CN107169645A - A kind of transmission line malfunction probability online evaluation method of meter and Rainfall Disaster influence - Google Patents

A kind of transmission line malfunction probability online evaluation method of meter and Rainfall Disaster influence Download PDF

Info

Publication number
CN107169645A
CN107169645A CN201710323118.1A CN201710323118A CN107169645A CN 107169645 A CN107169645 A CN 107169645A CN 201710323118 A CN201710323118 A CN 201710323118A CN 107169645 A CN107169645 A CN 107169645A
Authority
CN
China
Prior art keywords
rainfall
weather station
geographic grid
mrow
forecast
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201710323118.1A
Other languages
Chinese (zh)
Other versions
CN107169645B (en
Inventor
黄燕
吴琛
徐泰山
刘旭斐
常康
卢耀华
郁琛
王昊昊
赵明
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
YUNNAN ELECTRIC POWER DISPATCH CONTROL CENTER
Nari Technology Co Ltd
Nanjing NARI Group Corp
Original Assignee
YUNNAN ELECTRIC POWER DISPATCH CONTROL CENTER
Nari Technology Co Ltd
Nanjing NARI Group Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by YUNNAN ELECTRIC POWER DISPATCH CONTROL CENTER, Nari Technology Co Ltd, Nanjing NARI Group Corp filed Critical YUNNAN ELECTRIC POWER DISPATCH CONTROL CENTER
Priority to CN201710323118.1A priority Critical patent/CN107169645B/en
Publication of CN107169645A publication Critical patent/CN107169645A/en
Application granted granted Critical
Publication of CN107169645B publication Critical patent/CN107169645B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0635Risk analysis of enterprise or organisation activities
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06Energy or water supply

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Theoretical Computer Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Health & Medical Sciences (AREA)
  • Marketing (AREA)
  • General Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • Public Health (AREA)
  • Primary Health Care (AREA)
  • Water Supply & Treatment (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • General Health & Medical Sciences (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a kind of meter and the transmission line malfunction probability online evaluation method of Rainfall Disaster influence, belong to power system automation technology field.The geographic grid that the present invention calculates the target grid location of assessment first will assess the prediction rainfall in this period at moment, the history accumulation rainfall before current time in certain historical time section in current time to future;Then, prediction and the history rainfall information of transmission tower are calculated according to geographic grid rainfall data, shaft tower and weather station latitude and longitude information, topography and geomorphology parameter further according to shaft tower column foot, the synthesis effective precipitation for calculating with reference to shaft tower rainfall information transmission tower, and then the probability of malfunction of shaft tower is obtained, finally obtain considering the transmission line malfunction probability of Rainfall Disaster influence using relatively independent event algorithm.The present invention greatly improves computational efficiency on the premise of can calculating accuracy and precision ensureing shaft tower rainfall information.

