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Microtopography icing value prediction method and system

A numerical prediction and micro-topography technology, applied in prediction, CAD numerical modeling, data processing applications, etc., can solve the problems of computational fluid models without considering physical processes and coarse resolution, and achieve good versatility and rationality Effect

Pending Publication Date: 2021-08-10
STATE GRID HUNAN ELECTRIC POWER +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a numerical prediction method and system for micro-terrain icing, which is used to solve the technical problem that the resolution of the traditional numerical prediction model is coarse and the calculation fluid model does not consider the defects of physical processes

Method used

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  • Microtopography icing value prediction method and system
  • Microtopography icing value prediction method and system
  • Microtopography icing value prediction method and system

Examples

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Embodiment 1

[0043] The micro terrain icing numerical prediction method of the present embodiment comprises the following steps:

[0044] (1) Micro terrain classification:

[0045] Determine the line tower section M that needs to be predicted. According to the high-precision digital elevation data, use ArcGIS to extract the ridge line and valley line within 10km around M as the center, and calculate the directions of the ridge line and valley line closest to M Vectors H and L, and calculate the angle between the direction vector m of M and the two, and record it as θ H and θ L .

[0046]

[0047]

[0048] Sort the digital elevations in the 10km range around M from large to small, and obtain the sorted positions h1 and h2 of the altitudes of the towers on both sides of the M section, and set the threshold θ of the included angle α , θβ , satisfying 0α β α , h β , satisfying 0α β <100%, set the following classification identification table:

[0049] Table 1 Non-water body micro-to...

Embodiment 2

[0081] Taking a 500kV ice-covered micro-topography section as an example, the numerical prediction of micro-topography icing includes the following steps:

[0082] (1) Micro terrain classification:

[0083] Determine the line tower section M that needs to be predicted. According to the high-precision digital elevation data, use ArcGIS to extract the ridge line and valley line within 10km around M as the center, and calculate the directions of the ridge line and valley line closest to M Vectors H and L, and calculate the angle between the direction vector m of M and the two, and record it as θ H = π / 3 and θ L = π / 3.

[0084] Sort the digital elevations in the 10km range around M from large to small, and obtain the sorted positions of 85% and 90% of the altitude of the towers on both sides of the M section, and set the threshold of the included angle θ α = π / 12, θ β =5π / 12, satisfying 0α β α = 20%, h β =80%, satisfy 0α β <100%, meet the micro-topography of the pass accordin...

Embodiment 3

[0101] Taking a 220kV ice-covered micro-topography section as an example, the numerical prediction of micro-topography icing includes the following steps:

[0102] (1) Micro terrain classification:

[0103]Determine the line tower section M that needs to be predicted. According to the high-precision digital elevation data, use ArcGIS to extract the ridge line and valley line within 10km around M as the center, and calculate the directions of the ridge line and valley line closest to M Vectors H and L, and calculate the angle between the direction vector m of M and the two, and record it as θ H = π / 15 and θ L = π / 15.

[0104] Sort the digital elevations in the 10km range around M from large to small, and obtain the sorted positions of 85% and 90% of the altitude of the towers on both sides of the M section, and set the threshold of the included angle θ α = π / 12, θ β =5π / 12, satisfying 0α β α = 20%, h β =80%, satisfy 0α β <100%, meet the micro-topography of the pass accordi...

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Abstract

The invention discloses a microtopography icing value prediction method and system. The method comprises the steps: carrying out the classification of microtopography according to the elevation data of a to-be-predicted line tower section and the surroundings of the to-be-predicted line tower section; the classification comprises water body microtopography and non-water body microtopography, and the non-water body microtopography comprises canyons, terrain uplifts, bealocks and high mountains; according to the type of the microtopography, calculating a numerical calculation result of the area with the kilometer-level resolution by adopting a corresponding numerical mode and a parameter scheme, and then interpolating the numerical calculation result of the kilometer-level resolution into the transition layer to extract an initial field and a boundary field of calculation of the microtopography layer; according to the calculated initial field and boundary field, calculating physical parameters of the microtopographic layer; According to the icing model corresponding to the microtopography type, inputting physical parameters of the microtopography layer to obtain the icing thickness under the microtopography of the corresponding type. According to the method, kilometer-level numerical calculation and fluid calculation are combined, and accurate prediction of micro-terrain icing is achieved.

Description

technical field [0001] The invention relates to the technical field of power grid protection, in particular to a numerical prediction method and system for micro-terrain icing. Background technique [0002] In the context of global warming, the probability of ice disasters in the global power grid is increasing, and the ice coverage is increasing, and non-traditional ice-covered areas around the world are beginning to have serious ice-covered areas. Since the anti-icing level of power grids in non-traditional ice-covered areas is often low, once ice is covered, the loss will be more serious. For example: In February 2021, the Texas power grid in the non-iced area of ​​the United States encountered a rare freezing disaster, and more than 4 million users lost power, causing huge losses. In 2020, lines in North China and Northeast China will be severely iced. Among them, about 1.7 million users in Jilin will lose power, and nearly 3 million people in Changchun will be seriousl...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06F30/20G06F111/10
CPCG06Q10/04G06F30/20G06F2111/10Y02A90/10
Inventor 冯涛徐勋建蔡泽林郭俊李丽邸悦伦叶钰简洲
Owner STATE GRID HUNAN ELECTRIC POWER
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