CN106780586A - A kind of solar energy potential evaluation method based on ground laser point cloud - Google Patents
A kind of solar energy potential evaluation method based on ground laser point cloud Download PDFInfo
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Abstract
The invention discloses a kind of solar energy potential evaluation method based on ground laser point cloud, it is comprised the following steps：S1, original point cloud is vacuated；S2, to vacuating after point cloud P carry out the extraction of area-of-interest ground point set R,S3, setting light source deviation pilot angle；S4, position and number that basic point is quickly calculated using solstics Greedy strategy；S5, calculating basic point position of sun；S6, using broad sense hidden place remove algorithm be GHPR algorithms, carry out the sheltering analysis of three-dimensional point cloud scene, so as to carry out sunshine simulation calculate；S7, binaryzation shade drafting is carried out to sheltering analysis result；S8, solar radiation calculating is carried out to a cloud scene.Appraisal procedure of the invention can provide fast and efficiently solar energy resources automation assessment, can provide the user the three-dimensional solar resource map of survey area random time section.
Description
Technical field
The present invention relates to field of Computer Graphics, and in particular to one kind carries out solar energy resources assessment using laser point cloud
Method.
Background technology
Traditional solar energy Potential Evaluation is mainly in installation using the method for artificial subjective estimation, but
Solar radiation distribution depend on simultaneously time, weather and in investigation environment object spatial relation, it is simple investigate and
Reckoning is difficult to reply investigation environment complicated and changeable, such as city, forest land, the intensive traffic section.For the method that traditional-handwork is measured, its
Analysis efficiency is relatively low, and data acquisition and subsequent treatment link depart from, it is difficult to meet demand, therefore, when possessing in the urgent need to one kind
Space-variant changes the Accurate Analysis method of inverting ability.
In recent years, LiDAR (Light Detection and Ranging) technology is developed rapidly, and it is because of the scene of height
Reproduction and be suitable for sunshine sheltering analysis.Laser scanner can be quick, efficiently, accurately acquires three in survey area
Dimension information, the data for obtaining are three-dimensional laser point cloud data.At present, the work of solar energy Potential Evaluation is carried out using cloud data
Airborne cloud is concentrated on, and is in conceptual phase mostly.Its handling process is mainly by the digital table of original point cloud data generation
Surface model (DSM), then directly carries out shade calculating on DSM grids, and this method is mainly used in the sun of City-level yardstick
Can Potential Evaluation.And under microcosmic investigation yardstick (such as single building roof), it is still necessary to polygon is carried out to data and is built
Mould ensures to analyze quality that the reducing degree of building target depends on reserving degree of the CONSTRUCTED SPECIFICATION in modeling process.It is many
Side shape model needs the geometrical model and parameter of substantial amounts of manual operations or priori, and the complexity of urban environment is the method band
Carry out very big workload and challenge, miscellaneous Municipal Component (trees, power line, bridge and enclosure wall etc.) is required for being placed into
In model library.As can be seen that for cloud data, its application scenarios in solar energy Potential Evaluation is also more single
One, focus primarily upon city.Solar energy resources enquiry based work for suburb and forest zone is also less, the complexity of vegetation modeling
Property also govern the development of this aspect research simultaneously.
For airborne cloud modeling class method.First, it is difficult to obtain building due to airborne cloud is scanning visual angle
Side and concave structure, cause a cloud to form hierarchical structure, there are a large amount of spaces between each layer, are unfavorable for carrying out accurate sunshine
Analysis.Airborne cloud resolution ratio is general at 1 meter or so, and data acquisition and planning needs take a significant amount of time.Secondly, it is existing
Modeling method be based primarily upon surface model and carry out shade calculating, easily by the error propagation during surface modeling to blocking point
Among analysis.And the specific modeling to building target then more depends on interactive operation, the geometric parameters of priori are not only needed
The selectivity that the sample pattern storehouse of number or abundance, and to vegetation, means of transportation, massif rock etc. are difficult to model target is ignored equally
Error is produced when being easily caused inverting.
Method for region be directly facing a cloud, its sheltering analysis process is excessively simple extensive.The method that region be directly facing a cloud
All Main Basiss height values ignore object structure and shape in itself as basis for estimation.For example for vegetation, tree crown exists
High-altitude has outside ductility, and the shaded area that such method can be caused to produce is excessive, it is difficult to adapt to complicated scene.
