CN108961094A - Wind leaning fault method for early warning based on transmission line of electricity minimum air void online measuring - Google Patents
Wind leaning fault method for early warning based on transmission line of electricity minimum air void online measuring Download PDFInfo
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Abstract
The invention discloses a kind of wind leaning fault method for early warning based on transmission line of electricity minimum air void online measuring, including carry out electric power facility and refine three-dimensional modeling, and measure the minimum air void of transmission line of electricity on threedimensional model；The meteorologic factor of analyzing influence transmission line of electricity minimum air void, establishes the nonlinear regression model (NLRM) of transmission line of electricity minimum air void Yu relevant weather factor, and resolves model parameter；The assessment of wind leaning fault warning grade is carried out in conjunction with threshold classification according to the transmission line of electricity minimum air void value under the model prediction DIFFERENT METEOROLOGICAL CONDITIONS of foundation.The present invention efficiently solves wind leaning fault orientation problem, greatly improves the safety operation level of route.
Description
Technical field
The present invention relates to the wind leaning fault method for early warning based on transmission line of electricity minimum air void online measuring, in particular to
One kind serving minimum air void online measuring and wind leaning fault method for early warning in the inclined flashover of power transmission line wind, belongs to defeated
Electric line safe operation and administrative skill field.
Background technique
Windage yaw discharge accident is the major safety risks that power grid operates normally, with China's power grid Accelerating The Construction, each voltage
The transmission line of electricity of grade is fast-developing, especially super, extra high voltage line transmission distance is long, meteorological on the way, complex geographical environment,
In extreme weather conditions once windage yaw discharge accident occurs, large-area power-cuts will be caused, the safety for seriously affecting electric system is steady
Fixed operation, causes huge economic loss to electric system.There are many reason of causing windage yaw to discharge, wherein bad weather condition
Caused by the lower variation because of angle of wind deflection between conducting wire, conducting wire-shaft tower, the air gap of the adjacent object of conducting wire-such as trees it is electrically strong
Degree variation is to cause transmission line of electricity that windage yaw discharge failure and the most fundamental reason of accident occurs.
Periodic reinvestigation transmission tower minimum air void, conducting wire distance to the ground and close on foreign matter distance be power department windage yaw prevention and treatment
Major measure.Existing check method 1) empirical estimating, 2) angle of wind deflection is obtained, according between the minimum air of existing model reckoning
Gap.The factor many such as wind directions, wind speed of angle of wind deflection are influenced, therefore the acquired value of angle of wind deflection has certain approximation, in addition most
Small the air gap prediction model usually requires to be modified according to the actual situation, and minimum air void is accurate in real work
Value is difficult to obtain.Some online minimum air voids monitor system, need to lay data under harsh weather and conductive environment and adopt
Collect hardware, causes difficult in implementation process.In general, there is presently no one kind being capable of accurate measurement transmission line of electricity
The practical approach of minimum air void.
Summary of the invention
It is an object of the invention to be based in the inclined flashover of power transmission line wind most in view of the deficienciess of the prior art, providing
The wind leaning fault method for early warning of small the air gap online measuring solves transmission line safety operation and institute face in management process
The transmission line of electricity minimum air void faced measures and wind leaning fault early warning problem.
Technical solution of the present invention provides a kind of wind leaning fault early warning based on transmission line of electricity minimum air void online measuring
Method, comprising the following steps:
Step 1, it carries out electric power facility and refines three-dimensional modeling, and measure the minimum air of transmission line of electricity on threedimensional model
Gap；
Step 2, the meteorologic factor of analyzing influence transmission line of electricity minimum air void establishes transmission line of electricity minimum air void
With the nonlinear regression model (NLRM) of relevant weather factor, and model parameter is resolved；
Step 3, according to the transmission line of electricity minimum air void value under the model prediction DIFFERENT METEOROLOGICAL CONDITIONS of foundation, in conjunction with threshold
Value classification, carries out the assessment of wind leaning fault warning grade.
