A power distribution network fault location system and method based on multi-source information fusion

Abstract

This application provides a distribution network fault location system and method based on multi-source information fusion. The system collects synchronous phasor data and traveling wave recording data from various monitoring points in the distribution network. Initial candidate fault sections are selected from each line segment in the distribution network based on the synchronous phasor data. A first traveling wave criterion and a second traveling wave criterion are determined based on the traveling wave recording data corresponding to the initial candidate fault sections. The first and second traveling wave criters are used to jointly verify the initial candidate fault sections, generating a high-probability fault section sequence. The equivalent system impedance of the beginning and end of each candidate fault section is determined based on the current switching state and distributed power supply grid connection state of the distribution network. The target fault section of the distribution network is located based on the consistency relationship between the measured impedance of each candidate fault section and its corresponding equivalent system impedance. The technical solution provided by this application can accurately locate fault sections under real-time fluctuations in the equivalent impedance of the distribution network system.

Description

Technical Field

[0001] This invention relates to the field of power grid fault location technology, and in particular to a distribution network fault location system and method based on multi-source information fusion. Background Technology

[0002] With the advancement of smart grid construction, the distribution network structure is becoming increasingly complex, posing a severe challenge to traditional fault location methods. Traditional technologies such as impedance methods and traveling wave methods suffer from low location accuracy, insufficient high-impedance fault identification rate, and poor adaptability to multi-power source scenarios, making it difficult to meet the standard requirements for fault handling. Distributed power sources cause the fault current direction to vary, impedance mismatch in mixed lines causes signal interference, and insufficient equipment stability in extreme environments further exacerbates the difficulty of location. To improve power supply reliability, solve the bottlenecks of traditional technologies, and develop accurate fault location technologies that are adaptable to complex scenarios, it has become an urgent need for the upgrading of power grid operation and maintenance.

[0003] In existing power grid fault location methods, fault location is mostly based on the electrical quantity characteristics generated by the fault. The core principle revolves around the sudden change characteristics of voltage and current during a fault and the propagation law of electromagnetic signals. Impedance method collects voltage and current data from the beginning and end of the line before and after the fault, and calculates the distance from the fault point to the measurement end by combining the line impedance parameters. Traveling wave method captures the transient traveling wave signal generated at the moment of the fault, and calculates the fault location by measuring the time difference between the arrival of the wavefront at the two monitoring points and combining the wave velocity. However, in distribution network fault location, the random grid connection of distributed power sources (i.e., the access of distributed power sources changes the short-circuit current level and power flow distribution of the distribution network, causing the amplitude and phase of the measured impedance during the fault to deviate from the expected value) and frequent changes in switching operations cause real-time fluctuations in the equivalent impedance of the system. This makes it impossible for the fault location method based on traditional impedance method to accurately match the measured impedance with the theoretical impedance, thus leading to misjudgment of the fault section in the distribution network. Therefore, how to accurately locate the fault section under the real-time fluctuation of the equivalent impedance of the distribution network system has become a difficult problem for the industry. Summary of the Invention

[0004] This application provides a distribution network fault location system and method based on multi-source information fusion, which can accurately locate fault sections under real-time fluctuations in the equivalent impedance of the distribution network system.

[0005] Firstly, this application provides a method for fault location in distribution networks based on multi-source information fusion, comprising the following steps:

[0006] Collect synchronous phasor data and traveling wave recording data from various monitoring points in the power distribution network;

[0007] The voltage sag and negative sequence current amplitude of each line section in the distribution network are calculated based on the synchronous phasor data, and initial fault candidate sections are selected based on the voltage sag and negative sequence current amplitude.

[0008] Based on the traveling wave recording data corresponding to the initial fault candidate segment, the absolute time difference of the initial traveling wave wavehead arriving at different monitoring points is determined to form the first traveling wave criterion, and the high-frequency transient energy distribution of the traveling wave signal is extracted to form the second traveling wave criterion. The first traveling wave criterion and the second traveling wave criterion are used to jointly verify the initial fault candidate segment, thereby generating a high-probability fault segment sequence.

[0009] Obtain the current switching state and distributed generation grid connection state of the distribution network, and determine the equivalent system impedance of the first and last ends of each fault candidate segment in the high-probability fault segment sequence based on the switching state and distributed generation grid connection state.

[0010] The measured impedances at the beginning and end of each candidate fault segment in the high-probability fault segment sequence are determined, and then the target fault segment of the distribution network is located based on the consistency relationship between the measured impedance of each candidate fault segment and the corresponding equivalent system impedance.

[0011] In some embodiments, calculating the voltage sag and negative sequence current amplitude of each line section in the distribution network based on the synchronous phasor data specifically includes:

[0012] The synchronous three-phase voltage phasors and synchronous three-phase current phasors of each monitoring point in the distribution network are obtained from the synchronous phasor data.

[0013] Calculate the effective value of the three-phase voltage at each monitoring point based on the synchronous three-phase voltage phasor of each monitoring point;

[0014] Obtain the effective voltage reference value of each monitoring point under normal operating conditions of the distribution network, and calculate the voltage sag amplitude of each monitoring point from the effective three-phase voltage value of each monitoring point and the corresponding effective voltage reference value;

[0015] Based on the symmetrical component method, the synchronous three-phase current phasors of each monitoring point are decomposed to obtain the negative sequence current phasors of each monitoring point.

[0016] The negative sequence current amplitude of each monitoring point is determined based on the negative sequence current phasor of each monitoring point.

[0017] Based on the distribution network topology, determine the two-end monitoring points corresponding to each line segment in the distribution network, and associate the voltage sag amplitude and negative sequence current amplitude of the two-end monitoring points with the corresponding line segments.

[0018] In some embodiments, selecting initial fault candidate segments based on the voltage sag magnitude and negative sequence current magnitude specifically includes:

[0019] Set threshold values ​​for voltage sag and negative sequence current amplitude for distribution network fault characteristics;

[0020] Determine whether the voltage sag amplitude of each line segment is greater than or equal to the voltage sag amplitude threshold and whether the negative sequence current amplitude is greater than or equal to the negative sequence current amplitude threshold. If the conditions are met, the corresponding line segment is marked as an initial fault candidate segment; otherwise, the corresponding line segment is removed.

[0021] In some embodiments, determining the absolute time difference of the initial traveling wave front arriving at different monitoring points based on the traveling wave recording data corresponding to the initial fault candidate segment to form a first traveling wave criterion and extracting the high-frequency transient energy distribution of the traveling wave signal to form a second traveling wave criterion specifically includes:

[0022] Obtain the traveling wave recording data corresponding to the initial fault candidate segment;

[0023] The traveling wave recording data is preprocessed to obtain preprocessed traveling wave recording data, and the initial traveling wave head is identified from the preprocessed traveling wave recording data.

[0024] Calculate the absolute time difference between the arrival of the initial traveling wave front at different monitoring points in the initial fault candidate section, and construct the first traveling wave criterion based on all absolute time differences;

[0025] High-frequency band decomposition is performed on the preprocessed traveling wave recording data to extract high-frequency transient signals;

[0026] Calculate the high-frequency transient energy distribution of the high-frequency transient signal and use the high-frequency transient energy distribution as the second traveling wave criterion.

[0027] In some embodiments, determining the equivalent system impedance of the first and last ends of each candidate fault segment in the high-probability fault segment sequence based on the switching state and the grid connection state of the distributed power supply specifically includes:

[0028] Based on the switching state and the grid connection state of the distributed power source, the current operating topology of the distribution network is constructed;

[0029] For each candidate fault segment in the high-probability fault segment sequence, determine the electrical connection objects of the first and last ends of the candidate fault segment in the current operating topology;

[0030] Obtain the impedance parameters of each electrical connection object, including the main grid system impedance, the equivalent impedance of distributed power sources, and the impedance of the connection lines;

[0031] Based on the electrical connection relationship, the impedance parameters of each electrical connection object are calculated to obtain the equivalent system impedance at the beginning and end of each fault candidate section.

[0032] In some embodiments, determining the measured impedances at both ends of each candidate fault segment in the high-probability fault segment sequence specifically includes:

[0033] Obtain the monitoring points corresponding to the first and last ends of each candidate fault segment in the high-probability fault segment sequence;

[0034] Extract the three-phase voltage phasors and three-phase current phasors of the corresponding monitoring points at the beginning and end of the distribution network when a fault occurs.

[0035] Calculate the ratio of the three-phase voltage phasor to the three-phase current phasor at the monitoring point at the beginning of each candidate fault section to obtain the measured impedance at the beginning of the corresponding candidate fault section.

[0036] Calculate the ratio of the three-phase voltage phasor to the three-phase current phasor at the end monitoring point of each fault candidate section to obtain the end measurement impedance of the corresponding fault candidate section.

[0037] In some embodiments, synchronous phasor data and traveling wave recording data of each monitoring point in the distribution network are collected by synchronous phasor measurement equipment and traveling wave sensors equipped in the distribution network.

[0038] Secondly, this application provides a distribution network fault location system based on multi-source information fusion, used to execute a distribution network fault location method based on multi-source information fusion. The system includes:

[0039] The acquisition module is used to acquire synchronous phasor data and traveling wave recording data from various monitoring points in the power distribution network.

[0040] The processing module is used to calculate the voltage sag and negative sequence current amplitude of each line section in the distribution network based on the synchronous phasor data, and to screen out the initial fault candidate sections based on the voltage sag and negative sequence current amplitude.

[0041] The processing module is further configured to determine the absolute time difference between the arrival of the initial traveling wave front at different monitoring points based on the traveling wave recording data corresponding to the initial fault candidate segment to form a first traveling wave criterion and to extract the high-frequency transient energy distribution of the traveling wave signal to form a second traveling wave criterion, and to use the first traveling wave criterion and the second traveling wave criterion to jointly verify the initial fault candidate segment, thereby generating a high-probability fault segment sequence.

[0042] The processing module is also used to obtain the current switching state and distributed power grid connection state of the distribution network, and determine the equivalent system impedance of the first and last ends of each fault candidate segment in the high probability fault segment sequence based on the switching state and distributed power grid connection state.

[0043] The execution module is used to determine the measured impedances at both ends of each candidate fault segment in the high-probability fault segment sequence, and then locate the target fault segment of the distribution network based on the consistency relationship between the measured impedances of each candidate fault segment and the corresponding equivalent system impedance.

[0044] Thirdly, this application provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described method for fault location in power distribution networks based on multi-source information fusion.

[0045] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for fault location in a power distribution network based on multi-source information fusion.

[0046] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0047] The multi-source information fusion-based distribution network fault location system and method provided in this application first collects synchronous phasor data and traveling wave recording data from various monitoring points in the distribution network; secondly, it calculates the voltage sag and negative sequence current amplitude of each line section in the distribution network based on the synchronous phasor data, and selects initial fault candidate sections based on the voltage sag and negative sequence current amplitude; furthermore, it determines the absolute time difference of the initial traveling wave front arriving at different monitoring points based on the traveling wave recording data corresponding to the initial fault candidate sections to form a first traveling wave criterion, and extracts the high-frequency transient energy distribution of the traveling wave signal to form a second traveling wave criterion. The initial fault candidate sections are jointly verified using the first and second traveling wave criteria to generate a high-probability fault section sequence. Then, the current switching state and distributed generation grid connection state of the distribution network are obtained, and the equivalent system impedance of the first and last ends of each fault candidate section in the high-probability fault section sequence is determined based on the switching state and distributed generation grid connection state. Finally, the measured impedances of the first and last ends of each fault candidate section in the high-probability fault section sequence are determined, and the target fault section of the distribution network is identified based on the consistency relationship between the measured impedance of each fault candidate section and the corresponding equivalent system impedance.

[0048] Therefore, this application demonstrates accurate fault location under real-time fluctuations in the equivalent impedance of the distribution network system. First, it collects synchronous phasor data and traveling wave recording data from various monitoring points in the distribution network, providing multi-dimensional raw data support for subsequent fault feature extraction and analysis, achieving comprehensive fault information capture. Second, it calculates voltage sag and negative sequence current amplitude based on the synchronous phasor data and filters initial fault candidate sections, effectively eliminating non-fault interference such as load fluctuations and minor disturbances, quickly converging the fault investigation range, and reducing computational redundancy in subsequent target fault section analysis. Furthermore, it constructs a first traveling wave criterion (time difference feature) and a second traveling wave criterion (high-frequency energy distribution feature) based on the traveling wave recording data. Using the first and second traveling wave criterions to jointly verify the initial fault candidate sections generates a high-probability fault section sequence, further eliminating false fault candidate sections and improving the reliability of the candidate sections. The system first distinguishes between different levels of power supply and distribution network. Then, it acquires the switching status and distributed generation grid connection status and calculates the equivalent system impedance to dynamically match changes in the grid topology. This provides a reliable benchmark that closely matches the real-time operating status for subsequent impedance comparisons, avoiding inaccurate matching between measured and theoretical impedances caused by real-time fluctuations in the equivalent system impedance due to random grid connection of distributed generation and frequent changes in switching operations. Finally, it determines the measured impedances at both ends of each candidate fault segment in the high-probability fault segment sequence. Based on the consistency relationship between the measured impedances of each candidate fault segment and the corresponding equivalent system impedance, it locates the target fault segment of the distribution network. Then, through accurate comparison of measured and theoretical impedances, it achieves the final locking of the fault segment, effectively improving the accuracy of fault location in the distribution network and shortening the scope and time of fault investigation. In summary, the technical solution provided in this application can accurately locate fault segments under real-time fluctuations in the equivalent impedance of the distribution network system. Attached Figure Description

[0049] Figure 1 This is an exemplary flowchart of a power distribution network fault location method based on multi-source information fusion, as shown in some embodiments of this application.

[0050] Figure 2 This is an exemplary flowchart illustrating the determination of initial fault candidate segments according to some embodiments of this application;

[0051] Figure 3 This is a schematic diagram of the structure of a power distribution network fault location system based on multi-source information fusion, according to some embodiments of this application;

[0052] Figure 4 This is a schematic diagram of the structure of a computer device that implements a power distribution network fault location method based on multi-source information fusion, according to some embodiments of this application. Detailed Implementation

[0053] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] refer to Figure 1 The figure is an exemplary flowchart of a power distribution network fault location method based on multi-source information fusion according to some embodiments of this application. The figure mainly includes the following steps:

[0055] In step S101, synchronous phasor data and traveling wave recording data of each monitoring point in the power distribution network are collected.

[0056] In practice, synchronous phasor data and traveling wave recording data of each monitoring point in the distribution network can be collected by synchronous phasor measurement equipment and traveling wave sensors equipped in the distribution network. The synchronous phasor measurement equipment refers to an intelligent measurement device that collects voltage and current signals of the distribution network and calculates its synchronous phasors and related electrical quantities. The monitoring points can be set according to actual needs. For example, the monitoring points include, but are not limited to, being set at the section of the main line of the distribution network, the connection point between the branch line and the main line, the grid connection point of distributed power sources, and both sides of the ring network switch.

[0057] It should be noted that, in this application, synchronous phasor data refers to structured data containing amplitude, phase, and timestamps obtained after real-time acquisition and phasor calculation of voltage and current at different monitoring points in the distribution network. In this application, traveling wave recording data refers to electrical quantity data reflecting the propagation characteristics of transient traveling waves during a fault in the distribution network. It is used to record the waveform changes of high-frequency transient traveling waves of voltage and current caused by the fault, including key fault characteristics such as the arrival time of the traveling wave front, amplitude abrupt change, and high-frequency energy distribution. It can provide core data support for the construction of traveling wave criteria in the fault location of the distribution network.

[0058] In step S102, the voltage sag and negative sequence current amplitude of each line section in the distribution network are calculated based on the synchronous phasor data, and initial fault candidate sections are selected based on the voltage sag and negative sequence current amplitude.

[0059] In some embodiments, the calculation of voltage sag and negative sequence current amplitude of each line section in the distribution network based on the synchronization phasor data is achieved by the following steps:

[0060] The synchronous three-phase voltage phasors and synchronous three-phase current phasors of each monitoring point in the distribution network are obtained from the synchronous phasor data.

[0061] Calculate the effective value of the three-phase voltage at each monitoring point based on the synchronous three-phase voltage phasor of each monitoring point;

[0062] Obtain the effective voltage reference value of each monitoring point under normal operating conditions of the distribution network, and calculate the voltage sag amplitude of each monitoring point from the effective three-phase voltage value of each monitoring point and the corresponding effective voltage reference value;

[0063] Based on the symmetrical component method, the synchronous three-phase current phasors of each monitoring point are decomposed to obtain the negative sequence current phasors of each monitoring point.

[0064] The negative sequence current amplitude of each monitoring point is determined based on the negative sequence current phasor of each monitoring point.

[0065] Based on the distribution network topology, determine the two-end monitoring points corresponding to each line segment in the distribution network, and associate the voltage sag amplitude and negative sequence current amplitude of the two-end monitoring points with the corresponding line segments.

[0066] In specific implementation, firstly, the synchronous three-phase voltage phasors and synchronous three-phase current phasors of each monitoring point are extracted from the synchronous phasor data. The synchronous three-phase voltage phasor refers to a voltage sinusoidal quantity containing amplitude and phase information, and the synchronous three-phase current phasor refers to a current sinusoidal quantity containing amplitude and phase information. Secondly, for the synchronous three-phase voltage phasor of each monitoring point, the amplitude of the synchronous three-phase voltage phasor is divided by the square root of 2 according to the calculation principle of the effective value of sinusoidal AC voltage, thereby obtaining the effective value of the three-phase voltage of each monitoring point. The effective value of the three-phase voltage refers to the DC voltage value that produces the same thermal effect as the AC voltage in the same time period. Further, the voltage reference effective value of each monitoring point during normal operation of the distribution network (i.e., the average effective value of the three-phase voltage during the normal operation period of the distribution network) is obtained, and the voltage sag amplitude of each monitoring point is calculated by the ratio of (voltage reference effective value - current three-phase voltage effective value) to the voltage reference effective value. The voltage sag amplitude refers to the measurement of the voltage deviation from the normal level. The relative quantities are as follows: Further, the existing symmetrical component method in the power system is used to linearly transform the synchronous three-phase current phasors of each monitoring point, decomposing them to obtain the negative sequence current phasors. This will not be elaborated further here. The negative sequence current phasors are the components in the symmetrical component whose phase sequence is opposite to the positive sequence, used to characterize the degree of asymmetry in the system. Then, for each monitoring point, according to the principle of calculating the effective value of sinusoidal AC voltage, the amplitude of the negative sequence current phasor at the monitoring point is divided by the square root of 2 to obtain the corresponding negative sequence current amplitude. The negative sequence current amplitude refers to the effective value of the negative sequence current, which reflects the intensity of the asymmetrical current caused by the fault. Finally, according to the distribution network topology (i.e., the connection diagram of lines, nodes, and monitoring points in the distribution network, obtained from the specific distribution network parameter manual), the first and last monitoring points corresponding to each line segment are obtained. The voltage sag amplitude and negative sequence current amplitude of the first and last monitoring points are correlated with the corresponding line segments, thereby obtaining the voltage sag amplitude and negative sequence current amplitude of each line segment.

[0067] It should be noted that the line section refers to the section of the line between two adjacent electrical nodes in the distribution network. Because the distribution network has many branches and a wide coverage area, directly judging the fault of the entire line can easily lead to fuzzy location (such as only being able to determine that the fault is on a certain main line but not being able to distinguish the specific branch or section). However, by determining the line section, a one-to-one correspondence can be established between the synchronous phasor data and traveling wave data scattered at each monitoring point and the specific line section.

[0068] In some embodiments, reference Figure 2 As shown, this figure is an exemplary flowchart illustrating the determination of initial fault candidate segments according to some embodiments of this application. In this embodiment, the initial fault candidate segments can be screened based on the voltage sag and negative sequence current amplitude using the following steps:

[0069] In step S1021, the voltage sag threshold and negative sequence current amplitude threshold of the distribution network fault characteristics are set.

[0070] In step S1022, it is determined whether the voltage sag of each line segment is greater than or equal to the voltage sag threshold and whether the negative sequence current amplitude is greater than or equal to the negative sequence current amplitude threshold. If the conditions are met, the corresponding line segment is marked as an initial fault candidate segment; otherwise, the corresponding line segment is removed.

[0071] In specific implementation, firstly, based on the power transmission standards of the distribution network in the power industry, the voltage sag amplitude threshold and negative sequence current amplitude threshold of the distribution network fault characteristics can be set using the interval estimation method in existing mathematical statistics. In addition, the voltage sag amplitude threshold and negative sequence current amplitude threshold of the distribution network fault characteristics can also be set according to expert knowledge. Here, there is no limitation. The voltage sag amplitude threshold refers to the critical value of the degree of voltage sag that can distinguish between normal operation and fault state. The negative sequence current amplitude threshold refers to the critical value that characterizes the asymmetrical current caused by the fault reaching the fault judgment standard. Then, for each line segment with associated voltage sag amplitude and negative sequence current amplitude, the logical AND operation is used to compare the voltage sag amplitude and negative sequence current amplitude of each line segment with the set voltage sag amplitude threshold and negative sequence current amplitude threshold, respectively. If the voltage sag amplitude of the line segment is greater than or equal to the voltage sag amplitude threshold and the negative sequence current amplitude is greater than or equal to the negative sequence current amplitude threshold, then the corresponding line segment is marked as an initial fault candidate segment. Otherwise, the corresponding line segment is eliminated.

[0072] It should be noted that, in this application, the initial fault candidate section refers to the line section in the distribution network that is initially determined to have a fault. The voltage sag and the negative sequence current amplitude are the indicative electrical quantities of distribution network faults. The threshold screening logic strictly matches the characteristic differences between the fault state and the normal operating state to obtain the initial fault candidate section. This can effectively eliminate false signal interference caused by non-fault factors such as load fluctuations and minor disturbances, reduce the probability of misjudgment in the subsequent accurate fault section analysis stage, and provide high-quality initial analysis samples for the generation of high-probability fault section sequences.

[0073] In step S103, the absolute time difference of the initial traveling wave front arriving at different monitoring points is determined based on the traveling wave recording data corresponding to the initial fault candidate segment to form a first traveling wave criterion, and the high-frequency transient energy distribution of the traveling wave signal is extracted to form a second traveling wave criterion. The first traveling wave criterion and the second traveling wave criterion are used to jointly verify the initial fault candidate segment, thereby generating a high-probability fault segment sequence.

[0074] In some embodiments, the following steps are used to determine the absolute time difference of the initial traveling wave front arriving at different monitoring points based on the traveling wave recording data corresponding to the initial fault candidate segment to form a first traveling wave criterion, and to extract the high-frequency transient energy distribution of the traveling wave signal to form a second traveling wave criterion:

[0075] Obtain the traveling wave recording data corresponding to the initial fault candidate segment;

[0076] The traveling wave recording data is preprocessed to obtain preprocessed traveling wave recording data, and the initial traveling wave head is identified from the preprocessed traveling wave recording data.

[0077] Calculate the absolute time difference between the arrival of the initial traveling wave front at different monitoring points in the initial fault candidate section, and construct the first traveling wave criterion based on all absolute time differences;

[0078] High-frequency band decomposition is performed on the preprocessed traveling wave recording data to extract high-frequency transient signals;

[0079] Calculate the high-frequency transient energy distribution of the high-frequency transient signal and use the high-frequency transient energy distribution as the second traveling wave criterion.

[0080] In specific implementation, firstly, traveling wave recording data corresponding to the initial fault candidate section is acquired through a traveling wave sensor. This traveling wave recording data refers to electrical quantity data recording the changes over time of the transient traveling wave signal caused by the fault at each monitoring point within the initial fault candidate section. Secondly, the traveling wave recording data at each monitoring point within the initial fault candidate section is preprocessed using a wavelet threshold denoising algorithm commonly used in power signal processing, resulting in preprocessed traveling wave recording data for each monitoring point (details omitted here). Wavelet transform is then performed on the preprocessed traveling wave recording data, and the modulus maxima points representing abrupt changes in the traveling wave leading edge are extracted from the transform results. The time point corresponding to these modulus maxima points is taken as the initial traveling wave front at the corresponding monitoring point within the initial fault candidate section. The initial traveling wave front refers to the time node when the fault traveling wave first propagates to the monitoring point. The preprocessed traveling wave recording data refers to traveling wave recording data that retains pure traveling wave characteristics. Further, the calculation of the initial fault candidate section within the initial fault candidate section... The difference in arrival times of the initial traveling wave fronts at any two monitoring points is used to obtain the absolute time difference. The absolute time differences of all monitoring points are then combined to form the first traveling wave criterion, which is a fault segment discrimination standard constructed based on the difference in traveling wave propagation time. Next, a wavelet packet decomposition algorithm is used to decompose the preprocessed traveling wave recording data into high-frequency bands. After multi-scale wavelet packet decomposition, the decomposition coefficients corresponding to high-frequency bands above 800Hz are selected for signal reconstruction to extract high-frequency transient signals. These high-frequency transient signals refer to the signal components in the traveling wave recording data that reflect the transient characteristics of the fault. Finally, the sliding window integration method is used to calculate the high-frequency transient energy distribution of the high-frequency transient signals. Specifically, the high-frequency transient signals are divided into sliding windows at fixed time intervals, and the integral value of the square of the signal amplitude within each time window is calculated to form energy distribution curves under different time windows. These energy distribution curves are then used as the second traveling wave criterion.

[0081] It should be noted that the second traveling wave criterion in this application refers to a fault segment discrimination standard constructed based on the high-frequency transient energy distribution characteristics of traveling waves. The first traveling wave criterion in this application is constructed based on the absolute time difference of the initial traveling wave front arriving at the monitoring point within the segment. Its essence lies in verifying whether the candidate segment conforms to the propagation law of the fault traveling wave through the time characteristics of traveling wave propagation, so as to eliminate false candidate segments misjudged due to voltage and current transient disturbances. The second traveling wave criterion in this application is constructed based on the high-frequency transient energy distribution, focusing on the energy difference between the fault traveling wave and the normal operation signal in the high-frequency components. The transient traveling wave generated when the fault occurs will form significant energy in the high-frequency band. The high-frequency energy distribution during normal operation or non-fault disturbances is relatively dispersed, which can be used to further distinguish between fault and non-fault states. This makes up for the limitations of the single time difference criterion in complex topologies (such as multi-branch and close-range sections). The dual-criteria system jointly constructed by the two not only leverages the spatial positioning advantage of the traveling wave propagation time difference, but also utilizes the fault feature identification capability of the high-frequency transient energy distribution. This effectively improves the accuracy of the initial fault candidate section verification, ensuring that the subsequently generated high-probability fault section sequence has higher reliability and specificity, and laying the foundation for finally locking the target fault section through impedance consistency judgment.

[0082] In some embodiments, the following steps are used to jointly verify the initial fault candidate segments using the first traveling wave criterion and the second traveling wave criterion, thereby generating a high-probability fault segment sequence:

[0083] For each initial fault candidate section, the reference traveling wave wavefront time difference and reference high-frequency transient energy distribution corresponding to each initial fault candidate section are determined based on the distribution network topology and line parameters.

[0084] The consistency between the absolute time difference of the first traveling wave criterion and the time difference of the reference traveling wave wavehead is verified to obtain the time difference conformity of the corresponding initial fault candidate segment.

[0085] The consistency of the high-frequency transient energy distribution of the second traveling wave criterion with the reference high-frequency transient energy distribution is verified to obtain the energy distribution conformity of the corresponding initial fault candidate segment.

[0086] The joint criterion compliance of each initial fault candidate segment is calculated based on the time difference compliance and energy distribution compliance.

[0087] Initial fault candidate segments with joint criterion compliance exceeding the compliance threshold are selected and sorted from high to low according to the joint criterion compliance to generate a high-probability fault segment sequence.

[0088] In specific implementation, firstly, for each initial fault candidate section, based on the distribution network topology, the monitoring points within the initial fault candidate section are identified, along with line parameters (such as resistance per unit length, inductance, capacitance, and total line length). The propagation speed of the traveling wave in the initial fault candidate section is calculated using the traveling wave propagation speed formula. Then, based on the actual line distance between monitoring points and the propagation speed, the theoretical time for the traveling wave to propagate from one monitoring point to another is calculated. This yields the reference traveling wavefront time difference (i.e., the theoretical time difference for the fault traveling wave to reach each monitoring point) between different monitoring points in the initial fault candidate section. Simultaneously... Based on the aforementioned topology and line parameters, a simulation model of the initial fault candidate section is constructed using power system simulation software (such as ATP-EMTP). Typical fault types (such as single-phase grounding and two-phase short circuit) are set, and then a simulated traveling wave waveform signal is generated during the fault. Wavelet packet decomposition is used to extract high-frequency transient components from the simulated traveling wave waveform signal. By calculating the energy value of this high-frequency component within different time windows (energy calculation uses the integral of the square of the signal amplitude), a reference high-frequency transient energy distribution is obtained. This will not be elaborated further here. The reference traveling wavefront time difference refers to the time difference between the fault traveling wave and the corresponding initial fault candidate section. The theoretical time difference propagation between monitoring points within the selected section is used. The reference high-frequency transient energy distribution refers to the theoretical energy distribution characteristics of the high-frequency transient signal when a fault occurs in the initial fault candidate section. Secondly, a consistency check is performed using relative error analysis. This involves substituting the absolute time difference of the first traveling wave criterion and the corresponding reference traveling wave wavefront time difference into the relative error formula (|absolute time difference - reference traveling wave wavefront time difference| / reference traveling wave wavefront time difference) to calculate the time difference compliance of the corresponding initial fault candidate section. The time difference compliance refers to a quantitative indicator that measures the degree of matching between the measured traveling wave time difference and the theoretical time difference. Further, the cosine similarity algorithm is used to calculate the similarity between the high-frequency transient energy distribution of the second traveling wave criterion and the reference high-frequency transient energy distribution, and the similarity is used as the energy distribution conformity of the corresponding initial fault candidate segment. The energy distribution conformity refers to a quantitative parameter characterizing the consistency between the measured and theoretical high-frequency energy distribution patterns. Then, according to the influence of the time difference conformity and energy distribution conformity on the fault determination of the distribution network, the corresponding time difference conformity weight and energy distribution conformity weight are set. For example, the time difference conformity weight and energy distribution conformity weight can be set to 0.4 and 0, respectively.6. In other embodiments, settings can be made according to actual needs, which are not limited here. A normalized weighted summation formula (i.e., time difference compliance × time difference compliance weight + energy distribution compliance × energy distribution compliance weight) is used to calculate the joint criterion compliance of each initial fault candidate segment. The time difference compliance and energy distribution compliance in the normalized weighted summation formula are normalized values, which will not be elaborated here. The joint criterion compliance refers to the index used to determine the fault degree of the initial fault candidate segment by combining the first and second traveling wave criteria. Finally, a preset compliance threshold (i.e., the critical value for distinguishing between valid and invalid fault candidate segments) is obtained. Initial fault candidate segments with a joint criterion compliance exceeding the compliance threshold are selected and sorted from high to low according to the joint criterion compliance to generate a high-probability fault segment sequence. The specific compliance threshold can be set according to actual needs or expert knowledge, which is not limited here.

[0089] It should be noted that the high-probability fault segment sequence in this application is a set of fault candidate segments sorted by the probability of failure. By determining the high-probability fault segment sequence, the fault range can be further precisely focused and the analysis priority can be clearly defined based on the initial fault candidate segments. Through the quantitative evaluation of the joint criterion compliance, non-fault segments identified during the traveling wave verification process are effectively eliminated, the misjudgment component in the initial fault candidate segments is greatly reduced, and fault candidate segments with higher failure probability are retained. Ineffective calculations for low-probability fault candidate segments are avoided, significantly improving the execution efficiency of the entire fault location process and providing a highly reliable analytical basis for the final accurate identification of the target fault segment.

[0090] In step S104, the current switching state and distributed generation grid connection state of the distribution network are obtained, and the equivalent system impedance of the first and last ends of each fault candidate segment in the high-probability fault segment sequence is determined based on the switching state and distributed generation grid connection state.

[0091] In practice, the current switching status of the distribution network can be obtained from the distribution network monitoring platform, and the grid connection status of the distributed power sources in the distribution network can be obtained through the distributed power source monitoring terminal. In other embodiments, other acquisition devices can also be used to obtain the current switching status of the distribution network and the grid connection status of the distributed power sources, which is not limited here.

[0092] It should be noted that, in this application, the current switching state of the distribution network refers to the on / off operating state of various switching devices deployed at electrical nodes in the distribution network at the current operating moment. Specifically, it is manifested as the electrical connection state of the conductive circuit of the switching device being on (closed) or off (open). The current switching state directly reflects the power supply status of the corresponding line section and determines the current actual topology of the distribution network. In this application, the grid-connected state of distributed generation refers to the real-time operating state after being connected to the distribution network through the grid connection point. The grid-connected state of distributed generation directly affects the power flow distribution, equivalent impedance characteristics, and electrical quantity change patterns during faults in the distribution network. It is an important basic parameter for calculating the equivalent system impedance and analyzing fault characteristics in fault location.

[0093] In some embodiments, determining the equivalent system impedance of the first and last ends of each candidate fault segment in the high-probability fault segment sequence based on the switching state and the grid connection state of the distributed power supply is achieved through the following steps:

[0094] Based on the switching state and the grid connection state of the distributed power source, the current operating topology of the distribution network is constructed;

[0095] For each candidate fault segment in the high-probability fault segment sequence, determine the electrical connection objects of the first and last ends of the candidate fault segment in the current operating topology;

[0096] Obtain the impedance parameters of each electrical connection object, including the main grid system impedance, the equivalent impedance of distributed power sources, and the impedance of the connection lines;

[0097] Based on the electrical connection relationship, the impedance parameters of each electrical connection object are calculated to obtain the equivalent system impedance at the beginning and end of each fault candidate section.

[0098] In specific implementation, firstly, the adjacency matrix method commonly used in power systems is adopted. Node connectivity is characterized by switch states (0 for open state, 1 for closed state), combined with the distributed generation grid connection status (connected nodes are valid, disconnected nodes are invalid). This current operating topology of the distribution network is constructed, referring to a network model reflecting the real-time electrical connection relationships of the distribution network. Secondly, for each fault candidate segment in the high-probability fault segment sequence, the electrical nodes corresponding to the beginning and end of the fault candidate segment are located in the constructed current operating topology. Other electrical components connected to these electrical nodes are obtained, resulting in the electrical connection objects at the beginning and end of the fault candidate segment. These electrical connection objects refer to various power components that have direct electrical connections to the beginning and end nodes of the fault candidate segment. Then, the impedance parameters of each electrical connection object are obtained through the distribution network parameter database. These impedance parameters include the main grid system impedance, ... The equivalent impedance of distributed power sources and the impedance of connecting lines are defined as follows: impedance parameters refer to electrical parameters that characterize the ability of electrical components to impede the flow of current. The distribution network parameter database is a structured data set that specifically stores and manages the core electrical parameters and basic attribute information of various electrical components in the distribution network (including lines, switching equipment, transformers, distributed power sources, main grid interfaces, etc.). Its data sources include technical data from the distribution network design phase, equipment nameplate parameters, measured calibration data during operation and maintenance, and regularly updated parameter revision records. Finally, based on the series-parallel equivalent transformation rules in circuit theory, the impedance parameters of each connected object on the same electrical node are calculated using equivalent values ​​(i.e., series impedances are directly summed, and parallel impedances are calculated using 1 / (1 / Z1+1 / Z2+…+1 / Zn), where Zn is the complex impedance parameter of the nth electrical connected object on the same electrical node). The equivalent system impedances at the beginning and end of each fault candidate section are then obtained.

[0099] It should be noted that the equivalent system impedance in this application refers to the impedance value after all the electrical components connected at both ends of the fault candidate section are equivalent to a lumped impedance. By determining the equivalent system impedance, an accurate data benchmark can be provided for impedance consistency judgment in distribution network fault location. It is calculated by combining the real-time switch status and the grid connection status of distributed power sources. It can truly reflect the comprehensive impedance characteristics of the first and last ends of the high-probability fault section under the current operating topology, avoiding the defect that traditional fixed impedance parameters cannot adapt to the dynamic operating status of the power grid (such as switch opening and closing, distributed power source switching).

[0100] In step S105, the measured impedances at the beginning and end of each candidate fault segment in the high-probability fault segment sequence are determined, and then the target fault segment of the distribution network is located based on the consistency relationship between the measured impedance of each candidate fault segment and the corresponding equivalent system impedance.

[0101] In some embodiments, the measured impedances at the beginning and end of each candidate fault segment in the high-probability fault segment sequence are determined by the following steps:

[0102] Obtain the monitoring points corresponding to the first and last ends of each candidate fault segment in the high-probability fault segment sequence;

[0103] Extract the three-phase voltage phasors and three-phase current phasors of the corresponding monitoring points at the beginning and end of the distribution network when a fault occurs.

[0104] Calculate the ratio of the three-phase voltage phasor to the three-phase current phasor at the monitoring point at the beginning of each candidate fault section to obtain the measured impedance at the beginning of the corresponding candidate fault section.

[0105] Calculate the ratio of the three-phase voltage phasor to the three-phase current phasor at the end monitoring point of each fault candidate section to obtain the end measurement impedance of the corresponding fault candidate section.

[0106] In specific implementation, firstly, the monitoring points corresponding to the beginning and end of each fault candidate segment in the high-probability fault segment sequence are obtained; secondly, the time when the distribution network fault occurs (specifically, the time when the current surge in the distribution network exceeds the set fault threshold) is obtained, and the three-phase voltage phasors and three-phase current phasors of the corresponding monitoring points at the beginning and end are extracted from the synchronous phasor waveform data at that time. The three-phase voltage phasors and three-phase current phasors at the fault time refer to the synchronous electrical quantities reflecting the electrical state of the node at the instant the fault occurs; then, for each fault candidate segment, the fault candidates are classified according to the phasor operation rules of Ohm's law for AC circuits. The three-phase voltage phasors at the monitoring point at the beginning of the section are divided by complex numbers with the corresponding three-phase current phasors to obtain the measured impedance at the beginning of the corresponding fault candidate section. The measured impedance at the beginning of the section refers to the electrical parameter characterizing the equivalent impedance at the beginning of the fault candidate section. Finally, for each fault candidate section, according to the phasor operation rules of Ohm's law for AC circuits, the three-phase voltage phasors at the monitoring point at the end of the fault candidate section are divided by complex numbers with the corresponding three-phase current phasors to obtain the measured impedance at the end of the corresponding fault candidate section. The measured impedance at the end of the section refers to the electrical parameter characterizing the equivalent impedance at the end of the fault candidate section.

[0107] It should be noted that determining the core role of measuring the impedance at both ends of each candidate fault segment in a high-probability fault segment sequence can provide an accurate measured benchmark for subsequent impedance consistency judgment. The measurement at both ends of the candidate fault segment can truly reflect the actual impedance characteristics at both ends of the candidate fault segment under fault conditions, and can comprehensively cover the impedance change characteristics of the entire segment, avoiding the bias of judgment caused by data from a single endpoint.

[0108] In some embodiments, the target fault section of the distribution network is located based on the consistency relationship between the measured impedance of each fault candidate section and the corresponding equivalent system impedance using the following steps:

[0109] Set a consistency judgment threshold between the measured impedance and the equivalent system impedance, wherein the consistency judgment threshold includes an amplitude deviation threshold and a phase deviation threshold;

[0110] For each candidate fault section, calculate the amplitude and phase deviation between the measured impedance at the beginning of the candidate fault section and the equivalent system impedance at the beginning; calculate the amplitude and phase deviation between the measured impedance at the end of the candidate fault section and the equivalent system impedance at the end.

[0111] Determine whether each deviation is less than or equal to the corresponding consistency judgment threshold to obtain the impedance consistency result of each fault candidate section;

[0112] Candidate fault sections with acceptable impedance consistency are selected, and the candidate fault section with the highest compliance with the joint criterion is determined as the target fault section of the distribution network.

[0113] In specific implementation, firstly, based on the statistical results of the deviation between measured impedance and equivalent system impedance in the historical fault data of the distribution network, a consistency judgment threshold is set using the 3σ criterion (i.e., by calculating the mean and standard deviation of the deviation data between the historical measured impedance and equivalent system impedance, the deviation range is determined by the mean ± 3 times the standard deviation, and the upper limit of the deviation range is used as the consistency judgment threshold). The consistency judgment threshold includes an amplitude deviation threshold (i.e., a critical value for measuring the difference in impedance amplitude) and a phase deviation threshold (i.e., a critical value for measuring the difference in impedance phase). The consistency judgment threshold is a quantitative standard for distinguishing between normal impedance matching and abnormal deviation. Secondly, for each fault candidate section, the amplitude (i.e., the modulus of a complex number) and phase (i.e., the argument of a complex number) of the measured impedance at the beginning of the fault candidate section and the equivalent system impedance at the beginning are extracted respectively. The amplitude deviation at the beginning is calculated using the absolute error formula (i.e., |amplitude of the measured impedance at the beginning - amplitude of the equivalent system impedance at the beginning|). The absolute error is then used to calculate the amplitude deviation at the beginning. The phase deviation at the beginning of the circuit is calculated using the formula (|phase of the measured impedance at the beginning - phase of the equivalent system impedance at the beginning|). Similarly, the amplitude and phase deviations of the measured impedance at the end and the equivalent system impedance at the end are obtained using the same calculation logic. These amplitude and phase deviations are electrical parameters that quantify the degree of difference between the measured impedance and the equivalent system impedance. Then, using the logical AND operation, the amplitude and phase deviations at the beginning, the amplitude and phase deviations at the end, and the phase deviations at the end are all judged to be less than or equal to the corresponding consistency judgment thresholds. If all are satisfied, the impedance consistency result is considered compliant; otherwise, the impedance consistency result is considered non-compliant. The impedance consistency result refers to the judgment conclusion characterizing the degree of matching between the measured impedance and the theoretical impedance of the fault candidate section. Finally, the fault candidate sections with compliant impedance consistency results are selected, and the joint criterion compliance data calculated earlier is called up. The fault candidate section with the highest joint criterion compliance is selected as the target fault section of the distribution network.

[0114] It should be noted that the target fault section in this application refers to the line section in the distribution network where a fault actually occurs.

[0115] Furthermore, in another aspect of this application, in some embodiments, this application provides a power distribution network fault location system based on multi-source information fusion, referring to... Figure 3 The figure is a schematic diagram of the structure of a distribution network fault location system based on multi-source information fusion according to some embodiments of this application. The distribution network fault location system based on multi-source information fusion includes: a data acquisition module 201, a processing module 202, and an execution module 203, which are described below:

[0116] The acquisition module 201 in this application is mainly used to acquire synchronous phasor data and traveling wave recording data of each monitoring point in the power distribution network;

[0117] Processing module 202, in this application, is mainly used to calculate the voltage sag and negative sequence current amplitude of each line section in the distribution network based on the synchronous phasor data, and to screen out the initial fault candidate sections based on the voltage sag and negative sequence current amplitude.

[0118] The processing module 202 is further configured to determine the absolute time difference of the arrival of the initial traveling wave head at different monitoring points based on the traveling wave recording data corresponding to the initial fault candidate segment to form a first traveling wave criterion and to extract the high-frequency transient energy distribution of the traveling wave signal to form a second traveling wave criterion, and to use the first traveling wave criterion and the second traveling wave criterion to jointly verify the initial fault candidate segment, thereby generating a high-probability fault segment sequence.

[0119] In addition, the processing module 202 is also used to obtain the current switching state and distributed power grid connection state of the distribution network, and determine the equivalent system impedance of the first and last ends of each fault candidate segment in the high probability fault segment sequence based on the switching state and distributed power grid connection state.

[0120] The execution module 203 in this application is mainly used to determine the measured impedances at both ends of each fault candidate segment in the high-probability fault segment sequence, and then identify the target fault segment of the distribution network based on the consistency relationship between the measured impedance of each fault candidate segment and the corresponding equivalent system impedance.

[0121] In addition, this application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to acquire the code and execute the above-described method for fault location in power distribution networks based on multi-source information fusion.

[0122] In some embodiments, reference Figure 4 The figure is a schematic diagram of the structure of a computer device implementing a multi-source information fusion-based distribution network fault location method according to some embodiments of this application. The multi-source information fusion-based distribution network fault location method in the above embodiments can... Figure 4 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.

[0123] The processor 301 can be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more devices used to control the execution of the power distribution network fault location method based on multi-source information fusion in this application.

[0124] The communication bus 302 can be used to transmit information between the aforementioned components.

[0125] The memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 303 may exist independently and be connected to the processor 301 via the communication bus 302. The memory 303 may also be integrated with the processor 301.

[0126] The memory 303 stores program code for executing the scheme of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. In the above embodiments, the determination of the distribution network fault location method based on multi-source information fusion can be achieved by the processor 301 and one or more software modules in the program code in the memory 303.

[0127] Communication interface 304 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0128] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0129] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0130] In addition, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for fault location in power distribution networks based on multi-source information fusion.

[0131] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0132] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A power distribution network fault location method based on multi-source information fusion, characterized in that, Includes the following steps: Collect synchronous phasor data and traveling wave recording data from various monitoring points in the power distribution network; The voltage sag and negative sequence current amplitude of each line section in the distribution network are calculated based on the synchronous phasor data, and initial fault candidate sections are selected based on the voltage sag and negative sequence current amplitude. Based on the traveling wave recording data corresponding to the initial candidate fault segment, the absolute time difference of the initial traveling wave wavehead arriving at different monitoring points is determined to form the first traveling wave criterion, and the high-frequency transient energy distribution of the traveling wave signal is extracted to form the second traveling wave criterion. The first and second traveling wave criters are used to jointly verify the initial candidate fault segment, thereby generating a high-probability fault segment sequence; specifically, the following steps are adopted: For each initial fault candidate section, the reference traveling wave wavefront time difference and reference high-frequency transient energy distribution corresponding to each initial fault candidate section are determined based on the distribution network topology and line parameters. The consistency between the absolute time difference of the first traveling wave criterion and the time difference of the reference traveling wave wavehead is verified to obtain the time difference conformity of the corresponding initial fault candidate segment. The consistency of the high-frequency transient energy distribution of the second traveling wave criterion with the reference high-frequency transient energy distribution is verified to obtain the energy distribution conformity of the corresponding initial fault candidate segment. The joint criterion compliance of each initial fault candidate segment is calculated based on the time difference compliance and energy distribution compliance. Initial fault candidate segments with joint criterion compliance exceeding the compliance threshold are selected and sorted from high to low according to the joint criterion compliance to generate a high-probability fault segment sequence. The current switching status and distributed generation grid connection status of the distribution network are obtained, and the equivalent system impedance of the first and last ends of each candidate fault segment in the high-probability fault segment sequence is determined based on the switching status and distributed generation grid connection status; this is specifically achieved through the following steps: Based on the switching state and the grid connection state of the distributed power source, the current operating topology of the distribution network is constructed; For each candidate fault segment in the high-probability fault segment sequence, determine the electrical connection objects of the first and last ends of the candidate fault segment in the current operating topology; Obtain the impedance parameters of each electrical connection object, including the main grid system impedance, the equivalent impedance of distributed power sources, and the impedance of connection lines; Based on the electrical connection relationship, the impedance parameters of each electrical connection object are calculated to obtain the equivalent system impedance at the beginning and end of each fault candidate section; The measured impedances at the beginning and end of each candidate fault segment in the high-probability fault segment sequence are determined, and then the target fault segment of the distribution network is located based on the consistency relationship between the measured impedance of each candidate fault segment and the corresponding equivalent system impedance. The following steps are used to achieve this: Set a consistency judgment threshold between the measured impedance and the equivalent system impedance, wherein the consistency judgment threshold includes an amplitude deviation threshold and a phase deviation threshold; For each candidate fault section, calculate the amplitude and phase deviation between the measured impedance at the beginning of the candidate fault section and the equivalent system impedance at the beginning; calculate the amplitude and phase deviation between the measured impedance at the end of the candidate fault section and the equivalent system impedance at the end. Determine whether each deviation is less than or equal to the corresponding consistency judgment threshold to obtain the impedance consistency result of each fault candidate section; Candidate fault sections with acceptable impedance consistency are selected, and the candidate fault section with the highest compliance with the joint criterion is determined as the target fault section of the distribution network.

2. The power distribution network fault location method based on multi-source information fusion of claim 1, wherein, The calculation of voltage sag and negative sequence current amplitude in each line section of the distribution network based on the synchronous phasor data specifically includes: The synchronous three-phase voltage phasors and synchronous three-phase current phasors of each monitoring point in the distribution network are obtained from the synchronous phasor data. Calculate the effective value of the three-phase voltage at each monitoring point based on the synchronous three-phase voltage phasor of each monitoring point; Obtain the effective voltage reference value of each monitoring point under normal operating conditions of the distribution network, and calculate the voltage sag amplitude of each monitoring point from the effective three-phase voltage value of each monitoring point and the corresponding effective voltage reference value; Based on the symmetrical component method, the synchronous three-phase current phasors of each monitoring point are decomposed to obtain the negative sequence current phasors of each monitoring point. The negative sequence current amplitude of each monitoring point is determined based on the negative sequence current phasor of each monitoring point. Based on the distribution network topology, determine the two-end monitoring points corresponding to each line segment in the distribution network, and associate the voltage sag amplitude and negative sequence current amplitude of the two-end monitoring points with the corresponding line segments.

3. The power distribution network fault location method based on multi-source information fusion of claim 1, wherein, The initial fault candidate segment is selected based on the voltage sag and negative sequence current amplitude, specifically including: Set threshold values ​​for voltage sag and negative sequence current amplitude for distribution network fault characteristics; Determine whether the voltage sag amplitude of each line segment is greater than or equal to the voltage sag amplitude threshold and whether the negative sequence current amplitude is greater than or equal to the negative sequence current amplitude threshold. If the conditions are met, the corresponding line segment is marked as an initial fault candidate segment; otherwise, the corresponding line segment is removed.

4. The power distribution network fault location method based on multi-source information fusion of claim 1, wherein, Based on the traveling wave recording data corresponding to the initial fault candidate segment, the absolute time difference of the initial traveling wave wavefront arriving at different monitoring points is determined to form the first traveling wave criterion, and the high-frequency transient energy distribution of the traveling wave signal is extracted to form the second traveling wave criterion. Specifically, this includes: Obtain the traveling wave recording data corresponding to the initial fault candidate segment; The traveling wave recording data is preprocessed to obtain preprocessed traveling wave recording data, and the initial traveling wave head is identified from the preprocessed traveling wave recording data. Calculate the absolute time difference between the arrival of the initial traveling wave front at different monitoring points in the initial fault candidate section, and construct the first traveling wave criterion based on all absolute time differences; High-frequency band decomposition is performed on the preprocessed traveling wave recording data to extract high-frequency transient signals; Calculate the high-frequency transient energy distribution of the high-frequency transient signal and use the high-frequency transient energy distribution as the second traveling wave criterion.

5. The power distribution network fault location method based on multi-source information fusion of claim 1, wherein, Determining the measured impedances at both ends of each candidate fault segment in the high-probability fault segment sequence specifically includes: Obtain the monitoring points corresponding to the first and last ends of each candidate fault segment in the high-probability fault segment sequence; Extract the three-phase voltage phasors and three-phase current phasors of the corresponding monitoring points at the beginning and end of the distribution network when a fault occurs. Calculate the ratio of the three-phase voltage phasor to the three-phase current phasor at the monitoring point at the beginning of each candidate fault section to obtain the measured impedance at the beginning of the corresponding candidate fault section. Calculate the ratio of the three-phase voltage phasor to the three-phase current phasor at the end monitoring point of each fault candidate section to obtain the end measurement impedance of the corresponding fault candidate section.

6. The power distribution network fault location method based on multi-source information fusion of claim 1, wherein, Synchronous phasor measurement equipment and traveling wave sensors equipped in the distribution network are used to collect synchronous phasor data and traveling wave recording data at each monitoring point in the distribution network.

7. A power distribution network fault location system based on multi-source information fusion, configured to perform a power distribution network fault location method based on multi-source information fusion according to any one of claims 1 to 6. The system includes: The acquisition module is used to acquire synchronous phasor data and traveling wave recording data from various monitoring points in the power distribution network. The processing module is used to calculate the voltage sag and negative sequence current amplitude of each line section in the distribution network based on the synchronous phasor data, and to screen out the initial fault candidate sections based on the voltage sag and negative sequence current amplitude. The processing module is further configured to determine the absolute time difference between the arrival of the initial traveling wave front at different monitoring points based on the traveling wave recording data corresponding to the initial fault candidate segment to form a first traveling wave criterion and to extract the high-frequency transient energy distribution of the traveling wave signal to form a second traveling wave criterion, and to use the first traveling wave criterion and the second traveling wave criterion to jointly verify the initial fault candidate segment, thereby generating a high-probability fault segment sequence. The processing module is also used to obtain the current switching state and distributed power grid connection state of the distribution network, and determine the equivalent system impedance of the first and last ends of each fault candidate segment in the high probability fault segment sequence based on the switching state and distributed power grid connection state. The execution module is used to determine the measured impedances at both ends of each candidate fault segment in the high-probability fault segment sequence, and then locate the target fault segment of the distribution network based on the consistency relationship between the measured impedances of each candidate fault segment and the corresponding equivalent system impedance.

8. A computer device, comprising: The computer device includes a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute a power distribution network fault location method based on multi-source information fusion as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 8. When the computer program is executed by the processor, it implements a power distribution network fault location method based on multi-source information fusion as described in any one of claims 1 to 6.

Images