The content of the invention
It is an object of the invention to overcome above-mentioned the deficiencies in the prior art, there is provided a kind of sun based on ground laser point cloud
Can potential evaluation method.
The present invention specifically uses following technical scheme：
A kind of solar energy potential evaluation method based on ground laser point cloud, comprises the following steps：
S1, original point cloud is vacuated；
S2, to vacuating after point cloud P carry out the extraction of the ground point set R in area-of-interest,
S3, setting light source deviation pilot angle；
S4, using solstics Greedy strategy (farthest-first traversal) come the quick position for calculating basic point and
Number；
S5, calculating basic point position of sun；
S6, using broad sense hidden place remove algorithm be GHPR (Generalized Hidden Point Removal) algorithm
The sheltering analysis of three-dimensional point cloud scene are carried out, is calculated so as to carry out sunshine simulation；
S7, binaryzation shade drafting is carried out to sheltering analysis result；
S8, solar radiation calculating is carried out to a cloud scene.
Further, S1 is comprised the following steps that：
The three-dimensional ground laser point cloud P of inputraw, set one first and vacuate apart from Ls, method is then vacuated using voxel.
Voxel vacuates method and a cloud first is divided into the length of side for LsRegular cube voxel, then by point set in voxel central point as new
Data point, these new point sets form the point cloud P after vacuating.
Further, S2 is comprised the following steps that：
S21, first, ground point is extracted using the method based on the growth filtering of voxel elevation, based on whole point cloud most
Low height value sets a threshold level tz, the threshold level is usually 3 meters of height on area-of-interest height value.If one
The center elevation of individual voxel is higher than threshold value t with the relative altitude of minimum pointz, then it is assumed that it is unlikely to be ground point, if additionally,
One voxel less than threshold value can grow into threshold level tz, then it is assumed that be a part for wall or vertical object, also for
Non-ground points, so as to extract all ground point sets；
S22, then, Euclidean distance cluster is carried out to ground point collection, to the clustering cluster marking serial numbers for obtaining；
It is S23, last, the average density value of each class cluster is calculated, selection density highest one is used as area-of-interest
(respondent), returns to the point cloud after vacuating, and the data point r of area-of-interest is marked according to each point index valuei, ri∈R。
Further, S3 is comprised the following steps that：
The maximum allowable offset angle θ of simulation light deviation directional light is set, while the sun is set apart from d, such that it is able to true
Ultimate range l between fixed two basic points, has：
L=d/tan (pi/2-θ)
Further, S4 is comprised the following steps that:
S41, first, solstics strategy one area-of-interest point of random selection is used as initial basic point o1, build basic point sequence
Row O={ o1}；
S42, then, calculates point farthest with the sequence on area-of-interest point set, i.e.,And will
It is added in O, is O={ o1,o2, until any point ri, ri∈ R, meet
O={ o after S43, acquisition basic point sequencek| k ∈ [1, n] }, for each point r that area-of-interest point is concentratedi, ask for
Its nearest neighbor point on basic point collection, belongs to an area-of-interest point for basic point and constitutes a deviation control area Gk。
Further, S5 is comprised the following steps that：
S51, for each basic point ok, its corresponding position of sun s is calculated by a set of position of sun solving modelk,
Each basic point is additionally switched into a latitude and longitude coordinates from WGS84 coordinates, there is [oΨ,oΦ,oh]=T ([ox,oy,oz]), wherein, T
It is coordinate transform, [oΨ,oΦ] it is the latitude and longitude value of basic point, ohIt is height above sea level angle value, then, base is obtained according to position of sun model
Position of sun s, the s=[o of point oΨ+fd(y),oΦ-fd(x),oh+z]T, fdIt is the function that length is turned to the number of degrees, is sat in longitude and latitude
Can be calculated as below under mark:
X=dsin (90 ° of-α) cos (ψ)
Y=dsin (90 ° of-α) sin (ψ)
Z=dcos (90 ° of-α)
S52, longitude and latitude and height coordinate are gone back to WGS84 coordinates, obtain phase of the sun in a cloud scene three dimensions
To position, s=T ' (s), T ' are the inverse transformation of T.
