CN115793104A - Method and device for conjecturing call height and wind speed of power grid tower - Google Patents
Method and device for conjecturing call height and wind speed of power grid tower Download PDFInfo
- Publication number
- CN115793104A CN115793104A CN202211323353.6A CN202211323353A CN115793104A CN 115793104 A CN115793104 A CN 115793104A CN 202211323353 A CN202211323353 A CN 202211323353A CN 115793104 A CN115793104 A CN 115793104A
- Authority
- CN
- China
- Prior art keywords
- wind speed
- tower
- height
- power grid
- power
- 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.)
- Granted
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A30/00—Adapting or protecting infrastructure or their operation
Landscapes
- Wind Motors (AREA)
Abstract
The invention discloses a method and a device for conjecturing call height and wind speed of a power grid tower, wherein the method comprises the following steps: acquiring wind speed forecast data of a plurality of different heights; acquiring wind speed data of a meteorological observation station at 10m height around a power grid tower and different height layers of a wind measuring tower; determining the static power exponent of the near-formation wind speed under different wind power levels, and calculating first wind speed values of different height layers at the position of the anemometer tower and first wind speed values of the nominal height of a power grid tower; determining the power exponent of the whole layer of the near stratum, and calculating a second wind speed value; determining the wind speed power exponent of different height layers of the near stratum, and calculating a third wind speed value; and calculating absolute errors of different heights, determining the weights of the three wind speed values, and calculating the nominal height wind speed of the power grid tower of different heights of the near stratum at the current moment. The method can be used for estimating the wind speed at the nominal height of the power grid tower, and is beneficial to improving the forecasting and early warning capability of the wind speed with high influence at the power grid tower.
Description
Technical Field
The invention relates to a method and a device for conjecturing call height and wind speed of a power grid tower, belonging to the technical field of monitoring of the power grid tower.
Background
The influence of meteorological wind speed is considered at the beginning of the design of overhead lines and towers of a power grid, but the wind speed value at the position of the tower of the power grid still needs to be concerned at any moment in actual operation, and particularly when the extreme wind speed passes through the severe weather process, the extreme wind speed needs to be forecast and early-warned in time to prevent the pole falling and tower falling. The meteorological stations of the meteorological department are distributed according to the population and administrative divisions: the city is divided into a plurality of regions, and the country is distributed a few; the population is densely distributed, and the distribution in remote zones is less; the leveling areas are distributed more, and the mountain areas are distributed less; generally, the more meteorological stations are distributed, the easier it is to observe the local weather process. The distribution of the facilities and towers of the power grid department selects proper places and line trends according to the power grid industry standard, and is often far away from a meteorological observation station of a meteorological department. In addition, the construction and observation setting of the meteorological station need to meet the corresponding national or meteorological industry standards, and the requirements are obviously different from the actual requirements of the power grid. Therefore, the existing meteorological stations of the meteorological department are difficult to meet the actual operation requirements of the power grid, and the power grid department needs to presume the meteorological actual situation of the power grid tower by establishing the power meteorological monitoring station by itself or processing the data of the meteorological stations by adopting a certain technical means, so as to make up the defects of the existing meteorological element observation.
The nominal height of the power grid tower is the vertical distance from the lower plane of a wire cross arm of the iron tower to the construction base plane of a central pile of the tower, and the nominal heights of the towers with different voltage grades, common poles and the iron tower are different. And the standard height of wind speed observation of a meteorological department is 10 meters, so that a technical method is generally considered to convert the correction of the 10-meter wind speed of a meteorological observation station into the wind speed at the nominal height of a power grid tower.
The method generally comprises: (1) traditional statistical methods: through a statistical model and an atmosphere physics law, on the basis of fully considering landform characteristics, climate characteristics and space-time change rules of physical quantities, a proper empirical relation model is selected, and bidirectional correction and conversion between standard observation and non-standard observation are established, so that the method has the characteristics of clear physical significance, simplicity and high efficiency in calculation, excellent correction effect and the like; and (2) artificial intelligent methods such as machine learning and the like: the method has the advantages that technical ideas are advanced with times, data mining is sufficient, and the intrinsic physical process is easily ignored.
The traditional statistical method is mainly based on the near-stratum wind speed vertical profile, and after factors such as ground roughness, wind climate and low-level atmospheric layer junction state are fully considered, a correction conversion model is established. From the aspect of engineering application, the method is simple and efficient in calculation, clear in physical significance and good in correction effect, and therefore the correction conversion model based on the near-stratum wind speed vertical profile is adopted and the wind speed at the nominal height of the power grid is conjectured by combining the 10-meter wind speed of the meteorological observation station around the power grid tower.
Disclosure of Invention
In order to solve the problems, the invention provides a method and a device for estimating the nominal height and the wind speed of the power grid tower, which can analyze the actual nominal height and the wind speed of the power grid tower and obtain the reliable actual wind speed of the nominal height of the power grid tower.
The technical scheme adopted for solving the technical problems is as follows:
on one hand, the method for estimating the nominal height and the wind speed of the power grid tower provided by the embodiment of the invention comprises the following steps:
acquiring wind speed forecast data of a plurality of different heights in the NCEP-GFS near-stratum wind speed forecast;
acquiring wind speed data of a meteorological observation station at 10m height around a power grid tower and wind speed data of wind measuring towers at different height layers around the power grid tower;
determining a static power index of near-formation wind speed under different wind power levels by using wind speed data of the anemometer tower, and calculating first wind speed values of different height layers at the position of the anemometer tower and a first wind speed value WS1 at the nominal height of the power grid tower by combining the wind speed data of 10 meters of the meteorological observation station around the power grid tower;
dynamically determining the power exponent of the wind speed of the whole layer of the near stratum by using the NCEP-GFS forecast data and a power exponent fitting method, and calculating second wind speed values of different height layers at the position of the anemometer tower and a second wind speed value WS2 at the nominal height of the power grid tower by combining the 10-meter height wind speed data of the meteorological observation station around the power grid tower;
dynamically determining wind speed power indexes of different height layers of a near stratum by using NCEP-GFS forecast data and a power index fitting method, and calculating third wind speed values of different height layers at the position of the anemometer tower and a third wind speed value WS3 at the nominal height of the power grid tower by combining 10-meter height wind speed data of the meteorological observation station around the power grid tower;
and calculating absolute errors AE at different heights, determining the weight w of the three wind speed values, and calculating the nominal height wind speed of the power grid tower at the current moment and different heights of the near stratum.
