A method for identifying open flames on overhead power lines

Abstract

This invention relates to a method for detecting open flames on overhead conductors, comprising the following steps: acquiring zero-sequence current recording data and the start time of the zero-sequence current recording data; sequentially recording the data within the first power frequency cycle at each fixed time interval in the zero-sequence current recording data; processing all data to obtain the power frequency amplitude and third harmonic amplitude of each data point; calculating the judgment quantity of each data point using the power frequency amplitude and third harmonic amplitude; combining the judgment quantities of all data points into a judgment quantity sequence; filtering the judgment quantity sequence to obtain a filtered judgment quantity sequence; performing a first-order difference on the filtered judgment quantity sequence to obtain a first-order difference judgment quantity sequence; normalizing the filtered judgment quantity sequence and the first-order difference judgment quantity sequence; and calculating the time of open flame occurrence using the start time of the zero-sequence current recording data, the normalized filtered judgment quantity sequence, and the normalized first-order difference judgment quantity sequence.

Description

Technical Field

[0001] This invention relates to a method for identifying open flames on overhead conductors, belonging to the field of power system harmonic analysis. Background Technology

[0002] In recent years, forest fires have occurred frequently worldwide, causing enormous casualties and economic losses. The determination of liability after a fire has gradually become a focal point of public concern. my country's total power distribution line length exceeds 5.37 million kilometers, of which over 4.37 million kilometers are overhead lines, with over 3.89 million kilometers in rural areas. Single-phase grounding faults involving 10kV overhead conductors touching trees, caused by tree growth, strong winds, landslides, and other factors, occur frequently. The grounding current in a conductor-to-tree fault is characterized by a small initial value that gradually increases slowly as the fault develops. Current relay protection systems struggle to detect faults in their early stages; detection typically occurs in the middle to late stages of the fault process. During this phase, trees are highly likely to ignite due to increased carbonization, posing a high fire risk. Accurately determining the specific moment of ignition in a conductor-to-tree fault is crucial for reconstructing the fire's occurrence and determining liability.

[0003] Currently, neither relay protection systems nor fire protection systems have specific methods for determining the timing of open flames caused by conductor-to-tree faults. Generally, the fault detection time recorded by the relay protection system is used as the primary reference. However, since most 10kV grounding protection systems are based on zero-sequence current amplitude and their detection sensitivity is generally no more than 2 kΩ (maximum no more than 5 kΩ), the fault detection logic is not directly related to the tree ignition process. Estimating the actual timing of open flames caused by conductor-to-tree faults based on this detection time would result in significant errors, potentially misleading fire simulation and liability determination. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention proposes a method for identifying open flames on overhead power lines.

[0005] The technical solution of the present invention is as follows:

[0006] On the one hand, the present invention provides a method for identifying open flames on overhead power lines, comprising the following steps:

[0007] Collect zero-sequence current waveform data and record the start time of the zero-sequence current waveform data. Sequentially record the data within the first power frequency cycle at each fixed time interval in the zero-sequence current waveform data. Process all data to obtain the true amplitude of each data. Extract the power frequency amplitude and the third harmonic amplitude from the true amplitude of each data. Calculate the judgment quantity of each data using the power frequency amplitude and the third harmonic amplitude of each data. Combine the judgment quantities of all data into a judgment quantity sequence.

[0008] A first-order differential decision sequence is obtained based on the decision sequence; the time of open flame occurrence is calculated using the start time of the zero-sequence current recording data, the filtered decision sequence, and the first-order differential decision sequence. In a preferred embodiment of the invention, the true amplitude of each data point is obtained by performing a fast Fourier transform on the original data.

[0009] In a preferred embodiment of the present invention, the determination value of each data point is calculated as follows:

[0010] In = I1 × I3

[0011] Where: In is the determination value of a single data point; I1 is the power frequency amplitude of a single data point; I3 is the third harmonic amplitude of a single data point.

[0012] In a preferred embodiment of the present invention, the decision sequence is subjected to K-point median filtering and smoothing filtering.

[0013] In a preferred embodiment of the present invention, the specific calculation steps of the first-order difference decision sequence are as follows:

[0014] Suppose there are n data in the filter decision sequence. For all data in the filter decision sequence, subtract the previous data from the next data and take the absolute value to obtain a first-order difference decision sequence consisting of n-1 non-negative numbers.

[0015] In a preferred embodiment of the present invention, the specific calculation steps for the time of the open flame appearance are as follows:

[0016] Let t0 be the starting time of the zero-sequence current waveform data, and t1 be the fixed time interval in the zero-sequence current waveform data.

[0017] Extract the data that exceeds the filter decision threshold in the normalized filter decision sequence, and let this data be the k-th data item;

[0018] A positive integer value k0 is preset. From the normalized first-order difference decision quantity sequence, the k-k0th to the kth item, a total of k0+1 items of data, are taken. It is determined whether all k0+1 items of data are less than the threshold of the first-order difference decision quantity. If all the data are less than the threshold of the first-order difference decision quantity, the time of the open flame is t0+k×t1. If any data is greater than the threshold of the first-order difference decision quantity, k-1 is reduced, and the current step is repeated until the time of the open flame is obtained.

[0019] On the other hand, the present invention also provides an open flame detection system for overhead power lines, including a data preprocessing module and an open flame occurrence time determination module;

[0020] The data preprocessing module is used to collect zero-sequence current waveform data and record the start time of the zero-sequence current waveform data. It sequentially records the data within the first power frequency cycle at each fixed time interval in the zero-sequence current waveform data, processes all data to obtain the true amplitude of each data, extracts the power frequency amplitude and the third harmonic amplitude from the true amplitude of each data, calculates the judgment quantity of each data through the power frequency amplitude and the third harmonic amplitude of each data, and combines the judgment quantities of all data into a judgment quantity sequence.

[0021] A first-order differential decision sequence is obtained based on the decision sequence; the time of open flame occurrence is calculated using the start time of the zero-sequence current recording data, the filtered decision sequence, and the first-order differential decision sequence. In a preferred embodiment of the invention, the data preprocessing module obtains the true amplitude of each data point by performing a fast Fourier transform on the original data.

[0022] In a preferred embodiment of the present invention, the formula for calculating the determination value of each data point in the data preprocessing module is as follows:

[0023] In = I1 × I3

[0024] Where: In is the determination value of a single data point; I1 is the power frequency amplitude of a single data point; I3 is the third harmonic amplitude of a single data point.

[0025] In a preferred embodiment of the present invention, the open flame occurrence time determination module performs K-point median filtering and smoothing filtering on the determination quantity sequence.

[0026] In a preferred embodiment of the present invention, the open flame occurrence time determination module calculates the first-order difference determination quantity sequence through the following steps:

[0027] Suppose there are n data in the filter decision sequence. For all data in the filter decision sequence, subtract the previous data from the next data and take the absolute value to obtain a first-order difference decision sequence consisting of n-1 non-negative numbers.

[0028] In a preferred embodiment of the present invention, the open flame occurrence time determination module calculates the open flame occurrence time through the following steps:

[0029] Let t0 be the starting time of the zero-sequence current waveform data, and t1 be the fixed time interval in the zero-sequence current waveform data.

[0030] Extract the data that exceeds the filter decision threshold in the normalized filter decision sequence, and let this data be the k-th data item;

[0031] A positive integer value k0 is preset. From the normalized first-order difference decision quantity sequence, the k-k0th to the kth item, a total of k0+1 items of data, are taken. It is determined whether all k0+1 items of data are less than the threshold of the first-order difference decision quantity. If all the data are less than the threshold of the first-order difference decision quantity, the time of the open flame is t0+k×t1. If any data is greater than the threshold of the first-order difference decision quantity, k-1 is reduced, and the current step is repeated until the time of the open flame is obtained.

[0032] In another aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method as described in any embodiment of the present invention.

[0033] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the present invention.

[0034] The present invention has the following beneficial effects:

[0035] 1. The method for determining the time of open flame occurrence of a conductor-to-tree fault based on power waveform data fills a gap in this field in China. In principle, it is closely related to the physical mechanism of open flame development in conductor-to-tree faults. Compared with the existing method that uses the fault detection time as the open flame occurrence time, it has higher reliability and accuracy. In terms of implementation, the algorithm is clear and concise, with low computational resource consumption. The algorithm can be ported to existing relay protection devices, and it has strong versatility. Attached Figure Description

[0036] Figure 1 This is a flowchart of the method of the present invention;

[0037] Figure 2 This is a graph showing the zero-sequence current amplitude at power frequency and the amplitude of the third harmonic in an embodiment of the present invention.

[0038] Figure 3 This is a graph showing the sequence of determination quantities in an embodiment of the present invention.

[0039] Figure 4 This is a graph of the normalized first-order difference decision quantity sequence from an embodiment of the present invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0042] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0043] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0044] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0045] Example 1:

[0046] A method for detecting open flames on overhead power lines includes the following steps:

[0047] See Figure 1 Collect zero-sequence current waveform data and record the start time of the zero-sequence current waveform data. Sequentially record the data within the first power frequency cycle at each fixed time interval in the zero-sequence current waveform data. Process all data to obtain the true amplitude of each data. Extract the power frequency amplitude and the third harmonic amplitude from the true amplitude of each data.

[0048] See Figure 2 The decision value of each data point is calculated by combining the power frequency amplitude and the third harmonic amplitude of each data point, and the decision values ​​of all data points are combined into a decision value sequence.

[0049] See Figure 3 The decision sequence is filtered to obtain a filtered decision sequence. Then, the filtered decision sequence is first-order differentiated to obtain a first-order differential decision sequence. The filtered decision sequence and the first-order differential decision sequence are normalized. The time of open flame occurrence is calculated using the start time of the zero-sequence current recording data, the normalized filtered decision sequence, and the normalized first-order differential decision sequence.

[0050] In a preferred embodiment of this invention, the true amplitude of each data point is obtained by performing a Fast Fourier Transform on the original data.

[0051] In a preferred embodiment of this invention, the determination value of each data point is calculated as follows:

[0052] In = I1 × I3

[0053] Where: In is the determination value of a single data point; I1 is the power frequency amplitude of a single data point; I3 is the third harmonic amplitude of a single data point.

[0054] In a preferred embodiment of this example, the decision sequence is subjected to K-point median filtering and smoothing filtering, with K set to 41.

[0055] As a preferred embodiment of this invention, the specific steps for performing first-order differencing on the filter decision sequence are as follows:

[0056] Suppose there are n data in the filter decision sequence. For all data in the filter decision sequence, subtract the previous data from the next data and take the absolute value to obtain a first-order difference decision sequence consisting of n-1 non-negative numbers.

[0057] In a preferred embodiment of this invention, the specific steps for calculating the time of the open flame appearance are as follows:

[0058] Let t0 be the starting time of the zero-sequence current waveform data, and t1 be the fixed time interval in the zero-sequence current waveform data.

[0059] Extract the data that exceeds the filter decision threshold in the normalized filter decision sequence, and let this data be the k-th data item;

[0060] A positive integer value k0 is preset. From the normalized first-order difference decision quantity sequence, the k-k0th to the kth item, a total of k0+1 items of data, are taken. It is determined whether all k0+1 items of data are less than the threshold of the first-order difference decision quantity. If all the data are less than the threshold of the first-order difference decision quantity, the time of the open flame is t0+k×t1. If any data is greater than the threshold of the first-order difference decision quantity, k-1 is reduced, and the current step is repeated until the time of the open flame is obtained.

[0061] Specifically, in this embodiment:

[0062] Since there is no global clock in the data used, the starting time t0 of the zero-sequence current waveform data is set to 0, each fixed time interval t1 in the zero-sequence current waveform data is set to 1s, the threshold value of the filter decision quantity is set to 0.1, the threshold value of the first-order difference decision quantity is set to 0.0002, and the positive integer value k0 is set to 99.

[0063] Find the position k of the first value greater than 0.1 in the normalized filter decision sequence. In this embodiment, it is the 8096th item in the normalized filter decision sequence.

[0064] In the normalized first-order difference decision sequence, items 7997 to 8096 are selected. Starting from item 8096, the decision is made backward. If there is an item greater than or equal to 0.0002, then 8096 is reduced by 1. Then, from item 8095 to item 7996, the decision is made again to see if there is an item greater than or equal to 0.0002. This process is repeated until all 100 items are less than 0.0002. The time of the open flame is calculated using the formula t0 + k × t1. In this embodiment, the loop ends when k = 7757, so the time of the open flame is the 7757th second.

[0065] Example 2:

[0066] An open flame detection system for overhead power lines includes a data preprocessing module and an open flame occurrence time determination module;

[0067] The data preprocessing module is used to collect zero-sequence current waveform data and record the start time of the zero-sequence current waveform data. It sequentially records the data within the first power frequency cycle at each fixed time interval in the zero-sequence current waveform data, processes all data to obtain the true amplitude of each data, extracts the power frequency amplitude and the third harmonic amplitude from the true amplitude of each data, calculates the judgment quantity of each data through the power frequency amplitude and the third harmonic amplitude of each data, and combines the judgment quantities of all data into a judgment quantity sequence.

[0068] The open flame occurrence time determination module is used to filter the determination quantity sequence to obtain a filtered determination quantity sequence, then perform a first-order difference on the filtered determination quantity sequence to obtain a first-order difference determination quantity sequence, and normalize the filtered determination quantity sequence and the first-order difference determination quantity sequence. The open flame occurrence time is calculated using the start time of the zero-sequence current recording data, the normalized filtered determination quantity sequence, and the normalized first-order difference determination quantity sequence.

[0069] This embodiment is used to implement the function of Embodiment 1, and will not be described again here.

[0070] Example 3:

[0071] This embodiment proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method described in any embodiment of the present invention.

[0072] Example 4:

[0073] This embodiment proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in any embodiment of the present invention.

[0074] In this embodiment of the invention, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects have an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0075] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0076] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0077] In several embodiments provided by this invention, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0078] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for identifying open flames on overhead power lines, characterized in that, Includes the following steps: Collect zero-sequence current waveform data and record the start time of the zero-sequence current waveform data. Sequentially record the data within the first power frequency cycle at each fixed time interval in the zero-sequence current waveform data. Process all data to obtain the true amplitude of each data. Extract the power frequency amplitude and the third harmonic amplitude from the true amplitude of each data. Calculate the judgment quantity of each data using the power frequency amplitude and the third harmonic amplitude of each data. Combine the judgment quantities of all data into a judgment quantity sequence. A first-order difference decision sequence is obtained based on the decision sequence; The time of open flame occurrence is calculated using the start time of zero-sequence current recording data, the filter decision sequence, and the first-order difference decision sequence. The determination value for each data point is calculated as follows: in: The decision metric for a single data point; The power frequency amplitude of a single data point; The third harmonic amplitude of a single data point; Perform K-point median filtering and smoothing filtering on the decision sequence; The specific calculation steps for the first-order difference decision sequence are as follows: Suppose that the filter decision sequence has For each data point in the filter decision sequence, subtract the previous data point from the next data point and take the absolute value of the result to obtain the result from... A sequence of first-order difference decision quantities consisting of non-negative numbers; The specific steps for calculating the timing of the open flame are as follows: Let the starting time of the zero-sequence current recording data be... In the zero-sequence current recording data, each fixed time interval is... ; Extract the data that exceeds the filter decision threshold in the normalized filter decision sequence, and let this data be the first data. Item data; Preset positive integer value Take the first digit from the normalized first-order difference decision sequence. Item to No. Items, total Item data, judgment Are all data points less than the first-order difference decision threshold? If all data points are less than the first-order difference decision threshold, then the time of open flame occurrence is... If any data exceeds the threshold of the first-order difference decision quantifier, then... Repeat the current step until the moment when the open flame appears.

2. The method for identifying open flames on overhead power lines according to claim 1, characterized in that, The true amplitude of each data point is obtained by performing a Fast Fourier Transform on the original data.

3. A system for detecting open flames on overhead power lines, characterized in that, This includes a data preprocessing module and a module for determining the time of open flame appearance; The data preprocessing module is used to collect zero-sequence current waveform data and record the start time of the zero-sequence current waveform data. It sequentially records the data within the first power frequency cycle at each fixed time interval in the zero-sequence current waveform data, processes all data to obtain the true amplitude of each data, extracts the power frequency amplitude and the third harmonic amplitude from the true amplitude of each data, calculates the judgment quantity of each data through the power frequency amplitude and the third harmonic amplitude of each data, and combines the judgment quantities of all data into a judgment quantity sequence. The open flame occurrence time determination module is used to filter the determination quantity sequence to obtain a filtered determination quantity sequence, and then obtain a first-order differential determination quantity sequence based on the determination quantity sequence; the open flame occurrence time is calculated by the start time of the zero-sequence current recording data, the filtered determination quantity sequence, and the first-order differential determination quantity sequence. The formula for calculating the decision value of each data point in the data preprocessing module is shown below: in: The decision metric for a single data point; The power frequency amplitude of a single data point; The third harmonic amplitude of a single data point; The open flame occurrence time determination module performs K-point median filtering and smoothing filtering on the determination quantity sequence. The open flame occurrence time determination module calculates the first-order difference determination quantity sequence through the following steps: Suppose that the filter decision sequence has For each data point in the filter decision sequence, subtract the previous data point from the next data point and take the absolute value of the result to obtain the result from... A sequence of first-order difference decision quantities consisting of non-negative numbers; The open flame occurrence time determination module calculates the open flame occurrence time through the following steps: Let the starting time of the zero-sequence current recording data be... In the zero-sequence current recording data, each fixed time interval is... ; Extract the data that exceeds the filter decision threshold in the normalized filter decision sequence, and let this data be the first data. Item data; Preset positive integer value Take the first digit from the normalized first-order difference decision sequence. Item to No. Items, total Item data, judgment Are all data points less than the first-order difference decision threshold? If all data points are less than the first-order difference decision threshold, then the time of open flame occurrence is... If any data exceeds the threshold of the first-order difference decision quantifier, then... Repeat the current step until the moment when the open flame appears.

4. The overhead power line open flame detection system according to claim 3, characterized in that, The data preprocessing module obtains the true amplitude of each data point by performing a Fast Fourier Transform on the raw data.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 2.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 2.

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