Forest fire smoke particle adsorption degree prediction method, system, equipment and medium

Abstract

The invention discloses a forest fire smoke particle adsorption degree prediction method, system and device and a medium, and belongs to the field of power systems, and the method comprises the steps: obtaining forest fire data of a to-be-predicted overhead transmission line under a forest fire condition in a preset time period; inputting the forest fire data into a simulation calculation model, so that the simulation calculation model constructs a simulation model corresponding to the overhead transmission line to be predicted according to the forest fire data, determining a corresponding relation between coordinate data of each smoke particle and each simulation area according to the simulation model, and calculating the number and quality of the smoke particles in each simulation area, and outputting an adsorption degree prediction result corresponding to the target simulation area, the simulation model comprising a plurality of simulation areas, and each simulation area being obtained by division according to the space field intensity of the to-be-predicted overhead transmission line, so that through implementation of the method, the adsorption degree of the smoke particles in the overhead transmission line can be accurately predicted, and the prediction accuracy of the adsorption degree of the smoke particles in the overhead transmission line is improved. And the safety of the power system is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power systems, in particular to a forest fire smoke particle adsorption degree prediction method, system, device and medium. BACKGROUND

[0002] High-voltage overhead transmission lines are lines that efficiently transmit energy in the form of electric energy. However, these lines often pass through mountainous areas with dense vegetation. If a forest fire occurs, the vegetation burning process will produce a considerable concentration of charged particles, and the hetero-charged smoke particles are easily adsorbed and deposited on the surface of the conductor. When the cumulative amount reaches a certain amount, it will cause serious electric field distortion in the vicinity of the conductor, promote the process of gap discharge, and seriously endanger the insulation characteristics of the overhead transmission line to ground gap.

[0003] However, due to the influence of multi-physical field coupling on the movement of smoke particles in the transmission line gap, the distribution of smoke particles has high randomness and spatial non-uniformity. The traditional method is difficult to quantify the adsorption rule of particles, and lacks a quantitative statistical means for adsorbed particles on the surface of the conductor. Therefore, it is impossible to predict the adsorption degree of smoke particles on the overhead transmission line, and the safety of the power system is low. SUMMARY

[0004] The present application provides a forest fire smoke particle adsorption degree prediction method, system, device and medium, which can solve the problem of low safety of power system caused by the inability to predict the adsorption degree of smoke particles on the overhead transmission line, and realize accurate prediction of the adsorption degree of smoke particles on the overhead transmission line.

[0005] The present application provides a forest fire smoke particle adsorption degree prediction method, comprising:

[0006] In a predetermined time period, obtain forest fire data of a to-be-predicted overhead transmission line under forest fire conditions, wherein the forest fire data includes smoke particle data, temperature data, gap data and vegetation data;

[0007] input the forest fire data into a simulation calculation model, so that the simulation calculation model constructs a simulation model corresponding to the to-be-predicted overhead transmission line according to the forest fire data, determines the coordinate data of each smoke particle and the corresponding relationship of each simulation region according to the simulation model, and calculates the number and mass of smoke particles in each simulation region, and outputs the adsorption degree prediction result of the target simulation region corresponding to the to-be-predicted overhead transmission line. The simulation model includes a plurality of simulation regions, and each simulation region is divided according to the space field strength of the to-be-predicted overhead transmission line.

[0008] The embodiment of the present application collects smoke particle data, temperature data, gap data and vegetation data of the overhead transmission line under the mountain fire condition within a preset time period, which covers the main factors affecting the movement of smoke particles under the mountain fire condition, and provides comprehensive basic information for subsequent simulation modeling; the obtained mountain fire data is input into a simulation calculation model, so that the model constructs a simulation model according to the mountain fire data, and the simulation model further divides a plurality of simulation regions according to the spatial field strength of the overhead transmission line to be predicted, each simulation region can simulate the movement trajectory and adsorption probability of the smoke particles according to the electric field strength characteristics thereof, through the fusion of multi-source data and the fine regional division, the simulation model can more accurately simulate the physical environment around the transmission line and the movement state of the smoke particles under the mountain fire condition; the simulation calculation model calculates the number and mass of the smoke particles in each simulation region according to the coordinate data of the smoke particles in the simulation model and the corresponding relationship of each simulation region, and further determines the adsorption degree prediction result of the target simulation region of the overhead transmission line to be predicted, so that the embodiment can accurately predict the adsorption degree of the smoke particles on the transmission line, and the accurate prediction enables the power system operation and maintenance personnel to know the influence degree of the smoke particles on the insulation performance of the transmission line in advance, and improves the safety of the power system.

[0009] Further, the simulation model includes a plurality of simulation regions, each of which is divided according to the spatial field strength of the overhead transmission line to be predicted, specifically:

[0010] In the simulation calculation model, an initial simulation model is obtained;

[0011] According to the conductor radius of the overhead transmission line to be predicted and the smoke particle size data in the smoke particle data, the region radius of each simulation region is determined;

[0012] Based on the radial attenuation law of the spatial field strength along the conductor and the region radius of each simulation region, the initial simulation model is divided into simulation regions to obtain the simulation model.

