An Automatic Screening and Collection Method for Ground Fault Recordings in Distribution Networks Based on Sliding Time Window

Abstract

This invention proposes an automatic screening and aggregation method for ground fault waveform recordings in distribution networks based on a sliding time window, comprising the following steps: Step S1, the master station performs waveform recall on all terminals in the network topology where a ground fault occurs; Step S2, calculate the waveform density within the sliding time window; Step S3, use the data closest to the time reference point for each terminal as the initial aggregation object; Step S4, initially aggregate the data; Step S5, find the zero-sequence voltage of the terminal with the largest zero-sequence current as the reference voltage; Step S6, calculate the similarity between the zero-sequence voltage and the reference voltage waveforms of all other terminals; Step S7, waveforms with significant similarity are used as the dataset for the same fault. This invention can effectively eliminate waveform data with incomplete or erroneous fault information, aggregate all waveform recordings under the same fault event, avoid waveform confusion from multiple fault events interfering with fault location, and significantly improve the accuracy of centralized analysis of single-phase ground faults in distribution networks.

Description

Technical Field

[0001] This invention relates to the field of power system distribution automation technology, and in particular to an automatic screening and aggregation method for ground fault recordings in distribution networks based on a sliding time window. Background Technology

[0002] With increasingly stringent requirements for power distribution network reliability, distribution automation equipment such as fault indicators and integrated primary and secondary switches have been applied to improve power supply reliability, achieving significant results. However, as the types of equipment in distribution networks increase and their structures become more complex, a single-phase ground fault generates a large number of waveform recordings, impacting the data flow of single-phase ground fault analysis algorithms and affecting their timeliness and accuracy. Existing power grid monitoring devices can upload fault waveform recordings to a master station for centralized analysis. Therefore, associating waveform recordings from different terminals with the fault topology is crucial to ensure that the collected waveform data belongs to the same fault event. However, on the one hand, time synchronization errors exist between terminals, and due to differences in fault recording conditions, the number of waveforms and clocks vary for the same fault. On the other hand, signal strength issues at the site lead to significant differences in waveform upload rates between terminals, resulting in data delays and even packet loss during the waveform upload process. In summary, the factors mentioned above can easily lead to deviations in the timing, quantity, and quality of waveforms acquired by different terminals.

[0003] Existing fault data collection methods primarily use timestamps of fault waveforms to aggregate fault waveform data. However, due to time synchronization errors between different devices, the aggregated waveforms may not belong to the same fault event, significantly reducing the accuracy of fault location. Therefore, accurate and rapid screening and aggregation of recorded waveforms are essential conditions for the master station to accurately locate faults.

[0004] Therefore, a more reliable and accurate waveform screening and aggregation scheme for distribution network grounding faults is needed to more effectively aggregate all recorded waveforms and their topologies under the same fault event. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide an automatic screening and aggregation method for ground fault waveform recordings in distribution networks based on a sliding time window. This method filters all waveforms detected by the master station, eliminates abnormal waveforms, ensures that for each fault event, each terminal has at most one waveform participating in the centralized fault analysis, strictly controls the quality of waveform data participating in the centralized fault analysis, and improves the accuracy of the centralized analysis.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: an automatic screening and aggregation method for ground fault recordings in distribution networks based on a sliding time window, comprising the following steps:

[0007] Step S1: The master station performs waveform analysis on all terminals in the network topology where a ground fault has occurred. The waveforms of each terminal device are arranged in a time sequence to form a waveform sequence.

[0008] Step S2: Simultaneously shift the waveform sequence of each terminal according to the time sequence using a time sliding window, and calculate the waveform density within the time sliding window, that is, the number of waveforms covered by all terminals under the time sliding window;

[0009] Step S3: Select the time point with the highest waveform density within the sliding window as the reference point, and take the data of each terminal closest to the time reference point as the initial collection object to form the initial filtered dataset Set_p;

[0010] Step S4: Perform anomaly filtering on the initially collected data, remove abnormal waveforms, and form a secondary filtered dataset Set_s;

[0011] Step S5: In the filtered waveforms, find the zero-sequence voltage of the terminal with the largest zero-sequence current as the reference voltage;

[0012] Step S6: Calculate the similarity between the zero-sequence voltage and the reference voltage waveform for all other terminals;

[0013] Step S7: Waveforms with obvious similarity can be grouped together as the same fault dataset.

[0014] In a preferred embodiment, the master station recalls the waveforms of all terminals in the network topology where a ground fault has occurred. Based on the ground fault alarm information issued by the control center, the master station recalls the recorded waveforms of all devices in the corresponding topology for a duration of 5-10 minutes.

[0015] In a preferred embodiment, the waveform density within the time sliding window is statistically analyzed according to the chronological order of the time sequence, and the waveform density is the number of waveforms within the time sliding window.

[0016] In a preferred embodiment, the initially collected data undergoes anomaly screening to remove abnormal waveforms, including abnormal line voltage, phase loss, and abnormal waveform recording files. The criteria for judging abnormal line voltage are: the line voltage is less than 80% of the standard line voltage value; phase loss is defined as a waveform recording where one channel has a value of 0 or a fixed value; and abnormal waveform recording files include missing cfg or dat files, or discrepancies between the total number of sampling points in the dat file and the total number of sampling points in the cfg file.

[0017] In a preferred embodiment, the calculation of the similarity between the zero-sequence voltage and the reference voltage waveform for all other terminals is performed using the Pearson similarity formula, which is as follows:

[0018]

[0019] in, ρ is the average value of the zero-sequence voltage; N is the number of sampling points in the calculation data segment, which is generally an integer multiple of the number of power frequency cycle points; U1(i) is the reference zero-sequence voltage sampling point; U2(i) is the zero-sequence voltage sampling point of other terminals; and ρ is the similarity between the zero-sequence voltage of other terminals and the reference voltage.

[0020] In a preferred embodiment, waveforms with significant similarity are considered as the same fault dataset, and waveforms with a similarity to the reference voltage exceeding 0.7 can be grouped into a single dataset corresponding to the reference voltage.

[0021] In a preferred embodiment, the distribution network voltage level used in the method is medium voltage, i.e., 1kV to 35kV.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] (1) Waveform anomaly screening. The automatic screening and aggregation method for distribution network grounding fault waveforms based on sliding time window proposed in this invention can screen waveforms, remove waveform data with incomplete or incorrect fault information, and remove abnormal waveforms to improve the quality of waveforms participating in the analysis. It can also strictly control the number and quality of waveforms participating in the centralized analysis, and greatly improve the accuracy of centralized analysis of single-phase grounding faults in distribution networks.

[0024] (2) Effective waveform aggregation. The automatic screening and aggregation method for distribution network grounding fault recordings based on a sliding time window proposed in this invention can avoid the interference of waveform confusion from multiple fault events in fault location, and effectively aggregate all recorded waveforms and their topology under the same fault event, thereby achieving accurate and rapid fault location. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the method principle of the present invention;

[0026] Figure 2 This is a flowchart of the method of the present invention;

[0027] Figure 3 This is a schematic diagram of the terminal waveform sequence formed after the master station completes the call wave according to the present invention;

[0028] Figure 4 This is a schematic diagram illustrating the selection of the time reference point for this invention. Detailed Implementation

[0029] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0030] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0031] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations according to this application; as used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise; furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0032] like Figure 1 The diagram illustrates the principle of an automatic screening and aggregation method for distribution network grounding fault waveform recording based on a sliding time window in this embodiment. The terminal is a fault monitoring device in the distribution network, including fault indicators, primary and secondary fusion devices, and other distribution automation equipment. When a single-phase grounding fault occurs in the distribution network and meets the waveform recording conditions of the terminal device, the terminal device records electrical signals such as voltage and current on the feeder, forming waveform recording files in the Comtrade standard format. Each waveform recording file name includes key information about the fault recording time, which is the timestamp corresponding to the waveform. When the master station receives a grounding fault alarm from the control center, the master station actively recalls the waveform recording files of all terminals in the network topology where the grounding fault occurred. After the master station completes the recall, it filters and aggregates the fault data. Each filtered and aggregated waveform dataset contains the aggregated waveform, configuration file (xml), topology file, and other relevant information.

[0033] like Figure 2 The flowchart shown is for the automatic screening and aggregation method of ground fault recording in distribution networks based on sliding time windows in this embodiment.

[0034] like Figure 3 As shown, after the master station completes the fault waveform recall, the waveforms detected by each terminal device are arranged in a time sequence to form a waveform sequence.

[0035] like Figure 4As shown, a time sliding window is used to statistically analyze the waveform density within the window in the direction of the time series. The time point with the highest waveform density within the window is selected as the time reference point. The data from each terminal closest to the time reference point is used as the initial collection object to form the initial filtered dataset Set_p. In this embodiment, the time width of the sliding window is 4 seconds, and the sliding step size is 1 second. It slides from the smallest time scale of the fault data collection to the time scale value corresponding to the waveform at the last time. The time with the most waveforms in the window is selected as the reference time, and the waveform from each terminal closest to the reference time is added to the initial filtered dataset Set_p.

[0036] The initially collected data undergoes anomaly screening. By analyzing the contents of the comtrade file and combining key information such as file size and data sequence number, abnormal waveform data generated during terminal generation or waveform transmission is identified and removed. This process purifies the dataset, resulting in a more reliable secondary-screened dataset Set_s.

[0037] Among the filtered waveforms, the zero-sequence voltage of the terminal with the largest zero-sequence current is selected as the reference voltage;

[0038] The Pearson similarity algorithm was used to calculate the similarity between the zero-sequence voltage and the reference voltage waveform for all other terminals.

[0039] Waveforms with a similarity greater than 0.7 will be considered as the same fault dataset and can be grouped together.

[0040] The above description is a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

[0041] This patent is not limited to the above-described preferred embodiments. Anyone can derive other forms of terminal waveform alignment methods based on zero-voltage mutation points under the guidance of this patent. All equivalent changes and modifications made within the scope of this patent application shall fall within the scope of this patent.

Claims

1. A method for automatic screening and aggregation of grounding fault recordings in distribution networks based on a sliding time window, characterized in that: Includes the following steps: Step S1: The master station performs waveform analysis on all terminals in the network topology where a ground fault has occurred. The waveforms of each terminal device are arranged in a time sequence to form a waveform sequence. Step S2: Simultaneously shift the waveform sequence of each terminal according to the time sequence using a time sliding window, and calculate the waveform density within the time sliding window, that is, the number of waveforms covered by all terminals under the time sliding window; Step S3: Select the time point with the highest waveform density within the sliding window as the reference point, and take the data of each terminal closest to the time reference point as the initial collection object to form the initial filtered dataset Set_p; Step S4: Perform anomaly filtering on the initially collected data, remove abnormal waveforms, and form a secondary filtered dataset Set_s; Step S5: In the filtered waveforms, find the zero-sequence voltage of the terminal with the largest zero-sequence current as the reference voltage; Step S6: Calculate the similarity between the zero-sequence voltage and the reference voltage waveform for all other terminals; Step S7: Waveforms with obvious similarity can be grouped together as the same fault dataset.

2. The method for automatic screening and aggregation of grounding fault recordings in distribution networks based on a sliding time window, as described in claim 1, is characterized in that... The master station retrieves waveforms from all terminals in the network topology where a ground fault has occurred. Based on the ground fault alarm information issued by the control center, the master station retrieves the recorded waveforms of all devices in the corresponding topology for a duration of 5-10 minutes.

3. The method for automatic screening and aggregation of grounding fault recordings in distribution networks based on a sliding time window, as described in claim 1, is characterized in that... The waveform density within the time sliding window is calculated according to the chronological order of the time series, and the waveform density is the number of waveforms within the time sliding window.

4. The method for automatic screening and aggregation of grounding fault recordings in distribution networks based on a sliding time window, as described in claim 1, is characterized in that... The initially collected data is then subjected to anomaly screening to remove abnormal waveforms. The abnormal waveforms are identified as abnormal line voltage, phase loss, and abnormal waveforms in the waveform recording file. The criteria for judging abnormal line voltage are that the line voltage is less than 80% of the standard line voltage value. Phase loss is defined as the waveform recording having one channel with a value of 0 or a fixed value. Abnormal waveform recording files are defined as missing cfg or dat files, or discrepancies between the total number of sampling points in the dat file and the total number of sampling points in the cfg file.

5. The method for automatic screening and aggregation of grounding fault recordings in distribution networks based on a sliding time window, as described in claim 1, is characterized in that... The similarity between the zero-sequence voltage and the reference voltage waveform of all other terminals is calculated. The similarity is the Pearson similarity, and its calculation formula is as follows: in, ρ is the average value of the zero-sequence voltage; N is the number of sampling points in the calculation data segment, which is generally an integer multiple of the number of power frequency cycle points; U1(i) is the reference zero-sequence voltage sampling point; U2(i) is the zero-sequence voltage sampling point of other terminals; and ρ is the similarity between the zero-sequence voltage of other terminals and the reference voltage.

6. The method for automatic screening and aggregation of grounding fault recordings in distribution networks based on a sliding time window, as described in claim 1, is characterized in that... Waveforms with significant similarity are considered as belonging to the same fault dataset. Waveforms with a similarity to the reference voltage exceeding 0.7 can be grouped into a single dataset corresponding to the reference voltage.

7. The method for automatic screening and aggregation of grounding fault recordings in distribution networks based on a sliding time window, as described in claim 1, is characterized in that... The method uses a medium-voltage distribution network, i.e., 1kV to 35kV.

Images