def test_RadianceObj_1axis_gendaylit_end_to_end():
# 1-axis tracking end-to-end test with torque tube and gap generation.
# Takes 20 seconds for 2-sensor scan
module_height = 1.95 * 2 + 0.1 # module portrait dimension in meters
gcr = 0.35 # ground cover ratio, = module_height / pitch
albedo = 0.3 # ground albedo
hub_height = 2 # tracker height at 0 tilt in meters (hub height)
demo = RadianceObj() # Create a RadianceObj 'object'
demo.setGround(
albedo
) # input albedo number or material name like 'concrete'. To see options, run this without any input.
metdata = demo.readEPW(
MET_FILENAME) # read in the EPW weather data from above
#metdata = demo.readTMY(MET_FILENAME2) # select a TMY file using graphical picker
# create metdata files for each condition. keys are timestamps for gendaylit workflow
trackerdict = demo.set1axis(cumulativesky=False)
# create the skyfiles needed for 1-axis tracking
demo.gendaylit1axis(metdata=metdata, enddate='01/01')
# test modules with gap and rear tube
demo.makeModule(name='Longi_torquetube',
x=0.984,
y=1.95,
torquetube=True,
numpanels=2,
panelgap=0.1)
#demo.makeModule(name='Longi_torquetube',x=0.984,y=1.95)
# set module type to be used and passed into makeScene1axis
module_type = 'Longi_torquetube'
# Create the scene for the 1-axis tracking
sceneDict = {
'pitch': module_height / gcr,
'height': hub_height,
'orientation': 'portrait'
}
key = '01_01_11'
demo.makeScene1axis(
{key: trackerdict[key]},
module_type,
sceneDict,
cumulativesky=False,
nMods=10,
nRows=3,
modwanted=3,
rowwanted=3,
sensorsy=2
) #makeScene creates a .rad file with 20 modules per row, 7 rows.
demo.makeOct1axis(trackerdict,
key) # just run this for one timestep: Jan 1 11am
demo.analysis1axis(trackerdict,
key) # just run this for one timestep: Jan 1 11am
assert (np.mean(demo.Wm2Front) == pytest.approx(214.0, 0.01))
assert (np.mean(demo.Wm2Back) == pytest.approx(40.0, 0.1))
def test_RadianceObj_high_azimuth_angle_end_to_end():
# modify example for high azimuth angle to test different parts of makesceneNxR. Rear irradiance fraction roughly 17.3% for 0.95m landscape panel
# takes 14 seconds for sensorsy = 9, 11 seconds for sensorsy = 2
demo = RadianceObj() # Create a RadianceObj 'object'
demo.setGround(
'white_EPDM'
) # input albedo number or material name like 'concrete'. To see options, run this without any input.
#metdata = demo.readEPW() # read in the EPW weather data from above
metdata = demo.readTMY(
MET_FILENAME2) # select a TMY file using graphical picker
# Now we either choose a single time point, or use cumulativesky for the entire year.
fullYear = False
if fullYear:
demo.genCumSky(
demo.epwfile
) # entire year. # Don't know how to test this yet in pytest...
else:
demo.gendaylit(metdata, 4020) # Noon, June 17th
# create a scene using panels in landscape at 10 deg tilt, 1.5m pitch. 0.2 m ground clearance
sceneDict = {
'tilt': 10,
'pitch': 1.5,
'height': 0.2,
'orientation': 'landscape',
'azimuth': 30
}
demo.makeModule(name='simple_panel', x=0.95, y=1.59)
scene = demo.makeScene(
'simple_panel', sceneDict, nMods=10, nRows=3
) #makeScene creates a .rad file with 20 modules per row, 7 rows.
octfile = demo.makeOct(
demo.getfilelist()
) # makeOct combines all of the ground, sky and object files into a .oct file.
analysis = AnalysisObj(
octfile, demo.name
) # return an analysis object including the scan dimensions for back irradiance
analysis.analysis(octfile, demo.name, scene.frontscan,
scene.backscan) # compare the back vs front irradiance
#assert np.round(np.mean(analysis.backRatio),2) == 0.20 # bifi ratio was == 0.22 in v0.2.2
assert np.mean(analysis.Wm2Front) == pytest.approx(912, rel=0.005)
assert np.mean(analysis.Wm2Back) == pytest.approx(182, rel=0.01)
def test_RadianceObj_fixed_tilt_end_to_end():
# just run the demo example. Rear irradiance fraction roughly 11.8% for 0.95m landscape panel
# takes 12 seconds
demo = RadianceObj() # Create a RadianceObj 'object'
demo.setGround(
0.62
) # input albedo number or material name like 'concrete'. To see options, run this without any input.