As a possible implementation manner of this embodiment, the wind speed forecast data of different heights includes wind speed forecast data of heights of 10 meters, 20 meters, 30 meters, 40 meters, 50 meters, 80 meters and 100 meters.
As a possible implementation manner of this embodiment, the acquiring wind speed data of 10 meters of height of the meteorological observation station around the power grid tower and wind speed data of different height layers of the anemometer tower includes:
extracting 10-meter wind speed observation values of meteorological department observation stations around the power grid tower, and performing horizontal interpolation and terrain adjustment processing to obtain 10-meter height wind speed values of the wind measurement tower point positions of the power grid tower; and extracting the wind speed data of the wind measuring tower at different height layers around the power grid tower.
As a possible implementation manner of this embodiment, the determining a static power exponent of near formation wind speed in different wind power levels by using anemometry tower wind speed data, and calculating first wind speed values in different height layers at the position of the anemometry tower and a first wind speed value WS1 at the nominal height of the power grid tower by combining with wind speed data at the height of 10 meters of the meteorological observation station around the power grid tower, includes:
dividing the data of the anemometer tower into different wind power grade intervals by taking the wind speed of a 10-meter height layer of the anemometer tower as a reference;
obtaining near-stratum average wind speed profiles of different wind power grades;
fitting to obtain power indexes of different wind power grades by using a power index relation formula and a near-stratum average wind speed profile;
and calculating to obtain wind speed actual analysis values of different height layers at the position of the anemometer tower and wind speed actual analysis values of the nominal height of the power grid tower based on the wind speed of 10 meters at the meteorological observation station and the power indexes of different height layers.
As a possible implementation manner of this embodiment, the formula of the power exponent is as follows:
in the formula (I), the compound is shown in the specification,
is a height H 2 Wind speed (m/s);
is a height H 1 Wind speed (m/s), H 1 The height is generally 10 m; alpha is a wind shear index, the magnitude of which indicates the strength of the wind speed vertical shear.
As a possible implementation manner of this embodiment, the dynamically determining the power exponent of the wind speed of the whole layer of the near-earth layer by using the NCEP-GFS forecast data and the power exponent fitting method, and calculating the second wind speed values of different height layers at the position of the anemometer tower and the second wind speed value WS2 at the nominal height of the power grid tower by combining the wind speed data of the power grid tower at the height of 10 meters, includes:
extracting the nearest NCEP-GFS near-stratum wind speed forecast data to the live moment, and fitting by using a power exponent relational expression to obtain the whole layer wind speed gradient power exponent of the near stratum;
limiting the size of the power exponent by using a preset threshold interval;
and calculating to obtain the wind speed live values of different height layers at the position of the anemometer tower and the wind speed live values of the nominal height positions of the power grid tower based on the wind speed of 10m height of the meteorological observation station and the power indexes of different height layers.
As a possible implementation manner of this embodiment, the dynamically determining wind speed power exponents of different height layers of a near stratum by using the NCEP-GFS forecast data and the power exponent fitting method, and calculating third wind speed values of different height layers at the position of the anemometer tower and a third wind speed value WS3 at the nominal height of the power grid tower by combining with the 10-meter height wind speed data of the power grid tower surrounding meteorological observation station includes:
extracting the wind speed of the near stratum of the NCEP-GFS, and performing power exponent relation fitting on the near points at different heights to obtain power exponents at different heights;
limiting the size of the power exponent by using a preset interval range;
and calculating to obtain the actual wind speed values of different height layers at the position of the anemometer tower and the actual wind speed values of the nominal height of the power grid tower based on the wind speed of the meteorological observation station at the height of 10 meters and the power indexes of the different height layers.
As a possible implementation manner of this embodiment, the calculating absolute errors AE at different heights, determining weights w of the three wind speed values, and calculating nominal height wind speeds of power grid towers at different heights of the near-earth layer at the current time includes:
calculating near-formation wind speeds WS1, WS2 and WS3 of the position of the anemometer tower at the current moment;
calculating absolute errors AE of different heights by using the wind speed live condition of the wind measuring tower and the obtained near-stratum wind speed of the wind measuring tower position, and determining the weight w of the near-stratum wind speeds WS1, WS2 and WS 3:
AE ijk ＝|WS ijk -O jk |
calculating the nominal height wind speed WS of the power grid tower with different heights of the near stratum at the current moment according to the weight:
in the formula, AE represents absolute error, WS represents wind speed calculated by three methods, O is wind speed observation of a wind measuring tower, omega represents weights corresponding to wind speed observation at different moments, w represents weights corresponding to different wind speed calculation methods, i represents different wind speed calculation methods, j represents different moments, k represents different heights of a near stratum, and a represents a preset constant.
On the other hand, the device for estimating the nominal height and the wind speed of the power grid tower provided by the embodiment of the invention comprises the following components:
the forecasting data acquisition module is used for acquiring wind speed forecasting data of a plurality of different heights in the NCEP-GFS near-stratum wind speed forecasting;
the wind speed data acquisition module is used for acquiring wind speed data of 10m height of a meteorological observation station around a power grid tower and wind speed data of different height layers of the anemometer tower;
the first wind speed calculation module is used for determining the static power index of the near-formation wind speed under different wind power levels by utilizing the wind speed data of the anemometer tower, and calculating first wind speed values of different height layers at the position of the anemometer tower and a first wind speed value WS1 at the nominal height of the power grid tower by combining the wind speed data of 10m height of the meteorological observation station around the power grid tower;
the second wind speed calculation module is used for dynamically determining the power exponent of the wind speed of the whole layer of the near stratum by using the NCEP-GFS forecast data and a power exponent fitting method, and calculating second wind speed values of different height layers at the position of the anemometer tower and a second wind speed value WS2 at the nominal height of the power grid tower by combining the 10-meter height wind speed data of the meteorological observation station around the power grid tower;
the third wind speed calculation module is used for dynamically determining wind speed power indexes of different height layers of a near stratum by using the NCEP-GFS forecast data and a power index fitting method, and calculating third wind speed values of different height layers at the position of the anemometer tower and a third wind speed value WS3 at the nominal height of the power grid tower by combining 10m height wind speed data of the meteorological observation station around the power grid tower;
and the current wind speed calculation module is used for calculating absolute errors AE at different heights, determining the weight w of the three wind speed values and calculating the nominal height wind speed of the power grid tower at the current moment and different heights of the near stratum.
As a possible implementation manner of this embodiment, the wind speed forecast data of different heights includes wind speed forecast data of heights of 10 meters, 20 meters, 30 meters, 40 meters, 50 meters, 80 meters and 100 meters.