Further, S6 is comprised the following steps that：
S61, first, travels through sun point set S, for each position of sun si, and investigate the three-dimensional point after scene is vacuated
Collection P, P={ pi| i ∈ [1, m] }, wherein m is a cardinality, performs radial direction geometric transformation F, is had:
Wherein, if pi=s, thenPoint set after conversion isAnd fkIt is conversion
Kernel function.
S62 and then to point setA convex hull computation is done, and retains the point in convex closure for shade point set W.
Further, S7 is comprised the following steps that：
S71, for each position of sun sk, calculate a Wk；
S72 and then, take WkWith responsible region GkCommon factor be the shadow spots in each respective regions.After having traveled through, by each
Shadow result in region takes union, so as to obtain the illumination result of whole area-of-interest；
S73, finally by illumination result binaryzation, if fi(ri) it is that binaryzation function is used to represent point riBlock situation,
0 is labeled as to the shadow spots in area-of-interest, f is designated asi(ri)=0, rather than shadow spots are labeled as 1, are designated as fi(ri)=1.
Further, S8 is comprised the following steps that：
S81, the interpretation of result that sheltering analysis and shade drafting are carried out using Hottel models, when being input into the sun first, meter
Calculate this day extraatmospheric solar irradiance Io, then it is input into calculation of longitude ＆ latitude this area direct solar radiation transmitance τb, then calculate tiltedly
Face modifying factor ε, for modifying factor, first asks for the angle between sun beam incident optical and inclined-plane normal vector, afterwards using structure
Each area-of-interest point r is obtained with covariance matrix is decomposediNormal vectorThen, the connection sun and current traversal point structure
Directive amount is built into for s-ri, correction factor ε can be by rotation calculating more than the angle between incident vector and normal vector:
Wherein it is vector dot, and s is the position of sun corresponding to point correlation basic point；
Every bit r in S82, and then calculating area-of-interestiThe instantaneous direct radiation I of the sunb(KWh/m2) be：
Wherein, fi(ri) it is that the instantaneous of the point blocks situation, α is sun altitude at that time, then, calculates scattering radiation
Transmitance τd, so as to calculate solar scattered radiation Id(KWh/m2).It is calculated as follows：
Id=Io cosατd
It is S83, last, calculate the instantaneous Globalradiation I of the pointg(KWh/m2), there is Ig=Ib+Id, for random time section
Single-point riSolar energy global radiation can be obtained by horal total radiation is cumulative, i.e.,：
Wherein, tbeginAnd tendStarting and deadline for solar energy simulation, and result of calculation visualization is shown in use
Family interface.
After adopting the above technical scheme, the present invention is compared with background technology, have the following advantages that：
1st, present invention employs GHPR algorithms, the three-dimensional information of a cloud is taken full advantage of, for prolonging for building or plant
Malleability structure has good adaptability, therefore is suitable for the complicated investigation scene of environment；Compared with using the method for modeling,
The present invention is directly based upon a cloud computing, it is to avoid the data distortion in man-machine interactively operation and model modeling, has effectively facilitated money
The automation of source estimation flow, standardization；Compared with Traditional measurements method, the present invention can be provided the user intuitively, quantitative, entirely
The solar energy resources distribution results of office, the method is easy to preserve and repeatable simulation；
2nd, the present invention is calculated and computer capacity is limited in area-of-interest using global shade, so as to accelerate calculating
Speed, is conducive to implementing live solar energy resources and assesses, it is to avoid secondary object in modeling process (such as window, railing etc.) is lost and drawn
The error for rising, can provide the analysis result for settling at one go for the solar energy resources fieldworker of different industries；
3rd, the present invention proposes the light source Deviation Control Method in a kind of cloud scene, for constraining and controlling different light sources
Between the shade deviation that produces, and using the approximate solution of solstics Greedy strategy quick obtaining sun number of views and position, not only
Deviation is reduced, and improves efficiency.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of the embodiment of the present invention；
Fig. 2 (a) is embodiment of the present invention original point cloud data；B () is the extraction result of area-of-interest point set；C () is
Embodiment deviation control result；
Fig. 3 is embodiment of the present invention position of sun result of calculation；
Fig. 4 blocks analog result for embodiment sunshine：A () is the result of this method simulation；(b) be analog result with it is corresponding
Truth contrast (standard results) of time；
Fig. 5 is embodiment global radiation analog result：A () is single cropping degree analog result (embodiment is autumn)；B () is whole year
Analog result.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that specific embodiment described herein is only used to explain the present invention, not
For limiting the present invention.
Embodiment
Visible Fig. 1 of schematic flow sheet of the present embodiment, specific operation process is as follows：
1. survey area point set is extracted
Known three-dimensional ground laser point cloud PrawOriginal point cloud data such as Fig. 2 (a) shown in, down-sampling first is carried out to a cloud
(vacuating), that is, reduce the quantity of data point in point cloud.Under normal circumstances, the data precision of ground laser point cloud is for illumination calculation
Excessively redundancy.Accordingly, it would be desirable to first set one vacuate apart from LsSo that the point cloud spacing after vacuating may remain in LsLeft and right and
Point cloud structure keeps constant.This method vacuates method using the voxel with partial structurtes retentivity, and the method will put cloud first
The length of side is divided into for LsRegular cube voxel, then by point set in voxel central point as new data point, these new points
Collection forms the point cloud P after vacuating.
Then, to vacuating after point cloud P carry out the extraction of area-of-interest R,Region of interesting extraction purpose is
The data point set in survey area is obtained, what this method was mainly extracted is the ground point in region, for solar energy resources to be divided
Cloth result is drawn on ground point, so as to form solar energy resources distribution map.Accordingly, it would be desirable to filter elimination point cloud using ground point
In non-ground target.For different scenes, such as building balcony or road, their ground point morphologically still has
There is general character, i.e. ground point region inside gradient change is relatively gentle, and in vertical direction without violent step, therefore this method
Ground point is extracted using the method based on the growth filtering of voxel elevation.
First, point cloud press horizontal plane to be fixed length of side thick division is a series of square net regions, and records whole point cloud
Elevation minimum point.Three-dimensional subdivision is carried out once to the point set of each horizontal grid again, point set that will be in grid presses fixed edge
Length is divided into cube element, records the center height value of each voxel.Lowest elevation value z based on whole point cloudminSet one
Threshold level tz, depending on this is highly according to the height above sea level of area-of-interest, it is also possible to according to the substantially high of different respondents
Spend to set elevation threshold value tz.Usual laser scanner is set up on survey area, so this highly can be by scanner
Height value in the scene adds 3 meters of acquisitions.If a center elevation for voxel is higher than the threshold value with the relative altitude of minimum point
tz, then it is assumed that its is too high, it is impossible to be ground point.If a voxel less than threshold value can grow into threshold level tz, then recognize
Also it is non-ground points to be a part for wall or vertical object.Growing strategy is that nine neighboring voxels are deposited above its voxel
Whether there is non-NULL voxel in upper nine neighboring voxels of non-NULL, and iterative query non-NULL voxel, until the non-NULL voxel that certain is inquired about is high
In threshold level tz.Finally, retain the data point in the voxel of ground, form ground point set.
Then, ground point collection is clustered, will discrete point set be clustered into a series of objects.This method using it is European away from
From cluster, to the clustering cluster marking serial numbers for obtaining.Then, the average density value of each class cluster is calculated.Its theoretical foundation be by
What the operating type of terrestrial Laser scanner was determined, i.e., the sector scanning density close to laser scanner is very big, generally can be with
Reach more than 10 times of distant object density.Average density value is each point certain neighborhood (0.2 in original point cloud of such cluster
Rice) the interior average for putting quantity.Finally, class cluster is sorted by density value, selection density highest one (is adjusted as area-of-interest
Check as).The point cloud after vacuating is returned, the data point r of area-of-interest is marked according to each point index valuei, ri∈R.Wherein, feel
Interest region ground point collection is extracted shown in result such as Fig. 2 (b).
2. basic point is calculated and deviation control
The method that the present invention uses spot light simulated solar irradiation, it is therefore desirable to enter the control of line light source deviation, that is, control parallel
Shade deviation between light and spot light.Additionally, carry out position of sun calculate before, it is necessary to give basic point, i.e., based on certain point
Calculate the position of the sun.For the area-of-interest point set R after preservation, it is proposed that Deviation Control Method thought be selection sense
Used as basic point o, each basic point calculates a position of sun to some points in interest region, the sun position calculated by each basic point
Put as the sun reference position of neighborhood point set in basic point certain limit also, so that deviation when reducing shade drafting.Therefore,
If basic point point set is O, ok∈ O, position of sun point set is S, wherein S={ sk| k ∈ [1, n] }, each skCorresponding subvolume of interest
Region point set is Gk, meet ∪k∈[1,n]Gk=R and ∩k∈[1,n]Gk=φ.
