CN110442898A - A kind of electric power pylon health status model method for on-line optimization - Google Patents
A kind of electric power pylon health status model method for on-line optimization Download PDFInfo
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Abstract
The invention discloses a kind of electric power pylon health status model method for on-line optimization, which comprises initialization electric power pylon health status model；Control electric power pylon begins to use；Obtain electric power pylon health status data；Electric power pylon health status model is determined according to electric power pylon health status data comparison result；Obtain the data for influencing electric power pylon health status factor；Electric power pylon Life cycle health status model is determined by the data that judgement influences electric power pylon health status factor.The present invention is updated by updating electric power pylon health status data and carrying out the iteration of electric power pylon health status model, electric power pylon Life cycle health status model can be obtained, convenient for electric power pylon is comprehensively studied and monitored.
Description
Technical field
The invention belongs to electric power pylon technical field, in particular to a kind of electric power pylon health status model on-line optimization side
Method.
Background technique
Electric power pylon is the structures for supporting the conducting wire and lightning conducter of high pressure or super-pressure aerial power transmission line.In shape
Be generally divided into: wine glass-shaped, cathead, upper font, dry font and five kinds of barrel shape are had: anchor support, tangent tower, corner by purposes point
Tower, transposition tower (restringing phase position tower), terminal tower and crossover tower etc..Electric power pylon has the spies such as big flexible, small damping
Point, and it is sensitive to wind, therefore disaster caused by a windstorm is the main reason of electric power pylon loss.
Currently, proposing a kind of electric power pylon health status model, but answering for the ease of studying electric power pylon
During, electric power pylon health status model output value initially set and practical electric power pylon health status exist partially
Difference is not suitable for the health status of electric power pylon Life cycle, it is therefore necessary to carry out to model structure and parameter online excellent
Change.
Summary of the invention
In view of the above-mentioned problems, the present invention provides a kind of electric power pylon health status model method for on-line optimization, the side
Method includes:
Initialize electric power pylon health status model；
Control electric power pylon begins to use；
Obtain electric power pylon health status data；
Electric power pylon health status model is determined according to electric power pylon health status data comparison result；
Obtain the data for influencing electric power pylon health status factor；
Electric power pylon Life cycle health status is determined by the data that judgement influences electric power pylon health status factor
Model.
Further, the electric power pylon health status data include the health status data that generate in real time of electric power pylon and
The data of electric power pylon health status model output.
Further, the health status data that the electric power pylon generates in real time include sensor feedback on electric power pylon
The data of data and manual inspection feedback.
Further, described that electric power pylon health status model is determined according to electric power pylon health status data comparison result
Include:
The data of electric power pylon health status model output and the health status data error that electric power pylon generates in real time are small
In the threshold value of setting: being continued to run according to existing electric power pylon health status model；
The health status data error that the data and electric power pylon of electric power pylon health status model output generate in real time is not
Less than the threshold value of setting: the health status data point reuse electric power pylon health status model generated in real time according to newest electric power pylon
Parameter and structure, return to the acquisition electric power pylon health status data.
Further, the influence electric power pylon health status factor includes wind-force and electric power pylon service life.
Further, the data for influencing electric power pylon health status factor by judgement determine the full life of electric power pylon
Period health status model includes:
Wind-force reaches to electric power pylon damage strength: updating electric power pylon health status data and according to newest electric power pylon
The parameter and structure of the health status data point reuse electric power pylon health status model generated in real time, return to the acquisition power transmission line
Tower health status data；
Wind-force is not up to electric power pylon damage strength: judging electric power pylon service life size.
Further, the judgement electric power pylon service life size includes:
The electric power pylon service life reaches projected life: improving electric power pylon health status model according to data with existing and forms transmission of electricity
Transmission tower Life cycle health status model；
The electric power pylon service life is not up to projected life: continuing to run, returns according to existing electric power pylon health status model
It is described to obtain the data for influencing electric power pylon health status factor.
Further, terminate electric power pylon health status when forming the electric power pylon Life cycle health status model
Model optimization is simultaneously filed.
