16 - AgriPV - 3-up and 4-up collector optimization#
This journal helps the exploration of varying collector widths and xgaps in the ground underneath as well as on the rear irradiance for bifacial AgriPV. The optimization varies the numpanels combinations with xgaps for having 3-up and 4-up collectors with varying space along the row (xgap). The actual raytracing is not performed in the jupyter journal but rather on the HPC, but the geometry is the same as presented here.
The steps on this journal:
<li> <a href='#step1'> Making Collectors for each number panel and xgap case </a></li>
<li> <a href='#step2'> Builds the Scene so it can be viewed with rvu </a></li>
An area of 40m x 20 m area is sampled on the HPC, and is highlighted in the visualizations below with an appended terrain of ‘litesoil’. The image below shows the two extremes of the variables optimized and the raytrace results, including the worst-case shading experienced under the array ( 100 - min_irradiance *100 / GHI).
[1]:
import os
from pathlib import Path
testfolder = Path().resolve().parent.parent / 'bifacial_radiance' / 'TEMP' / 'Tutorial_16'
if not os.path.exists(testfolder):
os.makedirs(testfolder)
print ("Your simulation will be stored in %s" % testfolder)
Your simulation will be stored in C:\Users\sayala\Documents\GitHub\bifacial_radiance\bifacial_radiance\TEMP\Tutorial_16
[2]:
import bifacial_radiance
import numpy as np
rad_obj = bifacial_radiance.RadianceObj('tutorial_16', str(testfolder))
path = C:\Users\sayala\Documents\GitHub\bifacial_radiance\bifacial_radiance\TEMP\Tutorial_16
1. Making Collectors for each number panel and xgap case#
[3]:
x = 2
y = 1
ygap = 0.1524 # m = 6 in
zgap = 0.002 # m, veyr little gap to torquetube.
tubeParams = {'diameter':0.15,
'tubetype':'square',
'material':'Metal_Grey',
'axisofrotation':True,
'visible': True}
ft2m = 0.3048
xgaps = [3, 4, 6, 9, 12, 15, 18, 21]
numpanelss = [3, 4]
# Loops
for ii in range(0, len(numpanelss)):
numpanels = numpanelss[ii]
for jj in range(0, len(xgaps)):
xgap = xgaps[jj]*ft2m
moduletype = 'test-module_'+str(numpanels)+'up_'+str(round(xgap,1))+'xgap'
rad_obj.makeModule(moduletype,
x=x, y=y,
xgap=xgap, zgap=zgap, ygap = ygap, numpanels=numpanels,
tubeParams=tubeParams)
Module Name: test-module_3up_0.9xgap
Module test-module_3up_0.9xgap updated in module.json
Pre-existing .rad file objects\test-module_3up_0.9xgap.rad will be overwritten
Module Name: test-module_3up_1.2xgap
Module test-module_3up_1.2xgap updated in module.json
Pre-existing .rad file objects\test-module_3up_1.2xgap.rad will be overwritten
Module Name: test-module_3up_1.8xgap
Module test-module_3up_1.8xgap updated in module.json
Pre-existing .rad file objects\test-module_3up_1.8xgap.rad will be overwritten
Module Name: test-module_3up_2.7xgap
Module test-module_3up_2.7xgap updated in module.json
Pre-existing .rad file objects\test-module_3up_2.7xgap.rad will be overwritten
Module Name: test-module_3up_3.7xgap
Module test-module_3up_3.7xgap updated in module.json
Pre-existing .rad file objects\test-module_3up_3.7xgap.rad will be overwritten
Module Name: test-module_3up_4.6xgap
Module test-module_3up_4.6xgap updated in module.json
Pre-existing .rad file objects\test-module_3up_4.6xgap.rad will be overwritten
Module Name: test-module_3up_5.5xgap
Module test-module_3up_5.5xgap updated in module.json
Pre-existing .rad file objects\test-module_3up_5.5xgap.rad will be overwritten
Module Name: test-module_3up_6.4xgap
Module test-module_3up_6.4xgap updated in module.json
Pre-existing .rad file objects\test-module_3up_6.4xgap.rad will be overwritten
Module Name: test-module_4up_0.9xgap
Module test-module_4up_0.9xgap updated in module.json
Pre-existing .rad file objects\test-module_4up_0.9xgap.rad will be overwritten
Module Name: test-module_4up_1.2xgap
Module test-module_4up_1.2xgap updated in module.json
Pre-existing .rad file objects\test-module_4up_1.2xgap.rad will be overwritten
Module Name: test-module_4up_1.8xgap
Module test-module_4up_1.8xgap updated in module.json
Pre-existing .rad file objects\test-module_4up_1.8xgap.rad will be overwritten
Module Name: test-module_4up_2.7xgap
Module test-module_4up_2.7xgap updated in module.json
Pre-existing .rad file objects\test-module_4up_2.7xgap.rad will be overwritten
Module Name: test-module_4up_3.7xgap
Module test-module_4up_3.7xgap updated in module.json
Pre-existing .rad file objects\test-module_4up_3.7xgap.rad will be overwritten
Module Name: test-module_4up_4.6xgap
Module test-module_4up_4.6xgap updated in module.json
Pre-existing .rad file objects\test-module_4up_4.6xgap.rad will be overwritten
Module Name: test-module_4up_5.5xgap
Module test-module_4up_5.5xgap updated in module.json
Pre-existing .rad file objects\test-module_4up_5.5xgap.rad will be overwritten
Module Name: test-module_4up_6.4xgap
Module test-module_4up_6.4xgap updated in module.json
Pre-existing .rad file objects\test-module_4up_6.4xgap.rad will be overwritten
2. Build the Scene so it can be viewed with rvu#
[4]:
xgaps = np.round(np.array([3, 4, 6, 9, 12, 15, 18, 21]) * ft2m,1)
numpanelss = [3, 4]
sensorsxs = np.array(list(range(0, 201)))
# Select CASE:
xgap = np.round(xgaps[-1],1)
numpanels = 4
# All the rest
ft2m = 0.3048
hub_height = 8.0 * ft2m
y = 1
pitch = 0.001 # If I recall, it doesn't like when pitch is 0 even if it's a single row, but any value works here.
ygap = 0.15
tilt = 18
sim_name = ('Coffee_'+str(numpanels)+'up_'+
str(round(xgap,1))+'_xgap')
albedo = 0.35 # Grass value from Torres Molina, "Measuring UHI in Puerto Rico" 18th LACCEI
# International Multi-Conference for Engineering, Education, and Technology
azimuth = 180
if numpanels == 3:
nMods = 9
if numpanels == 4:
nMods = 7
nRows = 1
moduletype = 'test-module_'+str(numpanels)+'up_'+str(round(xgap,1))+'xgap'
rad_obj.setGround(albedo)
lat = 18.202142
lon = -66.759187
metfile = rad_obj.getEPW(lat,lon)
rad_obj.readWeatherFile(metfile)
sceneDict = {'tilt':tilt,'pitch':pitch,'hub_height':hub_height,'azimuth':azimuth, 'nMods': nMods, 'nRows': nRows}
scene = rad_obj.makeScene(module=moduletype,sceneDict=sceneDict, radname = sim_name)
rad_obj.gendaylit(4020)
octfile = rad_obj.makeOct(filelist = rad_obj.getfilelist(), octname = rad_obj.basename)
name='SampleArea'
text='! genbox litesoil cuteBox 40 20 0.01 | xform -t -20 -10 0.01'
customObject =rad_obj.makeCustomObject(name,text)
rad_obj.appendtoScene(scene.radfiles, customObject, '!xform -rz 0')
octfile = rad_obj.makeOct(rad_obj.getfilelist())
Loading albedo, 1 value(s), 0.350 avg
1 nonzero albedo values.
Getting weather file: PRI_Mercedita.AP.785203_TMY3.epw
... OK!
8760 line in WeatherFile. Assuming this is a standard hourly WeatherFile for the year for purposes of saving Gencumulativesky temporary weather files in EPW folder.
Coercing year to 2021
Saving file EPWs\metdata_temp.csv, # points: 8760
Calculating Sun position for Metdata that is right-labeled with a delta of -30 mins. i.e. 12 is 11:30 sunpos
Created tutorial_16.oct
Custom Object Name objects\SampleArea.rad
Created tutorial_16.oct
Or run it directly from Jupyter by removing the comment from the following cell:#
[5]:
## Comment the ! line below to run rvu from the Jupyter notebook instead of your terminal.
## Simulation will stop until you close the rvu window
#!rvu -vf views\front.vp -e .0265652 -vp 2 -21 2.5 -vd 0 1 0 makemod.oct
#!rvu -vf views\front.vp -e .0265652 -vp 5 0 70 -vd 0 0.0001 -1 makemod.oct