[0013] Thus, the region radius of the simulation region is determined by considering the conductor radius and the particle size of the smoke particle, and the initial simulation model is divided into simulation regions based on the radial attenuation law of the space field strength along the conductor and the region radius of each simulation region. This division method can accurately simulate the electric field strength and particle motion characteristics in different regions, thereby being closer to the actual physical scene. By reasonably dividing the simulation region, the charging characteristics and distribution law of the smoke particles in different regions can be more accurately described, thereby providing a more reliable basis for subsequent prediction of the adsorption degree; and since the simulation region division is more reasonable, the motion and adsorption behavior of the smoke particles in different regions can be more accurately simulated, thereby improving the prediction accuracy of the adsorption degree of each simulation region of the overhead transmission line.

[0014] Further, the simulation region includes a first simulation region and a second simulation region, and the conductor-to-ground gap of the overhead transmission line to be predicted is divided based on the radial attenuation law of the space field strength along the conductor and the region radius of each simulation region, specifically:

[0015] The initial simulation model is divided into a first partition and a second partition by taking the horizontal line where the target center position of the overhead transmission line to be predicted is located as a division line;

[0016] In the first partition, the first partition is divided into rectangular regions along the horizontal direction according to the region radius of each simulation region, thereby obtaining a plurality of first simulation regions;

[0017] In the second partition, the second partition is divided into sector regions along the vertical direction according to the region radius of each simulation region, thereby obtaining a plurality of second simulation regions;

[0018] The region radius corresponding to each first simulation region and each second simulation region is combined, thereby obtaining a plurality of simulation regions.

[0019] Thus, the conductor-to-ground gap is divided into a first partition and a second partition by taking the horizontal line where the target center position is located as a division line. This division method conforms to the general law of electric field distribution, i.e., the electric field characteristics may differ in the horizontal direction and the vertical direction. In the first partition, rectangular region division is adopted, and in the second partition, sector region division is adopted, which can better adapt to the electric field distribution characteristics of different partitions, thereby further improving the rationality of the simulation region division.

[0020] Further, in the simulation calculation model, an initial simulation model is obtained; the region radius of each simulation region is determined according to the conductor radius of the overhead transmission line to be predicted and the particle size data in the smoke particle data, specifically:

[0021] In each of the simulation areas, the simulation area with the shortest distance to the overhead transmission line to be predicted is determined as a target simulation area;

[0022] The radius of the target simulation area is determined based on the conductor radius and the maximum particle size in the smoke particle size data, and the radius of other simulation areas is determined according to the radius of the target simulation area.

[0023] In this way, the radius of the target simulation area is determined based on the conductor radius and the maximum smoke particle size, which fully considers the physical characteristics of the conductor and the smoke particles, and can ensure that the target simulation area effectively covers the area closest to the transmission line and with the highest adsorption probability. By reasonably determining the radius of the target simulation area, the interaction range between the smoke particles and the transmission line can be more accurately reflected, thereby improving the accuracy of the prediction of the adsorption degree of the smoke particles.

[0024] Further, the coordinate data is input into a simulation calculation model, so that the simulation calculation model obtains the adsorption degree prediction result of the overhead transmission line to be predicted according to the coordinate data and the corresponding relationship between each simulation area in the overhead transmission line to be predicted, specifically:

[0025] In the simulation calculation model, for each smoke particle, the size relationship between the longitudinal coordinate value in the coordinate data and the radius of the target simulation area is compared;

[0026] If the longitudinal coordinate value in the coordinate data is less than the radius of the target simulation area, then according to the size relationship between the horizontal coordinate value in the coordinate data and the radius of the target simulation area, the simulation area corresponding to the smoke particle is determined;

[0027] If the longitudinal coordinate value in the coordinate data is greater than or equal to the radius of the target simulation area, then according to the spatial distance between the smoke particle and the target center position, the simulation area corresponding to the smoke particle is determined;

[0028] The number and mass of the smoke particles in each simulation area are obtained by counting the simulation areas corresponding to each smoke particle.

[0029] In this way, the size relationship between the longitudinal coordinate value in the coordinate data and the radius of the target simulation area is compared, and further according to the size relationship between the horizontal coordinate value and the radius, or the spatial distance between the smoke particle and the target center position, the simulation area corresponding to each smoke particle is accurately determined, which can ensure that the attribution judgment of each smoke particle is more accurate and reliable, thereby improving the accuracy of the prediction of the adsorption degree of the smoke particles.

[0030] Further, the initial simulation model is specifically:

[0031] Based on the two-dimensional axisymmetric space dimension, the mutual relationship between the temperature field, fluid field, electric field and particle dynamic field in the to-be-predicted overhead transmission line is physically modeled, and the initial simulation model of multi-physical field coupling is obtained.

[0032] In this way, by using the two-dimensional axisymmetric space dimension, the three-dimensional gap is simplified into a two-dimensional model, and after partitioning, only the particle distribution of the typical section needs to be calculated, greatly reducing the calculation cost. The mutual relationship between the temperature field, fluid field, electric field and particle dynamic field is physically modeled, which can more comprehensively consider various physical factors involved in the adsorption process of mountain fire smoke particles and their interactions. Through the initial simulation model of multi-physical field coupling, the adsorption behavior of smoke particles in the actual complex environment can be more accurately simulated, thereby improving the reliability of the prediction of the adsorption degree of smoke particles on the overhead transmission line.

[0033] Further, the number and mass of the smoke particles in each simulation region are calculated, specifically:

[0034] P i =k i / N;

[0035]

[0036] Wherein, ρ is the smoke particle density of the smoke sample particle, r ij is the particle size of each smoke particle j in the simulation region i, k i is the number of smoke particles in the simulation region i, m i is the mass of the smoke particles in the simulation region i, P i is the proportion of the number of particle distribution in the simulation region i to the total number N of samples.

[0037] In this way, the number and mass of the particles are calculated through specific formulas, and the adsorption degree is quantified. This quantitative evaluation method can more intuitively reflect the adsorption degree of each simulation region.

[0038] Another embodiment of the present application also provides a mountain fire smoke particle adsorption degree prediction system, comprising: an acquisition module and a prediction module;

[0039] The acquisition module is used to acquire mountain fire data of a to-be-predicted overhead transmission line under mountain fire conditions within a preset time period, wherein the mountain fire data includes smoke particle data, temperature data, gap data and vegetation data.

[0040] The prediction module is configured to input the forest fire data into a simulation calculation model, so that the simulation calculation model constructs a simulation model corresponding to the to-be-predicted overhead power transmission line according to the forest fire data, determines the coordinate data of each smoke particle and the corresponding relationship of each simulation region according to the simulation model, calculates the number and mass of the smoke particles in each simulation region, and outputs the adsorption degree prediction result of the target simulation region of the to-be-predicted overhead power transmission line.

[0041] The embodiment of the present application collects smoke particle data, temperature data, gap data and vegetation data of the to-be-predicted overhead power transmission line under the condition of forest fire in a preset time period, which covers the main factors affecting the movement of smoke particles under the condition of forest fire, and provides comprehensive basic information for subsequent simulation modeling. The collected forest fire data is input into a simulation calculation model, so that the model constructs a simulation model according to the forest fire data. The simulation model further divides a plurality of simulation regions according to the spatial field strength of the to-be-predicted overhead power transmission line. Each simulation region can simulate the movement trajectory and adsorption probability of the smoke particles according to its electric field strength characteristics. Through the fusion of multi-source data and the fine division of regions, the simulation model can more accurately simulate the physical environment around the power transmission line and the movement state of the smoke particles under the condition of forest fire. The simulation calculation model calculates the number and mass of the smoke particles in each simulation region according to the coordinate data of the smoke particles in the simulation model and the corresponding relationship of each simulation region, and further determines the adsorption degree prediction result of the target simulation region of the to-be-predicted overhead power transmission line. Therefore, the embodiment can accurately predict the adsorption degree of the smoke particles on the power transmission line. This accurate prediction enables the power system operation and maintenance personnel to understand the influence of the smoke particles on the insulation performance of the power transmission line in advance, thereby improving the safety of the power system.

[0042] Another embodiment of the present application further provides a terminal device, which comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the steps of the forest fire smoke particle adsorption degree prediction method are implemented.

[0043] Another embodiment of the present application further provides a computer readable storage medium item, which comprises a stored computer program. When the computer program runs, the device where the computer readable storage medium is located executes the steps of the forest fire smoke particle adsorption degree prediction method. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the present application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort based on these drawings.

[0045] Figure 1 is a flowchart of a mountain fire smoke particle adsorption degree prediction method provided by an embodiment of the present application;

[0046] Figure 2 is a schematic diagram of smoke particle movement simulation in a conductor-to-ground gap provided by an embodiment of the present application;

[0047] Figure 3 is a schematic diagram of a smoke particle statistical partitioning method provided by an embodiment of the present application;

[0048] Figure 4 is a schematic diagram of a smoke particle adsorption system calculation flowchart provided by an embodiment of the present application;

[0049] Figure 5 is a structural schematic diagram of a mountain fire smoke particle adsorption degree prediction system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort fall within the scope of protection of the present application.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "include" and "have" and any variations thereof in the specification and claims of the present application and the above description of drawings are intended to cover non-exclusive inclusion.

[0052] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited.

[0053] Reference to“an embodiment” herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase“in an embodiment” in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily all referring to a common set of embodiments, of the application. It will be explicitly understood that the application described herein can be combined with another embodiment to produce a further embodiment.

[0054] In the description of the embodiments of the application, the term“and / or” only means an association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can mean that A exists alone, A and B exist together, and B exists alone. In addition, the character“ / ” herein generally means that the front and rear associated objects have an“or” relationship.

[0055] In the description of the embodiments of the application, the term“a plurality of” refers to two or more (including two), and similarly, “a plurality of groups” refers to two or more groups (including two groups), and “a plurality of pieces” refers to two or more pieces (including two pieces).

[0056] In the description of the embodiments of the application, unless otherwise explicitly specified and limited, the technical terms“mounting”,“connection”,“connection”,“fixing” and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanical connection, or it can be electrical connection; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meaning of the above terms in the embodiments of the application can be understood according to the specific circumstances.

[0057] Reference is made to Figure 1 To solve the problem of low safety of power system caused by the inability to predict the smoke particle adsorption degree of overhead transmission line in the prior art, an embodiment of the application provides a mountain fire smoke particle adsorption degree prediction method, which comprises steps S101-S102, specifically:

[0058] Step S101, in a preset time period, obtain mountain fire data of an overhead transmission line to be predicted under mountain fire conditions, wherein the mountain fire data comprises smoke particle data, temperature data, gap data and vegetation data.

[0059] In the embodiment, when there is a forest fire in the area where the overhead transmission line to be predicted is located, smoke particle data, temperature data, gap data and vegetation data of the area where the overhead transmission line to be predicted is located in a preset time period are acquired. The forest fire data can be obtained by detecting the vegetation type, burning temperature, gap length and smoke particle data when the forest fire occurs in the overhead transmission line to be predicted by a detector or a sensor, or can be obtained by image acquisition and image recognition by an image device. The embodiment of the present application is not limited to the specific implementation manner, as long as the forest fire data can be acquired.

[0060] In step S102, the forest fire data is input into a simulation calculation model, so that the simulation calculation model constructs a simulation model corresponding to the overhead transmission line to be predicted according to the forest fire data, determines the coordinate data of each smoke particle and the corresponding relationship of each simulation region according to the simulation model, calculates the number and mass of the smoke particles in each simulation region, and outputs the adsorption degree prediction result of the target simulation region of the overhead transmission line to be predicted. The simulation model includes a plurality of simulation regions, and each simulation region is divided according to the spatial field intensity of the overhead transmission line to be predicted.

[0061] In the embodiment, the simulation calculation model is used to study the charging characteristics and distribution law of the smoke particles. The simulation calculation model includes a simulation model determined based on the forest fire data. The simulation model can be a multi-physical field coupled simulation model, and the simulation model includes a plurality of simulation regions divided according to the spatial field intensity of the overhead transmission line to be predicted. In the simulation calculation model, the coordinate data of each smoke particle in the overhead transmission line to be predicted is determined based on the simulation model, and the smoke particles in each simulation region are calculated based on the coordinate data of each smoke particle and the corresponding relationship of each simulation region. Then, the adsorption degree of the target simulation region is predicted according to the calculation result, and the adsorption degree prediction result of the overhead transmission line to be predicted is obtained. The target simulation region is the simulation region closest to the conductor of the overhead transmission line to be predicted.

[0062] As an example of the embodiment of the present application, the initial simulation model is specifically: based on two-dimensional axisymmetric spatial dimensions, a physical model of the mutual relationship between the temperature field, fluid field, electric field and particle dynamic field in the overhead transmission line to be predicted is established, and the initial simulation model of multi-physical field coupling is obtained.

[0063] In the embodiment, the ground conductor gap below the overhead transmission line to be predicted can be divided into three gap regions of a smoke zone, a flame zone and a heat source zone. Referring to FIG. 1, the ground conductor gap below the overhead transmission line to be predicted is divided into three gap regions of a smoke zone 101, a flame zone 102 and a heat source zone 103. Figure 2The simulation diagram of the movement of smoke particles in the conductor-to-ground clearance is shown. Under the condition of a mountain fire, the movement of smoke particles in the three clearance regions is as follows: smoke particles are released from the gas-solid interface on the top surface of the wood pile; the flame region contains a large amount of plasma, and the whole is electrically neutral. In the model, the flame body is regarded as a high resistance region; the smoke particles generated by the heat source combustion are charged in the flame region, and move and diffuse to the smoke region under the action of fluid drag force, electric field force, gravity and inertia force. Based on the movement of smoke particles under the condition of a mountain fire, an initial simulation model coupled with multiple physical fields is established. The initial simulation model can describe the mutual relationship between the temperature field, the fluid field, the electric field and the particle dynamic field, analyze the mutual influence between the changes of the fluid drag force of the high temperature and turbulent flow generated by the flame combustion on the smoke particles and the electric field force of the electric field on the smoke particles and the movement state and spatial position distribution of the smoke particles. Considering the convergence problem of calculation and the limitation of examples, and the good symmetry of the electrostatic field generated by the predicted overhead transmission line as a rod electrode, the initial simulation model is simplified to a two-dimensional axisymmetric processing within a reasonable error range.

[0064] As an example of an embodiment of the present application, the simulation model includes a plurality of simulation regions, each of which is divided according to the spatial field strength of the overhead transmission line to be predicted. Specifically, in the simulation calculation model, an initial simulation model is obtained; the radii of the simulation regions are determined according to the conductor radii of the overhead transmission line to be predicted and the smoke particle size data in the smoke particle data; based on the radial decay law of the spatial field strength along the conductor and the radii of the simulation regions, the initial simulation model is divided into simulation regions to obtain the simulation model.

[0065] In this embodiment, test data is obtained based on a mountain fire simulation test, and the initial simulation model is trained based on the test data to obtain a trained initial simulation model. The trained initial simulation model determines the radii of the simulation regions according to the conductor radii of the overhead transmission line to be predicted and the smoke particle size data in the smoke particle data; based on the radial decay law of the spatial field strength along the conductor and the radii of the simulation regions, the trained initial simulation model is divided into simulation regions to obtain the simulation model. In the mountain fire simulation test, because the flame is distributed in the flame region and the heat source region, the proportion is adjusted according to the measured temperature results when the flame power is loaded, so that the simulated temperature distribution conforms to the temperature distribution when the flame burns. In the two-dimensional axisymmetric initial simulation model, different polarity high potentials are loaded to the overhead transmission line to be predicted, the wood pile part in the heat source region is grounded, and the particle take-off region and the flame body region are respectively loaded with two different power heat source powers. After repeated testing and adjustment of the amplitude and oscillation frequency of the heat source power, the simulation result can be consistent with the measured temperature distribution.

[0066] As an example of an embodiment of the present application, where each of the simulation regions includes a first simulation region and a second simulation region, the ground clearance of the overhead transmission line to be predicted is divided based on the spatial field strength along the radial direction of the conductor and the region radius of each of the simulation regions, specifically: the initial simulation model is divided into a first partition and a second partition with the horizontal line where the target center position of the overhead transmission line to be predicted is located as the dividing line; in the first partition, the first partition is divided into rectangular regions along the horizontal direction according to the region radius of each of the simulation regions, to obtain a plurality of the first simulation regions; in the second partition, the second partition is divided into sector regions along the vertical direction according to the region radius of each of the simulation regions, to obtain a plurality of the second simulation regions; and the first simulation regions and the second simulation regions are combined based on the region radius corresponding to each of the first simulation regions and each of the second simulation regions, to obtain a plurality of the simulation regions.

[0067] In the present embodiment, the simulation model includes six simulation regions, each of which includes a rectangular region and a quarter circular region, the rectangular region is arranged above the quarter circular region, and the center position of the quarter circular region is the conductor center position. With the center position as a boundary, the radius of the rectangular region and the circular region is equal, to facilitate the statistics of the distribution of charged particles in the space region near the rod electrode. Referring to the schematic diagram of the smoke particle statistics partition method as shown in Figure 3 The specific region division method is: the initial simulation model is divided into six simulation regions according to the spatial field strength along the radial direction of the conductor, with the horizontal line where the target center position (X', Y') is located as the dividing line, the first partition is the region from the dividing line to the horizontal line where Y0 is located, the x1 to x5 plumb lines in the horizontal direction are determined according to the region radii R1, R2, R3, R4, R5, and the first partition is divided according to the electrode surface and different positions away from the electrode from near to far according to the x0 to x5 plumb lines, to obtain six rectangular regions; the second partition is the region from the dividing line to the horizontal line where Y6 is located, with the target center position of the overhead transmission line to be predicted as the center of the concentric circle, five concentric circle arcs with region radii R1, R2, R3, R4, R5 are drawn, and the region between the dividing line and the horizontal line where Y6 is located is divided into six sector regions according to the distance from the target center position from near to far. The rectangular regions and the sector regions are combined based on the region radius corresponding to each of the rectangular regions in the first partition and each of the sector regions in the second partition, to obtain six simulation regions, and in Figure 3 In the present embodiment, the simulation model includes six simulation regions, each of which includes a rectangular region and a quarter circular region, the rectangular region is arranged above the quarter circular region, and the center position of the quarter circular region is the conductor center position. With the center position as a boundary, the radius of the rectangular region and the circular region is equal, to facilitate the statistics of the distribution of charged particles in the space region near the rod electrode. Referring to the schematic diagram of the smoke particle statistics partition method as shown in

[0068] As an example of an embodiment of the present application, in the simulation calculation model, an initial simulation model is obtained; according to the conductor radius of the overhead transmission line to be predicted and the smoke particle size data in the smoke particle data, the region radius of each simulation region is determined, specifically: in each simulation region, the simulation region with the shortest distance from the overhead transmission line to be predicted is determined as a target simulation region; the region radius of the target simulation region is determined based on the conductor radius and the maximum particle size in the smoke particle size data, and the region radius of other simulation regions is determined according to the region radius of the target simulation region.

[0069] In this embodiment, the region radius R1 of the simulation region close to the surface of the overhead transmission line to be predicted is set as the sum of the conductor radius and the maximum smoke particle size, and is used as the judgment range of the smoke particles adsorbed to the conductor surface, i.e., the target simulation region, and the region radius of other simulation regions is set as 2R1, 3R1, 4R1 and 5R1 respectively. The parameter values such as the conductor radius and the smoke particle size in the simulation calculation model can be adjusted by artificial setting, and the reference data is obtained from the wildfire simulation test.

[0070] As an example of an embodiment of the present application, the coordinate data is input into the simulation calculation model, so that the simulation calculation model obtains the adsorption degree prediction result of the overhead transmission line to be predicted according to the coordinate data and the corresponding relationship between each simulation region in the overhead transmission line to be predicted, specifically: in the simulation calculation model, for each smoke particle, the size relationship between the longitudinal coordinate value in the coordinate data and the region radius of the target simulation region is compared; if the longitudinal coordinate value in the coordinate data is less than the region radius of the target simulation region, then according to the size relationship between the horizontal coordinate value in the coordinate data and the region radius of the target simulation region, the simulation region corresponding to the smoke particle is determined; if the longitudinal coordinate value in the coordinate data is greater than or equal to the region radius of the target simulation region, then according to the spatial distance between the smoke particle and the target center position, the simulation region corresponding to the smoke particle is determined; the simulation regions corresponding to each smoke particle are counted to obtain the number and mass of smoke particles in each simulation region.

[0071] In this embodiment, as shown in FIG. 2, the coordinate data is input into the simulation calculation model, so that the simulation calculation model obtains the adsorption degree prediction result of the overhead transmission line to be predicted according to the coordinate data and the corresponding relationship between each simulation region in the overhead transmission line to be predicted. Figure 4The flow chart of the smoke particle adsorption system is shown, and a MATLAB programming logic control algorithm is used to realize the particle distribution statistics of different simulation regions, so as to obtain the number and mass of smoke particles of different particle sizes in different partitions of the simulation model, especially the number and mass percentage of smoke particles in the particle adsorption region of the conductor, so as to describe the adsorption degree of the smoke particles under the direct current condition. Through the statistical analysis of the time-space coordinates of the simulation smoke particles in a specified time period, the distribution of the smoke particles in the vicinity of the simulation electrode under different working conditions is calculated. The specific calculation steps are as follows: identify and determine the y j coordinate of the smoke particle. The time-space coordinates (x j , y j , t) of the smoke particle represent the spatial coordinate position (x j , y j ) corresponding to the time axis t of the particle motion under the condition of a specified simulation step. Wherein, j represents the index variable of each smoke particle, and i represents the index variable of each simulation region. According to the size relationship between y j coordinate and Y1, it is determined whether the smoke particle is attached to the surface of the conductor, wherein Y1 is determined according to the radius R1 of the target simulation region and the vertical coordinate value of the target center position. If y j < Y1, it indicates that the y j coordinate of the smoke particle is in the adsorption region of the conductor surface, and the x j coordinate is determined to determine whether the smoke particle is adsorbed. Specifically, the x j coordinate of the smoke particle is determined, and if x j ≥ x1, it indicates that the smoke particle is not adsorbed by the conductor, and the size relationship between x j and x2, x3, x4, x5 is compared to determine the simulation region corresponding to the smoke particle, and the number of smoke particles in the simulation region is counted i = i + 1, wherein x1, x2, x3, x4, x5 are determined according to the radius R1, R2, R3, R4, R5 of each region and the horizontal coordinate value of the target center position; if x j < x1, it indicates that the smoke particle has been adsorbed by the conductor, and the number and mass of the smoke particles on the surface of the conductor are counted, and the count is incremented n = n + 1, j = j + 1. If y j ≥ Y1, it indicates that the smoke particle is not adsorbed by the conductor, and the spatial distance d of the smoke particle is determined to confirm the simulation region where the smoke particle is located, wherein d is the distance from each smoke particle to the target center position. The above steps are repeated until the number and mass of all partition smoke particles are counted, and the number and mass data of the smoke particles in each partition are output to obtain the number and mass of the smoke particles in each simulation region. The calculation formula of the distance d from each smoke particle to the target center position is as follows:

[0072]

[0073] As an example of an embodiment of the present application, the number and mass of smoke particles in each of the simulation regions are calculated, specifically:

[0074] P i = k i / N;

[0075]

[0076] wherein p is the smoke particle density of the sample particles, r ij is the particle size of each smoke particle j in simulation region i, k i is the number of smoke particles in simulation region i, m i is the mass of smoke particles in simulation region i, P i is the proportion of the number of particle distributions in simulation region i to the total number of samples N.

[0077] In this embodiment, k i is the number of smoke particles in simulation region i, n is the number of smoke particles in the current statistics when the program is executed, m i is the mass count variable of different partition particle distributions, N is the total number of sample data, and M is the total mass of the sample.

[0078] P i = k i / N;

[0079]

[0080] wherein the smoke particle density p can refer to the graphite sample particle value used in the mountain fire simulation test, the lead surface determination region, i.e. the target simulation region, R1 is the concentric circular arc radius of the lead surface determination region, and x1 is the plummet division distance of the lead surface determination region. At the end of the program execution, the number count variable k i of different partition particle distributions and the proportion P i of the total number of samples N, the mass count variable m i of different partition particle distributions and the proportion Pm i of the total mass of the sample M are output. The number and mass of different particle size smoke particles in different partitions in the simulation model are obtained, in particular the number and mass percentage of smoke particles in the target simulation region, which are used to describe the adsorption degree of mountain fire smoke particles under direct current conditions.

[0081] The embodiment of the present invention collects smoke particle data, temperature data, clearance data, vegetation data and other data of the overhead transmission line to be predicted under wildfire conditions within a preset time period. These wildfire data cover the main factors affecting the movement of smoke particles under wildfire conditions and provide comprehensive basic information for subsequent simulation modeling; the acquired wildfire data is input into the simulation calculation model so that the model constructs a simulation model based on the wildfire data, and the simulation model is further divided into several simulation areas according to the spatial field strength of the overhead transmission line to be predicted. Each simulation area can simulate the movement trajectory and adsorption probability of smoke particles according to its electric field strength characteristics. The fusion of source data and refined regional division enable the simulation model to more accurately simulate the physical environment around the transmission lines and the movement state of smoke particles under wildfire conditions; the simulation calculation model calculates the number and mass of smoke particles in each simulation area based on the coordinate data of the smoke particles in the simulation model and the correspondence between each simulation area, and then determines the adsorption degree prediction result of the target simulation area of ​​the overhead transmission line to be predicted. Therefore, this embodiment can accurately predict the adsorption degree of smoke particles on the transmission line. This accurate prediction enables power system operation and maintenance personnel to understand in advance the impact of smoke particles on the insulation performance of the transmission line, thereby improving the safety of the power system.

[0082] like Figure 5 As shown, based on the above method embodiment, a corresponding system embodiment is provided; an embodiment of the present invention provides a wildfire smoke particle adsorption degree prediction system 500, including: an acquisition module 501 and a prediction module 502;

[0083] The acquisition module 501 is configured to acquire, within a preset time period, wildfire data of the overhead transmission line to be predicted under wildfire conditions, wherein the wildfire data includes smoke particle data, temperature data, clearance data, and vegetation data;

[0084] The prediction module 502 is used to input the wildfire data into a simulation calculation model so that the simulation calculation model constructs a simulation model corresponding to the overhead transmission line to be predicted based on the wildfire data, determines the correspondence between the coordinate data of each smoke particle and each simulation area based on the simulation model, calculates the quantity and mass of the smoke particles in each simulation area, and outputs the adsorption degree prediction result corresponding to the target simulation area of ​​the overhead transmission line to be predicted. The simulation model includes several simulation areas, and each simulation area is divided according to the spatial field strength of the overhead transmission line to be predicted.

[0085] It can be understood that the above-mentioned system embodiment corresponds to the method embodiment of the present invention, which can implement the method for predicting the adsorption degree of wildfire smoke particles provided by any of the above-mentioned method embodiments of the present invention.

[0086] It should be noted that the system embodiments described above are only illustrative, and part or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs. In addition, in the system embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which can be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0087] On the basis of the above-mentioned embodiment of the mountain fire smoke particle adsorption degree prediction method, another embodiment of the present application provides a terminal device, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the mountain fire smoke particle adsorption degree prediction method of any one embodiment of the present application is realized.

[0088] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the terminal device.

[0089] The terminal device can be a desktop computer, a notebook computer, a palm computer and a cloud server, etc. The terminal device can include, but is not limited to, a processor and a memory.

[0090] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and connects all parts of the terminal device through various interfaces and lines.

[0091] Based on the above-mentioned method embodiments, another embodiment of the present invention provides a computer-readable storage medium, including a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the wildfire smoke particle adsorption degree prediction method described in any one of the above-mentioned method embodiments of the present invention.

[0092] Wherein, the module / unit integrated in the device / terminal equipment, if implemented in the form of 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 present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0093] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for predicting the degree of adsorption of wildfire smoke particles, characterized in that: include: Acquiring, within a preset time period, wildfire data of the overhead transmission line to be predicted under wildfire conditions, wherein the wildfire data includes smoke particle data, temperature data, clearance data, and vegetation data; The wildfire data is input into a simulation calculation model so that the simulation calculation model constructs a simulation model corresponding to the overhead transmission line to be predicted based on the wildfire data, determines the correspondence between the coordinate data of each smoke particle and each simulation area based on the simulation model, calculates the quantity and mass of the smoke particles in each simulation area, and outputs the adsorption degree prediction result corresponding to the target simulation area of ​​the overhead transmission line to be predicted. The simulation model includes several simulation areas, and each simulation area is divided according to the spatial field strength of the overhead transmission line to be predicted.

2. The method for predicting the degree of adsorption of wildfire smoke particles according to claim 1, wherein: The simulation model includes several simulation areas, each of which is divided according to the spatial field strength of the overhead transmission line to be predicted, specifically: In the simulation calculation model, obtaining an initial simulation model; Determining the area radius of each simulation area according to the conductor radius of the overhead transmission line to be predicted and the smoke particle size data in the smoke particle data; Based on the radial attenuation law of the spatial field intensity along the conductor and the region radius of each simulation region, the initial simulation model is divided into simulation regions to obtain the simulation model.

3. The method for predicting the degree of adsorption of wildfire smoke particles according to claim 2, wherein: in, Each of the simulation areas includes a first simulation area and a second simulation area. The initial simulation model is divided into simulation areas based on the radial attenuation law of the spatial field intensity along the conductor and the area radius of each simulation area, specifically: The initial simulation model is divided into a first partition and a second partition using a horizontal line where the target center position of the overhead transmission line to be predicted is located as a dividing line; In the first partition, dividing the first partition into rectangular areas along the horizontal direction according to the area radius of each simulation area to obtain a plurality of first simulation areas; In the second partition, dividing the second partition into sector-shaped regions along the vertical direction according to the region radius of each simulation region to obtain a plurality of second simulation regions; A plurality of simulation areas are obtained by combining area radii corresponding to the first simulation areas and the second simulation areas.

4. The method for predicting the degree of adsorption of wildfire smoke particles according to claim 3, wherein: In the simulation calculation model, an initial simulation model is obtained; and the radius of each simulation area is determined according to the conductor radius of the overhead transmission line to be predicted and the smoke particle size data in the smoke particle data, specifically: In each of the simulation areas, determining the simulation area with the shortest distance to the overhead transmission line to be predicted as the target simulation area; The area radius of the target simulation area is determined based on the wire radius and the maximum particle size in the smoke particle size data, and the area radius of other simulation areas is determined according to the area radius of the target simulation area.

5. The method for predicting the degree of adsorption of wildfire smoke particles according to claim 4, wherein: The coordinate data is input into a simulation calculation model so that the simulation calculation model obtains a prediction result of the adsorption degree of the overhead transmission line to be predicted based on the correspondence between the coordinate data and each simulation area in the overhead transmission line to be predicted, specifically: In the simulation calculation model, for each smoke particle, comparing the size relationship between the ordinate value in the coordinate data and the area radius of the target simulation area; If the ordinate value in the coordinate data is smaller than the area radius of the target simulation area, determining the simulation area corresponding to the smoke particle according to the size relationship between the abscissa value in the coordinate data and the area radius of the target simulation area; If the vertical coordinate value in the coordinate data is greater than or equal to the area radius of the target simulation area, determining the simulation area corresponding to the smoke particle according to the spatial distance between the smoke particle and the target circle center position; The smoke particles in the target simulation area are counted to obtain the adsorption degree prediction result.

6. The method for predicting the degree of adsorption of wildfire smoke particles according to claim 2, wherein: The initial simulation model is specifically: Based on the two-dimensional axisymmetric space dimension, physical modeling is performed on the mutual relationship among the temperature field, fluid field, electric field and particle dynamic field in the overhead transmission line to be predicted to obtain the initial simulation model of multi-physical field coupling.

7. The method for predicting the degree of adsorption of wildfire smoke particles according to claim 1, wherein: The calculation of the quantity and mass of smoke particles in each simulation area is specifically as follows: P i =k i / N; Where ρ is the smoke particle density of the smoke sample particles, r ij is the particle size of each smoke particle j in the simulation area i, k i is the number of smoke particles in simulation area i, m i The mass of smoke particles in simulation area i, P i is the proportion of the particle distribution number in simulation area i to the total number of samples N.

8. A wildfire smoke particle adsorption degree prediction system, characterized by: include: Acquisition module and prediction module; The acquisition module is configured to acquire, within a preset time period, wildfire data of the overhead transmission line to be predicted under wildfire conditions, wherein the wildfire data includes smoke particle data, temperature data, clearance data, and vegetation data; The prediction module is used to input the wildfire data into a simulation calculation model so that the simulation calculation model constructs a simulation model corresponding to the overhead transmission line to be predicted based on the wildfire data, determines the correspondence between the coordinate data of each smoke particle and each simulation area based on the simulation model, calculates the quantity and mass of the smoke particles in each simulation area, and outputs the adsorption degree prediction result corresponding to the target simulation area of ​​the overhead transmission line to be predicted. The simulation model includes several simulation areas, and each simulation area is divided according to the spatial field strength of the overhead transmission line to be predicted.

9. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the method for predicting the adsorption degree of wildfire smoke particles according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that include: A stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the method for predicting the adsorption degree of wildfire smoke particles according to any one of claims 1 to 7.

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