The technical scheme of the embodiment of the invention has the following beneficial effects:
according to the method, wind speed live analysis data including different heights of the near stratum, namely the near stratum wind speed profile, are effectively established by analyzing the near stratum wind speed numerical forecast, the anemometer tower observation, the meteorological observation station wind speed observation numerical value and the basic geographic information, the calculated wind speed profile is close to the anemometer tower wind speed profile, and the method has good performance in systematic gale weather in spring and convective gale weather in summer; and furthermore, the wind speed at the nominal height of the power grid tower can be better presumed, and the high-influence wind speed forecasting and early warning capability at the power grid tower can be improved. The method has obvious effect on local near-stratum wind speed live analysis, is widely applied to the fields of weather, power grid and the like which need high influence on near-stratum wind speed live analysis, and has prominent significance in the crossing field of weather and energy.
Drawings
FIG. 1 is a flow diagram illustrating a method for power grid tower nominal height wind speed estimation in accordance with an exemplary embodiment;
FIG. 2 is a block diagram illustrating an apparatus for estimating nominal altitude wind speed for a tower of a power grid according to an exemplary embodiment;
FIG. 3 is a schematic illustration of a static near-formation wind velocity gradient power exponent calculation using meteorological tower historical data, in accordance with an exemplary embodiment;
FIG. 4 is a schematic illustration of a calculation of a near formation wind speed gradient power exponent at a time using numerical forecasting, in accordance with an exemplary embodiment;
FIG. 5 is a diagram illustrating a method for computing a power exponent of a wind speed gradient at different heights of a near formation at a time using numerical prediction, according to an exemplary embodiment;
FIG. 6 is a flow diagram illustrating a technique for performing grid tower nominal altitude wind speed estimation in accordance with the present invention in accordance with an exemplary embodiment;
FIG. 7 is a schematic diagram illustrating average wind speed under multiple calculation methods according to various embodiments, according to an exemplary embodiment.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the following figures:
in order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, specific example components and arrangements are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.
As shown in fig. 1, the method for estimating nominal height wind speed of a power grid tower provided by the embodiment of the invention includes the following steps:
acquiring wind speed forecast data of a plurality of different heights in the NCEP-GFS near stratum wind speed forecast;
acquiring wind speed data of a meteorological observation station around a power grid tower at the height of 10 meters and wind speed data of different height layers of a wind measuring tower;
determining a static power index of near-formation wind speed under different wind power levels by using wind speed data of the anemometer tower, and calculating first wind speed values of different height layers at the position of the anemometer tower and a first wind speed value WS1 at the nominal height of the power grid tower by combining the wind speed data of 10 meters of the meteorological observation station around the power grid tower;
dynamically determining the power exponent of the wind speed of the whole layer of the near stratum by using the NCEP-GFS forecast data and a power exponent fitting method, and calculating second wind speed values of different height layers at the position of the anemometer tower and a second wind speed value WS2 at the nominal height of the power grid tower by combining the 10-meter height wind speed data of the meteorological observation station around the power grid tower;
dynamically determining wind speed power indexes of different height layers of a near stratum by using NCEP-GFS forecast data and a power index fitting method, and calculating third wind speed values of different height layers at the position of the anemometer tower and a third wind speed value WS3 at the nominal height of the power grid tower by combining 10m height wind speed data of a meteorological observation station around the power grid tower;
and calculating absolute errors AE at different heights, determining the weight w of the three wind speed values, and calculating the nominal height wind speed of the power grid tower at the current moment and different heights of the near stratum.
As a possible implementation manner of this embodiment, the wind speed forecast data of different heights includes wind speed forecast data of heights of 10 meters, 20 meters, 30 meters, 40 meters, 50 meters, 80 meters and 100 meters.
As a possible implementation manner of this embodiment, the acquiring wind speed data of 10 meters of height of the meteorological observation station around the power grid tower and wind speed data of different height layers of the anemometer tower includes:
extracting 10-meter wind speed observation values of meteorological observation stations around the power grid tower, and performing horizontal interpolation and terrain adjustment processing to obtain 10-meter height wind speed values at the power grid tower and wind measuring tower point positions; and extracting the wind speed values of the wind measuring towers at the periphery of the power grid tower at different height layers.
As a possible implementation manner of this embodiment, the determining a static power exponent of near-formation wind speed at different wind power levels by using wind speed data of an anemometer tower, and calculating first wind speed values of different height layers at the position of the anemometer tower and a first wind speed value WS1 at a nominal height of the power grid tower by using wind speed data of the power grid tower at a height of 10 meters in combination with wind speed data of a meteorological observation station around the power grid tower includes:
dividing the data of the anemometer tower into different wind power grade intervals by taking the wind speed of a 10-meter height layer of the anemometer tower as a reference;
obtaining near-stratum average wind speed profiles of different wind power grades;
fitting to obtain power indexes of different wind power grades by using a power index relation formula and a near-stratum average wind speed profile;
and calculating to obtain wind speed live analytical values of different height layers at the position of the anemometer tower and wind speed live analytical values of the nominal height of the power grid tower based on the wind speed of 10 meters at the meteorological observation station and the power indexes of different height layers.
As a possible implementation manner of this embodiment, the formula of the power exponent is as follows:
in the formula (I), the compound is shown in the specification,
is a height H 2 Wind speed (m/s);
is a height H 1 Wind speed (m/s), H 1 The height is generally 10 m; alpha is a wind shear index, the magnitude of which indicates the strength of the wind speed vertical shear.
As a possible implementation manner of this embodiment, the dynamically determining the power exponent of the wind speed of the whole layer of the near-earth layer by using the NCEP-GFS forecast data and the power exponent fitting method, and calculating the second wind speed values of different height layers at the position of the anemometer tower and the second wind speed value WS2 at the nominal height of the power grid tower by combining the wind speed data of 10 meters height of the meteorological observation station around the power grid tower includes:
extracting the nearest NCEP-GFS near-stratum wind speed forecast data to the live moment, and fitting by using a power exponent relational expression to obtain the whole layer wind speed gradient power exponent of the near stratum;
limiting the size of the power exponent by using a preset threshold interval;
and calculating to obtain wind speed live analytical values of different height layers at the position of the anemometer tower and wind speed live analytical values of the nominal height of the power grid tower based on the wind speed of 10 meters at the meteorological observation station and the power indexes of different height layers.
