth voltage belongs to the preset range.

[0121] The implementation manners of step c and step d can refer to step b. To avoid repetition, they will not be described again here.

[0122] Step e: If any one of the first phase, the second phase, and the third phase satisfies the voltage falling characteristic, and the other two phases satisfy the voltage rising characteristic, it is determined that the fault of the distribution network is a single-phase grounding fault.

[0123] Since the neutral point of the distribution line is not directly grounded, if a single-phase grounding fault occurs, the neutral point will shift towards the faulty phase, resulting in the characteristics of a decrease in the power frequency voltage of the faulty phase and an increase in the power frequency voltage of the non-faulty phases. The change in the faulty power frequency current is not obvious. Based on this characteristic, if any one of the first phase, the second phase, and the third phase satisfies the voltage drop characteristic, and the other two phases satisfy the voltage rise characteristic, it is determined that the fault in the distribution network is a single-phase grounding fault.

[0124] In some embodiments, the electrical data further includes: power frequency current. When it is determined that there is a fault in the distribution network, the fault diagnosis method of the distribution network determines whether the fault in the distribution network is a short-circuit fault based on the power frequency current. Specifically, the implementation manner of determining whether the fault in the distribution network is a short-circuit fault based on the power frequency current includes the following steps 1 to 4:

[0125] Step 1: Obtain the number of current over-limit points of the power frequency current waveforms of the first phase, the second phase, and the third phase of the distribution network.

[0126] Wherein, the power frequency current waveform is a current waveform formed by the power frequency current collected within the first time period, and the number of current over-limit points is the number of power frequency current sampling points greater than the threshold current in the power frequency current waveform.

[0127] Exemplarily, the threshold current can be 600A.

[0128] In the above step 1, if the number of current over-limit points of the power frequency current waveforms of two of the first phase, the second phase, and the third phase is greater than the second threshold number, then perform the following step 2:

[0129] Step 2: Determine whether the polarities of the power frequency currents of the two faulty phases are opposite.

[0130] In some embodiments, the implementation manner of determining whether the polarities of the power frequency currents of the two faulty phases are opposite may include the following steps 2.1 to 2.3:

[0131] Step 2.1: Calculate the correlation coefficient of the power frequency currents of the two faulty phases through the following formula:

[0132]

[0133] Wherein, The correlation coefficient of the power frequency currents of the two phases, is the power frequency current of one of the faulty phases, is its mean value, is the power frequency current of the other faulty phase, is its mean value.

[0134] Step 2.2: Determine whether the correlation coefficient belongs to a preset coefficient range.

[0135] Exemplarily, the preset coefficient range can be [-1, -.8).

[0136] In the above step 2.2, if the correlation coefficient belongs to the preset coefficient range, then execute the following step 2.3:

[0137] Step 2.3: Determine that the current polarities of the two faulty phases are opposite.

[0138] In the above step 2.2, if the correlation coefficient does not belong to the preset coefficient range, then execute the following step 2.4:

[0139] Step 2.4: Determine that the current polarities of the two faulty phases are not opposite.

[0140] Exemplarily, the number of the second thresholds can be 100.

[0141] In the above step 2, if the current polarities of the power frequency currents of the two faulty phases are opposite, then execute the following step 3:

[0142] Step 3: Determine that the fault of the distribution network is a two-phase short circuit fault.

[0143] In the above step 1, if the number of current overlimit points of the power frequency current waveforms of the first phase, the second phase, and the third phase are all greater than the number of the second thresholds, then execute the following step 4:

[0144] Step 4: Determine that the fault of the distribution network is a three-phase short circuit fault.

[0145] If an interphase short circuit fault occurs in the distribution line, the power frequency current of the faulty phase will increase significantly. If it is a two-phase short circuit fault, the current polarities of the two faulty phases are completely opposite. According to this characteristic, the above embodiments can accurately diagnose the short circuit grounding fault.

[0146] As an extension and refinement of the above embodiments, the embodiments of the present application further provide another fault diagnosis method for a distribution network. Refer to Figure 3 As shown, the fault diagnosis method for the distribution network includes the following steps:

[0147] S301: Obtain the electrical data monitored by each monitoring terminal in the distribution network.