The present invention passes through the iteration for updating electric power pylon health status data and carrying out electric power pylon health status model
It updates, electric power pylon Life cycle health status model can be obtained, convenient for electric power pylon is comprehensively studied and supervised
It surveys.Other features and advantages of the present invention will be illustrated in the following description, also, partly become from specification it is aobvious and
It is clear to, or understand through the implementation of the invention.The objectives and other advantages of the invention can be by specification, claims
And pointed structure is achieved and obtained in attached drawing.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 shows electric power pylon health status model method for on-line optimization flow chart of the present invention；
Fig. 2 shows electric power pylon health status model on-line optimization process flow schematic diagrames of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical solution in the embodiment of the present invention clearly and completely illustrated, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
Every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
The present invention provides a kind of electric power pylon health status model method for on-line optimization, of the invention defeated as shown in figure 1
Electric wire tower health status model method for on-line optimization flow chart, the described method comprises the following steps:
Step 1；Initialize electric power pylon health status model；That is the health status of electric power pylon is that initial conditions are (complete
Health), meanwhile, the health status model of electric power pylon is also initial conditions model, parameter and structure including model.
Step 2；Control electric power pylon begins to use；
Step 3；Obtain electric power pylon health status data；Specifically, the electric power pylon health status data include defeated
The data for health status data and electric power pylon health status the model output that electric wire tower generates in real time.Further, described defeated
The health status data that electric wire tower generates in real time include the number of the data of sensor feedback and manual inspection feedback on electric power pylon
According to.
Step 4；Electric power pylon health status model is determined according to electric power pylon health status data comparison result；Specifically
, it is described to determine that electric power pylon health status model includes: according to electric power pylon health status data comparison result
The data of electric power pylon health status model output and the health status data error that electric power pylon generates in real time are small
In the threshold value of setting: being continued to run according to existing electric power pylon health status model；
The health status data error that the data and electric power pylon of electric power pylon health status model output generate in real time is not
Less than the threshold value of setting (threshold value is determined according to the structural strength of pole and tower design): being generated in real time according to newest electric power pylon
The parameter and structure of health status data point reuse electric power pylon health status model return to the acquisition electric power pylon health status
Data.
Step 5；Obtain the data for influencing electric power pylon health status factor；Specifically, the influence electric power pylon health
Situation factor includes wind-force and electric power pylon service life.
Step 6；Determine that electric power pylon Life cycle is strong by the data that judgement influences electric power pylon health status factor
Health status model.Specifically, the data for influencing electric power pylon health status factor by judgement determine that electric power pylon is given birth to entirely
Ordering period health status model includes:
Wind-force reaches to electric power pylon damage strength: updating electric power pylon health status data and according to newest electric power pylon
The parameter and structure of the health status data point reuse electric power pylon health status model generated in real time, return to the acquisition power transmission line
Tower health status data；
Wind-force is not up to electric power pylon damage strength: judging electric power pylon service life size.
Further, the judgement electric power pylon service life size includes:
The electric power pylon service life reaches projected life: improving electric power pylon health status model according to data with existing and forms transmission of electricity
Transmission tower Life cycle health status model, practical health status number run time wherein data with existing is electric power pylon difference
According to；
The electric power pylon service life is not up to projected life: continuing to run, returns according to existing electric power pylon health status model
It is described to obtain the data for influencing electric power pylon health status factor.
Terminate electric power pylon health status model optimization when forming the electric power pylon Life cycle health status model
And file.
Illustratively, Fig. 2 shows electric power pylon health status model on-line optimization process flow schematic diagrames of the present invention, such as
Shown in Fig. 2:
Step 1: control electric power pylon begins to use.When electric power pylon begins to use, the healthy shape of electric power pylon is defaulted
State is original state (health completely), meanwhile, the health status model of shaft tower is also original state, parameter and knot including model
Structure, i.e. formula (1).
Step 2: updating electric power pylon health status data.The state of health data of the electric power pylon newly obtained is replaced
Original data.When the health status of electric power pylon is original state (health completely), it is not required to update electric power pylon health shape
Condition data.
Step 3: adjusting the parameter and structure of health status model according to latest data.Joined according to newest data point reuse
After several and structure, new health status model is formed.When the health status of electric power pylon is original state (health completely), no
The parameter and structure of health status model, i.e. formula (1) need to be adjusted.
