CN107330189B - Method and system for layered and refined prediction of adjacent grid temperature - Google Patents

Method and system for layered and refined prediction of adjacent grid temperature Download PDF

Info

Publication number
CN107330189B
CN107330189B CN201710519880.7A CN201710519880A CN107330189B CN 107330189 B CN107330189 B CN 107330189B CN 201710519880 A CN201710519880 A CN 201710519880A CN 107330189 B CN107330189 B CN 107330189B
Authority
CN
China
Prior art keywords
point
temperature
analyzed
grid
vertical
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201710519880.7A
Other languages
Chinese (zh)
Other versions
CN107330189A (en
Inventor
陆佳政
冯涛
李波
方针
徐勋建
杨莉
郭俊
李丽
邸悦伦
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Corp of China SGCC
State Grid Hunan Electric Power Co Ltd
Disaster Prevention and Mitigation Center of State Grid Hunan Electric Power Co Ltd
Original Assignee
State Grid Corp of China SGCC
State Grid Hunan Electric Power Co Ltd
Disaster Prevention and Mitigation Center of State Grid Hunan Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by State Grid Corp of China SGCC, State Grid Hunan Electric Power Co Ltd, Disaster Prevention and Mitigation Center of State Grid Hunan Electric Power Co Ltd filed Critical State Grid Corp of China SGCC
Priority to CN201710519880.7A priority Critical patent/CN107330189B/en
Publication of CN107330189A publication Critical patent/CN107330189A/en
Application granted granted Critical
Publication of CN107330189B publication Critical patent/CN107330189B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/08—Thermal analysis or thermal optimisation

Abstract

The invention relates to the field of power transmission line equipment maintenance, and discloses a method and a system for predicting the temperature of an adjacent grid in a layered and refined manner so as to improve the vertical temperature resolution of an easily-dancing point, and the method and the system are high in accuracy and high in calculation speed and wide in range. Firstly, calculating the temperature of the ground altitude of the dance point to be analyzed in the vertical direction of the adjacent grid points in the corresponding series of grids according to the ground temperature reduction rate and related temperature data, and then calculating the temperature of the ground altitude of the dance point to be analyzed by a bilinear interpolation method according to the calculated value of each temperature; meanwhile, according to the vertical temperature reduction rate between any adjacent grids of the associated grid points, the vertical temperature reduction rate between the adjacent grids corresponding to the galloping point to be analyzed is calculated by a weighted average method; and finally, calculating the temperature data of each correspondingly subdivided layer according to the temperature of the ground altitude of the dancing point to be analyzed and the vertical temperature reduction rate between every two adjacent grids.