Moreover, the image data of power transmission and transformation line shaft tower and ambient enviroment is obtained using oblique photograph mode in step 1,
Aerial triangulation is carried out in conjunction with existing design data and control point data, establishes power transmission and transformation line shaft tower and ambient enviroment
Threedimensional model.
Moreover, in step 2, according to gray system theory GM (1, N) model foundation minimum air void and relevant weather because
The nonlinear regression model (NLRM) of element, using least square method fit regression model parameter.
Moreover, according to the model of foundation, predicting transmission line of electricity minimum air void under DIFFERENT METEOROLOGICAL CONDITIONS in step 3
Size, and compared on this basis with the reference data of specification, threshold value, the safety of evaluation means minimum air void are set.
Compared with the prior art, the advantages of the present invention are as follows: realize under cordless between transmission line part and with
The minimum air void of line environment measures, and the correlation model by establishing minimum air void and meteorologic factor, solves
Wind leaning fault early warning problem, to formulate the reasonable windage yaw precautionary measures, scientific optimization power transmission circuit caused by windage design parameter is improved
The safety operation level of route provides important technology and guarantees.
Detailed description of the invention
Fig. 1 is the flow chart of the embodiment of the present invention.
Specific embodiment
Below in conjunction with attached drawing and the embodiment of the present invention, the present invention is described in detail technical solution.
The present invention proposes a kind of transmission line of electricity the air gap online measuring and wind leaning fault early warning system.Pass through high-resolution
Image sensor acquires electric power line pole tower, suspension wire, line environment image in a non contact fashion, realizes and is based on photogrammetric side
The model of power transmission system of method constructs, and the minimum air void between accurate measurement transmission line part and with line environment；According to
The nonlinear regression model (NLRM) of gray system theory GM (1, N) model foundation minimum air void and meteorologic factor, realizes different gas
Minimum air void prediction and the assessment of wind leaning fault warning grade as under the conditions of.The present invention will position for wind leaning fault, formulate and close
The windage yaw precautionary measures of reason, scientific optimization power transmission circuit caused by windage design parameter, the safety operation level offer for improving route are important
Technology guarantees.
Referring to Fig. 1, a kind of windage yaw based on transmission line of electricity minimum air void online measuring provided in an embodiment of the present invention
Fault early warning method comprises the following specific steps that:
Step 1, using design data, control point data, multi-angle of view image realize electric power facility (electric force pole tower, electric wire, absolutely
Edge etc. and line environment) three-dimensional modeling is refined, and the minimum air void of transmission line of electricity is measured on threedimensional model.
Further, the image data that power transmission and transformation line shaft tower and ambient enviroment are obtained using oblique photograph mode, in conjunction with
Existing design data and control point data carry out aerial triangulation, establish the three of power transmission and transformation line shaft tower and ambient enviroment
Dimension module.
The multi-angle of view image data that this step obtains step 1 controls information (control point, design data etc.) using multi-source
As oriented control parameter, the orientation parameter that sky three resolves image is carried out.According to aerial triangulation as a result, by extracting shadow
As characteristic point, high density point cloud, semi-automatic fine modeling are generated, generates transmission line of electricity scene threedimensional model.By realizing electric power
Shaft tower, the high-precision of electric wire and route scene, fining reconstructing three-dimensional model, are measured online for transmission line of electricity minimum air void
It surveys and provides basic data with dynamic monitoring.Searched for by minimum distance, can be measured on the model of three-dimensional reconstruction shaft tower, suspension wire,
The minimum air voids such as insulator, route scene (trees).
In embodiment, using the oblique photograph mode of electronic multi-rotor unmanned aerial vehicle, photographed over the ground with lateral attitude in the sky,
Obtain the image data of power transmission and transformation line shaft tower and ambient enviroment；Made using multi-source control information (control point, design data etc.)
For oriented control parameter, the orientation parameter that sky three resolves image is carried out；According to aerial triangulation as a result, by extracting image
Characteristic point, generation high density point cloud and etc., it generates electric power facility (electric force pole tower, electric wire, insulator etc.) and refines three-dimensional mould
Type, to support to measure, it is proposed that precision can achieve 0.05 meter；By space length minimum value way of search, i.e., searched on model
Minimum range between rope two lines determines electric power line pole tower, suspension wire and the minimum air void between object.
Step 2, the meteorologic factor of analyzing influence transmission line of electricity minimum air void establishes transmission line of electricity minimum air void
With the nonlinear regression model (NLRM) of relevant weather factor, and model parameter is resolved.
Further, according to gray system theory GM (1, N) model foundation minimum air void and relevant weather factor
Nonlinear regression model (NLRM), using least square method fit regression model parameter.
In embodiment, minimum air void and relative meteorological factors non-linear relation that may be present are considered, analyze and true
It is fixed the meteorologic factor for ringing transmission line of electricity minimum air void, passes through fixed point, periodically acquisition transmission line of electricity image data, structure
Established model data and measurement minimum air void data, select gray system theory GM (1, N) model foundation minimum air void
With the nonlinear regression model (NLRM) of relevant weather factor, using least square curve fitting Parameters in Regression Model.
According to gray system theory,
If Y(0)={ y(0)(1),y(0)(2),…,y(0)It (n) } is minimum air void data sequence,
Wherein, y(0)(1),y(0)(2),…,y(0)(n) the 1st minimum air void measuring value, the 2nd minimum are respectively indicated
The air gap measuring value ... n-th minimum air void measuring value；
If Xi (0)={ xi (0)(1),xi (0)(2),…,xi (0)(n) } (i=1,2 ..., m) it is relative meteorological factors data sequence
Column,
Wherein, xi (0)(1),xi (0)(2),…,xi (0)(n) it respectively indicates the 1st time and measures corresponding meteorological element data i,
It is that relative meteorological factors are always a that 2 times, which measure corresponding meteorological element data i ... n-th to measure corresponding meteorological element data i, m,
Number, such as relative meteorological factors have wind direction, wind speed, humidity.
Y(1)={ y(1)(1),y(1)(2),…,y(1)And X (n) }i (1)={ xi (1)(1),xi (1)(2),…,xi (1)(n) } respectively
For Y(0)And Xi (0)One-accumulate formation sequence,
Wherein:K=1,2,3 ..., n.
I.e. in Accumulating generation sequence, k-th of y(1)(k)、xi (1)It (k) is respectively accordingly the sum of cumulative, such as: data item y(1)It (2) is Y(0)The sum of 2 before data sequence, data item y(1)It (n) is Y(0)The sum of n before data sequence.Data item xi (1)(2)
For Xi (0)The sum of 2 before data sequence, data item xi (1)It (n) is Xi (0)The sum of n before data sequence.
Then minimum air void and GM (1, N) model of relative meteorological factors are
y(0)(k)+az(1)(k)=b1x1 (1)(k)+b2x2 (1)(k)+…+bmxm (1)(k) (1)
Wherein: parameter z(1)(k)=(y(1)(k)+y(1)(k-1))/2；K=2,3 ..., n are Y(1)In adjacent two it is average
Value, a, b1、 b2…bmFor GM (1, N) model parameter.
Work as k=2, when 3 ..., n, least square method can be used and acquire model parameter(For a, b1、b2…bmBest estimate) be
In formula,
Wherein, matrix L is made of minimum air void sequence of observations item, and matrix B is by parameter z(1)(k) and meteorologic factor
One-accumulate sequence Item is constituted.
After acquiring model parameter value, the corresponding formula of time proximity of one-accumulate sequence is further acquired
Wherein,For e index, e is the truth of a matter,For index.
It is rightMake a regressive reduction treatment, the prediction type for obtaining original series is
It is as follows for the specific example that during reference convenient to carry out, provides GM (1, N) model:
Table 1 is the data of example, respectively transmission line of electricity minimum air void value, meteorologic factor (wind direction, wind speed and opposite
Humidity) 5 observation data.
Table 1 GM (1, N) model example data
The first step
According to table 1, minimum air void data sequence Y(0)={ y(0)(1),y(0)(2),y(0)(3),y(0)(4),y(0)(5)}
={ 265.74,309.59,347.98,389.55,456.25 }
Meteorologic factor Xi (0)={ xi (0)(1),xi (0)(2),xi (0)(3),xi (0)(4),xi (0)(5) } (i=1,2,3)
X1 (0)={ x1 (0)(1),x1 (0)(2),x1 (0)(3),x1 (0)(4),x1 (0)(5) }=36.6,44.9,52.4,62.4,
74.7}
X2 (0)={ x2 (0)(1),x2 (0)(2),x2 (0)(3),x2 (0)(4),x2 (0)(5) }=0.91,1.11,1.32,1.42,
1.66}
X3 (0)={ x3 (0)(1),x3 (0)(2),x3 (0)(3),x3 (0)(4),x3 (0)(5) }=24.7,30.3,38.9,49.6,
70.4}
To Y(0)One-accumulate is done, Y is obtained(1)={ y(1)(1),y(1)(2),y(1)(3),y(1)(4), y(1)(5) }=
{ 265.74,575.33,923.31,1312.86,1769.11 }
To Xi (0)One-accumulate is done, is obtained
X1 (1)={ x1 (1)(1),x1 (1)(2),x1 (1)(3),x1 (1)(4),x1 (1)(5) }=36.6,81.5,133.9,
196.3,271.0}
X2 (1)={ x2 (1)(1),x2 (1)(2),x2 (1)(3),x2 (1)(4),x2 (1)(5) }=0.91,2.02,3.34,4.76,
6.42}
X3 (1)={ x3 (1)(1),x3 (1)(2),x3 (1)(3),x3 (1)(4),x3 (1)(5) }=24.7,55.0,93.9,143.5,
213.9}
Second step
ByIt can calculate
So as to calculate
Acquire the corresponding formula of time proximity of one-accumulate sequence
It is rightMake a regressive reduction treatment, the prediction type for obtaining original series is
Step 3, according to the transmission line of electricity minimum air void value under the model prediction DIFFERENT METEOROLOGICAL CONDITIONS of foundation, in conjunction with threshold
Value classification, carries out the assessment of wind leaning fault warning grade.
Further, according to the model of foundation, the size of transmission line of electricity minimum air void under DIFFERENT METEOROLOGICAL CONDITIONS is predicted,
And compared on this basis with the reference data of specification, reasonable threshold value, the safety of evaluation means minimum air void are set
Property.
It is compared by the reference data of model predication value and specification, the suitable threshold value of nargin is set, pass through fuzzy class point
Class predicts power transmission circuit caused by windage fault level, it can be ensured that safe operation of the transmission line of electricity under extreme weather conditions.
Base in embodiment, according to the minimum air void value under the model prediction DIFFERENT METEOROLOGICAL CONDITIONS of foundation, with specification
Quasi- data comparison obtains corresponding warning level by fuzzy classification in conjunction with the warning grade of setting, and the result of assessment will be
Wind-deviation precautionary measures provide decision data.
If the minimum air void value that specification allows is L, in the minimum air void of certain meteorological condition drag prediction
Value is d, when: (1) d is less than L, is 1 grade of early warning；(2) d is greater than L, is less than 1.2L, is 2 grades of early warning；(3) d is greater than 1.2L, without pre-
It is alert.
This method effectively realizes the accurately transmission line of electricity minimum air void value based on model and measures, and changes tradition
Method obtains the situation of transmission line of electricity minimum air void approximation by calculating indirectly.When it is implemented, computer can be used
Software mode realizes the automatic running of the above process.
It further says, the present invention is by establishing the nonlinear model of transmission line of electricity minimum air void and relevant weather factor
Type solves the problems, such as the wind leaning fault early warning faced in transmission line of electricity operation, to improve the safety of transmission line of electricity operation.
Although the embodiments of the present invention have been disclosed as above, but its is not only in the description and the implementation listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easy
Other modification is realized on ground, therefore without departing from the general concept defined in the claims and the equivalent scope, and the present invention is not
It is limited to specific details and legend shown and described herein.