[0148] S302: Determine whether there is a fault in the distribution network according to the electrical data.

[0149] The implementation manner of determining whether there is a fault in the distribution network according to the electrical data can refer to any of the above embodiments. To avoid repetition, it will not be described again here.

[0150] In the above step S302, if it is determined that there is a fault in the power distribution network, the following steps are executed:

[0151] S303. Determine the power distribution line between the first monitoring terminal and the second monitoring terminal as the fault section.

[0152] Wherein, the first monitoring terminal and the second monitoring terminal are adjacent monitoring terminals in the power distribution network and the polarities of the detected traveling wave currents are opposite.

[0153] Refer to Figure 4 As shown in the schematic diagram of the fault section, the distance between the first monitoring terminal 41 and the second monitoring terminal 42 is L, and the time for the traveling wave current to propagate from the fault point 400 to the first monitoring terminal 41 is The time for the traveling wave current to propagate from the fault point 400 to the second monitoring terminal 42 is Then, the distance from the fault point 400 to the first monitoring terminal 41 Can be calculated by the following formula:

[0154]

[0155] The distance from the fault point 400 to the second monitoring terminal 42 Can be calculated by the following formula:

[0156]

[0157] Wherein, Is the propagation speed of the traveling wave current in the power distribution line.

[0158] Furthermore, considering that the transmission distance of the distribution network line is long, the span between adjacent poles and towers is large, and there is a sag effect, therefore, the sag effect is considered to improve the fault location accuracy. After considering the sag effect, the distance from the fault point 400 to the first monitoring terminal 41 Can be calculated by the following formula:

[0159]

[0160] Wherein, Is the sag effect coefficient.

[0161] Similarly, after considering the sag effect, the distance from the fault point 400 to the second monitoring terminal 42 Can be calculated by the following formula:

[0162]

[0163] As can be seen from the above formula, to obtain the length L of the power distribution line between the first monitoring terminal and the second monitoring terminal, the sag effect coefficient , the propagation speed of the traveling wave current in the power distribution line , the first moment when the traveling wave current reaches the first monitoring terminal and the second moment when the traveling wave current reaches the second monitoring terminal , the distance between the fault point and the first monitoring terminal or the second terminal can be calculated by substituting into the above formula.

[0164] S304. Perform continuous variational mode decomposition (CVMD) on the traveling wave current monitored by the first monitoring terminal or the second monitoring terminal to obtain the intrinsic mode function (IMF) components of each center frequency.

[0165] CVMD is a signal processing method, which is an improvement and expansion of the traditional variational mode decomposition (VMD). Specifically, the original signal is decomposed into the sum of a series of mode functions with different center frequencies, and each mode function is defined as an amplitude-modulated and frequency-modulated signal. Its core idea is to construct and solve a variational problem to determine the center frequencies and bandwidths of each intrinsic mode function, so that the decomposed mode functions can optimally approximate the original signal.

[0166] Exemplarily, as shown in Figure 5 , when the waveform of the traveling wave current is as shown in the curve graph 51 in Figure 5 , performing CVMD decomposition on the traveling wave current can obtain the IMF components of five center frequencies, and the waveforms of the IMF components of the five center frequencies are respectively as shown in Figure 5 the curve graphs 52, 53, 54, 55, and 56 in

[0167] S305. Obtain the kurtosis value of the IMF component with the highest center frequency.

[0168] The kurtosis value is a numerical statistic that reflects the distribution characteristics of a random variable, describes the non-Gaussian characteristics of the signal, can be used in the time domain to describe the intensity of the fault signal, is very sensitive to transient shocks in the signal, can effectively describe sudden changes in the waveform, and is extremely accurate for calibrating the arrival time of the traveling wave.

[0169] In some embodiments, the kurtosis value can be calculated by the following formula:

[0170]

[0171] Among them, is the number of sampling points, and are respectively the average value and the standard deviation of is the IMF component with the highest central frequency.

[0172] S306. Determine the moment corresponding to the sampling point with the largest amplitude among the kurtosis values as the first moment or the second moment.