New health status model is that continuous iteration updates to obtain on the basis of initial electric power pylon health status model
's.Specifically, initial electric power pylon health status model is the cumulant, defeated according to electric power pylon structural plane moment of flexure about the time
Structure, material, external environment variable, age of completing for use, ageing process of electric wire tower itself etc. comprehensively consider and establish,
Middle finger is designated as: electric power pylon health index -- TLTHI (Transmission Line Tower Health Index) can be with defeated
Electric wire tower health status model indicates:
In formula (1), t is the time, and z is height, MeffIt (t) is effectively destruction moment of flexure；AgeeffIt (t) is the effective aging of SMTHPt
Equation；Meff(t) and Ageeff(t) there is coupled relations between, and A and B are adjusting parameter, indicate that two different mechanism cause
Electric power pylon ageing results；M1The structural plane moment of flexure on electric power pylon is acted on for design wind lotus；MRIt is anti-for the bending resistance of structural plane
Power；Rud indicates nuisance parameter, works as M1(z,t)>rud MR(z) when occurring, show that electric power pylon is influenced at least to exist by wind load
Its section turn moment of certain point has exceeded the nominal designed value comprising redundancy, and the situation of falling tower very likely occurs, but also is not exhausted
To (assuming that rud=1.2).But in this case, we assume that the health status of tower itself has been " 0 ", need complete
The maintenance in face restores.Wherein, Meff(t) detailed definition is referred to following formula (2) and (3):
H is electric power pylon total height in formula.
The effective ageing equation Age of SMTHPteff(t) in detail be expressed as follows formula (4):
Ageeff(t)=f (Structure,Material, Temperature, Humidity, PH) and (4)
In formula, StructureFor configuration index；MaterialFor material index；Under two indexing parameter positioning different designs standards
Electric power pylon characteristic.TemperatureFor air themperature；HumidityFor air humidity；PH is air pH value coefficient.Different coefficients
Under the conditions of, the accumulation about the time generates different electric power pylon aging effects.And the aging speed instantly of electric power pylon
The demand for coupling with electric power pylon health index, but modeling for simplifying the analysis and tentatively, herein, it will be assumed that this coupling
Conjunction relationship can be ignored.
In electric power pylon structure, there is the vibrations between electric power pylon and power transmission line to influence each other, and constitutes one
A Nonlinear system mutually coupled.Therefore, electric power pylon tower body is by the structural plane moment of flexure effect of design wind load generation by straight
It connects the power for acting on electric power pylon tower body and is collectively constituted by the power that power transmission line acts on tower body.When the moment, t was determined, M1
The value of (z, t) is only related with height, and when electric power pylon height z is determined, z calculates depth of section z needed for being defined as0, then t moment
Required z0It may be defined as M by the moment of flexure that wind load action generates at height1(z0), M1(z0) can be indicated with following formula (5):
In formula, z0For the height for calculating section；F (z) is the equivalent arrangements wind load of electric power pylon tower body, and F (z) is by height
Variation influences, expression formula such as following formula (6):
In formula, ρairFor atmospheric density, ωmaxIt (z) is the maximum basic wind speed of wind load at electric power pylon z-height, CflgFor
Air force Shape Coefficient, CdynFor the dynamic response factor, AfFor the front face area of shaft tower.
The power transmission line system of equilibrium condition is under Static behavior, the horizontal component of pulling force is cancelled out each other, vertical component
Construction weight is increased, pulling force at this time does not generate the moment of flexure of structural plane.In the case where designing wind load action, power transmission line generates suitable
Wind direction displacement and deformation, are mutually balanced along conducting wire durection component due to the presence of insulator；But vertical power transmission line direction
Under component effect, the moment of flexure in Transmission Tower face is generated.The statics Analysis of power transmission line can be carried out by finite element modeling,
To seek tower body section turn moment.
But a large amount of calculate is consumed by the mode that finite element carries out mechanical analysis acquirement electric power pylon structural plane moment of flexure and is provided
Source, time cost is very high, is unfavorable for the real-time assessment and prediction of electric power pylon under disaster caused by a windstorm.It needs according to mechanical analysis, experience
Formula and test experiment database obtain simply, convenient for the analytic formula analyzed and calculated in real time, to solve the problems, such as this.
Under the Moment of electric power pylon, the bending resistance drag for deconstructing section is exponentially distributed along height.Therefore, structural plane
Bending resistance drag MRIt can be indicated with following formula (7):
MR(z)=α e-βz+γ (7)
In formula, α, β, γ are undetermined parameter, and different electric power pylons has different characteristics, needs to carry out finite element respectively
Analysis or mechanical test test are fitted undetermined parameter.
Regulation coefficient B can be defined as following formula (8):
In formula, electric power pylon structure, the material of a kind of standard are selected, ideal ageing environment air is chosen, illustratively,
With 25 DEG C of temperature, humidity 60%, for pH value is neutral PH=7, but not limited to this, TtotalFor ecotopia and static wind item
The electric power pylon specified full life design cycle under part, i.e., after this time, due to the effect of structure aging and fatigue, electric power pylon is
The corresponding section turn moment of specified wind load cannot be supported.
Regulation coefficient A can be defined as following formula (9):
In formula, MfallIt (z) is wind load FfallUnder corresponding tower section moment of flexure, be constant；FfallIn tower Life cycle
Tower body is uniformly applied to by a horizontal direction, and just in T that time of Deethanizer design end-of-lifetotalLead to a certain cross
Section cannot support the phenomenon of falling tower of real-time moment of flexure.The power F of this processfallFinite element analysis can be coupled by more physical quantitys to obtain
, to obtain the numerical solution of A.This is arrived, the health status modeling of electric power pylon terminates.
Step 4: whether judgment models output is less than given threshold with practical health status error.Model output is current
The data of existing electric power pylon health status model output, practical health status are the health status that electric power pylon generates in real time
Data, the data of data and manual inspection feedback including sensor feedback on electric power pylon.Illustratively, with existing at present
The data of electric power pylon health status model output are m, and practical health status is the health status number that electric power pylon generates in real time
According to for n, threshold value is illustrated for being w, when | m-n | when >=w, return to third step, the health generated in real time according to electric power pylon
Status data n adjusts the parameter and structure of current existing electric power pylon health status model, to form new power transmission line
Tower health status model.The 4th step is executed again, iteration updates optimization electric power pylon health status model, until | m-n | when < w,
Terminate iteration, executes the 5th step.
Step 5: according to existing health status model running.Electric power pylon health status model is after iteration updates, temporarily
When form newest electric power pylon health status model, electric power pylon continues according to this newest electric power pylon health status model
Operation.
Step 6: judging whether wind-force reaches to electric power pylon damage strength.In electric power pylon according to newest defeated at present
When electric wire tower health status model continues to run, the intensity of wind-force is judged.When wind-force reaches strong to electric power pylon damage
When spending, second step is returned, electric power pylon health status data is updated, electric power pylon health status model is iterated more again
Newly, until wind-force not up to electric power pylon damage strength, form the electric power pylon health status model advanced optimized；Work as wind
When power is not up to electric power pylon damage strength, the 7th step is executed.
Step 7: judging whether electric power pylon reaches projected life.When electric power pylon is not up to projected life, the is returned
Five steps continue to run until that electric power pylon reaches projected life according to current newest electric power pylon health status model；When defeated
When electric wire tower reaches projected life, the 8th step is executed.
Step 8: improving electric power pylon Life cycle health status model according to data with existing.To newest defeated at present
Electric wire tower health status model does last update, forms electric power pylon Life cycle health status model.
Step 9: model optimization terminates and files.
Identical symbol indicates the identical meaning in the present invention.
The present invention passes through the iteration for updating electric power pylon health status data and carrying out electric power pylon health status model
It updates, electric power pylon Life cycle health status model can be obtained, convenient for electric power pylon is comprehensively studied and supervised
It surveys.
Although the present invention is described in detail referring to the foregoing embodiments, those skilled in the art should manage
Solution: it is still possible to modify the technical solutions described in the foregoing embodiments, or to part of technical characteristic into
Row equivalent replacement；And these are modified or replaceed, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The spirit and scope of scheme.
Claims (8)
1. a kind of electric power pylon health status model method for on-line optimization, which is characterized in that the described method includes:
Initialize electric power pylon health status model；
Control electric power pylon begins to use；
Obtain electric power pylon health status data；
Electric power pylon health status model is determined according to electric power pylon health status data comparison result；
Obtain the data for influencing electric power pylon health status factor；
Electric power pylon Life cycle health status model is determined by the data that judgement influences electric power pylon health status factor.