Description

Method and system for layered and refined prediction of adjacent grid temperature
Technical Field
The invention relates to the field of power transmission line equipment maintenance, in particular to a method and a system for layered and refined prediction of adjacent grid temperature.
Background
In recent years, the scale of a power grid is rapidly enlarged, a power transmission line inevitably passes through an ice-coated and easily-waved area, the problems of hardware damage, wire breakage and the like caused by ice-coated waving are solved, a tower collapse phenomenon is caused in the serious case, and the safe operation of the power grid is seriously threatened.
Along with global climate change, various disasters frequently occur, the problem of power grid icing galloping is increasingly prominent, the rapid development of an icing galloping prediction technology is promoted, the power grid icing galloping prediction is converted into numerical prediction in a larger area range from traditional small-range experience prediction, however, researches show that the power grid icing galloping often occurs under a light ice condition, and the calculation of light ice not only provides higher refined prediction requirements for the ground, but also for the temperature of high altitude; at present, temperature is forecasted by a numerical mode on a regular grid point, however, in an actual situation, distribution of points, which are easy to wave and covered by ice, of a power grid is dispersed and is often located in the regular grid, and for the calculation of the discrete non-grid point, the numerical mode is difficult to be completely applicable and needs to be calculated in an interpolation mode. The traditional temperature refinement interpolation mainly adopts a statistical method, and does not consider the physical law of vertical temperature change, so that errors exist in a calculation result.
Therefore, under the physical process of considering the vertical decreasing of the temperature, the refinement of the temperature numerical prediction result is very important, and the method and the system for carrying out layered refinement prediction on the temperature of the adjacent grid are needed to be provided.
Disclosure of Invention
The invention aims to provide a method and a system for layered and refined prediction of the temperature of an adjacent grid, which are used for carrying out refined calculation on the vertical temperature of an icing and easily-waving point, greatly improve the vertical temperature resolution of the icing and easily-waving point, have high accuracy and high calculation speed and wide range, accord with the physical change rule of the vertical temperature, and provide powerful scientific support for refined prediction of the icing and waving of a power grid and guarantee of safe operation of the power grid.
In order to achieve the purpose, the invention discloses a method for predicting the temperature layering and refining of an adjacent grid, which comprises the following steps:
determining a calculation grid of the three-dimensional temperature field, calculating temperature data of grid points of each grid in the three-dimensional temperature field based on a meteorological WRF numerical mode, and calculating a vertical temperature reduction rate between adjacent grids in the vertical direction; wherein, the horizontal plane of the grid represents longitude and latitude, and the vertical direction represents altitude;
determining a series of related grids in the vertical direction according to the longitude and latitude of the dancing point to be analyzed, and carrying out homogenization layering on the series of grids, wherein the grid height in the vertical direction is delta z, the layer height in the vertical direction is delta 1, and delta z/delta 1 is an integer greater than or equal to 2;
calculating the temperature of the ground altitude of the waving point to be analyzed in the vertical direction of the adjacent grid points in the corresponding series of grids according to the ground temperature reduction rate and the related temperature data, and then calculating the temperature of the ground altitude of the waving point to be analyzed by a bilinear interpolation method according to the calculated value of each temperature; meanwhile, according to the vertical temperature reduction rate between any delta z of the associated lattice points, calculating the vertical temperature reduction rate between the same delta z of the waving points to be analyzed by a weighted average method;
and calculating the temperature data of each layer corresponding to the delta 1 according to the temperature of the ground altitude of the dancing point to be analyzed and the vertical temperature reduction rate between the delta z.
In order to achieve the above object, the present invention discloses a system for predicting temperature stratification of neighboring grids in a hierarchical manner, comprising:
the first calculation unit: the calculation grid is used for determining a three-dimensional temperature field, calculating temperature data of grid points of each grid in the three-dimensional temperature field based on a meteorological WRF numerical mode, and calculating a vertical temperature reduction rate between adjacent grids in the vertical direction; wherein, the horizontal plane of the grid represents longitude and latitude, and the vertical direction represents altitude;
a second calculation unit: the system comprises a vertical grid, a horizontal grid, a vertical grid and a vertical grid, wherein the vertical grid is connected with the horizontal grid through a connecting line, the vertical grid is connected with the vertical grid through the connecting line;
a third calculation unit: the system is used for calculating the temperature of the ground altitude of the waving point to be analyzed in the vertical direction of the adjacent grid points in the corresponding series of grids according to the ground temperature reduction rate and the related temperature data, and then calculating the temperature of the ground altitude of the waving point to be analyzed by a bilinear interpolation method according to the calculated value of each temperature; meanwhile, according to the vertical temperature reduction rate between any delta z of the associated lattice points, calculating the vertical temperature reduction rate between the same delta z of the waving points to be analyzed by a weighted average method;
a fourth calculation unit: and the method is used for calculating the temperature data of each layer corresponding to the delta 1 according to the temperature of the ground altitude of the dancing point to be analyzed and the vertical temperature reduction rate between the delta z.
The invention has the following beneficial effects:
the method and the system determine the related series of grids in the vertical direction according to the longitude and latitude of the waving point to be analyzed, uniformly layer the series of grids, consider the physical law of vertical change of temperature, greatly improve the vertical temperature resolution of the waving point, have high accuracy and wide calculation speed range, and provide powerful scientific support for finely predicting the icing waving of the power grid and ensuring the safe operation of the power grid.
Detailed Description
The following detailed description of embodiments of the invention, but the invention can be practiced in many different ways, as defined and covered by the claims.
Example 1
The embodiment discloses a method for layered and refined prediction of adjacent grid temperature, which comprises the following steps:
determining a calculation grid of the three-dimensional temperature field, calculating temperature data of grid points of each grid in the three-dimensional temperature field based on a meteorological WRF numerical mode, and calculating a vertical temperature reduction rate between adjacent grids in the vertical direction; wherein, the horizontal plane of the grid represents longitude and latitude, and the vertical direction represents altitude;
determining a series of related grids in the vertical direction according to the longitude and latitude of the dancing point to be analyzed, and carrying out homogenization layering on the series of grids, wherein the grid height in the vertical direction is delta z, the layer height in the vertical direction is delta 1, and delta z/delta l is an integer greater than or equal to 2;
calculating the temperature of the ground altitude of the waving point to be analyzed in the vertical direction of the adjacent grid points in the corresponding series of grids according to the ground temperature reduction rate and the related temperature data, and then calculating the temperature of the ground altitude of the waving point to be analyzed by a bilinear interpolation method according to the calculated value of each temperature; meanwhile, according to the vertical temperature reduction rate between any delta z of the associated lattice points, calculating the vertical temperature reduction rate between the same delta z of the waving points to be analyzed by a weighted average method;
and calculating the temperature data of each layer corresponding to the delta 1 according to the temperature of the ground altitude of the dancing point to be analyzed and the vertical temperature reduction rate between the delta z.
As a preferred embodiment of the present embodiment, the calculating the temperature of the ground altitude of the dance point to be analyzed includes:
(1) and determining the ground altitude and the longitude and latitude of the four grid points of the calculation grid, and calculating the temperature of the ground altitude of the four grid points through a three-dimensional temperature field.
(2) Calculating the temperature of the ground altitude of the waving point to be analyzed in the vertical direction of the four lattice points:
Figure BDA0001336558540000031
in the formula (I), the compound is shown in the specification,
Figure BDA0001336558540000032
temperature T representing the ground altitude of the waving point to be analyzed in the vertical direction of the four grid points(i，j，1，t)、T(i+1，j，1，t)、T(i，j+1，1，t)、T(i+1，j+1，1，t)Temperature, r, representing the ground altitude for four grid points0Represents the ground temperature decrease rate, H(i，j)、H(i+1，j)、H(i，j+1)、H(i+1，j+1)Representing the ground elevation of four grid points.
(3) Calculating the temperature of the ground altitude of the dancing point to be analyzed:
Figure BDA0001336558540000033
in the formula, T(Q，t)The temperature of the ground altitude representing the point of oscillation to be analyzed,
Figure BDA0001336558540000034
the temperature of the ground altitude of the dance point to be analyzed corresponding to the vertical direction of the four lattice points is represented, X represents the longitude of the dance point to be analyzed, Y represents the latitude of the dance point to be analyzed, and Xi、Xi+1Longitude, Y, representing two of the four grid pointsj、Yi+1Representing the latitude of two of the four grid points.
Specifically, taking the temperature hierarchical refinement prediction of the waving point to be analyzed of a certain 220kV line in a certain area as an example, confirming that the space range of a calculation grid is T, the resolution of a horizontal grid is 30km, the corresponding longitude and latitude is 0.25 degrees by 0.25 degrees, the vertical resolution is 1km, the corresponding number of horizontal grids is 5 multiplied by 5, the number of vertical grids is 5, marking the waving point to be analyzed as Q, obtaining longitude and latitude coordinates (111.36 degrees E, 29.40 degrees N) of the waving point Q to be analyzed (hereinafter referred to as Q point), and dividing the vertical direction of the Q point into 5 layers according to the vertical resolution of the calculation grid,for example: the height delta z of the adjacent grids in the vertical direction is 1000m, and the height delta 1 of the layer after vertical subdivision is 200 m; the altitude of the point Q is 127m, the horizontal plane coordinates of four grid points of the computational grid are determined to be (111.25 ° E, 29.25 ° N), (111.50 ° E, 29.25 ° N), (111.25 ° E, 29.50 ° N), (111.50 ° E, 29.50 ° N), the corresponding ground points are respectively recorded as a, B, C, and D, and the ground altitudes of the four grid points are respectively recorded as H(i，j)，H(i+1，j)，H(i，j+1)，H(i+1，j+1)Identifying the ground altitude of four grid points as H: (i，j)：103m，H(i+1，j)：101m，H(i，j+1)：255m，H(i+1，j+1)：92m。
Calculating the three-dimensional temperature field T of the grid points by taking 20 days of 1 month, 27 months and 2015 as starting time and setting the time length to be 24 hours(i，j，k，t)Wherein i is 1 … 5, j is 1 … 5, k is 1 … 5, t is 24, specifically, the temperatures of the ground altitudes of the four grid points a, B, C and D are calculated to be-0.75 ℃, -0.69 ℃, -1.88 ℃ and-0.61 ℃ based on the weather WRF numerical model, wherein the temperatures of the ground altitudes of the four grid points a, B, C and D corresponding to the point Q are calculated according to the uniform ground temperature direct reduction rate and the temperature data calculated by the three-dimensional temperature field:
Figure BDA0001336558540000041
that is, the temperatures of the ground altitudes of the four grid points a, B, C and D corresponding to the point Q are: point a is-0.89 ℃, point B is-0.85 ℃, point C is-1.11 ℃ and point D is-0.82 ℃, it should be noted that a ground temperature decrease rate of 0.006 is a natural phenomenon (as a variation, a vertical temperature decrease rate r can be subsequently calculated for each relevant grid point(i，j，k，t)Replacing the value of the middle position closest to the ground instead of uniformly taking the value of 0.006), namely, the altitude is 1000m higher per liter, and the temperature is reduced by 0.006 ℃; then, the temperature of the ground altitude at the point Q is calculated by a bilinear interpolation method:
Figure BDA0001336558540000051
that is, the temperature of the ground elevation at point Q at 20 days 1, 28, 2015 was-0.93 ℃.
As a preferred embodiment of this embodiment, the calculating the vertical temperature directly decreasing rate of the dancing point to be analyzed includes:
(1) calculating the vertical temperature direct reduction rate between two adjacent grids in the vertical direction of the four grid points:
Figure BDA0001336558540000052
in the formula, r(i，j，k，t)Represents the vertical temperature direct reduction rate, T, between two adjacent grids in the vertical direction of four grid points(i，j，k，t)And T(i，j，k+1，t)The temperature of two adjacent grids is shown, and the Δ z represents the height difference of the two adjacent grids.
Further, calculating the direct temperature reduction rate r of two grid points adjacent to the four grid points A, B, C and D from bottom to topkThe results are shown in table 1 below (unit ℃/m):
TABLE 1 direct temperature reduction rate r of four grid points from bottom to topk
Lattice points A B C D
r1(0-1000m) 0.0039 0.0037 0.0038 0.0041
r2(1000-2000m) -0.0024 -0.0032 -0.0026 -0.0022
r3(2000-3000m) -0.0039 -0.0028 -0.0047 -0.0040
r4(3000-4000m) 0.0035 0.0028 0.0047 0.0015
r5(4000-5000m) 0.0020 0.0027 0.0011 0.0043
(2) Recording the four grid points as A, B, C, D respectively, recording the dance point to be analyzed as Q, and calculating the weight coefficients between the four grid points and the dance point to be analyzed:
Figure BDA0001336558540000053
Figure BDA0001336558540000054
Figure BDA0001336558540000055
Figure BDA0001336558540000056
in the formula, alpha1、α2、α3、α4Respectively representing A, B, C, D weight coefficients between the four grid points and the dance point to be analyzed,
Figure BDA0001336558540000062
is the distance from point a to point Q,
Figure BDA0001336558540000063
is the distance from point B to point Q,
Figure BDA0001336558540000064
is the distance from the point C to the point Q,
Figure BDA0001336558540000065
and calculating to obtain the weight coefficients between the four grid points A, B, C and D and the point Q as the distance from the point D to the point Q: alpha is alpha1：0.26，α2：0.29，α3：0.21，α4：0.24。