[0173] If the continuous variational mode CVMD decomposition is performed on the traveling wave current monitored by the first monitoring terminal in step S304, the moment obtained in step S306 is the first moment; if the continuous variational mode CVMD decomposition is performed on the traveling wave current monitored by the second monitoring terminal in step S304, the moment obtained in step S306 is the second moment.

[0174] Exemplarily, referring to Figure 6 shown in Figure 6 is a schematic diagram of the kurtosis value of the IMF component with the highest central frequency. As Figure 6 shown, the sampling point with the largest amplitude of the kurtosis value of the IMF component with the highest central frequency is sampling point 600. Therefore, the moment corresponding to the sampling of sampling point 600 is determined as the moment when the traveling wave front arrives.

[0175] Through the above steps S304 to S306, the first moment when the traveling wave current reaches the first monitoring terminal and the second moment when the traveling wave current reaches the second monitoring terminal can be obtained respectively.

[0176] S307. Obtain the length of the power distribution line between the first monitoring terminal and the second monitoring terminal.

[0177] In some embodiments, the length of the power distribution line between the first monitoring terminal and the second monitoring terminal can be obtained from historical data or line inspection results.

[0178] S308. Based on the first moment, the second moment, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal, obtain the traveling wave speed and the sag effect coefficient through the Alternating Direction Method of Multipliers (ADMM).

[0179] ADMM is an algorithm for solving optimization problems, mainly used to handle convex optimization problems with equality constraints. Its form is:

[0180]

[0181] To solve such convex optimization problems, linear equality constraints can be added, and the augmented Lagrangian function is defined as follows:

[0182]

[0183] Using the method of dual ascent to solve the above formula, we can obtain:

[0184]

[0185]

[0186] Further, the final traveling wave velocity is obtained by alternately updating and solving and the sag effect coefficient .

[0187] S309. Obtain the length of the power distribution line between the fault location and the first monitoring terminal or the second monitoring terminal according to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal.

[0188] That is, substitute the length L of the power distribution line between the first monitoring terminal and the second monitoring terminal, the sag effect coefficient , the propagation speed of the traveling wave current in the power distribution line, the first moment when the traveling wave current reaches the first monitoring terminal, and the second moment when the traveling wave current reaches the second monitoring terminal into the formula to obtain the length of the power distribution line between the fault location and the first monitoring terminal, or substitute into the formula to obtain the length of the power distribution line between the fault location and the second monitoring terminal.

[0189] Based on the same inventive concept, an embodiment of the present application also provides a fault diagnosis device for a power distribution network for implementing the fault diagnosis method of the power distribution network involved above. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the fault diagnosis device for a power distribution network provided below can refer to the limitations on the fault diagnosis method of the power distribution network in the above text, and will not be repeated here.

[0190] In an exemplary embodiment, as Figure 7As shown, a fault diagnosis device 700 for a distribution network is provided, including: an acquisition module 71, a fault diagnosis module 72, an interval determination module 73, and a fault location module 74, where:

[0191] The acquisition module 71 is configured to acquire electrical data obtained by each monitoring terminal in the distribution network for electrical data monitoring;

[0192] The fault diagnosis module 72 is configured to determine whether there is a fault in the distribution network according to the electrical data;

[0193] The interval determination module 73 is configured to, when there is a fault in the distribution network, determine the power distribution line between the first monitoring terminal and the second monitoring terminal as the fault interval, where the first monitoring terminal and the second monitoring terminal are adjacent monitoring terminals in the distribution network and the polarities of the traveling wave currents they monitor are opposite;

[0194] The fault location module 74 is configured to acquire the first moment when the traveling wave current reaches the first monitoring terminal and the second moment when the traveling wave current reaches the second monitoring terminal; acquire the traveling wave velocity of the traveling wave current and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal, and according to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal, acquire the length of the power distribution line between the fault point and the first monitoring terminal or the second monitoring terminal.