Claims (4)
1. a kind of wind leaning fault method for early warning based on transmission line of electricity minimum air void online measuring, which is characterized in that including
Following steps:
Step 1, it carries out electric power facility and refines three-dimensional modeling, and on threedimensional model between the minimum air of measurement transmission line of electricity
Gap；
Step 2, the meteorologic factor of analyzing influence transmission line of electricity minimum air void establishes transmission line of electricity minimum air void and phase
The nonlinear regression model (NLRM) of meteorologic factor is closed, and resolves model parameter；
Step 3, according to the transmission line of electricity minimum air void value under the model prediction DIFFERENT METEOROLOGICAL CONDITIONS of foundation, in conjunction with threshold value point
Class carries out the assessment of wind leaning fault warning grade.
2. the wind leaning fault method for early warning according to claim 1 based on transmission line of electricity minimum air void online measuring,
It is characterized in that: in step 1, the image data of power transmission and transformation line shaft tower and ambient enviroment is obtained using oblique photograph mode, in conjunction with
Existing design data and control point data carry out aerial triangulation, establish the three-dimensional of power transmission and transformation line shaft tower and ambient enviroment
Model.
3. the wind leaning fault method for early warning according to claim 1 based on transmission line of electricity minimum air void online measuring,
It is characterized in that: in step 2, according to gray system theory GM (1, N) model foundation minimum air void and relevant weather factor
Nonlinear regression model (NLRM), using least square method fit regression model parameter.
4. the according to claim 1 or 2 or 3 pre- police of wind leaning fault based on transmission line of electricity minimum air void online measuring
Method, it is characterised in that: in step 3, according to the model of foundation, predict transmission line of electricity minimum air void under DIFFERENT METEOROLOGICAL CONDITIONS
Size, and compared on this basis with the reference data of specification, threshold value, the safety of evaluation means minimum air void are set.
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| CN112016739A (en) * | 2020-08-17 | 2020-12-01 | 国网山东省电力公司潍坊供电公司 | Fault detection method and device, electronic equipment and storage medium |
| CN112257028A (en) * | 2020-10-16 | 2021-01-22 | 广东电网有限责任公司 | Windage yaw flashover fault probability calculation method and device of power transmission line |
| CN112504208A (en) * | 2020-10-26 | 2021-03-16 | 国网河南省电力公司济源供电公司 | Power transmission line air gap analysis method |
| CN112886587A (en) * | 2021-03-29 | 2021-06-01 | 北京世纪百合科技有限公司 | Checking and representing method for air gap of tower head of power transmission line tower |
| CN117151336A (en) * | 2023-09-06 | 2023-12-01 | 连云港智源电力设计有限公司 | Device and method for evaluating limit wind resistance of power transmission line |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112016739A (en) * | 2020-08-17 | 2020-12-01 | 国网山东省电力公司潍坊供电公司 | Fault detection method and device, electronic equipment and storage medium |
| CN112016739B (en) * | 2020-08-17 | 2024-02-20 | 国网山东省电力公司潍坊供电公司 | Fault detection method and device, electronic equipment and storage medium |
| CN112257028A (en) * | 2020-10-16 | 2021-01-22 | 广东电网有限责任公司 | Windage yaw flashover fault probability calculation method and device of power transmission line |
| CN112257028B (en) * | 2020-10-16 | 2022-11-29 | 广东电网有限责任公司 | Windage yaw flashover fault probability calculation method and device of power transmission line |
| CN112504208A (en) * | 2020-10-26 | 2021-03-16 | 国网河南省电力公司济源供电公司 | Power transmission line air gap analysis method |
| CN112886587A (en) * | 2021-03-29 | 2021-06-01 | 北京世纪百合科技有限公司 | Checking and representing method for air gap of tower head of power transmission line tower |
| CN117151336A (en) * | 2023-09-06 | 2023-12-01 | 连云港智源电力设计有限公司 | Device and method for evaluating limit wind resistance of power transmission line |
| CN117151336B (en) * | 2023-09-06 | 2024-04-16 | 连云港智源电力设计有限公司 | Device and method for evaluating limit wind resistance of power transmission line |
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