As a possible implementation manner of this embodiment, the dynamically determining wind speed power exponents of different height layers of a near stratum by using the NCEP-GFS forecast data and the power exponent fitting method, and calculating third wind speed values of different height layers at the position of the anemometer tower and a third wind speed value WS3 at the nominal height of the power grid tower by combining with the 10-meter height wind speed data of the power grid tower surrounding meteorological observation station includes:
extracting the wind speed of the near stratum of the NCEP-GFS, and performing power exponent relation fitting on the near points at different heights to obtain power exponents at different heights;
limiting the size of the power exponent by using a preset interval range;
and calculating to obtain wind speed live analytical values of different height layers at the position of the anemometer tower and wind speed live analytical values of the nominal height of the power grid tower based on the wind speed of 10 meters at the meteorological observation station and the power indexes of different height layers.
As a possible implementation manner of this embodiment, the calculating absolute errors AE at different heights, determining weights w of the three wind speed values, and calculating nominal height wind speeds of the power grid tower at different heights in the near-stratum at the current time includes:
calculating near-formation wind speeds WS1, WS2 and WS3 of the position of the anemometer tower at the current moment;
calculating absolute errors AE of different heights by using a wind speed live of the wind measuring tower and the obtained near-stratum wind speed of the wind measuring tower position, and determining the weights w of the near-stratum wind speeds WS1, WS2 and WS 3:
AE ijk ＝|WS ijk -O jk |
calculating the nominal height wind speed WS of the power grid tower with different heights of the near stratum at the current moment according to the weight:
wherein AE represents absolute error, WS represents wind speed calculated by three methods, O is wind speed observation of anemometer tower, and omega j And the weight corresponding to the wind speed observation at the moment j is shown, w is shown, the weight corresponds to different wind speed calculation methods, i is shown in different wind speed calculation methods, j is shown in different moments, k is shown in different heights of the near stratum, and a is shown in a preset constant.
According to the method, a power grid tower call height wind speed live analysis method based on numerical prediction and near-stratum observation is established based on wind field data such as a wind measuring tower, a meteorological observation station and meteorological numerical mode prediction from a model representing near-stratum wind speed vertical change, so that a reliable wind speed live at the power grid tower call height is obtained.
As shown in fig. 2, an apparatus for estimating nominal height wind speed of a power grid tower provided in an embodiment of the present invention includes:
the forecasting data acquisition module is used for acquiring wind speed forecasting data of a plurality of different heights in the NCEP-GFS near-stratum wind speed forecasting;
the wind speed data acquisition module is used for acquiring wind speed data of 10m height of a meteorological observation station around a power grid tower and wind speed data of different height layers of the anemometer tower;
the first wind speed calculation module is used for determining the static power index of the near-formation wind speed under different wind power grades by using the wind speed data of the anemometer tower, and calculating first wind speed values of different height layers at the position of the anemometer tower and a first wind speed value WS1 at the nominal height of the power grid tower by combining the wind speed data of the power grid tower at the height of 10 meters;
the second wind speed calculation module is used for dynamically determining the power exponent of the wind speed of the whole layer of the near stratum by using the NCEP-GFS forecast data and a power exponent fitting method, and calculating second wind speed values of different height layers at the position of the anemometer tower and a second wind speed value WS2 at the nominal height of the power grid tower by combining the wind speed data of the power grid tower at the height of 10 meters;
the third wind speed calculation module is used for dynamically determining wind speed power indexes of different height layers of a near stratum by using the NCEP-GFS forecast data and a power index fitting method, and calculating third wind speed values of different height layers at the position of the anemometer tower and a third wind speed value WS3 at the nominal height of the power grid tower by combining 10m height wind speed data of the meteorological observation station around the power grid tower;
and the current wind speed calculation module is used for calculating absolute errors AE at different heights, determining the weight w of the three wind speed values and calculating the nominal height wind speed of the power grid tower at the current moment and different heights of the near stratum.
As a possible implementation manner of this embodiment, the wind speed forecast data of different heights includes wind speed forecast data of heights of 10 meters, 20 meters, 30 meters, 40 meters, 50 meters, 80 meters and 100 meters.
As a possible implementation manner of this embodiment, the wind speed data acquisition module is specifically configured to extract a 10-meter wind speed observation value of a meteorological department observation station around a power grid tower, perform horizontal interpolation and terrain adjustment processing, and obtain a 10-meter height wind speed value at the power grid tower and a wind measurement tower; and extracting the wind speed values of different height layers of the anemometer tower around the power grid tower.
As a possible implementation manner of this embodiment, the first wind speed calculation module is specifically configured to:
dividing the data of the anemometer tower into different wind power grade intervals by taking the wind speed of a 10-meter height layer of the anemometer tower as a reference;
obtaining near-stratum average wind speed profiles of different wind power grades;
fitting to obtain power indexes of different wind power grades by using a power index relation formula and a near-stratum average wind speed profile;
and calculating to obtain wind speed actual analysis values of different height layers at the position of the anemometer tower and wind speed actual analysis values of the nominal height of the power grid tower based on the wind speed of 10 meters at the meteorological observation station and the power indexes of different height layers.
As a possible implementation manner of this embodiment, the formula of the power exponent is as follows:
in the formula (I), the compound is shown in the specification,
is a height H 2 Wind speed (m/s);
is a height H 1 Wind speed (m/s), H 1 The height is generally 10 m; alpha is a wind shear index, the magnitude of which indicates the strength of the wind speed vertical shear.
As a possible implementation manner of this embodiment, the second wind speed calculation module is specifically configured to:
extracting the nearest NCEP-GFS near-stratum wind speed forecast data to the live moment, and fitting by using a power exponent relational expression to obtain the whole layer wind speed gradient power exponent of the near stratum;
limiting the size of the power exponent by using a preset threshold interval;
and calculating to obtain wind speed live analytical values of different height layers at the position of the anemometer tower and wind speed live analytical values of the nominal height of the power grid tower based on the wind speed of 10 meters at the meteorological observation station and the power indexes of different height layers.
As a possible implementation manner of this embodiment, the third wind speed calculating module is specifically configured to:
extracting the NCEP-GFS near-formation wind speed, and performing power exponent relation fitting on the near points at different heights to obtain power exponents at different heights;
limiting the size of the power exponent by using a preset interval range;
and calculating to obtain wind speed live analytical values of different height layers at the position of the anemometer tower and wind speed live analytical values of the nominal height of the power grid tower based on the wind speed of 10 meters at the meteorological observation station and the power indexes of different height layers.