[0195] As an optional implementation manner of an embodiment of the present application, the electrical data includes: zero-sequence voltage; the fault diagnosis module 72 is specifically configured to acquire the number of voltage overlimit points of the zero-sequence voltage waveform; if the number of voltage overlimit points is less than or equal to the first threshold number, it is determined that there is no fault in the distribution network; if the number of voltage overlimit points is greater than the first threshold number, perform band-pass filtering on the zero-sequence voltage waveform, determine the moment corresponding to the maximum amplitude point of the voltage waveform after band-pass filtering as the fault occurrence moment, and determine whether there is a traveling wave current within the second time period before the fault occurrence moment; if there is no traveling wave current, it is determined that there is no fault in the distribution network; if there is a traveling wave current, it is determined that there is a fault in the distribution network;

[0196] Wherein, the zero-sequence voltage waveform is a voltage waveform formed by the zero-sequence voltage collected within the first time period, and the number of voltage overlimit points is the number of zero-sequence voltage sampling points greater than the threshold voltage in the zero-sequence voltage waveform.

[0197] As an optional implementation manner of the embodiment of the present application, the electrical data further includes: power frequency voltage; the fault diagnosis module 72 is further configured to, when it is determined that a fault exists in the distribution network, obtain a first voltage, a second voltage, a third voltage, a fourth voltage, a fifth voltage, and a sixth voltage; determine whether the voltage of the first phase satisfies a decreasing characteristic or an increasing characteristic according to whether the ratio of the first voltage to the fourth voltage belongs to a preset range; determine whether the voltage of the second phase satisfies a decreasing characteristic or an increasing characteristic according to whether the ratio of the second voltage to the fifth voltage belongs to the preset range; determine whether the voltage of the third phase satisfies a decreasing characteristic or an increasing characteristic according to whether the ratio of the third voltage to the sixth voltage belongs to the preset range; if any one of the first phase, the second phase, and the third phase satisfies the voltage decreasing characteristic, and the other two phases satisfy the voltage increasing characteristic, it is determined that the fault of the distribution network is a single-phase grounding fault;

[0198] Wherein, the first voltage, the second voltage, and the third voltage are respectively the effective voltages of the first phase, the second phase, and the third phase of the distribution network from the starting moment of the zero-sequence voltage waveform to the fault occurrence moment, and the fourth voltage, the fifth voltage, and the sixth voltage are respectively the effective voltages of the first phase, the second phase, and the third phase of the distribution network from the fault occurrence moment to the ending moment of the zero-sequence voltage waveform.

[0199] As an optional implementation manner of the embodiment of the present application, the electrical data further includes: power frequency current; the fault diagnosis module 72 is further configured to, when it is determined that a fault exists in the distribution network, obtain the number of current overlimit points of the power frequency current waveforms of the first phase, the second phase, and the third phase of the distribution network; if the number of current overlimit points of the power frequency current waveforms of two of the first phase, the second phase, and the third phase is greater than a second threshold number and the polarities of the power frequency currents are opposite, it is determined that the fault of the distribution network is a two-phase short circuit fault; if the number of current overlimit points of the power frequency current waveforms of the first phase, the second phase, and the third phase are all greater than the second threshold number, it is determined that the fault of the distribution network is a three-phase short circuit fault;

[0200] Wherein, the power frequency current waveform is a current waveform formed by the power frequency current collected within the first duration, and the number of current overlimit points is the number of power frequency current sampling points greater than the threshold current in the power frequency current waveform.

[0201] As an optional implementation manner of an embodiment of the present application, the fault location module 74 is specifically configured to perform continuous variational mode decomposition on the traveling wave current monitored by the first monitoring terminal or the second monitoring terminal to obtain IMF components of each center frequency; obtain the kurtosis value of the IMF component with the highest center frequency; and determine the moment corresponding to the sampling point with the largest amplitude in the kurtosis values as the first moment or the second moment.

[0202] As an optional implementation manner of an embodiment of the present application, the fault location module 74 specifically obtains the length of the power distribution line between the first monitoring terminal and the second monitoring terminal; and based on the first moment, the second moment, and the length of the power distribution line between the first monitoring terminal and the second monitoring terminal, obtains the traveling wave velocity and the sag effect coefficient by using the alternating direction method of multipliers.

[0203] Each module in the above-mentioned fault diagnosis device of the power distribution network can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processing module in the computer device in the form of hardware or be independent of it, or can be stored in the storage module in the computer device in the form of software, so that the processing module can call and execute the operations corresponding to the above-mentioned modules.

[0204] In an exemplary embodiment, a computer device is provided. The computer device can be a service module, and its internal structure diagram can be as Figure 8 shown. The computer device includes a processing module 81, a storage module 82, an input / output interface (Input / Output, abbreviated as I / O) 83, and a communication interface 84. Among them, the processing module, the storage module, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processing module of the computer device is used to provide computing and control capabilities. The storage module of the computer device includes a non-volatile storage medium and an internal storage module. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal storage module provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the electrical data obtained by each monitoring terminal in the power distribution network through electrical data monitoring. The input / output interface of the computer device is used to exchange information between the processing module and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processing module, the above-mentioned fault diagnosis method of the power distribution network is implemented.

[0205] Those skilled in the art can understand, Figure 8The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0206] In an exemplary embodiment, a computer device is provided, including a storage module and a processing module. A computer program is stored in the storage module, and when the processing module executes the computer program, each process in the method embodiment is implemented.

[0207] In an embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by the processing module, each process in the method embodiment is implemented.

[0208] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0209] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a storage module, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile storage modules. The non-volatile storage module can include a read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage module, high-density embedded non-volatile storage module, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene storage module, etc. The volatile storage module can include a random access memory (RAM) or an external cache memory module, etc. By way of illustration and not limitation, RAM can be in various forms, such as a static random access memory (SRAM) or a dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on blockchain, etc., without limitation. The processing modules involved in the embodiments provided in the present application can be a general-purpose processing module, a central processing module, a graphics processing module, a digital signal processing module, a programmable logic module, a data processing logic module based on quantum computing, etc., without limitation.

[0210] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0211] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for fault diagnosis of a power distribution network, characterized in that: include: Acquire electrical data obtained by performing electrical data monitoring at each monitoring terminal in the power distribution network; determining whether there is a fault in the power distribution network based on the electrical data; If yes, the power distribution line between the first monitoring terminal and the second monitoring terminal is determined as a fault section, the first monitoring terminal and the second monitoring terminal are adjacent monitoring terminals in the power distribution network and the polarities of the monitored traveling wave currents are opposite; Obtaining a first moment when the traveling wave current reaches the first monitoring terminal and a second moment when the traveling wave current reaches the second monitoring terminal; obtaining a traveling wave velocity of the traveling wave current and a sag effect coefficient between the first monitoring terminal and the second monitoring terminal; According to the first moment, the second moment, the traveling wave velocity, the sag effect coefficient, and the length of the distribution line between the first monitoring terminal and the second monitoring terminal, the length of the distribution line between the fault point and the first monitoring terminal or the second monitoring terminal is obtained.

2. The method according to claim 1, characterized in that The electrical data includes: zero-sequence voltage; and determining whether the power distribution network has a fault according to the electrical data includes: Obtaining the number of voltage crossing points of a zero-sequence voltage waveform, wherein the zero-sequence voltage waveform is a voltage waveform formed by a zero-sequence voltage collected within a first time period, and the number of voltage crossing points is the number of zero-sequence voltage sampling points in the zero-sequence voltage waveform that are greater than a threshold voltage; If the number of voltage crossing points is less than or equal to a first threshold number, determining that there is no fault in the power distribution network; If the number of voltage crossing points is greater than the first threshold number, the zero-sequence voltage waveform is subjected to bandpass filtering, and the time corresponding to the maximum point of the amplitude of the voltage waveform after the bandpass filtering is determined as the time of fault occurrence, and whether there is a traveling wave current within a second time period before the time of fault occurrence is determined; If there is no traveling wave current, it is determined that there is no fault in the power distribution network; If the traveling wave current exists, it is determined that a fault exists in the power distribution network.

3. The method according to claim 2, characterized in that The electrical data further includes: power frequency voltage; when it is determined that there is a fault in the power distribution network, the method further includes: Obtain a first voltage, a second voltage, a third voltage, a fourth voltage, a fifth voltage and a sixth voltage, wherein the first voltage, the second voltage and the third voltage are respectively the effective voltages of the first phase, the second phase and the third phase of the power distribution network from the start time of the zero-sequence voltage waveform to the time when the fault occurs, and the fourth voltage, the fifth voltage and the sixth voltage are respectively the effective voltages of the first phase, the second phase and the third phase of the power distribution network from the time when the fault occurs to the time when the zero-sequence voltage waveform ends; determining whether the voltage of the first phase satisfies a decreasing characteristic or an increasing characteristic according to whether a ratio of the first voltage to the fourth voltage falls within a preset range; determining whether the voltage of the second phase satisfies a decreasing characteristic or an increasing characteristic according to whether a ratio of the second voltage to the fifth voltage falls within the preset range; determining whether the voltage of the third phase satisfies a falling characteristic or an rising characteristic according to whether a ratio of the third voltage to the sixth voltage falls within the preset range; If any one of the first phase, the second phase and the third phase meets the voltage drop characteristic, and the other two phases meet the voltage rise characteristic, it is determined that the fault of the power distribution network is a single-phase grounding fault.

4. The method according to claim 2, characterized in that: The electrical data further includes: power frequency current; when it is determined that there is a fault in the power distribution network, the method further includes: Obtaining the number of current crossing limit points of the power frequency current waveform of the first phase, the second phase, and the third phase of the power distribution network, wherein the power frequency current waveform is a current waveform formed by the power frequency current collected within the first time period, and the number of current crossing limit points is the number of power frequency current sampling points in the power frequency current waveform that are greater than a threshold current; If the number of current crossing points of the power frequency current waveforms of two phases among the first phase, the second phase and the third phase is greater than a second threshold number and the polarities of the power frequency currents are opposite, it is determined that the fault of the power distribution network is a two-phase short circuit fault; If the number of current crossing points of the power frequency current waveforms of the first phase, the second phase and the third phase are all greater than the second threshold number, it is determined that the fault of the power distribution network is a three-phase short circuit fault.

5. The method according to claim 1, characterized in that The obtaining a first time when the traveling wave current reaches the first monitoring terminal and a second time when the traveling wave current reaches the second monitoring terminal includes: Performing continuous variational mode decomposition on the traveling wave current monitored by the first monitoring terminal or the second monitoring terminal to obtain intrinsic mode function IMF components of each center frequency; Get the kurtosis value of the IMF component with the highest center frequency; The moment corresponding to the sampling point with the largest amplitude in the kurtosis value is determined as the first moment or the second moment.

6. The method according to claim 1, characterized in that The obtaining of the traveling wave velocity of the traveling wave current and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal includes: Obtaining the length of the power distribution line between the first monitoring terminal and the second monitoring terminal; Based on the first moment, the second moment, and the length of the distribution line between the first monitoring terminal and the second monitoring terminal, the traveling wave velocity and the sag effect coefficient are obtained by an alternating direction multiplier method.

7. A fault diagnosis device for a power distribution network, characterized in that: include: An acquisition module, used to acquire electrical data obtained by each monitoring terminal in the power distribution network through electrical data monitoring; a fault diagnosis module, configured to determine whether the power distribution network has a fault based on the electrical data; An interval determination module, configured to determine, when a fault occurs in the power distribution network, a power distribution line between a first monitoring terminal and a second monitoring terminal as a fault interval, wherein the first monitoring terminal and the second monitoring terminal are adjacent monitoring terminals in the power distribution network and the polarities of the monitored traveling wave currents are opposite; A fault location module is used to obtain the first moment when the traveling wave current reaches the first monitoring terminal and the second moment when the traveling wave current reaches the second monitoring terminal; obtain the traveling wave velocity of the traveling wave current and the sag effect coefficient between the first monitoring terminal and the second monitoring terminal, and obtain the length of the distribution line between the fault point and the first monitoring terminal or the second monitoring terminal based on the first moment, the second moment, the traveling wave velocity, the sag effect coefficient and the length of the distribution line between the first monitoring terminal and the second monitoring terminal.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory is used to store a computer program and the processor is used to enable the computer device to implement the fault diagnosis method for a power distribution network as described in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a computing device, the computing device implements the fault diagnosis method for a power distribution network according to any one of claims 1 to 6.

10. A computer program product, characterized in that When the computer program product is executed on a computer, the computer is enabled to implement the method for diagnosing faults in a power distribution network according to any one of claims 1 to 6.

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