A severe convection warning method and system for power lines based on meteorological radar data

Abstract

The present invention belongs to the technical field of power line monitoring and early warning, and discloses a method and system for early warning of severe convection of power lines based on meteorological radar data. The method obtains reflectivity grid data; judges the severe convection area according to the reflectivity grid data, and designs complexity parameters to measure the structural complexity and spatial connectivity of the severe convection area; judges whether a squall line is formed according to the spatial and temporal correlation between adjacent severe convection areas; judges the movement direction, movement speed and intensity change of the squall line, and evaluates the impact of the squall line on the power line, and issues an early warning. The present invention greatly improves the timeliness and accuracy of the early warning and reduces the false alarm rate and missed alarm rate by designing complexity parameters and conducting judgment and analysis of the squall line.

Description

Technical Field

[0001] The present invention belongs to the technical field of power line monitoring and early warning, and in particular relates to a method and system for early warning of severe convection in power lines based on meteorological radar data. Background Art

[0002] In the safe operation of the power system, severe convective weather warning is crucial to the stable operation of power lines. Severe convective weather, especially squall lines, thunderstorms, strong winds and heavy precipitation, often cause wind deviation of power lines, equipment damage, and even cause serious power outages and secondary disasters. Therefore, accurate and timely severe convective warning is of great significance to ensure the stable operation of the power system and improve the safety of power supply. However, traditional warning methods are usually based on meteorological station data, with low spatial resolution and real-time performance, and it is difficult to cope with the rapid development and complex changes of severe convective weather. Summary of the invention

[0003] The purpose of the present invention is to provide a method and system for early warning of severe convection in power lines based on meteorological radar data. The method uses the echo reflectivity data and other basic meteorological data of meteorological radar data, combined with power equipment data and terrain and climate characteristics to judge severe convective weather, and warns of power lines that may be affected based on the design parameters of the power equipment, thereby improving the ability of power operation and maintenance personnel to cope with severe convective weather.

[0004] The present invention is implemented by the following technical solution: a method for early warning of severe convection in power lines based on meteorological radar data, comprising the following steps:

[0005] Step S1: Obtain reflectivity grid data;

[0006] Step S2: Determine the strong convective area based on the reflectivity grid data, and design complexity parameters to measure the structural complexity and spatial connectivity of the strong convective area, so as to reflect the organization of the convective system in the strong convective area and the potential risk of strong convective weather;

[0007] Step S3: judging whether a squall line is formed based on the spatial and temporal correlation between adjacent severe convective areas;

[0008] Step S4: Analyze the movement direction, movement speed and intensity changes of the squall line;

[0009] Step S5: According to the movement direction, movement speed and intensity changes of the squall line, the impact of the squall line on the power line is evaluated and an early warning is issued.

[0010] Further preferably, the strong convection area is determined according to the reflectivity grid data in step S2 as:

[0011] For each time t and position (x, y), x is longitude and y is latitude, when the reflectivity value Z(t,x,y) exceeds the preset threshold When , the corresponding grid is marked as a strong convection grid, and one or more connected strong convection grids form a strong convection area.

[0012] Further preferably, the complexity parameter is expressed as:

[0013] ;

[0014] Among them, α is the weight coefficient of the severe convection grid ratio, β is the weight coefficient of the shape factor, is the severe convection grid ratio, is the shape factor.

[0015] Further preferably, the strong convection grid ratio is calculated as follows:

[0016] For each severe convection grid P(x,y), define a neighborhood range N(x,y):

[0017] ;

[0018] Where r is the radius of the neighborhood, is the grid position adjacent to the strong convection grid P(x,y);

[0019] Count the number of grids in the neighborhood N(x,y) that belong to the strong convection area , calculate its share of the total number of grids Ratio:

[0020] ;

[0021] in, is the number of grids in the strong convection region, is the total number of grids in the neighborhood.

[0022] Further preferably, the shape factor It is the ratio of the boundary length to the area of ​​the severe convection region.

[0023] Further preferably, step S3 includes the following sub-steps:

[0024] Step S3-1: spatial correlation analysis;

[0025] For each strong convection area i, find its adjacent strong convection area j and calculate the spatial distance between strong convection area i and strong convection area j. Differences from complexity parameters :

[0026] ;

[0027] ;

[0028] in, is the location of the severe convection region i, is the longitude of severe convection region i, is the latitude of severe convection region i, is the location of the strong convection region j, is the longitude of severe convection region j, is the latitude of severe convection region j, is the complexity parameter of severe convection region i, is the complexity parameter of the severe convection region j;

[0029] Step S3-2: time correlation analysis;

[0030] Calculate the difference in the appearance time between severe convection area i and severe convection area j ,in is the appearance time of severe convection area i, is the appearance time of severe convection area j;

[0031] Step S3-3: Comprehensive analysis of the squall line;

[0032] Defining the likelihood of a squall line forming :

[0033] ;

[0034] in, is the control parameter of spatial attenuation, is the control parameter of time decay, n is the number of severe convection regions;

[0035] By comparing the probability indicators of squall line formation The squall line threshold is set To determine whether a squall line has formed: If the squall line is formed, it is considered as regional severe convection.

[0036] Further preferably, step S4 includes the following sub-steps:

[0037] Step S4-1: Update the position and shape of the squall line;

[0038] A squall line is a belt-like system composed of multiple strong convective areas. The position and shape of the squall line are obtained by updating and calculating the position of each strong convective area.

[0039] Step S4-2: Prediction of the movement direction and speed of the squall line;

[0040] Step S4-3: Prediction of squall line intensity changes.

[0041] Further optimization, location update: through and The position change of the severe convection area between two moments is used to calculate the overall position update of the squall line; for the center position of the squall line, the position of the severe convection area that constitutes the squall line is used The centroid of is represented by:

[0042] ;

[0043] in, represents the center position of the squall line at time t, is the longitude of the center of the squall line, is the latitude of the center of the squall line, represents the center position of severe convective region i, n is the number of severe convective regions that make up the squall line, For the set time interval;

[0044] Morphology Update: The morphology of a squall line is characterized by describing the length of the major and minor axes of the squall line.

[0045] Further preferably, the movement direction and movement speed prediction of the squall line are specifically:

[0046] Movement direction prediction: Determine the movement direction of the squall line by calculating the position change of the squall line in consecutive time intervals; and They are and The center position of the squall line at the time, the direction of movement It is expressed as:

[0047] ;

[0048] Movement speed prediction: by calculating the squall line center position at time intervals The change in the squall line gives the speed of the squall line. :

[0049] .

[0050] Further preferably, the squall line intensity change prediction includes:

[0051] Intensity index: The intensity of the squall line is measured by the average radar reflectivity within the squall line area. express:

[0052] ;

[0053] in, is the radar reflectivity of the ith severe convection region;

[0054] Intensity change rate prediction: by calculating the continuous time and The intensity difference of the squall line is used to obtain the rate of change of the squall line intensity. :

[0055] ;

[0056] if , it indicates that the intensity of the squall line is increasing; if , indicating that the intensity of the squall line is weakening.

[0057] Further preferably, the step S5 comprises:

[0058] Analysis of the scope of power lines affected: Based on the predicted path of the squall line and the geographical location of the power lines, the coverage area of ​​the power lines passed by the squall line is determined by whether the longitude and latitude coordinates of the power line towers are within the predicted path of the squall line;

[0059] Impact time estimation: Calculate the time it takes for a squall line to reach the area covered by power lines :

[0060] ;

[0061] in, is the current time, is the distance between the power line and the squall line;

[0062] Potential impact assessment: combining the intensity of squall lines and the design tolerance of power lines , determine whether the squall line will cause damage to power lines: If If the squall line is too strong, an early warning will be issued. Otherwise, the changes of the squall line will continue to be monitored. The time it takes for the squall line to reach the area covered by the power lines The average value of radar reflectivity within the squall line area;

[0063] Design tolerance of power lines It is expressed as:

[0064] ;

[0065] in, It is the maximum wind pressure or wind force considered during design. is the maximum load-bearing capacity of the power line material, is the model parameter that determines the relative impact of wind pressure on the design tolerance is the model parameter that determines the relative impact of the load-bearing capacity on the design tolerance, It is an index that regulates the nonlinear effect of wind pressure and is determined by the corresponding power line design parameters.

[0066] Further preferably, in step S5, the warning signal is divided into different warning levels to reflect the severity of the weather event:

[0067] ;

[0068] in, Indicates the dynamic design tolerance of the power line; , , Represent the risk thresholds for red, orange and yellow warnings respectively.

[0069] The present invention also provides a severe convection warning system for power lines based on weather radar data, comprising:

[0070] Radar system to obtain reflectivity grid data;

[0071] The severe convective region assessment module is used to determine the severe convective region based on the reflectivity grid data, and to design complexity parameters to measure the structural complexity and spatial connectivity of the severe convective region, so as to reflect the organization of the convective system in the severe convective region and the potential severe convective weather risk;

[0072] The squall line assessment module is used to assess whether a squall line is formed based on the spatial and temporal correlations between adjacent severe convective areas.

[0073] Squall line movement trend analysis module, used to analyze the movement direction, movement speed and intensity changes of the squall line;

[0074] The early warning analysis module is used to evaluate the impact of squall lines on power lines and issue early warnings based on the movement direction, speed and intensity changes of the squall lines.

[0075] The present invention has the following advantages:

[0076] (1) The present invention introduces real-time analysis of radar reflectivity grid data and combines it with complexity parameter design tolerance model to accurately identify and judge the formation of severe convective weather and its potential threat to power lines. In particular, the judgment and analysis of squall lines greatly improves the timeliness and accuracy of early warning and reduces the false alarm rate and missed alarm rate.

[0077] (2) By comprehensively analyzing the strong convective areas in adjacent spaces within a continuous period, the formation process of the squall line can be effectively determined, and its intensity, movement trend, and future impact area can be further predicted. This process not only takes into account the dynamic changes of radar reflectivity, but also evaluates the potential development trend of the squall line through complexity parameters, making the prediction more scientific and reasonable.

[0078] (3) The power line design tolerance model introduced in the present invention can calculate the line load limit in real time based on the line's physical design parameters, wind pressure limit and material bearing capacity. Combined with real-time weather data, the present invention can dynamically evaluate the risk of line damage in severe convective weather, thereby deciding whether to issue an early warning. This dynamic risk assessment model effectively avoids excessive early warnings and ignoring potential risks, ensuring the stability of the power system.

[0079] (4) Since the present invention uses real-time radar reflectivity data acquired at a high frequency (e.g., every 6 minutes) and combines mathematical models and parameter evaluation for rapid calculation and judgment, it is possible to achieve real-time monitoring and rapid warning of severe convective weather and its impact on power lines. This high efficiency provides sufficient response time for power operation and maintenance personnel, thereby greatly reducing power outages caused by extreme weather.

[0080] (5) Through accurate early warning and analysis, the present invention can effectively reduce the operation and maintenance costs caused by false alarms or failure to discover risks in a timely manner, and improve the operation and maintenance efficiency of the power system. In addition, accurate early warning information can also help to formulate more reasonable emergency plans and maintenance strategies, thereby further saving costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0082] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0083] Example 1

[0084] like Figure 1 As shown, a severe convection warning method for power lines based on weather radar data includes the following steps:

[0085] Step S1: Obtain reflectivity grid data;

[0086] High-resolution weather radar is used to obtain reflectivity grid data in real time. The reflectivity grid data is 1km×1km grid data. It is read and converted into structured data through the program. Finally, each row of data is the reflectivity value Z(t,x,y), where t is time, x is longitude, and y is latitude. The radar is used at regular intervals. The entire area is scanned (e.g., 6 minutes) to obtain the reflectivity value Z(t,x,y) at each position (x,y).

[0087] Step S2: Determine the strong convective area based on the reflectivity grid data, and design the complexity parameter C(t,x,y) to measure the structural complexity and spatial connectivity of the strong convective area, so as to reflect the organization of the convective system in the strong convective area and the potential risk of strong convective weather. The steps for calculating the complexity parameter are as follows:

[0088] Step S2-1: Determine the strong convection area;

[0089] Reflectivity grid data is used to evaluate the formation conditions of severe convective weather. When the reflectivity value Z(t,x,y) of a grid exceeds the preset reflectivity threshold When the reflectivity value Z(t,x,y) exceeds the preset threshold, the area is judged to have the conditions for severe convective weather. When , the corresponding grid is marked as a strong convection grid, and one or more connected strong convection grids form a strong convection area.

[0090] Step S2-2: extracting the number of strong convection grids in the strong convection area grid neighborhood;

[0091] For each strong convection grid P(x,y), a neighborhood range N(x,y) is defined, which is usually 8 or more adjacent grids of the grid, determined by the neighborhood radius, which can be defined as:

[0092] ;

[0093] Where r is the radius of the neighborhood, The grid positions adjacent to the severe convection grid P(x,y) can be determined based on the spatial resolution of the analysis.

[0094] Step S2-3: Calculate the proportion of strong convection grids in the neighborhood;

[0095] Count the number of grids in the neighborhood N(x,y) that belong to the strong convection area , calculate its share of the total number of grids Ratio:

[0096] ;

[0097] in, is the severe convection grid ratio, is the number of grids in the strong convection region, is the total number of grids in the neighborhood.

[0098] Step S2-4: Calculate the shape factor of the strong convection area;

[0099] Form Factor It is used to quantify the shape complexity of the strong convection area. Generally, the strong convection area with complex shape will have a larger shape factor. The shape factor is expressed by calculating the ratio of the boundary length to the area of ​​the strong convection area:

[0100] ;

[0101] in, is the boundary length of the severe convection region, is the total area of ​​the severe convection region, and s represents the area.

[0102] Step S2-5: Comprehensively calculate complexity parameters;

[0103] The complexity parameter C(t,x,y) designed in the present invention combines the proportion and shape factor of the strong convection grid in the neighborhood and can be calculated by the following formula:

[0104] ;

[0105] Among them, α is the weight coefficient of the severe convection grid ratio, β is the weight coefficient of the shape factor, and α and β are set empirical constants, which are used to adjust the influence of the severe convection grid ratio and shape factor on the complexity parameters.

[0106] Step S3: Determine whether a squall line is formed based on the spatial and temporal correlations between adjacent severe convective areas.

[0107] Step S3-1: spatial correlation analysis;

[0108] For each strong convection area i, find its adjacent strong convection area j and calculate the spatial distance between strong convection area i and strong convection area j. Differences from complexity parameters :

[0109] ;

[0110] ;

[0111] in, is the location of the severe convection region i, is the longitude of severe convection region i, is the latitude of severe convection region i, is the location of the strong convection region j, is the longitude of severe convection region j, is the latitude of severe convection region j, is the complexity parameter of severe convection region i, is the complexity parameter of the severe convection region j.

[0112] Step S3-2: time correlation analysis;

[0113] Calculate the difference in the appearance time between severe convection area i and severe convection area j ,in is the appearance time of severe convection area i, is the appearance time of severe convection area j.

[0114] Step S3-3: Comprehensive analysis of the squall line;

[0115] If the spatial distance Less than the threshold and the complexity parameter difference Less than the threshold, and the time difference If the area is also smaller than the threshold, it means that these areas are continuous in space and time and may form a squall line. Therefore, the possibility index of squall line formation is defined as As a combined function of these regional complexity parameters:

[0116] ;

[0117] in, is the control parameter of spatial attenuation, is the control parameter of time decay, and n is the number of severe convection regions.

[0118] Finally, by comparing the probability indicators of squall line formation The squall line threshold is set To determine whether a squall line has formed: If the squall line is formed, it is considered as regional severe convection.

[0119] Step S4: Analyze the movement direction, movement speed and intensity changes of the squall line;

[0120] After a squall line is formed, predicting its movement trend is crucial for protecting power lines. The analysis of the squall line movement trend includes determining the squall line's movement direction, movement speed, intensity changes, and potential impact on power lines. The following are the specific steps for analyzing the squall line movement trend.

[0121] Step S4-1: Update the position and shape of the squall line;

[0122] A squall line is a belt-like system composed of multiple strong convective areas, each of which is a strong convective cell. Therefore, the position and shape of a squall line can be obtained by updating and calculating the positions of the various strong convective areas that make it up.

[0123] Location Update: Via and The position change of the severe convection area between two moments is used to calculate the overall position update of the squall line. For the center position of the squall line, the position of the severe convection area that makes up the squall line can be used The centroid of is represented by:

[0124] ;

[0125] in, represents the center position of the squall line at time t, is the longitude of the center of the squall line, is the latitude of the center of the squall line, represents the center position of severe convective region i, n is the number of severe convective regions that make up the squall line, The time interval is set.

[0126] Morphology update: The morphology of a squall line can be characterized by describing the length of its major and minor axes. These parameters can be obtained by performing principal component analysis (PCA) on the spatial distribution of severe convective areas.

[0127] Step S4-2: Prediction of the movement direction and speed of the squall line;

[0128] Predicting the movement direction and speed of a squall line is a core step in analyzing the movement trend of the squall line.

[0129] Movement direction prediction: Determine the movement direction of the squall line by calculating the position changes of the squall line in continuous time intervals. and They are and The center position of the squall line at the time, the direction of movement It can be expressed as:

[0130] ;

[0131] Movement speed prediction: by calculating the squall line center position at time intervals The change in the squall line gives the speed of the squall line. :

[0132] ;

[0133] Step S4-3: Prediction of squall line intensity change;

[0134] The intensity change of squall lines directly affects their potential threat to power lines. Therefore, it is necessary to evaluate the changing trend of the intensity of squall lines during their movement.

[0135] Intensity index: The intensity of a squall line can be determined by the average radar reflectivity within the squall line area. express:

[0136] ;

[0137] in, is the radar reflectivity of the ith severe convection area.

[0138] Intensity change rate prediction: by calculating the continuous time and The intensity difference of the squall line is used to obtain the rate of change of the squall line intensity. :

[0139] ;

[0140] if , it indicates that the intensity of the squall line is increasing; if , indicating that the intensity of the squall line is weakening.

[0141] Step S5: According to the movement direction, movement speed and intensity changes of the squall line, the impact of the squall line on the power line is evaluated and an early warning is issued.

[0142] Analysis of the scope of power line impact: Based on the predicted path of the squall line and the geographical location of the power lines, the power line coverage area that the squall line may pass through is determined by whether the longitude and latitude coordinates of the power line towers are within the predicted path of the squall line.

[0143] Impact time estimation: Calculate the time it takes for a squall line to reach the area covered by power lines :

[0144] ;

[0145] in, is the current time, is the distance between the power line and the squall line.

[0146] Potential impact assessment: combining the intensity of squall lines and the design tolerance of power lines , determine whether the squall line may cause damage to power lines: If If the squall line is too strong, an early warning will be issued. Otherwise, the changes of the squall line will continue to be monitored. The time it takes for the squall line to reach the area covered by the power lines The average value of radar reflectivity within the squall line area.

[0147] Design tolerance of power lines It is the maximum reflectivity value that the power line can withstand under extreme weather conditions. It depends on the material and structural design of the line, as well as the extreme conditions in historical meteorological data, and is a fixed threshold:

[0148] ;

[0149] in, It is the maximum wind pressure or wind force considered during design. is the maximum load-bearing capacity of the power line material, is the model parameter that determines the relative impact of wind pressure on the design tolerance is the model parameter that determines the relative impact of the load-bearing capacity on the design tolerance, It is an index that regulates the nonlinear effect of wind pressure and is determined by the corresponding power line design parameters.

[0150] Warning signals can be divided into different levels to reflect the severity of weather events. For example, the system can set different thresholds corresponding to different warning levels, such as yellow warning, orange warning and red warning:

[0151] ;

[0152] in, It indicates the dynamic design tolerance of the power line, and the value may change at different times. In short, it is the maximum strong convection impact capacity that the power line can withstand at a specific time; , , Represent the risk thresholds for red, orange and yellow warnings respectively.

[0153] Example 2

[0154] This embodiment provides a severe convection warning system for power lines based on weather radar data, including:

[0155] Radar system to obtain reflectivity grid data;

[0156] The severe convective region assessment module is used to determine the severe convective region based on the reflectivity grid data, and to design complexity parameters to measure the structural complexity and spatial connectivity of the severe convective region, so as to reflect the organization of the convective system in the severe convective region and the potential severe convective weather risk;

[0157] The squall line assessment module is used to assess whether a squall line is formed based on the spatial and temporal correlations between adjacent severe convective areas.

[0158] Squall line movement trend analysis module, used to analyze the movement direction, movement speed and intensity changes of the squall line;

[0159] The early warning analysis module is used to evaluate the impact of squall lines on power lines and issue early warnings based on the movement direction, speed and intensity changes of the squall lines.

[0160] Example 3

[0161] This embodiment provides a terminal, which includes a memory, a processor, and a computer program stored in the memory. When the computer program is executed by the processor, each step of the power line severe convection warning method based on meteorological radar data as described in any one of the above implementation modes is implemented.

[0162] Example 4

[0163] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, each step of the power line severe convection warning method based on meteorological radar data as described in any one of the above implementation modes is implemented.

[0164] Example 5

[0165] This embodiment provides a computer program product, including a computer program or instructions, which, when processed and executed, implements the steps of the method for severe convection warning for power lines based on meteorological radar data as described in any of the above implementations.

[0166] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0167] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0168] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0169] In the embodiments provided by the present invention, it should be understood that the disclosed systems or devices / terminal equipment and methods can be implemented in other ways. For example, the system or device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the system or unit can be electrical, mechanical or other forms.

[0170] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0171] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0172] The present invention is not limited to what is described in the specification and implementation modes, and therefore additional advantages and modifications can be easily realized by those skilled in the art. Therefore, without departing from the spirit and scope of the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details, representative devices, and illustrative examples shown and described herein.

Claims

1. A method for early warning of severe convection in power lines based on weather radar data, characterized in that: The following steps are involved: Step S1: Obtain reflectivity grid data; Step S2: Determine the strong convective area based on the reflectivity grid data, and design complexity parameters to measure the structural complexity and spatial connectivity of the strong convective area, so as to reflect the organization of the convective system in the strong convective area and the potential risk of strong convective weather; Step S3: judging whether a squall line is formed based on the spatial and temporal correlation between adjacent severe convective areas; Step S4: Analyze the movement direction, movement speed and intensity changes of the squall line; Step S5: assessing the impact of the squall line on the power lines based on the movement direction, movement speed and intensity changes of the squall line, and issuing an early warning; Step S3 includes the following sub-steps: Step S3-1: spatial correlation analysis; For each strong convection area i, find its adjacent strong convection area j and calculate the spatial distance between strong convection area i and strong convection area j. Differences in complexity parameters : ； ； in, is the location of the severe convection region i, is the longitude of severe convection region i, is the latitude of severe convection region i, is the location of the strong convection region j, is the longitude of severe convection region j, is the latitude of severe convection region j, is the complexity parameter of severe convection region i, is the complexity parameter of the severe convection region j; Step S3-2: time correlation analysis; Calculate the difference in the appearance time between severe convection area i and severe convection area j ,in is the appearance time of severe convection area i, is the appearance time of severe convection area j; Step S3-3: Comprehensive analysis of the squall line; Defining the likelihood of a squall line forming : ； in, is the control parameter of spatial attenuation, is the control parameter of time decay, n is the number of severe convection regions; By comparing the probability indicators of squall line formation The squall line threshold is set To determine whether a squall line has formed: If the squall line is formed, it is considered as regional severe convection.

2. The method for early warning of severe convection in power lines based on weather radar data according to claim 1, characterized in that: The strong convection area determined according to the reflectivity grid data in step S2 is: For each time t and position (x, y), x is longitude and y is latitude, when the reflectivity value Z(t,x,y) exceeds the preset threshold When , the corresponding grid is marked as a strong convection grid, and one or more connected strong convection grids form a strong convection area.

3. The method for early warning of severe convection in power lines based on weather radar data according to claim 2 is characterized in that: The complexity parameter is expressed as: ； Among them, α is the weight coefficient of the severe convection grid ratio, β is the weight coefficient of the shape factor, is the severe convection grid ratio, is the shape factor.

4. The method for early warning of severe convection in power lines based on weather radar data according to claim 3 is characterized in that: The calculation method of the severe convection grid ratio is as follows: For each severe convection grid P(x,y), define a neighborhood range N(x,y): ； Where r is the radius of the neighborhood, is the grid position adjacent to the strong convection grid P(x,y); Count the number of grids in the neighborhood N(x,y) that belong to the strong convection area , calculate its share of the total number of grids Ratio: ； in, is the number of grids in the strong convection region, is the total number of grids in the neighborhood; Form Factor It is the ratio of the boundary length to the area of ​​the severe convection region.

5. The method for early warning of severe convection in power lines based on weather radar data according to claim 1, characterized in that: Step S4 includes the following sub-steps: Step S4-1: Update the position and shape of the squall line; A squall line is a belt-like system composed of multiple strong convective areas. The position and shape of the squall line are obtained by updating and calculating the position of each strong convective area. Location Update: Via and The position change of the severe convection area between two moments is used to calculate the overall position update of the squall line; for the center position of the squall line, the position of the severe convection area that constitutes the squall line is used The centroid of is represented by: ； in, represents the center position of the squall line at time t, is the longitude of the center of the squall line, is the latitude of the center of the squall line, represents the center position of severe convective region i, n is the number of severe convective regions that make up the squall line, For the set time interval; Morphology update: The morphology of a squall line is characterized by describing the length of the major and minor axes of the squall line; Step S4-2: Prediction of the movement direction and speed of the squall line; Step S4-3: Prediction of squall line intensity changes.

6. The method for early warning of severe convection in power lines based on weather radar data according to claim 5, characterized in that: The movement direction and movement speed prediction of the squall line are as follows: Movement direction prediction: Determine the movement direction of the squall line by calculating the position change of the squall line in continuous time intervals; and They are and The center position of the squall line at the time, the direction of movement It is expressed as: ； Movement speed prediction: by calculating the squall line center position at time intervals The change in the squall line gives the speed of the squall line. : 。 7. The method for early warning of severe convection in power lines based on weather radar data according to claim 6, characterized in that: The forecast of changes in squall line intensity includes: Intensity index: The intensity of the squall line is measured by the average radar reflectivity within the squall line area. express: ； in, is the radar reflectivity of the ith severe convection region; Intensity change rate prediction: by calculating the continuous time and The intensity difference of the squall line is used to obtain the change rate of the squall line intensity. : ； if , it indicates that the intensity of the squall line is increasing; if , indicating that the intensity of the squall line is weakening.

8. The method for early warning of severe convection in power lines based on weather radar data according to claim 7, characterized in that: The step S5 comprises: Analysis of the scope of power line impact: Based on the predicted path of the squall line and the geographical location of the power line, the coverage area of ​​the power line through which the squall line passes is determined by whether the longitude and latitude coordinates of the power line towers are within the predicted path of the squall line; Impact time estimation: Calculate the time it takes for a squall line to reach the area covered by power lines : ； in, is the current time, is the distance between the power line and the squall line; Potential impact assessment: combining the intensity of squall lines and the design tolerance of power lines , determine whether the squall line will cause damage to power lines: If If the squall line is too strong, an early warning will be issued. Otherwise, the changes of the squall line will continue to be monitored. The time it takes for the squall line to reach the area covered by the power lines The average value of radar reflectivity within the squall line area; Design tolerance of power lines It is expressed as: ； in, It is the maximum wind pressure or wind force considered during design. is the maximum load-bearing capacity of the power line material, is the model parameter that determines the relative impact of wind pressure on the design tolerance is the model parameter that determines the relative impact of the load-bearing capacity on the design tolerance, It is an index that adjusts the nonlinear effect of wind pressure and is determined by the corresponding power line design parameters; Warning signals are divided into different warning levels to reflect the severity of the weather event: ； in, Indicates the dynamic design tolerance of the power line; , , Represent the risk thresholds for red, orange and yellow warnings respectively.

9. A system for implementing the power line severe convection early warning method based on weather radar data as described in any one of claims 1 to 8, characterized in that: include: Radar system to obtain reflectivity grid data; The severe convective region assessment module is used to determine the severe convective region based on the reflectivity grid data, and to design complexity parameters to measure the structural complexity and spatial connectivity of the severe convective region, so as to reflect the organization of the convective system in the severe convective region and the potential severe convective weather risk; The squall line assessment module is used to assess whether a squall line is formed based on the spatial and temporal correlations between adjacent severe convective areas. Squall line movement trend analysis module, used to analyze the movement direction, movement speed and intensity changes of the squall line; The early warning analysis module is used to evaluate the impact of squall lines on power lines and issue early warnings based on the movement direction, speed and intensity changes of the squall lines.

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