Power transmission channel-oriented local strong wind identification method, system and equipment and medium

Abstract

The invention discloses a power transmission channel-oriented local strong wind identification method, system and device, and a medium. The method comprises the steps of obtaining basic information of a power transmission channel and a gridded numerical weather forecast; according to the basic information of the power transmission channel and the gridded numerical weather forecast, calculating the wind speed of each section of power transmission line in the power transmission channel at a preset integral time step length at the height h; according to the wind speed of each section of power transmission line at the height h on the preset integral time step length, calculating the local strong wind speed of each section of power transmission line on the preset integral time step length; the local strong wind speed of the power transmission channel is determined according to the local strong wind speed of each section of power transmission line on the preset integral time step length, and the method, the system, the equipment and the medium can identify the local strong wind speed of the power transmission channel.

Description

Technical Field

[0001] The present invention belongs to the field of local strong wind forecast and warning for power transmission channels, and relates to a local strong wind identification method, system, equipment and medium for power transmission channels. Background Art

[0002] A transmission channel refers to a certain limited space that contains multiple important transmission lines. Transmission channels are of great significance to the stable transmission of electricity and the safe operation of power systems. In recent years, with the intensification of global climate change, extreme weather has occurred frequently, especially local strong wind weather, which can easily cause damage to power grid equipment in the transmission channel, damage to dense transmission channel equipment, and even cause serious economic losses and social effects. Therefore, how to accurately identify local strong winds for transmission channels directly affects the accuracy of forecasts and warnings for local strong winds for transmission channels and the safety level of transmission channels. At present, there are still technical challenges in the accurate identification of local strong winds for transmission channels. First, the identification of strong winds for transmission channels usually uses the wind speed of numerical weather forecasts 10 meters above the ground, which cannot accurately reflect the wind field at the height of the transmission line. Second, local strong winds usually occur simultaneously with deep convective systems such as gusty winds and severe convection. The convective activity of the atmosphere contributes to the development of strong winds. However, convective activity poses great challenges to accurate forecasting due to its strong local nature and short life span. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a method, system, device and medium for identifying local strong winds in power transmission channels. The method, system, device and medium can identify the local strong wind speed in the power transmission channel.

[0004] To achieve the above object, the present invention discloses a method for identifying local strong winds in a power transmission channel, comprising:

[0005] Obtain basic information on power transmission channels and grid-based numerical weather forecasts;

[0006] Calculate the wind speed of each section of the transmission line in the transmission channel at a height h at a preset integration time step according to the basic information of the transmission channel and the gridded numerical weather forecast;

[0007] Calculate the local strong wind speed of each section of the transmission line at the preset integration time step according to the wind speed of each section of the transmission line at the height h at the preset integration time step;

[0008] The local strong wind speed of the transmission channel is determined according to the local strong wind speed of each section of the transmission line at a preset integration time step.

[0009] The further improvement of the local strong wind identification method for power transmission channels of the present invention is:

[0010] Furthermore, the wind speed u of any section of the transmission line in the transmission channel at a height h at a preset integration time step is h for:

[0011]

[0012] Among them, u 10 is the wind speed at the grid point corresponding to the section of the transmission line at a height of 10 meters, z0 is the roughness of the grid point corresponding to the line during this period, L is the MO length of the grid point corresponding to the line during this period, and Ψ(h / L) represents the atmospheric stability function of the section of the transmission line at a height of h.

[0013] Further, the atmospheric stability function is expressed as:

[0014]

[0015] Where K is the Karman constant.

[0016] Furthermore, the wind speed u of any section of the transmission line at height h at the preset integration time step is gust for:

[0017] u gust =u h +c conv max(0,u 850 -u 950 ) (3)

[0018] Among them, c conv represents the convective mixing parameter at the corresponding space and time point, u 850 and u 950 They respectively represent the wind speeds on the 850hPa and 950hPa isobaric surfaces at the corresponding grid points in the numerical weather forecast.

[0019] Furthermore, the process of determining the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at the preset integration time step is:

[0020] The maximum value of the local strong wind speed of each section of the transmission line at a preset integration time step is determined, and the maximum value is used as the local strong wind speed of the transmission channel.