The angle of deviation size θ of constraint is set first, that is, simulates the maximum allowable angle of light deviation directional light, such that it is able to
Determine the ultimate range l between two basic points, also will thus be to be divided according to the area-of-interest to extracting.Additionally, also
It is the position of sun s in a cloud scene to need to set sun distance of the sun in d, this methodkFrom area-of-interest phase
Answer basic point okDistance, have | | ok-sk| |=d.Both of the above relation is as follows：
L=d/tan (pi/2-θ)
In usual scene, remote object is to the influence very little blocked, therefore θ generally sets 2 °, and d sets 600 meters.Under
One step, carries out the calculating of the number and position of basic point o.This method proposes quickly to calculate basic point using solstics Greedy strategy
Position and number, the target of the subprogram is within the limited time, as much as possible with minimum basic point number nminSo that whole base
The sphere of action of point set covers point set interested, i.e.,Ensure each point r in area-of-interestiIn the presence of
One basic point okIt is set to meet condition | | ri-ok||≤l.For each zoning Gk, there is Gk={ ri∈R|||ok-ri||≤
||ot-ri| |, k ≠ t and t ∈ [1, n], i ∈ [1, nR]}。nRIt is the gesture of point set R.
Solstics strategy one area-of-interest point of random selection is used as initial basic point o1, then build basic point sequence O=
{o1}.Then point farthest with the sequence on area-of-interest point set is calculated, i.e.,And it is added to O
In, it is O={ o1,o2}.Until any point ri, ri∈ R, meetObtain O={ o after basic point sequencek|k
∈ [1, n] }, for each point r that area-of-interest point is concentratedi, its nearest neighbor point on basic point collection is asked for, belong to one
The area-of-interest point of basic point constitutes a deviation control area Gk.Fig. 2 (c) is the deviation control result of the present embodiment, wherein
Parameter is set to d=400, θ=2 °, and pore represents basic point, and three responsible regions that basic point is divided are corresponded to respectively.
3. position of the sun in a cloud scene calculates
For each basic point ok, we calculate its corresponding position of sun s by a set of position of sun solving modelk。
When the input of the model is the longitude and latitude and the local sun of the basic point.Therefore, first step is the latitude and longitude coordinates of acquisition basic point,
Each basic point is additionally switched to a latitude and longitude coordinates by this method from WGS84 coordinates first, there is [oΨ,oΦ,oh]=T ([ox,oy,
oz]).Wherein, T is coordinate transform, [oΨ,oΦ] it is the latitude and longitude value of basic point, ohIt is height above sea level angle value.Then, when the sun is set
Between, declination angle is calculated according to the date：
δ=23.45 ° sin (360 (nd-80)/365)
Wherein, ndNumber of days in the whole year where Query Dates.Calculated too further according to the specific time (Hour Minute Second) for setting
Positive hour angle：
ω=15 ° (12-T)
Wherein T is the specific time of inquiry, it is necessary to note being the local sun time.So as to obtain solar azimuth ψ and height
Degree angle α, has：
Sin α=sin δ sinoΦ+cosδcosoΦcosω
Then, based on solar azimuth ψ, apart from d, then basic point o is too for sun altitude α and the sun that was set before us
Positive position s, s=[oΨ+fd(y),oΦ-fd(x),oh+z]T, fdIt is the function that length is turned to the number of degrees, can under latitude and longitude coordinates
To be calculated as below:
X=d sin (90 ° of-α) cos (ψ)
Y=d sin (90 ° of-α) sin (ψ)
Z=d cos (90 ° of-α)
Finally, longitude and latitude and height coordinate are converted WGS84 coordinates by us, and the acquisition sun is in a cloud scene three dimensions
Relative position, s=T ' (s), T ' for T inverse transformation.For each basic point ok, we calculate a sk, constitute sun point
Collection, S={ sk| k ∈ [1, n] }, spatially form sun dot matrix.Fig. 3 is the present embodiment position of sun result of calculation, is represented
The present embodiment simulate winter solstice in 2017 (December 22) point cloud scene overhead apparent motion of the sun track (bead color from it is bright to
It is secretly the position of sun from 6 points to 18 points).
