Method, system, processor and storage medium for determining dancing prediction results

Abstract

The present invention relates to the field of power grids, and discloses a method, system, processor and storage medium for determining a galloping prediction result. The method for determining a galloping prediction result comprises: obtaining a mesoscale meteorological prediction result of a to-be-predicted area on the day; matching the mesoscale meteorological prediction result with a pre-stored circulation situation database to determine the circulation situation of the to-be-predicted area in a preset time period in the future; matching the circulation situation and the mesoscale meteorological prediction result with a pre-stored micro-topography meteorological database to determine the meteorological data of the micro-topography of the to-be-predicted area; matching the meteorological data with a pre-stored line icing database to determine the icing data of the micro-topography; matching the meteorological data, icing data and line characteristics of the transmission line of the micro-topography with a pre-stored line galloping amplitude database to obtain the galloping prediction result of the transmission line of the micro-topography. The present invention can realize the rapid prediction of the galloping result of the micro-topography area.

Description

Technical Field

[0001] The present invention relates to the field of power grids, and in particular to a method, system, processor and storage medium for determining a galloping prediction result. Background Art

[0002] Ice-covered transmission lines are very prone to dancing under strong wind conditions, which can easily cause line tripping, hardware damage, and even tower collapse and disconnection. Microtopography refers to local small-scale terrain (for example, within a few hundred meters) that is very different from large-scale terrain (for example, several thousand meters). Since microtopography dancing mostly occurs between one or several levels of the line, the minimum scale is only tens of meters, and the wind speed and temperature in the microtopography area are affected by the terrain, the microtopography dancing prediction results are very different from those in the large-scale area. Therefore, it is necessary to carry out microtopography regional dancing prediction calculations, among which the small-scale large eddy model is one of the most commonly used modes for microtopography regional calculations. The large eddy model can handle small-scale surface non-uniformity well, with a resolution of 1-30 meters, and can provide more realistic surface meteorological conditions. However, the large eddy model can only simulate and calculate an area of ​​about 1-3km each time, and has high requirements for hardware conditions such as computer speed and memory. If large eddy simulations are carried out on all microtopography areas in each prediction calculation, the computing platform requirements are very high, and its computing speed is difficult to meet the prediction business needs. Therefore, how to achieve rapid prediction of dancing results in micro-topography areas is an urgent problem to be solved. Summary of the invention

[0003] The purpose of the embodiments of the present invention is to provide a method, system, processor and storage medium for determining a galloping prediction result, so as to achieve a rapid prediction of the galloping result of a micro-topography area.

[0004] In order to achieve the above object, the present invention provides a method for determining a dancing prediction result in a first aspect, the method comprising:

[0005] Obtain the mesoscale meteorological forecast results for the area to be predicted on that day;

[0006] Matching the mesoscale meteorological forecast results with the pre-stored circulation situation database to determine the circulation situation of the area to be predicted within a preset time period in the future;

[0007] Match the circulation situation and mesoscale meteorological forecast results with the pre-stored micro-topography meteorological database to determine the meteorological data of the micro-topography in the area to be predicted;

[0008] Matching the meteorological data with the pre-stored line icing database to determine the icing data of the micro-topography;

[0009] Meteorological data, ice cover data, and line characteristics of the micro-topography power transmission line are matched with a pre-stored line galloping amplitude database to obtain a galloping prediction result of the micro-topography power transmission line.

[0010] In an embodiment of the present invention, obtaining the circulation situation database includes: obtaining historical circulation situation data of the area to be predicted within a preset time interval; and performing cluster analysis on the historical circulation situation data to obtain the circulation situation database.

[0011] In an embodiment of the present invention, cluster analysis is performed on historical circulation situation data to obtain a circulation situation database, including: determining the distance between historical circulation situation data; dividing historical circulation situation data whose distance is less than or equal to a first preset threshold into the same class; determining the distance between each class; and merging the classes when the distance between the classes is less than or equal to a second preset threshold until the distance between the classes is greater than the second preset threshold.