(3) Calculating the vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed:
rQ(k，t)＝α1r(i，j，k，t)+α2r(i+1，j，k，t)+α3r(i，j+1，k，t)+α4r(i+1，j+1，k，t)；
in the formula, rQ(k，t)Representing the phase of the point of dance to be analyzedDirect rate of decrease of direct temperature, alpha, between two adjacent grids1、α2、α3、α4Respectively representing the weight coefficients r between the four grid points and the dancing points to be analyzed(i，j，k，t)、r(i+1，j，k，t)、r(i，j+1k，t)、r(i+1，j+1，k，t)Respectively showing the vertical temperature reduction rate between two adjacent grids in the vertical direction of the four grid points.
Further, the vertical temperature reduction rate between two adjacent grids at the point Q is calculated by the weight coefficients between the four grids a, B, C and D and the point Q and the vertical temperature reduction rate between two adjacent grids in the vertical direction, and is shown in table 2 below:
TABLE 2 vertical temperature sag rates between two adjacent grids at Q-point
Layer height 0-1000m 1000-2000m 2000-3000m 3000-4000m 4000-5000m
Reduction Rate (. degree. C./m) -0.0039 0.0026 0.0037 -0.0031 -0.0026
As a preferred embodiment of this embodiment, the calculating the temperature of each layer in the vertical direction of the oscillation point to be analyzed includes:
TQ(k，t，p)＝TQ(k，t，p-1)+rQ(k，t)Δl；k＝1...h，t＝1...L，p＝1...Δz/Δl；
in the formula, TQ(k，t，p)Representing the temperature, r, of the layers in the direction perpendicular to the point of oscillation to be analyzedQ(k，t)The vertical temperature direct reduction rate between two adjacent grids of the galloping point to be analyzed is represented, delta l represents the layer height of the galloping point to be analyzed in the vertical direction, delta z/delta l represents the number of grid points between two adjacent layers of the galloping point to be analyzed in the vertical direction, k represents the number of layers, t represents the time, and p represents the p-th grid point.
Specifically, the temperature after Q point layering refinement is calculated according to the temperature of the Q point ground altitude and the vertical temperature reduction rate between two adjacent grids at Q point as shown in table 3 below:
TABLE 3 temperature after Q Point delamination and refinement
Figure BDA0001336558540000061
Figure BDA0001336558540000071
It should be noted that, in this embodiment, the dancing point to be analyzed is affected by wind speed and the like to generate self-excited vibration in the vertical direction, and in an actual situation, because the size of the calculation grid is far larger than the length of the ice-covered line, the movement ranges of the dancing point to be analyzed all fall into the same calculation grid, and the situation of crossing the calculation grid does not exist; in addition, when the dance point to be analyzed is located between two grid points in common of two adjacent grids, the grid on the north or west side of the two grids is preferably used as the calculation grid of the dance point to be analyzed based on the geographic position. In addition, when the waving point coincides with a certain grid point, the above formula is still applicable as a special case in a specific calculation process such as bilinear interpolation processing; or, when the position of the dancing point to be analyzed is at the lattice point position of the calculation grid, calculating the temperature of each layer in the vertical direction of the dancing point to be analyzed by the following steps:
(1) and confirming the position of the lattice point where the dancing point to be analyzed is located, and acquiring three-dimensional temperature field data of the series of lattice points in the vertical direction of the lattice point as the three-dimensional temperature field data of the dancing point to be analyzed.
(2) Calculating the vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed:
Figure BDA0001336558540000072
in the formula, rQ(i，j，k，t)Represents the vertical temperature direct reduction rate, T, between two adjacent grids of the waving point to be analyzed(i，j，k，t)And T(i，j，k+1，t)The temperature of two adjacent grids in the vertical direction of the waving point to be analyzed is represented, and the delta z represents the height of the grids in the vertical direction of the waving point to be analyzed.
(3) Calculating the temperature of each layer in the vertical direction of the waving point to be analyzed comprises the following steps:
TQ(k，t，p)＝TQ(k，t，p-1)+rQ(i，j，k，t)Δl；k＝1...h，t＝1...L，p＝1...Δz/Δl；
in the formula, TQ(k，t，p)The temperature of each layer in the vertical direction of the waving point to be analyzed is represented, delta l represents the layer height in the vertical direction of the waving point to be analyzed, delta z/delta l represents the number of lattice points between two adjacent layers in the vertical direction of the waving point to be analyzed, rQ(i，j，k，t) The vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed is represented, k represents the number of layers, t represents the time, and p represents the p-th grid point.
It is worth mentioning that: the invention carries out refined temperature prediction on each layer above the ground dancing point in the vertical altitude direction, and the temperature prediction is based on that weather data of an upper layer can influence a lower layer, and weather data of rainfall, snowfall and the like of a higher layer can influence the self-excited vibration amplitude, frequency and the like of the analyzed ground dancing point, so that multidimensional reference is provided for the prediction of the dancing.
Example 2
Corresponding to the above method embodiment, this embodiment discloses a system for hierarchical refinement and prediction of adjacent grid temperature, which includes:
the first calculation unit: the calculation grid is used for determining a three-dimensional temperature field, calculating temperature data of grid points of each grid in the three-dimensional temperature field based on a meteorological WRF numerical mode, and calculating a vertical temperature reduction rate between adjacent grids in the vertical direction; the horizontal plane of the grid represents longitude and latitude, and the vertical direction represents altitude.
A second calculation unit: the method is used for determining a series of related grids in the vertical direction according to the longitude and latitude of the dancing point to be analyzed, and carrying out homogenization layering on the series of grids, wherein the height of the grids in the vertical direction is delta z, the height of the layers in the vertical direction is delta 1, and delta z/delta 1 is an integer greater than or equal to 2.
A third calculation unit: the system is used for calculating the temperature of the ground altitude of the waving point to be analyzed in the vertical direction of the adjacent grid points in the corresponding series of grids according to the ground temperature reduction rate and the related temperature data, and then calculating the temperature of the ground altitude of the waving point to be analyzed by a bilinear interpolation method according to the calculated value of each temperature; and meanwhile, calculating the vertical temperature reduction rate between the same delta z of the waving point to be analyzed by a weighted average method according to the vertical temperature reduction rate between any delta z of the associated lattice points.
A fourth calculation unit: and the method is used for calculating the temperature data of each layer corresponding to the delta 1 according to the temperature of the ground altitude of the dancing point to be analyzed and the vertical temperature reduction rate between the delta z.
As a preferred embodiment of this embodiment, the calculating, in the third unit, the temperature of the ground altitude of the dancing point to be analyzed includes:
(1) a first module: the method is used for determining the ground altitude of four grid points of the calculation grid and the longitude and latitude thereof, and calculating the temperature of the ground altitude of the four grid points through the three-dimensional temperature field.
(2) A second module: the temperature used for calculating the ground altitude of the waving point to be analyzed corresponding to the vertical direction of the four lattice points is as follows:
Figure BDA0001336558540000081
in the formula (I), the compound is shown in the specification,
Figure BDA0001336558540000082
temperature T representing the ground altitude of the waving point to be analyzed in the vertical direction of the four grid points(i，j，1，t)、T(i+1，j，1，t)、T(i，j+1，1，t)、T(i+1，j+1，1，t)Temperature, r, representing the ground altitude for four grid points0Represents a uniform ground temperature reduction rate, H(i，j)、H(i+1，j)、H(i，j+1)、H(i+1，j+1)Representing the ground elevation of four grid points.
(3) A third module: temperature for calculating the ground altitude of the point of oscillation to be analyzed:
Figure BDA0001336558540000083
in the formula, T(Q，t)The temperature of the ground altitude representing the point of oscillation to be analyzed,
Figure BDA0001336558540000084
the temperature of the ground altitude of the dance point to be analyzed corresponding to the vertical direction of the four lattice points is represented, X represents the longitude of the dance point to be analyzed, Y represents the latitude of the dance point to be analyzed, and Xi、Xi+1Longitude, Y, representing two of the four grid pointsj、Yj+1Representing the latitude of two of the four grid points.
As a preferred implementation manner of this embodiment, the calculating, in the third unit, the vertical temperature directly decreasing rate of the dancing point to be analyzed includes:
(1) a fourth module: the method is used for calculating the vertical temperature reduction rate between two adjacent grids in the vertical direction of four grid points:
Figure BDA0001336558540000091
in the formula, r(i，j，k，t)Represents the vertical temperature direct reduction rate, T, between two adjacent grids in the vertical direction of four grid points(i，j，k，t)And T(i，j，k+1，t)The temperature of two adjacent grids is shown, and the Δ z represents the height difference of the two adjacent grids.
(2) A fifth module: the method is used for recording the four grid points as A, B, C, D respectively, recording the dance point to be analyzed as Q, and calculating the weight coefficients between the four grid points and the dance point to be analyzed:
Figure BDA0001336558540000092
Figure BDA0001336558540000093
Figure BDA0001336558540000094
Figure BDA0001336558540000095
in the formula, alpha1、α2、α3、α4Respectively representing A, B, C, D weight coefficients between the four grid points and the dance point to be analyzed,
Figure BDA0001336558540000096
is the distance from point a to point Q,
Figure BDA0001336558540000097
is the distance from point B to point Q,
Figure BDA0001336558540000098
is the distance from the point C to the point Q,
Figure BDA0001336558540000099
the distance from point D to point Q.
(3) A sixth module: the method is used for calculating the vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed:
rQ(k，t)＝α1r(i，j，k，t)+α2r(i+1，j，k，t)+α3r(i，j+1，k，t)+α4r(i+1，j+1，k，t)；
in the formula, rQ(k，t)Represents the direct temperature reduction rate alpha between two adjacent grids of the waving point to be analyzed1、α2、α3、α4Respectively representing the weight coefficients r between the four grid points and the dancing points to be analyzed(i，j，k，t)、r(i+1，j，k，t)、r(i，j+1，k，t)、r(i+1，j+1，k，t)Respectively showing the vertical temperature reduction rate between two adjacent grids in the vertical direction of the four grid points.
As a preferred embodiment of this embodiment, the fourth unit is configured to calculate the temperature of each layer in the vertical direction of the dancing point to be analyzed:
TQ(k，t，p)＝TQ(k，t，p-1)+rQ(k，t)Δl；k＝1...h，t＝1...L，p＝1...Δz/Δl；
in the formula, TQ(k，t，p)Representing the temperature, r, of the layers in the direction perpendicular to the point of oscillation to be analyzedQ(k，t)The vertical temperature direct reduction rate between two adjacent grids of the galloping point to be analyzed is represented, delta l represents the layer height of the galloping point to be analyzed in the vertical direction, delta z/delta l represents the number of grid points between two adjacent layers of the galloping point to be analyzed in the vertical direction, k represents the number of layers, t represents the time, and p represents the p-th grid point.
As a preferred embodiment of this embodiment, when the position of the dancing point to be analyzed is at the grid point position of the computational grid, calculating the temperature of each layer in the vertical direction of the dancing point to be analyzed includes:
(1) a seventh module: the method is used for confirming the lattice point position of the dancing point to be analyzed and acquiring the three-dimensional temperature field data of the series of lattice points in the vertical direction of the lattice point as the three-dimensional temperature field data of the dancing point to be analyzed.
(2) An eighth module: the method is used for calculating the vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed:
Figure BDA0001336558540000101
in the formula, rQ(i，j，k，t)Represents the vertical temperature direct reduction rate, T, between two adjacent grids of the waving point to be analyzed(i，j，k，t)And T(i，j，k+1，t)The temperature of two adjacent grids in the vertical direction of the waving point to be analyzed is represented, and the delta z represents the height of the grids in the vertical direction of the waving point to be analyzed.
(3) A ninth module: the method for calculating the temperature of each layer in the vertical direction of the dancing point to be analyzed comprises the following steps:
TQ(k，t，p)＝TQ(k，t，p-1)+rQ(i，j，k，t)Δl；k＝1...h，t＝1...L，p＝1...Δz/Δl；
in the formula, TQ(k，t，p)The temperature of each layer in the vertical direction of the waving point to be analyzed is represented, delta l represents the layer height in the vertical direction of the waving point to be analyzed, delta z/delta l represents the number of lattice points between two adjacent layers in the vertical direction of the waving point to be analyzed, rQ(i，j，k，t)The vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed is represented, k represents the number of layers, t represents the time, and p represents the p-th grid point.
As described above, the adjacent grid temperature hierarchical refinement prediction method and system provided by the invention determine the associated series grid in the vertical direction according to the longitude and latitude of the dancing point to be analyzed, and carry out homogenization and layering on the series grid, firstly, the temperature of the ground altitude of the dancing point to be analyzed in the vertical direction of the adjacent grid point in the corresponding series grid is calculated according to the ground temperature direct reduction rate and the related temperature data, and then the temperature of the ground altitude of the dancing point to be analyzed is calculated by a bilinear interpolation method according to the calculated value of each temperature; meanwhile, according to the vertical temperature reduction rate between any adjacent grids of the associated grid points, the vertical temperature reduction rate between the adjacent grids corresponding to the galloping point to be analyzed is calculated by a weighted average method; finally, calculating the temperature data of each correspondingly subdivided layer according to the temperature of the ground altitude of the dancing point to be analyzed and the vertical temperature reduction rate between every two adjacent grids; the method and the system consider the physical law of vertical temperature change, greatly improve the vertical temperature resolution of the easy-to-wave point, have high accuracy and wide calculation speed range, and provide powerful scientific support for the fine prediction of the icing wave of the power grid and the guarantee of the safe operation of the power grid.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (6)

1. A method for hierarchical refinement and prediction of adjacent grid temperature is characterized by comprising the following steps:
determining a calculation grid of the three-dimensional temperature field, calculating temperature data of grid points of each grid in the three-dimensional temperature field based on a meteorological WRF numerical mode, and calculating a vertical temperature reduction rate between adjacent grids in the vertical direction; wherein, the horizontal plane of the grid represents longitude and latitude, and the vertical direction represents altitude;
determining a series of related grids in the vertical direction according to the longitude and latitude of the dancing point to be analyzed, and carrying out homogenization layering on the series of grids, wherein the grid height in the vertical direction is delta z, the layer height in the vertical direction is delta l, and delta z/delta l is an integer greater than or equal to 2;
calculating the temperature of the ground altitude of the adjacent grid points in the corresponding series of grids according to the ground temperature reduction rate and the temperature data of the adjacent grid points in the corresponding series of grids; then calculating the temperature of the ground altitude of the waving point to be analyzed in the vertical direction of the lattice point; then, calculating the temperature of the ground altitude of the waving point to be analyzed by a bilinear interpolation method according to the calculated value of each temperature; meanwhile, according to the vertical temperature reduction rate between any delta z of the associated lattice points, calculating the vertical temperature reduction rate between the same delta z of the waving points to be analyzed by a weighted average method;
calculating temperature data of each layer corresponding to delta l according to the temperature of the ground altitude of the dancing point to be analyzed and the vertical temperature reduction rate between each delta z;
calculating the temperature of the ground altitude of the dancing point to be analyzed comprises the following steps:
(1) determining the ground altitude and the longitude and latitude of four grid points of the calculation grid, and calculating the temperature of the ground altitude of the four grid points through a three-dimensional temperature field;
(2) calculating the temperature of the ground altitude of the waving point to be analyzed in the vertical direction of the four lattice points:
Figure FDA0002808731380000011
in the formula (I), the compound is shown in the specification,
Figure FDA0002808731380000012
temperature T representing the ground altitude of the waving point to be analyzed in the vertical direction of the four grid points(i,j,1,t)、T(i+1,j,1,t)、T(i,j+1,1,t)、T(i+1,j+1,1,t)Temperature, r, representing the ground altitude for four grid points0Represents a uniform ground temperature reduction rate, H(i,j)、H(i+1,j)、H(i,j+1)、H(i+1,j+1)Ground altitude, H, representing four grid pointsQThe altitude of the ground of the dancing point Q to be analyzed is represented by i, j and t, wherein i is the latitude direction number of the grid point, j is the longitude direction number of the grid point, and t represents the moment;
(3) calculating the temperature of the ground altitude of the dancing point to be analyzed:
Figure FDA0002808731380000021
in the formula, T(Q，t)The temperature of the ground altitude representing the point of oscillation to be analyzed,
Figure FDA0002808731380000022
to representThe vertical directions of the four grid points correspond to the temperature of the ground altitude of the dancing point to be analyzed, X represents the longitude of the dancing point to be analyzed, Y represents the latitude of the dancing point to be analyzed, and X represents the latitude of the dancing point to be analyzedi、Xi+1Longitude, Y, representing two of the four grid pointsj、Yj+1Representing the latitude of two of the four grid points;
wherein, calculating the vertical temperature reduction rate of the waving point to be analyzed comprises the following steps:
(1) calculating the vertical temperature direct reduction rate between two adjacent grids in the vertical direction of the four grid points:
Figure FDA0002808731380000023
in the formula, r(i,j,k,t)Represents the vertical temperature direct reduction rate, T, between two adjacent grids in the vertical direction of four grid points(i,j,k,t)And T(i,j,k+1,t)The temperature of two adjacent grids is represented, the delta z represents the height difference of the two adjacent grids, and h is the maximum layer number of the galloping points to be analyzed in the vertical direction;
(2) recording the four grid points as A, B, C, D respectively, recording the dance point to be analyzed as Q, and calculating the weight coefficients between the four grid points and the dance point to be analyzed:
Figure FDA0002808731380000024
Figure FDA0002808731380000025
Figure FDA0002808731380000026
Figure FDA0002808731380000027
in the formula, alpha1、α2、α3、α4Respectively representing A, B, C, D weight coefficients between the four grid points and the dance point to be analyzed,
Figure FDA0002808731380000028
is the distance from point a to point Q,
Figure FDA0002808731380000029
is the distance from point B to point Q,
Figure FDA00028087313800000210
is the distance from the point C to the point Q,
Figure FDA00028087313800000211
the distance from the point D to the point Q is shown;
(3) calculating the vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed:
rQ(k,t)＝α1r(i,j,k,t)+α2r(i+1,j,k,t)+α3r(i,j+1,k,t)+α4r(i+1,j+1,k,t)；
in the formula, rQ(k,t)Represents the direct temperature reduction rate alpha between two adjacent grids of the waving point to be analyzed1、α2、α3、α4Respectively representing the weight coefficients r between the four grid points and the dancing points to be analyzed(i,j,k,t)、r(i+1,j,k,t)、r(i,j+1,k,t)、r(i+1,j+1,k,t)Respectively showing the vertical temperature reduction rate between two adjacent grids in the vertical direction of the four grid points.
2. The neighbor grid temperature hierarchical refinement prediction method according to claim 1, wherein calculating the temperature of each layer in the vertical direction of the waving point to be analyzed comprises:
TQ(k,t,p)＝TQ(k,t,p-1)+rQ(k,t)△l；k＝1,...,h,t＝1,...,L,p＝1,...,△z/△l；
in the formula, TQ(k,t,p)Representing the temperature, r, of the layers in the direction perpendicular to the point of oscillation to be analyzedQ(k,t)The vertical temperature direct reduction rate between two adjacent grids of the galloping point to be analyzed is represented, delta L represents the layer height of the galloping point to be analyzed in the vertical direction, delta z/[ delta ] L represents the number of grid points between two adjacent layers of the galloping point to be analyzed in the vertical direction, k represents the number of layers, t represents the time, p represents the p-th grid point, and L is the maximum time.
3. The neighbor grid temperature hierarchical refinement prediction method according to claim 1, wherein when the position of the dancing point to be analyzed is at the grid point position of the computational grid, calculating the temperature of each layer in the vertical direction of the dancing point to be analyzed comprises:
(1) confirming the position of a lattice point where a dancing point to be analyzed is located, and acquiring three-dimensional temperature field data of a series of lattice points in the vertical direction of the lattice point as the three-dimensional temperature field data of the dancing point to be analyzed;
(2) calculating the vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed:
Figure FDA0002808731380000031
in the formula, rQ(i,j,k,t)Represents the vertical temperature direct reduction rate, T, between two adjacent grids of the waving point to be analyzed(i,j,k,t)And T(i,j,k+1,t)The temperature of two adjacent grids in the vertical direction of the waving point to be analyzed is represented, and the delta z represents the grid height in the vertical direction of the waving point to be analyzed;
(3) calculating the temperature of each layer in the vertical direction of the waving point to be analyzed comprises the following steps:
TQ(k,t,p)＝TQ(k,t,p-1)+rQ(i,j,k,t)△l；k＝1,...,h,t＝1,...,L,p＝1,...,△z/△l；
in the formula, TQ(k,t,p)Showing the temperature of each layer in the vertical direction of the waving point to be analyzed, delta l showing the layer height in the vertical direction of the waving point to be analyzed, delta z/delta l showing the number of lattice points between two adjacent layers in the vertical direction of the waving point to be analyzed, rQ(i,j,k,t)The vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed is represented, k represents the number of layers, t represents the time, p represents the p-th grid point, and L is the maximum time.
4. A system for hierarchical refinement and prediction of adjacent grid temperature, comprising:
the first calculation unit: the calculation grid is used for determining a three-dimensional temperature field, calculating temperature data of grid points of each grid in the three-dimensional temperature field based on a meteorological WRF numerical mode, and calculating a vertical temperature reduction rate between adjacent grids in the vertical direction; wherein, the horizontal plane of the grid represents longitude and latitude, and the vertical direction represents altitude;
a second calculation unit: the system comprises a vertical grid, a horizontal grid, a vertical grid and a vertical grid, wherein the vertical grid is connected with the horizontal grid through a connecting line, the vertical grid is connected with the vertical grid through a connecting line;
a third calculation unit: the system is used for calculating the temperature of the ground altitude of the adjacent grid points in the corresponding series of grids according to the ground temperature reduction rate and the temperature data of the adjacent grid points in the corresponding series of grids; then calculating the temperature of the ground altitude of the waving point to be analyzed in the vertical direction of the lattice point; then, calculating the temperature of the ground altitude of the waving point to be analyzed by a bilinear interpolation method according to the calculated value of each temperature; meanwhile, according to the vertical temperature reduction rate between any delta z of the associated lattice points, calculating the vertical temperature reduction rate between the same delta z of the waving points to be analyzed by a weighted average method;
a fourth calculation unit: the temperature data of each layer corresponding to delta l is calculated according to the temperature of the ground altitude of the dancing point to be analyzed and the vertical temperature reduction rate between each delta z;
the third calculation unit calculates the temperature of the ground altitude of the dancing point to be analyzed, and the third calculation unit comprises the following steps:
(1) a first module: the device is used for determining the ground altitude and the longitude and latitude of four grid points of the calculation grid and calculating the temperature of the ground altitude of the four grid points through a three-dimensional temperature field;
(2) a second module: the temperature used for calculating the ground altitude of the waving point to be analyzed corresponding to the vertical direction of the four lattice points is as follows:
Figure FDA0002808731380000041
in the formula (I), the compound is shown in the specification,
Figure FDA0002808731380000042
temperature T representing the ground altitude of the waving point to be analyzed in the vertical direction of the four grid points(i,j,1,t)、T(i+1,j,1,t)、T(i,j+1,1,t)、T(i+1,j+1,1,t)Temperature, r, representing the ground altitude for four grid points0Represents a uniform ground temperature reduction rate, H(i,j)、H(i+1,j)、H(i,j+1)、H(i+1,j+1)Ground altitude, H, representing four grid pointsQThe altitude of the ground of the dancing point Q to be analyzed is represented by i, j and t, wherein i is the latitude direction number of the grid point, j is the longitude direction number of the grid point, and t represents the moment;
(3) a third module: temperature for calculating the ground altitude of the point of oscillation to be analyzed:
Figure FDA0002808731380000043
in the formula, T(Q，t)The temperature of the ground altitude representing the point of oscillation to be analyzed,
Figure FDA0002808731380000044
the temperature of the ground altitude of the dance point to be analyzed corresponding to the vertical direction of the four lattice points is represented, X represents the longitude of the dance point to be analyzed, Y represents the latitude of the dance point to be analyzed, and Xi、Xi+1Longitude, Y, representing two of the four grid pointsj、Yj+1Representing the latitude of two of the four grid points;
wherein, the calculating the vertical temperature directly decreasing rate of the dancing point to be analyzed in the third calculating unit comprises:
(1) a fourth module: the method is used for calculating the vertical temperature reduction rate between two adjacent grids in the vertical direction of four grid points:
Figure FDA0002808731380000051
in the formula, r(i,j,k,t)Represents the vertical temperature direct reduction rate, T, between two adjacent grids in the vertical direction of four grid points(i,j,k,t)And T(i,j,k+1,t)The temperature of two adjacent grids is represented, the delta z represents the height difference of the two adjacent grids, and h is the maximum layer number of the galloping points to be analyzed in the vertical direction;
(2) a fifth module: the method is used for recording the four grid points as A, B, C, D respectively, recording the dance point to be analyzed as Q, and calculating the weight coefficients between the four grid points and the dance point to be analyzed:
Figure FDA0002808731380000052
Figure FDA0002808731380000053
Figure FDA0002808731380000054
Figure FDA0002808731380000055
in the formula, alpha1、α2、α3、α4Respectively representing A, B, C, D weight coefficients between the four grid points and the dance point to be analyzed,
Figure FDA0002808731380000056
is the distance from point a to point Q,
Figure FDA0002808731380000057
is the distance from point B to point Q,
Figure FDA0002808731380000058
is the distance from the point C to the point Q,
Figure FDA0002808731380000059
the distance from the point D to the point Q is shown;
(3) a sixth module: the method is used for calculating the vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed:
rQ(k,t)＝α1r(i,j,k,t)+α2r(i+1,j,k,t)+α3r(i,j+1,k,t)+α4r(i+1,j+1,k,t)；
in the formula, rQ(k,t)Represents the direct temperature reduction rate alpha between two adjacent grids of the waving point to be analyzed1、α2、α3、α4Respectively representing the weight coefficients r between the four grid points and the dancing points to be analyzed(i,j,k,t)、r(i+1,j,k,t)、r(i,j+1,k,t)、r(i+1,j+1,k,t)Respectively showing the vertical temperature reduction rate between two adjacent grids in the vertical direction of the four grid points.
5. The proximity grid temperature hierarchical refinement prediction system according to claim 4, characterized in that the fourth unit is configured to calculate the temperature of each layer in the vertical direction of the dancing point to be analyzed:
TQ(k,t,p)＝TQ(k,t,p-1)+rQ(k,t)△l；k＝1,...,h,t＝1,...,L,p＝1,...,△z/△l；
in the formula, TQ(k,t,p)Representing the temperature, r, of the layers in the direction perpendicular to the point of oscillation to be analyzedQ(k,t)The vertical temperature direct reduction rate between two adjacent grids of the galloping point to be analyzed is represented, delta l represents the layer height of the galloping point to be analyzed in the vertical direction, and delta z/[ delta ] l represents two adjacent layers of the galloping point to be analyzed in the vertical directionThe number of cells in between, k the number of layers, t the time, p the p-th cell, and L the maximum time.
6. The neighbor grid temperature hierarchical refinement prediction system according to claim 4, wherein when the position of the dancing point to be analyzed is at the grid point position of the computational grid, calculating the temperature of each layer in the vertical direction of the dancing point to be analyzed comprises:
(1) a seventh module: the system comprises a grid point position determining module, a temperature analyzing module, a data acquiring module and a data analyzing module, wherein the grid point position determining module is used for determining the grid point position of a dancing point to be analyzed, and acquiring three-dimensional temperature field data of a series of grid points in the vertical direction of the grid point as the three-dimensional temperature field data of the dancing point to be analyzed;
(2) an eighth module: the method is used for calculating the vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed:
Figure FDA0002808731380000061
in the formula, rQ(i,j,k,t)Represents the vertical temperature direct reduction rate, T, between two adjacent grids of the waving point to be analyzed(i,j,k,t)And T(i,j,k+1,t)The temperature of two adjacent grids in the vertical direction of the waving point to be analyzed is represented, and the delta z represents the grid height in the vertical direction of the waving point to be analyzed;
(3) a ninth module: the method for calculating the temperature of each layer in the vertical direction of the dancing point to be analyzed comprises the following steps:
TQ(k,t,p)＝TQ(k,t,p-1)+rQ(i,j,k,t)△l；k＝1,...,h,t＝1,...,L,p＝1,...,△z/△l；
in the formula, TQ(k,t,p)Showing the temperature of each layer in the vertical direction of the waving point to be analyzed, delta l showing the layer height in the vertical direction of the waving point to be analyzed, delta z/delta l showing the number of lattice points between two adjacent layers in the vertical direction of the waving point to be analyzed, rQ(i,j,k,t)The vertical temperature direct reduction rate between two adjacent grids of the waving point to be analyzed is represented, k represents the number of layers, t represents the time, p represents the p-th grid point, and L is the maximum time.
CN201710519880.7A 2017-06-29 2017-06-29 Method and system for layered and refined prediction of adjacent grid temperature Active CN107330189B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710519880.7A CN107330189B (en) 2017-06-29 2017-06-29 Method and system for layered and refined prediction of adjacent grid temperature

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710519880.7A CN107330189B (en) 2017-06-29 2017-06-29 Method and system for layered and refined prediction of adjacent grid temperature

Publications (2)

Publication Number Publication Date
CN107330189A CN107330189A (en) 2017-11-07
CN107330189B true CN107330189B (en) 2021-03-09

Family

ID=60198370

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710519880.7A Active CN107330189B (en) 2017-06-29 2017-06-29 Method and system for layered and refined prediction of adjacent grid temperature

Country Status (1)

Country Link
CN (1) CN107330189B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109492756B (en) * 2018-11-19 2022-06-10 中国气象局公共气象服务中心 Multi-element wire galloping early warning method based on deep learning and related device
CN111930866B (en) * 2020-07-31 2021-03-26 中国科学院地理科学与资源研究所 Grid-based layered heat early warning real-time publishing and displaying method, system and equipment

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0923404A4 (en) * 1996-07-23 2001-05-16 Williams Fire & Hazard Control Inc Methods for extinguishing tank fires
CN101038186A (en) * 2006-06-10 2007-09-19 伊仁图太 Device for online warning freezing and swing of transmission line
CN201413997Y (en) * 2009-03-30 2010-02-24 吉林省电力有限公司 Wind power prediction system
CN103473610A (en) * 2013-09-06 2013-12-25 国家电网公司 Power grid icing growth trend forecasting method based on digital elevation model
CN105184407A (en) * 2015-09-11 2015-12-23 国家电网公司 Power transmission line icing growth forecasting method based on atmospheric numerical model
CN106203718A (en) * 2016-07-15 2016-12-07 国网湖南省电力公司 Neighbouring grid powerline ice-covering Forecasting Methodology based on the height above sea level factor
WO2017051300A1 (en) * 2015-09-21 2017-03-30 A.A.A Taranis Visual Ltd Method and system for interpolating data
CN106682776A (en) * 2016-12-27 2017-05-17 国网湖南省电力公司 Fine forecasting and early warning method and system for dancing of overhead transmission line
CN106786167A (en) * 2017-02-13 2017-05-31 国网湖南省电力公司 A kind of transmission line of electricity ice damage Study on Decision-making Method for Optimization and its system

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0923404A4 (en) * 1996-07-23 2001-05-16 Williams Fire & Hazard Control Inc Methods for extinguishing tank fires
CN101038186A (en) * 2006-06-10 2007-09-19 伊仁图太 Device for online warning freezing and swing of transmission line
CN201413997Y (en) * 2009-03-30 2010-02-24 吉林省电力有限公司 Wind power prediction system
CN103473610A (en) * 2013-09-06 2013-12-25 国家电网公司 Power grid icing growth trend forecasting method based on digital elevation model
CN105184407A (en) * 2015-09-11 2015-12-23 国家电网公司 Power transmission line icing growth forecasting method based on atmospheric numerical model
WO2017051300A1 (en) * 2015-09-21 2017-03-30 A.A.A Taranis Visual Ltd Method and system for interpolating data
CN106203718A (en) * 2016-07-15 2016-12-07 国网湖南省电力公司 Neighbouring grid powerline ice-covering Forecasting Methodology based on the height above sea level factor
CN106682776A (en) * 2016-12-27 2017-05-17 国网湖南省电力公司 Fine forecasting and early warning method and system for dancing of overhead transmission line
CN106786167A (en) * 2017-02-13 2017-05-31 国网湖南省电力公司 A kind of transmission line of electricity ice damage Study on Decision-making Method for Optimization and its system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Application of the Multigrid Data Assimilation Scheme to the China Seas’ Temperature Forecast;Wei Li 等;《JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY》;20081001;2106-2116 *
输电线路覆冰厚度短期多变量灰色预测模型研究;陆佳政 等;《高电压技术》;20151031;3372-3377 *

Also Published As

Publication number Publication date
CN107330189A (en) 2017-11-07

Similar Documents

Publication Publication Date Title
CN111427100B (en) Typhoon center positioning method and device and typhoon path generation method
CN107403073B (en) Integrated flood forecasting method for improving and forecasting rainfall based on data assimilation
CN110298115A (en) A kind of wind field power NO emissions reduction method based on simplified landform aerodynamic parameter
CN110378540B (en) Atmospheric weighted average temperature calculation method suitable for northern Guangxi Bay region
CN104182594A (en) Method for drawing power system wind area graph
CN107330189B (en) Method and system for layered and refined prediction of adjacent grid temperature
Chen et al. Added value of a dynamical downscaling approach for simulating precipitation and temperature over Tianshan mountains area, Central Asia
CN110763271A (en) Beidou satellite railway iron tower monitoring device and method
CN106934191A (en) A kind of WRF pattern correction wind methods based on self-similarity
Ye et al. Flood forecasting based on TIGGE precipitation ensemble forecast
Li et al. Changes in the glacier extent and surface elevation in Xiongcaigangri region, Southern Karakoram Mountains, China
CN106295896B (en) In conjunction with the middle minute yardstick power grid windburn method for early warning of remote sensing terrain information
CN105679103A (en) Method for assessing air traffic volume accommodated in airport environment
CN109657988B (en) Tobacco leaf quality partitioning method based on HASM and Euclidean distance algorithm
Wang et al. Evaluation of five planetary boundary layer schemes in WRF over China's largest semi-fixed desert
CN105068075B (en) A kind of computational methods of strong wind near the ground
CN107316109B (en) Method, system and device for predicting wind speed of overhead line on ground in winter
CN113326624A (en) Method and system for predicting height of atmospheric boundary layer in desert area
CN105184667A (en) Method for dual-nested simulation of wind speed distribution of wind power plant
CN115511192B (en) Precipitation prediction method and system based on lightning data assimilation
CN109583095B (en) North Pacific typhoon extension period forecasting method based on hybrid statistical power model
CN108416082A (en) A kind of marine site pour point external disturbance gravitation horizontal component without unusual computational methods
Chane Ming et al. Elliptical structures of gravity waves produced by Typhoon Soudelor in 2015 near Taiwan
CN110674571A (en) Power transmission line bealock wind speed downscaling calculation method and system
Wang et al. Climatic factors and their availability in estimating long‐term variations of fine particle distributions over East China

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
CB02 Change of applicant information

Address after: 410000 Shaoshan North Road, Yuhua District, Hunan, No. 388, No.

Applicant after: State Grid Hunan Electric Power Co., Ltd.

Applicant after: National network Hunan Electric Power Co., Ltd. disaster prevention and Reduction Center

Applicant after: State Grid Corporation of China

Address before: 410000 Shaoshan North Road, Yuhua District, Hunan, No. 388, No.

Applicant before: State Grid Hunan Electric Power Company

Applicant before: State Grid Hunan Electric Power Company prevents and reduces natural disasters center

Applicant before: State Grid Corporation of China

CB02 Change of applicant information
GR01 Patent grant
GR01 Patent grant