CN103646157B - Method for evaluating transmission line fault caused by rainstorm - Google Patents
Method for evaluating transmission line fault caused by rainstorm Download PDFInfo
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- CN103646157B CN103646157B CN201310380170.2A CN201310380170A CN103646157B CN 103646157 B CN103646157 B CN 103646157B CN 201310380170 A CN201310380170 A CN 201310380170A CN 103646157 B CN103646157 B CN 103646157B
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Abstract
The invention discloses a method for evaluating a transmission line fault caused by rainstorm and belongs to the technical field of power systems and automation of the power systems. According to the mechanism that the rainstorm causes the transmission line fault, an accurate line fault probability model is established, and internal and external factors relevant with the transmission line fault are correctly reflected, so that evaluation on the transmission line fault caused by the rainstorm does not depend on accumulated historical data, pole tower stress and strength calculation are also avoided, various relevant factors are fully considered, and the method has good adaptability. By adopting the method, transmission line risk management is pushed greatly, and the capacity of defending the power systems against external disasters is enhanced.
Description
Technical field
The invention belongs to Power System and its Automation technical field, more precisely the present invention relates to a kind of assessment heavy rain
The method for causing transmission line malfunction probability.
Background technology
Because China's primary energy and economic development are extremely uneven in area distribution, primary energy such as coal, water conservancy are provided
Source etc. is concentrated mainly on west area, and economic development area concentration faster in East Coastal provinces and cities, macroscopically determines " complete
State's networking, transferring electricity from the west to the east, north and south supply mutually " becomes being substantially oriented for Chinese most optimum distribution of resources interior on a large scale.Cause national network
It is covered in High aititude, topographic and geologic complex area, safe and reliable operation and the close phase such as meteorology, geological environment of transmission line of electricity more
Close.Firstly, since the factor such as line corridor resource and geographical environment is restricted, transmission line of electricity high and steep mountains are erected at more, are easily received
To the impact of weather environment；Secondly, in recent years global environment deteriorates, and the disaster such as storm flood and landslide, mud-rock flow happens occasionally,
With it is sudden it is strong, have a very wide distribution, the oncoming force is violent the features such as, very big is endangered to electric power facility；In addition, power system at present is to cunning
The disasters such as slope, mud-rock flow rely primarily on personnel's line walking to find, and focus primarily upon and summarize afterwards, it is impossible to effectively pre-
The impact of the disasters such as alert defence landslide, mud-rock flow, differs greatly with electrical network automatic intelligent target, it is impossible to meet strong intelligence electricity
The new demand that net is managed transmission line of electricity operation risk.Therefore, it is necessary to study shadow of the external disasters such as heavy rain to transmission line of electricity
Ring, assess line fault probability, strengthen the weather environment risk management of transmission line of electricity, for dispatching of power netwoks operation necessary skill is provided
Art is supported.
For heavy rain causes the assessment of transmission line malfunction probability to be related to circuit inside and outside various factors.Correlative factor is numerous
And to each other the mechanism of action is complicated, several factors cannot accurately determine (such as geology landform factor) or even cannot approx determine
(the such as intensity of basic, each component of shaft tower), thus be difficult to use analytic method, such as by the event of real-time shaft tower force analysis circuit
The method of barrier probability, is difficult to apply to actual transmission line failure probability evaluation.
Based on the approximating method of historical data, then historical data and its accuracy are excessively depended on, and heavy rain can not be embodied
Cause the mechanism of line fault, and be difficult to obtain reliable historical data, therefore the method nothing within considerable time at present
Method is applied to Practical Project.
Fu embraces uncut jade and exists《The impact of landform and height above sea level to precipitation》(Geography Journal, 1992,47 (7):302-314.), Liao
Luxuriant and rich with fragrance, Hong Yanchao and Zheng Guoguang exists《The influence research general introduction of Terrain on Precipitation》(Meteorological Science And Technology, 2007,35 (3):309-316.),
Chen Ming, Fu embrace uncut jade and in it is strong et al.《The impact of Topography On Storm Rainfall》(Geography Journal, 1995,50 (3):256-263.) it is situated between
Impact of the factors such as height above sea level, topography and geomorphology that continued to rainfall.Kuang Lehong exists《Regional Heavy Rain mud-rock flow prediction methods
Research》(Hunan:Central South University, 2006.) in give the coefficient of stability computational methods of bulk solid mass.
In recent years, the frequency and degree that natural calamity occurs progressively increases and strengthens, and the threat to electricity net safety stable is got over
Come bigger, but there is presently no the probability quantization assessment technology for meeting safety on line analysis and early warning requirement, therefore urgent need is carried out
The research and development of correlation technique.
The content of the invention
The purpose of the present invention is：In order to overcome the above-mentioned deficiencies of the prior art, the invention provides a kind of it can be considered that each
Correlative factor is planted, the mechanism that heavy rain causes transmission line malfunction is embodied, realizes that heavy rain causes the quantitative evaluation of line fault probability
Method.
Specifically, the present invention is realized using following technical scheme, is comprised the following steps：
1) in the controlling the heart collects forecast and its live state information, the general meteorological forecast and its live letter of real-time heavy rain
Breath and in real time electrical network work information；
2) according to line corridor geographical feature and surrounding enviroment feature by line sectionalizing, with identical geographical feature and periphery
The circuit of environmental characteristic divides one section into, and using the shaft tower at domatic lower exit and in mountain valley water channel exit as receiving
The shaft tower that heavy rain affects；
3) according to the real-time detection data of Doppler radar, carry out linear extrapolation, forecast future time period rainfall scope and
Rainfall intensity, obtains the rainfall intensity in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period；
4) to every section of circuit, according to the shadow of line facility present position geographical feature and surrounding enviroment feature to rainfall intensity
Ring, on step 3) in the rainfall intensity in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in the forecasting period that obtains enter
Row amendment, obtains rainfall intensity I in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in revised forecasting period；
5) to every section of circuit, assessment calculates required dynamic variable, and the dynamic variable includes every section of line in forecasting period
Respectively affected by heavy rain in every section of circuit in the effective precipitation r in region residing for the shaft tower respectively affected by heavy rain in road, forecasting period
Shaft tower residing for the average height of run-off h in region, region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period
Bulk solid mass coefficient of stability K；
The effective precipitation r in region residing for the shaft tower respectively affected by heavy rain in every section of circuit in the forecasting period is by following
Formula is calculated：
R=ra+rz+rs
Wherein, raThe indirect early stage in region is effective residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period
Rainfall, rzThe direct early stage effective rainfall in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period
Amount, rsThe short duration raininess in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period；raAs follows
Calculate：
rikRepresent the rainfall before the i-th k days；βaTo characterize attenuation coefficient of the Rock And Soil to the retentivity of rainwater, βa≤
1.0；n1For total number of days of prophase programming；
The average height of run-off h in region residing for the shaft tower respectively affected by heavy rain in every section of circuit in the forecasting period by with
Under type is calculated：
For the shaft tower at domatic lower exit, the computing formula of the average height of run-off h in its residing region is：
Wherein, cdIt is the slope concentration coefficient in region residing for the shaft tower in every section of circuit respectively at the domatic lower exit, td
The rainwash time in region residing for the shaft tower in every section of circuit in forecasting period respectively at domatic lower exit；
For the shaft tower in mountain valley water channel exit, the computing formula of the average height of run-off h in its residing region is：
H=λ Itc
Wherein, λ is that the mountain valley water channel in region residing for the shaft tower in every section of circuit everywhere in mountain valley water channel exit confluxes and is
Number, tcThe earth's surface inlet time in region residing for the shaft tower in every section of circuit in forecasting period everywhere in mountain valley water channel exit；
The bulk solid mass in region is steady residing for the shaft tower respectively affected by heavy rain in every section of circuit in the forecasting period
Determine COEFFICIENT K to calculate by the coefficient of stability Mathematical Modeling of bulk solid mass：
Wherein,For the internal friction of bulk solid mass, θ is slope inclination angle, ρsatFor bulk solid mass after water of satisfying
Density, ρmFor the density of silt carrying flow, ρsFor solid bulk materials density, ρ is water density, and g is acceleration of gravity, and c is cohesion
Power, H is saturation bulk solid mass thickness, and h is respectively to be affected by heavy rain in every section of circuit in the above-mentioned forecasting period for calculating
The average height of run-off in region residing for shaft tower；Wherein, c andBetween relation be：
C=0.04w-0.95
Wherein, w is water content for relaxed matter；
6) to every section of circuit, residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the CALCULATING PREDICTION period as follows
The mountain torrents strength factor E in regionm：
Em=sr/ (rBβ)
Wherein, s is the topography and geomorphology coefficient in region residing for the shaft tower respectively affected by heavy rain in every section of circuit, rBOn the basis of rain
Value, β are the shaft tower safety coefficient of the shaft tower respectively affected by heavy rain in every section of circuit；
Then, the mountain torrents strength factor in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather report
Em, the shaft tower the weakness α of shaft tower that respectively affected by heavy rain in every section of circuit, calculate every section of circuit using fuzzy mathematical model
In the probability that breaks down under mountain flood of the shaft tower that respectively affected by heavy rain, finally calculate according to independent event new probability formula
Probability of malfunction p of the whole piece circuit under mountain flood1；
The process of setting up of fuzzy mathematical model is in this step：First, the shaft tower on respectively being affected by heavy rain in every section of circuit
The mountain torrents strength factor E of regionmMould is carried out with the shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit
Gelatinization is processed, and Triangleshape grade of membership function is set up respectively, calculates mountain torrents strength factor EmWith being subordinate to for shaft tower the weakness α
Degree；Then, obfuscation rule is set up according to measured data and historical data, shaft tower is obtained by weighted average method de-fuzzy
The probability broken down under mountain flood；Finally according to measured data, to mountain torrents strength factor EmWith shaft tower the weakness α
Membership function and fuzzy rule be modified, obtain final fuzzy mathematical model；
7) to every section of circuit, residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the CALCULATING PREDICTION period as follows
The landslide strength factor E in regionl：
El=sc1r/(rBβ)
Wherein, c1It is the geological environment coefficient in region residing for the shaft tower respectively affected by heavy rain in every section of circuit；
Then, the landslide strength factor in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather report
El, the shaft tower the weakness α of shaft tower that respectively affected by heavy rain in every section of circuit, calculate every section of circuit using fuzzy mathematical model
In the probability that breaks down under landslide disaster of the shaft tower that respectively affected by heavy rain, finally calculate according to independent event new probability formula
Probability of malfunction p of the whole piece circuit under landslide disaster2；
The process of setting up of fuzzy mathematical model is in this step：First, the shaft tower on respectively being affected by heavy rain in every section of circuit
The landslide strength factor E of regionlMould is carried out with the shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit
Gelatinization is processed, and Triangleshape grade of membership function is set up respectively, calculates landslide strength factor ElWith being subordinate to for shaft tower the weakness α
Degree；Then, obfuscation rule is set up according to measured data and historical data, shaft tower is obtained by weighted average method de-fuzzy
The probability broken down under landslide disaster；Finally according to measured data, to the strength factor E that comes downlWith shaft tower the weakness α
Membership function and fuzzy rule be modified, obtain final fuzzy mathematical model；
8) to every section of circuit, residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the CALCULATING PREDICTION period as follows
The mud-rock flow strength factor E in regionw：
Ew=Kr/ (rBβ)
Then, the mudstone intensity of flow system in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather report
Number Ew, the shaft tower the weakness α of shaft tower that respectively affected by heavy rain in every section of circuit, calculate every section of line using fuzzy mathematical model
The probability that the shaft tower respectively affected by heavy rain in road breaks down under mud-stone flow disaster, finally according to independent event new probability formula meter
Calculate probability of malfunction p of the whole piece circuit under mud-stone flow disaster3；
The process of setting up of fuzzy mathematical model is in this step：First, the shaft tower on respectively being affected by heavy rain in every section of circuit
The mud-rock flow strength factor E of regionwCarry out with the shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit
Fuzzy processing, sets up respectively Triangleshape grade of membership function, calculates mud-rock flow strength factor EwWith the person in servitude of shaft tower the weakness α
Category degree；Then, obfuscation rule is set up according to measured data and historical data, bar is obtained by weighted average method de-fuzzy
The probability that tower breaks down under mud-stone flow disaster；Finally according to measured data, to mud-rock flow strength factor EwIt is fragile with shaft tower
The membership function and fuzzy rule of degree index α is modified, and obtains final fuzzy mathematical model；
9) the total probability of malfunction p of whole piece circuit is calculated as follows：
P=1- (1-p1)(1-p2)(1-p3)
Finally, risk will be carried out to failure in the total probability of malfunction result of calculation access blackout defense system of whole piece circuit to comment
Estimate, be wide area measurement analysis Protection control system screening anticipation risk equipment collection according to risk evaluation result.
Above-mentioned technical proposal is further characterized by：The step 5) in, βaValue be 0.8.
Above-mentioned technical proposal is further characterized by：The step 5) in, for general heavy rain, n1Value is 20 days；
For torrential rain, n1Value is 10 days.
Above-mentioned technical proposal is further characterized by：The step 6), 7), 8) in, every section of line is calculated as follows
The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in road：
α=dmb
Wherein, d is the line span coefficient of every section of circuit, and m is the shaft tower of the shaft tower respectively affected by heavy rain in every section of circuit
Genre modulus, b is the pole and tower foundation strength factor of the shaft tower respectively affected by heavy rain in every section of circuit.
Beneficial effects of the present invention are as follows：Present invention achieves heavy rain causes the qualitative assessment of transmission line malfunction probability, root
Cause the mechanism of transmission line malfunction according to heavy rain, establish accurate line fault probabilistic model, correctly reflect and power transmission line
The related inside and outside portion's factor of road failure so that heavy rain causes line fault probability assessment to be not necessarily dependent on the accumulation of historical data,
Shaft tower stress and Strength co-mputation are avoided, the various correlative factors factor of precise quantification (particularly cannot), tool has been taken into full account
There is very strong adaptability.Therefore, this method has greatly promoted transmission line of electricity risk management, improves power system defence outside
The ability of disaster.
Description of the drawings
Fig. 1 is the flow chart of the inventive method.
Fig. 2 is the footpath flow diagram at domatic lower exit.
Fig. 3 is the footpath flow diagram in mountain valley water channel exit.
Specific embodiment
The present invention is described in further detail with reference to the accompanying drawings and with reference to example.
In Fig. 1 step 1 in the controlling the heart collect real-time heavy rain forecast and its live state information (rainfall intensity, when continuing
Between etc.), general meteorological forecast and its live state information and real-time electrical network work information.
In Fig. 1 step 2 according to geographical feature and surrounding enviroment feature by line sectionalizing, will be with similar or identical geographical special
The circuit of surrounding enviroment of seeking peace feature is divided into one section, and by domatic lower exit and in mountain valley water channel exit
Shaft tower is used as the shaft tower affected by heavy rain.
Step 3 carries out linear extrapolation according to the real-time detection data of Doppler radar in Fig. 1, forecasts the drop of future time period
Raininess degree and rainfall scope.
1) rainfall scope forecast
Extrapolation to radar return, employs and makees linear least square fitting in the position of adjacent moment to echo barycenter
Method.First position of the barycenter in rectangular coordinate system is calculated according to radar return rate reflected value, then obtain the echo of barycenter
Speed and moving direction, obtain rainfall scope.
2) rainfall intensity forecast
According to the actual measurement radar rainfall runoff process rate of front several periods, calculate and determine that a unit radar rainfall runoff process is several in the past
The average rate of change of individual period, and as the rate of change of the subsequent period radar return, thus obtain subsequent period
Radar return rate.According to weather report radar rainfall runoff process rate carries out rainfall intensity estimation, obtains each in every section of circuit in forecasting period
The rainfall intensity in region residing for the shaft tower affected by heavy rain.
Step 4 in Fig. 1, to every section of circuit, according to line facility present position geographical feature and surrounding enviroment feature to drop
The impact of raininess degree, on step 3) in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in the forecasting period that obtains
Rainfall intensity is modified, and obtains region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in revised forecasting period
Rainfall intensity I.
Wherein, clinoform is with the relation of rainfall intensity：When prevailing wind direction is zero with the angle of windward slope slope aspect, landform
Amplification maximum to rainfall (concrete numerical value is relevant with actual landform landforms)；When terrain slope is between 30 °～60 °, landform pair
The amplification change of rainfall is not apparent；Typically, in the case where terrain slope is homogeneous, windward slope rainfall is usually first with mountain
The increase of body height and increase, to Maximum rainfall height (Maximum rainfall height is generally present in the 70%～80% of relative elevation)
Afterwards, rainfall intensity reduces on the contrary with the increase of height, and the precipitation intensity on mountain top may be less than hillside pin；In mountain height phase
Meanwhile, the gradient is generally present in 45 ° or so to the maximum amplification of rainfall；When windward slope present ladder when, in fact it could happen that two or
Two or more Maximum rainfall height；Typically, in the case where terrain slope is homogeneous, always the precipitation intensity of leeward slope is high with massif
Degree is raised and increased；And the gradient is closer to 45 °, change more obvious.
Step 5 in Fig. 1, to every section of circuit, assessment calculates required dynamic variable, and the dynamic variable includes forecasting period
Receive in every section of circuit in the effective precipitation r in region, forecasting period residing for the shaft tower respectively affected by heavy rain in interior every section of circuit
The shaft tower respectively affected by heavy rain in every section of circuit in the average height of run-off h in region, forecasting period residing for the shaft tower that heavy rain affects
The coefficient of stability K of the bulk solid mass in residing region.
The formation of landslide, mud-rock flow etc. is early stage effective precipitation and the coefficient result of short duration raininess.It is general and
Speech, prophase programming lasts longer, and hillside rock mass contains water saturation, and intensity decreases, slopes become unstable.It is sudden and violent after continuous rainfall
Rain, is the dynamic condition for inducing this kind of disaster.Therefore, the shaft tower institute for respectively being affected by heavy rain in every section of circuit in the forecasting period
The effective precipitation r in place region is calculated as follows：
R=ra+rz+rs
Wherein, raThe indirect early stage in region is effective residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period
Rainfall, rzThe direct early stage effective rainfall in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period
Amount, rsThe short duration raininess in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period；raAs follows
Calculate：
rikRepresent the rainfall before the i-th k days；βaTo characterize attenuation coefficient of the Rock And Soil to the retentivity of rainwater, by area
Domain Rock And Soil gross properties decision, βa≤ 1.0, typically take 0.8；n1For total number of days of prophase programming, general heavy rain type value is 20
My god, torrential rain type value is 10 days.
The average height of run-off h in region residing for the shaft tower respectively affected by heavy rain in every section of circuit in the forecasting period by with
Under type is calculated：
For the shaft tower at domatic lower exit, its runoff situation is as shown in Figure 2.Start to produce after rainwater lands
During runoff, the current on hillside or sloping floor are initially very thin water layers, but through certain hour, can be produced in slope
Completely current, become stationary flow.It is assumed herein that：1) slope is straight line；2) when slope runoff is formed, slope top layer bulk solids
Material is fully saturated；3) within the forecast time period, storm intensity is constant with the time.Therefore, in domatic lower exit
The shaft tower at place, the computing formula of the average height of run-off h in its residing region is：
Wherein, cdIt is the slope concentration coefficient in region residing for the shaft tower in every section of circuit respectively at domatic lower exit,
As shown in table 1；tdThe earth's surface footpath in region residing for the shaft tower in every section of circuit in forecasting period respectively at domatic lower exit
The time required to stream time, i.e. current arrive from the hilltop shaft tower position, depending on apparent distance length, terrain slope and covered ground situation,
It is desirable 5～15 minutes.
For the shaft tower in mountain valley water channel exit, its runoff situation is as shown in Figure 3.The active cross-section class of mountain valley water channel
Type is complicated and changeable, for the ease of reflecting impact of the current to shaft tower, selects current height of run-off to be estimated.It is assumed herein that：1)
When raceway groove runoff is formed, raceway groove side slope bulk solid mass is fully saturated；2) within the forecast time period, storm intensity is at any time
Between it is constant.Therefore, for the shaft tower in mountain valley water channel exit, the computing formula of the average height of run-off h in its residing region
For：
H=λ Itc
Wherein, λ is that the mountain valley water channel in region residing for the shaft tower in every section of circuit everywhere in mountain valley water channel exit confluxes and is
Number, also as shown in table 1；tcThe ground in region residing for the shaft tower in every section of circuit in forecasting period everywhere in mountain valley water channel exit
, from mountain valley raceway groove top to shaft tower position required time, apparent distance length, terrain slope and ground are covered for table inlet time, i.e. current
Depending on lid situation, reference value is 5～15 minutes.
The slope concentration coefficient of table 1 and mountain valley water channel conflux coefficient
The bulk solid mass in region is steady residing for the shaft tower respectively affected by heavy rain in every section of circuit in the forecasting period
Determine COEFFICIENT K to calculate by the coefficient of stability Mathematical Modeling of bulk solid mass：
Wherein,For the internal friction of bulk solid mass, θ is slope inclination angle, ρsatFor bulk solid mass after water of satisfying
Density, reference value can use 2.1g/cm3, ρmFor the density of silt carrying flow, reference value can use 1.1g/cm3, ρsFor solid bulk materials
Density, reference value can use 2.5g/cm3, ρ is water density, and g is acceleration of gravity, and c is cohesive force, and H is saturation bulk solid mass
Thickness, reference value can use 0.4m, and h is residing for the shaft tower respectively affected by heavy rain in every section of circuit in the above-mentioned forecasting period for calculating
The average height of run-off in region；Wherein, c andBetween relation be：
C=0.04w-0.95
Wherein, w is water content for relaxed matter；
Additionally, other static informations used in the present invention include：The line span coefficient d of every section of circuit, takes actual shelves
Away from the ratio with a reference value；The shaft tower genre modulus m of the shaft tower respectively affected by heavy rain in every section of circuit, be with general shaft tower type
Benchmark (value 1.0), the higher shaft tower of ability to bear heightens coefficient (1.0～2.0), and the weaker shaft tower of ability to bear turns down coefficient
(0.5～1.0)；Shaft tower safety coefficient β of the shaft tower respectively affected by heavy rain in every section of circuit, span is 0～1.0；Per section
The geological environment coefficient c in region residing for the shaft tower respectively affected by heavy rain in circuit1, wherein, with general geology type environment as base
Accurate (value is 1.0), by the location for being easier to the disasters such as landslide coefficient (1.0～2.0) is heightened, and is not susceptible to the disasters such as landslide
Location turn down coefficient (0.7～1.0)；The topography and geomorphology coefficient s in region residing for the shaft tower respectively affected by heavy rain in every section of circuit,
On the basis of smooth relief (value is 1.0), the landform such as the precipitous, ravines and guillies criss-cross of physical features are heightened into coefficient (1.0～1.8), physical features
Flat, vegetation is luxuriant etc., and landform turns down coefficient (0.5～1.0)；The pole and tower foundation of the shaft tower respectively affected by heavy rain in every section of circuit
Strength factor b, on the basis of general shaft tower ground (value 1.0), firmer ground heightens coefficient (1.0～1.5), weak
Ground turn down coefficient (0.4～1.0)；The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit, α=
dmb。
Step 6 in Fig. 1, to every section of circuit, is respectively affected as follows in every section of circuit in the CALCULATING PREDICTION period by heavy rain
Shaft tower residing for region mountain torrents strength factor Em：
Em=sr/ (rBβ)
Wherein, s is the topography and geomorphology coefficient in region residing for the shaft tower respectively affected by heavy rain in every section of circuit, rBOn the basis of rain
Value (empirically value, can change according to actual conditions), the shaft tower safety that β is the shaft tower respectively affected by heavy rain in every section of circuit
Coefficient.
Then, the mountain torrents strength factor in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather report
Em, the shaft tower the weakness α of shaft tower that respectively affected by heavy rain in every section of circuit, calculate every section of circuit using fuzzy mathematical model
In the probability that breaks down under mountain flood of the shaft tower that respectively affected by heavy rain, finally calculate according to independent event new probability formula
Probability of malfunction p of the whole piece circuit under mountain flood1。
First, the mountain torrents strength factor E of the shaft tower region on respectively being affected by heavy rain in every section of circuitmWith every section of circuit
In the shaft tower the weakness α of shaft tower that respectively affected by heavy rain carry out Fuzzy processing, Triangleshape grade of membership function is set up respectively,
Calculate mountain torrents strength factor EmWith the degree of membership of shaft tower the weakness α；Then, mould is set up according to measured data and historical data
Gelatinization rule, by weighted average method de-fuzzy the probability that shaft tower breaks down under mountain flood is obtained；Finally according to
Measured data, to mountain torrents strength factor EmIt is modified with the membership function and fuzzy rule of shaft tower the weakness α, obtains
To final fuzzy mathematical model so that probability of malfunction is more accurate.
Step 7 in Fig. 1, to every section of circuit, is respectively affected as follows in every section of circuit in the CALCULATING PREDICTION period by heavy rain
Shaft tower residing for region landslide strength factor El：
El=sc1r/(rBβ)
Wherein, c1It is the geological environment coefficient in region residing for the shaft tower respectively affected by heavy rain in every section of circuit.
Then, the landslide strength factor in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather report
El, the shaft tower the weakness α of shaft tower that respectively affected by heavy rain in every section of circuit, calculate every section of circuit using fuzzy mathematical model
In the probability that breaks down under landslide disaster of the shaft tower that respectively affected by heavy rain, finally calculate according to independent event new probability formula
Probability of malfunction p of the whole piece circuit under landslide disaster2。
First, the landslide strength factor E of the shaft tower region on respectively being affected by heavy rain in every section of circuitlWith every section of circuit
In the shaft tower the weakness α of shaft tower that respectively affected by heavy rain carry out Fuzzy processing, Triangleshape grade of membership function is set up respectively,
Calculate landslide strength factor ElWith the degree of membership of shaft tower the weakness α；Then, mould is set up according to measured data and historical data
Gelatinization rule, by weighted average method de-fuzzy the probability that shaft tower breaks down under landslide disaster is obtained；Finally according to
Measured data, to the strength factor E that comes downlIt is modified with the membership function and fuzzy rule of shaft tower the weakness α, obtains
To final fuzzy mathematical model so that probability of malfunction is more accurate.
Step 8 in Fig. 1, to every section of circuit, is respectively affected as follows in every section of circuit in the CALCULATING PREDICTION period by heavy rain
Shaft tower residing for region mud-rock flow strength factor Ew：
Ew=Kr/ (rBβ)
Then, the mudstone intensity of flow system in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather report
Number Ew, the shaft tower the weakness α of shaft tower that respectively affected by heavy rain in every section of circuit, calculate every section of line using fuzzy mathematical model
The probability that the shaft tower respectively affected by heavy rain in road breaks down under mud-stone flow disaster, finally according to independent event new probability formula meter
Calculate probability of malfunction p of the whole piece circuit under mud-stone flow disaster3。
First, the mud-rock flow strength factor E of the shaft tower region on respectively being affected by heavy rain in every section of circuitwWith every section of line
The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in road carries out Fuzzy processing, and triangle degree of membership letter is set up respectively
Number, calculates mud-rock flow strength factor EwWith the degree of membership of shaft tower the weakness α；Then, according to measured data and historical data
Obfuscation rule is set up, the probability that shaft tower breaks down under mud-stone flow disaster is obtained by weighted average method de-fuzzy；
Finally according to measured data, to mud-rock flow strength factor EwWith the membership function and fuzzy rule of shaft tower the weakness α
It is modified, obtains final fuzzy mathematical model so that probability of malfunction is more accurate.
Step 9 in Fig. 1, calculates as follows the total probability of malfunction p of whole piece circuit：
P=1- (1-p1)(1-p2)(1-p3)
Finally, risk will be carried out to failure in the total probability of malfunction result of calculation access blackout defense system of whole piece circuit to comment
Estimate, be wide area measurement analysis Protection control system screening anticipation risk equipment collection according to risk evaluation result.
Although the present invention is disclosed as above with preferred embodiment, embodiment is not for limiting the present invention's.Not
Depart from the spirit and scope of the present invention, any equivalence changes done or retouching also belong to the protection domain of the present invention.Cause
The content that this protection scope of the present invention should be defined with claims hereof is as standard.
Claims (3)
1. the method that heavy rain causes transmission line malfunction probability is assessed, it is characterised in that comprised the steps：
1) in the controlling the heart collect the forecast and its live state information of real-time heavy rain, general meteorological forecast and its live state information with
And real-time electrical network work information；
2) according to line corridor geographical feature and surrounding enviroment feature by line sectionalizing, with identical geographical feature and surrounding enviroment
The circuit of feature divides one section into, and using the shaft tower at domatic lower exit and in mountain valley water channel exit as by heavy rain
The shaft tower of impact；
3) according to the real-time detection data of Doppler radar, linear extrapolation is carried out, forecasts rainfall scope and the rainfall of future time period
Intensity, obtains the rainfall intensity in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period；
4) to every section of circuit, according to the impact of line facility present position geographical feature and surrounding enviroment feature to rainfall intensity,
On step 3) in the rainfall intensity in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in the forecasting period that obtains carry out
Amendment, obtains rainfall intensity I in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in revised forecasting period；
5) to every section of circuit, assessment calculates required dynamic variable, and the dynamic variable is including in every section of circuit in forecasting period
The bar respectively affected by heavy rain in every section of circuit in the effective precipitation r in region residing for the shaft tower for respectively being affected by heavy rain, forecasting period
The pine in region residing for the shaft tower respectively affected by heavy rain in every section of circuit in the average height of run-off h in region residing for tower, forecasting period
The coefficient of stability K of scattered solid matter；
The effective precipitation r in region residing for the shaft tower respectively affected by heavy rain in every section of circuit in the forecasting period is as follows
Calculate：
R=ra+rz+rs
Wherein, raThe indirect early stage effective rainfall in region residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting period
Amount, rzThe direct early stage effective precipitation in region, r residing for the shaft tower that respectively affected by heavy rain in every section of circuit in forecasting periodsFor
The short duration raininess in region residing for the shaft tower respectively affected by heavy rain in every section of circuit in forecasting period；raCalculate as follows：
rikRepresent the rainfall before the i-th k days；βaTo characterize attenuation coefficient of the Rock And Soil to the retentivity of rainwater, βa≤1.0；n1
For total number of days of prophase programming；
The average height of run-off h in region residing for the shaft tower respectively affected by heavy rain in every section of circuit in the forecasting period is by with lower section
Formula is calculated：
For the shaft tower at domatic lower exit, the computing formula of the average height of run-off h in its residing region is：
Wherein, cdIt is the slope concentration coefficient in region residing for the shaft tower in every section of circuit respectively at the domatic lower exit, tdFor pre-
The rainwash time in region residing for shaft tower in section of giving the correct time in every section of circuit respectively at domatic lower exit；
For the shaft tower in mountain valley water channel exit, the computing formula of the average height of run-off h in its residing region is：
H=λ Itc
Wherein, λ is that the mountain valley water channel in region residing for the shaft tower in every section of circuit everywhere in mountain valley water channel exit confluxes coefficient, tc
The earth's surface inlet time in region residing for the shaft tower in every section of circuit in forecasting period everywhere in mountain valley water channel exit；
The stability series of the bulk solid mass in region residing for the shaft tower respectively affected by heavy rain in every section of circuit in the forecasting period
Number K presses the coefficient of stability Mathematical Modeling of bulk solid mass and calculates：
Wherein,For the internal friction of bulk solid mass, θ is slope inclination angle, ρsatFor satisfy water after bulk solid mass density,
ρmFor the density of silt carrying flow, ρsFor solid bulk materials density, ρ is water density, and g is acceleration of gravity, and c is cohesive force, and H is
Saturation bulk solid mass thickness, h is the shaft tower institute respectively affected by heavy rain in every section of circuit in the above-mentioned forecasting period for calculating
The average height of run-off in place region；Wherein, c andBetween relation be：
C=0.04w-0.95
Wherein, w is water content for relaxed matter；
6) to every section of circuit, region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the CALCULATING PREDICTION period as follows
Mountain torrents strength factor Em：
Em=sr/ (rBβ)
Wherein, s is the topography and geomorphology coefficient in region residing for the shaft tower respectively affected by heavy rain in every section of circuit, rBOn the basis of rainfall value,
β is the shaft tower safety coefficient of the shaft tower respectively affected by heavy rain in every section of circuit；
Then, the mountain torrents strength factor E in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather reportm, it is every
The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in section circuit, calculates each in every section of circuit using fuzzy mathematical model
The probability that the shaft tower affected by heavy rain breaks down under mountain flood, finally calculates whole piece according to independent event new probability formula
Probability of malfunction p of the circuit under mountain flood1；
The process of setting up of fuzzy mathematical model is in this step：First, the shaft tower respectively affected by heavy rain in every section of circuit is located
The mountain torrents strength factor E in regionmObfuscation is carried out with the shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit
Process, Triangleshape grade of membership function is set up respectively, calculate mountain torrents strength factor EmWith the degree of membership of shaft tower the weakness α；So
Afterwards, obfuscation rule is set up according to measured data and historical data, shaft tower is obtained on mountain by weighted average method de-fuzzy
The probability broken down under disaster；Finally according to measured data, to mountain torrents strength factor EmWith the person in servitude of shaft tower the weakness α
Category degree function and fuzzy rule are modified, and obtain final fuzzy mathematical model；
The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit is calculated as follows：
α=dmb
Wherein, d is the line span coefficient of every section of circuit, and m is the shaft tower type of the shaft tower respectively affected by heavy rain in every section of circuit
Coefficient, b is the pole and tower foundation strength factor of the shaft tower respectively affected by heavy rain in every section of circuit；
7) to every section of circuit, region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the CALCULATING PREDICTION period as follows
Landslide strength factor El：
El=sc1 r/(rBβ)
Wherein, c1It is the geological environment coefficient in region residing for the shaft tower respectively affected by heavy rain in every section of circuit；
Then, the landslide strength factor E in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather reportl, it is every
The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in section circuit, calculates each in every section of circuit using fuzzy mathematical model
The probability that the shaft tower affected by heavy rain breaks down under landslide disaster, finally calculates whole piece according to independent event new probability formula
Probability of malfunction p of the circuit under landslide disaster2；
The process of setting up of fuzzy mathematical model is in this step：First, the shaft tower respectively affected by heavy rain in every section of circuit is located
The landslide strength factor E in regionlObfuscation is carried out with the shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit
Process, Triangleshape grade of membership function is set up respectively, calculate landslide strength factor ElWith the degree of membership of shaft tower the weakness α；So
Afterwards, obfuscation rule is set up according to measured data and historical data, shaft tower is obtained by weighted average method de-fuzzy and is being slided
The probability broken down under the disaster of slope；Finally according to measured data, to the strength factor E that comes downlWith the person in servitude of shaft tower the weakness α
Category degree function and fuzzy rule are modified, and obtain final fuzzy mathematical model；
The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit is calculated as follows：
α=dmb
Wherein, d is the line span coefficient of every section of circuit, and m is the shaft tower type of the shaft tower respectively affected by heavy rain in every section of circuit
Coefficient, b is the pole and tower foundation strength factor of the shaft tower respectively affected by heavy rain in every section of circuit；
8) to every section of circuit, region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the CALCULATING PREDICTION period as follows
Mud-rock flow strength factor Ew：
Ew=K r/ (rBβ)
Then, the mud-rock flow strength factor E in region residing for the shaft tower for respectively being affected by heavy rain in every section of circuit in the period according to weather reportw、
The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit, is calculated in every section of circuit using fuzzy mathematical model
The probability that the shaft tower for respectively being affected by heavy rain breaks down under mud-stone flow disaster, finally calculates according to independent event new probability formula
Probability of malfunction p of the whole piece circuit under mud-stone flow disaster3；
The process of setting up of fuzzy mathematical model is in this step：First, the shaft tower respectively affected by heavy rain in every section of circuit is located
The mud-rock flow strength factor E in regionwObscured with the shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit
Change is processed, and Triangleshape grade of membership function is set up respectively, calculates mud-rock flow strength factor EwWith being subordinate to for shaft tower the weakness α
Degree；Then, obfuscation rule is set up according to measured data and historical data, shaft tower is obtained by weighted average method de-fuzzy
The probability broken down under mud-stone flow disaster；Finally according to measured data, to mud-rock flow strength factor EwWith shaft tower fragile degree
The membership function and fuzzy rule of index α is modified, and obtains final fuzzy mathematical model；
The shaft tower the weakness α of the shaft tower respectively affected by heavy rain in every section of circuit is calculated as follows：
α=dmb
Wherein, d is the line span coefficient of every section of circuit, and m is the shaft tower type of the shaft tower respectively affected by heavy rain in every section of circuit
Coefficient, b is the pole and tower foundation strength factor of the shaft tower respectively affected by heavy rain in every section of circuit；
9) the total probability of malfunction p of whole piece circuit is calculated as follows：
P=1- (1-p1)(1-p2)(1-p3)
Finally, the total probability of malfunction result of calculation of whole piece circuit is accessed in blackout defense system carries out risk assessment to failure,
It is wide area measurement analysis Protection control system screening anticipation risk equipment collection according to risk evaluation result.
2. the method that assessment heavy rain according to claim 1 causes transmission line malfunction probability, it is characterised in that：The step
It is rapid 5) in, βaValue be 0.8.
3. the method that assessment heavy rain according to claim 1 causes transmission line malfunction probability, it is characterised in that：The step
It is rapid 5) in, for general heavy rain, n1Value is 20 days；For torrential rain, n1Value is 10 days.
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| CN106952005A (en) * | 2016-01-06 | 2017-07-14 | 四川大学 | A kind of Study of Risk Evaluation Analysis for Power System method for considering rain-induced landslide geological disaster |
| CN106056851B (en) * | 2016-05-13 | 2019-03-22 | 国网浙江省电力公司台州供电公司 | Electrical network facilities heavy rain method for early warning |
| CN107092793B (en) * | 2017-04-20 | 2020-02-04 | 国网湖南省电力有限公司 | Method and system for calculating rainfall response degree along power transmission line |
| CN107169645B (en) * | 2017-05-09 | 2020-11-03 | 云南电力调度控制中心 | Power transmission line fault probability online evaluation method considering influence of rainstorm disaster |
| CN107274634B (en) * | 2017-07-13 | 2019-07-26 | 国网湖南省电力有限公司 | Precipitation Secondary Geological Hazards alarm calculation method and system along a kind of transmission line of electricity |
| CN109523090A (en) * | 2018-12-04 | 2019-03-26 | 国网湖南省电力有限公司 | A kind of transmission line of electricity heavy rain Prediction of Landslide and system |
| CN111738617B (en) * | 2020-07-01 | 2023-12-26 | 广东电网有限责任公司广州供电局 | Transformer substation risk assessment method and early warning system in heavy rainfall weather |
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| CN115047543B (en) * | 2022-08-16 | 2022-11-11 | 成都信息工程大学 | Power transmission corridor rainfall early warning method and system |
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