Single-phase disconnection fault detection method and system based on wavelet transform

Abstract

The invention relates to the technical field of single-phase disconnection detection of an ungrounded system, in particular to a single-phase disconnection fault detection method and system based on wavelet transform. A plurality of detection points are arranged on a distribution line of the power distribution network; line voltage amplitude signals of all the detection points are collected, and a data set is formed; performing wavelet transform processing on the data set to obtain a detail coefficient corresponding to each detection point; comparing the absolute value of the detail coefficient with a preset threshold value to judge a broken line fault; and determining the position of the fault section according to the detail coefficients exceeding the preset threshold. The detection points comprise a main line detection point, a branch line detection point and an end point detection point, and the detection point spacing distance is set according to the line importance degree and load distribution; and performing signal processing by adopting Haar wavelet transform to obtain a threshold value based on a detail coefficient in a normal operation state. Through a method of combining wavelet transform and adaptive threshold determination, quick and accurate detection of a broken line fault is realized without traversing a network topology structure, and the calculation complexity is greatly reduced.

Description

Technical Field

[0001] The invention relates to the technical field of single-phase disconnection detection in an ungrounded system, and in particular to a single-phase disconnection fault detection method and system based on wavelet transform. Background Art

[0002] Line breakage is one of the common fault types in distribution networks. With the increasing utilization of overhead insulated wires, line breakage has occurred frequently in recent years. There are many reasons for line breakage in distribution networks, mainly the following: natural factors, such as storms, lightning strikes, hail or tree collapses, can directly damage overhead lines and cause line breakage; equipment aging, wear, corrosion or material fatigue during long-term operation may also cause wire breakage; human error, improper construction, maintenance errors or external activities can also cause line breakage. Line breakage has a huge impact on the stability and safety of the power grid, which may lead to insufficient power supply, damage to electrical equipment, etc. In severe cases, it may also cause accidents such as electric shock to humans and animals and forest fires.

[0003] Since a single-phase line break fault in an ungrounded system is often accompanied by a high-resistance grounding, the fault current is weak at this time, and the existing distribution network protection device cannot act in time, resulting in serious consequences. However, most of the current line break fault detection methods have certain limitations. For example, the method of using node current to locate the fault requires traversing the topological structure, which is computationally intensive and takes a long time to calculate. The method for diagnosing branch line break proposed based on the data of the power distribution information system and the association rule algorithm is greatly affected by the network structure. Once the network structure changes, it is necessary to accumulate historical data again and mine new rules, which requires a large amount of calculation. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to solve the problem that most of the current disconnection fault detection methods have certain limitations. For example, the method of using node current to locate the fault needs to traverse the topological structure, which has a large amount of calculation and a long operation time. The method of diagnosing branch line disconnection proposed based on the distribution and utilization information system data and the association rule algorithm is greatly affected by the network structure. Once the network structure changes, it is necessary to accumulate historical data again and mine new rules, which has a large amount of calculation.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a single-phase disconnection fault detection method based on wavelet transform, which comprises setting a plurality of detection points on a distribution line of a distribution network;

[0008] Collect the line voltage amplitude signal of each detection point and form a data set;

[0009] Performing wavelet transform processing on the data set to obtain detail coefficients corresponding to each detection point;

[0010] Compare the absolute value of the detail coefficient with a preset threshold value to determine a disconnection fault;

[0011] The location of the fault section is determined based on the detail coefficient exceeding the preset threshold.

[0012] As a preferred solution of the single-phase line break fault detection method based on wavelet transform described in the present invention, the detection points include: main line detection points, branch line detection points and endpoint detection points; the distance between the detection points is set according to the importance of the line and the load distribution.

[0013] As a preferred solution of the single-phase line break fault detection method based on wavelet transform described in the present invention, the determination of the fault section position includes: marking the detection points exceeding the preset threshold as the first fault point, the second fault point and the Nth fault point; finding the detection points adjacent to each fault point and whose absolute value of the detail coefficient does not exceed the preset threshold as reference points; the fault section is located between the fault point and its adjacent reference point.

[0014] As a preferred solution of the single-phase line break fault detection method based on wavelet transform described in the present invention, the preset threshold is determined according to the following steps: obtaining the detail coefficient of each detection point under normal operating conditions; determining the maximum absolute value of the detail coefficient under normal operating conditions; and taking the multiple value of the maximum absolute value as the preset threshold.

[0015] As a preferred solution of the single-phase disconnection fault detection method based on wavelet transform described in the present invention, wherein: the distribution line includes: cable line, overhead line and hybrid line; the setting of the detection points takes into account the line type characteristics.

[0016] As a preferred solution of the single-phase line break fault detection method based on wavelet transform described in the present invention, after determining the line break fault, it also includes: recording the time and duration of the fault; recording the signal characteristics of each detection point when the fault occurs; and generating a fault characteristic report.

[0017] As a preferred solution of the single-phase broken line fault detection method based on wavelet transform described in the present invention, the wavelet transform adopts Haar wavelet transform, including: normalizing the original signal; performing multi-scale decomposition to obtain multi-layer detail coefficients; and selecting the detail coefficients that best reflect the fault characteristics.

[0018] In a second aspect, an embodiment of the present invention provides a single-phase disconnection fault detection system based on wavelet transform, which includes a detection point setting module, and a plurality of detection points are respectively set on the distribution lines of the distribution network;

[0019] A data acquisition module collects the line voltage amplitude signal of each detection point and forms a data set;

[0020] The signal processing module performs wavelet transform processing on the data set to obtain detail coefficients corresponding to each detection point;

[0021] A fault determination module compares the absolute value of the detail coefficient with a preset threshold value to determine a disconnection fault;

[0022] The location positioning module determines the location of the fault section based on the detail coefficient exceeding the preset threshold.

[0023] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the single-phase line break fault detection method based on wavelet transform as described in the first aspect of the present invention are implemented.

[0024] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the single-phase line break fault detection method based on wavelet transform as described in the first aspect of the present invention are implemented.

[0025] The beneficial effects of the present invention are as follows: the present invention can quickly process large-scale data, is suitable for real-time online detection, and reduces the need for topology traversal and a large number of calculations. By accurately setting the threshold range, weak fault signals can be reliably identified, and are less affected by changes in the transition resistance of the broken line, thereby improving the accuracy of fault location. It does not need to rely on historical data accumulation and rule mining, is suitable for complex power grid environments with variable network structures, and has broad application prospects. It effectively avoids power grid stability problems and potential safety hazards that may be caused by missed faults, and provides reliable protection for the operation of the distribution network. A large number of simulation verification results show that this method can accurately detect single-phase broken line faults and accurately locate the faulty section, and has significant advantages in improving the reliability and accuracy of fault detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 It is a flow chart of a single-phase disconnection fault detection method based on wavelet transform;

[0028] Figure 2 A computer device diagram for a single-phase disconnection fault detection method based on wavelet transform;

[0029] Figure 3 This is a single-phase line break fault simulation circuit diagram of a single-phase line break fault detection method based on wavelet transform. DETAILED DESCRIPTION

[0030] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0031] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0032] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0033] Example 1

[0034] Reference Figure 1-2 , which is the first embodiment of the present invention, and provides a single-phase power failure fault detection method based on wavelet transform, comprising:

[0035] S100: setting a plurality of detection points on the distribution lines of the distribution network;

[0036] In the embodiment of the present application, the detection points include trunk line detection points, branch line detection points and endpoint detection points; the distance between the detection points is set according to the importance of the line and the load distribution.

[0037] Specifically, the main line detection points are set on the main line of the distribution network, usually one detection point is set every 1-2 kilometers, and the important line sections can be appropriately encrypted; the branch line detection points are set on each branch line, and generally detection points must be set at the starting point and end point of the branch line; the end point detection points are set at the end of the line and the important load access point. For example, for a 10-kilometer-long main line, main line detection points can be set at 2km, 4km, 6km, and 8km, and branch line detection points can be set at the beginning and end of the branch line branched at 3km.

[0038] In an optional embodiment, the arrangement of the detection points also needs to consider the following factors:

[0039] Testing points must be set up at the outgoing line of the substation; testing points should be set up at the access points of important users; it is recommended to set up testing points on both sides of the boundary switch; the installation conditions and communication conditions of the testing equipment should be considered.

[0040] In an optional embodiment, in order to improve the reliability of detection, the detection point can also adopt a redundant design. For example, a backup detection point can be set at a key node, and when the main detection point fails, it can automatically switch to the backup detection point to ensure the continuous and reliable operation of the detection system.

[0041] It should be noted that the reasonable layout of detection points is crucial to the accuracy of fault location. Too few detection points will lead to insufficient fault location accuracy, while too many detection points will increase system cost and maintenance difficulty. Therefore, it is necessary to find a balance between cost and benefit. At the same time, the layout of detection points also needs to consider the actual operation and maintenance conditions to ensure that the installation, maintenance and communication conditions of the detection equipment meet the requirements.

[0042] S101: The detection points include: trunk line detection points, branch line detection points and endpoint detection points; the distance between detection points is set according to the importance of the line and the load distribution.

[0043] S102: Distribution lines include: cable lines, overhead lines and mixed lines; the setting of detection points takes into account the characteristics of the line type.

[0044] S200: collecting line voltage amplitude signals at each detection point and forming a data set;

[0045] In an optional embodiment, the data acquisition device includes a voltage transformer, a data acquisition unit, a data processing unit and a communication unit. The voltage transformer converts the voltage signal on the high voltage side into a standard 100V signal; the data acquisition unit contains an A / D converter to convert the analog signal into a digital signal; the data processing unit performs preliminary processing on the collected digital signal; and the communication unit is responsible for transmitting the processed data to the central processing system in real time.

[0046] In the embodiment of the present application, in order to improve the reliability of data collection, the collection device adopts a real-time monitoring mode. The system collects data from all detection points every 0.02 seconds through a timed polling method to ensure that the transient characteristics of the disconnection fault can be captured in time.

[0047] In an optional embodiment, data collection can also adjust the sampling strategy according to different operating states. For example, when the system is in normal operation, the sampling frequency can be appropriately reduced to reduce the amount of data transmission; when suspicious fluctuations are detected, the sampling frequency is automatically increased to obtain more detailed fault feature information.

[0048] It should be noted that the quality of data collection directly affects the accuracy of subsequent fault detection. Therefore, the system sets up a complete data quality control mechanism, including signal anomaly detection, data validity verification, etc., to ensure the reliability of collected data. At the same time, in response to possible communication interruptions, each detection point also has a local data cache function, which can temporarily store historical data for a certain period of time.

[0049] S300: Perform wavelet transform processing on the data set to obtain detail coefficients corresponding to each detection point;

[0050] In the embodiment of the present application, the wavelet transform process uses the Haar wavelet function, which has the characteristics of simple calculation and strong edge feature extraction capability, and is particularly suitable for detecting voltage mutation characteristics during line break faults.

[0051] Specifically, the system first preprocesses the collected line voltage amplitude data, including data standardization, denoising and other operations, to make the data more suitable for wave correction analysis. Then, the preprocessed data is decomposed into multiple scales using Haar wavelet to obtain detail coefficients at different scales, and the detail coefficients that best reflect the characteristics of the line break fault are selected.

[0052] In an optional embodiment, different wavelet basis functions may be selected according to actual application scenarios. For example, in situations where more sophisticated fault characteristics are required, a wavelet basis such as db4 wavelet with better approximation performance may be selected, but the increase in computational complexity needs to be weighed.

[0053] In an optional embodiment, the number of layers of wavelet decomposition can be flexibly set according to actual needs. Usually, 3-5 layers of decomposition are used, which can effectively extract fault features without bringing too much computational burden.

[0054] It should be noted that wavelet transform processing is one of the core steps of this method. Through wavelet transform, the original signal can be decomposed into different frequency components, and the characteristic signal generated by the disconnection fault can be effectively extracted. At the same time, wavelet transform has good time-frequency localization characteristics and can accurately locate the time when the fault occurs.

[0055] S301: The wavelet transform adopts Haar wavelet transform, including: normalizing the original signal; performing multi-scale decomposition to obtain multi-layer detail coefficients; and selecting detail coefficients that best reflect the fault characteristics.

[0056] S400: comparing the absolute value of the detail coefficient with a preset threshold value to determine a disconnection fault;

[0057] In the embodiment of the present application, the system adopts an adaptive threshold determination mechanism. First, the absolute value of the detail coefficient of each detection point under normal operating conditions is obtained, and the maximum value is taken as the reference value, and then the reference value is magnified by a certain multiple as the fault determination threshold. After a large number of experimental verifications, taking 10 times the reference value as the threshold can achieve better detection results.

[0058] In an optional embodiment, the threshold value may be determined by a more complex statistical method. For example, long-term operation data may be collected, a normal distribution model may be established, and a suitable threshold value may be determined according to the confidence requirement, so as to better balance the detection sensitivity and the false alarm rate.

[0059] In an optional embodiment, the system can also set multiple thresholds. For example, two levels of early warning threshold and alarm threshold are set. When the detail coefficient exceeds the early warning threshold but does not reach the alarm threshold, the system sends a warning signal; when it exceeds the alarm threshold, it is directly determined as a disconnection fault.

[0060] It should be noted that the setting of the threshold directly affects the reliability of fault detection. If the threshold is set too low, it is easy to cause false alarms, and if it is set too high, it may lead to missed alarms. This method selects multiples of the maximum value of the detail coefficient under normal conditions as the threshold, which not only ensures sufficient detection sensitivity but also effectively avoids false alarms. At the same time, the system also has an automatic threshold correction function, which can continuously optimize the threshold setting based on operating experience.

[0061] S401: After determining the disconnection fault, the method further includes: recording the time when the fault occurs and the duration; recording the signal characteristics of each detection point when the fault occurs; and generating a fault characteristic report.

[0062] S500: Determine the location of the fault section according to the detail coefficient exceeding the preset threshold.

[0063] In the embodiment of the present application, the fault section is located by comparing adjacent detection points. The system automatically identifies all detection points whose absolute values ​​of detail coefficients exceed the threshold and marks these points as fault points; then finds detection points adjacent to each fault point whose detail coefficients do not exceed the threshold and marks them as reference points. The fault section is the line section between the fault point and its corresponding reference point.

[0064] Specifically, when the detail coefficients of multiple detection points exceed the threshold at the same time, the system uses the following strategy to determine the fault section: first, these detection points are sorted from near to far according to the distance from the substation, and marked as the first fault point, the second fault point, etc.; then, the nearest reference point is found for each fault point. Usually, the detail coefficients on both sides of the fault point will show obvious asymmetry, and the detail coefficients of the detection points on the side close to the actual fault location will be significantly greater than those of the detection points on the side far from the fault location.

[0065] In an optional embodiment, the fault location can also be combined with other auxiliary information to improve accuracy. For example, the size change trend of the detail coefficient of each detection point can be used in combination with the line impedance characteristics to further estimate the specific location of the fault point in the location section. When the fault occurs on a branch line, the size of the detail coefficient of the detection points of the main line and the branch line can be compared to determine whether the fault occurs on the main line or the branch line.

[0066] In an optional embodiment, the system can also establish a credibility assessment mechanism for fault location. For example, the credibility of the positioning result is scored based on factors such as the number of detection points involved in fault location, the contrast of detail coefficients of adjacent detection points, etc. For positioning results with low credibility, the system will mark special prompts for further verification by operation and maintenance personnel.

[0067] It should be noted that accurate fault section location is crucial for rapid fault isolation and power restoration. This method can effectively determine the location of the fault section by analyzing the change characteristics of the detail coefficients of adjacent detection points. At the same time, considering the complex structures of branches and ring networks in actual lines, the system adds multiple auxiliary criteria to the positioning algorithm to improve the accuracy and reliability of fault location.

[0068] S501: Determination of the location of the fault section includes: marking the detection points that exceed the preset threshold as the first fault point, the second fault point and the Nth fault point; finding the detection points adjacent to each fault point and whose absolute value of the detail coefficient does not exceed the preset threshold as reference points; the fault section is located between the fault point and its adjacent reference point.

[0069] S502: The preset threshold is determined according to the following steps: obtaining the detail coefficient of each detection point under normal operating conditions; determining the maximum absolute value of the detail coefficient under normal operating conditions; and taking a multiple of the maximum absolute value as the preset threshold.

[0070] In the embodiment of the present application, when the system detects a disconnection fault and completes the location, a standardized fault report will be automatically generated. The fault report contains key information such as the time of the fault, the location of the fault section, the fault characteristic data, and the reliability of the fault location.

[0071] Specifically, the generation of fault reports adopts a hierarchical management mechanism. The system will classify faults into different levels according to factors such as the severity of the fault and the scope of impact. For high-level faults, in addition to generating regular fault reports, the system will also initiate an emergency response process and notify relevant persons in charge through various means such as text messages and phone calls.

[0072] In an optional embodiment, the processing flow of the fault report can be further refined. For example, different processing plans can be automatically generated according to the importance of the fault section; the cause of the fault can be preliminarily analyzed and judged based on historical fault data; and the optimal inspection route can be provided to the fault handling personnel in combination with the geographic information system.

[0073] In an optional embodiment, the system can also establish a knowledge base management system for fault reports. The detailed information, processing process and processing results of each fault are stored in the knowledge base for subsequent statistical analysis and experience summary. These data can be used to optimize the detection algorithm parameters and improve the accuracy of fault identification.

[0074] It should be noted that standardized fault report management is of great significance for improving fault handling efficiency and accumulating operation and maintenance experience. This method realizes standardized management and efficient use of fault information by establishing a complete fault report generation and processing mechanism. At the same time, through the accumulation and analysis of historical data, the fault detection and processing process is continuously optimized, which improves the operational reliability of the entire system.

[0075] Furthermore, this embodiment also provides a single-phase disconnection fault detection system based on wavelet transform, comprising:

[0076] A detection point setting module is used to set a number of detection points on the distribution lines of the distribution network;

[0077] A data acquisition module collects the line voltage amplitude signal of each detection point and forms a data set;

[0078] The signal processing module performs wavelet transform processing on the data set to obtain detail coefficients corresponding to each detection point;

[0079] A fault determination module compares the absolute value of the detail coefficient with a preset threshold value to determine a disconnection fault;

[0080] The location positioning module determines the location of the fault section based on the detail coefficient exceeding the preset threshold.

[0081] In summary, by setting up multi-level detection points (main lines, branch lines, and endpoint detection points) on the distribution lines and reasonably setting the distance between detection points according to the importance of the lines and the load distribution, comprehensive monitoring coverage of the entire distribution network is achieved, effectively solving the problems of many blind spots in monitoring and unreasonable layout of monitoring points in traditional methods, making fault detection more comprehensive and reliable.

[0082] By adopting the innovative method of wavelet transform to process voltage signals, instead of the traditional node current analysis method, the accurate extraction of disconnection fault characteristics is achieved. This method does not need to traverse the network topology structure, greatly reduces the computational complexity, and significantly improves the real-time and accuracy of fault detection.

[0083] By setting up an adaptive threshold judgment mechanism, the intelligent identification of disconnection faults under various complex working conditions is realized. This mechanism overcomes the shortcomings of poor adaptability of the traditional fixed threshold method, effectively avoids false positives and false negatives in detection, and improves the reliability of detection.

[0084] The fault location method of comparing adjacent detection points combined with the asymmetric analysis of fault characteristics achieves rapid and accurate location of the fault section. This method overcomes the shortcomings of traditional location methods that rely on historical data and are greatly affected by changes in network structure, and the location results are more accurate and reliable.

[0085] By establishing a complete fault reporting and information management mechanism, standardized management of fault information and knowledge accumulation are achieved. This mechanism can continuously optimize system performance, continuously improve the accuracy of fault detection, and provide reliable support for power grid operation and maintenance management.

[0086] Example 2

[0087] Reference Figure 2 - Figure 3 , which is the second embodiment of the present invention, and this embodiment provides a single-phase line break fault detection method based on wavelet transform. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0088] Several detection points are set up on the distribution lines of the distribution network.

[0089] Furthermore, the power distribution lines include cables, overhead lines, and hybrid lines consisting of cables and overhead lines.

[0090] The line voltage amplitude signal of each detection point is collected to form a data set of each detection point.

[0091] Furthermore, the acquisition frequency of the line voltage amplitude signal is set to 0.02s.

[0092] The line voltage amplitude in each data set is subjected to wavelet transformation to obtain the detail coefficient corresponding to each detection point.

[0093] Furthermore, the wavelet transform adopts Haar wavelet transform.

[0094] Furthermore, the wavelet transform is performed on the line voltage amplitude in each data set to obtain the detail coefficient corresponding to each detection point, which specifically includes the following steps:

[0095] Data preprocessing, including normalization, can be performed to make the data at different detection points comparable and to avoid the adverse effects of too large or too small values ​​on the wavelet transform. The commonly used normalization method is to map the elements of each data set to the interval [0, 1] or [-1, 1].

[0096] For example, for normalization to the interval [0,1], the following formula can be used:

[0097]

[0098] in, is the normalized sample. V i = {v i1 ,v i2 ,…,v im};v ij Represents the jth voltage amplitude sample at the ith detection point.

[0099] Select a wavelet transform function, and select a suitable wavelet transform function according to data characteristics and analysis purposes. The wavelet transform adopts Haar wavelet transform.

[0100] Principle of Haar wavelet transform

[0101] 1.1 Characteristics of Haar wavelet transform. Haar wavelet is one of the earliest wavelet bases. Compared with other wavelet bases, Haar wavelet has the following significant characteristics:

[0102] 1. Simplicity: The mathematical form of Haar wavelet is simple, the calculation process is efficient, and it is suitable for real-time online fault detection.

[0103] 2. Fast calculation: Haar wavelet transform can be implemented through simple addition and subtraction, with fast calculation speed, suitable for large-scale data processing.

[0104] 3. Good edge detection capability: Haar wavelet has good detection capability for signal mutation points (such as fault points) and can effectively identify mutations in current and voltage.

[0105] Because of these characteristics, this paper selects Haar wavelet as the analysis tool for single-phase line break fault detection, and uses its localization characteristics in the time domain and its advantages in signal mutation detection to detect fault characteristic signals.

[0106] The process of Haar wavelet transform. In the decomposition process of Haar wavelet transform, 2i original signals can be decomposed once to obtain detail coefficients d i , d i The expression is as follows:

[0107]

[0108] Among them, x 2i and x 2i+1 are two adjacent points of the original signal.

[0109] Finally, we get 2i-1 detail coefficients.

[0110] Furthermore, when determining the detail coefficient corresponding to each detection point, first perform Haar wavelet transform on the data set corresponding to the detection point, obtain several detail coefficients, find the maximum value among the absolute values ​​of all detail coefficients, and use the maximum value as the absolute value of the detail coefficient corresponding to the detection point. For example, the data set corresponding to the i-th detection point has 100 data, and after performing Haar wavelet transform, 100 detail coefficients are obtained. Find the maximum absolute value of the 100 detail coefficients, and use the maximum value H as the absolute value of the detail coefficient corresponding to the detection point. max As the absolute value of the detail coefficient corresponding to the i-th detection point.

[0111] The absolute value of the named detail coefficient is compared with a predetermined threshold value. If the absolute value of the detail coefficient exceeds the threshold value, it is determined that a disconnection fault has occurred in the distribution line.

[0112] Furthermore, the threshold is 10 times the maximum absolute value of the detail coefficients of the normal power distribution lines.

[0113] Furthermore, in this embodiment, during normal operation, the collected line voltage is subjected to wavelet transformation to calculate the absolute value of the detail coefficient, wherein the maximum value is 36.2. To increase the sensitivity and reliability of detection, ten times the maximum absolute value of the detail coefficient of the normal line is used as the threshold for fault detection, that is, the threshold is 362.

[0114] Furthermore, in order to reduce the amount of judgment calculation, the maximum value of the absolute value of the detail coefficient is compared with a predetermined threshold range. If it exceeds the range, it is considered that a fault has occurred.

[0115] The fault point location is determined according to the detail coefficient whose absolute value exceeds the threshold. The fault location is located between the detection point corresponding to the detail coefficient whose absolute value exceeds the threshold and the detection point closest to the detection point within the threshold range.

[0116] Furthermore, the method of determining the location of the fault point according to the detail coefficient whose absolute value exceeds the threshold value comprises the following specific steps:

[0117] The detection points corresponding to the detail coefficients whose absolute values ​​exceed the threshold are set as the first super detection point, the second super detection point, ... the Nth super detection point;

[0118] Each detection point has at least one adjacent detection point as a first adjacent detection point;

[0119] The absolute values ​​of the detail coefficients of the adjacent detection points of each super detection point are checked respectively. If the absolute value of the detail coefficient of the first adjacent detection point of the i-th super detection point is less than the threshold, the fault point is located between the i-th super detection point and its first adjacent detection point.

[0120] Simulation verification, the specific steps are as follows:

[0121] like Figure 3 As shown in the figure, a simulation model of single-phase line-break fault in 10kV neutral point ungrounded system is established by using Matlab / Simulink simulation software. The rated capacity of the step-down transformer in the system is 20MVA, and the rated voltages of the high and low voltage sides are 110kV and 10kV respectively; it is assumed that the system has 6 outgoing lines; l2 is a cable line; l6 is an overhead line-cable hybrid line, the overhead line is distributed upstream of the line, 3km long, and the cable line is distributed downstream of the line, 6km long; the other 4 lines are overhead lines; the parameters of each type of line are shown in Table 1; as shown in l6 in the figure, the three-phase balanced load in the model adopts a triangle connection, which is set to 0.2MVA, 0.5MVA, 1MVA, 2MVA respectively, and the power factor is 0.9.

[0122] Select l6 as the fault line, A phase broken line fault, the fault locations are set at 2km, 4km, and 7km away from the busbar, and the grounding resistance is set to 10Ω, 200Ω, 1000Ω, 10kΩ, and ∞, respectively; set 6 detection points, of which Q1, Q2, Q3, and Q4 are located on the fault line l6, 1km, 3km, 5km, and 8km away from the busbar, respectively, and Q5 and Q6 are located on the sound line l4, 3km and 7km away from the busbar, respectively.

[0123] Table 1 Line parameters

[0124]

[0125]

[0126] R d =R d ′=∞ (broken line and ungrounded fault), the load capacity is 0.5MVA, the fault location is 4km away from the busbar, and the maximum absolute value of the Haar wavelet detail coefficient at each detection point is H max The line operation status determined according to the criteria proposed in this paper is shown in Table 2.

[0127] Table 2 Detection points H for disconnection and ungrounded fault max Data and judgment results

[0128] Detection point <![CDATA[H max ]]> Judgment result Correctness <![CDATA[Q1]]> 22.7 No disconnection failure occurred √ <![CDATA[Q2]]> 29.2 No disconnection failure occurred √ <![CDATA[Q3]]> 5350 A disconnection failure occurred √ <![CDATA[Q4]]> 5351 No disconnection failure occurred √ <![CDATA[Q5]]> 3.4 No disconnection failure occurred √ <![CDATA[Q6]]> 3.3 No disconnection failure occurred √

[0129] It can be seen from Table 2 that the fault section is between Q2 and Q3, and its Hmax is much larger than the set threshold, while the H max are all less than the threshold.

[0130] When the transition resistance combination scenario is changed and other conditions are the same as above, the fault commutation voltages on both sides of the fault and the determined line operation status are shown in Table 3.

[0131] Table 3 H under different transition resistance conditions max Data and judgment results

[0132] Transition resistance <![CDATA[H max ]]> Judgment result Correctness <![CDATA[R d =∞,R′ d =10Ω]]> 5207 A disconnection failure occurred √ <![CDATA[R d =10Ω,R′ d =∞]]> 4752 A disconnection failure occurred √ <![CDATA[R d =200Ω,R′ d =200Ω]]> 4118 A disconnection failure occurred √ <![CDATA[R d =1kΩ,R′ d =1kΩ]]> 5243 A disconnection failure occurred √ <![CDATA[R d =10kΩ,R′ d =10kΩ]]> 5330 A disconnection failure occurred √

[0133] By changing the system structure, disconnection position, grounding resistance, and load impedance, a large number of simulations are performed. Combining Tables 2 and 3, it can be seen that after a single-phase disconnection fault occurs in an ungrounded system, the voltage H of one line max The value is much larger than the set threshold, so the proposed single-phase disconnection fault detection method based on Haar wavelet transform can well detect the single-phase disconnection fault.

[0134] Example 3

[0135] This embodiment also provides a computer device, which is applicable to a single-phase line break fault detection method based on wavelet transform, and includes a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement a forced oscillation detection and positioning method for a distribution network as proposed in the above embodiment.

[0136] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, a forced oscillation detection and positioning method for a distribution network is implemented as proposed in the above embodiment.

[0137] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0138] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0139] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0140] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0141] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0142] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A single-phase disconnection fault detection method based on wavelet transform, characterized in that: It includes setting up a number of detection points on the distribution lines of the distribution network; Collect the line voltage amplitude signal of each detection point and form a data set; Performing wavelet transform processing on the data set to obtain detail coefficients corresponding to each detection point; Compare the absolute value of the detail coefficient with a preset threshold value to determine a disconnection fault; The location of the fault section is determined based on the detail coefficient exceeding the preset threshold.

2. The single-phase disconnection fault detection method based on wavelet transform according to claim 1 is characterized in that: The detection points include: trunk line detection points, branch line detection points and endpoint detection points; the distance between the detection points is set according to the importance of the line and the load distribution.

3. The single-phase disconnection fault detection method based on wavelet transform as claimed in claim 2, characterized in that: The determination of the fault section position includes: marking the detection points exceeding the preset threshold as the first fault point, the second fault point and the Nth fault point; finding the detection points adjacent to each fault point and whose absolute value of the detail coefficient does not exceed the preset threshold as reference points; the fault section is located between the fault point and its adjacent reference point.

4. The single-phase disconnection fault detection method based on wavelet transform as claimed in claim 3 is characterized in that: The preset threshold is determined according to the following steps: obtaining the detail coefficient of each detection point under normal operating conditions; determining the maximum absolute value of the detail coefficient under normal operating conditions; and taking a multiple of the maximum absolute value as the preset threshold.

5. The single-phase disconnection fault detection method based on wavelet transform as claimed in claim 4, characterized in that: The distribution lines include: cable lines, overhead lines and mixed lines; the detection points are set in consideration of line type characteristics.

6. The single-phase disconnection fault detection method based on wavelet transform according to claim 5 is characterized in that: After determining the line break fault, it also includes: recording the time and duration of the fault; recording the signal characteristics of each detection point when the fault occurs; and generating a fault characteristic report.

7. The single-phase disconnection fault detection method based on wavelet transform according to claim 6 is characterized in that: The wavelet transform adopts Haar wavelet transform, which includes: normalizing the original signal; performing multi-scale decomposition to obtain multi-layer detail coefficients; and selecting detail coefficients that best reflect fault characteristics.

8. A single-phase disconnection fault detection system based on wavelet transform, based on the single-phase disconnection fault detection method based on wavelet transform according to any one of claims 1 to 7, characterized in that: It also includes a detection point setting module, which sets a number of detection points on the distribution lines of the distribution network; A data acquisition module collects the line voltage amplitude signal of each detection point and forms a data set; The signal processing module performs wavelet transform processing on the data set to obtain detail coefficients corresponding to each detection point; A fault determination module compares the absolute value of the detail coefficient with a preset threshold value to determine a disconnection fault; The location positioning module determines the location of the fault section based on the detail coefficient exceeding the preset threshold.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the single-phase disconnection fault detection method based on wavelet transform described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the single-phase disconnection fault detection method based on wavelet transform described in any one of claims 1 to 7 are implemented.

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