Description

A kind of transmission line malfunction probability online evaluation method of meter and Rainfall Disaster influence
Technical field
The invention belongs to power system automation technology field, specifically the present invention relates to one kind meter and Rainfall Disaster shadow Loud transmission line malfunction probability online evaluation method.
Background technology
Heavy rain is one of common meteorological disaster of China, and a wide range of prolonged heavy showers can directly result in flood. Continue heavy showers or have the short-duration rainstorm of prophase programming cumulative function, rainwater accumulation, seepage flow can cause slope Rock And Soil severe Increase, ground softening, the reduction of slide strips strengths of rock and soil etc., and then trigger the serious Derived Hazard such as landslide and mud-rock flow.
The height requirement to power consumption triggered along with rapid growth economic in recent years, power industry is quickly sent out Exhibition, gradually forms transferring electricity from the west to the east, the electric alternating current-direct current series-parallel connection power transmission network main grid structure mutually helped in south.Due to generating end and the distance of receiving end Farther out, distribution network users disperse, and overhead transmission line is frequently necessary to cross over mountain after mountain, the various complicated geographical environments of approach.Severe Rainstorm weather in the case of, be located in the shaft tower in the easily disaster area such as hillside, mountain peak, valley, river valley, basin, horn mouth, can be by Considerable influence, and then influence the safe and stable operation of transmission line of electricity and power network.It is therefore desirable to the reality for transmission line of electricity Situation carries out Rainfall Disaster risk assessment, and the shaft tower larger to disaster probability and circuit provide disaster alarm.
At present, the domestic influence research direction in Rainfall Disaster to transmission line of electricity is mainly grouped as based on big data screening point The off-line model research of analysis.Compare it is representational have patent application " assess heavy rain trigger transmission line malfunction probability method " (201310380170.2), patent application " a kind of modeling method of power transmission and transforming equipment failure probability model towards risk assessment " (201510908694.3) a kind of, patent application " rainstorm disaster risk evaluation method for foundation slope of transmission line tower " (201210301265.6)。
Patent application " assessing the method that heavy rain triggers transmission line malfunction probability " (201310380170.2) proposes basis Actual measurement rainfall data carry out the rainfall scope and rainfall intensity that linear extrapolation obtains forecasting future time period, and according to line corridor Transmission tower event will be calculated after line sectionalizing further according to transmission tower probability of malfunction computation model by managing feature and surrounding enviroment feature Hinder probability, finally obtain the probability of malfunction of circuit.
Patent application " a kind of modeling method of power transmission and transforming equipment failure probability model towards risk assessment " (201510908694.3) propose to be based on power transmission and transforming equipment real-time state monitoring, microclimate and natural calamity forecast information, for Its life cycle management information of distinct device ontoanalysis and aperiodic random information, will be each using big data screening assays Item risk factors are integrated into several risk indicators as the defeated of the power transmission and transforming equipment failure probability model based on proportional hazard model Enter, and then quantify influence of each risk factors to fault trend.
Patent application " a kind of rainstorm disaster risk evaluation method for foundation slope of transmission line tower " (201210301265.6) propose to draw control power transmission line according to a large amount of disaster statisticses and rain making slope erosion test statistics The dangerous Flood inducing factors of line pole tower basis side slope heavy rain;Flood inducing factors, slope stability are quantified, adopted after normalized The weight vectors that each Flood inducing factors cause calamity to influence heavy rain are tried to achieve with step analysis calculation procedure is improved, electric power line pole tower is set up The mathematical modeling that basic side slope heavy rain Landslide hazard is assessed, is realized to specifying transmission line tower foundation side slope heavy rain risk to comment Estimate.
But, above-mentioned existing technological achievement does not consider weather station history rainfall information and weather forecast letter The influence to following rainfall trend and shaft tower is ceased, while needing huge basic database, the maintenance of substantial amounts of calculating parameter, complexity Modular concept carry out probability of malfunction calculating, it is difficult to realize Rainfall Disaster to transmission line malfunction probability it is online fast and safely Assess.
The content of the invention
The present invention seeks to:In view of the shortcomings of the prior art, the transmission line of electricity event of a kind of meter and Rainfall Disaster influence is proposed Hinder probability online evaluation method.This method is intended to, according to weather station history rainfall information and Weather Forecast Information, calculate electricity The rainfall information of the geographic grid of location is netted, can not be truly anti-when overcoming only with reference to weather station history rainfall product data Reflect following rainfall trend and the defect of enough meteorological measuring point information can not be obtained when weather station layouts less;According to geography Grid rainfall data, shaft tower and weather station latitude and longitude information calculate the rainfall information of transmission tower, solve according to effectively away from The problem of mode inefficiency of the nearest weather station information of shaft tower correspondence being searched for from interior point-to-point;Power transmission rod is chosen by priority The topography and geomorphology parameter in tower column foot location, realizes the purpose that emphasis shaft tower, key area parameter emphasis are safeguarded, is ensureing parameter The problem of shaft tower supplemental characteristic maintenance workload is big is solved on the premise of precision.
Specifically, the present invention is realized using following technical scheme, is comprised the following steps:
1) calculate according to the following steps the geographic grid of power network location assessed in current time to future the moment this Prediction rainfall in period and the history accumulation rainfall before current time in certain historical time section, the geography network Lattice refer to the geographic grid set being divided into according to the minimax longitude and latitude of power network location, certain historical time section Refer to consider the multiple influence such as topographic and geologic weather environment decline rainfall can also be remaining certain through pervaporation and after being lost in The rainfall of ratio infiltrate through ground or accumulation in earth's surface and may finally cause landslide, mountain torrents, mud-rock flow generation it is effective Historical time section:
1-1) according to the longitude and latitude scope of geographic grid, calculate geographic grid and forecast that the overlapping area of scope is accounted for weather station The percentage of geographic grid area whether be more than threshold value set in advance, determine geographic grid whether weather station forecast model In enclosing;
Forecast scope, including directly forecast scope and indirectly forecast scope, the direct forecast model of weather station in the weather station Enclose and refer to centered on the longitude and latitude of weather station, the maximum allowable survey station spacing in weather station is multiplied by coefficient klFor the circle where radius Region;The indirect forecast scope of weather station, refers to centered on the longitude and latitude of weather station, and the maximum allowable survey station spacing in weather station multiplies With coefficient klFor inner ring, the annular region that the maximum allowable survey station spacing in weather station is outer shroud;Wherein, klTake no more than 1 positive number;
The maximum allowable survey station spacing in weather station for can ensure observed meteorological element power network location insert Value all has enough precision and representative weather station distribution distance;
If 1-2) geographic grid is in the range of the forecast of weather station, the rainfall of geographic grid is calculated in accordance with the following methods Measure information:
It is determined that mainly influenceing weather station:If geographic grid is in the directly or indirectly forecast model of one or more weather stations In enclosing, then main influence weather station is the history accumulation in certain historical time section before current time in directly forecast weather station Rainfall the maximum;If geographic grid is in the range of the indirect forecast of one or more weather stations, main influence is meteorological Stand as history accumulation rainfall the maximum before current time in forecast weather station indirectly in certain historical time section;
History accumulation rainfall before calculating geographic grid current time by formula (1) in certain historical time section, Unit is mm:
Wherein, t0For current time, TcFor certain historical time section, unit is h, r (t) for main influence weather station when The rainfall intensity that t is measured is carved, unit is mm/h;
Prediction rainfall of the geographic grid within assessment this period at moment in current time to future is calculated by formula (2) Amount, unit is mm:
Wherein, Δ t is current time t0To the following time span for assessing the moment, unit is h, rpreFor geographic grid institute The average rainfall intensity in this period at moment will be assessed in current time to future in regional weather forecast, unit is mm/ H, k1For the weight coefficient of weather station measured value, k2For the weight coefficient of weather forecast value, wherein k1+k2=1;
If geographic grid is not in the range of the forecast of weather station, the rainfall of geographic grid is calculated in accordance with the following methods Information:
History accumulation rainfall list before calculating geographic grid current time by formula (3) in certain historical time section Position is mm;
Rpast=r 'preTc (3)
Wherein, r 'preFor the weather forecast of geographic grid location before current time it is flat in certain historical time section Equal rainfall intensity, unit is mm/h;
Prediction rainfall of the geographic grid within assessment this period at moment in current time to future is calculated by formula (4) Amount, unit is mm;
Rpre=rpreΔt (4)
2) longitude and latitude of the longitude and latitude and each weather station of contrast transmission tower, if the longitude and latitude of transmission tower and certain The longitude and latitude of individual weather station is identical, then the prediction rainfall of transmission tower and history accumulation rainfall measures the prediction drop of the weather station Rainfall and history accumulation rainfall, the prediction rainfall and the circular such as formula of history accumulation rainfall of weather station (1) r (t) in, (2), wherein formula (1) takes the rainfall intensity that weather station is measured in moment t, during unit is mm/h, formula (2) rpreThe average rainfall for taking the weather forecast of weather station location to be assessed in current time to future in this period at moment is strong Degree, unit is mm/h;
If the longitude and latitude of the longitude and latitude of transmission tower and all weather stations is differed, the prediction rainfall of transmission tower Amount and history accumulation rainfall measure step 1) in the prediction rainfall of the affiliated geographic grid of transmission tower that calculates and history it is tired Product rainfall;
3) the topography and geomorphology parameter in transmission tower column foot location is determined, in conjunction with step 2) in obtain transmission tower it is pre- Rainfall and history accumulation rainfall are surveyed, the synthesis effective precipitation for obtaining transmission tower is calculated;Finally combine transmission tower event Hinder probability calculation model, calculate and obtain transmission tower because heavy rain causes the probability of malfunction of calamity;
The synthesis effective precipitation R=R of the transmission towerz+Rs, wherein, Rz, can be according to public affairs for early stage effective precipitation Formula (5) is calculated;RsFor amendment short duration raininess, calculated according to formula (6):
Rz=kp*Rpast (5)
Rs=kcor*Rpre (6)
Wherein kpFor history rainfall overall attenuation coefficient, kcorTo predict rainfall quantity correction coefficient, according to transmission tower tower The topography and geomorphology parameter of base section takes different kpAnd kcor
4) according to step 3) in obtained transmission tower probability of malfunction, using relatively independent event algorithm, calculating obtains sudden and violent Rain disaster scenarios it descends the probability of malfunction of each bar transmission line of electricity, terminates this method.