As a possible implementation manner of this embodiment, the current wind speed calculation module is specifically configured to:
calculating near-stratum wind speeds WS1, WS2 and WS3 of the position of the anemometer tower at the current moment;
calculating absolute errors AE of different heights by using the wind speed live condition of the wind measuring tower and the obtained near-stratum wind speed of the wind measuring tower position, and determining the weight w of the near-stratum wind speeds WS1, WS2 and WS 3:
AE ijk ＝|WS ijk -O jk |
calculating the nominal height wind speed WS of the power grid tower with different heights of the near stratum at the current moment according to the weight:
in the formula, AE represents absolute error, WS represents wind speed calculated by three methods, O is wind speed observation of a wind measuring tower, omega represents weights corresponding to wind speed observation at different moments, w represents weights corresponding to different wind speed calculation methods, i represents different wind speed calculation methods, j represents different moments, k represents different heights of a near stratum, and a represents a preset constant.
According to the device, a power grid nominal height wind speed live condition with the resolution of 1 hour of a target position is finally generated by inputting 0.25-degree multiplied by 0.25-degree spatial resolution, 1-hour time resolution and an NCEP-GFS near-stratum wind speed forecast updated every 6 hours and using a statistical correction method.
As shown in fig. 6, the process of estimating the nominal height wind speed of the tower of the power grid according to the present invention is as follows.
And extracting 7-layer wind field forecast with the height of 10 meters, 20 meters, 30 meters, 40 meters, 50 meters, 80 meters and 100 meters in the numerical forecast.
And extracting 10m wind speed observation values of observation stations of meteorological departments around the power grid tower, and obtaining the 10m wind speed value of the power grid tower by using methods such as horizontal interpolation, terrain adjustment and the like.
And extracting the wind speed observation values of the wind measuring tower at different height layers around the power grid tower.
And determining the static power exponent of the near-formation wind speed under different wind power levels by using wind speed data of the anemometer tower, and analyzing by a power exponent formula to obtain a wind speed live value (WS 1) at the nominal height of the power grid. The specific calculation method is as follows: (1) dividing the data of the anemometer tower into different wind power grade intervals by taking the wind speed of a 10-meter height layer of the anemometer tower as a reference; (2) obtaining the average wind speed profile of the near stratum with different wind power levels, as shown in FIG. 3; (3) fitting to obtain power indexes of different wind power grades by using a power index relation formula and a near-stratum average wind speed profile; (4) based on the wind speed of 10m height of the meteorological observation station and the power exponent at different height layers obtained by calculation, the wind speed live analytical values of different height layers at the position of the wind measuring tower and the wind speed live analytical value at the nominal height of the power grid tower can be further obtained.
The power exponent equation is as follows:
in the formula (I), the compound is shown in the specification,
is a height H 2 Wind speed (m/s);
is a height H 1 Wind speed (m/s), H 1 The height is generally 10 m; alpha is a wind shear index, the magnitude of which indicates the strength of the wind speed vertical shear.
And dynamically determining the power exponent of the wind speed of the whole layer of the near stratum by using the NCEP-GFS forecast data and a power exponent fitting method, and analyzing by using a power exponent formula to obtain a wind speed live value (WS 2) at the nominal height of the power grid. The method comprises the following specific steps: (1) extracting the nearest NCEP-GFS near-stratum wind speed forecast data (including wind speeds of 7 layers of height such as 10 meters, 20 meters, 30 meters, 40 meters, 50 meters, 80 meters, 100 meters and the like, as shown in figure 4) at the live moment, and fitting by using a power exponential relation to obtain the power exponent of the whole layer wind speed gradient of the near stratum; (2) limiting the size of the power exponent by using a preset threshold interval; (3) based on the wind speed of 10m height of the meteorological observation station and the power exponent at different height layers obtained by calculation, the wind speed live analytical values of different height layers at the position of the anemometer tower and the wind speed live analytical value at the nominal height of the power grid tower can be obtained.
And dynamically determining the wind speed power exponent of different height layers of the near stratum by using the NCEP-GFS forecast data and a power exponent fitting method, and analyzing by a power exponent formula to obtain a wind speed live value (WS 3) at the nominal height of the power grid. The specific calculation process is as follows: (1) extracting the wind speed of the near-formation of the NCEP-GFS, and performing power exponent relation fitting on the near points at different heights to obtain power exponents at different heights, as shown in FIG. 5, for example, the power exponent at 50m is obtained by fitting the wind speeds at the heights of 40 m, 50m and 80 m, and the power exponent fitting methods at other heights are similar; (2) limiting the size of the power exponent by using a preset interval range; (3) based on the wind speed of 10m height of the meteorological observation station and the power exponent of different height layers obtained through calculation, the wind speed live analysis value of different height layers at the position of the anemometer tower and the wind speed live analysis value of the nominal height of the power grid tower can be obtained.
Considering that the error causes of the three methods are different, and the respective errors are different when facing different weather systems, the wind speed at the designated height of the near stratum (such as the nominal height of a power grid tower) is further calculated by adopting an integrated method. The specific method comprises the following steps:
(1) and calculating the near-stratum wind speeds (WS 1, WS2 and WS 3) of the position of the anemoscope tower at the current moment according to the three methods by using numerical forecasting, a 10-meter wind speed live condition and a static wind speed gradient power exponent.
(2) And calculating absolute errors AE at different heights by using wind speed (WS 1, WS2 and WS 3) of the near-stratum at the wind measuring tower positions obtained by the three methods and the wind speed condition of the wind measuring tower nearby for a plurality of times (self-defined specific quantity), and further determining the weight w of each method.
AE ijk ＝|WS ijk -O jk |
In the formula, AE represents an absolute error, WS represents wind speed calculated by three methods, O is wind speed observation of a wind measuring tower, omega represents weights corresponding to wind speed observation at different moments, w represents weights corresponding to different wind speed calculation methods, i represents different wind speed calculation methods, j represents different moments, k represents different heights of a near stratum, and a represents a preset constant.
(3) And calculating the nominal height wind speed WS of the power grid tower with different heights of the near stratum at the current moment according to the weight.
The numerical prediction data of the invention uses the near-stratum wind speed prediction of the global prediction system NCEP-GFS of the American environment prediction center: spatial resolution: 0.25 °; temporal resolution: 1 hour; updating frequency: the total number of times per day was 4. A near-stratum wind speed live analysis experiment and test are carried out on a typical example of the Shandong Ji south chapter area in 2020, and the product comprises wind speed values (such as 10m, 30m, 50m and the like) at different heights of the near stratum and wind speed values at nominal heights of a power grid. The observation data of the wind speed required for verification are from the average wind speed of 1 hour of a meteorological station and the average wind speed of different heights of a wind measuring tower. The inspection indexes include: average Error of wind speed (Mean Error), average absolute Error MAE (Mean Average Error).
Table 1 lists main gale weather processes in the Shandong Ji south chapter and dune area in 2020, wherein each example W01-W05 is mainly a gale process in the north in winter and spring, and is mainly a systematic gale process accompanied with cold air in the north in the south, the average wind power level is about 4, and local gust can reach 6 levels to 7 levels; W06-W12 list the strong-convection weather during the strong-wind weather from spring end to summer, and the average wind power level is not large, but the strong-wind weather is often accompanied with local thunderstorm.
FIG. 7 shows the near-formation mean wind velocity profiles for different examples using different calculation methods: generally speaking, the wind speed profiles obtained by different calculation methods are closer to the actual condition of the wind measuring tower, and in the strong wind process in spring, the wind speed profiles obtained by calculation are larger than the actual condition of the wind measuring tower. Different calculation methods are compared to find that: average errors of different calculation methods in the summer strong wind process (W06-W12) are smaller and similar in performance, while tie errors of different calculation methods in the spring strong wind process (W01-W05) are more discrete; in spring, the wind speed profile obtained by the WS3 method is closer to the actual condition of the anemometer tower, and in summer, the WS effect of the integration method is better. From the form of the vertical profile, the wind speed profile calculated by various methods is relatively close to the wind speed profile of the anemometer tower.
The average absolute error and the average error of the wind speed forecast of different examples after different calculation methods are adopted are respectively listed in table 2 and table 3, and the results show that: the average absolute error/average error difference of each calculation method in the summer gale process (W06-W12) is smaller, and the performance is similar; in spring gale processes (W01-W05), the average absolute error/average error of each calculation method is more discrete, the average absolute error of the calculation method WS2 is smaller than that of other methods, and the average error of the calculation method WS1 is better than that of other methods.
In the whole view, the calculation method can effectively establish wind speed live analysis data comprising different heights of the near stratum by utilizing near stratum wind speed numerical prediction, wind measuring tower observation, wind speed observation numerical values of a meteorological observation station and basic geographic information, so that the wind speeds of the power grid towers at different heights of the near stratum can be better presumed, and the high-influence wind speed prediction and early warning capability of the power grid towers can be improved.
Table 1: major gale cases in the chapter-dune area of Shandong Jinan in 2020
| Personal sample number | Time | Weather phenomenon | Average wind power rating |
| W01 | 13 days in 2 months to 17 days in 2 months | Snow in small rain | Wind power level 3 |
| W02 | 11 days in 3 months to 12 days in 3 months | Little rain in sunny days | Wind power 4-level or so |
| W03 | 18 days in 3 months to 20 days in 3 months | All-weather | Wind power 4-level or so |
| W04 | 24 days in 4 months to 25 days in 4 months | Cloudy in sunny days | Wind power 3-4 |
| W05 | 28 days in 4 months to 1 day in 5 months | All-weather | Wind power level 4 or so |
| W06 | 16 days in 5 months to 18 days in 5 months | Thunderstorm weather changing into fine | Wind power 3-4 |
| W07 | 29 days in 5 months to 31 days in 5 months | Cloudy or cloudy | Wind power 3-4 |
| W08 | 2 days in 7 months to 5 days in 7 months | Light rain or thunderstorm rain | Wind power about 3 level |
| W09 | 8 months and 5 days-8 months and 7 days | Heavy to heavy rain | Wind power level 2 or so |
| W10 | 8 months and 12 days to 8 months and 15 days | Heavy storm or thunderstorm | 2 to 3 grades of wind power |
| W11 | 18 days in 8 months to 20 days in 8 months | Rainstorm or thunderstorm | Wind power 2-3 |
| W12 | 23 days in 8 months to 24 days in 8 months | Rainstorm or thunderstorm | 2 to 3 grades of wind power |
Table 2: mean absolute error of wind speed (unit: m/s) for different calculation methods
Table 3: average error of wind speed (unit: m/s) for different calculation methods
The invention establishes a power grid tower nominal height wind speed live conjecture method based on numerical prediction and near-stratum observation, and the inspection result shows that: the calculation method can effectively establish wind speed actual situation analysis data including different heights of the near stratum, namely near stratum wind speed profiles, by analyzing the near stratum wind speed numerical forecast, the wind measuring tower observation, the wind speed observation numerical value of the meteorological observation station and the basic geographic information, the calculated wind speed profiles are close to the wind speed profiles of the wind measuring tower, and the calculation method has better performance in systematic gale weather in spring and convective gale weather in summer. And furthermore, the wind speed at the nominal height of the power grid tower can be better presumed, and the high-influence wind speed forecasting and early warning capability at the power grid tower can be improved.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A method for conjecturing call height and wind speed of a power grid tower is characterized by comprising the following steps:
acquiring wind speed forecast data of a plurality of different heights in the NCEP-GFS near stratum wind speed forecast;
acquiring wind speed data of a meteorological observation station at the height of 10 meters around a power grid tower and wind speed data of different height layers of a anemometer tower;
determining a static power index of the near-formation wind speed under different wind power levels by using wind speed data of the anemometer tower, and calculating first wind speed values of different height layers at the position of the anemometer tower and a first wind speed value WS1 at the nominal height of the power grid tower by combining 10-meter height wind speed data of a meteorological observation station around the power grid tower;
dynamically determining the power exponent of the wind speed of the whole layer of the near stratum by using the NCEP-GFS forecast data and a power exponent fitting method, and calculating second wind speed values of different height layers at the position of the anemometer tower and a second wind speed value WS2 at the nominal height of the power grid tower by combining the 10-meter height wind speed data of the meteorological observation station around the power grid tower;
dynamically determining wind speed power indexes of different height layers of a near stratum by using NCEP-GFS forecast data and a power index fitting method, and calculating third wind speed values of different height layers at the position of the anemometer tower and a third wind speed value WS3 at the nominal height of the power grid tower by combining 10m height wind speed data of a meteorological observation station around the power grid tower;
and calculating absolute errors AE at different heights, determining the weight w of the three wind speed values, and calculating the nominal height wind speed of the power grid tower at the current moment and different heights of the near stratum.
2. The method for estimating nominal height and wind speed of power grid tower as claimed in claim 1, wherein the wind speed forecast data for different heights comprises wind speed forecast data for heights of 10 meters, 20 meters, 30 meters, 40 meters, 50 meters, 80 meters and 100 meters.
3. The method for estimating the call height and the wind speed of the power grid tower according to claim 1, wherein the step of acquiring the wind speed data of the meteorological observation station around the power grid tower at the height of 10 meters and the wind speed data of the anemometer tower at different height layers comprises the following steps:
extracting 10-meter wind speed observation values of meteorological department observation stations around the power grid tower, and performing horizontal interpolation and terrain adjustment processing to obtain 10-meter height wind speed values at the power grid tower and wind measuring tower point positions; and extracting the wind speed data of different height layers of the anemometer tower around the power grid tower.