4. sheltering analysis and shade drafting
We draw sunshine shade using GHPR algorithms, are calculated so as to carry out sunshine simulation.First, sun point set S is traveled through,
For each position of sun si, and investigate three-dimensional point set P, the P={ p after scene is vacuatedi| i ∈ [1, m] }, wherein m is point set
Gesture, perform radial direction geometric transformation F, have:
Wherein, if pi=s, thenPoint set after conversion isAnd fkIt is conversion
Kernel function:
fk(||pi- s | |)=2 λ maxpi∈P||pi-s||-||pi-s||
Wherein λ is path length amplifying parameters, there is λ >=1.Then to point setA convex hull computation is done, and retains convex closure
Interior point is shade point set W.
During traversal, for each position of sun sk, we calculate a Wk.Then, we take WkWith responsible area
Domain GkCommon factor be the shadow spots in each respective regions.After having traveled through, the shadow result in each region is taken union by us,
So as to obtain the illumination result of whole area-of-interest.
Final step be by illumination result binaryzation, will shadow spots be labeled as 0, be designated as fi(ri)=0, rather than shadow spots
Labeled as 1, f is designated asi(ri)=1, because the shade of mark exists only in area-of-interest, region of interest is overseas can not to be calculated,
Same zero setting, so as to reduce the intersection operation time.The present embodiment sunshine blocks analog result as shown in figure 4, wherein Fig. 4 (a) is
The result of this method simulation, Fig. 4 (b) is that analog result contrasts (standard results) with the truth of corresponding time.
5. solar radiation model is calculated
Because territorial laser scanning point cloud sheet is in Primary Stage Data acquisition phase, can be obtained by location equipments such as GPS
Geodetic coordinates WGS84, therefore can directly perform solar radiation estimation.Solar radiation assessment needs to set up in solar energy spoke
Penetrate on the basis of model and sheltering analysis result.It is main herein to use Hottel models for solar radiation model.Input is too
When positive, the extraatmospheric solar irradiance in any one day can be obtained by below equation：
Io=Is[1+0.033cos(360°n/365)]
Wherein, IsIt is solar constant, i.e., the solar irradiance that exoatmosphere is received with radiation direction when vertical has Is=
1353W/m2.Then area-of-interest point concentrates certain point r in point cloud sceneiThe instantaneous direct radiation I of the sunb(KWh/m2) be：
Wherein, τbIt is direct solar radiation transmitance, ε is inclined-plane modifying factor, fi(ri) it is that the instantaneous of the point blocks situation.This
Outward, also there is solar scattered radiation Id(KWh/m2).Its relational expression is as follows：
Id=Io cosατd
Wherein τdIt is scattering Radiation Transmittance.Direct solar radiation is calculated as follows with scattering Radiation Transmittance：
τb=a0+a1e-k/cosα
τd=0.2710-0.293 τb
Wherein, for τbParameter can be by being calculated as below：
a0=(0.4327-0.00821 (oh-6)2)r0
a1=(0.5055+0.00595 (oh-6.5)2)r1
K=(0.2711+0.01858 (oh-2.5)2)rk
Wherein, [r0,r1,rk] it is the weather amendment in location, three parameters can be inquired about by setting up longitude and latitude weather
Table is automatically obtained.For example, by taking the subtropical zone of Xiamen as an example, its three parameters are respectively r0=0.95, r1=0.98, rk=
1.02。
Then, the instantaneous ramp modifying factor of direct solar radiation is calculated, the step is firstly the need of the incident inclined-plane of consideration
Slope, considers that Tilt factor can just make result closer to real situation in solar energy resources assessment.Therefore, we ask for too
Angle between positive beam incident optical and inclined-plane normal vector, so as to carry out Tilt factor amendment.First, it is to obtain normal vector, this
Step can just be carried out after area-of-interest is extracted.We travel through the point of each area-of-interest, often traverse one it is interested
Region point ri, its neighborhood just is searched for kd-tree, so as to build neighborhood point set R', R'={ ri'|i∈[1,Kr]}.This point
On the basis of collection, the center of gravity of neighborhood point set is first calculatedCovariance matrix M is built again.
Then matrix decomposition is carried out to covariance matrix, the characteristic vector and eigenvalue matrix of covariance matrix is obtained.Carry
The corresponding unit vector of smallest real eigenvalue is taken for normal vectorThe normal vectorIt is exactly the normal vector of local surface.
Then, the connection sun and current traversal point are built into directive amount for s-ri.Correction factor ε can be by incident vector
Revolved more than angle between normal vector and calculated, relational expression is calculated as follows:
Wherein it is vector dot, and s is the position of sun corresponding to point correlation basic point.
Then, the instantaneous Globalradiation I of the point is calculatedg(KWh/m2), there is Ig=Ib+Id, then for the list of random time section
The global radiation of point solar energy can be obtained by horal total radiation is cumulative, i.e.,：
Wherein, tbeginAnd tendStarting and deadline for solar energy simulation, can be on demand a few hours, and a couple of days is very
To the several years.
Finally, by result of calculation visualization be shown in user interface, rendered by different color show each point between
Radiation value difference, so as to provide the user the solar energy Potential Evaluation result of visualization, quantification, the overall situationization.Fig. 5 is this reality
A global radiation analog result is applied, wherein Fig. 5 (a) is single cropping degree analog result (autumn), and Fig. 5 (b) is annual analog result, data
Point color from it is shallow to deeply feel show solar energy resources distribution results in radiation value from minimum value to greatest measure, big figure is vertical view
Angle of field, the small figure in the black surround of the upper right corner is side-looking angle of field, and the colour gamut column on right side shows radiation value (KWh/m2) change
Scope.
The above, the only present invention preferably specific embodiment, but protection scope of the present invention is not limited thereto,
Any one skilled in the art the invention discloses technical scope in, the change or replacement that can be readily occurred in,
Should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with scope of the claims
It is defined.
Claims (6)
1. a kind of solar energy potential evaluation method based on ground laser point cloud, it is characterised in that：Comprise the following steps：
S1, original point cloud is vacuated；
S2, to vacuating after point cloud P carry out the extraction of the ground point set R in area-of-interest,
S3, setting light source deviation pilot angle；
S4, position and number that basic point is quickly calculated using solstics Greedy strategy；
S5, calculating basic point position of sun；
S6, using broad sense hidden place remove algorithm be GHPR algorithms, the sheltering analysis of three-dimensional point cloud scene are carried out, so as to carry out day
Calculated according to simulation；
S7, binaryzation shade drafting is carried out to sheltering analysis result；
S8, solar radiation calculating is carried out to a cloud scene.
2. a kind of solar energy potential evaluation method based on ground laser point cloud according to claim 1, it is characterised in that：
The S1's comprises the following steps that：
The three-dimensional ground laser point cloud P of inputraw, set one first and vacuate apart from Ls, method is then vacuated using voxel.Voxel is taken out
A cloud is first divided into the length of side for L by dilute methodsRegular cube voxel, then by point set in voxel central point as new data
Point, these new point sets form the point cloud P after vacuating.
3. a kind of solar energy potential evaluation method based on ground laser point cloud according to claim 1, it is characterised in that：
The S2's comprises the following steps that：
S21, first, ground point is extracted using the method based on the growth filtering of voxel elevation, the minimum height based on whole point cloud
Journey value sets a threshold level tzIf a center elevation for voxel is higher than threshold value t with the relative altitude of minimum pointz, then
Think that it is unlikely to be ground point, if additionally, a voxel less than threshold value can grow into threshold level tz, then it is assumed that it is
A part for wall or vertical object, is also non-ground points, so as to extract all ground point sets；
S22, then, Euclidean distance cluster is carried out to ground point collection, to the clustering cluster marking serial numbers for obtaining；
It is S23, last, the average density value of each class cluster is calculated, selection density highest one is used as area-of-interest (investigation
Object), the point cloud after vacuating is returned, the data point r of area-of-interest is marked according to each point index valuei, ri∈R。
4. a kind of solar energy potential evaluation method based on ground laser point cloud according to claim 1, it is characterised in that：
S3's comprises the following steps that：
The maximum allowable offset angle θ of simulation light deviation directional light is set, while setting the sun apart from d, two is may thereby determine that
Ultimate range l between individual basic point, has：
L=d/tan (pi/2-θ)
5. a kind of solar energy potential evaluation method based on ground laser point cloud according to claim 1, it is characterised in that：
S4's comprises the following steps that:
S41, first, solstics strategy one area-of-interest point of random selection is used as initial basic point o1, build basic point sequence O=
{o1}；
S42, then, calculates point farthest with the sequence on area-of-interest point set, i.e.,And added
It is added in O, is O={ o1,o2, until any point ri, ri∈ R, meet
O={ o after S43, acquisition basic point sequencek| k ∈ [1, n] }, for each point r that area-of-interest point is concentratedi, ask for its
Nearest neighbor point on basic point collection, belongs to an area-of-interest point for basic point and constitutes a deviation control area Gk。
6. a kind of solar energy potential evaluation method based on ground laser point cloud according to claim 1, it is characterised in that：
S6's comprises the following steps that：
S61, first, travels through sun point set S, for each position of sun si, and investigate three-dimensional point set P, the P={ p after scene is vacuatedi
| i ∈ [1, m] }, wherein m is a cardinality, performs radial direction geometric transformation F, is had:
Wherein, if pi=s, thenPoint set after conversion is And fkIt is the core letter of conversion
Number；
S62 and then to point setA convex hull computation is done, and retains the point in convex closure for shade point set W.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108132096A (en) * | 2017-12-20 | 2018-06-08 | 中南林业科技大学 | A kind of woods window solar radiation monitoring method based on laser radar |
| CN110163065A (en) * | 2018-12-04 | 2019-08-23 | 腾讯科技（深圳）有限公司 | Processing Method of Point-clouds, point cloud data loading method and device and equipment |
| CN112560258A (en) * | 2020-12-10 | 2021-03-26 | 中国第一汽车股份有限公司 | Test method, device, equipment and storage medium |
| CN113836484A (en) * | 2021-08-11 | 2021-12-24 | 浙江省测绘科学技术研究院 | Self-adaptive point cloud rarefying method based on path point adjacent domain and ground filtering |
| US11568520B2 (en) * | 2017-01-24 | 2023-01-31 | Leica Geosystems Ag | Method and device for inpainting of colourised three-dimensional point clouds |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010093675A1 (en) * | 2009-02-13 | 2010-08-19 | Harris Corporation | Registration of 3d point cloud data to 2d electro-optical image data |
| CN102446354A (en) * | 2011-08-29 | 2012-05-09 | 北京建筑工程学院 | Integral registration method of high-precision multisource ground laser point clouds |
| CN103942420A (en) * | 2014-04-08 | 2014-07-23 | 北京大学 | Rapid estimation method for solar energy in construction size |
-
2016
- 2016-11-14 CN CN201611000480.7A patent/CN106780586B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010093675A1 (en) * | 2009-02-13 | 2010-08-19 | Harris Corporation | Registration of 3d point cloud data to 2d electro-optical image data |
| CN102446354A (en) * | 2011-08-29 | 2012-05-09 | 北京建筑工程学院 | Integral registration method of high-precision multisource ground laser point clouds |
| CN103942420A (en) * | 2014-04-08 | 2014-07-23 | 北京大学 | Rapid estimation method for solar energy in construction size |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11568520B2 (en) * | 2017-01-24 | 2023-01-31 | Leica Geosystems Ag | Method and device for inpainting of colourised three-dimensional point clouds |
| CN108132096A (en) * | 2017-12-20 | 2018-06-08 | 中南林业科技大学 | A kind of woods window solar radiation monitoring method based on laser radar |
| CN110163065A (en) * | 2018-12-04 | 2019-08-23 | 腾讯科技（深圳）有限公司 | Processing Method of Point-clouds, point cloud data loading method and device and equipment |
| CN112560258A (en) * | 2020-12-10 | 2021-03-26 | 中国第一汽车股份有限公司 | Test method, device, equipment and storage medium |
| CN113836484A (en) * | 2021-08-11 | 2021-12-24 | 浙江省测绘科学技术研究院 | Self-adaptive point cloud rarefying method based on path point adjacent domain and ground filtering |
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