2. electric power pylon health status model method for on-line optimization according to claim 1, which is characterized in that the transmission of electricity
Transmission tower health status data include the health status data that electric power pylon generates in real time and the output of electric power pylon health status model
Data.
3. electric power pylon health status model method for on-line optimization according to claim 2, which is characterized in that the transmission of electricity
The health status data that transmission tower generates in real time include the data of the data of sensor feedback and manual inspection feedback on electric power pylon.
4. electric power pylon health status model method for on-line optimization according to claim 1 to 3, which is characterized in that institute
It states and determines that electric power pylon health status model includes: according to electric power pylon health status data comparison result
The health status data error that the data of electric power pylon health status model output generate in real time with electric power pylon, which is less than, to be set
Fixed threshold value: it is continued to run according to existing electric power pylon health status model；
The health status data error that the data of electric power pylon health status model output generate in real time with electric power pylon is not less than
The threshold value of setting: according to the ginseng for the health status data point reuse electric power pylon health status model that newest electric power pylon generates in real time
Several and structure returns to the acquisition electric power pylon health status data.
5. electric power pylon health status model method for on-line optimization according to claim 1 to 3, which is characterized in that institute
It includes wind-force and electric power pylon service life that stating, which influences electric power pylon health status factor,.
6. electric power pylon health status model method for on-line optimization according to claim 1 to 3, which is characterized in that institute
It states and determines electric power pylon Life cycle health status model packet by the data that judgement influences electric power pylon health status factor
It includes:
Wind-force reaches to electric power pylon damage strength: update electric power pylon health status data are simultaneously real-time according to newest electric power pylon
It is strong to return to the acquisition electric power pylon for the parameter and structure of the health status data point reuse electric power pylon health status model of generation
Health status data；
Wind-force is not up to electric power pylon damage strength: judging electric power pylon service life size.
7. electric power pylon health status model method for on-line optimization according to claim 6, which is characterized in that the judgement
Electric power pylon service life size includes:
The electric power pylon service life reaches projected life: improving electric power pylon health status model according to data with existing and forms electric power pylon
Life cycle health status model；
The electric power pylon service life is not up to projected life: continuing to run according to existing electric power pylon health status model, described in return
Obtain the data for influencing electric power pylon health status factor.
8. electric power pylon health status model method for on-line optimization according to claim 7, which is characterized in that described in formation
Terminate electric power pylon health status model optimization when electric power pylon Life cycle health status model and file.
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|---|---|---|---|---|
| WO2008003033A2 (en) * | 2006-06-29 | 2008-01-03 | Edsa Micro Corporation | Automatic real-time optimization and intelligent control of electrical power distribution and transmission systems |
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| CN106447210A (en) * | 2016-10-10 | 2017-02-22 | 国家电网公司 | Distribution network equipment health degree dynamic diagnosis method involving credibility evaluation |
| US20170102234A1 (en) * | 2015-10-09 | 2017-04-13 | Micatu Inc. | Enhanced power transmission tower condition monitoring system for overhead power systems |
| CN106570644A (en) * | 2016-11-04 | 2017-04-19 | 国网山东省电力公司电力科学研究院 | Power transmission and transformation equipment quantization evaluation method based on statistical tool |
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2019
- 2019-06-14 CN CN201910518212.1A patent/CN110442898B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2008003033A2 (en) * | 2006-06-29 | 2008-01-03 | Edsa Micro Corporation | Automatic real-time optimization and intelligent control of electrical power distribution and transmission systems |
| CN105469156A (en) * | 2014-09-11 | 2016-04-06 | 国网四川省电力公司电力科学研究院 | MOA condition management and fault prediction method and MOA condition management and fault prediction system |
| US20170102234A1 (en) * | 2015-10-09 | 2017-04-13 | Micatu Inc. | Enhanced power transmission tower condition monitoring system for overhead power systems |
| CN106447210A (en) * | 2016-10-10 | 2017-02-22 | 国家电网公司 | Distribution network equipment health degree dynamic diagnosis method involving credibility evaluation |
| CN106570644A (en) * | 2016-11-04 | 2017-04-19 | 国网山东省电力公司电力科学研究院 | Power transmission and transformation equipment quantization evaluation method based on statistical tool |
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