[0021] The present invention discloses a local strong wind identification system for power transmission channels, comprising:

[0022] The acquisition module is used to obtain basic information of the transmission channel and gridded numerical weather forecasts;

[0023] The first calculation module is used to calculate the wind speed of each section of the transmission line in the transmission channel at a height h at a preset integration time step according to the basic information of the transmission channel and the gridded numerical weather forecast;

[0024] A second calculation module is used to calculate the local strong wind speed of each section of the transmission line at a preset integral time step according to the wind speed of each section of the transmission line at a height h at a preset integral time step;

[0025] The determination module is used to determine the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at a preset integration time step.

[0026] The further improvement of the local strong wind identification system for power transmission channels of the present invention is:

[0027] Furthermore, the wind speed u of any section of the transmission line in the transmission channel at a height h at a preset integration time step is h for:

[0028]

[0029] Among them, u 10 is the wind speed at the grid point corresponding to the section of the transmission line at a height of 10 meters, z0 is the roughness of the grid point corresponding to the line during this period, L is the MO length of the grid point corresponding to the line during this period, and ψ(h / L) represents the atmospheric stability function of the section of the transmission line at a height of h.

[0030] Further, the atmospheric stability function is expressed as:

[0031]

[0032] Where k is the Karman constant.

[0033] Furthermore, the wind speed u of any section of the transmission line at height h at the preset integration time step is gust for:

[0034] u gust =u h +c conv max(0,u 850 -u 950 ) (3)

[0035] Among them, c conv represents the convective mixing parameter at the corresponding space and time point, u 850 and u 950 They respectively represent the wind speeds on the 850hPa and 950hPa isobaric surfaces at the corresponding grid points in the numerical weather forecast.

[0036] Furthermore, the process of determining the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at the preset integration time step is:

[0037] The maximum value of the local strong wind speed of each section of the transmission line at a preset integration time step is determined, and the maximum value is used as the local strong wind speed of the transmission channel.

[0038] The present invention discloses a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for identifying local strong winds facing a power transmission channel are implemented.

[0039] The present invention discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for identifying local strong winds for power transmission channels are implemented.

[0040] The present invention has the following beneficial effects:

[0041] The local strong wind identification method, system, device and medium for power transmission channel of the present invention are used in specific operation according to the basic information of the power transmission channel and the gridded numerical weather forecast.

[0042] The wind speed of each section of the transmission line in the transmission channel at a height of h at a preset integration time step is calculated, so as to accurately reflect the wind field at the height of the transmission line. At the same time, according to the wind speed of each section of the transmission line at a height of h at a preset integration time step, the local strong wind speed of each section of the transmission line at the preset integration time step is calculated, and the local strong wind speed of the transmission channel is determined based on this. That is, by iteratively calculating each integration time step in the numerical forecast, the maximum value obtained is used as the local strong wind speed in the period, so as to realize the identification of the local strong wind speed of the transmission channel. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0044] Figure 1 is a flow chart of the method of the present invention;

[0045] Figure 2 It is a system structure diagram of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0048] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0049] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0050] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0051] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0053] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0054] Embodiment 1

[0055] refer to Figure 1 The local strong wind identification method for power transmission channels of the present invention comprises the following steps:

[0056] 1) Obtain the basic information of the transmission channel and the gridded numerical weather forecast. The basic information of the transmission channel includes the terrain, longitude and latitude of the transmission channel and the height information of the transmission line. A matching relationship is established between the longitude and latitude information and the gridded numerical weather forecast to extract the wind speed, roughness and MO length at the height of 10 meters and 100 meters of the corresponding grid points.

[0057] The specific operations of step 1) are:

[0058] 11) For the transmission channel area, obtain the height of the transmission line, the longitude and latitude information of the tower, and the topographic data in the transmission channel. Let h i is the height of the transmission line, x i ,y i is the longitude and latitude of the line tower, where the subscript i represents the number of the line tower, and the longitude and latitude information sequence of each tower in the line is constructed.

[0059] 12) Based on the gridded numerical weather forecast data of the transmission channel, according to the longitude and latitude information sequence of each line constructed in step 11), a matching relationship between the towers of the transmission line and the gridded numerical weather forecast is established respectively, and the wind speed u at a height of 10 meters at the corresponding grid point is extracted from the numerical weather forecast respectively. 10 , roughness z0 and MO length L.

[0060] It should be noted that the forecast data is a two-dimensional matrix, the first dimension is the spatial dimension, indicating that there are multiple line tower records in the transmission channel, and the second dimension is the time dimension, that is, it contains multiple time series data within a forecast validity period. The present invention performs iterative calculations for each line tower at each integral time step of the numerical weather forecast. Therefore, for the simplification of the expression form, it is recorded in the above form, without using the form of a two-dimensional matrix, which introduces the complexity of the spatial and temporal dimensions.

[0061] 2) Construct a baseline wind speed diagnostic model at the height of the transmission line under unstable atmospheric conditions. Strong winds that affect transmission lines generally occur under unstable atmospheric conditions. Therefore, it is impossible to obtain the wind speed at the height of the transmission line by logarithmic interpolation or simple linear interpolation based on the assumption that the atmosphere is neutral. The present invention applies the Monin-Obukhov similarity theory, focusing on the influence of atmospheric stability on the vertical wind profile, and constructs a wind speed model at the height of the transmission line.

[0062] The specific process of step 2) is:

[0063] 21) According to meteorological analysis, strong winds that have adverse effects on transmission lines all occur under unstable atmospheric conditions. Therefore, when constructing a wind speed model at the height of the transmission line, it is impossible to use the logarithmic wind profile or linear interpolation based on the assumption that the atmosphere is neutral. Based on the Monin-Obukhov similarity theory and the influence of atmospheric stability on the vertical wind profile, a wind speed calculation model at the height of the transmission line is proposed. The wind speed calculation model at the height of the transmission line h is expressed as:

[0064]

[0065] Among them, u h represents the wind speed of a section of the transmission line at a certain integral time step at height h, u 10 is the wind speed at a height of 10 meters, z0 is the roughness of the corresponding grid and time extracted in step 12), L is the MO length extracted in step 12), and Ψ represents the atmospheric stability function.

[0066] 22) The above analysis shows that strong winds occur under unstable atmospheric conditions. Therefore, the present invention only focuses on the atmospheric stability function Ψ under unstable conditions. The atmospheric stability function is related to the length and height of MO. The atmospheric stability function Ψ (h / L) under unstable conditions is:

[0067]

[0068] Where κ is the Karman constant, which is approximately 0.4.

[0069] 3) A local strong wind identification method considering the contribution of mid- and low-level atmospheric convection is established. The generation of local strong winds in the transmission channel is inseparable from the convection contribution of deep convective systems corresponding to gusts and strong convective events. The present invention adopts vertical wind shear as the convection contribution item to establish a local strong wind identification scheme for the transmission channel.

[0070] The process of step 3) is:

[0071] The local strong winds that have an adverse impact on the transmission channel often occur simultaneously with local gusty winds or strong convective events, that is, local strong winds occur in deep convective systems. Therefore, the present invention uses the function of vertical wind shear to represent the convective contribution term and adds it to the calculation of local gusts, that is:

[0072] u gust =u h +c conv max(0,u 850 -u 950 ) (3)

[0073] in, ust represents the wind speed of a local strong wind on a certain transmission line at a certain integral time step, u h represents the reference wind speed, c conv represents the convective mixing parameter at the corresponding space and time point, c conv The value range of u is [0.3, 0.6], 850 and u 950 They respectively represent the wind speeds at the 850hPa and 950hPa isobaric surfaces at the corresponding grid points of the numerical weather forecast. The wind speed at 850hPa represents the wind field in the middle atmosphere, and the wind speed at 950hPa represents the wind field in the lower atmosphere. The vertical shear between the two layers of wind fields characterizes the intensity of convective activity between the middle and lower atmospheres.

[0074] 32) For each line section and tower in the transmission channel of interest, as well as each integral time step of the numerical weather forecast, a calculation is required according to formula (3). Finally, the u of each section of the transmission line in the forecast time is calculated. gust ; Select each section of the transmission line in the forecast time u gustThe maximum value is taken as the local strong wind speed in the transmission channel within this forecast period.

[0075] It should be noted that the present invention adopts the Monin-Obukhov similarity theory and proposes a wind speed diagnosis model at the height of the transmission line under unstable atmospheric conditions; further points out the contribution of deep convective systems to local strong winds, proposes to characterize the convective contribution term with the middle and low-level vertical wind shear function, and establishes a local strong wind identification method that considers both atmospheric stability conditions and convective contributions; finally, through iterative calculation of each level of line section tower within the forecast time limit, the maximum value within the forecast period is obtained as the local strong wind within the period. The present invention combines the basic information of the transmission channel and the conventional data of numerical weather forecasting, adopts the Monin-Obukhov similarity theory in meteorology and related theories such as vertical wind shear of deep convective systems, and constructs a local strong wind identification model for transmission line towers. It can not only perfectly solve all the current computational problems, but also be more in line with the actual situation, and the model is more theoretical and has higher fitting accuracy.

[0076] Embodiment 2

[0077] refer to Figure 2 The local strong wind identification system for power transmission channels of the present invention comprises:

[0078] The acquisition module is used to obtain basic information of the transmission channel and gridded numerical weather forecasts;

[0079] The first calculation module is used to calculate the wind speed of each section of the transmission line in the transmission channel at a height h at a preset integration time step according to the basic information of the transmission channel and the gridded numerical weather forecast;

[0080] A second calculation module is used to calculate the local strong wind speed of each section of the transmission line at a preset integral time step according to the wind speed of each section of the transmission line at a height h at a preset integral time step;

[0081] The determination module is used to determine the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at a preset integration time step.

[0082] The further improvement of the local strong wind identification system for power transmission channels of the present invention is:

[0083] Furthermore, the wind speed u of any section of the transmission line in the transmission channel at a height h at a preset integration time step is h for:

[0084]

[0085] Among them, u 10is the wind speed at the grid point corresponding to the section of the transmission line at a height of 10 meters, z0 is the roughness of the grid point corresponding to the line during this period, L is the MO length of the grid point corresponding to the line during this period, and Ψ(h / L) represents the atmospheric stability function of the section of the transmission line at a height of h.

[0086] Further, the atmospheric stability function is expressed as:

[0087]

[0088] Where k is the Karman constant.

[0089] Furthermore, the wind speed u of any section of the transmission line at height h at the preset integration time step is gus t is:

[0090] u gust =u h +c conv max(0,u 850 -u 950 ) (3)

[0091] Among them, c conv represents the convective mixing parameter at the corresponding space and time point, u 850 and u 950 They respectively represent the wind speeds on the 850hPa and 950hPa isobaric surfaces at the corresponding grid points in the numerical weather forecast.

[0092] Furthermore, the process of determining the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at the preset integration time step is:

[0093] The maximum value of the local strong wind speed of each section of the transmission line at a preset integration time step is determined, and the maximum value is used as the local strong wind speed of the transmission channel.

[0094] The division of modules in the embodiments of the present invention is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present invention may be integrated into one processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0095] Embodiment 3

[0096] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of implementing the local strong wind identification method for a transmission channel are, for example, comprising: obtaining basic information of the transmission channel and a gridded numerical weather forecast; calculating the wind speed of each section of the transmission line in the transmission channel at a height h at a preset integration time step according to the basic information of the transmission channel and the gridded numerical weather forecast; calculating the local strong wind speed of each section of the transmission line at the preset integration time step according to the wind speed of each section of the transmission line at a height h at the preset integration time step; determining the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at the preset integration time step. The memory may include a memory, such as a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk memory, etc. The processor, network interface, and memory are interconnected through an internal bus, and the internal bus may be an industrial standard architecture bus, a peripheral component interconnection standard bus, an extended industrial standard architecture bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program may include a program code, and the program code includes computer operation instructions. The memory may include a memory and a non-volatile memory, and provide instructions and data to the processor.

[0097] Embodiment 4

[0098] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of implementing the local strong wind identification method for a transmission channel, for example, include: obtaining basic information of the transmission channel and a gridded numerical weather forecast; calculating the wind speed of each section of the transmission line in the transmission channel at a preset integral time step at a height h according to the basic information of the transmission channel and the gridded numerical weather forecast; calculating the local strong wind speed of each section of the transmission line at a preset integral time step according to the wind speed of each section of the transmission line at a height h at a preset integral time step; determining the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at a preset integral time step. Specifically, the computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include a read-only memory (ROM), a hard disk, a flash memory, an optical disk, a magnetic disk, etc.

[0099] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0101] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0102] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0103] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and disclosure of the invention. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The description and examples are to be regarded as exemplary only, and the true scope and spirit of the present invention is indicated by the following claims.

[0104] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

[0105] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any simple modification, change and equivalent structural change made to the above embodiment based on the technical essence of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for identifying local strong winds in a power transmission channel, characterized in that: include: Obtain basic information on power transmission channels and grid-based numerical weather forecasts; Calculate the wind speed of each section of the transmission line in the transmission channel at a height h at a preset integration time step according to the basic information of the transmission channel and the gridded numerical weather forecast; Calculate the local strong wind speed of each section of the transmission line at the preset integration time step according to the wind speed of each section of the transmission line at the height h at the preset integration time step; The local strong wind speed of the transmission channel is determined according to the local strong wind speed of each section of the transmission line at a preset integration time step.

2. The method for identifying local strong winds for power transmission channels according to claim 1, characterized in that: The wind speed u of any section of the transmission line in the transmission channel at a height h at a preset integration time step h for: Among them, u 10 is the wind speed at the grid point corresponding to the section of the transmission line at a height of 10 meters, z0 is the roughness of the grid point corresponding to the line during this period, L is the MO length of the grid point corresponding to the line during this period, and Ψ(h / L) represents the atmospheric stability function of the section of the transmission line at a height of h.

3. The method for identifying local strong winds for power transmission channels according to claim 2, characterized in that: The atmospheric stability function is expressed as: Where κ is the Karman constant.

4. The method for identifying local strong winds for power transmission channels according to claim 2, characterized in that: The wind speed u of any section of the transmission line at height h over the preset integration time step gust for: u gust =u h +c conv max(0,u 850 -u 950 ) (3) Among them, c conv represents the convective mixing parameter at the corresponding space and time point, u 850 and u 950 They respectively represent the wind speeds on the 850hPa and 950hPa isobaric surfaces at the corresponding grid points in the numerical weather forecast.

5. The method for identifying local strong winds for power transmission channels according to claim 1, characterized in that: The process of determining the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at the preset integration time step is: The maximum value of the local strong wind speed of each section of the transmission line at a preset integration time step is determined, and the maximum value is used as the local strong wind speed of the transmission channel.

6. A local strong wind identification system for power transmission channels, characterized in that: include: The acquisition module is used to obtain basic information of the transmission channel and gridded numerical weather forecasts; The first calculation module is used to calculate the wind speed of each section of the transmission line in the transmission channel at a height h at a preset integration time step according to the basic information of the transmission channel and the gridded numerical weather forecast; A second calculation module is used to calculate the local strong wind speed of each section of the transmission line at a preset integral time step according to the wind speed of each section of the transmission line at a height h at a preset integral time step; The determination module is used to determine the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at a preset integration time step.

7. The local strong wind identification system for power transmission channels according to claim 6, characterized in that: The wind speed u of any section of the transmission line in the transmission channel at a height h at a preset integration time step h for: Among them, u 10 is the wind speed at the grid point corresponding to the section of the transmission line at a height of 10 meters, z0 is the roughness of the grid point corresponding to the line during this period, L is the MO length of the grid point corresponding to the line during this period, and Ψ(h / L) represents the atmospheric stability function of the section of the transmission line at a height of h.

8. The local strong wind identification system for power transmission channels according to claim 7, characterized in that: The atmospheric stability function is expressed as: Where κ is the Karman constant.

9. The local strong wind identification system for power transmission channels according to claim 7, characterized in that: The wind speed u of any section of the transmission line at height h over the preset integration time step gust for: u gust =u h +c conv max(0,u 850 -u 950 ) (3) Among them, c conv represents the convective mixing parameter at the corresponding space and time point, u 850 and u 950 They respectively represent the wind speeds on the 850hPa and 950hPa isobaric surfaces at the corresponding grid points in the numerical weather forecast.

10. The local strong wind identification system for power transmission channels according to claim 6, characterized in that: The process of determining the local strong wind speed of the transmission channel according to the local strong wind speed of each section of the transmission line at the preset integration time step is: The maximum value of the local strong wind speed of each section of the transmission line at a preset integration time step is determined, and the maximum value is used as the local strong wind speed of the transmission channel.

11. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for identifying local strong winds for power transmission channels as described in any one of claims 1-5 are implemented.

12. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for identifying local strong winds for power transmission channels as described in any one of claims 1 to 5 are implemented.

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