4. The method for estimating the height and the wind speed of the tower call of the power grid according to any one of claims 1 to 3, wherein the method for determining the static power exponent of the wind speed of the near-formation at different wind power levels by using the wind speed data of the anemometer tower and calculating the first wind speed values of different height layers at the position of the anemometer tower and the first wind speed value WS1 at the height of the tower call of the power grid by combining the 10-meter height wind speed data of the meteorological observation station around the tower of the power grid comprises the following steps:
dividing the data of the anemometer tower into different wind power grade intervals by taking the wind speed of a 10-meter height layer of the anemometer tower as a reference;
obtaining near-stratum average wind speed profiles of different wind power grades;
fitting to obtain power indexes of different wind power grades by using a power index relation formula and a near-stratum average wind speed profile;
and calculating to obtain wind speed actual analysis values of different height layers at the position of the anemometer tower and wind speed actual analysis values of the nominal height of the power grid tower based on the wind speed of 10 meters at the meteorological observation station and the power indexes of different height layers.
5. The method for estimating nominal height and wind speed of power grid towers according to claim 4, wherein the power exponent is expressed as follows:
in the formula (I), the compound is shown in the specification,
is a height H 2 The wind speed of (d);
is a height H 1 The wind speed of (d); alpha is the wind shear index, indicating the strength of the wind speed vertical shear.
6. The method for estimating the height and the wind speed of the tower call scale of the power grid according to any one of claims 1 to 3, wherein the power exponent of the wind speed of the whole layer of the near stratum is dynamically determined by using the NCEP-GFS forecast data and the power exponent fitting method, and the second wind speed values of different height layers at the position of the wind measuring tower and the second wind speed value WS2 at the height of the tower call scale of the power grid are calculated by combining the 10-meter height wind speed data of the meteorological observation station around the power grid tower, and the method comprises the following steps:
extracting the NCEP-GFS near-stratum wind speed forecast data at the live moment, and fitting by using a power exponent relational expression to obtain a near-stratum whole-layer wind speed gradient power exponent;
limiting the size of the power exponent by using a preset threshold interval;
and calculating to obtain the wind speed live values of different height layers at the position of the anemometer tower and the wind speed live values of the nominal height positions of the power grid tower based on the wind speed of 10m height of the meteorological observation station and the power indexes of different height layers.
7. The method for estimating the height and the wind speed of the tower call scale of the power grid according to any one of claims 1 to 3, wherein the method for dynamically determining the power exponent of the wind speed of different height layers of the near stratum by using the NCEP-GFS forecast data and the power exponent fitting method, and calculating the third wind speed value of different height layers at the position of the wind measuring tower and the third wind speed value WS3 at the height of the tower call scale of the power grid by combining the 10m height wind speed data of the meteorological observation station around the power grid tower comprises the following steps:
extracting the wind speed of the near stratum of the NCEP-GFS, and performing power exponent relation fitting on the near points at different heights to obtain power exponents at different heights;
limiting the size of the power exponent by using a preset interval range;
and calculating to obtain the wind speed live values of different height layers at the position of the anemometer tower and the wind speed live values of the nominal height positions of the power grid tower based on the wind speed of 10m height of the meteorological observation station and the power indexes of different height layers.
8. The method for estimating the call height wind speed of the power grid tower according to any one of claims 1 to 3, wherein the steps of calculating the absolute error AE of different heights, determining the weight w of the three wind speed values, and calculating the call height wind speed of the power grid tower of different heights of the near stratum at the current moment comprise:
calculating near-formation wind speeds WS1, WS2 and WS3 of the position of the anemometer tower at the current moment;
calculating absolute errors AE of different heights by using a wind speed live of the wind measuring tower and the obtained near-stratum wind speed of the wind measuring tower position, and determining the weights w of the near-stratum wind speeds WS1, WS2 and WS 3:
AE ijk ＝|WS ijk -O jk |
calculating the nominal height wind speed WS of the power grid tower with different heights of the near stratum at the current moment according to the weight:
in the formula, AE represents absolute error, WS represents wind speed calculated by three methods, O is wind speed observation of a wind measuring tower, omega represents weights corresponding to wind speed observation at different moments, w represents weights corresponding to different wind speed calculation methods, i represents different wind speed calculation methods, j represents different moments, k represents different heights of a near stratum, and a represents a preset constant.
9. A device for conjecturing height and wind speed of a call scale of a power grid tower is characterized by comprising:
the forecasting data acquisition module is used for acquiring wind speed forecasting data of a plurality of different heights in the NCEP-GFS near-stratum wind speed forecasting;
the wind speed data acquisition module is used for acquiring wind speed data of a meteorological observation station around a power grid tower at the height of 10 meters and wind speed data of different height layers of the anemometer tower;
the first wind speed calculation module is used for determining the static power index of the near-formation wind speed under different wind power grades by using the wind speed data of the anemometer tower, and calculating first wind speed values of different height layers at the position of the anemometer tower and a first wind speed value WS1 at the nominal height of the power grid tower by combining the wind speed data of the power grid tower at the height of 10 meters;
the second wind speed calculation module is used for dynamically determining the power exponent of the wind speed of the whole layer of the near stratum by using the NCEP-GFS forecast data and a power exponent fitting method, and calculating second wind speed values of different height layers at the position of the anemometer tower and a second wind speed value WS2 at the nominal height of the power grid tower by combining the wind speed data of the power grid tower at the height of 10 meters;
the third wind speed calculation module is used for dynamically determining wind speed power indexes of different height layers of a near stratum by using the NCEP-GFS forecast data and a power index fitting method, and calculating third wind speed values of different height layers at the position of the anemometer tower and a third wind speed value WS3 at the nominal height of the power grid tower by combining the 10-meter height wind speed data of the meteorological observation station around the power grid tower;
and the current wind speed calculation module is used for calculating absolute errors AE at different heights, determining the weight w of the three wind speed values and calculating the nominal height wind speed of the power grid tower at the current moment and different heights of the near stratum.
10. The device for estimating nominal height and wind speed of power grid tower according to claim 9, wherein the wind speed forecast data of different heights comprises height wind speed forecast data of 10 meters, 20 meters, 30 meters, 40 meters, 50 meters, 80 meters and 100 meters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211323353.6A CN115793104B (en) | 2022-10-26 | 2022-10-26 | Method and device for estimating calling height wind speed of power grid tower |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211323353.6A CN115793104B (en) | 2022-10-26 | 2022-10-26 | Method and device for estimating calling height wind speed of power grid tower |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115793104A true CN115793104A (en) | 2023-03-14 |
| CN115793104B CN115793104B (en) | 2023-06-27 |
Family
ID=85433995
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211323353.6A Active CN115793104B (en) | 2022-10-26 | 2022-10-26 | Method and device for estimating calling height wind speed of power grid tower |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115793104B (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010096593A (en) * | 2008-10-15 | 2010-04-30 | Japan Weather Association | Wind prediction device and program |
| CN106934191A (en) * | 2015-12-30 | 2017-07-07 | 中国电力科学研究院 | A kind of WRF pattern correction wind methods based on self-similarity |
| CN108491630A (en) * | 2018-03-23 | 2018-09-04 | 河海大学 | A kind of wind speed Extrapolation method based on atmospheric stability wind direction standard deviation method |
| CN108518117A (en) * | 2018-03-30 | 2018-09-11 | 国网山东省电力公司烟台供电公司 | A kind of compound tower head in double loop and a kind of narrow base power transmission tower |
| CN108595872A (en) * | 2018-05-07 | 2018-09-28 | 深圳供电局有限公司 | A kind of powernet security and stability analysis method |
| CN110598939A (en) * | 2019-09-18 | 2019-12-20 | 中国电建集团青海省电力设计院有限公司 | Method for improving wind measuring efficiency and reliability of wind measuring system |
| CN111239857A (en) * | 2020-02-18 | 2020-06-05 | 潘新民 | Strong wind forecasting method for special terrain |
| US20210063429A1 (en) * | 2018-08-28 | 2021-03-04 | Ball Aerospace & Technologies Corp. | Optical Wind Lidar-Based Multifunctional Instrument for Enhanced Measurements and Prediction of Clear Air Turbulence and Other Wind-Based Aviation Related Phenomena |
| CN113222019A (en) * | 2021-05-13 | 2021-08-06 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | Meteorological forecast data processing method, device and equipment for power transmission line tower |
| CN114021858A (en) * | 2021-12-06 | 2022-02-08 | 国网浙江省电力有限公司经济技术研究院 | Refined wind speed prediction method for power transmission line |
-
2022
- 2022-10-26 CN CN202211323353.6A patent/CN115793104B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010096593A (en) * | 2008-10-15 | 2010-04-30 | Japan Weather Association | Wind prediction device and program |
| CN106934191A (en) * | 2015-12-30 | 2017-07-07 | 中国电力科学研究院 | A kind of WRF pattern correction wind methods based on self-similarity |
| CN108491630A (en) * | 2018-03-23 | 2018-09-04 | 河海大学 | A kind of wind speed Extrapolation method based on atmospheric stability wind direction standard deviation method |
| CN108518117A (en) * | 2018-03-30 | 2018-09-11 | 国网山东省电力公司烟台供电公司 | A kind of compound tower head in double loop and a kind of narrow base power transmission tower |
| CN108595872A (en) * | 2018-05-07 | 2018-09-28 | 深圳供电局有限公司 | A kind of powernet security and stability analysis method |
| US20210063429A1 (en) * | 2018-08-28 | 2021-03-04 | Ball Aerospace & Technologies Corp. | Optical Wind Lidar-Based Multifunctional Instrument for Enhanced Measurements and Prediction of Clear Air Turbulence and Other Wind-Based Aviation Related Phenomena |
| CN110598939A (en) * | 2019-09-18 | 2019-12-20 | 中国电建集团青海省电力设计院有限公司 | Method for improving wind measuring efficiency and reliability of wind measuring system |
| CN111239857A (en) * | 2020-02-18 | 2020-06-05 | 潘新民 | Strong wind forecasting method for special terrain |
| CN113222019A (en) * | 2021-05-13 | 2021-08-06 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | Meteorological forecast data processing method, device and equipment for power transmission line tower |
| CN114021858A (en) * | 2021-12-06 | 2022-02-08 | 国网浙江省电力有限公司经济技术研究院 | Refined wind speed prediction method for power transmission line |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115793104B (en) | 2023-06-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110298115B (en) | Wind field power downscaling method based on simplified terrain aerodynamic parameters | |
| CN103336860B (en) | A kind of electrical network wind speed profile drawing generating method | |
| Tieleman | Strong wind observations in the atmospheric surface layer | |
| US20160203245A1 (en) | Method for simulating wind field of extreme arid region based on wrf | |
| Ahmed | Investigation of wind characteristics and wind energy potential at Ras Ghareb, Egypt | |
| CN108983320A (en) | A kind of numerical weather forecast-artificial intelligence coupling prediction method of coastal typhoon Maximum wind speed | |
| CN102254239A (en) | Power grid wind damage early warning system based on micro-landform wind field distribution and typhoon superimposed effect | |
| CN104182594A (en) | Method for drawing power system wind area graph | |
| CN112541654B (en) | Regional wind energy resource refined assessment method | |
| Morgenstern et al. | Differentiating lightning in winter and summer with characteristics of the wind field and mass field | |
| CN115808727A (en) | Hundred-meter-level gust objective forecasting method and device | |
| Hoekstra et al. | Weather forecasted thermal line rating model for the Netherlands | |
| CN104951492B (en) | Based on the monitoring of power grid GIS wind power plant Professional Meteorological and method for early warning and system | |
| CN104361532A (en) | Method for researching influence of micro-landform strong wind area on safety operation of electric transmission line | |
| CN116384733A (en) | Power transmission line risk early warning method based on weather radar in strong convection weather | |
| CN111666725A (en) | Anemometer tower planning and site selection method and system suitable for wind power plant with non-complex terrain | |
| CN107316109B (en) | Method, system and device for predicting wind speed of overhead line on ground in winter | |
| CN114444020A (en) | Air temperature forecast correction system for power grid tower point | |
| Chen et al. | Observation of nocturnal low-level wind shear and particulate matter in urban Beijing using a Doppler wind lidar | |
| CN113075751A (en) | Method and system for fusing observation data in short-term forecasting | |
| CN113176420A (en) | Wind speed forecasting and correcting system for power grid tower point | |
| CN115793104A (en) | Method and device for conjecturing call height and wind speed of power grid tower | |
| CN115511192A (en) | Rainfall forecasting method and system based on lightning data assimilation | |
| CN110298114B (en) | Wind field power downscaling method and storage medium | |
| CN113325488A (en) | Method and system for predicting gust occurrence range in strong convection weather |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |