CN110008576A - A kind of Monte Carlo solar radiant energy density emulation mode of peak steady - Google Patents
A kind of Monte Carlo solar radiant energy density emulation mode of peak steady Download PDFInfo
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Abstract
The invention discloses a kind of Monte Carlo solar radiant energy density emulation modes of peak steady, comprising the following steps: (1) according to sun incidence light model, samples to incident light direction；(2) incident light and the intersection point on heliostat surface are sampled；(3) incident light is carried out blocking energy density distribution initial simulation result of the test to obtain receiver surface；(4) the initial simulation result of the energy density distribution on receiver surface is filtered calculating, obtains Monte Carlo solar radiant energy density simulation result.The Monte Carlo solar radiant energy density emulation mode of peak steady of the present invention adds previous step to post-process by the result to Ray Tracing Algorithm simulation calculation: filtering calculates, under the premise of the gross energy for guaranteeing that receiver surface receives is constant, so that peak value is closer and more stable with true value, while reducing RMSE.Stable peak value and with GT is closer is distributed as subsequent related algorithm research and emulation provides reliable guarantee.
Description
Technical field
The present invention relates to solar power generation analogue technique fields, more particularly to a kind of Monte Carlo sun of peak steady
Radiant energy dfensity emulation mode.
Background technique
As the shortage of resources of fossil energy environmental problem with caused by is got worse in recent years, clean reproducible energy draws
The extensive concern of Qi Liao academia and industrial sphere.Solar energy is exactly in the common renewable resource of one kind.As the main of the earth
The sun of source provider, solar energy have natural safe and clean, easy acquisition, renewable and rich reserves feature.If it exists
A kind of technology can fully convert the solar into other energy of necessary for human, then theoretically solar energy can satisfy full generation
The demand of the bound pair energy.Although solar energy has huge utility value, the contribution that solar energy supplies global energy at this stage
Still insignificant.
Solar light-heat power-generation technology is one of current most common application of solar energy mode.And modern sun energy photo-thermal is sent out
The utilization efficiency for determining solar energy of heliostat mirror field reflective projection efficiency high degree in electric system.Therefore in order to be promoted too
The generating efficiency of positive energy solar-thermal generating system, needs to optimize the design layout and focusing strategy of heliostat mirror field.Wherein
Carrying out emulation to the radiant energy dfensity distribution on receiver surface is the basis solved these problems.
Two kinds of radiant energy dfensity emulation modes: ray trace and analytic method are mainly used at present.Ray tracing method pair
The path of a large amount of light is simulated, and optical path is copied to close in heliostat mirror field with the intersection of other objects, refraction, reflection etc.
System, to simulate the intersection point and energy value for deriving light and receiver.In computer graphics application, Ray Tracing Algorithm can
To draw out the extremely strong image of the sense of reality, therefore it can also obtain and really be distributed close in heliostat projection reflective application
As a result.But on the one hand, since Ray Tracing Algorithm needs calculate a large amount of opticpaths, computational efficiency is lower；Separately
On the one hand, due to the discreteness of Ray Tracing Algorithm, there is uncertain noise in the result of radiant energy dfensity emulation.
The essence of analytic method is to can parse the expression formula of calculating by one, directly calculating receiver surface any one
The radiant energy dfensity value of point.Since analytic method computational efficiency is higher, have great advantage in the emulation of large-scale Jing Chang.But due to
Any one analytic modell analytical model is approached one of true hot spot.Therefore, analytic method not only Precision Theory lower than light with
Track method, and due to the precision in order to guarantee simulation, analytic method needs to determine the parsing letter for each heliostat in advance
Several parameters, and these parameter values are usually obtained by the result of ray trace.So efficient and accurate Ray Tracing Algorithm is
There is irreplaceable status on the basis of analytic method correlative study in radiant energy dfensity emulation area research.
The uncertain noise of Ray Tracing Algorithm simulation result has two aspects at present:
Even if one, being directed to the emulation of single heliostat, radiation energy of the ray trace reflective projection on receiver surface is close
Spend peak value (abbreviation peak value refers to receiver surface within the unit time, received greatest irradiation energy energy on unit area) always
Unstable.An important factor for accuracy of peak value is assessment radiant energy dfensity simulation result.On the one hand, the erroneous estimation of peak value
It will affect the service life of receiver；On the other hand, peak value is also the fitting parameter that many analytical calculation models use.And due to
Ray trace is a kind of discrete calculation method, and the peak value of simulation result is very unstable, can achieve 10% in some cases
Error.Unstable peak value will necessarily make a big impact to mirror field design result.
Two, ray trace reflective projection receiver surface radiant energy distribution and true value distribution (ground truth,
Abbreviation GT) root-mean-square error (Root Mean Square Error, abbreviation RMSE) it is larger.This point is by the every of ray trace
Secondary operation generates caused by different random numbers.The larger confidence level that can equally reduce simulation result of RMSE, thus to such as mirror
The relevant parameter and truth deviation provided in the researchs such as field layout designs, site parameter optimization, focus optimization.
Summary of the invention
For a kind of Monte Carlo solar radiant energy density emulation mode for being designed to provide peak steady of invention, reduce
RMSE in Ray Tracing Algorithm simulation result, so that peak value is closer and more stable with true value.
A kind of Monte Carlo solar radiant energy density emulation mode of peak steady, comprising the following steps:
(1) according to sun incidence light model, incident light direction is sampled；
(2) incident light and the intersection point on heliostat surface are sampled；
(3) incident light is carried out blocking energy density distribution initial simulation result of the test to obtain receiver surface；
(4) the initial simulation result of the energy density distribution on receiver surface is filtered calculating, obtains Monte Carlo too
Positive radiant energy dfensity simulation result.
Preferably, the sun incidence light model is Buie sunlight distributed model, PillBox sunlight distributed model
Or Gauss sunlight distributed model.
Preferably, sampling uses the random number generator of uniform sampling in step (2).Using random number generator into
The method of row uniform sampling realizes simple, computational efficiency height.
Preferably, block test method in step (3) the following steps are included:
If (a) incident light is blocked by other objects in scene, stop calculating；
(b) otherwise, the micro- surface normal direction sampled according to incident light direction calculates it and reflects light direction；
(c) reflected light is carried out blocking test；
If (d) reflected light is blocked by other objects in scene, stop calculating；
(e) otherwise, the location of pixels that reflected light intersects with receiver is calculated, which is added to the picture
Element.
The application is a kind of emulation mode, so calculating pixel position in the location of pixels that reflected light intersects with receiver herein
Setting is the virtual location stored using array, by incident optical energy metric density be added to the pixel be exactly to corresponding array into
Row processing.
Preferably, it is described filtering be calculated as gaussian filtering calculate, mean filter calculate, trimmed mean filtering calculate, in
Digit filtering calculates or bilateral filtering calculates.More preferably.The filtering is calculated as trimmed mean filtering and calculates.
The method that trimmed mean filtering calculates are as follows: in simulation result initial for the energy density distribution on receiver surface
Each element will delete respective numbers most according to removal ratio p in the k × k element adjoined when trimmed mean filtering calculates
Big value and minimum value, then the average value of surplus element is calculated as currentElement treated value.Wherein the selection of parameter is to knot
Fruit tool has a significant impact, and preferably k value is 9~13.It is preferred that P value is 0.01~0.05.
The Monte Carlo solar radiant energy density emulation mode of peak steady of the present invention is by emulating Ray Tracing Algorithm
The result of calculating adds previous step to post-process: filtering calculates, and under the premise of the gross energy for guaranteeing that receiver surface receives is constant, makes
It is closer and more stable with true value to obtain peak value, while reducing RMSE.Stable peak value and with GT it is closer be distributed as it is subsequent
Related algorithm research and emulation provide reliable guarantee.
Detailed description of the invention
Fig. 1 is showing for the position distribution of model accuracy design single side planar heliostats and planar receiver that verifying proposes
It is intended to.
Fig. 2 is the flow chart for carrying out trimmed mean filtering to each pixel and calculating.
Fig. 3 is that the application is verifying proposition method validity, is projected in planar receiver surface to single side planar heliostats
The radiant energy dfensity distribution of generation carries out comparison diagram before and after the processing, wherein Fig. 3 (a) shows classical Monte carlo algorithm
With the radiant energy dfensity distributed simulation profile diagram comparison diagram of GT；Fig. 3 (b) shows classical Monte carlo algorithm knot in Fig. 3 (a)
After fruit is plus the application processing, the radiant energy dfensity distributed simulation profile diagram comparison diagram with GT.
Fig. 4 is the sectional view comparative result figure that Fig. 3 (a) and (b) are equal to 0 plane in z coordinate value.
Fig. 5 is statistical results chart of 100 ray trace results before and after carrying out trimmed mean filtering operation, wherein Fig. 5
It (a) is peak value statistical chart；Fig. 5 (b) is RMSE statistical chart.
Specific embodiment
Embodiment 1
By taking existing two-way Monte Carlo Ray Tracing Algorithm is to receiver surface emissivity energy density simulation algorithm as an example,
Steps are as follows for calculating:
1. being sampled according to sun incidence model to incident light direction.Radiation direction is by elevation angle (being set as θ) and orientation
Angle (is set as) determine.For example, when using Buie sunlight distributed model,Being uniformly distributed in obedience section [0,2 π], and θ
Buie distributed model is obeyed, respectively as shown in formula 1 and formula 2:
Wherein the calculation method of κ and γ is shown in formula 3,
Wherein χ represents control Buie sunlight distributed model distribution situation when light is greater than sun subtended angle (4.65mrad)
CSR parameter.
2. pair incident light and the intersection point on heliostat surface sample.Heliostat surface generates a point at random, in sky
Between in intersection point of the position as incident ray and heliostat；
3. pair incident light carries out blocking test:
3.1. if incident ray is blocked by other objects in scene, stop calculating.
3.2. otherwise, calculate it and reflect light direction.Micro- surface normal perturbation direction is also by parameter elevation angle (being set as α) and side
Parallactic angle (being set as β) determines that formula 4 and formula 5 are shown in the distribution of α and β:
α~N (0, σ2) formula 4
β '~U (0,2 π), β=arctan (β ') formula 5
Wherein σ is standard deviation, its value depends on the planarization on heliostat surface.
3.3. reflection light is carried out blocking test:
3.3.1. if reflection light is blocked by other objects in scene, stop calculating.
3.3.2. otherwise, the location of pixels that reflection light intersects with receiver is calculated, its energy density is added to the picture
Element, energy density calculate formula and see formula 6:
Wherein IDIt is solar energy metric density, unit is W/m2；ShsubAnd SrsubIt is the area of heliostat and pixel respectively,
Unit is m2；φ is the angle between incident light direction and micro- surface normal；ρ is reflectivity, in [0,1] section；NcIt is emulation
In the light number that intersects with heliostat；ηaαIt is atmosphere attenuation coefficien, value is determined by atmospheric attenuation model, such as formula 7:
Wherein d is distance of the launch point to receiver surface, and unit is m.
4. the above 1-3 step is repeated, until the light number generated reaches the N of settingc.I.e. to each incident light into
The above-mentioned processing of row, until all incident lights handle completion.
Since the calculating of original Monte Carlo Ray Tracing Algorithm is discrete, and it is related to random number in the process and adopts
Sample, therefore the peak results calculated every time have larger floating, and RMSE value is larger.Wherein the calculation method of RMSE is shown in formula 8:
The application technical issues that need to address are how to post-process to ray trace radiant energy dfensity simulation result,
And under the premise of guaranteeing that receiver surface gross energy is constant, so that peak value is closer and more stable with GT.Meanwhile treated
As a result the RMSE between GT distribution reduces.Fig. 1 is that the application is the model accuracy design single side plane settled date that verifying proposes
The schematic diagram of the position distribution of mirror and planar receiver, specific experiment parameter are as shown in table 1.It is wherein 0 ° to the north of azimuth,
It is positive clockwise.
The Monte Carlo ray trace simulation result experiment parameter of 1 single side heliostat reflective projection of table
There are five types of widely used filtering method: gaussian filtering, mean filter, trimmed mean filtering, median filtering and
Bilateral filtering.It is the RMSE and peak value statistical value of above five kinds of filtering operations processing Monte Carlo simulation result shown in table 2.Its
In, be not filtered operation refer to it is imitative to receiver surface emissivity energy density with existing two-way Monte Carlo Ray Tracing Algorithm
The result that true algorithm obtains.Statistical result shows trimmed mean filtering better than other four kinds of methods.Therefore, in the application emphatically pair
Trimmed mean filtering is introduced.
The RMSE and peak value statistics of 2 five kinds of filtering operation processing MCRT simulation results of table
For the radiant energy dfensity distribution that Monte Carlo ray trace emulates, each of which pixel all carries out trimmed mean
Filtering calculates.For each pixel, p element minimum and maximum in the k × k pixel adjoined is deleted in trimmed mean filtering
(p ∈ [0,0.5)), residual value carries out average computation, the result of the calculating value new as current pixel.
Save least member and most in trimmed mean filtering respectively using the most raft and most rickle of two same sizes
Big element set.Most rickle and most raft are complete binary tree, wherein the value of each father node is less than or equal to it in most rickle
Two child nodes；In contrast, the value of each father node is greater than or equal to two child nodes to most raft.It is noticeable
It is that save in most raft is the smallest element set, and most rickle is then to save maximum element set.To ray trace meter
Steps are as follows for the trimmed mean calculating of each pixel pixel in the radiant energy dfensity distribution of calculating:
1. the value that sum is arranged is 0.
2. two sizes of initialization areMost rickle and most raft；
3. circulation, which reads the pixel, adjoins k × k pixel, the value of reading is set as currentValue:
It 3.1., will be in currentValue insertion most rickle and most raft if most raft and most rickle is less than；
3.2. otherwise:
3.2.1. if currentValue is greater than most rickle heap top element, most rickle heap top element is deleted, is accumulated it
It is inserted into heap to sum, and by currentValue；
3.2.2. if currentValue is less than most raft heap top element, most raft heap top element is deleted, is accumulated it
It is inserted into heap to sum, and by currentValue；
3.2.3. as being unsatisfactory for step 3.2.1 and 3.2.2 simultaneously, then currentValue is added to sum.
4. the new value of preceding pixel is equal to sum divided by the number for retaining element.
The flow chart of the above process is shown in Fig. 2, makes to each pixel in the distribution of ray trace calculated radiant energy dfensity
It is calculated with the trimmed mean method.Particularly, which is very suitable for carrying out parallel computation.The algorithm is realized on GPU
When, the heap in algorithm can be stored in shared drive, to accelerate computational efficiency.Time complexity in GPU is only O
(k2·log(k·p))。
Table 3 enumerates RMSE and peak value statistics of the trimmed mean filtering in different k and p values.It can be found that in p in area
Between 0.01~0.05 and k value effect in section 9~13 it is preferable, the value of RMSE is lower, and peak value is closer to GT.Fig. 3 (a)
It is the silhouette contrast figure of corresponding Monte Carlo ray trace simulation result and GT distribution, wherein GT peak value is 380.74W/m2。
When trimmed mean filtering is not added and calculates, the value of RMSE is 10.80W/m2.Fig. 3 (b) is then in the result that Fig. 3 (a) is calculated
The new distribution obtained after trimmed mean filtering calculates is added, wherein k and p is respectively 11 and 2%, and the value of RMSE is 0.83W/ at this time
m2.Fig. 4 is then the sectional view result that Fig. 3 is equal to 0 plane in z coordinate value.It is not difficult to find that without trimmed mean filtering operation
The result of processing is full of noise and boundary is crude, these noises are exactly to cause peak value unstable and the larger reason of RMSE value.Place
After reason, simulation result is distributed the distribution for being more nearly GT.
RMSE and peak value statistics of 3 trimmed mean of the table filtering in different k and p values
Be respectively shown in Fig. 5 (a) and Fig. 5 (b) 100 ray trace results peak value and RMSE value before post-processing
Statistical chart afterwards.It can be found that after post-processing (increase trimmed mean filtering to calculate, k and p be respectively 11 and peak value 2%) more
Stablize, the value of RMSE is significantly reduced.
In trimmed mean filtering, due to deleting the uncertainty of element, gross energy can change, but the variation of energy
Within 0.5%.Therefore, in being strict with the constant application scenarios of gross energy, p can be set as 0, truncation is filtered and is degenerated
It is calculated at the mode of mean filter, to keep gross energy constant.
Claims (9)
1. a kind of Monte Carlo solar radiant energy density emulation mode of peak steady, which comprises the following steps:
(1) according to sun incidence light model, incident light direction is sampled；
(2) incident light and the intersection point on heliostat surface are sampled；
(3) incident light is carried out blocking energy density distribution initial simulation result of the test to obtain receiver surface；
(4) the initial simulation result of the energy density distribution on receiver surface is filtered calculating, obtains Monte Carlo sun spoke
Penetrating can density simulation result.
2. solar radiant energy density emulation mode in Monte Carlo as described in claim 1, which is characterized in that the sun is incident
Light model is Buie sunlight distributed model, PillBox sunlight distributed model or Gauss sunlight distributed model.
3. solar radiant energy density emulation mode in Monte Carlo as described in claim 1, which is characterized in that step is adopted in (2)
Sample uses the random number generator of uniform sampling.
4. solar radiant energy density emulation mode in Monte Carlo as described in claim 1, which is characterized in that hidden in step (3)
Keep off test method the following steps are included:
If (a) incident light is blocked by other objects in scene, stop calculating；
(b) otherwise, the micro- surface normal direction sampled according to incident light direction calculates it and reflects light direction；
(c) reflected light is carried out blocking test；
If (d) reflected light is blocked by other objects in scene, stop calculating；
(e) otherwise, the location of pixels that reflected light intersects with receiver is calculated, which is added to the pixel.
5. solar radiant energy density emulation mode in Monte Carlo as described in claim 1, which is characterized in that the filtering calculates
It is calculated for gaussian filtering, mean filter calculates, trimmed mean filtering calculates, median filtering calculates or bilateral filtering calculates.
6. solar radiant energy density emulation mode in Monte Carlo as claimed in claim 5, which is characterized in that the filtering calculates
It filters and calculates for trimmed mean.
7. solar radiant energy density emulation mode in Monte Carlo as claimed in claim 6, which is characterized in that trimmed mean filtering
The method of calculating are as follows: each element in simulation result initial for the energy density distribution on receiver surface, trimmed mean filter
The maximum value and minimum value of respective numbers will be deleted according to removal ratio p in the k × k element adjoined when wave calculates, then calculated
The average value of surplus element as currentElement treated value.
8. solar radiant energy density emulation mode in Monte Carlo as claimed in claim 7, which is characterized in that k value is 9~13.
9. solar radiant energy density emulation mode in Monte Carlo as claimed in claim 7, which is characterized in that P value be 0.01~
0.05。
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