CN105095589A - Drawing method of power network wind zone distribution map in mountainous area - Google Patents

Drawing method of power network wind zone distribution map in mountainous area Download PDF

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CN105095589A
CN105095589A CN201510483726.XA CN201510483726A CN105095589A CN 105095589 A CN105095589 A CN 105095589A CN 201510483726 A CN201510483726 A CN 201510483726A CN 105095589 A CN105095589 A CN 105095589A
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wind
data
wind speed
district
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CN105095589B (en
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黄欢
彭赤
毛先胤
罗洪
杜昊
曹双和
任曦
犹珀玉
王邦民
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Guizhou electric power design institute
Electric Power Research Institute of Guizhou Power Grid Co Ltd
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Guizhou electric power design institute
Electric Power Research Institute of Guizhou Power Grid Co Ltd
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Abstract

The invention discloses a drawing method of a power network wind zone distribution map in a mountainous area. The method comprises the steps of data acquisition, data processing, data analysis, wind zone calculation model establishment, wind zone division, wind zone distribution map drawing and the like, the distribution map which can reflect recurrence periods of instantaneous maximum wind speed of the mountainous area can be obtained finally, the route design can be guided, the design which can be applied to adjusting measures to local conditions is conducted according to the instantaneous maximum wind speed wind zone level to drain wind deflection, the project manufacturing cost is reduced, the design which can be applied to selecting the safest and economical line route and prevent wind deflection accidents when building or transformation is conducted on a transmission line can be guided, and the problem that in the prior art, the wind zone distribution map drawing method can not meet the requirements of prevention and control work of wind deflection accidents in plateau mountain areas is solved; the technical problems that in the prior art, the wind zone distribution map lacks years of proofs of data collection, statistics of acquisition and modeling comparison and lacks theoretical support are solved.

Description

A kind of electrical network wind district, mountain area distribution drawing drawing method
Technical field
The invention belongs to power transmission line transportation work style and distinguish Butut field of drawing, particularly relate to electrical network wind district, a kind of mountain area distribution drawing drawing method.
Background technology
Power industry wind used is distinguished Butut and is mainly divided into two classes, a class be carry out for developing wind energy plant using wind energy size as the fetch graph defined, the wind speed index that this type of figure is mainly used in calculating is seasonal average wind; Equations of The Second Kind be Maximum instantaneous Wind speed size for preventing " windage yaw " accident as the wind speed profile figure defined, the wind speed index that this type of figure is mainly used in calculating is the wind speed maximum cycle reproduction value of statistics throughout the year.It is the basis instructing transmission line of electricity to carry out " windage yaw " disaster prevention that Maximum instantaneous Wind speed wind distinguishes Butut, also be the important parameter that design transmission line of electricity is optimized, correct Maximum instantaneous Wind speed wind distinguish Butut can guide line design time the design drainage windage yaw of suiting measures to local conditions, save construction costs, also can instruct the design carrying out selecting when building or transform safe, the most economic line alignment and prevention " windage yaw " accident at transmission line of electricity.The coastland paid close attention to of prior art affects in typhoon class strong convective weather due to Maximum instantaneous Wind speed basic source, than being easier to find rule, and in area, mountain area, plateau, affect by seasonal monsoon climate, add that topographic condition is changeable, Maximum instantaneous Wind speed rule is difficult to grasp.Along with south electric network local each province meteorological condition is changeable in recent years, the secondary disaster that strong convective weather causes takes place frequently, the incidence of " windage yaw " accident also increases year by year thereupon, and the wind district distribution drawing drawing method of prior art can not meet area, mountain area, plateau " windage yaw " Accident prevention requirements of one's work; On the other hand, original wind distinguishes Butut, is drawn by design experiences mode, lacks long-term Data Collection, gathers the demonstration of statistics, modeling comparison, lack theory support.
Summary of the invention
The technical problem to be solved in the present invention: provide electrical network wind district, a kind of mountain area distribution drawing drawing method, can not meet area, mountain area, plateau " windage yaw " Accident prevention requirements of one's work with the wind district distribution drawing drawing method solving prior art; And original wind distinguishes Butut, is drawn by design experiences mode, lack long-term Data Collection, gather the demonstration of statistics, modeling comparison, lack the technical matterss such as theory support.
Technical scheme of the present invention:
A kind of electrical network wind district, mountain area distribution drawing drawing method, it comprises:
Step 1, data acquisition: gather the Wind observation record data that in coverage of survey area, all weather stations are over the years, work transmission line design data of wind data over the years and field strong wind enquiry data, obtain surveying in district the temperature on average of each weather station in 10 years each department reoccurrence periods, 50 years, a 100 years wind pressure value of meeting and survey district, average gas pressure and vapour pressure data, then data classified, screen and extract;
Step 2, data processing: weather station Wind observation record data are carried out that wind speed height is corrected, wind speed number of times convert, time apart from converting and frequency computation part, obtain each weather station wind speed frequency value;
Step 3, data analysis: according to each weather station wind speed frequency result of calculation, utilize extreme value type I probability distribution computing method to obtain each weather station different reoccurrence wind speed;
Step 4, structure wind district computation model: wind speed and the elevation data of reappearing district according to weather station difference, utilize the parameter of curve estimation technique of SPSS statistical product and service solution software, the computation model obtaining different reoccurrence wind speed and height above sea level is:
in formula: V is wind speed, h is sea level elevation;
Step 5, wind Division: be decided to be 1m/s by differential for wind speed magnitude;
Step 6, wind distinguish Butut draw: adopt digital photogrammetry make digital complex demodulation, to this DEM process and repair splicing obtain complete survey district grid DEM, secondly for electric power line pole tower, transformer station, power plant and political divisions data carry out vectorized process, then according to the wind district computation model set up in step 4, the raster symbol-base device in Arcgis map algebra instrument is adopted to calculate, after calculating completes, with the spacing of 1 meter per second, statistics is carried out to result of calculation divide according to " the meteorological prospecting technique code of power engineering " (DL/T5158-2012), collocating kriging interpolation result is adopted to revise it afterwards, finally that the coordinate system of all data is unified, and arrange according to legend and carry out drafting and publish picture, finally complete the drafting that wind distinguishes Butut.
Data extraction method described in step 1 is: Wind observation record data are carried out arrangement according to date and the project of serveing as a lookout and are made as EXCEL file; Work transmission line design data of wind data over the years are extracted and are as the criterion according to work transmission line strong wind control time, engineering are rearranged according to the time, are marked by each engineering design strong wind different brackets.
Data processing described in step 2 also comprises carries out source book examination to weather station Wind observation record data, and examination content comprises the reliability of Wind observation record data, representativeness and consistance.
Wind speed number of times described in step 2 converts, time apart from convert and frequency calculation method for: by unified for the weather station air speed data 10min mean wind speed for specification required by, finally adopt the wind speed of extreme value type I probability distribution to each weather station website 30 years chances, 50 years chances, 100 years chances to carry out frequency computation part.
The determination of the computation model of different reoccurrence wind speed and height above sea level described in step 4 adopts the power function in the parameter of curve estimation technique of SPSS to realize.
Employing digital photogrammetry described in step 6 makes digital complex demodulation, its method for making is: adopt digital photogrammetry to make the transmission line of electricity Law of DEM Data of 1:5000 engineer's scale, the correction of image is adopted to generate digital terrain model data, set up the triangulation network, after inserting property value, form format is that the standardization DEM of .GIFf, DEM generation achievement mesh spacing controls within 5m, elevation value is 0.1m, and area, mountain region error range is at below 1.2m.