metdata = demo.readEPW(
epwfile=MET_FILENAME) # read in the EPW weather data from above
#metdata = demo.readTMY() # select a TMY file using graphical picker
# Now we either choose a single time point, or use cumulativesky for the entire year.
fullYear = False
if fullYear:
demo.genCumSky(demo.epwfile) # entire year.
else:
demo.gendaylit(metdata, 4020) # Noon, June 17th
# create a scene using panels in landscape at 10 deg tilt, 1.5m pitch. 0.2 m ground clearance
sceneDict = {
'tilt': 10,
'pitch': 1.5,
'height': 0.2,
'orientation': 'landscape'
}
demo.makeModule(name='simple_panel', x=0.95, y=1.59)
scene = demo.makeScene(
'simple_panel', sceneDict, nMods=10, nRows=3
) #makeScene creates a .rad file with 20 modules per row, 7 rows.
octfile = demo.makeOct(
demo.getfilelist()
) # makeOct combines all of the ground, sky and object files into a .oct file.
analysis = AnalysisObj(
octfile, demo.name
) # return an analysis object including the scan dimensions for back irradiance
analysis.analysis(octfile, demo.name, scene.frontscan,
scene.backscan) # compare the back vs front irradiance
#assert np.round(np.mean(analysis.backRatio),decimals=2) == 0.12 # NOTE: this value is 0.11 when your module size is 1m, 0.12 when module size is 0.95m
assert np.mean(analysis.backRatio) == pytest.approx(0.12, abs=0.01)
epwfile = demo.getEPW(
37.5, -77.6
) #Pull TMY weather data for any global lat/lon. In this case, Richmond, VA
metdata = demo.readEPW(epwfile) # read in the weather data
# create separate metdata files for each 1-axis tracker angle (5 degree resolution).
trackerdict = demo.set1axis(metdata,
limit_angle=limit_angle,
backtrack=True,
gcr=gcr)
# create cumulativesky functions for each tracker angle: demo.genCumSky1axis
trackerdict = demo.genCumSky1axis(trackerdict)
# Create a new moduletype: Prism Solar Bi60. width = .984m height = 1.695m. Bifaciality = 0.90
demo.makeModule(name='Prism Solar Bi60', x=0.984, y=module_height, bifi=0.90)
# print available module types
demo.printModules()
# create a 1-axis scene using panels in portrait, 2m hub height, 0.33 GCR. NOTE: clearance needs to be calculated at each step. hub height is constant
sceneDict = {
'pitch': module_height / gcr,
'height': hub_height,
'orientation': 'portrait'
}
module_type = 'Prism Solar Bi60'
trackerdict = demo.makeScene1axis(
trackerdict, module_type, sceneDict, nMods=20,
nRows=7) #makeScene creates a .rad file with 20 modules per row, 7 rows.
trackerdict = demo.makeOct1axis(trackerdict)
# This is a standard fixed-tilt setup for one hour. Gencumsky could be used too for the whole year.
#
# The key here is that we are setting in sceneDict the variable **appendRadfile** to true.
# In[4]:
demo = RadianceObj("MultipleObj",
path=testfolder) # Create a RadianceObj 'object'
demo.setGround(0.62)
epwfile = demo.getEPW(lat=37.5, lon=-77.6)
metdata = demo.readWeatherFile('EPWs\\USA_VA_Richmond.Intl.AP.724010_TMY.epw')
fullYear = True
demo.gendaylit(metdata,
4020) # Noon, June 17th . # Gencumsky could be used too.
module_type = 'Prism Solar Bi60 landscape'
demo.makeModule(name=module_type, y=1, x=1.7)
sceneDict = {
'tilt': 10,
'pitch': 1.5,
'clearance_height': 0.2,
'azimuth': 180,
'nMods': 5,
'nRows': 2,
'appendRadfile': True
}
sceneObj1 = demo.makeScene(module_type, sceneDict)
# Checking values after Scene for the scene Object created
# In[5]: