Hybrid distribution line fault location method and device based on high-precision sampling, storage medium and program product
By optimizing and performing variational mode decomposition on the raw monitoring data of mixed power distribution lines, the complexity of fault location in mixed power distribution lines is solved, and the accurate location and rapid positioning of faults are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-27
- Publication Date
- 2026-06-16
AI Technical Summary
The difference in electrical characteristics between overhead and cable in mixed power distribution lines causes complex reflection and refraction phenomena in the transient traveling wave signals generated by faults at the connection points, making it difficult to effectively locate the fault.
By acquiring and optimizing the original monitoring data of the mixed power distribution lines, and using the variational mode decomposition model to decompose the signal, the time difference and propagation speed of the target signal are determined, thereby accurately locating the fault location.
It improves the accuracy and speed of fault location, reduces time costs, and enables accurate location of faults in mixed power distribution lines.
Smart Images
Figure CN122218378A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of power fault monitoring technology, and in particular to a method, device, storage medium and program product for locating faults in hybrid power distribution lines based on high-precision sampling. Background Technology
[0002] With the development of power systems, power load density continues to increase, and the requirements for power supply reliability are constantly rising. However, on the one hand, while single overhead distribution lines are easy to maintain, they are susceptible to severe weather, have a high failure rate, and are difficult to deploy on a large scale in urban core areas; on the other hand, while single cable distribution lines offer high power supply reliability, they are costly to construct and complex to locate faults. Therefore, hybrid distribution systems have emerged. Hybrid distribution lines, by flexibly combining overhead and cable sections, can effectively adapt to complex terrains and urban environments, optimizing investment costs while ensuring power supply reliability. However, the electrical characteristics of overhead and cable sections in hybrid distribution lines differ significantly, causing complex reflection and refraction phenomena to occur at the connection points of transient traveling wave signals generated by faults.
[0003] Therefore, how to locate faults in mixed power distribution lines has become an urgent problem to be solved. Summary of the Invention
[0004] Therefore, it is necessary to provide a method, device, storage medium, and program product for locating faults in hybrid power distribution lines based on high-precision sampling, in response to the above-mentioned technical problems.
[0005] Firstly, this application provides a method for locating faults in hybrid power distribution lines based on high-precision sampling, including:
[0006] The raw monitoring data of the mixed power distribution lines is obtained and optimized to obtain the optimized monitoring data.
[0007] The optimized monitoring data is input into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0008] Determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0009] The fault location of the mixed power distribution line is determined based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal.
[0010] Secondly, this application also provides a hybrid power distribution line fault location device based on high-precision sampling, comprising:
[0011] The optimization module is used to acquire the raw monitoring data of the mixed power distribution lines and optimize the raw monitoring data to obtain optimized monitoring data.
[0012] The decomposition module is used to input the optimized monitoring data into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0013] The first determining module is used to determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0014] The second determining module is used to determine the fault location of the mixed power distribution line based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal.
[0015] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:
[0016] The raw monitoring data of the mixed power distribution lines is obtained and optimized to obtain the optimized monitoring data.
[0017] The optimized monitoring data is input into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0018] Determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0019] The fault location of the mixed power distribution line is determined based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal.
[0020] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:
[0021] The raw monitoring data of the mixed power distribution lines is obtained and optimized to obtain the optimized monitoring data.
[0022] The optimized monitoring data is input into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0023] Determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0024] The fault location of the mixed power distribution line is determined based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal.
[0025] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:
[0026] The raw monitoring data of the mixed power distribution lines is obtained and optimized to obtain the optimized monitoring data.
[0027] The optimized monitoring data is input into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0028] Determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0029] The fault location of the mixed power distribution line is determined based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal.
[0030] The aforementioned method, device, storage medium, and program product for fault location of hybrid power distribution lines based on high-precision sampling acquires the original monitoring data of the hybrid power distribution line and optimizes the original monitoring data to obtain optimized monitoring data. The optimized monitoring data is then input into a variational mode decomposition model for signal decomposition to obtain the target signal. The first time difference between the two ends of the hybrid power distribution line, the second time difference between the first arrival of the target signal at different nodes in the hybrid power distribution line, and the propagation speed of the target signal are determined. Based on the first time difference between the two ends of the hybrid power distribution line, the second time difference between the first arrival of the target signal at different nodes in the hybrid power distribution line, and the propagation speed of the target signal, the fault location of the hybrid power distribution line is determined. The above method, through data optimization processing, can remove interference data from the original monitoring data, improving the accuracy of subsequent model decomposition of signals; by using variational mode model to achieve accurate signal decomposition, it can effectively extract target signals directly related to the fault, and by calculating time difference and propagation speed, it can accurately locate the fault location of mixed distribution lines; and by using the time difference of different nodes, it can quickly locate the fault location, reducing time costs, and thus improving the accuracy of fault location when a fault occurs in a mixed distribution line. Attached Figure Description
[0031] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0032] Figure 1 This is an application environment diagram of a hybrid power distribution line fault location method based on high-precision sampling in one embodiment;
[0033] Figure 2 This is one of the flowcharts illustrating a hybrid power distribution line fault location method based on high-precision sampling in one embodiment;
[0034] Figure 3 This is a second flowchart illustrating a hybrid power distribution line fault location method based on high-precision sampling in one embodiment.
[0035] Figure 4 This is a diagram illustrating the propagation path of an initial traveling wave surge in a hybrid distribution line in one embodiment.
[0036] Figure 5 This is the third flowchart of a hybrid power distribution line fault location method based on high-precision sampling in one embodiment;
[0037] Figure 6 This is the fourth flowchart of a hybrid power distribution line fault location method based on high-precision sampling in one embodiment;
[0038] Figure 7 This is a schematic diagram of a hybrid power distribution line structure in one embodiment;
[0039] Figure 8 This is a flowchart illustrating the fault location process for a hybrid power distribution line in one embodiment.
[0040] Figure 9 This is the fifth flowchart illustrating a hybrid power distribution line fault location method based on high-precision sampling in one embodiment;
[0041] Figure 10 This is a simulation model of a hybrid power distribution line in one embodiment;
[0042] Figure 11 This is a flowchart of a hybrid power distribution line fault location method based on high-precision sampling in one embodiment;
[0043] Figure 12 This is a simplified structural diagram of a hybrid power distribution line in one embodiment;
[0044] Figure 13 This is the seventh flowchart of a hybrid power distribution line fault location method based on high-precision sampling in one embodiment;
[0045] Figure 14 Here is a flowchart of a distribution network intelligent monitoring method based on a primary and secondary integrated switch in one embodiment;
[0046] Figure 15 This is the eighth flowchart of a hybrid power distribution line fault location method based on high-precision sampling in one embodiment;
[0047] Figure 16 This is a structural block diagram of a hybrid power distribution line fault location device based on high-precision sampling in one embodiment;
[0048] Figure 17 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation
[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0050] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.
[0051] With the development of power systems, power load density continues to increase, and the requirements for power supply reliability are constantly rising. However, on the one hand, while single overhead distribution lines are easy to maintain, they are susceptible to severe weather, have a high failure rate, and are difficult to deploy on a large scale in urban core areas; on the other hand, while single cable distribution lines offer high power supply reliability, they are costly to construct and complex to locate faults. Therefore, hybrid distribution systems have emerged. Hybrid distribution lines, by flexibly combining overhead and cable sections, can effectively adapt to complex terrains and urban environments, optimizing investment costs while ensuring power supply reliability. However, the electrical characteristics of overhead and cable sections in hybrid distribution lines differ significantly, causing complex reflection and refraction phenomena to occur at the connection points of transient traveling wave signals generated by faults.
[0052] Therefore, how to locate faults in mixed power distribution lines has become an urgent problem to be solved.
[0053] In view of the above-mentioned technical problems, this application provides a method for locating faults in hybrid power distribution lines based on high-precision sampling. The following embodiments will specifically illustrate this method for locating faults in hybrid power distribution lines based on high-precision sampling.
[0054] The fault location method for hybrid power distribution lines based on high-precision sampling provided in this application can be applied to, for example... Figure 1 The system shown is a high-precision sampling-based fault location system for hybrid power distribution lines. The hybrid power distribution line 101 consists of overhead lines and cable lines. Primary and secondary fusion switches 102 are deployed at different nodes on the overhead and cable lines and at both ends of the hybrid power distribution line. These fusion switches, acting as field devices integrating sensors and intelligent units, can record and monitor traveling wave signals on the hybrid power distribution line and transmit the recorded signals to a fault location device 103. The fault location device 103 processes and analyzes the recorded traveling wave signals to determine if a fault exists in the hybrid power distribution line. If a fault exists, the fault location device 103 determines the location of the fault and displays the result using a display device 104.
[0055] Those skilled in the art will understand that Figure 1 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the high-precision sampling-based hybrid power distribution line fault location system applied thereto. A specific high-precision sampling-based hybrid power distribution line fault location system may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.
[0056] In one exemplary embodiment, such as Figure 2 As shown, a method for locating faults in hybrid power distribution lines based on high-precision sampling is provided, and this method is applied to... Figure 1 Taking the fault location device in the middle as an example, the explanation includes:
[0057] S201: Obtain the original monitoring data of the mixed power distribution line, and optimize the original monitoring data to obtain the optimized monitoring data.
[0058] The optimization process includes at least one of resampling, dimensionality reduction, scaling, and standardization.
[0059] In this embodiment, the fault location device can acquire the original monitoring data of the mixed power distribution line in real time through a high-precision current sensor, such as the traveling wave signal characteristics of the three-phase current and total current, and key electrical signals such as zero-sequence current and zero-sequence voltage. To address issues such as sampling rate differences, redundant data, inconsistent dimensions, and noise interference in the original monitoring data, the fault location device can optimize the original monitoring data using optimization methods. For example, it can adjust the sampling frequency of the original monitoring data through resampling methods (such as linear interpolation or anti-aliasing filtering), extract the feature vector of the original monitoring data through dimensionality reduction algorithms (such as principal component analysis) to reduce the data dimensionality, and perform standardization through minimum and maximum value normalization or Z-score to eliminate the influence of amplitude differences in the three-phase current and the dimension of the zero-sequence voltage, ensuring that all monitoring data conforms to a unified normal distribution benchmark, thus obtaining optimized monitoring data.
[0060] S202, the optimized monitoring data is input into the variational mode decomposition model for signal decomposition to obtain the target signal.
[0061] The target signal refers to the fault transient traveling wave signal when a fault occurs in a hybrid power distribution line.
[0062] In this embodiment, the fault location device inputs optimized monitoring data into a variational mode decomposition model for signal decomposition, so as to obtain the fault transient traveling wave signal when a fault occurs in the hybrid distribution line from the optimized monitoring data. After inputting the optimized monitoring data into the variational mode decomposition model, the fault location device first divides the optimized monitoring data into mode components with the same preset number of mode components, and performs Hilbert-Huang transform on the mode components. Subsequently, the center frequency and bandwidth of the preset number of mode components are estimated, and the spectrum of the mode components is adjusted to a specific frequency band based on the estimation results. The frequency band is constrained so that the superposition generates a transient signal that conforms to the fault condition. Then, using the Lagrangian function, the constrained problem is transformed into an unconstrained problem and the optimal solution is obtained, thereby obtaining the fault transient traveling wave signal when a fault occurs in the hybrid distribution line, i.e., the target signal.
[0063] S203, determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal.
[0064] Here, different nodes refer to the connection points of the mixed power distribution lines, on which primary and secondary integrated switches are deployed to monitor the signals arriving at the nodes.
[0065] In this embodiment of the application, the fault location device can collect and record in real time the first time difference when the target signal first arrives at both ends of the mixed power distribution line and the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, based on the primary and secondary fusion switches deployed at both ends and different nodes of the mixed power distribution line; at the same time, based on the known length of the mixed power distribution line and the arrival time data of the target signal, the propagation speed of the target signal on the line is calculated, and the propagation speed of the target signal is obtained.
[0066] S204. Based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal, determine the fault location of the mixed power distribution line.
[0067] In this embodiment, the fault location device can determine the fault location of the power distribution line by obtaining the first time difference of the target signal arriving at both ends of the mixed power distribution line, the second time difference of the target signal arriving at different nodes in the mixed power distribution line for the first time, and the propagation speed of the target signal. For example, the fault location system can first calculate the distance difference from the fault point to both ends of the mixed power distribution line based on the first time difference and the propagation speed of the target signal. Combined with the total length of the mixed power distribution line, the main branch section where the fault is located can be initially identified. Then, by analyzing the second time difference calculated by the fault location device at different nodes, an adjustment sequence is established to convert the time difference information of each node into spatial distance difference information, thereby determining the relative distance between the fault point and each node. Finally, the fault location device can determine the precise location information of the fault point within the determined fault interval through spatial geometric relationships.
[0068] In the above-mentioned high-precision sampling-based fault location method for hybrid power distribution lines, the original monitoring data of the hybrid power distribution lines is acquired and optimized to obtain optimized monitoring data. The optimized monitoring data is then input into a variational mode decomposition model for signal decomposition to obtain the target signal. The first time difference between the two ends of the hybrid power distribution line, the second time difference between the first arrival of the target signal at different nodes in the hybrid power distribution line, and the propagation speed of the target signal are determined. Based on the first time difference between the two ends of the hybrid power distribution line, the second time difference between the first arrival of the target signal at different nodes in the hybrid power distribution line, and the propagation speed of the target signal, the fault location of the hybrid power distribution line is determined. The above method, through data optimization processing, can remove interference data from the original monitoring data, improving the accuracy of subsequent model decomposition of signals; by using variational mode model to achieve accurate signal decomposition, it can effectively extract target signals directly related to the fault, and by calculating time difference and propagation speed, it can accurately locate the fault location of mixed distribution lines; and by using the time difference of different nodes, it can quickly locate the fault location, reducing time costs, and thus improving the accuracy of fault location when a fault occurs in a mixed distribution line.
[0069] In an exemplary embodiment, the phrase "determining the fault location of the mixed power distribution line based on the first time difference between the arrival of the target signal at both ends of the mixed power distribution line, the second time difference between the first arrival of the target signal at different nodes in the mixed power distribution line, and the propagation speed of the target signal" in S204 above is as follows: Figure 3 As shown, it includes:
[0070] S301, based on the second time difference of the first arrival of the target signal at different nodes in the hybrid power distribution line, the setting time sequence is obtained.
[0071] In this embodiment, the fault location device makes assumptions about each node on the hybrid distribution line. When a fault occurs at any node, it calculates the time difference between the first arrival of the fault traveling wave front at both ends of the line. The two ends of the line are denoted as M and N. As shown in the figure, A, B, C, and D are assumed to be nodes on the hybrid distribution line, and the time difference between the first arrival of the fault traveling wave front at both ends of the line is denoted as... ,in, This represents the time difference between the arrival of the faulty traveling wavefront at both ends of the line when a fault occurs at node A. This represents the time difference between the arrival of the faulty traveling wavefront at both ends of the line when a fault occurs at node B. This represents the time difference between the arrival of the faulty traveling wavefront at both ends of the line when a fault occurs at node C. This represents the time difference between the arrival of the faulty traveling wave front at both ends of the line when a fault occurs at node D. The fault location device uses the recorded time differences between the arrival of the faulty transient traveling wave front at each node as a positive definite sequence, for example... .
[0072] S302, determine the fault location of the mixed power distribution line based on the first time difference, the set time sequence, and the propagation speed of the target signal.
[0073] In this embodiment, the fault location device makes a preliminary judgment on the faulty area based on the relationship between the first time difference and the set time sequence. When making this preliminary judgment, the first time difference—the time difference between the first arrival of the target signal at both ends of the line—is used as the core basis. Figure 4 As shown, MP represents overhead lines in a mixed power distribution line, and PN represents cable lines in a mixed power distribution line. Their spatial lengths are respectively... and Assuming the fault occurs at connection point P of the line, the times when the target signal first arrives at M and N are respectively... The time difference can be represented by the relation (1), which is shown below:
[0074] (1);
[0075] in, and These represent the propagation speeds of traveling waves in overhead lines and cable lines, respectively. This indicates the time difference between the arrival of the fault traveling wave at both ends of the line.
[0076] When the fault point is located within the overhead line section MP, the following relationship exists, which is represented by relation (2), as shown below:
[0077] (2);
[0078] When the fault point is located within the PN section of the cable, the following relationship exists, which is expressed by equation (3), as shown below:
[0079] (3);
[0080] Furthermore, in actual engineering, the time data collected by the primary and secondary fusion switches may have errors. Therefore, when determining whether the two time differences are equal, a preset threshold needs to be added. That is, when The default is that the two are equal, and the preset threshold is used. The decision should be made based on the actual situation; at the same time, when the fault location device determines whether the distances are equal, a preset threshold should also be applied, i.e. .
[0081] After obtaining the first time difference, the fault location device can judge the fault interval based on the first time difference and the set time sequence, and determine the location of the fault point of the mixed power distribution line based on the judgment result, the propagation speed of the target signal, and the spatial geometric relationship.
[0082] In an exemplary embodiment, the phrase "determining the fault location of the hybrid distribution line based on the first time difference, the setting time sequence, and the propagation speed of the target signal" in S302 above is as follows: Figure 5 As shown, it includes:
[0083] S401, based on the relationship between the first time difference and each second time difference in the setting time sequence, determine the fault range of the hybrid distribution line.
[0084] In this embodiment, after a fault occurs, the fault location device can use high-precision sensors deployed at both ends of the line to capture the traveling wave signal generated at the fault point in real time and accurately record the time when the traveling wave front first arrives at the monitoring points at both ends. Based on the time data from both ends, the fault location device calculates the first time difference of the fault traveling wave propagation. Subsequently, the fault location device retrieves pre-established tuning sequence data, matches the first time difference calculated in real time with the threshold in the sequence, and determines the specific segment where the fault occurred.
[0085] S402, determine the fault location of the mixed distribution line based on the fault section, the first time difference, and the propagation speed of the target signal in the fault section.
[0086] In this embodiment, the fault location device first determines the fault range of the hybrid power distribution line by using the first time difference signal generated at the fault point and combining it with a preset setting sequence. Then, based on the determined fault range, the fault location device uses the first time difference data of the fault signal and the propagation speed of the target signal (i.e., the traveling wave of the fault signal) in the fault range, and establishes a mathematical model through the spatial topology and geometric relationship of the line. Finally, by solving the model, the device achieves accurate spatial location of the fault point of the hybrid power distribution line.
[0087] In an exemplary embodiment, the phrase "determining the fault range of the hybrid distribution line based on the relationship between the first time difference and each second time difference in the setting time sequence" in S401 above, such as... Figure 6 As shown, it includes:
[0088] S501, determine the time position of the first time difference based on the time range between each two adjacent second time differences.
[0089] In this embodiment of the application, after determining the time range between every two adjacent second time differences, the fault location device can compare the second time difference with the first time difference and determine the time position of the first time difference. For example, by Figure 7 As shown, after the fault occurs, the fault location device determines the location based on the first time difference. Fault search begins from the M end of the mixed distribution line. < If so, it indicates that the fault occurred in the MA interval; if ≤ < If, then it indicates that the fault occurred in the AB interval; if ≤ < This indicates that the fault occurred in the BC interval; if ≤ < This indicates that the fault occurred in the CD interval; if ≤ If the fault occurs in the DN section, then the fault location device can determine the fault section of the mixed distribution line.
[0090] S502, determine the positions of two switches on the line associated with the time position of the first time difference, and take the line section between the two switch positions as the fault section of the mixed distribution line.
[0091] In the embodiments of this application, such as Figure 8As shown, after obtaining the traveling wave signal of the fault current, the fault location device first uses Variational Mode Decomposition (VMD) to extract the traveling wave front information of the fault signal. Then, the fault location device determines the length of each section of the mixed distribution line and obtains the propagation speed of the traveling wave front in the cable and overhead line, respectively. Next, it calculates the time difference (i.e., the second time difference) of the traveling wave front reaching each connection point of the mixed distribution line using information recorded by the deployed primary and secondary fusion switches, and determines the time difference (i.e., the first time difference) between the two ends of the busbar (i.e., the two ends of the mixed distribution line). Then, it compares the first time difference with the second time difference, filters out two switch positions on the line associated with the position at the time of the first time difference, and marks the line section between these two switch positions as the fault interval. Finally, if the fault traveling wave is within this fault interval, the fault location device determines that the fault occurred within this interval and calculates the distance from the fault point to the two ends of the mixed distribution line. If it is not within this fault interval, then this interval is a non-fault interval.
[0092] In an exemplary embodiment, the phrase "determine the fault location of the hybrid distribution line based on the fault interval, the first time difference, and the propagation speed of the target signal in the fault interval" in S402 above is as follows: Figure 9 As shown, it includes:
[0093] S601, determine the first boundary position and the second boundary position of the fault range.
[0094] In this embodiment, the fault location device determines the fault range by comparing the first time difference with the second time difference. Subsequently, the first and second boundary positions of the fault range are determined based on the nodes corresponding to the fault range in the hybrid power distribution line.
[0095] S602, based on the first time difference and the propagation speed of the target signal in the fault interval, calculate the first distance between the fault point and the first boundary position and the second distance between the second boundary position.
[0096] In this embodiment, the fault location device first determines a first time difference based on the time it takes for the target signal to arrive at the first boundary and the time it takes for the signal to arrive at the second boundary. Then, combining the propagation speed of the target signal within the fault region, and based on the relationship between speed and time, the fault location device can calculate the first distance between the fault point and the first boundary, and the second distance between the fault point and the second boundary. Optionally, if the total distance of the fault region is known, the fault location device can also calculate the distance between the fault point and the second boundary using the distance at the first boundary and the total distance.
[0097] S603, determine the location of the fault point based on the first distance, the second distance, and the fault range.
[0098] In this embodiment of the application, the fault location device can determine the location of the fault point based on a first distance, a second distance, and a fault interval. For example, by... Figure 10 As shown, when the fault location device detects that the fault point is located at the connection point P between the cable and the overhead line, the distance from the fault point to the two ends M and N of the hybrid line can be represented by the relationship (4), which is shown below:
[0099] (4);
[0100] in, This represents the distance from the fault point to M; This represents the distance from the fault point to N; Indicates the cable length; This indicates the length of the overhead power line.
[0101] When the fault point is located within the overhead line section MP, there exists a relationship represented by equation (5), which is shown below:
[0102] (5);
[0103] in, This indicates the time it takes for the fault traveling wave to reach the M terminal; This indicates the time it takes for the fault traveling wave to reach the N terminal; This indicates the speed of the fault traveling wave on the cable; This indicates the speed of the fault traveling wave on the overhead line.
[0104] Therefore, the fault location device can calculate the distance from the fault point to end M according to the relationship (6), which is shown below:
[0105] (6);
[0106] Therefore, the fault location device can calculate the distance from the fault point to end N according to the relationship (7), which is shown below:
[0107] (7);
[0108] When the fault point is located within the cable section PN, there exists a relationship represented by equation (8), which is shown below:
[0109] (8);
[0110] Therefore, the fault location device can calculate the distance from the fault point to end N according to the relationship (9), which is shown below:
[0111] (9);
[0112] Therefore, the fault location device can calculate the distance from the fault point to end M according to the relationship (10), which is shown below:
[0113] (10);
[0114] Therefore, the fault location device can locate and determine the position of the fault point.
[0115] In one exemplary embodiment, the hybrid power distribution line fault location method based on high-precision sampling further includes, as... Figure 11 As shown, it includes:
[0116] S701 performs time interval filtering on the optimized monitoring data to determine the target time interval.
[0117] In this embodiment, after optimizing the original monitoring data, the fault location device can filter the time interval based on the optimized monitoring data to determine the time interval in which the first reflected wave arrives at both ends of the hybrid power distribution line. Figure 12 As shown, the fault location device first determines the earliest time when the traveling wave arrives at the measuring device by assuming the fault point, given the known fault range. and latest time Determine the time interval during which the first reflected wave arrives at the measuring device. Subsequently, assuming the fault occurs at connection point A, the closest point between the fault point and the busbar, the first reflected wave only travels once between this node and the busbar, and the time for the fault traveling wave to propagate to the busbar is the shortest time within the fault interval. The shortest time in the fault range It can be represented by relation (11), which is shown below:
[0118] (11);
[0119] in Let be the propagation speed of the traveling wave in the MA interval. If MA is a cable line, then... Take the speed of travel wave propagation in the cable; if MA is an overhead line, then Take the speed of travel wave propagation in the overhead line; This represents the distance between MA.
[0120] Subsequently, the fault location device assumes that the fault occurred at connection point B at the end of the fault section. The first reflected wave, in addition to one round trip between this connection point and the busbar, also travels three times between nodes A and B. The time it takes for the fault traveling wave to propagate to the busbar is the longest time in the fault section. The longest time of the fault interval It can be represented by relation (12), which is shown below:
[0121] (12);
[0122] in, Indicates the distance between MB; This represents the distance between A and B.
[0123] Then, since the fault point occurs between nodes A and B, i.e. within the AB section of the branch line, the time for the fault traveling wave to travel to the measuring device is between the shortest and longest time. That is, the time for the fault traveling wave to travel to the measuring device can be expressed by the relationship (13), which is shown below:
[0124] (13);
[0125] Therefore, the fault location device can perform preliminary screening of the original monitoring data and determine the time interval in which the first reflected wave arrives at the bus measurement device, i.e., the target time interval.
[0126] S702 inputs the signal in the target time segment into the variational mode decomposition model for signal decomposition to obtain the target signal.
[0127] In this embodiment of the application, after determining the target interval, the fault location device can input the signal in the target interval into the variational mode decomposition model for signal decomposition. First, the fault location device assumes that there are K modal components, and then performs Hilbert transform on these K modal components. The signal function can be represented by relation (14), which is shown below:
[0128] (14);
[0129] in, Indicates about time The partial derivative operator; Dirac Function (unit impulse function); The kernel function (time-domain form) representing the Hilbert transform; This represents the Kth mode component obtained after variational mode decomposition.
[0130] Subsequently, the fault location device uses a variational mode decomposition model to predict the center frequencies and bandwidths of these K modal components. Then, based on the prediction results, the spectrum of the modal components is adjusted to a specific frequency band, and the bandwidth is constrained so that their superposition conforms to the transient signal after the fault. The specific calculation is expressed by equation (15), which is shown below:
[0131] (15);
[0132] in: Represents K IMF components; This represents the center frequency of the K components.
[0133] Subsequently, using the Lagrange function, the constrained problem is transformed into an unconstrained problem and the optimal solution is obtained. The transformation relationship is expressed as in relation (16), which is shown below:
[0134] (16);
[0135] in, It represents the Lagrange multiplier.
[0136] During the solution process, through and By alternating updates, saddle points can be obtained. The specific process is as follows:
[0137] First, the initial estimates of each modal component of K. The initial center frequencies of the K modal components The initial frequency domain form of Lagrange multipliers Initialize with the balance factor n;
[0138] Subsequently, the K IMF components and the center frequencies of the K components are updated. The update of the K IMF components can be represented by relation (17), as shown below; the update of the center frequencies of the K components can be represented by relation (18), as shown below:
[0139] (17);
[0140] (18);
[0141] Subsequently, the Lagrange multipliers are updated in conjunction with relation (19), which is shown below:
[0142] (19);
[0143] Perform iterative calculations until the condition is met. in, , which represents the set convergence tolerance.
[0144] When the fault location device uses the variational mode decomposition model for phase mode transformation, K=4 is selected, that is, the three-phase current and total current of the fault traveling wave are used.
[0145] In an exemplary embodiment, the "optimized monitoring data includes operational distribution status data, and the original monitoring data is optimized to obtain optimized monitoring data" in S402 above, such as Figure 13 As shown, it includes:
[0146] S801 optimizes the raw monitoring data to obtain processed monitoring data.
[0147] In this embodiment, the fault location device can acquire the original monitoring data of the mixed power distribution line in real time through a high-precision current sensor, such as the traveling wave signal characteristics of the three-phase current and the total current, as well as key electrical signals such as zero-sequence current and zero-sequence voltage. To address issues such as sampling rate differences, redundant data, inconsistent dimensions, and noise interference in the original monitoring data, the fault location device can optimize the original monitoring data using optimization processing methods. For example, it can standardize the original monitoring data based on its normal distribution relationship. The standardization process can be represented by equation (20), which is shown below:
[0148] (20);
[0149] in, This is the original data; S is the mean of the data; S is the standard deviation of the data.
[0150] For data with unclear features, such as amplitude, scaling can be performed. The scaling process can be represented by the relation (21), which is shown below:
[0151] (twenty one);
[0152] in, The minimum value representing a characteristic of the original monitoring data; This represents the maximum value of the original monitoring data characteristics.
[0153] The fault location device can resample (upsample / downsample) multi-source monitoring signals, increasing or decreasing the frequency of the monitoring signals based on the original data, and performing principal component analysis to obtain the characteristic parameters of the online monitoring data samples. It can be represented by relation (22), which is shown below:
[0154] (twenty two);
[0155] in, This represents the random monitoring variable in this dimension of the original monitoring data.
[0156] S802 extracts nonlinear and linear online monitoring parameters from the monitoring data, and combines them with the online monitoring hyperplane equation to fuse the nonlinear and linear online monitoring parameters, thus obtaining the fused monitoring parameters.
[0157] Among them, the hyperplane equation for online monitoring is obtained by applying assumptions to the nonlinear sample data using the kernel function of the support vector machine.
[0158] In this embodiment of the application, since the parameters of the hybrid power distribution line are constantly changing during operation, the fault location device can also perform online monitoring and evaluation of the operating status of the hybrid power distribution line, and can evaluate the load rate of the hybrid power distribution line according to the online monitoring and evaluation process. The load rate of the hybrid power distribution line can be represented by the relationship (23), which is shown below:
[0159] (twenty three);
[0160] in, This indicates the line load distribution value; This indicates the operating current of the line.
[0161] The fault location device performs assumed processing on the nonlinear sample data using the kernel function of the support vector machine based on different types of online monitoring parameters. The resulting online monitoring hyperplane equation can be represented by relation (24), which is shown below:
[0162] (twenty four);
[0163] in, and Indicates different monitoring thresholds; This indicates the characteristics of the monitoring dimension.
[0164] The fault location device can perform fusion processing of the S-shaped function of the nonlinear online monitoring parameters and the linear online monitoring parameters based on the relation (24) to obtain the fused monitoring parameters.
[0165] S803 determines the operational distribution status data of the hybrid power distribution lines based on the integrated monitoring parameters.
[0166] In this embodiment, after obtaining the fused monitoring parameters, the fault location device can determine the operational distribution status data of the mixed distribution line based on the fused monitoring parameters. The fault location device first collects monitoring data of the mixed distribution line (such as current, voltage, line loss rate, power supply reliability, heavily overloaded areas, low-voltage areas, lifespan factor, and load rate). After collection, the monitoring data is resampled and processed using principal component analysis. The processed data is then input into a support vector machine model trained using the sample dataset for analysis, yielding the monitoring results, i.e., the operational distribution status data of the mixed distribution line. Figure 14 As shown.
[0167] In summary, based on all the above embodiments, a method for locating faults in hybrid power distribution lines based on high-precision sampling is also provided, such as... Figure 15 As shown, the method includes:
[0168] S901: Obtain the raw monitoring data of the mixed power distribution line, and optimize the raw monitoring data to obtain the processed monitoring data;
[0169] S902 extracts nonlinear and linear online monitoring parameters from the monitoring data, and combines them with the online monitoring hyperplane equation to fuse the nonlinear and linear online monitoring parameters to obtain the fused monitoring parameters;
[0170] S903, based on the integrated monitoring parameters, determines the operating distribution status data of the hybrid power distribution lines, and obtains optimized monitoring data;
[0171] S904, the optimized monitoring data is filtered by time interval to determine the target time interval;
[0172] S905 inputs the signal in the target time segment into the variational mode decomposition model to decompose the signal and obtain the target signal;
[0173] S906, determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0174] S907, based on the second time difference of the first arrival of the target signal at different nodes in the hybrid power distribution line, the setting time sequence is obtained;
[0175] S908, determine the time position of the first time difference based on the time range between each two adjacent second time differences;
[0176] S909, determine the two switch positions on the line associated with the time position of the first time difference, and take the line section between the two switch positions as the fault section of the mixed distribution line;
[0177] S910, determine the first and second boundary positions of the fault range;
[0178] S911, based on the first time difference and the propagation speed of the target signal in the fault interval, calculate the first distance between the fault point and the first boundary position and the second distance between the second boundary position;
[0179] S912 determines the location of the fault point based on the first distance, the second distance, and the fault interval.
[0180] The methods described in each of the above steps have been described in the foregoing embodiments. For details, please refer to the foregoing descriptions. They will not be repeated here.
[0181] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.
[0182] Based on the same inventive concept, this application also provides a high-precision sampling-based hybrid power distribution line fault location device for implementing the high-precision sampling-based hybrid power distribution line fault location method described above. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the hybrid power distribution line fault location device provided below can be found in the limitations of the high-precision sampling-based hybrid power distribution line fault location method described above, and will not be repeated here.
[0183] In one exemplary embodiment, such as Figure 16 As shown, a hybrid power distribution line fault location device based on high-precision sampling is provided, comprising:
[0184] The optimization module 11 is used to acquire the original monitoring data of the mixed power distribution line and optimize the original monitoring data to obtain the optimized monitoring data.
[0185] Decomposition module 12 is used to input the optimized monitoring data into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0186] The first determining module 13 is used to determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0187] The second determining module 14 is used to determine the fault location of the mixed power distribution line based on the first time difference between the arrival of the target signal at both ends of the mixed power distribution line, the second time difference between the arrival of the target signal at different nodes in the mixed power distribution line for the first time, and the propagation speed of the target signal.
[0188] Each module in the aforementioned high-precision sampling-based hybrid power distribution line fault location device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.
[0189] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 17As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a hybrid power distribution line fault location method based on high-precision sampling. The display unit of the computer device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.
[0190] Those skilled in the art will understand that Figure 17 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0191] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:
[0192] The raw monitoring data of the mixed power distribution lines is obtained and optimized to obtain the optimized monitoring data.
[0193] The optimized monitoring data is input into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0194] Determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0195] The fault location of the mixed power distribution line is determined based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal.
[0196] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:
[0197] The raw monitoring data of the mixed power distribution lines is obtained and optimized to obtain the optimized monitoring data.
[0198] The optimized monitoring data is input into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0199] Determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0200] The fault location of the mixed power distribution line is determined based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal.
[0201] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:
[0202] The raw monitoring data of the mixed power distribution lines is obtained and optimized to obtain the optimized monitoring data.
[0203] The optimized monitoring data is input into the variational mode decomposition model for signal decomposition to obtain the target signal;
[0204] Determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal;
[0205] The fault location of the mixed power distribution line is determined based on the first time difference when the target signal arrives at both ends of the mixed power distribution line, the second time difference when the target signal first arrives at different nodes in the mixed power distribution line, and the propagation speed of the target signal.
[0206] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.
[0207] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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, they should be considered to be within the scope of this application.
[0208] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.
Claims
1. A method for locating faults in hybrid power distribution lines based on high-precision sampling, characterized in that, The method includes: The original monitoring data of the hybrid power distribution line is obtained, and the original monitoring data is optimized to obtain optimized monitoring data; The optimized monitoring data is input into a variational mode decomposition model for signal decomposition to obtain the target signal; Determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal; The fault location of the hybrid power distribution line is determined based on the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal.
2. The method according to claim 1, characterized in that, The step of determining the fault location of the hybrid power distribution line based on the first time difference between the arrival of the target signal at both ends of the hybrid power distribution line, the second time difference between the first arrival of the target signal at different nodes in the hybrid power distribution line, and the propagation speed of the target signal includes: The setting time sequence is obtained based on the second time difference of the first arrival of the target signal at different nodes in the hybrid power distribution line; The fault location of the hybrid power distribution line is determined based on the first time difference, the set time sequence, and the propagation speed of the target signal.
3. The method according to claim 2, characterized in that, Determining the fault location of the hybrid power distribution line based on the first time difference, the set time sequence, and the propagation speed of the target signal includes: Based on the relationship between the first time difference and each second time difference in the set time sequence, the fault range of the hybrid power distribution line is determined; The fault location of the hybrid power distribution line is determined based on the fault interval, the first time difference, and the propagation speed of the target signal in the fault interval.
4. The method according to claim 3, characterized in that, The step of determining the fault range of the hybrid distribution line based on the relationship between the first time difference and each second time difference in the set time sequence includes: The time position of the first time difference is determined based on the time range between each two adjacent second time differences; Determine the two switch positions on the line associated with the time position of the first time difference, and define the line interval between the two switch positions as the fault interval of the hybrid power distribution line.
5. The method according to claim 3, characterized in that, Determining the fault location of the hybrid power distribution line based on the fault interval, the first time difference, and the propagation speed of the target signal in the fault interval includes: Determine the first and second boundary positions of the fault interval; Based on the first time difference and the propagation speed of the target signal in the fault interval, calculate the first distance between the fault point and the first boundary position and the second distance between the second boundary position; The location of the fault point is determined based on the first distance, the second distance, and the fault interval.
6. The method according to claim 1, characterized in that, The method further includes: The optimized monitoring data is then filtered by time interval to determine the target time interval. The step of inputting the optimized monitoring data into a variational mode decomposition model for signal decomposition to obtain the target signal includes: The signal in the target time segment is input into the variational mode decomposition model for signal decomposition to obtain the target signal.
7. The method according to any one of claims 1-5, characterized in that, The optimized monitoring data includes operational distribution status data. The optimization process of the original monitoring data to obtain the optimized monitoring data includes: The original monitoring data is optimized to obtain the processed monitoring data; Nonlinear and linear online monitoring parameters are extracted from the processed monitoring data, and then fused using the online monitoring hyperplane equation to obtain the fused monitoring parameters. The online monitoring hyperplane equation is obtained by applying assumptions to the nonlinear sample data using the kernel function of a support vector machine. The operational distribution status data of the hybrid power distribution line are determined based on the integrated monitoring parameters.
8. A hybrid power distribution line fault location device based on high-precision sampling, characterized in that, The device includes: An optimization module is used to acquire the original monitoring data of the hybrid power distribution line and optimize the original monitoring data to obtain optimized monitoring data. The decomposition module is used to input the optimized monitoring data into the variational mode decomposition model for signal decomposition to obtain the target signal; The first determining module is used to determine the first time difference when the target signal arrives at both ends of the hybrid power distribution line, the second time difference when the target signal first arrives at different nodes in the hybrid power distribution line, and the propagation speed of the target signal; The second determining module is used to determine the fault location of the hybrid power distribution line based on the first time difference between the arrival of the target signal at both ends of the hybrid power distribution line, the second time difference between the first arrival of the target signal at different nodes in the hybrid power distribution line, and the propagation speed of the target signal.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.