[0012] In the embodiment of the present invention, determining the distance between each class includes: determining the average value of the historical circulation situation data of each class; and determining the distance between each average value to obtain the distance between each class.

[0013] In an embodiment of the present invention, obtaining a micro-topography meteorological database includes: obtaining the type of micro-topography in the area to be predicted; and obtaining a micro-topography meteorological database based on the type and historical circulation situation data based on the mesoscale meteorological model and the large eddy model.

[0014] In an embodiment of the present invention, obtaining the line icing database includes: obtaining the line icing database according to the micro-topography meteorological database through climate simulation experiments and / or an icing growth model.

[0015] In an embodiment of the present invention, obtaining the line galloping amplitude database includes: obtaining the line galloping amplitude database according to the micro-topography meteorological database, the line icing database and the line characteristics of the transmission line through a galloping amplitude prediction simulation experiment of a galloping simulation platform.

[0016] A second aspect of the present invention provides a processor configured to execute the above method for determining a dancing prediction result.

[0017] A third aspect of the present invention provides a system for determining a dancing prediction result, comprising: a processor according to the above.

[0018] A fourth aspect of the present invention provides a machine-readable storage medium, on which instructions are stored. When the instructions are executed by a processor, the processor executes the method for determining a dancing prediction result as described above.

[0019] The above technical solution obtains the mesoscale meteorological forecast results of the area to be predicted on the same day, and matches the mesoscale meteorological forecast results with the pre-stored circulation situation database to determine the circulation situation of the area to be predicted in the future preset time period, thereby matching the circulation situation and the mesoscale meteorological forecast results with the pre-stored micro-topography meteorological database to determine the meteorological data of the micro-topography of the area to be predicted, and further matches the meteorological data with the pre-stored line icing database to determine the icing data of the micro-topography, and matches the meteorological data, icing data, and line characteristics of the micro-topography transmission line with the pre-stored line dancing amplitude database to obtain the dancing prediction results of the micro-topography transmission line. The above scheme establishes the circulation situation database, micro-topography meteorological database, line icing database and line dancing amplitude database in advance. When the dancing prediction results are needed, the dancing prediction results of the micro-topography transmission line in the area to be predicted can be obtained according to the mesoscale meteorological forecast results of the area to be predicted on the same day and the above database, thereby avoiding the time required for real-time calculation, improving the prediction efficiency, and realizing the rapid prediction of the dancing results of the micro-topography area.

[0020] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0022] Figure 1 The flowchart of the method for determining the dancing prediction result in one embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0023] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0024] Figure 1 The flowchart of the method for determining the dancing prediction result in one embodiment of the present invention is schematically shown. Figure 1 As shown, in an embodiment of the present invention, a method for determining a dancing prediction result is provided. Taking the method applied to a processor as an example for explanation, the method may include the following steps:

[0025] Step S102, obtaining the mesoscale meteorological forecast result for the area to be predicted on that day.

[0026] It can be understood that mesoscale meteorology, or mesoscale climate, refers to climate phenomena with a horizontal scale of tens to hundreds of kilometers and a time scale of several hours to dozens of hours. According to its nature, it is divided into mesoscale convective climate and mesoscale stability climate. Among them, mesoscale convective climate includes thunderstorms, short-term heavy rainfall, hail, thunderstorms, tornadoes, and downbursts, etc. It is caused by the mesoscale climate system formed by the interaction of various physical conditions in a certain large-scale circulation background. The subjective analysis of mesoscale convective climate is to use various high-altitude and ground observation data, remote sensing detection data such as radar and satellites, numerical analysis and forecast products and other data to analyze the mesoscale convective system that produces mesoscale convective climate and the environmental field conditions for its occurrence and development. The mesoscale meteorological forecast result is the weather forecast.

[0027] The area to be predicted is the area or range where the transmission line galloping prediction result needs to be obtained.

[0028] Specifically, the processor can obtain the mesoscale meteorological forecast results for the area to be predicted on that day, that is, obtain the weather forecast for the area to be predicted on that day, which can be obtained through user input or sent by the meteorological forecast platform.