Described in step 6, vectorized process is carried out to electric power line pole tower, transformer station, power plant and political divisions data, its disposal route comprises: step 1, by the corner coordinate of electric power line pole tower in Excel list data, transformer station, power plant and political divisions data by WGS84 coordinate system, adopt X, the mode that Y adds, carries out vector quantization one by one; Step 2, carry out point set according to the shaft tower number field of shaft tower data and turn line, draw transmission line of electricity vector quantization layer; Step 3, transmission line of electricity, transformer station, power plant are adopted and classify by electric pressure, attribute, represent by a layer; Step 4, transmission line of electricity, administrative division separated time are classified according to electric pressure and administrative hierarchy, represent with line chart layer; Data after step 5, all process carry out projection change process according to WGS84 coordinate system, and final coordinate system is defined as WGS84, are stored into standard Geodatabase.
Employing collocating kriging interpolation described in step 6 is revised, and its method comprises: step 1, by the history disaster caused by a windstorm accident of falling tower, abnormal point numerical certificate, by coordinate WGS84 and recurrence period, be added to raster file one by one; Step 2, employing collocating kriging interpolation are revised, and during correction, respectively the coverage of the accident point of falling tower and abnormity point is set to 3-5 km; Step 3, the result of correction is converted into raster file, under equal coverage, the raster file drawn before substituting, divides wind district after completing again.
Beneficial effect of the present invention:
The present invention is to " windage yaw " accident data of the design and operation of transmission line of electricity in the mountainous terrain of plateau, the historical wind speed that each observatory (station) observes, the multipaths such as wind pressure data, the Wind Data data that multimode is collected arrange, analyze, calculate, accurately find out and survey district by different regions, the Maximum instantaneous Wind speed regularity of distribution that landform divides, build the wind section model of different reoccurrence, draw Maximum instantaneous Wind speed wind on this basis and distinguish Butut, and combine the result of actual " windage yaw " disaster accident investigation, carry out verifying to one-tenth figure and revise, finally obtain the result map that can reflect each reoccurrence period distribution of mountain area Maximum instantaneous Wind speed, can design by guide line, the design drainage windage yaw of suiting measures to local conditions is carried out according to Maximum instantaneous Wind speed wind district grade, save construction costs, also can instruct carry out selecting when building or transform at transmission line of electricity the safest, economic line alignment and the design of prevention " windage yaw " accident, the wind district distribution drawing drawing method solving prior art can not meet area, mountain area, plateau " windage yaw " Accident prevention requirements of one's work, and original wind distinguishes Butut, is drawn by design experiences mode, lack long-term Data Collection, gather the demonstration of statistics, modeling comparison, lack the technical matterss such as theory support.
Embodiment
Understand technical solution of the present invention for the ease of those skilled in the art, the embodiment of the present invention is further described technical solution of the present invention for Guizhou mountainous area.
A kind of electrical network wind district, mountain area distribution drawing drawing method, it comprises:
Step 1, data acquisition: gather the Wind observation record data that in coverage of survey area, all weather stations are over the years, work transmission line design data of wind data over the years and field strong wind enquiry data, according to table in " loading code for design of building structures " (GB50009-2012) E.5 " crushing by snow in national each city and wind pressure value table " and figure E.6.3 " national fundamental wind pressure distribution plan " obtain 10 years each department reoccurrence periods in survey district, 50 years, the wind pressure value of meeting for 100 years one and survey the temperature on average of each weather station in district, air pressure and vapour pressure data, then data are classified, screening and extraction.
Distinguish the accuracy of Butut to improve mountain area electrical network wind, during image data, the Wind observation record data over the years of periphery weather station, Ke Jiangce district include acquisition range in.
The present embodiment is described for Guizhou mountainous area: collect 1981 ~ 2014 years the whole provinces, 84 weather stations and the Wind observation record of periphery provinces and cities part weather station three more than ten years, collect data and mainly comprise each weather station evolution (geographic coordinate, elevation), annual mean wind speed, year maximum timing wind speed, year maximum timing wind speed and direction, maximum timing wind speed date in year, year at most wind direction, year maximum wind direction frequencies etc.; According to table in " loading code for design of building structures " (GB50009-2012) E.5 " crushing by snow in national each city and wind pressure value table " and figure E.6.3 " national fundamental wind pressure distribution plan " obtain wind velocity pressure and weather station, 84, the Guizhou Province data such as temperature on average, air pressure, vapour pressure of 1981 ~ 2014 years 34 years of 10 years Guizhou Province's domestic each department reoccurrence periods, 50 years, a 100 years chance; Work transmission line design data of wind over the years mainly comprises: the large wind data of line design of the whole province 220kV and Above Transmission Lines design strong wind grade and part 110kV; Field strong wind enquiry data, mainly comprise there is history strong wind disaster time, place, frequency and the data such as instantaneous wind speed that calculates according to strong wind disaster degree.After completing, data are carried out classifying, screen and extracting, remove gibberish and error.For different data sources, the mode of employing is divided into following three kinds:
(1) weather station data of serveing as a lookout are extracted: data of this sampling are txt text formatting file, need be changed into excel file for ease of late time data process and by date, all kinds of project of serveing as a lookout rearranges.
(2) work transmission line data over the years are extracted: be reference according to work transmission line strong wind control time, engineering are rearranged according to the time, are marked by each engineering design strong wind different brackets.
(3) strong wind enquiry data: formulated corresponding collection according to demand and made a report on form, in order to departure in data-gathering process, when carrying out field strong wind investigation, often organize personnel at least two people, record adopts the mode of double separately investigation records to carry out, and strong wind investigation in same position is at least twice.
Step 2, data processing: weather station Wind observation record data are carried out that wind speed height is corrected, wind speed number of times convert, time apart from converting and frequency computation part, obtain each weather station wind speed frequency value.
In order to improve accuracy and the accuracy of the data processed result of each weather station wind speed frequency value, before carrying out correction wind, should first examine weather station Wind observation record data source book.
Specific implementation is: different data sources has different processing modes.Weather station serve as a lookout that the process of data mainly comprises source book examination, wind speed height is corrected, secondary time convert, frequency computation part, first examine the reliability of data, representativeness, consistance; Highly correct on this basis, weather station anemoscope true altitude is converted to 10m design wind speed; Then carry out wind speed number of times and time apart from converting, by unified for the weather station Wind Data 10min mean wind speed required by specification; Extreme value type I probability distribution is finally adopted to carry out frequency computation part to an each website 30 years chance, 50 years chances, 100 years wind speed of meeting.
Wind pressure value inverse wind speed mainly goes out the wind speed of its correspondence by different reoccurrence wind velocity pressure and coefficient of wind pres inverse.
Other data processings mainly comprise the process that work transmission line over the years designs large wind data and the large wind data of field study, the referential data that these type of data distribute as wind district.
Step 3, data analysis: according to each weather station wind speed frequency result of calculation, utilize extreme value type I probability distribution computing method to obtain each weather station different reoccurrence wind speed;
Data analysis specific implementation and reason are: through weather station actual measurement Wind Data frequency budgetary estimate and the contrast of wind pressure value inverse wind speed achievement, wind pressure value result of calculation is wind pressure distribution graph exploitation result in large regions, its achievement theoretical property is stronger, poor relative to weather station field data accuracy, therefore use weather station field data frequency budgetary estimate achievement.Meanwhile, utilize extreme value type I and P-III type two kinds of probability distribution to calculate the wind speed of weather station different reoccurrence of studying and comparing respectively, contrast finds that extreme value type I probability distribution is better than the fitting effect of P-III type probability distribution to each website measured value.Because on the basis of 93 average maximum wind velocity sequences of the revised 10min over the years in weather station of studying and comparing, adopt extreme value type I to calculate and obtain 93 weather station different reoccurrence wind speed.
Step 4, structure wind district computation model: wind speed and the elevation data of reappearing district according to weather station difference, utilize the parameter of curve estimation technique of SPSS, obtain not containing the fitting result of the logarithmic curve of constant term, quafric curve, cube curve and power function, its result all has significant correlation, shown by the result of comparative analysis, the curve interpretation amount of power function is maximum, reach 99.5%, be the best curve equation that wind speed changes with sea level elevation, therefore show that the computation model of different reoccurrence wind speed and height above sea level is:
in formula: V is wind speed, h is sea level elevation;
Build the specific implementation of subregion computation model: be the relation between research height above sea level and wind speed, by reappearing wind speed and the elevation data in district to 93 website differences, utilize the parameter of curve estimation technique of SPSS, obtain not containing the fitting result of the logarithmic curve of constant term, quafric curve, cube curve and power function, by the comparative analysis of result, obtain the prediction model of different reoccurrence wind speed and height above sea level.
With sea level elevation h for independent variable, wind speed V is that dependent variable carries out SPSS curve estimation, by comparative analysis, selects not rebuild Wind speed model containing the logarithmic model of constant term, secondary model, cubic model and power function model; Then respectively matching is carried out to the data of 30 years one chances, 50 years chances and 100 years one chances, obtain the fitting result of different curve.
(1) 30 year one chance
Table 1 is 30 years one multiple curve-fitting results of meeting
Note: R2 is the non-linear explanation amount of matched curve; F value is F Distribution Value; Sig. value and P value is the inspection level of matched curve.
As can be seen from Table 1: if the level of signifiance gets 0.001, four fit curve equation all have conspicuousness, but R2 reduces from power function, logarithmic curve, a cube curve successively to quafric curve, illustrate that the non-linear interpretability of fit curve equation successively reduces; The F value of matched curve reduces from power function, logarithmic curve, a cube curve successively to quafric curve, and the level of significance of curve reduces gradually.Therefore, can find out by analyzing, the curve interpretation amount of power function is maximum, reaches 99.5%, is the best curve equation that wind speed changes with sea level elevation.
(2) 50 years one chances
Table 2 is 50 years one multiple curve-fitting results of meeting
As can be seen from Table 2: if the level of signifiance gets 0.001, four fit curve equation all have conspicuousness, but R2 reduces from power function, logarithmic curve, a cube curve successively to quafric curve, illustrate that the non-linear interpretability of fit curve equation successively reduces; The F value of matched curve reduces from power function, logarithmic curve, a cube curve successively to quafric curve, and the level of significance of curve reduces gradually.Therefore, can find out by analyzing, the curve interpretation amount of power function is maximum, reaches 99.4%, is the best curve equation that wind speed changes with sea level elevation.
(3) 100 years one chances
Table 3 is 100 years one multiple curve-fitting results of meeting
As can be seen from Table 3: if the level of signifiance gets 0.001, four fit curve equation all have conspicuousness, but R2 reduces from power function, logarithmic curve, a cube curve successively to quafric curve, illustrate that the non-linear interpretability of fit curve equation successively reduces; The F value of matched curve reduces from power function, logarithmic curve, a cube curve successively to quafric curve, and the level of significance of curve reduces gradually.Therefore, can find out by analyzing, the curve interpretation amount of power function is maximum, reaches 99.4%, is the best curve equation that wind speed changes with sea level elevation.
conclusion: (1) is the level of signifiance 0.001 time, the fitting degree of the curvilinear equation containing constant term can not show a candle to not containing the curvilinear equation of constant term, and not containing in the curvilinear equation of constant term, the fitting degree of logarithmic model, secondary model, cubic model and power function model is much larger than other several curve method.
(2) the level of signifiance 0.001 time, no matter be 30 years one chances, 50 years chances or the matched curve of meeting for 100 years, the curve interpretation amount of power function is maximum, reach 99.5%, 99.4% and 99.4% respectively, and F value is all maximum, the effect thus using power function fitting wind speed to change with sea level elevation is best.
(3) different reoccurrence, the prediction model of wind speed V and sea level elevation h is as follows:
Step 5, wind Division: according to " the meteorological prospecting technique code of power engineering " (DL/T5158-2012) specialized range, be decided to be 1m/s by differential for wind speed magnitude; Maximum wind velocity block plan color is set to blue series gradient color, with the size of color depth reflection wind speed;
Embodiment: the meteorological background in systematic study Guizhou Province, statistics the whole province 88 counties and cities' disaster caused by a windstorm generation frequencys, thus draw the distribution characteristics of the whole province's disaster caused by a windstorm, simultaneously by studying mima type microrelief to the impact of wind speed and points for investigation periphery weather station wind speed variation tendency, formulate wind Division foundation and division principle.
climatic Background Analysis: by analyzing the climatic environment, landform, landforms etc. in Guizhou Province, show that the immediate cause forming wind is pressure gradient-force, under lifting function influence, wind speed increases with the increase of elevation, and rule is obvious.And due to Guizhou province topographic variation trend obvious, wind speed also corresponding topography variation is linearly inclined to, and WESTERN GUIZHOU is Spring layer, successively decreases from west to east.
sum up Guizhou strong wind Disaster Characteristics: by disaster caused by a windstorm disaster statistics and the regularity of distribution, analyze mima type microrelief effect to the impact of wind speed, points for investigation periphery weather station wind speed variation tendency, sums up Guizhou strong wind Disaster Characteristics.
formulate wind Division foundation and principle: partitioning standards is the data that step 1 is collected; Division principle: according to " the meteorological prospecting technique code of power engineering " (DL/T5158-2012) regulation, when dividing wind district for overhead transmission line segmentation, general wind district is differential is 1m/s ~ 5m/s, considers and is decided to be 1m/s by differential for this project wind speed magnitude; Maximum wind velocity block plan color is set to blue series gradient color, with the size of color depth reflection wind speed, bright and clear to user, visual impression clearly.
Table 4 is wind district grading standard (unit: meter per second)
Step 6, wind is distinguished Butut and is drawn: adopt digital photogrammetry to make digital complex demodulation, to DEM process and repair splicing obtain complete survey district grid DEM, secondly for electric power line pole tower, transformer station, power plant and political divisions data carry out vectorized process, then according to the wind district computation model set up in step 4, the raster symbol-base device in Arcgis map algebra instrument is adopted to calculate, after calculating completes, with the spacing of 1 meter per second, statistics is carried out to result of calculation divide according to " the meteorological prospecting technique code of power engineering " (DL/T5158-2012), collocating kriging interpolation result is adopted to revise it afterwards, finally that the coordinate system of all data is unified, and arrange according to legend and carry out drafting and publish picture, finally complete the drafting that wind distinguishes Butut.
Described employing digital photogrammetry makes digital complex demodulation, its method for making is: adopt digital photogrammetry to make the transmission line of electricity Law of DEM Data of 1:5000 engineer's scale, the correction of image is adopted to generate digital terrain model data, set up the triangulation network, after inserting property value, form format is that the standardization DEM of .GIFf, DEM generation achievement mesh spacing controls within 5m, elevation value is 0.1m, and area, mountain region error range is at below 1.2m.
Specific implementation: digital complex demodulation makes: adopt digital photogrammetry to make the transmission line of electricity Law of DEM Data of 1:5000 engineer's scale, the correction of image is adopted to generate digital terrain model data, before carrying out the correction of image, check aerotriangulation achievement and measure feature dotted line, set up the triangulation network, after inserting property value, form format is that the standardization DEM of .GIFf, DEM generation achievement mesh spacing controls within 5m, elevation value is 0.1m, and area, mountain region error range controls at below 1.2m.
splicing: the dem data form collected mainly is divided into two types, and a class is the linear vector terrain file adopting Mapinfo to carry out the .tab form drawn, the DEM point cloud file of the AscII code encryption of the another kind of suitable general making for State Bureau of Surveying and Mapping's sale.Due to source DEM type, locus difference, need two class DEM to be processed into the laggard row relax of same type file, splicing, obtain complete Guizhou Province grid DEM.
vectorized process: carry out mainly for data such as electric power line pole tower, transformer station, power plant, political divisions.First, electric power line pole tower, transformer station, power plant's corner coordinate in Excel list data are pressed WGS84 coordinate system, the mode adopting X, Y to add, carries out vector quantization one by one.And carry out point set according to the shaft tower number field of shaft tower data and turn line, draw transmission line of electricity vector quantization layer, wherein, transmission line of electricity, transformer station, power plant adopt and classify by electric pressure, attribute etc., represent by a layer; Transmission line of electricity, administrative division separated time etc. are classified according to electric pressure, administrative hierarchy, represent with line chart layer; Water system adopts face file to represent.Before administrative map boundary vector, carry out having carried out geographic registration to the map of scanning.After all data processings are complete, carry out projection change process according to WGS84 coordinate system.And final coordinate system is defined as WGS84, be stored into the Geodatabase of standard.
spatial analysis: before carrying out raster data analysis, adopt mask in spatial analysis instrument to extract and carry out the unit collection region cutting research.Grid is 10m × 10m as initial point size, and both single picture initial point represented 100m 2interior dispersed elevation value.Then according to the wind district computation model that step 2 is set up, adopt the spatial analysis module in Arcgis software, utilize the raster symbol-base device in map algebra instrument to calculate.After calculating completes, statistics is carried out to result of calculation divide according to " the meteorological prospecting technique code of power engineering ", " the meteorological prospecting technique code of power engineering ", " 110 ~ 750kV aerial power transmission line design specifications ", carry out maximum wind velocity with the spacing of 1 meter per second and divide Division.
revise: the data such as the disaster caused by a windstorm accident of falling tower, abnormity point will be there are in the past, by coordinate (WGS84), recurrence period, be added to raster file one by one.Collocating kriging interpolation (Co-Kriging) result is adopted to revise it.Each point setting coverage, depending on analysis situation definition 3km ~ 5km.Finally revised result is converted into raster file, under equal coverage, the raster file that Substitute For Partial was drawn originally, divides wind district after completing again.
coordinate transformation and unification: the coordinate information that the basic data of this project is relevant is inconsistent, therefore, needs the coordinate information in uniform data, and based on WGS84 coordinate system, the mode of zonule continuous correction, carries out dynamic projection exploitation to the data of input.Accomplish under different coordinates, same showing interface and analysis.
compilation with publish picture: carry out layer and legend setting according to specification, employing 1:25 ten thousand ratio, coordinate system use WGS84 coordinate, longitude and latitude graticule mesh are spaced apart: through differing from 1 ° 30 ', the meridional difference 1 °, carry out drafting of publishing picture.

Claims (8)

1. a mountain area electrical network wind district distribution drawing drawing method, it comprises:
Step 1, data acquisition: gather the Wind observation record data that in coverage of survey area, all weather stations are over the years, work transmission line design data of wind data over the years and field strong wind enquiry data, obtain surveying in district the temperature on average of each weather station in 10 years each department reoccurrence periods, 50 years, a 100 years wind pressure value of meeting and survey district, average gas pressure and vapour pressure data, then data classified, screen and extract;
Step 2, data processing: weather station Wind observation record data are carried out that wind speed height is corrected, wind speed number of times convert, time apart from converting and frequency computation part, obtain each weather station wind speed frequency value;
Step 3, data analysis: according to each weather station wind speed frequency result of calculation, utilize extreme value type I probability distribution computing method to obtain each weather station different reoccurrence wind speed;
Step 4, structure wind district computation model: wind speed and the elevation data of reappearing district according to weather station difference, utilize the parameter of curve estimation technique of SPSS, the computation model obtaining different reoccurrence wind speed and height above sea level is:
in formula: V is wind speed, h is sea level elevation;
Step 5, wind Division: be decided to be 1m/s by differential for wind speed magnitude;
Step 6, wind distinguish Butut draw: adopt digital photogrammetry make digital complex demodulation, to this DEM process and repair splicing obtain complete survey district grid DEM, secondly for electric power line pole tower, transformer station, power plant and political divisions data carry out vectorized process, then according to the wind district computation model set up in step 4, the raster symbol-base device in Arcgis map algebra instrument is adopted to calculate, after calculating completes, with the spacing of 1 meter per second, statistics is carried out to result of calculation divide according to " the meteorological prospecting technique code of power engineering " (DL/T5158-2012), collocating kriging interpolation result is adopted to revise it afterwards, finally that the coordinate system of all data is unified, and arrange according to legend and carry out drafting and publish picture, finally complete the drafting that wind distinguishes Butut.
2. electrical network wind district, a kind of mountain area according to claim 1 distribution drawing drawing method, is characterized in that: the data extraction method described in step 1 is: Wind observation record data are carried out arrangement according to date and the project of serveing as a lookout and are made as EXCEL file; Work transmission line design data of wind data over the years are extracted and are as the criterion according to work transmission line strong wind control time, engineering are rearranged according to the time, are marked by each engineering design strong wind different brackets.
3. electrical network wind district, a kind of mountain area according to claim 1 distribution drawing drawing method, it is characterized in that: the data processing described in step 2 also comprises carries out source book examination to weather station Wind observation record data, examination content comprises the reliability of Wind observation record data, representativeness and consistance.
4. electrical network wind district, a kind of mountain area according to claim 1 distribution drawing drawing method, it is characterized in that: wind speed number of times described in step 2 converts, time apart from convert and frequency calculation method for: by unified for the weather station air speed data 10min mean wind speed for specification required by, finally adopt the wind speed of extreme value type I probability distribution to each weather station website 30 years chances, 50 years chances, 100 years chances to carry out frequency computation part.
5. electrical network wind district, a kind of mountain area according to claim 1 distribution drawing drawing method, is characterized in that: described in step 4, the computation model of different reoccurrence wind speed and height above sea level adopts the power function in the parameter of curve estimation technique of SPSS to realize.
6. electrical network wind district, a kind of mountain area according to claim 1 distribution drawing drawing method, it is characterized in that: the employing digital photogrammetry described in step 6 makes digital complex demodulation, its method for making is: adopt digital photogrammetry to make the transmission line of electricity Law of DEM Data of 1:5000 engineer's scale, the correction of image is adopted to generate digital terrain model data, set up the triangulation network, after inserting property value, form format is the standardization DEM of .GIFf, DEM generates achievement mesh spacing and controls within 5m, elevation value is 0.1m, and area, mountain region error range is at below 1.2m.
7. electrical network wind district, a kind of mountain area according to claim 1 distribution drawing drawing method, it is characterized in that: described in step 6, vectorized process is carried out to electric power line pole tower, transformer station, power plant and political divisions data, its disposal route comprises: step 1, by the corner coordinate of electric power line pole tower in Excel list data, transformer station, power plant and political divisions data by WGS84 coordinate system, adopt X, the mode that Y adds, carries out vector quantization one by one; Step 2, carry out point set according to the shaft tower number field of shaft tower data and turn line, draw transmission line of electricity vector quantization layer; Step 3, transmission line of electricity, transformer station, power plant are adopted and classify by electric pressure, attribute, represent by a layer; Step 4, transmission line of electricity, administrative division separated time are classified according to electric pressure and administrative hierarchy, represent with line chart layer; Data after step 5, all process carry out projection change process according to WGS84 coordinate system, and final coordinate system is defined as WGS84, are stored into standard Geodatabase.
8. electrical network wind district, a kind of mountain area according to claim 1 distribution drawing drawing method, it is characterized in that: the employing collocating kriging interpolation described in step 6 is revised, its method comprises: step 1, by the history disaster caused by a windstorm accident of falling tower, abnormal point numerical certificate, by coordinate WGS84 and recurrence period, be added to raster file one by one; Step 2, employing collocating kriging interpolation are revised, and during correction, respectively the coverage of the accident point of falling tower and abnormity point is set to 3-5 km; Step 3, the result of correction is converted into raster file, under equal coverage, the raster file drawn before substituting, divides wind district after completing again.
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