CN108321749B - Power transmission line windage yaw forecasting method and device based on numerical meteorological data - Google Patents

Power transmission line windage yaw forecasting method and device based on numerical meteorological data Download PDF

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CN108321749B
CN108321749B CN201810063123.8A CN201810063123A CN108321749B CN 108321749 B CN108321749 B CN 108321749B CN 201810063123 A CN201810063123 A CN 201810063123A CN 108321749 B CN108321749 B CN 108321749B
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transmission line
power transmission
meteorological data
wind speed
insulator
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CN108321749A (en
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李鹏
刘彬
杨加伦
费香泽
李丹煜
展雪萍
姬昆鹏
张立春
赵彬
司佳钧
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
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China Electric Power Research Institute Co Ltd CEPRI
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Abstract

The invention provides a method and a device for forecasting the windage yaw of a power transmission line based on numerical meteorological data. The technical scheme provided by the invention can forecast the windage yaw state of the target power transmission line in advance, provides technical support for timely and effectively preventing and controlling the windage yaw disaster of the power transmission line, and has wide application prospect in the field of power grid disaster prevention and reduction.

Description

Power transmission line windage yaw forecasting method and device based on numerical meteorological data
Technical Field
The invention relates to the technical field of disaster prevention and reduction of a power transmission line, in particular to a method and a device for forecasting windage yaw of the power transmission line based on numerical meteorological data.
Background
The wind deviation of the power transmission line refers to the wind deviation swing phenomenon generated by the insulator string and the power transmission line hung by the insulator string under the action of wind load. Wind deviation can cause serious electrical and mechanical faults, and has great harm to the safe and stable operation of a power grid. In order to improve the pertinence and timeliness of the windage yaw prevention and control work of the power transmission line in the operation and maintenance stage, it is necessary to develop windage yaw forecasting. The wind deflection angle is a key index for describing the wind deflection of the power transmission line, the maximum static wind deflection angle of an insulator string is solved mainly through a rigid body straight rod method in the wind deflection research in the prior art, the calculation problem of the static wind deflection angle and model parameters thereof in the design stage is solved, and the real-time prediction and early warning of the dynamic wind deflection angle of the power transmission line cannot be realized. There are two difficulties in accurately forecasting the wind drift angle of the transmission line: 1) due to uncertainty of a wind field and micro-terrain factors, the actual wind load of the position of the line is different from the observed value of a meteorological station, and wind field data of an actual power transmission line is adopted as much as possible when the wind drift angle is predicted; 2) due to the pulsating effect of the wind field, the static wind drift angle calculated based on the average wind load cannot accurately forecast the wind drift state of the power transmission line.
In the prior art, electric transmission line windage yaw flashover early warning is carried out based on numerical weather forecast results, but the forecasting of dynamic windage yaw angles of electric transmission lines is lacked mainly aiming at forecasting of static windage yaw angles and windage flashover voltages, and the accuracy of the forecasting results of the windage yaw states of the electric transmission lines is low.
Disclosure of Invention
In order to overcome the defect of accuracy of a prediction result of a windage yaw state of a power transmission line in the prior art, the invention provides a method and a device for predicting the windage yaw of the power transmission line based on numerical meteorological data.
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
on one hand, the invention provides a power transmission line windage yaw forecasting method based on numerical meteorological data, which comprises the following steps:
analyzing the received numerical meteorological data, and determining an included angle between the power transmission line and the wind direction and a random wind speed according to the analyzed meteorological data;
calculating a random wind load according to an included angle between the power transmission line and the wind direction and a random wind speed, and calculating the horizontal displacement of the power transmission line according to the random wind load;
and determining the dynamic windage yaw angle of the insulator according to the horizontal displacement of the power transmission line, and forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator.
The analyzing the received numerical meteorological data comprises the following steps:
coordinate correction is carried out on the numerical meteorological data through a geographic information system to obtain the numerical meteorological data after coordinate correction, and the numerical meteorological data after coordinate correction is stored;
positioning all towers to grids with the same precision as the numerical meteorological data after coordinate correction according to the geographic coordinates of the towers, and obtaining the analyzed meteorological data through grid indexing according to the rows and the columns of the towers, wherein the analyzed meteorological data comprises the average wind speed and the wind direction of the power transmission line corresponding to the numerical meteorological data.
According to the analyzed meteorological data, determining an included angle between the power transmission line and the wind direction according to the following formula:
θ＝arctan|(k2-k1)/(1+k1k2)|
wherein theta represents the included angle between the power transmission line and the wind direction, and k1Representing the slope, k, of the transmission line2Indicating the wind direction slope.
Determining the random wind speed according to the analyzed meteorological data by the following process:
according to the average wind speed at standard altitude, by
Figure BDA0001555915370000021
Determining an average wind speed at a reference altitude, based on
Figure BDA0001555915370000022
Obtaining random wind speed by a harmonic superposition method; wherein,
Figure BDA0001555915370000023
denotes an average wind speed at a reference altitude, v denotes an average wind speed at a standard altitude, and β denotes a terrain roughness index.
According to the included angle between the power transmission line and the wind direction and the random wind speed, calculating the random wind load according to the following formula:
F(t)＝0.625αμscdv(t)2Lsin2θ
wherein F (t) represents the random wind load at the time t, v (t) represents the random wind speed at the time t, alpha represents the wind pressure uneven coefficient, muscAnd the size coefficient of the power transmission line is represented, d represents the outer diameter of the power transmission line, and L represents the span of the power transmission line.
The step of calculating the horizontal displacement of the power transmission line according to the random wind load comprises the following steps:
determining a nonlinear finite element power equation of the power transmission line according to the following formula:
Md″(t)+Cd′(t)+Kd(t)＝F(t)
wherein M represents a mass matrix of the insulator, C represents a rigidity matrix of the insulator, K represents a damping matrix of the insulator, d (t) represents the horizontal displacement of the transmission line, d '(t) represents a first derivative of d (t), and d' (t) represents a second derivative of d (t);
solving the nonlinear finite element power equation of the transmission line to obtain d (t).
According to the horizontal displacement of the power transmission line, determining the dynamic wind deflection angle of the insulator according to the following formula:
Figure BDA0001555915370000031
wherein,
Figure BDA0001555915370000032
and the dynamic windage yaw angle of the insulator at the time t is shown, and l represents the length of the insulator.
On the other hand, the invention provides a power transmission line windage yaw forecasting device based on numerical meteorological data, which comprises:
the determining module is used for analyzing the received numerical meteorological data and determining an included angle between the power transmission line and the wind direction and a random wind speed according to the analyzed meteorological data;
the calculation module is used for calculating random wind load according to the included angle between the power transmission line and the wind direction and the random wind speed and calculating the horizontal displacement of the power transmission line according to the random wind load;
and the forecasting module is used for determining the dynamic windage yaw angle of the insulator according to the horizontal displacement of the power transmission line and forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator.
The determining module comprises:
the receiving unit is used for receiving numerical meteorological data according to a preset interval by adopting a file transmission protocol, wherein the numerical meteorological data comprises the average wind speed and the wind direction at the standard height.
The determining module comprises:
the analysis unit is used for analyzing the received numerical meteorological data according to the following processes:
coordinate correction is carried out on the numerical meteorological data through a geographic information system to obtain the numerical meteorological data after coordinate correction, and the numerical meteorological data after coordinate correction is stored;
positioning all towers to grids with the same precision as the numerical meteorological data after coordinate correction according to the geographic coordinates of the towers, and obtaining the analyzed meteorological data through grid indexing according to the rows and the columns of the towers, wherein the analyzed meteorological data comprises the average wind speed and the wind direction of the power transmission line corresponding to the numerical meteorological data.
The determining module comprises:
and the included angle determining unit is used for determining the included angle between the power transmission line and the wind direction according to the analyzed meteorological data and the following formula:
θ＝arctan|(k2-k1)/(1+k1k2)|
wherein theta represents the included angle between the power transmission line and the wind direction, and k1Representing the slope, k, of the transmission line2Indicating the wind direction slope.
The random wind speed determining unit is used for determining the random wind speed according to the analyzed meteorological data according to the following processes:
according to the average wind speed at standard altitude, by
Figure BDA0001555915370000033
Determining an average wind speed at a reference altitude, based on
Figure BDA0001555915370000034
Obtaining random wind speed by a harmonic superposition method; wherein,
Figure BDA0001555915370000041
denotes an average wind speed at a reference altitude, v denotes an average wind speed at a standard altitude, and β denotes a terrain roughness index.
The calculation module comprises:
the random wind load calculation unit is used for calculating the random wind load according to the included angle between the power transmission line and the wind direction and the random wind speed and according to the following formula:
F(t)＝0.625αμscdv(t)2Lsin2θ
wherein F: (t) represents random wind load at time t, v (t) represents random wind speed at time t, alpha represents wind pressure non-uniformity coefficient, muscAnd the size coefficient of the power transmission line is represented, d represents the outer diameter of the power transmission line, and L represents the span of the power transmission line.
The calculation module further includes a horizontal displacement calculation unit including:
the equation determining unit is used for determining a nonlinear finite element power equation of the power transmission line according to the following formula:
Md″(t)+Cd′(t)+Kd(t)＝F(t)
wherein M represents a mass matrix of the insulator, C represents a rigidity matrix of the insulator, K represents a damping matrix of the insulator, d (t) represents the horizontal displacement of the transmission line, d '(t) represents a first derivative of d (t), and d' (t) represents a second derivative of d (t);
and the solving unit is used for solving the nonlinear finite element power equation of the power transmission line to obtain d (t).
The forecasting module comprises:
the dynamic wind drift angle determining unit is used for determining the dynamic wind drift angle of the insulator according to the horizontal displacement of the power transmission line and the following formula:
Figure BDA0001555915370000042
wherein,
Figure BDA0001555915370000043
the dynamic wind deflection angle of the insulator at the moment t is shown, and l represents the length of the insulator;
and the forecasting unit is used for forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator.
Compared with the closest prior art, the technical scheme provided by the invention has the following beneficial effects:
according to the method for forecasting the windage yaw of the power transmission line based on the numerical meteorological data, the received numerical meteorological data are analyzed, the included angle between the power transmission line and the wind direction and the random wind speed are determined according to the analyzed meteorological data, the random wind load is calculated according to the included angle between the power transmission line and the wind direction and the random wind speed, the horizontal displacement of the power transmission line is calculated according to the random wind load, the dynamic windage yaw angle of the insulator is determined according to the horizontal displacement of the power transmission line, the windage yaw state of the power transmission line is forecasted according to the dynamic windage yaw angle of the insulator, the windage yaw forecast of the power transmission line based on the numerical meteorological data and the dynamic windage yaw angle of the insulator is achieved, and the accuracy of the forecast result of the windage yaw state of the power transmission line is improved;
the power transmission line windage yaw forecasting device based on the numerical meteorological data further comprises a determining module, a calculating module and a forecasting module, wherein the determining module is used for analyzing the received numerical meteorological data and determining an included angle between the power transmission line and the wind direction and a random wind speed according to the analyzed meteorological data; the calculation module is used for calculating random wind load according to the included angle between the power transmission line and the wind direction and the random wind speed and calculating the horizontal displacement of the power transmission line according to the random wind load; the forecasting module is used for determining the dynamic windage yaw angle of the insulator according to the horizontal displacement of the power transmission line and forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator, so that the windage yaw forecasting of the power transmission line based on numerical meteorological data and the dynamic windage yaw angle of the insulator is realized, and the accuracy of the windage yaw state forecasting result of the power transmission line is improved;
in the technical scheme provided by the invention, the geographic information system is used for carrying out coordinate correction and index positioning on the numerical meteorological data received by adopting the file transmission protocol, and the analyzed numerical meteorological data is accurately obtained;
according to the technical scheme provided by the invention, the average wind speed and the wind direction of the target power transmission line are adopted to forecast the wind deviation of the power transmission line, so that the accuracy of random wind load is improved, and errors caused by adopting general regional meteorological forecast data are avoided;
the technical scheme provided by the invention can forecast the windage yaw state of the target power transmission line in advance, provides technical support for timely and effectively preventing and controlling the windage yaw disaster of the power transmission line, and has wide application prospect in the field of power grid disaster prevention and reduction.
Drawings
FIG. 1 is a flow chart of a method for forecasting windage yaw of a power transmission line based on numerical meteorological data in an embodiment of the invention;
FIG. 2 is a schematic diagram of random wind speeds at a power transmission line in an embodiment of the present invention;
fig. 3 is a schematic diagram of horizontal displacement of the transmission line in the embodiment of the invention;
fig. 4 is a schematic view of a dynamic windage yaw angle of an insulator according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The embodiment of the invention provides a power transmission line windage yaw forecasting method based on numerical meteorological data, a specific flow chart is shown in figure 1, and the specific process is as follows:
s101: analyzing the received numerical meteorological data, and determining an included angle between the power transmission line and the wind direction and a random wind speed according to the analyzed meteorological data;
s102: calculating a random wind load according to the determined included angle between the power transmission line and the wind direction and the random wind speed, and calculating the horizontal displacement of the power transmission line according to the random wind load;
s103: and determining the dynamic windage yaw angle of the insulator according to the horizontal displacement of the power transmission line calculated in the step S102, and forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator.
In S101, the numerical weather data is received at preset intervals by using a file transfer protocol, and the numerical weather data includes an average wind speed and a wind direction at a standard height.
In S101, the specific process of analyzing the received numerical weather data is as follows:
1) coordinate correction is carried out on the numerical meteorological data through a geographic information system to obtain the numerical meteorological data after coordinate correction, and the numerical meteorological data after coordinate correction is stored;
2) positioning all towers to grids with the same precision as the numerical meteorological data after coordinate correction according to the geographic coordinates of the towers, and obtaining the analyzed meteorological data through grid indexing according to the rows and the columns of the towers, wherein the analyzed meteorological data comprises the average wind speed and the wind direction of the power transmission line corresponding to the numerical meteorological data.
The specific process of determining the included angle between the power transmission line and the wind direction and the random wind speed according to the analyzed meteorological data in the step S101 is as follows:
1) according to the analyzed meteorological data, determining an included angle between the power transmission line and the wind direction according to the following formula:
θ＝arctan|(k2-k1)/(1+k1k2)|
wherein theta represents the included angle between the power transmission line and the wind direction, and k1Representing the slope, k, of the transmission line2Represents the wind direction slope;
2) determining the random wind speed according to the analyzed meteorological data by the following process:
according to the average wind speed at standard altitude, by
Figure BDA0001555915370000061
Determining an average wind speed at a reference altitude, based on
Figure BDA0001555915370000062
And obtaining random wind speed (as shown in figure 2) by a harmonic superposition method; wherein,
Figure BDA0001555915370000063
denotes an average wind speed at a reference altitude, v denotes an average wind speed at a standard altitude, and β denotes a terrain roughness index.
In the step S102, a random wind load is calculated according to an included angle between the power transmission line and the wind direction and a random wind speed as follows:
F(t)＝0.625αμscdv(t)2Lsin2θ
wherein F (t) represents the random wind load at the time t, v (t) represents the random wind speed at the time t, alpha represents the wind pressure uneven coefficient, muscAnd the size coefficient of the power transmission line is represented, d represents the outer diameter of the power transmission line, and L represents the span of the power transmission line.
In the above S102, calculating the horizontal displacement of the power transmission line according to the random wind load includes:
1) determining a nonlinear finite element power equation of the power transmission line according to the following formula:
Md″(t)+Cd′(t)+Kd(t)＝F(t)
wherein M represents a mass matrix of the insulator, C represents a rigidity matrix of the insulator, K represents a damping matrix of the insulator, d (t) represents the horizontal displacement of the transmission line, d '(t) represents a first derivative of d (t), and d' (t) represents a second derivative of d (t);
2) solving the nonlinear finite element power equation of the transmission line to obtain d (t), as shown in fig. 3.
In step S103, the dynamic windage yaw angle of the insulator is determined according to the following formula:
Figure BDA0001555915370000071
wherein,
Figure BDA0001555915370000072
the dynamic windage yaw angle of the insulator at time t is shown (as shown in fig. 4), and l is the length of the insulator.
Based on the same inventive concept, the embodiment of the invention also provides a power transmission line windage yaw forecasting device based on numerical meteorological data, which comprises a determining module, a calculating module and a forecasting module, wherein the functions of the modules are respectively described in detail as follows:
the determining module is used for analyzing the received numerical meteorological data and determining an included angle between the power transmission line and the wind direction and a random wind speed according to the analyzed meteorological data;
the computing module is used for computing random wind load according to an included angle between the power transmission line and the wind direction and random wind speed, and computing the horizontal displacement of the power transmission line according to the random wind load;
the forecasting module is used for determining the dynamic windage yaw angle of the insulator according to the horizontal displacement of the power transmission line and forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator.
The above-mentioned determining module includes:
1) the receiving unit is used for receiving numerical meteorological data according to a preset interval by adopting a file transmission protocol, wherein the numerical meteorological data comprises the average wind speed and the wind direction at the standard height.
2) The analysis unit is used for analyzing the received numerical meteorological data according to the following processes:
2-1) carrying out coordinate correction on the numerical meteorological data through a geographic information system to obtain the numerical meteorological data after coordinate correction, and storing the numerical meteorological data after coordinate correction;
and 2-2) positioning all towers to grids with the same precision as the numerical meteorological data after coordinate correction according to the geographic coordinates of the towers, and obtaining analyzed meteorological data through grid indexing according to the rows and columns of the towers, wherein the analyzed meteorological data comprise the average wind speed and the wind direction of the power transmission line corresponding to the numerical meteorological data.
3) And the included angle determining unit is used for determining the included angle between the power transmission line and the wind direction according to the analyzed meteorological data and the following formula:
θ＝arctan|(k2-k1)/(1+k1k2)|
wherein theta represents the included angle between the power transmission line and the wind direction, and k1Representing the slope, k, of the transmission line2Indicating the wind direction slope.
4) A wind speed determination unit for determining a wind speed based on the average wind speed at the standard height
Figure BDA0001555915370000073
Determining an average wind speed at a reference altitude, based on
Figure BDA0001555915370000074
And obtaining random wind speed (as shown in figure 2) by a harmonic superposition method; wherein,
Figure BDA0001555915370000075
denotes the average wind speed at the reference altitude, v denotes the average wind speed at the standard altitude, β denotes the topographic roughnessAnd (4) degree index.
The above-mentioned calculation module includes:
1) the random wind load calculation unit is used for calculating the random wind load according to the included angle between the power transmission line and the wind direction and the random wind speed and according to the following formula:
F(t)＝0.625αμscdv(t)2Lsin2θ
wherein F (t) represents the random wind load at the time t, v (t) represents the random wind speed at the time t, alpha represents the wind pressure uneven coefficient, muscAnd the size coefficient of the power transmission line is represented, d represents the outer diameter of the power transmission line, and L represents the span of the power transmission line.
2) A horizontal displacement calculation unit including:
2-1) an equation determining unit for determining a nonlinear finite element power equation of the transmission line according to the following formula:
Md″(t)+Cd′(t)+Kd(t)＝F(t)
wherein M represents a mass matrix of the insulator, C represents a rigidity matrix of the insulator, K represents a damping matrix of the insulator, d (t) represents the horizontal displacement of the transmission line, d '(t) represents a first derivative of d (t), and d' (t) represents a second derivative of d (t);
2-1) a solving unit for solving the nonlinear finite element power equation of the transmission line to obtain d (t).
The forecasting module comprises:
1) the dynamic wind drift angle determining unit is used for determining the dynamic wind drift angle of the insulator according to the horizontal displacement of the power transmission line and the following formula:
Figure BDA0001555915370000081
wherein,
Figure BDA0001555915370000082
the dynamic wind deflection angle of the insulator at the moment t is shown, and l represents the length of the insulator;
2) and the forecasting unit is used for forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator.
For convenience of description, each part of the above-described apparatus is separately described as being functionally divided into various modules or units. Of course, the functionality of the various modules or units may be implemented in the same one or more pieces of software or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only intended to illustrate the technical solution of the present invention and not to limit the same, and a person of ordinary skill in the art can make modifications or equivalents to the specific embodiments of the present invention with reference to the above embodiments, and such modifications or equivalents without departing from the spirit and scope of the present invention are within the scope of the claims of the present invention as set forth in the claims.

Claims (8)

1. A power transmission line windage yaw forecasting method based on numerical meteorological data is characterized by comprising the following steps:
analyzing the received numerical meteorological data, and determining an included angle between the power transmission line and the wind direction and a random wind speed according to the analyzed meteorological data;
calculating a random wind load according to an included angle between the power transmission line and the wind direction and a random wind speed, and calculating the horizontal displacement of the power transmission line according to the random wind load;
determining a dynamic windage yaw angle of the insulator according to the horizontal displacement of the power transmission line, and forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator;
the analyzing the received numerical meteorological data comprises the following steps:
coordinate correction is carried out on the numerical meteorological data through a geographic information system to obtain the numerical meteorological data after coordinate correction, and the numerical meteorological data after coordinate correction is stored;
positioning all towers into grids with the same precision as the numerical meteorological data after coordinate correction according to the geographic coordinates of the towers, and obtaining analyzed meteorological data through grid indexing according to the rows and columns of the towers, wherein the analyzed meteorological data comprise the average wind speed and the wind direction of the power transmission line corresponding to the numerical meteorological data;
according to the analyzed meteorological data, determining an included angle between the power transmission line and the wind direction according to the following formula:
θ＝arctan|(k2-k1)/(1+k1k2)|
wherein theta represents the included angle between the power transmission line and the wind direction, and k1Representing the slope, k, of the transmission line2Represents the wind direction slope; determining the random wind speed according to the analyzed meteorological data by the following process:
according to the average wind speed at standard altitude, by
Figure FDA0003363203900000011
Determining an average wind speed at a reference altitude, based on
Figure FDA0003363203900000012
Obtaining random wind speed by a harmonic superposition method; wherein,
Figure FDA0003363203900000013
denotes an average wind speed at a reference altitude, v denotes an average wind speed at a standard altitude, β denotes a terrain roughness index, and z denotes a reference altitude.
2. The method for forecasting the windage yaw of the power transmission line based on the numerical meteorological data as recited in claim 1, wherein the random wind load is calculated according to the included angle between the power transmission line and the wind direction and the random wind speed as follows:
F(t)＝0.625αμscdv(t)2Lsin2θ
wherein F (t) represents the random wind load at the time t, v (t) represents the random wind speed at the time t, alpha represents the wind pressure uneven coefficient, muscAnd the size coefficient of the power transmission line is represented, d represents the outer diameter of the power transmission line, and L represents the span of the power transmission line.
3. The method for forecasting the windage yaw of the power transmission line based on the numerical meteorological data as claimed in claim 2, wherein the calculating the horizontal displacement of the power transmission line according to the random wind load comprises:
determining a nonlinear finite element power equation of the power transmission line according to the following formula:
Md″(t)+Cd′(t)+Kd(t)＝F(t)
wherein M represents a mass matrix of the insulator, C represents a rigidity matrix of the insulator, K represents a damping matrix of the insulator, d (t) represents the horizontal displacement of the transmission line, d '(t) represents a first derivative of d (t), and d' (t) represents a second derivative of d (t);
solving the nonlinear finite element power equation of the transmission line to obtain d (t).
4. The method for forecasting the windage yaw of the power transmission line based on the numerical meteorological data as recited in claim 3, wherein the dynamic windage yaw angle of the insulator is determined according to the following formula according to the horizontal displacement of the power transmission line:
Figure FDA0003363203900000021
wherein,
Figure FDA0003363203900000022
and the dynamic windage yaw angle of the insulator at the time t is shown, and l represents the length of the insulator.
5. The utility model provides a transmission line windage yaw forecasting device based on numerical value meteorological data which characterized in that includes:
the determining module is used for analyzing the received numerical meteorological data and determining an included angle between the power transmission line and the wind direction and a random wind speed according to the analyzed meteorological data;
the calculation module is used for calculating random wind load according to the included angle between the power transmission line and the wind direction and the random wind speed and calculating the horizontal displacement of the power transmission line according to the random wind load;
the forecasting module is used for determining a dynamic windage yaw angle of the insulator according to the horizontal displacement of the power transmission line and forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator;
the determining module comprises:
the analysis unit is used for analyzing the received numerical meteorological data according to the following processes:
coordinate correction is carried out on the numerical meteorological data through a geographic information system to obtain the numerical meteorological data after coordinate correction, and the numerical meteorological data after coordinate correction is stored;
positioning all towers into grids with the same precision as the numerical meteorological data after coordinate correction according to the geographic coordinates of the towers, and obtaining analyzed meteorological data through grid indexing according to the rows and columns of the towers, wherein the analyzed meteorological data comprise the average wind speed and the wind direction of the power transmission line corresponding to the numerical meteorological data;
the determining module further comprises:
and the included angle determining unit is used for determining the included angle between the power transmission line and the wind direction according to the analyzed meteorological data and the following formula:
θ＝arctan|(k2-k1)/(1+k1k2)|
wherein theta represents the included angle between the power transmission line and the wind direction, and k1Representing the slope, k, of the transmission line2Represents the wind direction slope; the random wind speed determining unit is used for determining the random wind speed according to the analyzed meteorological data according to the following processes:
according to the average wind speed at standard altitude, by
Figure FDA0003363203900000032
Determining an average wind speed at a reference altitude, based on
Figure FDA0003363203900000033
Obtaining random wind speed by a harmonic superposition method; wherein,
Figure FDA0003363203900000034
denotes an average wind speed at a reference altitude, v denotes an average wind speed at a standard altitude, β denotes a terrain roughness index, and z denotes a reference altitude.
6. The device according to claim 5, wherein the computing module comprises:
the random wind load calculation unit is used for calculating the random wind load according to the included angle between the power transmission line and the wind direction and the random wind speed and according to the following formula:
F(t)＝0.625αμscdv(t)2Lsin2θ
wherein F (t) represents the random wind load at the time t, v (t) represents the random wind speed at the time t, alpha represents the wind pressure uneven coefficient, muscAnd the size coefficient of the power transmission line is represented, d represents the outer diameter of the power transmission line, and L represents the span of the power transmission line.
7. The device according to claim 6, wherein the calculation module further comprises a horizontal displacement calculation unit, and the horizontal displacement calculation unit comprises: the equation determining unit is used for determining a nonlinear finite element power equation of the power transmission line according to the following formula:
Md″(t)+Cd′(t)+Kd(t)＝F(t)
wherein M represents a mass matrix of the insulator, C represents a rigidity matrix of the insulator, K represents a damping matrix of the insulator, d (t) represents the horizontal displacement of the transmission line, d '(t) represents a first derivative of d (t), and d' (t) represents a second derivative of d (t);
and the solving unit is used for solving the nonlinear finite element power equation of the power transmission line to obtain d (t).
8. The device according to claim 7, wherein the forecasting module comprises:
the dynamic wind drift angle determining unit is used for determining the dynamic wind drift angle of the insulator according to the horizontal displacement of the power transmission line and the following formula:
Figure FDA0003363203900000031
wherein,
Figure FDA0003363203900000035
the dynamic wind deflection angle of the insulator at the moment t is shown, and l represents the length of the insulator;
and the forecasting unit is used for forecasting the windage yaw state of the power transmission line according to the dynamic windage yaw angle of the insulator.
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