[0029] Step S104, matching the mesoscale meteorological forecast result with the pre-stored circulation situation database to determine the circulation situation of the area to be predicted within a preset time period in the future.

[0030] It can be understood that the future preset time period is a certain time period in the future, such as the next three days or the next five days. The circulation situation database is a pre-established historical database about the circulation situation. The circulation situation is the comprehensive characteristics of multiple circulation factors. Atmospheric circulation refers to the atmospheric movement conditions on a global scale, mainly including long-wave and ultra-long-wave troughs and ridges, planetary fronts and jet streams, blocking high pressure, polar vortex, subtropical high and other planetary-scale weather systems. The basic state of atmospheric circulation, commonly known as the weather system, is the circulation background for various weather processes to occur. Under a circulation situation with certain characteristics, a certain type of weather system is generated, a specific weather process prevails, and corresponding weather conditions occur. Therefore, weather forecasting must start with the analysis of the circulation situation and be based on the forecast of the circulation situation.

[0031] Specifically, the processor can match the mesoscale meteorological forecast results of the area to be predicted on the day with the pre-stored circulation situation database to determine the circulation situation of the area to be predicted within a preset time period in the future (for example, the next three days). That is to say, based on the weather forecast results of the day and the circulation situation database, determine the type of circulation situation in a certain time period in the future.

[0032] Step S106, matching the circulation situation and the mesoscale meteorological forecast results with the pre-stored micro-topography meteorological database to determine the meteorological data of the micro-topography of the area to be predicted.

[0033] It can be understood that the micro-topography meteorological database is a pre-established historical database including meteorological characteristics of various micro-topography. Meteorological data is meteorological characteristics, and meteorological data may include but is not limited to characteristic data such as temperature, wind speed, wind direction, and humidity.

[0034] Specifically, the processor can match the circulation situation of the area to be predicted in a preset time period in the future, the mesoscale meteorological forecast results of the area to be predicted on the day, and the pre-stored micro-topography meteorological database to obtain the meteorological data of the micro-topography of the area to be predicted.

[0035] Step S108, matching the meteorological data with the pre-stored line icing database to determine the icing data of the micro-topography.

[0036] It can be understood that the line icing database is a pre-established historical database of ice thickness and shape of transmission lines. The icing data may include but is not limited to ice thickness and shape.

[0037] Specifically, the processor may match the meteorological data of the micro-topography of the area to be predicted with the pre-stored line icing database to determine the icing data of the micro-topography of the area to be predicted.

[0038] Step S110, matching meteorological data, ice cover data, and line characteristics of the micro-topography power transmission line with a pre-stored line galloping amplitude database to obtain a galloping prediction result of the micro-topography power transmission line.

[0039] It can be understood that the line characteristics of the power transmission line are pre-set and stored data such as line structure. The line galloping amplitude database is a pre-established historical database of the galloping amplitude of the power transmission line. The galloping prediction result is the prediction result of the galloping amplitude of the power transmission line.

[0040] Specifically, the processor may match meteorological data, ice cover data, line characteristics of the micro-topography power transmission line with a pre-stored line galloping amplitude database to obtain a galloping prediction result of the micro-topography power transmission line.

[0041] The above method for determining the dancing prediction result obtains the mesoscale meteorological prediction result of the area to be predicted on the day, and matches the mesoscale meteorological prediction result with the pre-stored circulation situation database to determine the circulation situation of the area to be predicted in the future preset time period, thereby matching the circulation situation and the mesoscale meteorological prediction result with the pre-stored micro-topography meteorological database to determine the meteorological data of the micro-topography of the area to be predicted, further matching the meteorological data with the pre-stored line icing database to determine the icing data of the micro-topography, matching the meteorological data, icing data, and line characteristics of the micro-topography transmission line with the pre-stored line dancing amplitude database to obtain the dancing prediction result of the micro-topography transmission line. The above scheme establishes the circulation situation database, micro-topography meteorological database, line icing database and line dancing amplitude database in advance. When the dancing prediction result is needed, the dancing prediction result of the micro-topography transmission line in the area to be predicted can be obtained according to the mesoscale meteorological prediction result of the area to be predicted on the day and the above database, thereby avoiding the time required for real-time calculation, improving the prediction efficiency, and realizing the rapid prediction of the dancing result of the micro-topography area.

[0042] In one embodiment, obtaining the circulation situation database includes: obtaining historical circulation situation data of the area to be predicted within a preset time interval; and performing cluster analysis on the historical circulation situation data to obtain the circulation situation database.

[0043] It can be understood that the preset time interval is the winter of a certain period of time in the past, such as the winter of the past five years, and the winter can be, for example, November of the first year to March of the second year.

[0044] Specifically, the processor can obtain historical circulation situation data of the area to be predicted within a preset time interval (for example, the winters of the past ten years), and then use a clustering analysis method to perform cluster analysis on the historical circulation situation data, divide the typical weather situation types, and obtain a circulation situation database.

[0045] In one embodiment, cluster analysis is performed on historical circulation situation data to obtain a circulation situation database, including: determining the distance between historical circulation situation data; dividing historical circulation situation data whose distance is less than or equal to a first preset threshold into the same class; determining the distance between each class; and merging the classes when the distance between the classes is less than or equal to a second preset threshold until the distance between the classes is greater than the second preset threshold.

[0046] It can be understood that the cluster analysis method is to digitally classify different samples, quantitatively determine the closeness and distance between samples, and divide them into different types. The first preset threshold is the distance benchmark between each historical circulation situation data. If the distance between two historical circulation situation data is less than or equal to the first preset threshold, the two historical circulation situation data can be divided into one class, otherwise they are divided into different classes. The second preset threshold is the distance benchmark between each class. If the distance between two classes is less than or equal to the second preset threshold, the classes can be merged into a new class, otherwise they are still two different classes.

[0047] Specifically, the daily winter circulation situation data of the predicted area in the past ten years are first regarded as a class. Taking November 1st to March 31st as an example, there are 1510 samples in the past ten winters, with a total of 1510 classes. Then, the distance between samples and the distance between classes are specified, and the smallest distance is selected to form a new class. The distance between the new class and other classes is calculated, and then the two classes with close distances are merged. Repeat until the distance between each class is greater than the set distance between classes. Clustering is completed, and a total of 1510 samples are divided into k classes: B = {b1, b2..., bk}, where bx represents each typical circulation situation data.

[0048] In one embodiment, determining the distance between each class includes: determining the average value of the historical circulation situation data of each class; and determining the distance between each average value to obtain the distance between each class.

[0049] Specifically, when the distance between each class needs to be calculated, the average value of the historical circulation situation data in each class can be determined first, and then the distance between each average value can be determined, thereby obtaining the distance between each class.

[0050] In one embodiment, obtaining the micro-topography meteorological database includes: obtaining the type of micro-topography in the area to be predicted; and obtaining the micro-topography meteorological database based on the type and historical circulation situation data based on the mesoscale meteorological model and the large eddy model.

[0051] It can be understood that the types of various micro-topography may include but are not limited to passes, canyons, mountains, independent hills, windward slopes, water bodies, etc. The mesoscale meteorological model and the large eddy model, namely the WRF-LES coupling model, the WRF-LES coupling model can adopt 6 layers of nesting, the mesoscale model adopts three layers of nesting, and three small-scale simulation areas are designed inside the mesoscale area for large eddy simulation. The mesoscale meteorological model (WRF) can capture mesoscale processes, but its resolution is limited, generally not less than 1 km, so it cannot characterize small-scale surface heterogeneity (especially complex terrain) and small-scale meteorological processes. The large eddy model (LES) can handle small-scale surface heterogeneity well, has a smaller resolution, and gives more realistic surface fluxes and large eddy motion processes.

[0052] Specifically, the processor can obtain the type of micro-topography of the area to be predicted, and based on the mesoscale meteorological model and the large eddy model, obtain a micro-topography meteorological database according to the type of the micro-topography and the historical circulation situation data. In other words, the mesoscale meteorological-large eddy model can be used to simulate the refined meteorological conditions of various typical micro-topography areas under various typical circulation conditions, obtain the distribution characteristics of temperature, wind speed, wind direction, humidity, etc. of the micro-topography area under different mesoscale meteorological numerical forecast results, and establish a database of refined meteorological conditions of typical micro-topography areas under typical circulation conditions.

[0053] In one embodiment, obtaining the line icing database includes: obtaining the line icing database according to the micro-topography meteorological database through climate simulation experiments and / or an icing growth model.

[0054] Specifically, the processor can obtain a line icing database based on the micro-topography meteorological database through climate simulation experiments and / or ice growth models. That is to say, simulation experiments based on artificial climate chamber simulation results and / or ice growth models can be carried out to establish a large database of ice thickness and shape of transmission lines under different temperature, wind speed, wind direction and humidity conditions in the micro-topography area.

[0055] In one embodiment, obtaining the line galloping amplitude database includes: obtaining the line galloping amplitude database according to the micro-topography meteorological database, the line icing database and the line characteristics of the transmission line through a galloping amplitude prediction simulation experiment of a galloping simulation platform.

[0056] Specifically, the processor can obtain the line dancing amplitude database according to the micro-topography meteorological database, the line icing database and the line characteristics of the transmission line through the dancing amplitude prediction simulation experiment of the dancing simulation platform. That is to say, a dancing prediction amplitude simulation experiment based on the dancing simulation platform can be carried out to establish a line dancing amplitude database under different temperature, wind speed, wind direction, ice thickness, ice shape and line structure conditions.

[0057] In a specific embodiment, the method for determining the dancing prediction result may include the following steps:

[0058] (1) Collection and collation of basic data

[0059] Determine the scope of the prediction area and collect all the dancing micro-topography areas in the prediction area, including micro-topography location and terrain data, typical micro-topography types, micro-topography area lines and tower information. Typical micro-topography type A = {a 1 ,a 2 ,..a m}, where m represents m types of typical micro-topography. Currently, the common typical micro-topography types mainly include passes, canyons, high mountains, independent hills, windward slopes, water bodies, etc.

[0060] The winter circulation situation data of the forecast area in the past ten years were collected, and the typical weather situation types were divided using cluster analysis methods to establish a typical circulation situation database.

[0061] The cluster analysis method is to use mathematical methods to digitally classify different samples, quantitatively determine the closeness and distance between samples, and divide them into different types. First, the daily winter circulation situation data of the forecast area in the past ten years are regarded as one category. Taking November 1st to March 31st as an example, there are 1510 samples in the past ten winters, and there are 1510 categories in total; then the distance between samples and the distance between classes are specified, and the smallest distance is selected to form a new class, and the distance between the new class and other classes is calculated. Then the two classes with close distances are merged, and the process is repeated until the distance between each class is greater than the set distance between classes. Clustering is completed, and a total of 1510 samples are divided into k categories: B = {b 1 ,b 2 ...,b k}, where b x Represents data for each typical circulation situation.

[0062] (2) A database of micro-topographic regional meteorological conditions based on the simulation of the mesoscale meteorological model and the large eddy model

[0063] The mesoscale meteorological-large eddy model is used to simulate the refined meteorological conditions of various typical micro-topography areas under various typical circulation situations. The distribution characteristics of temperature, wind speed, wind direction, humidity and other characteristics of micro-topography areas under different mesoscale meteorological numerical forecast results are obtained, and a database C of refined meteorological conditions of typical micro-topography areas under typical circulation situations is established.

[0064]

[0065] (3) Line icing database based on icing growth model

[0066] Carry out X based on the simulation results of artificial climate chamber 1 and / or ice growth model X 2 Through simulation experiments, a large database D of ice thickness and shape of transmission lines under different temperature, wind speed, wind direction and humidity conditions in micro-topography areas is established.

[0067]

[0068] (4) A large database of line vibration amplitude based on vibration simulation experiments

[0069] Conduct a simulation test of the predicted dancing amplitude based on the dancing simulation platform, and establish a line dancing amplitude database E under different temperatures, wind speeds, wind directions, ice thicknesses, ice shapes, and line structure conditions (i.e., L in the following formula).

[0070]

[0071] (5) Rapid prediction and calculation of micro-topography regional sway based on big data

[0072] According to the daily mesoscale meteorological data forecast results, match them with the typical circulation situation database B to determine the typical circulation situation b in the next three days x According to the typical circulation situation and the predicted mesoscale meteorological conditions, the meteorological conditions database C under the typical circulation situation in the typical micro-topography area is matched to determine the refined temperature, wind speed, wind direction, humidity and other meteorological conditions c in the typical micro-topography area x According to the refined meteorological conditions of the micro-topography area, match it with the large ice database D of the line based on the ice growth model to determine the ice thickness and shape d in the micro-topography area x According to the refined meteorological conditions, icing conditions, and line structure conditions of typical micro-topography areas, they are matched with the line vibration amplitude database E to quickly obtain the micro-topography area vibration prediction result e x , and can be displayed through visual methods such as pictures, texts, and warning texts.

[0073] Therefore, the method for determining the dancing prediction results provided in the embodiment of the present invention uses big data to establish a historical database. Each time the dancing prediction of the micro-topography area is performed, the prediction results can be obtained by quickly matching with the database, thereby quickly obtaining the dancing prediction results of the micro-topography area.

[0074] An embodiment of the present invention provides a processor configured to execute the method for determining a dancing prediction result according to the above embodiment.

[0075] An embodiment of the present invention provides a system for determining a dancing prediction result, comprising: a processor, wherein the processor is configured to: obtain a mesoscale meteorological forecast result for the day of the area to be predicted; match the mesoscale meteorological forecast result with a pre-stored circulation situation database to determine the circulation situation of the area to be predicted within a preset time period in the future; match the circulation situation and the mesoscale meteorological forecast result with a pre-stored micro-topography meteorological database to determine the meteorological data of the micro-topography of the area to be predicted; match the meteorological data with a pre-stored line icing database to determine the icing data of the micro-topography; match the meteorological data, icing data, and line characteristics of the transmission line of the micro-topography with a pre-stored line dancing amplitude database to obtain the dancing prediction result of the transmission line of the micro-topography.

[0076] The system for determining the dancing prediction result obtains the mesoscale meteorological prediction result of the area to be predicted on the day, and matches the mesoscale meteorological prediction result with the pre-stored circulation situation database to determine the circulation situation of the area to be predicted in the future preset time period, thereby matching the circulation situation and the mesoscale meteorological prediction result with the pre-stored micro-topography meteorological database to determine the meteorological data of the micro-topography of the area to be predicted, further matching the meteorological data with the pre-stored line icing database to determine the icing data of the micro-topography, matching the meteorological data, icing data, and line characteristics of the micro-topography transmission line with the pre-stored line dancing amplitude database to obtain the dancing prediction result of the micro-topography transmission line. The above scheme establishes the circulation situation database, micro-topography meteorological database, line icing database and line dancing amplitude database in advance. When the dancing prediction result is needed, the dancing prediction result of the micro-topography transmission line in the area to be predicted can be obtained according to the mesoscale meteorological prediction result of the area to be predicted on the day and the above database, thereby avoiding the time required for real-time calculation, improving the prediction efficiency, and realizing the rapid prediction of the dancing result of the micro-topography area.

[0077] In one embodiment, the processor is further configured to: obtain historical circulation situation data of the area to be predicted within a preset time interval; and perform cluster analysis on the historical circulation situation data to obtain a circulation situation database.

[0078] In one embodiment, the processor is further configured to: determine the distance between historical circulation situation data; classify historical circulation situation data whose distance is less than or equal to a first preset threshold into the same class; determine the distance between each class; and merge the classes when the distance between the classes is less than or equal to a second preset threshold until the distance between the classes is greater than the second preset threshold.

[0079] In one embodiment, the processor is further configured to: determine an average value of the historical circulation situation data of each class; and determine the distance between each average value to obtain the distance between each class.

[0080] In one embodiment, the processor is further configured to: obtain the type of micro-topography of the area to be predicted; and obtain a micro-topography meteorological database based on the type and historical circulation situation data based on the mesoscale meteorological model and the large eddy model.

[0081] In one embodiment, the processor is further configured to obtain a line icing database according to a micro-topography meteorological database through climate simulation experiments and / or an icing growth model.

[0082] In one embodiment, the processor is further configured to obtain a line dancing amplitude database according to a micro-topography meteorological database, a line icing database and line characteristics of the transmission line through a dancing amplitude prediction simulation experiment of a dancing simulation platform.

[0083] An embodiment of the present invention provides a machine-readable storage medium, on which instructions are stored. When the instructions are executed by a processor, the processor executes the method for determining a dancing prediction result according to the above embodiment.

[0084] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0085] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0086] 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.

[0087] 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 1The steps for the functions specified in one or more boxes.

[0088] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0089] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0090] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0091] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0092] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for determining a dancing prediction result, characterized in that: The method comprises: Obtain the mesoscale meteorological forecast results for the area to be predicted on that day; Matching the mesoscale meteorological forecast results with a pre-stored circulation situation database to determine the circulation situation of the area to be predicted within a preset time period in the future; Matching the circulation situation and the mesoscale meteorological forecast results with a pre-stored micro-topography meteorological database to determine the meteorological data of the micro-topography of the area to be predicted; Matching the meteorological data with a pre-stored line icing database to determine icing data of the micro-topography; The meteorological data, the ice cover data, the line characteristics of the power transmission line of the micro-topography are matched with a pre-stored line galloping amplitude database to obtain a galloping prediction result of the power transmission line of the micro-topography.

2. The method according to claim 1, characterized in that The acquisition of the circulation situation database includes: Acquire historical circulation situation data of the area to be predicted within a preset time interval; Cluster analysis is performed on the historical circulation situation data to obtain the circulation situation database.

3. The method according to claim 2, characterized in that The cluster analysis of the historical circulation situation data to obtain the circulation situation database includes: Determining the distance between the historical circulation situation data; Classify the historical circulation situation data whose distance is less than or equal to the first preset threshold into the same class; Determine the distance between each cluster; When the distance between the classes is less than or equal to a second preset threshold, the classes are merged until the distance between the classes is greater than the second preset threshold.

4. The method according to claim 3, characterized in that: Determining the distance between each class includes: Determining an average of the historical circulation situation data for each of the said classes; The distances between the respective mean values ​​are determined to obtain the distances between the respective classes.

5. The method according to claim 2, characterized in that: The micro-topography meteorological database is obtained by: Obtaining the type of micro-topography of the area to be predicted; Based on the mesoscale meteorological model and the large eddy model, the micro-topography meteorological database is obtained according to the type and the historical circulation situation data.

6. The method according to claim 1, characterized in that The line icing database is obtained by: The line icing database is obtained according to the micro-topography meteorological database through climate simulation experiments and / or icing growth models.

7. The method according to claim 1, characterized in that The acquisition of the line dancing amplitude database includes: Through the dancing amplitude prediction simulation experiment of the dancing simulation platform, the line dancing amplitude database is obtained according to the micro-topography meteorological database, the line icing database and the line characteristics of the transmission line.

8. A processor, characterized in that: The method is configured to perform the method for determining a galloping prediction result according to any one of claims 1 to 7.

9. A system for determining a dancing prediction result, characterized in that: include: A processor according to claim 8.

10. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is caused to perform the method for determining a dancing prediction result according to any one of claims 1 to 7.

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