Above-mentioned technical proposal is further characterized by, the step 3) in transmission tower column foot location topography and geomorphology Parameter is chosen according to priority, and priority level sequence is as follows:The topography and geomorphology parameter of transmission tower>Geography belonging to transmission tower Grid topography and geomorphology parameter>The typical topography and geomorphology parameter of power network location.
Beneficial effects of the present invention are as follows:The present invention proposes to be believed according to weather station history rainfall information and weather forecast Breath, calculates the rainfall information of the geographic grid of power network location, overcomes only with reference to weather station history rainfall product data Shi Buneng, which truly reflects, can not obtain lacking for enough meteorological measuring point information when following rainfall trend and weather station layout less Fall into.The longitude and latitude of present invention contrast transmission tower and the longitude and latitude of each weather station obtain the rainfall information of transmission tower, Ensure that shaft tower rainfall information greatly improves computational efficiency on the premise of calculating accuracy and precision.The present invention is according to power transmission rod The typical topography and geomorphology parameter priority of geographic grid, power network location belonging to tower, transmission tower chooses transmission tower tower The topography and geomorphology parameter of base section, realizes the purpose that emphasis shaft tower, key area parameter emphasis are safeguarded, is ensureing parameters precision Under the premise of solve the problem of shaft tower supplemental characteristic maintenance workload is big.
Brief description of the drawings
Fig. 1 is the flow chart of the present invention.
Fig. 2 is grid and shaft tower rainfall calculating schematic diagram in the inventive method.
Embodiment
With reference to embodiment and the present invention is described in further detail referring to the drawings.
Embodiment 1:
One embodiment of the present of invention, implementation step is as shown in Figure 1.
Step 1 in Fig. 1, Fig. 1 is referred to describe to calculate the geographic grid of power network location at current time to not To assess the prediction rainfall in this period at moment, the history accumulation rainfall before current time in certain historical time section Amount.The geographic grid refers to the geographic grid set being divided into according to the minimax longitude and latitude of power network location, described Certain historical time section refers to considering the multiple influence decline rainfall such as topographic and geologic weather environment through pervaporation and loss After can also remaining a certain proportion of rainfall infiltrate through ground or accumulate in earth's surface and may finally cause landslide, mountain torrents, mud Effective historical time section that rock glacier occurs.
Step 1) detailed process be:First, according to the longitude and latitude scope of geographic grid, geographic grid and weather station are calculated Forecast that whether the overlapping area of scope takes up an area the percentage for managing grid area more than threshold value set in advance, determine geographic grid Whether in the range of the forecast of weather station;
Forecast scope, including directly forecast scope and indirectly forecast scope, the direct forecast model of weather station in the weather station Enclose and refer to centered on the longitude and latitude of weather station, the maximum allowable survey station spacing in weather station is multiplied by coefficient klFor the circle where radius Region;The indirect forecast scope of weather station, refers to centered on the longitude and latitude of weather station, and the maximum allowable survey station spacing in weather station multiplies With coefficient klFor inner ring, the annular region that the maximum allowable survey station spacing in weather station is outer shroud;Wherein, klTake no more than 1 positive number, K can be takenl=0.5;
The maximum allowable survey station spacing in weather station for can ensure observed meteorological element power network location insert Value all has enough precision and representative weather station distribution distance;
If geographic grid is in the range of the forecast of weather station, the rainfall letter of geographic grid is calculated in accordance with the following methods Breath:
It is determined that mainly influenceing weather station:If geographic grid is in the directly or indirectly forecast model of one or more weather stations In enclosing, then main influence weather station is the history accumulation in certain historical time section before current time in directly forecast weather station Rainfall the maximum;If geographic grid is in the range of the indirect forecast of one or more weather stations, main influence is meteorological Stand as history accumulation rainfall the maximum before current time in forecast weather station indirectly in certain historical time section;
History accumulation rainfall before calculating geographic grid current time by formula (1) in certain historical time section, Unit is mm:
Wherein t0For current time, TcFor certain historical time section, unit is h, and r (t) is main influence weather station at the moment The rainfall intensity that t is measured, unit is mm/h;
Prediction rainfall of the geographic grid within assessment this period at moment in current time to future is calculated by formula (2) Amount, unit is mm:
Wherein, Δ t is current time t0To the following time span for assessing the moment, unit is h, rpreFor geographic grid institute The average rainfall intensity in this period at moment will be assessed in current time to future in regional weather forecast, unit is mm/ H, k1For the weight coefficient of weather station measured value, k2For the weight coefficient of weather forecast value, wherein k1+k2=1, k can be taken1=k2 =0.5;
By taking Fig. 2 as an example, geographic grid is taken to forecast that the overlapping area of scope is more than or equal to geographic grid with weather station here Area 50% when, geographic grid be in weather station direct forecast scope.
