Early leakage current prediction method, device, equipment and medium for tree line touch fault

Abstract

The present application discloses a method, device, equipment and medium for predicting early leakage current of tree-line touch faults, belonging to the technical field of distribution line grounding fault detection. The method includes: establishing a multi-factor coupled tree body temperature rise time-domain model, where the tree body temperature rise time-domain model is a mathematical model describing the tree body temperature rise changing with time, and the multi-factors considered include tree size, moisture content and ambient temperature; establishing a variety of equivalent fault resistance-tree temperature models, where the equivalent fault resistance-tree temperature model is a mathematical model describing the change of the equivalent fault resistance value with the tree temperature; calculating the prediction errors of each equivalent fault resistance-tree temperature model respectively, and selecting the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model; using the optimal equivalent fault resistance-tree temperature model to calculate the equivalent fault resistance, and the effective value of the leakage current can be predicted according to the calculated equivalent fault resistance and the fault phase voltage.

Description

Technical Field

[0001] This application belongs to the technical field of distribution line grounding fault detection, and particularly relates to a method, device, equipment and medium for predicting early leakage current of tree-line touch faults. Background Technique

[0002] In the operation of mountain or forest area distribution networks, due to the too-close distance between conductors and trees, tree-line touch faults (TTWF) are likely to occur. TTWF usually does not directly cause tripping or power supply interruption, but long-term leakage current can cause local overheating, burning of trees and even fires. This not only endangers power supply safety, but may also cause serious casualties and property losses. Therefore, it is of great significance to study the TTWF fault mechanism and prevention and control technologies.

[0003] The research on TTWF fault detection faces the following challenges: (1) Weak fault characteristics: TTWF belongs to a type of high-resistance grounding fault, and its leakage current is usually less than 1% of the load current, making it difficult to trigger traditional power grid protection devices; at the same time, characteristic signals such as leakage current and voltage gradient during the fault process are significantly affected by environmental factors, further increasing the monitoring difficulty. (2) Multi-stage complexity: The process of TTWF from tree-line contact to flame combustion can be divided into four typical stages: preheating stage, water ejection stage, carbonization channel development stage and fire spread stage. The electrical and thermal characteristics of these stages are significantly different, and it is necessary to establish staged models for different stages. (3) Great influence of external factors: Tree size, moisture content and environmental temperature are the key factors affecting the TTWF process. For example, tree size: The trunk diameter and length directly affect heat accumulation and the propagation path of leakage current. Moisture content: Trees with high moisture content are difficult to heat up quickly, but once the moisture evaporates, the local carbonized area will accelerate heat accumulation. Environmental temperature: A higher environmental temperature will shorten the time for open fire generation and exacerbate the fire risk. (4) Lack of on-site data: Due to the small number of accident data caused by TTWF, and the fault simulation under laboratory conditions is limited by test conditions, the existing research has limitations in terms of data.

[0004] The existing research on tree-line touch faults is mainly divided into the following categories:

[0005] (1) Emanuel model and HIF high-resistance grounding fault simulation technology: It uses the Emanuel model and two anti-parallel DC sources to simulate the nonlinear characteristics of HIF, and can reproduce the distortion characteristics of high-resistance grounding faults.

[0006] (2) Equivalent resistance exponential decay fault model: The TTWF fault characteristics are studied through the change law of the equivalent resistance of trees. Assuming that the equivalent resistance only changes with the length of the tree, an attenuation model is formed.

[0007] (3)Fault detection method based on high-frequency signal analysis: By analyzing the high-frequency signal components in the leakage current of the wire, the fault characteristics are captured. It can identify the abnormalities of high-frequency signals caused by TTWF.

[0008] However, the above existing technologies have the following problems and limitations:

[0009] Existing technologies usually equate TTWF with traditional high-impedance grounding faults (HIF), such as the Emanuel model or the double anti-parallel DC source model, which are only applicable to wire degradation or metal contact faults. They cannot capture the unique stage dynamic characteristics of TTWF (such as slow change of leakage current and temperature rise effect), resulting in inaccurate description of fault characteristics before an open fire.

[0010] Existing technologies often analyze the influence of tree size or moisture content on faults separately and do not establish a multi-factor comprehensive model. They cannot fully consider the coupled influence of environmental temperature, tree size, and moisture content, which limits the applicability of the model in various scenarios and lacks robustness. This leads to insufficient early warning ability for TTWF.

[0011] Existing technologies are mostly based on the characteristic signals after an open fire (such as high-frequency discharge signals or obvious arc characteristics) and pay less attention to the dynamic changes of leakage current before an open fire. They cannot capture the hidden characteristics of TTWF ignition in advance, resulting in delayed identification of fire risks and increased accident risks.

[0012] Existing technologies often cannot fully restore the tree characteristics and environmental factors in a complex natural environment, resulting in large prediction errors in the established model and poor application effects in actual scenarios. Summary of the Invention

[0013] To solve the problems existing in the existing TTWF fault detection technology, this application proposes an early leakage current prediction method, device, equipment, and medium for tree-line touch faults. This application focuses on the fault stage before an open fire in TTWF and establishes a leakage current time-domain model. This model predicts the leakage current and equivalent resistance values at each fault moment by inputting parameters such as the fault duration (starting from the moment of tree-line contact), tree size, moisture content, and environmental temperature.

[0014] This application is implemented through the following technical solutions:

[0015] An early leakage current prediction method for tree-line touch faults, comprising:

[0016] Establish a time-domain model of tree body temperature rise with multi-factor coupling. The time-domain model of tree body temperature rise is a mathematical model describing the temperature rise of the tree body over time, and the multi-factors considered include tree size, moisture content, and environmental temperature;

[0017] Establish multiple equivalent fault resistance-tree temperature models, where the equivalent fault resistance-tree temperature model is a mathematical model describing the variation of the equivalent fault resistance value with the tree temperature;

[0018] Calculate the prediction errors of each equivalent fault resistance-tree temperature model respectively, and select the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model;

[0019] Calculate the equivalent fault resistance using the optimal equivalent fault resistance-tree temperature model, and the effective value of the leakage current can be predicted based on the calculated equivalent fault resistance and the fault phase voltage.

[0020] In some embodiments, the establishment process of the tree body temperature rise time domain model includes:

[0021] Calculate the specific heat capacity of wood based on the specific heat capacity of absolutely dry state wood, the specific heat capacity of water, and the absolute moisture content of wood;

[0022] Calculate the input heat power based on the applied voltage value and the trunk body resistance;

[0023] Calculate the convective heat dissipation power according to the convective heat transfer coefficient, the tree skin temperature, the ambient temperature, and the trunk side area;

[0024] Calculate the radiative heat dissipation power according to the medium emissivity, the Stefan-Boltzmann constant, the thermodynamic temperature of the tree skin, the trunk side area, and the thermodynamic temperature of the test environment using the Stefan-Boltzmann law;

[0025] Obtain the output heat power according to the convective heat dissipation power and the radiative heat dissipation power;

[0026] Calculate the tree body temperature rise rate based on the input heat power, the output heat power, the wood density, the tree height at the tree line connection, the average trunk radius, and the specific heat capacity of wood;

[0027] Obtain the average tree body temperature according to the tree body temperature rise rate and the ambient temperature.

[0028] In some embodiments, the establishment of multiple equivalent fault resistance-tree temperature models includes:

[0029] Repeat the experiment on multiple groups of samples, and record the average tree body temperature and the equivalent fault resistance value in real time;

[0030] It is obtained through the analysis of the average tree body temperature and the equivalent fault resistance value recorded in real time that: the equivalent fault resistance shows a decaying trend with the increase of the average tree body temperature;

[0031] Select multiple function models suitable for describing the decaying trend of the equivalent fault resistance with the increase of the tree temperature;

[0032] The parameters in the function model are determined by fitting with measured data.

[0033] In some embodiments, calculating the prediction errors of each equivalent fault resistance-tree temperature model respectively, and selecting the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model includes:

[0034] Calculating the root mean square error between the equivalent fault resistance values obtained by simulating each equivalent fault resistance-tree temperature model and the measured equivalent fault resistance values respectively;

[0035] Taking the model with the smallest root mean square error as the optimal equivalent fault resistance-tree temperature model.

[0036] In some embodiments, the multiple function models selected include: linear function model, exponential function model and power function model.

[0037] In some embodiments, the optimal equivalent fault resistance-tree temperature model adopts an exponential function model.

[0038] In a second aspect, the present application proposes a device for predicting the early leakage current of a tree-line touch fault, which is characterized by including:

[0039] A first modeling unit, configured to establish a multi-factor coupled tree body temperature rise time domain model, where the tree body temperature rise time domain model is a mathematical model describing the tree body temperature rise changing with time; the multi-factors considered include tree size, moisture content and environmental temperature;

[0040] A second modeling unit, configured to establish multiple equivalent fault resistance-tree temperature models, where the equivalent fault resistance-tree temperature model is a mathematical model describing the change of the equivalent fault resistance value with the tree temperature;

[0041] A model optimization unit, configured to calculate the prediction errors of each equivalent fault resistance-tree temperature model respectively, and select the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model;

[0042] And a calculation unit, which calculates the equivalent fault resistance by using the optimal equivalent fault resistance-tree temperature model, and can predict the effective value of the leakage current according to the calculated equivalent fault resistance and the fault phase voltage.

[0043] In some embodiments, the first modeling unit is configured to:

[0044] Calculate the specific heat capacity of wood based on the specific heat capacity of absolutely dry state wood, the specific heat capacity of water and the absolute moisture content of wood;

[0045] Calculate the input heat power based on the applied voltage value and the trunk body resistance;

[0046] Calculate the convective heat dissipation power based on the convective heat transfer coefficient, the tree bark temperature, the ambient temperature, and the lateral area of the tree trunk;

[0047] Calculate the radiative heat dissipation power according to the medium emissivity, the Stefan-Boltzmann constant, the thermodynamic temperature of the tree bark, the lateral area of the tree trunk, and the thermodynamic temperature of the test environment by using the Stefan-Boltzmann law;

[0048] Obtain the output heat power based on the convective heat dissipation power and the radiative heat dissipation power;

[0049] Calculate the tree body temperature rise rate based on the input heat power, the output heat power, the wood density, the height of the tree at the tree line connection, the average radius of the tree trunk, and the specific heat capacity of the wood;

[0050] Obtain the average temperature of the tree body according to the tree body temperature rise rate and the ambient temperature.

[0051] In a third aspect, the present application provides an electronic device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the above-mentioned methods are implemented.

[0052] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any one of the above-mentioned methods are implemented.

[0053] A method for predicting early leakage current of tree-line touch faults in the present application comprehensively considers various key factors (such as size, moisture content, and ambient temperature), establishes a multi-factor coupling model to simulate the fault characteristics of TTWF in a real environment, improves the robustness of the model, and ensures that the prediction results have high adaptability in multiple scenarios; focusing on the early stage of TTWF, it can accurately predict the slow changes of the equivalent fault resistance and leakage current, provide real-time early warning before a fire occurs, and based on the effective value of the leakage current and the tree body temperature rise rate, identify the fault risk in advance, providing sufficient response time for power operation and maintenance and wildfire prevention and control; the present application optimizes the model parameters by combining experimental data to improve the adaptability and robustness of the model; through experimental verification, the prediction error of the present application is less than 6%, and the prediction accuracy is improved by more than 50% compared with the prior art, and it is applicable to various vegetation characteristics (size, moisture content) and complex natural environmental conditions, significantly enhancing its applicability.

[0054] Correspondingly, a device, equipment, and medium for predicting early leakage current of tree-line touch faults proposed in the present application also have the same above-mentioned technical effects. Description of the Drawings

[0055] The accompanying drawings described herein are used to provide a further understanding of the embodiments of the present application, form a part of the present application, and do not limit the embodiments of the present application. In the drawings:

[0056] Figure 1 It is a schematic flow chart of the prediction method proposed in the embodiment of the present application;

[0057] Figure 2 It is a full-process diagram of the TTWF igniting trees and the fire spreading obtained by actual measurement in the embodiment of the present application;

[0058] Figure 3 It is the effective value of the leakage current corresponding to the whole process of TTWF obtained by actual measurement in the embodiment of the present application;

[0059] Figure 4 It is a comparison schematic diagram of the tree temperature obtained by actual measurement in the embodiment of the present application and the tree temperature simulated by using the tree body temperature rise time domain model;

[0060] Figure 5(a) is a comparison schematic diagram of the equivalent fault resistance value obtained by actual measurement in the embodiment of the present application and the equivalent fault resistance value calculated by using the linear function model;

[0061] Figure 5(b) is a comparison schematic diagram of the equivalent fault resistance value obtained by actual measurement in the embodiment of the present application and the equivalent fault resistance value calculated by using the exponential function model;

[0062] Figure 5(c) is a comparison schematic diagram of the equivalent fault resistance value obtained by actual measurement in the embodiment of the present application and the equivalent fault resistance value calculated by using the power function model;

[0063] Figure 6 It is a schematic diagram of the phenomenon of the appearance of a flickering open flame in TTWF;

[0064] Figure 7 It is a comparison schematic diagram of the effective value of the leakage current calculated in the embodiment of the present application and the effective value of the leakage current measured;

[0065] Figure 8(a) is a comparison schematic diagram of the leakage current values at six open flame moments calculated by using the existing model and the measured data;

[0066] Figure 8(b) is a comparison schematic diagram of the leakage current values at six open flame moments calculated by using the embodiment of the present application and the measured data;

[0067] Figure 9 It is a schematic diagram of the principle architecture of the prediction device proposed in the embodiment of the present application;

[0068] Figure 10 It is a schematic diagram of the principle of the prediction system proposed in the embodiment of the present application;

[0069] Figure 11Schematic diagram of the principle of the electronic device proposed in the embodiments of the present application;

[0070] Figure 12 Schematic diagram of the computer-readable storage medium proposed in the embodiments of the present application;

[0071] Reference numerals and corresponding component names:

[0072] 200 - Prediction device, 201 - First modeling unit, 202 - Second modeling unit, 203 - Model optimization unit, 204 - Calculation unit, 300 - Prediction system, 301 - Input device, 302 - Output device, 303 - Processor A, 304 - Memory A, 400 - Electronic device, 410 - Memory B, 420 - Processor B, 411 - Computer program A, 500 - Computer-readable storage medium, 511 - Computer program B. Detailed implementation manners

[0073] In the following, the term "comprise" or "may comprise" that can be used in various embodiments of the present application indicates the presence of the invented functions, operations or elements, and does not limit the addition of one or more functions, operations or elements. Further, as used in various embodiments of the present application, the terms "comprise", "have" and their cognates are only intended to represent specific features, numbers, steps, operations, elements, components or combinations of the foregoing items, and should not be construed as precluding the existence or addition of one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing items first.

[0074] In various embodiments of the present application, the expression "or" or "at least one of A or / and B" includes any combination or all combinations of the listed words. For example, the expression "A or B" or "at least one of A or / and B" may include A, may include B, or may include both A and B.

[0075] Expressions (such as "first", "second", etc.) used in various embodiments of the present application may modify various constituent elements in various embodiments, but do not limit the corresponding constituent elements. For example, the above expressions do not limit the order and / or importance of the elements. The above expressions are only for the purpose of distinguishing one element from other elements. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, without departing from the scope of various embodiments of the present application, the first element may be referred to as the second element, and similarly, the second element may also be referred to as the first element.

[0076] It should be noted that: If it is described that a component is "connected" to another component, the first component can be directly connected to the second component, and a third component can be "connected" between the first component and the second component. Conversely, when a component is "directly connected" to another component, it can be understood that there is no third component between the first component and the second component.

[0077] The terms used in the various embodiments of the present application are for the purpose of describing specific embodiments only and are not intended to limit the various embodiments of the present application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of the present application belong. The terms (such as those defined in a commonly used dictionary) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning, unless clearly defined in the various embodiments of the present application.

[0078] To make the objectives, technical solutions, and advantages of the present application clearer and more understandable, the present application will be further described in detail below in conjunction with embodiments and drawings. The illustrative embodiments and descriptions of the present application are only used to explain the present application and do not serve as a limitation to the present application.

[0079] Embodiment: This embodiment proposes a method for predicting the early leakage current of a tree-line touch fault. First, a tree body temperature rise time-domain model is established by combining thermodynamics and electrical theories; then, an equivalent fault resistance-tree body temperature exponential function model is obtained by fitting real test data for calculating the equivalent fault resistance value; then, the effective value of the leakage current before the open fire can be predicted from the grounding phase voltage and the equivalent fault resistance value.

[0080] Description of related terms:

[0081] Tree-line touch fault (TTWF): Refers to a grounding fault formed by a tree touching a certain phase conductor of a distribution line.

[0082] Leakage current: Refers to the current flowing through the tree body after the tree contacts the conductor.

[0083] Equivalent resistance: Reflects the resistance characteristics of the fault in the electrical circuit and changes with the temperature and moisture content of the tree.

[0084] Ignition point: The temperature at which a tree starts to show an open fire under certain conditions.

[0085] As Figure 1 shown, the prediction method proposed in this embodiment includes the following steps:

[0086] Step 110, establish a tree body temperature rise time domain model with multi-factor coupling, which is a mathematical model describing the tree body temperature rise changing with time.

[0087] In actual fault scenarios, it is difficult to measure the tree body temperature of TTWF in real time. Therefore, in this embodiment, a tree body temperature rise time domain model before TTWF ignition is established, and the specific process is as follows:

[0088] Assume that the ambient temperature remains constant during the experiment. The tree body temperature rise rate depends on the input heat power and the output heat power. Then the tree body temperature rise rate is expressed as:

[0089] (1)

[0090] Among them, represents the tree body temperature rise rate; and respectively represent the input heat power and the output heat power at time t (i.e., the heat power flowing into and out of the tree body); represents the wood density, which can be taken as 530 kg / m 3 ; represents the height of the tree line connection to the ground; represents the average radius of the tree trunk; represents the specific heat capacity of wood, which is related to the moisture content of wood and independent of the tree species. Its calculation formula is:

[0091] (2)

[0092] Among them, represents the specific heat capacity of wood in the absolutely dry state, about 1368.17 J / (kg·°C); represents the specific heat capacity of water, about 4200 J / (kg·°C); represents the absolute moisture content of wood, and its calculation formula is:

[0093] (3)

[0094] Among them, represents the weight of water in the sample; represents the weight of the sample after drying.

[0095] The input heat power can only consider the main part of the tree trunk. The joule heat generated by the leakage current is the main heat source for the tree body temperature rise, and its calculation formula is as follows:

[0096] (4)

[0097] Among them, represents the applied voltage value; represents the resistance of the tree trunk body, and its calculation formula is:

[0098] (5)

[0099] Among them, the water-containing wood has a certain conductivity, and the resistivity decreases with the increase of temperature and can be expressed by an exponential function:

[0100] (6)

[0101] Among them, represents the resistivity at the initial temperature of the wood; represents the ambient temperature; represents the undetermined coefficient; represents the average temperature of the tree body.

[0102] It is usually very difficult to accurately calculate the output heat power, but it can be estimated as the sum of heat convection and heat radiation. Among them, the convective heat dissipation is proportional to the temperature difference, and the calculation formula is:

[0103] (7)

[0104] Among them, represents the convective heat dissipation power; represents the convective heat transfer coefficient, with the unit of W / (m 2 ·℃); represents the tree surface temperature; represents the surface area of the tree in contact with the air (the lateral area of the tree trunk), and its calculation formula is:

[0105] (8)

[0106] The radiative heat dissipation can be estimated by the Stefan-Boltzmann Law:

[0107] (9)

[0108] Among them, represents the radiative heat dissipation power; represents the medium thermal emissivity; represents the Stefan-Boltzmann constant, approximately 5.67×10 -8 W / (m 2 ·K 4 ); represents the thermodynamic temperature of the tree surface; represents the thermodynamic temperature of the test environment. The thermodynamic temperature and the Celsius temperature conversion formula is:

[0109] (10)

[0110] Then the output thermal power calculation formula is:

[0111] (11)

[0112] Combining the above equations (1) to (11) to calculate the tree temperature rise rate, we can get the average tree temperature at time t: , expressed as:

[0113] (12)

[0114] Step 120 , establishing a plurality of equivalent fault resistance-tree temperature models, wherein the equivalent fault resistance-tree temperature model is a mathematical model that describes the variation of the equivalent fault resistance value with the tree temperature.

[0115] On the 10kV overhead test line, the test was repeated on multiple groups of samples, and the average tree temperature and equivalent fault resistance value were recorded in real time;

[0116] By analyzing the real-time recorded average temperature of the tree and the equivalent fault resistance value, it can be found that the equivalent fault resistance shows a decreasing trend as the average temperature of the tree increases;

[0117] Select a variety of function models suitable for describing the attenuation trend of the equivalent fault resistance with the increase of the tree temperature. This embodiment takes three function models, namely, a linear function model, an exponential function model, and a power function model, as examples for explanation. The equivalent fault resistances under the linear function model, the exponential function model, and the power function model are respectively expressed as:

[0118] (13)

[0119] (14)

[0120] (15)

[0121] in, represents the equivalent fault resistance; Indicates the initial grounding resistance; represents the average temperature of the tree, which is calculated using the above formula (12); Represents the model parameters, which can be determined by fitting the measured data.

[0122] Step 130 , respectively calculate the prediction errors of the equivalent fault resistance-tree temperature models, and select the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model.

[0123] The specific process of step 130 is as follows:

[0124] First, calculate the RMSE (Root Mean Squared Error) values of the equivalent fault resistance values obtained by simulating the linear function model, exponential function model, and power function model respectively and the measured equivalent fault resistance values.

[0125] Then, select the model with the smallest RMSE value as the optimal equivalent fault resistance-tree temperature model for calculating the equivalent fault resistance in subsequent applications.

[0126] Step 140, calculate the equivalent fault resistance using the optimal equivalent fault resistance-tree temperature model, and the effective value of the leakage current can be predicted based on the calculated equivalent fault resistance and the fault phase voltage.

[0127] The prediction method proposed in this embodiment constructs a coupling relationship that dynamically reflects the coupling relationship between the tree body temperature rise, the attenuation of the equivalent fault resistance, and the slow change of the leakage current by integrating thermodynamics and electrical characteristics. This coupling relationship integrates key factors such as tree size, moisture content, and environmental temperature, simulates the fault characteristics of TTWF in a real environment, has high robustness, and ensures that the prediction results have high adaptability in multiple scenarios. The method proposed in this embodiment focuses on the early stage of TTWF, can accurately predict the slow changes of the leakage current and the equivalent resistance, provide real-time early warning before the fire occurs, and can identify the fault risk in advance based on the effective value of the leakage current and the tree body temperature rise speed, providing sufficient response time for power operation and maintenance and wildfire prevention and control.

[0128] Furthermore, in this embodiment, an experiment is carried out by building a TTWF test platform. The TTWF test platform includes: a voltage regulator and a step-up transformer, which are used as the power supply part; a current transformer and a voltage transformer, which are used as the measurement part; an oscilloscope, an infrared thermometer, an environmental temperature monitor, a high-speed camera, and an overhead line as the data acquisition part. The specific experimental process is as follows:

[0129] Select test samples: Select fresh camellia trees commonly distributed in the regions of Yunnan, Guizhou, and Sichuan, with an average radius of 1.7 - 2.6 cm (taking the average value of the radii at the bottom, middle, and connection of the tree trunk), and a moisture content of 61% - 77%.

[0130] Build the test platform: According to relevant regulations, take the overlapping height of 1.5 m between the 10 kV distribution line and the trees at the mountainside cliffs, etc. in extreme cases, and set the phase voltage of the fault phase to 5.8 kV to simulate the real TTWF.

[0131] Data collection and recording: Use the environmental temperature monitor to record the environmental temperature where the test samples are located; use the oscilloscope to collect the leakage current signal (sampling accuracy is 5 mA, sampling rate is 20 kS / s); use the infrared thermometer to collect the temperature data of the test samples; use the high-speed camera to record the whole process of TTWF igniting the trees.

[0132] Data analysis: After the tree line is connected, four stage phenomena occur during the whole process from the ignition of the tree by TTWF to the spread of the fire, namely the contact point arc (Stage I: Arc generation stage), the fluttering of open flames (Stage II: Open flame fluttering stage), the large-scale ejection of water vapor (Stage III: Large-scale water vapor ejection stage), and the penetration of combustion (Stage IV: Intense combustion stage), as Figure 2 shown. After the end of the first stage of TTWF, open flames are quickly generated. In dry and windy weather, it is easy to ignite the surrounding combustibles and accelerate the spread of the fire.

[0133] The effective values of the leakage current corresponding to the four stages of TTWF are as Figure 3 shown. It can be seen that compared with the fire development stage, the arc generation stage (the first stage) of TTWF has the longest duration, and the leakage current shows a smooth and slow upward trend. At this stage, the temperature of the tree has not reached the condition for water vapor ejection, and the influence of the evaporation effect on the equivalent fault resistance is not significant. Considering the Joule heat generated by the energization of the tree is the main reason for the increase in the leakage current.

[0134] Select a set of typical data: the ambient temperature is 18.1 °C; the connection height is 1.5 m; the average radius of the tree is 1.7 cm; the water content of the tree trunk is 77%. Calculated at intervals of 10 s, the RMSE value between the tree temperature obtained by simulating the tree temperature rise time domain model and the measured tree temperature reaches 0.9824, and the fitting effect is as Figure 4 shown. It can be seen that the above-mentioned tree temperature rise time domain model established in this embodiment can well reflect the dynamic process of the tree temperature rise.

[0135] At the same time, in this embodiment, based on the above test platform and measured data, various equivalent fault resistance-tree temperature models established in this embodiment are optimized. First, the model parameters of the linear function model, exponential function model, and power function model are respectively obtained by fitting the measured data which are: 0.015; 0.026; 0.978 respectively. Then, the prediction errors RMSE of the linear function model, exponential function model, and power function model are calculated respectively as: 0.68426; 0.96501; 0.90736, and the fitting effects are shown in Figure 5(a), Figure 5(b), and Figure 5(c) respectively. It can be seen that the exponential function model shows a better effect when describing the change trend of the equivalent fault resistance. Therefore, this embodiment selects the exponential function model to calculate the equivalent fault resistance.

[0136] As Figure 6 shown, an obvious open flame fluttering phenomenon appears about 495 s after TTWF starts. Using the above-mentioned model proposed in this embodiment, the value of the equivalent fault resistance can be calculated, and the effective value of the leakage current can be calculated in combination with the fault phase voltage (5.8 kV). The comparison between the measured and simulation results is as Figure 7As shown, it can be seen from the figure that the prediction result of the prediction method proposed in this embodiment can well describe the change trend of the actual leakage current of TTWF, so as to provide real-time early warning before the fire occurs and sufficient response time for power operation and maintenance and wildfire prevention and control.

[0137] In addition, this embodiment also uses the existing model that only considers the tree length as a comparative example to verify that the effective value of the leakage current predicted by the prediction method proposed in this embodiment shows better accuracy. Specifically, the existing equivalent resistance model is used to calculate the effective value of the leakage current at the moment of open fire:

[0138] (16)

[0139] Where represents the resistance when the carbonization channel is completely formed; represents the decay time constant, which is only related to the tree length L, and the calculation formula is:

[0140] (17)

[0141] Using the above existing model and the prediction method proposed in this embodiment, the comparison diagrams of the leakage current values at the moment of open fire of six groups calculated respectively and the measured data are shown in FIGS. 8(a) and 8(b). It can be seen from the comparison diagram of the leakage current values calculated by the existing model shown in FIG. 8(a) and the measured data that the calculation errors of the leakage current values at the moment of open fire of six groups calculated by the existing model are: 13.8%, 16.0%, 4.8%, 5.4%, 17.9%, 8.8%; while the calculation errors of the leakage current values at the moment of open fire of six groups calculated by the method proposed in this embodiment shown in FIG. 8(b) are: 2.8%, 3.0%, 2.9%, 2.1%, 5.5%, 5.1%. By comparison, the prediction method proposed in this embodiment comprehensively considers factors such as tree size, moisture content, and environmental temperature, and has better accuracy for simulating the change trend of the leakage current before the open fire of TTWF.

[0142] This embodiment also proposes an early leakage current prediction device for tree-line touch faults, as Figure 9 shown. The prediction device 200 includes:

[0143] The first modeling unit 201 is used to establish a multi-factor coupled tree body temperature rise time domain model, and the tree body temperature rise time domain model is a mathematical model that describes the change of the tree body temperature rise over time. The specific tree body temperature rise time domain model is as shown in formulas (1)-(12) of the above method, and will not be elaborated here.

[0144] The second modeling unit 202 is used to establish multiple equivalent fault resistance-tree temperature models, and the equivalent fault resistance-tree temperature model is a mathematical model describing the change of the equivalent fault resistance value with the tree temperature. The specific model establishment process is as described in the above method and will not be elaborated here.

[0145] The model optimization unit 203 is used to calculate the prediction errors of the respective equivalent fault resistance-tree temperature models, and select the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model. The specific selection process is as described in the above method and will not be elaborated here.

[0146] Moreover, the calculation unit 204 uses the optimal equivalent fault resistance-tree temperature model to calculate the equivalent fault resistance, and the effective value of the leakage current can be predicted based on the calculated equivalent fault resistance and the fault phase voltage.

[0147] This embodiment also proposes a leakage current prediction system for tree-line touch faults, as Figure 10 shown. The prediction system 300 proposed in this embodiment includes:

[0148] An input device 301, an output device 302, a processor A 303, and a memory A 304; among them, the number of the processor A 303 and the memory A 304 can be one or more, Figure 3 and one processor A 303 and one memory A 304 are taken as examples for illustration. The input device 301, the output device 302, the processor A 303, and the memory A 304 can be connected through a bus or other means, Figure 10 and taking the connection through a bus as an example.

[0149] Among them, by calling the operation instructions stored in the memory A 304, the processor A 303 is used to execute the following steps:

[0150] Establish a multi-factor coupled tree body temperature rise time domain model, and the tree body temperature rise time domain model is a mathematical model describing the tree body temperature rise changing with time;

[0151] Establish multiple equivalent fault resistance-tree temperature models, and the equivalent fault resistance-tree temperature model is a mathematical model describing the change of the equivalent fault resistance value with the tree temperature;

[0152] Calculate the prediction errors of the respective equivalent fault resistance-tree temperature models, and select the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model;

[0153] Use the optimal equivalent fault resistance-tree temperature model to calculate the equivalent fault resistance, and the effective value of the leakage current can be predicted based on the calculated equivalent fault resistance and the fault phase voltage.

[0154] Optionally, by calling the operation instructions stored in memory A304, the processor A303 is also used to execute any implementation manner in the corresponding embodiment of the above prediction method.

[0155] In another embodiment, this embodiment also proposes an electronic device 400, as Figure 11 shown, the electronic device 400 includes: a memory B410, a processor B420, and a computer program A411 stored on the memory B410 and executable on the processor B420. When the processor B420 executes the computer program A411, the following steps are implemented:

[0156] Establish a multi-factor coupled tree body temperature rise time domain model, which is a mathematical model describing the tree body temperature rise changing with time;

[0157] Establish a variety of equivalent fault resistance-tree temperature models, which are mathematical models describing the change of equivalent fault resistance values with tree temperature;

[0158] Calculate the prediction errors of each equivalent fault resistance-tree temperature model respectively, and select the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model;

[0159] Use the optimal equivalent fault resistance-tree temperature model to calculate the equivalent fault resistance, and the effective value of the leakage current can be predicted according to the calculated equivalent fault resistance and the fault phase voltage.

[0160] Optionally, when the processor B420 executes the computer program A411, any implementation manner in the corresponding embodiment of the above prediction method can be implemented.

[0161] It should be noted that the electronic device proposed in this embodiment is the device used to implement the above prediction method. Therefore, based on the above prediction method proposed in this embodiment, those skilled in the art can understand the specific implementation manner and various variation forms of the electronic device in this embodiment. Therefore, the specific implementation of how this electronic system implements the above prediction method will not be introduced in detail here. As long as the electronic device used by those skilled in the art to implement the above prediction method belongs to the scope protected by this application.

[0162] In another embodiment, this embodiment also proposes a computer-readable storage medium 500, as Figure 12 shown, a computer program B511 is stored on the computer-readable storage medium 500. When the computer program B511 is executed by a processor, the following steps are implemented:

[0163] Establish a multi-factor coupled tree body temperature rise time domain model, which is a mathematical model describing the tree body temperature rise changing with time;

[0164] Establish multiple equivalent fault resistance-tree temperature models, where the equivalent fault resistance-tree temperature model is a mathematical model that describes the variation of the equivalent fault resistance value with the tree temperature;

[0165] Calculate the prediction errors of each equivalent fault resistance-tree temperature model respectively, and select the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model;

[0166] Calculate the equivalent fault resistance using the optimal equivalent fault resistance-tree temperature model, and the effective value of the leakage current can be predicted based on the calculated equivalent fault resistance and the fault phase voltage.

[0167] Optionally, when the computer program B511 is executed by a processor, it can implement any one of the implementation manners in the embodiments corresponding to the above prediction method.

[0168] It should be noted that in the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0169] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0170] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the processes and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0171] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device implements the functions in the process Figure 1one or more processes and / or blocks Figure 1 the functions specified in one or more blocks.

[0172] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide for implementing the steps of the functions specified in Figure 1 one or more processes and / or blocks Figure 1 the functions specified in one or more blocks.

[0173] The specific embodiments described above further elaborate on the purpose, technical solutions, and beneficial effects of the present application. It should be understood that the above description is only the specific embodiments of the present application and is not used to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for predicting early leakage current of tree-line touch faults, characterized in that Including: Establish a time-domain model of tree body temperature rise with multi-factor coupling. The time-domain model of tree body temperature rise is a mathematical model describing the tree body temperature rise changing with time. The multi-factors considered include tree size, moisture content, and environmental temperature; Establish multiple equivalent fault resistance-tree temperature models. The equivalent fault resistance-tree temperature model is a mathematical model describing the change of the equivalent fault resistance value with the tree temperature; Calculate the prediction errors of each equivalent fault resistance-tree temperature model respectively, and select the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model; Calculate the equivalent fault resistance using the optimal equivalent fault resistance-tree temperature model. Based on the calculated equivalent fault resistance and the fault phase voltage, the effective value of the leakage current can be predicted.

2. The early leakage current prediction method for tree-line touch fault according to claim 1, wherein The process of establishing the time-domain model of tree body temperature rise includes: Based on the specific heat capacity of wood in the absolutely dry state, the specific heat capacity of water, and the absolute moisture content of wood, calculate the specific heat capacity of wood; Based on the applied voltage value and the trunk body resistance, calculate the input heat power; According to the convective heat transfer coefficient, the tree skin temperature, the environmental temperature, and the trunk side area, calculate the convective heat dissipation power; According to the medium thermal radiation rate, the Stefan-Boltzmann constant, the thermodynamic temperature of the tree skin, the trunk side area, and the thermodynamic temperature of the test environment, use the Stefan-Boltzmann law to calculate the radiative heat dissipation power; Based on the convective heat dissipation power and the radiative heat dissipation power, obtain the output heat power; Based on the input heat power, the output heat power, the wood density, the tree height at the tree line connection, the average radius of the trunk, and the specific heat capacity of wood, calculate the tree body temperature rise rate; According to the tree body temperature rise rate and the environmental temperature, obtain the average temperature of the tree body.

3. A method for predicting early leakage current of tree-line touch fault according to claim 1 or 2, characterized in that, The establishment of multiple equivalent fault resistance-tree temperature models includes: Repeat the experiment on multiple groups of samples, and record the average temperature of the tree body and the equivalent fault resistance value in real time; Through the analysis of the average temperature of the tree body and the equivalent fault resistance value recorded in real time, it is obtained that the equivalent fault resistance shows a decaying trend with the increase of the average temperature of the tree body; Select multiple function models suitable for describing the decaying trend of the equivalent fault resistance with the increase of the tree temperature; Among them, the parameters in the function model are determined by fitting with measured data.

4. A method for predicting early leakage current of tree-line touch fault according to claim 3, characterized in that, The calculation of the prediction errors of each equivalent fault resistance-tree temperature model respectively, and the selection of the equivalent fault resistance-tree temperature model with the smallest prediction error as the optimal equivalent fault resistance-tree temperature model includes: Calculate the root mean square error between the equivalent fault resistance value obtained by simulating each equivalent fault resistance-tree temperature model and the measured equivalent fault resistance value respectively; Select the model with the smallest root mean square error as the optimal equivalent fault resistance-tree temperature model.

5. A method for predicting early leakage current of tree-line touch fault according to claim 3, characterized in that, The multiple function models selected include: linear function model, exponential function model, and power function model.

6. A method for predicting early leakage current of tree-line touch fault according to claim 4 or 5, characterized in that The optimal equivalent fault resistance-tree temperature model adopts the exponential function model.

7. An early leakage current prediction device for tree line touch faults, characterized in that, Including: The first modeling unit is used to establish a time-domain model of tree body temperature rise with multi-factor coupling. The time-domain model of tree body temperature rise is a mathematical model describing the tree body temperature rise changing with time; the multi-factors considered include tree size, moisture content, and environmental temperature; A second modeling unit, configured to establish a variety of equivalent fault resistance-tree temperature models, where the equivalent fault resistance-tree temperature model is a mathematical model describing the variation of the equivalent fault resistance value with the tree temperature; A model optimization unit, configured to calculate the prediction errors of the respective equivalent fault resistance-tree temperature models and select the equivalent fault resistance-tree temperature model with the minimum prediction error as the optimal equivalent fault resistance-tree temperature model; And a calculation unit, configured to calculate the equivalent fault resistance by using the optimal equivalent fault resistance-tree temperature model, and predict the effective value of the leakage current according to the calculated equivalent fault resistance and the fault phase voltage.

8. An early leakage current prediction device for tree-line touch faults according to claim 7, characterized in that, The first modeling unit is configured as follows: Based on the specific heat capacity of the wood in the absolutely dry state, the specific heat capacity of water, and the absolute moisture content of the wood, calculate the specific heat capacity of the wood; Based on the applied voltage value and the trunk body resistance, calculate the input heat power; According to the convective heat transfer coefficient, the tree surface temperature, the ambient temperature, and the trunk side area, calculate the convective heat dissipation power; According to the medium thermal emissivity, the Stefan-Boltzmann constant, the tree surface thermodynamic temperature, the trunk side area, and the test environment thermodynamic temperature, calculate the radiative heat dissipation power by using the Stefan-Boltzmann law; Based on the convective heat dissipation power and the radiative heat dissipation power, obtain the output heat power; Based on the input heat power, the output heat power, the wood density, the tree height at the tree line connection, the average trunk radius, and the specific heat capacity of the wood, calculate the tree body temperature rise rate; According to the tree body temperature rise rate and the ambient temperature, obtain the average tree body temperature.

9. An electronic device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-6.

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

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