Geographic grid x1y4 is in the range of weather station D direct forecast, and surrounding is without other influences weather station, its main shadow It is weather station D to ring weather station;Geographic grid x2y4, x2y3 are in the range of weather station D indirect forecast, and it mainly influences meteorology Station is weather station D;Geographic grid x2y3 is in the range of weather station B, C indirect forecast, need to compare the current of B, C weather station History accumulation rainfall before moment in certain historical time section, it is main influence weather station to take wherein the greater;Geography network Lattice x4y2 is in the range of weather station A, B indirect forecast, certain historical time before need to comparing the current time of A, B weather station History accumulation rainfall in section, it is main influence weather station to take wherein the greater;Geographic grid x5y2 is between weather station A Connect in the range of forecast, it mainly influences weather station to be weather station A;
If geographic grid is not in the range of weather station forecast, the rainfall letter of geographic grid is calculated in accordance with the following methods Breath:
History accumulation rainfall list before calculating geographic grid current time by formula (3) in certain historical time section Position is mm;
Rpast=r 'preTc (3)
Wherein, r 'preFor the weather forecast of geographic grid location before current time it is flat in certain historical time section Equal rainfall intensity, unit is mm/h;
Prediction rainfall of the geographic grid within assessment this period at moment in current time to future is calculated by formula (4) Amount, unit is mm;
Rpre=rpreΔt (4)
By taking Fig. 2 as an example, wherein geographic grid x1y1, x1y2, x3y5, x4y5, x5y5, x6y5, x6y3, x6y4 is not at gas In the range of the forecast of station, history and actual measurement rainfall need to be asked for according to formula (3) formula (4);
Fig. 1 steps 2) longitude and latitude, the longitude and latitude of weather station according to transmission tower, and step 1 are described) in obtain The affiliated geographic grid of transmission tower prediction rainfall and history accumulation rainfall, determine transmission tower prediction rainfall and History accumulation rainfall.Its detailed process is as follows:
The longitude and latitude of transmission tower and the longitude and latitude of each weather station are contrasted, if the longitude and latitude of transmission tower and some The longitude and latitude of weather station is identical, then the prediction rainfall of transmission tower and history accumulation rainfall measures the prediction rainfall of the weather station Amount and history accumulation rainfall, the prediction rainfall of weather station and the circular such as formula (1) of history accumulation rainfall, (2), the r (t) wherein in formula (1) takes the rainfall intensity that weather station is measured in moment t, and unit is r in mm/h, formula (2)pre The weather forecast of weather station location is taken to assess the average rainfall intensity in this period at moment in current time to future, Unit is mm/h;If the longitude and latitude of the longitude and latitude of transmission tower and all weather stations is differed, the prediction of transmission tower Rainfall and history accumulation rainfall measure step 1) in the prediction rainfall of the affiliated geographic grid of transmission tower that calculates and go through History accumulation rainfall;
By taking Fig. 2 as an example, shaft tower T1 longitudes and latitudes are identical with weather station D longitude and latitude, its rainfall information (prediction rainfall and History accumulation rainfall) take weather station D rainfall data;Longitude and latitude identical weather station therewith is not present in shaft tower T2~T6, its Rainfall data takes the rainfall information of its affiliated geographic grid, and wherein shaft tower T2 affiliated geographic grid is x2y4, shaft tower T3 Affiliated geographic grid be x2y3, shaft tower T4 affiliated geographic grid is x3y3, and shaft tower T5 affiliated geographic grid is x4y2, bar Tower T6 affiliated geographic grid is x5y2.
Fig. 1 steps 3) description the topography and geomorphology parameter for being to determine transmission tower column foot location, in conjunction with step 2) in The prediction of the transmission tower arrived and history rainfall information, calculate the synthesis effective precipitation for obtaining transmission tower;Finally combine Transmission tower probability of malfunction computation model, calculates and obtains transmission tower because heavy rain causes the probability of malfunction of calamity;
Here transmission tower probability of malfunction computation model can use various transmission tower probability of malfunction meters of the prior art Model is calculated, as used in patent application " assessing the method that heavy rain triggers transmission line malfunction probability " (201310380170.2) Transmission tower probability of malfunction computation model etc..
The topography and geomorphology parameter in the transmission tower column foot location can be chosen according to priority, and priority level sequence is as follows: The topography and geomorphology parameter of transmission tower>Geographic grid topography and geomorphology parameter belonging to transmission tower>The typical case of power network location Topography and geomorphology parameter;
By taking Fig. 2 as an example, geographic grid x1y3, x2y3, x1y4, x2y4 are at mud-rock flow, landslide severely afflicated area, wherein shaft tower T1 In disaster area core location, emphasis maintains shaft tower T1, geographic grid x1y3, x2y3, x1y4, x2y4 topography and geomorphology parameter, with And the typical topography and geomorphology parameter of the region n where power network;Then shaft tower T1 takes the topography and geomorphology parameter of transmission tower, and T2 takes geography Grid x2y4 topography and geomorphology parameter, T3 takes geographic grid x2y3 topography and geomorphology parameter, and T4~T6 takes region n typical landform Landforms parameter.
The synthesis effective precipitation R=R of the transmission towerz+Rs, wherein, Rz, can be according to public affairs for early stage effective precipitation Formula (5) is calculated;RsFor amendment short duration raininess, it can be calculated according to formula (6):
Rz=kp*Rpast (5)
Rs=kcor*Rpre (6)
Wherein kpFor history rainfall overall attenuation coefficient, kcorTo predict rainfall quantity correction coefficient, according to transmission tower tower The topography and geomorphology parameter of base section takes different values;
Fig. 1 steps 4) describe according to step 3) in obtained transmission tower probability of malfunction, using relatively independent event Algorithm, calculating obtains the probability of malfunction of each bar transmission line of electricity in the case of Rainfall Disaster.
Although the present invention is disclosed as above with preferred embodiment, embodiment is not for limiting the present invention's.Not In the spirit and scope for departing from 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 using claims hereof is standard.

Claims (2)

1. a kind of meter and the transmission line malfunction probability online evaluation method of Rainfall Disaster influence, it is characterised in that including following Step:
1) geographic grid for calculating power network location according to the following steps will assess this time at moment in current time to future Rainfall and the history accumulation rainfall before current time in certain historical time section are predicted in section, the geographic grid is Refer to the geographic grid set being divided into according to the minimax longitude and latitude of power network location, certain historical time section refers to Can also remaining certain proportion after pervaporation and loss considering the multiple influence decline rainfall such as topographic and geologic weather environment Rainfall infiltrate through ground or accumulation in earth's surface and may finally cause landslide, mountain torrents, mud-rock flow generation effective history Period:
1-1) according to the longitude and latitude scope of geographic grid, calculate geographic grid and forecast that the overlapping area of scope takes up an area reason with weather station The percentage of grid area whether be more than threshold value set in advance, determine geographic grid whether weather station forecast scope It is interior;
The weather station forecasts scope, including directly forecast scope and indirectly forecast scope, and the direct forecast scope of weather station is Refer to centered on the longitude and latitude of weather station, the maximum allowable survey station spacing in weather station is multiplied by coefficient klFor the circle where radius Domain;The indirect forecast scope of weather station, refers to centered on the longitude and latitude of weather station, and the maximum allowable survey station spacing in weather station is multiplied by Coefficient klFor inner ring, the annular region that the maximum allowable survey station spacing in weather station is outer shroud;Wherein, klTake no more than 1 positive number;
The maximum allowable survey station spacing in weather station for can ensure observed meteorological element power network location interpolation all With enough precision and representative weather station distribution distance;
If 1-2) geographic grid is in the range of the forecast of weather station, the rainfall letter of geographic grid is calculated in accordance with the following methods Breath:
It is determined that mainly influenceing weather station:If geographic grid is in the directly or indirectly forecast scope of one or more weather stations Interior, then main influence weather station is the history accumulation drop in certain historical time section before current time in directly forecast weather station Rainfall the maximum;If geographic grid is in the range of the indirect forecast of one or more weather stations, main influence weather station For history accumulation rainfall the maximum in certain historical time section before current time in forecast weather station indirectly;
History accumulation rainfall before calculating geographic grid current time by formula (1) in certain historical time section, unit For mm:
<mrow> <msub> <mi>R</mi> <mrow> <mi>p</mi> <mi>a</mi> <mi>s</mi> <mi>t</mi> </mrow> </msub> <mo>=</mo> <msubsup> <mo>&amp;Integral;</mo> <mrow> <msub> <mi>r</mi> <mn>0</mn> </msub> <mo>-</mo> <msub> <mi>T</mi> <mi>c</mi> </msub> </mrow> <msub> <mi>t</mi> <mn>0</mn> </msub> </msubsup> <mi>r</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mi>d</mi> <mi>t</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>
Wherein, t0For current time, TcFor certain historical time section, unit is h, and r (t) surveys for main influence weather station in moment t The rainfall intensity obtained, unit is mm/h;
Prediction rainfall of the geographic grid within assessment this period at moment in current time to future is calculated by formula (2), Unit is mm:
<mrow> <msub> <mi>R</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>k</mi> <mn>1</mn> </msub> <mfrac> <mrow> <mi>&amp;Delta;</mi> <mi>t</mi> </mrow> <msub> <mi>T</mi> <mi>c</mi> </msub> </mfrac> <msub> <mi>R</mi> <mrow> <mi>p</mi> <mi>a</mi> <mi>s</mi> <mi>t</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>k</mi> <mn>2</mn> </msub> <msub> <mi>r</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> </mrow> </msub> <mi>&amp;Delta;</mi> <mi>t</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>
Wherein, Δ t is current time t0To the following time span for assessing the moment, unit is h, rpreFor geographic grid location Weather forecast will assess the average rainfall intensity in this period at moment in current time to future, and unit is mm/h, k1For The weight coefficient of weather station measured value, k2For the weight coefficient of weather forecast value, wherein k1+k2=1;
If geographic grid is not in the range of the forecast of weather station, the rainfall letter of geographic grid is calculated in accordance with the following methods Breath:
It is by the history accumulation rainfall unit before formula (3) calculating geographic grid current time in certain historical time section mm;
Rpast=r'preTc (3)
Wherein, r'preFor average drop of the geographic grid location weather forecast before current time in certain historical time section Rainfall density, unit is mm/h;
Prediction rainfall of the geographic grid within assessment this period at moment in current time to future is calculated by formula (4), Unit is mm;
Rpre=rpreΔt (4)
2) longitude and latitude of the longitude and latitude and each weather station of contrast transmission tower, if longitude and latitude and some gas of transmission tower As the longitude and latitude at station is identical, then the prediction rainfall of transmission tower and history accumulation rainfall measures the prediction rainfall of the weather station And history accumulation rainfall, weather station prediction rainfall and history accumulation rainfall circular such as formula (1), (2), the r (t) wherein in formula (1) takes the rainfall intensity that weather station is measured in moment t, and unit is r in mm/h, formula (2)pre The weather forecast of weather station location is taken to assess the average rainfall intensity in this period at moment in current time to future, Unit is mm/h;
If the longitude and latitude of the longitude and latitude of transmission tower and all weather stations is differed, the prediction rainfall of transmission tower and History accumulation rainfall measures step 1) in the prediction rainfall of the affiliated geographic grid of transmission tower that calculates and history accumulation drop Rainfall;
3) the topography and geomorphology parameter in transmission tower column foot location is determined, in conjunction with step 2) in obtain transmission tower prediction drop Rainfall and history accumulation rainfall, calculate the synthesis effective precipitation for obtaining transmission tower;Finally combine transmission tower failure general Rate computation model, calculates and obtains transmission tower because heavy rain causes the probability of malfunction of calamity;
The synthesis effective precipitation R=R of the transmission towerz+Rs, wherein, Rz, can be according to formula (5) for early stage effective precipitation Calculate;RsFor amendment short duration raininess, calculated according to formula (6):
Rz=kp*Rpast (5)
Rs=kcor*Rpre (6)
Wherein kpFor history rainfall overall attenuation coefficient, kcorFor prediction rainfall quantity correction coefficient, according to transmission tower column foot The topography and geomorphology parameter of section takes different kpAnd kcor
4) according to step 3) in obtained transmission tower probability of malfunction, using relatively independent event algorithm, calculating obtains heavy rain calamity The probability of malfunction of each bar transmission line of electricity in the case of evil, terminates this method.
2. meter according to claim 1 and the transmission line malfunction probability online evaluation method of Rainfall Disaster influence, it is special Levy and be, the step 3) in the topography and geomorphology parameter in transmission tower column foot location chosen according to priority, priority level row Sequence is as follows:The topography and geomorphology parameter of transmission tower>Geographic grid topography and geomorphology parameter belonging to transmission tower>Power network location Typical topography and geomorphology parameter.
CN201710323118.1A 2017-05-09 2017-05-09 Power transmission line fault probability online evaluation method considering influence of rainstorm disaster Active CN107169645B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710323118.1A CN107169645B (en) 2017-05-09 2017-05-09 Power transmission line fault probability online evaluation method considering influence of rainstorm disaster

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710323118.1A CN107169645B (en) 2017-05-09 2017-05-09 Power transmission line fault probability online evaluation method considering influence of rainstorm disaster

Publications (2)

Publication Number Publication Date
CN107169645A true CN107169645A (en) 2017-09-15
CN107169645B CN107169645B (en) 2020-11-03

Family

ID=59813855

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710323118.1A Active CN107169645B (en) 2017-05-09 2017-05-09 Power transmission line fault probability online evaluation method considering influence of rainstorm disaster

Country Status (1)

Country Link
CN (1) CN107169645B (en)

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108132980A (en) * 2017-12-13 2018-06-08 国家电网公司 Electric power rescue and relief work paths planning method in mountain area under a kind of rainstorm weather
CN108960599A (en) * 2018-06-22 2018-12-07 国网湖南省电力有限公司 Transmission line of electricity Rainfall Disaster fining prediction technique and system based on inversion algorithm
CN110428190A (en) * 2019-08-16 2019-11-08 国电南瑞科技股份有限公司 A kind of transmission line malfunction probability online evaluation method counted and mountain fire disaster influences
CN111738617A (en) * 2020-07-01 2020-10-02 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
CN112257956A (en) * 2020-11-10 2021-01-22 国网湖南省电力有限公司 Method, device and equipment for predicting power transmission line suffering from rainstorm disaster
CN112749904A (en) * 2021-01-14 2021-05-04 国网湖南省电力有限公司 Power distribution network fault risk early warning method and system based on deep learning
CN113313342A (en) * 2021-04-08 2021-08-27 云南电网有限责任公司西双版纳供电局 Method and system for analyzing power grid equipment fault probability caused by multiple natural disasters
CN113610270A (en) * 2021-07-01 2021-11-05 广西电网有限责任公司电力科学研究院 Distribution transformer operation risk prediction method and system considering branch slot influence
CN113673617A (en) * 2021-08-26 2021-11-19 山东大学 Mars dust storm space-time probability prediction method and system based on remote sensing image
CN116579617A (en) * 2023-07-12 2023-08-11 国网山东省电力公司邹城市供电公司 Power grid risk assessment method and system

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102629294A (en) * 2011-12-31 2012-08-08 国网电力科学研究院 Probability evaluation method of failure caused by typhoon to power transmission line
CN103646157A (en) * 2013-08-28 2014-03-19 南京南瑞集团公司 Method for evaluating transmission line fault caused by rainstorm
CN103729692A (en) * 2013-12-24 2014-04-16 广西壮族自治区气象服务中心 Hydropower station drainage basin dividing and face rainfall monitoring method based on GIS
CN105203153A (en) * 2014-06-27 2015-12-30 国家电网公司 Electric power user major fault risk index prediction device and prediction method
CN105279612A (en) * 2015-10-30 2016-01-27 广西电网有限责任公司电力科学研究院 Poisson distribution-based power transmission line tripping risk assessment method
CN105868872A (en) * 2016-05-30 2016-08-17 东北大学 Power distribution network lightning disaster failure prediction method
CN106503881A (en) * 2016-09-23 2017-03-15 中国南方电网有限责任公司超高压输电公司检修试验中心 The appraisal procedure of DC power transmission line typhoon risk

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102629294A (en) * 2011-12-31 2012-08-08 国网电力科学研究院 Probability evaluation method of failure caused by typhoon to power transmission line
CN103646157A (en) * 2013-08-28 2014-03-19 南京南瑞集团公司 Method for evaluating transmission line fault caused by rainstorm
CN103729692A (en) * 2013-12-24 2014-04-16 广西壮族自治区气象服务中心 Hydropower station drainage basin dividing and face rainfall monitoring method based on GIS
CN105203153A (en) * 2014-06-27 2015-12-30 国家电网公司 Electric power user major fault risk index prediction device and prediction method
CN105279612A (en) * 2015-10-30 2016-01-27 广西电网有限责任公司电力科学研究院 Poisson distribution-based power transmission line tripping risk assessment method
CN105868872A (en) * 2016-05-30 2016-08-17 东北大学 Power distribution network lightning disaster failure prediction method
CN106503881A (en) * 2016-09-23 2017-03-15 中国南方电网有限责任公司超高压输电公司检修试验中心 The appraisal procedure of DC power transmission line typhoon risk

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
WU Y J, XUE Y S,WANG H H: "Extension of power system early-warning defense schemes by inregrating typhoon information", 《2ND INTERNATIONAL CONFERENCE ON SUSTAINABLE POWER GENERATION AND SUPPLY ON SUPERGEN》 *
冯伟明: "考虑冰灾的电网运行风险评估及网络化保护", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 *
吴勇军,薛禹胜,谢云云: "台风及暴雨对电网故障率的时空影响", 《电力***自动化》 *

Cited By (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108132980B (en) * 2017-12-13 2021-07-23 国家电网公司 Electric power emergency rescue and disaster relief path planning method for mountainous area in rainstorm weather
CN108132980A (en) * 2017-12-13 2018-06-08 国家电网公司 Electric power rescue and relief work paths planning method in mountain area under a kind of rainstorm weather
CN108960599A (en) * 2018-06-22 2018-12-07 国网湖南省电力有限公司 Transmission line of electricity Rainfall Disaster fining prediction technique and system based on inversion algorithm
CN108960599B (en) * 2018-06-22 2020-04-07 国网湖南省电力有限公司 Power transmission line rainstorm disaster refined prediction method and system based on inversion algorithm
CN110428190A (en) * 2019-08-16 2019-11-08 国电南瑞科技股份有限公司 A kind of transmission line malfunction probability online evaluation method counted and mountain fire disaster influences
CN111738617A (en) * 2020-07-01 2020-10-02 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
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
CN112257956A (en) * 2020-11-10 2021-01-22 国网湖南省电力有限公司 Method, device and equipment for predicting power transmission line suffering from rainstorm disaster
CN112749904B (en) * 2021-01-14 2023-06-27 国网湖南省电力有限公司 Power distribution network fault risk early warning method and system based on deep learning
CN112749904A (en) * 2021-01-14 2021-05-04 国网湖南省电力有限公司 Power distribution network fault risk early warning method and system based on deep learning
CN113313342A (en) * 2021-04-08 2021-08-27 云南电网有限责任公司西双版纳供电局 Method and system for analyzing power grid equipment fault probability caused by multiple natural disasters
CN113313342B (en) * 2021-04-08 2023-03-31 云南电网有限责任公司西双版纳供电局 Method and system for analyzing failure probability of power grid equipment caused by multiple natural disasters
CN113610270A (en) * 2021-07-01 2021-11-05 广西电网有限责任公司电力科学研究院 Distribution transformer operation risk prediction method and system considering branch slot influence
CN113610270B (en) * 2021-07-01 2024-03-26 广西电网有限责任公司电力科学研究院 Distribution transformer operation risk prediction method and system considering branch groove influence
CN113673617B (en) * 2021-08-26 2022-11-25 山东大学 Mars dust storm space-time probability prediction method and system based on remote sensing image
CN113673617A (en) * 2021-08-26 2021-11-19 山东大学 Mars dust storm space-time probability prediction method and system based on remote sensing image
CN116579617A (en) * 2023-07-12 2023-08-11 国网山东省电力公司邹城市供电公司 Power grid risk assessment method and system
CN116579617B (en) * 2023-07-12 2023-11-03 国网山东省电力公司邹城市供电公司 Power grid risk assessment method and system

Also Published As

Publication number Publication date
CN107169645B (en) 2020-11-03

Similar Documents

Publication Publication Date Title
CN107169645A (en) A kind of transmission line malfunction probability online evaluation method of meter and Rainfall Disaster influence
CN112070286B (en) Precipitation forecast and early warning system for complex terrain river basin
Liberti et al. Wave energy resource assessment in the Mediterranean, the Italian perspective
CN109697323B (en) Rainfall observation method integrating satellite remote sensing and mobile communication base station signals
CN111651885A (en) Intelligent sponge urban flood forecasting method
CN104951585B (en) A kind of typhoon method for early warning and device based on grid equipment
CN112506994B (en) Power equipment flood hidden danger point monitoring and early warning method and related device
CN103673960A (en) Method and device for predicating icing state of power transmission line
CN104851051A (en) Dynamic-modification-combined storm rainfall fine alarming method for power grid zone
CN109118035B (en) Grid early warning information-based typhoon and waterlogging disaster power distribution network risk assessment method
CN109063975A (en) A kind of electric power microclimate disaster monitoring and prior-warning device
CN105278004B (en) A kind of weather condition analysis method of grid power transmission circuit section
CN111612315A (en) Novel power grid disastrous gale early warning method
CN104182594A (en) Method for drawing power system wind area graph
CN106611245A (en) GIS-based typhoon disaster risk assessment method for power grid
CN105447770A (en) Assessment method for applying power grid monitoring data to refined weather forecast
Gentle Concurrent wind cooling in power transmission lines
CN107422180A (en) A kind of power prediction system of the photovoltaic plant based on cloud monitoring
Aniskevich et al. Modelling the spatial distribution of wind energy resources in Latvia
CN104050518B (en) Power grid convection disaster-causing strong wind early warning method based on Doppler weather radar
CN209417901U (en) Mountain flood dynamic early-warning system based on soil moisture content real time correction
CN117477558A (en) Prediction method and system based on power grid load
CN109471205B (en) Monitoring and early warning method based on gridding meteorological data in power grid operation
CN107944188A (en) Typhoon eye of wind radius discrimination method near the ground based on weather station measured data
CN106295896A (en) Middle minute yardstick electrical network windburn method for early warning in conjunction with remote sensing terrain information

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant